bluuebunny/crossref_metadata_2025 huggingface dataset:
Spatial multi-omics integration: metabolites meet RNA
Authors: Waldie Bishoy , Alexandrov Theodore
Published: October 2024

Recently emerged spatial omics technologies provide unprecedented insights into spatial aspects of gene expression, protein localisation, and metabolite concentrations in tissues. Now, the increasingly recognised challenge lies in integrating layers of individual spatial omics into a multi-omics molecular inventory describing cellular machinery and its spatial co-organisation across transcription, translation, and metabolism.
This webinar will focus on spatial metabolomics and cover various computational approaches for analysing Spatial-multi-omics datasets, emphasising the integration of transcriptomics and metabolomics at both spatial and single-cell resolution.
IMPLICATIONS AND CONSIDERATIONS OF THE NEW ELECTRONIC INFORMATION AND TRANSACTION LAW
Authors: Purwono Agus , M. Zamroni M. Zamroni , Santoso Hardi Anugrah , Miarsa Fajar Rachmad Dwi
Published: October 2024

Regarding regulations related to the electronic world, the purpose of this study is to link the law on Electronic Information and Transactions (ITE Law) No. 1 of 2024 which is the second amendment to Law No. 11 of 2008. The emergence of various problems regarding the ambiguity of protection in the scope of ITE has caused the public to urge the government to revise it as soon as possible. The methodology used in this study is normative juridical type sourced from primary and secondary legal materials. With an approach through legislation (Statute Approach) and a historical approach (Historical Approach). The Law on Information and Electronic Transactions which was born in 2008 (ITE Law No. 11 of 2008) contains provisions governing the electronic realm. Apart from that, the ITE Law has many weaknesses that conclude multiple interpretations of the contents of the article. To overcome this, the government made the first revision contained in Law No. 19 of 2016. The emergence of controversy has not been able to answer the changes in the first change. So there are still articles that reap pros and cons in the form of interpretation. Among them are Article 27, Article 28, Article 29, and Article 36. So the government made a second revision contained in Law No. 1 of 2024.
Avaliação da ocorrência de parasitos em fezes caninas coletadas em praças públicas do município de Taubaté – SP
Authors: Coêlho Matheus , Vieira da Silva Denis , Lourenço de Carvalho Romeiro Luciana , Pâmela Martins da Silva Fernanda , Paula Guedes Josiane , Miranda de Paula Marina , Alves da Silva Coêlho Francine
Published: October 2024

Os cães  (Cannis familiaris) consistem nos animais domésticos mais estimados pela população brasileira, porém algumas pecliaridades relacionadas aos hábitos higiênicos e sanitários dos mesmos e dos seus donos, traz a tona um risco para que haja transmissão de doenças zoonóticas, dentre as quais algumas doenças parasitárias. No presente estudo objetivou-se avaliar a presença de parasitos em fezes de cães coletadas em praças públicas do município de Taubaté, visando identificar os principais parasitos que podem representar riscos à saúde pública, devido à sua capacidade de infectar tanto animais quanto seres humanos. Para a realização do estudo, foram coletadas amostras de fezes caninas em diversas praças do município de Taubaté e para análise das amostras foi utilizado o método de Ritchie modificado. Observou-se uma ocorrência de 17,5% de amostras positivas, com destaque para Ancylostoma spp. , que foi diagnosticado em 50% das amostras positivas, trazendo a tona a necessidade da adoção de medidas prventivas aplicáveis para diminuir o risco de infecção, não só de cães, como também de seres humanos.
THE INFLUENCE OF PRODUCT QUALITY AND SERVICE QUALITY ON CUSTOMER LOYALTY THROUGH CONSUMER SATISFACTION OF KENTUCKY FRIED CHICKEN (KFC) IN JEMBER
Authors: Yulisetiarini Diah , Farid Mochammad , Nanda Elisa , Sudarsih Sudarsih , Prasetiyaningtiyas Susanti , Irawan Bambang
Published: October 2024

This research aims to determine the effect of product and service quality on customer loyalty through KFC consumer satisfaction in Jember. This research is explanatory research, which aims to show the position and influence of the variables studied. The population in this research is all KFC Jember consumers. The sampling method is non-probability sampling with a purposive sampling technique. The sample used was 100 respondents. This research uses quantitative data. The data source in this research is primary data by distributing questionnaires directly to selected respondents. The data analysis method used is path analysis. The research results show that: Product quality has a significant effect on consumer satisfaction. Service quality has a substantial effect on consumer satisfaction. Product quality has a significant effect on customer loyalty. Consumer satisfaction has a significant effect on customer loyalty. Product quality has a significant effect on customer loyalty through consumer satisfaction. Service quality has a significant effect on customer loyalty through consumer satisfaction. The findings of this research are that service quality does not have a significant effect on customer loyalty.
MITIGATING OPERATION, QUALITY AND REGULATORY CHALLENGES IN THE PACKAGED DRINKING WATER INDUSTRY: A FAILURE MODE EFFECT ANALYSIS (FMEA) APPROACH
Authors: M. Shende Kunal
Published: October 2024

