bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mechanisms of the Non‐Uniform Breach Morphology Evolution of Landslide Dams Composed of Unconsolidated Sediments During Overtopping Failure
Authors: Zhou Gordon G. D. , Lu Xueqiang , Xie Yunxu , Cui Kahlil F. E. , Tang Hui 
Published: September 2022

AbstractOvertopping flows in landslide dams erode and entrain materials on the dam surface resulting in erosional features that undermine the dam stability and facilitate the subsequent outburst flooding. A comprehensive understanding of dam surface evolution is therefore crucial for flood risk assessment and hazard mitigation. In this research, we study the mechanisms that influence the non‐uniform morphology evolution of landslide dam breaches (i.e., non‐linear variation of the dam surface gradient) through experiments and numerical modeling. Analog landslide dam models, constructed using unconsolidated poorly sorted soils, are exposed to different inflow discharges. We find that although the breach discharge evolves more consistently with the erosion along the sidewalls than with bed erosion, it is the erosion along the bed that controls the change in dam surface profiles. Erosion rates, expressed as a function of the difference between the flow shear stress and the apparent erosion resistance, vary at different points along the dam surface due to localized erosional features induced by scouring. The apparent erosion resistance is found to increase linearly along the dam surface. Dam failure is numerically modeled using depth‐averaged equations which assume that the complex evolution of the dam profiles is due to the coupled effects of erosion, entrainment, and channel bed collapse. Good agreement between the observed and modeled dam profiles further demonstrates that the gradual saturation of the breach flow with entrained sediment is responsible for the linear variation of the apparent erosion resistance, which in turn contributes to the formation of the surface scouring.
Mechanisms Controlling Water‐Level Variations in the Middle Yangtze River Following the Operation of the Three Gorges Dam
Authors: Hu Yong , Li Dongfeng , Deng Jinyun , Yue Yao , Zhou Junxiong , Chai Yuanfang , Li Yitian 
Published: September 2022

AbstractUnderstanding the mechanisms controlling downstream water‐level variations after the operation of the Three Gorges Dam is important for riverine flood and drought management. However, our quantitative understanding of the multiple controls of river morphology, vegetation, and floodplain resistance on water levels in the Middle Yangtze River (MYR) remains limited. Here, we analyze changes in river channels and floodplain resistance in the MYR using 450 cross‐sectional profiles as well as data on discharge, water levels, sediment, and satellite images from 2003 to 2015. Results show an overall decline in low‐flow water‐levels (at a given small discharge) due to severe incisions of low‐flow channels caused by a sharp reduction of ∼90% in sediment loads from 1950–2002 to 2003–2020. In contrast, high‐flow water‐levels (at a given large discharge) display minor changes. Our analysis shows that the notably increased floodplain resistance due to vegetation growth is likely the dominant factor elevating flood water‐levels, followed by riverbed coarsening and greater fluctuations in the river longitudinal profiles. Our findings further the understanding of downstream geomorphic response to dam operation and their impacts on water levels and have important implications for riverine flood management in dammed river systems.
Tracking mutational semantics of SARS-CoV-2 genomes
Authors: Singh Rohan , Nagpal Sunil , Pinna Nishal K. , Mande Sharmila S. 
Published: September 2022

AbstractNatural language processing (NLP) algorithms process linguistic data in order to discover the associated word semantics and develop models that can describe or even predict the latent meanings of the data. The applications of NLP become multi-fold while dealing with dynamic or temporally evolving datasets (e.g., historical literature). Biological datasets of genome-sequences are interesting since they are sequential as well as dynamic. Here we describe how SARS-CoV-2 genomes and mutations thereof can be processed using fundamental algorithms in NLP to reveal the characteristics and evolution of the virus. We demonstrate applicability of NLP in not only probing the temporal mutational signatures through dynamic topic modelling, but also in tracing the mutation-associations through tracing of semantic drift in genomic mutation records. Our approach also yields promising results in unfolding the mutational relevance to patient health status, thereby identifying putative signatures linked to known/highly speculated mutations of concern.
Investigation of bioactivity of unsaturated oligo‑galacturonic acids produced from apple waste by Alcaligenes faecalis AGS3 and Paenibacillus polymyxa S4 Pectinases
Authors: Ashrafian Behnam , Hosseini-Abari Afrouzossadat 
Published: September 2022

