ethicalabs/Research-Intent-Collab huggingface dataset:
An Overview of the Applications and Conditions for Using Artificial Intelligence and Digitalization in Occupational Health and Safety in the Workplace

Introduction: Artificial Intelligence (AI) and digitalization are pivotal in enhancing Occupational Healthand Safety (OHS), reducing workplace accidents, improving conditions, and boosting organizationalproductivity. This study examines the impacts, challenges, and opportunities of these technologies inworkplace safety.  Material and Methods: A narrative review was conducted via databases (Google Scholar, PubMed,IEEE Xplore, ScienceDirect) using keywords like “AI in occupational safety” (2013–January 2025). Afterscreening 125 articles, 71 met the inclusion criteria (Persian or English publications). Qualitative contentanalysis identified key challenges and opportunities.  Results: Artificial intelligence has been used in predicting incidents, monitoring, process optimization,and analyzing OHS challenges. By analyzing historical data and hazard patterns, AI enables proactive riskmitigation. Continuous learning in AI models enhances predictive accuracy and environmental adaptability.However, data quality issues persist; techniques such as transfer learning offer potential solutions. AI-driven automation reduces human error, yet challenges include ethical concerns and infrastructure gaps.  Conclusion: AI and digital technologies are transforming OHS through predictive analytics and real-timesurveillance. To fully leverage these benefits, future efforts must focus on addressing data quality issues,establishing robust ethical frameworks, and developing advanced infrastructure. Further research isessential for the practical implementation of AI in a variety of work environments
Four Issues in Cost-Effectiveness Analysis and Health Technology Assessment: a View from the Touch-line

Like many fathers and grandfathers, I have spent long hours in bad weather on touchlines urging on bunches of muddy little – and not so little – knots of boys and girls in amateur soccer league matches (in my case it has been almost exclusively soccer – a game I never played myself).
Low-frequency observations of Galactic supernova remnants and the distribution of low-density ionized gas in the interstellar medium

New long-wavelength observations of Galactic SNRs at 30.9 and 57.5 MHz are used to derive detailed low-frequency radio spectra for 32 SNRs. Of these, about two-thirds show turnovers at low frequencies, implying the presence of a widespread, but inhomogeneous, ionized absorbing medium along the lines of sight. These observations are combined with other low-frequency data to derive free-free optical depths toward 457 SNRs and to constrain the physical properties of the ionized gas responsible for the absorption. These optical depths are consistent with the expected absorbing properties of extended H II region envelopes. 43 refs.
Consistent Dropout for Policy Gradient Reinforcement Learning

Dropout has long been a staple of supervised learning, but is rarely used in reinforcement learning. We analyze why naive application of dropout is problematic for policy-gradient learning algorithms and introduce consistent dropout, a simple technique to address this instability. We demonstrate consistent dropout enables stable training with A2C and PPO in both continuous and discrete action environments across a wide range of dropout probabilities. Finally, we show that consistent dropout enables the online training of complex architectures such as GPT without needing to disable the model's native dropout.
Legal Certainty of Filing Judicial Review in Tax Dispute Resolution After the Constitutional Court Decision No. 24/PUU-XXI/2024

Judicial review plays a crucial role in ensuring justice and legal certainty in tax dispute resolution, particularly in Indonesia, which adheres to the principle of a rule of law (Recht Staat). The Constitutional Court Decision No. 24/PUU-XXI/2024, however, limits the Directorate General of Taxes from filing judicial reviews, creating challenges for addressing errors in tax dispute decisions. This research uses a normative juridical approach to analyze the legal implications of this restriction, examining its impact on state revenue and legal fairness. Findings indicate that such limitations not only reduce legal certainty but also hinder the correction of judicial errors, potentially causing state financial losses. To address these issues, the study recommends a regulatory model that balances the rights of both taxpayers and tax authorities, fostering fair legal certainty and supporting tax revenue optimization for the State Budget. This regulatory refinement is vital for maintaining justice and fiscal stability in Indonesia.
Interpreting the role of artificial intelligence (AI) tools and assistive technologies in enhancing accessibility in primary school special education

