Academic literature on the topic 'Data residual relationships'
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Journal articles on the topic "Data residual relationships"
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Shin, Kyuhee, Joon Jin Song, Wonbae Bang, and GyuWon Lee. "Quantitative Precipitation Estimates Using Machine Learning Approaches with Operational Dual-Polarization Radar Data." Remote Sensing 13, no. 4 (February 14, 2021): 694. http://dx.doi.org/10.3390/rs13040694.
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Traditional radar-based rainfall estimation is typically done by known functional relationships between the rainfall intensity (R) and radar measurables, such as R–Zh, R–(Zh, ZDR), etc. One of the biggest advantages of machine learning algorithms is the applicability to a non-linear relationship between a dependent variable and independent variables without any predefined relationships. We explored the potential use of two supervised machine learning methods (regression tree and random forest) in rainfall estimation using dual-polarization radar variables. The regression tree does not require normalization and scaling of data; however, this method is quite unstable since each split depends on the parent split. Since the random forest is an ensemble method of regression trees, it has less variability in prediction compared with regression trees, but consumes more computer resources. We considered several different configurations for machine learning algorithms with different sets of dependent and independent variables. The random forest model was appropriately tuned. In the test of variable importance, the specific differential phase (differential reflectivity) was the most important variable to predict the rainfall rate (residual that is the difference between the true rainfall rate and the one estimated from the R–Z relationship). The models were evaluated by 10-fold cross-validation. The best model was the random forest model using a residual with the non-classified training set. The results indicated that the machine learning algorithms outperformed the traditional R–Z relationship. Then, we applied the best machine learning model to an S-band dual-polarization radar (Mt. Myeonbong) and validated the result with ground rain gauges. The results of the application to radar data showed that the estimates of the residuals had spatial variability. The stratiform and weak rain areas had positive residuals while convective areas had negative residuals, indicating that the spatial error structure driven by the R–Z relationship was well captured by the model. The rainfall rates of all pixels over the study area were adjusted with the estimated residuals. The rainfall rates adjusted by residual showed excellent agreement with the rain gauge, especially at high rainfall rates.
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Ortolani, Matteo, Cristy Leonor Azanza Ricardo, and Paolo Scardi. "Analysis of Residual Stress-Texture Relationships in Thin Films." Advanced Materials Research 89-91 (January 2010): 425–30. http://dx.doi.org/10.4028/www.scientific.net/amr.89-91.425.
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A new software was developed for the X-ray stress analysis of textured materials, especially useful in the case of thin films and coating. Literature data for a sputtered Cu thin film were used as a test case. Good agreement with the published results was found considering a grain interaction mechanism based on the combination of four models (Ruess/Voigt/Vook-Witt/inverse Vook-Witt). A similar value for the in-plane residual stress was obtained by the Eshelby-Kröner model, by optimizing the grain aspect-ratio. Main features and numerical/graphic output are briefly discussed.
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Sharma, M. L. "Attenuation relationship for estimation of peak ground horizontal acceleration using data from strong-motion arrays in India." Bulletin of the Seismological Society of America 88, no. 4 (August 1, 1998): 1063–69. http://dx.doi.org/10.1785/bssa0880041063.
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Abstract An attenuation relationship for peak horizontal ground accelerations for Himalayan region in India has been developed. The data base consists of 66 peak ground horizontal accelerations from five earthquakes recorded by strong-motion arrays in India. The present analysis uses a two-step stratified regression model. The attenuation relationship proposed is log ( A ) = − 1.072 + 0.3903 M − 1.21 log ( X + e 0.5873 M ) , where A is the peak ground acceleration (g), M is the magnitude, and X is the hypocentral distance from the source. The residual sum of squares is 0.14. Comparison with other such attenuation relationships have been made. The proposed relationship giving lesser values at shorter distances compared to other relationships needs further investigation with a larger data set. The attenuation relationship needs upgradation when more data become available in future.
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Arciszewski, Tim J., and David R. Roberts. "Analyzing Relationships of Conductivity and Alkalinity Using Historical Datasets from Streams in Northern Alberta, Canada." Water 14, no. 16 (August 14, 2022): 2503. http://dx.doi.org/10.3390/w14162503.
Full textAbstract:
Many measurements, tools, and approaches are used to identify and track the influence of human activities on the physicochemical status of streams. Commonly, chemical concentrations are utilized, but in some areas, such as downstream of coal mines, capacity indices such as specific conductivity have also been used to estimate exposure and risk. However, straightforward tools such as conductivity may not identify human influences in areas with saline groundwater inputs, diffuse exposure pathways, and few discharges of industrial wastewater. Researchers have further suggested in conductivity relative to alkalinity may also reveal human influences, but little has been done to evaluate the utility and necessity of this approach. Using data from 16 example sites in the Peace, Athabasca, and Slave Rivers in northern Alberta (but focusing on tributaries in Canada’s oil sands region) available from multiple regional, provincial, and national monitoring programs, we calculated residual conductivity and determined if it could identify the potential influence of human activity on streams in northern Alberta. To account for unequal sampling intervals within the compiled datasets, but also to include multiple covariates, we calculated residual conductivity using the Generalized Estimating Equation (GEE). The Pearson residuals of the GEEs were then plotted over time along with three smoothers (two locally weighted regressions and one General Additive Model) and a linear model to estimate temporal patterns remaining relative to known changes in human activity in the region or adjacent to the study locations. Although there are some inconsistencies in the results and large gaps in the data at some sites, many increases in residual conductivity correspond with known events in northern Alberta, including the potential influence of site preparation at oil sands mines, reductions in particulate emissions, mining, spills, petroleum coke combustion at one oil sands plant, and hydroelectric development in the Peace basin. Some differences in raw conductivity measurements over time were also indicated. Overall, these analyses suggest residual conductivity may identify broad influences of human activity and be a suitable tool for augmenting broad surveillance monitoring of water bodies alongside current approaches. However, some anomalous increases without apparent explanations were also observed suggesting changes in residual conductivity may also be well-suited for prompting additional and more detailed studies or analyses of existing data.
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Fu, ShuYing, WenDong Lin, XiNing Zhao, ShengJin Ge, and ZhangGang Xue. "Quantitative Relationships between Pulmonary Function and Residual Neuromuscular Blockade." BioMed Research International 2018 (2018): 1–6. http://dx.doi.org/10.1155/2018/9491750.
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Background. Neuromuscular blockade is a risk factor for postoperative respiratory weakness during the immediate postoperative period. The quantitative relationships between postoperative pulmonary-function impairment and residual neuromuscular blockade are unknown. Methods. 113 patients who underwent elective laparoscopic cholecystectomy were enrolled in this study. They all had a pulmonary-function test (PFT) during the preoperative evaluation. Predictive values based on demographic data were also recorded. The train-of-four ratio (TOFR) was recorded at the same time as the PFT and at every 5 minutes in the qualified 98 patients in the postanesthesia care unit (PACU). We analyzed the degree of PFT recovery when the TOFR had recovered to different degrees. Results. There was a significant difference (P<0.05) between the preoperative baseline value and the postoperative forced vital capacity at each TOFR point, except at a TOFR value of 1.1. There was also a significant difference (P<0.05) between the preoperative baseline value and the postoperative peak expiratory flow at each TOFR point. Conclusions. Postoperative residual neuromuscular blockade was common (75.51%) after tracheal extubation, and pulmonary function could not recover to an acceptable level (85% of baseline value), even if TOFR had recovered to 0.90. Trial Registration. Chinese Clinical Trial Register is ChiCTR-OOC-15005838.
