bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lepton mass matrix from double covering of A
4 modular flavor symmetry*
Authors: Okada Hiroshi , Orikasa Yuta 
Published: September 2022

Abstract
We study a double covering of modular

flavor symmetry. To this end, we construct lepton models for canonical and radiative seesaw scenarios. Using irreducible doublet representations, heavier Majorana fermion masses are characterized by one free parameter that would differentiate from

symmetry. symmetry. Through χ square numerical analysis, we demonstrate that both scenarios produce some predictions in case of normal hierarchy reproducing neutrino oscillation data. However, no solution satisfies the neutrino oscillation data in case of radiative seesaw of inverted hierarchy.
A Lightweight Deep Learning Framework for Galaxy Morphology Classification
Authors: Wu Donglin , Zhang Jinqu , Li Xiangru , Li Hui 
Published: September 2022

Abstract
With the construction of large telescopes and the explosive growth of observed galaxy data, we are facing the problem to improve the data processing efficiency while ensuring the accuracy of galaxy morphology classification. Therefore, this work designed a lightweight deep learning framework, EfficientNet-G3, for galaxy morphology classification. The proposed framework is based on EfficientNet which integrates the Efficient Neural Architecture Search algorithm. Its performance is assessed with the data set from the Galaxy Zoo Challenge Project on Kaggle. Compared with several typical neural networks and deep learning frameworks in galaxy morphology classification, the proposed EfficientNet-G3 model improved the classification accuracy from 95.8% to 96.63% with F1-Score values of 97.1%. Typically, this model uses the least number of parameters, which is about one tenth that of DenseNet161 and one fifth that of ResNet-26, but its accuracy is about one percent higher than them. The proposed EfficientNet-G3 can act as an important reference for fast morphological classification for massive galaxy data in terms of efficiency and accuracy.
Subhalo Abundance and Satellite Spatial Distribution in Milky Way-Andromeda-like Paired Haloes
Authors: Li Kemeng , Shao Shi , He Ping , Gu Qing , Wang Jie 
Published: September 2022

Abstract
We study the subhalo and satellite populations in haloes similar to the Milky Way (MW)-Andromeda paired configuration in the Millennium II and P-Millennium simulations. We find subhaloes are 5%–15% more abundant in paired haloes than their isolated counterparts that have the same halo mass and large-scale environmental density. Paired haloes tend to reside in a more isotropic environment than isolated haloes, the shear tensor of their large-scale tidal field is possibly responsible for this difference. We also study the thickness of the spatial distribution of the top 11 most massive satellite galaxies obtained in the semi-analytic galaxy sample constructed from the Millennium II simulation. Moreover, satellites that have lost their host subhaloes due to the resolution limit of the simulation have been taken into account. As a result, we find that the difference in the distribution of the satellite thickness between isolated and paired haloes is indistinguishable, which suggests that the paired configuration is not responsible for the observed plane of satellites in the MW. The results in this study indicate the paired configuration could bring some nonnegligible effect on the subhalo abundance in the investigation of the MW’s satellite problems.
Lung cancer subtype diagnosis using weakly-paired multi-omics data
Authors: Wang Xingze , Yu Guoxian , Wang Jun , Zain Azlan Mohd , Guo Wei 
Published: September 2022

Abstract

Motivation
Cancer subtype diagnosis is crucial for its precise treatment and different subtypes need different therapies. Although the diagnosis can be greatly improved by fusing multiomics data, most fusion solutions depend on paired omics data, which are actually weakly paired, with different omics views missing for different samples. Incomplete multiview learning-based solutions can alleviate this issue but are still far from satisfactory because they: (i) mainly focus on shared information while ignore the important individuality of multiomics data and (ii) cannot pick out interpretable features for precise diagnosis.

Results
We introduce an interpretable and flexible solution (LungDWM) for Lung cancer subtype Diagnosis using Weakly paired Multiomics data. LungDWM first builds an attention-based encoder for each omics to pick out important diagnostic features and extract shared and complementary information across omics. Next, it proposes an individual loss to jointly extract the specific information of each omics and performs generative adversarial learning to impute missing omics of samples using extracted features. After that, it fuses the extracted and imputed features to diagnose cancer subtypes. Experiments on benchmark datasets show that LungDWM achieves a better performance than recent competitive methods, and has a high authenticity and good interpretability.