Access to safe drinking water is vital for human development; however, challenges arising from industrialization, agriculture, and population growth threaten its availability. The packaged drinking water industry, a crucial alternative, encounters difficulties in meeting quality, operational, and regulatory requirements. Refillable polyethylene terephthalate (PET) jars, undergoing multiple cycles of refilling, pose higher risks of contamination, requiring more attention. This study advocates the use of a proactive method, Failure Mode and Effects Analysis (FMEA), to anticipate and prevent problems in the processing and refilling of PET water jars before they occur, promoting a proactive approach to quality and risk management. Findings reveal inadequate cleaning of PET water jars with the highest Risk Priority Number (RPN) of 378, followed by aging of UV lamp, scaling on the UV lamp shield impacting the disinfection of product water and biological contamination due to unsanitary practices during manual filling of jars, each with RPNs of 315, 324, and 270. Addressing these top contributors promises substantial improvements in water quality. Implementing corrective actions reduced RPNs to 81, 54, 36, & 36, respectively. This systematic application of FMEA yielded significant improvements in quality, safety, and reliability within the packaged drinking water industry. Proactive strategies developed through FMEA hold promise beyond the packaged drinking water industry, improving water quality management.
SUSTAINABLE ISLAMIC FINANCE: BIBLIOMETRIC AND VISUALIZED ANALYSIS OF CURRENT EMPIRICAL RESEARCH
Authors: Rosediana Dewi Ivana , Zulaikha Siti , Sudaryanto Sudaryanto , Hanim Anifatul
Published: October 2024

This study aims to develop the research gap in sustainable Islamic Finance using a bibliometric analysis of recent empirical research outputs in the area, which comprises publications in scholarly journal articles and book chapters. Data were collected from Scopus for the period 1997 – 2022. This study analyses 285 Scopus scientific documents using Vosviewer, RStudio and Biblioshiny for bibliometric tools to process scientific documents extracted from various sources. Our study shows that the most prominent word in the Scopus scientific papers on Sustainable Islamic Finance is Islamic finance, followed by sustainable development, finance, banking, and investments. The keywords that Scopus scientific documents use little on the topic are ethical investing, climate change, Islamic social finance, waqf, zakat, takaful, green sukuk, and microfinance. There is a clear gap in knowledge around Islamic financial instruments in research that follow our findings and would benefit from further research.
To Integrate and Optimize the Use of Programmable Logic Controller in Development of Horizontal Flow Wrap Packaging Machinery for Industry Needs
Authors: Bhanwrela Lalit , Managre Jitendra , Purohit Naresh , Gupta Namit
Published: October 2024

This paper focuses on the use of PLC and HMI in the automation industry for a highly effective and versatile horizontal flow wrap plastic film packaging solution. The machine's functioning and efficiency are thoroughly evaluated through extensive testing and validation procedures across multiple criteria. The main aim of this paper is to do the automatic plastic film packaging of any product with packaging dimensions of 4cm X 5cm. For the process automation the FX5U 32MT PLC of Mitsubishi is used for controlling and automating the system using ladder logic. The result shows that the developed system provides fully automatic wrap packaging of products and able to do automatic packaging of 24 packets in one minute. Additionally, the results show the increased efficiency of product rate in less time for automatic packaging system. Finally, it has been observed that the system is very beneficial for the automatic packaging process using PLC and the process can be monitored and visualized on a display screen using HMI. Future advancements are required in the system to meet industry4.0 needs. By incorporating some smart technologies, deeper integration with Industry 4.0 principles could boost capabilities in data analytics, connectivity, and remote monitoring for predictive maintenance.
COMMUNITY POLICING AND CRIME PREVENTION IN NIGERIA
Authors: Ande Ivorgba Emmanuel
Published: October 2024

Community policing has emerged as a promising strategy for crime prevention and enhancing public safety around the world and in Nigeria. This is due to the difficult task of conventional policing, especially where the community is not actively involved in crime prevention. It has been realized that safety in any given community requires an investment not only of money, but also time and talent, and that sometimes the best solutions are found in understanding the underlying causes of crime and disorder. Nigeria is one of the countries in the world that has embraced the idea of community policing with great enthusiasm for about two decades ago. Consequently, Nigeria, has introduced several policy measures with the main aim of encouraging the community to take up some responsibility for their safety and security of their environment. Drawing on empirical research and case studies, this paper examines the key principles, approaches and challenges of implementing community policing initiatives, to highlight the significance and impact of collaboration between local communities and law enforcement agencies on crime prevention, trust-building and social cohesion in Nigerian communities. The paper also emphasizes the importance of capacity building, sustainable funding, and institutional support in strengthening the effectiveness of community policing in Nigeria.
The legal regime for cryptocurrencies in Kazakhstan and impossible control of their circulation
Authors: Karagusov Farhad , Bondarev Alexey
Published: October 2024