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Eleonsky, Sviatoslav, Vladimir Pisarev, Mikhail Zajtsev, Mikhail Zichenkov, and Marat Abdullin. "Residual stresses near cold-expanded hole at different stages of high-cycle fatigue by crack compliance data." Frattura ed Integrità Strutturale 15, no. 56 (March 28, 2021): 171–96. http://dx.doi.org/10.3221/igf-esis.56.14.
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Experimental method for a characterization of high-cycle fatigue evolution of residual stress near cold-expanded hole is developed and implemented. The technique is based on simultaneous measurements of deformation response to narrow notch, inserted in residual stress field, on opposite specimen’s faces by electronic speckle-pattern interferometry (ESPI). Two-side measurements of notch opening displacements are performed when a single notch, emanating from cold-expanded hole edge, is inserted. The transition from in-plane displacement component to residual stress intensity factor (SIF) values follows from the relationships of modified version of the crack compliance method. The approach provides a difference in residual stress values referred to mandrel entrance and exit surface. Notches are inserted at different stages of low-cycle fatigue without applying external load. The results obtained describe fine nuances of residual stress evolution, which cannot be considered as monotonic relaxation.
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Cartocci, Nicholas, Marcello R. Napolitano, Francesco Crocetti, Gabriele Costante, Paolo Valigi, and Mario L. Fravolini. "Data-Driven Fault Diagnosis Techniques: Non-Linear Directional Residual vs. Machine-Learning-Based Methods." Sensors 22, no. 7 (March 29, 2022): 2635. http://dx.doi.org/10.3390/s22072635.
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Linear dependence of variables is a commonly used assumption in most diagnostic systems for which many robust methodologies have been developed over the years. In case the system nonlinearities are relevant, fault diagnosis methods, relying on the assumption of linearity, might potentially provide unsatisfactory results in terms of false alarms and missed detections. In recent years, many authors have proposed machine learning (ML) techniques to improve fault diagnosis performance to mitigate this problem. Although very powerful, these techniques require faulty data samples that are representative of any fault scenario. Additionally, ML techniques suffer from issues related to overfitting and unpredictable performance in regions which are not fully explored in the training phase. This paper proposes a non-linear additive model to characterize the non-linear redundancy relationships among the system signals. Using the multivariate adaptive regression splines (MARS) algorithm, these relationships are identified directly from the data. Next, the non-linear redundancy relationships are linearized to derive a local time-dependent fault signature matrix. The faulty sensor can then be isolated by measuring the angular distance between the column vectors of the fault signature matrix and the primary residual vector. A quantitative analysis of fault isolation and fault estimation performance is performed by exploiting real data from multiple flights of a semi-autonomous aircraft, thus allowing a detailed quantitative comparison with state-of-the-art machine-learning-based fault diagnosis algorithms.
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Bandyopadhyay, S. K., and R. De. "Nitrogen relationships and residual effects of intercropping sorghum with legumes." Journal of Agricultural Science 107, no. 3 (December 1986): 629–32. http://dx.doi.org/10.1017/s0021859600069793.
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SUMMARYIntercropped with legumes, sorghum removed more N from the growing medium than when grown alone. 16N data showed that out of the total N removed by sorghum in a sorghum + mung mixture 18·1% was derived from the fertilizer urea and 81·9% came from the soil pool; the latter included 21·9 % N derived from current fixation by the legumes. When grown alone sorghum plants derived 18·6 % N from urea and 81·4 % from the soil.The yield of wheat grown in sequence was 5·13 t/ha after a previous sole crop of mung and 3·47 t/ha after sorghum. The yield of wheat after sole crops of legume was greater than after their mixture with sorghum. The latter was, however, greater than its yield after sole sorghum.The economic optimum rate of N required after wheat, computed from an experiment with several rates of applied N on an adjacent plot, was 124 and 105 kg N/ha at expected yields of 5·2 and 4·5 t/ha of wheat respectively. By interpolation the relative yield advantage from sole legumes ranged between 28 and 68 kg N/ha in 1982–3 and was more than 90 kg N/ha in the next year. These advantages from legume + non-legume mixtures equalled 12–17 kg N/ha applied to wheat, in addition to 50 kg N/ha applied uniformly to the sequential crop of wheat.
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Northwood, Derek O., Lily He, Erin Boyle, and Randy J. Bowers. "Retained Austenite - Residual Stress - Distortion Relationships in Carburized SAE 6820 Steel." Materials Science Forum 539-543 (March 2007): 4464–69. http://dx.doi.org/10.4028/www.scientific.net/msf.539-543.4464.
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SAE 8620 steel is typically used in the carburized condition for powertrain applications in the automotive industry, e.g. gears, roller bearings, camshafts. Such steels always contain retained austenite to varying degrees in the as-hardened and also in the tempered microstructures. As well as retained austenite, heat treatment can produce residual stresses, which lead to distortion (size and shape). The intent of this study was to investigate the effect of heat treatment parameters on the amount of retained austenite, residual stress and distortion in carburized SAE 8620 steel. A specially designed specimen, the Navy C-ring, was used for this study. The steel was first normalized prior to machining the Navy C-ring specimens. The specimens were then heat treated by carburizing at 927°C or 954°C (1700°F or 1750°F) at four levels of carbon potential (0.9, 1.0, 1.1, 1.2) followed by oil quenching and tempering at either 149°C or 177°C (300°F or 350°F). The distortion of the C-ring was evaluated by dimensional measurements of the inner diameter, outer diameter, gap width and thickness for size distortion, as well as flatness, cylindricity and roundness for shape distortion. X-ray diffraction (XRD) techniques were used to determine the residual stress and the amount of retained austenite. The amount of retained austenite was also measured by optical metallography. The amount of retained austenite and the residual stress increased with increasing carburizing temperature and carbon potential and decreased upon tempering. There was not a significant further reduction in the amount of retained austenite and residual stress when the tempering temperature was increased from 149°C to 177°C. Distortion was influenced by both the amount of retained austenite and the magnitude of the residual stress. With increasing retained austenite/residual stress, the distortion became more serious. Based on the distortion data for 3 parameters (OD, gap width and flatness) for the quenched and tempered specimens, the amount of retained austenite for minimum distortion was approximately 25%.
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Reist, James D. "An empirical evaluation of coefficients used in residual and allometric adjustment of size covariation." Canadian Journal of Zoology 64, no. 6 (June 1, 1986): 1363–68. http://dx.doi.org/10.1139/z86-203.
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Univariate computation of residuals or allometric variates should be used to estimate the shape of body parts of ectothermic vertebrates. For studies involving more than one group, three types of relationships may be used to calculate the slopes or allometric coefficients necessary for computing the shape variate: pooled group, common-within groups, and individual-within groups. For both residuals and allometric variates, the pooled and common-within groups coefficients resulted in similar estimates of shape when there was no between-group heterogeneity in relationships. Within-group coefficients resulted in quite different estimates of shape. Heterogeneity of slopes or allometric coefficients resulted in different estimates of shape for the same individual for pooled common-within and within-groups data. Such differences in the shape variates were cumulative in subsequent analyses such that considerably different biological interpretations of group interrelationships resulted. Thus, if any between-group heterogeneity exists in regression or allometric relationships, it is imperative that shape be estimated from the common-within groups relationship.
Dissertations / Theses on the topic "Data residual relationships"
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Teng, Luyao. "Research on Joint Sparse Representation Learning Approaches." Thesis, 2019. https://vuir.vu.edu.au/40024/.
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Dimensionality reduction techniques such as feature extraction and feature selection are critical tools employed in artificial intelligence, machine learning and pattern recognitions tasks. Previous studies of dimensionality reduction have three common problems: 1) The conventional techniques are disturbed by noise data. In the context of determining useful features, the noises may have adverse effects on the result. Given that noises are inevitable, it is essential for dimensionality reduction techniques to be robust from noises. 2) The conventional techniques separate the graph learning system apart from informative feature determination. These techniques used to construct a data structure graph first, and keep the graph unchanged to process the feature extraction or feature selection. Hence, the result of feature extraction or feature selection is strongly relying on the graph constructed. 3) The conventional techniques determine data intrinsic structure with less systematic and partial analyzation. They maintain either the data global structure or the data local manifold structure. As a result, it becomes difficult for one technique to achieve great performance in different datasets.
