ethicalabs/Research-Intent-Collab huggingface dataset:
Frost risk projections in a changing climate are highly sensitive in time and space to frost modelling approaches

Late spring frost is a major challenge for various winegrowing regions across the world, its occurrence often leading to important yield losses and/or plant failure. Despite a significant increase in minimum temperatures worldwide, the spatial and temporal evolution of spring frost risk under a warmer climate remains largely uncertain. Recent projections of spring frost risk for viticulture in Europe throughout the 21st century show that its evolution strongly depends on the model approach used to simulate budburst. Furthermore, the frost damage modelling methods used in these projections are usually not assessed through comparison to field observations and/or frost damage reports. The present study aims at comparing frost risk projections simulated using six spring frost models based on two approaches: a) models considering a fixed damage threshold after the predicted budburst date (e.g BRIN, Smoothed-Utah, Growing Degree Days, Fenovitis) and b) models considering a dynamic frost sensitivity threshold based on the predicted grapevine winter/spring dehardening process (e.g. Ferguson model). The capability of each model to simulate an actual frost event for the Vitis vinifera cv. Chadonnay B was previously assessed by comparing simulated cold thermal stress to reports of events with frost damage in Chablis, the northernmost winegrowing region of Burgundy. Models exhibited scores of κ &gt; 0.65 when reproducing the frost/non-frost damage years and an accuracy ranging from 0.82 to 0.90. Spring frost risk projections throughout the 21st century were performed for all winegrowing subregions of Bourgogne-Franche-Comté under two CMIP5 concentration pathways (4.5 and 8.5) using statistically downscaled 8×8 km daily air temperature and humidity of 13 climate models. Contrasting results with region-specific spring frost risk trends were observed. Three out of five models show a decrease in the frequency of frost years across the whole study area while the other two show an increase that is more or less pronounced depending on winegrowing subregion. Our findings indicate that the lack of accuracy in grapevine budburst and dehardening models makes climate projections of spring frost risk highly uncertain for grapevine cultivation regions.
Challenges of software process and product quality improvement: catalyzing defect root-cause investigation by process enactment data analysis

It is claimed by software quality management that the quality of a software product is highly influenced by the quality of the software process followed to develop it. Since measurement of the software process is a challenging task, it is frequently the defects in the software product that are used to measure development quality. By extracting semantic information from defect records, practitioners can investigate and address root causes of software defects to improve development process and product quality. Investigating root causes requires effort for a detailed analysis into the components of the development process that originated the software defects, and is therefore encouraged only at higher maturity levels by most known process improvement models such as Capability Maturity Model Integration (CMMI). This practice, however, postpones the benefits that root-cause analysis would bring in gaining process awareness to improve the software development process and product quality in emergent organizations or organizations residing at lower maturity levels (MLs). In this article, we present a method for and results from applying root-cause analysis for software defects recorded in a software-intensive project of a CMMI ML3 certified institute. The suggested method combines process enactment data collection and analysis with Orthogonal Defect Classification which is a known technique in defect root-cause analysis. Prior to and after implementing the method in the study, defect attributes were analyzed and compared in order to understand any improvements in development performance and product quality. The results of the comparison indicate that the suggested method was efficient in the effort it required and effective in improving development performance and product quality. Defect triggers have become more active in identifying software defects in the earlier phases of software development, and the cost of quality due to software defects has decreased in consequence.
E-Government for Transparency, Anti-Corruption, and Accountability

This chapter discusses the development of e-Government in Central American countries. The study presents an analysis of the role that e-Government has played during the last decade (2000-2010) in order to promote transparency, accountability, and anti-corruption measures. It starts with a definition of the principal concepts of the study and the e-Government development in the Region. It then reviews the laws and regulations and analyzes Web technology deployment in new agencies that have been legally established by Central American governments to advance transparency, accountability, and anti-corruption initiatives. In this context, the research aims to explore the question about whether information and communication technologies (specifically e-Government) facilitate transparency and accountability, and limit corruption in developing countries. The results provide support to this general statement and also suggest that public institutions themselves, and their non-digital procedures, still play a significant role in promoting more transparent practices. Finally, the text concludes with how to reinforce the policy of employing digital technology as an instrument for promoting good government in emerging economies.
Harnessing the transformative potential of the constitutional human right to a clean and healthy environment in the context of corporate environmental damage in Kenya: a critical perspective

