ethicalabs/Research-Intent-Collab huggingface dataset:
Self-Supervised Human Activity Recognition With Localized Time-Frequency Contrastive Representation Learning

In this paper, we propose a self-supervised learning solution for human activity recognition with smartphone accelerometer data. We aim to develop a model that learns strong representations from accelerometer signals, in order to perform robust human activity classification, while reducing the model's reliance on class labels. Specifically, we intend to enable cross-dataset transfer learning such that our network pre-trained on a particular dataset can perform effective activity classification on other datasets (successive to a small amount of fine-tuning). To tackle this problem, we design our solution with the intention of learning as much information from the accelerometer signals as possible. As a result, we design two separate pipelines, one that learns the data in time-frequency domain, and the other in time-domain alone. In order to address the issues mentioned above in regards to cross-dataset transfer learning, we use self-supervised contrastive learning to train each of these streams. Next, each stream is fine-tuned for final classification, and eventually the two are fused to provide the final results. We evaluate the performance of the proposed solution on three datasets, namely MotionSense, HAPT, and HHAR, and demonstrate that our solution outperforms prior works in this field. We further evaluate the performance of the method in learning generalized features, by using MobiAct dataset for pre-training and the remaining three datasets for the downstream classification task, and show that the proposed solution achieves better performance in comparison with other self-supervised methods in cross-dataset transfer learning.
Using Technology Acceptance Model (TAM Model) to Increase Effectiveness the Use of Human Resource Information System (HRIS)

Studies related to HRIS Applications show that the Technology Acceptance Model can be used to increase the use of HRIS Applications in a company. This research aims to test and reveal empirical factors that influence using the HRIS-Pakoku Application in the Pako Group. The two direct factors are perceived ease of use and perceived usefulness, and the indirect factor is a behavioural intention to use. This research was conducted at Pako Group using a questionnaire survey method, and samples were taken using the proposed stratified random sampling technique of 138 employees using HRIS at Pako Group. SEM analysis is used to determine the influence between research variables. The research results show a positive and significant influence of perceived ease of use on actual system use, a positive and significant influence of perceived usefulness on actual system use, and a positive and significant influence of behavioural intention to use on actual system use. There is a positive and insignificant influence of perceived ease of use on actual use through intention to use behaviour, and there is a positive and insignificant influence of perceived usefulness on actual system use through intention to use behaviour.
Qualitative analysis of state/event fault trees for supporting the certification process of software-intensive systems

For the certification of modern safety critical systems tree based failure models, like standardized fault trees (FTs), are frequently used methodologies. But when it comes to software-intensive systems these techniques have some crucial disadvantages, especially in modeling timing behavior. To deal with these weak points state/event fault trees (SEFTs) [6] were developed. However, these kind of fault trees can only be analyzed in a quantitative way. In this paper we propose an approach to analyze them qualitatively as well. This results in ordered event sequences which represent different ways for triggering a critical event of the underlying SEFTs, which can be seen as a time-dependent equivalent of the minimal cut set (MCS) analysis of standardized FTs. To evaluate our approach, we implemented the SEFTAnalyzer to apply it on a software-controlled fire alert system.
A Systems Approach to Evaluating Ionizing Radiation: Six Focus Areas to Improve Quality, Efficiency, and Patient Safety

Ionizing radiation is an essential component of the care process. However, providers and patients may not be fully aware of the risks involved, the level of ionizing radiation delivered with various procedures, or the potential for harm through incidental overexposure or cumulative dose. Recent high-profile incidents demonstrating the devastating short-term consequences of radiation overexposure have drawn attention to these risks, but applicable solutions are lacking. Although various recommendations and guidelines have been proposed, organizational variability challenges providers to identify their own practical solutions. To identify potential failure modes and develop solutions to preserve patient safety within a large, national healthcare system, we assembled a multidisciplinary team to conduct a comprehensive analysis of practices surrounding the delivery of ionizing radiation. Workgroups were developed to analyze existing culture, processes, and technology to identify deficiencies and propose solutions. Six focus areas were identified: competency and certification; equipment; monitoring and auditing; education; clinical pathways; and communication and marketing. This manuscript summarizes this comprehensive, multidisciplinary, and systemic analysis of risk and provides examples to illustrate how these focus areas can be used to improve the use of ionizing radiation. The proposed solutions, once fully implemented, may advance patient safety and care.
Application of Sustainable Agricultural Technology to Increase Productivity and Food Security

