bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of the seismic isolation characteristics of the overall friction pendulum bearing (OFPB) of a pagoda under three types of seismic actions
Authors: He Qing , Liu Dewen , Lei Min , Li Xiaopeng , Wu Haoxuan 
Published: August 2024

Abstract

In this study, the seismic performance of an ancient pagoda with significant historical and cultural values in China is upgraded by using overall friction pendulum bearing (OFPB) seismic isolation technology. By implementing the OFPB seismic isolation retrofit on the pagoda and comparing and analyzing it with the unretrofitted seismic model, the response of the pagoda under the action of nine seismic waves of three types, namely, near-field earthquakes, far-field earthquakes, and common earthquakes, is investigated. The results show that the OFPB seismic isolation technique significantly reduces the seismic response of the ghats, in which the acceleration amplification factor is reduced by a maximum of 82.46%, the inter-story displacement is reduced by a maximum of 85.15%, and the base shear force is reduced by a maximum of 96.76%. In addition, the tensile damage of the ghats with OFPB seismic isolation was significantly controlled. While the model without seismic isolation has serious damage under the same seismic action and even faces the risk of collapse. The results of the study confirm that the OFPB seismic isolation technology plays a key role in improving the seismic performance of the tower, which is of great theoretical and practical significance to the protection of the tower, and provides an effective technical way for the protection of the tower in the seismic-prone areas.
Using Borda and Bargaining algorithms to prioritize potential contamination of springs
Authors: Haghizadeh Ali , Hassanvand Mahsa , kamarhei Bahram , Ghasemi Leila 
Published: August 2024

Abstract

The selection of an optimal decision-making method for water resource management is important and necessary. In this context, game theory makes a significant contribution to the advancement of decision-making for achieving optimal outcomes due to its high efficiency in solving multi-objective problems and offering diverse modeling techniques. In this study, the prioritization of potential contamination of springs in Khorramabad was considered, and by using the Borda and bargaining algorithms in game theory, the most effective parameters and the most critical resources in terms of potential contamination were identified. Various parameters, including pH, NO3 and etc., were collected and calculated for studied springs and entered into the algorithms based on their importance in creating pollution potential. The Landsat 8 satellite's OLI sensor with an imagery date of 2017 was utilized to generate a LU/LC map for the region. By employing the Borda scoring method, the CO3, K, and HCO3 parameters were the most effective, with scores of 232, 157.5 and 153.5, respectively. Implementing the bargaining algorithm, CO3, K, and pH parameters were the most effective, with scores of 254, 177 and 165, respectively. Finally, the prioritization of water resources was presented using both methods. In the Borda method, the Golestan and Qeyu, springs were ranked first. implementing the bargaining algorithm, the Qeyu and Dareh-Saki springs are ranked as top priorities. Which of these methods is more suitable for groundwater resource management, according to its guiding principles, depends on the preferences of the decision-makers and their goals for water resource management.
Fine-scaled habitat preference of the Yangtze finless porpoise in the Yangtze River
Authors: Zhang Ping , Yu Zhongyin , Zhang Kang , Yu Daoping , Chen Minmin 
Published: August 2024

Abstract

The Yangtze finless porpoise (Neophocaena asiaeorientalis) is critically endangered and suffered from extensive habitat loss and fragmentation. Knowledge on habitat preference of the Yangtze finless porpoise could assist finless porpoise and associated ecosystem-based conservation by knowing porpoises’ suitable environments and prioritizing conservation sectors. In the present study, porpoise occurrences and numbers were collected in a 30-kilometer mainstream of the Yangtze River. Environmental variables were uniformly sampled in the dry and wet seasons. The maximum entropy model (MaxEnt) was then applied to porpoise data and environmental variables to analyze the effects of environmental variables on porpoises habitat preference. Within the study area, suitable habitats of the finless porpoises accounted for 19.0% and 15.4% of the study area during the dry and wet seasons. The suitable habitat of the finless porpoises shifted from the mainstream in the dry season to the sandbar head and tributary area in the wet season. In the dry season, variables influencing finless porpoise distribution were phytoplankton biomass, flow rate and zooplankton biomass, which contributed 97.05% variation in the MaxEnt modeling. In the wet season, water depth and surface water temperature accounted for 88.45% of the porpoise distribution. Above results highlighted higher conservation priority for the finless porpoise in the dry season when fish resources are relatively scarce while porpoises mainly distribute in the mainstream. Measures including monitoring and evaluating prey resources, management of shipping routes and shipping speed should be considered.
Construction of machine learning diagnostic models for cardiovascular pan-disease based on blood routine and biochemical detection data
Authors: Wang Zhicheng , Gu Ying , Huang Lindan , Liu Shuai , Chen Qun , Yang Yunyun , Hong Guolin , Ning Wanshan 
Published: August 2024

