bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of high contents of nickel and silicon on the microstructure and properties of Cu–Ni–Si alloys
Authors: Tao Shiping , Lu Zhenlin , Xie Hui , Zhang Jinlong , Wei Xin 
Published: April 2022

Abstract
Cu-Ni-Si alloys have been widely used in electronics and electrical industries.The preparation method of alloy was not limited to smelting, powder metallurgy method has also attracted the attention of many researchers. In this study, Cu-Ni-Si alloys were prepared using hot-pressed sintering and elemental copper powders, in which nickel and silicon powders were used as raw materials. The results show that, when the Cu-Ni-Si alloys were prepared using hot-pressed sintering, there were no Ni-Si intermetallic compounds except the δ-Ni2Si phase in the microstructure of alloys. After the ageing treatment, when the mass ratios of Ni/Si were 2:1 and 3:1, the precipitation of δ-Ni2Si phase was significantly less. However, when the mass ratios of Ni/Si were 4:1 and 5:1, the precipitation of δ-Ni2Si phase particles increased significantly. The results from electrical conductivity and Vickers hardness show that, after the ageing treatment, both the electrical conductivity and Vickers hardness of the alloys greatly improved.
Plasma sanitization of cherry belle radish seeds for Space agricultural applications
Authors: Gott Ryan P , Engeling K. W , Johnson Christina M , Boles Haley O , Brown Victoria C , Hummerick Mary , Massa Gioia D , Meier Annie J 
Published: April 2022

Abstract
As human innovation continuously expands the knowledge base for life beyond Earth, the need for self-sufficient spacecraft is essential. With that, space crop production facilities are ever expanding for research and development. A current area of key interest is seed sanitation before transport from ground to the International Space Station (ISS). Sanitation practices are performed to mitigate any potential biohazard and to ensure the viability of the seed. Conventional methods involve fumigation of seeds or chemical processes but are not effective with all seed types. Therefore, plasma technology was implemented in this research to explore low-temperature plasmas as an alternative means for seed sanitation without the need for chemicals. This project investigated the viability of plasma as a means for sanitation by incorporating three different plasma types within the study. For the treatment of Cherry Belle radish seeds, the optimal system was a radio frequency (RF) sub-atmospheric plasma chamber. Treatments of 100 W for 10 min or longer with the Diener system consistently reduced microbial loads by 90% or more. While 20-min treatments caused reductions in germination rate, a treatment of 15 min with the Diener system at 100 W consistently resulted in germination rates above 80% after 1 month of seed storage. For the 5 and 10 min treatments at a pressure of 187 mTorr and power of 100 W, growth was also accelerated. Additionally, plasma provided 90% reduction of Escherichia coli and Bacillus pumilis and a 99% reduction of Fusarium ozysporum on inoculated seeds. Overall, the plasma systems show promising potential but require further exploration.
Optical wafer defect inspection at the 10 nm technology node and beyond
Authors: Zhu Jinlong , Liu Jiamin , Xu Tianlai , Yuan Shuai , Zhang Zexu , Jiang Hao , Gu Honggang , Zhou Renjie , Liu Shiyuan 
Published: April 2022

Abstract
The growing demand for electronic devices, smart devices, and the Internet of Things constitutes the primary driving force for marching down the path of decreased critical dimension and increased circuit intricacy of integrated circuits. However, as sub-10 nm high-volume manufacturing is becoming the mainstream, there is greater awareness that defects introduced by original equipment manufacturer components impact yield and manufacturing costs. The identification, positioning, and classification of these defects, including random particles and systematic defects, are becoming more and more challenging at the 10 nm node and beyond. Very recently, the combination of conventional optical defect inspection with emerging techniques such as nanophotonics, optical vortices, computational imaging, quantitative phase imaging, and deep learning is giving the field a new possibility. Hence, it is extremely necessary to make a thorough review for disclosing new perspectives and exciting trends, on the foundation of former great reviews in the field of defect inspection methods. In this article, we give a comprehensive review of the emerging topics in the past decade with a focus on three specific areas: (a) the defect detectability evaluation, (b) the diverse optical inspection systems, and (c) the post-processing algorithms. We hope, this work can be of importance to both new entrants in the field and people who are seeking to use it in interdisciplinary work.
A range characterization of the single-quadrant ADRT
Authors: Li Weilin , Ren Kui , Rim Donsub 
Published: April 2022

