bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fault rock heterogeneity can produce fault weakness and reduce fault stability
Authors: Bedford John D. , Faulkner Daniel R. , Lapusta Nadia 
Published: January 2022

AbstractGeological heterogeneity is abundant in crustal fault zones; however, its role in controlling the mechanical behaviour of faults is poorly constrained. Here, we present laboratory friction experiments on laterally heterogeneous faults, with patches of strong, rate-weakening quartz gouge and weak, rate-strengthening clay gouge. The experiments show that the heterogeneity leads to a significant reduction in strength and frictional stability in comparison to compositionally identical faults with homogeneously mixed gouges. We identify a combination of weakening effects, including smearing of the weak clay; differential compaction of the two gouges redistributing normal stress; and shear localization producing stress concentrations in the strong quartz patches. The results demonstrate that geological heterogeneity and its evolution can have pronounced effects on fault strength and stability and, by extension, on the occurrence of slow-slip transients versus earthquake ruptures and the characteristics of the resulting events, and should be further studied in lab experiments and earthquake source modelling.
Photocatalytic defluoroalkylation and hydrodefluorination of trifluoromethyls using o-phosphinophenolate
Authors: Liu Can , Shen Ni , Shang Rui 
Published: January 2022

AbstractUnder visible light irradiation, o-phosphinophenolate functions as an easily accessible photoredox catalyst to activate trifluoromethyl groups in trifluoroacetamides, trifluoroacetates, and trifluoromethyl (hetero)arenes to deliver corresponding difluoromethyl radicals. It works in relay with a thiol hydrogen atom transfer (HAT) catalyst to enable selective defluoroalkylation and hydrodefluorination. The reaction allows for the facile synthesis of a broad scope of difluoromethylene-incorporated carbonyl and (hetero)aromatic compounds, which are valuable fluorinated intermediates of interest in the pharmaceutical industry. The ortho-diphenylphosphino substituent, which is believed to facilitate photoinduced electron transfer, plays an essential role in the redox reactivity of phenolate. In addition to trifluoromethyl groups, pentafluoroethyl groups could also be selectively defluoroalkylated.
Completely aqueous processable stimulus responsive organic room temperature phosphorescence materials with tunable afterglow color
Authors: Li Dan , Yang Yujie , Yang Jie , Fang Manman , Tang Ben Zhong , Li Zhen 
Published: January 2022

AbstractMany luminescent stimuli responsive materials are based on fluorescence emission, while stimuli-responsive room temperature phosphorescent materials are less explored. Here, we show a kind of stimulus-responsive room temperature phosphorescence materials by the covalent linkage of phosphorescent chromophore of arylboronic acid and polymer matrix of poly(vinylalcohol). Attributed to the rigid environment offered from hydrogen bond and B-O covalent bond between arylboronic acid and poly(vinylalcohol), the yielded polymer film exhibits ultralong room temperature phosphorescence with lifetime of 2.43 s and phosphorescence quantum yield of 7.51%. Interestingly, the RTP property of this film is sensitive to the water and heat stimuli, because water could destroy the hydrogen bonds between adjacent poly(vinylalcohol) polymers, then changing the rigidity of this system. Furthermore, by introducing another two fluorescent dyes to this system, the color of afterglow with stimulus response effect could be adjusted from blue to green to orange through triplet-to-singlet Förster-resonance energy-transfer. Finally, due to the water/heat-sensitive, multicolor and completely aqueous processable feature for these three afterglow hybrids, they are successfully applied in multifunctional ink for anti-counterfeit, screen printing and fingerprint record.
A polytherapy based approach to combat antimicrobial resistance using cubosomes
Authors: Lai Xiangfeng , Han Mei-Ling , Ding Yue , Chow Seong Hoong , Le Brun Anton P. , Wu Chun-Ming , Bergen Phillip J. , Jiang Jhih-hang , Hsu Hsien-Yi , Muir Benjamin W. , White Jacinta , Song Jiangning , Li Jian , Shen Hsin-Hui 
Published: January 2022

