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Mao, Quan, and Yuechen Liu. "Post-Disaster Performance and Restoration Sequences of Interdependent Critical Infrastructure Systems Considering Various Socioeconomic Impacts." Sustainability 16, no. 15 (2024): 6609. http://dx.doi.org/10.3390/su16156609.
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The failures of interdependent critical infrastructure systems (CISs) caused by disasters could result in significant impacts on the economy and society of cities. Although existing studies have proposed several socioeconomic impact indicators of CIS failures, using these indicators as optimization objectives of restoration sequences, most of them only selected one indicator and failed to reveal their differences. This study aims to analyze the differences between various socioeconomic impact indicators in evaluating post-disaster CIS performance and to identify their effects on the optimized restoration sequences. To achieve this objective, this study simulates the failure propagation and recovery process of CISs, based on network modeling, and constructs six socioeconomic impact indicators for evaluating CIS performance and optimizing the restoration sequence. Then, this study analyzes the effects of different socioeconomic impact indicators by comparing the differences between post-disaster CIS performance, as well as the corresponding restoration sequence and recovery efficiency, among five groups. The results indicate that ignoring social impacts would significantly underestimate the consequences of CIS failures, and the restoration sequence aimed at minimizing social impact differs from other methods, with the recovery efficiency in regards to the social impact notably lower than that of the economic impact. This implies that evaluating the multidimensional social impacts is essential for accurately understanding the worst-case consequences of CIS failures with a bottom-line perspective.
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Lebedev, Ilya. "Adaptive Regression Model Construction Based on the Functional Quality Analysis of the Sequence Segment Processing." Informatics and Automation 24, no. 2 (2025): 363–94. https://doi.org/10.15622/ia.24.2.1.
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The article considers the problem of constructing an adaptive model aimed at improving the quality indicators of processing information sequences. In data processing techniques that have found application in many application areas, the applied analysis of observation objects is computationally resource-intensive and requires many iterations in case of changes in data properties. The article proposes a technique for selecting segments of an information sequence obtained in different ways, which differs in the use of the quality functional of regression models for processing subsequences. The sequences of observation objects received at the input of the model are divided by various specified segmentation algorithms. Pre-selected regression models are trained on each obtained segment and, depending on the obtained values of the calculated quality functional, the best models in terms of quality indicators are assigned to the segments. This allows us to form an aggregation model for data processing. Based on the experiment on model data and samples, the proposed technique is assessed. The values of the quality indicator MSE and MAE are obtained for different processing algorithms and with a different number of segments. The proposed method makes it possible to increase the MSE and MAE indicators by segmentation and assignment of regression models that have the best indicators on individual segments. The proposed solution is aimed at further improvement of ensemble methods. Its application allows to increase the efficiency of setting up basic algorithms in case of data property transformation and to improve the interpretability of results. The method can be used in developing models and methods for processing information sequences.
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Liu, Peng, Linfeng Wu, Yanzhong Wang, and Lize Guo. "Optimization Method for Assembly Sequence Evaluation Based on Assembly Cost and Ontology of Aviation Reducers." Applied Sciences 14, no. 12 (2024): 5116. http://dx.doi.org/10.3390/app14125116.
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An assembly sequence evaluation is one of the most important research directions of assembly sequence planning (ASP) for complex mechanical transmission products. Currently, aviation reducers lack a multi-perspective and multi-level evaluation of their assembly sequence. The existing evaluation indicators vary. The evaluation methods have low effectiveness and poor practicability. Therefore, a comprehensive multidimensional evaluation method for complex assembly sequences is proposed in this paper. A multidimensional comprehensive evaluation of the overall assembly quality and performance indices of aviation reducer products is realized. Firstly, the main factors affecting assembly sequence planning are considered: the attributes of the basic unit parts and the cost control of the assembly process. An evaluation index system of assembly sequence planning based on the two dimensions of assembly cost and ontology is constructed. Then, according to the multidimensional evaluation index, fuzzy evaluation theory is used to establish a fuzzy set and a matrix for each dimensional evaluation index. The index weight is divided. A comprehensive evaluation model and the function of each dimension are established. After a comprehensive evaluation, the multidimensional assembly sequence evaluation method for aviation reducers is formed. Finally, the method is applied to the assembly process of the primary reducer of a helicopter’s main reducer, and a comprehensive evaluation of its assembly sequence scheme is completed to verify the feasibility of the proposed method. This article constructs a complex assembly sequence evaluation method that includes 12 evaluation indicators, improves the assembly sequence planning evaluation index system of aviation reducers, and can effectively promote the progress of optimization technology for complex assembly sequences of aviation reducers.
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Newton, Ryan J., Jessica L. VandeWalle, Mark A. Borchardt, Marc H. Gorelick, and Sandra L. McLellan. "Lachnospiraceae and Bacteroidales Alternative Fecal Indicators Reveal Chronic Human Sewage Contamination in an Urban Harbor." Applied and Environmental Microbiology 77, no. 19 (2011): 6972–81. http://dx.doi.org/10.1128/aem.05480-11.
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ABSTRACTThe complexity of fecal microbial communities and overlap among human and other animal sources have made it difficult to identify source-specific fecal indicator bacteria. However, the advent of next-generation sequencing technologies now provides increased sequencing power to resolve microbial community composition within and among environments. These data can be mined for information on source-specific phylotypes and/or assemblages of phylotypes (i.e., microbial signatures). We report the development of a new genetic marker for human fecal contamination identified through microbial pyrotag sequence analysis of the V6 region of the 16S rRNA gene. Sequence analysis of 37 sewage samples and comparison with database sequences revealed a human-associated phylotype within theLachnospiraceaefamily, which was closely related to the genusBlautia. This phylotype, termed Lachno2, was on average the second most abundant fecal bacterial phylotype in sewage influent samples from Milwaukee, WI. We developed a quantitative PCR (qPCR) assay for Lachno2 and used it along with the qPCR-based assays for humanBacteroidales(based on the HF183 genetic marker), totalBacteroidalesspp., and enterococci and the conventionalEscherichia coliand enterococci plate count assays to examine the prevalence of fecal and human fecal pollution in Milwaukee's harbor. Both the conventional fecal indicators and the human-associated indicators revealed chronic fecal pollution in the harbor, with significant increases following heavy rain events and combined sewer overflows. The two human-associated genetic marker abundances were tightly correlated in the harbor, a strong indication they target the same source (i.e., human sewage). Human adenoviruses were routinely detected under all conditions in the harbor, and the probability of their occurrence increased by 154% for every 10-fold increase in the human indicator concentration. Both Lachno2 and humanBacteroidalesincreased specificity to detect sewage compared to general indicators, and the relationship to a human pathogen group suggests that the use of these alternative indicators will improve assessments for human health risks in urban waters.
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Tverdokhlebov, V. A. "Models of Functional Dependencies of Elements in Sequences for Solving Problems of Control and Management." Mekhatronika, Avtomatizatsiya, Upravlenie 20, no. 10 (2019): 579–88. http://dx.doi.org/10.17587/mau.20.579-588.
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In paper developed version of the basic concepts, models and methods for the formulation and solution of problems of control and diagnosing of processes in systems, tasks of constructing models of processes in which the causal relationships of events are transformed into functional dependencies between elements in sequences, problems of formalizing of process control rules, etc. For this extended classical recurrent definition of the sequences, which presents the functional elements depending on the immediately preceding to them m elements to offered Z-recurrent definition, which defines the functional relationship between sets of elements in the sequence. The orders of Z-recurrent forms have the form of a set of numbers and are convenient for accurate and complete characterization of the connections of events in processes. The tasks of control, diagnosing, constructing new models of processes, assessing the complexity of processes and rules for managing processes can be formulated and solved using numerical indicators of Z-recurrent definitions. A classification of Z-recurrent definitions of sequences and a classification of processes are constructed, an algorithm for checking the feasibility of determining a Z-recurrent form for given sequences of form is developed. The Z-recurrent definition of sequence is complemented by the Z-recurrent sequence pattern method, which includes: introducing a linear order on the base set of sequence elements, constructing an image for the sequence in the form of a sequence of executing or non-executing relationships between the elements represented by a linear order, and applying Z-recurrent definitions to the constructed image of the sequence. The problem on which the solution of the considered problems is based is the recognition of two sequences by properties, which are determined by the indicators of Z-recurrent definitions of sequences, which have the form of orders of Z-recurrent forms. Sets of orders in executing or non-executing Z-recurrent forms characterize the sequences and the analyzed sets of sequences, which allows you to set and solve problems related to system management: problems of control and diagnosing of processes in the system, problems of constructing process models, problems of formalizing and complexity estimation of control rules of processes.