Development of a legal framework for cryptocurrencies in Kazakhstan is described in this article: from very first steps in 2018 when financial intermediaries were just warned from use of Bitcoins and alike in their transactions to prohibition of their circulation established into 2020, with cancellation of the prohibition and strengthening regulation of crypto mining in 2023. Authors show that neither existence nor absence of a legislative restriction of cryptocurrencies’ circulation can help the State to control respective turnover. Respectively, no efficient solution can be said existing to both support a public order and protect individual property rights to cryptocurrencies. Keywords: Republic of Kazakhstan, cryptocurrency, Law on Informatisation, digital assets, AIFC, digital mining, regulation, legal framework.
Проблемы в осуществлении родительских прав родителем, проживающим отдельно от несовершеннолетнего ребенка
Authors: Guliev Aziz
Published: October 2024

This article discusses legal problems in the exercise of parental rights to communicate with a minor child by a conscientious and law-abiding parent living separately from the child.The relevance of the topic is justified by the weakening of the traditional institution of the family, which is characterized by a continuous increase in the number of divorced marriages and, accordingly, an increase in the number of single-parent families.The legal framework regulating the exercise of parental rights is analyzed.It examines how much the real legal status of a separated parent differs from the declared one and whether it is sufficient to carry out parental responsibilities for the upbringing and development of a minor child.It is shown that in the current legal reality, the equality of rights and responsibilities of spouses after their divorce is not respected, since the parental rights of a separately living parent are significantly limited, which ultimately leads to the actual loss of responsibility for raising the child by this parent. Keywords: Parental rights, parent, minor child, legal norms, family code, constitution, court, guardianship, separate residence, equality of rights and responsibilities, marriage, single-parent family.
Müqavilənin standart şərtləri
Authors: Rasulzade Subhan
Published: October 2024

The article examines the institution of "standard terms of contract", which is an important parameter of today's civil law sphere. The place of the concept in question in the modern legal system is discussed. In relation to this issue, the legislator's position, court practice and approaches available in the doctrine are analyzed. Important nuances such as the understanding of the standard terms of the contract, their place in the legal system of the Republic of Azerbaijan, their elements, verification, reliability, and defense mechanisms formed by the legislator against abuses that may arise from it are touched upon. In particular, the imperative requirements regulating this institution are considered in the legislation. It is clarified whether this type of condition is necessary and desirable from the perspective of civil law. Key words: contract, standard, condition, element, validity, check, mechanism, court, legislator, imperative, interpretation, content
Yaradıcılıq azadlığının təminatının hüquqi və təcrübi aspektləri
Authors: Rzayeva Gulnaz , Babayeva Turkana
Published: October 2024

The freedom of creativity, which is established in different forms in various legal regulations, is considered one of the main freedoms related to the development of the material and spiritual existence of a person due to its characteristics. In the modern era, digitalization processes and the transition to the information society have conditioned this freedom to take a new form, to include not only artistic works, but a wider content. The article analyzes the nature of freedom of creativity, its main elements, mechanisms of legal protection, as well as the interaction of this freedom with other rights and freedoms. In addition, recommendations on methods of protection against illegal interference aimed at freedom of creativity have been presented. At this time, the important aspects of the interaction of freedom of creativity and information culture were also studied. Keywords: freedom of creativity, information product, artistic work, information culture, limitations, legality.
The maternity dashboard is an effective tool for the improvement of maternal and neonatal care outcomes: a prospective observational study from Iraq
Authors:   Department of Community Medicine, Kerbala Public Health, Ministry of Health, Kerbala, Iraq, Alsaigh Noor Jalil ,   Department of Community Medicine, College of Medicine, Al-Mustansiriyah University, Baghdad, Iraq, Al-Ani Waleed Arif Tawfeeq ,   Department of Community Medicine, College of Medicine, Al-Mustansiriyah University, Baghdad, Iraq
Published: October 2024