Abstract

Background
Cardiovascular disease, also known as circulation system disease, remains the leading cause of morbidity and mortality worldwide. Traditional methods for diagnosing cardiovascular disease are often expensive and time-consuming. So the purpose of this study is to construct machine learning models for the diagnosis of cardiovascular diseases using easily accessible blood routine and biochemical detection data and explore the unique hematologic features of cardiovascular diseases, including some metabolic indicators.
Methods
After the data preprocessing, 25794 healthy people and 32822 circulation system disease patients with the blood routine and biochemical detection data were utilized for our study. We selected logistic regression, random forest, support vector machine, eXtreme Gradient Boosting (XGBoost), and deep neural network to construct models. Finally, the SHAP algorithm was used to interpret models.
Results
The circulation system disease prediction model constructed by XGBoost possessed the best performance (AUC: 0.9921; Acc: 0.9618; Sn: 0.9690; Sp: 0.9526; PPV: 0.9631; NPV: 0.9600; MCC: 0.9224; F1 score: 0.9661). Most models of distinguishing various circulation system diseases also had good performance, the model performance of distinguishing dilated cardiomyopathy from other circulation system diseases was the best (AUC: 0.9267). The model interpretation by the SHAP algorithm indicated features from biochemical detection made major contributions to predicting circulation system disease, such as potassium (K), total protein (TP), albumin (ALB), and indirect bilirubin (NBIL). But for models of distinguishing various circulation system diseases, we found that red blood cell count (RBC), K, direct bilirubin (DBIL), and glucose (GLU) were the top 4 features subdividing various circulation system diseases.
Conclusions
The present study constructed multiple models using 50 features from the blood routine and biochemical detection data for the diagnosis of various circulation system diseases. At the same time, the unique hematologic features of various circulation system diseases, including some metabolic-related indicators, were also explored. This cost-effective work will benefit more people and help diagnose and prevent circulation system diseases.
Regulatory Role of LncRNA TUG1 in Hypertrophic Scar Development through miR-627 and IGFR1 Signaling
Authors: Bai Zeming , Liang Jiulong , Han Ziyang , Wang Hongyi , Zou Rifeng , Li Zhe , Lin Feng , Kong Xiangzi , Han Dong 
Published: August 2024

Abstract

Hypertrophic scar (HS) is a sequela of abnormal dermal repair, marked by the excessive proliferation of fibroblasts and dermal fibrosis. While long-non-coding RNAs (LncRNAs) have emerged as crucial modulators in HS, the underlying mechanisms are yet to be fully elucidated. Our study employed DNA Microarrays to analyze differentially expressed LncRNAs in HS and identified significant upregulation of TUG1. Further analysis based on the TargetScan database revealed that TUG1 has binding sites for miR-627 and its target gene IGFR1. Quantitative Real-Time PCR (qRT-PCR) confirmed the upregulation of TUG1 and IGFR1, and downregulation of miR-627 in HS samples. Subsequent assays, including qRT-PCR, luciferase reporter gene, and Western Blot, were conducted to explore the interactions between TUG1, miR-627, and IGFR1. MTT and Transwell assays assessed the proliferative and migratory abilities of hypertrophic scar fibroblasts (HSFs). Furthermore, the rabbit ear scar model supported our findings. We discovered that upregulation of TUG1 or downregulation of miR-627 facilitated HSF proliferation and migration, elucidating a negative regulatory relationship between TUG1 and miR-627. Mechanically, TUG1 competitively binds to miR-627, thus freeing IGFR1 for upregulation. In conclusion, TUG1 knockout can inhibit HSF proliferation and migration by upregulating miR-627, which subsequently downregulates IGFR1. These findings offer novel insights for the effective treatment of HS.
A Comprehensive Hybrid Framework to Study the Impact of Dams on the Shoreline Evolution in the Downstream Estuarian Region
Authors: Palanimanickam Vengadesan , Annamalaisamy Sannasiraj Sannasi , Bhallamudi Murty 
Published: August 2024