Food security is an important global issue to overcome. The increasing world population and climate change bring new challenges to ensuring the availability of sufficient and nutritious Food. Sustainable agriculture offers solutions to increase productivity and Food security while preserving the environment. This research aims to evaluate the effectiveness and impact of implementing sustainable agricultural technology in increasing agricultural productivity and food security in an area or community. This study used qualitative research methods. The data collection technique in this research is a literature study. The data that has been collected is then analyzed in three stages, namely data reduction, data presentation, and conclusion. The research results show that sustainable agricultural technology can increase productivity and Food security. Farmers who apply sustainable agricultural technology generally produce higher yields and are more resistant to pests and disease. However, its implementation still needs challenges, such as limited access to technology and knowledge, high costs, and lack of policy support.
Long‐Term Cosmic‐Ray Modulation in the Heliosphere

A time-dependent model based on a numerical solution of Parker's transport equation is used to model the modulation of cosmic-ray protons, electrons, and helium for full 11 year and 22 year modulation cycles using a compound approach. This approach incorporates the concept of propagating diffusion barriers, increases in the heliospheric magnetic field as they propagate from the Sun throughout the heliosphere, time-dependent gradient, curvature, and current-sheet drifts, and other basic modulation mechanisms. The model results are compared with those of the observed 11 year and 22 year cycles for 1.2 GV electrons and 1.2 GV helium at Earth for the period of 1975-1998. The model solutions are also compared with the observed charge-sign-dependent modulation along the Ulysses trajectory for the period of 1990-1998. This compound approach to long-term modulation, especially charge-sign-dependent modulation, is found to be remarkably successful. It is shown that the model can account for the latitude dependence of cosmic-ray protons and electrons by assuming a large perpendicular diffusion in the polar direction. This approach contributes to an improved understanding of how diffusion and drifts vary from solar minimum to maximum modulation and what the time dependence of the heliospheric diffusion coefficients may be. It is found that less than 10% of the available drifts are needed at solar maximum, when the solar magnetic field reverses, to explain, e.g., the observed electron-to-proton ratio along the Ulysses trajectory.
Performance of Natural Language Processing for Information Extraction From Electronic Health Records Within Cancer:Systematic Review

Background: Over the last decade, natural language processing (NLP) has provided various solutions for information extraction (IE) from textual clinical data. In recent years, the use of NLP in cancer research has gained considerable attention, with numerous studies exploring the effectiveness of various NLP techniques for identifying and extracting cancer-related entities from clinical text data. Objective: We aimed to summarize the performance differences between various NLP models for IE within the context of cancer to provide an overview of the relative performance of existing models. Methods: This systematic literature review was conducted using 3 databases (PubMed, Scopus, and Web of Science) to search for articles extracting cancer-related entities from clinical texts. In total, 33 articles were eligible for inclusion. We extracted NLP models and their performance by F 1-scores. Each model was categorized into the following categories: rule-based, traditional machine learning, conditional random field-based, neural network, and bidirectional transformer (BT). The average of the performance difference for each combination of categorizations was calculated across all articles. Results: The articles covered various scenarios, with the best performance for each article ranging from 0.355 to 0.985 in F 1-score. Examining the overall relative performances, the BT category outperformed every other category (average F 1-score between 0.2335 and 0.0439). The percentage of articles on implementing BTs has increased over the years. Conclusions: NLP has demonstrated the ability to identify and extract cancer-related entities from unstructured textual data. Generally, more advanced models outperform less advanced ones. The BT category performed the best.
Air Shower Signal Shape Analysis: A New Method to Separate Ultra-High-Energy Photons from Cosmic Rays

Contains fulltext : 216228.pdf (Publisher’s version ) (Open Access)
Toxicology and risk assessment in the analysis and management of environmental risk

Abstract                Risk-based decision making increasingly has global dimensions, extending from the international management of chemical risks to the sustainable development of our planet. Environmental risk assessment is firmly based on toxicological sciences with input from other public health disciplines. Increasing understanding of how the human genotype and phenotype affects absorption, distribution, metabolism, and excretion of external agents, including foods, is providing insight into answers to the oldest human question about disease: ‘Why me?’ The risk paradigm components of hazard assessment, dose–response analysis, exposure assessment, and risk characterization, and the toxicological concepts on which they are based, have proven durable in approaching increasingly complex environmental hazards. Newer approaches to managing risk, such as the precautionary principle, and newer challenges ranging from nanotechnology to the health impacts of global climate change, are necessitating more systematic thinking on how best to protect human health and the environment.
Independent root-cause analysis of contributing factors, including dismantling of 2 duodenoscopes, to investigate an outbreak of multidrug-resistant Klebsiella pneumoniae

