bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine learning approach to force reconstruction in photoelastic materials
Authors: Sergazinov Renat , Kramár Miroslav 
Published: September 2021

Abstract
Photoelastic techniques have a long tradition in both qualitative and quantitative analysis of the stresses in granular materials. Over the last two decades, computational methods for reconstructing forces between particles from their photoelastic response have been developed by many different experimental teams. Unfortunately, all of these methods are computationally expensive. This limits their use for processing extensive data sets that capture the time evolution of granular ensembles consisting of a large number of particles. In this paper, we present a novel approach to this problem that leverages the power of convolutional neural networks to recognize complex spatial patterns. The main drawback of using neural networks is that training them usually requires a large labeled data set which is hard to obtain experimentally. We show that this problem can be successfully circumvented by pretraining the networks on a large synthetic data set and then fine-tuning them on much smaller experimental data sets. Due to our current lack of experimental data, we demonstrate the potential of our method by changing the size of the considered particles which alters the exhibited photoelastic patterns more than typical experimental errors.
A binary classifier based on a reconfigurable dense network of metallic nanojunctions
Authors: Mirigliano Matteo , Paroli Bruno , Martini Gianluca , Fedrizzi Marco , Falqui Andrea , Casu Alberto , Milani Paolo 
Published: September 2021

Abstract
Major efforts to reproduce the brain performances in terms of classification and pattern recognition have been focussed on the development of artificial neuromorphic systems based on top-down lithographic technologies typical of highly integrated components of digital computers. Unconventional computing has been proposed as an alternative exploiting the complexity and collective phenomena originating from various classes of physical substrates. Materials composed of a large number of non-linear nanoscale junctions are of particular interest: these systems, obtained by the self-assembling of nano-objects like nanoparticles and nanowires, results in non-linear conduction properties characterized by spatiotemporal correlation in their electrical activity. This appears particularly useful for classification of complex features: nonlinear projection into a high-dimensional space can make data linearly separable, providing classification solutions that are computationally very expensive with digital computers. Recently we reported that nanostructured Au films fabricated from the assembling of gold clusters by supersonic cluster beam deposition show a complex resistive switching behaviour. Their non-linear electric behaviour is remarkably stable and reproducible allowing the facile training of the devices on precise resistive states. Here we report about the fabrication and characterization of a device that allows the binary classification of Boolean functions by exploiting the properties of cluster-assembled Au films interconnecting a generic pattern of electrodes. This device, that constitutes a generalization of the perceptron, can receive inputs from different electrode configurations and generate a complete set of Boolean functions of n variables for classification tasks. We also show that the non-linear and non-local electrical conduction of cluster-assembled gold films, working at room temperature, allows the classification of non-linearly separable functions without previous training of the device.
Social Contagion of Vasovagal Symptoms in Blood Donors: Interactions With Empathy
Authors: Mennitto Serena , Vachon David D , Ritz Thomas , Robillard Pierre , France Christopher R , Ditto Blaine 
Published: September 2021

AbstractBackgroundVasovagal reactions (VVRs) are commonly experienced in medical situations such as blood donation. Many believe that psychosocial contagion can contribute to the development of VVRs, but this is largely clinical lore.PurposeThe goal of the present investigation was to examine the physiological effects of observing another experience a reaction, focusing on the potential moderating effects of empathy.MethodsThis study was part of a randomized controlled trial of behavioral techniques on the prevention of VVRs in blood donors. The sample was composed of 530 healthy university students. Measures of symptoms were obtained with the Blood Donation Reactions Inventory (BDRI) and through observation. Physiological variables were measured using respiratory capnometry and a digital blood pressure monitor. The Affective and Cognitive Measure of Empathy was administered to 230 participants.ResultsDonors who witnessed another experiencing a reaction were more likely to spontaneously report symptoms during the blood draw, to be treated for a reaction, to score higher on the BDRI, and to exhibit smaller compensatory heart rate increases. Donors with higher affective empathy reported more symptoms, exhibited hyperventilation, and were more likely to be treated. Donors with higher cognitive empathy were less likely to require treatment if they witnessed a reaction.ConclusionThese results suggest that psychosocial contagion of physical symptoms can occur. The moderating effects of empathy differed depending on the subtype of empathy. Perhaps a better cognitive understanding of how other people are feeling functions as a coping response, whereas feeling sympathetic about others’ distress increases one’s own.
Integrating Scalable Genome Sequencing Into Microbiology Laboratories for Routine Antimicrobial Resistance Surveillance
Authors: Kekre Mihir , Arevalo Stefany Alejandra , Valencia María Fernanda , Lagrada Marietta L , Macaranas Polle Krystle V , Nagaraj Geetha , Oaikhena Anderson O , Olorosa Agnettah M , Aanensen David M ,   NIHR Global Health Research Unit on Genomic Surveillance of Antimicrobial Resistance, Abudahab Khalil , Abrudan Monica , Argimón Silvia , Harste Harry , Muddyman Dawn , Taylor Ben , Underwood Anthony , Wheeler Nicole , David Sophia , Donado-Godoy Pilar , Fabian Bernal Johan , Arevalo Alejandra , Osma Castro Erik C D , Ravikumar K L , Shamanna Varun , Govindan Vandana , Prabhu Akshata , Sravani D , Shincy M R , Rose Steffimole , Ravishankar K N , Okeke Iruka N , Afolayan Ayorinde O , Ajiboye Jolaade J , Ewomazino Odih Erkison , Carlos Celia , Gayeta June M , Herrera Elmer M , Molloy Ali , Stelling John , Vegvari Carolin 
Published: September 2021

