bluuebunny/crossref_metadata_2025_split huggingface dataset:
Productivity Management: a Systematic Review of Approaches, Trends and Future Research Agendas
Authors: Barreto Bruna , Lopes Mariana , Caldas Lucas , Campos Lais , Silvério Júlia , Brandão Daniel , Meneses Pedro , Serrano André , Neumann Clóvis 
Published: January 2024

Abstract
This systematic literature review (SLR) aims to explore various approaches and characteristics related to productivity management, addressing an identified gap in the literature. The article seeks to present the current landscape of studies, identify international scientific production trends, and propose an agenda with new challenges for future research. The present SLR used the Scopus database with constructs published from 2018 onwards. Bibliometric results highlight extensive scientific production on productivity, outlining key contributions from authors, countries, and institutions in the field. Thematic analysis provides a comprehensive view of well-developed, specialized, emerging or declining areas in productivity. A detailed analysis of different productivity measurement approaches offers valuable insights into the diversity of practices adopted by reviewed studies. Future challenges and research opportunities include a deeper understanding of qualitative aspects of productivity management, exploring the interaction between efficiency and effectiveness, and investigating productivity management in specific sectors. This SLR provides a solid foundation for future research, emphasizing existing gaps and opportunities for advancements in understanding productivity management.
A Comparative Study on the Tensile Strength of Single Natural Fibers
Authors: Gashawtena Endalkachew , Kidane Addis , Sirahbizu Belete 
Published: January 2024

Abstract
In recent times, material scientists have been paying great attention to the replacement of synthetic materials with natural materials in the essence of minimizing global climate change and environmental pollution. This study intends to extract natural fibers such as sisal, false banana, and banana plant fibers and characterize their mechanical properties. Mechanical and chemical treatment was employed to obtain the optimum cross-sectional area (CSA) of the fibers. The quality of the fiber and the CSA of each fiber was examined using a Zeta 20 optical 3D microscope. The tensile strength of each type of single fiber was evaluated using A Textechno Statimat Me + Tensile Testing Machine with the help of thick paper as a specimen holder. The values of the tensile strength of each type of fiber were compared to see their relative advantage. The result also revealed that chemical treatment increased the quality of the fiber and simplified the determination of the CSA of the fiber from its diameter. Furthermore, the false banana fiber demonstrates a higher tensile strength and tensile strain than those of sisal and banana fibers, but it has a lower modulus of elasticity. The linear density and tenacity of false banana were also lower than sisal fiber, but slightly higher than banana fiber.
A Chemical Interpretation for the Post-Reversion Upturn in the Natural Rubber/Accelerated Sulfur System Based on the Viscoelastic Properties and Crosslink Density Measurements
Authors: Pöschl Marek , Sathi Shibulal Gopi , Stoček Radek 
Published: January 2024

Abstract
The curing cycle of natural rubber (NR) with a conventional accelerated sulfur (CV) system generally exhibits three phases. The induction phase, the crosslinking phase, and the reversion phase. Prolonged curing of NR/CV system even at a temperature of 150°C, can show reversion. Many research reports are available in the literature with reference to the reversion behavior and the subsequent network modifications of natural rubber with accelerated sulfur. However, the literature regarding post-reversion curing behavior is scanty. This article describes the post-reversion upturn of natural rubber with a conventional accelerator sulfur system at a higher curing temperature. A network rebuilding after collapsing the initially formed network due to reversion was identified as the primary reason for the post-reversion upturn. The dynamic rheological testing capability of the Rubber Process Analyzer (RPA) was employed to characterize the network formed during curing, reversion and post-reversion phases. The cure-strain sweep data from the RPA indicated that the shear storage modulus (G') of the broken network increased due to the post-reversion upturn. The chemical crosslink densities of the samples were also found to increase due to the upturn curing behavior. From these experimental results and the information conceived from the previous literature, two plausible mechanisms have been proposed to interpret the post-reversion upturn cure behavior.
Development of a Low-Cost Gas Leakage Detection System With Auditory and Visual Alerts
Authors: Ajinaja Micheal Olalekan , Fakoya Johnson Tunde , Akeem Abiona 
Published: January 2024