This work characterizes the range of the single-quadrant approximate discrete Radon transform (ADRT) of square images. The characterization follows from a set of linear constraints on the codomain. We show that for data satisfying these constraints, the exact and fast inversion formula by Rim [Appl. Math. Lett. 102 (2020), 106159] yields a square image in a stable manner. The range characterization is obtained by first showing that the ADRT is a bijection between images supported on infinite half-strips, then identifying the linear subspaces that stay finitely supported under the inversion formula.
Overcoming biases in causal inference of molecular interactions
Authors: Kumar Sajal , Song Mingzhou 
Published: April 2022

AbstractMotivationComputer inference of biological mechanisms is increasingly approachable due to dynamically rich data sources such as single-cell genomics. Inferred molecular interactions can prioritize hypotheses for wet-lab experiments to expedite biological discovery. However, complex data often come with unwanted biological or technical variations, exposing biases over marginal distribution and sample size in current methods to favor spurious causal relationships.ResultsConsidering function direction and strength as evidence for causality, we present an adapted functional chi-squared test (AdpFunChisq) that rewards functional patterns over non-functional or independent patterns. On synthetic and three biology datasets, we demonstrate the advantages of AdpFunChisq over 10 methods on overcoming biases that give rise to wide fluctuations in the performance of alternative approaches. On single-cell multiomics data of multiple phenotype acute leukemia, we found that the T-cell surface glycoprotein CD3 delta chain may causally mediate specific genes in the viral carcinogenesis pathway. Using the causality-by-functionality principle, AdpFunChisq offers a viable option for robust causal inference in dynamical systems.Availability and implementationThe AdpFunChisq test is implemented in the R package ‘FunChisq’ (2.5.2 or above) at https://cran.r-project.org/package=FunChisq. All other source code along with pre-processed data is available at Code Ocean https://doi.org/10.24433/CO.2907738.v1Supplementary informationSupplementary materials are available at Bioinformatics online.
Scoring protein sequence alignments using deep learning
Authors: Shrestha Bikash , Adhikari Badri 
Published: April 2022

AbstractMotivationA high-quality sequence alignment (SA) is the most important input feature for accurate protein structure prediction. For a protein sequence, there are many methods to generate a SA. However, when given a choice of more than one SA for a protein sequence, there are no methods to predict which SA may lead to more accurate models without actually building the models. In this work, we describe a method to predict the quality of a protein’s SA.ResultsWe created our own dataset by generating a variety of SAs for a set of 1351 representative proteins and investigated various deep learning architectures to predict the local distance difference test (lDDT) scores of distance maps predicted with SAs as the input. These lDDT scores serve as indicators of the quality of the SAs.Using two independent test datasets consisting of CASP13 and CASP14 targets, we show that our method is effective for scoring and ranking SAs when a pool of SAs is available for a protein sequence. With an example, we further discuss that SA selection using our method can lead to improved structure prediction.Availability and implementationCode and the data underlying this article are available at https://github.com/ba-lab/Alignment-Score/.Supplementary informationSupplementary data are available at Bioinformatics online.
Short-term prediction of atrial fibrillation from ambulatory monitoring ECG using a deep neural network
Authors: Singh Jagmeet P , Fontanarava Julien , de Massé Grégoire , Carbonati Tanner , Li Jia , Henry Christine , Fiorina Laurent 
Published: April 2022

Abstract

Aims
Atrial fibrillation (AF) is associated with significant morbidity but remains underdiagnosed. A 24 h ambulatory electrocardiogram (ECG) is largely used as a tool to document AF but yield remains limited. We hypothesize that a deep learning model can identify patients at risk of AF in the 2 weeks following a 24 h ambulatory ECG with no documented AF.

