bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genomic strategies to untangle the etiology of autism: A primer
Authors: Vashisth Shayal , Chahrour Maria H. 
Published: November 2022

AbstractAutism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in communication, diminished social skills, and restrictive and repetitive behaviors and interests. ASD affects approximately 2.3% of the population and is highly heterogeneous, both phenotypically and genetically. As genomic technologies advance, our understanding of the genetic architecture of ASD is becoming clearer, encompassing spontaneous and inherited alterations throughout the genome, and delineating alterations that are either rare or common in the population. This commentary provides an overview of the genomic strategies and resulting major findings of genetic alterations associated with ASD.
Genetic ablation of Toll‐like Receptor 4 seems to activate the apoptosis pathway in the skeletal muscle of mice after acute physical exercise
Authors: Marafon Bruno B. , Pinto Ana P. , de Vicente Larissa G. , da Rocha Alisson L. , Simabuco Fernando M. , Ropelle Eduardo R. , de Moura Leandro P. , Cintra Dennys E. , Pauli José R. , Silva Adelino S. R. da 
Published: November 2022

AbstractMany conditions, such as inflammation and physical exercise, can induce endoplasmic reticulum (ER) stress. Toll‐like Receptor 4 (TLR4) can trigger inflammation and ER stress events. However, there are still no data in the literature regarding the role of TLR4 in ER stress during exercise in skeletal muscle. Therefore, the current investigation aimed to verify the responses of ER stress markers in wild‐type (WT) andTlr4global knockout (KO) mice after acute and chronic physical exercise protocols. Eight‐week‐old male WT and KO mice were submitted to acute (moderate or high intensity) and chronic (4‐week protocol) treadmill exercises. Under basal conditions, KO mice showed lower performance in the rotarod test. Acute high‐intensity exercise increased eIF2α protein in the WT group. After the acute high‐intensity exercise, there was an increase inCasp3andDdit3mRNA for the KO mice. Acute moderate exercise increased the cleaved Caspase‐3/Caspase‐3 in the KO group. In response to chronic exercise, the KO group showed no improvement in any performance evaluation. The 4‐week chronic protocol did not generate changes in ATF6, CHOP, p‐IRE1α, p‐eIF2α/eIF2α, and cleaved Caspase‐3/Caspase‐3 ratio but reduced BiP protein compared with the KO‐Sedentary group. These results demonstrate the global deletion ofTlr4seems to have the same effects on UPR markers of WT animals after acute and chronic exercise protocols but decreased performance. The cleaved Caspase‐3/Caspase‐3 ratio may be activated by another pathway other than ER stress inTlr4KO animals.
Ultrathin origami accordion‐like structure of vacancy‐rich graphitized carbon nitride for enhancing CO2 photoreduction
Authors: Jia Guangri , Wang Zhongxu , Gong Ming , Wang Ying , Li Lu Hua , Dong Yilong , Liu Lulu , Zhang Lei , Zhao Jingxiang , Zheng Weitao , Cui Xiaoqiang 
Published: November 2022

AbstractRetaining the ultrathin structure of two‐dimensional materials is very important for stabilizing their catalytic performances. However, aggregation and restacking are unavoidable, to some extent, due to the van der Waals interlayer interaction of two‐dimensional materials. Here, we address this challenge by preparing an origami accordion structure of ultrathin two‐dimensional graphitized carbon nitride (oa‐C3N4) with rich vacancies. This novel structured oa‐C3N4 shows exceptional photocatalytic activity for the CO2 reduction reaction, which is 8.1 times that of the pristine C3N4. The unique structure not only prevents restacking but also increases light harvesting and the density of vacancy defects, which leads to modification of the electronic structure, regulation of the CO2 adsorption energy, and a decrease in the energy barrier of the carbon dioxide to carboxylic acid intermediate reaction. This study provides a new avenue for the development of stable high‐performance two‐dimensional catalytic materials.
A suggested data structure for transparent and repeatable reporting of bibliographic searching
Authors: Haddaway Neal R. , Rethlefsen Melissa L. , Davies Melinda , Glanville Julie , McGowan Bethany , Nyhan Kate , Young Sarah 
Published: November 2022

