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1
Corinthios, Michael J. "New Laplace, z and Fourier-related transforms." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 463, no. 2081 (2007): 1179–98. http://dx.doi.org/10.1098/rspa.2007.1814.
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In this paper, the author uses his recently proposed complex variable generalized distribution theory to expand the domains of existence of bilateral Laplace and z transforms, as well as a whole new class of related transforms. A vast expansion of the domains of existence of bilateral Laplace and z transforms and continuous-time and discrete-time Hilbert, Hartley and Mellin transforms, as well as transforms of multidimensional functions and sequences are obtained. It is noted that the Fourier transform and its applications have advanced by leaps and bounds during the last century, thanks to the introduction of the theory of distributions and, in particular, the concept of the Dirac-delta impulse. Meanwhile, however, the truly two-sided ‘bilateral’ Laplace and z transforms, which are more general than Fourier, remained at a standstill incapable of transforming the most basic of functions. In fact, they were reduced by half to one-sided transforms and received no more than a passing reference in the literature. It is shown that the newly proposed generalized distributions expand the domains of existence and application of Laplace and z transforms similar to and even more extensively than the expansion of the domain of Fourier transform that resulted from the introduction, nearly a century ago, of the theory of distributions and the Dirac-delta impulse. It is also shown that the new generalized distributions put an end to an anomaly that still exists today, which meant that for a large class of basic functions, the Fourier transform exists while the more general Laplace and z transforms do not. The anomaly further manifests itself in the fact that even for the one-sided causal functions, such as the Heaviside unit step function u ( t ) and the sinusoid sin βtu ( t ), the Laplace transform does not exist on the j ω -axis, and the Fourier transform which does exist cannot be deduced thereof by the substitution s =j ω in the Laplace transform, which by definition it should. The extended generalized transforms are well defined for a large class of functions ranging from the most basic to highly complex fast-rising exponential ones that have so far had no transform. Among basic applications, the solution of partial differential equations using the extended generalized transforms is provided. This paper clearly presents and articulates the significant impact of extending the domains of Laplace and z transforms on a large family of related transforms, after nearly a century during which bilateral Laplace and z transforms of even the most basic of functions were undefined, and the domains of definition of related transforms such as Hilbert, Hartley and Mellin transforms were confined to a fraction of the space they can now occupy.
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Zhu, Jun, Xiao Jia Lu, and Xiang Liu. "Application of Chirp-z Transform in Doppler Weather Radar." Applied Mechanics and Materials 513-517 (February 2014): 4265–68. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.4265.
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Among the signal processing methods of Doppler weather radar, the FFT (Fast Fourier Transform) method is widely used. If the measurement accuracy needs to be improved, the number of FFT points also needs to be increased. As a result, the amount of computation increases exponentially. Chirp-z transform can directly refine certain spectrum in the spectrum of weather echoes. In the case that the sampling points and the amount of computation increase fewer, the measurement accuracy can be greatly advanced.
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El-Kareem, Mona Abd, and Ibrahiem M. M. El-Emary. "Towards Developing An Advanced Methodology For Image Enhancement Based On Z-Transform." Bioscience Biotechnology Research Communications 12, no. 1 (2019): 66–72. http://dx.doi.org/10.21786/bbrc/12.1/9.
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Said, Archana Ganesh, and Bharti Joshi. "Advanced multimodal thermal imaging for high-precision fruit disease segmentation and classification." Journal of Autonomous Intelligence 7, no. 5 (2024): 1618. http://dx.doi.org/10.32629/jai.v7i5.1618.
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<p>The urgent necessity to bolster agricultural productivity while ensuring quality control has amplified the demand for advanced diagnostic methods for fruit disease detection. Thermal imaging, a promising non-destructive technique, remains underutilized due to complexities and inefficiencies in existing processing models, particularly in handling multiple disease types and maintaining performance at scale. Current methods falter with increased disease variability, presenting a challenge in real-time applications due to their computational intensity and reduced accuracy. Addressing these limitations, this study introduces a robust multimodal analysis framework for fruit disease segmentation and classification based on thermal scans. The proposed model begins with the collection of thermal images of fruits, employing entropy-based Saliency Maps for precise image segmentation. To effectively represent the distinctions of these segmented images, the model harnesses a comprehensive suite of transformations—Frequency, Z Transform, S Transform, and Gabor Transforms—tailoring multi domain features to distinguish between disease states. A pivotal advancement is the integration of Coot Optimization (CO), which streamlines the feature selection process, significantly diminishing redundancy and isolating the most discriminative features for disease identification. Classification is adeptly managed by a novel Graph-based Generative Adversarial Network (Graph GAN) that innovatively combines Graph Neural Networks with the generative capabilities of GANs, offering a powerful blend for categorizing fruit diseases. Upon rigorous testing with mango and apple thermal images, the model demonstrated a remarkable increase in performance metrics, outstripping contemporary methods by achieving a 9.4% enhancement in accuracy, a 4.5% rise in precision, a 3.9% improvement in recall, and a substantial 8.3% reduction in processing delays. The implications of this work are profound, signaling a paradigm shift in agricultural disease management. By significantly elevating the speed and precision of disease detection through thermal imaging, this model paves the way for large-scale, real-time monitoring, potentially revolutionizing fruit disease diagnosis and helping to secure global food supplies in an era of increasing environmental challenges.</p>
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Islam, MD Saiful, Young Kyoung Ji, Kihyun Kim, and Hyo-Young Kim. "Advanced Machine Learning Techniques for Predicting Z-Axis Belt Wear in Wafer Transfer Robots." International Journal of Precision Engineering and Manufacturing-Smart Technology 3, no. 1 (2025): 17–30. https://doi.org/10.57062/ijpem-st.2024.00157.
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Wafer-transfer robots (WTRs) are critical to semiconductor manufacturing, where precision and efficiency are essential to ensure high production yields and minimize defects. A key challenge is the wear and degradation of the Z-axis belt, which can cause misalignments, operational disruptions, and costly downtimes. This study presents a data-driven approach leveraging machine learning to predict Z-axis belt wear, enhancing WTR reliability and performance. High-frequency acceleration sensor data from the Upper Blade axis of WTRs were utilized to develop and test various machine learning classification models, including K-Nearest Neighbors (KNN), Logistic Regression, Naive Bayes, Decision Tree, and Random Forest. The Random Forest model achieved the highest predictive accuracy at 99.8%, significantly surpassing traditional maintenance methods. These findings highlight the potential of machine learning to transform predictive maintenance in semiconductor manufacturing. By anticipating and preventing faults with exceptional precision, machine learning-based predictive maintenance enables more reliable and efficient operations, reducing costs and enhancing system longevity. This study not only demonstrates the effectiveness of machine learning in predictive maintenance but also sets the foundation for future applications aimed at optimizing the performance and lifespan of critical manufacturing equipment.
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Lee, Eun-Hye, Mi-Kyung Lee, and Soo-Jeong Lim. "Enhanced Stability of Indocyanine Green by Encapsulation in Zein-Phosphatidylcholine Hybrid Nanoparticles for Use in the Phototherapy of Cancer." Pharmaceutics 13, no. 3 (2021): 305. http://dx.doi.org/10.3390/pharmaceutics13030305.
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Indocyanine green (ICG) is a clinically approved near-infrared dye that has shown promise as a photosensitizer for the phototherapy of cancer. However, its chemical instability in an aqueous solution has limited its clinical application. Encapsulating ICG in liposomes, phosphatidylcholine nanoparticles (PC-NP), has shown partial effectiveness in stabilizing it. Prompted by our recent finding that the zein-phosphatidylcholine hybrid nanoparticles (Z/PC-NP) provide an advanced drug carrier compared to PC-NP, we herein investigated the potential of Z/PC-NP as an improved ICG formulation. Dynamic light scattering analysis, transmission electron microscopy, and Fourier-transform infrared spectroscopy studies showed that ICG was encapsulated in Z/PC-NP without hampering the high colloidal stability of the Z/PC-NP. During storage, the Z/PC-NP almost completely inhibited the ICG aggregation, whereas the PC-NP did so partially. The Z/PC-NP also more effectively blocked the ICG degradation compared to the PC-NP. The phototoxicity of ICG encapsulated in Z/PC-NP on cancer cells was twofold higher than that in the PC-NP. The ICG encapsulated in Z/PC-NP, but not in PC-NP, maintained its photocytotoxicity after four-day storage. These findings highlight the promising potential of Z/PC-NP as an ICG formulation that provides a higher stabilization effect than PC-NP.
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Wen, Yuan. "Optimization design of biomechanical parameters based on advanced mathematical modelling." Molecular & Cellular Biomechanics 21, no. 3 (2024): 463. http://dx.doi.org/10.62617/mcb463.
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In recent years the use of biomechanics in athletic training and performance has received a lot of attention, especially in university sports programs. Biomechanics is the study of the mechanical principles that control how biological things move or are constructed. It is critical for understanding the intricate relationships between physical performance, body mechanics, and injury prevention. The objective of this study is to establish how biomechanical variables can be designed and optimized in universities using mathematical modeling. In this study, a novel Emperor Penguin Search-driven Dynamic Feedforward Neural Network (EPSO-DFNN) is proposed to optimize the biomechanical parameters of athletes. Various biomechanical data are utilized from athletes participating in different sports. Biomechanical parameters include muscle activation patterns, joint angles, forces, and movement. The data was preprocessed using Z-score normalization from the obtained data. The Fast Fourier Transform (FFT) using features is extracted from preprocessed data. The proposed method is to identify the optimal configurations for athlete’s movements tailored to their sports and individual biomechanical profiles. The proposed method is the performance of various evaluation metrics such as F1-score (92.76%), precision (91.42%), accuracy (90.02%), and recall (89.69%). The result demonstrated that the proposed method effectively improved the performance in athletic capabilities compared to other traditional algorithms. This study demonstrates how mathematical modeling may be used to optimize biomechanical characteristics, providing insightful information that can be used to improve athletic performance and encourage safer behaviors in athletic settings.
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Cutmore, Tim R. H., and Patrick Celka. "Composite Noise Reduction of ERPs Using Wavelet, Model-Based, and Principal Component Subspace Methods." Journal of Psychophysiology 22, no. 3 (2008): 111–20. http://dx.doi.org/10.1027/0269-8803.22.3.111.
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This paper used three theoretically different algorithms for reducing noise in event-related potential (ERP) data. It examined the possibility that a hybrid of these methods could show gains in noise reduction beyond that obtained with any single method. The well-known ERP oddball paradigm was used to evaluate three denoising methods: statistical wavelet transform (wavelet-Z), a smooth subspace wavelet filter (wavelet-S), and subspace PCA. The six possible orders of serial application of these methods to the oddball waveforms were compared for efficacy in signal enhancement. It was found that the order was not commutative, with the best results obtained from applying the wavelet-Z first. Comparison of oddball and frequent trials in the grand average and in individual averages showed considerable enhancement of the differences. It was concluded that denoising to remove variance caused by rare sizeable artifacts is best done first, followed by state space PCA and a light-bias model-based wavelet denoising. The ability to detect and distinguish the effects of variables (such as task, drug effects, individual differences, etc.) on ERPs related to human cognition could be considerably advanced using the denoising methods described here.
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Vesala, G. T., V. S. Ghali, S. Subhani, and Y. Naga Prasanthi. "Material characterisation by enhanced resolution in non-stationary thermal wave imaging." Insight - Non-Destructive Testing and Condition Monitoring 63, no. 12 (2021): 721–26. http://dx.doi.org/10.1784/insi.2021.63.12.721.
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In the recent past, quadratic frequency-modulated thermal wave imaging (QFMTWI) has been advanced with a chirp z-transform (CZT)-based processing approach to facilitate enhanced subsurface anomaly detection, depth quantification and material property estimation with enhanced depth resolution. In the present study, the applicability of CZT-based phase analysis for foreign object defect detection in a structural steel sample using QFMTWI is validated through finite element-based numerical modelling rather than experimental verification due to limited available resources. Furthermore, the enhanced defect detection capability of the CZT phase approach is qualitatively compared with the frequency- and time-domain phase approaches using the defect signal-to-noise ratio (SNR) as a quality metric. Also, an empirical relationship between the observed phases and the thermal reflection coefficient is obtained, which recommends the CZT phase as a prominent approach for foreign material defect detection.