Corporate environmental damage in Kenya manifests as a complex mix of humanitarian and ecological harms superimposed over serious environmental governance challenges. The existing legal framework is neither a sufficient deterrent to prevent the occurrence of harm, nor does it offer optimal remedies whenever harm occurs. The limitations inherent in law are primarily because laws are designed to reflect an economic rationality that prioritizes economic growth and profit maximization above all else. Even in cases where a causal relationship between such a rationality and the design of law cannot be ascertained, the limitations of law ultimately inure to the benefit of corporate perpetrators of harm. As a result, the law facilitates the externalization of the costs of environmental damage to the advantage of corporate perpetrators. The constitutional human right to a clean and healthy environment stands as law's response to this problem. Drawing on insights from critical theories of human rights, this article argues that the right can be an effective instrument against corporate environmental damage if it is construed in a manner that prioritizes maximum protection of the well-being of humans and ecosystems. Constructing the right in this way assumes that the new norm is itself a reflection of a new rationality, constituted by a set of values different from those that have played a predominant role in shaping legal and institutional responses to environmental damage so far. These values should guide courts, administrators and legislators in the exercise of their respective environmental protection duties.
Measuring Adoption of Patient Priorities–Aligned Care Using Natural Language Processing of Electronic Health Records: Development and Validation of the Model (Preprint)

BACKGROUND                         Patient Priorities Care (PPC) is a model of care that aligns health care recommendations with priorities of older adults who have multiple chronic conditions. Following identification of patient priorities, this information is documented in the patient’s electronic health record (EHR).                                                                       OBJECTIVE                         Our goal is to develop and validate a natural language processing (NLP) model that reliably documents when clinicians identify patient priorities (ie, values, outcome goals, and care preferences) within the EHR as a measure of PPC adoption.                                                                       METHODS                         This is a retrospective analysis of unstructured National Veteran Health Administration EHR free-text notes using an NLP model. The data were sourced from 778 patient notes of 658 patients from encounters with 144 social workers in the primary care setting. Each patient’s free-text clinical note was reviewed by 2 independent reviewers for the presence of PPC language such as priorities, values, and goals. We developed an NLP model that utilized statistical machine learning approaches. The performance of the NLP model in training and validation with 10-fold cross-validation is reported via accuracy, recall, and precision in comparison to the chart review.                                                                       RESULTS                         Of 778 notes, 589 (75.7%) were identified as containing PPC language (kappa=0.82, &lt;i&gt;P&lt;/i&gt;&amp;lt;.001). The NLP model in the training stage had an accuracy of 0.98 (95% CI 0.98-0.99), a recall of 0.98 (95% CI 0.98-0.99), and precision of 0.98 (95% CI 0.97-1.00). The NLP model in the validation stage had an accuracy of 0.92 (95% CI 0.90-0.94), recall of 0.84 (95% CI 0.79-0.89), and precision of 0.84 (95% CI 0.77-0.91). In contrast, an approach using simple search terms for PPC only had a precision of 0.757.                                                                       CONCLUSIONS                         An automated NLP model can reliably measure with high precision, recall, and accuracy when clinicians document patient priorities as a key step in the adoption of PPC.
A Survey of the Federated Learning and Differential Privacy Techniques

For å kunne bruke et datasett som inneholder sensitiv informasjon, må det være sikret og beskyttet. Federated learning er en metode innen maskinlæring som prøver å løse dette problemet. Ved å bringe en global modell til en lokal enhet kan brukere dra nytte og lære av en felles modell, samtidig som de beholder sin data lokalt. Siden dette er et relativt nytt konsept derimot, er det fremdeles noen utfordringer med metoden. Derfor er ikke federated learning alene alltid sterkt nok til å beskytte datasettet. Av den grunn brukes det ofte i kombinasjon med differensielt personvern (DP). Dette er en definisjon som sikrer personvern ved bruk av støy. Den originale definisjonen av differensielt personvern, (epsilon)-DP, er ofte for streng til at det kan brukes i praksis. Derfor har det blitt utviklet mange variasjoner av definisjonen, og den mest vanlige er (epsilon, delta)-DP. Dette er en avslappet definisjon som godtar noe lekkasje av informasjon. Videre er det flere mekanismer som sikrer differensielt personvern. Laplace mekanismen og den eksponentielle mekanismen er noen av de vanligste metodene. Mange maskinlæringsklassifiserere, slik som lineær og logistikk regresjon, dype nevrale nettverk og support vektor maskiner, kan tilpasses til å sikre differensielt personvern. Personvernbudsjettet, epsilon, gir en avveining mellom ytelsen til modellen og personvernet til datasettet. Eksperimenter avslører at graden av avveining er påvirket av valget av for eksempel datasett, klassifiserer, modell og fremgangsmåte. Noen av eksperimentene viser ingen betydelig avveining, mens andre viser alvorlige avveininger. I tillegg eksisterer det fremdeles noen åpne spørsmål rundt både federated learning og differensielt personvern som krever videre undersøkelser.
Optimizing suburban public transport through smart city logistics: a study on information flow and passenger management

