bluuebunny/crossref_metadata_2025_split huggingface dataset:
Epidemiological characteristics and temporal-spatial clustering analysis on human brucellosis in Jiangsu Province, 2006–2021
Authors: Zhang Nan , Fang Xin-yu , Zhou Wei-zhong , Tan Zhong-ming , Liang Shu-yi , Wang Xiao-chen , Hu Jian-li , Bao Chang-jun , Liu Wen-dong 
Published: November 2023

AbstractThe marked increase in the incidence rate of brucellosis is a serious public health concern in Jiangsu Province. However, its temporal and spatial distribution has not been studied in depth. The main purpose of this study is to depict the demographic, temporal and spatial distribution patterns and clustering characteristics of brucellosis cases in Jiangsu Province, China, from 2006 to 2021 to develop and implement effective scientific prevention and control strategies. Data for human brucellosis cases in Jiangsu Province from 2006 to 2021 were obtained from the Nationwide Notifiable Infectious Diseases Reporting Information System (NIDRIS). Spatial autocorrelation analysis and temporal-spatial scan statistics were used to identify potential changes in the spatial and temporal distributions of human brucellosis in Jiangsu Province. During the years 2006–2021, 1347 brucellosis cases were reported in Jiangsu Province, with an average annual incidence rate of 0.1036 per 100,000 individuals. Middle-aged and elderly individuals (aged 40–69 years) were the main infected populations, accounting for 69.72% (939/1347) of all reported cases. The incidence of brucellosis in Jiangsu showed a long-term increasing trend and displayed pronounced seasonal variations, with the peak occurring between April and June annually. The incidence gradually expanded from the northern and southern areas to the central areas between 2006 and 2021. Global spatial autocorrelation analysis demonstrated a positive correlation in the incidence of brucellosis between 2008 and 2012–2021. Temporal-spatial clustering analysis showed that the primary cluster was detected in the northern, highly endemic regions of Jiangsu, and the three secondary clusters were in areas where there had been outbreaks of brucellosis. Human brucellosis remains a serious public health issue in Jiangsu Province. Northern and southern Jiangsu regions, with high rates of brucellosis, may require special plans and measures to monitor and control the disease. Additionally, the capacity to respond to outbreaks in high-incidence areas should be improved to prevent further brucellosis outbreaks.
Evaluation of behavioural selection processes in conflict scenarios using a newly developed mouse behavioural paradigm
Authors: Miyagami Yurika , Honshuku Yuki , Nomura Hiroshi , Minami Masabumi , Hitora-Imamura Natsuko 
Published: November 2023

AbstractSelecting an appropriate behaviour is critical for survival in conflict scenarios, wherein animals face both appetitive and aversive stimuli. Behavioural selection consists of multiple processes: (1) animals remain quiet in a safe place to avoid aversive stimuli (suspension), (2) once they decide to take risks to approach appetitive stimuli, they assess the risks (risk assessment), and (3) they act to reach the reward. However, most studies have not addressed these distinct behavioural processes separately. Here, we developed a new experimental paradigm called the three-compartment conflict task to quantitatively evaluate conflict processes. Our apparatus consisted of start, flat, and grid compartments. Mice needed to explore the grid compartment, where they might receive foot shocks while trying to obtain sucrose. Applying foot shocks increased sucrose acquisition latency in subsequent trials, reflecting elevated conflict levels throughout trials. The time spent in the start compartment and the number of retreats were determined to measure the conflict levels in suspension and risk assessment, respectively. Foot shocks increased these parameters, whereas diazepam decreased them. Our new paradigm is valuable for quantitatively evaluating distinct behavioural processes and contributes to developing effective treatments for psychiatric disorders associated with maladaptive behaviours in conflict scenarios.
Optimization of an experimental study of cationic Pb metal adsorption by resin polymer
Authors: Bensalah Jaouad , Doumane Ghizlane , Iraqi Oumayma , Elhenawy Ahmed A. , Ouaddari Hanae , Okla Mohammad K. , Nafidi Hiba-Allah , younous Youssouf Ali , Bourhia Mohammed , Habsaoui Amar 
Published: November 2023