The integration of artificial intelligence (AI) and assistive technologies in primary school special education offers new opportunities to enhance accessibility for students with disabilities. However, effective use of these tools depends heavily on how teachers adopt and implement them in classroom settings. Despite the potential of AI-powered tools such as speech-to-text applications and adaptive learning platforms to support diverse learning needs, significant challenges remain. This study addresses the issue of limited effective implementation of AI tools in special education due to a lack of training, financial limitations, technical difficulties, and ethical concerns. The objective is to explore the experiences, perspectives, and challenges of primary school special education teachers in using AI-integrated tools for inclusive education. Using a hermeneutic qualitative approach, semi-structured interviews were conducted with 10 special education teachers who had experience with AI in their classrooms. Findings reveal that teachers acknowledge the benefits of AI in supporting personalized learning and bridging accessibility gaps. However, barriers such as inadequate professional development, lack of institutional support, and concerns over reduced teacher-student interaction hinder meaningful adoption. The study recommends a teacher-centered approach to AI integration. Key suggestions include providing structured professional development programs, increasing government and institutional funding for AI in education, and promoting ethical practices to address data privacy and algorithmic bias. Overall, the research highlights that AI should enhance not replace traditional teaching methods, ensuring primary special education remains inclusive, equitable, and focused on human connection.
Effects of integrated pest management, biological control and prophylactic use of insecticides on the management and sustainability of soybean

This study aimed to evaluate the prophylactic use of insecticides (PUI) in comparison with integrated pest management (IPM) and biological control (BC) strategies. Five replicated experiments were carried out independently in two Brazilian soybean-producing states, Goias and Parana, where those pest-control strategies were evaluated during two consecutive growing seasons. The evaluated treatments were integrated pest management (IPM); prophylactic use of insecticides (PUI), a practice that has been increasingly adopted by soybean growers in Brazil as well as in other Latin American countries; biological control (BC) and the control (C), which involved no pest treatment. Although the pest infestation rates in the BC and IPM treatments were higher than that in the PUI treatment, crop productivity, in general, was similar among these treatments and differed only from the control with no pest treatment. These results indicate that the prophylactic use of insecticides on soybeans does not result in higher productivity in the field and that this practice merely requires larger amounts of pesticides, which can impair the sustainability of the soybean crop. Therefore, the use of IPM still remains the best alternative for pest management in soybean fields.
General Data Protection Regulation (GDPR) in the airline industry: privacy in the eyes of the Lebanese consumers

The General Data Protection Regulation (GDPR), an EU–wide piece of legislation became active on 25 May 2018. The binding regulation impacts all human data objects and its implementation and effectiveness have raised many questions. The GDPR is, indeed, very serious with the compilation, usage, and preservation of personal data. This article explains, with the help of an online survey, the consumers' perception of this new regulation (i.e. GDPR) and also analyses its expected outcomes. The primary research question under investigation is the level of awareness of GDPR and how it affects the data subject's rights. The GDPR articles were themed to build a set of questionnaires. The study found that although Lebanese consumers are somehow aware of the changing rules of privacy, they have only a moderate concern over personal data and are willing to trade them for any apparent personal gain.
‘Horizontal’ Compliance with Decisions of the African Court on Human and Peoples’ Rights

Abstract                This chapter develops an innovative approach to the furtherance of compliance with decisions of supranational human rights tribunals beyond the vertical context of decisions of these tribunals applying only to the respondent states. Through a reflection on the African Court on Human and Peoples’ Rights (African Court), it introduces the idea of ‘horizontal’ compliance where the Court can seek to ensure compliance with its decisions involving the validity of laws vis-à-vis states with comparable legal provisions to the respondent state. Indeed, the pursuance of horizontal compliance would allow the Court to radiate its key decisions, involving the validity of legal provisions, beyond the specific respondent state. Horizontal compliance would also require an adaptation of the Court’s functions from merely serving as a reactive to a proactive protector of continental human rights standards. While this new function may be seen as crossing the blurry boundaries of the Court’s protective mandate towards a promotional mandate, this would not constitute an undue expansion of the Court’s reach as it will be limited to instances where the decision involves the validity of legal provisions, which is true in a small minority of cases.
Science Communication as Co-Creation: Insights from Stakeholder Engagement in the Philippine Public Sector

