bluuebunny/crossref_metadata_2025_split huggingface dataset:
Large magnetocaloric effect in rapidly quenched Mn50−

x
Co
x
Ni40In10 nanomaterials
Authors: Zhang Wenyong , Kharel Parashu , Valloppilly Shah , Sellmyer David J 
Published: January 2021

Abstract
The effect of Co addition on magnetic hysteresis, martensitic transformation temperature, and magnetic entropy change of rapidly-quenched Mn50−x
Co
x
Ni40In10 alloy nanomaterials has been investigated. The melt-spun Mn50Ni40In10 sample exhibits a small magnetic hysteresis which is further reduced by Co doping as measured between 0 and 2 T. The martensitic transformation temperature increases linearly with the electron concentration in the alloy from 195 K for Mn50Ni40In10 to 378 K for Mn45Co5Ni40In10. The Mn47Co3Ni40In10 alloy, which has phase-transition temperature close to room temperature, exhibits a substantial peak entropy change of 29.7 J kg−1 K−1 at magnetic field change of 2 T. Our results demonstrate that Mn47Co3Ni40In10 nanomaterial exhibits promising magnetocaloric properties for near-room-temperature magnetic refrigeration.
On the rate of convergence of the Legendre spectral collocation method for multi-dimensional nonlinear Volterra–Fredholm integral equations
Authors: Elkot Nermeen A , Zaky Mahmoud A , Doha Eid H , Ameen Ibrahem G 
Published: January 2021

Abstract
While the approximate solutions of one-dimensional nonlinear Volterra–Fredholm integral equations with smooth kernels are now well understood, no systematic studies of the numerical solutions of their multi-dimensional counterparts exist. In this paper, we provide an efficient numerical approach for the multi-dimensional nonlinear Volterra–Fredholm integral equations based on the multi-variate Legendre-collocation approach. Spectral collocation methods for multi-dimensional nonlinear integral equations are known to cause major difficulties from a convergence analysis point of view. Consequently, rigorous error estimates are provided in the weighted Sobolev space showing the exponential decay of the numerical errors. The existence and uniqueness of the numerical solution are established. Numerical experiments are provided to support the theoretical convergence analysis. The results indicate that our spectral collocation method is more flexible with better accuracy than the existing ones.
Resilience modes of an ancient mountain valley grassland in South Africa indicated by palaeoenvironmental methods
Authors: Dabengwa Abraham N , Gillson Lindsey , Bond William J 
Published: January 2021

Abstract
Grassland ecosystems supporting wildlife and livestock populations have undergone significant transformation in the last millennium. Climate, herbivory, fire, and people are identified as important drivers of ecosystems dynamics; however, grassland resilience has been rarely explored in landscapes with mixed grazing histories. Here we analyse ecosystems states from a South African mountain valley grassland in the last 1250 years using palaeoenvironmental proxies. Our results suggest that a tallgrass phase maintained by climate, people and fire replaced a shortgrass phase driven by indigenous herbivores after ca. 690 cal BP. Furthermore, the tallgrass phase had unpalatable grasses and disturbed soil. We suggest these ecological changes were linked to climate change and arrival of pastoralists in the region. Therefore, our results indicate that human activities may undermine resilience of grasslands and that reversing some changes may be difficult.
Efficient photoluminescence enhancement and tunable photocarrier transfer in vertical 2D organic–inorganic heterostructure by energy funneling
Authors: Qiao Jia-Wei , Niu Meng-Si , Wen Zhen-Chuan , Yang Xi-Kai , Chen Zhi-Hao , Wang Yan-Xin , Feng Lin , Qin Wei , Hao Xiao-Tao 
Published: January 2021

Abstract
Two-dimensional (2D) transition metal dichalcogenides (TMDCs) are attractive for their novel physical properties. However, the photoluminescence (PL) quantum yield of TMDCs has been limited, due to their abundant defects and strong many-body effect. Here, we present a vertical energy funneling channel which is constructed in organic–inorganic heterostructures comprising MoSe2, pentacene and graphene oxide. These heterostructures show efficient PL enhancement (3.7 times) ratio of monolayer MoSe2. Besides, the PL signal is further increased as high as 4.7 times at low temperature due to reduced electron-phonon interactions and also sensitive to the gradient magnetic field. Apart from the efficient PL enhancement, the photocarrier pumping efficiency which is modulated by energy offset of top layer and external field is >130 times greater than that in isolated MoSe2. These findings focused on manipulating the efficient photocarrier transfer open up a new route to adjust the luminescent properties of monolayer TMDCs for designing future 2D material based optoelectronic devices.
Thermal conductivity of Mg2Si1−xSnx nanowire assemblies synthesized using solid-state phase transformation of silicon nanowires
Authors: Ali Azhar , Shamberger Patrick , Vaddiraju Sreeram 
Published: January 2021