Abstract
Household gas leakage stands as a significant contributor to domestic accidents in society. This study focuses on addressing this issue by introducing an affordable and easily accessible device capable of delivering both audio and visual alerts in local dialects based on the language spoken within the household. The system incorporated a 5v buzzer for audio alerts and an LCD for visual alerts, forming the core components of this innovative solution. The coding, executed through Arduino IDE, orchestrated the interaction between the MQ2 sensor and the Arduino Nano, activating auditory alerts via the buzzer and visual alerts through the LCD. The findings highlighted system's efficacy as an affordable safety device for homes, addressing potential dangers associated with gas leaks. The utilization of commonly available components enhanced its cost-effectiveness, ensuring accessibility for households with budget constraints. Furthermore, the system's adaptability was showcased through the programmable LCD, allowing users to display messages in local dialects based on household language preferences. This feature enhanced user experience, making the system more inclusive and aligned with the diverse needs of different households.
Germacrone attenuates memory impairment, hippocampal inflammation, and neurological deficits induced by Lipopolysaccharide in mice
Authors: Zhang Lanyue , Tan Zekai , Wang Ying , Wu Caixia , Xu Anjing , Lian Xiuying , Zeng Yixi , Yuan Yanghe , Li Weini , Peng Jiangling 
Published: January 2024

Abstract
Background
Uncontrolled neuroinflammation contributes to a range of neurodegenerative diseases, as such targeting neuroinflammation may be a promising therapeutic strategy. Germacrone (GE) is the primary ingredient of Curcumae Wenyujin Y.H. Chenet C Ling, one of the most commonly used traditional Chinese medicine boasting anti-inflammatory pharmacology effects. However, there are no reports related to the protective effects of GE on LPS-induced neuroinflammation in mice. In the present study, the therapeutic effects of GE on the LPS-induced neuroinflammation in mice were assessed and the molecular mechanisms regarding neuroinflammation and neuronal apoptotic pathways was investigated.
Methods
C57 mice were treated with LPS for 7 days, followed by treatment with GE for 14 days. Behavioral testing was carried out to examine cognitive functions using the Morris water maze. Nissl Staining was applied to assess pathological changes. Immunohistochemistry was used to analyze the expression levels of inflammatory cytokines TNF-α and Iba-1 in the hippocampus. Immunofluorescence staining was used to detect the inhibitory effect of GE on microglia activation. RNA-seq technique was used to analyze the differential gene regulation of neuroinflammation in brain tissue of LPS-stimulated mice to investigate the anti-inflammation effect of GE.
Results
In C57 mice, GE counteracted cognitive decline, effectively alleviating the neuronal injury induced by LPS, and attenuated the activation of microglia and astrocytes in the cortex and hippocampus. GE significantly reduced the concentration of inflammation factor TNF-α and Iba-1 in both the hippocampus and cerebral cortex, particularly in the former. The gene expression variances post LPS treatment and GE treatment revealed that GE has the potential to diminish neuroinflammation by suppressing the production of inflammatory factors induced by LPS stimulation.
Conclusions
GE effectively counteracted cognitive decline by regulating neuroinflammation through reducing the concentration of inflammation factor TNF-α and Iba-1 in both hippocampus and cerebral cortex in LPS-induced neuroinflammation in C57 mice, providing preliminary experimental evidence that GE is a promising therapeutic agent in neurodegenerative diseases treatment.
Measuring the Unmeasurable through Machine Learning Regressions and Classifications: Multidimensional Poverty Predictions in the Poorest Region of Luzon, Philippines
Authors: Onsay Emmanuel , Rabajante Jomar 
Published: January 2024