Worldwide, an increasing number of duodenoscope-associated outbreaks are reported. The high prevalence rate of contaminated duodenoscopes puts patients undergoing ERCP at risk of exogenous transmission of microorganisms. The contributing factors of the duodenoscope design to contamination are not well understood. This article reports on the investigation after the outbreak of a multidrug-resistant Klebsiella pneumoniae (MRKP) related to 2 Olympus TJF-Q180V duodenoscopes.We conducted a contact patient screening and microbiologic laboratory database search. Reprocessing procedures were audited, and both duodenoscopes were fully dismantled to evaluate all potential contamination factors. Outcomes were reviewed by an experienced independent expert.In total, 102 patients who had undergone an ERCP procedure from January to August 2015 were invited for screening. Cultures were available of 81 patients, yielding 27 MRKP-infected or -colonized patients. Ten patients developed an MRKP-related active infection. The 2 duodenoscopes had attack rates (the number of infected or colonized cases/number of exposed persons) of 35% (17/49) and 29% (7/24), respectively. Identical MRKP isolates were cultured from channel flushes of both duodenoscopes. The review revealed 4 major abnormalities: miscommunication about reprocessing, undetected damaged parts, inadequate repair of duodenoscope damage, and duodenoscope design abnormalities, including the forceps elevator, elevator lever, and instrumentation port sealing.Outbreaks are associated with a combination of factors, including duodenoscope design issues, repair issues, improper cleaning, and systemic monitoring of contamination. To eliminate future duodenoscope-associated infections, a multipronged approach is required, including clear communication by all parties involved, a reliable servicing market, stringent surveillance measures, and eventually new duodenoscope designs and reprocessing procedures with a larger margin of safety.
Ultra-fast GST-based optical neuron for the implementation of integrated photonic neural networks

A fast-integrated optical neuron is proposed based on a micro-ring resonator structure. The GST phase change material is used in the MRR structure, and neuron switching is achieved by the electrical actuation of this material. The nonlinear activation function of the neuron is extracted through three-dimensional electrical and optical simulations. The neuron is then employed in a three-layer perceptron network using the extracted activation function, and its performance is examined in the classification of handwritten digits. The overall performance of the proposed neuron is compared with the previous optical neural networks. Simulations show an ultra-fast switching time of 200fs, which is one order of magnitude faster than the best-reported value, and an accuracy of 98.9% (in the classification of MNIST handwritten digits dataset) which is among the best results, while the estimated neuron footprint is relatively small.
Transparency, Accountability, and Judicial Independence in Brazil’s Fight against Corruption: Lessons for Latin America from the Car Wash Operation

This article examines transparency, accountability, and judicial independence in combating corruption in Latin America, focusing on Brazil’s Integrity System and the transnational Car Wash Operation. Recognizing the limitations of external anti-corruption frameworks and perception-based indices, my research here adopts a Latin American perspective to analyze the region’s unique institutional challenges. Analysis reveals a critical paradox: while Brazil’s institutional framework successfully investigated high-level corruption across multiple Latin American countries, serious procedural violations by key judicial actors threatened that investigation’s legitimacy. Media coverage and leaked documents shaped public opinion, demonstrating transparency’s dual role as both essential and potentially disruptive. The Supreme Court’s intervention annulling tainted proceedings proved that the system’s institutional checks and balances were strong enough to self-correct. I conclude that robust judicial independence, particularly through specialized electoral courts, combined with a free press and an engaged citizenry, is essential for democratic resilience. As anti-system leaders globally test democratic integrity systems, this article offers timely insights for Latin American countries navigating the complex balance between transparency and due process in anti-corruption efforts.
GDPR and New Media Regulation: The Data Metaphor and the EU Privacy Protection Strategy

Data is a key concept in EU privacy policies. Imposing one interpretation of the definition of data (or information) over another can threaten the protection of privacy. This chapter seeks to answer the following question: How do several interpretations of the data metaphor compete to redefine data in privacy policies? The theory of the metaphor suggests that several interpretations coexist in the definition of data, which is embedded in a context (i.e., privacy policies). These interpretations stem from different semantic fields, i.e., technological, economic, and human rights. CDS permits to analyze the metaphor of data in light of these different interpretations. The material analyzed encompasses the privacy policies of the GAFAM, the laws of the EU regulatory framework for privacy that concern telecommunications and data directly, and 14 interviews of lobbyists and EU policymakers. Findings suggest that there are prominent technological and economic interpretations in the redefinition of the metaphor of data in privacy policies, while the human rights interpretation does not have much space left.
Effect of Safety Culture, Safety Leadership, and Safety Climate on Employee Commitments and Employee Performance PT. Pelindo III (Persero) East Java Province