AbstractA depleted antimicrobial drug pipeline combined with an increasing prevalence of Gram-negative ‘superbugs’ has increased interest in nano therapies to treat antibiotic resistance. As cubosomes and polymyxins disrupt the outer membrane of Gram-negative bacteria via different mechanisms, we herein examine the antimicrobial activity of polymyxin-loaded cubosomes and explore an alternative strategy via the polytherapy treatment of pathogens with cubosomes in combination with polymyxin. The polytherapy treatment substantially increases antimicrobial activity compared to polymyxin B-loaded cubosomes or polymyxin and cubosomes alone. Confocal microscopy and neutron reflectometry suggest the superior polytherapy activity is achieved via a two-step process. Firstly, electrostatic interactions between polymyxin and lipid A initially destabilize the outer membrane. Subsequently, an influx of cubosomes results in further membrane disruption via a lipid exchange process. These findings demonstrate that nanoparticle-based polytherapy treatments may potentially serve as improved alternatives to the conventional use of drug-loaded lipid nanoparticles for the treatment of “superbugs”.
Microbiome differential abundance methods produce different results across 38 datasets
Authors: Nearing Jacob T. , Douglas Gavin M. , Hayes Molly G. , MacDonald Jocelyn , Desai Dhwani K. , Allward Nicole , Jones Casey M. A. , Wright Robyn J. , Dhanani Akhilesh S. , Comeau André M. , Langille Morgan G. I. 
Published: January 2022

AbstractIdentifying differentially abundant microbes is a common goal of microbiome studies. Multiple methods are used interchangeably for this purpose in the literature. Yet, there are few large-scale studies systematically exploring the appropriateness of using these tools interchangeably, and the scale and significance of the differences between them. Here, we compare the performance of 14 differential abundance testing methods on 38 16S rRNA gene datasets with two sample groups. We test for differences in amplicon sequence variants and operational taxonomic units (ASVs) between these groups. Our findings confirm that these tools identified drastically different numbers and sets of significant ASVs, and that results depend on data pre-processing. For many tools the number of features identified correlate with aspects of the data, such as sample size, sequencing depth, and effect size of community differences. ALDEx2 and ANCOM-II produce the most consistent results across studies and agree best with the intersect of results from different approaches. Nevertheless, we recommend that researchers should use a consensus approach based on multiple differential abundance methods to help ensure robust biological interpretations.
Microbial co-occurrence network topological properties link with reactor parameters and reveal importance of low-abundance genera
Authors: Guo Bing , Zhang Lei , Sun Huijuan , Gao Mengjiao , Yu Najiaowa , Zhang Qianyi , Mou Anqi , Liu Yang 
Published: January 2022

AbstractOperational factors and microbial interactions affect the ecology in anaerobic digestion systems. From 12 lab-scale reactors operated under distinct engineering conditions, bacterial communities were found driven by temperature, while archaeal communities by both temperature and substrate properties. Combining the bacterial and archaeal community clustering patterns led to five sample groups (ambient, mesophilic low-solid-substrate, mesophilic, mesophilic co-digestion and thermophilic) for co-occurrence network analysis. Network topological properties were associated with substrate characteristics and hydrolysis-methanogenesis balance. The hydrolysis efficiency correlated (p < 0.05) with clustering coefficient positively and with normalized betweenness negatively. The influent particulate COD ratio and the relative differential hydrolysis-methanogenesis efficiency (Defficiency) correlated negatively with the average path length (p < 0.05). Individual genera’s topological properties showed more connector genera in thermophilic network, representing stronger inter-module communication. Individual genera’s normalized degree and betweenness revealed that lower-abundance genera (as low as 0.1%) could perform central hub roles and communication roles, maintaining the stability and functionality of the microbial community.
Machine learned interatomic potentials using random features
Authors: Dhaliwal Gurjot , Nair Prasanth B. , Singh Chandra Veer 
Published: January 2022

AbstractWe present a method to model interatomic interactions such as energy and forces in a computationally efficient way. The proposed model approximates the energy/forces using a linear combination of random features, thereby enabling fast parameter estimation by solving a linear least-squares problem. We discuss how random features based on stationary and non-stationary kernels can be used for energy approximation and provide results for three classes of materials, namely two-dimensional materials, metals and semiconductors. Force and energy predictions made using the proposed method are in close agreement with density functional theory calculations, with training time that is 96% lower than standard kernel models. Molecular Dynamics calculations using random features based interatomic potentials are shown to agree well with experimental and density functional theory values. Phonon frequencies as computed by random features based interatomic potentials are within 0.1% of the density functional theory results. Furthermore, the proposed random features-based potential addresses scalability issues encountered in this class of machine learning problems.
The effects of medications for treating COPD and allied conditions on stroke: a population-based cohort study
Authors: Shen Ai-Ling , Lin Hsiu-Li , Lin Hsiu-Chen , Chao Jane Chen-Jui , Hsu Chien-Yeh , Chen Chung-Yu 
Published: January 2022

