ethicalabs/Research-Intent-Collab huggingface dataset:
AdaMSS: Adaptive Multi-Modality Segmentation-to-Survival Learning for Survival Outcome Prediction from PET/CT Images

Survival prediction is a major concern for cancer management. Deep survival models based on deep learning have been widely adopted to perform end-to-end survival prediction from medical images. Recent deep survival models achieved promising performance by jointly performing tumor segmentation with survival prediction, where the models were guided to extract tumor-related information through Multi-Task Learning (MTL). However, these deep survival models have difficulties in exploring out-of-tumor prognostic information. In addition, existing deep survival models are unable to effectively leverage multi-modality images. Empirically-designed fusion strategies were commonly adopted to fuse multi-modality information via task-specific manually-designed networks, thus limiting the adaptability to different scenarios. In this study, we propose an Adaptive Multi-modality Segmentation-to-Survival model (AdaMSS) for survival prediction from PET/CT images. Instead of adopting MTL, we propose a novel Segmentation-to-Survival Learning (SSL) strategy, where our AdaMSS is trained for tumor segmentation and survival prediction sequentially in two stages. This strategy enables the AdaMSS to focus on tumor regions in the first stage and gradually expand its focus to include other prognosis-related regions in the second stage. We also propose a data-driven strategy to fuse multi-modality information, which realizes adaptive optimization of fusion strategies based on training data during training. With the SSL and data-driven fusion strategies, our AdaMSS is designed as an adaptive model that can self-adapt its focus regions and fusion strategy for different training stages. Extensive experiments with two large clinical datasets show that our AdaMSS outperforms state-of-the-art survival prediction methods.
Integrating conservation and forestry production: exploring trade-offs between biodiversity and production in regional land-use assessment

Abstract   Regional integration of biodiversity conservation and forestry production requires land-use allocations based on trade-offs that attempt to maximise long-term net benefits to society. In this context, effective surrogate information for biodiversity must be used in order estimate the complementarity value of each area—its unique contribution to biodiversity, given other already-protected areas. Net benefits will be maximised only when the complementarity value for each protected area exceeds its weighted cost or suitability for an alternative land use. This study explored this issue using one particular surrogacy approach, based on environmental data, combined with a recently-developed procedure that incorporates biodiversity assessment into a multi-criteria analysis framework. This procedure, as implemented in a software package DIVERSITY, allows the study of a range of relative weightings on biodiversity protection versus suitabilities for alternative land uses, identifying sets of protected areas that maximise total net benefit. A case study integrating biodiversity and forestry production in the Bateman's Bay region of New South Wales, Australia, is presented, in which the suitabilities for forestry are estimated using a spatial decision-support package, LUPIS. LUPIS is linked to the DIVERSITY package in order to combine exploration of different weightings on various forestry-related criteria with weightings on biodiversity. The results demonstrate that, relative to biodiversity allocations that ignore competing land-uses, taking trade-offs into account can lead in principle to an allocation of protected areas that maintains a high degree of biodiversity representation while reducing conflict with forestry requirements.
Improving Critical Infrastructure Protection and Resilience against Terrorism Cyber Threats

Nowadays business continuity and disaster management procedures and policies are increasingly based on the notion of resilience. This relatively young topic is gaining increasing importance now that more recent experiences have shown that not all the attacks or accidents to critical information infrastructures (CIIs) can be avoided even if protection measures are correctly implemented. Such a circumstance implies that the response to &amp;lsquo;protection&amp;rsquo; needs, which has mainly shown the use of technology as a possible solution to all of the issues, is not sufficient in covering the entire lifecycle of modern information infrastructures which requires instead the implementation of redundancy measures together with specific procedures that are designed and implemented in view to facilitate a faster recovery of an asset that has suffered an unavoidable accident. The aforementioned scenario is somehow confirmed by the reorientation of the EU policies in the field and, more specifically, by the 2014-2020 European Programme for Critical Infrastructure Protection (EPCIP) which now mainly rotates around key resilience concepts like prevention, preparedness and response. This paper, after a short description of the most significant vectors of attacks directed towards CIIs, offers a review of the main principles of resilience and a basic scheme that should guide those stakeholders that are in the phase of studying how to effectively implement those measures in the management lifecycle of technology driven infrastructures.
Security and the performative politics of resilience: Critical infrastructure protection and humanitarian emergency preparedness

