bluuebunny/crossref_metadata_2025 huggingface dataset:
The influence of halal label, price, and brand image on cosmetic product purchase decisions among female students at FEBI UIN KHAS Jember
Authors: Musaidah Ahlam , Ahmadiono Ahmadiono , Masrohatin Siti
Published: September 2024

IntroductionHumans have two primary needs: basic and secondary needs. Women in particular have distinct needs related to their appearance. Cosmetics serve not only to beautify but also to care for the body from head to toe. Many women incorporate cosmetics into their daily routines and use them from morning to night.ObjectivesThe objective of this study is to determine the influence of halal label, price, and brand image on purchasing decisions for cosmetics among female students at UIN KHAS Jember.MethodThis quantitative research employed multiple linear regression analysis. The sample size was determined using Slovin's formula and data were collected through questionnaires distributed to a selected sample of students. The study analyzed the validity, reliability, and classical assumption tests (normality, heteroskedasticity, and multicollinearity) and used multiple linear regression to assess the impact of the independent variables (halal label, price, and brand image) on the dependent variable (purchase decision).ResultsThe findings reveal that halal label and brand image positively influence the purchasing decisions of cosmetic products. These results indicate that students at UIN KHAS Jember consider halal label, price, and brand image as determinants when making cosmetic purchase decisions.ImplicationsThis study highlights the importance of halal labeling in reducing consumer doubts about product halal status, particularly for Muslim consumers who use cosmetics daily. The positive impact of brand image suggests that students are influenced by the reputation and perceived quality of cosmetic brands. These findings also suggest that competitive pricing strategies can significantly affect purchase decisions.Originality/NoveltyThis study provides insights into the factors influencing cosmetic purchase decisions among Muslim students, emphasizing the role of halal certification. This study contributes to the understanding of consumer behavior in the context of halal products, which is critical for marketers targeting Muslim consumers.
Pre- and post-merger efficiency of Islamic state-owned bank: A case study of Bank Syariah Indonesia
Authors: Hakimi Fifi , Maf'ula Faricha , Gultom Rifyal Zuhdi
Published: September 2024

IntroductionThe increased development of Islamic banks in Indonesia is one way that the government is promoting the rise of state financial inclusion. On January 27, 2021, the Financial Services Authority (OJK) formally granted corporate merger permission. Subsequently, on February 1, 2021, BRI Syariah, Bank Syariah Mandiri, and BNI Syariah—three Islamic banking companies— were officially merged to form Bank Syariah Indonesia. This study evaluates the performance efficiency of these three Islamic banks before and after the merger and compares it to other state-owned conventional banks using the Data Envelopment Analysis (DEA) approach with the BCC model framework.ObjectivesThis study aims to compare the efficiency levels of Bank Syariah Indonesia before and after the merger and assess its performance relative to other BUMN conventional banks.MethodThis research utilizes the DEA method with the BCC model to analyze quarterly financial data from March 2019 to March 2023. The inputs considered are total deposits, personal expenses, and fixed assets, whereas the outputs are financing (loans) and income.ResultsThe results indicate that Bank Syariah Indonesia is more efficient than other conventional state-owned banks after the merger. However, pre-merger, BRI Syariah, and BNI Syariah were ranked first in efficiency compared with conventional BUMN banks. The post-merger analysis shows a stable and high level of efficiency for Bank Syariah Indonesia, despite fluctuations.ImplicationsThe findings suggest that the merger improved the performance efficiency of Bank Syariah Indonesia, making it a benchmark for other state-owned banks. The study highlights the importance of mergers in enhancing efficiency and suggests areas for further improvement, such as risk-mitigation strategies during economic downturns.Originality/NoveltyThis study provides additional literature on the impact of mergers on the efficiency of Islamic banks in Indonesia. This is an extension of previous studies on Islamic bank mergers, offering insights into performance differences before and after the merger, using Bank Syariah Indonesia as a case study.
Role of Pedagogy in the Development and Vicissitude of Buddhism
Authors: Ghimire Shurendra
Published: September 2024

From the point of historical analysis, this study recognises the role of pedagogy in bringing vicissitude to Buddhism from its origin to now, and revisits Comte’s three-stage theory in the Indian sub-continent. It also demystifies religious philosophy by illustrating its epistemological base of origin, expansion, and reinterpretation. Information was generated from the translated Nikaya texts and other secondary texts, and analysis was carried out using a hermeneutic approach. From its origin in Varanasi in 600 BC to the Tibetan Plateau in the 20th Century, Buddhism accomplished three major turning points and some minor vicissitudes. Buddhism, whose original form is Dharma-Vinaya, a combination of doctrine and practice, emerged from the practice of the middle path, and the doctrine was developed as a byproduct. Around 300 AD, a new school, Mahayana, emerged that ascended an arhat up to the saviour God. Similarly, around 1400 AD, the noble eightfold path was revised to tantric sex and the arhat into the Tulku. While expanding the doctrine, scholars, monks, and sages interpreted and taught it as per the learners’ epistemological base by changing the content. Pedagogy is the primary cause of vicissitude in Buddhism, and new emergences are the product of fulfilling the ‘gap’ in the epistemological paradigm between the teachers and the learners.
Hegemony, Power Structure and Tribal Resistance: A Subaltern Geopolitics View on Mahasweta Devi’s Chotti Munda and His Arrow (2018)
Authors: Vincent John , Devi Meenakshi K
Published: September 2024

