bluuebunny/crossref_metadata_2025_split huggingface dataset:
All-trans retinoic acid alleviates collagen-induced arthritis and promotes intestinal homeostasis
Authors: Zhang Yiqi , Luo Yating , Shi Jiangchun , Xie Yumeng , Shao Huangfang , Li Yun 
Published: January 2024

AbstractAll-trans retinoic acid (ATRA) has emerged as a promising adjunctive treatment for rheumatoid arthritis. However, the mechanism by which ATRA mitigates arthritis remains unclear. In this study, we aimed to explore ATRA alleviation of arthritis and the role of ATRA in regulating intestinal homeostasis. Thus, we established a collagen-induced arthritis (CIA) model in Wistar rats. After 6 weeks of ATRA treatment, the arthritis index of CIA rats decreased, synovial inflammation was alleviated, and the disruption of Th17/Treg differentiation in peripheral blood was reversed. Additionally, the Th17/Treg ratio in the mesenteric lymph nodes decreased and the expression of Foxp3 mRNA increased and that of IL-17 mRNA decreased in the colon and ileum. Microscopically, we observed reduced intestinal inflammation. Transmission electron microscopy revealed that ATRA could repair tight junctions, which was accompanied by an increase in the expression of Claudin-1, Occludin and ZO-1. Moreover, ATRA regulated the composition of the gut microbiota, as was characterized based on the reduced abundance of Desulfobacterota and the increased abundance of Lactobacillus. In conclusion, ATRA demonstrates the potential to alleviate arthritis in CIA rats, which might be correlated with modulating the gut microbiota and regulating the intestinal immune response. Our findings provide novel insights into ATRA-mediated alleviation of arthritis.
Surface roughness characterization using representative elementary area (REA) analysis
Authors: Singh Kuldeep , Paliwal Nitin , Kasamias Konstantinos 
Published: January 2024

AbstractWe proposed the Representative Elementary Area (REA) analysis method and illustrated how it is needed to evaluate representative roughness parameters of surfaces. We used mean height (Sa) roughness to study how its variations converge to a steady state as we expanded the area of investigation (AOI) using combined scan tiles obtained through Confocal Laser Scanning Microscopy. We tested quartz and glass surfaces, subjecting them to various levels of polishing with grit sizes ranging between # 60 and #1200. The scan tiles revealed a multiscale roughness texture characterized by the dominance of valleys over peaks, lacking a fractal nature. REA analysis revealed Sa variations converged to a steady state as AOI increased, highlighting the necessity of the proposed method. The steady-state Sa, denoted as $${{\text{Sa}}}_{{\text{REA}}}$$

Sa
REA

, followed an inverse power law with polishing grit size, with its exponent dependent on the material hardness. The REA length representing $${{\text{Sa}}}_{{\text{REA}}}$$

Sa
REA

of glass surfaces, followed another inverse power law with polishing grit size and an indeterminate relationship for quartz surfaces. The multiscale characteristics and convergence to steady state were also evident in skewness, kurtosis, and autocorrelation length (Sal) parameters. Sal increased to a maximum value before decreasing linearly as AOI was linearly increased. The maximum Sal, termed as $${{\text{Sal}}}_{{\text{max}}}$$

Sal
max

, exhibited a linear relationship with REA. In the absence of REA analysis, the magnitude of uncertainty depended on the polishing grit size. Finely polished surfaces exhibited a 10–20% variability, which increased to up to 70% relative to the steady-state Sa with coarser polishing.
Explainable artificial intelligence approaches for COVID-19 prognosis prediction using clinical markers
Authors: Chadaga Krishnaraj , Prabhu Srikanth , Sampathila Niranjana , Chadaga Rajagopala , Umakanth Shashikiran , Bhat Devadas , G S Shashi Kumar 
Published: January 2024