Abstract
Poverty is notoriously difficult to quantify, it is multidimensional and is deemed unmeasurable in the field of social science. Current poverty measurements are time-consuming, labor-intensive, and cost-expensive. Hence, policy targeting becomes challenging for policymakers to implement poverty alleviation programs. Thus, this work proposes new measures of poverty in the poorest region of Luzon, Philippines by training and testing the community-based system datasets. We have utilized machine learning regression and classification algorithms matched with advanced econometrics models. For regression, we applied 7 algorithms, for 273 ensemble runs, and for classification, we employed 12 algorithms, for 468 ensemble runs to analyze 34 locals, 4 sectors at disaggregation system, and then combined. Random forest regression outperforms all models with MSE(0.0792), RMSE(0.3298), and R-square(0.92075), while random forest classifier outperforms all models with the highest accuracy(91.08% at random and 95.95% at pipeline). It also validates the existing correlation and causation between multidimensional attributes (27 variables) and poverty outcomes (Incidence, gap, severity, and watts). This work highlights the feasibility of machine learning for poverty prediction that can minimize cost, reduce labor, and maximize time, particularly in the poorest regions of the Philippines. Finally, the output has provided policy targeting tools for poverty reduction for various locals at different poverty configurations.
Antibiotics-associated pseudomembranous colitis: a disproportionality analysis of the US Food and Drug Administration Adverse Event Reporting System (FAERS) database
Authors: Chen Jinhua , Yu Weijiang , Sun Cuicui , Zhang Wenzhou 
Published: January 2024

Abstract
Antibiotics have been established as an important risk factor for pseudomembranous colitis (PMC), a potential life-threatening complication. Evaluating the antibiotics most commonly associated with PMC is of great significance. In this study, we extracted the data from fourth quarter of 2003 to third quarter of 2023 in the US Food and Drug Administration Adverse Event Reporting System (FAERS). Disproportionality analysis was performed to evaluate the potential association between antibiotics and PMC. The results showed that eighty-one antibiotics which met the three algorithms simultaneously were enrolled. A total of 11737133 adverse event (ADE) reports were identified in the FAERS database, of which 1683 reports were associated with the enrolled antibiotics related PMC. It showed that the elderly and females are more susceptible to the antibiotics-associated PMC, especially for patients aged > 60 years. The top twenty-four antibiotics included four penicillins, eleven cephalosporins, three carbapenems, two lincosamides, one cephamycin, one aminoglycoside, one fosfomycin, and one echinocandin. This study also showed that cefoxitin, streptomycin, fosfomycin, and micafungin have a high risk of PMC, but there are few reports in the literature. This is helpful to reduce the potential damage of antibiotics-associated PMC.
Single‐cell and spatial transcriptomics reveal ACKR1+ endothelial cells associated with transcytosis in Leprosy
Authors: Freitas Heloisa Almeida , Paz Mikael Nikson Vilela Tenório da , Silva Gabriel Victor Lucena , Simizo Adriana , Baggio Jussara Almeida Oliveira , Rodrigues Amanda Karine Barros Ferreira , Moreira Jammily Oliveira Vieira , Farias Karol Fireman , Figueiredo Elaine Virginia Martins Souza , Santos Márcio Bezerra , Marques Carolinne Sales , Fraga Carlos Alberto Carvalho 
Published: January 2024

Abstract
Background
Leprosy exhibits a dysregulated immune response, leading to excessive and inefficient inflammatory action. This can result in nerve damage, granuloma formation, and other clinical manifestations.
Methods
Single-cell RNA-sequencing (scRNA-seq) and spatial transcriptomic analyses were applied to explore the intricate cellular landscape of leprosy, focusing on endothelial cells. The study encompasses a dataset of 36,517 cells obtained from normal skin, clinical form lepromatous leprosy (LL), and reversal reaction (RR). We applied advanced techniques, including pseudotime trajectory analysis, cell–cell interaction studies, and high-dimensional weighted gene co-expression network analysis (hdWGCNA).
Results
The profiling of cellular composition revealed significant disparities among leprosy types, emphasizing the role of specific cell types in each condition. CellChat and hdWGCNA analysis unveiled intricate intercellular interactions in the leprosy microenvironment, with a focus on the ACKR1 gene-mediated cytokine regulation in endothelial cells. Disease-associated endothelial cells highlighted a unique gene signature associated with vesicle-related processes, suggesting their involvement in vascular alterations in leprosy. Spatial transcriptome profiling in normal skin and leprosy sections provided insights into the heterogeneity of parenchyma cells, with distinct clusters observed in lepromatous leprosy. ACKR1 exhibited high expression in regions enriched with endothelial cells only in lepromatous leprosy, indicating a localized mechanism for cytokine regulation.
Conclusions
The central involvement of ACKR1 + endothelial cells in transcytosis and cytokine regulation provides potential avenues for therapeutic exploration. This study underscores the importance of advanced technologies in comprehending immune microenvironments for targeted interventions in leprosy and related infectious diseases.
Associations between the gut microbiota and prostatitis: visions from a two-sample Mendelian randomization analysis
Authors: Zhang Yetong , Zhao Mingjian , Ding Xuefei , Cao Fenghong 
Published: January 2024