We propose three learning models that overcome prementioned problems for various tasks
under different learning environment. Specifically, our research outcomes are listing as
followings:
1) We propose a novel learning model that joints Sparse Representation (SR) and
Locality Preserving Projection (LPP), named Joint Sparse Representation and
Locality Preserving Projection for Feature Extraction (JSRLPP), to extract
informative features in the context of unsupervised learning environment. JSRLPP
processes the feature extraction and data structure learning simultaneously, and is
able to capture both the data global and local structure. The sparse matrix in the
model operates directly to deal with different types of noises. We conduct
comprehensive experiments and confirm that the proposed learning model
performs impressive over the state-of-the-art approaches.
2) We propose a novel learning model that joints SR and Data Residual Relationships
(DRR), named Unsupervised Feature Selection with Adaptive Residual Preserving
(UFSARP), to select informative features in the context of unsupervised learning
environment. Such model does not only reduce disturbance of different types of
noise, but also effectively enforces similar samples to have similar reconstruction
residuals. Besides, the model carries graph construction and feature determination
simultaneously. Experimental results show that the proposed framework improves
the effect of feature selection.
3) We propose a novel learning model that joints SR and Low-rank Representation
(LRR), named Sparse Representation based Classifier with Low-rank Constraint
(SRCLC), to extract informative features in the context of supervised learning environment. When processing the model, the Low-rank Constraint (LRC) regularizes both the within-class structure and between-class structure while the sparse matrix works to handle noises and irrelevant features. With extensive experiments, we confirm that SRLRC achieves impressive improvement over other approaches.
To sum up, with the purpose of obtaining appropriate feature subset, we propose three novel learning models in the context of supervised learning and unsupervised learning to complete the tasks of feature extraction and feature selection respectively. Comprehensive experimental results on public databases demonstrate that our models are performing superior over the state-of-the-art approaches.
Books on the topic "Data residual relationships"
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A, Geller Marvin, and Laboratory for Atmospheres (Goddard Space Flight Center), eds. Residual circulations calculated from satellite data: Their relationships to observed temperature and ozone distributions. Stony Brook, NY: Institute for Terrestrial and Planetary Atmospheres, State University of New York at Stony Brook, 1990.
Find full textBook chapters on the topic "Data residual relationships"
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Anderson, Raymond A. "Predictive Modelling Techniques." In Credit Intelligence & Modelling, 503–46. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192844194.003.0014.
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This chapter covers commonly-used supervised-learning techniques and combinations, with guidance on choices. (1) A view from on high—i) caveats—data dependency of predictive modelling; ii) language—in academic literature for representation of formulae and concepts. (2) Parametric—make assumptions about the relationships between predictors and predicted, and their distributions {linear regression, linear probability modelling (LPM), probit/logit, discriminant analysis, linear programming}. (3) Non-parametric—require few or no assumptions {k-nearest neighbours, Decisions Trees and Random Forests (RF)s, support vector machines, artificial neural networks, genetic algorithms}. (4) Conglomerations—of models and approaches, whether i) practical—for business reasons; ii) parallel—developed using the same data, and then fused; iii) residual—subsequent models predict what prior models could not. Machine learning is introduced. (5) Making the choice—factors affecting the choice {regulatory/compliance, transparency/opacity, suitability to the statistical and business problems, skills availability, longer-term maintenance, development and implementation timeframes, speed of execution once implemented}.
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Tomii, Kentaro, and Minoru Kanehisa. "Systematic Detection of Protein Structural Motifs." In Pattern Discovery in Biomolecular Data. Oxford University Press, 1999. http://dx.doi.org/10.1093/oso/9780195119404.003.0012.
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It is widely believed that the prediction of the 3D structure of a protein from its amino acid sequence is important because the structure will help understand the function. As the number of protein structures resolved is increasing, most predictive methods have become based on the knowledge of the repertoire of 3D folds taken by actual proteins. We must emphasize, however, that this type of structure prediction, or fold recognition, concerns the overall folding of the polypeptide chain. Since two similar folds could be due to entirely different sequences and even two similar sequences could have different functions, it is unlikely that successful fold recognition will uncover any functional clue that cannot otherwise be obtained by sequence analysis alone. In contrast to the global feature of 3D folds, the concept of structural motifs or local structures is far more important in understanding protein function. It has been revealed that there are common local folding patterns that appear in many proteins of globally different structures and that are involved in conserved function. In addition, the local sequence patterns associated with these local structures are also often conserved, though the whole sequences can be quite different. At the supersecondary structure level there are, for example, βαβ -unit, EF hand, and helix-turn-helix motifs. Various dehydrogenases have a common structural motif called Rossman fold, which is composed of two consecutive βαβ -units, and most of those proteins also have the sequence motif GxGxxG around the nucleotide binding region (Wierenga and Hol, 1983; Wierenga et al., 1986). The EF hand consisting of the helix-loop-helix structure (Tufty and Kretsinger, 1975) occurs in many calcium-binding domains, and the residues that participate in ligand binding are well conserved. The helix-turn-helix motif that involves about 20 residues appears in a class of DNA-binding domains, and glycine tends to be conserved at a special position in the turn whose conformation corresponds to the left-handed helix. A number of known sequence motifs are registered in the motif libraries such as PROSITE (Bairoch and Bucher, 1994) that compile the relationships between sequence patterns and functions.
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"Community Ecology of Stream Fishes: Concepts, Approaches, and Techniques." In Community Ecology of Stream Fishes: Concepts, Approaches, and Techniques, edited by Gary D. Grossman and John L. Sabo. American Fisheries Society, 2010. http://dx.doi.org/10.47886/9781934874141.ch20.
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<em>Abstract.—</em>Stochastic dynamics are central to theory, data analysis, and understanding in the fields of hydrology and population ecology. More importantly, hydrologic variability has been identified as a key process affecting biodiversity and coexistence in stream fish assemblages. Until recently, however, we have lacked tools by which hydrologic variability can be directly linked to measures of community stability. Herein, we show how a modification of Fourier analysis of daily average discharge data can be used to quantify aspects of hydrologic variability for three reference streams and then linked to measures of fish assemblage stability in Coweeta Creek, North Carolina; Sagehen Creek, California; and Otter Creek, Indiana) via multivariate autoregressive (MAR) models. Specifically, we define the magnitude of catastrophic variability as the standard deviation of <em>residual </em>flows referenced to a long-term annual trend, and individual catastrophic events as flows greater than (floods) or less than (droughts) two times this magnitude (i.e., 2 𝛔). We then directly link the magnitude of annual <em>residual </em>flows with MAR models that quantify the relationship between flows and the stability of fish assemblages from the same or nearby streams. Our results confirm that these streams represent a gradient in the stability properties of fish assemblages; Sagehen Creek is the most stable, whereas Otter Creek is the least stable. The timing of catastrophic high and low flows is most predictable in Sagehen Creek and least predictable in Big Raccon Creek (reference stream for Otter Creek), whereas the magnitude and frequency of <em>catastrophic </em>events varied in a manner less consistent with the gradient in fish community stability. Nevertheless, the stability of fish communities covaried significantly with both residual flow magnitudes (high- and low-flow events). Although this technique is not without limitations (e.g., it is most relevant to resident species), it appears to be a promising new tool for linking hydrologic variability directly to fish assemblage stability and, more broadly, for quantifying links between flow regulation and the viability of native aquatic faunas.
