bluuebunny/crossref_metadata_2025_split huggingface dataset:
Is the association of physical activity with mental burden mediated by quality of life? A cross-sectional study with undergraduate students
Authors: Silva Michael Pereira da , Matias Thiago Souza , Demenech Lauro Miranda , Dumith Samuel Carvalho 
Published: December 2024

Abstract

Background
The literature lacks studies investigating the role of quality of life in the relationship between physical activity and mental health. The objectives were: i) to analyze the association of physical activity with mental burden among college students and ii) to determine whether the domains of quality of life mediate the association between physical activity and mental burden.
Methods
A cross-sectional study with a random sample of undergraduate students from southern Brazil was conducted. The data collection was carried out in 2019 using self-administered questionnaires. Depression, anxiety, and stress outcomes were clustered, resulting in three clusters (very high, high, and low risk of mental burden). A general structural equation model was used to examine mediation.
Results
This study analyzed data from 766 individuals (66% of the eligible sample). The prevalence of active individuals (150 min/wk or more) was 2.5-fold greater for cluster 3 of mental burden (lower risk) compared to cluster 1 (higher risk). The physical and psychological domains of quality of life mediated the association between physical activity and mental burden.
Conclusion
Physical activity had a protective effect on mental burden, partially mediated by physical and psychological domains of quality of life.
Recent Advancements in Grad-CAM and variants: Enhancing Brain Tumor Detection, Segmentation, and Classification
Authors: Kumar Krishan , Jyoti Kiran 
Published: December 2024

Abstract

Brain tumors, caused by abnormal tissue growth in the brain, can significantly impair brain functions and pose significant health risks. As the tumor progresses to higher stages, the patient's prognosis and survival decline, resulting in a high mortality rate. With advances in medical imaging, particularly the use of MRI, AI approaches have emerged as powerful tools for detecting, segmenting, and classifying brain tumors. CNN and hybrid models such as Vision Transformers (ViTs) have provided promising insights in this area. Despite their high accuracy, but the reasoning behind the prediction often remained unanswered. AI models lack transparency and interpretability, paving the way for the development of explainable AI methods in diagnosing brain diseases. In recent years, gradient weighted class activation mapping (Grad-CAM) and its variants have emerged as powerful techniques for visualizing and interpreting deep learning models in medical imaging tasks, including brain tumor detection, segmentation, and classification. This paper provides a comprehensive overview of Grad-CAM and its improvements, with particular emphasis on their applications in brain tumor analysis. In this article, we reviewed the 31 research papers based on data from various research databases. This review highlights the importance of interpretability in deep learning for clinical applications and explores how Grad-CAM can complement traditional metrics to provide deeper insights into model decisions. The results provide valuable guidance for researchers developing explainable AI frameworks for accelerating brain tumor analysis, with the objective of developing trust, efficiency and clinical utility in resource-limited settings.
Weakly supervised free-space segmentation by fusing spatial priors and region features for auto-driving
Authors: Huang Dongbo , Wang Hui , Zhao Yuqian , Guo Feifei , Zhang Fan , Chen Pei , Yang Chunhua , Gui Weihua 
Published: December 2024

Abstract

Weakly supervised semantic segmentation can significantly alleviate the annotation burden of the pixel-level collection used in full supervision. However, most existing works are based on simple images and only include a few tags, which are not applicable to free-space segmentation under complex driving scenes. In this study, we develop an effective weakly supervised framework with image-level label for free-space segmentation by incorporating the spatial priors with geometric context of road. The proposed method jointly leverages the locating capability of image tags and low-level structure information of superpixels, and fuses spatial weights and superpixel region features by a region-based clustering method. These strategies guarantee the satisfying segmentation results while facing the complex driving scenes. Extensive experimental results on the Cityscapes datasets show that our work outperforms some competing weakly supervised methods in terms of intersection over union (IoU), and is a feasible way to perform free-space segmentation in complex environments for auto-driving application.
Transparelect: A Comprehensive Approach to Biometric-Enabled Electronic Voting
Authors: M Shunmugathammal , k Lalitha , V Mughuntha , B Harish , BM Sai Akash , KB Nithish 
Published: December 2024