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Bogachek, Naum L. "ANALYTICAL SYSTEM FOR DEVELOPING AND TESTING PREDICTIVE SCENARIOS OF OPERATIONS WITH MARKETING TOOLS." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 3/3, no. 156 (2025): 88–95. https://doi.org/10.36871/ek.up.p.r.2025.03.03.011.
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The article is devoted to the analytical system of development and testing of forecast scenarios of operations with marketing tools, which is the most important component of the digital information environment of the marketing system in business project management. The presented system provides economic analysis of operations with marketing tools based on signals of technical indicators. In the article on an example of operations with partner marketing investment bonuses Elmed Bonus H the application of indicator MACD is considered, profitability of sequence of operations on the basis of signals of the indicator is calculated, the comparative analysis with the forecast scenario within the limits of strategy buy-hold is carried out, results of testing of the indicator are presented, the optimum sequence of operations with marketing instruments is defined, the financial result is calculated. The conducted research allowed to draw conclusions about the importance of the analytical system of development and testing of forecast scenarios in increasing the efficiency of business project management and about the application of technical indicators in the marketing system.
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Mohan, A., S. Wedemeyer, S. Pandit, M. Saberi, and P. H. Hauschildt. "EMISSA (Exploring Millimeter Indicators of Solar-Stellar Activity)." Astronomy & Astrophysics 655 (November 2021): A113. http://dx.doi.org/10.1051/0004-6361/202142095.
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Context. Due to their wide wavelength coverage across the millimeter to centimeter (mm–cm) range and their increased sensitivity, modern interferometric arrays facilitate observations of the thermal and non-thermal radiation that is emitted from different layers in the outer atmospheres of stars. Aims. We study the spectral energy distribution (Sobs(ν)) of main-sequence stars based on archival observations in the mm–cm range with the aim to study their atmospheric stratification as a function of stellar type. Methods. The main-sequence stars with significant detection in mm bands were identified in the ALMA Science Archive. These data were then complemented with spectral flux data in the extreme ultraviolet to cm range as compiled from various catalogues and observatory archives. We compared the resultant Sobs(ν) of each star with a photospheric emission model (Smod(ν)) calculated with the PHOENIX code. The departures of Sobs(ν) from Smod(ν) were quantified in terms of a spectral flux excess parameter (ΔS∕Smod) and studied as a function of stellar type. Results. The initial sample consists of 12 main-sequence stars across a broad range of spectral types from A1 to M3.5 and the Sun-as-a-star as reference. The stars with Teff = 3000–7000 K (F–M type) showed a systematically higher Sobs(ν) than Smod(ν) in the mm–cm range. Their ΔS∕Smod exhibits a monotonic rise with decreasing frequency. The steepness of this rise is higher for cooler stars in the Teff = 3000–7000 K range, although the single fully convective star (Teff ~ 3000 K) in the sample deviates from this trend. Meanwhile, Sobs(ν) of the A-type stars agrees with Smod(ν) within errors. Conclusions. The systematically high ΔS∕Smod in F–M stars indicates hotter upper atmospheric layers, that is, a chromosphere and corona in these stars, like for the Sun. The mm–cm ΔS∕Smod spectrum offers a way to estimate the efficiency of the heating mechanisms across various outer atmospheric layers in main-sequence stars, and thereby to understand their structure and activity. We emphasise the need for dedicated surveys of main-sequence stars in the mm–cm range.
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Sumarni, Sri, and Farah Salsabila. "THE INFUSION OF CRITICAL THINKING SKILLS INDICATORS AND MICROLEARNING PRINCIPLES IN THE ENGLISH READING Materials for Vocational School Students: A Content Analysis." English Review: Journal of English Education 11, no. 3 (2023): 699–708. http://dx.doi.org/10.25134/erjee.v11i3.8819.
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This study aims to reveal the critical thinking skills indicators and microlearning features integrated in the English reading materials for vocational school students in Indonesia. A content analysis was employed to examine reading materials available in the English Coursebook Work in Progress for SMA/SMK/MA Grade X published by the Ministry of Education, Culture, Research, and Technology of the Republic of Indonesia 2022. The critical thinking skills analysis was meant to capture to what extend do the reading materials coverage signify to the lifelong learning, while the microlearning features investigation was meant to portray how the reading materials are presented to support self-directed learning. 8 critical thinking skills indicators proposed by Anderson and Krathwohl. (2001) were hired as the parameters in determining the integration of the critical thinking skills. Microlearning framework proposed by Allela (2021) were used to determine the reading lesson sequences, with which instructional methods associating each sequence. The results revealed that the reading materials for grade X are presented in 8 printed texts covered descriptive, recount, procedures, expository and narrative. These texts have potentially carried critical thinking skills indicators. The contexts are all pictures and instructions that have potentially presented 3 critical thinking skill indicators. The activities cover 15 comprehension activities and 4 beyond the comprehension activities; 7 Critical thinking indicators are potentially embedded in this part. The reading materials presentation, one set are clearly sequenced in the framework of microlearning covers pre-text, text, and post-text. While the other 7 sets sequenced text and post-text. The analysis indicated most of the critical thinking indicators integrated in the reading materials are under analysis and evaluation.
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Millan, Kelly M., and Susan R. Mikkelsen. "Sequence-selective biosensor for DNA based on electroactive hybridization indicators." Analytical Chemistry 65, no. 17 (1993): 2317–23. http://dx.doi.org/10.1021/ac00065a025.
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Guo, Wei, Han Qiu, Zimian Liu, Junhu Zhu, and Qingxian Wang. "An integrated model based on feedforward neural network and Taylor expansion for indicator correlation elimination." Intelligent Data Analysis 26, no. 3 (2022): 751–83. http://dx.doi.org/10.3233/ida-215955.
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Existing correlation processing strategies make up for the defect that most evaluation algorithms do not consider the independence between indicators. However, these solutions may change the indicator system’s internal connection, affecting the final evaluation result’s interpretability and accuracy. Besides, traditional independent analysis methods cannot accurately describe the complex multivariate correlation based on the linear relationship. Aimed at these problems, we propose an indicators correlation elimination algorithm based on the feedforward neural network and Taylor expansion (NNTE). Firstly, we propose a generalized n-power correlation and a feedforward neural network to express the relationship between indicators quantitatively. Secondly, the low-order Taylor expression expanded at every sample is pointed to eliminate nonlinear relationships. Finally, to control the expansions’ accuracy, the layer-by-layer stripping method is presented to reduce the dimensionality of the correlations among multiple indicators gradually. This procedure continues to iterate until there are all simple two-dimensional correlations, eliminating multiple variables’ correlations. To compare the elimination efficiency, the ranking accuracy is proposed to measure the distance of the resulting sequence to the benchmark sequence. Under Cleveland and KDD99 two datasets, the ranking accuracy of the NNTE method is 71.64% and 96.41%, respectively. Compared with other seven common elimination methods, our proposed method’s average increase is 13.67% and 25.13%, respectively.
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Guo, Wei, Han Qiu, Zimian Liu, Junhu Zhu, and Qingxian Wang. "An integrated model based on feedforward neural network and Taylor expansion for indicator correlation elimination." Intelligent Data Analysis 26, no. 3 (2022): 751–83. http://dx.doi.org/10.3233/ida-215955.
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Existing correlation processing strategies make up for the defect that most evaluation algorithms do not consider the independence between indicators. However, these solutions may change the indicator system’s internal connection, affecting the final evaluation result’s interpretability and accuracy. Besides, traditional independent analysis methods cannot accurately describe the complex multivariate correlation based on the linear relationship. Aimed at these problems, we propose an indicators correlation elimination algorithm based on the feedforward neural network and Taylor expansion (NNTE). Firstly, we propose a generalized n-power correlation and a feedforward neural network to express the relationship between indicators quantitatively. Secondly, the low-order Taylor expression expanded at every sample is pointed to eliminate nonlinear relationships. Finally, to control the expansions’ accuracy, the layer-by-layer stripping method is presented to reduce the dimensionality of the correlations among multiple indicators gradually. This procedure continues to iterate until there are all simple two-dimensional correlations, eliminating multiple variables’ correlations. To compare the elimination efficiency, the ranking accuracy is proposed to measure the distance of the resulting sequence to the benchmark sequence. Under Cleveland and KDD99 two datasets, the ranking accuracy of the NNTE method is 71.64% and 96.41%, respectively. Compared with other seven common elimination methods, our proposed method’s average increase is 13.67% and 25.13%, respectively.