AbstractPatients with chronic obstructive pulmonary disease (COPD) are at higher risk of stroke. This study aimed to investigate the clinical factors of stroke risk in COPD and allied conditions patients and associations between medications for treating COPD and allied conditions. The population-based study cohort comprised 24,173 patients diagnosed with COPD and allied conditions between 2000 and 2013, and 24,170 selected matched patients without COPD comprised the comparison cohort from a nationwide database. Cox-proportional hazard regression was performed to determine the impact of medical therapies, comorbidities, and other clinical factors on stroke risk. Of the 48,343 included patients, 1394 (2.9%) experienced stroke during follow-up, with a significant difference between COPD and allied conditions cohort (1003/4.2%) and comparison cohort (391/1.6%) (adjusted hazard ratio [aHR]: 2.72, p < 0.001). Cox-regression analysis revealed that COPD and allied conditions patients who were older (>65 years) (HR: 1.06); male (HR: 1.39); with hypertension (HR: 1.46), diabetes mellitus (HR: 1.33) and atrial fibrillation (HR: 1.63) had increased stroke risk. Mucolytics (HR: 0.44) and combination therapy with inhaled corticosteroids (ICS) and long-acting β2-agonists (LABA) (HR: 0.75) were associated with decreased stroke risk in COPD and allied conditions patients. Among COPD and allied conditions patients, major comorbidities increase risk of stroke. Therapy with mucolytic agents and combination ICS/LABA is associated with risk reduction.
Enhancing protein inter-residue real distance prediction by scrutinising deep learning models
Authors: Rahman Julia , Newton M. A. Hakim , Islam Md Khaled Ben , Sattar Abdul 
Published: January 2022

AbstractProtein structure prediction (PSP) has achieved significant progress lately via prediction of inter-residue distances using deep learning models and exploitation of the predictions during conformational search. In this context, prediction of large inter-residue distances and also prediction of distances between residues separated largely in the protein sequence remain challenging. To deal with these challenges, state-of-the-art inter-residue distance prediction algorithms have used large sets of coevolutionary and non-coevolutionary features. In this paper, we argue that the more the types of features used, the more the kinds of noises introduced and then the deep learning model has to overcome the noises to improve the accuracy of the predictions. Also, multiple features capturing similar underlying characteristics might not necessarily have significantly better cumulative effect. So we scrutinise the feature space to reduce the types of features to be used, but at the same time, we strive to improve the prediction accuracy. Consequently, for inter-residue real distance prediction, in this paper, we propose a deep learning model named scrutinised distance predictor (SDP), which uses only 2 coevolutionary and 3 non-coevolutionary features. On several sets of benchmark proteins, our proposed SDP method improves mean Local Distance Different Test (LDDT) scores at least by 10% over existing state-of-the-art methods. The SDP program along with its data is available from the website https://gitlab.com/mahnewton/sdp.
The waist-to-body mass index ratio as an anthropometric predictor for cardiovascular outcome in subjects with established atherosclerotic cardiovascular disease
Authors: Hsuan Chin-Feng , Lin Fang-Ju , Lee Thung-Lip , Yang Kai-Chien , Tseng Wei-Kung , Wu Yen-Wen , Yin Wei-Hsian , Yeh Hung-I. , Chen Jaw-Wen , Wu Chau-Chung ,   The Taiwanese Secondary Prevention for Patients with AtheRosCLErotic Disease (T-SPARCLE) Registry Investigators, Wu Chau-Chung , Chang Wei-Tien , Lee Yi-Heng , Chen Jaw-Wen , Sheu Huey-Herng , Hsieh I.-Chang , Chen Yih-Sharng , Liu Ming-En , Chen Chen-Huan , Lin Lian-Yu , Yeh Hung-I. , Sung Shih-Hsien , Liu Ping-Yen , Wu I.-Hui , Wang Zhi-Hong , Chiu Kuan-Ming , Wu Yen-Wen , Kuo Chi-Tai , Wang Tzung-Dau , Hung Chung-Lieh , Wang Chih-Hsien , Wang Chun-Chieh , Wang Chih-Yuan , Jeng Jiann-Shing , Lin Tsung-Hsien , Kao Hsien-Li , Chu Pao-Hsien , Lin Fang-Ju , Chen Zhih-Cherng , Chang Kuan-Cheng , Yin Wei-Hsian , Tseng Wei-Kung 
Published: January 2022