This article reflects on #OneDOST4U, a unifying communication handle adopted by the Republic of the Philippines’ Department of Science and Technology (DOST) across multiple media vehicles. The campaign sought to strengthen a single institutional identity while inviting participation and feedback from diverse audiences, such as researchers, educators, local governments, industry partners, and communities. Through focus group discussions with stakeholders from 11 agency projects, we explored how publics interpreted and engaged with the campaign. Using qualitative thematic analysis, we identified recurring themes of value-in-use, dialogic engagement, and communal identity. Findings illustrate how institutional branding tools operate as boundary objects: recognisable symbols that different groups interpret in context while contributing to a shared sense of meaning. For science communication practice, #OneDOST4Udemonstrates that unifying institutional campaigns are most effective when treated as participatory boundary objects—tools that allow diverse stakeholders to negotiate meaning, build trust, and co-create the public value of science.
Learning Heterogeneous Knowledge Base Embeddings for Explainable Recommendation

Providing model-generated explanations in recommender systems is important to user experience. State-of-the-art recommendation algorithms - especially collaborative filtering (CF)-based approaches with shallow or deep models - usually work with various unstructured information sources for recommendation, such as textual reviews, visual images, and various implicit or explicit feedbacks. Though structured knowledge bases were considered in content-based approaches, they have been largely ignored recently due to the research focus on CF approaches. However, structured knowledge exhibit unique advantages in personalized recommendation systems. When the explicit knowledge about users and items is considered for recommendation, the system could provide highly customized recommendations based on users' historical behaviors and the knowledge is helpful for providing informed explanations regarding the recommended items. A great challenge for using knowledge bases for recommendation is how to integrate large-scale structured data, while taking advantage of collaborative filtering for highly accurate performance. Recent achievements in knowledge-base embedding (KBE) sheds light on this problem, which makes it possible to learn user and item representations while preserving the structure of their relationship with external knowledge for explanation. In this work, we propose to explain knowledge-base embeddings for explainable recommendation. Specifically, we propose a knowledge-base representation learning framework to embed heterogeneous entities for recommendation, and based on the embedded knowledge base, a soft matching algorithm is proposed to generate personalized explanations for the recommended items. Experimental results on real-world e-commerce datasets verified the superior recommendation performance and the explainability power of our approach compared with state-of-the-art baselines.
Human Rights in a World of Surveillance: Managing Privacy and Security Concerns

The issue of how security needs and individual privacy combine has been under heavy scrutiny in recent times as the fast-moving age of technology marches on. This abstract considers how the development and occupation of space by different technologies penetrate the use of their place as a right or concept to guarantee infringing onto someone's human rights. It has been such that surveillance serves for the purpose of security in governments and corporations, bringing the dilemma to the forefront in the areas of privacy violations, data breaches, and abuse of power. This abstract elaborates almost exclusively on the areas of modification of law and ethics with regard to surveillance, indicating contentious issues and cross-cultural perspectives on that context. Among others, the fundamental human rights affected by these developments include freedom of expression, privacy, and assembly. This abstract seeks to clarify the evolving dynamic that characterizes the contemporary discussion developed so far through the following channels-historical case studies, emerging technologies, or global initiatives to offer a good balance between security and privacy. In the end, this abstract seeks a clear and broad-based dialogue that will stand the test of time concerning shaping responsible surveillance policies that will be at once respectful of individual rights and uphold the principles of a free and democratic society.
BIRDNet: Mining and Encoding Boolean Implication Knowledge Graphs as Interpretable Deep Neural Networks

5 pages; 1 figure, 4 tables
Development of an engineered extracellular vesicles-based vaccine platform for combined delivery of mRNA and protein to induce functional immunity

Abstract                                    mRNA incorporated in lipid nanoparticles (LNPs) became a new class of vaccine modality for induction of immunity against COVID-19 and ushered in a new era in vaccine development. Here, we report a novel, easy-to-execute, and cost effective engineered extracellular vesicles (EVs)-based combined mRNA and protein vaccine platform (EV                   X-M+P                   vaccine) and explore its utility in proof-of-concept immunity studies in the settings of cancer and infectious disease. As a first example, we engineered EVs to contain ovalbumin mRNA and protein (EV                   OvaM+P                   ) to serve as cancer vaccine against ovalbumin-expressing melanoma tumors. EV                   OvaM+P                   administration to mice with established melanoma tumors resulted in tumor regression associated with effective humoral and adaptive immune responses. As a second example, we generated engineered EVs, natural nanoparticle carriers shed by all cells, that contain mRNA and protein Spike (S) protein to serve as a combined mRNA and protein vaccine (EV                   SpikeM+P                   vaccine) against SARS-CoV-2 infection. EV                   SpikeM+P                   vaccine administration in mice and baboons elicited robust production of neutralizing IgG antibodies against RBD (receptor binding domain) of S protein and S protein specific T cell responses. Our proof-of-concept study describes a new platform with an ability for rapid development of combination mRNA and protein vaccines employing EVs for deployment against cancer and other diseases.
Double Robust Semi-Supervised Inference for the Mean: Selection Bias under MAR Labeling with Decaying Overlap

