ethicalabs/Research-Intent-Collab huggingface dataset:
The environmental committee: corruption, accountability and sustainable supply chain transparency

Purpose                     The purpose of this study is to investigate whether public governance quality (i.e. control of corruption and voice and accountability) and corporate governance strength (i.e. environmental committee existence) are influential in stimulating supply chain transparency and how these two governance characteristics interact in enhancing supply chain transparency.                                                           Design/methodology/approach                     Our investigation draws on a sample of 25,096 firm-year observations affiliated with the manufacturing industry in 50 countries and executes country-year fixed effects.                                                           Findings                     We find that the strength of control of corruption, voice and accountability is positively associated with supply chain transparency, supporting institutional theory. Furthermore, the environmental committee’s existence is positively related to sustainable supply chain transparency, confirming the upper echelons theory. The moderating analysis rejects the complementary effect but supports the substitution effect, confirming the negative moderating role of the environmental committee between the control of corruption and voice and accountability and sustainable supply chain transparency.                                                           Originality/value                     No empirical study has drawn on an international sample to (1) explicate the worldwide adoption of sustainable supply chain transparency, (2) link corruption and accountability to green supply chain transparency or (3) investigate how sustainable supply chain transparency is affected by the interplay of institutions and environmental management committees. Thus, we highlight the substitutive or complementary role of internal and external governance mechanisms in inciting firms toward greener supply chain management by developing a novel sustainable supply chain transparency index that draws on five indicators.
Context Autoencoder for Self-supervised Representation Learning

We present a novel masked image modeling (MIM) approach, context autoencoder (CAE), for self-supervised representation pretraining. We pretrain an encoder by making predictions in the encoded representation space. The pretraining tasks include two tasks: masked representation prediction - predict the representations for the masked patches, and masked patch reconstruction - reconstruct the masked patches. The network is an encoder-regressor-decoder architecture: the encoder takes the visible patches as input; the regressor predicts the representations of the masked patches, which are expected to be aligned with the representations computed from the encoder, using the representations of visible patches and the positions of visible and masked patches; the decoder reconstructs the masked patches from the predicted encoded representations. The CAE design encourages the separation of learning the encoder (representation) from completing the pertaining tasks: masked representation prediction and masked patch reconstruction tasks, and making predictions in the encoded representation space empirically shows the benefit to representation learning. We demonstrate the effectiveness of our CAE through superior transfer performance in downstream tasks: semantic segmentation, object detection and instance segmentation, and classification. The code will be available at https://github.com/Atten4Vis/CAE.
Research on the Teaching Reform and Innovation of Business Ethics and Corporate Social Responsibility Course Assisted by Artificial Intelligence

With the deep penetration of artificial intelligence technology in the field of education, the traditional course of Business Ethics and Corporate Social Responsibility is facing challenges such as insufficient timeliness of cases, low student participation, single teaching methods, and limitations of the assessment system . Based on the advantages of artificial intelligence technology, this paper explores the path of teaching reform from three dimensions: reconstruction of teaching objectives, innovation of teaching methods, and improvement of assessment systems. Research shows that by introducing artificial intelligence tools such as intelligent case libraries, virtual simulation teaching, and personalized learning systems, the practicality, interactivity, and pertinence of the course can be effectively enhanced. Such channels can be used to cultivate students' ability to practice ethical standards and social responsibilities in complex business scenarios, which can provide a reference for the intelligent reform of business courses.
Exploring change in tourism systems: a qualitative study on hospitality operators and the new Salerno airport’s impact on destination management