AbstractThe COVID-19 influenza emerged and proved to be fatal, causing millions of deaths worldwide. Vaccines were eventually discovered, effectively preventing the severe symptoms caused by the disease. However, some of the population (elderly and patients with comorbidities) are still vulnerable to severe symptoms such as breathlessness and chest pain. Identifying these patients in advance is imperative to prevent a bad prognosis. Hence, machine learning and deep learning algorithms have been used for early COVID-19 severity prediction using clinical and laboratory markers. The COVID-19 data was collected from two Manipal hospitals after obtaining ethical clearance. Multiple nature-inspired feature selection algorithms are used to choose the most crucial markers. A maximum testing accuracy of 95% was achieved by the classifiers. The predictions obtained by the classifiers have been demystified using five explainable artificial intelligence techniques (XAI). According to XAI, the most important markers are c-reactive protein, basophils, lymphocytes, albumin, D-Dimer and neutrophils. The models could be deployed in various healthcare facilities to predict COVID-19 severity in advance so that appropriate treatments could be provided to mitigate a severe prognosis. The computer aided diagnostic method can also aid the healthcare professionals and ease the burden on already suffering healthcare infrastructure.
Seepage stability analysis of geogrid reinforced tailings dam
Authors: Du Changbo , Tao Han , Yi Fu 
Published: January 2024

AbstractTo investigate the influence of a geogrid-reinforced tailings dam on the seepage stability of the dam body, this paper was based on the field test of a reinforced tailings accumulation dam. The study utilized the finite element strength reduction method to simulate the stability of the main dam of the Fengshuigou tailings reservoir under different seepage conditions using ABAQUS software. Additionally, the paper discussed the impact of conventional heightening, dry beach length, and geogrid reinforcement on the position and safety factor of the saturation line of the dam body. The results showed that when the dam body was raised, the saturation line rose by 2.8–5.3 m, resulting in a decrease in the safety factor. The geogrid effectively reduced the height of the saturation line in the tailings dam. In comparison to the unreinforced condition (dam heightening), the saturation line of the tailings dam decreased by 0.9–2.8 m under the local reinforcement condition and by 3.2–12.5 m under the overall reinforcement condition. The geogrid significantly improved the stability of the tailings dam. Furthermore, under the local reinforcement condition, the safety factor of the dam increased by 3.8–5.5%, and under the overall reinforcement condition, it increased by 35.9–42.9%, when compared to the unreinforced condition. Increasing the dry beach length improved the stability of the tailings dam, and under normal working conditions, the safety of the tailings dam was much higher than under the minimum dry beach condition. These results served as a reference for the design of the dam and the new tailings reservoir, laying a foundation for the sustainable development and environmental protection of the tailings pond.
Sea surface temperature warming to inhibit mitigation of tropical cyclone destructiveness over East Asia in El Niño
Authors: Park Doo-Sun R. , Seo Eunkyo , Lee Minkyu , Cha Dong-Hyun , Kim Dasol , Ho Chang-Hoi , Lee Myong-In , Kim Hyeong-Seog , Min Seung-Ki 
Published: January 2024

AbstractGiven their conditions to reside in and intensify longer over warm oceans, tropical cyclones (TCs) in the western North Pacific (WNP) present a stronger lifetime maximum intensity during El Niño than during La Niña. By using observational data, we found that the anomalously cool sea surface temperature (SST)s in the basin act as effective barriers against intense TCs approaching East Asia during El Niño, weakening their destructiveness at landfall. Based on our high-resolution pseudo-global-warming simulations, the basin-wide 2K SST warming within the WNP basin can, however, shatter this cool SST barrier, exposing East Asia to more destructive TCs during El Niño, compared to those during La Niña. Considering that the 2K warmer WNP will likely occur in the mid-21st century under a high emission scenario and in the late 21st century under a moderate emission scenario, our findings support that more aggressive efforts of global warming mitigation are needed.
Development of a stemness-related prognostic index to provide therapeutic strategies for bladder cancer
Authors: Fu Shi , Tan Zhiyong , Shi Hongjin , Chen Junhao , Zhang Yawei , Guo Chunming , Feng Wei , Xu Haole , Wang Jiansong , Wang Haifeng 
Published: January 2024

