bluuebunny/crossref_metadata_2025_split huggingface dataset:
Brachytherapy for organ-preserving treatment of bladder cancer
Authors: Zaborskiy I. N. , Safiullin K. N. , Smolenov E. I. , Shchukina E. O. , Chaykov V. S. , Troyanov A. V. , Dementiev I. O. , Karyakin O. B. , Ivanov S. A. , Kaprin A. D. 
Published: August 2024

Bladder cancer is the 9th most common malignant tumor worldwide. Muscle-invasive bladder cancer is an aggressive malignant neoplasm with a tendency for early metastases. The main approach for muscle-invasive bladder cancer treatment is radical cystectomy with lymph node dissection and polychemotherapy. In recent decades, organ-preserving conservative therapy has been actively investigated. Currently, the most studied approach to organ-preserving treatment of muscle-invasive bladder cancer is the trimodality therapy which includes transurethral resection of the bladder wall with the tumor, chemotherapy, and external beam radiotherapy. The article presents an approach which additionally includes intratumoral radiation therapy. In our study, we have investigated the current state of brachytherapy in bladder cancer treatment and its development.
Comparison of the effectiveness of radiation and surgical treatment methods in high and very high risk prostate cancer
Authors: Novikov S. N. , Samartseva E. E. , Novikov R. V. , Nosov A. K. , Protsenko S. A. , Buevich N. N. , Petrov S. B. , Ilyin N. D. , Merezhko Yu. O. , Antipov F. E. , Kanaev S. V. 
Published: August 2024

Aim. To perform comparative analysis of overall and recurrence-free survival in patients with prostate cancer (PCa) of high and very high risk (HVHR) receiving combination treatment based on surgical or radiation therapy.Materials and methods. Between 2012 and 2022 at the N.N. Petrov National Medical Research Center of Oncology (Saint Petersburg), 2 prospective studies were performed. In 138 patients with HVHR PCa (mean age 63.1 ± 6.6 years, median followup 28.7 (12.4; 45.6) months), comparative analysis of the effectiveness of radical prostatectomy with extended lymph node dissection in combination with neoadjuvant chemohormonal therapy or without it was performed. In the parallel independent prospective study, in 220 patients with HVHR PCa (mean age 667 ± 6.5 years, median follow-up 61.3 (49.1; 82.3) months), the effectiveness of combination radiation therapy with simultaneous androgen deprivation therapy (ADT) was evaluated: pelvic lymph nodes and prostate were irradiated in accordance with the standard dose fractionation (total focal dose 46–50 Gy) with subsequent additional prostate irradiation using brachytherapy or stereotactic radiotherapy.Results. In the patient group receiving surgical treatment, actuarial 5-year survival without the signs of biochemical recurrence was 35.7–44.2 % which was significantly lower than 67.1 % in the group receiving radiotherapy with ADT (р <0.0001, log-rank test). Five-year overall survival did not significantly differ between the compared groups and amounted to 88–90 % (р = 0.84, log-rank test).Conclusion. In patients with locally advanced HVHR PCa, radiotherapy in combination with ADT leads to significant increase in biochemical recurrence-free survival compared to patients who underwent prostatectomy with extended lymph node dissection including cases where surgery was combined with neoadjuvant ADT or chemohormonal therapy.
Uncertainty and Spatial Correlation in Station Measurements for mb Magnitude Estimation
Authors: Yeck William L. , Ringler Adam T. , Shelly David R. , Earle Paul , Benz Harley , Wilson David C. 
Published: August 2024