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Pataki-Bittó, Fruzsina, and Kata Kapusy. "Work environment transformation in the post COVID-19 based on work values of the future workforce." Journal of Corporate Real Estate 23, no. 3 (2021): 151–69. http://dx.doi.org/10.1108/jcre-08-2020-0031.
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Purpose The purpose of this study is to find out the future workforce’s work values and, based on them, to examine the work environment Generation Z are looking for in the situation of job search. Moreover, this study aims to provide ideas for organizations on how to transform the work environment for the post-COVID-19 era to attract and retain employees, especially the members of Generation Z. Design/methodology/approach The research design is based on the theory development method. Data were generated and collected from 28 focus groups and a survey (n = 773). First, initial coding was done with an affinity diagram, followed by the intermediate coding phase, when the authors compared the codings’ results and selected the core data. Finally, the advanced coding resulted in a work value model, which presents Generation Z’s core work value categories. Findings The paper presents a work value theory for Generation Z, which reflects their expectations of the physical work environment and the flexible work arrangements among the work values. To prepare for the post-COVID-19 era, this study suggests organizations applying hybrid working models. Practical implications Based on impacts and expected transformations in office work in the post-COVID-19 era, the paper calls attention to the critical management issues concerning Generation Z’s preferences and expectations. Originality/value The findings propose a broader work value theory approach that highlights the work environment’s convenience features and integrates values that support the employees’ desired lifestyle and well-being.
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Fotie, Ghislain, Stefano Gazzotti, Marco Aldo Ortenzi, and Luciano Piergiovanni. "Implementation of High Gas Barrier Laminated Films Based on Cellulose Nanocrystals for Food Flexible Packaging." Applied Sciences 10, no. 9 (2020): 3201. http://dx.doi.org/10.3390/app10093201.
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In this work, three types of cellulose nanocrystals (CNCs) were used: CNCSO3H extracted from wood pulp by sulfuric acid (H2SO4), CNCCOOH extracted from cotton linters by ammonium persulfate (APS) and CNCCOOR obtained by esterification of the previous two CNCCOOH and CNCSO3H. For a comparative assessment of gas barrier performance, plastic films such as PLA, PET, PE, PP, OPP and OPA were selected, coated with the three types of CNCs and finally laminated with a solvent-based polyurethanic adhesive. First, all dispersed CNCs were characterized by apparent hydrodynamic diameter and Z potential by means of dynamic light scattering (DLS) and electrophoretic light scattering (ELS) techniques, respectively, followed by the crystallinity index (XRD), thermogravimetric analysis (TGA) and evaluation of Fourier-transform infrared spectroscopy (FTIR), as well as the charges density. The surface chemistry of coated plastics (CNCs-P) was assessed by the Z potential through the electrokinetic technique (streaming potential method) and the optical contact angle (OCA). Lastly, laminated films (P-CNC-P) were evaluated by gas permeability measurements at 23 °C and 50–80% RH. It is worth noting that improvements between 90% and 100% of oxygen barrier were achieved after the lamination. This paper provides insights on the choice of cellulosic nanomaterials for the design and development of advanced and sustainable food packaging materials.
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Korte, Lisa, and Sabine Bohnet-Joschko. "Digitization in Everyday Nursing Care: A Vignette Study in German Hospitals." International Journal of Environmental Research and Public Health 19, no. 17 (2022): 10775. http://dx.doi.org/10.3390/ijerph191710775.
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(1) Background: Digitization in hospital nursing promises to transform the organization of care processes and, therefore, provide relief to nurse staffing shortages. While technological solutions are advanced and application fields numerous, comprehensive implementation remains challenging. Nursing leadership is crucial to digital change processes. This vignette study examined the effects of the motives and values on nurses’ motivation to use innovative technologies. (2) Methods: We asked hospital nurses in an online vignette study to assess a fictitious situation about the introduction of digital technology. We varied the devices on the degree of novelty (tablet/smart glasses), addressed motives (intrinsic/extrinsic), and values (efficiency/patient orientation). (3) Results: The analysis included 299 responses. The tablet vignettes caused more motivation than those of the smart glasses (Z = −6.653, p < 0.001). The dataset did not show significant differences between intrinsic and extrinsic motives. The nursing leader was more motivating when emphasizing efficiency rather than patient orientation (Z = −2.995, p = 0.003). (4) Conclusions: The results suggest efficiency as a motive for using known digital technologies. The nursing staff’s willingness to use digital technology is generally high. Management actions can provide a structural framework and training so that nursing leaders can ensure their staff’s engagement in using also unknown devices.
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Kubiak, Ireneusz, and Artur Przybysz. "Fourier and Chirp-Z Transforms in the Estimation Values Process of Horizontal and Vertical Synchronization Frequencies of Graphic Displays." Applied Sciences 12, no. 10 (2022): 5281. http://dx.doi.org/10.3390/app12105281.
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The electromagnetic protection of IT devices includes a number of organizational and technical measures aimed at ensuring control over radiated and conducted revealing emissions. This is of particular importance for ensuring information security in wireless communication and the processing of data presented in graphic form. In each of these cases, the occurring electromagnetic emissions pose the risk of a lack of electromagnetic immunity to the so-called eavesdropping process based on forming revealing emissions. Included in the elements of the security chain preventing electromagnetic eavesdropping on wireless communication and the devices building such systems are activities related to the determination of the Technical Device Security Level (TDSL) or its class. The above is related to the performance of electromagnetic emissions tests and identifying which of them must be treated as revealing emissions, which are only disturbances and do not threaten the security of the processed information. It is intuitively understandable that it is particularly important to ensure the security of interfaces that process video data. The nature of the electromagnetic emission signals generated by these interfaces means that the related information can be intercepted with the use of relatively simple methods, and under favorable circumstances even with the use of a receiving device not very technologically advanced. In the case of the electromagnetic safety assessment of video devices, common practice is therefore activities aimed at reconstructing information related to the video signal. This requires the parameters of the reconstructed image appropriate for the eavesdropped device operation mode and the conditions of recording the revealing emission signals to be determined. The article presents the results of works related to the analysis of the possibility of using spectral analysis methods (Fast Fourier FFT transform and Chirp-Z transform) to automate the process of determining the above-mentioned parameters in the case of reproducing images from emission signals recorded by using the ADC analog-to-digital converter.
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Deiotte, R., and R. La Valley. "COMPARISON OF SPATIOTEMPORAL MAPPING TECHNIQUES FOR ENORMOUS ETL AND EXPLOITATION PATTERNS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-4/W2 (October 19, 2017): 7–13. http://dx.doi.org/10.5194/isprs-annals-iv-4-w2-7-2017.
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The need to extract, transform, and exploit enormous volumes of spatiotemporal data has exploded with the rise of social media, advanced military sensors, wearables, automotive tracking, etc. However, current methods of spatiotemporal encoding and exploitation simultaneously limit the use of that information and increase computing complexity. Current spatiotemporal encoding methods from Niemeyer and Usher rely on a Z-order space filling curve, a relative of Peano’s 1890 space filling curve, for spatial hashing and interleaving temporal hashes to generate a spatiotemporal encoding. However, there exist other space-filling curves, and that provide different manifold coverings that could promote better hashing techniques for spatial data and have the potential to map spatiotemporal data without interleaving. The concatenation of Niemeyer’s and Usher’s techniques provide a highly efficient space-time index. However, other methods have advantages and disadvantages regarding computational cost, efficiency, and utility. This paper explores the several methods using a range of sizes of data sets from 1K to 10M observations and provides a comparison of the methods.
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Isha Das and Ishan Das. "Beyond the Equations: A Visual Journey into Multivariable Calculus." World Journal of Advanced Research and Reviews 21, no. 2 (2024): 2083–87. https://doi.org/10.30574/wjarr.2024.21.2.0408.
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Multivariable calculus, a cornerstone of advanced mathematics, often confounds learners with its abstract, multidimensional concepts—surfaces, gradients, and vector fields that defy simple intuition. Traditional tools like static graphs and equations fall short in bridging this gap. This paper introduces a novel visualization system designed to transform these complex ideas into an accessible, interactive experience. Leveraging real-time 3D rendering and user-adjustable parameters, the system enables students to explore functions like z = f(x, y) dynamically, revealing the hidden geometry of calculus. Tested with a cohort of learners, it demonstrated significant improvements—participants reported a 40% increase in comprehension of key concepts, such as partial derivatives, and educators noted enhanced engagement. While dependent on computational resources, this tool marks a leap forward in mathematical education, offering a visual journey that transcends the limitations of equations alone. This study outlines the system’s design, its impact, and its potential to redefine how multivariable calculus is taught and understood.
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Pailler, Lucas, Pascal Renard, Edith Nicol, Laurent Deguillaume, and Angelica Bianco. "How Well Do We Handle the Sample Preparation, FT-ICR Mass Spectrometry Analysis, and Data Treatment of Atmospheric Waters?" Molecules 27, no. 22 (2022): 7796. http://dx.doi.org/10.3390/molecules27227796.
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FT-ICR MS (Fourier-transform ion cyclotron resonance mass spectrometry) analysis has shown great potential to aid in the understanding of the extremely high molecular diversity of cloud water samples. The main goal of this work was to determine the differences in terms of formula assignment for analytical (i.e., measurement replicates) and experimental replicates of a given cloud water sample. The experimental replicates, obtained by solid phase extraction, were also compared to the results obtained for freeze-dried samples to evaluate whether the presence of salts interferes with the analysis. Two S/N ratios, generally adopted for atmospheric samples, were evaluated, and three different algorithms were used for assignment: DataAnalysis 5.3 (Bruker), Composer (Sierra Analytics), and MFAssignR (Chemical Advanced Resolution Methods Lab). In contrast to other works, we wanted to treat this comparison from the point of view of users, who usually must deal with a simple list of m/z ratios and intensity with limited access to the mass spectrum characteristics. The aim of this study was to establish a methodology for the treatment of atmospheric aqueous samples in light of the comparison of three different software programs, to enhance the possibility of data comparison within samples.
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Riji, Aminu Bello, Abubakar Dahiru Rimi, and Sulaiman Auwal Sabo. "Isolation and Structural Elucidation of Antimicrobial Molecules from Crinum ornatum (Aiton) Rhizome of Dutsin-Ma." Sahel Journal of Life Sciences FUDMA 1, no. 1 (2023): 169–88. http://dx.doi.org/10.33003/sajols-2023-0101-019.
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Crinum ornatum is a well-known traditional herb used used traditionally to treat various diseases including wounds, sores, vomiting, ear-aches, urinary tract infection, coughs and cold, renal and hepatic conditions, sexually transmitted diseases and backaches. The rhizomes of C. ornatum were collected, identified, air-dried and pulverized and subjected to cold extraction using hexane, dichloromethane (DCM), ethyl acetate (EtOAc) and methanol (MeOH) respectively. Antimicrobial activity of the extracts was determined using standard antimicrobial tests with Staphylococcus aureus, Salmonella typhi, Baccilus subtilis and Pseudomonas aeruginosa as test microorganisms. The most active extract was thereafter subjected to Gas chromatography Mass Spectrometry (GCMS) analysis, the Structural elucidation of the isolated molecule was performed using advanced spectroscopic techniques, including nuclear magnetic resonance (NMR), Fourier transform infrared (FTIR), Results of the antimicrobial activity test of the extracts showed appreciable antimicrobial activity against Staphylococcus aureus, Bacillus subtilis, Pseudomonas aeruginosa, Salmonella typhi (with MIC value ranging from 200 mg/ml to 25 mg/ml). The results demonstrated significant inhibitory effects, highlighting the potential of the compound as an antimicrobial agent. GCMS analysis identified 45 compounds in the most active (DCM) extract. Out of these, eight (8) compounds were most abundant (revealed >5% peak areas on GC chromatogram). These are: n-hexanedecanoic acid, hexadecanoic acid ethyl ester, 9,12-octadecadienoic acid (Z,Z),oleic acid, linoleic acid ethyl ester, ethyl oleate, squalene and tetrapentacontane. Antibacterial activity exhibited by the plant could be ascribed to the presence of the major phytocompounds in the plant and this provides scientific proof of some of ethnomedicinal uses of Crinum ornatum rhizome.