AbstractBladder cancer (BC) is a heterogeneous disease with varying clinical outcomes. Recent evidence suggests that cancer progression involves the acquisition of stem-like signatures, and assessing stemness indices help uncover patterns of intra-tumor molecular heterogeneity. We used the one-class logistic regression algorithm to compute the mRNAsi for each sample in BLCA cohort. We subsequently classified BC patients into two subtypes based on 189 mRNAsi-related genes, using the unsupervised consensus clustering. Then, we identified nine hub genes to construct a stemness-related prognostic index (SRPI) using Cox regression, LASSO regression and Random Forest methods. We further validated SRPI using two independent datasets. Afterwards, we examined the molecular and immune characterized of SRPI. Finally, we conducted multiply drug screening and experimental approaches to identify and confirm the most proper agents for patients with high SRPI. Based on the mRNAsi-related genes, BC patients were classified into two stemness subtypes with distinct prognosis, functional annotations, genomic variations and immune profiles. Using the SRPI, we identified a specific subgroup of BC patients with high SRPI, who had a poor response to immunotherapy, and were less sensitive to commonly used chemotherapeutic agents, FGFR inhibitors, and EGFR inhibitors. We further identified that dasatinib was the most promising therapeutic agent for this subgroup of patients. This study provides further insights into the stemness classification of BC, and demonstrates that SRPI is a promising tool for predicting prognosis and therapeutic opportunities for BC patients.
Towards precision oncology discovery: four less known genes and their unknown interactions as highest-performed biomarkers for colorectal cancer
Authors: Liu Yongjun , Xu Yuqing , Li Xiaoxing , Chen Mengke , Wang Xueqin , Zhang Ning , Zhang Heping , Zhang Zhengjun 
Published: January 2024

AbstractThe goal of this study was to use a new interpretable machine-learning framework based on max-logistic competing risk factor models to identify a parsimonious set of differentially expressed genes (DEGs) that play a pivotal role in the development of colorectal cancer (CRC). Transcriptome data from nine public datasets were analyzed, and a new Chinese cohort was collected to validate the findings. The study discovered a set of four critical DEGs - CXCL8, PSMC2, APP, and SLC20A1 - that exhibit the highest accuracy in detecting CRC in diverse populations and ethnicities. Notably, PSMC2 and CXCL8 appear to play a central role in CRC, and CXCL8 alone could potentially serve as an early-stage marker for CRC. This work represents a pioneering effort in applying the max-logistic competing risk factor model to identify critical genes for human malignancies, and the interpretability and reproducibility of the results across diverse populations suggests that the four DEGs identified can provide a comprehensive description of the transcriptomic features of CRC. The practical implications of this research include the potential for personalized risk assessment and precision diagnosis and tailored treatment plans for patients.
High-resolution assessment of multidimensional cellular mechanics using label-free refractive-index traction force microscopy
Authors: Lee Moosung , Jeong Hyuntae , Lee Chaeyeon , Lee Mahn Jae , Delmo Benedict Reve , Heo Won Do , Shin Jennifer H. , Park YongKeun 
Published: January 2024

AbstractA critical requirement for studying cell mechanics is three-dimensional assessment of cellular shapes and forces with high spatiotemporal resolution. Traction force microscopy with fluorescence imaging enables the measurement of cellular forces, but it is limited by photobleaching and a slow acquisition speed. Here, we present refractive-index traction force microscopy (RI-TFM), which simultaneously quantifies the volumetric morphology and traction force of cells using a high-speed illumination scheme with 0.5-Hz temporal resolution. Without labelling, our method enables quantitative analyses of dry-mass distributions and shear (in-plane) and normal (out-of-plane) tractions of single cells on the extracellular matrix. When combined with a constrained total variation-based deconvolution algorithm, it provides 0.55-Pa shear and 1.59-Pa normal traction sensitivity for a 1-kPa hydrogel substrate. We demonstrate its utility by assessing the effects of compromised intracellular stress and capturing the rapid dynamics of cellular junction formation in the spatiotemporal changes in non-planar traction components.
Strain-tunable Dirac semimetal phase transition and emergent superconductivity in a borophane
Authors: Zhong Chengyong , Li Xuelian , Yu Peng 
Published: January 2024