Abstract
The body-wave magnitude (mb) is a long-standing network-averaged, amplitude-based magnitude used to estimate the magnitude of seismic sources from teleseismic observations. The U.S. Geological Survey National Earthquake Information Center (NEIC) relies on mb in its global real-time earthquake monitoring mission. Although waveform modeling-based moment magnitudes are the modern standard to characterize earthquake size, mb is important because (1) in many cases, waveform modeling is not possible (e.g., low signal-to-noise events), (2) mb is applicable over a broad range of magnitudes, ∼M 4–7, and (3) there is a many decades-long history of estimating mb magnitudes. We use the NEIC Preliminary Determination of Epicenters earthquake catalog to investigate the uncertainty in NEIC station mb measurements. We show that mb measurements are spatially correlated, which can bias event mb, and we describe an empirical relation between this spatial correlation and station-to-station distance. We further describe an approach to mitigate bias from the spatial correlation. Accounting for the spatial covariance of observations can change the event mb from −0.15 to 0.07 mb units (10th to 90th percentile) for smaller events (mb≤4.5). These smaller events have the largest mb standard deviations ranging from 0.05 to 0.15 mb units (10th to 90th percentile).
Duration of reproductive period and metabolic syndrome and its components: findings from the Henan Rural Cohort Study in menopausal women
Authors: Du Zhen , Wang Wanbo , Zhao Bing , Wu Xueyan , Yang Huili , Liao Wei , Hu Ze , Yang Jing , Dong Xiaokang , Zhao Hongfei , Liu Xiaotian , Wang Chongjian 
Published: August 2024

Abstract

Purpose: The purpose of this study was to investigate the relationship of duration of reproductive period with metabolic syndrome (MetS) and its components in rural population.
Methods: In all, 14596 menopausal women were enrolled from the Henan Rural Cohort study. Logistic regression and linear regression were used to evaluate the association between duration of reproductive period and MetS and its components (including central obesity, abnormal fasting plasma glucose (FPG), abnormal blood pressure (BP), abnormal triglycerides (TG) and abnormal high-density lipoprotein cholesterol (HDL-C)). In addition, the mediation and interaction effects were performed by mediation analyses and generalized linear model.
Results: Each year of increase reproductive period correlated with an increased risk of MetS (OR = 1.031; 95% CI = 1.023-1.039; P < 0.05). This association changed slightly after adjusting for BMI and remained statistically significant (OR (95% CI): 1.012(1.003, 1.021)). A positive association between duration of reproductive period and central obesity, abnormal FPG, abnormal BP, abnormal TG, and abnormal HDL-C were revealed (all P < 0.05). The relationship with abnormal FPG (OR (95% CI): 1.009(1.000, 1.017)) and abnormal TG (OR (95% CI): 1.013(1.005, 1.021)) were attenuated after adjusting for BMI and remained statistically significant except for central obesity, abnormal BP and abnormal HDL-C. In addition, participants with earlier menarche age and later menopause age might have a higher risk of MetS. In addition, BMI partially mediated the relationship between duration of reproductive period and MetS, abnormal FPG, or abnormal TG, and completely mediated the relationship between duration of reproductive years and abnormal BP, or abnormal HDL-C. The significant interaction of high fat diet was found in association between duration of reproductive period and MetS (P interaction = 0.011).
Conclusion: The longer duration of reproductive period might raise a woman's risk of MetS and its components. More importantly, the association was largely mediated by BMI. There is an interaction effect between duration of reproductive period and high fat diet on the risk of MetS.
Cocooning with Cassava: Exploring the commercial rearing and seed production potential of Samia ricini Donovan on different Cassava varieties
Authors: Natarajan Lalitha , Hridya H , Bhuyan R , Bordoloi H , Sivakumar P.S , Borpuzari P. 
Published: August 2024

Abstract

Different cassava varieties’ differential preferences and performance of eri silkworm Samia ricini (Donovan), seed cocoon rearing and its reproductive performance were studied. In the current study, seven foliage rich cassava varieties were selected and evaluated as feed for Samia ricini in comparison with the primary food plant castor (NBR1). The treatments were arranged in a completely randomized design (CRD) in three replications. A significant difference was observed in rearing performance of eri silkworms when fed to leaves of different cassava varieties. Majuli var fed worms recorded mature larval weight (7.01 ± 0.62); pupation percentage (95.93 ± 0.37),effective rate of rearing (81.76 ± 1.24%), single cocoon weight (3.96 ± 0.17g), pupal weight (3.44 ± 0.21g) better than all the other varieties of cassava used for rearing followed by Sree Raksha and Tura. Shell ratio percentage of all cassava varieties were on par with control. Based on the eri seed production data, cassava varieties Majuli and Sree Raksha were found to be much superior to all other foliage-rich cassava varieties considered for the study. Overall, the better-performing varieties on par with control are as follows Majuli, Sree Raksha and Tura. These varieties can be recommended for the farmers in Assam for eri cocoon production besides tuber production.
Analysis of Electrode Locations on Limb Condition Effect for Myoelectric Pattern Recognition
Authors: Wang Hai , Li Na , Gao Xiaoyao , Jiang Ning , He Jiayuan 
Published: August 2024