Methods and results
We identified a training set of Holter recordings of 7–15 days duration, in which no AF could be found in the first 24 h. We trained a neural network to predict the presence or absence of AF in the 15 following days, using only the first 24 h of the recording. We evaluated the neural network on a testing set and an external data set not used during algorithm development. In the testing data set, out of 9993 Holters with no AF on the first day, we found 361 (4%) recordings with AF within the 15 subsequent days of monitoring [5808, 218 (4%), respectively in the external data set]. The neural network could discriminate future AF with an area under the receiver operating curve, a sensitivity, and specificity of 79.4%, 76%, and 69%, respectively (75.8%, 78%, and 58% in the external data set), and outperformed ECG features previously shown to be predictive of AF.

Conclusion
We show here the very first study of short-term AF prediction using 24 h Holter monitoring. This could help identify patients who would benefit the most from longer recordings and proactively initiate treatment and AF mitigation strategies in high-risk patients.
The impact of environmental pH on the gut microbiota community structure and short chain fatty acid production
Authors: Firrman Jenni , Liu LinShu , Mahalak Karley , Tanes Ceylan , Bittinger Kyle , Tu Vincent , Bobokalonov Jamshed , Mattei Lisa , Zhang Huanjia , Van den Abbeele Pieter 
Published: April 2022

Abstract
Environmental pH is a critical parameter for maintenance of the gut microbiota. Here, the impact of pH on the gut microbiota luminal and mucosal community structure and short chain fatty acid (SCFA) production was evaluated in vitro, and data compiled to reveal a donor-independent response to an increase or decrease in environmental pH. The results found that raising environmental pH significantly increased luminal community richness and decreased mucosal community evenness. This corresponded with an increased abundance of Ruminococcaceae Ruminococcus and Erysipelotrichaceae Erysipelatoclostridium, and a decreased abundance of Coriobacteriaceae Collinsella and Enterobacteriaceae Shigella for both the luminal and mucosal communities. Total SCFA levels were significantly higher, primarily due to an increase in acetic and 2-methylbutanoic acids. Lowering pH decreased luminal community evenness and decreased mucosal community evenness and richness. This corresponded with an increased abundance of Lachnospiraceae Enterocloster, Veillonellaceae Megasphaera, Veillonellaceae Sporomusa, Erysipelotrichaceae Eubacterium, and Alcaligenaceae Sutterella, and decreased abundance of Odoribacteraceae Butyricimonas, Fusobacteriaceae Fusobacterium, Veillonellaceae Phascolarctobacterium, and multiple Enterobacteriaceae species for both the luminal and mucosal communities. Total SCFA levels were significantly lower, with an observed drop in acetic and propionic acids, and increased butyric and valeric acids. Taken together, these results indicate that alterations to environmental pH can modulate the gut microbiota community structure and function, and some changes may occur in a donor-independent manner.
Giant viruses of theMegavirinaesubfamily possess biosynthetic pathways to produce rare bacterial-like sugars in a clade-specific manner
Authors: Notaro Anna , Poirot Olivier , Garcin Elsa D , Nin Sebastien , Molinaro Antonio , Tonetti Michela , De Castro Cristina , Abergel Chantal 
Published: April 2022