&lt;p&gt;This study aims to analyze the effects of safety culture, safety leadership and the safety climate on organizational commitment and employee performance. Using the survey method, responses from 218 respondents were collected to understand the complete picture of a port service industry in Indonesia. Data were analyzed with Structural Equation Model (SEM) and it reveals that each safety culture variable, safety climate safety leadership, and employee commitment has a positive and significant impact on employee performance. Organizational commitment variables may enhance the effects of safety culture, safety leadership and a safety climate on employee performance.&lt;/p&gt;
PPP (Public-Private Partnership)-Based Cyber Resilience Enhancement Efforts for National Critical Infrastructures Protection in Japan

Emerging vulnerability of the national critical infrastructures (CIs) against to the cyber risk including cyberattacks and unintentional large-scale information system or network failures have increased frequency and the scale of socioeconomic impacts to our society. As dependencies among critical infrastructures have increased rapidly, the impact of a single cyber incident at a certain critical infrastructure tends to spread very quickly and widely to external systems and networks in other critical infrastructures or areas through widely connected networks. Considering the situation, PPP (Public-Private Partnership) efforts between critical infrastructure service providers and responsible governmental agencies have become very important to protect critical infrastructures from cyber risks. Based on this recognition, PPP-based cybersecurity exercises for critical infrastructure protection (CIP) have been executed for the last decade in Japan. This paper summarizes the over 10 years joint efforts of the Japanese government and critical infrastructure service providers and discusses the lessons learned and challenges to be shared with other countries to collaborate in the cybersecurity field.
Workplace genetic testing: which employees are likely to participate, what are their concerns with employer sponsorship, and which design features could reduce barriers and increase participation?

Voluntary genetic testing (GT) leverages low-cost DNA sequencing and other testing methods to provide genetic risk screening for healthy individuals. Given the potential to prevent disease and promote health, some employers now offer GT as an employee benefit (workplace GT, or wGT), but participation remains low. To investigate facilitators and barriers to wGT participation, we conducted one of the first representative surveys of working U.S. adults on this topic (n = 958). We assessed factors that could influence participation, including: sponsoring entity (health provider or employer), program design, and individual demographics. Two-thirds (68%) of respondents indicated willingness to participate in some type of GT, but only half (49%) expressed willingness to participate through their employer. Women were 60% more willing to participate than men, and individuals with previous genetic testing experience were 143% more willing to participate than those without such experience. Across all demographic groups, certain GT program design features tended to increase or decrease willingness to participate. The ability to have one’s data deleted from the GT database increased willingness most often (true for 67% of respondents), while selling data to pharmaceutical companies decreased willingness most often (true for 63% of respondents).
THE IMPORTANCE OF URBAN AND PERI-URBAN AGRICULTURE IN SUSTAINABLE DEVELOPMENT AND INCREASING FOOD SECURITY

The concepts of urban and peri-urban agriculture, although they are not new, are current as a result of the fact that one of the problems that arose during the Covid-19 crisis was that of food security as a result of the need to ensure food resources from nearby sources , in the conditions in which transport and other sectors of activity have reduced or suspended their activity. In this paper, we propose that, starting from the study of the specialized literature regarding urban and peri-urban agriculture, to identify their development possibilities, to identify the forms of practice of urban and peri-urban agriculture, to present the strengths and weaknesses weak related to their development and to propose solutions for their integration in the development of cities on a sustainable basis. The research methodology assumed the study of specialized literature, the consultation of internal and international databases, the processing and analysis of data with the aim of formulating conclusions that can be the basis of future studies, but also formulating conclusions that can be integrated into future policies regarding the development of urban and peri-urban agriculture, taking into account the fact that at the moment there is still no exact formulation regarding their support.
ARTISTIC FREEDOM AND LEGAL BOUNDARIES: NAVIGATING CENSORSHIP AND EXPRESSION IN INDONESIA’S DEMOCRATIC FRAMEWORK

Art has increasingly become a target for political agendas, often subjected to legal restrictions that limit freedom of expression. This phenomenon is evident in countries like Myanmar, where several laws have been enacted to criminalize speech, surpassing international legal standards. In Indonesia, the rise of authoritarian tendencies has been linked to the weakening of artistic freedom, as reflected in the rising number of cases of artistic repression. This study explores the legal and practical realities of artistic freedom in Indonesia, addressing how the legal system handles attacks on artistic expression and the involvement of state and non-state institutions in strengthening legal protection for artists. It discusses the theoretical framework of artistic freedom, its protection under international human rights law, and Indonesia’s legal context, particularly through laws like the 1945 Constitution and various international agreements such as the ICCPR. The research highlights the challenges of balancing artistic freedom with public morality, security, and order, and critiques the misuse of legal restrictions that often result in excessive censorship. By examining historical and contemporary legal cases, the study proposes an ideal legal framework to ensure robust protection for artistic expression in a democratic society, advocating for a balanced approach between law enforcement and fundamental human rights.