Abstract
Recent studies have indicated that doping, alloying, interface-engineering and nanostructuring are some of the strategies useful for obtaining high power factors and low thermal conductivities in materials that are needed for the fabrication of highly efficient thermoelectrics. With the intent of experimentally demonstrating the use of these strategies for designing highly efficient thermoelectrics, our group has in the past reported a solid-state phase transformation strategy for converting silicon nanowires into Mg2Si nanowires and Mg2Si welded nanowire networks. In this paper, the phase transformation strategy is extended to obtain Mg2Si0.92Sn0.08 nanowires from silicon nanowires. This report discusses not only the synthesis of Mg2Si0.92Sn0.08 nanowires from silicon nanowires, but also demonstrates that it is possible to control their diameters using variations of the silicon nanowire diameters as a parameter. Moreover, thermal conductivities of the nanowire assemblies discussed in detail in this paper indicated that nanostructuring through the formation of Mg2Si0.92Sn0.08 nanowires led to a drastic decrease in their thermal conductivities.
Preparation and photocatalytic activity of red light-emitting carbon dots/P25 heterojunction photocatalyst with ultra-wide absorption spectrum
Authors: Han Junqiang , Han Zhaoxia , Da Xianniu , Yang Zhijin , Zhang Dawei , Hong Ruijin , Tao Chunxian , Lin Hui , Huang Yuanshen 
Published: January 2021

Abstract
Carbon dots have attracted growing research interest due to its unique properties, and are expected to be used in the field of photocatalysis to solve the visible absorption loss problem of TiO2 (P25). In this paper, red light-emitting carbon dots (RCDs) with high fluorescence quantum yield (40%) and RCDs/P25 heterojunction photocatalysts were synthesized by a simple and green hydrothermal method. Characterization results indicated that RCDs were successfully coupled with P25, and RCDs could effectively broaden the visible absorption region of bare P25 from 410 nm to 800 nm. The photocatalytic activity of the as-synthesized RCDs/P25 on the degradation of rhodamine B (RhB) under visible light irradiation was greatly improved compared with that of bare P25. The degradation rate of RhB by 2%RCDs/P25 reached 98.4% in 150 min, the degradation efficiency was 7.4 times that of bare P25. The RCDs played an important role in improving the photocatalytic activity of RCDs/P25, which not only increased visible light absorption, but also promoted efficient separation of photogenerated electron-hole pairs. Furthermore, the possible degradation mechanism of RCDs/P25 heterojunction photocatalyst was given.
Characterization of 2D boron nitride nanosheets with hysteresis effect in the Schottky junctions
Authors: Ortiz Wilber , Ramirez Nereida J , Barrionuevo Danilo , Bhattarai Mohan K , Feng Peter 
Published: January 2021