Abstract

Background
Gesture recognition using surface electromyography (sEMG) has garnered significant attention due to its potential for intuitive and natural control in wearable human-machine interfaces. However, ensuring robustness remains essential and is currently the primary challenge for practical applications.
Methods
This study investigates the impact of limb conditions and analyzes the influence of electrode placement. Both static and dynamic limb conditions were examined using electrodes positioned on the wrist, elbow, and the midpoint between them. Initially, we compared classification performance across various training conditions at these three electrode locations. Subsequently, a feature space analysis was conducted to quantify the effects of limb conditions. Finally, strategies for group training and feature selection were explored to mitigate these effects.
Results
The results indicate that with the state-of-the-art method, classification performance at the wrist was comparable to that at the middle position, both of which outperformed the elbow, consistent with the findings from the feature space analysis. In inter-condition classification, training under dynamic limb conditions yielded better results than training under static conditions, especially at the positions covered by dynamic training. Additionally, fast and slow movement speeds produced similar performance outcomes. To mitigate the effects of limb conditions, adding more training conditions reduced classification errors; however, this reduction plateaued after four conditions, resulting in classification errors of 22.72%, 22.65%, and 26.58% for the wrist, middle, and elbow, respectively. Feature selection further improved classification performance, reducing errors to 19.98%, 19.75%, and 27.14% at the respective electrode locations, using three optimal features derived from single-condition training.
Conclusions
The study demonstrated that the impact of limb conditions was mitigated when electrodes were placed near the wrist. Dynamic limb condition training, combined with feature optimization, proved to be an effective strategy for reducing this effect. This work contributes to enhancing the robustness of myoelectric-controlled interfaces, thereby advancing the development of wearable intelligent devices.
The Power of ESG Factors in Driving Financial Growth - Insights from Palestine
Authors: Alslaibi Naji , Abdalkarim Naser 
Published: August 2024

Abstract

Purpose: This study examines the effects of environmental, social, and governance disclosure (ESG) components on the financial performance (FP) of firms listed on the Palestine Stock Exchange (PEX) from 2016 to 2022, focusing on the moderating role of corporate governance.
Design/methodology/approach: This study used primary data from 44 PEX-listed companies. A context analysis technique was used through company websites and disclosures, the entire population (308 observations) was used for this study, and the study used STATA utilizing the required statistical analysis for this research.
Findings: The study finds that environmental, social, and governance disclosures significantly influence the Return on Equity and Return on Assets. Testing for the moderating role of Corporate Governance, especially board diversity and size, shows that board diversity moderates the association between social and governance disclosure and firm performance. Board size moderates the relationship between social disclosure and firm performance. By contrast, Board Size and Diversity do not moderate the relationship between environmental disclosure and firm performance.
Originality: The study contributes to the literature as the first of its kind conducted in Palestine, examining the moderating effects of board size and diversity on the association between ESG disclosure and firm performance.
Identification of Potential Inhibitors of SARS-CoV-2 Using Machine Learning, Molecular Docking and MD Simulation
Authors: Nayarisseri Anuraj , Bhrdwaj Anushka , Khan Arshiya , Sharma Khushboo , Shaheen Uzma , Panwar Umesh , Natchimuthu V. , chaudhary Rinku , Kumar Abhishek , Dey Taniya , Panicker Aravind , Prajapati Leena , Bezerra Francisco Jaime , Singh Sanjeev Kumar 
Published: August 2024