Abstract

Ensuring fair and transparent elections is reliant on the authenticity of voters and the purity of ballots cast. This paper discusses the way that double voting and fraudulently verifying voters can be solved with biometric technologies incorporated together with machine learning. To do this, a dual authentication system is proposed which uses a fingerprint sensor for utmost accuracy during identification, coupled with face recognition in order to minimize instances of dual registration in traditional (Electronic Voting Machine) EVM. The system continuously checks the identities of individual voters while relaying the details of their verification process to a central control unit; this increases both effectiveness and safety. Besides, this research develops as well as tests algorithms of machine learning where Neural Networks (NN) are used to estimate turnout percentages. In addition, techniques associated to data pre-processing have been utilized in order to improve accuracy. Consequently, it shows how proposed NN based models work when predicting voting results hence contributing towards better secured and freer from any form manipulation polling systems.
Latent profile analysis of mental workload among emergency department nurses: a cross-sectional study
Authors: Hao Xiaoyan , Dai Yueguang , Jia Shengjie , Liu Shuqin , Zhao Chunling , Liu Xiaomin 
Published: December 2024

Abstract

Aim Emergency department nurses experience varying degrees of mental workload due to various reasons. The group with medium to high levels of mental workload needs to be given attention. There is limited research on the potential profiles of mental workload among emergency department nurses. The purpose of this study is to identify different potential profiles of mental workload among emergency department nurses and analyze influencing factors.Design: A cross-sectional study.Methods This study follows the STROBE guidelines. This study used the NASA-TLX scale to assess the mental workload of emergency department nurses and employed latent profile analysis to identify different potential profile of their mental workload. Statistical methods Pearson chi-square and logistic regression analyses were performed to identify factors affecting the mental workload of emergency department nurses.Results A total of 305 emergency department nurses completed the survey, with the majority experiencing moderate to severe mental workload. mental workload is influenced by multiple factors and is a complex and dynamic process. The main factors that affect mental workload included age(year), marital status, monthly income(RMB), support style, coping style, and personality traits.Conclusion The results of this study suggested that mental workload experienced by emergency department nurses was widespread. We should pay attention to the mental needs of emergency department nurses and pay attention to their mental health status.
Impact of repositioning errors on the aerodynamic performances in cycling
Authors: Foguenne Léonore , Schwartz Cédric , Andrianne Thomas 
Published: December 2024

Abstract

Aerodynamic drag is a significant force in cycling, especially at speeds above 40 km/h, where it can account for up to 90% of total resistance. Accurate aerodynamic assessment is essential for optimizing cycling performance through equipment and positional adjustments. However, traditional wind tunnel testing uses static models that fail to replicate the dynamic nature of actual cycling, limiting their ability to investigate biomechanical or physiological factors. This study quantifies the variability introduced by cyclists' repositioning during wind tunnel tests, compares it to drag differences from equipment changes, and evaluates the effectiveness of a real-time feedback system in reducing this variability. The study involved three phases: baseline helmet testing on a static mannequin, development of a position-tracking system, and wind tunnel testing with one amateur and one advanced cyclist. Differences in drag area (CDA) between aero-helmets were around 0.0032 m². Repositioning variability without feedback ranged from 0.003 m² to 0.072 m² for the amateur cyclist and from 0 m² to 0.020 m² for the advanced cyclist. Feedback reduced the amateur cyclist’s variability to 0.005 m² to 0.027 m², comparable to the advanced cyclist. However, feedback had limited effect on the advanced cyclist, with a drag variability of 0 m² to 0.013 m². These findings suggest that repositioning errors can overshadow aerodynamic gains from equipment, particularly for less experienced cyclists. While feedback helps reduce these errors, improved testing methods are needed to fully account for rider variability and optimize performance.
Environmental DNA metabarcoding pinpoints changes in microbial community assemblages due to urban pollution in a tropical megacity (Mexico City)
Authors: Cruz-Cano R , Bretón-Deval L , Martínez-García M , Díaz-Jaimes P , Kolb M 
Published: December 2024