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Md. Shakeel Alam and Nidhi Shrivastava. "Exploring key compounds in callicarpa longifolia: a study on isolation and identification." Journal of Applied Pharmaceutical Research 13, no. 1 (2025): 75–85. https://doi.org/10.69857/joapr.v13i1.751.
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Background: The present study aims to extract the bioactive phyto-components from the hydroalcoholic extract of Callicarpa longifolia. The study also aims to isolate and characterize the phytochemicals through quantitative and qualitative measures. Methodology: The mixture of Toluene, Ethyl Acetate, and Acetic Acid (8:4:0.4) was used as a solvent system with the thin-layer chromatography (TLC) technique. Twelve distinct spots were observed, indicating the presence of a variety of compounds with Rf values ranging from 0.12 to 0.89. The specific fractions were isolated using silica gel column chromatography, which was further analyzed with TLC. Results and Discussion: Fraction F showed consistency with standard terpenoids and was subjected to advanced analytical techniques for further evaluation. UV-visible spectroscopy identified a key absorption peak at 288 nm, while Fourier-transform infrared (FTIR) spectroscopy revealed functional groups such as alcohols, hydroxyls, alkanes, alkenes, and carboxylic acids. The compound's structure and proton environment were confirmed through ^1H Nuclear Magnetic Resonance (NMR) spectroscopy. The compound was identified as Methyl 3,11-dioxo-olean-12-en-28-oate with the molecular formula C₃₁H₄₆O₄, supported by mass spectrometry (M+ peak at 482.33 m/z). Conclusion: The significant bioactive terpenoids identified in the C. longifolia hydroalcoholic extract highlight its potential for developing therapeutic agents, particularly for anti-inflammatory and anticancer applications. The detailed phytochemical characterization provides a robust foundation for future studies exploring the pharmacological and clinical applications of C. longifolia. Quantitative analysis and advanced spectroscopic techniques confirmed the compound's identity and established its importance in medicinal chemistry.
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K.L, Jhanavarshini. "QUANTUM-INSPIRED CRYPTO SOLUTIONS:PIONEERING SUSTAINABLE FREQUENCIES." International Journal of Advanced Research 13, no. 01 (2025): 12–40. https://doi.org/10.21474/ijar01/20160.
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This project aims to develop a secure application that leverages quantum, computing and Google Quantum AI with a strong focus on sustainability .The application will employ advanced cryptographic techniques, including XOR gate signal processing and control engineering binomial z-transform methods, to ensure robust security and effectively prevent cybercrime. The application will be powered by renewable energy sources, specifically solar power, hydroelectric energy, and wind turbines. These renewable sources will be integrated with the quantum processor, utilizing AI predictive optimization control to efficiently manage energy consumption and maximize performance.This integration ensures that the application operates at peak efficiency while minimizing its carbon footprint. For example, the quantum processors operation can be optimized to align with the availability of renewable energy. During peak sunlight hours, solar panels can supply abundant power to the quantum processor, while the AI system predicts and adjusts the processors workload accordingly. Similarly, hydroelectric and wind turbine-generated power can be monitored and managed to provide consis- tent energy, ensuring that the quantum processor maintains high efficiency even when renewable energy availability fluctuates. Overall, this project represents a pioneering effort in the integration of quantum computing with sustainable practices, aiming to provide a secure and eco-friendly solution for modern cryptographic challenges.
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Yu, F., H. Wang, and Z. Y. Chen. "A MODIFIED TWO-SCALE MICROWAVE SCATTERING MODEL FOR A GAUSSIAN-DISTRIBUTED CONDUCTING ROUGH SURFACE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 2141–46. http://dx.doi.org/10.5194/isprs-archives-xlii-3-2141-2018.
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A modified two-scale microwave scattering model (MTSM) was presented to describe the scattering coefficient of natural rough surface in this paper. In the model, the surface roughness was assumed to be Gaussian so that the surface height <i>z(x, y)</i> can be split into large-scale and small-scale components relative to the electromagnetic wavelength by the wavelet packet transform. Then, the Kirchhoff Model (KM) and Small Perturbation Method (SPM) were used to estimate the backscattering coefficient of the large-scale and small-scale roughness respectively. Moreover, the ‘tilting effect’ caused by the slope of large-scale roughness should be corrected when we calculated the backscattering contribution of the small-scale roughness. Backscattering coefficient of the MTSM was the sum of backscattering contribution of both scale roughness surface. The MTSM was tested and validated by the advanced integral equation model (AIEM) for dielectric randomly rough surface, the results indicated that, the MTSM accuracy were in good agreement with AIEM when incident angle was less than 30&amp;deg; (<i>&amp;theta;<sub>i</sub></i>&amp;thinsp;&amp;lt;30&amp;deg;) and the surface roughness was small (<i>ks</i>&amp;thinsp;=&amp;thinsp;0.354).
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Tian, Tuo. "Wearable sensor-based real time monitoring system for physical education teaching and training." Molecular & Cellular Biomechanics 22, no. 1 (2025): 1027. https://doi.org/10.62617/mcb1027.
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The comprehensive progress of mental and physical quality is majorly influenced by the college physical education, which is considered a part of the educational system. Developing a scientific and efficient evaluation index is significant to compute physical education teaching quality. The traditional methods of assessing performance in physical education often rely on subjective evaluations or delayed feedback from manual data collection. To overcome these challenges, a design based on a real-time monitoring system is introduced that leverages wearable biosensor technology to improve physical education teaching and training. Initially, some physiological indicators, namely heart rate, respiration rate, body temperature, and motion activity, were recorded and analysed to provide individualized insights into physical performance. Data pre-processing is performed using a median filter to reduce noise and Z-score normalization to standardize the input dataset. Key features are extracted using Fast Fourier Transform (FFT), enabling the identification of critical performance metrics. A Rat Swarm Optimized Efficient Random Forest (RSO-ERF) algorithm was introduced to enhance classification accuracy and optimize system performance. Experimental results demonstrate the proposed system’s effectiveness in providing real-time feedback, identifying individual fitness levels, and supporting adaptive teaching strategies. The increased system’s analysis tendency allows for customized training regimens, ongoing feedback, and improved physical health metrics monitoring. It also gives educators the ability to make data-driven decisions, encourage safety, and improve the educational experience for athletes and students. The findings underscore the potential of wearable biosensor technology combined with advanced algorithms in transforming physical education methodologies for improved engagement and performance outcomes.
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Zhou, Yuliang. "Research on real-time collection and analysis of student health and physical fitness data using biosensors." Molecular & Cellular Biomechanics 21, no. 4 (2024): 625. https://doi.org/10.62617/mcb625.
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Biosensors have emerged as efficient devices for monitoring personal fitness levels and health profiles as an important part of this technological development. With growing concern about students’ health and bodily fitness, educational and health experts as well as lawmakers have increasingly emphasized their importance. The goal of the study is to explore a real-time system for collecting and analyzing data on students’ physical fitness and health utilizing biosensors and advanced algorithms. The study proposed a novel Efficient Osprey Optimized Adjustable Random Forest (EOO-ARF) to predict the student health and physical fitness level. The student health and physical fitness data was gathered from a Kaggle source. To gather information using wearable biosensors to constantly monitor crucial health parameters such as blood oxygen levels, body temperature, heart rate, and physical activity. The data was pre-processed using the Z-score normalization to enhance the quality of the data. The Principal Component Analysis (PCA) was used to extract the features from pre-processed data. This model takes the indices of students’ physical health as the input parameters and produces an overall health score. EOO is used for optimization, and the process aims at selecting the most appropriate features to identify the health metrics most relevant to influencing students’ general fitness levels. ARF is applied to predict the health and fitness levels of students. The performance of the suggested approach is evaluated in terms of F1-score (98.13%), recall (98.2%), and accuracy (98.44%). The integration of biosensors with innovative analytic methods could transform the monitoring and improvement of the physical fitness and health of students take place in real-time.
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Zavarize, Danilo Gualberto, João G. de Oliveira Neto, Kamila Rodrigues Abreu, Alejandro Pedro Ayala, Francisco Ferreira de Sousa, and Adenilson Oliveira dos Santos. "A Novel Fe(III)-Complex with 1,10-Phenanthroline and Succinate Ligands: Structure, Intermolecular Interactions, and Spectroscopic and Thermal Properties for Engineering Applications." Processes 13, no. 5 (2025): 1267. https://doi.org/10.3390/pr13051267.
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A new complex, tetrakis(1,10-phenanthroline)-bis(succinate)-(µ₂-oxo)-bis(iron(III)) nonahydrate, [Fe2(Phen)4(Succinate)2(μ-O)](H2O)9, was synthesized using the slow evaporation method. This study provides a comprehensive characterization of this coordination compound, focusing on its structural, spectroscopic, and thermal properties, which are relevant for applications in catalysis, material science, and chemical engineering processes. Single-crystal X-ray diffraction (XRD), Raman spectroscopy, Fourier-transform infrared (FT-IR), ultraviolet-visible (UV-Vis) spectroscopy, and thermoanalytical analyses were employed to investigate the material properties. Intermolecular interactions were further explored through Hirshfeld surface analysis. XRD results revealed a monoclinic crystal system with the C2/c space group, lattice parameters: a = 12.7772(10) Å, b = 23.0786(15) Å, c = 18.9982(13) Å, β = 93.047(2)°, V = 5594.27(7) Å3, and four formulas per unit cell (Z = 4). The crystal packing is stabilized by C–H⋯O, C–O⋯H, C–H⋯π, and π⋯π intermolecular interactions, as confirmed by vibrational spectroscopy. The heteroleptic coordination environment, combining weak- and strong-field ligands, results in a low-spin state with an estimated crystal field stabilization energy of −4.73 eV. Electronic properties indicate direct allowed transitions (γ = 2) with a maximum optical band gap of 2.66 eV, suggesting potential applications in optoelectronics and photochemical processes. Thermal analysis demonstrated good stability within the 25–136 °C range, with three main stages of thermal decomposition, highlighting its potential for use in high-temperature processes. These findings contribute to the understanding of Fe(III)-based complexes and their prospects in advanced material design, catalytic systems, and process optimization.
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E., E., K. A. Naminova, I. S. Abdullayev, A. E. Ilyin, R. A. Shichiyakh, and E. Laxmi Lydia. "Optimizing Financial Fraud Detection: Understandings from Variable Selection with Neutrosophic Vague Soft Set." International Journal of Neutrosophic Science 25, no. 3 (2025): 219–30. http://dx.doi.org/10.54216/ijns.250320.
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Neutrosophy is the neutralities study and prolongs the discussion of the truth of opinions. Neutrosophic logic might be used in all sectors, to provide the solution for the indeterminate challenges. Some real-time data experience issues like inconsistency, incompleteness, and indeterminacy. A fuzzy set (FS) offers an uncertain solution, and an intuitionistic fuzzy set (IFS) processes partial data, but both fail to handle uncertain data. Financial fraud, believed as a deceptive strategy to gain financial assistance, has recently become a common threat in organizations and companies. Traditional methods namely manual inspections and verifications are costly, time-consuming, and imprecise to identify such fraudulent actions. With the development of artificial intelligence (AI), machine learning (ML)-based algorithms are applied logically to identify fraud transactions by investigating a larger amount of financial data. Therefore, the study offers an Optimizing Financial Fraud Detection using Bayesian Optimization and Variable Selection with Neutrosophic Vague Soft Set (OFFDBO-VSNVS) Algorithm. The OFFDBO-VSNVS model presents an optimized framework for fraud detection by integrating advanced variable selection techniques and classification models. Initially, the OFFDBO-VSNVS technique applies the Z-score data normalization technique to transform input data into a compatible layout. Next, the grey wolf optimizer (GWO)--based feature selection to effectively reduce dimensionality and highlight the most relevant features. For the classification and detection of financial fraud, the neutrosophic vague soft set (NVS) model can be employed. Eventually, the Bayesian optimization (BO) model adjusts the hyperparameter values of the NVS algorithm optimally and outcomes in greater classification performance. The stimulated outcome study of the OFFDBO-VSNVS model occurs and the outcomes are examined in terms of changing features. The experimental study represented the superiority of the OFFDBO-VSNVS method across the existing state-of-the-art methods
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Domi, Domi, and G. Usha. "Deep Learning Driven LSTM with Spider Wasp Optimizer Algorithm for Frictional Force Based Landslides Prediction Model." Journal of Intelligent Systems and Internet of Things 14, no. 1 (2024): 293–304. http://dx.doi.org/10.54216/jisiot.140123.
