Successful Model Research Articles

YOLOv5 Model Application in Real-Time Robotic Eggplant Harvesting

Deep learning studies in agricultural automation have accelerated in recent years due to its benefits such as increasing product efficiency and reducing labor force. Deep learning is a powerful tool for automation in agriculture with applications ranging from disease identification and crop yield detection to fruit ripeness classification. It helps to automate various processes in agriculture and to perform time-consuming tasks in a shorter time. It quickly processes the data required for robotic harvesting systems and makes it available to the system. In this study, a machine learning study was carried out to be used in the robotic harvesting of eggplant fruit, which is a product that can take time to select and collect in the agricultural area where it is cultivated. YOLOv5 (nano-small-medium and large models) was used for the deep learning method. All training and test metric values of the models were analyzed. It was determined that the most successful model was the model trained with YOLOv5m algorithm on images of 640 × 640 size with 12 Batches and 110 Epochs. The results of the model values were analyzed as “metrics/precision”, “metrics/recall”, “metrics/mAP_0.5” and “metrics/mAP_0.5:0.95”. These are key metrics that measure the detection success of a model and indicate the performance of the relevant model on the verification dataset. It was determined that the metric data of the “YOLOv5 medium” model was higher compared to other models. The YOLOv5m model gave the highest score with F1 score of 85.66%, precision of 95.65%, recall of 96.15%, and mAP at 0.5:0.65 of 78.80%. Hence, it was understood that “Model 3” was the best detection model to be used in robotic eggplant harvesting to separate the eggplant from branch.

Models and strategies for implementation of social responsibility in modern enterprises

As contemporary enterprises navigate the complex landscape of global business, the imperative to embrace and effectively manage social responsibility has become paramount. This research article delves into the multifaceted dimensions of social responsibility within modern enterprises, exploring the evolving role of businesses in addressing societal and environmental challenges. The study employs a comprehensive review of existing literature, case analyses, and empirical investigations to illuminate the strategies and frameworks employed by enterprises in managing their social responsibility. The first section analyses the theoretical foundations of social responsibility management, emphasizing the evolving perspectives and conceptual frameworks that guide corporate behavior. It critically evaluates the integration of ethical considerations, stakeholder engagement, and sustainable business practices within the broader context of social responsibility. The second section investigates the practical implementation of social responsibility initiatives across diverse industries. The article examines successful models and identifies common challenges faced by enterprises in aligning their operations with socially responsible practices. It analyzes the impact of such initiatives on corporate reputation, stakeholder relations, and overall business performance. This research article contributes to the existing body of knowledge by offering theoretical insights, practical implications, and future considerations for businesses seeking to navigate the dynamic landscape of social responsibility.

Enhancing Conservation Strategies for Wild and Migratory Bird Habitats in South Asia: A Comprehensive Review

Birds are important elements of an environment. The review articles show the significance, challenges, and conservation strategies for wild and migratory bird habitats in South Asia which have diverse landscapes host crucial ecosystems, providing breeding grounds, stopovers, and wintering areas for countless bird species. Anthropogenic activities, climate change, pollution, and invasive species threaten these habitats, necessitating effective conservation measures. Habitat assessment, monitoring, restoration techniques, and adaptation strategies are explored. The impact of climate change on bird habitats is discussed, emphasizing the importance of habitat resilience and adaptive management. Community engagement and education are pivotal in conservation, with successful models involving local communities in decision-making processes. The article also addresses the status of illegal bird hunting in the Indian subcontinent, emphasizing the need for strengthened law enforcement and community involvement. Though birds are important element of the environment, however, they are cause to spread some disease in especially migratory birds. It’s have contribution to biodiversity, pest control, and pollination but can also cause economic losses in agriculture and pose risks to aviation. Managing coexistence between birds and human activities is required for successful conservation program. Interdisciplinary research, long-term monitoring, and quantitative assessments of habitat resilience is underscored. The article concludes with a future plan for wild and migratory bird management in Bangladesh, outlining measures such as habitat protection, community involvement, and international collaboration.
 Graphical Abstract