AbstractObesity is an independent risk factor for atherosclerotic cardiovascular disease (ASCVD). However, ‘obesity paradox’ is observed in patients with coronary artery disease while defining obesity by body mass index (BMI). The purpose of this study is to identify a better anthropometric parameter to predict cardiovascular events in patients with ASCVD. The study was conducted using the Taiwanese Secondary Prevention for patients with AtheRosCLErotic disease (T-SPARCLE) Registry. A total of 6,920 adult patients with stable ASCVD, enrolled from January 2010 to November 2014, were included, with a mean age of 65.9 years, 73.9% males, and a mean BMI of 26.3 kg/m2 at baseline. These patients were followed up for a median of 2.5 years. The study endpoint was the composite major adverse cardiovascular event (MACE), defined as cardiovascular death, nonfatal myocardial infarction or stroke, or cardiac arrest with resuscitation. Multivariable Cox proportional hazards regression showed a significant positive association between waist-to-BMI ratio and MACE (adjusted hazard ratio 1.69 per cm‧m2/kg increase in waist-to-BMI ratio, 95% CI 1.12–2.49, p = 0.01) after adjusting for potential risk factors and confounders. Traditional anthropometric parameters, such as BMI, weight, waist and waist-hip ratio, or newer waist-based indices, such as body roundness index and a body shape index, did not show any significant linear associations (p = 0.09, 0.30, 0.89, 0.54, 0.79 and 0.06, respectively). In the restricted cubic spline regression analysis, the positive dose–response association between waist-to-BMI ratio and MACE persisted across all the range of waist-to-BMI ratio. The positive dose–response association was non-linear with a much steeper increase in the risk of MACE for waist-to-BMI ratio > 3.6 cm‧m2/kg. In conclusion, waist-to-BMI ratio may function as a positive predictor for the risk of MACE in established ASCVD patients.
Joint analysis of the intention to vaccinate and to use contact tracing app during the COVID-19 pandemic
Authors: Caserotti Marta , Girardi Paolo , Tasso Alessandra , Rubaltelli Enrico , Lotto Lorella , Gavaruzzi Teresa 
Published: January 2022

AbstractPharmacological and non-pharmacological measures will overlap for a period after the onset of the pandemic, playing a strong role in virus containment. We explored which factors influence the likelihood to adopt two different preventive measures against the COVID-19 pandemic. An online snowball sampling (May–June 2020) collected a total of 448 questionnaires in Italy. A Bayesian bivariate Gaussian regression model jointly investigated the willingness to get vaccinated against COVID-19 and to download the national contact tracing app. A mixed-effects cumulative logistic model explored which factors affected the motivation to adopt one of the two preventive measures. Despite both COVID-19 vaccines and tracing apps being indispensable tools to contain the spread of SARS-CoV-2, our results suggest that adherence to the vaccine or to the national contact tracing app is not predicted by the same factors. Therefore, public communication on these measures needs to take in consideration not only the perceived risk associated with COVID-19, but also the trust people place in politics and science, their concerns and doubts about vaccinations, and their employment status. Further, the results suggest that the motivation to comply with these measurements was predominantly to protect others rather than self-protection.
Methylation statuses of NCOR2, PARK2, and ZSCAN12 signify densities of tumor-infiltrating lymphocytes in gastric carcinoma
Authors: Wen Xianyu , Jin Hye-Yeong , Li Meihui , Kim Younghoon , Cho Nam-Yun , Kwak Yoonjin , Bae Jeong Mo , Lee Hye Seung , Kang Gyeong Hoon 
Published: January 2022

AbstractIndividual cell types of human tissues have their own CpG site methylation profiles, which might be utilized for the development of methylation markers to denote tumor-infiltrating lymphocytes (TILs). We aimed to develop DNA methylation markers that recapitulate the densities of TILs in gastric carcinoma (GC). Through genome-wide methylation profiling, NCOR2, PARK2, and ZSCAN12 were found to be highly methylated in CD3-positive and CD8-positive cells and rarely methylated in tumor cells. Scores of the three methylation markers were analyzed for their relationship with the overall survival and recurrence-free survival of patients with advanced GC (n = 471). The scores of three methylation markers were closely associated with densities of CD3-positive or CD8-positive cells at the tumor center or invasive front of GCs and found to be a significant prognostic factor in univariate analysis of overall survival and recurrence-free survival. In multivariate analysis, the highest score showed hazard ratios of 0.513 (CI 0.306–0.857) and 0.434 (CI 0.261–0.720) for overall survival and recurrence-free survival, respectively. The findings suggest that methylation markers signifying TILs might be utilized for the recapitulation of TIL density in GCs and serve as biomarkers for predicting prognosis in patients with GC.
Impacts of offshore wind farms on the atmospheric environment over Taiwan Strait during an extreme weather typhoon event
Authors: Lee Tsung-Yu , Wu Yu-Ting , Kueh Mien-Tze , Lin Chuan-Yao , Lin Yi-Ying , Sheng Yang-Fan 
Published: January 2022