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Landslides establish a main geologic threat of strong concern in many parts of the world. The vigor of soil, rocks, or other rubbish moving down a slope can destroy whatever in its track. Landslides happen in an extensive variety of geological and structural settings, geomechanical contexts, and as a response to numerous triggering and loading procedures. They are frequently related to other main natural disasters like floods, earthquakes, and volcanic waves. Landslides occasionally attack without noticeable warning. While only some cases have been examined the earlier, modern monitoring models are certain to deliver a wealth of novel quantitative observations based on SAR (synthetic aperture radar) and GPS technology for mapping the surface velocity area. This study emphasizes the latent of incorporating advanced machine learning (ML) models with geophysical data to improve prediction of landslides and risk management strategies. This study develops a Predicting Landslides with frictional-based Deep Learning using Spider Wasp Optimizer (PLFFDL-SWO) Method. The major intention of the PLFFDL-SWO technique lies in the robust frictional force based on predicting landslides. In the presented PLFFDL-SWO model, Z-score normalization is performed to transform the raw data into compatible format. Then, the long short-term memory (LSTM) model is utilized for the prediction of landslides. LSTM is a recurrent neural network (RNN) type, for predicting landslides based on frictional force data. Traditional landslide prediction methods often struggle with temporal dynamics and nonlinear relationships inherent in geophysical data. Finally, the spider wasp optimizer (SWO) algorithm is exploited for the optimal hyper parameter adjustment of the LSTM model to improve prediction accuracy. The experimentation result investigation of the PLFFDL-SWO technique can be examined by employing a benchmark dataset. The simulation outcomes reported the supremacy of the PLFFDL-SWO technique under different measures
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Qian, Guhan, Hongrong Zhang, Aine Knott, Jon Zettervall, Ingunn Stromnes, and Paolo Provenzano. "Abstract C020: Unconvering the hidden immunosuppressive landscape in pancreatic ductal adenocarcinoma." Cancer Research 84, no. 2_Supplement (2024): C020. http://dx.doi.org/10.1158/1538-7445.panca2023-c020.
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Abstract Pancreatic ductal adenocarcinoma (PDA) is one of the deadliest forms of cancer with an extremely low survival rate. Despite the success of therapeutic T cells in hematologic cancers, many solid tumors, including PDA, remain unresponsive with such therapies, partly due to its mechanically complex, dense, and immunosuppressive stroma. Therefore, understanding the dynamic interplay between therapeutic T cells and the tumor microenvironment (TME) is crucial for revealing engineering targets for next-generation immunotherapies. We approach this problem with genetically engineered KPC (KrasLSL-G12D/+; Trp53LSL-R172H/+; Pdx-1-Cre) mouse models that recapitulates PDA disease progression and stromal dynamics. Within live tumor slices from primary tumors, we are defining how stromal components such as dense collagen fiber networks and tumor-associated macrophages (TAMs) orchestrate an immunosuppressive landscape. We employ multiphoton laser scanning microscopy (MPLSM) to generate multiphoton excitation of fluorescence (cell dyes and immunofluorescence) and second harmonic generation (SHG) for collagen fibers to acquire multidimensional data (x, y, z, c, t) of T cell migration and interaction within the TME. We subsequently reveal T cell migration and interaction as a function of its physical and biological ECM components using advanced computer vision and machine learning algorithms based on the Clustered Random Convolutional Kernel Transform (cROCKET), revealing a hidden landscape in the feature space. Perturbations to the TME in KPC mice with CCR2 inhibitor CCX598 (in vivo) and clodronate liposomes (ex vivo) deplete CD11b+ myeloid cells, resulting in altered behaviors of the infiltrating T cells. Anti-PD-1 monoclonal antibody neutralizes the PD-1/PD-L1 axis in T cells, resulting in enhanced migration and infiltration in tumor slices. Citation Format: Guhan Qian, Hongrong Zhang, Aine Knott, Jon Zettervall, Ingunn Stromnes, Paolo Provenzano. Unconvering the hidden immunosuppressive landscape in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C020.
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Lacroix-Andrivet, Oscar, Marie Hubert-Roux, Corinne Loutelier Bourhis, Samira Moualdi, Anna Luiza Mendes Siqueira, and Carlos Afonso. "Characterization of Base Oil and Additive Oxidation Products from Formulated Lubricant by Ultra-High Resolution Mass Spectrometry." Lubricants 11, no. 8 (2023): 345. http://dx.doi.org/10.3390/lubricants11080345.
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Automotive formulated lubricants are high value products composed of 80% base oil and 20% various additives. During their life service, lubricants are exposed to several factors that will cause degradation over time, such as high temperature, shear, and oxidation. Base oil is a complex combination of hydrocarbons that are relatively sensitive to oxidation. During the initiation phase of oxidation, free radicals are formed, leading to the production of hydroperoxide ROOH and an alkyl radical R•. These compounds will react with the base oil molecules to form aldehydes, ketones, and carboxylic acids in the termination phase. Owing to the molecular complexity of these mixtures, Fourier transform mass spectrometry seems to be the most appropriate tool to cover their wide range of compounds due to its ultra-high resolving power and mass accuracy. In this study, a native formulated lubricant and its different oxidized states at 140 °C under air flow (3, 5, 7, 8, and 9 days of oxidation) were analyzed by FTICR MS. The combination of atmospheric pressure chemical ionization (APCI) was used to achieve a non-selective ionization of molecules, including base oils, while Electrospray ionization (ESI) was used to selectively ionize acidic molecules. Apparent Kendrick mass defect (aKMD) plots were used to separate homologous series of molecules on different horizontal lines on the basis of the CH2 repetition unit. Aging of lubricants was mainly characterized by a rapid consumption of certain additive families, such as molybdenum dithiocarbamates (MoDTCs) and zinc dithiophosphate (ZnDTPs), but also by the emergence of many oxidation products. Thus, the presence of aldehydes, ketones, and acids was characterized in the early stage of aging while larger products from polymerization were observed in a more advanced stage of aging. Interaction products between peroxy radicals and hindered phenols/alkyl diphenylamines (ADPAs) antioxidations were elucidated toward the high m/z. The formation of such products can be explained by trapping mechanisms of these additives at high temperature (>120 °C). Other types of interaction products were observed with the formation of antioxidant complexes. Additive degradation products were also characterized. For instance, polyisobutenyl succinimide dispersant oxidation products were clearly evidenced on the aKMD plots due to the gaps of 56 Da between each point. Overall, this study demonstrated the efficiency of the aKMD approach, and the use of ESI/APCI to characterize base oil and additive oxidation products.
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Cengiz, Taner. "Periodic structures of Great Lakes levels using wavelet analysis." Journal of Hydrology and Hydromechanics 59, no. 1 (2011): 24–35. http://dx.doi.org/10.2478/v10098-011-0002-z.
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Periodic structures of Great Lakes levels using wavelet analysisThe recently advanced approach of wavelet transforms is applied to the analysis of lake levels. The aim of this study is to investigate the variability of lake levels in four lakes in the Great Lakes region where the method of continuous wavelet transform and global spectra are used. The analysis of lake-level variations in the time-scale domain incorporates the method of continuous wavelet transform and the global spectrum. Four lake levels, Lake Erie, Lake Michigan, Lake Ontario, and Lake Superior in the Great Lakes region were selected for the analysis. Monthly lake level records at selected locations were analyzed by wavelet transform for the period 1919 to 2004. The periodic structures of the Great Lakes levels revealed a spectrum between the 1-year and 43- year scale level. It is found that major lake levels periodicities are generally the annual cycle. Lake Michigan levels show different periodicities from Lake Erie and Lake Superior and Lake Ontario levels. Lake Michigan showed generally long-term (more than 10 years) periodicities. It was shown that the Michigan Lake shows much stronger influences of inter-annual atmospheric variability than the other three lakes. The other result was that some interesting correlations between global spectrums of the lake levels from the same climatic region were found.
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Hasan, Golan, and Ervi Scorpianti. "The influence of usefulness, entertainment, interaction, enjoyment, and familiarity to purchase music platform subscriptions in Millennials and Gen-z communities through trust mediation." Jurnal Manajemen dan Pemasaran Jasa 15, no. 2 (2022): 161–76. http://dx.doi.org/10.25105/jmpj.v15i2.14071.
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Advances in technology significantly transform the means of communication between users and companies. The music industry is also experiencing technological innovation as more consumers subscribe to paid and free online streaming services. Therefore, this study aimed to determine the effect of usefulness, entertainment, interaction, enjoyment, and familiarity on purchase intention for music streaming platform subscriptions in millennials and gen-z communities in Batam City through trust mediation. A quantitative method was adopted with data collected through questionnaires from 348 respondents and processed using the Partial Least Square program. The results indicated that familiarity and interaction significantly influenced purchase intention through trust mediation. As managerial implications, familiarity must be increased for trust and interaction to influence purchase intention. This study only focused on millennials and gen-z communities and conducted a survey through Google Forms. Therefore, future studies could expand the scope beyond a single generation or region.
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Tangjitsitcharoen, Somkiat, Prae Thesniyom, and Suthas Ratanakuakangwan. "A wavelet approach to predict surface roughness in ball-end milling." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 231, no. 14 (2015): 2468–78. http://dx.doi.org/10.1177/0954405415605951.
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This research proposed an advance in the prediction of the in-process surface roughness during the ball-end milling process by utilizing the wavelet transform to monitor and decompose the dynamic cutting forces. The chatter detection system has been adopted from the previous research of the author to avoid the chatter first, and hence, the dynamic cutting force ratio is introduced to predict the in-process surface roughness during the normal cutting by taking the ratio of the decomposed dynamic cutting force in X axis to that in Z axis. The Daubechies wavelet transform is employed in this research to analyze the in-process surface roughness. The experimentally obtained results showed that the surface roughness frequency occurred at the same level of the decomposed dynamic cutting forces although the cutting conditions are changed. It is understood that the in-process surface roughness can be predicted effectively under various cutting conditions referring to the proposed monitoring system.
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Bremer, M., and M. Grewing. "An Iterative Method for the Reconstruction of Two-Dimensional Density Distributions." Symposium - International Astronomical Union 155 (1993): 218. http://dx.doi.org/10.1017/s0074180900170809.
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As hydrodynamic models of planetary nebulae advance from 1D to 2D calculations, it becomes desirable to make the same step for reconstruction techniques, which aim at deriving from the 2D intensity distributions of PNe images their 3D structure. A basic step is the determination of a symmetry axis and its orientation in space which can be described by two angles, one measured in the plane of the sky, and one measured with respect to the tangential plane. While the first one can be determined from the images, e.g. by applying the criterion of maximum normalized correlation between the object halves, which we found to yield the best results, the second angle is treated as a free parameter (see below). The steps of the iterative reconstruction algorithm are the following (with image(x, y) = input image): 1.Fill a 3D kartesian density grid(xyz) (random or continuous), observing the constraint ∫ grid(xyz)dz = image(x, y), where z is along the line of sight.2.Transform to cylindrical symmetry system (r, z', ϕ) and read out density (r, z') averaging over ϕ.3.Return density(r, z') into grid(xyz) and normalize the ∫ grid(xyz)dz to match the input image.4.Return to (2.) as long as two subsequent density(r, z') estimations differ by more than a specified limit.