Abstract

The global water crisis affects water quality and aquatic ecosystems leading to shifts in the structure of microbial community that can be used for monitoring environmental change. The current study aims to use eDNA metabarcoding to elucidate the structure and diversity of microbial communities along a pollution gradient in a tropical river. Sampling was carried out at four sites, along an anthropogenic disturbance gradient in Mexico City (Magdalena River). The results show clear differences in the composition of the prokaryotic and microeukaryotic communities between sites. Bacterial communities in sites with low to moderate disturbance were associated with nitrogen biogeochemical processes or plant-microbe interactions, while those in sites with moderate to high disturbance levels were associated with enteric, nosocomial, or fecal nature. Microbial communities in peri-urban sites had a greater diversity of phyla, while microeukaryotic communities decreased in the number of present phyla, as the gradient of human influence progresses, showing that 2 phyla together contribute with a relative abundance greater than 75% through the year. We propose that the characterization of the microbial community structure is better for identifying anthropogenic influences on lotic systems than the use of single species.
Team Virtue as a Predictor of Transactional Style
Authors: Sharma Santosh Kumar , Khan Imran Ahmed , Indiran Jayasri 
Published: December 2024

Abstract

In the history of organizational development, there was a time when performance of an individual employee was given significant weightage especially during performance appraisal. However, with the changing landscape of organizational dynamics, focus of performance measurement has been shifted from individual to team level. The possible reason for this tectonic shift is the evaluator’s mindset who work as a business leader most of the times and believes that if an employee is not able to work as a team member, his or her performance contribution can be neglected from the organizational perspective. With this backdrop, it is assumed in the present research paper that if an employee has any kind of team virtue, her or him transactional style can be predicted to a reasonable extent. Based on the predicted transactional style, some kind of training interventions can be applied especially in the areas like communication, team building and similar ones. Data has been collated through secondary (literature review) and primary sources (questionnaire-based survey). Based on correlational and regression analysis through SPSS (version 25), results have been discussed followed by conclusions and implications.
Enhancing Text Quality with Human-Machine Collaboration: A Refinement Approach
Authors: Sun Yicheng , Wang Yi , Yang Jianwei , Liu Tao , Yang Hanbo 
Published: December 2024

Abstract

Human writing often exhibits a range of styles and levels of sophistication. However, automated text generation systems typically lack the nuanced understanding required to produce refined and elegant prose. Due to the inherent one-to-many relationship between inputs and outputs in natural language generation tasks, achieving annotator consistency is challenging. This complexity makes the annotation process considerably more difficult compared to tasks focused on natural language understanding. Our study focuses on the typical task of text refinement, which faces annotation difficulties, aiming to generate sentences with more elegant expressions while preserving the original semantics of the input sentence. This paper proposes a semi-automatic data construction method that combines auto-generation with human judgment. Initially, this method translates collected sentences containing elegant expressions into ordinary expressions through back translation. Subsequently, in an iterative quality control process, data filtering and human judgment are introduced to screen the auto-generated data based on quality standards, resulting in a large-scale text refinement dataset. By replacing manual annotation with human judgment and involving only a small amount of data for human judgment in each iteration, this method significantly reduces annotation difficulty and workload. With minimal human effort, it acquires a substantial amount of labeled data for text refinement, laying a foundation for further research in the field.
Development of Conductive Hydrogel-Based Anode Materials for Lithium-Ion Batteries
Authors: Yimer Wondwossen Melaku 
Published: December 2024