Abstract
Carbon doped two-dimensional (2D) hexagonal boron nitride nanosheets (BNNSs) are obtained through a CO2—pulsed laser deposition (CO2—PLD) technique on silicon dioxide (SiO2) or molybdenum (Mo) substrates, showing - stable hysteresis characteristics over a wide range of temperatures, which makes them a promising candidate for materials based on non-volatile memory devices. This innovative material with electronic properties of n-type characterized in the form of back-to-back Schottky diodes appears to have special features that can enhance the device performance and data retention due to its functional properties, thermal-mechanical stability, and its relation with resistive switching phenomena. It can also be used to eliminate sneak current in resistive random-access memory devices in a crossbar array. In this sense constitutes a good alternative to design two series of resistance-switching Schottky barrier models in the gold/BNNS/gold and gold/BNNS/molybdenum structures; thus, symmetrical and non-symmetrical characteristics are shown at low and high bias voltages as indicated by the electrical current-voltage (I–V) curves. On the one hand, the charge recombination caused by thermionic emission does not significantly change the rectification characteristics of the diode, only its hysteresis properties change due to the increase in external voltage in the Schottky junctions. The addition of carbon to BNNSs creates boron vacancies that exhibit partially ionic character, which also helps to enhance its electrical properties at the metal-BNNS-metal interface.
Frailty is associated with in-hospital mortality in older hospitalised COVID-19 patients in the Netherlands: the COVID-OLD study
Authors: Blomaard Laura C , van der Linden Carolien M J , van der Bol Jessica M , Jansen Steffy W M , Polinder-Bos Harmke A , Willems Hanna C , Festen Jan , Barten Dennis G , Borgers Anke J , Bos Jeannet C , van den Bos Frederiek , de Brouwer Esther J M , van Deudekom Floor J A , van Dijk Suzanne C , Emmelot-Vonk Mariëlle H , Geels Raya E S , van de Glind Esther M M , de Groot Bas , Hempenius Liesbeth , Kamper Ad M , Kampschreur Linda M , de Koning Marre M M , Labots Geert , Looman Roy , Lucke Jacinta A , Maas Huub A A M , Mattace-Raso Francesco U S , el Moussaoui Rachida , van Munster Barbara C , van Nieuwkoop Cees , Oosterwijk Leanne (B L E) , Regtuijt Marlies (E M) , Robben Sarah H M , Ruiter Rikje , Salarbaks Aisha M , Schouten Henrike J , Smit Orla M , Smits Rosalinde A L , Spies Petra E , Vreeswijk Ralph , de Vries Oscar J , Wijngaarden Marjolein A , Wyers Caroline E , Mooijaart Simon P 
Published: January 2021

Abstract

Background
During the first wave of the coronavirus disease 2019 (COVID-19) pandemic, older patients had an increased risk of hospitalisation and death. Reports on the association of frailty with poor outcome have been conflicting.

Objective
The aim of the present study was to investigate the independent association between frailty and in-hospital mortality in older hospitalised COVID-19 patients in the Netherlands.

Methods
This was a multicentre retrospective cohort study in 15 hospitals in the Netherlands, including all patients aged ≥70 years, who were hospitalised with clinically confirmed COVID-19 between February and May 2020. Data were collected on demographics, co-morbidity, disease severity and Clinical Frailty Scale (CFS). Primary outcome was in-hospital mortality.

Results
A total of 1,376 patients were included (median age 78 years (interquartile range 74–84), 60% male). In total, 499 (38%) patients died during hospital admission. Parameters indicating presence of frailty (CFS 6–9) were associated with more co-morbidities, shorter symptom duration upon presentation (median 4 versus 7 days), lower oxygen demand and lower levels of C-reactive protein. In multivariable analyses, the CFS was independently associated with in-hospital mortality: compared with patients with CFS 1–3, patients with CFS 4–5 had a two times higher risk (odds ratio (OR) 2.0 (95% confidence interval (CI) 1.3–3.0)) and patients with CFS 6–9 had a three times higher risk of in-hospital mortality (OR 2.8 (95% CI 1.8–4.3)).

Conclusions
The in-hospital mortality of older hospitalised COVID-19 patients in the Netherlands was 38%. Frailty was independently associated with higher in-hospital mortality, even though COVID-19 patients with frailty presented earlier to the hospital with less severe symptoms.
Systematic Review and Dose–Response Meta-Analysis on the Relationship Between Alcohol Consumption and Sickness Absence
Authors: Marzan Melvin , Callinan Sarah , Livingston Michael , Leggat Geoffrey , Jiang Heng 
Published: January 2021

ABSTRACT

Aims
Alcohol consumption (AC) may cause workplace absence, but the findings of individual studies vary markedly. To date, no dose–response meta-analysis (DRMA) of the relationship between AC and sickness absence (SA) has been completed. This paper aims to estimate the dose–response relationship between AC and the risk of SA based on published observational studies.

Methods
We used DRMA and modelling to investigate the effects of varying doses of AC (including heavy episodic drinking (HED)) onSA.

Results
The meta-analysis included 21 studies (12 cohort studies and 9 cross-sectional). It showed that HED, risky (20–40 g of alcohol/day) and high-risk (&gt;40 g of alcohol/day) drinkers had an elevated risk of SA when compared with light-to-moderate drinkers for both sexes. Those who abstained from alcohol had a higher risk of SA than those who drink moderately.