Abstract

The advent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of the coronavirus disease 2019 (COVID-19) pandemic, has promoted physical and mental health worldwide. Due to the unavailability of effective antiviral drugs, there is an unmet demand for a robust therapeutic approach for the development of anti-SARS-CoV-2 drugs. Myriad investigations have recognized ACE2 as the primary receptor of SARS-CoV-2, and this amalgamation of ACE2 with the spike protein of the subsequent coronavirus is paramount for viral entry into host cells and inducing infection. Consequently, limiting or restricting the accessibility of the causal virus to ACE2 offers an alternative therapeutic approach for averting this illness. Thus, the objective of the study was to determine the highly efficacious inhibitors exhibiting an augmented affinity for ACE2 protein and asses their pharmacological efficacy using molecular docking analysis. Machine learning algorithms were employed to govern the novel compounds by taking the ACE2-inhibiting compounds, Quninaprill, Moexipril, etc, and pre-established repurposed viral compounds, Birinapant, Remdesivir, etc., as test datasets. Structural stability was further confirmed via MD simulation approach which comparatively assessed the novel machine-learning, and pre-established compounds, followed by toxicity and pharmacophore studies. The study therefore concludes that the novel machine-learning compound (PubChem ID: 23658468) can be a potent therapeutic agent for combatting SARS-CoV-2.
Salmonella enterica Virulence Databases and Bioinformatic Analysis Tools Development
Authors: Han Jing , Tang Hailin , Zhao Shaohua , Foley Steven L. 
Published: August 2024

Abstract

Salmonella enterica, a prominent foodborne pathogen, contributes significantly to global foodborne illnesses annually. This species exhibits significant genetic diversity, potentially impacting its infectivity, disease severity, and antimicrobial resistance. Whole genome sequencing (WGS) offers comprehensive genetic insights that can be utilized for virulence assessment. However, existing bioinformatic tools for studying Salmonella virulence have notable limitations. To address this gap, a Salmonella Virulence Database with a non-redundant, comprehensive list of putative virulence factors was constructed. Two bioinformatic analysis tools, Virulence Factor Profile Assessment and Virulence Factor Profile Comparison tools, were developed. The former provides data on similarity to the reference genes, e-value, and bite score, while the latter assesses the presence/absence of virulence genes in Salmonella isolates and facilitates comparison of virulence profiles across multiple sequences. To validate the database and associated bioinformatic tools, WGS data from 43,853 Salmonella isolates spanning 14 serovars was extracted from GenBank, and WGS data previously generated in our lab was used. Overall, the Salmonella Virulence database and our bioinformatic tools effectively facilitated virulence assessment, enhancing our understanding of virulence profiles among Salmonella isolates and serovars. The public availability of these resources will empower researchers to assess Salmonella virulence comprehensively, which could inform strategies for pathogen control and risk evaluations associated with human illnesses.
The van der Waals Heterostructures of Blue Phosphorene with GaN/GeC for High-Performance Thermoelectric Applications
Authors: Wang Xue-Peng , Ahmad Iqtidar , Shahid Ismail , Ali Anwar , Shah Syed , Lyu Tu , Li En , Ding Keyuan , Chen Xin , Rao Feng 
Published: August 2024

Abstract

Thermoelectric devices have substantial potential as an environmentally compatible and sustainable power source. In this article, the density functional theory and Boltzmann's transport equation are employed to investigate the thermoelectric characteristics of blue phosphorene (P)/GaN and P/GeC van der Waals heterostructures (vdWHs). Both vdWHs exhibit a small lattice thermal conductivity at 300 K because of the enhanced phonon boundary dispersion. The anisotropy in terms of longer relaxation time results in a high figure of merit (ZT) for n-type doping up to 5.07 and 4.67 for both P/GaN and P/GeC vdWHs at effective temperature. Meanwhile, they also exhibit the average ZT as high as 3.91 (P/GaN) and 3.44 (P/GaC). We also observed that these vdWHs exhibit an excellent conversion efficiency, up to 26% (P/GaN) and 25% (P/GeC) at 700 K. Our findings demonstrate that both vdWHs have practical potential for thermoelectric applications, representing significant progress in developing better thermoelectric devices.
A Comparative Analysis of Genetic Algorithms, Particle Swarm Optimization, and Biogeography-Based Optimization for Social Media Influencer Optimization
Authors: Tyagi Neha , Bhargava Prof.(Dr.) Deepshikha , Ahlawat Anil 
Published: August 2024