Abstract

The development of rechargeable lithium-ion batteries with high-strength density and long-cycle lifestyles is essential to address the growing demand for dense storage in various technology applications, including portable electronics, hybrid and electric vehicles, and power system. grid-scale energy storage. All of these must be sustainable electrochemically and generally robust. The main limitation in recognizing these functions is the lack of electrodes with excellent mechanical and electrochemical properties. CHs combine the electrical conductive properties of metals or semiconductors with the unique properties of hydrogels and are important for forming and assembling lithium ion battery electrodes. Which can contain a large amount of electrolyte solution in the conductive network of 3D nanostructures, providing a large number of sites on the surface for the required electrochemical reactions. Until now, 3D nanostructured CH has shown excellent performance when used as an electrode materials for LIBs. Future efforts are based on improving the intentional CH with controllable size, composition, shape, and interface. In this review, we focus on fabrication of CH, how conductive hydrogels are incorporated into the active materials (Si nanparticles, tin-metal alloy and transition metal oxides) of LIBs, and show some of the hydrogel electrode materials in LIBs based on Si, tin alloys and transition metal oxides based hydrogels.
Climate change trends in the Southeastern Anatolia region of Türkiye: precipitation and drought
Authors: Kartal Veysi , Yavuz Veysel Süleyman , Ariman Sema , Kaya Kübra , Alkanjo Safa , Simsek Oguz 
Published: December 2024

ABSTRACT
Drought, earthquake, flood, and fire are disasters whose effects occur after a more extended period than other disasters. Meteorological drought is called the beginning of drought types. In this study, trend analyses and temporal changes in temperature, precipitation, and drought index values were carried out between 1981 and 2022 at three meteorological observation stations in the Southeastern Anatolia region of Türkiye. Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index, China-Z Index, and Effective Drought Index methods were used for drought analysis, while Sen's slope, Mann–Kendall, and innovative trend analysis methods were used to detect the trend in precipitation. It was determined that precipitation generally had tended to decrease, and drought increased since 1996. Although every type of dry and wet periods has occurred, normal dry periods were observed more. In the spatial distribution of drought, the inverse distance weighted method gives larger areas with more extreme drought and wet values than the Kriging method. The increase in extreme values in the region indicates that the severity of drought will increase. It has been determined that the region's water resources and agricultural activities are under pressure due to climate change and drought.
TRIBUTAÇÃO IMOBILIÁRIA E DIREITO À CIDADE:
Authors: Carvalho Guimarães Leôncio Érica Milena , Ferreira Cardoso da Silva Alexsandro 
Published: December 2024

Este artigo analisa a tributação imobiliária em Natal-RN a partir do IPTU e do ITBI, impostos reconhecidos pelo potencial de recaptura de mais-valias urbanas. O município analisado possui uma dinâmica imobiliária acentuada, mas ainda carece de um planejamento urbano que se conecte a tributação municipal e possibilite a distribuição mais igualitária dos bônus dessa arrecadação. Nesse sentido, é feita uma reflexão sobre a capacidade de captar recursos para o desenvolvimento urbano no contexto de uma agenda de inflexão ultraliberal no país, que repercute diretamente nas cidades, historicamente dependentes de recursos dos demais entes federativos para implementar infraestrutura urbana. Diante disso, analisa-se a legislação municipal desses dois impostos, as receitas provenientes de ambos e as despesas do município com desenvolvimento urbano e, por fim, a distribuição da arrecadação do IPTU e do ITBI nos bairros, distribuídos nas quatro regiões administrativas do município, bem como por tipologias distintas. A partir das análises dos dados questiona-se como esses impostos, aqui compreendidos enquanto instrumentos urbanísticos e tributários ainda podem ser utilizados em prol do financiamento das cidades, para a efetivação da função social da propriedade e, numa perspectiva ampliada, na garantia do direito à cidade à população.
Design of Novel Acat Inhibitors as Potent Anti-Hyperlipidemic Agents Using Chemometric Approaches
Authors: Khan Shagufta , Paliwal Sarvesh , Jain Smita , Sharma Pragya 
Published: December 2024

Aim:
A 2D QSAR study of acyl-coenzyme A (CoA): cholesterol acyltransferase (ACAT)
inhibitors revealed that electronic, topological, and steric properties are important structural features
required for activity against ACAT.

Background:
In order to interpret the evidence encrypted by the molecular structure of the compounds,
a standard physicochemical descriptors-centered, and Quantitative Structure-Activity Relationship
(QSAR) approach was implemented on a data set of Indoline derivatives were reported to be
acyl-coenzyme A (CoA): cholesterol acyltransferase ACAT inhibitors.

Objective:
The ACAT enzyme plays an important role in the absorption of dietary cholesterol. Therefore,
the inhibition of ACAT is a key strategy or primary objective for the treatment of hypercholesterolemia
and atherosclerosis.

