ethicalabs/Research-Intent-Collab huggingface dataset:
Evaluating quality of life measurement in psoriasis and the development of new solutions to improve the use of patient-reported outcomes

Psoriasis has considerable impact on the quality of life (QoL) not only of patients but also of their relatives. This impact is as important to consider as clinical parameters in the management of psoriasis. This thesis aims to evaluate current practices in QoL measurement and devise new solutions to improve these processes, to benefit patients, clinicians and policy makers. The systematic review describing data from 100 psoriasis randomised controlled trials (33 topical, 18 systemic small molecules, 39 biologics and 19 other interventions) in 33,215 subjects highlights that QoL assessment is integral to the assessment of new therapies and to the management of psoriasis.\ud Amongst a variety of generic and disease-specific measures, the Dermatology Life Quality Index (DLQI) is the most commonly utilised QoL tool, though there is heterogeneity in its reporting and analysis. The Minimal Important Clinical Difference (MCID) is an essential baseline in determining\ud treatment efficacy, particularly across measures, but remains grossly under-utilised. This thesis proposes a novel concept of ‘multiple-MCID’, as well as recommendations on QoL reporting.\ud In order to address some of these identified recommendations, an electronic version of the DLQI has\ud been validated for the first time using International Society for Pharmacoeconomics and Outcomes Research (ISPOR) guidelines (n=104). The electronic version was scored equivalently to the paper counterpart, was preferred by majority of patients (76%) and provided advantages such as costefficiency, quicker completion times and more accurate data analysis. The electronic Psoriasis Area Severity Index (PASI) was also validated demonstrating reduced inter-rater variability. Electronic use of these measures would help standardise QoL measurement and propel psoriasis management into the digital era.\ud Whilst QoL information is invaluable for clinical decision-making, generic measures are utilised by healthcare policy-makers for resource allocation. This is not always representative of the impact revealed by disease-specific QoL measures. In order to solve this dilemma, the DLQI was mapped to EQ-5D to generate utility values using ordinal logistic regression (OLR) from a dataset of 4,010 patients. This sample size was large enough to allow it to be split in half to perform external and internal validity. Where previous methods have failed, the OLR mapping method successfully allowed the conversion of DLQI scores to utility values for large cohorts of patients, using split half validation and Monte Carlo Simulation. This has the potential to be very useful in economic appraisals of any skin disease, including psoriasis.\ud By standardising QoL measurement, validating its electronic data capture and translating this information into meaningful healthy utility information, it is hoped this work further consolidates the central role of QoL assessment in psoriasis.
Efficacy, safety, and cost-effectiveness analysis of aflibercept in metastatic colorectal cancer: A rapid health technology assessment

Background: Metastatic colorectal cancer (mCRC) imposes a heavy tumor burden worldwide due to limited availability of therapeutic drugs. Aflibercept, a kind of recombinant protein of the anti-vascular endothelial growth factor (VEGF) family, has been approved in clinical application among mCRC patients since 2012. A comprehensive analysis of the efficacy, safety, and cost-effectiveness of aflibercept in mCRC treatment is necessary.Objective: To evaluate the efficacy, safety, and cost-effectiveness of aflibercept for the treatment of mCRC in order to provide a decision-making reference for the selection of targeted drugs for second-line treatment of mCRC in Hong Kong, Macao, and Taiwan regions of China and the selection of new drugs for medical institutions in these regions.Methods: A systematic retrieve on databases including PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang, and Weipu, as well as relevant websites and databases of health technology assessment including the National Institute of Health and Clinical Optimization, Centre for Evaluation and Communication at the University of York, and the Canadian Agency for Medicines and Health Technology, was conducted. The literature was screened according to the inclusion and exclusion criteria, and data were extracted and analyzed by two authors, while the quality of the literature was assessed.Results: Finally, we included two HTA reports, 11 systematic reviews/meta-analyses, and two cost-effectiveness studies in the rapid health technology assessment. For mCRC patients receiving second-line treatment, aflibercept combined with FOLFIRI significantly increased progression-free survival (PFS) and overall survival (OS) and the objective response rate (ORR) also improved, compared with folinic acid + fluorouracil + irinotecan (FOLFIRI). In terms of safety, mCRC patients who received aflibercept combined with FOLFIRI therapy had a higher incidence of grade 3–4 adverse events than those who received FOLFIRI alone, including anti-VEGF–related adverse events (hypertension, hemorrhagic events, and proteinuria) and chemotherapy-related adverse events (diarrhea, weakness, stomatitis, hand-foot syndrome, neutropenia, and thrombocytopenia). In terms of cost-effectiveness, two economic studies conducted in the United Kingdom and Japan, respectively, found that compared with FOLFIRI, aflibercept combined with FOLFIRI had no cost-effectiveness advantage in mCRC patients receiving second-line treatment.Conclusion: Compared with FOLFIRI treatment, aflibercept combined with FOLFIRI for the second-line treatment of mCRC patients has better efficacy, worse safety, and is not cost-effective. More high-quality clinical studies are required for further exploration of aflibercept’s clinical value. Medical institutions in Hong Kong, Macao, and Taiwan regions of China should be cautious when using or introducing aflibercept plus FOLFIRI as a mCRC treatment.
AI-driven music composition: Melody generation using Recurrent Neural Networks and Variational Autoencoders

