ethicalabs/Research-Intent-Collab huggingface dataset:
Turning the medical gaze in upon itself: Root cause analysis and the investigation of clinical error

In this paper, we discuss how a technique borrowed from defense and manufacturing is being deployed in hospitals across the industrialized world to investigate clinical errors. We open with a discussion of the levers used by policy makers to mandate that clinicians not just report errors, but also gather to investigate those errors using root cause analysis (RCA). We focus on the tensions created for clinicians as they are expected to formulate 'systems solutions' that go beyond blame. In addressing these matters, we present a discourse analysis of data derived during an evaluation of the NSW Health Safety Improvement Program. Data include transcripts of RCA meetings which were recorded in a local metropolitan teaching hospital. From this analysis we move back to the argument that RCA involves clinicians in 'immaterial labour', or the production of communication and information, and that this new labour realizes two important developments. First, because RCA is anchored in the principle of health care practitioners not just scrutinizing each other, but scrutinizing each others'errors, RCA is a challenging task. Second, thanks to turning the clinical gaze in on the clinical observer, RCA engenders a new level of reflexivity of clinical self and of clinical practice. We conclude with asking whether this reflexivity will lock the clinical gaze into a micro-sociology of error, or whether it will enable this gaze to influence matters superordinate to the specifics of practice and the design of clinical treatments; that is, the over-arching governance and structuring of hospital care.
Co-defining WASH (In)Security challenges among people experiencing homelessness. A qualitative study on the Human Right to Water and Sanitation from Bonn, Germany

Access to safe and affordable drinking water, sanitation and hygiene (WASH) for all is needed to safeguard human health, high on societal and political agendas. According to official estimates, populations in high-income countries (HICs) are well served. Vulnerable communities at the margins of rich societies, including people experiencing homelessness, however, are often underserved and overlooked. For them, safe WASH is often a dream rather than reality. To date, no study has been conducted in Germany - one of the countries most affected in Europe.We chose a qualitative mixed-method approach to understand WASH (in)security challenges that people experiencing homelessness are facing. Data were collected in Bonn, Germany, from 25 people experiencing homelessness (in-depth interviews, arts-based workshops, group discussions), their service providers (social workers), and (un)available public infrastructure (inspections), in 2023. Data were analyzed following the dimensions of the Human Right to Water and Sanitation (HRTWS): availability; accessibility; affordability; acceptability; quality and safety.People experiencing homelessness largely lack available, accessible, affordable, acceptable and safe WASH. Open urination and defecation are often the only alternative, resulting in substantial health risks and diseases. Women face particular challenges, especially while menstruating. Extreme weather events complicate existing WASH insecurity further, creating additional hardships for unhoused people and their service providers. The missed realization of the HRTWS has far-reaching consequences, making it harder to transition out of homelessness.Much remains to be done to serve unhoused people in HICs better with WASH. Their experiences shed light on the underlying complexities, and the implications of different often interconnected challenges, including instability, mobility, preexisting diseases, mental health conditions and substance use disorder. Different insecurities exist among different sub-groups (e.g. women, people with limited mobility). They are valuable key informants for targeted health messaging and interventions.
Agricultural production and biodiversity conservation: A typology of Swiss farmers’ land use patterns

Understanding farmers' land use behaviour is a prerequisite for designing effective policies that aim to protect and enhance biodiversity in agriculture. We develop a typology of Swiss farmers' land use patterns in terms of their agricultural production and biodiversity conservation. We contribute by adopting a comprehensive perspective encompassing not only EFAs (Ecological Focus Areas) but also non-EFAs. Relying on a sample of 2341 Swiss farm observations from the Farm Agri-Environmental and the Farm Accountancy Data Network, we conducted – for each agricultural region (plain, hill and mountain) – a K-means clustering to identify farmland use patterns. We considered four clustering variables, namely agricultural production intensity, the extent of a farm's participation in agri-environmental payment schemes and the impact of farm agricultural practices on the organismal biodiversity of 1) EFAs and 2) non-EFAs. The analysis reveals four distinct farmland use patterns beyond the classical dichotomy of low shares of EFAs and high agricultural production intensity versus high shares of EFAs and low agricultural production intensity. Three of the four land use patterns are similar across all agricultural regions. Our findings show that biodiversity enhancement is possible outside of EFA direct payment programmes. One cluster succeeded in exhibiting both a high agricultural production intensity and a high overall biodiversity score, which highlights that these dimensions are not mutually exclusive. The low or moderate use intensity of mineral fertilisers, pesticides and purchased feedstuffs in combination with a high use efficiency of these inputs seems to be the key to reconciling agricultural production and biodiversity conservation.
Space Charge Effect and Mirror Charge Effect in Photoemission Spectroscopy