Predictive radiation heat transfer modeling in fibrous insulation at high temperature

The modeling of heat transfer in fibrous materials is important for designing and improving thermal insulation systems. At high temperatures and low sample density, thermal radiation is expected to be the primary mode of heat transfer in fibrous insulation. Currently, the most common and successful models for modelling heat transfer in insulation at high temperatures require the use of semi-empirical methods. The main limitation of this approach is that the model parameters need to be determined from thermal measurements for each possible material and re-determined if the morphological structure is modified, even for the same material. This paper presents a predictive model for radiation heat transfer based solely on physical and morphological properties. The model was validated using experimental determinations of the effective thermal conductivity in a low-density alumina-based insulation. The model demonstrates good agreement with experimental measurements, and its predictions fall within the experimental uncertainty limits for temperatures between 800 K and 1700 K.

Evaluating an Enterprise-Wide Initiative to enhance healthcare coordination for rural women Veterans using the RE-AIM framework.

The Veterans Health Administration (VA) Office of Rural Health (ORH) and Office of Women's Health Services (OWH) in FY21 launched a three-year Enterprise-Wide Initiative (EWI) to expand access to preventive care for rural, women Veterans. Through this program, women's health care coordinators (WHCC) were funded to coordinate mammography, cervical cancer screening and maternity care for women Veterans at selected VA facilities. We conducted a mixed-methods evaluation using the RE-AIM framework to assess the program implementation. We collected quantitative data from the 14 program facilities on reach (i.e., Veterans served by the program), effectiveness (e.g., cancer screening compliance, communication), adoption, and maintenance of women's health care coordinators (WHCC) in FY2022. Implementation of the program was examined through semi-structured interviews with the facility WHCC funding initiator (e.g., the point of contact at facility who initiated the request for WHCC funding), WHCCs, and providers. Reach. The number of women Veterans and rural women Veterans served by the WHCC program grew (by 50% and 117% respectively). The program demonstrated effectiveness as screening rates increased for cervical and breast cancer screening (+0.9% and +.01%, respectively). Also, maternity care coordination phone encounters with Veterans grew 36%. Adoption: All facilities implemented care coordinators by quarter two of FY22. Implementation. Qualitative findings revealed facilitators and barriers to successful program implementation and care coordination. Maintenance: The EWI facilitated the recruitment and retention of WHCCs at respective VA facilities over time. In rural areas, WHCCs can play a critical role in increasing Reach and effectiveness. The EWI demonstrated to be a successful care coordination model that can be feasibly Adopted, Implemented, and Maintained at rural VA facilities.

From Railways to Aircraft: Officine Meccaniche Reggiane’s Successful Product Transition in the 1930s

In 1936 Gianni Caproni, one of the biggest aircraft producers in Italy, bought one of the biggest engineering companies in Emilia Romagna, the Officine Meccaniche Reggiane, and started manufacturing and exporting some of the topmost fighters ever produced in Italy. Based on different archival sources this paper would like to shed light on why, despite a national technological obsolescence in the field a company, which focused on the production of railway material, was able to come up with the most technologically innovative fighters (the Re. 2000 and successive models) which soon conquered the Italian and foreign markets. The author would like to indicate the original characteristics which help explain its primacy: the unique features of the Reggiane, the role of the new owner, risk-taker and forward-looking entrepreneur Gianni Caproni and in particular the importance of the transmission of knowledge, which in those autarchic years and in this particular case was reached by attracting human capital from abroad. The general argumentation of the paper would like to show the importance of deeply excavating in the company’s history, managerial choices, risk-taking attitudes, and knowledge transfer in explaining an otherwise almost inexplicable international business success in a such a competitive sector. The approach is not purely descriptive: the paper analyses the facts and figures of the Officine Meccaniche Reggiane before and after the Caproni takeover, it evaluates the company’s innovative production strategy in the new field of aircraft production and offers new interpretations on its success story in this field.

