bluuebunny/crossref_metadata_2025_split huggingface dataset:
Work Conflict, Stress, and Job Satisfaction: A Study of Bus Crew Employees
Authors: Cahya Elit Siendhang , Ubaidillah Hasan 
Published: April 2023

This study aimed to investigate how workload, physical work environment, and work conflict affect job satisfaction, with job stress as a moderating variable, among bus crew employees at PO Pratama Putra. The research design used was quantitative, with a population of 52 employees and a non-probability sampling technique called saturated sampling. Smart PLS 3.2.8 software was used for data analysis. The results showed that workload and physical work environment did not have a significant effect on job satisfaction, while work conflict had a significant effect. However, workload and physical work environment did not have a significant effect on job satisfaction through job stress as a moderating variable, but work conflict did. Furthermore, job stress had a significant effect on job satisfaction. The implications of this study are that employers should prioritize conflict management strategies to enhance job satisfaction, and employees should focus on managing job stress to improve their job satisfaction.
Highlights:

Work conflict had a significant effect on job satisfaction among bus crew employees, highlighting the importance of conflict management strategies in the workplace.

Job stress was found to have a significant effect on job satisfaction, emphasizing the need for employees to focus on managing their stress levels to improve their overall job satisfaction.

Workload and physical work environment were not significant predictors of job satisfaction, indicating that employers may need to focus on other factors to improve their employees' job satisfaction.
Taxpayer Awareness and Knowledge Boost Tax Compliance during COVID-19: Role of Socialization
Authors: Shoffan Muchammad Abi , Ernandi Herman 
Published: April 2023

The aim of this study is to investigate the influence of taxpayer attitude, awareness, and tax knowledge on tax compliance during the COVID-19 pandemic, with tax socialization as a moderating variable. The study focuses on 33 businesses registered under the Indonesian Contractor and Mechanical Association (AKLI) Sidoarjo branch in 2022, using purposive sampling criteria. The SmartPLS (Partial Least Square) analysis was used to analyze the data. The results indicate that taxpayer attitude does not significantly affect tax compliance, while taxpayer awareness and tax knowledge do have an impact. Tax socialization moderates taxpayer awareness but does not moderate taxpayer attitude or tax knowledge on tax compliance. The study implies that tax authorities should prioritize tax socialization programs to increase taxpayer awareness and ultimately improve tax compliance during the COVID-19 pandemic.
Highlights:

Taxpayer awareness and knowledge have a significant impact on tax compliance during the COVID-19 pandemic.
Tax socialization moderates taxpayer awareness but does not affect taxpayer attitude or tax knowledge on tax compliance.
Tax authorities should prioritize tax socialization programs to increase taxpayer awareness and ultimately improve tax compliance during the COVID-19 pandemic.
Improving Employee Performance: The Impact of Job Analysis, Work Discipline, and Workload
Authors: Jannah Safira Nur , Sumartik  
Published: April 2023

This study aimed to investigate the impact of job analysis, work discipline, and workload on employee performance at PT.ALP Petro Industry in Pasuruan, using a quantitative approach. The population of the study consisted of 70 employees, and a sample size of 60 respondents was selected using random sampling. The data was analyzed using SPSS software. The findings of the study indicated that job analysis, work discipline, and workload had a significant effect on employee performance, both partially and simultaneously. These results suggest that improving job analysis, work discipline, and workload management can lead to better employee performance. The implications of this study are that companies should prioritize employee job analysis, work discipline, and workload management to improve overall performance and productivity.
Highlights:

The study highlights the significant impact of job analysis, work discipline, and workload on employee performance, both partially and simultaneously.

The use of a quantitative approach and SPSS software for data analysis adds to the rigor of the study.

The study's implication is that companies should prioritize improving job analysis, work discipline, and workload management to enhance employee performance and productivity.
Unlocking Profitability in Indonesian Banks: The Impact of Liquidity and Working Capital Turnover
Authors: Rizaldy Rahmat , Hariasih Misti 
Published: April 2023

This scientific article examines how liquidity, leverage, and working capital turnover affect profitability in the Indonesian banking sub-sector financial companies listed on the Indonesia Stock Exchange between 2017 and 2021. The study used a sample of 15 companies selected randomly, and data analysis was done using SPSS version 22 for Windows. The results indicate that liquidity and working capital turnover significantly impact profitability, either partially or simultaneously. However, the adjusted R-square test revealed that only 14.8% of the variation in profitability is influenced by these variables, while the remaining 85.2% is influenced by other factors not studied in this research. The implication of this study is that Indonesian banking sub-sector financial companies should focus on improving liquidity and working capital turnover to increase profitability.
Highlights:

