bluuebunny/crossref_metadata_2025_split huggingface dataset:
The possessive investment in guns: towards a material, social, and racial analysis of guns
Authors: Hunter-Pazzara Brandon 
Published: May 2020

AbstractIn the midst of public attention to the question of racial gun violence both at the hands of vigilantes and police, this essay draws from anthropological theory on object–human relationships to reframe our understanding of racial gun violence. Following Appadurai’s (1986, 2015) attention to the “social lives” of objects and the way that objects function as both “median and materiality,” this essay argues that the demand for self-defense has altered the meaning of firearms and produced a system in which racial gun violence is normalized. Formed in three parts, the first develops a theoretical framework for thinking about the role of objects, in this case guns, in the production of social relationships. Doing so, this essay argues, allows us to take objects seriously as actors that work to produce moments of racial gun violence, as well as understand how these patterns of gun violence are the result of the mass production, distribution, and racialized marketing of the gun for the purpose of self-defense. In the second section, I utilize this framework to trace the legal, marketing, and engineering shifts that have resulted in the expansion of concealed carry laws, the development of a highly racialized marketing strategy that ties gun ownership to self-defense, and the production of smaller and more powerful pistols which now dominate the gun market. This new era of guns in American life builds from a longer history in which the gun remains central to the maintenance of the American racial order. Yet, the gun in this sense is not simply a signifier of race, but as this essay maintains, is both a material component shaping the bodily practices and cognitive capacities of gunowners, and a billion-dollar industry that has lobbied successfully to make guns more accessible and to make their use, for whites, less accountable under the law. In the final section, I undertake a rereading of the murder of Trayvon Martin, focusing on George Zimmerman’s murder weapon and the role it played both in the killing of Martin, and in sparing Zimmerman from conviction. By focusing on the role guns play in instances of racial violence and inequality, this essay demonstrates how new materialist scholarship can chart new pathways for understanding this important and timely issue.
The three agent demoting prefixes (ki-, m-u-, kur-) in Katripul Puyuma
Authors: Teng Stacy Fang-ching 
Published: May 2020

Abstract
This paper discusses the origins and possible grammaticalization pathways of three agent demoting prefixes in
Katripul Puyuma, ki-, m-u- and kur-. All three morphemes can attach to both
nominal and verbal stems. When they attach to nominal stems, they denote the meaning of ‘get’, ‘go’, and ‘reflexive’,
respectively, and when they attach to verbal stems, they express situation types that are often associated with the middle domain
(Kemmer 1993). Working from the perspective of grammaticalization, this paper
traces the origins and possible development of the three named morphemes, with supporting evidence drawn from cognates of other
Formosan languages.
Relationship between teaching motivation and teaching behaviour of secondary education teachers in Indonesia (Relación entre la motivación docente y el comportamiento docente en profesores de educación secundaria en Indonesia)
Authors: Irnidayanti Yulia , Maulana Ridwan , Helms-Lorenz Michelle , Fadhilah Nurul 
Published: May 2020

Research on teacher motivation is increasing substantially. Several studies have demonstrated the relationship between the motivation and teaching behaviour of teachers. The objective of this study was to investigate the relationship between the perceived motivation of teachers and their actual teaching behaviour in the context of secondary education. A survey on teacher motivation yielded responses from 315 teachers from 28 schools across 13 provinces in Indonesia. These teachers were observed in their classrooms by trained observers using a validated observation scheme. Results of a multilevel analysis indicate that: (1) perceived controlled motivation does not predict actual teaching behaviour; (2) perceived autonomous motivation is a positive predictor of at least some domains of actual teaching behaviour. Higher levels of perceived autonomous motivation are associated with higher scores on classroom management and clarity of instruction. There is also a slight tendency ( p < .10) for autonomous motivation to explain differences in other domains of teaching behaviour, with the exception of activating teaching. This study highlights the importance of autonomous motivation in relation to teaching quality.
Gendered patterns of coping responses with academic sexism in a group of Spanish secondary students (Diferencias de género en las respuestas de afrontamiento del sexismo académico en un grupo de estudiantes españoles de secundaria)
Authors: Sáinz Milagros , Martínez José-Luis , Meneses Julio 
Published: May 2020

This study analyses predictors of students’ coping responses to academic sexism. 954 high school students ( M Age = 17; SD Age = 0.90, 57% girls) participated. Boys were therefore more likely to use avoidance responses, whereas girls confronting and help-seeking responses. Likewise, hierarchical regressions suggest that girls and boys and girls whose parents had a high educational level and were without sexist attitudes about women’s higher level of competence in biology and languages were more likely to deploy confronting responses. Similarly, participants who did not embrace stereotypes about boys’ and girls’ higher abilities in some domains were more likely to seek help. Furthermore, boys and girls who believed that girls are better at biology and languages were more likely to develop avoidance responses. Interaction between gender and parental educational level shows that boys with highly educated parents were more likely to avoid the sexism. The present research contributes to the study of factors shaping gender differences in students’ coping with academic sexism. The role played by students’ adherence to stereotyped beliefs about boys’ and girls’ academic abilities is also discussed.
Magnetoelastic properties and behaviour of 4C pyrrhotite, Fe7S8, through the Besnus transition
Authors: Haines C R S , Dutton S E , Volk M W R , Carpenter M A 
Published: May 2020