Correlating multicomponent surface tension data with Padé approximants. Part I. Surface tension

Eberhardt (1966), Connors and Wright (1989), Piñeiro et al. (2001), Das and Bhattacharyya (2003) and Belda (2009) all proposed successful mixture models for correlating the surface tension data for binary liquid mixtures. Rational extensions of these semi-theoretical and empirical models are derived in order to cater for multicomponent mixtures. It is shown that a canonical Padé approximant emanates from the Piñeiro et al. (2001) and Das et al. (2003) proposals:σ=∑iβiixiσi∑jκijxj/∑i∑jβijxixjWhere the σi’s are the surface tensions of the pure components as a function of temperature. The βij and κij are adjustable model constants (with κii = 1) and they carry some physical meaning. The other models are special cases that are obtained by the application of different combining rules. For example, when the Extended Langmuir model developed by Piñeiro et al. (2001) holds, one obtains βij=βiiβjj; on the other hand, it reduces to the Connors and Wright (1989) model if βij=βii+βjj/2. The theories underpinning these models, suggest that the parameters βij and κij might be temperature dependent. However, Shardt and Elliott (2017) found that, for binary systems they can be assumed constant, i.e. that the temperature dependence is carried solely by the pure component surface tensions. This premise was confirmed for the seven ternary systems which were used to validate the proposed multicomponent canonical Padé approximant.

Prediction and decision making in corona virus using fuzzy mathematical model

During the period of 2019–20, forecasting was of utmost priority for health care planning and to combat COVID-19 pandemic. Almost everyone’s life has been greatly impacted by COVID-19. Understanding how the disease spreads is crucial to know how the disease behaves dynamically. The aim of the research is to construct an SEI Q1Q2 R model for COVID-19 with fuzzy parameters. The fuzzy parameters are the transmission rate, the infection rate, the recovery rate and the death rate. We compute the basic reproduction number, using next-generation matrix method, which will be used further to study the model’s prediction. The COVID-free and endemic equilibrium points attain local and global stability when R0 < 1. A sensitivity analysis of the reproduction number against its internal parameter has been done. The results of this model showed that intervention measures. The numerical simulation along with graphical representations at COVID-free and endemic points are shown. The SEIQ1Q2R model is a successful model to analyse the spreading and controlling the epidemics like COVID-19.

The underlying mechanisms of DNA methylation in high salt memory in hypertensive vascular disease

This study demonstrates the effect and DNA methylation-related mechanisms of a high-salt diet and salt memory-induced hypertension and vasculopathy. Thirty Sprague Dawley rats were randomly divided into a control (CON) group (n = 6) and a modeling group (n = 24). A 12% NaCl solution (1 mL/100 g) was intragastrically administered for 60 consecutive days for modeling. An increase in blood pressure up to 140 mmHg was considered successful modeling. Twelve of fifteen successfully modeled rats were randomly selected and divided into a High Salt Diet (HSD) group and a High Salt Memory (HSM) group (n = 6). Rats in HSD group were intragastrically administered a 12% NaCl solution, while rats in HSM group were administered a 3% NaCl solution twice a day for 30 days. At the end of the intervention, blood pressure and the serum levels of ET-1, NO, TNF-α and IL-1β were measured. RRBS-heavy sulfite sequencing technology was selected for DNA methylation analysis. The systolic blood pressure of rats in the HSD group and HSM group was significantly higher than that in the CON group. Compared with those in the CON group, the serum levels of ET-1 in the HSM group and the serum levels of NO in the HSD group and HSM group were significantly increased. The methylation level of the CON group was lower than that of the HSD group and the HSM group, and there was no significant difference between the HSD group and the HSM group. The methylation level of Myoz3 was downregulated in the HSD group and HSM group. The methylation level of Fgd3 were upregulated in HSD group and downregulated in the HSM group. The methylation levels of AC095693.1, Adamts3, PDGFA and PDGFRα were downregulated in the HSD group and upregulated in the HSM group. According to the GO database, the differentially methylated genes were significantly enriched in the coordination of cell function, genetic development, and RNA transcription. There were three main metabolic pathways that were enriched in the differentially expressed genes between the groups: the PI3K-Akt signaling pathway, MAPK signaling pathway, and Hippo signaling pathway. Excessive salt intake may cause hypertension and vascular damage, and this damage may continue after the reduction of salt intake. Therefore, salt memory phenomenon exists, and this memory effect may be correlated with the levels of DNA methylation.