Abstract

The increasing demand for fresh water has led to a proliferation of dams worldwide. While humans benefit from water storage projects, the environment faces growing pressure. Dams significantly impact flow dynamics, reducing freshwater and sediment flow. This alteration in flow results in increased tidal dominance in estuarine areas. The combined effects of changes in water and sediment flow in the river, along with heightened tidal influence, have a significant impact on downstream morpho-dynamics. Understanding the long-term impacts of dam construction on shorelines is crucial as changes in shoreline evolution can have significant ecological, economic, and social implications. The present study proposes a novel hybrid framework, which combines Range of Variability Analysis (RVA) of river discharges, hydrologic modeling for sediment trapping by dams, hydrodynamic modeling of estuaries, and digital shoreline analysis, for gaining insight into shoreline changes triggered by the construction of large dams on rivers, and identifying the factors driving these changes. To illustrate the proposed methodology, it is applied to the Narmada River estuary in central India to study the impacts of the world’s second-largest concrete dam, Sardar Sarovar Dam (SSD). The construction of SSD reduced the magnitude of the flood by more than 40% and the sediment flow by 90%. The rate of shoreline change in the estuary has reduced during the post-construction period although the shoreline length undergoing erosion has significantly increased. The analysis using the hybrid approach suggests that the decreased rate of shoreline change is most likely due to reduced monsoonal flow, while the increased extent of erodible areas can be related to decreased sediment transport.
Effect of lignin structure composition on anaerobic digestion based on lignin monomer model compounds
Authors: Li Qiumin , Yang Bin , Liang Chengyue , Wu kai , zhao Xingling , wang Changmei , liu Jing , yang Hong , yin Fang , Zhang Wudi 
Published: August 2024

Abstract

Lignin crucially influences the methanogenesis of lignocellulose. However, the specific mechanism of lignin that affects anaerobic digestion remains unclear. Accordingly, this study investigated the effects of the structural monomers of lignin on anaerobic digestion using batch fermentation and model compounds. The results reveal that at low concentrations (0.02–0.1 g/L) phenol and guaiacol promoted biogas production, whereas higher concentrations inhibited methanogenesis and delayed peak biogas production. Complete inhibition of biogas production occurred at phenol concentrations ≥ 3.0 g/L or guaiacol concentrations ≥ 8.0 g/L. Furthermore, 2,6-dimethoxyphenol had no significant effect on digestion at 0.02–0.2 g/L, but increased both the delay period and overall biogas production at 1.0–4.0 g/L. The inhibitory effects are ascribed primarily to acid production being hindered, particularly acetic acid for phenol and guaiacol, whereas 2,6-dimethoxyphenol caused acidification. As found, the inhibitory effect of syringyl lignin was lower than those of guaiacyl lignin and p-hydroxyphenyl lignin. These findings underscore the complex interactions between lignin monomers and anaerobic digestion for methane production.
Estimating soil moisture and organic matter contents in salt-affected farmlands using hyperspectral remote sensing machine learning
Authors: Ding Qidong , Huang Huayu , Zhang Junhua , Wang Yijing , Jia Keli 
Published: August 2024