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Wu, Daniel, and Xiaohua Hu. "Topological Analysis and Sub-Network Mining of Protein-Protein Interactions." In Research and Trends in Data Mining Technologies and Applications, 209–40. IGI Global, 2007. http://dx.doi.org/10.4018/978-1-59904-271-8.ch008.
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In this chapter, we report a comprehensive evaluation of the topological structure of protein-protein interaction (PPI) networks, by mining and analyzing graphs constructed from the popular data sets publicly available to the bioinformatics research community. We compare the topology of these networks across different species, different confidence levels, and different experimental systems used to obtain the interaction data. Our results confirm the well-accepted claim that the degree distribution follows a power law. However, further statistical analysis shows that residues are not independent on the fit values, indicating that the power law model may be inadequate. Our results also show that the dependence of the average clustering coefficient on the vertices degree is far from a power law, contradicting many published results. For the first time, we report that the average vertex density exhibits a strong powder law dependence on the vertices degree for the networks studied, regardless of species, confidence levels, and experimental systems. We also present an efficient and accurate approach to detecting a community in a protein-protein interaction network from a given seed protein. Our experimental results show strong structural and functional relationships among member proteins within each of the communities identified by our approach, as verified by MIPS complex catalog database and annotations.
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Tzanetou, Evagelia, and Helen Karasali. "Glyphosate Residues in Soil and Air: An Integrated Review." In Pests, Weeds and Diseases in Agricultural Crop and Animal Husbandry Production. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.93066.
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Glyphosate [N-(phosphonomethyl) glycine] (GPS) is currently the most commonly applied herbicide worldwide. Given the widespread use of glyphosate, the investigation of the relationship between glyphosate and soil ecosystem is critical and has great significance for its valid application and environmental safety evaluation. However, although the occurrence of glyphosate residues in surface and groundwater is rather well documented, only few information are available for soils and even fewer for air. Due to this, the importance of developing methods that are effective and fast to determine and quantify glyphosate and its major degradation product, aminomethylphosphonic acid (AMPA), is emphasized. Based on its structure, the determination of this pesticide using a simple analytical method remains a challenge, a fact known as the “glyphosate paradox.” In this chapter a critical review of the existing literature and data comparison studies regarding the occurrence and the development of analytical methods for the determination of pesticide glyphosate in soil and air is performed.
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David Durán-Aranguren, Daniel, Caren Juliana Alméciga Ramírez, Laura Catalina Villabona Díaz, Manuela Ayalde Valderrama, and Rocío Sierra. "Production of Pectin from Citrus Residues: Process Alternatives and Insights on Its Integration under the Biorefinery Concept." In Pectins [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.100153.
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This chapter describes the pectin production process from citrus residues. It discusses the importance of essential oils removal before processing through steam distillation, hydrodistillation, or solvent extraction. Also, it presents different extraction methods (acid hydrolysis, microwave-assisted acid hydrolysis, and hydrodistillation) that have been employed and different solvents that can be used for its purification. Since all these processing parameters can affect the final pectin yield and quality, a discussion is made on which processing options and conditions could be used based on recently reported data. The best operational conditions based on the percentages of pectin recovery and their relationship with quality parameters, such as the galacturonic acid content and degree of esterification are presented. Finally, a discussion is made regarding the opportunities for its integration under the biorefinery concept that could help to enhance several economic and environmental aspects of the process.
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P. Agbo, Emmanuel. "The Role of Statistical Methods and Tools for Weather Forecasting and Modeling." In Weather Forecasting [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.96854.
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The need to understand the role of statistical methods for the forecasting of climatological parameters cannot be trivialized. This study gives an in depth review on the different variations of the Mann-Kendall (M-K) trend test and how they can be applied, regression techniques (Simple and Multiple), the Angstrom-Prescott model for solar radiation, etc. The study then goes ahead to apply some of them with data obtained from the Nigerian Meteorological Agency (NiMet), and applying tools like the python programming language and Wolfram Mathematica. Results show that the maximum ambient temperature for Calabar is increasing (Z = 2.52) significantly after the calculated p-value <0.05 (significant level). The seasonal M-K test was also applied for the dry and wet seasons and both were found to be increasing (Z = 3.23 and Z = 4.04 respectively) after their calculated p-values <0.05. The relationship between refractivity and other meteorological parameters relating to it was discerned using partial differential equations giving the gradient of each with refractivity; this was compared with results from the correlation matrix to show that the water vapor contents of the atmosphere contributes significantly to the variation of refractivity. Multiple linear regression has also been adopted to give an accurate model for the prediction of refractivity in the region after the residual error between the calculated refractivity and predicted refractivity was minimal.
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Flowerdew, Robin. "Modelling Migration with Poisson Regression." In Technologies for Migration and Commuting Analysis, 261–79. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-61520-755-8.ch014.
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Most statistical analysis is based on the assumption that error is normally distributed, but many data sets are based on discrete data (the number of migrants from one place to another must be a whole number). Recent developments in statistics have often involved generalising methods so that they can be properly applied to non-normal data. For example, Nelder and Wedderburn (1972) developed the theory of generalised linear modelling, where the dependent or response variable can take a variety of different probability distributions linked in one of several possible ways to a linear predictor, based on a combination of independent or explanatory variables. Several common statistical techniques are special cases of the generalised linear models, including the usual form of regression analysis, Ordinary Least Squares regression, and binomial logit modelling. Another important special case is Poisson regression, which has a Poisson-distributed dependent variable, linked logarithmically to a linear combination of independent variables. Poisson regression may be an appropriate method when the dependent variable is constrained to be a non-negative integer, usually a count of the number of events in certain categories. It assumes that each event is independent of the others, though the probability of an event may be linked to available explanatory variables. This chapter illustrates how Poisson regression can be carried out using the Stata package, proceeding to discuss various problems and issues which may arise in the use of the method. The number of migrants from area i to area j must be a non-negative integer and is likely to vary according to zone population, distance and economic variables. The availability of high-quality migration data through the WICID facility permits detailed analysis at levels from the region to the output areas. A vast range of possible explanatory variables can also be derived from the 2001 Census data. Model results are discussed in terms of the significant explanatory variables, the overall goodness of fit and the big residuals. Comparisons are drawn with other analytic techniques such as OLS regression. The relationship to Wilson’s entropy maximising methods is described, and variants on the method are explained. These include negative binomial regression and zero-censored and zero-truncated models.
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Shevchuk, Oleksandr, and Svitlana Kiporenko. "FINANCIAL SUSTAINABILITY OF AGRICULTURAL ENTERPRISES: DEVELOPMENT AND APPROVAL OF THE INTEGRATED EVALUATION MODEL." In Global trends and prospects of socio-economic development of Ukraine. Publishing House “Baltija Publishing”, 2022. http://dx.doi.org/10.30525/978-9934-26-193-0-14.
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The methodological and practical bases of integrated assessment of the financial condition of an agricultural enterprise are considered in the work. It is emphasized that the integrated method of assessment is the most objective for such an analysis, as it allows you to quantify and evaluate the relationship between the main factors and predict their level in the future. An expert method was used to determine the system of basic relative indicators for assessing the level of financial stability of the enterprise and their ratios. Verification of co-ordination of opinions of experts was conducted by the method of grade correlation with a calculation to the Kendall’s coefficient of concordance and determination of statistical importance of opinions of experts on the Pearson criterion χ2. The normative values of indicators were also adapted in accordance with the specifics of the industry and modern operating conditions. The values of the standards were determined on the basis of the results of financial and economic activities of the most efficient enterprises in the region, selected by the method of rating and scoring. Approbation of the developed model of financial condition assessment was carried out on the basis of financial reporting data of agricultural enterprises of Vinnytsia district for five years. The obtained results of calculations were used to check the presence of multicollinearity of factor features, which allowed to establish linearly dependent groups of relative indicators and to optimize the proposed model accordingly. A detailed econometric analysis of a number of dynamics of the integrated indicator of financial stability over ten years was conducted on the example of the most successful agricultural enterprise of Vinnytsia district. Theoretically and practically checked the presence of anomalous levels; the presence of a trend is determined; smoothing and alignment of a number of dynamics is carried out; the trend model is selected and its parameters are calculated; the trend model for adequacy, accuracy and presence of autocorrelation of residues is investigated; point and interval forecasting was carried out.