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Barnes, Sydney A. "Gyrochronology and its usage for main sequence field star ages." Proceedings of the International Astronomical Union 4, S258 (2008): 345–56. http://dx.doi.org/10.1017/s1743921309032001.
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AbstractThe construction of all age indicators consists of certain basic steps which lead to the identification of the properties desirable for stellar age indicators. Prior age indicators for main sequence field stars possess only some of these properties. The measured rotation periods of cool stars are particularly useful in this respect because they have well-defined dependencies that allow stellar ages to be determined with ~20% errors. This method, called gyrochronology, is explained informally in this talk, shown to have the desired properties, compared to prior methods, and used to derive ages for samples of main sequence field stars.
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Wang, Yijing, Yuning Cheng, Sisi Zlatanova, and Shi Cheng. "Quantitative Analysis Method of the Organizational Characteristics and Typical Types of Landscape Spatial Sequences Applied with a 3D Point Cloud Model." Land 13, no. 6 (2024): 770. http://dx.doi.org/10.3390/land13060770.
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(1) Background: Sequential landscape changes give people experiences of dynamic beauty, and the key to creating spatial sequences lies in the organization of spatial changes. The purpose of this study is to use a 3D point cloud model to achieve a refined description of spatial sequences’ organizational characteristics from information acquisition to description and explore the quantitative interpretation methods of typical sequence organizational characteristics. (2) Methods: The proposed model contains three main steps: data acquisition and extraction, characteristic index system construction and data processing, and quantitative characterization analysis. A typology research method that combines quantitative induction with qualitative statistical verification is proposed. (3) Results: Seventy-two spatial sequence point cloud models of study cases are obtained; 4 indicators are established; 3 typical organization types are summarized, namely fluctuating, reversal and moderate type; and the characterization factors and threshold intervals for each sequence organization type are analyzed to validate the type classification result. (4) Conclusions: This research improves the accuracy of spatial data, the comprehensiveness of sequence organization characterization factors, and the reliability of classification results. It supplements the existing spatial sequence theoretical knowledge system and provides parameters that can be referred to in practical design.
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Xu, Ruiyang, Chunmao Jiang, and Lijuan Sun. "A Novel Three-Way Decision Model for Improving Computational Thinking Based on Grey Correlation Analysis." Scientific Programming 2022 (January 25, 2022): 1–15. http://dx.doi.org/10.1155/2022/3575457.
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Computational thinking (CT) is an approach that applies the fundamental concepts of computer science to solve problems, design systems, and understand human behavior, which can help students develop lifetime learning and generate new topics. It has been the elements of competency expected of the next generation of talents. However, the current research on computational thinking evaluation is still at a relatively weak stage. The existing related evaluation research is still limited to traditional curriculum evaluation methods. Therefore, the training effect of computational thinking cannot be well quantified, and the characteristics of students cannot be further explored. In this work, we propose a three-way decision model for improving computation thinking. We first developed a system of evaluation metrics, including five specific primary indicators and several secondary indicators. Next, the weight of each indicator was determined by applying an expert similarity measure, consequently getting the best metric sequence. We employ a grey correlation analysis to calculate the distance of each test result from this optimal sequence. Then, we trisect the set of testers based on the distance to build three regions of high score sequences, medium score sequences, and low score sequences inspired by the three-way decision. We can then exploit these rules on target students in the relatively low regions to improve their computational thinking. An example analysis illustrates the effectiveness and applicability of the method. This article provides a solid theoretical basis for improving students’ computational thinking ability. Teaching administrators can conveniently formulate computational thinking teaching strategies, and timely warning and intervention for students with poor computational thinking ability can effectively improve students’ computational thinking ability. The corresponding training measures are given to students of different ability levels to achieve differentiated and personalized training.
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Cross, Frederick R., Michal Breker, and Kristi Lieberman. "Validated Bayesian Differentiation of Causative and Passenger Mutations." G3 Genes|Genomes|Genetics 7, no. 7 (2017): 2081–94. http://dx.doi.org/10.1534/g3.117.039016.
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Abstract In many contexts, the problem arises of determining which of many candidate mutations is the most likely to be causative for some phenotype. It is desirable to have a way to evaluate this probability that relies as little as possible on previous knowledge, to avoid bias against discovering new genes or functions. We have isolated mutants with blocked cell cycle progression in Chlamydomonas and determined mutant genome sequences. Due to the intensity of UV mutagenesis required for efficient mutant collection, the mutants contain multiple mutations altering coding sequence. To provide a quantitative estimate of probability that each individual mutation in a given mutant is the causative one, we developed a Bayesian approach. The approach employs four independent indicators: sequence conservation of the mutated coding sequence with Arabidopsis; severity of the mutation relative to Chlamydomonas wild-type based on Blosum62 scores; meiotic mapping information for location of the causative mutation relative to known molecular markers; and, for a subset of mutants, the transcriptional profile of the candidate wild-type genes through the mitotic cell cycle. These indicators are statistically independent, and so can be combined quantitatively into a single probability calculation. We validate this calculation: recently isolated mutations that were not in the training set for developing the indicators, with high calculated probability of causality, are confirmed in every case by additional genetic data to indeed be causative. Analysis of “best reciprocal BLAST” (BRB) relationships among Chlamydomonas and other eukaryotes indicate that the temperature sensitive-lethal (Ts-lethal) mutants that our procedure recovers are highly enriched for fundamental cell-essential functions conserved broadly across plants and other eukaryotes, accounting for the high information content of sequence alignment to Arabidopsis.
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Nakhevskiy, M. V. "Assessing Efficiency of Management System for Business Incubators in Conditions of Import-Substitution." Vestnik of the Plekhanov Russian University of Economics, no. 6 (November 25, 2023): 209–15. http://dx.doi.org/10.21686/2413-2829-2023-6-209-215.
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The article provides the author’s methodology of assessing the efficiency of business incubator management in the period of import-substitution. This methodology is based on the regulatory system of social and economic indicators worked out by the prominent soviet economist, O. M. Syroezhin that is used for analyzing finance and economic results. The essence of the method implies comparison of actual sequence of changes in key indicators with standard sequence in order to find the efficiency of economic system. However, it can be difficult to define the standard sequence, especially in market economy.
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Hedenås, Henrik, and Lars Ericson. "Epiphytic macrolichens as conservation indicators: successional sequence in Populus tremula stands." Biological Conservation 93, no. 1 (2000): 43–53. http://dx.doi.org/10.1016/s0006-3207(99)00113-5.
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Masellis, Mario, and Jo Knight. "Comment: Unraveling DNA sequence to identify cerebral indicators of dementia risk." Neurology 90, no. 3 (2017): 109. http://dx.doi.org/10.1212/wnl.0000000000004838.
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Komorowska, B., and M. Cieślińska. "First Report of Cherry green ring mottle virus on Sweet Cherry in Poland." Plant Disease 89, no. 12 (2005): 1363. http://dx.doi.org/10.1094/pd-89-1363a.
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Cherry green ring mottle virus (CGRMV), a member of the genus Foveavirus, infects several Prunus species including sweet cherry, sour cherry, ornamental cherry, peach, and apricot throughout North America and Europe. On sour cherry, the virus causes leaf yellowing and dark mottle around secondary veins. Sweet cherry trees are symptomless hosts of CGRMV. During the 2004 growing season, 27 sour and sweet cherry trees were tested for the presence of CGRMV. RNA was isolated from leaves using an RNeasy kit (Qiagen GmbH, Hilden, Germany) and then evaluated by reverse transcription-polymerase chain reaction (RT-PCR) amplification. Two primer sets, GRMV7956/GRMV8316 (1) and NCP5/NCP3 (2), were used for amplification of the CGRMV coat protein gene (807 bp) or its fragment (366 bp), respectively. The cDNA fragments were cloned into bacterial vector pCR 2.1-TOPO, sequenced and analyzed using the Lasergene (DNASTAR, Madison, WI) computer program. Nucleotide sequence of the C328 isolate (GenBank Accession No. AY841279) was compared with corresponding regions of published sequences of CGRMV isolates. The nucleotide sequence of this isolate was 98% identical to the Leb isolate (GenBank Accession No. AF533157) from sour cherry. The lowest similarity (80%) was between the CP sequences of isolate C328 and an isolate from apricot (GenBank Accession No. AY172334.1). Results of biological indexing on Prunus serrulata ‘Shirofugen’ and ‘Kwanzan’ confirmed the infection of ‘Star’ sweet cherry with CGRMV. The indicators showed leaf epinasty and necrosis of fragments of midrib or veins characteristic for CGRMV (2). The CGRMV infection of the indicators was confirmed using RT-PCR. References: (1) M. E. Rott and W. Jelkmann. Eur. J. Plant Pathol. 107:411, 2001. (2) Y. Zhang et al. J. Gen. Virol. 79:2275, 1998.