AbstractPectin is one of the main structural components in fruits and an indigestible fiber made of d-galacturonic acid units with α (1-4) linkage. This study investigates the microbial degradation of pectin in apple waste and the production of bioactive compounds. Firstly, pectin-degrading bacteria were isolated and identified, then pectinolytic activity was assessed by DNS. The products were evaluated by TLC and LC–MS–ESI. The antioxidative effects were investigated using DPPH and anti-cancer effects and cytotoxicity were analyzed by MTT and flow cytometry. In this study two new bacterial isolates, Alcaligenes faecalis AGS3 and Paenibacillus polymyxa S4 with the pectinolytic enzyme were introduced. Structure analysis showed that the products of enzymatic degradation include unsaturated mono, di, tri, and penta galacturonic acids with 74% and 69% RSA at 40 mg/mL for A. faecalis and P. polymyxa S4, respectively. The results of anti-tumor properties on MCF-7 cells by MTT assay, for products of AGS3 and S4 at 40 mg/mL after 48 h, showed 7% and 9% survival, respectively. In the flow cytometric assessment, the compounds of AGS3 at 40 mg/mL were 100% lethal in 48 h and regarding S4 isolate caused 98% death. Cytotoxicity evaluation on L-929 cells showed no significant toxicity on living cells.
Addressing imbalance of sample datasets in dissolved gas analysis by data augmentation: Generative adversarial networks
Authors: Li Yuan , Xu Yaoyu , Li Xinghui , Li Rui , Lin Jinshan , Zhang Guanjun 
Published: September 2022

AbstractDissolved gas analysis (DGA) is an efficient technique to diagnose transformer faults; however, the imbalance of the sample datasets is frequently observed in DGA, which has become one of the main challenges for accurate fault diagnosis. A generative adversarial network (GAN) model is proposed to realize the data augmentation for addressing these problems. The GAN model is nested by two backpropagation neural networks (BPNN) containing a generator and a discriminator. The generator produces real‐like data and continuously shapes the real‐like data approximate to real data. The discriminator works to distinguish between the real‐like data and the real data until the real‐like data cannot be discriminated. Under this adversarial learning, the generator output obtains the real‐like DGA samples to supplement the minority samples. To verify the diagnosis accuracy after the DGA data augmentation, three typically intelligent models, that is, BPNN, support vector machine (SVM) and deep belief network (DBN) are introduced to establish the diagnostic models. The results show that the recognition accuracy of the minority samples acquires average 30%, 25% and 50% increases for the three models respectively. It is shown that the GAN model well balances the sample datasets and strengthens the performance of the fault diagnostic models.
A multi‐criteria methodology for wind energy resource assessment and development at an intercontinental level: Facing low‐carbon energy transition
Authors: Wu Jiawei , Xiao Jinyu , Hou Jinming , Sun Wei , Li Peng , Lyu Xunyan 
Published: September 2022

AbstractQuantitative assessment and effective utilization of wind energy resources in global range are substantively meaningful in contemporary low‐carbon energy scenarios. In order to enrich the assessment with large‐scale applicability, multi‐factor consideration and quantitative economic analysis, a multi‐criteria assessment method for global wind energy with consideration of both environmental and economic factors (existing power grids, transportation, etc.) is proposed. Based on 18 items of basic digital data, a model is established from three dimensions of theoretical, technical and economic criteria, respectively. Global wind resources assessment is then accomplished with a spatial resolution of 500 m. The results indicate that global technical potential is 206 TW, of which 73% is from onshore wind, and around 132 TW is suitable for centralized development. Specifically, the global average development cost is 4.28 ¢/kWh, including 4.13 ¢/kWh onshore and 4.57 ¢/kWh offshore. The global distribution maps are drawn. Furthermore, combining geospatial calculation and statistical analysis, the cumulative probability distribution curves are obtained with two key indexes of capacity factor and development cost. A case study supporting a low‐carbon energy transition scenario indicates the overall cost of the future wind power demand of 6.76 TW can reduce to 2.48 ¢/kWh ideally in 2035. Finally, a rationality verification method is proposed. By the case study of global built wind farms, the geographical location coincidence of the assessment results is 83%.
Uniform convergence rates for Lipschitz learning on graphs
Authors: Bungert Leon , Calder Jeff , Roith Tim 
Published: September 2022