Changes in destination accessibility can trigger shifts in a tourism system, requiring management strategies and strategic alliances to turn these changes into competitive assets. Such changes may pose challenges without proper management, negatively affecting a destination’s attractiveness. This paper adopts a case study approach to examine tourism system change following the opening of Salerno Costa D’Amalfi Airport in July 2024. This event marks an opportunity to enhance the destination’s appeal and strengthen its economic base. While Salerno has traditionally been secondary to renowned neighbouring destinations like Naples and the Amalfi Coast, the new airport infrastructure offers a chance to redefine its competitive positioning in regional and international markets. However, this change also affects tourism employment, services, and seasonality. This study will explore hospitality owners, managers and hosts’ perceptions of change through the theoretical lens of the tourism competitiveness six A’s framework. Preliminary findings suggest that stakeholders perceive improved accessibility as a first step towards an ecosystem change that can tackle urgent issues such as seasonality, low levels of stable tourism employment, and overdependence on specific tourism segments. Indeed, the new airport could lead to a new network of services benefiting tourists and residents and turn Salerno into a hub for tourists and neighbouring regions suffering from accessibility issues. The new airport could enhance Salerno’s attractiveness to new tourism segments such as sports and business tourism if guided by new amenities and ancillary services like working spaces, fairs, exhibitions, and cultural and business events. However, findings suggest that it is crucial to have a proper inclusive tourism strategy guided by tourism stakeholders capable of identifying the most suitable strategies to pursue based on the territory’s main challenges. Without the involvement of local tourism stakeholders, there is the risk of encountering challenges that affect the tourism ecosystem, such as a deregulated increase in tourism accommodation, a lack of intermodal connectivity and the development of attractions that do not value the local culture and economy.
Comparative Cost and Capacity Analysis of Managed Service and Non-Managed Service API Gateway Architectures on Leading Cloud Platforms

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PRIORITY SECTORS FOR THE MACEDONIAN TRANSITION TO A CIRCULAR ECONOMY: STRATEGIC PATHWAYS FOR SUSTAINABLE TRANSFORMATION

The circular economy (CE) offers a comprehensive framework for decoupling economic growth from resource use and environmental degradation. For the Republic of North Macedonia (RNM), transitioning to a CE is both an environmental necessity and an economic opportunity, alignedwith the country’s EU accession commitments and the Green Agenda for the Western Balkans. This paper1 identifies five priority sectors with the greatest potential for transformation: construction; biomass and food; textiles; mining and metallurgy; and cultural and creative industries. The first four were identified in the OECD’s Circular Economy Roadmap for North Macedonia based on four key criteria-economic importance, policy relevance, circularity potential, and decarbonisation potential, while the fifth sector, cultural and creative industries, is introduced here as an emerging priority following further analysis.Beyond identifying these sectors, the paper outlines strategic implications, explores cross-sectoral synergies, and proposes targeted policy measures to support their transition. By focusing on these sectors and fostering coordinated action, the analysis aims to guide governance, policy design, and investment toward areas where the CE transition can deliver the most significant economic,social, and environmental benefits for the Republic of North Macedonia.
Explaining Deep Learning Models in Full Waveform Inversion: Enhancing Transparency in Seismic Data Interpretation

Abstract                We present a physics-informed neural network approach for full-waveform inversion (FWI) that embeds a Deep Image Prior (DIP) U-Net within the inversion loop and applies explainable AI (XAI) methods to interpret the learned model. Starting from a decimated Marmousi velocity model, we generate synthetic seismic data via 2D acoustic wave propagation. A smoothed version of the true model initializes a randomly initialized U-Net (the DIP), which is pretrained to replicate the smoothed model. Thereafter, the DIP's weights replace the cell-wise velocity parameters in FWI, and an iterative optimizer adjusts these weights to minimize discrepancies between observed and simulated waveforms. The resulting high-resolution velocity model arises from physics-constrained learning. To reveal the network's decision process, we compute attribution maps using SHapley Additive exPlanations (SHAP), Integrated Gradients, and occlusion sensitivity. These maps highlight the spatial features; primarily high-contrast layers and anomalies that drive the DIP's output. Comparative analyses of true vs. predicted models, residuals, and combined depth/lateral sensitivity profiles confirm that the deep model captures essential subsurface structures. This framework enhances transparency in seismic inversion by linking data-driven models to geophysical knowledge, thus bridging the gap between "black-box" deep learning and interpretable imaging.
Ecological Efficiency of Voluntary Conservation of Boreal‐Forest Biodiversity