The study explores how Smart City technologies influence logistics operations in suburban public transportation systems. By enhancing passenger and vehicle movement, the study assesses the role of sensor data, real-time information, and data analysis in improving the flow of materials, personnel, and information in suburban transit. Findings demonstrate that Smart City initiatives lead to shorter wait times, improved route optimization, and greater reliability, thereby boosting overall transport logistics. Through real-time data processing, suburban systems can manage flow dynamically, offering valuable insights for scalable implementations in both urban and suburban logistics.
Exploring anti-corruption, transparency, and accountability in the World Health Organization, the United Nations Development Programme, the World Bank Group, and the Global Fund to Fight AIDS, Tuberculosis and Malaria

AbstractCorruption is recognized by the global community as a threat to development generally and to achieving health goals, such as the United Nations Sustainable Development Goal # 3: ensuring healthy lives and promoting well-being for all. As such, international organizations such as the World Health Organizations and the United Nations Development Program are creating an evidence base on how best to address corruption in health systems. At present, the risk of corruption is even more apparent, given the need for quick and nimble responses to the COVID-19 pandemic, which may include a relaxation of standards and the rapid mobilization of large funds. As international organizations and governments attempt to respond to the ever-changing demands of this pandemic, there is a need to acknowledge and address the increased opportunity for corruption.In order to explore how such risks of corruption are addressed in international organizations, this paper focuses on the question: How are international organizations implementing measures to promote accountability and transparency, and anti-corruption, in their own operations? The following international organizations were selected as the focus of this paper given their current involvement in anti-corruption, transparency, and accountability in the health sector: the World Health Organization, the United Nations Development Program, the World Bank Group, and the Global Fund to Fight Aids, Tuberculosis and Malaria. Our findings demonstrate that there has been a clear increase in the volume and scope of anti-corruption, accountability, and transparency measures implemented by these international organizations in recent years. However, the efficacy of these measures remains unclear. Further research is needed to determine how these measures are achieving their transparency, accountability, and anti-corruption goals.
CEO’s Letter Accompanying the Report on Corporate social Responsibility of Canadian Listed Firms: An Analysis of the Content and the Links with Some of the Firms’ Characteristics

The disclosure of Corporate Social Responsibility (CSR) by Canadian firms is not mandatory. This provides an ideal context to describe the nature of what is being freely disclosed by large firms and to study the firms’ characteristics which lead to such disclosure. We searched all TSX listed firms to find those which disclose a CSR report accompanied by a letter from the CEO. In the end, we study 89 CEO’s letters; that is, all the firms disclosing both a CSR report and a CEO’s letter. We first looked at the nature of the elements disclosed. We classified them in 3 categories: (1) actual accomplishments in the field of CSR, (2) values and (3) future objectives. The «actual accomplishments» is the category with the fewest elements disclosed (proportionally to all the elements that we identified as potentially disclosed in this category) while the category «values» is the one with the most elements. On average, less than 50% of the elements we identified as possibly disclosed were actually discussed in the CEO’s letters.We also looked at the relationship between the level of disclosure and some of the characteristics of the firms. We found that only the variables «profitability» and «sectors of activities» are significantly related.This is obviously an exploratory research which will be followed by a study of the Corporate Social Report and the relationship between the report itself and the elements found in the CEO’s letter.
Multi-view contrastive self-supervised learning of accounting data representations for downstream audit tasks

8 pages (excl. appendix), 4 Figures, 3 Tables
Black holes in X-ray binaries - Marginal existence and rotation reversals of accretion disks

We adopt the hypothesis that black holes in X-ray binaries are accreting gas from an accretion disk fed by a stellar wind emanating from the primary. The formation of such a disk is found to be marginal in the case of a steady, spherically symmetric stellar wind and may be controlled by random fluctuations in the wind parameters. Such fluctuations may cause reversals in the rotation direction of the disk. Reversals in a disk around a rapidly rotating black hole lead to two distinct intensity states and may be associated with the two states observed for Cyg X-1. (AIP)
Towards discard quantification of Data Limited Stocks based in on-board observers data: the case of Spanish fresh trawlers targeting black hake in NW Africa.