Availability and implementation
The code is available at http://www.sdu-idea.cn/codes.php?name=LungDWM.

Supplementary information
Supplementary data are available at Bioinformatics online.
The role of community health worker-based care in post-conflict settings: a systematic review
Authors: Werner Kalin , Kak Mohini , Herbst Christopher H , Lin Tracy Kuo 
Published: September 2022

Abstract
Countries affected by conflict often experience the deterioration of health system infrastructure and weaken service delivery. Evidence suggests that healthcare services that leverage local community dynamics may ameliorate health system-related challenges; however, little is known about implementing these interventions in contexts where formal delivery of care is hampered subsequent to conflict. We reviewed the evidence on community health worker (CHW)-delivered healthcare in conflict-affected settings and synthesized reported information on the effectiveness of interventions and characteristics of care delivery. We conducted a systematic review of studies in OVID MedLine, Web of Science, Embase, Scopus, The Cumulative Index to Nursing and Allied Health Literature (CINHAL) and Google Scholar databases. Included studies (1) described a context that is post-conflict, conflict-affected or impacted by war or crisis; (2) examined the delivery of healthcare by CHWs in the community; (3) reported a specific outcome connected to CHWs or community-based healthcare; (4) were available in English, Spanish or French and (5) were published between 1 January 2000 and 6 May 2021. We identified 1976 articles, of which 55 met the inclusion criteria. Nineteen countries were represented, and five categories of disease were assessed. Evidence suggests that CHW interventions not only may be effective but also efficient in circumventing the barriers associated with access to care in conflict-affected areas. CHWs may leverage their physical proximity and social connection to the community they serve to improve care by facilitating access to care, strengthening disease detection and improving adherence to care. Specifically, case management (e.g. integrated community case management) was documented to be effective in improving a wide range of health outcomes and should be considered as a strategy to reduce barrier to access in hard-to-reach areas. Furthermore, task-sharing strategies have been emphasized as a common mechanism for incorporating CHWs into health systems.
Tissue- and cell-specific whole-transcriptome meta-analysis from brain and retina reveals differential expression of dystrophin complexes and new dystrophin spliced isoforms
Authors: García-Cruz César , Aragón Jorge , Lourdel Sophie , Annan Ahrmad , Roger Jérôme E , Montanez Cecilia , Vaillend Cyrille 
Published: September 2022

Abstract
The large DMD gene encodes a group of dystrophin proteins in brain and retina, produced from multiple promoters and alternative splicing events. Dystrophins are core components of different scaffolding complexes in distinct cell types. Their absence may thus alter several cellular pathways, which might explain the heterogeneous genotype–phenotype relationships underlying central comorbidities in Duchenne muscular dystrophy (DMD). However, the cell-specific expression of dystrophins and associated proteins (DAPs) is still largely unknown. The present study provides a first RNA-Seq-based reference showing tissue- and cell-specific differential expression of dystrophins, splice variants and DAPs in mouse brain and retina. We report that a cell type may express several dystrophin complexes, perhaps due to expression in separate cell subdomains and/or subpopulations, some of which with differential expression at different maturation stages. We also identified new splicing events in addition to the common exon-skipping events. These include a new exon within intron 51 (E51b) in frame with the flanking exons in retina, as well as inclusions of intronic sequences with stop codons leading to the presence of transcripts with elongated exons 40 and/or 41 (E40e, E41e) in both retina and brain. PCR validations revealed that the new exons may affect several dystrophins. Moreover, immunoblot experiments using a combination of specific antibodies and dystrophin-deficient mice unveiled that the transcripts with stop codons are translated into truncated proteins lacking their C-terminus, which we called N-Dp427 and N-Dp260. This study thus uncovers a range of new findings underlying the complex neurobiology of DMD.
Warming Accelerates the Onset of the Molecular Stress Response and Increases Mortality of Larval Atlantic Cod
Authors: Oomen Rebekah A , Knutsen Halvor , Olsen Esben M , Jentoft Sissel , Stenseth Nils Chr , Hutchings Jeffrey A 
Published: September 2022