Subaltern studies address postcolonial notions, binary oppositions, and power structures, enabling us to perceive history from an oppressed perspective. Similarly, subaltern geopolitics challenges the traditional narratives that often present the interest of the dominant community and omit the marginalised history. It provides perspectives of the dominant group with geographical imaginaries. This article aims to trace hegemony and power structures with geographical imaginaries through the theoretical framework of subaltern geopolitics in Mahaswetha Devi’s Chotti Munda and his Arrow (2018), translated by Gayatri Chakravarti Spivak.  Munda tribes are connected to the land, and the acquisition of land played a pivotal role in the domination and subjugation of the natives. With the subaltern geopolitics, the process of imperialism against the Tribal community during and after the colonisation is studied. Through the lens of hegemony, the cultural exploitation of tribal communities is analysed. It also focuses on the power structure in terms of political and economic structures and elucidates the resistance of the Munda tribal community. The paper identifies three hegemonic power structures that existed during the colonial period, after the colonial period, and in the contemporary period. The article investigates the power structures imposed on Munda tribes through the ownership of the lands and the tribes’ resistance, irrespective of government. The paper brings out the significance of resistance and the importance of land in the lives of tribal people. It concludes that resistance against the authorities is the only means of their survival.
Government Initiatives and Its Implications in Primary Education during COVID-19 Pandemic: A Qualitative Study in Sylhet, Bangladesh
Authors: Paul Moni , Saha Akash , Biswas Sanjay Krishno
Published: September 2024

The COVID-19 pandemic posed unprecedented challenges to the primary education sector globally, significantly impacting countries like Bangladesh. Focusing on the context of Bangladesh, this research aimed to explore the challenges and effectiveness of government interventions in continuing primary education. This study employed a qualitative approach to collect data from primary schools in two sub-districts (Sylhet Sadar and Sreemangal) in the Sylhet region of Bangladesh. We conducted in-depth interviews with eight primary school teachers and sixteen guardians of primary-level students, as well as key informant interviews with four headmistresses of government primary schools and two Upazilas (sub-district) education officers. Respondents were purposefully selected based on various characteristics such as sex, education, economic status, teaching experience, involvement in child education, and access to information technology. The data was managed using NVivo 14 software and analysed thematically using an inductive approach. The findings highlight the varied outcomes of government efforts during the COVID-19 pandemic, encompassing both successes and challenges. Positive implications include introducing a remote learning platform, innovative instructional approaches, and increased community engagement. However, the study also uncovered flaws in those initiatives, such as unequal learning opportunities, pedagogical shifts, a lack of clear instructions, a lack of child-friendly learning content, and a lack of supervision and monitoring. This research significantly advances existing knowledge by thoroughly examining government initiatives and identifying gaps specific to primary schools at the Upazila level in Bangladesh. The practical implications of these initiatives provide invaluable insights for policymakers and stakeholders shaping educational strategies during emergencies.
Encapsulated Bacteria with a Light-Repressed Deadman Switch for Liver Gene Delivery
Authors: Renteln Michael
Published: September 2024

Adeno-associated viruses (AAVs) have been used for liver gene therapy. Hemgenix and Roctavian are AAV-based treatments for hemophilia B and A, respectively. They cost $3 million and $2.8 million per dose, respectively. While AAV vectors may eventually be cheaper to mass produce, a bacteria-based DNA delivery system might be much cheaper for patients. Also, “bactofection” would allow for the delivery of much larger DNA packages. Such a bacterial system may now be possible, and a prototype for the liver could possibly be developed immediately.
A Novel Tiny Open-Source Board BioRon_EEG for Dry Active Electrode
Authors: rakhmatulin ildar
Published: September 2024

This paper introduces an open-source active high-precision signal amplifier designed for enhancing biodata acquisition, specifically focusing on EEG signals. The compact device, with a diameter of 18 mm, seamlessly integrates electronics, signal processing, and meticulous design considerations. Incorporated within the single board are circuits for low-noise amplification, an analog interface equipped with bandpass filters, and an integrated ADC for precise digitization. A comprehensive evaluation of signal quality has been conducted, encompassing aspects such as noise levels, electrode bias tolerance, and common mode rejection ratio. To facilitate this evaluation, the widely recognized Silver Chloride electrode (Ag/AgCl) has been employed. Additionally, this paper delves into an extensive discussion concerning diverse sources of noise, along with strategies to curtail input noise and minimize noise originating from electrodes and amplifiers. Leveraging the substantial advancements achieved in the design of dry contact electrodes, this specific device is poised to carve a notable niche in the realm of brain-computer interface.
Guiding IT Growth and Sustaining Performance in SMEs through Enterprise Architecture and Information Management: A Systematic Review
Authors: Thango (Y2-rated Researcher) Bonginkosi
Published: September 2024

