ethicalabs/Research-Intent-Collab huggingface dataset:
A Novel Reconfigurable Architecture of a DSP Processor for Efficient Mapping of DSP Functions using Field Programmable DSP Arrays

Development of modern integrated circuit technologies makes it feasible to develop cheaper, faster and smaller special purpose signal processing function circuits. Digital Signal processing functions are generally implemented either on ASICs with inflexibility, or on FPGAs with bottlenecks of relatively smaller utilization factor or lower speed compared to ASIC. Field Programmable DSP Array (FPDA) is the proposed DSP dedicated device, redolent to FPGA, but with basic fixed common modules (CMs) (like adders, subtractors, multipliers, scaling units, shifters) instead of CLBs. This paper introduces the development of reconfigurable system architecture with a focus on FPDA that integrates different DSP functions like DFT, FFT, DCT, FIR, IIR, and DWT etc. The switching between DSP functions is occurred by reconfiguring the interconnection between CMs. Validation of the proposed architecture has been achieved on Virtex5 FPGA. The architecture provides sufficient amount of flexibility, parallelism and scalability.
Supplementary Table 2 from Sample Size Estimations Based on Human Microbiome Temporal Stability Over 6 Months: A Shallow Shotgun Metagenome Sequencing Analysis

&lt;p&gt;Supplementary Table 2. ICCs based on the untransformed relative abundance of the species which were present in at least 5% of samples with relative abundance of &gt;0&lt;/p&gt;
Application of Discrete-Event Simulation in Health Technology Assessment: A Cost-Effectiveness Analysis of Alzheimer’s Disease Treatment Using Real-World Evidence in Thailand

Decision-analytic models for Alzheimer's disease (AD) have been advanced to a discrete-event simulation (DES), in which individual-level modeling of disease progression across continuous severity spectra become feasible. This study aimed to apply DES to perform cost-effectiveness analysis of AD treatment in Thailand.A data set of Thai AD patients, representing unique demographic and clinical characteristics, was bootstrapped to generate a baseline cohort of 50 000 patients. Each patient was cloned and assigned to donepezil, galantamine, rivastigmine, memantine, or no treatment. Correlated changes in cognitive and behavioral status over time were developed using patient-level data. Treatment effects were obtained from the most recent network meta-analysis. Treatment persistence; mortality; and predictive equations for functional status, costs (Thai baht in 2017), and quality-adjusted life-year (QALY) were derived from country-specific real-world data.From a societal perspective, only the prescription of donepezil to AD patients with all disease-severity levels was found to be cost-effective (incremental cost-effectiveness ratio): 138 524 Thai baht/QALY ($4062/QALY)]. Regardless of whether the treatment-stopping rule when the mini-mental state examination score <10 was introduced, providing early treatment with donepezil to mild AD patients further reduced the incremental cost-effectiveness ratio. Extensive sensitivity analyses indicated robust simulation findings.Discrete-event simulation greatly enhances the real-world representativeness of decision-analytic models for AD. Donepezil is the most cost-effective treatment option for AD in Thailand and is worth being considered for universal financial coverage. Application of DES in heath technology assessment should be encouraged, especially when the validity of the model is questionable with classical modeling methods.
Root cause analysis applied to the investigation of serious untoward incidents in mental health services

The Department of Health publication Building a Safer NHS for Patients sets out the Government's plans for promoting patient safety (Department of Health, 2001). This follows growing international recognition that health services around the world have underestimated the scale of unintended harm or injury experienced by patients as a result of medical error and adverse events occurring in health care settings. These plans include a commitment to replace the procedures set out in the Department of Health circular HSG(94)27. This guidance details the methods for investigating every homicide (and some suicides) by patients in current or recent contact with specialist mental health services. Part of the process to modernise HSG(94)27 includes a plan to build expertise within the National Health Service (NHS) in the technique of root cause analysis. This investigative process was developed in industry to identify causal or systems factors in serious adverse events.
Continual Deep Reinforcement Learning to Prevent Catastrophic Forgetting in Jamming Mitigation