Liquidity and working capital turnover have a significant impact on profitability in the Indonesian banking sub-sector financial companies.
Improving liquidity and working capital turnover can increase profitability in these companies.
Other factors not studied in this research also play a significant role in influencing profitability in the Indonesian banking sub-sector financial companies.
Digital Trends of Criminology and Criminal Justice of the 21st Century
Authors: Asli M. R. 
Published: April 2023

Objective: to define the key trends in the development of criminology and criminal justice under significant broadening of digitalization and using modern technologies.Methods: the priority of analytical method combined with descriptive method provided an optimal set of tools for searching and revealing the main digital trends in the development of criminology and criminal justice in the 21st century.Results: the growing dependence was revealed between criminal-legal science and digital technologies, which leads to the change in essence and types of contemporary criminality, models of criminals’ behavior, methods and mechanism of crime control and prevention in the light of requirements of criminal policy and justice. The dual role of the global digitalization trend is highlighted, the achievements of which are used both by the agencies of criminal justice system (in particular, for crime control, management and prevention) and criminals when implementing their criminal intents. It was determined that the essential transformation of criminology and criminal justice is largely caused by a dramatic development of digitalization in the 21st century, as well as by the modern technologies created on its basis, which appear to be more effective than the standard methods of traditional criminology, including quantitative and qualitative estimations, observation, interviews, polls, etc.Scientiﬁc novelty: new spheres of criminal-legal knowledge are introduced, as well as the corresponding disciplines formed exclusively under the influence of digitalization, such as cyber criminology and cyber victimology; algorithmic (computational) criminology, based on actuarial justice and the theory of risks, is highlighted as the most recent trend in criminological science.Practical signiﬁcance: the account of trends and positive experience gained in the sphere of digitalization determines the successful solution of the tasks associated with crime counteraction, transformation of approaches to the content, goals and methodology of applied criminology and criminal justice. The global megatrend of digitalization essentially changes the appearance of the criminal-legal science, sets the new theoretical and applied directions of its development. Timely upgrade and adaptation of knowledge, skills and capabilities in compliance with the achievements of digitalization will allow criminology and criminal justice to correspond to the tasks of the new millennium.
Identification of biomarkers associated with heart failure caused by idiopathic dilated cardiomyopathy using WGCNA and machine learning algorithms
Authors: Sun Mengyi , Li Linping 
Published: April 2023

Abstract
Background: The genetic factors and pathogenesis of idiopathic dilated cardiomyopathy-induced heart failure (IDCM-HF) have not been understood thoroughly; there is a lack of specific diagnostic markers and treatment methods for the disease. Hence, we aimed to identify the mechanisms of action at the molecular level and potential molecular markers for this disease.
Methods: Gene expression profiles of IDCM-HF and non-heart failure (NF) specimens were acquired from the database of Gene Expression Omnibus (GEO). We then identified the differentially expressed genes (DEGs) and analyzed their functions and related pathways by using “Metascape”. Weighted gene co-expression network analysis (WGCNA) was utilized to search for key module genes. Candidate genes were identified by intersecting the key module genes identified via WGCNA with DEGs, further screened via the support vector machine-recursive feature elimination (SVM-RFE) method and the least absolute shrinkage and selection operator (LASSO) algorithm. At last, the biomarkers were validated and evaluated the diagnostic efficacyby the area under curve (AUC) value, and further confirmed the difference expression in the IDCN-HF and NF groups using an external database.
Results: We detected 490 genes exhibiting differential expression between IDCM-HF and NF specimens from the GSE57338 dataset, with most of them being concentrated in the extracellular matrix of cells related to biological processes and pathways. After screening, thirteen candidate genes were identified. Aquaporin 3 (AQP3) and cytochrome P450 2J2 (CYP2J2) showed high diagnostic efficacyin the GSE57338 and GSE6406 datasets, respectively. In comparison to the NF group, AQP3 was significantly down-regulated in the IDCM-HF group, while CYP2J2 was significantly up-regulated.
Conclusion: As far as we know, this is the first study that combines WGCNA and machine learning algorithms to screen for potential biomarkers of IDCM-HF. Our findings suggest that AQP3 and CYP2J2 could be used as novel diagnostic markers and treatment targets of IDCM-HF.
Autologous mesenchymal stromal cells embedded with Tissucol Duo® for prevention of air leak after anatomical lung resection: results of a prospective phase I/II clinical trial with long-term follow-up
Authors: Jiménez Marcelo F. , Gomez-Hernandez M. Teresa , Villarón Eva M. , López-Parra Miriam , Sánchez-Guijo Fermin 
Published: April 2023