Abstract
Background
A growing body of research indicates a substantial correlation between the gut microbiota and prostatitis. However, there is still a lack of relevant evidence at the big data level. Two-sample Mendelian randomization was employed to evaluate the association between the gut microbiota and prostatitis.
Materials and methods
We performed a two-sample Mendelian randomization (MR) study by applying combined data on the gut microbiota and prostatitis from the extensive genome-wide association study (GWAS) undertaken by the MiBioGen consortium. The primary method considered to analyze causal relationships was inverse variance weighting (IVW) in the TwoSampleMR (TSMR) framework. Furthermore, we performed various sensitivity analyses to evaluate the reliability of the outcomes obtained through the TSMR.
Result
With the current TSMR analysis, we found that the Parasutterella genus [OR = 0.74,(0.57–0.96),P = 0.023], RuminococcaceaeUCG009 genus [OR = 0.77(0.60–0.98),P = 0.03], Eubacterium(coprostanoligenes group) genus[OR = 0.66(0.45–0.96),P = 0.03], Erysipelatoclostridium genus [ OR = 0.71(0.55–0.92),P = 0.01], Slackia genus [OR = 1.28(1.03–1.59),P = 0.03] may have a protective effect against prostatitis, in the meanwhile Lachnospiraceae (UCG004) genus[OR = 1.54(1.10–2.18), P = 0.01], Faecalibacterium genus[OR = 1.59(1.08–2.34), P = 0.018], Sutterella genus [OR = 1.28(1.03–1.59), P = 0.03], Sterella genus[OR = 1.28(1.03–1.59), P = 0.03], Sutterella genus [OR = 1.58(1.13–2.19), P = 0.007], Paraprevotella genus [OR = 1.28(1.03–1.59), P = 0.03], Odoribacter genus [OR = 1.68(1.01–2.81), P = 0.046] suggested a possible risk factor for prostatitis. There was no adequate evidence of directional horizontal pleiotropy or instrumental variable heterogeneity. The reverse TSMR analysis did not reveal any reverse causal relationship between prostatitis and the gut microbiota.
Conclusion
Our study established a causal relationship between the intestinal flora and prostatitis, suggesting a novel approach for therapeutic investigations of this disease. Specifically, by targeting and regulating the dysbiosis of specific bacterial taxa, prostatitis prevention and treatment can be improved.
Waste Detection and Water Quality Assessment in Aquatic Environments: A Comprehensive Study Using YoloV8 and XGBoost
Authors: Parasar Deepa , Vadalia Shivam R , Chavan Siddharth S , Bhere Krunal R , Nabi Faizan , Patel Abdullah Zuber 
Published: January 2024

Abstract
This research paper presents a structured approach to address the critical concerns associated with water quality assessment and underwater waste detection, employing advanced machine learning techniques. It commences with an exposition on the significance of water pollution's impact on aquatic ecosystems. Subsequently, the methodology employed in this study encompasses the utilization of the YOLOv8 model for the identification of underwater waste, a rule-based classifier for the evaluation of water quality, and the application of the XGBoost algorithm for predicting water potability. The ensuing sections delve into the practical implementation of these components, offering in-depth insights into their technical intricacies and seamless integration. A thorough evaluation follows, substantiating the system's effectiveness and reliability in three key dimensions: underwater waste detection, water quality assessment, and water potability prediction. As indicated by the lower map50-95 score, the Yolov8 model showed impressive precision and recall in recognising positive cases; however, improvements are required for complex object detection scenarios. Analysing the confusion matrix revealed particular categories that needed to be improved. On the other hand, the XGBoost classifier produced encouraging outcomes, demonstrating excellent accuracy, f1 score, precision, and recall in a variety of categories, underscoring its efficacy in precise sample class prediction. The research paper concludes by underscoring the transformative potential of this multifaceted approach in bolstering environmental conservation and safeguarding aquatic ecosystems against the pernicious effects of water pollution.
Knowledge of, first-aid measures and attitudes towards epilepsy among university students in Syria
Authors: Darra Ahmad Al , Thomas Thomas , Latifeh Youssef 
Published: January 2024