AbstractTo eliminate lead (Pb) ions from metallic solutions, the cationic resin in solid form was utilized. The characterization of the adsorbent was performed using GTA/GTD, SEM spectroscopy, and EDX analysis. The results of these analyses provided insights into the structure and composition of the resin. The removal of Pb (II) ions was found to be highly dependent on various parameters. Firstly, the pH of the metal solution played a crucial role, as the adsorption capacity increased with the pH of the solution, at a maximum equal to (R = 84.78%), at a pH = 8.0. Additionally, the concentration of Pb (II) ions present in the solution influenced the adsorption technique’s capacity, with higher concentrations leading to increased adsorption, analysis overhead of high concentration present (100 mg L−1) of the metal lead (II) study, a saturation corresponding a plateau to the resin polymeric saturation is 93.18 mg g−1. To determine the optimal mass of the resin adsorbent, a study was conducted to maximize the removal of Pb (II) ions, at the mass 1.0 g showed that the proportion of inorganic pollutants removed from Pb (II) is entirely qualitative (100%). Furthermore, the effect of temperature on the adsorption process was investigated. It was observed that the rate of the Pb (II) adsorption process decreased as the temperature increased. Kinetic studies were performed to gain further insights into the adsorption process. Pseudo-first-order and pseudo-second-order models, along with the intra-particle diffusion model, were utilized for this purpose. The results indicated that the adsorption process was fast, as evidenced by the findings from the pseudo-second-order study. The saturation technical process was studied, employing several different isothermal models, including Langmuir, Freundlich, and Temkin. Among these models, the Langmuir model was found to best describe the phenomenon of lead metal adsorption by the resin polymeric, is equal to 11.23 mg g−1, with the experimental value precisely (R2 = 0.999). Finally, various thermodynamic techniques were applied to analyze the adsorption process. The thermodynamic parameters such as ΔG° (− 9.78 to − 9.27 kJ mol−1), ΔH° (14.85 kJ mol−1), and ΔS° (0.017 kJ mol−1) were determined. These values indicated that the adsorption process was endothermic and spontaneous, further emphasizing its impetuous nature. The results of the molecular dynamics calculations demonstrated that amino groups are very important in defining the characteristics of cation adsorption. We conclude that this new adsorbent has the potential to significantly improve the process of regularly removing heavy metal ions from wastewater.
New ex vivo method to objectively assess insulin spatial subcutaneous dispersion through time during pump basal-rate based administration
Authors: Jacquemier Pauline , Retory Yann , Virbel-Fleischman Clara , Schmidt Alexandra , Ostertag Agnes , Cohen-Solal Martine , Alzaid Fawaz , Potier Louis , Julla Jean-Baptiste , Gautier Jean-François , Venteclef Nicolas , Riveline Jean-Pierre 
Published: November 2023

AbstractGlycemic variability remains frequent in patients with type 1 diabetes treated with insulin pumps. Heterogeneous spreads of insulin infused by pump in the subcutaneous (SC) tissue are suspected but were barely studied. We propose a new real-time ex-vivo method built by combining high-precision imaging with simultaneous pressure measurements, to obtain a real-time follow-up of insulin subcutaneous propagation. Human skin explants from post-bariatric surgery are imaged in a micro-computed tomography scanner, with optimised parameters to reach one 3D image every 5 min during 3 h of 1UI/h infusion. Pressure inside the tubing is recorded. A new index of dispersion (IoD) is introduced and computed upon the segmented 3D insulin depot per time-step. Infusions were hypodermal in 58.3% among 24 assays, others being intradermal or extradermal. Several minor bubbles and one occlusion were observed. IoD increases with time for all injections. Inter-assay variability is the smallest for hypodermal infusions. Pressure elevations were observed, synchronised with air bubbles arrivals in the tissue. Results encourage the use of this method to compare infusion parameters such as pump model, basal rate, catheter characteristics, infusion site characteristics or patient phenotype.
New insights into the genetic predisposition of brucellosis and its effect on the gut and vaginal microbiota in goats
Authors: Sallam Ahmed M. , Abou-souliman Ibrahim , Reyer Henry , Wimmers Klaus , Rabee Alaa Emara 
Published: November 2023