Conclusions
Our results indicate that risky, high-risk drinking and HED may increase the risk of absenteeism. The implementation of population-based strategies may be appropriate to address the burdens of alcohol-related SA. Additionally, economic evaluations of alcohol policies should incorporate their impacts on SA. However, the current literature has substantial limitations, relying on modestly designed studies from just a few settings and more studies are needed—especially those that measure abstention in more nuancedways.
Female-biased sex ratios in urban centers create a “fertility trap” in post-war Finland
Authors: Pettay Jenni E , Lummaa Virpi , Lynch Robert , Loehr John 
Published: January 2021

AbstractBecause sex ratios are a key factor regulating mating success and subsequent fitness both across and within species, there is widespread interest in how population-wide sex ratio imbalances affect marriage markets and the formation of families in human societies. Although most modern cities have more women than men and suffer from low fertility rates, the effects of female-biased sex ratios have garnered less attention than male-biased ratios. Here, we analyze how sex ratios are linked to marriages, reproductive histories, dispersal, and urbanization by taking advantage of a natural experiment in which an entire population was forcibly displaced during World War II to other local Finnish populations of varying sizes and sex ratios. Using a discrete time-event generalized linear mixed-effects model, and including factors that change across time, such as annual sex ratio, we show how sex ratios, reproduction, and migration are connected in a female-dominated environment. Young childless women migrated toward urban centers where work was available to women, and away from male-biased rural areas. In such areas where there were more females, women were less likely to start reproduction. Despite this constraint, women showed little flexibility in mate choice, with no evidence for an increase in partner age difference in female-biased areas. We propose that together these behaviors and conditions combine to generate an “urban fertility trap” which may have important consequences for our understanding of the fertility dynamics of today including the current fertility decline across the developed world.
The stacking strategy-based hybrid framework for identifying non-coding RNAs
Authors: Wang Xin , Yang Yang , Liu Jian , Wang Guohua 
Published: January 2021

Abstract
With the development of next-generation sequencing technology, a large number of transcripts need to be analyzed, and it has been a challenge to distinguish non-coding ribonucleic acid (RNAs) (ncRNAs) from coding RNAs. And for non-model organisms, due to the lack of transcriptional data, many existing methods cannot identify them. Therefore, in addition to using deoxyribonucleic acid-based and RNA-based features, we also proposed a hybrid framework based on the stacking strategy to identify ncRNAs, and we innovatively added eight features based on predicted peptides. The proposed framework was based on stacking two-layer classifier which combined random forest (RF), LightGBM, XGBoost and logistic regression (LR) models. We used this framework to build two types of models. For cross-species ncRNAs identification model, we tested it on six different species: human, mouse, zebrafish, fruit fly, worm and Arabidopsis. Compared with other tools, our model was the best in datasets of Arabidopsis, worm and zebrafish with the accuracy of 98.36%, 99.65% and 94.12%. For performance metrics analysis, the datasets of the six species were considered as a whole set, and the sensitivity, accuracy, precision and F1 values of our model were the best. For the plant-specific ncRNAs identification model, the average values of the six metrics of the two experiments were all greater than 95%, which demonstrated it can be used to identify ncRNAs in plants. The above indicates that the hybrid framework we designed is universal between animals and plants and has significant advantages in the identification of cross-species ncRNAs.
A dynamic recursive feature elimination framework (dRFE) to further refine a set of OMIC biomarkers
Authors: Han Yuanyuan , Huang Lan , Zhou Fengfeng 
Published: January 2021

Abstract

Motivation
A feature selection algorithm may select the subset of features with the best associations with the class labels. The recursive feature elimination (RFE) is a heuristic feature screening framework and has been widely used to select the biological OMIC biomarkers. This study proposed a dynamic recursive feature elimination (dRFE) framework with more flexible feature elimination operations. The proposed dRFE was comprehensively compared with 11 existing feature selection algorithms and five classifiers on the eight difficult transcriptome datasets from a previous study, the ten newly collected transcriptome datasets and the five methylome datasets.

Results
The experimental data suggested that the regular RFE framework did not perform well, and dRFE outperformed the existing feature selection algorithms in most cases. The dRFE-detected features achieved Acc = 1.0000 for the two methylome datasets GSE53045 and GSE66695. The best prediction accuracies of the dRFE-detected features were 0.9259, 0.9424 and 0.8601 for the other three methylome datasets GSE74845, GSE103186 and GSE80970, respectively. Four transcriptome datasets received Acc = 1.0000 using the dRFE-detected features, and the prediction accuracies for the other six newly collected transcriptome datasets were between 0.6301 and 0.9917.