Abstract
Lipschitz learning is a graph-based semisupervised learning method where one extends labels from a labeled to an unlabeled data set by solving the infinity Laplace equation on a weighted graph. In this work we prove uniform convergence rates for solutions of the graph infinity Laplace equation as the number of vertices grows to infinity. Their continuum limits are absolutely minimizing Lipschitz extensions (AMLEs) with respect to the geodesic metric of the domain where the graph vertices are sampled from. We work under very general assumptions on the graph weights, the set of labeled vertices and the continuum domain. Our main contribution is that we obtain quantitative convergence rates even for very sparsely connected graphs, as they typically appear in applications like semisupervised learning. In particular, our framework allows for graph bandwidths down to the connectivity radius. For proving this we first show a quantitative convergence statement for graph distance functions to geodesic distance functions in the continuum. Using the ‘comparison with distance functions’ principle, we can pass these convergence statements to infinity harmonic functions and AMLEs.
6 Validation and Application of a Survey of on-Farm Worker Attitudes Towards Euthanasia
Authors: Leon Nancy F Acevedo , Garcia Arlene , Schroeder Katy , Boren Amy , Lamino Pablo 
Published: September 2022

Abstract
On-farm euthanasia of pigs considers aspects of welfare and economics, but few comprehensive guidelines are available for swine producers and further, do not consider cultural barriers. The Hispanic workforce largely represents the bulk of agricultural workers. Euthanasia requires the ability to identify compromised pigs, technical skills, and willingness to euthanize pigs. In addition, timely euthanasia is part of the Common Swine Industry Audit (CSIA) and thus, can lead to failed audits. The U.S. swine industry employs a large percentage of Latin American workers through NAFTA visas. These workers vary in their degree of education and pig experience. Proper training of this workforce and identification of the barriers to performing timely euthanasia is critical. The objectives of this study were to: 1) develop and validate surveys (including demographic information, swine management, moral injury events scale, impact of event scale and the professional quality of life scale) in Spanish to determine Hispanic caretaker attitudes towards timely euthanasia and 2) to assess Hispanic caretakers using the validated surveys to determine the barriers associated to timely euthanasia. A total of 163 workers were surveyed and data were analyzed using Chi-Square. The results indicated that employees with less time working in the company presented less CSIA knowledge and a reduced capacity to identify pigs that needed to be euthanizing (P&lt; 0.001). Spearman's rank-order correlations indicated that stress was the most frequently correlated scale, related with burnout, transgressions, betrayals, and worker satisfaction (P=0.022). A Mann-Whitney U test determined that there was a gender difference, presenting a high level of stress and a low level of satisfaction in females and the opposite results in males (P=0.026). It is important to identify the factors that decrease or negatively affect the ability of employees to perform euthanasia in order to provide efficient training that improves good practices in the swine industry.
9 Is a Climate Neutral Animal Agriculture Possible?
Authors: Kebreab Ermias , Pressman Eleanor 
Published: September 2022

Abstract
Animal agriculture contributed 4% to the total greenhouse gas (GHG) emission from the US in 2019. Most of the climate impact from animal production are due to emissions of methane, which contributed about 70% of all livestock GHG emissions. Methane lasts in the atmosphere for around a decade. However, its warming potential over a 20-year period is up to 84 times compared to CO2. The impact on warming from methane is not gradual build-up over time but from relatively recent years. Therefore, reducing methane emissions is one the most effective ways to slow down the rate of climate warming. By some estimates, reducing methane by just 0.3% per year will result in no more warming from methane. Scaling it up further, may even reverse global warming. There are several mitigation options that can help achieve methane reduction in the short term. These can be broadly categorized into dietary and rumen manipulation. Dietary manipulation methods include increasing feed digestibility, such as concentrate to forage ratio, or increasing fats and oils, which are associated with lower methane emissions. These methods can potentially reduce methane emissions by up to 30%. Rumen manipulation through feed additives can be through either modifying the rumen environment, which indirectly affect emissions or directly inhibiting methanogenesis. The rumen environment modifiers include plant bioactive compounds such as essential oils and tannins, and nitrate rich feeds. Their effectiveness ranges between 10 to 30%. The inhibitor category include 3-nitroxypropanol (3-NOP) and seaweeds containing halogenated compounds. 3-NOP reduces enteric methane emissions by over 30% and has been approved for use in certain countries. Seaweed, in particular Asparagopsis spp., reduce emissions by over 90% in beef cattle. The combination of dietary and rumen manipulation options, including feed additives, is expected to reduce enteric methane emissions by over 30% in the next decade and help move the livestock industry closer to climate neutrality.
31 Genotype Concordance between SNP Chip and Imputed Low-Pass Whole-Genome Sequence in Beef Cattle
Authors: Sanglard Leticia P , Kuehn Larry A , Snelling Warren M , Spangler Matthew L 
Published: September 2022