Regional geographies and public health lessons of the COVID-19 pandemic in the Arctic.

This study examines the COVID-19 pandemic's spatiotemporal dynamics in 52 sub-regions in eight Arctic states. This study further investigates the potential impact of early vaccination coverage on subsequent COVID-19 outcomes within these regions, potentially revealing public health insights of global significance. We assessed the outcomes of the COVID-19 pandemic in Arctic sub-regions using three key epidemiological variables: confirmed cases, confirmed deaths, and case fatality ratio (CFR), along with vaccination rates to evaluate the effectiveness of the early vaccination campaign on the later dynamics of COVID-19 outcomes in these regions. From February 2020 to February 2023, the Arctic experienced five distinct waves of COVID-19 infections and fatalities. However, most Arctic regions consistently maintained Case Fatality Ratios (CFRs) below their respective national levels throughout these waves. Further, the regression analysis indicated that the impact of initial vaccination coverage on subsequent cumulative mortality rates and Case Fatality Ratio (CFR) was inverse and statistically significant. A common trend was the delayed onset of the pandemic in the Arctic due to its remoteness. A few regions, including Greenland, Iceland, the Faroe Islands, Northern Canada, Finland, and Norway, experienced isolated spikes in cases at the beginning of the pandemic with minimal or no fatalities. In contrast, Alaska, Northern Sweden, and Russia had generally high death rates, with surges in cases and fatalities. Analyzing COVID-19 data from 52 Arctic subregions shows significant spatial and temporal variations in the pandemic's severity. Greenland, Iceland, the Faroe Islands, Northern Canada, Finland, and Norway exemplify successful pandemic management models characterized by low cases and deaths. These outcomes can be attributed to successful vaccination campaigns, and proactive public health initiatives along the delayed onset of the pandemic, which reduced the impact of COVID-19, given structural and population vulnerabilities. Thus, the Arctic experience of COVID-19 informs preparedness for future pandemic-like public health emergencies in remote regions and marginalized communities worldwide that share similar contexts.

Species-Abundance Models for the Early Postfire Succession of Subalpine Shrub Grassland

Fire is one of the principal factors influencing subalpine ecosystem succession. Species numbers and plant compositions are used to determine postfire disturbance, vegetation, structural change, and succession. Ecologists also integrate species diversity and mathematical models to enable researchers to obtain increasingly detailed insights into habitats during post-disturbance restoration processes. This study employed five species-abundance models, namely the niche preemption model, the broken-stick model, the log-normal model, the Zipf model, and the Zipf–Mandelbrot model, to perform fitting analysis on the abundance data of postfire species coverage in shrub grasslands near 369 Hut at Xue Mountain in Shei-Pa National Park, Taiwan. We performed the logarithmic transformation on plant-coverage areas for each period of postfire shrub-grassland succession, and then, based on histograms drawn for species–coverage distribution modes, the test results consistently showed normal distributions (p < 0.05). Species-coverage histograms measuring various periods showed that there were comparatively higher numbers of common species during postfire succession and that the numbers of rare species progressively increased. The fitting results of the five species-abundance models showed that although the most suitable abundance models for each period of postfire succession varied, the majority of these periods demonstrated decent fitting with respect to the Zipf–Mandelbrot model. These findings showed that fuel consumption provided nutrients in a manner that facilitated postfire regeneration. Moreover, dominant species, such as Yushania niitakayamensis, and Miscanthus transmorrisonensis, did not fully occupy growing spaces and resource availabilities; consequently, seeded species were able to grow.