AbstractA two-dimensional (2D) Dirac semimetal with concomitant superconductivity has been long sought but rarely reported. It is believed that light-element materials have the potential to realize this goal owing to their intrinsic lightweight and metallicity. Here, based on the recently synthesized β12 hydrogenated borophene, we investigate its counterpart named β12-B5H3. Our first-principles calculations suggest it has good stability. β12-B5H3 is a scarce Dirac semimetal demonstrating a strain-tunable phase transition from three Dirac cones to a single Dirac cone. Additionally, β12-B5H3 is also a superior phonon-mediated superconductor with a superconducting critical temperature of 32.4 K and can be further boosted to 42 K under external strain. The concurrence of Dirac fermions and superconductivity, supplemented with dual tunabilities, reveals β12-B5H3 is an attractive platform to study either quantum phase transition in 2D Dirac semimetal or the superconductivity or the exotic physics brought about by their interplay.
Injection spectroscopy of momentum state lattices
Authors: Paladugu Sai Naga Manoj , Chen Tao , An Fangzhao Alex , Yan Bo , Gadway Bryce 
Published: January 2024

AbstractThe energy spectrum of quantum systems contain a wealth of information about their underlying properties. Spectroscopic techniques, especially those with access to spatially resolved measurements, can be challenging to implement in real-space systems of cold atoms in optical lattices. Here we explore a technique for probing energy spectra in synthetic lattices that is analogous to scanning tunneling microscopy. Using one-dimensional synthetic lattices of coupled atomic momentum states, we explore this spectroscopic technique and observe qualitative agreement between the measured and simulated energy spectra for small two- and three-site lattices as well as a uniform many-site lattice. Finally, through simulations, we show that this technique should allow for the exploration of the topological bands and the fractal energy spectrum of the Hofstadter model as realized in synthetic lattices.
Underplated melts control sulfide segregation at the continental crust-mantle transition
Authors: Pieterek Bartosz , Tribuzio Riccardo , Matusiak-Małek Magdalena , Ciążela Jakub , Horn Ingo , Weyer Stefan , Strauss Harald , Kuhn Thomas , Muszyński Andrzej 
Published: January 2024

AbstractExposures of the Earth’s crust-mantle transition are scarce, thus, limiting our knowledge about the formation of subcontinental underplate cumulates, and their significance for metal storage and migration. Here, we investigated chalcophile metals to track sulfide crystallization within the Contact Series, an <150-m-thick pyroxenite-gabbronorite sequence, formed by mantle-derived melts, highlighting the boundary between the Balmuccia mantle peridotite and gabbronoritic Mafic Complex of the Ivrea-Verbano Zone. Within the Contact Series, numerous sulfides crystallized in response to the differentiation of mantle-derived underplated melts. Such sulfide-controlled metal differentiation resulted in anomalous Cu contents (up to ~380 ppm), compared to reference mantle (~19 ppm) and crustal samples (~1 ppm). We propose that the assimilation of continental crust material is a critical mechanism driving sulfide segregation and sulfide-controlled metal storage. Our results evidence that sulfides are trapped in the underplated mafic-ultramafic cumulates and that their enrichment in Cu may provide essential implications for crustal metallogeny.
An efficient implementation for linear convolution with reduced latency in FPGA
Authors: Xue Dingli , DeBrunner Linda S. , DeBrunner Victor , Huang Zhen , Xiao Ying , Zhang Zhaohang 
Published: January 2024

AbstractA recently developed linear convolution filter based on Hirschman theory has shown its advantage in saving computations compared with other convolution filters. Here, the Hirschman convolution filter is improved with the use of the split‐radix algorithm and explore its latency‐reduced advantage for the first time. A comparison of hardware resources in Field Programmable Gate Array (FPGA) between the proposed Hirschman‐based filter and other convolution filters is presented. Simulation results indicate that the split‐radix Hirschman convolution filter achieves a promising reduction in latency by 18.15% on average with an acceptable power consumption rise by about 3.05%. In the case of a device capacity limited implementation, the proposed Hirschman convolution filter is still computationally attractive as it uses a small‐size originator function instead of larger Fourier transform.
Utility‐scale solar photovoltaic power plant emulating a virtual synchronous generator with simultaneous frequency and voltage control provision
Authors: Owais Raja , Javed Iqbal Sheikh 
Published: January 2024