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Casas, Madeline C., Ky Putnam, Adam B. Mantz, Steven W. Allen, and Taweewat Somboonpanyakul. "Optical Photometric Indicators of Galaxy Cluster Relaxation." Astrophysical Journal 967, no. 1 (2024): 14. http://dx.doi.org/10.3847/1538-4357/ad41de.
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Abstract The most dynamically relaxed clusters of galaxies play a special role in cosmological studies as well as astrophysical studies of the intracluster medium (ICM) and active galactic nucleus feedback. While high-spatial-resolution imaging of the morphology of the ICM has long been the gold standard for establishing a cluster’s dynamical state, such data are not available from current or planned surveys, and thus require separate, pointed follow-up observations. With optical and/or near-IR photometric imaging, and red-sequence cluster finding results from those data, expected to be ubiquitously available for clusters discovered in upcoming optical and millimeter-wavelength surveys, it is worth asking how effectively photometric data alone can identify relaxed cluster candidates, before investing in, e.g., high-resolution X-ray observations. Here we assess the ability of several simple photometric measurements, based on the redMaPPer cluster finder run on Sloan Digital Sky Survey data, to reproduce X-ray classifications of dynamical state for an X-ray selected sample of massive clusters. We find that two simple metrics contrasting the bright central galaxy (BCG) to other cluster members can identify a complete sample of relaxed clusters with a purity of ∼40% in our data set. Including minimal ICM information in the form of a center position increases the purity to ∼60%. However, all three metrics depend critically on correctly identifying the BCG, which is presently a challenge for optical red-sequence cluster finders.
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Takeshita, Toru. "Quartz Microstructures from the Sambagawa Metamorphic Rocks, Southwest Japan: Indicators of Deformation Conditions during Exhumation." Minerals 11, no. 10 (2021): 1038. http://dx.doi.org/10.3390/min11101038.
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The Sambagawa metamorphic rocks in central Shikoku, southwest Japan consist of an inverted metamorphic sequence from the upper chlorite to oligoclase-biotite zones at the lower structural level (LSL), which is overlain by a normal metamorphic sequence consisting of the albite-biotite and garnet zones at the upper structural level (USL). These sequences form a large-scale recumbent fold called the Besshi nappe. To unravel the mechanism of recrystallization and physical conditions in quartz, and their relation to exhumation tectonics, microstructures of recrystallized quartz grains in quartz schist from the Asemi-Saruta-Dozan River traverse were analyzed. The recrystallized quartz grain size increases with increasing structural level from 40 µm in the upper chlorite zone to 160 µm in the garnet zone of the USL. Further, the mechanism of dynamic recrystallization of quartz changes from subgrain rotation to grain boundary migration with increasing structural level across the uppermost garnet zone of the LSL. From these data, the deformation temperatures in quartz schist are calculated to increase with increasing structural level within the range between 300 and 450 °C using paleopiezometers and experimental flow laws. It could be interpreted that a rapid cooling of the Besshi nappe from above is responsible for the deformation temperatures recorded in quartz schist.
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SHVAHIREV, Maksym. "Assessment of management efficiency in the process of achieving final results of enterprise integration in the conditions of change." Economics. Finances. Law 2/2025, no. - (2025): 33–36. https://doi.org/10.37634/efp.2025.2.8.
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The main factor in achieving business success at an enterprise during its integration process is effective and efficient human resources management. Therefore, one of the most important tasks is to provide the enterprise with highly qualified personnel who are able to solve not only simple, routine tasks, but also ensure the development of the enterprise, occupy strong competitive positions in the market, and define and implement strategic goals. Since the process of enterprise management includes a significant number of sub-processes (such as setting strategic goals, operational planning and control, managing financial flows, etc.), the assessment of management effectiveness usually includes a whole set of indicators that reflect the effectiveness of these sub-processes. A new approach to determining the overall assessment of the effectiveness of management activities is proposed with the allocation of new indicators - management effectiveness or management performance and its application to assess the activities of managers of the enterprise in the process of its integration. To obtain a comprehensive assessment of the effectiveness of management activities, a justified sequence of actions is proposed, which ultimately allows quantitatively measuring the level of each component in assessing the level of management activities. It was determined that in order to obtain a comprehensive assessment of the effectiveness of management activities, it is necessary to provide for the following sequence of actions: 1) identify key aspects of the object of study; 2) within each aspect, identify the main indicators or groups of indicators that most fully reveal this or that aspect; 3) identify within each indicator or in each group of indicators the minimum number of indicators, the sum of which allows quantitatively measuring the level of individual components and, thus, assessing the overall level of management effectiveness.
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Kuznetsov, A. A., A. V. Potii, N. A. Poluyanenko, and I. V. Stelnik. "Nonlinear complication functions for symmetric stream ciphers." Radiotekhnika, no. 195 (December 28, 2018): 125–37. http://dx.doi.org/10.30837/rt.2018.4.195.12.
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Currently, nonlinear Boolean functions are being investigated very actively around the world. However, many open questions remain in this area. The theory of nonlinear Boolean functions suitable for use in robust cryptographic algorithms is largely incomplete. Despite the presence of numerous publications on these topics, many issues related to the interrelation of design characteristics affecting the performance of the generator and its cryptographic characteristics are still open. The generation of a special type of sequences, called de Brain sequences, with minimal hardware and software costs, the rationale for their use as non-linear functions of the complexity of stream encryption systems, is the main theme of this work. The paper presents estimates of cryptographic indicators of nonlinear complexity functions of iterative bit sequence generators with various characteristics of the generated sequence, such as linear complexity and autocorrelation.
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Erni, Resi. "Analysis of Mathematical Problem-Solving Ability of Class XI Senior High School Students on Sequences and Series Materials." Journal of Research on Mathematics Instruction (JRMI) 2, no. 2 (2021): 28–40. http://dx.doi.org/10.33578/jrmi.v2i2.48.
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The objective of this study was to analyze the mathematical problem-solving abilities of class XI high school students in solving sequence and series questions. This research is a descriptive study that aims to describe the mathematical problem-solving ability of class XI students in solving problems of sequences and series. The population in this study were students of class XI SMA in the academic year 2020/2021. The sample was selected by purposive sampling obtained students XI MIPA 1 totaling 25 students. The data was obtained from the results of the mathematical problem-solving ability essay test on the material of sequences and series as many as 4 questions taken from the 2018 National Examination questions. The purpose of this study was to determine and analyze students' mathematical problem-solving abilities on the material of sequences and series. From the results of the study, it can be concluded that the mathematical problem-solving ability on indicators 1, 2, and 3 are categorized as medium and high. In accordance with the research method, students are categorized as having low mathematical problem-solving abilities if they obtain medium, high, and very high criteria. The percentage of indicator 1 is 68.75%, the percentage of indicator 2 is 55.75%, the percentage of indicator 3 is 62.2% while the percentage of indicator 4 is 34.75.
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Tazkia, Savirra, and Tatag Yuli Eko Siswono. "Scaffolding in Supporting Senior High School Students’ Critical Thinking Skills in Sequences and Series Problems." MATHEdunesa 12, no. 1 (2023): 207–20. http://dx.doi.org/10.26740/mathedunesa.v12n1.p207-220.
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Critical thinking skills are important for every individual, that they need to be developed in classroom learning, one of which is through learning sequences and series material. However, there are still many students who have difficulty solving problems on sequences and series material, so they need help using scaffolding. This study aims to describe students' thinking skills on sequences and series material, as well as scaffolding which helps students' critical thinking skills in solving sequence and series material questions. The subjects of this study were 2 students who failed to complete the two critical thinking skills tests given. The two students were then interviewed and given scaffolding. The interviews were conducted in a semi-structured manner, that the researcher prepared several questions which could indicate indicators of critical thinking skills, as well as scaffolding which could assist students in solving problems, but the researcher was free to improvise by asking for other information according to the conditions during the interview. The data obtained was then analyzed by reducing the data, presenting the data, and drawing conclusions. The results showed that scaffolding in the form of reviewing played a dominant role for supporting the failure of critical thinking skills on the indicators of interpretation, analysis, evaluation and explanation. Restructuring helps the failure of critical thinking skills on the indicators of interpretation. Explaining helps the failure of critical thinking skills on evaluation indicators. Developing conceptual thinking helps indicators of critical thinking skills analysis, inference, and self-regulation.