Abstract
BACKGROUND: Prolonged air leak (PAL) is the most frequent complication after pulmonary resection. Several measures have been described to prevent the occurrence of PAL in high-risk patients, however, the potential role of mesenchymal stem cells (MSCs) applied in the parenchymal suture line to prevent postoperative air leak in this setting has not been fully addressed.
OBJECTIVE: To analyse the feasibility, safety and potential clinical efficacy of the implantation of autologous MSCs embedded in Tissucol Duo® as a prophylactic alternative to prevent postoperative prolonged air leak after pulmonary resection in high-risk patients.
STUDY DESIGN: Phase I/II single-arm prospective clinical trial.
METHODS: Six patients with high risk of PAL undergoing elective pulmonary resection were included. Autologous bone marrow-derived MSCs were expanded at our Good Manufacturing Practice (GMP) Facility and implanted (embedded in a Tissucol Duo® carrier) in the parenchymal suture line during pulmonary resection surgery. Patients were monitored in the early postoperative period and evaluated for possible complications or adverse reactions. In addition, all patients were followed-up to 5 years for clinical outcomes.
RESULTS: The median age of patients included was 66 years (range: 55-70 years) and male/female ratio was 5/1. Autologous MSCs were expanded in five cases, in one case MSCs expansion was insufficient. There were no adverse effects related to cell implantation. Regarding efficacy, median air leak duration was 0 days (range: 0-2 days). The incidence of PAL was nil. Radiologically, only one patient presented pneumothorax in the chest x-ray at discharge. No adverse effects related to the procedure were recorded during the follow-up.
CONCLUSIONS: The use of autologous MSCs for prevention of PAL in patients with high risk of PAL is feasible, safe, and potentially effective.
TRIAL REGISTRATION: no. EudraCT: 2013-000535-27. Clinicaltrials.gov idenfier: NCT02045745.
Pillars for successful operationalization of One Health as an ecosystem approach: Experience from a human-animal interface in the Maasai Steppe in Tanzania
Authors: Gwakisa Paul , George Janeth , Sindato Calvin , Ngonyoka Anibariki , Nnko Happiness , Assenga Justine , Kimera Sharadhuli I , Nessele Moses Ole 
Published: April 2023

Abstract
Background Solving complex public health challenges requires integrated approaches to health, such as One Health. A key element of the One Health approach is the interrelationship between human, animal and environmental health and the associated multistakeholder collaboration across many cultural, disciplinary, institutional and sectoral boundaries. Here we describe a pragmatic approach for One Health operationalisation basing on our long-term engagement with communities faced with health challenges in a human-livestock-wildlife interface in the Maasai steppe in northern Tanzania.Methods Using a qualitative study design we performed an outcome mapping to document insights on results integration from our previous project. Data were collected through participatory community meetings, in-depth interviews and field observations. Field notes were coded and analysed using inductive thematic analysis.Results We found that effective implementation of One Health interventions in complex ecosystems works best by understanding local conditions and their context and by working closely with the local people and relevant disciplinary players as one complex adaptive system. Community engagement, systems analysis, transdisciplinarity as well as political commitment played critical roles in successful operationalization of One Health. We have further emphasized that project ownership is as important to the local community as it is to the researchers. When used in combination, these elements (community engagement, systems analysis, transdisciplinarity) provide essential pillars for co-creation and maintaining collective action to set a common vision across disciplines, serving as inputs for a metrics-based toolbox for One Health operationalisation.Conclusion Considering the novelty and complexity of One Health operationalisation, there is need also to develop scorecard-based guidance for assessment of One Health programs at local and national level. This paper proposes a framework for the optimization of an ecosystems-based One Health approach for prevention and control of Vector-Borne Diseases implemented at the local, sub-national or national level.
A Multicentre Double Blind, Placebo Controlled Randomized Trial to Evaluate the Safety and Efficacy of Bovine Colostrum in the Treatment of Severe Alcoholic Hepatitis (SAH).
Authors: Sidhu Sandeep , Dusseja A , . Shalimar , Nijhawan Sandeep , Kapoor Dharmesh , Goyal Omesh , Kishore Harsh 
Published: April 2023