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Tofa, Tajkia Syeed, Karthik Laxman Kunjali, Paul Swaraj, and Joydeep Dutta. "Visible light photocatalytic degradation of microplastic residues with zinc oxide nanorods." Environmental Chemistry Letters 17 (February 16, 2019): 1341–46. https://doi.org/10.1007/s10311-019-00859-z.
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Microplastics have recently become a major environmental issue due to their ubiquitous distribution, uncontrolled environ- mental occurrences, small sizes and long lifetimes. Actual remediation methods include filtration, incineration and advanced oxidation processes such as ozonation, but those methods require high energy or generate unwanted by-products. Here we tested the degradation of fragmented, low-density polyethylene (LDPE) microplastic residues, by visible light-induced het- erogeneous photocatalysis activated by zinc oxide nanorods. The reaction was monitored using Fourier-transform infrared spectroscopy, dynamic mechanical analyser and optical imaging. Results show a 30% increase of the carbonyl index of resi- dues, and an increase of brittleness accompanied by a large number of wrinkles, cracks and cavities on the surface. The degree of oxidation was directly proportional to the catalyst surface area. A mechanism for polyethylene degradation is proposed
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Lipiński, Konrad. "Niektóre problemy tożsamości czynu ciągłego (art. 12 § 1 k.k.). Uwagi na marginesie wyroku Sądu Apelacyjnego w Warszawie z 4 września 2019 r. (II AKa 53/19)." Studia Iuridica, no. 86 (June 14, 2021): 129–40. http://dx.doi.org/10.31338/2544-3135.si.2020-86.8.
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The article explores the issue of unity of a continuous act referred to in Art. 12 para 1 of the Criminal Code. The author considers whether and (if so) to what extent it is permissible for the adjudicating court to transform separate, concurrent offenses (as listed in the indictment) into one - supplemented by an element of continuity - continuous act of Art. 12 para 1 CC. According to the thesis advanced in the article, such a transformation should be considered admissible as long as the attributed offence does not encompass any additional behavior not expressly listed in the indictment, occurring chronologically before the first behavior of the indictment, after the last one, or between them.
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Steinberg, Katherine, and Betar M. Gallant. "Revealing the Functionality of Li2CO3 in the Li-Metal SEI Via Study of Gas-Reacted Li Films." ECS Meeting Abstracts MA2024-01, no. 1 (2024): 90. http://dx.doi.org/10.1149/ma2024-01190mtgabs.
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The solid electrolyte interphase (SEI) governs transport and reactivity at lithium interfaces, so its structure and composition are essential factors in improving the cyclability of next-generation lithium-metal anodes (1). An ideal SEI should passivate Li against continuous reactions with electrolyte while promoting facile transport of Li+ ions. However, achieving these properties is challenging, in part because our understanding of the relative desirability of different SEI materials is often based on qualitative relationships between characterization and cell performance; quantitative experimental conductivity (2, 3) and stability (4) measurements are limited. As a further complication, the highly reductive conditions (-3.04 V vs SHE) and the complex nanoscale structure of the SEI can lead to markedly different behavior in practical contexts compared to bulk environments (2, 5, 6). In previous work, our group developed techniques to synthesize single-component, nanoscale films of LiF and Li2O on Li, enabling direct measurements of their transport properties and reactivity in relevant electrolytes (6-8). Here, we turn to Li2CO3, which has a mixed reputation as an SEI material. While many papers assert its desirability based on high ionic conductivity (9-12), others raise concerns related to reductive instability (13-15). In this work, we synthesized Li2CO3 films via sequential reactions of O2 and CO2 on polished lithium surfaces at slightly elevated temperature (175-200°C). Scanning electron microscopy (SEM) and air exposure tests showed that the prepared films are conformal, tens of nanometers thick, and relatively pinhole-free. Fourier transform infrared spectroscopy (FTIR) was used to confirm the speciation of the films, and titration-based quantification yielded insights into their composition. We found that the formation of Li2CO3 is associated with generation of Li2O and Li2C2, confirming that the reductive instability of Li2CO3 results in the evolution of a more reduced inner SEI layer at the Li | Li2CO3 interface. We also studied the stability of films at the SEI | electrolyte interface, performing electrolyte soak tests then assessing native SEI evolution using FTIR and titration-based quantification of LiF. We found that Li2CO3 is poorly-passivating in fluorinated electrolytes, leading to continuous formation of native SEI. However, in 1M LiClO4 PC electrolyte, the Li2CO3 film remains intact, enabling the use of electrochemical impedance spectroscopy (EIS) to study film transport properties. This analysis reveals an ionic conductivity of ~4-8 nS/cm, which is substantially greater than ionic conductivities previously measured in Li2O (~1 nS/cm) and LiF (~0.5 nS/cm) (6). Together, these results show that though Li2CO3 has some stability limitations, it could promote facile Li+ ion transport as a stable meso-SEI layer in less-fluorinated electrolytes. This work was funded by the 2022-2023 ECS Toyota Young Investigator Fellowship award. References E. Peled and S. Menkin, Journal of The Electrochemical Society, 164, A1703 (2017). S. Lorger, K. Narita, R. Usiskin and J. Maier, Chemical Communications, 57, 6503 (2021). P. Lu and S. J. Harris, Electrochemistry Communications, 13, 1035 (2011). B. S. Parimalam, A. D. MacIntosh, R. Kadam and B. L. Lucht, Journal of Physical Chemistry C, 121, 22733 (2017). S. Shi, Y. Qi, H. Li and L. G. Hector, (2013). R. Guo and B. M. Gallant, Chemistry of Materials, 32, 5525 (2020). R. Guo, D. N. Wang, L. Zuin and B. M. Gallant, Acs Energy Letters, 6, 877 (2021). M. F. He, R. Guo, G. M. Hobold, H. N. Gao and B. M. Gallant, Proceedings of the National Academy of Sciences of the United States of America, 117, 73 (2020). E. Plichta, S. Slane, M. Uchiyama, M. Salomon, D. Chua, W. B. Ebner and H. W. Lin, J. Electrochem. Soc., 136, 1865 (1989). D. Aurbach, A. Zaban, Y. Gofer, E. Ely, I. Weissman, O. Chusid and O. Abramson, Recent studies of the lithium-liquid electrolyte interface Electrochemical, morphological and spectral studies of a few important systems, in Journal of Power Sources, p. 76 (1995). T. Osaka, T. Momma, Y. Matsumoto and Y. Uchida, Journal of Power Sources, 68, 497 (1997). J. Besenhard, M. W. Wagner, M. Winter, A. D. Jannakoudakis, P. D. Jannakoudakis and E. Theodoridou, Journal of Power Sources, 413 (1993). K. Leung, F. Soto, K. Hankins, P. B. Balbuena and K. L. Harrison, Journal of Physical Chemistry C, 120, 6302 (2016). N. Tian, C. Hua, Z. Wang and L. Chen, Journal of Materials Chemistry A, 3, 14173 (2015). B. Han, Z. Zhang, Y. C. Zou, K. Xu, G. Y. Xu, H. Wang, H. Meng, Y. H. Deng, J. Li and M. Gu, Advanced Materials, 33 (2021). Figure 1
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Raulo, Avinash, Saheed Adewale Lateef, and Golareh Jalilvand. "Development of a Resilient Binder for Stable Cycling of High Sulfur Loading Lithium-Sulfur Batteries." ECS Meeting Abstracts MA2024-02, no. 5 (2024): 601. https://doi.org/10.1149/ma2024-025601mtgabs.
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Lithium-sulfur battery (LSB) is considered one of the most promising alternatives to modern lithium-ion batteries (LIBs) due to its high theoretical energy density (2600 Wh kg–1) – five times higher than that of LIBs. Despite its high theoretical energy density, the path to deployment of LSBs has not been paved due to its poor cycle life. One of the root causes of capacity decay in LSBs is the significant volume change of sulfur during lithiation and delithiation, which results in severe structural damage, thus cathode degradation and capacity loss. Such an effect is amplified in electrodes with high sulfur loadings, which typically involve thicker electrodes. Over the years, a substantial number of studies have reported various approaches to address the challenges in LSBs. Novel structural sulfur hosts are predominantly used to accommodate sulfur volume expansion. However, the excessive hollow spaces in those host structures decrease the practical energy density of sulfur cathode. Therefore, other approaches to improve mechanical integrity of sulfur cathode during lithiation-delithiation cycles, without compromising the LSB energy density is imperative. Binder plays a critical role in sulfur cathode by glueing the active material and conductive carbon together and to the current collector and thereby, maintaining the mechanical framework of the electrode.1 Accordingly, modifying binders to provide desired structural and mechanical characteristics is a promising approach to enhance longevity of LSBs, while preserving the high energy density of the battery. PVDF is a widely used binder in battery electrodes, due to its excellent chemical, electrochemical, and thermal stability in wide ranges of voltage and temperature. However, its adhesive properties are insufficient to withstand the significant stresses that highly loaded sulfur cathodes experience during both the electrode preparation (due to shrinkage of thick electrode film after slurry deposition), and battery cycling (due to volume variation of sulfur). These stresses further result in the formation of cracks and subsequently an increase in electrode impedance and ultimately, cell failure.2 Among various approaches to alleviate the insufficient adhesion and mechanical properties of PVDF, crosslinking is considered a potential solution. Cross-linked PVDF can provide a more stable framework for the active material and conductive agents through a covalently bonded 3D nanonet structure. To date, electromagnetic beam radiation has been the most common technique to crosslink PVDF.3,4 However, crosslinking through radiation is impractical for batteries on an industrial scale due to its complicated, expensive, and safety-demanding process. On the contrary, chemical methods can be simple and scalable, thus are highly preferred to cross-link PVDF for battery electrodes. However, cross-linking PVDF through chemical methods is known to be challenging due to its high thermal stability, which requires temperatures above 250°C for its effective cross-linkage. This is while most chemical crosslinking agents are unstable at such high temperatures. To the best of our knowledge, there has been no report on cross-linking PVDF through simple and scalable chemical methods for battery applications. In this work we present a simple chemical process in solution phase at room temperature for rapid crosslinking of PVDF, making it a promising method to produce crosslinked PVDF binder for high sulfur loading cathodes. Through this method, in addition to the adhesive properties of PVDF, the ionic conductivity of PVDF is also improved. The process involves the controlled addition of organically dissolved PVDF to an aqueous basic solution containing Li ions. Chemical evaluations are conducted using electron paramagnetic resonance (EPR), Fourier transform infrared (FTIR), and X-ray photoelectron spectroscopy (XPS) to confirm the cross-linkage of PVDF. The formation of a resilient structure of the crosslinked PVDF is ascertained by tensile measurement. Moreover, electrochemical measurements are carried out to study the ionic conductivity, charge-discharge process, and cycle performance of the cross-linked PVDF. The cathode with cross-linked PVDF binder at an areal sulfur loading of 4mg cm-2 remained stable for 200 cycles at 0.1 C-rate. Further post-cycling characterizations show improved structural uniformity of the electrodes using cross-linked PVDF. The obtained results suggest cross-linked PVDF as a promising binder for LSBs with high energy density and longevity. References (1) Kannan, S. K.; Joseph, J.; Joseph, M. G. Energy Fuels 2023, 37 (9), 6302–6322. https://doi.org/10.1021/acs.energyfuels.3c00155. (2) Zou, F.; Manthiram, A. Advanced Energy Materials 2020, 10 (45), 2002508. https://doi.org/10.1002/aenm.202002508. (3) Gao, Y.; Tan, Z.; Song, Z.; Qian, J.; Fu, C.; Nie, W.; Ran, X. Polymer Testing 2021, 99, 107202. https://doi.org/10.1016/j.polymertesting.2021.107202. (4) Fan, K.; Liu, C.; Zeng, H.; Li, J. H. High Energy Chem 2021, 55 (6), 436–441. https://doi.org/10.1134/S0018143921060059.
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Yusop, Hanafi M., M. F. Ghazali, M. F. M. Yusof, M. A. Pi Remli, and M. Samykano. "Fault Identification in Pipeline System Using Normalized Hilbert Huang Transform and Automatic Selection of Intrinsic Mode Function." MATEC Web of Conferences 221 (2018): 02002. http://dx.doi.org/10.1051/matecconf/201822102002.