AbstractThe recent discovery that giant viruses encode proteins related to sugar synthesis and processing paved the way for the study of their glycosylation machinery. We focused on the proposed Megavirinae subfamily, for which glycan-related genes were proposed to code for proteins involved in glycosylation of the layer of fibrils surrounding their icosahedral capsids. We compared sugar compositions and corresponding biosynthetic pathways among clade members using a combination of chemical and bioinformatics approaches. We first demonstrated that Megavirinae glycosylation differs in many aspects from what was previously reported for viruses, as they have complex glycosylation gene clusters made of six and up to 33 genes to synthetize their fibril glycans (biosynthetic pathways for nucleotide-sugars and glycosyltransferases). Second, they synthesize rare amino-sugars, usually restricted to bacteria and absent from their eukaryotic host. Finally, we showed that Megavirinae glycosylation is clade-specific and that Moumouvirus australiensis, a B-clade outsider, shares key features with Cotonvirus japonicus (clade E) and Tupanviruses (clade D). The existence of a glycosylation toolbox in this family could represent an advantageous strategy to survive in an environment where members of the same family are competing for the same amoeba host. This study expands the field of viral glycobiology and raises questions on how Megavirinae evolved such versatile glycosylation machinery.
The Graying of Divorce: A Half Century of Change
Authors: Brown Susan L , Lin I-Fen 
Published: April 2022

Abstract

Objectives
We traced the historical arc of the rise in gray divorce (i.e., divorce that occurs among adults aged 50 and older) in the United States since 1970, elucidating unique patterns for middle-aged (aged 50–64) versus older (aged 65 and older) adults.

Methods
Data from the 1970, 1980, and 1990 U.S. Vital Statistics Reports and the 2010 and 2019 American Community Survey (ACS) were used to chart the trends in gray divorce over the past half century. Drawing on the 2019 ACS, we estimated gray divorce rates across sociodemographic subgroups for today’s middle-aged and older adults. We pooled the 2010 (N = 757,835) and 2019 (N = 892,714) ACS data to assess whether divorce risks are shifting for middle-aged versus older adults.

Results
The gray divorce rate was low and grew only modestly between 1970 and 1990 before doubling by 2010. Since 2010, the rate has decreased slightly (but the decrease is not statistically significant). The gray divorce rate has stagnated among middle-aged adults but continues to climb among older adults.

Discussion
Our study illustrates the graying of divorce over the past half century. Nowadays, 36% of U.S. adults getting divorced are aged 50 or older. The only age group with an increasing divorce rate is adults aged 65 and older, raising new questions about how they will navigate old age.
Why APIs? Anticipated value, barriers, and opportunities for standards-based application programming interfaces in healthcare: perspectives of US thought leaders
Authors: Gordon William J , Rudin Robert S 
Published: April 2022

Abstract

Objective
Improving health data interoperability through application programming interfaces (APIs) is a focus of US policy initiatives and could have tremendous impact on many aspects of care delivery, such as innovation, operational efficiency, and patient-centered care. To better understand the landscape of API use cases, we interviewed US thought leaders involved in developing and implementing standard-based APIs.

Materials and Methods
We conducted semi-structured virtual interviews with US subject matter experts (SMEs) on APIs. SMEs were asked to describe API use cases along with value and barriers for each use case. Written summaries were checked by the SME and analyzed by the study team to identify findings and themes.

Results
We interviewed 12 SMEs representing diverse sectors of the US healthcare system, including academia, industry, public health agencies, electronic health record vendors, government, and standards organizations. Use cases for standards-based APIs fell into six categories: patient-facing, clinician-facing, population health and value-based care, public health, administrative, and social services. The value across use cases was viewed as unrealized to date, and barriers to the use of APIs varied by use case.

Conclusions
SMEs identified a diverse set of API use cases where standard-based APIs had the potential to generate value. As policy efforts seek to increase API adoption, our work provides an early look at the landscape of API use cases, value propositions, and barriers. Additional effort is needed to better understand the barriers and how to overcome them to create value, such as through demonstration projects and rigorous evaluations for specific use cases.
Findings from the first colorectal cancer screening among 103 542 individuals in Vietnam with systematic review of colorectal cancer screening programs in Asia-Pacific region
Authors: Tran Chi Thi-Du , Nguyen Mai Vu-Tuyet , Tran Mo Thi , Tuong Thuy Thi-Van , Tran Quang Hong , Le Linh Cu , Pham Huong Thi-Thu , Bui Nam Chi , Vu Hien Huy , Nguyen Tu Thi-Cam , Ta Phuong Que , Ha Hien Thi-Thu , Trinh Dung Tuan , Bui Hanh Thi-My , Trinh Dien Quang , Van Nguyen Khanh , Le Song Huu , Van Vu Khien , Van Tran Thuan , Tran Huong Thi-Thanh , Shrubsole Martha J , Ye Fei , Cai Qiuyin , Zheng Wei , Boffetta Paolo , Shu Xiao-Ou , Luu Hung N 
Published: April 2022

Abstract

Background
Colorectal cancer is a leading cancer incidence and cause of death worldwide and in Vietnam. Although screening is considered an effective measure to prevent and control colorectal cancer, there is no such effort in Vietnam.