Method:
Chemo metric models were designed by inserting a battery of statistical techniques in the
current study that demonstrate the linear approaches of analysis, including multiple linear regression
(MLR), partial least square PLS, and non-linear methods such as artificial neural networks (ANN).

Result:
The activity contributions of these molecules were analyzed through regression equation, and
the best QSAR model was created with an excellent correlative and predictive ability. Significant statistical
values S = 0.35, F = 60.30, r = 0.92, r² = 0.85, r² (CV) = 0.82 of the designed models were obtained
using stepwise MLR and a comparable PLS and FFNN model with r² (CV) = 0.82, 0.88 and
0.86 respectively and the relevant descriptors like inertia moment 1 size, Kier Chiv4 (cluster) index,
Kier Chiv6(ring) index offered important information regarding this model.

Conclusion:
The model reveals that inertia moment 1 size, Kier Chiv4 (cluster) index, and Kier
Chiv6 (ring) index are prerequisite descriptors to determine other promising ACAT antagonists with
high and liable potency against the target. Therefore, these characteristics may be used efficiently for
the design and evaluation of active compounds as new ACAT inhibitors thanks to their utilization.
Antioxidant Effect of the Aerial Part of P. granatum: Exploring the Protective and Restorative Effect in Gentamycin and Cisplatin-Induced Hepatorenal Toxicity in Rat Models
Authors: Desai Charmi , Srivastava Rajnish , Kumar Manish 
Published: December 2024

Aim:
The present study aimed to explore the hepatorenal efficacy of ethanolic and
hydroalcoholic extract against Gentamicin and Cisplatin-induced toxicity in experimental rats.

Background:
The current research focuses on the characterization and evaluation of the hepatorenal
efficacy of P.granatum extracts on cellular and tissue models, particularly in terms of its restorative
actions following cytotoxic damage induced by Gentamicin and Cisplatin. This work builds upon
several key areas of contemporary scientific research.

Objective:
The objective of the current investigation was to establish an association of oxidative
stress in hepatorenal insufficiency caused by Gentamicin and Cisplatin xenobiotics and its amelioration
with the antioxidant activity of ethanolic extract of Punica granatum (EEPG) and hydroalcoholic
extract of Punica granatum (HAEPG).

Methods:
Using ascorbic acid as a standard, the in vitro antioxidant activity of EEPG and HAEPG
was assessed using the DPPH method. The hepatorenal efficiency of the EEPG and HAEPG were
studied in Gentamicin and Cisplatin-induced models. The hepatorenal toxicity was induced by
100mg/kg/day i.p. of Gentamicin for 12 days and 1.5mg/kg/day i.p. cisplatin for 3 weeks in Wistar
albino rats. Lipid profile, serum hepatorenal markers, and hepatorenal tissue oxidative markers such
as, CAT, MDA, GSH, and SOD were estimated to assess the extent of hepatorenal efficiency. Using
Masson trichrome (MT) stained tissue sections, renal and hepatic tissue damage was assessed. The
degree of renal tissue damage was evaluated using tubular necrosis, perivascular edema, intratubular
proteinaceous cast, and vascular congestion.

Result:
In vitro studies have shown that the HAEPG containing higher total phenolic and flavonoid
content, exhibits greater antioxidant activity compared to the EEPG. The severity of hepatotoxicity
and renal toxicity was found to be more severe in cisplatin than Gentamicin. The Cisplatin treatment
more severely affects the level of CAT, GSH, and SOD, respectively compared to Gentamicin induction.
Cisplatin also significantly decreased SOD and increased MDA levels. Treatment with EEPG
and HAEPG demonstrated beneficial effects by reducing the levels of oxidative enzymes, which contributes
to the restoration of hepatorenal damage due to their antioxidant properties.The MT panels of
the treated groups revealed and supported hepatorenal regenerative changes.

Conclusion:
The antioxidant properties of EEPG and HAEPG showed beneficial effects and ameliorated
the levels of tissue hepatorenal oxidative enzymes and were found to possess restoration of
hepatorenal damage in a dose-dependent manner.