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Azizah, Nurul Izatul, Yenita Roza, and Maimunah Maimunah. "Computational thinking process of high school students in solving sequences and series problems." Jurnal Analisa 8, no. 1 (2022): 21–35. http://dx.doi.org/10.15575/ja.v8i1.17917.
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Kemampuan berpikir komputasi merupakan keterampilan berpikir yang dibutuhkan pada abad 21. Penelitian ini bertujuan untuk mendeskripsikan proses berpikir komputasi siswa SMA/MA dalam menyelesaikan masalah barisan dan deret. Penelitian ini merupakan penelitian deskriptif dengan pendekatan kualitatif. Teknik pengumpulan data dilakukan dengan tes dan wawancara. Subjek dalam penelitian ini adalah siswa kelas XI IPA MA Muhammadiyah Kota Pekanbaru sebanyak 15 orang. Analisis terhadap kemampuan berpikir komputasi siswa dilihat melalui indikator. Hasil analisis menunjukkan bahwa siswa yang berkemampuan tinggi berada dalam kategori sangat baik pada indikator dekomposisi (87,5%) dan abstraksi (97,5%), kategori baik pada indikator berpikir algoritma (65%) dan kategori cukup pada indikator pengenalan pola (50%). Siswa berkemampuan sedang dalam kategori baik pada indikator abstraksi (62%), kategori cukup pada indikator dekomposisi (51,5%), kategori rendah pada indikator pengenalan pola (33,5%) dan berpikir algoritma (39%). Siswa berkemampuan rendah berada dalam kategori rendah untuk tiga indikator yaitu dekomposisi (38,3%), abstraksi (33,3%), berpikir algoritma (21,7%), dan kategori sangat rendah pada pengenalan pola (11,67%). The ability of computational thinking is logical thinking that is needed in the 21st century. This research aims to describe the process of computational thinking in the Senior High School students in completing the problem of arithmetic sequence and series. This research is descriptive research using a qualitative approach. The data collection technique uses tests and interviews. Furthermore, the subject of the research is 15 students of class XI IPA at MA Muhammadiyah Pekanbaru. The students’ computational thinking could be seen through decomposition indicators, pattern recognition, abstraction, and algorithmic thinking. The results of the analysis indicate that students with high abilities are in a very good category on the decomposition indicators (87.5%) and abstraction (97.5%), good categories on the algorithmic thinking indicator (65%), and, the moderate category on the indicators. pattern recognition (50%). For students with moderate abilities, they are in a good category on the abstraction indicator (62%), sufficient category on the decomposition indicator (51.5%), the low category on the pattern recognition indicator (33.5%), and algorithmic thinking (39%). Meanwhile, low-ability students are in the low category for three indicators, namely decomposition (38.3%), abstraction (33.3%), algorithmic thinking (21.7%), and very low category on pattern recognition indicators (11.67%).
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Chabibah, Linda Nur, Emy Siswanah, and Dyan Falasifa Tsani. "Analisis kemampuan pemecahan masalah siswa dalam menyelesaikan soal cerita barisan ditinjau dari adversity quotient." Pythagoras: Jurnal Pendidikan Matematika 14, no. 2 (2019): 199–210. http://dx.doi.org/10.21831/pg.v14i2.29024.
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Tujuan dari penelitian kualitatif ini adalah untuk mendeskripsikan kemampuan pemecahan masalah siswa dalam menyelesaikan soal cerita pada materi barisan ditinjau dari Adversity Quotient (AQ). Kemampuan pemecahan masalah memiliki 4 indikator yaitu: 1) mengidentifikasi masalah, 2) merumuskan masalah, 3) melaksanakan strategi, dan 4) memverifikasi solusi. Penelitian dilaksanakan pada semester genap tahun ajaran 2018/2019. Subjek penelitian terdiri dari 30 Siswa kelas XI IPA 1 SMA Kesatrian 1 Semarang yang telah diajarkan materi barisan. Kemudian dipilih subjek berdasarkan tipe AQ yaitu Climber, Camper dan Quitter. Teknik pengumpulan data menggunakan angket AQ, tes kemampuan pemecahan masalah, dan wawancara. Teknik analisis data penelitian ini meliputi reduksi data, penyajian data, dan penarikan kesimpulan/verifikasi. Hasil penelitian menunjukkan bahwa siswa bertipe Climber mampu memenuhi seluruh indikator dari 4 indikator kemampuan pemecahan masalah yaitu indikator 1, 2, 3, dan 4. Siswa bertipe Camper mampu memenuhi 3 dari 4 indikator kemampuan pemecahan masalah yaitu indikator 1, 2, dan 3. Siswa bertipe Quitter hanya mampu memenuhi 1 indikator kemampuan pemecahan masalah yaitu indikator 2. Analysis of students' problem-solving abilities in solving word problem sequence in terms of adversity quotientAbstractThe purpose of this qualitative research was to describe the students' problem-solving abilities in solving word problems in the sequences material in terms of Adversity Quotient (AQ). Problem-solving has four indicators namely: 1) overcoming the problem, 2) formulating the problem, 3) implementing the strategy, and 4) verifying the solution. The study was conducted in the even semester of the 2018/2019 academic year. The research subjects consisted of 30 students of class XI IPA 1 of Kesatrian 1 Semarang High School who had taught the sequences material. Then the subject was chosen based on the type of AQ namely climber, camper and quitter. Data collection techniques using the AQ questionnaire, the problem-solving test, and interview. The data analysis techniques of this study include data reduction, data presentation, and conclusion. The results showed that students of the climber type were able to meet all the indicators of the four indicators of problem-solving namely indicators 1, 2, 3, and 4. Students of the camper type were able to fulfill three from four indicators of problem-solving namely indicators 1, 2, and 3. Students' quitter type were only able to meet one indicator of problem-solving, namely indicator 2.
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Krivosheeva, O. A. "INFLUENCE OF CHARACTERISTICS OF SEQUENCE OF INDICATORS ON CONVERGENCE OF EXPONENTIAL SERIES." Vestnik Bashkirskogo universiteta 7, no. 2 (2018): 281. http://dx.doi.org/10.33184/bulletin-bsu-2018.2.5.
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Mann, Stephanie, Mark P. Johnson, Mara Rosner, R. Douglas Wilson, and Michael Bebbington. "503: Prognostic indicators in twin reversed arterial perfusion sequence: Does size matter?" American Journal of Obstetrics and Gynecology 197, no. 6 (2007): S147. http://dx.doi.org/10.1016/j.ajog.2007.10.505.
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Raţiu, Augusta, and Nicuşor Minculete. "About Aczél Inequality and Some Bounds for Several Statistical Indicators." Mathematics 8, no. 4 (2020): 574. http://dx.doi.org/10.3390/math8040574.
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In this paper, we will study a refinement of the Cauchy–Buniakowski–Schwarz inequality and a refinement of the Aczél inequality by the technique of the monotony of a sequence. In the final part, we present some properties of bounds of several statistical indicators of variation.
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Qi, Cheng, Qiang Wei, Yuting Ye, et al. "Fixation of Expression Divergences by Natural Selection in Arabidopsis Coding Genes." International Journal of Molecular Sciences 25, no. 24 (2024): 13710. https://doi.org/10.3390/ijms252413710.
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Functional divergences of coding genes can be caused by divergences in their coding sequences and expression. However, whether and how expression divergences and coding sequence divergences coevolve is not clear. Gene expression divergences in differentiated cells and tissues recapitulate developmental models within a species, while gene expression divergences between analogous cells and tissues resemble traditional phylogenies in different species, suggesting that gene expression divergences are molecular traits that can be used for evolutionary studies. Using transcriptomes and evolutionary proxies to study gene expression divergences among differentiated cells and tissues in Arabidopsis, expression divergences of coding genes are shown to be strongly anti-correlated with phylostrata (gene ages), indicators of selective constraint Ka/Ks (nonsynonymous replacement rate/synonymous substitution rate) and indicators of positive selection (frequency of loci with Ka/Ks > 1), but only weakly or not correlated with indicators of neutral selection (Ks). Our results thus suggest that expression divergences largely coevolve with coding sequence divergences, suggesting that expression divergences of coding genes are selectively fixed by natural selection but not neutral selection, which provides a molecular framework for trait diversification, functional adaptation and speciation. Our findings therefore support that positive selection rather than negative or neutral selection is a major driver for the origin and evolution of Arabidopsis genes, supporting the Darwinian theory at molecular levels.