AbstractAcademic searching is integral to research activities: (1) searching to retrieve specific information, (2) to expand our knowledge iteratively, (3) and to collate a representative and unbiased selection of the literature. Rigorous searching methods are vital for reliable, repeatable and unbiased searches needed for these second and third forms of searches (exploratory and systematic searching, respectively) that form a core part of evidence syntheses. Despite the broad awareness of the importance of transparency in reporting search activities in evidence syntheses, the importance of searching has been highlighted only recently and has been the explicit focus of reporting guidance (PRISMA‐S). Ensuring bibliographic searches are reported in a way that is transparent enough to allow for full repeatability or evaluation is challenging for a number of reasons. Here, we detail these reasons and provide for the first time a standardised data structure for transparent and comprehensive reporting of search histories. This data structure was produced by a group of international experts in informatics and library sciences. We explain how the data structure was produced and describe its components in detail. We also demonstrate its practical applicability in tools designed to support literature review authors and explain how it can help to improve interoperability across tools used to manage literature reviews. We call on the research community and developers of reference and review management tools to embrace the data structure to facilitate adequate reporting of academic searching in an effort to raise the standard of evidence syntheses globally.
An accurate fake news detection approach based on a Levy flight honey badger optimized convolutional neural network model
Authors: Dixit Dheeraj Kumar , Bhagat Amit , Dangi Dharmendra 
Published: November 2022

SummaryPeople can quickly acquire the news through a variety of sources, including websites, blogs, and social media, among others. The spread of fake news has become easier as a result of the availability of these platforms. Anybody with access to these networks generates and distributes fake news for professional or personal gain. Numerous studies relying on supervised and unsupervised learning techniques are available to address the issue of recognizing fake news. All of those studies, though, have one flaw: they all deliver mostly inaccurate or unmatched results. Poor accuracy is attributed to a variety of factors, including imbalanced datasets, inefficient parameter tuning, poor feature selection, and so on. To tackle these issues, we proposed a novel approach for fake news detection. Initially, the data were obtained from the ISOT dataset and data cleaning is performed. After that, preprocessing is done which includes three major steps such as stemming, stop word removal, and tokenization are carried out. Next to preprocessing, various features that involve name entity recognition‐based features are selected during feature extraction. From this, the short dimensionality features are selected with the help of the ensemble modified independent component analysis model. Finally, the hybrid convolutional neural network‐based Levy flight‐based honey badger algorithm detects fake news. The experiments are simulated using python software with various performance metrics such as accuracy, specificity, sensitivity, precision, and F‐scores to validate the performance of the proposed method. The proposed model offers a precision, recall, and accuracy value of 95%, 97%, and 98% when evaluated with the ISOT dataset. When compared to the existing state‐of‐art methods, the proposed method yielded superior detection results and higher accuracy rates.
An optimized adaptive ensemble model with feature selection for network intrusion detection
Authors: Yang Zhongjun , Liu Zhi , Zong Xuejun , Wang Guogang 
Published: November 2022

SummaryNetwork intrusion detection system (NIDS) is a key component to identify abnormal behavior of network systems and plays an important role in preventing the occurrence of network attacks. Although a considerable number of machine learning methods have been applied in the field of intrusion detection, it is still a challenge for existing solutions to achieve a good classification performance. The existing traffic datasets generally have redundant and irrelevant features, which hinder classifiers from making more accurate predictions. Furthermore, a single classifier has limited classification performance and may not be able to achieve a better detection performance overall in the face of unbalanced multi‐category traffic data. Therefore, in order to improve the classification performance of intrusion detection models, this paper proposes an adaptive ensemble model by combining feature selection techniques and effective ensemble methods. Firstly, a heuristic feature selection algorithm (NRS‐SSA) is proposed by introducing the neighborhood dependency degree of the neighborhood rough set (NRS) into the salp swarm algorithm (SSA). Then, an improved adaptive weighted voting algorithm is designed. The SSA is introduced to optimize the weight matrix when setting the voting weight. Finally, we use the designed voting algorithm to combine the classification advantages of homogeneous classifiers and heterogeneous classifiers, respectively, and propose an M‐Tree algorithm and an adaptive ensemble model. The experimental results on multiple intrusion detection datasets show that the proposed adaptive ensemble model achieves an advanced detection level.
Dewetting Behavior of Random Copolymer Films Induced by Solvent Vapor Annealing
Authors: Zhang Wang , Wen Gangyao , Li Hongfei 
Published: November 2022

AbstractIn recent years, the dewetting behavior of block copolymer films has been studied a lot, but that of random copolymer films was rarely studied. In this study, effects of film thickness and solvent vapor annealing duration (0 s–24 h) on the dewetting behavior of the spin‐coated poly(styrene‐co‐acrylonitrile) (SAN) random copolymer films were mainly investigated by atomic force microscopy and contact angle method for the first time. The film thicknesses of the SAN films prepared at different concentrations were characterized by X‐ray reflectometry to be 6–34 nm. With the annealing of acetone vapor, the SAN films first appear holes and then rupture into droplets which fuse and break periodically. The periodic evolutions of the droplets are due to the preferred affinity of acetone molecules with the AN segments and the change of surface energy. This phenomenon is different from the single evolutions in the spin‐coated polystyrene‐block‐poly(methyl methacrylate) (PS‐b‐PMMA) block copolymer films. This illustrates the interactions between AN segments and the substrate are stronger than those between PMMA segments and the substrate in the spin‐coated films.
TAEffect: Quantifying interaction risks in trust‐enabled communication systems
Authors: Lu Yunfeng , Fan Xinxin , Jing Quanliang 
Published: November 2022

SummaryThe interactive risks of different devices, serving as clients or servers, have increasingly attracted huge attention in various communication systems, such as wireless sensor networks, wireless communication networks, and mobile crowd‐sensing. At present, lots of countermeasures had been proposed and deployed accordingly. Nevertheless, the investigation on the interaction risks between different devices is still very limited to date. In this paper, we propose a novel adverse effect inference mechanism TAEffect for malicious behaviors of devices emerged in various decentralized and open communication systems/networks through network‐percolation theory. At first, four typical malicious interactional behaviors are mapped into four topologies, then, upon which a network influence‐inspired approach is employed to quantify the adverse effect. Finally, multifacet experiments using five real‐world datasets and a synthetic testbed are performed to validate the efficiency and effectiveness. The experimental results show our proposed approach is significant and rational to quantitatively calculate and qualitatively mirror the four kinds of malicious interactional behaviors in diverse misbehavior‐emerged communication systems.
Community phylogeny and spatial scale affect phylogenetic diversity metrics in a species‐rich rainforest in Borneo
Authors: Okuno Seiya , Yin Tingting , Nanami Satoshi , Matsuyama Shuhei , Kamiya Koichi , Tan Sylvester , Davies Stuart J. , Mohamad Mohizah , Yamakura Takuo , Itoh Akira 
Published: November 2022

AbstractCommunity phylogenetic analysis is an effective approach to understanding the process of community formation. The phylogenetic tree of the species pool is reconstructed in the first step, and the phylogenetic tree obtained in the second step is used to analyze phylogenetic diversity. Sythetic trees have often been used in the construction of phylogenentic trees; however, in tropical rainforests with many closely related species, synthetic trees contain many unresolved nodes, which may affect the results of phylogenetic structure analysis. Here, we constructed a phylogenetic tree using DNA barcode sequences (rbcL,matK,trnH‐psbA) for 737 tree species from the rainforests of Borneo, which have a high‐species diversity and many closely related species. The phylogenetic tree had fewer polytomies and more branch length variations than the Phylocom synthetic trees. Comparison of community phylogenetic analyses indicated that values of the standardized effect size of mean pairwise distance (SES–MPD) were highly correlated between Phylocom and DNA barcode trees, but less so for the standardized effect size of mean nearest taxon distance (SES–MNTD), suggesting that caution is needed when using synthetic trees for communities containing many congeneric species, especially when using SES–MNTD. Simulation analysis suggested that spatial dependence on phylogenetic diversity is related to the phylogenetic signal of the species' habitat niche and the spatial structure of habitat, indicating the importance of detailed phylogeny in understanding community assembly processes.
It's raining species: Rainwash eDNA metabarcoding as a minimally invasive method to assess tree canopy invertebrate diversity
Authors: Macher Till‐Hendrik , Schütz Robin , Hörren Thomas , Beermann Arne J. , Leese Florian 
Published: November 2022

AbstractForest canopies are highly diverse ecosystems, but despite several decades of intense research, there remain substantial gaps in our knowledge of their biodiversity and ecological interactions. One fundamental challenge in canopy research is the limited accessibility of the ecosystem. Consequently, previous studies have relied on the application of either highly invasive methods such as chemical knockdown, or on time‐consuming and expensive setups such as canopy walkways or cranes. Therefore, time‐ and cost‐efficient, ideally minimally invasive yet comprehensive applications are required to help close this knowledge gap. High‐throughput metabarcoding of environmental DNA (eDNA) collected from water, soil, or air provides a minimally invasive method for biodiversity assessment, yet its potential for canopy biodiversity monitoring has not been explored. Herein, we conducted metabarcoding of eDNA washed off the canopy via rainwater to explore its potential for biodiversity monitoring and ecological research. We placed four 1 m2 rain samplers beneath the canopies of four different trees (beech, oak, larch, and pine) prior to a major rain event, filtered eDNA from the collected rainwater, and performed cytochrome c oxidase subunit I (COI) gene metabarcoding to profile the invertebrate community. Additionally, we collected and identified all specimens present in the rainwater to assess if eDNA only came from specimens physically present in the rainwater. We detected 50 invertebrate species by eDNA metabarcoding, of which 43 were not physically present in the water sample, thus likely representing true canopy biodiversity signals. Furthermore, we observed distinct species occurrence patterns corresponding to the four trees, suggesting that ecological patterns such as host specificity can potentially be assessed using the method. In conclusion, our study provides a proof of principle that rainwash eDNA metabarcoding offers a minimally invasive and comprehensive method for biodiversity monitoring in tree canopies.
Heart failure in patients with atrial fibrillation: Insights from Polish part of the EORP‐AF general long‐term registry
Authors: Budnik Monika , Gawałko Monika , Lodziński Piotr , Tymińska Agata , Ozierański Krzysztof , Grabowski Marcin , Peller Michał , Wancerz Anna , Kiliszek Marek , Opolski Grzegorz , Lenarczyk Radosław , Kalarus Zbigniew , Lip Gregory Y.H. , Balsam Paweł 
Published: November 2022

AbstractAimsThis study aimed to determine the impact of heart failure (HF) on clinical outcomes in patients with atrial fibrillation (AF).Methods and resultsWe analysed data from Polish participants of the EURObservational Research Programme‐AF General Long‐Term Registry. The primary endpoint was all‐cause death, and the secondary endpoints included hospital readmissions, cardiovascular (CV) interventions, thromboembolic and haemorrhagic events, rhythm control interventions, and other CV or non‐CV diseases development during one‐year follow up. Overall, 688 patients with available data on HF were included into analysis; 51% (n = 351) had HF; of these 48% (n = 168) had reduced ejection fraction (HFrEF), 22% (n = 77) mid‐range EF (HFmrEF), and 30% (n = 106) preserved EF (HFpEF). Compared with patients without HF, those with HF had higher mortality rate (aHR 5.61; 95% CI 1.94–16.22, P < 0.01). Patients with HF (vs. without HF) had more often CV interventions (10% vs. 5.4%, P = 0.046) and events (14% vs. 7.1%, P = 0.02), and had less often atrial arrhythmia‐related hospital admissions (6.8% vs. 15%, P < 0.01). Over follow‐up, patients with HFmrEF and HFpEF had similar mortality rate versus HFrEF (aHR 0.45, 95% CI 0.13–1.57, P = 0.45 for HFmrEF and aHR 0.54, 95% CI 0.20–1.48, P = 0.54 for HFpEF). Mortality rate was similar among rhythm versus rate control group (aHR 0.34; 95% CI 0.10–1.16; P = 0.34).ConclusionsAF patients with HF have greater mortality rate and more CV interventions/events. No statistically significant difference in long‐term outcomes between patients with HFrEF, HFmrEF, and HFpEF highlights the need to develop therapeutic strategies targeting functional status and survival for patients with HF and AF.
Cultural group norms for harmony explain the puzzling negative association between objective status and system justification in Asia
Authors: Owuamalam Chuma Kevin , Tan Chee Meng , Caricati Luca , Rubin Mark , Spears Russell 
Published: November 2022

AbstractWhy do poorer and less educated Asians trust their institutions of governance more than their richer and well educated counterparts, despite their disadvantaged position within society? System justification theory (SJT) assumes that this trust is driven by a system‐level motivation that operates independently from social identity needs. In two nationally representative surveys spanning several years (Ntotal = 221,297), we compared SJT's explanation with a newer social identity model of system attitudes (SIMSA): that system justification amongst disadvantaged Asians is driven by a group norm for harmony, especially amongst those who are strongly invested in their national ingroup. The results supported SIMSA more than SJT. Specifically, a strong sense of national identification boosted trust in systems of governance amongst poorer and less‐educated Asians, both when societal norms for harmony (Study 1), and personal endorsement of this norm (Study 2) were strong. Hence, social identity needs help to explain stronger system justification among objectively disadvantaged Asians.
Techno‐economic evaluation of regional CCUS implementation: The STRATEGY CCUS project in the Ebro Basin (Spain)
Authors: Fernández‐Canteli Álvarez Paula , García Crespo Jesús , Martínez Orío Roberto , Mediato Arribas Jose Francisco , Ramos Adriá , Berrezueta Edgar 
Published: November 2022

AbstractSTRATEGY CCUS (Strategic Planning of Regions and Territories in Europe for Low‐Carbon Energy and Industry through CCUS) is a 3‐year project (2019‐2022) funded by the European Commission to support the development of low‐carbon energy and industry in eight regions of Southern and Eastern Europe by 2050. Among the three most promising regions selected was Ebro Basin (Spain) where local development plans (or scenarios) were defined for CO2 capture, utilisation and storage (CCUS) technologies implementation based on an industrial cluster approach. Potential regional impact analysis of these CCUS implementation plans was carried out based on the environmental impact assessment, social‐economics factors, social acceptance and in‐depth techno‐economic analysis.The Ebro Basin region is located at the north‐east (NE) of Spain and was selected based on its level of CO2 industrial emissions, estimated geological storage capacity and well‐defined transport network (pipelines, roads, rail and ports). The base scenario presented was built with the aim of covering the most extensive CO2 network but limited by the storage possibilities in the area. It covers the 15 largest emitters in the region, 3 storage sites and a complete transportation network including trucks, pipelines and ships. An alternative scenario was also proposed considering only those industries where CCUS technologies are already included in their decarbonisation strategy.The economic analysis of proposed scenarios is presented as an in‐depth set of key performance indicators (KPIs), as cost per tonne of CO2 avoided, allowing an effective comparison of the scenarios, understanding the real potential for CCUS implementation in the area and pointing out key needs for making it possible. © 2022 The Authors. Greenhouse Gases: Science and Technology published by Society of Chemical Industry and John Wiley & Sons Ltd.
The eventuality of diffusiophoresis and chemical reaction in a flow with variable fluid properties through an upright channel
Authors: Kalita Bhrigu K. , Choudhury Rita 
Published: November 2022

AbstractThe quintessence of this article encompasses the effect of diffusiophoresis, chemical reaction, and varying viscosity as well as thermal conductivity on a fully developed dissipative flow through an upright channel. The fluid is electrically conducting undergoing mixed convection. The governing equations, after transfiguring into dimensionless formation, are solved through a numerical procedure for boundary value problems incorporating MATLAB solver. Imperative scrutiny is made to visualize associative impacts of flow parameters, namely, magnetic parameter, the Brinkmann number, the Schmidt number, variable viscosity parameter, variable thermal conductivity parameter, chemical reaction parameter, diffusiophoretic parameter, and particle diffusion parameter, on the flow. The velocity field, the temperature field, the solute concentration field, the particle concentration field, the skin friction, the Nusselt number, the Sherwood number, and the particle concentration gradient are assessed in view of alteration of the aforesaid parameters with the help of visual illustrations in graphical form and tabular form. Solute mass transposition and colloidal particle locomotion are the fresh inclusions to the scrutiny of upright channel flow in light of solving scheme of bvp4c. Chemical reaction engulfs both solute and particle concentration. Growing viscosity hinders the fluid velocity and heats up the flow encouraging interlayer friction.