In today’s fast-paced technological landscape, businesses must adapt to evolving business models and harness the power of data to thrive. Small and Medium-sized Enterprises (SMEs) face significant challenges in aligning IT infrastructure with business objectives while navigating digital transformation. This systematic review, conducted using PRISMA 2020 guidelines, investigates the role of Enterprise Architecture (EA) and Information Management (IM) in driving IT growth and sustaining competitive performance in SMEs. Through a synthesis of academic research, industry analysis, and case studies from the last decade, this review identifies key frameworks—such as TOGAF, Zachman, and FEAF—that support the alignment of IT capabilities with organizational goals. The integration of IM within EA frameworks is found to enhance decision-making, resource allocation, and operational efficiency. Emerging technologies like Artificial Intelligence (AI) and cloud computing are highlighted for their transformative impact, enabling real-time data analysis, improved scalability, and enhanced agility. Our review reports that 43.44% of the studies focused on cloud-based solutions, while 24.59% adopted hybrid models, offering SMEs scalable and flexible IT infrastructures. The findings emphasize the necessity of strong governance frameworks to ensure compliance, adaptability, and long-term sustainability in a dynamic environment. This research contributes to a comprehensive roadmap for SMEs, enabling them to leverage EA and IM for sustained growth and competitive advantage in the digital era.
Research on the Synergistic Effects and Driving Mechanisms of Urban Agglomeration Spatial Expansion: A Case Study of Beibu Gulf in Guangxi, China
Authors: Chen Zhantu , Xiao Limei , Ren Li , Feng Bing , Xie Ling
Published: September 2024

The spatial expansion of urban agglomerations is a direct manifestation of regional urbanization, reflecting the changes in scale and morphological characteristics of urban in temporal and spatial dimensions, which affects the efficiency of regional urbanization. This study employed a range of analytical techniques, including the urban spatial intensity index, center-of-gravity model, synergy index, inverse distance weighting interpolation method, and Geodetector, to examine the spatiotemporal evolution pattern and driving factors of the Beibu Gulf Urban Agglomeration in Guangxi, China between 2012 and 2022. The findings indicate that: (1) The Beibu Gulf Urban Agglomeration in Guangxi has been in a stable expansion trend over the past decade. However, the polarization effect of the central city space has gradually weakened, and the spatial expansion differences between cities have gradually narrowed, indicating an extensional development mode. (2) The economic and social gravity centers show a tendency of "eastward and southward" migration, which is opposite to the direction of the urban gravity center's displacement. The displacement directions of population and ecological gravity centers are roughly consistent with that of urban center. The distribution of economic and social resources are not aligned with the configuration of urban development, and the trajectory of the center of gravity of various development dimensions has shifted. (3) Economic and social expansion is significantly faster than population and ecology, but slower than urban expansion. The intensity of urban expansion is inconsistent with the distribution of synergies. The spatial differences in synergies between cities are gradually narrowing. The central city's radiation-driven role is insufficient. The development of nodal cities is less than expected. However, the benefits of urbanization in coastal cities are constantly being strengthened. (4) The disposable income of urban residents and per capita arable land area are the primary driving forces of urban expansion, while population density and urban green space area are significant contributors to urban expansion. Based on the above findings, it is recommended that the Beibu Gulf Urban Agglomeration of Guangxi should continue to enhance the scale efficiency of population agglomeration, optimize economic development and industrial resource allocation, promote urban-rural integration, strengthen inter-city connections, optimize spatial layout, and improve the overall production and living efficiency of regional cities and towns.
Contribution of Tree Farming on Improvement of Livelihood Assets to Smallholder Farmers in Njombe District, Tanzania
Authors: Mayala Nyanjige Mbembela
Published: September 2024

As a coping mechanism to job creation and income poverty reduction, people in the rural areas are engaging in commercial farm activities commonly known as agribusinesses including tree farming. The study assessed the contribution of tree farming by smallholder farmers on livelihood assets in the study area before and after their engagement. Household survey and key informant interviews were used to collect data from 270 respondents randomly selected from 4 Wards of Njombe Distrct to include Ihanga, Iwungilo Kifanya and Lugenge which mostly practice tree farming; and 4 key informants’ interviews were done to the district officers in the Department of Agriculture, Irrigation and Cooperative. Seven out of nine livelihood asset ownerships were found to have significantly improved after farmers’ being engaged in tree farming. A paired sample ttest was conducted to evaluate the possession of assets by respondents and it was found that household assets before tree farming was (M= 1.80, SD= 0.752) and after engaging in tree farming was (M=2.00, SD= 0.199), t (269) = 8.706, p<0.0005(two-tailed). The mean increase score in houses ownership for instance was 0.2 at 95% confidence interval ranging from -0.433 to 0.033. The eta squared statistic of (0.219) indicated a strong effect on tree farmers’ livelihood in the study area and a significant improvement in livelihood assets after engagement in tree farming. It is concluded that, this activity has contributed to income poverty reduction by giving smallholder farmers a good purchasing power for the livelihood assets. It is recommended that; the government should control the market of forest related products and ensure price stability.
Approximate Unlearning in Finance
Authors: Qi Chang
Published: September 2024