Synopsis
Temperature profoundly affects ectotherm physiology. Although differential thermal responses influence fitness, thus driving population dynamics and species distributions, our understanding of the molecular architecture underlying these responses is limited, especially during the critical larval stage. Here, using RNA-sequencing of laboratory-reared Atlantic cod (Gadus morhua) larvae of wild origin, we find changes in gene expression in thousands of transcripts consistent with a severe cellular stress response at both ambient and projected (+2°C and +4°C) temperatures. In addition, specific responses to stress, heat, and hypoxia were commonly identified in gene ontology enrichment analyses and 33 of the 44 genes comprising the minimum stress proteome of all organisms were upregulated. Earlier onset of the stress response was evident at higher temperatures; concomitant increased growth and mortality suggests a reduction in fitness. Temporal differences in gene expression levels do not correspond to differences in growing degree days, suggesting negative physiological consequences of warming beyond accelerated development. Because gene expression is costly, we infer that the upregulation of thousands of transcripts in response to warming in larval cod might act as an energetic drain. We hypothesize that the energetically costly stress response, coupled with increased growth rate at warmer temperatures, leads to faster depletion of energy reserves and increased risk of mortality in larval cod. As sea surface temperatures continue to rise over the next century, reduced fitness of Atlantic cod larvae might lead to population declines in this ecologically and socioeconomically important species. Further, our findings expand our understanding of transcriptomic responses to temperature by ectothermic vertebrate larvae beyond the critical first-feeding stage, a time when organisms begin balancing the energetic demands of growth, foraging, development, and maintenance. Linking the molecular basis of a thermal response to key fitness-related traits is fundamentally important to predicting how global warming will affect ectotherms.
Analyzing green view index and green view index best path using Google street view and deep learning
Authors: Zhang Jiahao , Hu Anqi 
Published: September 2022

Abstract
As an important part of urban landscape research, analyzing and studying street-level greenery can increase the understanding of a city’s greenery, contributing to better urban living environment planning and design. Planning the best path of urban greenery is a means to effectively maximize the use of urban greenery, which plays a positive role in the physical and mental health of urban residents and the path planning of visitors. In this paper, we used Google street view to obtain street view images of Osaka City. The semantic segmentation model is adopted to segment the street view images and analyze the green view index (GVI) of Osaka City. Based on the GVI, we take advantage of the adjacency matrix and Floyd–Warshall algorithm to calculate GVI best path, solving the limitations of ArcGIS software. Our analysis not only allows the calculation of specific routes for the GVI best paths but also realizes the visualization and integration of neighborhood urban greenery. By summarizing all the data, we can conduct an intuitive feeling and objective analysis of the street-level greenery in the research area. Based on this, such as urban residents and visitors can maximize the available natural resources for a better life. The dataset and code are available at https://github.com/Jackieam/GVI-Best-Path.
New and Persistent Sedative-Hypnotic Use After Adjuvant Chemotherapy for Breast Cancer
Authors: Cogan Jacob C , Raghunathan Rohit R , Beauchemin Melissa P , Accordino Melissa K , Huang Yongmei , Elkin Elena B , Melamed Alexander , Wright Jason D , Hershman Dawn L 
Published: September 2022

Abstract

Background
Sedative-hypnotic medications are used to treat chemotherapy-related nausea, anxiety, and insomnia. However, prolonged sedative-hypnotic use can lead to dependence, misuse, and increased health-care use. We aimed to estimate the rates at which patients who receive adjuvant chemotherapy for breast cancer become new persistent users of sedative-hypnotic medications, specifically benzodiazepines and nonbenzodiazepine sedative-hypnotics (Z-drugs).

Methods
Using the MarketScan health-care claims database, we identified sedative-hypnotic–naïve patients who received adjuvant chemotherapy for breast cancer. Patients who filled 1 and more prescriptions during chemotherapy and 2 and more prescriptions up to 1 year after chemotherapy were classified as new persistent users. Univariate and multivariable logistic regression analyses were used to estimate odds of new persistent use and associated characteristics.