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Nafisah, Hilma Siti. "Mathematical connection skills in sequence and series." Jurnal Inovasi Pembelajaran Matematika: PowerMathEdu 2, no. 3 (2023): 253–60. http://dx.doi.org/10.31980/pme.v2i3.1763.
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This research is a qualitative descriptive study that aims to analyze how the mathematical connection abilities of high school students of class XI in the material of the rows and rows. The subjects of this study were 3 random students from class XI in SMA in Putrajawa Village. The instrument used in this study was in the form of 3 questions that referred to the indicators of students 'mathematical connection ability. The results of this study showed that the students' mathematical connection ability was in the moderate category, as seen from the percentage of errors made by students on the indicators of recognizing and applying mathematics. in contexts outside mathematics. Penelitian ini merupakan penelitian deskriptif kualitatif yang bertujuan untuk menganalisis bagaimana kemampuan koneksi matematis yang dimiliki oleh siswa SMA kelas XI pada materi Barisan dan Deret . Subjek dari penelitian ini adalah 3 orang siswa secara acak kelas XI di SMA di Desa Putrajawa. Instrumen soal yang digunakan dalam penelitian ini berupa 3 buah soal yang mengacu pada indikator kemampuan koneksi matematis siswa.. Hasil dari penelitian ini menunjukkan bahwa kemampuan koneksi matematis siswa tergolong dalam kategori sedang, yang terlihat dari persentasi kesalahan yang dilakukan siswa pada indikator mengenali dan menerapkan matematika dalam kontek-konteks di luar matematika.
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Mittag, M., J. H. M. M. Schmitt, and K. P. Schröder. "Revisiting the connection between magnetic activity, rotation period, and convective turnover time for main-sequence stars." Astronomy & Astrophysics 618 (October 2018): A48. http://dx.doi.org/10.1051/0004-6361/201833498.
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The connection between stellar rotation, stellar activity, and convective turnover time is revisited with a focus on the sole contribution of magnetic activity to the Ca II H&K emission, the so-called excess flux, and its dimensionless indicator R+HK in relation to other stellar parameters and activity indicators. Our study is based on a sample of 169 main-sequence stars with directly measured Mount Wilson S-indices and rotation periods. The R+HK values are derived from the respective S-indices and related to the rotation periods in various B–V-colour intervals. First, we show that stars with vanishing magnetic activity, i.e. stars whose excess flux index R+HK approaches zero, have a well-defined, colour-dependent rotation period distribution; we also show that this rotation period distribution applies to large samples of cool stars for which rotation periods have recently become available. Second, we use empirical arguments to equate this rotation period distribution with the global convective turnover time, which is an approach that allows us to obtain clear relations between the magnetic activity related excess flux index R+HK, rotation periods, and Rossby numbers. Third, we show that the activity versus Rossby number relations are very similar in the different activity indicators. As a consequence of our study, we emphasize that our Rossby number based on the global convective turnover time approaches but does not exceed unity even for entirely inactive stars. Furthermore, the rotation-activity relations might be universal for different activity indicators once the proper scalings are used.
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Wang, Cheng Yuan, Wen Yu Zhang, Ju Jie Wang, and Wen Fang Zhao. "The Prediction of SO2 Pollutant Concentration Using a RBF Neural Network." Applied Mechanics and Materials 55-57 (May 2011): 1392–96. http://dx.doi.org/10.4028/www.scientific.net/amm.55-57.1392.
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Air pollution may cause pernicious effects on human health, and is a widespread problem in the world. Air quality management systems have became an important research issue with strong implications for inhabitants’ health. Monitoring and forecasting of air quality indicators plays an important role in the management systems. Artificial intelligent techniques are successfully used in modelling of highly complex and nonlinear phenomena. In this paper, a model, which is radial basis function (RBF) neural network, is established to estimate the impact of meteorological indicators on SO2. The proposed model achieves 9.91% in mean absolute percentage error (MAPE) compared to real observation data sequence. For air quality, it could be a promising candidate for forecasting the air quality indicators data sequence.
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Zhang, Jinling, Jun Yang, and Min Zhao. "Automatic Segmentation Algorithm of Magnetic Resonance Image in Diagnosis of Liver Cancer Patients under Deep Convolutional Neural Network." Scientific Programming 2021 (September 10, 2021): 1–13. http://dx.doi.org/10.1155/2021/4614234.
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To study the influence of different sequences of magnetic resonance imaging (MRI) images on the segmentation of hepatocellular carcinoma (HCC) lesions, the U-Net was improved. Moreover, deep fusion network (DFN), data enhancement strategy, and random data (RD) strategy were introduced, and a multisequence MRI image segmentation algorithm based on DFN was proposed. The segmentation experiments of single-sequence MRI image and multisequence MRI image were designed, and the segmentation result of single-sequence MRI image was compared with those of convolutional neural network (FCN) algorithm. In addition, RD experiment and single-input experiment were also designed. It was found that the sensitivity (0.595 ± 0.145) and DSC (0.587 ± 0.113) obtained by improved U-Net were significantly higher than the sensitivity (0.405 ± 0.098) and DSC (0.468 ± 0.115, P < 0.05 ) obtained by U-Net. The sensitivity of multisequence MRI image segmentation algorithm based on DFN (0.779 ± 0.015) was significantly higher than that of FCN algorithm (0.604 ± 0.056, P < 0.05 ). The multisequence MRI image segmentation algorithm based on the DFN had higher indicators for liver cancer lesions than those of the improved U-Net. When RD was added, it not only increased the DSC of the single-sequence network enhanced by the hepatocyte-specific magnetic resonance contrast agent (Gd-EOB-DTPA) by 1% but also increased the DSC of the multisequence MRI image segmentation algorithm based on DFN by 7.6%. In short, the improved U-Net can significantly improve the recognition rate of small lesions in liver cancer patients. The addition of RD strategy improved the segmentation indicators of liver cancer lesions of the DFN and can fuse image features of multiple sequences, thereby improving the accuracy of lesion segmentation.
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Rudakova, Lidiya V. "AN APPROACH TO ECONOMIC MODELING BASED ON BUSINESS INDICATORS." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 5/4, no. 146 (2024): 13–20. http://dx.doi.org/10.36871/ek.up.p.r.2024.05.04.002.
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The article highlights and substantiates the approach to economic modeling from the point of view of the conceptual aspect (based on business indicators) and practical (based on formal measurement tools), given that the sequence of data analysis stages can be enriched. The scientific novelty and practical significance of the work lies in the development of a data collection modeling project based on business indicators and the justification of the main categories of information tools used to calculate business indicators in the development of economic models: tools for calculating business indicators, data processing tools, educational tools.
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Pilgrim, Erik M., Nathan J. Smucker, Huiyun Wu, et al. "Developing Indicators of Nutrient Pollution in Streams Using 16S rRNA Gene Metabarcoding of Periphyton-Associated Bacteria." Water 14, no. 15 (2022): 2361. http://dx.doi.org/10.3390/w14152361.
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Indicators based on nutrient-biota relationships in streams can inform water quality restoration and protection programs. Bacterial assemblages could be particularly useful indicators of nutrient effects because they are species-rich, important contributors to ecosystem processes in streams, and responsive to rapidly changing conditions. Here, we sampled 25 streams weekly (12–14 times each) and used 16S rRNA gene metabarcoding of periphyton-associated bacteria to quantify the effects of total phosphorus (TP) and total nitrogen (TN). Threshold indicator taxa analysis identified assemblage-level changes and amplicon sequence variants (ASVs) that increased or decreased with increasing TP and TN concentrations (i.e., low P, high P, low N, and high N ASVs). Boosted regression trees confirmed that relative abundances of gene sequence reads for these four indicator groups were associated with nutrient concentrations. Gradient forest analysis complemented these results by using multiple predictors and random forest models for each ASV to identify portions of TP and TN gradients at which the greatest changes in assemblage structure occurred. Synthesized statistical results showed bacterial assemblage structure began changing at 24 µg TP/L with the greatest changes occurring from 110 to 195 µg/L. Changes in the bacterial assemblages associated with TN gradually occurred from 275 to 855 µg/L. Taxonomic and phylogenetic analyses showed that low nutrient ASVs were commonly Firmicutes, Verrucomicrobiota, Flavobacteriales, and Caulobacterales, Pseudomonadales, and Rhodobacterales of Proteobacteria, whereas other groups, such as Chitinophagales of Bacteroidota, and Burkholderiales, Rhizobiales, Sphingomonadales, and Steroidobacterales of Proteobacteria comprised the high nutrient ASVs. Overall, the responses of bacterial ASV indicators in this study highlight the utility of metabarcoding periphyton-associated bacteria for quantifying biotic responses to nutrient inputs in streams.