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Yurdakul, Emrecan, Ali İmer, and Mustafa Cihan. "Timing and Nature of Mineralization and Associated Hydrothermal Alteration at the Öksüt High-Sulfidation Epithermal Au-Cu Deposit (Kayseri Province, Central Anatolia)." In Tectonomagmatic Influences on Metallogeny and Hydrothermal Ore Deposits: A Tribute to Jeremy P. Richards (Volume I), 49–68. Society of Economic Geologists, 2021. http://dx.doi.org/10.5382/sp.24.04.
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ABSTRACT Öksüt is a breccia-hosted high-sulfidation epithermal gold-copper deposit, situated within the Develidağ Volcanic Complex in south-central Anatolia. The volcanic complex, exposed on the northern edge of the Tauride range, is largely made up of late Miocene andesitic to dacitic porphyries, covered by a succession of Pliocene basalts and basaltic andesites. A series of N-S- to NNW-trending faults of the regional central Anatolian fault zone partly cut and border the volcanic complex to the east and west. Mineralization at Öksüt follows a predominant north-northwest trend that correlates well with the regional stress regime. The bulk of the mineralization occurs in two domains, the Keltepe and Güneytepe orebodies, where steeply dipping and pervasively supergene oxidized breccia zones exploited funnel-shaped diatreme conduits within pyroxene andesite porphyry. Emplacement of these phreatomagmatic breccias was largely controlled by vertical to subvertical faults with dominant normal-slip components. Mineralized breccias comprise a central zone of residual vuggy to massive silica alteration, laterally and vertically grading into zones of quartz-alunite and quartz-alunite-clay alteration. These silica-altered breccias contain relatively high gold grades, whereas significant mineralization was also encountered in quartz-alunite-clay alteration. In the oxide zone, gold occurs in native form, whereas in the hypogene zone it occurs both as native gold or within pyrite-enargite accompanied by marcasite, and rare chalcopyrite and tetrahedrite. To the west of Keltepe and in Güneytepe, at depth, the altered and mineralized breccias pass into barren zones of argillic and then into biotite-magnetite ± K-feldspar ± anhdyrite alteration, the latter typical of porphyry-type systems. Sporadic zones of calc-silicate alteration, represented by grossularite, diopside, and vesuvianite, are also present. Three 40Ar/39Ar ages obtained from alunite and illite range between 5.7 to 5.5 Ma and are concordant with previously reported U-Pb and 40Ar/39Ar ages (~6–5.5 Ma) from host pyroxene andesite porphyry. This suggests that high-sulfidation alteration and mineralization developed contemporaneously with postsubduction magmatism at the Develidağ Volcanic Complex, in relationship to regional E-W-directed extension that commenced at ~6 Ma. Our new ages also confirm Öksüt as the youngest epithermal gold deposit discovered to date in Anatolia, and possibly in the entire Western Tethyan metallogenic belt. The topographic prominence of the volcanic edifice combined with high permeability of the breccias favored deep supergene sulfide oxidation, thereby rendering Öksüt economically viable. Gold encapsulated in hypogene sulfides was liberated during the oxidation, whereas the copper was leached to produce a discontinuous chalcocite- and covellite-dominated enrichment zone, up to 50 m thick, at the base of oxidation.
Conference papers on the topic "Data residual relationships"
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Warren, A. W., and Y. B. Guo. "An Experimental Study on Subsurface Mechanical Behavior, Residual Stress, and Microstructure Induced by Process Dynamics in Machining." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-60021.
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Surface integrity of machined components is critical for product performance in service. Process dynamic parameters, such as cutting speed and the changing contact condition between the tool flank face and machined surface, have a significant influence on surface integrity of a machined surface. Due to the very small scale of surface integrity factors on a machined surface, nanoindentation can be used to determine the surface/subsurface mechanical properties. However, the test data may be significantly influenced by machining induced residual stresses, strain hardening, and microstructure changes. The fundamental relationships between residual stress, microstructure, and nanohardness in the machined surface are yet to be understood. Further, it is not clear how to determine residual stress, at least its nature of tensile or compressive, from the nanoindentation data with the presence of complex residual stress state, strain hardening, and microstructure changes. This study focuses on the effects of cutting speed and machining system damping or rigidity (through varying tool flank wear) on subsurface mechanical state and the basic relationships between residual stress, white layer, and nanohardness. A series of nanoindentation tests were conducted to machined samples with distinct surface integrity by hard turning, grinding, and honing. It was found that white layer increases nanohardness and dark layer decreases nanohardness in subsurface, while strain hardening only slightly increases subsurface hardness. The research results indicate that subsurface residual stress can be qualitatively characterized by the load-displacement curve pattern and its parameters such as slope at initial loading, total depth, residual depth, and the ratio of residual depth to total depth. Residual stress would affect a load-displacement curve shape only at onset of yielding. Microstructure changes would make a significant difference on the characteristics of a load-displacement curve, while strain hardening exerts slight influence on the curve characteristics. In addition, the mechanism of residual stress on indentation depth was explained using a Mohr’s circle.
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Sun, Li, Jianchun Fan, Xing Meng, Ximing Zhang, Yuting Sun, Di Liu, and Zhou Yang. "Research on Residual Strength of Corroded Tubing of Gas Well With Sustained Casing Pressure." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-51443.
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Corrosion and sustained casing pressure have serious threats to the integrity of tubing of gas well. Researching the residual strength of corroded tubing has great significance to ensure the safety of gas well. The finite element method was used to study the relationships between residual strength and corrosion defects size, internal pressure, external pressure, axial load. The results show that, for tubing with uniform corrosion, the defect depth, internal pressure and external pressure have greater impacts on the von Mises equivalent stress of tubing, and the defect width and defect length have little effects on it. For tubing with pitting corrosion, the defect depth, internal pressure and external pressure have greater impacts on the von Mises equivalent stress of tubing, while the defect radius has little effect on it. These simulation data were fitted into the functions of residual strength of corroded tubing according to different corrosion morphology types. Both of the verifications of the fitting results show that most of the error between the original calculation data and the fitting calculation data is less than 4%. The fitting formulas can be used conveniently to evaluate the safety of the tubing of gas well with sustained casing pressure.
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Kim, Inki, Adam Gordon, and Scarlett R. Miller. "Stochastic Event Detection in Needle-Tissue Interaction." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47384.
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Over the last decade, many dynamic models that express needle-force relationships under tissues of varying mechanical properties have been developed. While great progress has been made in the development of these high-fidelity models, they are only valid within certain boundary conditions limiting their match with reality. This gap in realism is aggravated by variability in human tissues, needles, and the modes of interaction with the tissue. In an effort to develop more realistic models, the current paper was developed to create and test an event (i.e. changes of variability) detection method based on the probability distribution of residues — difference between force models and measurements. To obtain force measurements, we repeated robotic-driven needle insertion into a simulated mannequin. Needle types and tissue thickness were varied in the measurements in order to add realistic variability. To obtain the force model, the measurement data was used as an input to a Grey-Box model. From the measurements and models, we estimated the probability distribution of residues. For validation, a Gaussian-Mixture Model (GMM) was used to confirm the stochastic model successfully distinguishes the residual distributions under different variability. We found that by examining the residual distributions it is possible to detect unexpected variability in needle-tissue interactions. The findings from this paper have implications for developing real-time event detection methods and simulating patient-variability in haptic applications.