Background: The implementation of maternal dashboards in hospitals is both feasible and effective in improving healthcare quality. The dashboards provide rapid feedback on local outcomes in an accessible format and enable early detection of potential problems. They serve as a simple computerized tool that graphically presents the health facility’s clinical data, utilizing a traffic-light coding system so as to alert front-line staff about changes in the frequency of clinical outcomes. Aim: The aim of this study was to assess the effectiveness of the maternity dashboard in improving maternal health, reducing Neonatal Intensive Care Unit (NICU) admissions, as well as enhancing maternal and neonatal outcomes in an Iraqi hospital. Methodology: Data were collected over one year, from January 1st to December 30th, 2023. A prospective observational study (hospital-based record review) was conducted at the Obstetrics and Gynaecology Teaching Hospital in Kerbala, Iraq. Data were obtained from the medical records of all patients admitted to the obstetrical ward for labor, delivery, and the postpartum period during 2023. The maternal dashboard, a traffic light program (green, amber, red), was used in order to monitor outcomes. Data were collected manually from the outpatient department, the labor ward, the NICU registers, and the electronic records by using Excel. Results: A total of 136,519 women (who were either pregnant, in labor, or postpartum for up to 42 days) were admitted to the Obstetrics and Gynaecology Teaching Hospital in Kerbala during the study period, with 18,791 of them delivering. The implementation of the maternity dashboard resulted in significant changes: the normal vaginal delivery rate increased from 66% to 68% (p=0.0024), the caesarean section rate decreased from 33% to 31% (p=0.0001), the stillbirth monthly cases declined from 16±5 to 12±3 (p<0.05), the NICU admission monthly instances decreased from 96±14 to 71±17 (p<0.05), and early neonatal death monthly cases were reduced from 12±5 to 9±3 (p<0.05). Conclusion: The study results show that maternity dashboards are vital instruments for monitoring and improving the quality of maternity care. They effectively enhance maternal and neonatal care quality indicators when comparing results before and after their implementation.
Speaker Recognition: A Comparative analysis Between Deep Learning and Non-Deep Learning Methodologies
Authors: Faisal Ahmad , Mustafa Muhammad , Ahmed Zoha , Akbar Sakhi Usman
Published: October 2024

This work carries out a comparative study of two methodologies for speaker recognition. It is Deep Learning (DL) and Vector Quantization (VQ). The key area in biometric au-thentication systems involves speaker recognition. This requires durable and efficient algorithms. The aim is to ensure a high accuracy and reliability. The study delves into a deep neural network (DNN) model implementation. It leverages advanced feature extraction. It uses pattern recognition capabilities which are in DL. The study also examines a traditional VQ approach. This method makes use of codebook generation and quantization for speaker ID. Extensive experimentation was done on standard datasets. The project evaluates the performance of two methods. It compares accuracy. It assesses computational complexity. It does so for noise and for variations in speech. The findings of this analysis reveal the strengths and limitations of each technique. Looking at their practical applicability in real-world scenarios provides insights. The comparative results of these techniques aim to guide future developments. This concerns speaker recognition systems - particularly their potential for enhanced performance.
Exploration of PQC-Based Digital Signature Schemes in TLS Certificates
Authors: Akram Muhammad Umer , Ashraf Muhammad , Rehman Tayyab , Abdur Rehman Javaid Muhammad , Khalid Muhammad Ali
Published: October 2024

The rapid development in quantum computers brings huge risks to traditional cryptographic systems. This paper talks about the integration of PQC-based digital signature schemes to solve challenges posed on Transport Layer Security certificates. In this paper, we give an analysis of the efficacy, security, and performance implications of various schemes in PQC—particularly lattice-based, hash-based, and multivariate polynomial-based algorithms. We detail more closely the challenges of the real deployment, directly connected with these digital signatures, considering communication overhead and computational costs. Our findings indicate that hybrid certificate chains, which integrate multiple PQC schemes, offer a feasible solution for a seamless transition to quantum-resistant standards with manageable performance trade-offs. Moreover, our study extends to the quantification of security benefits these PQC schemes provide against both quantum and classical computational attacks, underscoring their potential in enhancing the resilience of digital communication systems. This paper aims to contribute valuable insights to ongoing standardization discussions and support the broader adoption of PQC, thereby ensuring robust and future-proof security in digital communications amidst the advancing quantum computing era.
Flood Risk Analysis in Sindh, Pakistan: Predicting the Most Affected Tehsil Using Statistical and Machine Learning Models with Comprehensive Data
Authors: Aziz Amna , Ali Muhammad , Zaidi Syed Muhammad Hassan , Nawaz Faisal , Sheikh Faryal
Published: October 2024

Extreme weather events pose significant risks and threats to the Sindh region, shedding light on the potential havoc they can wreak on livestock, human lives, and public infrastructure. Unusual monsoon rains in 2022 transformed the geography of Sindh, leading to devastating floods and significant damage. The current flood management strategies are effective, but there is some gap in early warning systems. Different findings suggest a need for refined approaches to improve predictive accuracy and response efficiency. The primary goal is to assess and improve existing flood response measures, identify opportunities for improvement, and strengthen resilience against flood events. In response to these challenges, this study provides actionable insights for policymakers and emergency planners to refine flood management strategies, ultimately aiming to bolster community resilience and preparedness. This paper presents a novel framework for a hybrid predictive model that combines machine learning and statistical analysis to improve the prediction of flood-induced displacement, providing timely warnings and preparing for future flood events. The selected dataset used for this research is from the 'Sindh Flood Data Analysis and Prediction 2022', which includes both demographic and geographical variables. By integrating machine learning and statistical models, the research evaluates their effectiveness in predicting flood impacts and identifying the most affected Tehsils using Python language and Seaborn library for analysis. The Gradient Boosting Classifier achieved the highest accuracy at 97.67%, followed by Logistic Regression at 95%. In contrast, Decision Trees and Lasso Regression demonstrated lower accuracies of 25% and 55%, respectively.
Exploring the Construction of Angela Merkel's Identity by Global Print Media across International Platforms
Authors: Ali Muhammad , Jamshed Humaira , Dost Khyzer Bin
Published: October 2024