Abstract                   This article critically examines the performative politics of resilience in the context of the current UK Civil Contingencies (UKCC) agenda. It places resilience within a wider politics of (in)security that seeks to govern risk by folding uncertainty into everyday practices that plan for, pre-empt, and imagine extreme events. Moving beyond existing diagnoses of resilience based either on ecological adaptation or neoliberal governmentality, we develop a performative approach that highlights the instability, contingency, and ambiguity within attempts to govern uncertainties. This performative politics of resilience is investigated via two case studies that explore 1) critical national infrastructure protection and 2) humanitarian emergency preparedness. By drawing attention to the particularities of how resilient knowledge is performed and what it does in diverse contexts, we repoliticize resilience as an ongoing, incomplete, and potentially self-undermining discourse.
POSITIVE OBLIGATIONS AND THE INTERNATIONAL CRIMINAL TRIBUNALS’ LAW OF DETENTION: FUNDING FAMILY VISITS AND THE ICC PRESIDENCY'S NGUDJOLO DECISION

This article addresses the issue of whether the international criminal tribunals are under an obligation to fund family visits for indigent detainees. It examines the concept of positive obligations and its relation to the detention situation and describes the practice of funding family visits as it has developed at the International Criminal Court. It further analyses relevant developments in the Court's case law. It argues that the Court is indeed obliged to fund family visits. In this regard, the mere recognition of a detainee's right to family visits in the tribunals’ legal frameworks and in international soft-law penological standards can be said to inadequately reflect the particularities of international detention
Efetividade do Órgão de Solução de Controvérsias da Organização Mundial do Comércio: uma análise sobre os seus doze primeiros anos de existência e das propostas para seu aperfeiçoamento The Effectiveness of the Dispute Settlement Body of the World Trade Organization: an analysis of its first twelve years of existence and proposals for its improvement

O presente artigo tem com objetivo analisar a atuação do Órgão de Solução de Controvérsias da Organização Mundial do Comércio, entre os anos de 1995 e 2007. Trata-se de um dos principais fóruns de solução internacional de conflitos, sobretudo em função da quantidade de contenciosos, de Estados envolvidos e de valores. O texto procura destacar o cumprimento dos procedimentos previstos; a originalidade dos mecanismos de estimulo à obediência das decisões: o ganho de legitimidade do sistema com o tempo e as principais sugestões de reforma em discussão.This article analyses the performance of the Dispute Settlement Body of World Trade Organization, between 1995 and 2007. This organ is one of the most important fora for conflict resolution today, because the number of cases, states and amounts in dispute. I intend to study the fulfillment of proceedings; the originality of the mechanisms to induce compliance; the progressive legitimacy of the whole system and the main suggestions to reform it.
Space-time distributions

The space-time foliation Sigma compatible with the gravitational field g on a 4-manifold M determines a fibration pi of M, pi : M -> N is a surjective submersion over the 1-dimensional leaves space N. M is then written as a disjoint union of the leaves of Sigma, which are 3-dimensional spacelike surfaces on M.   The decomposition, TM=Sigma + T^0 M, also implies that we can define a lift of the curves on N to curves (non-spacelike) on M.   The stable causality condition M coincides with Sigma being a causal space-time distribution, generated by an exact timelike 1-form omega^0 = dt where t is some real function on M. In this case M is written as a disjoint union of a family of spacelike 3-surfaces of constant t, which cover D^+(S) of a initial 3-surface S of M.
Artificial Intelligence in Demand Forecasting and Inventory Optimization in Supply Chain and Logistics Management