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Farrow, Gary H., Andrew E. Potts, Eric Jal, Nicholas D’Arcy Evans, and Andrew A. Kilner. "Review and Comparison of Collated Offshore Mooring Chain Fatigue Test Data." In ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/omae2019-95875.
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Abstract The first phase of the Chain FEARS (Finite Element Analysis of Residual Strength) Joint Industry Project (JIP) aimed to develop guidance for the determination of a rational discard criteria for mooring chains subject to severe pitting corrosion which, based on current code requirements, would otherwise require immediate removal and replacement. Critical to the ability to evaluate the residual fatigue life of a degraded chain, is to have an accurate estimate of the chain in its as-new condition, thereby providing a benchmark for any loss in fatigue life associated with severe corrosion or wear. A large collection of fatigue test data was collated for comparison and to establish underlying trends in as-new mooring chain fatigue response, and a non-linear multi-axial Finite Element Analysis (FEA) fatigue assessment method was developed to correlate against available as-new chain link fatigue test data and underlying failure trends [1,2] as part of the JIP achieving this critical requirement. This study sought through collation and review of available fatigue test data to: • Identify relationships between chain fatigue performance and the key input parameters of chain type, grade and environmental conditions. • Compare and validate the fatigue test data against the current Code formulations for chain fatigue endurance. • Determine chain nominal stress S-N fatigue endurance curves against which to validate a numerical model developed as part of the Chain FEARS JIP for the assessment of as-new chain link fatigue endurance. The collated fatigue data was separated into groups associated with offshore mooring chain type (i.e. stud and studless), grade (i.e. ORQ, R3, R4 and R5) and environmental conditions (i.e. free corrosion in seawater and in-air) for review. Good correlation occurred between the two standard deviation lower bound of the mean curves and current Code formulation design curves. The mean curves of the collated fatigue test data were considered representative of the overall fatigue performance of chain links and as such formed a good basis for subsequent development and the validation of an FEA model for the assessment of chain fatigue endurance [1,2].
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Badr, Elie A., and Joanne Ishak. "High-Cycle Fatigue Behavior of Type 4340 Steel Pressurized Blocks Including Mean Stress Effect." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-10353.
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Abstract Mean stress effects in pressurized steel blocks were examined under constant amplitude fatigue loading. The tests were performed to provide experimental data needed to study the effect of mean stress on fatigue lives of subject specimen, and to substantiate the use of analytical expressions to account for the mean stress. The mean stress was the result of subjecting the specimens to an autofrettage pressure which induced compressive residual stresses at the crossbore intersection of the specimens. Fatigue tests were carried out under both tensile and compressive mean stress levels. Test results were compared to several mean stress accounting relationships such as the Smith-Watson Topper, Bergmann and Seeger, modified Goodman, Gerber and Soderberg. Test results indicated that the modified Goodman equation is favorable in accounting for the effect of both tensile and compressive mean stresses on fatigue life (up to a compressive mean stress to ultimate stress ratio of −0.2). The behavior under compressive mean stress to ultimate stress ratio of less than −0.2 indicated that a linear correction relationship was required.
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Enaworu, Efeoghene, Tim Pritchard, and Sarah J. Davies. "An Approach for Exploring the Application of the Flow Zone Index Concept in Describing Petrophysical Properties Using Available SCAL Data Relative Permeability." In SPE Nigeria Annual International Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/208244-ms.
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Abstract This paper describes a unique approach for exploring the Flow Zone Index (FZI) concept using available relative permeability data. It proposes an innovative routine for relating the FZI parameter to saturation end-points of relative permeability data and produces a better model for relative permeability curves. In addition, this paper shows distinct wettabilities for various core samples and validated functions between FZI and residual oil saturation (Sor), irreducible water saturation (Swi), maximum oil allowed to flow (Kro, max), maximum water allowed to flow (Krw, max),and mobile/recoverable oil (100-Swi-Sor). The wettability of the core samples were defined using cross-plots of relative permeability of oil (Kro), relative permeability of water (Krw), and water saturation (Sw). After classifying the data sets into their respective wettabilities based on these criteria, a stepwise non-linear regression analysis was undertaken to develop realistic correlations between the FZI parameter, initial water saturation and end-point relative permeability parameters. In addition, a correlation using Corey's type generalised model was developed using relative permeability data, with new power law constants and well defined curves. Other parameters, including Sor, Swi, Kro, max, Krw,max and mobile oil, were plotted against FZI and correlations developed for them showed unique well behaved plots with the exception of the Sor plot. A possible theory to explain this unexpected behaviour of the FZI Vs Sor cross plot was noted and discussed. These derived functions and established relationships between the FZI term and other petrophysical parameters such as permeability, porosity, water saturation, relative permeability and residual oil saturation can be applied to other wells or reservoir models where these key parameters are already known or unknown. These distinctive established correlations could be employed in the proper characterization of a reservoir as well as predicting and ground truthing petrophysical properties.
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Lee, Cheol W., Taejoon Choi, and Yung C. Shin. "Intelligent Modeling of Complex Manufacturing Processes Using Hierarchical Fuzzy Basis Function Networks." In ASME 2001 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/imece2001/dsc-24590.
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Abstract This paper presents a generalized modeling approach to modeling of complex manufacturing processes. Fuzzy basis function networks with a novel training algorithm are used to capture the cause-effect relationships of complex manufacturing processes. The modeling scheme allows for utilization of the existing knowledge in the form of analytical models, experimental data and heuristic rules in developing a suitable model. The method is implemented for the surface grinding processes based on the hierarchical structure of fuzzy basis function networks proposed by Lee and Shin [21]. Process models for surface roughness and residual stress are developed based on the available grinding model structures with a small number of experimental data to demonstrate the concept. The accuracy of developed models is validated through independent sets of grinding experiments.
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Davies, P., N. Lacotte, G. Kibsgaard, R. Craig, D. Cannell, S. François, O. Lodeho, et al. "Bend Over Sheave Durability of Fibre Ropes for Deep Sea Handling Operations." In ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/omae2013-11332.
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This paper describes work performed within a Joint Industry Project aiming to evaluate the lifetime of deep sea handling ropes. Various HMPE (High Modulus Polyethylene) fiber ropes, with and without coatings, have been studied under both tensile and cyclic bend over sheave (CBOS) loading. A large test program has enabled both tension-cycle to failure relationships and empirical expressions for residual strength after cycling to be determined. A special device was then developed to apply a known couple to the sheave, allowing both dynamic friction measurements to be made and the influence of applied couple on cycles to failure to be measured. These experimental data were used in the development of a numerical model which can be used to study the influence of rope and sheave parameters.
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Lall, Pradeep, Nokibul Islam, Kaysar Rahim, and Jeff Suhling. "Prognosis Methodologies for Health Management of Electronics and MEMS Packaging." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-62319.
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The current state-of-art in managing system reliability is geared towards the development of life-prediction models for unaged pristine materials under known loading conditions based on relationships such as the Paris’s Power Law [Paris, et. al 1960, 1961], Coffin-Manson Relationship [Coffin 1954; Tavernelli, et. al. 1959; Smith, et. al. 1964; Manson, et. al. 1964] and the S-N Diagram. There is need for methods and processes which will allow interrogation of complex systems and sub-systems to determine the remaining useful life prior to repair or replacement. This capability of determination of material or system state is called “prognosis”. In this paper, a methodology for prognosis-of-electronics has been demonstrated with data of leading indicators of failure for accurate assessment of product damage significantly prior to appearance of any macro-indicators of damage. Proxies for leading indicators of failure have been developed including – micro-structural evolution characterized by average phase size and interfacial stresses at interface of silicon structures. Structures examined include – electronics package, MEMS Packages and interconnections on a metal backed printed circuit board typical of electronics deployed in harsh environments. Since, an aged material knows its state the research presented in this paper focuses on enhancing the understanding of material damage to facilitate proper interrogation of material state. Mathematical relationship has been developed between phase growth rate and time-to-1-percent failure to enable the computation of damage manifested and a forward estimate of residual life.