Abstract:                      Current networks of protected areas are biased in many countries toward landscapes of low productivity. Voluntary conservation incentives have been suggested as a socially acceptable way to supplement existing networks with more productive, privately owned areas of high priority for nature conservation. The limited resources committed to nature conservation demand cost‐efficiency. Efficiency, however, depends not only on costs incurred to society from alternative ways of maintaining biodiversity but also on ecological values that can be captured. We examined the ecological efficiency of the new market‐based voluntary program to preserve forest habitats on private land in southwestern Finland. We compared sites that have become protected (10‐year contracts) in the program with managed forests, with sites that have been negotiated for protection for which no contract has been signed, and with the most ecologically valuable privately owned sites in the region that have not been offered for protection by forest owners. We surveyed sites for the amount of dead wood, wood‐decomposing fungi, and epiphytic lichens to evaluate their ecological quality. Contracted sites had more features important for overall biodiversity than managed forests and negotiated sites with no contract. These results indicate that procedures used during site selection and negotiations were appropriate and not opportunistic. The contracted sites were also as valuable in ecological terms as the best, still‐unprotected, privately owned forests in the region that have not been offered for protection. We conclude that voluntary conservation programs have the potential to yield ecologically valuable sites for protection if the site‐selection procedures are appropriate. Reliance on completely voluntary programs, however, may entail uncertainties and inadequacies, for example, in terms of spatial configuration and persistence of the ecological values. Thus, such programs may often need to be supplemented with alternative methods such as land purchase to achieve an ecologically effective network of protected sites.
Ethics Lost in Translation: Trustworthy AI from Governance to Regulation

The policy reaction of the European Union to the societal quest for fairer and more transparent Artificial Intelligence (AI) was immediate, yet partially unsatisfactory. Given the inadequacy of the liability regime and the absence of appropriate regulation of AI, the appointed High-Level Expert Group turned to ethics to develop the notion of Trustworthy AI. Generally, AI ethics was first tasked with providing guidance for global consensus on principles for AI governance. However, such ethics guidelines lack appropriate enforcement mechanisms, hence the unsuitability to provide clear guidance for AI regulation, leading to a potential phenomenon of ‘ethics washing’. The present article unveils the quintessentially political nature of the ethics guidelines, arguing that the strictly ethical nature of the guidelines got lost in translation in light of the proposed EU regulation of AI. Instead, it is claimed that the principle of accountability bridges the gap between the ethics guidelines and the regulatory framework, as shown by a first comparative glance at the US-proposed Algorithmic Accountability Act and the EU-proposed AI Act through the lenses of the recently proposed amendments concerning foundation models, thus providing the necessary enforcement mechanism to achieve trust in AI.
Central Bank Digital Currencies and the European Framework for Payments: Friends or Foes?

Central bank digital currencies have triggered important theoretical, policy-oriented questions and normative concerns regarding their integration within the current set-up of the payment system. This chapter conceptualises the links between the digital euro project and the European framework for payments by, first, focusing on fundamental trade-offs and policy choices; second, taking stock of the European harmonisation process for payments in which the digital euro is embedded; third, analysing how potential design choices for a digital euro could be coordinated with the current legal set-up for payments and possibly address some open regulatory issues; and finally, assessing the impact of a digital currency on central banking payment oversight tasks.
An innovative way of thinking nuclear waste management – Neutron physics of a reactor directly operating on SNF

A solution for the nuclear waste problem is the key challenge for an extensive use of nuclear reactors as a major carbon free, sustainable, and applied highly reliable energy source. Partitioning and Transmutation (P&T) promises a solution for improved waste management. Current strategies rely on systems designed in the 60's for the massive production of plutonium. We propose an innovative strategic development plan based on invention and innovation described with the concept of developments in s-curves identifying the current boundary conditions, and the evolvable objectives. This leads to the ultimate, universal vision for energy production characterized by minimal use of resources and production of waste, while being economically affordable and safe, secure and reliable in operation. This vision is transformed into a mission for a disruptive development of the future nuclear energy system operated by burning of existing spent nuclear fuel (SNF) without prior reprocessing. This highly innovative approach fulfils the sustainability goals and creates new options for P&T. A proof on the feasibility from neutronic point of view is given demonstrating sufficient breeding of fissile material from the inserted SNF. The system does neither require new resources nor produce additional waste, thus it provides a highly sustainable option for a future nuclear system fulfilling the requests of P&T as side effect. In addition, this nuclear system provides enhanced resistance against misuse of Pu and a significantly reduced fuel cycle. However, the new system requires a demand driven rethinking of the separation process to be efficient.
Genetic discrimination by insurance companies in Aotearoa New Zealand: experiences and views of health professionals