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Pressure transient analysis has been widely used to monitor the condition of pipelines and its assessment in water distribution systems. This is a low-cost nonintrusive technique with the ability to locate uncertainties (leak, pipe fitting, blockage) at a greater distance from the measurement point. In this research, Normalised Hilbert Huang Transform (NHHT) is used as the method to analyse the pressure transient signal. However, this method has difficulty in selecting the suitable intrinsic mode function (IMF) for the advance data analysing. As an alternative, Integrated Kurtosis-based Algorithm for z-filter Technique (Ikaz), which allows automatic selection of intrinsic mode function (IMF) been used to substitute the NHHT limitation in this study. The analysis is conducted on a 67.9-meter Medium High-Density PolyEthylene (MDPE) pipe installed with single artificial leak simulator at a water pressure in the range of 1-4 bar.
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Wang, Hai-Gang, Yong-Lei Lin, and Wu-Qiang Yang. "Investigation and analysis of a fluidized bed dryer by process tomography sensor." Petroleum Science 17, no. 2 (2019): 525–36. http://dx.doi.org/10.1007/s12182-019-00406-z.
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AbstractIn the pharmaceutical industry, fluidized beds are typically used for pellets drying, coating and granulation. The gas–solids flow characteristic in the process plays an important role to control the heat and mass transfer as well as the end-point product quality. Therefore, it is necessary to investigate the flow characteristics based on advanced measurement technologies. In this research, electrical capacitance tomography (ECT) sensor with eight electrodes was used to investigate the pharmaceutical fluidized bed drying process with different operation conditions. Key process parameters including solids concentration, particle moisture and capacitance signals in the process are given and analysed based on the ECT sensor. In addition, the fluidized bed process with Wurster tube is also investigated based on this ECT sensor. The effect of Wurster tube on the hydrodynamic behaviour and the dominant frequency spectrum distribution in the chamber were analysed based on fast Fourier transform. Test results reveal that process moisture change can be addressed from the raw capacitance of adjacent electrode pair combined with calibration model. Experimental result also indicates that ECT technology can provide useful information for process monitor in a fluidized bed dryer.
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Macrander, Albert, Lahsen Assoufid, Suresh Narayanan, and Ruben Khachatryan. "Diffuse X-ray scattering from polished silicon: application of the distorted wave Born approximation." Journal of Synchrotron Radiation 29, no. 2 (2022): 447–55. http://dx.doi.org/10.1107/s1600577522000534.
Full textAbstract:
Measured diffuse X-ray scattering data for a `smooth' as well as for a `rough' silicon sample were fit to theoretical expressions within the distorted wave Born approximation (DWBA). Data for the power spectral density (PSD) for both samples were also obtained by means of atomic force microscopy and optical interferometry. The Fourier transforms of trial correlation functions were fit to the PSD data and then applied to the DWBA formalism. The net correlation functions needed to fit the PSD data for each sample comprised the sum of two terms with different cutoff lengths and different self-affine fractal exponents. At zero distance these correlation functions added up to yield net values of σ2 = (2)2 and (71)2 Å2 for the smooth and rough samples, respectively. X-ray scattering data were obtained at beamline 1-BM of the Advanced Photon Source. Data and fits at values of q z = 0.05 and 0.10 Å−1 for the smooth sample are reported. Good fits for the smooth sample were obtained at both q z values simultaneously, that is, identical fitting parameters were applied at both values of q z . The smooth sample also exhibited weak Yoneda wings and a clear distinction between the strong specular scattering and the weak diffuse scattering. Data for the rough sample were qualitatively different and exhibited very weak scattering at the specular condition in contrast to extremely large Yoneda wings. Fits for the rough sample are reported for q z = 0.04, 0.05, and 0.06 Å−1. Although the large Yoneda wings could be fit quite well in both position and amplitude, scattering near the specular condition could not be equally well fit by applying the same fitting parameters at all values of q z . Albeit imperfect, best-fitting results at the specular condition were obtained by invoking only diffuse scattering, that is, without including a separate theoretical expression for specular scattering.
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Chen, Zhisheng. "Metaverse in tourism service: Exploring digital tourism innovation." Metaverse 5, no. 1 (2024): 2664. http://dx.doi.org/10.54517/m.v5i1.2664.
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<p>This study explores the integration and challenges of metaverse technology in tourism, analyzing perspectives from the industry, travelers, and management. It underscores the digital transformation accelerated by the COVID-19 pandemic, technological advances, and Generation Z influences. The research identifies key applications of metaverse technology, such as digital eco-tours, museums, cultural performances, and souvenirs, which redefine the traditional tourism model. It also examines the unique experiences provided to tourists by the metaverse at various stages of travel—before, during, and after trips—and evaluates the implications for customer perception and behavior. From a management viewpoint, the study highlights the necessity for thorough assessments of metaverse implementations in customer relations, marketing, and organizational strategies to fully gauge its impact. The discussion section addresses the long-term effects on traditional tourism practices and destinations and articulates how these technologies transform customer engagement and operational paradigms. This research provides a comprehensive overview of how metaverse technology reshapes the tourism landscape, offering insights for future technological integration and strategic development.</p>
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Shermuradova, Malika, Mavlyuda Gadoeva, Shukhrat Rahmatov, Uktamjon Abdullaev, and Dilshod Aralov. "Study of algorithmic approaches to digital signal filtering and the influence of input quantization on output accuracy." E3S Web of Conferences 627 (2025): 04016. https://doi.org/10.1051/e3sconf/202562704016.
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This article explores the design and application of intelligent control systems tailored for industrial and production environments, with a particular focus on integrating advanced digital filtering and noise reduction strategies. Traditional adaptive control systems often struggle to maintain flexibility and responsiveness in uncertain and dynamic conditions. In response, the study investigates the potential of intelligent control architectures, enhanced by neural networks and fuzzy logic, to overcome these limitations. A comprehensive comparison is made between classical and modern algorithmic approaches to digital filtering, highlighting the critical role of software-based solutions in suppressing quantization errors and mitigating the influence of random noise in analogue sensor data. The implementation of both recursive and non-recursive digital filter models is addressed through digital signal processing techniques, enabling real-time correction and analysis of incoming signals. Using mathematical tools such as Z-transforms and transfer functions, the paper provides an in-depth performance evaluation of filter behaviour under both deterministic and stochastic inputs. The research supports the broader integration of AI-driven technologies in modern automation systems, paving the way for more adaptive, efficient, and fault-tolerant control mechanisms in complex environments.
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Purwana, Agung, I. Made Ariana, and Wisnu Wardhana. "Numerical study on the cavitation noise of marine skew propellers." Journal of Naval Architecture and Marine Engineering 18, no. 2 (2021): 97–107. http://dx.doi.org/10.3329/jname.v18i2.38099.
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In this study, numerical simulations on the noise of the underwater marine propeller for different pressures, skew angles, and performance conditions are investigated. The study has been carried out for the prediction of cavity and noise cavitation characteristics of the propeller. The blade sheet cavitation created by an underwater propeller is then evaluated using numerical analysis. The cavitation and cavity around marine propellers were predicted using MRF (Multiple Reference Frame) techniques. The simulation uses the Reynolds Averaged Navier-Stokes (RANS) formulation with the turbulence model k-ω Shear Stress Transport and the Fast Fourier Transform. The FW-H equation is used to measure far-field radiation under various operating conditions. The simulation is carried out to present that the pressure and skew propeller angles have an effect on the form and area of the cavity, as well as cavitation noise. The noise characteristics at various positions of hydrophones and speeds of the marine propeller are presented. The 3D model of B-series marine propeller with D=250 mm, Z=4, P/D= 1.0, AE/AO=0.55, skew angles of 16, 35, 53, and 72 degrees at advance coefficient, J=0.221, is used for the simulation
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Shuryak, Edward. "Instanton-dyon ensembles reproduce deconfinement and chiral restoration phase transitions." EPJ Web of Conferences 175 (2018): 12001. http://dx.doi.org/10.1051/epjconf/201817512001.
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Paradigm shift in gauge topology at finite temperatures, from the instantons to their constituents – instanton-dyons – has recently lead to studies of their ensembles and very significant advances. Like instantons, they have fermionic zero modes, and their collectivization at suffciently high density explains the chiral symmetry breaking transition. Unlike instantons, these objects have electric and magnetic charges. Simulations of the instanton-dyon ensembles have demonstrated that their back reaction on the Polyakov line modifies its potential and generates the deconfinement phase transition. For the Nc = 2 gauge theory the transition is second order, for QCD-like theory with Nc = 2 and two light quark flavors Nf = 2 both transitions are weak crossovers at happening at about the same condition. Introduction of quark-flavor-dependent periodicity phases (imaginary chemical potentials) leads to drastic changes in both transitions. In particulaly, in the so called Z(Nc) – QCD model the deconfinement transforms to strong first order transition, while the chiral condensate does not disappear at all. The talk will also cover more detailed studies of correlations between the dyons, effective eta’ mass and other screening masses.
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Vandenbroucke, Sofie S. T., Lowie Henderick, Louis T. De Taeye, et al. "Titanium Carboxylate Molecular Layer Deposited Hybrid Films As Protective Coatings for Lithium-Ion Batteries." ECS Meeting Abstracts MA2022-02, no. 31 (2022): 1137. http://dx.doi.org/10.1149/ma2022-02311137mtgabs.
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Thirty years after the release of the first commercial lithium-ion battery, capacity fading due to complex ageing mechanisms remains one of the major concerns in lithium-ion battery research. Lithium-ion battery cathodes age due to phenomena as transition metal dissolution, electrolyte oxidation and volume expansions.[1] To suppress these effects, a protective coating can be applied to the cathode’s surface to avoid direct contact with the liquid electrolyte. Many studies exist in literature, showing the protective effect of conformal and pinhole-free Atomical Layer Deposited (ALD) coatings. However, the inorganic coatings deposited by ALD are rigid and will crack upon volume expansion of the cathode.[2] Molecular Layer Deposition (MLD) offers the same benefits as ALD but can be used to deposit hybrid inorganic/organic flexible films that can accommodate potential volume expansions of the cathode. To our knowledge, apart from ‘metalcones’ i.e. MLD films grown using a metal containing precursor and an alcohol, MLD films remain to be explored as protective and flexible coatings for lithium-ion batteries.[3] In this work, hybrid MLD titanium carboxylate thin films are deposited using tetrakis(dimethylamido)titanium (TDMAT) and various dicarboxylic acid precursors: oxalic acid, malonic acid, succinic acid, glutaric acid and 3,6-dioxaoctanedioic acid. The latter containing two ethylene oxide units per molecule, potentially increasing the lithium-ion conductivity.[4] The growth of the titanium carboxylate MLD processes is studied using in situ ellipsometry at a substrate temperature of 100 °C and 160 °C. Only the TDMAT/oxalic acid process is found to display good saturation behavior, while a parasitic CVD component is present during the TDMAT pulse for the other processes. The structure of the as-deposited films is physically characterized using Fourier Transform IR spectroscopy (FTIR) and X-Ray Photoelectron Spectroscopy (XPS), confirming the successful deposition of titanium carboxylate films. The films are found to be stable in air up to 50 days as shown by FTIR. This is in contrast to many metalcone MLD films which are considered to be air sensitive as the organic backbone degrades upon air exposure. In addition, FTIR, X-Ray Reflectivity (XRR) and X-Ray Fluorescence (XRF) measurements show that the titanium carboxylate films remain intact upon immersion into a solution of 1 M LiClO4 in propylene carbonate, the liquid electrolyte used for electrochemical characterization. The electrochemical properties of a 5 nm TDMAT/oxalic acid, TDMAT/3,6-dioxaoctanedioic acid and TDMAT/glycerol film (conventional titanicone film [5]) are tested on top of three ideal electrode systems: anatase TiO2, TiN and LiMnO2 (LMO). The titanium carboxylate films are observed to have little to no effect on the lithium-ion kinetics of the TiO2 electrode system compared to the uncoated electrode. This is in contrast to the titanicone film displaying a detrimental effect on the kinetics. All films are observed to effectively suppress electrolyte oxidation when exposing the TiN electrode system to elevated potentials. On the LMO electrode an activation step is necessary for all films, after which a good lithium-ion mobility through the titanium carboxylate films is observed without the severe irreversible reactions detected in the potential profile for the titanicone films. Overall, the explorative tests on thin film electrodes in this work indicate that the electrochemical properties of the titanium carboxylate films seem promising candidates as protective and flexible coating of lithium-ion battery cathodes. [1] Vetter, J., Novák, P., Wagner, M. R., Veit, C., Möller, K. C., Besenhard, J. O., ... & Hammouche, A. (2005). Ageing mechanisms in lithium-ion batteries. Journal of power sources, 147(1-2), 269-281. [2] Ban, C., & George, S. M. (2016). Molecular layer deposition for surface modification of lithium‐ion battery electrodes. Advanced Materials Interfaces, 3(21), 1600762. [3] Zhao, Y., Zhang, L., Liu, J., Adair, K., Zhao, F., Sun, Y., ... & Sun, X. (2021). Atomic/molecular layer deposition for energy storage and conversion. Chemical Society Reviews, 50(6), 3889-3956. [4] Xue, Z., He, D., & Xie, X. (2015). Poly (ethylene oxide)-based electrolytes for lithium-ion batteries. Journal of Materials Chemistry A, 3(38), 19218-19253. [5] Van de Kerckhove, K., Mattelaer, F., Deduytsche, D., Vereecken, P. M., Dendooven, J., & Detavernier, C. (2016). Molecular layer deposition of “titanicone”, a titanium-based hybrid material, as an electrode for lithium-ion batteries. Dalton Transactions, 45(3), 1176-1184.