AbstractGoats contribute significantly to the global food security and industry. They constitute a main supplier of meat and milk for large proportions of people in Egypt and worldwide. Brucellosis is a zoonotic infectious disease that causes a significant economic loss in animal production. A case–control genome-wide association analysis (GWAS) was conducted using the infectious status of the animal as a phenotype. The does that showed abortion during the last third period of pregnancy and which were positive to both rose bengal plate and serum tube agglutination tests, were considered as cases. Otherwise, they were considered as controls. All animals were genotyped using the Illumina 65KSNP BeadChip. Additionally, the diversity and composition of vaginal and fecal microbiota in cases and controls were investigated using PCR-amplicone sequencing of the V4 region of 16S rDNA. After applying quality control criteria, 35,818 markers and 66 does were available for the GWAS test. The GWAS revealed a significantly associated SNP (P = 5.01 × 10–7) located on Caprine chromosome 15 at 29 megabases. Four other markers surpassed the proposed threshold (P = 2.5 × 10–5). Additionally, fourteen genomic regions accounted for more than 0.1% of the variance explained by all genome windows. Corresponding markers were located within or in close vicinity to several candidate genes, such as ARRB1, RELT, ATG16L2, IGSF21, UBR4, ULK1, DCN, MAPB1, NAIP, CD26, IFIH1, NDFIP2, DOK4, MAF, IL2RB, USP18, ARID5A, ZAP70, CNTN5, PIK3AP1, DNTT, BLNK, and NHLRC3. These genes play important roles in the regulation of immune responses to the infections through several biological pathways. Similar vaginal bacterial community was observed in both cases and controls while the fecal bacterial composition and diversity differed between the groups (P < 0.05). Faeces from the control does showed a higher relative abundance of the phylum Bacteroidota compared to cases (P < 0.05), while the latter showed more Firmicutes, Spirochaetota, Planctomycetota, and Proteobacteria. On the genus level, the control does exhibited higher abundances of Rikenellaceae RC9 gut group and Christensenellaceae R-7 group (P < 0.05), while the infected does revealed higher Bacteroides, Alistipes, and Prevotellaceae UCG-003 (P < 0.05). This information increases our understanding of the genetics of the susceptibility to Brucella in goats and may be useful in breeding programs and selection schemes that aim at controlling the disease in livestock.
Deep learning-based solution for smart contract vulnerabilities detection
Authors: Tang Xueyan , Du Yuying , Lai Alan , Zhang Ze , Shi Lingzhi 
Published: November 2023

AbstractThis paper aims to explore the application of deep learning in smart contract vulnerabilities detection. Smart contracts are an essential part of blockchain technology and are crucial for developing decentralized applications. However, smart contract vulnerabilities can cause financial losses and system crashes. Static analysis tools are frequently used to detect vulnerabilities in smart contracts, but they often result in false positives and false negatives because of their high reliance on predefined rules and lack of semantic analysis capabilities. Furthermore, these predefined rules quickly become obsolete and fail to adapt or generalize to new data. In contrast, deep learning methods do not require predefined detection rules and can learn the features of vulnerabilities during the training process. In this paper, we introduce a solution called Lightning Cat which is based on deep learning techniques. We train three deep learning models for detecting vulnerabilities in smart contract: Optimized-CodeBERT, Optimized-LSTM, and Optimized-CNN. Experimental results show that, in the Lightning Cat we propose, Optimized-CodeBERT model surpasses other methods, achieving an f1-score of 93.53%. To precisely extract vulnerability features, we acquire segments of vulnerable code functions to retain critical vulnerability features. Using the CodeBERT pre-training model for data preprocessing, we could capture the syntax and semantics of the code more accurately. To demonstrate the feasibility of our proposed solution, we evaluate its performance using the SolidiFI-benchmark dataset, which consists of 9369 vulnerable contracts injected with vulnerabilities from seven different types.
Clinical complications after a traumatic brain injury and its relation with brain biomarkers
Authors: Yuguero Oriol , Bernal Maria , Farré Joan , Martinez-Alonso Montserrat , Vena Ana , Purroy Francisco 
Published: November 2023