Approximate unlearning is an emerging field in machine learning that addresses the challenge of efficiently removing specific data points from models without the need for full retraining. In the financial sector, where models are built on sensitive customer data and market information, the ability to unlearn data is crucial for meeting privacy regulations like GDPR and ensuring model adaptability in real-time environments. This paper explores the categorization of approximate unlearning into two main approaches: data-driven approximation and model-driven approximation. Data-driven approximation focuses on selectively retraining parts of the dataset to simulate the removal of data, while model-driven approximation adjusts the model’s internal parameters to nullify the influence of unwanted data points. Both methods offer computational and memory-efficient ways to balance the need for privacy compliance with the performance demands of financial models. The paper discusses practical applications in algorithmic trading, fraud detection, and risk assessment, and highlights the challenges associated with each approach. Through case studies and literature references, we demonstrate how approximate unlearning can be applied to maintain system efficiency, data privacy, and regulatory compliance in the financial domain. This research provides a roadmap for future developments in approximate unlearning, particularly in the context of real-time financial systems and federated learning environments.
A Ceramide Theory of Multiple Sclerosis
Authors: Rappoport Ari
Published: September 2024

This paper presents a new theory explaining the pathological mechanisms of multiple sclerosis (MS). MS is triggered by persistently activated immune cells, mainly B cells, as in reactivated Epstein-Barr virus infection. Activated immune cells release cytokines, the main one here being TNFa. A major role of TNFa is to support immune cell motility and tissue penetration, by promoting the breakdown of ceramide products that stabilize membranes (sphingomyelin (SPM) and galactosylceramide (GalCer)), by stimulating membrane breakdown via ceramide 1-phosphate-induced liberation of arachidonic acid, and by promoting the production of sphingosine 1-phosphate, a ceramide product that promotes immune motility. These ceramide products are expressed in endothelial cells, including the blood-brain barrier, and have a large presence in myelin. Thus, excessive cytokine release both allows immune penetration into the brain, and impairs existing myelin sheaths. SPM and GalCer are essential for myelin maintenance but not for its synthesis, explaining the dominant relapsing-remitting nature of the disease. The theory is supported by diverse evidence, and supports modern B cell-based treatment directions.
Predicting Above-Ground Biomass of Forest in South Carolina: Integrating Remote Sensing, Machine Learning, and Interpolation Techniques
Authors: Sharma Sanjeev , Khanal Puskar
Published: September 2024

This study evaluates the effectiveness of a Random Forest model for predicting above-ground biomass in South Carolina (SC), utilizing diverse remote sensing and climatic data sources. SC, with its humid subtropical climate and varied geography, including the Atlantic coastal plain, Piedmont, and Blue Ridge Mountains, poses unique challenges for biomass estimation. We integrated global biomass datasets for 2010, MODIS vegetation indices (NDVI and EVI), Leaf Area Index (LAI) from MOD15A2H, and climate data from TerraClimate. The model was trained using 2010 data and applied to 2022 datasets to assess biomass changes. To validate the model, plot-level biomass estimates from the 2023 FIA data were interpolated using Inverse Distance Weighting (IDW). Performance evaluation showed a strong positive correlation between predicted and observed biomass, with a correlation coefficient of 0.77 and an R² value of 0.62, indicating that the model explains 62% of the variability in biomass. Comparison with IDW-interpolated biomass data resulted in a correlation coefficient of 0.64, confirming the model's validity. Although the Random Forest model demonstrated reliable predictions, the study suggests potential improvements by incorporating additional data sources and advanced modeling techniques. The findings emphasize the value of integrating remote sensing data, machine learning, and interpolation methods to enhance biomass estimation accuracy. This research provides crucial insights into biomass distribution in SC and establishes a basis for future studies on forest monitoring and carbon accounting, highlighting the importance of combining various data sources for comprehensive environmental analysis.
Cyber Harassment in the Digital Age: Trends, Challenges, and Countermeasures
Authors: Ahmed Rashed
Published: September 2024

The advent of the digital age has introduced unprecedented opportunities for communication and connectivity, but it has also given rise to new forms of harassment, collectively termed cyber harassment. This research article provides an in-depth exploration of cyber harassment, examining its prevalence, the profound impact it has on victims, and potential solutions to mitigate its effects.The study is structured around three primary research objectives. Firstly, it investigates the psychological impact of cyber harassment on victims, highlighting the severe emotional and mental health consequences that can arise from such abuse. Secondly, the article scrutinizes the role of social media platforms in both facilitating and combating cyber harassment, analyzing how these platforms can act as both enablers of harassment and as venues for intervention. Thirdly, the research evaluates the current legal frameworks and responses to cyber harassment, considering their effectiveness and suggesting possible improvements. Recent research findings and diverse methodologies are integrated to provide a comprehensive understanding of the multi-faceted nature of cyber harassment. By addressing these key areas, the article aims to contribute to the development of more effective strategies to prevent and respond to cyber harassment, ultimately fostering a safer online environment.
Enhanced Modal Fusion Learning for Multimodal Sentiment Interpretation
Authors: Robinson Kayla , Martinez Ava , Turner Ethan
Published: September 2024