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Hong, Wangbing, Jie Meng, Changdong Li, Shengyi Yan, Xin He, and Guobin Fu. "Effects of Temperature on Structural Properties of Hydrated Montmorillonite: Experimental Study and Molecular Dynamics Simulation." Advances in Civil Engineering 2020 (December 5, 2020): 1–11. http://dx.doi.org/10.1155/2020/8885215.
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Montmorillonite (MMT) is highly sensitive to environmental changes and therefore plays a key role in the structural evolution of rocks and soils and even damage and disasters. The effects of important environmental factors (the temperature and water content) on MMT structural properties require in-depth study. The structure and morphology of sodium montmorillonite (Na-MMT) and its thermal products (micro-nanoparticles) were characterized by X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, and scanning electron microscopy (SEM). A molecular dynamics (MD) simulation was performed to investigate how temperature (below the failure temperature of the Na-MMT crystal layer) affects the structural properties of hydrated MMT. (1) The laboratory results showed that increasing the temperature significantly affected water molecules, and the particle aggregates exhibited inhomogeneous thermal expansion. The interlayer structure collapsed at 500–700°C. (2) In the simulation, the pull-off force inhibited interactions among oxides, crystal layers on both sides of the sample, and the bonding structure of water molecules, thus exposing the stress on the bonding body for analysis. The MMT ultimate stresses in the X, Y, and Z directions all trended downward with increasing water content and temperature. (3) Environmentally induced damage was most likely to occur in the Z direction. Increasing the number of interlayer water molecules increased the layer spacing and considerably weakened van der Waals forces, such that the roles of the electrostatic force and the interlayer hydrogen bond network gradually became significant. The most significant impact of increasing the temperature was reflected in the hydrogen bonding network, resulting in the destruction of the interlayer water bridge, the gradual failure of the layered bonding structure, and the formation or development of cracks. This improved understanding of the structural properties of MMT aggregates under environmental change advances research on the evolutionary behaviour of nano-, micro-, and macrostructures of rocks and soils.
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P., A. Murade*. "Influence of Strontium Doping on The Growth, Structural, Optical, And Nonlinear Optical Properties of Zinc Thiourea Chloride Crystals." International Journal of Scientific Research and Technology 2, no. 4 (2025): 105–10. https://doi.org/10.5281/zenodo.15176168.
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In this study, the crystal growth and characterization of pure and strontium (Sr)-doped zinc thiourea chloride (ZTC) crystals have been investigated. Single crystals of ZTC and Sr-doped ZTC with doping concentrations of 2 mol% were successfully grown by using the slow evaporation technique at a constant temperature of 35°C. The structural properties of the grown crystals were examined through powder X-ray diffraction (XRD) techniques to determine unit cell dimensions and analyze crystalline phase variations. Optical transparency was studied using UV-Visible spectroscopy, which revealed that the grown crystals exhibited wide transparency across the visible region. Fourier Transform Infrared (FT-IR) spectroscopy was employed to identify functional groups and bonding characteristics. Nonlinear optical (NLO) properties were assessed through second harmonic generation (SHG) studies using the Kurtz-Perry powder technique with an ND-YAG laser at 1064 nm in Q-switched mode. The results indicate that Sr doping significantly influences the structural, optical, and NLO properties of ZTC crystals, enhancing their potential for photonic and optoelectronic applications. This comprehensive analysis highlights the effectiveness of Sr as a dopant in improving the material's performance, making it a promising candidate for advanced nonlinear optical technologies.
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Akhtar, Md Haseen, Mark Anderson, and Thomas Cochrane. "Implementing Augmented Reality and Virtual Reality for authentic healthcare education." Pacific Journal of Technology Enhanced Learning 6, no. 1 (2024): 2–3. http://dx.doi.org/10.24135/pjtel.v6i1.177.
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Augmented reality (AR) and virtual reality (VR) technologies have demonstrated immense potential to transform fields like education and healthcare through immersive and interactive virtual environments (Bower et al., 2014; Dhar et al., 2023; Moro et al., 2021)). However, high costs of proprietary headsets and content platforms have inhibited widespread adoption of these technologies in resource-constrained contexts, especially in developing countries (Karre et al., 2019).
 Augmented reality (AR) and virtual reality (VR) have the potential to transform how we approach education and healthcare, enhancing access and outcomes especially in developing countries. AR/VR furthers United Nations (UN) Sustainable Development Goals (SDGs) 3 and 4 through inclusive, equitable education and healthcare (United Nations, 2016). VR can simulate immersive learning environments, providing hands-on medical training to healthcare workers in regions with limited resources. By using VR for anatomy and surgery education, healthcare professionals can gain experience without risk to patients. This improves local healthcare capacity and retention of health workers in remote areas.
 Similarly, AR and VR can enable experiential learning for students without access to labs or materials (Sinou et al., 2023). This facilitates authentic learning for financially or geographically constrained students (van der Meer et al., 2023). AR/VR health interventions can also improve patient diagnosis and care (Sureja et al., 2023). AR glasses for doctors could display patient vitals or past records during examinations to improve diagnostic capabilities. Remote consultations can connect rural healthcare workers with urban specialists via AR assistive tools during complex treatments. AR/VR distraction therapy has also proven effective during painful procedures for children and the elderly (Vaillant-Ciszewicz et al., 2022). Such solutions enhance community health literacy and comfort with medical services, a key challenge in developing contexts.
 This presentation proposes a practical methodology for opportunities to expand access to AR/VR healthcare and education tools in low-resource settings through three pathways - utilising low-cost VR headsets, employing inclusive user interface design, and using participatory methodologies during content development.
 The Educational Design Research (EDR) methodology will guide the project through four main phases (McKenney and Reeves, 2020; Kartoğlu et al., 2020):
 
 Analysis and Exploration Phase
 
 
 Conduct a literature review on AR/VR adoption in healthcare education.
 Engage stakeholders (educators, students, industry partners) through focus groups and interviews.
 Analyze existing curricula, learning objectives, and assessment practices in healthcare education programs across Australasia.
 
 
 Design and Development Phase
 
 
 Develop design principles and guidelines for creating effective AR/VR experiences in healthcare education.
 Collaborate with interdisciplinary teams to design and prototype AR/VR experiences aligned with learning objectives and assessment practices.
 Conduct iterative cycles of prototyping, testing, and refinement with stakeholder feedback.
 
 
 Implementation and Evaluation Phase
 
 
 Implement the developed AR/VR experiences in selected healthcare education programs across Australasia.
 Evaluate the effectiveness through mixed methods, including quantitative measures of learning outcomes, engagement, and skill development, as well as qualitative analysis of user experiences.
 Conduct formative evaluations for improvement and refinement.
 
 
 Reflection and Dissemination Phase
 
 
 Analyze and synthesize findings from the implementation and evaluation phases.
 Refine the design principles and guidelines based on research findings.
 Develop a comprehensive framework and guidelines for effective AR/VR implementation in healthcare education across Australasia.
 Disseminate research findings, framework, and guidelines through publications, conferences, workshops, and online resources.
 
 The project will apply the principles of EDR, such as interdisciplinary collaboration, contextual adaptation, and iterative refinement, to develop a robust and contextualized solution for AR/VR adoption in healthcare education programs across Australasia.
 References
 Bower, M., Howe, C., McCredie, N., Robinson, A., & Grover, D. (2014). Augmented Reality in education – cases, places and potentials. Educational Media International, 51(1), 1–15. https://doi.org/10.1080/09523987.2014.889400
 Dhar, E., Upadhyay, U., Huang, Y., Uddin, M., Manias, G., Kyriazis, D., Wajid, U., AlShawaf, H., & Syed Abdul, S. (2023). A scoping review to assess the effects of virtual reality in medical education and clinical care. DIGITAL HEALTH, 9, 20552076231158022. https://doi.org/10.1177/20552076231158022
 Kartoğlu, Ü., Siagian, R. C., & Reeves, T. C. (2020). Creating a "Good Clinical Practices Inspection" Authentic Online Learning Environment through Educational Design Research. TechTrends : for leaders in education & training, 1-12. https://doi.org/10.1007/s11528-020-00509-0
 Karre, S. A., Mathur, N., & Reddy Y. R. (2019). Usability evaluation of VR products in industry. https://doi.org/10.1145/3297280.3297462
 McKenney, S., & Reeves, T. C. (2020). Educational design research: Portraying, conducting, and enhancing productive scholarship. Medical Education, 55(1), 82–92. https://doi.org/10.1111/medu.14280
 Moro, C., Birt, J., Stromberga, Z., Phelps, C., Clark, J., Glasziou, P., & Scott, A. M. (2021). Virtual and Augmented Reality Enhancements to Medical and Science Student Physiology and Anatomy Test Performance: A Systematic Review and Meta-Analysis. Anatomical sciences education, 14(3), 368-376. https://doi.org/10.1002/ase.2049
 Sinou, N., Sinou, N., & Filippou, D. (2023). Virtual Reality and Augmented Reality in Anatomy Education During COVID-19 Pandemic. CUREUS JOURNAL OF MEDICAL SCIENCE, 15(2). https://doi.org/10.7759/cureus.35170
 Sureja, N., Mehta, K., Shah, V., & Patel, G. (2023). Machine Learning in Wearable Healthcare Devices. In Machine Learning for Advanced Functional Materials (pp. 281-303). Springer Nature. https://doi.org/10.1007/978-981-99-0393-1_13
 United Nations. (2016). Transforming our world: The 2030 agenda for sustainable development. UN Publishing. https://www.un.org/sustainabledevelopment/
 Vaillant-Ciszewicz, A. J., Quin, C., Michel, E., Sacco, G., & Guerin, O. (2022). Customised virtual reality (VR) on mood disorders in nursing homes and long term care unit: A case study on a resident with moderate cognitive impairment [Article]. Annales Medico-Psychologiques. https://doi.org/10.1016/j.amp.2022.10.018
 van der Meer, N., van der Werf, V., Brinkman, W. P., & Specht, M. (2023). Virtual reality and collaborative learning: a systematic literature review. Frontiers in Virtual Reality, 4, Article 1159905. https://doi.org/10.3389/frvir.2023.1159905
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Krebs, Moritz Lukas, and Ferdi Schüth. "Electrochemical Production of Nitrite and Nitrate via Cathodic Oxygen Activation in Liquefied Ammonia." ECS Meeting Abstracts MA2024-02, no. 56 (2024): 3767. https://doi.org/10.1149/ma2024-02563767mtgabs.