AbstractWe aimed to find out which are the most frequent complications for patients who suffer a traumatic brain injury (TBI) and its relation with brain biomarker levels. We conducted a hospital cohort study with patients who attended the Hospital Emergency Department between 1 June 2018 and 31 December 2020. Different variables were collected such as biomarkers levels after 6 h and 12 h of TBI (S100, NSE, UCHL1 and GFAP), clinical and sociodemographic variables, complementary tests, and complications 48 h and 7 days after TBI. Qualitative variables were analysed with Pearson’s chi-square test, and quantitative variables with the Mann–Whitney U test. A multivariate logistic regression model for the existence of complications one week after discharge was performed to assess the discriminatory capacity of the clinical variables. A total of 51 controls and 540 patients were included in this study. In the TBI group, the mean age was 83 years, and 53.9% of the patients were male. Complications at seven days were associated with the severity of TBI (p < 0.05) and the number of platelets (p = 0.016). All biomarkers except GFAP showed significant differences in their distribution of values according to gender, with significantly higher values of the three biomarkers for women with respect to men. Patients with complications presented significantly higher S100 values (p < 0.05). The patient’s baseline status, the severity of the TBI and the S100 levels can be very important elements in determining whether a patient may develop complications in the few hours after TBI.
Bayesian AEWMA control chart under ranked set sampling with application to reliability engineering
Authors: Khan Imad , Noor-ul-Amin Muhammad , Muhammad Khan Dost , Khalil Umair , Ismail Emad A. A. , Yasmeen Uzma , Ahmad Bakhtiyar 
Published: November 2023

AbstractThe article introduces a novel Bayesian AEWMA Control Chart that integrates different loss functions (LFs) like the square error loss function and Linex loss function under an informative prior for posterior and posterior predictive distributions, implemented across diverse ranked set sampling (RSS) designs. The main objective is to detect small to moderate shifts in the process mean, with the average run length and standard deviation of run length serving as performance measures. The study employs a hard bake process in semiconductor production to demonstrate the effectiveness of the proposed chart, comparing it with existing control charts through Monte Carlo simulations. The results underscore the superiority of the proposed approach, particularly under RSS designs compared to simple random sampling (SRS), in identifying out-of-control signals. Overall, this study contributes a comprehensive method integrating various LFs and RSS schemes, offering a more precise and efficient approach for detecting shifts in the process mean. Real-world applications highlight the heightened sensitivity of the suggested chart in identifying out-of-control signals compared to existing Bayesian charts using SRS.
Markers of inflammation predict survival in newly diagnosed cirrhosis: a prospective registry study
Authors: Mynster Kronborg Thit , Webel Henry , O’Connell Malene Barfod , Danielsen Karen Vagner , Hobolth Lise , Møller Søren , Jensen Rasmus Tanderup , Bendtsen Flemming , Hansen Torben , Rasmussen Simon , Juel Helene Bæk , Kimer Nina 
Published: November 2023