Abstract
Genotypes generated from common single nucleotide polymorphisms (SNP) chips have been the sole source of genomic information for current beef cattle genetic evaluations. More recently, the development of low-pass whole-genome sequencing (LPS) followed by imputation to full sequence and variant calls has provided an alternative option to generate genotypes for inclusion into genetic evaluations. The objective of this study was to estimate the genotype concordance between SNP chip and LPS genotypes. Ear samples, via tissue sampling units, were obtained from 226 individuals. A subset of 109 individuals also had blood samples collected. Samples were sent to GeneSeek (Neogen company, Lincoln, NE) for genotyping (100K or 50K) and LPS and imputation was performed by Gencove. A total of 33,451 and 78,032 SNP overlapping between SNP panel and LPS for ear and blood samples, respectively, were used for further analyses. Genotype concordance was performed by counting the number of matching genotypes per SNP between (1) SNP chip vs. LPS in ear and blood samples, and (2) LPS in blood vs. LPS in ear samples. The average concordances between SNP chip vs. LPS in ear and blood samples were 0.97±0.04 and 0.98±0.06, respectively. The average concordance between LPS in blood vs. ear samples was 0.97±0.03. In conclusion, the concordance was high regardless of the tissue type, and, at least in these data, differences in resulting genetic predictions would not be expected between the use of genotypes derived from SNP chips or LPS. Additional work is warranted to determine sensitivity to relationships between target animals and the reference set used for imputation. The USDA is an equal opportunity provider and employer.
37 Associations Among Individual Gilt Birth Weight with Subsequent Weights, Selection Rates, and Age to Reach 135 kg
Authors: Silva Gefferson , Vier Carine M , Siqueira Amanda P , Gonsalves Ray , Almeida Fernanda , Zappani Vanderlei , Beraldin Evandro , Alberton Geraldo , Donin Daiane , Lu Ning , Dritz Steve , Orlando Uislei A 
Published: September 2022

Abstract
Our objective was to investigate the associations among individual gilt birth weight (BiWt) of modern genotype gilts with their subsequent weights, age at puberty, and selection rates for the breeding herd. A total of 3,452 PIC gilts (Landrace x Large White) were included in the analysis. Gilts were individually weighed within 12h of birth, and associations with weights at weaning, the end of nursery, and at selection were determined through regression models. Gilts BiWt was also classified into four categories: Below1.04kg, 1.04-1.38kg, 1.38-1.72kg, Above1.72kg. Stimulus for puberty onset started when gilts were 146d old. Gilt age at the first detected heat was recorded. Selection rate was determined as: Selection Rate, % = number of gilts selected at 146d/number of gilts born alive; and Age to 135kg, d = Age at selection+Days to 135kg, where Days to 135kg = (135–Selection Weight,kg)/Average Daily Gain from Birth to Selection. Data were analyzed using generalized linear models with the lm and glm functions of R. Results suggested that weaning and end of nursery weights increased (linear, P≤0.05) as the gilt BiWt increased. For each additional 100g in gilt BiWt, weaning and end of nursery weights were increased by 131g and 379g, respectively. The weight at selection increased (quadratic, P≤0.05) as gilt BiWt increased. There was no evidence of gilt BiWt impact on age at first detected heat (P&gt;0.10; 170.2, 167.7, 168.2, and 167.4d). Heavier gilts at birth reached 135kg at a reduced age (P≤0.05; 211.8, 201.4, 194.5, and 188.0d) and had greater selection rate (P≤0.05; 44.0, 58.1, 62.2, and 64.9%). In summary, this data indicated that gilts with phenotypically greater birth weight had better chances to be selected for the breeding herd and achieved the minimum weight target (135kg) for the first breeding at a younger age.
39 Genetic Associations between Feeding Behavior and Economic Interest Traits in Group-Housed Broilers
Authors: Carvalho Alves Anderson A , Fernandes Arthur F A , Lopes Fernando B , Breen Vivian , Hawken Rachel , Rosa Guilherme J J M 
Published: September 2022