In today’s dynamic and highly competitive business environment, accurate demand forecasting and efficient inventory optimization are critical components of supply chain management. Traditional forecasting methods often fail to adapt to volatile market conditions, leading to stockouts, excess inventory, and financial losses. This study explores the role of Artificial Intelligence (AI) in transforming demand forecasting and inventory optimization processes. AI-driven systems leverage machine learning, big data analytics, cloud computing, and IoT technologies to analyze structured and unstructured data, detect complex patterns, and generate real-time predictions. The study highlights the advantages of AI, including improved forecast accuracy, cost reduction, enhanced customer satisfaction, and increased operational efficiency. It also discusses challenges such as high implementation cost, data security concerns, and integration complexity. The findings emphasize that AI-enabled supply chains are more resilient, adaptive, and sustainable in the face of uncertainty.
Sentenced by an algorithm — Bias and lack of accuracy in risk-assessment software in the United States criminal justice system

Developments in artificial intelligence and machine learning have caused governments to start outsourcing authority in performing public functions to machines. Indeed, algorithmic decision-making is becoming ubiquitous, from assigning credit scores to people, to identifying the best candidates for an employment position, to ranking applicants for admission to university. Apart from the broader social, ethical and legal considerations, controversies have arisen regarding the inaccuracy of AI systems and their bias against vulnerable populations. The growing use of automated risk-assessment software in criminal sentencing is a cause for both optimism and scepticism. While these tools could potentially increase sentencing accuracy and reduce the risk of human error and bias by providing evidence-based reasons in place of ‘ad-hoc’ decisions by human beings beset with cognitive and implicit biases, they also have the potential to reinforce and exacerbate existing biases, and to undermine certain of the basic constitutional guarantees embedded in the justice system. A 2016 decision in the United States, S v Loomis, exemplifies the threat that the unchecked and unrestrained outsourcing of public power to AI systems might undermine human rights and the rule of law.
Agentic Fog: A Policy-driven Framework for Distributed Intelligence in Fog Computing

Fog and edge computing require adaptive control schemes that can handle partial observability, severe latency requirements, and dynamically changing workloads. Recent research on Agentic AI (AAI) increasingly integrates reasoning systems powered by Large Language Models; however, these tools are not applicable to infrastructure-level systems due to their high computational cost, stochastic nature, and poor formal analyzability. In this paper, a generic model, Agentic Fog (AF), is presented, in which fog nodes are represented as policy-driven autonomous agents that communicate via p2p interactions based on shared memory and localized coordination. The suggested architecture decomposes a system's goals into abstract policy guidance and formalizes decentralized fog coordination as an exact potential game. The framework is guaranteed to converge and remain stable under asynchronous updates, bounded-rational best-response dynamics, and node failures. Simulations demonstrate that the AF system achieves lower average latency and adapts more efficiently to varying demand than greedy heuristics and integer linear programming under dynamic conditions. The sensitivity analysis also demonstrates the capability to perform optimally under different memory and coordination conditions.
CCTV Cameras Surveillance, Data Protection &amp; Privacy Under International Human Rights Laws

The study aims to find out and suggest that how equilibrium among surveillance through CCTVs, right of privacy and personal data protection regime can be maintained. With the objective in mind, it discusses the CCTVs’ surveillance, its purposes, and scope of privacy in public or private domains under International Human Rights Law. It also focuses on General Data Protection Regulations, 2018 and its amplifications on CCTV surveillance.
Interlinking the human rights to water and sanitation with struggles for food and better livelihoods

Safe and secure access to drinking water and sanitation are human rights that are vital to social, economic, and environmental wellbeing. While interpretations of these rights often focus on domestic water access – for example, whether someone has sufficient drinking water – there is increasing recognition that water for health, food security and nutrition, and basic livelihood needs are inextricably linked. A progressive approach to the human rights to water needs to consider interlinked priorities around food and livelihoods.
Copyright in Generative Deep Learning