Deep Reinforcement Learning (DRL) has been highly effective in learning from and adapting to RF environments and thus detecting and mitigating jamming effects to facilitate reliable wireless communications. However, traditional DRL methods are susceptible to catastrophic forgetting (namely forgetting old tasks when learning new ones), especially in dynamic wireless environments where jammer patterns change over time. This paper considers an anti-jamming system and addresses the challenge of catastrophic forgetting in DRL applied to jammer detection and mitigation. First, we demonstrate the impact of catastrophic forgetting in DRL when applied to jammer detection and mitigation tasks, where the network forgets previously learned jammer patterns while adapting to new ones. This catastrophic interference undermines the effectiveness of the system, particularly in scenarios where the environment is non-stationary. We present a method that enables the network to retain knowledge of old jammer patterns while learning to handle new ones. Our approach substantially reduces catastrophic forgetting, allowing the anti-jamming system to learn new tasks without compromising its ability to perform previously learned tasks effectively. Furthermore, we introduce a systematic methodology for sequentially learning tasks in the anti-jamming framework. By leveraging continual DRL techniques based on PackNet, we achieve superior anti-jamming performance compared to standard DRL methods. Our proposed approach not only addresses catastrophic forgetting but also enhances the adaptability and robustness of the system in dynamic jamming environments. We demonstrate the efficacy of our method in preserving knowledge of past jammer patterns, learning new tasks efficiently, and achieving superior anti-jamming performance compared to traditional DRL approaches.
Blended Learning Model to Promote the Ability to Analytical Thinking and  Learning Outcomes of Computer and Educational Technology Students

The purposes of this research were: 1) to develop a blended learning model to promote analytical thinking ability and learning outcomes of Computer and Educational technology students 2) to compare analytical scores before and after blended teaching of Computers and Educational Technology students and 3) to study the satisfaction of students about the blended learning method. The researcher conducted the instructional design theory of ADDIE MODEL used in this research. The experiment was conducted with the sample group in the study were 3rd year students 30 students in Computer and Educational technology students the academic year 2021 who study in the first semester of academic year 2021. The instruments in this research were 1) Teaching Management Plan 3 plans to 4 hours in total 12 hours 2) Analytical thinking ability test for 3rd year students of Computer and Educational Technology in Faculty of Education at Nakhon Sawan Rajabhat University and 3) The satisfaction questionnaire of students that blended learning model. The statistics used in data analysis were mean, standard deviation and t-test.The findings of this research as following:It has resulted in the development of a teaching style that combines integration with the analytical thinking process in the course of learning management in computational science at the primary and secondary level. There are five steps in the learning process: 1) reviewing 2) thinking 3) sharing 4) constructing and 5) applying and the results of checking the appropriateness of the teaching management plan that integrates with the analytical thinking process found that the experts assessed the quality of the teaching management plan integrated with the analytical thinking process. It was very appropriate (x̄ = 4.70) when students receive integrated teaching and learning management with the analytical thinking process of the course of learning management in computational science at primary and secondary levels. The students’ analytical thinking ability after study was statistically significantly higher than before at the .05 level and were satisfied towards blended learning at a high level.
Drafting the Future: The Dawn of AI Report Generation in                     Radiology

The ability of artificial intelligence systems such as multimodal large language models to generate draft reports from medical images holds transformative potential for radiology; however, robust validation frameworks remain essential for safety.
Detecting denial of sleep attacks by analysis of wireless sensor networks and the Internet of Things

The Internet of Things (IoT) amalgamates a large number of physical objects that are distinctively identified, ubiquitously interconnected and accessible through the Internet. IoT endeavors to renovate any object in the real world into a computing device that has sensing, communicating, computing and control capabilities. There are a budding number of IoT devices and applications and this escort to an increase in the number and complexity of malicious attacks. It is important to defend IoT systems against malicious attacks, especially to prevent attackers from acquiring control over the devices. Energy utilization is significant for battery-enabled devices in the IoT and wireless sensor networks which are operated long time period. The Denial-of-Sleep attack is an explicit type of denial-of-service attack that beleaguered a battery-powered device’s power supply that results in the exhaustion of this critical resource. This paper focuses on the survey on Denial of sleep attacks in Wireless Sensor networks and the IoT.
Receptor- ligand interactions in plant inmate immunity revealed by AlphaFold protein structure prediction