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Nitrite and nitrate play pivotal roles in industrial applications, being utilized in the synthesis of pharmaceuticals, nylon precursors, explosives, and especially as fertilizer compounds. However, their synthesis primarily relies on the energy-intensive Ostwald process, which operates at high temperatures. Recently, there has been growing interest in producing nitrite and nitrate through the electrooxidation of ammonia. This method shows promise for enabling decentralized small-scale production under mild conditions while directly utilizing renewable energy sources.[1] However, production is currently restricted to low ammonia concentrations (typically 0.1 M) in aqueous systems while requiring high cell voltages.[2,3] An alternative yet unexplored concept is the electrooxidation of liquefied ammonia gas with molecular oxygen. This concept would enable nitrite and nitrate production at lower cell voltages without being restricted to low ammonia concentrations. In fact, the pioneering studies of Allen Bard have demonstrated that cathodic activation of gaseous oxygen in liquefied ammonia is possible.[4] Nonetheless, the possibility of producing nitrite and nitrate in liquefied ammonia has yet to be investigated. By using an autoclave for electrochemistry experiments, we are able to investigate the possibility of nitrite and nitrate synthesis at ammonia equilibrium pressures, elevated temperatures, and different oxygen partial pressures.[5] In a two-electrode configuration, a Pt coil and a Pt sheet (1cm x 1cm) are used as the cathode and anode, respectively. In this work, we utilize the high overpotential of Pt electrodes in the hydrogen evolution reaction (HER) in liquefied ammonia to selectively form active oxygen species via the competitive oxygen reduction reaction (ORR). The so-formed oxygen species then react with the ammonium-containing electrolyte to form nitrogen oxides. By introducing 30 bars of pressure of O2 (4%) in Ar, we observed a reduction in the overall cell voltage by approximately 800 mV at current densities of 20 mA cm-2. After transferring 100 C of charge, ion chromatography (IC) confirms the formation of both nitrite and nitrate with formal faradaic efficiencies of 15% and 41%, respectively. Additional headspace analysis via diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) disproved the formation of significant amounts of gaseous NOx species. Via GC analysis, we confirmed that the ORR successfully suppresses the HER. At the same time, the Faraday efficiency towards the anodic nitrogen evolution (NER) is unchanged, indicating a solely cathodically driven reaction mechanism. To determine the role of in-situ formed water in the reaction mechanism, we conducted experiments examining the impact of water addition. These investigations revealed that adding water is advantageous in the presence of oxygen. However, when water was the exclusive source of oxygen, only trace amounts of nitrite were observed, and no nitrate was formed. This indicates that in-situ-formed water molecules are not the primary active species responsible for the production of nitrite and nitrate. Currently, we further study the reaction mechanism and the influence of different electrolyte salts and ammonium-ion concentrations on the nitrite and nitrate yield. In addition, experiments at various reaction temperatures have been conducted, further improving nitrite and nitrate efficiency. In summary, we present a novel method for the electrochemical formation of nitrite and nitrate in liquefied ammonia under equilibrium pressures, which, to the best of our knowledge, is the first study of this kind. By exploring various reaction parameters, we additionally probe the impact of water content, reaction temperature, and different electrolyte salts on the yields of the nitrogen oxides, thereby advancing our understanding of the underlying reaction mechanism. [1] Chen, J. G.; Crooks, R. M.; Seefeldt, L. C.; Bren, K. L.; Bullock, R. M.; Darensbourg, M. Y.; Holland, P. L.; Hoffman, B.; Janik, M. J.; Jones, A. K.; Kanatzidis, M. G.; King, P.; Lancaster, K. M.; Lymar, S. V.; Pfromm, P.; Schneider, W. F.; Schrock, R. R. Beyond fossil fuel-driven nitrogen transformations. Science 2018, 360 (6391). DOI: 10.1126/science.aar6611. [2] Bunce, N. J.; Bejan, D. Mechanism of electrochemical oxidation of ammonia. Electrochim. Acta 2011, 56 (24), 8085–8093. DOI: 10.1016/j.electacta.2011.07.078. [3] Tian, Y.; Mao, Z.; Wang, L.; Liang, J. Green Chemistry: Advanced Electrocatalysts and System Design for Ammonia Oxidation. Small Structures 2023, 4 (6), B83. DOI: 10.1002/sstr.202200266. [4] Uribe, F. A.; Bard, A. J. Electrochemistry in liquid ammonia. 5. Electroreduction of oxygen. Inorg. Chem. 1982, 21 (8), 3160–3163. DOI: 10.1021/ic00138a048. [5] Britschgi, J.; Kersten, W.; Waldvogel, S. R.; Schüth, F. Electrochemically Initiated Synthesis of Methanesulfonic Acid. Angew. Chem. In. Ed. 2022, 61 (41), e202209591. DOI: 10.1002/anie.202209591. Figure 1
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Schultz, Andrew R., Saeed Alahmari, Pallavi Singh, et al. "Abstract A013: Integrating imaging and sequencing to compute the subcellular organization of a cell’s transcriptome." Cancer Research 82, no. 10_Supplement (2022): A013. http://dx.doi.org/10.1158/1538-7445.evodyn22-a013.
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Abstract Background: Incorporation of prior information in the form of pathway activity profiles was key in the success of the algorithm that won the DREAM challenge to predict in vitro cell fitness from transcriptomic and other multi-omic datasets (Costello, C. C et al, 2014). We hypothesize that leveraging additional prior information on the spatial distribution of transcriptome activity inside the cell will yield better predictions of cell fitness, which span longer timeframes. Methods: We integrated (i) sequencing and (ii) imaging data obtained from a stomach cancer cell line (NCI-N87). For (i), we used previously published scRNA-seq data available for 3,246 NCI-N87 cells. Cells were assigned to either G0/G1, S or G2M phase; and G0G1 cells were grouped into subpopulations defined by somatic copy number alterations. In addition, we calculated the pathway activity profile of each cell using gene set variation analysis. For (ii), cells were imaged on a Leica confocal SP8 using 63X objective, collecting 70 z slices of target dye and brightfield with interslice interval 0.29 µm. We trained a previously developed label-free U-Net convolutional neural network (CNN) (Ounkomol, C. et al, 2018) on Z-stacks of images containing the nuclei or mitochondria (mito) to calculate the spatial distribution of the two organelles. Models were trained for nucleus using train (N=37)/test (N=5) and mito using train (N=24)/test (N=5) with the Adam optimizer for 150,000 minibatch iterations monitoring the weighted mean squared error (MSE). The model training pipeline was implemented in PyTorch on a Nvidia DGX A100 Tesla V100 GPU. The accuracy of the model was assessed by calculating the Pearson correlation coefficient between the pixel intensities of the model’s predicted output and the independent test images. The predicted 3D organelles were used as input for segmentation using the Cellpose algorithm (String, C. et al, 2021), giving us nucleus and mito coordinates (X,Y,Z) for each cell. To integrate (i) and (ii) we overlaid the distributions of nucleus and mito area and volume onto the activity of pathways expressed in the nucleus, mito, and their respective membranes. Sequenced and imaged NCI-N87 cells were then co-clustered together to obtain a tree that links profiles between the two assays. Results: Overall, the correlation coefficient (r) was higher when using nucleus images for training (r=[0.759, 0.833]; average 0.780) compared to mito (r=[0.633 - 0.783]; average 0.680), even when the sample sizes were equivalent. Of the imaged cells detected within a given field of view, 50-80% were linked to a sequenced cell. Linking sequenced and imaged cells allows visualizing the spatial distribution of pathway activity among various organelles inside a cell. Conclusions: While our results demonstrate how this can be achieved in principle computationally, they will require extensive experimental validation. Doing so will transform omics-based predictions of cell fitness into problems that can be solved by image classification algorithms and recent advances in computer vision. Citation Format: Andrew R. Schultz, Saeed Alahmari, Pallavi Singh, Zaid Siddiqui, Emily Thomas, Emek Demir, Laura Heiser, Noemi Andor. Integrating imaging and sequencing to compute the subcellular organization of a cell’s transcriptome [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr A013.
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Banack, Hailey R., Jean Wactawski-Wende, Heather M. Ochs-Balcom, et al. "A protocol for remote collection of skeletal muscle mass via D3-creatine dilution in community-dwelling postmenopausal women from the Women’s Health Initiative." PLOS ONE 19, no. 4 (2024): e0300140. http://dx.doi.org/10.1371/journal.pone.0300140.
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Background There is emerging evidence that cancer and its treatments may accelerate the normal aging process, increasing the magnitude and rate of decline in functional capacity. This accelerated aging process is hypothesized to hasten the occurrence of common adverse age-related outcomes in cancer survivors, including loss of muscle mass and decrease in physical function. However, there is no data describing age-related loss of muscle mass and its relation to physical function in the long-term in cancer survivors. Methods This study protocol describes the use of a novel method of muscle mass measurement, D3-creatine dilution method (D3Cr), in a large sample (n~6000) of community dwelling postmenopausal women from the Women’s Health Initiative (WHI). D3Cr will be used to obtain a direct measure of muscle mass remotely. Participants will be drawn from two sub-cohorts embedded within the WHI that have recently completed an in-home visit. Cancer survivors will be drawn from the Life and Longevity After Cancer (LILAC) cohort, and cancer-free controls will be drawn from the WHI Long Life Study 2. The overall objective of this study is to examine the antecedents and consequences of low muscle mass in cancer survivors. The study aims are to: 1) create age-standardized muscle mass percentile curves and z-scores to characterize the distribution of D3- muscle mass in cancer survivors and non-cancer controls, 2) compare muscle mass, physical function, and functional decline in cancer survivors and non- cancer controls, and 3) use machine learning approaches to generate multivariate risk-prediction algorithms to detect low muscle mass. Discussion The D3Cr method will transform our ability to measure muscle mass in large-scale epidemiologic research. This study is an opportunity to advance our understanding of a key source of morbidity among older and long-term female cancer survivors. This project will fill knowledge gaps, including the antecedents and consequences of low muscle mass, and use innovative methods to overcome common sources of bias in cancer research. The results of this study will be used to develop interventions to mitigate the harmful effects of low muscle mass in older adults and promote healthy survivorship in cancer survivors in the old (>65) and oldest-old (>85) age groups.
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Minh, Pham Thi, Bui Thi Tuyet, Tran Thi Thu Thao, and Le Thi Thu Hang. "Application of ensemble Kalman filter in WRF model to forecast rainfall on monsoon onset period in South Vietnam." VIETNAM JOURNAL OF EARTH SCIENCES 40, no. 4 (2018): 367–94. http://dx.doi.org/10.15625/0866-7187/40/4/13134.
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This paper presents some results of rainfall forecast in the monsoon onset period in South Vietnam, with the use of ensemble Kalman filter to assimilate observation data into the initial field of the model. The study of rainfall forecasts are experimented at the time of Southern monsoon outbreaks for 3 years (2005, 2008 and 2009), corresponding to 18 cases. In each case, there are five trials, including satellite wind data assimilation, upper-air sounding data assimilation, mixed data (satellite wind+upper-air sounding data) assimilation and two controlled trials (one single predictive test and one multi-physical ensemble prediction), which is equivalent to 85 forecasts for one trial. Based on the statistical evaluation of 36 samples (18 meteorological stations and 18 trials), the results show that Kalman filter assimilates satellite wind data to forecast well rainfall at 48 hours and 72 hours ranges. With 24 hour forecasting period, upper-air sounding data assimilation and mixed data assimilation experiments predicted better rainfall than non-assimilation tests. The results of the assessment based on the phase prediction indicators also show that the ensemble Kalman filter assimilating satellite wind data and mixed data sets improve the rain forecasting capability of the model at 48 hours and 72 hour ranges, while the upper-air sounding data assimilation test produces satisfactory results at the 72 hour forecast range, and the multi-physical ensemble test predicted good rainfall at 24 hour and 48 hour forecasts. The results of this research initially lead to a new research approach, Kalman Filter Application that assimilates the existing observation data into input data of the model that can improve the quality of rainfall forecast in Southern Vietnam and overall country in general.References Bui Minh Tuan, Nguyen Minh Truong, 2013. 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