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Liu, Kai, and Hua Wang. "High-Order Co-Clustering via Strictly Orthogonal and Symmetric L1-Norm Nonnegative Matrix Tri-Factorization." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/340.
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Different to traditional clustering methods that deal with one single type of data, High-Order Co- Clustering (HOCC) aims to cluster multiple types of data simultaneously by utilizing the inter- or/and intra-type relationships across different data types. In existing HOCC methods, data points routinely enter the objective functions with squared residual errors. As a result, outlying data samples can dominate the objective functions, which may lead to incorrect clustering results. Moreover, existing methods usually suffer from soft clustering, where the probabilities to different groups can be very close. In this paper, we propose an L1 -norm symmetric nonnegative matrix tri-factorization method to solve the HOCC problem. Due to the orthogonal constraints and the symmetric L1 -norm formulation in our new objective, conventional auxiliary function approach no longer works. Thus we derive the solution algorithm using the alternating direction method of multipliers. Extensive experiments have been conducted on a real world data set, in which promising empirical results, including less time consumption, strictly orthogonal membership matrix, lower local minima etc., have demonstrated the effectiveness of our proposed method.
Reports on the topic "Data residual relationships"
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Brosh, Arieh, Gordon Carstens, Kristen Johnson, Ariel Shabtay, Joshuah Miron, Yoav Aharoni, Luis Tedeschi, and Ilan Halachmi. Enhancing Sustainability of Cattle Production Systems through Discovery of Biomarkers for Feed Efficiency. United States Department of Agriculture, July 2011. http://dx.doi.org/10.32747/2011.7592644.bard.
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Feed inputs represent the largest variable cost of producing meat and milk from ruminant animals. Thus, strategies that improve the efficiency of feed utilization are needed to improve the global competitiveness of Israeli and U.S. cattle industries, and mitigate their environmental impact through reductions in nutrient excretions and greenhouse gas emissions. Implementation of innovative technologies that will enhance genetic merit for feed efficiency is arguably one of the most cost-effective strategies to meet future demands for animal-protein foods in an environmentally sustainable manner. While considerable genetic variation in feed efficiency exist within cattle populations, the expense of measuring individual-animal feed intake has precluded implementation of selection programs that target this trait. Residual feed intake (RFI) is a trait that quantifies between-animal variation in feed intake beyond that expected to meet energy requirements for maintenance and production, with efficient animals being those that eat less than expected for a given size and level of production. There remains a critical need to understand the biological drivers for genetic variation in RFI to facilitate development of effective selection programs in the future. Therefore, the aim of this project was to determine the biological basis for phenotypic variation in RFI of growing and lactating cattle, and discover metabolic biomarkers of RFI for early and more cost-effective selection of cattle for feed efficiency. Objectives were to: (1) Characterize the phenotypic relationships between RFI and production traits (growth or lactation), (2) Quantify inter-animal variation in residual HP, (3) Determine if divergent RFIphenotypes differ in HP, residual HP, recovered energy and digestibility, and (4) Determine if divergent RFI phenotypes differ in physical activity, feeding behavior traits, serum hormones and metabolites and hepatic mitochondrial traits. The major research findings from this project to date include: In lactating dairy cattle, substantial phenotypic variation in RFI was demonstrated as cows classified as having low RMEI consumed 17% less MEI than high-RMEI cows despite having similar body size and lactation productivity. Further, between-animal variation in RMEI was found to moderately associated with differences in RHP demonstrating that maintenance energy requirements contribute to observed differences in RFI. Quantifying energetic efficiency of dairy cows using RHP revealed that substantial changes occur as week of lactation advances—thus it will be critical to measure RMEI at a standardized stage of lactation. Finally, to determine RMEI in lactating dairy cows, individual DMI and production data should be collected for a minimum of 6 wk. We demonstrated that a favorably association exists between RFI in growing heifers and efficiency of forage utilization in pregnant cows. Therefore, results indicate that female progeny from parents selected for low RFI during postweaning development will also be efficient as mature females, which has positive implications for both dairy and beef cattle industries. Results from the beef cattle studies further extend our knowledge regarding the biological drivers of phenotypic variation in RFI of growing animals, and demonstrate that significant differences in feeding behavioral patterns, digestibility and heart rate exist between animals with divergent RFI. Feeding behavior traits may be an effective biomarker trait for RFI in beef and dairy cattle. There are differences in mitochondrial acceptor control and respiratory control ratios between calves with divergent RFI suggesting that variation in mitochondrial metabolism may be visible at the genome level. Multiple genes associated with mitochondrial energy processes are altered by RFI phenotype and some of these genes are associated with mitochondrial energy expenditure and major cellular pathways involved in regulation of immune responses and energy metabolism.
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Menéses-González, María Fernanda, Angélica María Lizarazo-Cuéllar, Diego Cuesta-Mora, and Daniel Esteban Osorio-Ramírez. Financial Development and Monetary Policy Transmission. Banco de la República Colombia, November 2022. http://dx.doi.org/10.32468/be.1219.
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This paper estimates the effect of financial development on the transmission of monetary policy. To do so, the paper employs a panel data set containing financial development indicators, policy rates, lending rates, and deposit rates for 43 countries for the period 2000-2019 and applies the empirical strategy of Brandao Marques et al. (2020): firstly, monetary policy shocks are estimated using a Taylor-rule specification that relates changes in the policy rate to inflation, the output gap and other observables that are likely to influencemonetary policy decisions; secondly, the residuals of this estimation (policy shocks) are used in a specification that relates lending or deposit rates to, among others, policy shocks and the interaction between policy shocks and measures of financial development. The coefficient on this interaction term captures the effect of financial development on the relationship between policy shocks and lending or deposit rates. The main findings of the paper are twofold: on the one hand, financial development does strengthen the monetary policy transmission channel to deposit rates; that is, changes in the policy rate in economies with more financial development induce larger changes (in the same direction) in deposit rates than is the case in economies with less financial development. This result is particularly driven by the effect of the development of financial institutions on policy transmission – the effect of financial markets development turns out to be smaller in magnitude. On the other hand, financial development does not strengthen the transmission of monetary policy to lending rates. This is consistent with a credit channel which weakens in the face of financial development in a context where banks cannot easily substitute short-term funding sources. These results highlight the relevance of financial development for the functioning of monetary policy across countries, and possibly imply the necessity of a more active role of monetary authorities in fostering financial development.
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Chefetz, Benny, and Baoshan Xing. Sorption of hydrophobic pesticides to aliphatic components of soil organic matter. United States Department of Agriculture, 2003. http://dx.doi.org/10.32747/2003.7587241.bard.