This study is an attempt to observe and analyze the intricate operations of media discourses in the identity construction of “world leader” i.e.  Angela Merkel. It highlights that how through the explicit and implicit discourse layers’ construction, the macro and micro semantic structures are created in a newspaper, for portraying the desired positive or negative image of a world leader. The theoretical framework has been structured over the basics of the Van Dijk’s (1980) The Theory of Semantic Macrostructures. The macro- level analysis focuses the core themes and main propositions publicized in the selected data. The micro-level analysis concentrates on the lexicalization and syntactic patterns employed by media experts in creating the larger positive image as world leader through smaller level discourse language constructions, focusing her social and political posterities. Furthermore, the study highlights the gradually constructed personal, social and political identities’ portrayal of Angela Merkel as a powerful world leader, through the world newspaper articles discourse and discursive practices.
Social Media Use: A Cognitive Dissonance Analysis of Heavy Users and Engagement Dynamics
Authors: Muneer Saba , Ali Muhammad , Qamar Nida , Dost Khyzer Bin
Published: October 2024

Abstract Purpose – This research investigates the correlation between the utilization of social networking sites, user engagement, and cognitive dissonance. It explores the mediating influence of e-compulsive buying behavior (ECBB) in the connection between SNS use, user engagement, and cognitive dissonance, while also examining the moderating impact of self-esteem on SNS use, user engagement, and ECBB.
Methodology – Utilizing purposive sampling, this study collected cross-sectional data from 232 female participants actively engaged in social networking sites (SNSs) and who had made 4-5 online purchases during the last six months. Data were gathered through an electronically administered questionnaire. Descriptive data analysis was conducted using SPSS version 21, while SmartPLS version 4.0 was employed to test the proposed hypotheses.
Findings – The findings indicate a significant association between the utilization of social networking sites (SNSs) and user engagement with cognitive dissonance and ECBB. Additionally, it was observed that self-esteem played a moderating role in the relationship between SNS use, user engagement, ECBB, and cognitive dissonance, revealing a heightened impact of cognitive dissonance at lower levels of self-esteem.
Practical Implications – These results carry implications for implementing interventions aimed at mitigating the adverse consequences associated with social networking site (SNSs) use, thereby fostering favorable mental health outcomes within the community. Moreover, this study offers valuable insights for managers seeking to enhance their social media strategies by analyzing the varied impacts of social media content and understanding the dynamics between posts to engage both active and passive users effectively.
Originality/Value – This study contributes to the limited body of empirical research by examining the correlation between social networking site (SNSs) use, user engagement, and cognitive dissonance through the lens of ECBB. Additionally, in response to recent calls from various empirical studies in this field, the inclusion of self-esteem as a moderating variable predicting cognitive dissonance enhances the novelty of this research.
Identifying Credit Card Fraud with Machine Learning: Evaluation of Algorithms and Oversampling Techniques
Authors: Ahmed Beenish , Hussain Sarfraz , Shakir Daniyal , Rehman Najeeb ur , Nadeem Ghalib
Published: October 2024

The physical loss of a credit card or the theft of sensitive credit card data is referred to as credit card fraud. For detection, a variety of machine learning methods can be applied. This study presents several algorithms for identifying transactions as authentic or fraudulent. The study used the credit card fraud detection dataset. The SMOTE approach was utilized for oversampling due to the extremely unbalanced nature of the dataset. Additionally, a feature selection process was carried out, and the dataset was divided into training and test sets. The experiment employed eight machine learning models, including Random Forest, AdaBoost, Support Vector Classifier, Extreme Gradient Boost, and Logistic Regression algorithms. The findings indicate that few algorithms have a high degree of accuracy when detecting credit card fraud. The Random Forest model can be applied to find further anomalies. This approach has proven to be effective in accurately detecting fraudulent activity and reducing the number of false positives and negatives. The results of the experiment also highlight the importance of feature selection in improving the performance of the models by the highest accuracy score with 96%, precision of 100, Recall of 91, and F1Scroe of 95. By using a combination of different machine learning algorithms, financial institutions can enhance their fraud detection systems and better protect their customers from potential financial losses. The findings from this study demonstrate the potential for significant advancements in the field of fraud detection using machine learning techniques.
Efficient Malware Investigation and Recognition Using Machine Learning Algorithms
Authors: Siddiqui Ali Ahmad , Ali Israr , Arbab Saira , Kumari Shilpa
Published: October 2024