AbstractWind is one of the cleanest renewable energy resources. Through the “Thousand Wind Turbines Project”, Taiwan is planning to increase the proportion of power generation from renewable energy and has set a target of 5.7 GW for offshore wind by 2025. The effects of future offshore wind farms (OWFs) over the Taiwan Strait on the atmospheric environment have not been evaluated. This study examined the potential effects of proposed OWFs on the atmospheric environment if the OWFs had existed during Tropical Storm Haitang (2017) by using Weather Research and Forecasting (WRF) model. A small set of ensemble simulations was conducted for studying the sensitivity of the ambient conditions in the region to the wind farm locations, the number and density of the turbines, and the initial time of simulations. Following the landfall and northward movement of Tropical Storm Haitang, a series of complex interactions between the typhoon circulation and the wind farm emerged, including small time slots of wake effect and mountain blocking effect. The combination of these rapidly changing OWFs-related effects contributed to a weak reduction in precipitation (− 1.08 mm) and hub-height wind speed (− 0.25 m s−1), as well as minimal warming near the surface (+ 0.13 °C) over southern Taiwan.
Informative predictors of pregnancy after first IVF cycle using eIVF practice highway electronic health records
Authors: Xu Tingting , de Figueiredo Veiga Alexis , Hammer Karissa C. , Paschalidis Ioannis Ch. , Mahalingaiah Shruthi 
Published: January 2022

AbstractThe aim of this study is to determine the most informative pre- and in-cycle variables for predicting success for a first autologous oocyte in-vitro fertilization (IVF) cycle. This is a retrospective study using 22,413 first autologous oocyte IVF cycles from 2001 to 2018. Models were developed to predict pregnancy following an IVF cycle with a fresh embryo transfer. The importance of each variable was determined by its coefficient in a logistic regression model and the prediction accuracy based on different variable sets was reported. The area under the receiver operating characteristic curve (AUC) on a validation patient cohort was the metric for prediction accuracy. Three factors were found to be of importance when predicting IVF success: age in three groups (38–40, 41–42, and above 42 years old), number of transferred embryos, and number of cryopreserved embryos. For predicting first-cycle IVF pregnancy using all available variables, the predictive model achieved an AUC of 68% + /− 0.01%. A parsimonious predictive model utilizing age (38–40, 41–42, and above 42 years old), number of transferred embryos, and number of cryopreserved embryos achieved an AUC of 65% + /− 0.01%. The proposed models accurately predict a single IVF cycle pregnancy outcome and identify important predictive variables associated with the outcome. These models are limited to predicting pregnancy immediately after the IVF cycle and not live birth. These models do not include indicators of multiple gestation and are not intended for clinical application.
A computational efficient optimization of flow shop scheduling problems
Authors: Liang Zhongyuan , Zhong Peisi , Liu Mei , Zhang Chao , Zhang Zhenyu 
Published: January 2022

AbstractFlow shop scheduling problems are NP-hard problems. Heuristic algorithms and evolutionary metaheuristic algorithms are commonly used to solve this kind of problem. Although heuristic algorithms have high solving speed, the solution quality is not good. Evolutionary algorithms make up for this defect in small-scale problems, but the solution performance will deteriorate with the expansion of the problem scale and there will be premature problems. In order to improve the solving accuracy of flow shop scheduling problems, a computational efficient optimization approach combining NEH and niche genetic algorithm (NEH-NGA) is developed. It is strengthened in the following three aspects: NEH algorithm is used to optimize the initial population, three crossover operators are used to enhance the genetic efficiency, and the niche mechanism is used to control the population distribution. A concrete application scheme of the proposed method is introduced. The results of compared with NEH heuristic algorithm and standard genetic algorithm (SGA) evolutionary metaheuristic algorithm after testing on 101 FSP benchmark instances show that the solution accuracy has been significantly improved.