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Eiler, Alexander, Domenico Savio, Laurent Fontaine, and Lorenzo Pin. "Developing prokaryotic water quality indicators." ARPHA Conference Abstracts 4 (March 4, 2021): e65409. https://doi.org/10.3897/aca.4.e65409.
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Despite the importance of prokaryotes in aquatic ecosystem and their predictable diversity patterns across space and time, biomonitoring tools relying on prokaryotes are widely lacking. Using metabarcoding, as well as other molecular methods, we were able to identify multiple prokaryotic descriptors and illustrate their reliability and advantages in aquatic environmental assessment. Multivariate statistical and machine learning methods combined with variation coefficient and overall prevalence of taxonomic groups were used to detect possible biological indicators among prokaryotes for various anthropogenic pressures, i.e. acidification, eutrophication and faecal contamination in aquatic environments. In addition, text mining approaches provide powerful alternatives for sequence based status classification and source tracking of contaminants. While these individual sequencing based indicator approaches seem to be powerful, alpha and beta diversity indices provide so far minor precision in ecological status classification. Reasons are the often non-linear association between prokaryotic alpha and beta-diversity with environmental gradients as indicated by first modeling attempts. Still, our results suggest that the limitations in reliably describing reference communities and developing general and robust classification systems for water quality assessment based on prokaryotic sequencing data can be overcome by extensive training data.
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Bialobrzheskyi, O., A. Postil, and S. Yakimets. "Accounting for a positive, negative and zero sequences power in a three-phase unbalanced electrical system." Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, no. 6 (December 23, 2023): 93–99. http://dx.doi.org/10.33271/nvngu/2023-6/093.
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Purpose. Based on the instantaneous electrical power of a three-phase asymmetric system of sinusoidal periodic current, to determine positive, negative, zero-sequences active and reactive power, as well as invariance power factor. Methodology. In the unbalance case in three-phase electrical system, the electrical energy quality is evaluated by means on voltage and current positive, negative, zero-sequences. At the same time, similar components of active and reactive power have not received practical distribution. But it is precisely in terms of power that electricity is accounted for. The instantaneous power orthogonal components in the time domain are determined using the symmetrical components of voltage and current. Active, reactive powers of positive, negative and zero-sequences are allocated. The result obtained has the property of representativeness, which most of the known results lack. Findings. The three-phase system’s instantaneous power components are analytically determined, including the amplitudes of the oscillating power components. The need to take into account the oscillating instantaneous power components has been proven by means of a graphical interpretation of a special case of the three-phase system mode. As an integral indicator that takes into account the oscillating components of the three-phase system instantaneous power, its root-mean-square value over the repetition period is used. Originality. By calculating the transformer efficiency of the studied model according to the active power positive sequence and the same indicator according to the active power as a whole, it was established, that the component sequence separation affects the results of calculating the generalized indicators, including the power transmission system objects. This can lead to erroneous judgments about the efficiency of the specified facilities functioning. Practical value. The invariance power factor was used to characterize the electrical energy quality level of a three-phase sinusoidal current system in an unbalanced mode.
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Du, Zhuoming, Junfeng Zhang, and Bo Kang. "A Data-Driven Method for Arrival Sequencing and Scheduling Problem." Aerospace 10, no. 1 (2023): 62. http://dx.doi.org/10.3390/aerospace10010062.
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Decision support tools for arrival sequencing and scheduling could assist air traffic controllers in managing the arrival aircraft in terminal areas. However, one critical issue is that the current method for dealing with the arrival sequencing and scheduling problem does not consider the dynamic traffic situation and the human working experience, which results in a deviation between the scheduled and actual landing sequences. This paper develops a data-driven method to address this issue. Firstly, the random forest model is applied to predict the estimated time of arrival (ETA). During the ETA prediction, the trajectory, operation, and airport-related factors that could increase the prediction accuracy are considered. Secondly, the landing sequence is obtained by sorting the predicted ETAs. Thirdly, two optimization methods are proposed to generate the scheduled time of arrival (STA). The former uses the predicted ETAs as inputs and then directly optimizes the landing sequence and the STA. The latter uses both the predicted ETA and the landing sequence as inputs for further optimization. Finally, these proposed methods are evaluated with three sets of historical data on arrival operations at Changsha Huanghua International Airport (ZGHA). The results show that the RF-based ETA prediction method could improve scheduling performance. Moreover, the proposed optimization methods could provide controllers with a more appropriate decision advisory. Such advisories could simultaneously reduce the operation efficiency indicators (average/maximum delay or dwell time) and the operation complexity indicators (Kendall rank correlation or position shift).
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Kaminskiy, Roman, Nataliya Shakhovska, Jana Kajanová, and Yurii Kryvenchuk. "Method of Distinguishing Styles by Fractal and Statistical Indicators of the Text as a Sequence of the Number of Letters in Its Words." Mathematics 9, no. 19 (2021): 2410. http://dx.doi.org/10.3390/math9192410.
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The method of the analysis of different texts styles is developed in the paper. Integer numerical sequences are used as models. The elements of the sequence are the number of letters in the words of the text. The algorithm for calculating the exact value of the fractal dimension is developed. It provides the determination of the exact value of the Hurst index. The value of the power dependence constant is calculated. The obtained indicators in the aspect of fractality completely describe the objects of research.
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Sherstneva, Alina A., and Olga G. Sherstneva. "Reliability parameters transformation using parametric method." T-Comm 16, no. 6 (2022): 25–30. http://dx.doi.org/10.36724/2072-8735-2022-16-6-25-30.
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As a whole calculation of reliability indicators and obtaining estimates of the reliability for infocommunication systems and networks is based on various assumptions about the distributions laws of empirical data obtained as a result of an experiment or during operation. As theoretical and practical studies an algorithm for calculating the numerical values of a random variable in a random process using the parametric method is presented. The article is aimed to transform different types of distribution. Calculated formulas are derived. The problem of obtaining a chi-square distribution from four normally distributed random sequences is solved. Software implementation was performed using the mathematical modeling program Matlab. Graphs are proposed to illustrate the transformation of a uniformly distributed random sequence into an exponentially distributed sequence. A comparison between theoretically and practically completed transformations is given.
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Cook, Robert A. "Single Component Sites with Long Sequences of Radiocarbon Dates: The Sunwatch Site and Middle Fort Ancient Village Growth." American Antiquity 72, no. 3 (2007): 439–60. http://dx.doi.org/10.2307/40035855.
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Radiocarbon dates from single-component prehistoric sites often span temporal sequences too long to be accounted for by spatial overlap in the patterning of features. One such example is the SunWatch site, which was long interpreted as a single-component occupation of relatively short duration (15–20 years), although the radiocarbon sequence comfortably spans a 500-year period (ca. A.D. 1000 to 1500). This study compares spatial contexts of the SunWatch radiocarbon dates with other temporal indicators, including architectural rebuilding, feature form and volume, and diagnostic artifact attributes. Two distinct portions of the radiocarbon sequence can be accounted for by reference to these other lines of evidence. Village growth is linked with internal and external processes, including the arrival of a small Mississippian group and the possibility of site reoccupation, common among shifting agricultural systems.
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Zhang, Jing, Wei Guo, Ruoyu Liang, Lei Wang, Zhonglin Fu, and Jiang Sun. "How to Find the Key Participants in Crowdsourcing Design? Identifying Lead Users in the Online Context Using User-Contributed Content and Online Behavior Analysis." Sustainability 14, no. 4 (2022): 2094. http://dx.doi.org/10.3390/su14042094.
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Lead users are the most valuable innovation sources in crowdsourcing design; how to identify these users is a research hotspot in the field of design and management. Existing approaches to discover lead users in the context of the online community, such as the manual method and ordering algorithm, have some limitations, for instance, low coverage and accuracy. To address these deficiencies, this article proposes a method that applies text-mining techniques, analysis of user behavior, and contributed content to identify lead users. We suggest a three-step analytical approach: First, a criterion system to evaluate the user’s leading-edge status is constructed. Second, we utilize a fuzzy analytical hierarchy process to assess the weighted value of each indicator and develop the reference sequence of the indicators. Third, grey relational analysis is employed to analyze the correlations between users’ indicators and reference sequences, and lead users are recognized based on each user’s correlation ranking. An empirical analysis is used to examine the effectiveness of the proposed method. The results reveal that the method has good precision and recall rate, can automatically process large-scale data, and has no strict requirements for respondents. Finally, the article discusses the limitations and provides possible directions for future research.