Multimodal sentiment analysis is rapidly gaining traction due to its ability to comprehensively interpret opinions expressed in video content, which is ubiquitous across various digital platforms. Despite its promising potential, the field is hindered by the limited availability of high-quality, annotated datasets, which poses substantial challenges to the generalizability of predictive models. Models trained on such scarce data often inadvertently assign excessive importance to irrelevant features, such as personal attributes (e.g., eyewear), thereby diminishing their accuracy and robustness. To address this issue, we propose an Enhanced Modal Fusion Learning (EMFL) methodology aimed at significantly improving the generalization capabilities of neural networks. EMFL achieves this by optimizing the integration and interpretation processes of multimodal data, ensuring that sentiment-relevant features are prioritized over confounding attributes. Through extensive experiments conducted on multiple benchmark datasets, we demonstrate that EMFL consistently elevates the accuracy of sentiment predictions across verbal, acoustic, and visual modalities. These findings underscore EMFL's efficacy in mitigating the impact of non-relevant features and enhancing the overall performance of multimodal sentiment analysis models.
Diverse Fatty Acid Profiles and Antioxidant Properties in Different Populations of Ox Tongue (Echium amoenum) Fisch. & Mey
Authors: Emami Bistgani Zohreh , Rowshan Sarvestani Vahid , Hashemi Masoud
Published: September 2024

Ox Tongue (Echium amoenum) is an important medicinal plant rich in secondary metabolites, including alkaloids, quinones, and unsaturated fatty acids. The present study examined the concentration of oil, fatty acid profiles, and antioxidant activity of six different Iranian Echium accessions. The oil concentration varied across these populations, ranging from 16.20% to 22.36% in the first year and from 21.00% to 25.50% in the second year. The major fatty acids identified in the oils were oleic acid (18.35% to 19.40%), linoleic acid (23.80% to 26.20%), and α-linolenic acid (32.30% to 34.20%) during the first year. In the second year, the predominant fatty acids were oleic acid (15.82% to 19.32%), linoleic acid (21.55% to 24.70%), and α-linolenic acid (33.95% to 37.40%). Principal component analysis revealed distinct profiles for each population: Sari was notable for its high α-linolenic acid and γ-linolenic acid content, Fasa was distinguished by its high stearidonic acid levels, Roodsar had a high concentration of stearic acid, Vazneh Sar was rich in linoleic acid and palmitic acid, and Leron had the highest oleic acid content. The Sari population had the highest oil content at 25.50%, while Fasa had the highest α-linolenic acid content at 37.40% during the establishment year. Leron exhibited the highest antioxidant attributes. These findings indicate that selecting elite Echium populations with high levels of unsaturated fatty acids and potent antioxidant properties could be advantageous for the food industry, as they offer enhanced nutritional and functional qualities.
The Impact of Data Packet Loss on Neural Decoding
Authors: Zheng Jiaqi , Li Yuan , Chen Liangliang , Wang Fei , Gu Boxuan , Sun Qixiang , Gao Xiang , Zhou Fan
Published: September 2024

Background: In the field of brain-computer interfaces, neural decoding plays a crucial role in translating neural signals into meaningful physical actions. These signals are transmitted to processors for decoding via wired or wireless channels, often encountering data loss, commonly referred to as "packet loss." Despite its importance, the impact of different types and degrees of packet loss on neural decoding has yet to be comprehensively studied. Understanding this impact is critical for advancing neural signal processing and data filtering.
Methods: This paper addresses this gap by constructing four distinct packet loss models, simulating congestion packet loss, distributed packet loss, and burst packet loss scenarios. Using macaque superior arm-movement decoding experiments, we evaluate the effects of these packet loss types on decoding performance.
Results: Our findings reveal that continuous burst packet loss significantly degrades decoding performance at the same packet loss probability, and decoding parameters that are sensitive to data continuity are more heavily impacted by packet loss.
Conclusions: This study provides an analysis of the relationship between packet loss and neural decoding results, offering valuable insights for future strategies aimed at preventing and handling packet loss in neural signal acquisition.
Multimodal Information Fusion with Neural Gating
Authors: Smith Olivia , Martinez Ava , Brown Noah
Published: September 2024

In this study, we introduce an innovative framework for multimodal learning that leverages enhanced fusion gate units within gated neural network architectures. The proposed Fusion Gate Unit (FGU) serves as a pivotal component in neural network designs, aiming to derive a comprehensive intermediate representation by amalgamating data from diverse modalities. The FGU is adept at determining the extent to which each modality influences the unit's activation through the utilization of multiplicative gating mechanisms. We conducted evaluations on a multilabel genre classification task for movies, utilizing both plot summaries and poster images as input modalities. The results demonstrate that the FGU significantly elevates the macro F-score compared to single-modality approaches and surpasses existing fusion techniques, including mixture of experts models. Additionally, we present the MM-IMDb dataset alongside this publication, which, to our knowledge, represents the most extensive publicly accessible multimodal dataset for movie genre prediction to date. This dataset is expected to facilitate further research and development in the field of multimodal information processing.
Evaluation Metrics for Machine Unlearning
Authors: Lindstrom Cassandra
Published: September 2024