Semi-supervised (SS) inference has received much attention in recent years. Apart from a moderate-sized labeled data, L, the SS setting is characterized by an additional, much larger sized, unlabeled data, U. The setting of |U| >> |L|, makes SS inference unique and different from the standard missing data problems, owing to natural violation of the so-called positivity or overlap assumption. However, most of the SS literature implicitly assumes L and U to be equally distributed, i.e., no selection bias in the labeling. Inferential challenges in missing at random (MAR) type labeling allowing for selection bias, are inevitably exacerbated by the decaying nature of the propensity score (PS). We address this gap for a prototype problem, the estimation of the response's mean. We propose a double robust SS (DRSS) mean estimator and give a complete characterization of its asymptotic properties. The proposed estimator is consistent as long as either the outcome or the PS model is correctly specified. When both models are correctly specified, we provide inference results with a non-standard consistency rate that depends on the smaller size |L|. The results are also extended to causal inference with imbalanced treatment groups. Further, we provide several novel choices of models and estimators of the decaying PS, including a novel offset logistic model and a stratified labeling model. We present their properties under both high and low dimensional settings. These may be of independent interest. Lastly, we present extensive simulations and also a real data application.
Challenges and issues in collaborative software developments

The software development process has evolved with respect to the problems in developing large and complex applications. There is a paradigm shift towards collaborative development, which necessitates the need to evaluate this approach. A number of tools are used for collaborative software development (CSD) including social media and web 2.0 features. Collaborative development facilities are provided by IDEs and project hosting websites. In this paper, we present a survey of collaboratively developed projects and discuss challenges and issues in CSD. We analyze various issues of communication, coordination, support, lifecycle management and discuss their effect on software quality.
Dynamics and key directions of sustainable development of regional agriculture in the context of ensuring national and food security of the Russian Federation

The article identifies the problems and features of agricultural production in Russia’s regions. The main arguments proving the relevance of target qualitative indicators in the methodology of regional management of the agricultural sector (improved efficiency of agricultural sector and increased output of agricultural and food products to the level that ensures regional food security) were chosen according to the initial and projected situation in food supply. This allowed the authors to apply statistical forecasting methods and make a matrix of key directions in the development of agricultural production according to the national security requirements, to identify significant differences between Russia’s regions and to present an optimal ratio of productivity and profitability, production and consumption of agricultural products for each territory. Thus, the article provides general theoretical ideas adapted to the current trends of social-economic and scientific-technical development to assess the role of agriculture and agro-industrial complex in Russian regions with different climatic conditions, and the authors formulate scientifically sound recommendations on the scope and directions for expanding agricultural specialization even in regions with unfavorable climatic conditions
The European Union’s General Data Protection Regulation (GDPR) and its Implications for South African Data Privacy Law: An Evaluation of Selected ‘Content Principles’

After a lengthy legislative process, South Africa implemented the Protection of Personal Information Act 4 of 2013 (POPI Act) on 1 July 2020. The POPI Act is an omnibus data-protection Act that conforms to the former benchmark for data-protection laws worldwide, namely, the 1995 EU Data Protection Directive. At the time of drafting the proposed Bill that would later become the Act, the South African Law Reform Commission emphasised the importance of a South African data-protection Act that complies with international standards on data protection, especially with the EU’s Directive. The Directive, in Article 25, imposed a prohibition on the transfer of personal data to non-member countries that do not ensure an adequate level of protection when personal data of their citizens are processed. South Africa’s Act needed to comply with the standard set in the Directive for the protection of personal information if South Africa wanted to remain part of the international information technology market. In 2016, the EU adopted the General Data Protection Regulation (GDPR) that replaced the 1995 Directive with effect from May 2018. The question now arises whether the South African Act still meets the minimum standards for data protection set out by this Regulation and whether amendments to the Act are needed. This article compares certain provisions of the GDPR with similar provisions of the POPI Act in order to establish whether the South African Act meets the standard set in the GDPR.