The Benign Brand Operation of Professional Sports Leagues: A Case Study on Real Madrid

Real Madrid's profitability continued to grow during the epidemic period, making it a rare club in Europe to still be profitable during COVID-19. Based on this event, the purpose of this exploration was to exploare what kind of management style and business strategy Real Madrid used during the epidemic period of 20192022. Using Real Madrid as a case study, this paper analyzed the information sources applied to Real Madrid's revenues in different aspects as well as Real Madrid's business formula. The first reason was Real Madrid's market management philosophy, and the corresponding recommendation was to increase fan loyalty by strengthening the development of the players and improving the rights of the fans, along with digital marketing tools. The second reason was Real Madrid's excellent youth training system, and the corresponding recommendation was to make more use of modern data analysis systems to track the development of each player. The third reason was Real Madrid's team culture, and the recommendation was to utilize the celebrity effect to promote the team's culture. The main objective of such an exploration was to help national soccer clubs learn from Real Madrid's successful management model to improve their profitability.

Exploring the User Adoption Mechanism of Green Transportation Services in the Context of the Electricity–Carbon Market Synergy

Promoting green transportation development in the context of electric–carbon market synergy can help promote sustainable transport and tackle climate change. The sharing economy has given rise to innovative and successful business models in recent years. To occupy current and potential markets, many enterprises that participate in sharing economy activities have engaged in a fiercely competitive environment. It is an important way for enterprises to generate profits and improve competitiveness by encouraging consumers’ continuous consumption or stimulating repurchase intentions. This study investigates the effects of consumer satisfaction on consumer repurchase intention (CRI) and how such effects are moderated by the consumer’s risk perception and sustainability awareness in the case of ride-sharing services, which are viewed as a mode of green transportation service. The results of a survey of 358 Chinese consumers who have used ride-sharing services suggest that transaction-based and experience-based satisfaction have positive and significant effects on the CRI of ride-sharing services. Moreover, the results indicate that consumer risk perception negatively moderates the relationships between satisfaction and CRI, while consumer sustainability awareness plays different roles depending on the type of satisfaction (transaction-based versus experience-based). Finally, implications and suggestions for future studies are discussed.

Employee Attrition: Analysis of Data Driven Models

Companies constantly strive to retain their professional employees to minimize the expenses associated with recruiting and training new staff members. Accurately anticipating whether a particular employee is likely to leave or remain with the company can empower the organization to take proactive measures. Unlike physical systems, human resource challenges cannot be encapsulated by precise scientific or analytical formulas. Consequently, machine learning techniques emerge as the most effective tools for addressing this objective. In this paper, we present a comprehensive approach for predicting employee attrition using machine learning, ensemble techniques, and deep learning, applied to the IBM Watson dataset. We employed a diverse set of classifiers, including Logistic regression classifier, K-nearest neighbour (KNN), Decision Tree, Naïve Bayes, Gradient boosting, AdaBoost, Random Forest, Stacking, XG Boost, “FNN (Feedforward Neural Network)”, and “CNN (Convolutional Neural Network)” on the dataset. Our most successful model, which harnesses a deep learning technique known as FNN, achieved superior predictive performance with highest Accuracy, recall and F1-score of 97.5%, 83.93% and 91.26%.