AbstractNetwork operators with significant solar photovoltaic (PV) penetration are having difficulty maintaining grid frequency and voltage within acceptable bounds due to the progressive displacement of synchronous machines. Utility‐scale solar PV plants have a huge potential for participation in frequency and voltage regulation since they are linked to the grid through power electronic interfaces with flexible, decoupled control of active and reactive power. A comprehensive control strategy for a utility‐scale solar PV plant is proposed to simultaneously participate in frequency and voltage control without the aid of any energy storage. The frequency response is accomplished by maintaining some active power reserves that enable the PV plant to participate in both over‐ and under‐frequency events. The active power of the PV plant is modulated by operating the PV as a virtual synchronous generator (VSG). Unlike the classic notion of VSG, an intelligent fuzzy‐based technique is employed to adapt the gains of the VSG controller for improved control performance. Additionally, an adaptive droop‐based voltage control mechanism is proposed to control the reactive power reference for the PV plant. The gain of the droop controller is adapted to the varying maximum reactive power capacity of the PV plant. This ensures that the PV system's unused reactive power capability is fully utilised. Through simulation studies, the efficiency of the proposed frequency and voltage control mechanisms is validated under a range of realistic circumstances. The findings show that the suggested control approach can efficiently leverage the PV plants' capacity to handle both frequency and voltage events.
Frequency support scheme of grid‐forming based hybrid cascaded HVDC integrated wind farms
Authors: Fan Xiaojie , Chi Yongning , Wang Zhibing 
Published: January 2024

AbstractThe grid‐following control‐based hybrid cascaded high‐voltage direct current (HC‐HVDC) links may contribute to the worsening of inertia decline and instability issues, especially in situations characterized by a weak grid. To address the challenge, this paper proposes a grid‐forming (GFM) based optimal frequency support scheme (OFSS) for HC‐HVDC integrated wind farms. Firstly, a GFM control for hybrid converter is proposed and its stability under weak grid conditions is evaluated through a small‐signal model. Then, DC current–voltage droop control is introduced to the line commutated converter (LCC). This control approach ensures the consistency of reactive power in the LCC by regulating the DC voltage and current in the same direction, thereby mitigating AC voltage fluctuations. It also facilitates active power control in the LCC in response to grid frequency variations. Furthermore, the OFSS can convey the frequency of receiving‐end grid to the rectifier and wind farms without communication for precise power control. Finally, to validate the effectiveness of OFSS, a point‐to‐point HC‐HVDC and a 4‐machine test model are constructed on PSCAD/EMTDC. The OFSS significantly enhances the frequency support capability of HC‐HVDC links and improves the robustness in weak grid.
Fuse saving coordination scheme for active distribution systems: State‐of‐the‐art and a novel quasi‐voltage current based scheme
Authors: Bisheh Hadi , Fani Bahador , Shahgholian Ghazanfar , Sadeghkhani Iman 
Published: January 2024

AbstractIncreasing the penetration level of distributed generation (DG) units requires overcoming the technical challenges associated with their integration into the distribution systems, especially protection problems. Change in the current profile of the distribution system due to the presence of DG units disrupts the operation of the conventional fuse saving coordination (FSC) scheme. The first objective of this paper is to provide an overview of the state‐of‐the‐art of FSC schemes in distribution systems with distributed generators that has not been systematically presented yet. In addition to comparing the features of reliability, cost, speed, implementation, calculation burden, and requirements, the impact of presence of distributed generations on the performance of the conventional FSC scheme is investigated in details. The second objective of this paper is to propose an FSC restoration scheme for minimizing the challenges of previous works. Using a quasi‐voltage current term, the proposed scheme modifies the adjustable time coefficient of the recloser in two ways of pro and plus. The former scheme provides an approximate FSC with a simple setting while the latter scheme provides complete coordination at the expense of a more complex setting. No need for voltage measurement makes its implementation practical in available distribution systems. The effective performance of the proposed FSC scheme is verified through extensive simulation studies in the ETAP environment.