Abstract

Background and Aim:
Patients with epilepsy generally face misconceptions and negative attitudes about various aspects of the disease and are vulnerable to physical injuries during seizures. Lack of awareness of first aid measures leads to inappropriate actions while trying to provide assistance to patients. Therefore, our study aims to provide knowledge of first aid procedures and trends. Towards epilepsy among university students in Syria.
Methods and material:
A cross-sectional study was conducted during the period from 5/1/2023 to 26/12/2023 in Damascus, Syria. Data were collected through electronic questionnaires distributed randomly on social networking sites. The characteristics section included (age, gender, university branch, the first year), the second section included an awareness section (general awareness, causes, symptoms, triggers of seizures, first aid measures, and recommended treatments).
Results:
In general, 950 male and female students participated in the survey, and the students’ knowledge of epilepsy was very high, but there was little knowledge about the spread of epilepsy, the causes of epilepsy, the characteristics of epilepsy, the symptoms and signs of epilepsy, and the treatment of epilepsy. There was a significant increase in positive attitudes when seeing an affected person. With epilepsy, but on the other hand, negative attitudes were high, and the percentage of students’ knowledge on the knowledge and stigma scale was good, and the average of the scale among the students was (20.23 degrees).
A comprehensive review of machine learning prediction in the production of bio-oil from lignocellulose via pyrolysis
Authors: Lee Hyojin , Choi Il-Ho , Hwang Kyung-Ran 
Published: January 2024

Abstract
Bio-oil produced through pyrolysis of lignocellulosic biomass has recently received significant attention due to its possible uses as a second-generation biofuel. The yield and characteristics of produced bio-oil are affected by reaction conditions (reactor type, particle size, feed rate, operating temperature, heating rate, retention time, etc.) and the type of feedstock that is used (softwood, hardwood, agricultural plant residues, miscanthus, etc.). Recently, machine learning (ML) techniques have been widely employed to forecast the performance of the pyrolysis and the characteristics of bi-oil. In this study, a comprehensive review of ML research on bio-oil has been carried out. Regression methods were most frequently employed to build prediction models. The top five ML methods for bio-oil research were random forest, artificial neural network, gradient boosting, support vector regression, and linear regression. In addition, users frequently extract features using their own knowledge and restricted datasets were employed I previous studies. We highlighted the challenges and potential of cutting-edge ML techniques in bio-oil production.
Corruption in apartheid South Africa under John Vorster: a case study
Authors: Ntuli Hebert Sihle 
Published: January 2024

The object of research: This article explores corruption during apartheid South Africa. The first part describes corruption and articulates or presents its effects on service delivery.
Investigated problem: This study examines John Vorster’s role in corruption during the 1970’s. It argues that Vorster and some cabinet ministers were implicated in corrupt practices during the period in question.
The main scientific results: The findings of this study reveal that corruption was rife in South Africa during apartheid era; it is not new. This research study adds to our understanding of political oddities in the 1970’s that affected the subsequent years.
The area of practical use of research results: The value of this study is that it may be possible to determine historical patterns and/or responses that can be applied in fighting corruption in present day South Africa. It concludes by stating that to combat corruption would require putting in place appropriate anti-corruption and legal machinery; and prosecute, without fear or favour, violations of public service codes of conduct.
Innovative technological product: The historical patterns investigated in this article can inform government policy on how to provide for the strengthening of measures to prevent and combat corruption and corrupt activities in modern South Africa; as well as to provide for the investigative measures in respect of corruption and related corrupt activities.
Scope of the innovative technological product: The Prevention and Combating of Corrupt Activities Act, 2004, provides for the establishment and endorsement of a Register in order to place certain restrictions on persons convicted of corrupt activities relating to tenders and contracts. Further, South Africans have welcomed the National Anti-Corruption Strategy which is a whole-of-society effort that envisions an ethical and accountable state, business and society characterized by high level of integrity and respect for the rule of law.