Availability and implementation
The experiments in this study are implemented and tested using the programming language Python version 3.7.6.

Supplementary information
Supplementary data are available at Bioinformatics online.
wiSDOM: a visual and statistical analytics for interrogating microbiome
Authors: Su Shih-Chi , Galvin James E. , Yang Shun-Fa , Chung Wen-Hung , Chang Lun-Ching 
Published: January 2021

Abstract

Motivation
We proposed a wiSDOM (web-based inclusionary analysis Suite for Disease-Oriented Metagenomics) R Shiny application which comprises six functional modules: (i) initial visualization of sampling effort and distribution of dominant bacterial taxa among groups or individual samples at different taxonomic levels; (ii) statistical and visual analysis of α diversity; (iii) analysis of similarity (ANOSIM) of β diversity on UniFrac, Bray-Curtis, Horn-Morisita or Jaccard distance and visualizations; (iv) microbial biomarker discovery between two or more groups with various statistical and machine learning approaches; (v) assessment of the clinical validity of selected biomarkers by creating the interactive receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC) for binary classifiers; and lastly (vi) functional prediction of metagenomes with PICRUSt or Tax4Fun.

Results
The performance of wiSDOM has been evaluated in several of our previous studies for exploring microbial biomarkers and their clinical validity as well as assessing the alterations in bacterial diversity and functionality. The wiSDOM can be customized and visualized as per users’ needs and specifications, allowing researchers without programming background to conduct comprehensive data mining and illustration using an intuitive browser-based interface.

Availability and implementation
The browser-based R Shiny interface can be accessible via (https://lun-ching.shinyapps.io/wisdom/) and freely available at (https://github.com/lunching/wiSDOM).

Supplementary information
Supplementary data are available at Bioinformatics online.
Missing at random: a stochastic process perspective
Authors: Farewell D M , Daniel R M , Seaman S R 
Published: January 2021

SummaryWe offer a natural and extensible measure-theoretic treatment of missingness at random. Within the standard missing-data framework, we give a novel characterization of the observed data as a stopping-set sigma algebra. We demonstrate that the usual missingness-at-random conditions are equivalent to requiring particular stochastic processes to be adapted to a set-indexed filtration. These measurability conditions ensure the usual factorization of likelihood ratios. We illustrate how the theory can be extended easily to incorporate explanatory variables, to describe longitudinal data in continuous time, and to admit more general coarsening of observations.
The Composition and Metabolic Potential of the Human Small Intestinal Microbiota Within the Context of Inflammatory Bowel Disease
Authors: Ruigrok Renate A A A , Collij Valerie , Sureda Paula , Klaassen Marjolein A Y , Bolte Laura A , Jansen Bernadien H , Voskuil Michiel D , Fu Jingyuan , Wijmenga Cisca , Zhernakova Alexandra , Weersma Rinse K , Vich Vila Arnau 
Published: January 2021

Abstract

Background and Aims
The human gastrointestinal tract harbours distinct microbial communities essential for health. Little is known about small intestinal communities, despite the small intestine playing a fundamental role in nutrient absorption and host-microbe immune homeostasis. We aimed to explore the small intestine microbial composition and metabolic potential, in the context of inflammatory bowel disease [IBD].

Methods
Metagenomes derived from faecal samples and extensive phenotypes were collected from 57 individuals with an ileostomy or ileoanal pouch, and compared with 1178 general population and 478 IBD faecal metagenomes. Microbiome features were identified using MetaPhAn2 and HUMAnN2, and association analyses were performed using multivariate linear regression.

Results
Small intestinal samples had a significantly lower bacterial diversity, compared with the general population and, to a lesser extent, IBD samples. Comparing bacterial composition, small intestinal samples clustered furthest from general population samples and closest to IBD samples with intestinal resections. Veillonella atypica, Streptococcus salivarius, and Actinomyces graevenitzii were among the species significantly enriched in the small intestine. Predicted metabolic pathways in the small intestine are predominantly involved in simple carbohydrate and energy metabolism, but also suggest a higher pro-inflammatory potential.

Conclusions
We described the bacterial composition and metabolic potential of the small intestinal microbiota. The colonic microbiome of IBD patients, particularly with intestinal resections, showed resemblance to that of the small intestine. Moreover, several features characterising the small intestinal microbiome have been previously associated with IBD. These results highlight the importance of studying the small intestinal microbiota to gain new insight into disease pathogenesis.