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Tamirrino, Nindra Giandra, Heris Hendriana, and Wahyu Hidayat. "Analysis of Mathematical Creative Thinking Abilities of High School Students in West Bandung Regency." (JIML) JOURNAL OF INNOVATIVE MATHEMATICS LEARNING 6, no. 2 (2023): 104–12. http://dx.doi.org/10.22460/jiml.v6i2.15580.
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The rapid development of technology requires creative human resources to solve various mathematical problems. The importance of thinking creatively is contained in the Graduate Competency Standards (SKL). This study aims to determine the mathematical creative thinking skills of high school students in West Bandung using sequence and series materials. The research method used is the descriptive qualitative research method. The study was conducted on 35 class XI students at a high school in West Bandung. The instrument used is four items about the ability to think creatively on the material sequences and series. The research was conducted in the odd semester of the 2022-2023 school year. The results showed that the percentage of flexibility indicator questions was 61.143%, which means most students can work on questions with the flexibility indicator. The rate of fluency indicator items was 52%, the percentage of originality indicator items was 43.169%, and the elaboration indicator was 40%. These results show that the elaboration indicator has the rate percentage compared to other indicators of creative thinking ability. The study’s results concluded that the creative thinking skills of high school students in West Bandung Regency were still low, with a percentage of 49.19%. Researchers recommend using interactive learning media such as e-LKPD to improve mathematical creative thinking abilities.
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DR., GULSARAKHON M. OSTONAKULOVA, JAMSHID GANIJONOVICH JALILOV, and BEKZOD TOXIROVICH MUXSINOV. "Mechanisms of Economic Analysis of Marketing Activities." International Journal of Academic Research in Business, Arts & Science ( IJARBAS.COM ) 3, no. 5 (2021): 153–58. https://doi.org/10.5281/zenodo.4994496.
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The article proposes an algorithm for a complex economic analysis of marketing activities with a description of the tasks and methods of analysis at each stage of the sequence of mechanisms. The sources, process and results of marketing activities are analyzed in order to identify trends, behaviors, resources and opportunities to increase the effectiveness of marketing activities. <strong>Keywords:</strong> mechanisms of economic analysis of marketing activities, comprehensive analysis of marketing activities, marketing indicators, financial indicators,
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Li, Chengang, Xuan Wang, Yongxiang Hu, Ying Yan, Han Jin, and Guofei Shang. "Forecasting shipping index using CEEMD-PSO-BiLSTM model." PLOS ONE 18, no. 2 (2023): e0280504. http://dx.doi.org/10.1371/journal.pone.0280504.
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Shipping indices are extremely volatile, non-stationary, unstructured and non-linear, and more difficult to forecast than other common financial time series. Based on the idea of "decomposition-reconstruction-integration", this article puts forward a combined forecasting model CEEMD-PSO-BiLSTM for shipping index, which overcomes the linearity limitation of traditional models. CEEMD is used to decompose the original sequence into several IMF components and RES sequences, and the IMF components are recombined by reconstruction. Each sub-sequence is predicted and analyzed by PSO-BiLSTM neural network, and finally the predicted value of the original sequence is obtained by summing up the predicted values of each sub-sequence. Using six major shipping indices in China’s shipping market such as FDI and BDI as test data, a systematic comparison test is conducted between the CEEMD-PSO-BiLSTM model and other mainstream time-series models in terms of forecasting effects. The results show that the model outperforms other models in all indicators, indicating its universality in different shipping markets. The research results of this article can deepen and improve the understanding of shipping indices, and also have important implications for risk management and decision management in the shipping market.
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Amihai, Ido, Arzam Kotriwala, Diego Pareschi, Moncef Chioua, and Ralf Gitzel. "Using Learned Health Indicators and Deep Sequence Models to Predict Industrial Machine Health." Engineering Proceedings 5, no. 1 (2021): 7. http://dx.doi.org/10.3390/engproc2021005007.
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In this paper, we describe a machine learning approach for predicting machine health indicators with a large time horizon into the future. The approach uses state-of-the-art neural network architectures for sequence modelling and can incorporate numerical-sensor and categorical data using entity embeddings. Moreover, we describe an unsupervised labelling approach where classes are generated using continuous sensor values in the training data and a clustering algorithm. To validate our approach, we performed an ablation study to verify the effectiveness of each of our model’s components. In this context, we show that entity embeddings can be used to generate effective features from categorical inputs, that state-of-the-art models, while originally developed for a different set of problems, can nonetheless be transferred to perform industrial asset health classification and provide a performance boost over simpler networks that have been traditionally used, such as relatively shallow recurrent or convolutional networks. Taken together, we present a machine health monitoring system that can accurately generate asset health predictions. This system can incorporate both numerical and categorical information, the current state-of-the-art for sequence modelling, and generate labels in an unsupervised fashion when explicit labels are unavailable.
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Durrant, Gabriele B., Olga Maslovskaya, and Peter W. F. Smith. "Using Prior Wave Information and Paradata: Can They Help to Predict Response Outcomes and Call Sequence Length in a Longitudinal Study?" Journal of Official Statistics 33, no. 3 (2017): 801–33. http://dx.doi.org/10.1515/jos-2017-0037.
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AbstractIn recent years the use of paradata for nonresponse investigations has risen significantly. One key question is how useful paradata, including call record data and interviewer observations, from the current and previous waves of a longitudinal study, as well as previous wave survey information, are in predicting response outcomes in a longitudinal context. This article aims to address this question. Final response outcomes and sequence length (the number of calls/visits to a household) are modelled both separately and jointly for a longitudinal study. Being able to predict length of call sequence and response can help to improve both adaptive and responsive survey designs and to increase efficiency and effectiveness of call scheduling. The article also identifies the impact of different methodological specifications of the models, for example different specifications of the response outcomes. Latent class analysis is used as one of the approaches to summarise call outcomes in sequences. To assess and compare the models in their ability to predict, indicators derived from classification tables, ROC (Receiver Operating Characteristic) curves, discrimination and prediction are proposed in addition to the standard approach of using the pseudo R2value, which is not a sufficient indicator on its own. The study uses data from Understanding Society, a large-scale longitudinal survey in the UK. The findings indicate that basic models (including geographic, design and survey data from the previous wave), although commonly used in predicting and adjusting for nonresponse, do not predict the response outcome well. Conditioning on previous wave paradata, including call record data, interviewer observation data and indicators of change, improve the fit of the models slightly. A significant improvement can be observed when conditioning on the most recent call outcome, which may indicate that the nonresponse process predominantly depends on the most current circumstances of a sample unit.
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Krawczyk, Marcin, Kamila Ryzner, Jacek Skurzyński, and Zdzisław Jary. "Lithological indicators of loess sedimentation of SW Poland." Contemporary Trends in Geoscience 6, no. 2 (2017): 94–111. http://dx.doi.org/10.1515/ctg-2017-0008.
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Abstract High-resolution grain-size investigations were carried out in two SW Polish loess sections: Biały Kościół (Niemcza-Strzelin Hills) and Zaprężyn (Trzebnica Hills). Each sequence was sampled by using the same methodology and samples were taken at 5 centimeters intervals. The particle size distribution was obtained with a Mastersizer 2000 laser, used for diffraction methods. From the obtained results the basic parameters and grain size indicators were calculated: Mz, Grain Size Index ratio, U-ratio and the percentage content of clay (< 4μm) and sand (> 63 μm). Both loess-soil sequences are composed of interfluve and slope loess facies and consist of five litho-pedostratigraphic units developed during the Late Pleistocene and Holocene: two loess units L1LL1, L1LL2 and three polygenetic fossil soils sets S0, S1 and L1SS1. The distance between these two profiles is about 60 km. Zaprężyn, as a section located more to the north, has almost no lower younger loess and higher level of weathering which could be related to proximity of this site to the Ice Sheet margin. The climate here was more extreme and harsh. What is more, the difference in development of soil L1SS1 can be observed: while in Biały Kościół pedogenesis process was slower and less disturbed than in Zaprężyn. The upper part of L1SS1 in Biały Kościół was deformed by gelifluction, frost heave and other periglacial processes. Mz indicator by the grain-size distribution in these sediments reflects subtle variations in the climatic system. Moreover, in Zaprężyn the content of sand fraction is higher than in Biały Kościół what can be the evidence of short episodes of strong winds during cold period of sedimentation. The aim of this paper is to compare two loess profiles by their stratigraphical and lithological similarities which are result of climate conditions and features of surrounding environment.