Results
We identified 22 039 benzodiazepine-naïve patients and 23 816 Z-drug–naïve patients who received adjuvant chemotherapy from 2008 to 2017. Among benzodiazepine-naïve patients, 6159 (27.9%) filled 1 and more benzodiazepine prescriptions during chemotherapy, and 963 of those (15.6%) went on to become new persistent users. Among Z-drug–naïve patients, 1769 (7.4%) filled 1 and more prescriptions during chemotherapy, and 483 (27.3%) became new persistent users. In both groups, shorter durations of chemotherapy and receipt of opioid prescriptions were associated with new persistent use. Medicaid insurance was associated with new persistent benzodiazepine use (odds ratio = 1.88, 95% confidence interval = 1.43 to 2.47) compared with commercial or Medicare insurance.

Conclusions
Patients who receive sedative-hypnotic medications during adjuvant chemotherapy for breast cancer are at risk of becoming new persistent users of these medications after chemotherapy. Providers should ensure appropriate sedative-hypnotic use through tapering dosages and encouraging nonpharmacologic strategies when appropriate.
Automated galaxy–galaxy strong lens modelling: No lens left behind
Authors: Etherington Amy , Nightingale James W , Massey Richard , Cao XiaoYue , Robertson Andrew , Amorisco Nicola C , Amvrosiadis Aristeidis , Cole Shaun , Frenk Carlos S , He Qiuhan , Li Ran , Tam Sut-Ieng 
Published: September 2022

ABSTRACT
The distribution of dark and luminous matter can be mapped around galaxies that gravitationally lens background objects into arcs or Einstein rings. New surveys will soon observe hundreds of thousands of galaxy lenses and current labour-intensive analysis methods will not scale up to this challenge. We develop an automatic Bayesian method, which we use to fit a sample of 59 lenses imaged by the Hubble Space Telescope. We set out to leave no lens behind and focus on ways in which automated fits fail in a small handful of lenses, describing adjustments to the pipeline that ultimately allows us to infer accurate lens models for all 59 lenses. A high-success rate is key to avoid catastrophic outliers that would bias large samples with small statistical errors. We establish the two most difficult steps to be subtracting foreground lens light and initializing a first approximate lens model. After that, increasing model complexity is straightforward. We put forward a likelihood cap method to avoid the underestimation of errors due to pixel discretization noise inherent to pixel-based methods. With this new approach to error estimation, we find a mean ∼1 per cent fractional uncertainty on the Einstein radius measurement, which does not degrade with redshift up to at least z = 0.7. This is in stark contrast to measurables from other techniques, like stellar dynamics and demonstrates the power of lensing for studies of galaxy evolution. Our PyAutoLens software is open source, and is installed in the Science Data Centres of the ESA Euclid mission.
Stability of urea in astrophysical ices. A laboratory study of VUV irradiation and high-energy electron bombardment
Authors: Herrero Víctor J , Tanarro Isabel , Jiménez-Serra Izaskun , Carrascosa Héctor , Muñoz Caro Guillermo M , Maté Belén 
Published: September 2022

ABSTRACT
The recent detection of urea in the interstellar medium raises questions about its stability in different astronomical environments. In this work, we have studied the stability of urea ices and urea/water ice mixtures under vacuum-ultraviolet (VUV; 6.3–10.9 eV) irradiation and high-energy (5 keV) electron bombardment at 30, 100, and 200 K. The evolution of the ices was monitored with infrared spectroscopy. CO2, HNCO, and OCN− were identified as reaction products in the 30 K samples. At the higher temperatures CO2 and HNCO were hardly found in the processed ices. The measurements provided destruction cross-sections and allowed the derivation of radiation yields, G100, and half-life doses for urea. G100 values were found to be low (≈3.6–0.3 molecules/100 eV) both for VUV photons and high-energy electrons with electrons being slightly more efficient for the destruction of the molecule. These low G100 values are likely due to favourable mechanisms of energy dissipation or urea recombination. The stability of urea under irradiation increases with temperature which suggests that higher mobility improves the repair mechanisms. Estimates based on these laboratory data indicate that urea should be stable (≈108–109 yr) against irradiation in cold dense clouds and hot cores. It would not survive long (≈103–104 yr) on the bare surface of a Kuiper belt object, but would be well protected (≈109 yr) against radiation below a 30 $\mu$m ice layer. The high resistance of the molecule to radiation damage makes it a good candidate for prebiotic chemistry.
Morphology modulation of artificial muscles by thermodynamic-twist coupling
Authors: Hu Xiaoyu , Li Jiatian , Li Sitong , Zhang Guanghao , Wang Run , Liu Zhongsheng , Chen Mengmeng , He Wenqian , Yu Kaiqing , Zhai Wenzhong , Zhao Weiqiang , Khan Abdul Qadeer , Fang Shaoli , Baughman Ray H , Zhou Xiang , Liu Zunfeng 
Published: September 2022