Automatic melody generation has recently gained significant attention in music creation and artificial intelligence. However, existing models often lack accuracy in emotional expression, coherence, and diversity. To address these issues, we propose a melody generation model based on Recurrent Neural Networks (RNN) and Variational Autoencoders (VAE), integrating emotional consistency loss and generative adversarial loss. This approach enhances melody diversity via VAE and captures long- and short-term dependencies using RNNs for better structural coherence. Emotional consistency loss helps maintain target emotions during generation, while generative adversarial loss improves naturalness and fluency. Experimental results show that our model outperforms traditional models like Music Transformer, MuseNet, and DeepBach in fluency, creativity, emotional expression, and harmony. The generated melodies are more expressive and innovative, providing a new method and perspective in melody generation, improving emotional expression and diversity, and laying a foundation for advancing automatic music creation technology.
OCCUPATIONAL SAFETY AND HEALTH AND ITS RELATIONSHIP WITH WORKPLACE ACCIDENTS IN INFORMAL MINING – HUANCAVELICA – 2020-2021

This paper provides an approach related to the criteria for the development and implementation of a Health and Safety Plan for informal mining, based on the needs of workers in this sector. A proposal was developed for the ongoing implementation of preventive measures and new technologies to achieve maintenance and continuous improvement of expected future standards.  Workers or collaborators are considered the most important element within the various informal mining companies. They are always the main cause of accidents caused by human error, as well as those caused by the use of facilities and the handling of deficient or poorly maintained equipment and tools. These are the most important causes of the increased incident rates among personnel in the performance of their activities.  Considering the importance of safety in any field, this study focused on the relationship between the implementation of an Occupational Health and Safety Management System (OHSMS) and the minimization of occupational accidents in informal mining. The results of this proposal were adapted to improve safety in informal mining, given that any work activity represents a risk that can lead to incidents and accidents with undesirable consequences.  Furthermore, the study aims to strengthen awareness of prevention and compliance with national occupational health and safety regulations and standards in the country, which aim to optimize working conditions and establish a safety culture that enables appropriate and appropriate development for workers.
Adding Alignment Control to Language Models

Post-training alignment has increasingly become a crucial factor in enhancing the usability of language models (LMs). However, the strength of alignment varies depending on individual preferences. This paper proposes a method to incorporate alignment control into a single model, referred to as CLM. This approach adds one identity layer preceding the initial layers and performs preference learning only on this layer to map unaligned input token embeddings into the aligned space. Experimental results demonstrate that this efficient fine-tuning method performs comparable to full fine-tuning. During inference, the input embeddings are processed through the aligned and unaligned layers, which are then merged through the interpolation coefficient. By controlling this parameter, the alignment exhibits a clear interpolation and extrapolation phenomenon.
Historical Evolution of Laws on Armed Conflicts: A Jurisprudential Perspective from Geneva Conventions

Codification of laws of war is one the significant achievements of international law from the nineteenth century. The wars after then were fought with a different nature and scale. The realization of the need to limit the destructive force of war changed the momentum to codify the international war laws. The codification of international war laws in their primary condition thus emphasized the need of making distinction between 'armed forces and civilians'. The most remarkable aspect to be noted is that it linked the development of law of armed conflict with the international protection of human rights. It was the Charter of the United Nations which clearly condemned war and defined the war of aggression as a crime against international peace and humanity. But since this attempt was not so promising enough International Committee of Red Cross initiated to revise the Geneva Conventions and an additional Convention relative to the protection of civilian persons in the time of war was adopted. This article elucidates the four Geneva Conventions with their additional protocols including norms for control and restraints of war, which as such are considered helpful to protect and promote peace, and respect human rights of combatants and civilians. The basic highlights of this article is the historical events that led to the codification and development of international conventions relating to war with special focus on evolution of modern laws of armed conflict. Further it also focus on the important achievements of humanitarian laws.
Analysis of Factors contributing to Warehousing Risk Management and operations: A quantitative Assessment