Malware is unique of the biggest problems that modern internet users have to deal with. Polymorphic malware is a new type of harmful software that is extra pliable than prior peers of bugs. Polymorphic malware continuously alters its signature characteristics in order to evade detection by conventional malware detection techniques. We applied various machine learning algorithms to detect malware or dangerous threats. A high detection ratio meant that the most accurate algorithm had been chosen to be used within the system. One advantage of the confusion matrix is its ability to track false positives and false negatives, providing deeper insights into the system’s performance. In particular, it revealed that machine learning algorithms like Naïve Bayes, Support Vector Machine (SVLM), Random Forest (RF), and K-Nearest Neighbor (kNN) can be used to detect harmful traffic on computer systems by calculation changes in correlation patterns. This approach enhances the effectiveness of malware detection and overall security in computer networks. The findings demonstrated that NB (87%), kNN (91.76%), SVM (92.41%), and RF (98.07%) performed well in terms of detection accuracy when compared to other classifiers. These findings are important as malicious software is growing more prevalent and sophisticated.
Data on Violence and Abuse Among Nurses and the Use of Antidepressant Medications
Authors: Rani Sadaf , Tahira Sobia , Akmal Pawan
Published: October 2024

This study investigates the impact of physical and emotional violence on emotional exhaustion among nurses and explores the moderating role of antidepressant use. Conducted at Mayo Hospital in Lahore, the study surveyed 126 nurses to examine the relationships between violence exposure, emotional exhaustion, task interruptions, and the use of antidepressants. The research utilized a structured questionnaire covering demographic details, experiences of violence, emotional exhaustion levels, task interruptions, and antidepressant use. The results reveal that both physical and emotional violence significantly contribute to emotional exhaustion, with emotional exhaustion itself playing a substantial role in predicting antidepressant use. Emotional exhaustion was found to partially mediate the relationship between physical and emotional violence and the use of antidepressants. Additionally, task interruptions were identified as a mediator between violence exposure and emotional exhaustion, though they did not significantly moderate the relationship between emotional violence and antidepressant use. The study's findings underscore the severe impact of violence on nurses' emotional well-being and the crucial role of antidepressants in managing emotional exhaustion. The results suggest the need for targeted interventions to address workplace violence and its psychological effects, as well as recommendations for reducing task interruptions to improve overall nurse well-being and efficiency.
Data on the Sense of Coherence Among Nurses
Authors: Shamim Iqra , Mushtaq Humaira , Muslim Naiba , Akmal Pawan
Published: October 2024

The purpose of this study is to determine the sense of coherence among nurses and its effect on nurses’ relationship with patients. And how therapeutic relationship affected by the coping mechanism of the nurses.  The data were collected by using the questionnaires adapted from the previous studies. The study is cross sectional and quantitative using a deductive approach. Population of the study was the nurses and convenient sampling method used for collecting data. Sample size was 191 nurses. Finally, 119 valid questionnaires were used for data analysis.  The result of my study is positive that is nurses with stronger sense of coherence can successfully develop a nurse patient interaction which benefits the both the nurses and the patients. Because stress and anxiety directly affect the nurses performance those who can manage the work related stressors more productively can do better as compare to those who fails to cope with depression.  From the results of the study, it is concluded that the stronger sense of coherence resulted in the better coping mechanism in response to any stress or fears related to work and eventually they maintained good nurse patient therapeutic relationship.
The Integration of Fintech in Energy Markets: Economic Benefits and Policy Considerations
Authors: Farooqi Muhammad Wali , Banori Noshad Hussain Shah , Ullah Naqeeb , Sultan Burree , Niaz Amna
Published: October 2024

This study investigates the impact of, financial technology (fintech) integration, on the efficiency, cost reduction, and, sustainability of energy markets, with a, particular focus on, Pakistan. Employing, the Technology-Organization-Environment, (TOE) framework, the research, explores how fintech, adoption, investment in, fintech, regulatory support, technological, infrastructure, and market transparency, influence key market, outcomes. A structured questionnaire, was distributed to professionals, and stakeholders in the, energy sector, yielding 320,responses. The analysis, conducted using, Structural Equation Modeling (SEM) ,in Smart PLS, reveals that fintech, adoption significantly, enhances market efficiency, while, investment in fintech and market, transparency contribute to, cost reduction. Regulatory, support and technological, infrastructure are crucial, for market efficiency, and sustainability, respectively. The, study underscores the, need for a balanced approach that, includes supportive regulatory, frameworks and robust, technological infrastructure to fully, leverage fintech's potential. The findings, offer valuable insights for, policymakers and energy, market participants, highlighting, the critical role of fintech in driving, economic benefits and addressing, market inefficiencies. Future, research should expand, to multiple countries to validate these findings and explore additional contextual factors.
Early Detection and Classification of Apple Leaf Diseases Using Deep Learning Technique
Authors: Khan Areej Gul , Javed Rabia , Malik Ahsan Mukhtar , Mirza Ahmad Faisal , Aslam Shazia , Shabbir Aqsa , Tauseef Huma
Published: October 2024