Abstract
This study aimed to assess the genetic relationship among feeding behavior (FB), feed efficiency (FE), and production traits in broilers. A total of 44,234,350 feeders visit logs from 55,400 birds allocated into 88 trials were recorded by radio-frequency identification system. The daily data were averaged per animal for FB traits, considering the entire trial period. FB traits included the number of meals (NMEAL, count/day), time spent at feeders (TSF, hours/day), average portion size (PS, g), feeding rate (FR, g/hour), feeding activity range (FAR, hours/day), number of visited stations (NVS, count/day), and number of visited feeders (NVF, count/day). The total feed intake (FI), residual feed intake (RFI), and feed conversion rate (FCR) were also considered. Further, the body weight was measured at the start (SBW) and ending (FBW) of the trial. Multi-trait animal models were fitted for estimating the (co)variance components, considering the effects of sex and contemporary group as fixed. FB traits presented moderate to high heritability (h2) values, ranging from 0.26±0.02 (FAR) to 0.58±0.02 (TSF), whereas for FE and growth traits the h2 ranged from 0.16±0.01 (FBW) to 0.27±0.02 (RFI). The traits NMEAL, NVS, NVF, and FAR presented negative genetic correlations with FI, SBW, and FBW (-0.36 to -0.13) while PS and FR were positively correlated with all FE and production traits (0.12 to 0.43). RFI only presented non-null genetic correlations with PS (0.26±0.04), FR (0.23±0.03), and NVS (-0.11±0.04). Similarly, NMEAL and NVS also presented a weak negative correlation with FCR (-0.12±0.05 and -0.17±0.05, respectively). FB traits have a sizable genetic component and, therefore, may present a fast response to selection. The results also suggest that future selection for welfare-related feeding behavior (e.g., NMEAL, NVS, and NVF) would not affect negatively FE traits, although it might result in lighter animal lines in the long term.
41 Awardee Talk: Synergistic Power of Genomic Selection, Assisted Reproductive Technologies, and Gene Editing to Drive Genetic Improvement of Cattle
Authors: Mueller Maci L , Van Eenennaam Alison L 
Published: September 2022

Abstract
Genetic improvement of cattle around the globe has and will continue to be, an important driver of animal agriculture sustainability because the advances are permanent and cumulative. There are several reproductive and molecular biotechnologies that can be used in genetic improvement programs, and their outcomes are maximized when combined synergistically in a structured breeding program with a clear breeding objective. One of the most recently developed and increasingly popular tools, gene editing, allows animal breeders to precisely add, delete, or replace letters in the genetic code so as to influence a specific trait of interest (e.g., thermotolerance or disease resistance), in as little as one generation. Specifically, the ability to use gene editing to inactivate targeted gene function (i.e., knockout genes), knock-in genes, or achieve allele introgression in the absence of undesired linkage drag, offers promising opportunities to introduce useful genetic variation into cattle breeding programs. However, for gene editing to play an important role in genetic improvement, it must integrate smoothly into conventional cattle breeding programs to maintain or accelerate the rate of genetic gain. This presentation will first outline the current state of genomic selection and key reproductive biotechnologies (e.g., artificial insemination, embryo transfer, and ovum-pick up with in vitro embryo production) available for the accelerated genetic improvement of cattle, and then discuss potential strategies for effectively incorporating gene editing into cattle genetic improvement programs and methods for disseminating the improved traits in cattle populations. The approaches will vary depending on the region of the world and the cattle industry sector (i.e., dairy or beef), due to their differing population and management structures, in which these strategies are being deployed.