This study presents a comprehensive analysis of factors influencing warehousing risk management. Critical components such as warehousing management, staff quality, safety practices, inventory, theft, and government policies pose a serious risk to warehouse management which likely affect the operational supply chain of warehouse effectiveness. The research employed a quantitative approach using a structured questionnaire distributed among the warehouse personnel, and data collated from 71 responses were tested for reliability and level of significance using Cronbach’s Alpha and analysis of variance (ANOVA). Horizontal bar graphs categorizing various risk components labeled A to E. The graph illustrates the percentage of agreement from respondents regarding the validity of each, highlighting  A3:83% of warehouse management and E1:83% of warehouse theft as the most critical contributors to warehousing management risk, while A10:49.3% of warehouse management demonstrates lower consensus. The findings underscore the importance of comprehensive risk management for improving warehouse efficiency, balancing supply and demand, and enhancing competitiveness in dynamic industrial environments.
Additional file 5 of Photovoltaics in agricultural landscapes: “Industrial land use” or a “real compromise” between renewable energy and biodiversity? Perspectives of German nature conservation associations

Additional file 5: Profile matrix of the analytical units included in the nested case study.
sj-pdf-1-wjn-10.1177_01939459221114079 – Supplemental material for Nurse Managers’ Leadership, Patient Safety, and Quality of Care: A Systematic Review

Supplemental material, sj-pdf-1-wjn-10.1177_01939459221114079 for Nurse Managers’ Leadership, Patient Safety, and Quality of Care: A Systematic Review by Seung Eun Lee, Lee Hyunjie and Somin Sang in Western Journal of Nursing Research
Improved predictions on Higgs-Starobinsky inflation and reheating with ACT DR6 and primordial gravitational waves

We investigate the implications of recent CMB observations for Higgs-Starobinsky inflationary models and their associated reheating dynamics, utilizing data from ACT DR6, Planck 2018, BICEP/Keck 2018, and DESI, collectively referred to as P-ACT-LB-BK18. In addition to direct CMB constraints, we incorporate indirect bounds arising from the potential overproduction of primordial gravitational waves (PGWs), particularly through limits on the effective number of relativistic species, $ΔN_{\rm eff}$, during Big Bang Nucleosynthesis (BBN). These constraints become especially relevant in scenarios featuring a stiff post-inflationary equation of state $w_{\rm RH}\geq 0.58$. Our analysis shows that, when both P-ACT-LB-BK18 data and $ΔN_{\rm eff}$ bounds are considered, the viable number of inflationary e-folds is restricted to the range ($57.9$-$62.2$) at the $2σ$ confidence level (C.L.). Correspondingly, the reheating temperature is constrained to lie between the BBN energy scale and $10^{12}$ GeV, with the post-inflationary equation-of-state parameter satisfying $w_{\rm RH} &gt; 0.41$. However, no parameter space remains viable at the $1σ$ C.L. once $ΔN_{\rm eff}$ constraints from PGWs are included, rendering the Higgs-Starobinsky model highly restricted.
Media (social accountability) and corruption (transparency) in brazilian municipalities

In Brazil, corruption has permeated the public administration. Transparency is a successful governance requirement for fighting corruption. Media freedom is a transparency strategy. In this context, this article seeks to verify the relationship between media (social accountability) and corruption (transparency) in Brazilian municipalities. To this end, it employs a multiple linear regression model, with the proxy for corruption being the evaluation of the transparency of public management carried out by the Federal Public Ministry, the presence of newspapers and radio-am as variables of interest (media) and as variables of control demographic and socioeconomic factors used in the corruption literature, such as: population concentration, Firjan Municipal Development Index for: Employment and Income, education and health; GDP per capita and share of current government expenditure in the municipality's GDP. The year of analysis is 2016. The positive relationship between media and transparency in public management shows that a free press is a fundamental pillar of a democratic society and essential for sustained efforts to fight corruption.
Traffic Surveillance and Human Rights: How Can States Overcome the Negative Impact of Surveillance Technologies on the Individual Right to Respect for Privacy and Personal Data Protection?

The crucial role of surveillance technologies for the enforcement of traffic laws and prevention of traffic accidents, as well as for the development of modern traffic management systems and regulation of traffic jams, is acknowledged widely but so far little attention has been given to human rights concerns arising from traffic surveillance. However, traffic surveillance greatly affects several individual human rights, more specifically the individual right to private life and personal data protection. In the case of traffic surveillance, interference by a public authority can be reasonably justified with the legitimate purpose of detecting traffic law violations, an action necessary ‘in a democratic society’ and for ‘the prevention of disorder or crime’. In this regard, human rights concerns may arise not from the very fact of video monitoring, but the recording and processing of data which may create an unlawful interference with individual human rights. In the process of traffic surveillance and further proceedings in response to traffic law violations, general principles of personal data protection may be significantly affected, specifically the requirements of personal data being ‘obtained and processed fairly and lawfully’, ‘processed for specified and legitimate purposes and not used in a way incompatible with those purposes’; ‘not excessive in relation to the purposes for which they are processed’; ‘preserved in a form which permits identification of the data subjects for no longer than is required for the purpose for which those data are stored’. The case study of traffic law enforcement in the Republic of Armenia (RA) reveals several examples of how protection of individual human rights may be challenged through traffic law enforcement policies and procedures and offers useful lessons for mitigating the negative impact of surveillance technologies on the right to respect for private life and personal data protection.
Epigenetic regulation of BCL6 in aggresive B-cell lymphoma: role of CTCF chromatin regulator and effects of a histone deacetylase inhibitor