We report the observation and systematic investigation of the space charge effect and mirror charge effect in photoemission spectroscopy. When pulsed light is incident on a sample, the photoemitted electrons experience energy redistribution after escaping from the surface because of the Coulomb interaction between them (space charge effect) and between photoemitted electrons and the distribution of mirror charges in the sample (mirror charge effect). These combined Coulomb interaction effects give rise to an energy shift and a broadening which can be on the order of 10 meV for a typical third-generation synchrotron light source. This value is comparable to many fundamental physical parameters actively studied by photoemission spectroscopy and should be taken seriously in interpreting photoemission data and in designing next generation experiments.
Lasso estimation for GEFCom2014 probabilistic electric load forecasting

We present a methodology for probabilistic load forecasting that is based on lasso (least absolute shrinkage and selection operator) estimation. The model considered can be regarded as a bivariate time-varying threshold autoregressive(AR) process for the hourly electric load and temperature. The joint modeling approach incorporates the temperature effects directly, and reflects daily, weekly, and annual seasonal patterns and public holiday effects. We provide two empirical studies, one based on the probabilistic load forecasting track of the Global Energy Forecasting Competition 2014 (GEFCom2014-L), and the other based on another recent probabilistic load forecasting competition that follows a setup similar to that of GEFCom2014-L. In both empirical case studies, the proposed methodology outperforms two multiple linear regression based benchmarks from among the top eight entries to GEFCom2014-L.
The Interactive Impact of Investor Attention and Company Performance on Corporate Social Responsibility Reporting

In the current situation, the allocation of a part of the company's profit to implement activities related to social responsibility has been given more attention. Paying attention to this issue not only improves the professional and social dimensions of companies' activities but also affects the financial performance of companies by increasing their attractiveness to retail and institutional investors. For this reason, the increase in investor's attention and sensitivity to the company's performance will increase accountability and, as a result, address the issues related to social responsibility and its reporting by the company. Investors and external users consider social responsibility reports as an important source of communication with the company.This research, to measure the investor's attention from the Google search volume of the company's symbol and to measure the degree of social responsibility reporting from the analytical method of the content test using the criteria considered in the checklist designed by Hassas Yeganeh and Barzegar (2014) was used. Also, to calculate the performance of the company, the return on assets ratio was used. The data examined in the research are related to 175 companies admitted to the Tehran Stock Exchange from 2015 to 2014. To test the research hypotheses, multivariate regression was used.Based on the findings of this research, investor attention has a positive and significant relationship with the degree of Corporate social responsibility reporting by the company. Also, the company's performance intensifies the positive relationship between investor attention and the degree of social responsibility reported by the company.In general, increasing the level of investor attention will increase the company's disclosure level about social responsibility.Addressing the issue of investor sensitivity and attention can lead companies to improve the mechanisms designed to act on social responsibility, and as a result, improve high quality and create attractiveness for investors.
Surveillance Technology and State Security in Africa: Pegasus, Cellebrite, and Privacy Rights: Climate Change Dimensions

This article examines Surveillance Technology and State Security in Africa: Pegasus, Cellebrite, and Privacy Rights: Climate Change Dimensions with a focused emphasis on São Tomé and Príncipe within the field of Political Science. It is structured as a action research study that organises the problem, the strongest verified scholarship, and the main analytical implications in a concise publication-ready format. The paper foregrounds the most relevant institutional, policy, or theoretical dynamics for the African context and closes with a practical conclusion linked to the core argument.
TRANSPARENCY, ACCOUNTABILITY, AND AUDIT FINDINGS IN BPK RI TO MINIMIZING THE LEVEL OF CORRUPTION

According to the data from KPK in 2017, the Ministry and Local Government of Indonesia were laced in the 5th rank of biggest number of corruption case in 2017. This study aims to determine the effect of transparency, accountability, and BPK-RI’s audit findings in minimalize the level of corruption both partially and simultaneously.  The population of this study was the Ministry and Local Government of Indonesia in 2017. Samples were determined by using purposive sampling analysis which obtained 24 samples data in total. The data analyzed used in this study were descriptive analysis and multiple linear regression. The result of this study showed that transparency, accountability, and BPK RI’s audit finding have effect in minimalizing the corruption level.
Comprehensive Review on Grain Quality Enhancement and Development of Disease-Resistant Genotypes in Rice (Oryza sativa L.): Addressing Food Security Through Sustainable Agriculture