Genetic discrimination in insurance is a significant clinical, research and consumer issue. Recently, the Australian life insurance industry introduced a partial moratorium on the use of genetic test results. However, in Aotearoa New Zealand, both life and health insurers can still use genetic results legally to discriminate against applicants. We aimed to document experiences and concerns of New Zealand-based health professionals (HPs) around the potential misuse of genetic test results for insurance purposes.We administered an online survey to New Zealand HPs who discuss genetic testing with patients, their experiences regarding the use of genetic test results in insurance and views on regulation.Twenty-three New Zealand HPs responded, 15 of whom worked in genetics clinics, representing >60% of the total New Zealand clinical genetics workforce. Eleven respondents reported having patients who experienced adverse outcomes related to insurance based on genetic results. Respondents reported patients sometimes/often delayed (n=11) or refused (n=4) genetic testing due to insurance concerns. Over 80% of those who answered (n=17/21) believe insurers' use of genetic results should be legally regulated.New Zealand HPs have concerns about insurance companies using genetic test results in underwriting, including the effect on patients, and strongly believe government legislation is required.
Enhancing language acquisition through personalized learning: The role of collaborative filtering and recommender systems in TESOL

This paper explores the transformative potential of Collaborative Filtering (CF) and Recommender Systems (RS) in Teaching English to Speakers of Other Languages (TESOL). By leveraging data-driven insights from learner interactions, these technologies offer personalized learning experiences that significantly enhance language acquisition, engagement, and retention. Through empirical evidence and quantitative analyses, we demonstrate the positive impact of CF and RS on learners' proficiency, vocabulary acquisition, and communicative competence. The integration of CF and RS into TESOL not only facilitates adaptive learning pathways but also addresses practical implementation challenges, including privacy, ethical concerns, and technological barriers. This study underscores the efficacy of personalized learning recommendations in creating more engaging, efficient, and effective language learning environments.
Exploration of materials electrochemistry in rechargeable batteries using advanced                     <i>in situ</i>                     /                     <i>operando</i>                     x-ray absorption spectroscopy

Abstract                                        Rechargeable batteries (Li-ion batteries and beyond) have received extensive attention as powerful boosters for the development of human society. The rapid progress achieved in this research area largely relies on the in-depth efforts on the improvement of battery electrode materials and decrease of the cost. However, the application of rechargeable batteries is still hindered by low energy density, serious voltage hysteresis, and long-term degradation. Therefore, it is of great importance for understanding the underlying redox reaction and capacity fading mechanisms to circumvent these problems and improve the overall battery performance. Advanced characterization techniques, especially synchrotron-based x-ray absorption spectroscopy (XAS), have been widely applied to the mechanistic understanding of rechargeable batteries. Particularly,                     in situ                     /                     operando                     XAS allows the characterization of practical working mechanisms by measuring the electronic structure evolution of the electrode materials under real operation conditions, which is an imperative prerequisite for the further optimization of the battery performance. Herein, the recent progress in the understanding of the operating principles of several common rechargeable batteries (including lithium-ion batteries, sodium-ion batteries, and lithium–sulfur batteries) based on                     in situ                     /                     operando                     XAS technique is reviewed and summarized. We aim to provide a comprehensive treatise on                     in situ                     /                     operando                     characterization of rechargeable batteries using XAS, which could provide guidance for further improvement of battery performance.
Figure S1 from Insights into the Links between MYC and 3D Chromatin Structure and Epigenetics Regulation: Implications for Cancer Therapy

&lt;p&gt;Schematic model for MYC-mediated transcription regulation. MYC potentially regulates the expression of a variety of genes involved in cell growth, apoptosis, proliferation, and immortalization by recruiting a large number of proteins. MYC interacts with two major protein complexes including HATs with GCN5, and Tip60 for ATP-dependent chromatin remodeling. HAT: histone acetyl-transferases; MAX: MYC associated factor X; Tip60: tat interactive protein 60; P300/CBP: p300/CREB-binding protein; GCN5: Gcn5-related N-acetyltransferase: SWI/SNF: SWItch/sucrose non-fermentable SWI/SNF.&lt;/p&gt;
Self-optimisation using runtime code generation for Wireless Sensor Networks Internet-of-Things

Self-optimisation using runtime code generation for Wireless Sensor Networks
sj-docx-8-css-10.1177_24705470231169106 - Supplemental material for Mental Health Among People Presenting for Care of Physical Symptoms: The Factors Associated with Suicidality and Symptoms of Depression and Anxiety are Similar Across Specialties

Supplemental material, sj-docx-8-css-10.1177_24705470231169106 for Mental Health Among People Presenting for Care of Physical Symptoms: The Factors Associated with Suicidality and Symptoms of Depression and Anxiety are Similar Across Specialties by Sina Ramtin, Kathleen Carberry, Maria Correa, David Ring, Carol Alter and Donna Shanor in Chronic Stress