Apple leaf diseases represent a critical challenge for apple crop production, threatening both the quality and quantity of harvests. Leaves are essential to the growth and health of apple trees, as they play a pivotal role in photosynthesis and nutrient transport. When these leaves become infected, the diseases can rapidly spread across the entire tree, leading to significant damage that can impact the yield and the overall health of the orchard. The consequences of such outbreaks can be devastating, with severe economic losses for farmers and potentially reduced marketability of the crops. To mitigate these risks, timely and accurate detection of apple leaf diseases is crucial. Early intervention allows farmers to apply targeted treatments and prevent the spread of infection to other parts of the tree or adjacent trees in the orchard. This research proposes an improved deep learning approach, utilizing the VGG16 model, to detect early signs of apple leaf diseases. By focusing on small spots and widespread lesions, the model can identify symptoms at an early stage, allowing for prompt intervention to prevent further spread. The study employs a dataset from Kaggle and a custom repository called Apple Fungal Diseases Dataset, with the classification results compared to other leading techniques to ensure accuracy. By providing a reliable method for early detection, this research aims to support farmers in managing apple leaf diseases more effectively, ultimately contributing to healthier orchards and improved crop yields.
Acceptance and Commitment Therapy for the Treatment of Postpartum Depression: A Case Study Approach
Authors: Javed Humaira , Aslam Shazia , Mukhtar Ahsan , Muazzam Amina
Published: October 2024

The prevalence of postpartum depression (PPD) has been linked to contradictory outcomes for mothers, infants, and mother-child relationships. Pakistan has the greatest prevalence percentage among the Asian countries which ranges from 28%-63% (Habiba et al., 2020). When it comes to treating postpartum depression, one of the best methods is Acceptance and Commitment Therapy. (Hayes et al., 2006). However, a large number of new mothers choose not to seek expert assistance, which highlights the need for new platforms to be developed in order to provide health care services in Pakistan. As noted by Waters et al. (2020) the primary goal of this research is to develop and evaluate the ACT for postpartum depression in postpartum women. This treatment approach addresses mood and anxiety problems related to perinatal diseases. Utilizing the single-case study design. Our main resource who woman who volunteered, from teenage mothers to women in their forties who give birth. The intervention protocols and the strategy were developed in close collaboration with seasoned clinical psychologists and psychiatrists who are experts in the sector. The program was conducted weekly for a minimum of 12 weeks, during which the technique and treatment plan were explained in full. Compiling the patient's progress report and compiling the data received during treatment were done using computation. At the conclusion of the session, there was a notable decline in the severity of anxiety and depression symptoms. The goal is to compile positive evidence supporting the feasibility, efficacy, and proof-of-concept of ACT in reducing depressive symptoms in the postpartum phase. The advantages and disadvantages of this format were examined, along with their prospective applications in clinical health care and future research.
Optimizing Deep Learning Parameters for Enhanced Image Classification Accuracy: A Theoretical and Empirical Analysis
Authors: Khan Muhammad Ali , Khurshid Hina
Published: October 2024

This study investigates the,impact of key deep learning,parameters—algorithm,type, dataset size, learning,rate, batch size, and number,of epochs—on image,classification accuracy, a,critical concern,in industries such as,healthcare, security, and,technology. Despite,advancements in deep learning, optimizing,these parameters for maximum,accuracy remains,challenging. To address,this issue, a,survey was conducted,among 381 professionals and,academics experienced,in deep learning, and,the data was analyzed,using Partial Least Squares,Structural Equation,Modeling (PLS-SEM). The,results confirm that all,five parameters significantly,influence image classification,accuracy, with optimized,settings leading to substantial,improvements. This,study contributes to,the theoretical understanding,of the Bias-Variance,Tradeoff Theory in the,context of deep learning,and offers practical guidelines,for enhancing model,performance. However, limitations,such as reliance on,self-reported data suggest,the need for further,experimental research. The,findings provide a comprehensive,framework for optimizing,deep learning models, offering,both academic insights and,practical solutions for,improving accuracy in,critical applications.
Vehicle And Driver Recognition for Access Control
Authors: Siddiqui Yasir Hussain , Siddiqui Sohaib Hussain , Rashid Munaf , Iqbal Kashif , Nasim Shahzad
Published: October 2024