Rice (Oryza sativa L.), the seed of life, holds immense nutritional, cultural, and medicinal importance, especially in Asia where it serves as a staple food for over 90% of the population. While white rice is most commonly consumed, it loses significant nutritional components such as fiber, vitamins, and minerals during refining. In contrast, pigmented rice varieties—such as black, red, brown, and purple rice—retain their bran layers and are rich in essential nutrients, antioxidants, and bioactive compounds, including anthocyanins and γ-oryzanols. These properties make colored rice increasingly popular among health-conscious consumers for addressing micronutrient deficiencies like anaemia and zinc deficiency, as well as chronic diseases through antioxidant intake. Biofortification to enhance zinc and iron content, coupled with improvements in protein (especially glutelin), starch quality, and fiber, is crucial to address malnutrition and support sustainable health outcomes. Equally important is managing the major biotic stress—Bacterial Leaf Blight (BLB)—caused by Xanthomonas oryzae pv. oryzae, which has historically caused yield losses up to 80% and significantly affected grain quality. In India, major outbreaks have been reported in states like Andhra Pradesh, Haryana, Punjab, and Maharashtra. Management strategies include genetic, cultural, biological, chemical, and mechanical approaches, among which genetic resistance is the most eco-friendly and sustainable. Over 40 resistance (R) genes (e.g., Xa21, xa5, xa13) have been identified, and marker-assisted selection and gene pyramiding have proven effective in developing resistant varieties such as IRBB60. These gene combinations not only provide long-lasting resistance but also preserve grain nutritional traits. Thus, integrating breeding programs for enhanced grain nutritional quality and robust disease resistance offers a dual strategy to improve rice productivity, ensure food security, reduce environmental degradation, and deliver health benefits to consumers. This approach aligns with global efforts toward achieving sustainable agriculture and better nutritional outcomes.
The impact of protected areas on biodiversity conservation under different climate and land use change projections

Increasing conservation efforts are required to avert biodiversity decline caused by climate and land use changes.In a recent study (Hari et al. in prep), we combined climate change scenarios (RCP2.6 and RCP6.0) and land use change projections to assess their impact on future species distribution for a large number of mammals, birds and amphibians. Future projections of land use change were derived from the Land Use Harmonization dataset v2 (LUH2), which does not make any explicit assumptions about the area under protection in these scenarios.Here, we extend the scope of our future biodiversity projections by adding new land use scenarios explicitly accounting for different &amp;#8220;Nature Futures&amp;#8221; in the sense of different levels of biodiversity conservation (i.e., current protected areas or 30x30 target). In the first conservation scenario, we fix the protected areas based on the World Database on Protected Areas (WDPA), thereby assuming that protected areas will remain the same in the future as it is today. In a second category of scenarios, we create land use scenarios compatible with the Global Biodiversity Framework&amp;#8217;s &amp;#8220;30x30&amp;#8221; target based on the spatially optimized dataset by Jung et al. (2021) combined with LUH2.We then quantify how incorporating different levels of protected areas for conservation change the future species richness based on our land use filtering approach. We also analyze how these two scenarios of land management for conservation interfere with different levels of global warming and what are the implications for the climate resilience of different biodiversity conservation choices.
Nurse staffing level and overtime associated with patient safety, quality of care, and care left undone in hospitals: A cross-sectional study

The purpose of this study was to explore the association of nurse staffing and overtime with nurse-perceived patient safety, nurse-perceived quality of care, and care left undone.A cross-sectional survey.A total of 65 hospitals were selected from all of the acute hospitals (n=295) with 100 or more beds in South Korea by using a stratified random sampling method based on region and number of beds, and 60 hospitals participated in the study. All RNs working on the date of data collection in units randomly selected from the list of units in each hospital were invited to participate. The analyses in this study included only bedside RNs (n=3037) and hospitals (n=51) with responses from at least 10 bedside RNs.We collected data on nurse staffing level, overtime, nurse-perceived patient safety, nurse-perceived quality of care, nurse-reported care left undone, and nurse characteristics through a nurse survey. Facility data from the Health Insurance Review Agency (HIRA) were used to collect hospital characteristics. Multilevel logistic regression models considering that nurses are clustered in hospitals were used to analyze the effects of hospital nurse staffing and overtime on patient safety, quality of care, and care left undone.A higher number of patients per RN was significantly associated with higher odds of reporting poor/failing patient safety (OR=1.02, 95% CI=1.004-1.03) and poor/fair quality of care (OR=1.02, 95% CI=1.01-1.04), and of having care left undone due to lack of time (OR=1.03, 95% CI=1.01-1.05). Compared with RNs who did not work overtime, RNs working overtime reported an 88% increase in failing or poor patient safety (OR=1.88, 95% CI=1.40-2.52), a 45% increase in fair or poor quality of nursing care (OR=1.45, 95% CI=1.17-1.80), and an 86% increase in care left undone (OR=1.86, 95% CI=1.48-2.35).Our findings suggest that ensuring appropriate nurse staffing and working hours is important to improve the quality and safety of care and to reduce care left undone in hospitals.
Reforms to the United Nations&apos; Security Council: A Case Study of Nigeria