Abstract
Antimicrobial resistance (AMR) is considered a global threat, and novel drug discovery needs to be complemented with systematic and standardized epidemiological surveillance. Surveillance data are currently generated using phenotypic characterization. However, due to poor scalability, this approach does little for true epidemiological investigations. There is a strong case for whole-genome sequencing (WGS) to enhance the phenotypic data. To establish global AMR surveillance using WGS, we developed a laboratory implementation approach that we applied within the NIHR Global Health Research Unit (GHRU) on Genomic Surveillance of Antimicrobial Resistance. In this paper, we outline the laboratory implementation at 4 units: Colombia, India, Nigeria, and the Philippines. The journey to embedding WGS capacity was split into 4 phases: Assessment, Assembly, Optimization, and Reassessment. We show that on-boarding WGS capabilities can greatly enhance the real-time processing power within regional and national AMR surveillance initiatives, despite the high initial investment in laboratory infrastructure and maintenance. Countries looking to introduce WGS as a surveillance tool could begin by sequencing select Global Antimicrobial Resistance Surveillance System (GLASS) priority pathogens that can demonstrate the standardization and impact genome sequencing has in tackling AMR.
Species Composition, Abundance, and Seasonal Dynamics of Perilla Seed Bugs (Heteroptera: Lygaeidae) in Weeds and Perilla Fields in Korea
Authors: Maharjan Rameswor , Yoon Youngnam , Jang Yunwoo , Kim Juil , Yeun Nam Hwa , Jeong Mihye , Park Kido , Yi Hwijong 
Published: September 2021

Abstract
Perilla seed bugs (Nysius sp.) are considered to be the emerging pests causing nutritional and yield losses in perilla and cereal crops. A survey of perilla seed bugs on weeds and perilla crops was conducted over the course of 2 yr in Korea to determine the species composition, abundance, and seasonal dynamics of perilla seed bugs. Three species of Heteroptera (Nysius plebeius, Nysius hidakai, and Nysius inconspicuus), nymphs of Nysius species, and several parasitoid species were collected from weeds and perilla crops. Nysius hidakai was the most abundant perilla seed bugs. In 2019, adult perilla seed bugs, nymphs of perilla seed bugs, and parasitoid species were more abundant in weed species than in perilla crops. An early peak with a greater number of adult perilla seed bug (N. hidakai) was observed in weeds in 2020. However, an identical peak with a similar number of perilla seed bug (N. hidakai) was found in perilla crops in both years. Peak perilla seed bugs densities were observed in the 4th week of June, 2020 in weeds. Parasitoid species from Aphidiidae (1), Braconidae (11), Eulophidae (7), Figitidae (5), Ichneumonidae (7), Platygastridae (1), and Pteromalidae (5) subfamilies were collected. Perilla seed bugs seem to be a serious and increasingly important pest in several field crop species including perilla crops grown on the southern Korean peninsula. Monitoring and early detection of insect species are vital to predicting seasonal colonization and population build-up of perilla seed bugs on perilla crops from a climate change perspective, and essential for developing appropriate management techniques. Thus, continuous monitoring of perilla seed bugs in alternative weed hosts is needed to protect perilla crops from perilla seed bug infestation.
Nonparametric Parameters of 24-Hour Rest–Activity Rhythms and Long-Term Cognitive Decline and Incident Cognitive Impairment in Older Men
Authors: Xiao Qian , Sampson Joshua N , LaCroix Andrea Z , Shadyab Aladdin H , Zeitzer Jamie M , Ancoli-Israel Sonia , Yaffe Kristin , Stone Katie ,   Osteoporotic Fractures in Men (MrOS) Study Group
Published: September 2021