Detection of Epstein-Barr virus infection in primary junctional epithelial cell cultures

ABSTRACT Background Junctional epithelium (JE) provides the front-line defense against pathogens invading periodontium. The breakdown of the JE barrier is the hallmark of periodontitis. Recent studies have implicated the Epstein-Barr virus (EBV) as one of the etiopathogenetic factors of periodontitis. EBV exhibits tropism for two target cells in vivo: B cells, where it primarily remains latent, and epithelial cells, where viral replication occurs. Objective Our knowledge of junctional epithelial cell (JEC) infection with EBV has been limited by the difficulty of generating cell cultures and the inability to infect JECs in vitro readily. Design To study EBV infection in JECs, we developed human JEC cultures derived from a periodontitis patient. Furthermore, we established a successful contact-free co-culture infection model between the EBV-donor B95–8 cell line and the EBV-permissive JEC culture. JECs and EBV infection of JECs were detected using immunofluorescent staining of cytokeratin 19 and EBNA1, respectively. In addition, EBV infection was confirmed by RT-qPCR for EBNA1, LMP1, and BZLF1 expression. Results and conclusions Our results suggest that the infection of JECs with EBV can occur in an in vitro experimental model. These outcomes have the potential to enhance our understanding of EBV’s involvement in periodontitis and advance periodontal research.

Bioinformatic identification and experiment validation reveal 6 hub genes, promising diagnostic and therapeutic targets for Alzheimer’s disease

BackgroundAlzheimer’s disease (AD) is a progressive neurodegenerative disease that can cause dementia. We aim to screen out the hub genes involved in AD based on microarray datasets.MethodsGene expression profiles GSE5281 and GSE28146 were retrieved from Gene Expression Omnibus database to acquire differentially expressed genes (DEGs). Gene Ontology and pathway enrichment were conducted using DAVID online tool. The STRING database and Cytoscape tools were employed to analyze protein-protein interactions and identify hub genes. The predictive value of hub genes was assessed by principal component analysis and receiver operating characteristic curves. AD mice model was constructed, and histology was then observed by hematoxylin-eosin staining. Gene expression levels were finally determined by real-time quantitative PCR.ResultsWe obtained 197 overlapping DEGs from GSE5281 and GSE28146 datasets. After constructing protein-protein interaction network, three highly interconnected clusters were identified and 6 hub genes (RBL1, BUB1, HDAC7, KAT5, SIRT2, and ITGB1) were selected. The hub genes could be used as basis to predict AD. Histological abnormalities of brain were observed, suggesting successful AD model was constructed. Compared with the control group, the mRNA expression levels of RBL1, BUB1, HDAC7, KAT5 and SIRT2 were significantly increased, while the mRNA expression level of ITGB1 was significantly decreased in AD groups.ConclusionRBL1, BUB1, HDAC7, KAT5, SIRT2 and ITGB1 are promising gene signatures for diagnosis and therapy of AD.

Yanghe Pingchuan granules mitigates oxidative stress and inflammation in a bronchial asthma rat model: role of the IKK/IκB/NF-κB signalling pathway.

Bronchial asthma (BA) is a chronic inflammatory airway disease. Previous research has shown that Yanghe Pingchuan granules (YPG), among the granules formulated by the First Affiliated Hospital of the Anhui University of Chinese Medicine, exerts a precise therapeutic effect on BA. We previously showed that YPG improves airway inflammation in BA rats. Other studies have shown that the inhibitor of kappa-B kinase (IKK)/inhibitor of NF-κB (IκB)/nuclear factor kappa-B (NF-κB) signalling pathway plays a key role in inflammation mediation. Therefore, this study explored whether YPG could intervene in BA through the IKK/IκB/NF-κB signalling pathway. Ovalbumin-induced method was used to established BA rat model. After successful modelling, the authors used YPG to intervene the rats in BA rats. Hematoxylin-eosin (HE) staining was used to detect the bronchial pathological changes in BA rats, enzyme-linked immunosorbent assay (ELISA) was used to detect the changes of inflammatory factors (IL-1β and IL-6) and oxidative stress indexes malondialdehyde (MDA), superoxide dismutase (SOD) and nitrogen monoxide (NO), Quantitative real-time polymerase chain reactionCR and western blot were used to detect the expression of IKK/IκB/NF-κB signalling pathway. In BA model rats, YPG significantly improved the inflammatory response in bronchial tissues, reduced inflammatory factors IL-1β and IL-6, alleviated oxidative stress, reduced MDA and NO, and increased SOD. Quantitative real-time polymerase chain reaction and western blot results showed that YPG could block the IKK/IκB/NF-κB signalling pathway. These findings showed that YPG had a definite therapeutic effect on BA, which may be related to blocking the IKK/IκB/NF-κB signalling pathway and improving inflammation and oxidative stress.