The evaluation of machine unlearning has become increasingly significant as machine learning systems face growing demands for privacy, security, and regulatory compliance. This paper focuses on categorizing and analyzing evaluation metrics for machine unlearning, essential for assessing the success of unlearning processes. We divide the metrics into three key dimensions: unlearning effectiveness, unlearning efficiency, and model utility. Unlearning effectiveness examines the degree to which data is removed from the model, utilizing methods such as data removal completeness, privacy leakage detection, and perturbation analysis to ensure thorough data erasure. Unlearning efficiency considers metrics like time to unlearn, computational cost, and scalability, which are crucial for maintaining system performance in real-time environments. Model utility metrics, including accuracy retention, robustness, and fairness, ensure that unlearning does not compromise the model’s predictive capabilities. Through this categorization, we present a comprehensive framework for evaluating machine unlearning, providing a foundation for developing unlearning techniques that balance privacy, performance, and regulatory needs across diverse industries, particularly finance.
How Agroecological Transition Frameworks Are Reshaping Agroecology: A Review
Authors: Fonseca Ana Filipa , Polita Fabíola , Madureira Lívia
Published: September 2024

The "agroecological transition" has emerged as a framework that aims to explain the complex changes taking place in agrifood systems. This study offers a mapping of the emergence of this framework, and aims to demonstrate that the “agroecological transition” can refer to different perspectives beyond the simple combination of two concepts. We carried out a bibliometric analysis of 298 articles (2012 - 2023), searched under the command "agroecologic* transition*". We used VOSviewer software, which is able to reveal clusters of co-citations of the most cited authors and articles. This result, in turn, indicates the existence of different perspectives on the use of "agroecological transitions". Four clusters were found: "Techniques and Practices", represented by articles that document the agroecological transition as an expression of specific agricultural techniques and practices; “Transition Theory", which employs the emerging theory and its conceptual contributions; "Transition Criteria", which involves the use of criteria to monitor the transition; "Political and Social", made up of articles that explore the political and social movement dimension of agroecology. Each of these clusters, and their approaches, contribute different interpretations of agroecology itself, indicating the emergence of a new framework capable of attributing new meanings to it.
Synergies between Class Incremental Learning and Machine Unlearning
Authors: Qi Chang
Published: September 2024

The convergence of Class Incremental Learning (CIL) and Machine Unlearning (MU) is a rapidly developing field in machine learning, especially relevant in adaptive and privacy-sensitive environments like finance. CIL enables models to learn new data classes over time without losing previously acquired knowledge, while MU focuses on selectively forgetting specific data to comply with privacy laws or mitigate security risks. In this paper, we examine the theoretical foundations and practical applications of both approaches, particularly in the financial domain. We explore how these two paradigms interact and complement each other, discuss key algorithms, and present examples to illustrate their applications in areas such as portfolio management, fraud detection, and data privacy. Finally, we explore challenges and potential future directions in achieving optimal synergy between CIL and MU.
Threat Models to Machine Unlearning
Authors: Milner Larry
Published: September 2024

Machine unlearning is a critical process designed to allow machine learning models to forget or remove specific data upon request, particularly for privacy protection. While the primary objective of unlearning is to safeguard sensitive information, it introduces substantial privacy and security risks. This paper explores the two major categories of threats to machine unlearning: privacy attacks and security attacks. Privacy attacks, such as membership inference and model inversion, exploit residual information to infer or reconstruct sensitive data that should have been erased. Security attacks, particularly specific data poisoning, involve the injection of malicious data into the training process, which may leave lingering effects even after the unlearning process. In this paper, we provide an in-depth examination of these threats and propose several defense mechanisms. Differential privacy, adversarial training, and query limitations are highlighted as key defenses against privacy attacks, while data validation, adversarial examples, and post-unlearning audits are critical in mitigating security risks. Additionally, we discuss emerging methodologies like data provenance tracking and fine-tuning as crucial for ensuring unlearning processes are thorough and effective. Through these analyses, we aim to provide a comprehensive framework for strengthening the security and privacy of machine unlearning systems, enabling their broader adoption across industries such as healthcare, finance, and AI-driven technologies.
The Predictive Impact of Antipsychotics on Functionality Index in Schizophrenia (PIAF)
Authors: Marinescu Gabriel Cristian , Ifteni Petru Iulian , Teodorescu Andreea , Georgescu Radu
Published: September 2024

Schizophrenia can lead to significant and long-lasting deficits in patients' functionality. The present study aims to identify a theoretical index that predicts the ability of an antipsychotic to improve the functionality of patients with schizophrenia. An advantage of such a theoretical index is that it represents an attempt to supplement with theoretical information the data coming from meta-analysis and systematic reviews and could directly compare antipsychotics. Aspects such as pharmacodynamics, pharmacokinetics, and pharmaceutical forms have been considered. A total of 29 typical and atypical antipsychotics were analyzed. It was constructed the Predictive Impact of Antipsychotics on Functionality Index (PIAF). This parameter considers pharmacodynamics and administration comfort, each expressed through other parameters. PIAF is higher for antipsychotics with both high Pharmacodynamic Scores, which are correlated only with the active substance, and good Comfort of Administration Scores, which are correlated with both the pharmaceutical forms of antipsychotics and the active substance. The best ranking was obtained by the only partial agonist dopaminergic D2 antipsychotic with LAI formulation (aripiprazole LAI), followed by the atypical LAI antipsychotic with the rarest administrations (paliperidone LAI 6M). Given this ranking, a better antipsychotic would result from the combination of a partial dopaminergic agonist with the lowest possible administration frequency. According to PIAF, the most favourable for the functionality are atypical LAI antipsychotics. The partial agonist mechanism of D2 dopamine represents an advantage. Based on this functionality index, the clinical psychiatrist could select the most suitable antipsychotic for patients, with the ultimate goal of achieving individual maximum potential.
The Role of Statins in the Prevention and Management of Alzheimer’s Disease: A Focused Review
Authors: Copelin Taylor A. , Kobzeff Madison L. , Franco Rachelle A. , Gafurova Songul M.
Published: September 2024