Abstract                                    One of the common mechanisms to trigger plant innate immunity is recognition of pathogen avirulence gene products directly by products of major resistance (                   R                   ) genes in a gene for gene manner. In the USA, the                   R                   genes,                   Pik-s, PiKh/m                   , and                   Pi-ta, Pi-39(t)                   , and                   Ptr                   genes have been effectively deployed to prevent the infections of                   M. oryzae                   races, IB49, and IC17 for some time.                   Pi-9                   is only recently being deployed to provide overlapped and complimentary resistance to                   Magnaporthe oryzae                   races IB49, IC17 and IE1k in the USA. Pi-ta, Pi-39(t), Pi9 are major nuclear binding site-leucine rich (NLR) proteins, and Ptr is an atypical R protein with 4 armadillo repeats. AlphaFold is an artificial intelligence system that predicts a protein 3D structure from its amino acid sequence. Here we report genome sequence analyses of the effectors and avirulence (                   AVR                   ) genes,                   AVR-Pita                   and                   AVR-Pik                   , and                   AVR-Pi9                   , in 3 differential                   M. oryzae                   races. Using AlphaFold 2 and 3 we find strong evidence of direct interactions of products of resistance genes                   Pi-ta                   and                   Pik                   with                   M. oryzae                   avirulence (                   AVR                   ) genes,                   AVR-Pita                   and                   AVR-Pik                   respectively. We also found that AVR-Pita interacts with Pi-39(t) and Ptr, and Pi9 interacts with both AVR-Pi9 and AVR-Pik. Validation of direct interactions of two pairs of R and AVR proteins supported a direct interaction mechanism of plant innate immunity. Detecting interaction of both Ptr and Pi39(t) with AVR-Pita, and Pi-9 with both AVR-Pi9 and AVR-Pik, revealed a new insight into recognition of pathogen signaling molecules by these host R genes in triggering plant innate immunity.
Artificial Intelligence (AI) in Translation and Interpreting: Exploring AI’s Potential in Translation and Interpreting Profession and Pedagogy in the Medical Context and its Ethical Implications

Artificial Intelligence has a central place in modern life due to its vast applicability to several domains of human activity. Within this context, artificial intelligence interacts in a dynamic way with the fields of translation and interpreting. This new state of affairs raises serious questions about the evaluation of the impact that artificial intelligence-inspired technology has on the professional practice of translation and interpreting. This study aims at addressing this concern by exploring the synergy between artificial intelligence and translation and interpreting. To this end, our work focuses on exploring the potentiality of artificial intelligence in professional and educational settings as well as the ethical implications of this synergy. The research design draws upon the mixed methods approach to scientific inquiry and uses an embedded design for data collection, coding, analysis and interpretation. The data are collected, processed, and interpreted both quantitively and qualitatively. The research instrument of the study is a tripartite web-based survey addressing three different categories of respondents, namely professional translators and/or interpreters, educators and students within the translation and interpreting field. Its goal is twofold: (1) to examine the targeted respondents ’attitudes towards embedding artificial intelligence technologies in the translation and interpreting profession and especially in medical/healthcare settings and (2) to gain insight into the perspectives of educators and students in the field of translation and interpreting studies. The findings show that there is a consensus as to the advantages and disadvantages of the interplay between artificial intelligence and the practice of translation and interpreting and the ethical prerequisites that should be in effect to ensure trustworthy artificial intelligence use.
Survival of Right to Privacy under Administrative Surveillance: A Comparative Legal Study

The right to privacy, recognised as a fundamental human right, faces serious challenges in the era of expanding administrative surveillance. Governments across the world increasingly rely on mass surveillance to address concerns of national security, crime prevention, and efficient governance. However, such practices often result in excessive data collection, intrusion into personal autonomy, and the risk of misuse of sensitive information. This paper examines the survival of privacy rights amid growing state surveillance, focusing on the delicate balance between individual freedoms and legitimate state interests. It analyses legal frameworks governing surveillance in democratic societies and evaluates the adequacy of existing privacy safeguards. Landmark judicial decisions, including K.S. Puttaswamy v. Union of India and Carpenter v. United States, are critically examined. The study also explores how technological advancements such as artificial intelligence, biometric systems, and data mining intensify privacy concerns. Emphasising proportionality and necessity, the paper advocates stronger oversight, transparency, and privacy-oriented digital governance to protect privacy rights.
Lingering Issues on Psychological Safety and Organizational Safety Culture Affecting Compliance to  Occupational Health and Safety Promotion in the Workplace: Basis for  Interventional Program Development