The following paper proposes an advanced vehicle and driver recognition system to enhance security at vehicular entry-exit points in response to the growing needs of more efficient and secure access control systems at these checkpoints. The proposed system will integrate license plate recognition and facial recognition technologies using state of-the-art machine-learning models from Ultralytics: YOLOv8 and EasyOCR, respectively. It works in three stages: license plate detection, character alpha-numeric identification, and then driver identity with facial recognition. Hence, the two-tier authentication process based on license plate detection and facial identification ensures further prevention from unauthorized entry. Preliminary evaluation of the system also produced very high values for precision, recall, and the mean average precision, indicating that the VDR system offers substantial advances in effectiveness and security when compared to conventional methodologies for access control.
Atención bioquímica con perspectiva de género
Authors: Alejandre Mariel Emilce , Usandizaga Graciela , Madalena Leticia Bibiana
Published: October 2024

Los cambios sociales y el marco regulatorio actual referidos al género inciden en la conformación de las poblaciones que demandan a nuestras instituciones. Desde la atención bioquímica (AB) propiciamos el conocimiento de las normativas que nos permitan brindar a nuestros pacientes un servicio acorde con las nuevas construcciones de ciudadanías. En este sentido, reflexionamos acerca de dos ejes principales: uno social, que incluye la identidad de las personas y la nueva conformación de familias, y otro centrado en los cuerpos. Nos proponemos interpelar a los y las profesionales bioquímicos e instarlos a incorporar la perspectiva de género para una AB integral, con los objetivos de: 1) contemplar e incorporar los cambios sociales y regulatorios al acto de atención en los laboratorios de análisis clínicos, 2) reflexionar sobre los cuerpos y su implicancia en la salud de las personas y 3) identificar al género como categoría de análisis en investigaciones en salud.
Mutaciones en el gen HFE y estado del hierro en voluntarios sanos del noroeste argentino
Authors: Mónaco María Eugenia , Alvarez Asensio Natalia Sofía , Haro Cecilia , Terán Magdalena María , Ledesma Achem Miryam Emilse , Issé Blanca Alicia , Lazarte Sandra Stella
Published: October 2024

Introducción: La proteína HFE (Human hemochromatosis protein) es codificada por el gen HFE y participa en la regulación del metabolismo del hierro. Tres variantes alélicas del gen HFE se han correlacionado con la hemocromatosis hereditaria: C282Y, H63D y S65C. Objetivos: Establecer la prevalencia de las mutaciones más frecuentes en el gen HFE en una población de individuos aparentemente sanos y estudiar su relación con el metabolismo del hierro. Materiales y Métodos: Sesenta y nueve individuos (48 mujeres y 21 hombres) fueron analizados durante el período de septiembre de 2015 a agosto de 2018 en Tucumán, Argentina. Se determinó hemograma, hierro, transferrina, saturación y ferritina. Las mutaciones en el gen HFE se efectuaron mediante PCR en tiempo real. Resultados: La prevalencia fue del 28 % (19/69; IC95% = 18-39%). El 9 % (6/69) presentó mutación heterocigota C282Y y 19 % (13/69; 11 heterocigotos y 2 homocigotos), en codón 63 (H63D). No se detectó la mutación S65C. En los individuos que no portaban mutación, los parámetros de la serie roja y el análisis de hierro fueron más altos en los hombres que en las mujeres (p< 0,05). No hubo diferencias significativas en el metabolismo del hierro entre los voluntarios sanos y los portadores de C282Y o H63D (p> 0,05). Conclusiones: Este es el primer estudio que muestra la frecuencia de las tres variantes del gen de la hemocromatosis en el noroeste argentino.La mutación más prevalente fue la H63D. La presencia de la mutación en el gen HFE no resultó en una sobrecarga bioquímica significativa de hierro.
Una historia de la autoridad: de la respublica christiana al estado moderno
Authors: Nosetto Luciano
Published: October 2024

Este artículo toma como punto de partida las dificultades contemporáneas al momento de distinguir autoridad y autoritarismo, y rastrea el origen de esa confusión en el eclipse moderno de la autoridad por el poder. De allí, parte una reconstrucción histórica de la autoridad, orientada por Carl Schmitt, que conduce a una caracterización de la forma política de la respublica christiana. Hecho esto, el texto procede a evaluar la permanencia de la autoridad en el Estado absolutista y moderno, mediante una serie de claves provistas por Giorgio Agamben. Finalmente se establece una distinción entre autoridad y autoritarismo.Palabras clave: autoridad, poder, imperio, iglesia, Estado A History of Authority: From the Respublica Christiana to the Modern State AbstractThis article begins by acknowledging the contemporary difficulties in distinguishing authority and authoritarianism, and traces the origin of this confusion in the modern eclipse of authority by power. From there, a historical account of authority is provided, guided by Carl Schmitt, which leads to a characterization of the political form of the respublica christiana. The text then proceeds to an evaluation of the permanence of authority within both Absolutist and Modern States, through a series of keys provided by Giorgio Agamben. A distinction between autority and authoritarianism is finally provided. Key-words: Authority, Power, Empire, Church, State ARK CAICYT: https://id.caicyt.gov.ar/ark:/s16668979/xtgkqu0vo