Abstract

Soil salinisation and alkalinisation are a major constraint to sustainable agricultural development, especially in arid and semi-arid areas. Hyperspectral remote sensing enables rapid and dynamic monitoring of soil properties, but it is still a challenge to improve the estimation accuracy. The aim of this study was to improve the accuracy of estimating soil moisture content (SMC) and soil organic matter (SOM) in salt-affected farmlands based on multi-source data. Nine study sites in the Hetao Plain, northwestern China were selected to acquire field hyperspectral data and measure soil properties. Spectral transformations were performed after preprocessing of the original hyperspectral reflectance data. Feature bands were selected by competitive adaptive reweighted sampling and multi-band spectral index development. Topographic, climatic and edaphic covariates were introduced to build models for SMC and SOM estimation based on four machine learning algorithms. The results showed that standard normal variate and fractional-order derivative transformations effectively captured subtle information in spectral data. Three-band spectral indices showed stronger correlations with SMC and SOM than two-band spectral indices. For the two soil properties, extremely randomised tree (ERT) models achieved the highest accuracy, followed by random forest, support vector machine and partial least squares regression models. The ERT models yielded R2 values of 0.91 and 0.96 for SMC and SOM, respectively. Interpretation of the ERT models using SHapley Additive exPlanations revealed that soil total nitrogen, followed by climatic factors, was the leading factor contributing to both SMC and SOM estimation. While the contribution of three-band spectral indices to model estimation was no greater than that of two-band spectral indices, there were notable differences in the contribution of single spectral bands. This study provides a new perspective to accurately estimate SMC and SOM in salt-affected farmlands. Recommendations for site-specific farmland management are given to facilitate soil amelioration.
Combating Multidrug Resistance in Escherichia coli and Klebsiella pneumoniae: A Synergistic Approach with Repurposed Drugs
Authors: Rani Kusum , Harikota Hepsiba , Mohapatra Saroj K. , Tripathi Shyam , Sharma Shingini , Sharma Amit , Poornima Sheba Samuel , Rattan Ashok , Raj V. Samuel 
Published: August 2024

Abstract

Introduction
Antimicrobial resistance (AMR) is a pressing global crisis endangering public health and the economy worldwide. The rise of multidrug-resistant (MDR) pathogens, such as Escherichia coli and Klebsiella pneumoniae, has led to a critical situation where treating infections caused by bacteria resistant to antibiotics like carbapenems and colistin, has become increasingly challenging and costly. In response, combination antibiotic therapy has emerged as a crucial strategy when single-drug treatments prove ineffective, offering a potential solution to combat the highly resistant pathogens effectively.
Objectives
The objective of this study was to investigate AMR in E. coli and K. pneumoniae, as well as the potential synergistic effects of combining Auranofin and MMV675968 with other FDA approved antimicrobial agents.
Methods
The antimicrobial susceptibility test used the broth micro-dilution method, and polymerase chain reactions were employed to detect resistance genes associated with AMR in clinical isolates. Combination studies were performed using the checkerboard assay against E. coli and K. pneumoniae isolates resistant to meropenem and colistin.
Results
The study revealed high rate of ESBLs and carbapenemase-producing MDR clinical isolates of E. coli and K. pneumoniae. It demonstrated that Auranofin exhibited synergistic activity with colistin (80%), meropenem (60%) levofloxacin (60%), and nitrofurantoin (90%). Additionally, a combination of MMV675968 with colistin (50%), meropenem (40%) with levofloxacin (80%), and nitrofurantoin (60%) also showed synergy against these MDR isolates.
Conclusion
Repurposing existing drugs and combining them in novel ways offers a rapid and resource-efficient strategy to combat MDR Gram-negative bacterial infections and address the growing threat of AMR.
25-hydroxycholesterol promotes brain cytokine production and leukocyte infiltration in a mouse model of lipopolysaccharide-induced neuroinflammation
Authors: Romero Johnathan , Toral-Rios Danira , Yu Jinsheng , Paul Steven M , Cashikar Anil G 
Published: August 2024