Abstract
Pyrrhotite, Fe7S8, is a commonly occurring carrier of magnetic remanence and has a low temperature transition, the Besnus transition, involving a change in spin state. Variations of the thermodynamic, magnetic and elastic properties through this transition at ∼33 K in a natural sample of 4C pyrrhotite have been tested against a group theoretical model for coupling between order parameters relating to Fe/vacancy ordering (irrep U
1(1/2,0,1/4)) and magnetic ordering (irreps m

Γ

4

+

and m

Γ

5

+

). Magnetoelastic coupling is weak but the pre-existing microstructure of ferroelastic and magnetic domains, that develop as a consequence of Fe/vacancy and ferrimagnetic ordering during slow cooling in nature (P63/mmc → C2′/c′), causes subtle changes in the low temperature transition (C2′/c′ → P

1

¯

). The Besnus transition involves a rotation of magnetic moments out of the a–c plane of the monoclinic structure, but it appears that the transition temperature might vary locally according to whether it is taking place within the pre-existing domain walls or in the domains that they separate. Evidence of metamagnetic transitions suggests that the magnetic field–temperature phase diagram will display some interesting diversity. Low temperature magnetic transitions in minerals of importance to the palaeomagnetism community have been used to identify the presence of magnetite and haematite in rocks and the Besnus transition is diagnostic of the existence of pyrrhotite, Fe7S8.
Basic magnetic properties of magnetoactive elastomers of mixed content
Authors: Becker T I , Stolbov O V , Borin D Yu , Zimmermann K , Raikher Yu L 
Published: May 2020

Abstract
The results of theoretical and experimental investigations of the polymer composites that belong to a class of magnetoactive elastomers with mixed magnetic content (MAEs-MC) are presented. The fundamental distinction of such composites from ordinary magnetoactive elastomers is that the magnetic filler of MAEs-MC comprises both magnetically soft (MS) particles of size 3–5 µm and magnetically hard (MH) particles whose size is an order of magnitude greater. Since MH particles of the magnetic filler are mixed into a composition in a non-magnetised state, this can ensure preparation of samples with fairly homogeneous distribution of the filler. The ‘initiation’ process of a synthesised MAE-MC is done by its magnetisation in a strong magnetic field that imparts to the sample unique magnetic and mechanical properties. In this work, it is shown that the presence of MS particles around larger MH particles, firstly, causes an augmentation of magnetic moments, which the MH particles acquire during initiation, and secondly, enhances the magnetic susceptibility and remanent magnetisation of MAEs-MC. These magnetic parameters are evaluated on the basis of the macroscopic magnetostatics from the experimental data of spatial scanning of the field over the space around MAEs-MC made in the shape of a spheroid. A set of samples with a fixed MH and varying MS volume contents that are initiated in two different fields, is used. The developed mesoscopic model of magnetic interactions between the MH and MS phases is able to explain the experimentally observed dependencies of the magnetic parameters on the concentration of the MS phase. The problem is solved numerically under the assumption that the elastic matrix of MAEs-MC is rigid, i.e. the mutual displacements of the particles are negligible. The model helps to elucidate the interaction of the magnetic phases and to establish that the MS phase plays thereby a dual role. On the one hand, the MS phase screens out the field acting inside MH particles, and on the other hand, it forms mesoscopic magnetic bridges between adjoining MH particles, which in turn enhance their field. The combined interplay of these contributions defines the resulting material properties of MAEs-MC on the macroscopic scale.
A study on microstructure and erosion-corrosion performance of Fe–Cr–Ni–B alloy
Authors: Yi Da-Wei , Li Chong , Shi Yu-Pu , Chen Jin 
Published: May 2020

Abstract
The microstructure and erosion-corrosion performance of Fe–Cr–Ni–B alloy were studied. The experimental results were analyzed by hardness tester, energy spectrum analyzer, scanning electron microscope, X-ray diffraction analyzer. The results show that the Fe–Cr–Ni–B alloy consists of martensite and borocarbides [M2(B, C) and M7(B, C)3], and M2(B,C) and M7(B,C)3 borocarbides both have more chromium and less nickel than the matrix. After heat treatment, the hardness of the alloy reaches 52.3HRC. For the test alloys, the higher rotating speed test condition results in higher erosion-corrosion weight loss, and the erosion-corrosion weight loss increases first and then decreases with the increase of the impingement angle. Compared with Cr28 high chromium cast iron, in the erosion-corrosion surface of Fe–Cr–Ni–B alloy, the borocarbides are slightly broken, so, the Fe–Cr–Ni–B alloy exhibits excellent erosion-corrosion resistance under the borocarbide protection.
Evaluation of high-resolution rapid refresh (HRRR) forecasts for extreme precipitation
Authors: Yue Haowen , Gebremichael Mekonnen 
Published: May 2020