Abstract
Altered 24-hour rest–activity rhythms may be associated with cognitive impairment in older adults, but evidence from prospective studies is limited. Nonparametric methods were used to assess actigraphy-based activity patterns in 2 496 older men. Incident cognitive impairment was assessed 4 times over 12 years using the Modified Mini-Mental State Examination (3MS) and Trails B tests, self-reported medication use, and clinical diagnosis. The highest quartile (vs the lowest) of intradaily variability and the lowest quartiles (vs the highest) of interdaily stability and relative amplitude were associated with incident cognitive impairment (hazard ratio [95% confidence interval]: 1.82 [1.31–2.53], 1.36 [0.99–1.86], and 1.85 [1.33–2.56], respectively). A larger increase in intradaily variability over 7.5 years was associated with a greater subsequent decline in 3MS scores but not in Trails B performance. In conclusion, less stable and more variable rest–activity rhythms may represent early biomarkers of cognitive impairment in older men.
Association of female reproductive tract microbiota with egg production in layer chickens
Authors: Su Yuan , Tian Shilin , Li Diyan , Zhu Wei , Wang Tao , Mishra Shailendra Kumar , Wei Ranlei , Xu Zhongxian , He Mengnan , Zhao Xiaoling , Yin Huadong , Fan Xiaolan , Zeng Bo , Yang Mingyao , Yang Deying , Ni Qingyong , Li Yan , Zhang Mingwang , Zhu Qing , Li Mingzhou 
Published: September 2021

Abstract

Background
The microbiota of the female reproductive tract is increasingly recognized as playing fundamental roles in animal reproduction. To explore the relative contribution of reproductive tract microbiomes to egg production in chickens, we investigated the microbiota in multiple reproductive and digestive tract sites from 128 female layer (egg-producing) chickens in comparable environments.

Results
We identified substantial differences between the diversity, composition, and predicted function of site-associated microbiota. Differences in reproductive tract microbiota were more strongly associated with egg production than those in the digestive tract. We identified 4 reproductive tract microbial species, Bacteroides fragilis, Bacteroides salanitronis, Bacteroides barnesiae, and Clostridium leptum, that were related to immune function and potentially contribute to enhanced egg production.

Conclusions
These findings provide insights into the diverse microbiota characteristics of reproductive and digestive tracts and may help in designing strategies for controlling and manipulating chicken reproductive tract microbiota to improve egg production.
Audio-Visual Mixed Reality Representation of Hazard Zones for Safe Pedestrian Navigation of a Space
Authors: San Martin Ane , Kildal Johan 
Published: September 2021

Abstract
It is difficult to estimate the boundaries of the hazard zones generated around autonomous machines and robots when navigating a space shared with them. We investigated the use of multimodal (auditory and/or visual) mixed-reality (MR) displays to warn users about invading such hazards zones and to help them return to safety. Two single-modality auditory and visual displays were designed, which were subjectively comparable as generic hazard displays. An experimental user study was then conducted to compare the designed single-modality displays as well as an audio-visual display that combined both. When the display included auditory information, users returned sooner to safety, although this had a small effect on performance when carrying out an independent navigation task. Additional nuanced possible differences are reported and discussed in relation to display design characteristics, as well as in relation to the limitations of the implementations that are possible with current MR head-mounted display devices.
Purebred-crossbred genetic parameters for reproductive traits in swine
Authors: Kramer Luke M , Wolc Anna , Esfandyari Hadi , Thekkoot Dinesh M , Zhang Chunyan , Kemp Robert A , Plastow Graham , Dekkers Jack C M 
Published: September 2021

Abstract
For swine breeding programs, testing and selection programs are usually within purebred (PB) populations located in nucleus units that are generally managed differently and tend to have a higher health level than the commercial herds in which the crossbred (CB) descendants of these nucleus animals are expected to perform. This approach assumes that PB animals selected in the nucleus herd will have CB progeny that have superior performance at the commercial level. There is clear evidence that this may not be the case for all traits of economic importance and, thus, including data collected at the commercial herd level may increase the accuracy of selection for commercial CB performance at the nucleus level. The goal for this study was to estimate genetic parameters for five maternal reproductive traits between two PB maternal nucleus populations (Landrace and Yorkshire) and their CB offspring: Total Number Born (TNB), Number Born Alive (NBA), Number Born Alive &gt; 1 kg (NBA &gt; 1 kg), Total Number Weaned (TNW), and Litter Weight at Weaning (LWW). Estimates were based on single-step GBLUP by analyzing any two combinations of a PB and the CB population, and by analyzing all three populations jointly. The genomic relationship matrix between the three populations was generated by using within-population allele frequencies for relationships within a population, and across-population allele frequencies for relationships of the CB with the PB animals. Utilization of metafounders for the two PB populations had no effect on parameter estimates, so the two PB populations were assumed to be genetically unrelated. Joint analysis of two (one PB plus CB) vs. three (both PB and CB) populations did not impact estimates of heritability, additive genetic variance, and genetic correlations. Heritabilities were generally similar between the PB and CB populations, except for LWW and TNW, for which PB populations had about four times larger estimates than CB. Purebred-crossbred genetic correlations (rpc) were larger for Landrace than for Yorkshire, except for NBA &gt; 1 kg. These estimates of rpc indicate that there is potential to improve selection of PB animals for CB performance by including CB information for all traits in the Yorkshire population, but that noticeable additional gains may only occur for NBA &gt; 1 kg and TNW in the Landrace population.
Urine Drug Screening in the Era of Designer Benzodiazepines: Comparison of Three Immunoassay Platforms, LC–QTOF-MS and LC–MS-MS
Authors: Puzyrenko Andrii , Wang Dan , Schneider Randy , Wallace Greg , Schreiber Sara , Brandt Kristen , Gunsolus Ian L 
Published: September 2021