Abstract
Background
Alcoholic Hepatitis (AH) in patients of 2 contemporary Randomized Controlled Trials in India was extremely severe: Maddrey’s Discriminant Function (mDF) [score of 77.4–84 ; MELD of 26–27.5]. The survival rate was very low: 22–30.4%. A pilot study from our group had recently treated ten patients with Severe Alcoholic Hepatitis (SAH) with Bovine colostrum (BC) [20 g thrice in a day for eight weeks] and prednisolone [40 mg once a day for four weeks, tapered over four weeks]. This combo therapy improved the biological function and the survival rate in these extremely sick patients. The aim of this study is to study the safety and efficacy of BC in the treatment of extremely SAH .
Method
This is a multicenter, parallel, double-blind, randomised (1:1) placebo- controlled trial. Patients will be diagnosed with AH using clinical criteria. Up to 174 participants will be recruited from 5 academic centers in the India. Patients will receive freeze dried BC or placebo by random 1:1 allocation for 4 weeks. The primary outcome measure is survival at 3 months. The secondary outcome measures are survival at 1 month, change in mDF and MELD scores, change in Endotoxin and Cytokines (alpha TNF, IL6 & IL8 ) levels, number of episodes of sepsis (Pneumonia, Spontaneous Bacterial Peritonitis, Cellulitis, Urinary Tract Infection) from baseline to 4 weeks.
Discussion
This study will confirm the safety and efficacy of Bovine Colostrum in improving the survival of patients with extremely severe SAH .
Trial Registration
ClinicalTrials.gov Identifier: NCT02473341. Prospectively registered on June 16, 2015
Protocol version: V-4.0
AdsorbML: A Leap in Efficiency for Adsorption Energy Calculations using Generalizable Machine Learning Potentials
Authors: Lan Janice , Palizhati Aini , Shuaibi Muhammed , Wood Brandon , Wander Brook , Das Abhishek , Uyttendaele Matt , Zitnick C. , Ulissi Zachary 
Published: April 2023

Abstract
Computational catalysis is playing an increasingly significant role in the design of catalysts across a wide range of applications. A common task for many computational methods is the need to accurately compute the minimum binding energy — the adsorption energy — for an adsorbate and a catalyst surface of interest. Traditionally, the identification of low energy adsorbate-surface configurations relies on heuristic methods and researcher intuition. As the desire to perform high-throughput screening increases, it becomes challenging to use heuristics and intuition alone. In this paper, we demonstrate machine learning potentials can be leveraged to more accurately and efficiently identify low energy adsorbate-surface configurations. Our DFT verified algorithm provides a spectrum of performance trade-offs, with one balanced option finding the lowest energy configuration, within a 0.1 eV threshold, 86.33% of the time, while achieving a 1331x speedup in computation. To standardize benchmarking, we introduce the Open Catalyst Dense dataset containing nearly 1,000 diverse surfaces and 85,658 unique configurations.
A Meta-Heuristic Routing Optimization Framework for Reducing Traveling Time in Smart Cities
Authors: Song Haiying , Xie Wenwu , Zhu Peng 
Published: April 2023

Abstract
Increasing of cities number and urban population has created huge impact on smart cities, intelligent tourism and intelligent logistics. We propose a meta-heuristic routing optimization framework (MROF) based on flower pollination algorithm (FPA) to obtain the planned path with the shortest traveling time. Firstly, we design an iteration-based Gaussian selection method to balance the search capability between global exploration and local exploitation. Then, we design two selection strategies based on Lévy flight and Cauchy distribution to select neighboring structures, in which both self-pollination and cross-pollination require suitable updating strategies to improve search ability. Finally, the tabu strategy, to increase the proposed framework’s search ability, is integrated into the proposed method. The experimental results show that the proposed method outperforms the state-of-the-art algorithms significantly.
Influence of Sexual Dimorphism and Dichromatism on Reproductive Success in a Rare Native Cactus
Authors: Ramadoss Niveditha , Steele Scarlet , Flores-Renteria Lluvia 
Published: April 2023

Abstract
Identifying plant sexual dimorphic traits is critical in advancing our knowledge on plant-pollinator interactions. For example, dimorphism in floral colors, or sexual dichromatism, is a crucial mediator of pollinator choice on foraging decisions. We studied Cylindropuntia wolfii, an exemplary model system, with diverse flower colors and a functionally dioecious sexual system. However, it is struggling to reproduce sexually as it has a low seed set especially in naturally pollinated fruits. Thus, it is critical to this native species’ conservation to investigate its relationship with pollinators. Our goals were to: a) investigate the sexual dimorphism including the sexual dichromatism in the flowers of the cactus, and b) determine whether sexually dimorphic traits affect the pollinator attraction of both the sexes. We measured several quantitative and qualitative traits for sexual dimorphism and compared them using statistical analyses. Then we recorded the pollinator visitation rate in nature for both sexes and tracked pollinator color preference using fluorescent dyes as pollen analogues. Our study showed that male flowers of C. wolfii are bigger and brighter, and they attract more potential pollinators than females, supporting that sexual dimorphism influences pollinator visitation preference. Fluorescence dichromatism plays a role on pollinator visitation in this species, in which female flowers’ anthers fluoresce more than male flower anthers suggesting this could be female flowers’ strategy to compensate for their dark colors and small size. The results from this study showed that C. wolfii exhibits sexual dichromatism and fluorescence dichromatism, which is a novel finding in plant research.