Abstract
This study evaluates the accuracy of short-range (1-h to 18-hr lead-time) forecasts from the High-Resolution Rapid Refresh (HRRR) model for five extreme storms in the United States: (1) the September 21–23, 2016, frontal storms in Iowa, (2) the April 28-May 1, 2017, frontal storms in the Southern Midwestern US, (3) the August 25–31, 2017, Hurricane Harvey storms in Texas, (4) the September 13–17, 2018, Hurricane Florence storms in the Carolinas, and (5) the September 4–6, 2019, Hurricane Dorian storms in the Carolinas. The evaluation was carried out by comparison with gauge-corrected Multi-Radar/Multi-Sensor (MRMS-GC) products. In terms of temporal variability, there was a good agreement between the forecasted and observed precipitation on an hourly basis. Thus, the HRRR products provide relatively reliable forecasts. However, the forecasts were mostly biased: they tend to overestimate rainfall for both hurricanes, underestimate rainfall for tropical storms in Iowa, and produce almost unbiased estimates for the frontal storms in Southern Midwestern US. In terms of spatial pattern, the forecasts are able to capture the spatial pattern of hurricanes, however, they produce too many, localized, high-rain intensities for the frontal storms than what the observations show. With regard to the effect of lead times, the 1-h lead forecasts have often lower accuracy than the other lead-time forecasts, while there was no much systematic difference in accuracy among the 2-h to 18-h lead-time forecasts. The bias estimates in the forecast are also examined at different spatial scales, ranging from 2 km × 2 km all the way to 128 km × 128 km. The results show that the bias estimated at smaller spatial scales vary within a large range, mostly within the range of −100% to +100%, indicating that the bias estimates obtained at large scale (hundreds of km grids) are not applicable to bias estimates at small scales, and vice versa. Local-bias correction approaches are therefore preferable over global bias-correction approaches.
Sexual selection on size and shape in Japanese beetles (Popillia japonica)
Authors: Kelly Clint D 
Published: May 2020

AbstractThe mobility hypothesis argues that species in which males compete for mates in scrambles often exhibit female-biased size dimorphism because smaller male body size should increase male mobility and success in searching for mates. Sexual dimorphism can be further exaggerated if fecundity or sexual selection concurrently selects for larger female size. Scramble competition can select for trait characteristics that optimize locomotion; for example, long and slender wings should be favored if aerial speed is important to mating success. I tested these predictions in the scrambling Japanese beetle (Popillia japonica), a female-biased size dimorphic insect pest that is invasive to North America. Multivariate selection analyses support the prediction that smaller body size and larger wings in males benefit their mating success. My analyses also revealed significant selection for larger wings in females but, contrary to prediction, direct sexual selection favors smaller body size in females. These results support the mobility hypothesis and partially explain the evolution of female-biased size dimorphism in this species. Sexual selection favored rounder bodies in females and more tapered bodies in males, whereas, in both sexes, the effect of wing shape appears less important to fitness than wing size.
Using conceptual modeling to improve genome data management
Authors: Pastor Óscar , León Ana Palacio , Reyes José Fabián Román , García Alberto Simón , Casamayor Juan Carlos Rodenas 
Published: May 2020

Abstract
With advances in genomic sequencing technology, a large amount of data is publicly available for the research community to extract meaningful and reliable associations among risk genes and the mechanisms of disease. However, this exponential growth of data is spread in over thousand heterogeneous repositories, represented in multiple formats and with different levels of quality what hinders the differentiation of clinically valid relationships from those that are less well-sustained and that could lead to wrong diagnosis. This paper presents how conceptual models can play a key role to efficiently manage genomic data. These data must be accessible, informative and reliable enough to extract valuable knowledge in the context of the identification of evidence supporting the relationship between DNA variants and disease. The approach presented in this paper provides a solution that help researchers to organize, store and process information focusing only on the data that are relevant and minimizing the impact that the information overload has in clinical and research contexts. A case-study (epilepsy) is also presented, to demonstrate its application in a real context.
Topological and kernel-based microbial phenotype prediction from MALDI-TOF mass spectra
Authors: Weis Caroline , Horn Max , Rieck Bastian , Cuénod Aline , Egli Adrian , Borgwardt Karsten 
Published: May 2020

Abstract

Motivation
Microbial species identification based on matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) has become a standard tool in clinical microbiology. The resulting MALDI-TOF mass spectra also harbour the potential to deliver prediction results for other phenotypes, such as antibiotic resistance. However, the development of machine learning algorithms specifically tailored to MALDI-TOF MS-based phenotype prediction is still in its infancy. Moreover, current spectral pre-processing typically involves a parameter-heavy chain of operations without analyzing their influence on the prediction results. In addition, classification algorithms lack quantification of uncertainty, which is indispensable for predictions potentially influencing patient treatment.