[EN]: BCL6 is a transcriptional repressor expressed in B-lymphocytes and which expression pattern is highly regulated. Several mechanisms have been described, but BCL6 is deregulated in some types of lymphomas including Burkitt lymphoma, follicular lymphoma and diffuse large B cell lymphoma. CTCF is a chromatin regulator. Among the multiple functions of CTCF, its role in the epigenetic regulation of genes involved in cancer such us p53, RB, MYC, etc is highlighted. Alterations in epigenetic mechanisms are frequently found in hematological diseases. Epigenetic alterations are potentially reversible using drugs. Among them is romidepsin, a histone deacetylase inhibitor already successfully used for the treatment of some types of T-cell lymphoma. This Thesis work provides new insights in the mechanisms involved in the epigenetic regulation of BCL6 and the role of CTCF and romidepsin.
Citizens, research ethics committee members and researchers’ attitude toward information and consent for the secondary use of health data: Implications for research within learning health systems

A provincial survey was conducted to assess citizens, research ethics committee (REC) members and researchers’ attitude toward information and consent for the secondary use of health data for research within a learning health system (LHS). The results show that: 1) reuse of health data for research to advance knowledge and improve care is values by all parties; 2) consent regarding health data use for research is fundamental particularly to citizens, even when the data are de-identified; 3) a secure website to support the information and consent processes was appreciated by all. Researchers were more comfortable with the use of de-identified health data for research without informing nor seeking consent from people than citizen and REC member respondents. This survey was part of a larger project that aims at exploring public perspectives on alternate approaches to the current consent models in Quebec to take into consideration the unique features of LHS. The revised consent model will need to ensure that citizens are given the opportunity to be better informed about incoming researches with their health data and have their say, when possible, in the use of their data.
Present State and Recent Developments of Artificial Intelligence and Machine Learning in Gastric Cancer Diagnosis and Prognosis:  A Systematic Review

Objective: The objective of this study is to thoroughly investigate the use of artificial intelligence (AI) and machine learning (ML) techniques for diagnosing and predicting prognosis in gastric cancer, utilizing the latest available data. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)guidelines, a systematic review investigated AI and ML applications in gastric cancer diagnosis and prognostic prediction. PubMed and Google Scholar were searched from February 2019 to January 2024 using specific syntax. Eligible trials were selected based on inclusion criteria including recent publication, focus on AI and ML in gastric cancer, and reporting diagnostic or prognostic outcomes. Data were extracted and quality assessed independently, with discrepancies resolved through discussion. Due to design heterogeneity, detailed analysis was omitted, and descriptive summaries of included articles were provided. Results: This review included a total of 8 articles. AI and ML techniques, including  convolutional neural networks (CNN) and deep learning models, have played pivotal roles in accurately diagnosing chronic atrophic gastritis, predicting postoperative gastric cancer prognosis, and identifying peritoneal metastasis in gastric cancer patients. These technologies offer potential advantages such as streamlining diagnostic procedures, guiding treatment decisions,  and enhancing patient outcomes in gastric cancer management. Conclusion: In the near future, AI applications may have a significant role in the diagnosis and prognosis prediction of gastric cancer.
Music Recommendation System using Content and Collaborative Filtering Methods

Rapid development of mobile devices and internet has made possible for us to access different music resources freely. While the Music industry may favor certain forms of music over others, it's important to grasp that there isn’t one human culture on earth that has existed without music. during this paper, we've designed, implemented and analyzed a song recommendation system. we've used Song Dataset provided to search out correlations between users and songs and to find out from the previous listening history of users to supply recommendations for songs which users would like to concentrate most. The dataset contains over ten thousand songs and listeners are recommended the simplest available songs supported the mood, genre, artist and top charts of that year. With an interactive UI we show the listener the highest songs that were played the foremost and top charts of the year. Listener even have the choice to pick out his/her favorite artist and genres on which songs are recommended to them using the dataset. Keywords- Collaborative model, Content based model, Recommendation System, Popularity model