Since 1993, the United Nations (UN) General Assembly has debated calls for reform to the United Nations Security Council (UNSC). Proposed reforms have included amendments to the use of the veto, improved representation of member countries in the permanent membership and an expansion of the Council&apos;s permanent members. The continent of Africa is not represented in the permanent membership of the UNSC, though it is the largest regional group in the UN. With three of the Council’s five permanent members from Europe and one each from the Americas and Asia, the African Union argues this situation is historically unjust and contributes to a lack of balance of the Council. This thesis seeks to examine any possibilities of expansions to the UNSC’s permanent membership, as well as whether Nigeria, an African country, may qualify for such a seat, based on defined criteria and as captured in the following research questions: 1. Is there a case for expansion of permanent member seats on the United Nations Security Council (UNSC)? 2. If there is a case for such expansion, is Nigeria eligible, based on defined criteria, for one of these additional permanent member seats? To answer the two research questions, this thesis explored events leading to the formation of the UN and the UNSC, and leading up to calls for reforms to the latter. Using qualitative comparative analysis, it reviews four major reform proposals and seeks to determine whether there is a case for expansion of UNSC permanent members and whether Nigeria, as a case study, is eligible for a permanent member seat, based on this study’s defined criteria. While these two elements are confirmed by this research, the study concludes that any reforms would be difficult to achieve consensus from UN and UNSC members without significant compromise.
Oriented object detection in optical remote sensing images using deep learning: a survey

Oriented object detection is a fundamental yet challenging task in remote sensing (RS), aiming to locate and classify objects with arbitrary orientations. Recent advancements in deep learning have significantly enhanced the capabilities of oriented object detection methods. Given the rapid development of this field, a comprehensive survey of the recent advances in oriented object detection is presented in this paper. Specifically, we begin by tracing the technical evolution from horizontal object detection to oriented object detection and highlighting the specific related challenges, including feature misalignment, spatial misalignment, oriented bounding box (OBB) regression problems, and common issues encountered in RS. Subsequently, we further categorize the existing methods into detection frameworks, OBB regression techniques, feature representation approaches, and solutions to common issues and provide an in-depth discussion of how these methods address the above challenges. In addition, we cover several publicly available datasets and evaluation protocols. Furthermore, we provide a comprehensive comparison and analysis involving the state-of-the-art methods. Toward the end of this paper, we identify several future directions for oriented object detection research.
Autonomous Self-Evolving Automl Framework using Reinforcement-Guided Neural Architecture Search and Concept Drift Adaptation

Artificial intelligence systems operating in real- world environments must adapt to continuously evolving data dis- tributions. Traditional machine learning pipelines require manual architecture design and hyperparameter tuning, which limits scalability and adaptability. This paper proposes an autonomous self-evolving AutoML framework that integrates neural architec- ture search, reinforcement-guided evolution, transformer-based predictive modeling, concept drift detection, and self-healing mechanisms.The proposed system maintains a population of neural archi- tectures and continuously evaluates them on streaming data. A reinforcement controller guides architecture mutation and model selection, enabling the system to automatically discover improved models over time. Concept drift detection mechanisms monitor changes in the data distribution and trigger adaptive retraining when significant drift occurs. Experimental evaluation using simulated system monitoring data demonstrates that the framework successfully maintains predictive accuracy while autonomously evolving model architec- tures. The results show improved performance across multiple evaluation metrics including mean squared error, R squared score, precision, recall, F1 score, and accuracy. The proposed framework represents a step toward au- tonomous artificial intelligence systems capable of continuous self-optimization and adaptive learning.
WIMP mass from direct, indirect dark matter detection experiments and colliders: A complementary and model-independent approach

To appear in the Proceedings of the 43rd Rencontres de Moriond EW session, La Thuile, Italy, 1-8 March 2008