This study encompasses the exploration of lingering issues in psychological safety, organizational safety, and their relationship with compliance with occupational health and safety promotion in the workplace. Using a multiphase design guided by the ADDIE model, the research progresses through needs analysis, tool development, survey correlational studies, regression and mediation analysis, program design, and expert validation. The study targets employees from specific high-risk industries such as manufacturing, healthcare, and construction, which are particularly prone to occupational health and safety challenges. By focusing on these sectors, the study aims to provide an in-depth understanding of how lingering safety issues impact compliance and what interventions can effectively address these concerns. The scope includes analyzing trends and challenges through literature reviews and surveys, designing and validating a tailored questionnaire, investigating statistical relationships between variables, developing an intervention using the Outcome-Based Education (OBE) Curricular Framework, and validating the proposed program through expert consensus using the Delphi method. The study is subject to several limitations. First, its findings may have limited generalizability due to the purposive selection of industries and respondents. While focusing on high-risk sectors provides valuable insights, the results may not fully apply to low-risk industries or diverse organizational contexts. Second, although Cochran's formula ensures an appropriate sample size, the reliance on a single round of data collection limits the ability to capture longitudinal changes or evolving safety practices. Third, the context- specific focus of the study may overlook regional, cultural, or regulatory differences in occupational health and safety practices, further constraining the applicability of the findings. Fourth, self-reported data from the questionnaire introduces potential biases, such as social desirability or recall bias, as respondents may underreport non-compliance or safety concerns. Fifth, the Delphi validation process involves a limited number of 15 experts, which, while sufficient for consensus-building, may not reflect the full diversity of perspectives from the field. Lastly, the study primarily emphasizes psychological and organizational safety factors, potentially overlooking external influences such as economic policies, technological advancements, or societal trends that could also impact compliance.
Implementation and Impact of an Antimicrobial Stewardship Post-Prescription Review Program: Challenges Amid Rising Resistance in a Tertiary Hospital

Abstract                                    Background  Antimicrobial resistance (AMR) represents a major global health emergency.  This study evaluated a pilot Antimicrobial Stewardship (AMS) program based on post-prescription review of selected antibiotics at Fondazione IRCCS Policlinico San Matteo in Pavia, Italy. Methods  This quasi-experimental study analysed the first six months (March-August 2024) of an AMS program in Internal Medicine, General Surgery, and Hematology departments. The intervention focused on post-prescription review of carbapenems, new beta-lactam/beta-lactamase inhibitors, and cefiderocol. Multiple outcome measures were assessed, including prescription appropriateness, intervention effects, microbiological patterns, antibiotic consumption, and costs, with comparison to the corresponding period in 2023. Results  We analysed 210 antibiotic prescriptions (64 in Internal Medicine, 40 in General Surgery, 106 in Hematology). Overall appropriateness was 50.0% (95% CI: 43.2–56.8%), with therapy duration being the principal factor of inappropriateness (75.0% of inappropriate cases). Inappropriate therapy was associated with a significantly higher risk of unfavourable outcomes (χ2 = 9.41; p = 0.002) and longer hospital stays (median difference: 2 days; p &lt; 0.001). Antibiotic consumption increased significantly (+ 41.93%), primarily in Hematology (+ 54.17%), with overall costs rising by 56.12%. The prevalence of multidrug-resistant organisms increased substantially, with NDM-producing                   Klebsiella                   spp. showing increases in both colonization (+ 77.58%) and infection (+ 95.10%). There was a significant association between inappropriate prescriptions and subsequent modification (χ²=6.42; p = 0.011), more evident for targeted than for empirical therapies. Conclusions  The pilot AMS program identified significant challenges in optimizing antibiotic use amid increasing resistance rates. Department-specific responses suggest tailored approaches may be more effective than uniform strategies. Enhanced infection control, targeted economic stewardship, and an improved handshake model of intervention are recommended to improve future outcomes.
International treaty and international custom as sources of international law: determination and interrelation

The article is devoted to the issues of the correlation of an international treaty and international custom, their determination and interrelation. Since an international treaty and international custom are the main and most widespread sources of modern international law, the analysis of their correlation is quite relevant.  International treaties and international customs are subject to constant application by subjects of international law (states and international organizations), which requires optimization and search for effective mechanisms for improvement in modern international relations, which makes the study of these main sources of international law relevant.  The analysis is carried out of the UN General Assembly Resolution A/RES/73/203 of December 20, 2018 “Identification of customary international law”, which is important for the theory and practice of international law, especially for the issues of sources of international law.  The results of this study indicate that an international treaty differs from an international custom in its specificity, the peculiarity of the object of legal regulation, the form of consolidation and the significant advantage of treaties in terms of their number in modern international law. An international treaty arises and is formed as a result of negotiations and fruitful work of subjects of international law on rules, mutual rights and obligations on certain issues of cooperation. International treaties have specific names and a clearly established subject of legal regulation.  It is noted that international custom is formed as a result of the practice of activities of subjects of international law in the course of the historical process of international relations. The legal nature of international custom is consensual on the part of subjects of international law, primarily states and international organizations.It is concluded that in the process of transition from the emergence of international custom to the adoption of an international treaty, customs help to fill gaps in international law. The reverse process is also possible, when international treaties become widely applicable and take on the character of international custom, for example, international legal treaties in the field of human rights protection, which subsequently become general practice.