Abstract

Neuroinflammation has been implicated in the pathogenesis of several neurologic and psychiatric disorders. Microglia are key drivers of neuroinflammation and in response to different inflammatory stimuli overexpress a proinflammatory signature of genes. Among these, Ch25h is a gene overexpressed in brain tissue from Alzheimer’s disease as well as various mouse models of neuroinflammation. Ch25h encodes cholesterol 25-hydroxylase, an enzyme upregulated in activated microglia under conditions of neuroinflammation, hydroxylates cholesterol to form 25-hydroxycholesterol (25HC). 25HC can be further metabolized to 7α,25-dihydroxycholesterol, which is a potent chemoattractant for leukocytes. We have previously shown that 25HC increases production and secretion of the proinflammatory cytokine, IL-1β, by primary mouse microglia treated with lipopolysaccharide (LPS). In the present study, wildtype (WT) and Ch25h-knockout (CKO) mice were peripherally administered LPS to induce an inflammatory state in the brain. In LPS-treated WT mice, Ch25h expression and 25HC levels increased in brain relative to vehicle-treated WT mice. Among LPS-treated WT mice, females produced significantly higher levels of 25HC and showed transcriptomic changes reflecting higher levels of cytokine production and leukocyte migration than WT male mice. However, females were similar to males among LPS-treated CKO mice. Ch25h-deficiency coincided with decreased microglial activation in CKO mice relative to WT mice in response to systemic LPS. Proinflammatory cytokine production and intra-parenchymal infiltration of leukocytes were significantly lower in CKO compared to WT mice. Amounts of IL-1b and IL-6 in the brain strongly correlated with 25HC levels. Our results suggest a proinflammatory role for 25HC in the brain following peripheral administration of LPS.
Article Title]{Algebraic Cryptanalysis of Reduced-Round International Data Encryption Algorithm
Authors: Gundaram Praveen Kumar 
Published: August 2024

Abstract

SMT stands for Satisfiability Modulo Theories. SMT framework for addressing first-order logic-based constraint fulfillment problems. The following cryptographic procedures have used SMT solvers: SMT solver tools are used for differential cryptanalysis, collision attack, pre-image attack, modular root-finding, and cryptographic primitives verification. We demonstrate the effectiveness of SMT solvers for solving block cipher cryptanalysis constraints. During a cryptanalytic attack, we transform the boolean equations representing a block cipher into a more suitable format (Z3py). The performance of the IDEA cipher is evaluated utilizing the proposed cryptanalysis method. This technique uses plaintext and ciphertext pairs, partial key bits to recover the partial secret key and a predetermined number of rounds.
Evaluating predictive scheme for thermomechanical properties of Si-diamond composites
Authors: Zhao Feng-Yuan , Jiang Jun , Bai Shu-Xin , Chen Qiang , Ye Yi-Cong 
Published: August 2024

Abstract

A kind of multiscale correlational constitutive model without tunable parameter was developed to predict the thermomechanical properties of Si-diamond composites, including the effective elastic modulus, effective bulk modulus, effective shear modulus, effective Poisson’s ratio, coefficients of thermal expansion, as well as thermal conductivity. Based on this model, the effective thermomechanical response of composites was simulated, and the mechanism of thermomechanical coupling of constituents were also evaluated. The results were shown that the effective elastic properties of composites, such as effective elastic modulus, effective bulk modulus, effective shear modulus, increased with diamond and SiC, and that the introduction of dispersed diamond with high thermal conductivity and low thermal expansion resulted in improvement of thermal response and heat transport of Si-diamond-SiC composites, the thermomechanical coupling of which was inspired by the effective elastic properties of composites and mismatch between intrinsic properties of constituents.
Musculoskeletal Healthcare Professionals' perspectives on objective postural assessment (Expectation and Experience): A UK (Multiprofessional) nationwide survey
Authors: Martin Daniel Christopher , McGuigan Polly , Matei Raluca , Kandasamy Gok 
Published: August 2024

Abstract

Background: Spinal pain is commonly assessed by physiotherapists, osteopaths and chiropractors in musculoskeletal practice in the UK. Typically, assessment involves some form of visual estimation, but further objective measurement is not preferred due to logistical factors. This study explored the views of physiotherapists, osteopaths, and chiropractors around objective postural assessment and factors that may influence clinical reasoning.
Methods: An online, exploratory, ad-hoc, cross-sectional survey was designed to collect data on views around objective postural assessment. The survey was distributed among relevant professional groups.
Results: A total of 431 respondents (343 physiotherapists, 43 osteopaths, and 45 chiropractors) took part. As much as 85% of respondents use some form of postural assessment within clinical practice. Most respondents perceived that posture can change and that the changes can be short-term and long-standing. Exercise, education, and behavioural change were perceived as top interventions to change posture.
Conclusion: These results provide insights into the current position of MHPs' views within the UK and facilitate conversation regarding the objective measurement of posture in the 21st century.