Abstract
This study investigated the presence of designer benzodiazepines in 35 urine specimens obtained from emergency department patients undergoing urine drug screening. All specimens showed apparent false-positive benzodiazepine screening results (i.e., confirmatory testing using a 19-component liquid chromatography–tandem mass spectrometry (LC–MS-MS) panel showed no prescribed benzodiazepines at detectable levels). The primary aims were to identify the possible presence of designer benzodiazepines, characterize the reactivity of commercially available screening immunoassays with designer benzodiazepines and evaluate the risk of inappropriately ruling out designer benzodiazepine use when utilizing common urine drug screening and confirmatory tests. Specimens were obtained from emergency departments of a single US Health system. Following clinically ordered drug screening using Abbott ARCHITECT c assays and laboratory-developed LC–MS-MS confirmatory testing, additional characterization was performed for investigative purposes. Specifically, urine specimens were screened using two additional assays (Roche cobas c502 and Siemens Dimension Vista) and LC–quadrupole time-of-flight mass spectrometry (LC–QTOF-MS) to identify presumptively positive species, including benzodiazepines and non-benzodiazepines. Finally, targeted, qualitative LC–MS-MS was performed to confirm the presence of 12 designer benzodiazepines. Following benzodiazepine detection using the Abbott ARCHITECT, benzodiazepines were subsequently detected in 28/35 and 35/35 urine specimens using Siemens and Roche assays, respectively. LC–QTOF-MS showed the presumptive presence of at least one non-Food and Drug Administration (FDA)-approved benzodiazepine in 30/35 specimens: flubromazolam (12/35), flualprazolam (11/35), flubromazepam (2/35), clonazolam (4/35), etizolam (9/35), metizolam (5/35), nitrazepam (1/35) and pyrazolam (1/35). Two or three designer benzodiazepines were detected concurrently in 13/35 specimens. Qualitative LC–MS-MS confirmed the presence of at least one designer benzodiazepine or metabolite in 23/35 specimens, with three specimens unavailable for confirmatory testing. Urine benzodiazepine screening assays from three manufacturers were cross-reactive with multiple non-US FDA-approved benzodiazepines. Clinical and forensic toxicology laboratories using traditionally designed LC–MS-MS panels may fail to confirm the presence of non-US FDA-approved benzodiazepines detected by screening assays, risking inappropriate interpretation of screening results as false positives.
Mammography Screening and Research Evidence: The Swedish Contribution
Authors: Duffy Stephen W 
Published: September 2021

Abstract
Sweden has made a contribution to mammography screening research considerably disproportionate to its size. With 0.13% of the world’s population, Sweden contributed almost half of the randomized trial evidence on mammography screening. In addition to the fundamental efficacy of screening in preventing deaths from breast cancer, Swedish researchers have produced a considerable volume of research evaluating mammography screening in the routine healthcare services setting and illuminating issues of breast cancer progression and natural history. The basic result that screening prevents deaths from breast cancer has informed policy and led to substantial preservation of life internationally.
Bayesian phylogenetic analysis of linguistic data using BEAST
Authors: Hoffmann Konstantin , Bouckaert Remco , Greenhill Simon J , Kühnert Denise 
Published: September 2021

AbstractBayesian phylogenetic methods provide a set of tools to efficiently evaluate large linguistic datasets by reconstructing phylogenies—family trees—that represent the history of language families. These methods provide a powerful way to test hypotheses about prehistory, regarding the subgrouping, origins, expansion, and timing of the languages and their speakers. Through phylogenetics, we gain insights into the process of language evolution in general and into how fast individual features change in particular. This article introduces Bayesian phylogenetics as applied to languages. We describe substitution models for cognate evolution, molecular clock models for the evolutionary rate along the branches of a tree, and tree generating processes suitable for linguistic data. We explain how to find the best-suited model using path sampling or nested sampling. The theoretical background of these models is supplemented by a practical tutorial describing how to set up a Bayesian phylogenetic analysis using the software tool BEAST2.