Abstract

This study concerns a comparative work of how Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Biogeography-Based Optimization helped to enhance the performance of social media influencers. The fitness function combines engagement rate with conversion and audience growth for influencer marketing is presented in this paper. Results Compared Performance Analysis of Algorithms with their Compute Efficiencies in Different Generation In this paper, In this paper we have raised a question of investigating Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Biogeography-Based Optimization method to optimize selection mechanism for social media influencers. In order to measure the effectiveness of influencer approaches, a fitness function which evaluates engagement rates, conversion and audience growth is incorporated so we can determine the best algorithm. We demonstrate that each of these algorithm modes improves the average and best fitness values over multiple generations, although they exhibit significantly different computational cost performances and consistency in their behaviour.
Contactless monitoring of respiratory rate variability in laboratory animals under anesthesia with a compact 24GHz microwave radar sensor
Authors: Sun Guanghao , Kurosawa Masaki , Ninomiya Yoshiki , Baba Kohei , Son Nguyen Huu , Yen Hoang Thi , Suzuki Satoshi , Kano Yutaka 
Published: August 2024

Abstract

Objective: The objective of this study was to develop and validate a noncontactmonitoring system for respiratory rate variability in laboratory animals under anesthesia using a 24GHz microwave radar sensor. This study aimed to address the need for stress-free monitoring techniques that comply with the 3Rs principle (Reduction, Replacement, and Refinement) in laboratory animal settings.
Methods: Utilizing a 24GHz microwave radar sensor, this system detects subtle body surface displacements induced by respiratory movements in anesthetized rats. The setup includes a 24.05 to 24.25 GHz radar module coupled with a single-board computer, specifically Raspberry Pi, for signal acquisition and processing. The experiment involved four male Wistar rats tracking the variability in their respiratory rates at various isoflurane anesthesia depths to compare the radar system’s performance withreference measurements.
Results: The radar system demonstrated high accuracy in respiratory rate monitoring, with a mean difference of 0.11 breaths per minute compared to laser references. The Pearson’s correlation coefficient was high (0.92, P < 0.05), indicating a strong linear relationship between the radar and reference measurements. The system also accurately reflected changes in respiratory rates corresponding to different isoflurane anesthesia levels. Variations in respiratory rates were effectively mapped across different anesthesia levels, confirming the reliability and precision of the system forreal-time monitoring.
Conclusion: The microwave radar-based monitoring system significantly enhanced the animal welfare and research methodology. Thissystem minimizes animal stress and improves the integrity of physiological data in research settingsby providing a non-invasive, accurate, and reliable means of monitoring respiratory rates.
Multiobjective Optimization for Sizing and Placing Electric Vehicle Charging Stations Considering Comprehensive Uncertainties
Authors: Mohammed Abdallah , Saif Omar , Abo-Adma Maged A , Elazab Rasha 
Published: August 2024

Abstract

The dynamic integration of electric vehicles (EVs) necessitates efficient charging infrastructure. This study introduces an algorithm using particle swarm optimization for the optimal placement and sizing of charging stations, addressing uncertainties in vehicle specifics, road and user factors, station owner considerations, and environmental impacts. Integrating a comprehensive dataset from road networks, driver behaviors, station owners, and EV manufacturers, the algorithm guides station placement to accommodate individualized charging needs. By optimizing charg er types for four distinct EV battery types, the method ensures balanced and efficient infrastructure. The cost‒benefit objective function aligns technical and environmental criteria, offering a sustainable solution for charging station planning. The results indicate that 14 fast charging stations (FCSs) are required along the studied freeway, with a total installation cost of $289,820 and an annual operation cost of $4,223,050. This infrastructure leads to annual CO2 emissions of 1,843,572.57 kg. Stations are strategically placed to optimize coverage and minimize waiting times, with the highest number of chargers at high-traffic nodes. Forecasting individual daily load profiles demonstrates the ability of the algorithm to manage power system behavior, ensure balanced load distribution and prevent grid overload. This approach enhances user satisfaction and economic viability and reduces environmental impact, making it a valuable tool for policymakers, urban planners, and stakeholders in developing sustainable EV charging networks.