Alzheimer’s disease (AD) is a neurodegenerative disease that is characterized as a progressive decline in cognitive functions that primarily affects older adults. Alzheimer’s is pathophysiologically characterized by the accumulation of amyloid-beta (Aβ) plaques, neuroinflammation, accumulation of tau proteins in neurofibrillary tangles (NFTs), and tissue loss. These three main characteristics are hallmarks of neurodegeneration. Statins are a class of medications that lower the cholesterol levels in the blood, and their anti-inflammatory effects have gained attention for their potential impact on influencing AD progression. This literature review explores the relationship between the use of statins and AD, examining the effect of statins on cholesterol metabolism, neuroinflammation, apolipoprotein E (ApoE), and Aβ production. This literature review was conducted using PubMed and Google Scholar to summarize the association between statins and AD. The neurodegenerative properties of Alzheimer’s disease have been imaged and documented in both rodent models and humans. Experiments using transgenic mice and knock-in mice have shown that specific human genes enhance neurodegeneration, and the overactivation of glial cells in the brain causes hallmark neuroinflammation. These rodents all subsequently suffered from neurodegeneration and AD symptoms. Humans showed promise of possible AD biomarkers in the blood and brain through the presence of excess isoprostanes and oxysterols, respectively, providing hope for future research into early detection/treatment. There has been evidence that statins exhibit neuroprotective pleiotropic effects in rodent models, showcasing reductions in cellular adhesion molecules (the main molecule in inflammation), oxidative stress, and inflammatory peptides. ApoE is a cholesterol transport protein in the brain and is critical to forming an effective synapse. Statin use has effectively altered the ApoE4 allele and reduced the Aβ production in the brain. However, the mechanism for which statins slow the progression of neurodegeneration in AD is still unclear and warrants further research before it can be officially called a treatment.
Seroprevalence of transfusion transmissible hepatitis viruses in Kwara state Nigeria.
Authors: Izevbuwa Osazee Ekundayo
Published: September 2024

The burden of hepatocellular carcinoma as well as other health complications associated with infections due to Hepatis B and C Viruses are significant around the world. A number of research suggests that assumed healthy living individuals and potential blood donors are the major reservoirs of the Viruses in the community. During the course of this study, a total of 300 apparently healthy blood donors who presented to the blood group serology unit for blood donation across Ilorin, Kwara State, Nigeria, were screened to determine the Sero-prevalence of Transfusion Transmissible Hepatitis Viruses (Hepatitis B and C Viruses). Blood samples obtained from consented potential blood donors were collected and tested for Hepatitis B surface antigen (HBsAg) and Anti-HCV using immunochromatographic methods. The positive samples after the initial qualitative screening were subjected to Enzyme Linked Immunosorbent assay (ELISA) for confirmation of HBV and HCV Immunoglobulin G (IgG) following standard best practices. The results showed that 10% and 0.7% of the blood samples tested positive for HBV and HCV respectively. The male donors had more HBV infection 24 (8.0%) than the females 6 (2.0%). Donors with O Rhesus D positive blood type had more HBV infection 12 (4.0), while blood groups AB Negative, B Negative and O negative showed the least prevalence of 0 (0.0%). The age group of donors above 30 years of age had more HBV prevalence with 37.3% while the age group of 26 to 30 years showed the least prevalence of 28.7%. Data obtained from the piloted structured questionnaires designed to study the socio-demography of the participants showed that HBV was more prevalent among single blood donors, Civil servant/professional workers, and among blood donors that have successfully completed their tertiary education. The data from this research however, showed a negative correlation between the spread of the transfusion transmissible hepatitis viruses and the educational/ occupational standards of the test subjects who were included in this research. The highest rates of viremia were recorded among blood donors residing in urban areas however, the prevalence was not statistically different (p≥0.05).
PENGGUNAAN LAGU DAN MUSIK SECARA KOMERSIAL YANG DIBAWAKAN OLEH PENYANYI/GRUP MUSIK DI PERNIKAHAN BERDASARKAN UNDANG-UNDANG NO. 28 TAHUN 2014 TENTANG HAK CIPTA
Authors: Sanda Femy , Pujiyono '
Published: September 2024