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Sorption of hydrophobic compounds to aliphatic components of soil organic matter (SOM) is poorly understood even though these aliphatic carbons are a major fraction of SOM. The main source of aliphatic compounds in SOM is above- and below-ground plant cuticular materials (cutin, cutan and suberin). As decomposition proceeds, these aliphatic moieties tend to accumulate in soils. Therefore, if we consider that cuticular material contributes significantly to SOM, we can hypothesize that the cuticular materials play an important role in the sorption processes of hydrophobic compounds (including pesticides) in soils, which has not yet been studied. The overall goal of this research was to illustrate the mechanism and significance of the refractory aliphatic structures of SOM in sorbing hydrophobic compounds (nonionic and weakly polar pesticides). The importance of this study is related to our ability to demonstrate the sorption relationship between key pesticides and an important fraction of SOM. The specific objectives of the project were: (1) To isolate and characterize cuticular fractions from selected plants; (2) To investigate the sorption mechanism of key hydrophobic pesticides and model compounds to cuticular plant materials; (3) To examine the sorption mechanisms at the molecular level using spectroscopic techniques; (4) To investigate the sorption of key hydrophobic pesticides to synthetic polymers; (5) To evaluate the content of cuticular materials in agricultural soils; and (6) To study the effect of incubation of plant cuticular materials in soils on their sorptive capabilities. This project demonstrates the markedly high sorption capacity of various plant cuticular fractions for hydrophobic organic compounds (HOCs) and polar organic pollutants. Both cutin (the main polymer of the cuticle) and cutan biopolymers exhibit high sorption capability even though both sorbents are highly aliphatic in nature. Sorption by plant cuticular matter occurs via hydrophobic interactions and H-bonding interactions with polar sorbates. The cutin biopolymer seems to facilitate reversible and noncompetitive sorption, probably due to its rubbery nature. On the other hand, the epicuticular waxes facilitate enhance desorption in a bi-solute system. These processes are possibly related to phase transition (melting) of the waxes that occur in the presence of high solute loading. Moreover, our data highlight the significance of polarity and accessibility of organic matter in the uptake of nonpolar and polar organic pollutants by regulating the compatibility of sorbate to sorbent. In summary, our data collected in the BARD project suggest that both cutin and cutan play important roles in the sorption of HOCs in soils; however, with decomposition the more condensed structure of the cutin and mainly the cutan biopolymer dominated sorption to the cuticle residues. Since cutin and cutan have been identified as part of SOM and humic substances, it is suggested that retention of HOCs in soils is also controlled by these aliphatic domains and not only by the aromaticrich fractions of SOM.
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Wolf, Eva. Chemikalienmanagement in der textilen Lieferkette. Sonderforschungsgruppe Institutionenanalyse, 2022. http://dx.doi.org/10.46850/sofia.9783941627987.
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The World Summit on Sustainable Development in Johannesburg in 2002 set the goal of minimising the adverse impacts of chemicals and waste by 2020. This goal has not been achieved yet. Therefore, other approaches are needed to prevent, minimise, or replace harmful substances. One possible approach is this master thesis which deals with the challenges that the textile importer DELTEX is facing with regard to a transparent communication of chemicals used and contained in the product in its supply chain. DELTEX is bound by legal regulations and requirements of its customer and must ensure that there are no harmful substances in the garments. For each order, the customer requires a chemical inventory from DELTEX which contains the chemical substances and formulations used (so-called "order-wise chemical inventory"). Currently, the suppliers are not willing to pass this on to DELTEX. As a result, DELTEX is faced with the problem of having no knowledge of the materials used in the garments and is thus taking a high risk. The structure of this study is based on the transdisciplinary "delta analysis" of the Society for Institutional Analysis at the University of Applied Sciences Darmstadt. This compares the target state with the actual state and derives a delta from the difference. Based on this, suitable design options are to be developed to close the delta. The study defines the target state on the basis of normative requirements and derives three criteria from this, which can be used to measure design options. By means of guideline-based interviews with experts, an online survey and literature research, it examines the current state. The analysis shows that the relevant actors are in an unfavourable incentive and barrier situation. The textile supply chain can be seen as a complex construct in which a whole series of production sites (often in developing and emerging countries where corruption and low environmental standards exist) carry out many processing steps. Chemicals are used at almost all stages of processing, some of which have harmful effects on people and the environment. At the same time, factory workers in the production countries are under enormous price and time pressure and often have insufficient know-how about chemical processes. DELTEX is dependent on its main customer and therefore has little room for price negotiations. To close this delta, the study formulates design options on macro, meso and micro levels and measures them against the developed criteria. None of the measures completely meets all the criteria, which is why a residual delta remains. The study concludes that not one, but rather a combination of several design options at all levels can achieve the target state. For DELTEX, an alliance with other textile importers, membership in the Fair Wear Foundation, strengthening the relationship with its suppliers and cooperation with another customer are recommended. Furthermore, the use of material data tools that support proactive reporting approaches such as a Full Material Declaration is recommended. The study is carried out from the perspective of the textile importer DELTEX. The results can therefore only be applied to the entire textile supply chain to a limited extent.
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Lurie, Susan, John Labavitch, Ruth Ben-Arie, and Ken Shackel. Woolliness in Peaches and Nectarines. United States Department of Agriculture, 1995. http://dx.doi.org/10.32747/1995.7570557.bard.
Full textAbstract:
The overall goal of the research was to understand the processes involved in the development of woolliness in peaches and nectarines. Four specific hypotheses were proposed and in the course of the research evidence was gathered t support two of them and to not support two others. The hypotheses and a summary of the evidence are outlined below. 1. That woolliness arises from an imbalance between the activities of the cell wall pectin degrading enzymes. Using 'Flavortop' nectarines and 'Hermoza' peaches as model systems, storage regimes were manipulated to induce or prevent woolliness. The expression (mRNA abundance), protein content (Western blotting), and activity of polygalacturonase (PG) and pectin esterase (PE) were followed. Expression of the enzymes was not different, but activity and the ratio between PG and PE activities were quite different in fruits developing woolliness or ripening normally. This was also examined by looking at the substrate, the pectin moiety of the cell wall, and i woolly fruit there were more high molecular weight pectins with regions of non-methylated galacturonic acid residues. Taking an in vitro approach it was found a) that PE activity was stable at 0oC while PG activity decreased; b) incubating the calcium pectate fraction of the cell wall with PE extracted from peaches caused the polymers to form a gel characteristic of the visual woolly symptoms in peaches. 2. That continued cell wall synthesis occurs during storage and contributes to structural changes i cell walls and improper dissolution and softening after storage. We tried to adapt our technique of adding 13C-glucose to fruit discs, which was used successfully to follow cell wall synthesis during tomato ripening. However, the difference in sugar content between the two fruits (4% in tomato and 12% in peach) meant that the 13C-glucose was much more diluted within the general metabolite pool. We were unable to see any cell wall synthesis which meant that either the dilution factor was too great, or that synthesis was not occurring. 3. That controlled atmosphere (CA) prevents woolliness by lowering all enzyme activities. CA was found to greatly reduce mRNA abundance of the cell wall enzymes compared to regular air storage. However, their synthesis and activity recovered during ripening after CA storage and did not after regular air storage. Therefore, CA prevented the inhibition of enzyme activation found in regular air storage. 4. That changes in cell wall turgor and membrane function are important events in the development of woolliness. Using a micro pressure probe, turgor was measured in cells of individual 'O'Henry' and 'CalRed' peaches which were woolly or healthy. The relationship between firmness and turgor was the same in both fruit conditions. These data indicate that the development and expression of woolliness are not associated with differences in membrane function, at least with regard to the factors that determine cell turgor pressure. In addition, during the period of the grant additional areas were explored. Encoglucanase, and enzyme metabolizing hemicellulose, was found to be highly expressed air stored, but not in unstored or CA stored fruit. Activity gels showed higher activity in air stored fruit as well. This is the first indication that other components of the cell wall may be involved in woolliness. The role of ethylene in woolliness development was also investigated at it was found a) that woolly fruits had decreased ability to produce ethylene, b) storing fruits in the presence of ethylene delayed the appearance of woolliness. This latter finding has implication for an inexpensive strategy for storing peaches and nectarines.