Do Your Genes Fit: How Life Insurance Companies Discriminate Based on Genetic Test Results

Abstract The Genetic Information Nondiscrimination Act of 2008 (GINA) represents a significant legislative step in protecting U.S. citizens from genetic discrimination in health insurance and employment. However, despite its broad preventive measures, GINA has limitations in scope and enforcement. Notably, it does not extend protections to life insurance, disability, and long-term care insurance, leaving U.S. citizens susceptible to genetic discrimination. State-level legislative efforts have tried to reconcile these vulnerabilities. Many state-level legislative efforts vary in effectiveness, with some states like Florida and Illinois enacting more robust laws. The future of genetic information protection requires an amendment to GINA or new federal legislation, drawing from successful state models to ensure adequate protections. This paper advocates for such national legislation, highlighting the minimal impact on the life insurance market and the importance of safeguarding genetic privacy to foster trust in genetic testing and scientific progress.

Repairing Effect of Mesenchymal Stem Cells on Lead Acetate-Induced Testicular Injury in Mice.

Lead acetate can cause testicular damage in males. In this study, we assessed the repairing effects of human umbilical cord mesenchymal stem cells (MSCs) on testicular injury caused by lead acetate in mice. MSCs were injected into mice with testicular injury by intraperitoneal injection, and the organ coefficient of reproductive organs, sperm motility, hormone level and antioxidant index of mice were tested. Compared with the normal group, the coefficient of reproductive organs and sperm motility were reduced in the model group, and histopathology showed obvious testicular injury, proving successful modeling. Compared with the model group, the reproductive organ coefficient and sperm motility were improved in the experimental group, and histopathology showed that the testicular injury could be significantly improved. Sex hormone secretion tends to be normal, and the antioxidant index increased. Sequencing results showed that there were 485 upregulated genes and 172 downregulated genes between the model group and the control group, and 210 upregulated genes and 482 downregulated genes between the experimental group and the model group. Differentially expressed genes are mainly concentrated in AMP-activated protein kinase (AMPK) signaling pathway, apoptosis signaling pathway, and arginine biosynthesis signaling pathway. Overall, MSCs can significantly improve the degree of damages to mice testis caused by lead acetate and have a certain repairing effect.

Innovative Approaches to Managing Zakat within the Context of Sustainable Development and Societal Well-Being in Indonesia

The objective of this research is to investigate and assess innovative approaches to managing Zakat within the context of sustainable development and societal well-being in Indonesia. Given the multifaceted challenges confronting Indonesian society, Zakat holds tremendous potential as a tool for fostering sustainable development and enhancing social welfare. This research employs a literature review to examine pioneering practices in Zakat management within Indonesia. Information gathered from diverse sources, including research papers, scholarly publications, and case studies, will be utilized to analyze various successful models of Zakat management implemented in the country. The findings of this study aim to shed light on effective innovations in Zakat management that contribute to achieving sustainable development and augmenting social welfare in Indonesia. Moreover, the research will identify critical factors that facilitate the successful implementation of innovative Zakat management strategies, while also evaluating the resulting social and economic ramifications. It is anticipated that the outcomes of this study will furnish pertinent policy recommendations for the government, Zakat management institutions, and the general populace, aimed at enhancing the efficacy of Zakat management for sustainable development and the advancement of social welfare in Indonesia. Furthermore, this research endeavor seeks to foster a deeper comprehension of Zakat’s potential as a substantial funding source to fortify key sectors in propelling inclusive economic growth and fostering social equity within Indonesia.