Quantification of discard per unit effort rates (DPUE) has been proposed by the European Commission as a measure to manage the discarding of commercially fished organisms. In the Spanish fresh trawling fleet operating in North West Africa, both target species of black hakes, Merluccius polli and Merluccius senegalensis are data limited stocks (DLS). Hence, discards of these fleets are even more unknown but not unimportant part of the total catch (retained and discarded). Onboard observer data from commercial surveys from 2016 to 2018 provide a detailed source of scientific information about catches, discards, effort and technical factors in this fleet. This is the first quantitative analysis to model DPUE through generalised linear mixed models (GLMM), based on the explicit distinction between abundance and technical factors coming from information of observer surveys. We describe the relationship between discards and environment, catches of target and other species, effort of the fleet, spatial and temporal variation in discard accessibility, vessel characteristics, strategy of the skippers and market decisions. Unlike hake catches, discards were higher and more dispersed in shallower than in deeper waters. We identified two separate métiers for the Spanish fresh trawling fleet determined by depth and treated total discards as a stock unit susceptible of being monitored, managed and assessed. The strategy of the skipper appears to have a more important effect on discards than vessel characteristics. This study shows the importance of observer data for this fishery and identifies recommendations for the improvement in the scientific usefulness of logbook information.
Pairwise-additive and polarizable atomistic force fields for molecular dynamics simulations of proteins

Protein force fields have been undergoing continual development since the first complete parameter sets were introduced nearly four decades ago. The functional forms that underlie these models have many common elements for the treatment of bonded and nonbonded forces, which are reviewed here. The most widely used force fields to date use a fixed-charge convention in which electronic polarization effects are treated via a mean-field approximation during partial charge assignment. Despite success in modeling folded proteins over many years, the fixed-charge assumption has limitations that cannot necessarily be overcome within their potential energy equations. To overcome these limitations, several force fields have recently been derived that explicitly treat electronic polarization effects with straightforward extensions of the potential energy functions used by nonpolarizable force fields. Here, we review the history of the most popular nonpolarizable force fields (AMBER, CHARMM, OPLS, and GROMOS) as well as studies that have validated them and applied them to studies of protein folding and misfolding. Building upon these force fields are more recent polarizable interaction potentials, including fluctuating charge models, POSSIM, AMOEBA, and the classical Drude oscillator. These force fields differ in their implementations but all attempt to model electronic polarization in a computationally tractable manner. Despite their recent emergence in the field of protein folding, several studies have already applied these polarizable models to challenging problems in this domain, including the role of polarization in folding free energies and sequence-specific effects on the stability of α-helical structures.
Determination of the Total Solar Modulation Factors in the Heliosphere For Cosmic Ray Protons and Electrons by Comparing Interstellar Spectra Deduced from Voyager Measurements and PAMELA Spectra of These Particles at the Earth

15 pages, 4 figures
Corporate social responsibility and business ethics in Indonesia: a Scopus-based bibliometric analysis (2005–2025)

Abstract                   Corporate Social Responsibility (CSR) has gained increasing prominence in Indonesia due to the regulatory reforms, sustainability commitments and the rising expectations for the ethical corporate conduct. While the scholarly interest in the CSR has expanded considerably over the past two decades, limited attention has been paid to how this body of research has evolved structurally and how the CSR has been conceptually integrated with Business Ethics in the Indonesian context. Addressing this gap, this study conducts a Scopus-based bibliometric analysis of 634 CSR-related journal articles published between 2005 and 2025. Using the Biblioshiny interface of the Bibliometrix R package, the analysis examines the publication and the citation trends, influential authors and sources, thematic structures, intellectual foundations and the collaboration networks.                   The results indicate a significant growth in the Indonesian CSR scholarship, particularly following the key regulatory milestones such as the Law No. 40/2007 and the OJK Sustainable Finance Roadmap. The thematic mapping reveals a clear transition from the philanthropic and compliance-oriented CSR toward more strategic and ethically grounded approaches, organized around four dominant clusters: sustainability and ESG integration, ethical governance and accountability, community engagement and empowerment and CSR–performance linkages. The co-citation patterns demonstrate that the Indonesian CSR research is anchored in the globally established theories (such as the stakeholder and legitimacy theories) while simultaneously integrating the locally embedded ethical values, including the collective responsibility (gotong royong).                   Overall, this study offers a consolidated overview of the evolution and structure of the CSR and Business Ethics scholarship in Indonesia. By clarifying how the global theoretical frameworks interact with the national regulations and the cultural norms, the findings contribute to a deeper understanding of the ethical governance within the emerging market CSR research and provide directions for future studies on the ESG integration and the context-specific CSR practices.
A hybrid framework to assess the risk of change in construction projects using fuzzy fault tree and fuzzy event tree analysis

Changes in construction projects are a common risk that often have an adverse impact on project performance. Thus, proactive change management plays a significant role in the successful completion ...