AbstractThe inflammatory activity in cirrhosis is often pronounced and related to episodes of decompensation. Systemic markers of inflammation may contain prognostic information, and we investigated their possible correlation with admissions and mortality among patients with newly diagnosed liver cirrhosis. We collected plasma samples from 149 patients with newly diagnosed (within the past 6 months) cirrhosis, and registered deaths and hospital admissions within 180 days. Ninety-two inflammatory markers were quantified and correlated with clinical variables, mortality, and admissions. Prediction models were calculated by logistic regression. We compared the disease courses of our cohort with a validation cohort of 86 patients with cirrhosis. Twenty of 92 markers of inflammation correlated significantly with mortality within 180 days (q-values of 0.00–0.044), whereas we found no significant correlations with liver-related admissions. The logistic regression models yielded AUROCs of 0.73 to 0.79 for mortality and 0.61 to 0.73 for liver-related admissions, based on a variety of modalities (clinical variables, inflammatory markers, clinical scores, or combinations thereof). The models performed moderately well in the validation cohort and were better able to predict mortality than liver-related admissions. In conclusion, markers of inflammation can be used to predict 180-day mortality in patients with newly diagnosed cirrhosis. Prediction models for newly diagnosed cirrhotic patients need further validation before implementation in clinical practice.Trial registration: NCT04422223 (and NCT03443934 for the validation cohort), and Scientific Ethics Committee No.: H-19024348.
Mechanism of strength deterioration of red sandstone on reservoir bank slopes under the action of dry–wet cycles
Authors: Chen Chao , Zhao Baoyun , Zhang Liyun , Huang Wei 
Published: November 2023

AbstractTo investigate the micro-scale mechanism of strength deterioration under different times of dry–wet cycles, laboratory tests of physical properties, triaxial compression, X-ray diffraction (XRD) and scanning electron microscopy (SEM) were conducted on red sandstone on reservoir bank slopes. The research results showed that when the 5th dry–wet cycle ended, the dry mass and peak strength started to rapidly decline, while the porosity and saturated mass increased rapidly. In general, all of these behaviours become relatively stable when the number of cycles increased. Similarly, cohesion and internal friction angle changed most significantly from 0 to 10 cycles and then became stable. In addition, the physical expansion of the adsorbed water film and the dissolution and expansion of mineral particles increased the number of internal microcracks and pores and the porosity and saturated mass of the sample. In addition, the pore fluid effect and fracture flow effect made the microcracks in the red sandstone grow and connect; thus, the peak strength of the sample decreased. Moreover, during the dry–wet cycles, the change in the relative content of mineral particles and the pore fluid effect weakened the clay cementation, and then the dry mass and cohesion of the samples decreased. The research reported in this paper will play a very significant role in the scientific analysis of slope stability in the Three Gorges Reservoir area.
Analog neuromorphic circuit for spontaneous Ca2+ oscillations
Authors: Câmara Beatriz O. , Guimarães Janaina G. , Pereira Junior Marcelo L. 
Published: November 2023

AbstractThis study proposes an innovative analog neuromorphic circuit design to mimic spontaneous Ca2+ oscillations observed in astrocytes. Unlike traditional models, this approach does not rely on synaptic stimulation, suggesting that astrocytes may play a key role in generating neuronal activity. The circuit is built using transistor differential pairs to approximate the nonlinear sigmoidal biological functions, and its performance is validated through simulation and compared against mathematical models using phase diagram analysis. Results indicate a good fit between the circuit and the mathematical model. Finally, the circuit’s ability to simulate the release of glutamate and ATP through spontaneous oscillations is demonstrated.
A new set of metrics and framework to assess the colonization potential of riverscapes by wind-dispersed plant species
Authors: Wagner Thomas C. , Woellner Romy 
Published: November 2023

AbstractQuantifying the potential of a braided riverscape to be colonized by a plant species is essential for assessing the ecological state of the river and provides an important basis for nature conservation planning and the implementation of restoration measures. Common connectivity indices are largely unsuitable for describing the situation for the mostly wind-dispersed plant species. Our approach provides a set of comparable metrics that allows the quantification of the colonization potential of riverscapes at the patch and riverscape level. We propose a set of cell-based, spatially explicit measures that can easily be implemented. We demonstrate their application using two typical plant species and three riverscapes with different habitat configurations as examples. Our metrics consider shape, size and the spatial configuration of habitat patches, along with the dispersal characteristics of the respective species. The metrics provide a linear, balanced, and realistic representation of the colonization potential at the cell, patch, and riverscape levels. The results are comparable between different riverscapes and species, can be easily extended and used for further modeling. The metrics provide a valuable tool for the planning and evaluation of conservation, restoration, and reintroduction measures and close the gap between habitat availability analyses and large-scale terrestrial connectivity indices.