Results
We present a novel prediction method for antimicrobial resistance based on MALDI-TOF mass spectra. First, we compare the complex conventional pre-processing to a new approach that exploits topological information and requires only a single parameter, namely the number of peaks of a spectrum to keep. Second, we introduce PIKE, the peak information kernel, a similarity measure specifically tailored to MALDI-TOF mass spectra which, combined with a Gaussian process classifier, provides well-calibrated uncertainty estimates about predictions. We demonstrate the utility of our approach by predicting antibiotic resistance of three clinically highly relevant bacterial species. Our method consistently outperforms competitor approaches, while demonstrating improved performance and security by rejecting out-of-distribution samples, such as bacterial species that are not represented in the training data. Ultimately, our method could contribute to an earlier and precise antimicrobial treatment in clinical patient care.

Availability and implementation
We make our code publicly available as an easy-to-use Python package under https://github.com/BorgwardtLab/maldi_PIKE.
Identifying diagnosis-specific genotype–phenotype associations via joint multitask sparse canonical correlation analysis and classification
Authors: Du Lei , Liu Fang , Liu Kefei , Yao Xiaohui , Risacher Shannon L , Han Junwei , Guo Lei , Saykin Andrew J , Shen Li ,   for the Alzheimer’s Disease Neuroimaging Initiative
Published: May 2020

Abstract

Motivation
Brain imaging genetics studies the complex associations between genotypic data such as single nucleotide polymorphisms (SNPs) and imaging quantitative traits (QTs). The neurodegenerative disorders usually exhibit the diversity and heterogeneity, originating from which different diagnostic groups might carry distinct imaging QTs, SNPs and their interactions. Sparse canonical correlation analysis (SCCA) is widely used to identify bi-multivariate genotype–phenotype associations. However, most existing SCCA methods are unsupervised, leading to an inability to identify diagnosis-specific genotype–phenotype associations.

Results
In this article, we propose a new joint multitask learning method, named MT–SCCALR, which absorbs the merits of both SCCA and logistic regression. MT–SCCALR learns genotype–phenotype associations of multiple tasks jointly, with each task focusing on identifying one diagnosis-specific genotype–phenotype pattern. Meanwhile, MT–SCCALR cannot only select relevant SNPs and imaging QTs for each diagnostic group alone, but also allows the selection of those shared by multiple diagnostic groups. We derive an efficient optimization algorithm whose convergence to a local optimum is guaranteed. Compared with two state-of-the-art methods, MT–SCCALR yields better or similar canonical correlation coefficients and classification performances. In addition, it owns much better discriminative canonical weight patterns of great interest than competitors. This demonstrates the power and capability of MTSCCAR in identifying diagnostically heterogeneous genotype–phenotype patterns, which would be helpful to understand the pathophysiology of brain disorders.

Availability and implementation
The software is publicly available at https://github.com/dulei323/MTSCCALR.

Supplementary information
Supplementary data are available at Bioinformatics online.
Benchmarking gene ontology function predictions using negative annotations
Authors: Warwick Vesztrocy Alex , Dessimoz Christophe 
Published: May 2020

Abstract

Motivation
With the ever-increasing number and diversity of sequenced species, the challenge to characterize genes with functional information is even more important. In most species, this characterization almost entirely relies on automated electronic methods. As such, it is critical to benchmark the various methods. The Critical Assessment of protein Function Annotation algorithms (CAFA) series of community experiments provide the most comprehensive benchmark, with a time-delayed analysis leveraging newly curated experimentally supported annotations. However, the definition of a false positive in CAFA has not fully accounted for the open world assumption (OWA), leading to a systematic underestimation of precision. The main reason for this limitation is the relative paucity of negative experimental annotations.

Results
This article introduces a new, OWA-compliant, benchmark based on a balanced test set of positive and negative annotations. The negative annotations are derived from expert-curated annotations of protein families on phylogenetic trees. This approach results in a large increase in the average information content of negative annotations. The benchmark has been tested using the naïve and BLAST baseline methods, as well as two orthology-based methods. This new benchmark could complement existing ones in future CAFA experiments.

Availability and Implementation
All data, as well as code used for analysis, is available from https://lab.dessimoz.org/20_not.

Supplementary information
Supplementary data are available at Bioinformatics online.