ABSTRACT
Human muscles can grow and change their length with body development; therefore, artificial muscles that modulate their morphology according to changing needs are needed. In this paper, we report a strategy to transform an artificial muscle into a new muscle with a different morphology by thermodynamic-twist coupling, and illustrate its structural evolution during actuation. The muscle length can be continuously modulated over a large temperature range, and actuation occurs by continuously changing the temperature. This strategy is applicable to different actuation modes, including tensile elongation, tensile contraction and torsional rotation. This is realized by twist insertion into a fibre to produce torsional stress. Fibre annealing causes partial thermodynamic relaxation of the spiral molecular chains, which serves as internal tethering and inhibits fibre twist release, thus producing a self-supporting artificial muscle that actuates under heating. At a sufficiently high temperature, further relaxation of the spiral molecular chains occurs, resulting in a new muscle with a different length. A structural study provides an understanding of the thermodynamic-twist coupling. This work provides a new design strategy for intelligent materials.
Inflammatory Political Campaigns and Racial Bias in Policing
Authors: Grosjean Pauline , Masera Federico , Yousaf Hasin 
Published: September 2022

Abstract
Can political rallies affect the behavior of law enforcement officers toward racial minorities? Using data from 35 million traffic stops, we show that the probability that a stopped driver is Black increases by 5.74% after a Trump rally during his 2015–2016 campaign. The effect is immediate, specific to Black drivers, lasts for up to 60 days after the rally, and is not justified by changes in driver behavior. The effects are significantly larger among law enforcement officers whose estimated racial bias is higher at baseline, in areas that score higher on present-day measures of racial resentment, those that experienced more racial violence during the Jim Crow era, and in former slave-holding counties. Mentions of racial issues in Trump speeches, whether explicit or implicit, exacerbate the effect of a Trump rally among officers with higher estimated racial bias.
Detection and Species Differentiation of Neopestalotiopsis spp. from Strawberry (Fragaria × ananassa) in Florida Using a High-Resolution Melting Analysis
Authors: Rebello Carolina S. , Wang Nan-Yi , Marin Marcus V. , Baggio Juliana S. , Peres Natalia A. 
Published: September 2022

Since 2017, a new Neopestalotiopsis sp. has been reported causing severe Pestalotia leaf spot (PLS) outbreaks in Florida. The threat of this new species has forced several strawberry growers to destroy their fields early in the season. The need for a fast and accurate diagnosis of PLS came from growers’ concerns and the fact that PLS symptoms can be easily confused with leaf spots caused by other pathogens. Moreover, although N. rosae can be isolated from symptomatic tissues, it is not as aggressive as the new Neopestalotiopsis sp. in Florida. Therefore, this study aimed to develop a high-resolution melting (HRM) assay to accurately detect and differentiate Neopestalotiopsis spp. associated with strawberry and validate this assay for its practical application in a plant diagnostic clinic. Two sets of primers were designed based on the partial beta-tubulin gene (β -tub) and by cross-comparison of their HRM results. This molecular assay was able to differentiate Neopestalotiopsis spp. into three groups: the new Neopestalotiopsis sp. associated with PLS outbreaks, N. rosae, and other Neopestalotiopsis spp. represented by several other species within the genus. The HRM assay had a detection limit of 10 pg of genomic DNA or 10 conidia and was found to be efficient and accurate to be implemented in our plant diagnostic clinic, allowing for a quick turnaround of results. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .