bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing sugar-sweetened beverage consumption in early pregnancy using a substance abuse framework
Authors: Ker Chin-Ru , Yang Hao-Ching , Wang Shih-Han , Chan Te-Fu 
Published: November 2023

AbstractSugar-sweetened beverages (SSB) are previously reported to jeopardize maternal fetal health, most well-known for gestational diabetes, childhood obesity, and cognitive impairment. Although warnings and diet recommendations urge pregnant women to consume less SSB, there is no noticeable difference in their behavior. How and why reproductive women change their SSB consumption patterns were not investigated previously. Our study aims to investigate beverage consumption patterns and how these patterns change in pregnancy in the context of substance use disorder (SUD). We invited all pregnant women visiting the clinic to answer a structured 20-min questionnaire every trimester during the regular antennal visit. At the end of the study, 337 pregnant women aged over 20 participated. A total of 301 responses entered for final analysis, with a response rate of 89.3%. Our finding showed those with high DSM-5-TR scores reduced SSB intake after becoming pregnant, while those with mild or low DSM-5-TR scores increased SSB intake after becoming pregnant. The top 3 factors related to their SSB consumption were “use despite of known health hazard (n = 133)”, “increased desire to drink (n = 88)”, and “excessive time spent on seeking SSB (n = 85)”. The least reported factors were in the domains of social impairment (ranging from n = 3 to n = 26), pharmacologic effects (i.e., tolerance (n = 24) and withdrawal (n = 70). When participants reduced SSB consumption after becoming pregnant, their choice of beverages largely shifted to sugarless beverage but not much plain water. The result provided new insights in deciphering pregnant women’s psychomotor factors for SSB intake, which served as useful references for making clinical or even public health recommendations.
A low dietary sodium dose is associated with a more pronounced aldosterone response in normotensive than in hypertensive individuals
Authors: Graudal Niels , Hubeck-Graudal Thorbjørn , Jurgens Gesche 
Published: November 2023

AbstractIn this comprehensive meta-regression analysis encompassing 79 randomized controlled trials, we observed that in populations assigned to a high sodium intake level exceeding 94 mmol, there was no discernible link between plasma aldosterone levels and sodium intake. However, among populations with normal blood pressure subjected to a lower sodium intake, falling below 111 mmol (N = 1544), the association between sodium intake and plasma aldosterone levels manifested as a decrease of 192 pg/ml per 100 mmol of sodium (95% CI − 303 to − 81). In hypertensive populations (N = 1145), this association was less pronounced, with a reduction of 46 pg/ml per 100 mmol sodium, (95% CI − 112 to 20). Furthermore, in normotensive populations the plasma aldosterone increase associated with a decrease in sodium intake was 70 pg/ml per 100 mmol sodium (95% CI 27 to 113). In hypertensive populations, the observed increase was more modest, at 30 pg/ml per 100 mmol sodium, (95% CI 6.8 to 54). A limitation of this study lies in the absence of individual participant data. Our analysis included adjustments for potential effect-modifiers, encompassing bias estimation, which did not substantially alter these associations. One perspective of the present results may be to prompt a reconsideration of current sodium reduction recommendations.
Empagliflozin suppresses hedgehog pathway, alleviates ER stress, and ameliorates hepatic fibrosis in rats
Authors: Abdalla Nourihan , Abo-ElMatty Dina M. , Saleh Sami , Ghattas Maivel H. , Omar Nesreen Nabil 
Published: November 2023

AbstractWorldwide mortality from hepatic fibrosis remains high, due to hepatocellular carcinoma and end stage liver failure. The progressive nature of hepatic fibrosis from inflammation to cicatrized tissues warrants subtle intervention with pharmacological agents that hold potential. Empagliflozin (Empa), a novel hypoglycemic drug with antioxidant and anti-inflammatory properties, has lately been proposed to have additional antifibrotic activities. In the current study, we examined the antifibrotic effect of the Empa through modulating the activity of hepatic stellate cells by hedgehog (Hh) pathway. We also assessed the markers of inflammatory response and endoplasmic reticulum (ER) stress. Male Albino rats were treated with either CCl4 (0.4 mg/kg twice/week) and/or Empa (10 mg/kg/day) for eight weeks. In this study, CCl4 rats had active Hh signaling as indicated by overexpression of Patched 1, Smoothened and Glioblastoma-2. CCl4 induced ER stress as CHOP expression was upregulated and ERAD was downregulated. CCl4-induced inflammatory response was demonstrated through increased levels of TNF-α, IL-6 and mRNA levels of IL-17 while undetectable expression of IL-10. Conversely, Empa elicited immunosuppression, suppressed the expression of Hh markers, and reversed markers of ER stress. In conclusion, Empa suppressed CCl4-induced Hh signaling and proinflammatory response, meanwhile embraced ER stress in the hepatic tissues, altogether provided hepatoprotection.
A gut microbial metabolite of linoleic acid ameliorates liver fibrosis by inhibiting TGF-β signaling in hepatic stellate cells
Authors: Kasahara Nanaho , Imi Yukiko , Amano Reina , Shinohara Masakazu , Okada Kumiko , Hosokawa Yusei , Imamori Makoto , Tomimoto Chiaki , Kunisawa Jun , Kishino Shigenobu , Ogawa Jun , Ogawa Wataru , Hosooka Tetsuya 
Published: November 2023

AbstractThe antidiabetic drug pioglitazone ameliorates insulin resistance by activating the transcription factor PPARγ. In addition to its blood glucose–lowering action, pioglitazone exerts pleiotropic effects including amelioration of nonalcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH). The mechanism by which pioglitazone achieves this latter effect has remained unclear, however. We here show that pioglitazone administration increases the amount of linoleic acid (LA) metabolites in adipose tissue of KK-Ay mice. These metabolites are produced by lactic acid bacteria in the gut, and pioglitazone also increased the fraction of Lactobacillus in the gut microbiota. Administration of the LA metabolite HYA (10-hydroxy-cis-12-octadecenoic acid) to C57BL/6 J mice fed a high-fat diet improved liver histology including steatosis, inflammatory cell infiltration, and fibrosis. Gene ontology analysis of RNA-sequencing data for the liver revealed that the top category for genes downregulated by HYA treatment was related to extracellular matrix, and the expression of individual genes related to fibrosis was confirmed to be attenuated by HYA treatment. Mechanistically, HYA suppressed TGF-β–induced Smad3 phosphorylation and fibrosis-related gene expression in human hepatic stellate cells (LX-2). Our results implicate LA metabolites in the mechanism by which pioglitazone ameliorates liver fibrosis, and they suggest that HYA is a potential therapeutic for NAFLD/NASH.
A community partitioning algorithm for cyberspace
Authors: Qi Kai , Zhang Heng , Zhou Yang , Liu Yifan , Li Qingxiang 
Published: November 2023

AbstractCommunity partitioning is an effective technique for cyberspace mapping. However, existing community partitioning algorithm only uses the topological structure of the network to divide the community and disregards factors such as real hierarchy, overlap, and directionality of information transmission between communities in cyberspace. Consequently, the traditional community division algorithm is not suitable for dividing cyberspace resources effectively. Based on cyberspace community structure characteristics, this study introduces an algorithm that combines an improved local fitness maximization (LFM) algorithm with the PageRank (PR) algorithm for community partitioning on cyberspace resources, called PR-LFM. First, seed nodes are determined using degree centrality, followed by local community expansion. Nodes belonging to multiple communities undergo further partitioning so that they are retained in the community where they are most important, thus preserving the community’s original structure. The experimental data demonstrate good results in the resource division of cyberspace.
HLA allele-calling using multi-ancestry whole-exome sequencing from the UK Biobank identifies 129 novel associations in 11 autoimmune diseases
Authors: Butler-Laporte Guillaume , Farjoun Joseph , Nakanishi Tomoko , Lu Tianyuan , Abner Erik , Chen Yiheng , Hultström Michael , Metspalu Andres , Milani Lili , Mägi Reedik , Nelis Mari , Hudjashov Georgi ,   Estonian Biobank Research Team, Yoshiji Satoshi , Ilboudo Yann , Liang Kevin Y. H. , Su Chen-Yang , Willet Julian D. S. , Esko Tõnu , Zhou Sirui , Forgetta Vincenzo , Taliun Daniel , Richards J. Brent 
Published: November 2023

AbstractThe human leukocyte antigen (HLA) region on chromosome 6 is strongly associated with many immune-mediated and infection-related diseases. Due to its highly polymorphic nature and complex linkage disequilibrium patterns, traditional genetic association studies of single nucleotide polymorphisms do not perform well in this region. Instead, the field has adopted the assessment of the association of HLA alleles (i.e., entire HLA gene haplotypes) with disease. Often based on genotyping arrays, these association studies impute HLA alleles, decreasing accuracy and thus statistical power for rare alleles and in non-European ancestries. Here, we use whole-exome sequencing (WES) from 454,824 UK Biobank (UKB) participants to directly call HLA alleles using the HLA-HD algorithm. We show this method is more accurate than imputing HLA alleles and harness the improved statistical power to identify 360 associations for 11 auto-immune phenotypes (at least 129 likely novel), leading to better insights into the specific coding polymorphisms that underlie these diseases. We show that HLA alleles with synonymous variants, often overlooked in HLA studies, can significantly influence these phenotypes. Lastly, we show that HLA sequencing may improve polygenic risk scores accuracy across ancestries. These findings allow better characterization of the role of the HLA region in human disease.
Learning continuous models for continuous physics
Authors: Krishnapriyan Aditi S. , Queiruga Alejandro F. , Erichson N. Benjamin , Mahoney Michael W. 
Published: November 2023

AbstractDynamical systems that evolve continuously over time are ubiquitous throughout science and engineering. Machine learning (ML) provides data-driven approaches to model and predict the dynamics of such systems. A core issue with this approach is that ML models are typically trained on discrete data, using ML methodologies that are not aware of underlying continuity properties. This results in models that often do not capture any underlying continuous dynamics—either of the system of interest, or indeed of any related system. To address this challenge, we develop a convergence test based on numerical analysis theory. Our test verifies whether a model has learned a function that accurately approximates an underlying continuous dynamics. Models that fail this test fail to capture relevant dynamics, rendering them of limited utility for many scientific prediction tasks; while models that pass this test enable both better interpolation and better extrapolation in multiple ways. Our results illustrate how principled numerical analysis methods can be coupled with existing ML training/testing methodologies to validate models for science and engineering applications.
A proposal on centralised and distributed optimisation via proportional–integral–derivative controllers (PID) control perspective
Authors: Liu Jiaxu , Chen Song , Cai Shengze , Xu Chao 
Published: November 2023

AbstractMotivated by the excellent performance of proportional–integral–derivative controllers (PIDs) in the field of control, the authors injected the philosophy of PID into optimisation and introduced two types of novel PID optimisers from a continuous‐time view, which benefit from the idea that discrete‐time optimisation algorithm can be modelled as a continuous dynamical system/controlled system. For centralised optimisation, the authors discuss the idea of the first‐order PID optimiser and the second‐order accelerated PID optimiser. Furthermore, this framework is extended into distributed optimisation settings, and a distributed PID optimiser is proposed. Finally, some numerical examples are given to verify our ideas.
Adaptive fuzzy fault‐tolerant control for cooperative output regulation with unknown nonlinear disturbances and actuator faults
Authors: Liu Aoxiang , Wang Zinan , Xu Jiacan , Li Penghua , Miao Jianguo 
Published: November 2023

AbstractThe cooperative output regulation problem with actuator faults and unknown nonlinear disturbances is a challenging research area in multi‐agent systems. This paper proposes an adaptive fuzzy fault‐tolerant controller to address this problem by employing a fuzzy logic system for approximating the unknown nonlinear disturbances. The internal model principle is utilized to transform the cooperative output regulation problem into a stability problem of an auxiliary system, with the aim of compensating for actuator failures in the system. By incorporating fuzzy logic system, the adaptive controller is able to approximate and compensate for the unknown nonlinear disturbances. Extensive simulations are conducted to validate the robustness and performance of the proposed method. The adaptive controller effectively handles actuator faults and achieves output regulation with unknown nonlinear disturbances.
Improved triplet loss for domain adaptation
Authors: Wang Xiaoshun , Li Yunhan , Zhang Xiangliang 
Published: November 2023

AbstractA technique known as domain adaptation is utilised to address classification challenges in an unlabelled target domain by leveraging labelled source domains. Previous domain adaptation approaches have predominantly focussed on global domain adaptation, neglecting class‐level information and resulting in suboptimal transfer performance. In recent years, a considerable number of researchers have explored class‐level domain adaptation, aiming to precisely align the distribution of diverse domains. Nevertheless, existing research on class‐level alignment tends to align domain features either on or in proximity to classification boundaries, which introduces ambiguous samples that can impact classification accuracy. In this study, the authors propose a novel strategy called class guided constraints (CGC) to tackle this issue. Specifically, CGC is employed to preserve the compactness within classes and separability between classes of domain features prior to class‐level alignment. Furthermore, the authors incorporate CGC in conjunction with similarity guided constraint. Comprehensive evaluations conducted on four public datasets demonstrate that our approach outperforms numerous state‐of‐the‐art domain adaptation methods significantly and achieves greater improvements compared to the baseline approach.
Compact folded‐shorted patch array offering dual‐band operation and dual‐circularly polarized radiation for picosatellites and other small satellites
Authors: Alshammari Bandar , Alrushud Khalid M. , Li Yuepei , Podilchak Symon K. 
Published: November 2023

AbstractThe development of a dual‐band folded shorted patch (FSP) antenna array is presented which offers dual‐circularly polarized radiation. Applications include small satellites like CubeSats and picosatellites. The proposed 2 × 2 FSP array design operates at 1.1 and 2.4 GHz and offers good radiation performance in terms of minimal reflection coefficient losses, broad beamwidths (which is generally required for low gain antenna structures ensuring link connectivity), as well as low cross‐polarization levels. The antenna array consists of a meandered layer defining the top of the FSPs. The shorting and folding technique as well as the noted meandering allows further size reduction of the quarter‐wavelength patch. In particular, the proposed antenna array is compact with a total size of 50 mm by 50 mm (or 0.18λ by 0.18λ at the lower operational frequency). An eight‐port coaxial and microstrip feed system is integrated onto the backside of the antenna ground plane, two ports for each element, and with external phase feeding of 90°, dual‐circularly polarized is made possible for the compact antenna unit. To the best knowledge of the authors, no similar antenna structure has been designed, manufactured and tested being useful for picosatellites and other small satellites.
DeepFake detection against adversarial examples based on D‐VAEGAN
Authors: Chen Ping , Xu Ming , Qi Jianxiang 
Published: November 2023

AbstractRecent years, the development of DeepFake has raise a lot of security problems. Therefore, detection of DeepFake is critical. However, the existing DeepFake detection methods are often vulnerable to adversarial attacks, i.e. adding carefully crafted imperceptible perturbations into forged images is possible to evade detection. In this paper, a DeepFake detection method based on image denoising is proposed by combining variational autoencoder (VAE) and generative adversarial network (GAN), namely D‐VAEGAN. Firstly, an encoder is designed to extract the features of the image in a low‐dimensional latent space. Then, a decoder reconstructs the original clean image using the features in this low‐dimensional latent space. Secondly, an auxiliary discriminative network is introduced to further improve the performance of the model, which improves the quality of the reconstructed images. Furthermore, feature similarity loss is added as a penalty term to the reconstruction optimization function to improve the adversarial robustness. Experimental results on the FaceForensics++ dataset show that the proposed approach significantly outperforms the five adversarial training‐based defence methods. The approach achieves 96% in accuracy, which is on average about 50% higher than other comparison methods.
Bridge bottom crack detection and modeling based on faster R‐CNN and BIM
Authors: Gan Linfeng , Liu Hu , Yan Yue , Chen Aoran 
Published: November 2023

AbstractThe bridge bottom crack detection provides important state information for bridge disease control and safety assessment. This paper proposes a detection method based on deep learning Faster R‐CNN and BIM (Building Information Modeling). The UAV (Unmanned Aerial Vehicle) was used for close aerial photography to obtain high‐resolution crack images of the concrete surface at the bottom of a bridge. Through deep learning algorithms, a Faster R‐CNN model is trained and established for crack identifications. The crack identification accuracy rate and recall rate reach 92.03% and 96.54%, respectively. Crack images are mapped to a BIM model developed for the chosen bridge, and the box girder family with cracks and the three crack families of transverse cracks, longitudinal cracks and turtle cracks are established. The cracks are located and the visualization of the beam bridge with cracks was completed. In order to better assess the health condition of the bridge. The results show that the combination of UAV bridge crack detection and modelling solves the remote, visual and automated detection of cracks on the surface of bridge structures, which are difficult to reach manually, and has important scientific research and engineering application value.
Synthesis of Modified C-Nucleosides of Therapeutic Significant: A Succinct Account
Authors: Mukherjee Debaraj , Hudait Nandagopal , Sakander Norein , Kundu Sanchari , Rasool Bisma , Sengupta Jhimli 
Published: November 2023

AbstractSince their discovery in the 1950s, C-nucleosides have piqued the interest of both biologists and medicinal chemists. In this regard, C-nucleosides and their synthetic analogues have resulted in promising leads in drug design. Concurrently, advances in chemical syntheses have contributed to structural diversity and drug discovery efforts. Convergent and modular approaches to synthesis have gained much attention in this regard. Among them nucleophilic substitution at C-1 has seen wide applications, providing flexibility in synthesis, good yields, the ability to maneuver stereochemistry as well as to incorporate structural modifications. In this account, we briefly discuss the modular synthesis of C-nucleosides with a focus on mechanistic studies and sugar modifications that have resulted in potent lead molecules. Meanwhile, various FDA-approved C-nucleoside analogues have been reported previously for their antiviral and/or anticancer potential, with examples being pyrazomycin, remdesivir, pseudouridine, and pseudouridimycin.1	Introduction and Motivation2	Strategies for the Synthesis of C-Nucleosides3	Biologically Active C-Nucleosides4	Mechanistic Analysis of C-Nucleoside Formation5	Synthesis and Manipulation of Medicinally Important C-Nucleoside Analogues6	C-Nucleosides: Synthesis of C–C Bonds with a C-1′ Base7	Conclusion
Discursive representations of sexual minorities in China’s English-language news media: a corpus-based study
Authors: Zhang Ke , Zhuang Huibin , Lu Chao , Zhang Jingyuan 
Published: November 2023

AbstractIn contemporary China, sexual minorities (SMs) are still a marginalized community. Prior studies have accorded SMs a great deal of attention, but little research has been conducted on the representations of lesbian, gay, bisexual, and trans people in Chinese English-language news media. This article uses corpus linguistic tools to examine popular views on SMs in a larger corpus of 354 news articles, filling the gap in research. Based on data collected from four English-language newspapers in mainland China and informed by discursive strategies, the article concludes that Chinese SMs are prominently represented as unhealthy individuals, but also victims and progressionists. The findings also indicate that conservative and liberal perspectives on SMs co-exist in the English-language newspapers. In addition, potential contributing factors to these representations are discussed.
Subject integration and theme evolution of STEM education in K-12 and higher education research
Authors: Zhan Zehui , Niu Shijing 
Published: November 2023

AbstractOver the past two decades, the field of STEM education has produced a wealth of research findings. This study systematically reviewed the published literature from the perspective of subject integration and theme evolution, considering both K-12 and higher education. It was found that STEM education originated from higher education, but the main emphasis is gradually shifting to the K-12 stage. There were mainly sixteen subjects involved in STEM education, showing the gradual in-depth integration of science, engineering, technology, math, humanities, and social sciences, in which humanism is increasingly emphasized. Culture is a new perspective for understanding the diversity of participants, which also gives STEM education a distinctive regional character. In addition, in the K-12 stage, research related to computer science and art stands out alongside the four main subjects, demonstrating relatively even distribution across research themes. Conversely, in higher education, engineering, and chemistry garner considerable attention, with research themes predominantly concentrated on learning outcomes and social relevance. On a holistic scale, researchers exhibit a pronounced interest in learning outcomes, yet relatively less emphasis is placed on pedagogical aspects. Regarding prospective trends, there should be a heightened focus on the cultivation of students’ thinking competencies, students’ career development, and pedagogy.