Methods
Between 01 January 2018 and 31 October 2019, a population-based colorectal cancer screening program was conducted in Hanoi, Vietnam. A health advocacy campaign and follow-up phone calls were used to enroll residents aged ≥40 years old to complete an immunochemical-fecal occult blood testing. Positive immunochemical-fecal occult blood testing was followed by a colonoscopy. We also conducted a systematic review of the colorectal cancer screening programs in the Asia-Pacific region that used similar approach by searching Ovid Medline and PubMed databases.

Results
During study period, 103 542 individuals among 672 742 eligible residents attended the screening of whom 81.5% participants finished immunochemical-fecal occult blood testing test and the positive rate was 6.1%. The coverage rate for immunochemical-fecal occult blood testing test was 11.9%. Among 2278 individuals who underwent colonoscopy, 3.5% were histologically diagnosed with cancer, 17.8% with advanced adenomas, and 23.1% with non-advanced adenomas. Males had significantly higher detection rate of advanced adenomas, cancer or ≥ two polyps/tumor than females (P &lt; 0.0001). The systematic review showed that in two-step modality (i.e. immunochemical-fecal occult blood testing/fecal immunochemical test and colonoscopy), the test positive was from 4.1 to 10.6%. Once colonoscopy was performed subsequently, the rate of cancer among positive participants was from 1.7 to 16.4% and that of advanced adenomas was from 7.1 to 23.1%.

Conclusion
We showed that the two-step modality is a promising strategy for colorectal cancer screening in Vietnam that might apply to similar settings with limited resources
Combining canopy reflectance spectrometry and genome-wide prediction to increase response to selection for powdery mildew resistance in cultivated strawberry
Authors: Tapia Ronald , Abd-Elrahman Amr , Osorio Luis , Whitaker Vance M , Lee Seonghee 
Published: April 2022

Abstract
High-throughput phenotyping is an emerging approach in plant science, but thus far only a few applications have been made in horticultural crop breeding. Remote sensing of leaf or canopy spectral reflectance can help breeders rapidly measure traits, increase selection accuracy, and thereby improve response to selection. In the present study, we evaluated the integration of spectral analysis of canopy reflectance and genomic information for the prediction of strawberry (Fragaria × ananassa) powdery mildew disease. Two multi-parental breeding populations of strawberry comprising a total of 340 and 464 pedigree-connected seedlings were evaluated in two separate seasons. A single-trait Bayesian prediction method using 1001 spectral wavebands in the ultraviolet–visible–near infrared region (350–1350 nm wavelength) combined with 8552 single nucleotide polymorphism markers showed up to 2-fold increase in predictive ability over models using markers alone. The integration of high-throughput phenotyping was further validated independently across years/trials with improved response to selection of up to 90%. We also conducted Bayesian multi-trait analysis using the estimated vegetative indices as secondary traits. Three vegetative indices (Datt3, REP_Li, and Vogelmann2) had high genetic correlations (rA) with powdery mildew visual ratings with average rA values of 0.76, 0.71, and 0.71, respectively. Increasing training population sizes by incorporating individuals with only vegetative index information yielded substantial increases in predictive ability. These results strongly indicate the use of vegetative indices as secondary traits for indirect selection. Overall, combining spectrometry and genome-wide prediction improved selection accuracy and response to selection for powdery mildew resistance, demonstrating the power of an integrated phenomics–genomics approach in strawberry breeding.