Artikel ini bertujuan untuk mengetahui problematika hukum perlindungan hak cipta terhadap lagu dan musik yang dibawakan oleh penyanyi/grup musik di pernikahan. Penelitian ini adalah penelitian normatif yang bersifat preskriptif. Hasil penelitian menunjukkan bahwa terjadi peningkatan pada tiga tahun terakhir yaitu 2018-2020 terkait pelanggaran dibidang hak cipta lagu/musik milik pencipta/pemegang hak cipta. Hal ini terjadi karena tidak ada pengaturan mengenai pembayaran royalti apabila lagu yang dikomersialkan dibawakan oleh sekelompok orang seperti penyanyi/grup musik di acara pernikahan; permohonan izin lisensi masih sulit serta; DJKI serta para aparat hukum yang berwajib tidak bisa segera memproses jika terjadi adanya dugaan pelanggaran pada lagu/musik milik pencipta.
PERLINDUNGAN HUKUM TERHADAP KREDITUR DALAM EKSEKUSI OBJEK HAK TANGGUNGAN DARI SITA EKSEKUSI PIHAK KETIGA (Studi Putusan No. 61/Pdt.Plw/2017/PN. Jmb)
Authors: Azani Annisa Puspita , Suraji '
Published: September 2024

Abstrak

Abstrak

Artikel ini bertujuan untuk menjelaskan perlindungan hukum bagi kreditur atas haknya terhadap objek hak tanggungan, ketika dieksekusi oleh pihak lain. Penelitian ini 2 merupakan penelitian hukum normatif yang bersifat preskriptif dengan pendekatan perundang-undangan (statute approach). Sumber bahan hukum adalah bahan hukum primer, sekunder, dan tersier. Teknik pengumpulan bahan hukum menggunakan teknik studi kepustakaan (library research) dengan cara mengunduh (download), menyalin (copy), mengoleksi literatur yang berupa buku-buku atau jurnal kemudian mengkualifikasi bahan hukum. Selanjutnya dianalisis menggunakan metode silogisme dengan pola berpikir deduktif. Permasalahan hukum yang timbul yaitu objek hak tanggungan yang sedang dilelang oleh kreditur untuk pelunasan hutang debitur, dilakukan sita eksekusi oleh pengadilan karena adanya perkara lain. Sesuai dengan teori perlindungan hukum yang dikemukakan oleh Moch. Isnaeni, kreditur dapat diberikan perlindungan secara internal maupun eksternal. Perlindungan hukum internal yaitu dengan dibuatnya perjanjian hutang-piutang yang mengatur hak dan kewajiban para pihak dalam perjanjian untuk mengurangi resiko kerugian. Bentuk perlindungan hukum eksternal yaitu adanya regulasi yang digunakan sebagai dasar perlindungan kreditur, yakni Undang-Undang No.4 Tahun 1996 tentang Hak Tanggungan Hal tersebut terbukti di dalam amar Putusan No. 61/Pdt.Plw/2017/PN. Jmb yang menyatakan bahwa sita eksekusi terhadap objek hak tanggungan harus dibatalkan.

Kata Kunci: Eksekusi Objek Hak Tanggungan; Hak Tanggungan; Perlindungan Hukum
PERTANGGUNGJAWABAN PERDATA AHLI WARIS PELAKU TINDAK PIDANA KORUPSI YANG SUDAH MENINGGAL
Authors: Sirait Obed Joshua , Nugraheni Anjar Sri Ciptorukmi
Published: September 2024

Abstract

This articles aims to analyze the construction of the legal relationship between testator, heirs, and the state as well as to study and analyze the form of accountability for state losses that have been caused by criminal offenders who have died in court proceedings. The research method is using normative legal research with statute approach, case approach, and conseptual approach. The legal materials used are primary and secondary legal materials, with data collection techniques used are document study technique or library study technique. Based on the result of the research, it can be concluded that there is a relationship between the heir and the state resulting from the act of the testator who commits corruption and the obligation to pay the loss still exists even though in the Criminal Code the criminal obligation has been terminated because the perpetrator died, the heirs of the perpetrators of a criminal act of corruption are obliged to be responsible if the person concerned receives the inheritance and the inheritance has been proven to contain losses to state finances.

Keywords: Heirs; Inheritance; Responsibilities; State Finance Loss

Abstrak

Artikel ini bertujuan untuk menganalisis konstruksi hubungan hukum antara pewaris, ahli waris, dan negara serta mengkaji dan menganalisis bentuk pertanggungjawaban dari kerugian negara yang telah diakibatkan oleh pelaku tindak pidana yang sudah meninggal di dalam proses pengadilan. Metode penelitian yang digunakan adalah penelitian hukum normatif dengan pendekatan perundang - undangan, pendekatan kasus, dan pendekatan konseptual. Bahan hukum yang digunakan adalah bahan hukum primer dan sekunder, dengan teknik pengumpulan data yang digunakan adalah teknik studi dokumen atau studi kepustakaan. Berdasarkan hasil pembahasan dapat diketahui bahwa adanya konstruksi hubungan antara ahli waris dengan negara yang ditimbulkan dari perbuatan pewaris yang melakukan korupsi dan kewajiban untuk membayar kerugiannya tetap masih ada walaupun di dalam KUHP kewajiban pidananya telah gugur dikarenakan pelakunya meninggal dunia, Ahli waris dari pelaku tindak pidana korupsi wajib bertanggungjawab apabila yang bersangkutan menerima harta warisan tersebut dan harta warisan tersebut telah secara nyata terbukti mengandung kerugian keuangan negara.

Kata Kunci: Ahli Waris; Kerugian Keuangan Negara; Tanggung Jawab; Waris