Machine-generated artworks are now part of the contemporary art scene: they are attracting significant investments and they are presented in exhibitions together with those created by human artists. These artworks are mainly based on generative deep learning techniques, which have seen a formidable development and remarkable refinement in the very recent years. Given the inherent characteristics of these techniques, a series of novel legal problems arise. In this article, we consider a set of key questions in the area of generative deep learning for the arts, including the following: is it possible to use copyrighted works as training set for generative models? How do we legally store their copies in order to perform the training process? Who (if someone) will own the copyright on the generated data? We try to answer these questions considering the law in force in both the United States of America and the European Union, and potential future alternatives. We then extend our analysis to code generation, which is an emerging area of generative deep learning. Finally, we also formulate a set of practical guidelines for artists and developers working on deep learning generated art, as well as some policy suggestions for policymakers.
Anti-corruption, Transparency and Accountability: Case Study of Healthcare in the Arab Countries

Background: The Arab states suffer from high levels of corruption. The UNDP's team there developed an approach to tackle corruption and enhance transparency and accountability in healthcare as part of its broader efforts to support the Sustainable Development Goals. This work evolved into a proper tool, the Conceptual Framework for Corruption Risk Assessment at Sectoral Level (hereafter 'Framework'), with implementation guides that enable tailoring to sector and country context.Objectives: This article documents the development of the Framework, its methodology and observed added value.Methods: Qualitative methods were utilized comprising desk research, field experience, stakeholder outreach, and focus group observation and documentation. It was most appropriate because the objective was to develop a methodology with specific characteristics.Results: The new approach uses anti-corruption as an explicit entry point to governance reforms. It articulates a structured evidence-based method to apply risk management methodology - tailored to the specificities of corruption as a risk - in healthcare whereby assessment and mitigation are (a) within institutions (b) focused on decision points and (c) around transactions while bringing together health and anti-corruption communities towards designing measurable results-oriented reforms.Conclusions: The Framework may be effective in driving concrete governance reform efforts that demonstrably reduce corruption by means of creating a common language and agenda among different stakeholders, changing the mindset towards reform, and developing targeted solutions with higher return on investment. As such, it may be capable of generating observable and sustainable progress towards healthcare reform.
THE IMPACT OF OCCUPATIONAL SAFETY AND HEALTH (OSH) TRAINING ON FOSTERING A CULTURE OF SUSTAINABILITY IN THE WORKPLACE: A CONCEPTUAL PAPER

Occupational Safety and Health (OSH) training has emerged as a key component in fostering workplace sustainability by promoting safety, health, and environmentally responsible practices. This study explores the role of OSH training in driving sustainability by examining its influence on employee awareness, behavioural change, and organizational policies. The conceptual framework developed in this paper highlights how OSH training contributes to sustainability goals through mechanisms that enhance workplace safety while aligning with environmental and social responsibility initiatives. Despite the potential benefits, challenges such as organizational resistance, resource constraints, and regulatory complexities hinder the effective integration of OSH training with sustainability. This study also discusses theoretical, practical, and policy implications, emphasizing the need for regulatory support and strategic organizational commitment. Future research should empirically validate the proposed framework through longitudinal studies, cross-industry comparisons, and qualitative investigations into employee and managerial perspectives. By embedding sustainability principles into OSH training programs, organizations can enhance employee engagement, improve compliance with sustainability standards, and foster long-term resilience. This research contributes to the growing literature on workplace sustainability by integrating safety training into broader environmental, social, and governance (ESG) strategies, offering insights for both academia and industry.
Additional file 1 of Governance of food and nutrition security in Eswatini: an analysis of government policies and reports

Additional file 1. Nutrition sensitive and nutrition specific interventions provided by the Eswatini government.
Caste System Turns into A Social Curse and Social Discrimination: A Study of Mulk Raj Anand’s Untouchable in the Perspective of Post-independence Bangladesh

The caste system roots in the heart of Hinduism and falls apart Hindus into touchable and untouchable. The sweepers are regarded as untouchables and are given no choice and access to their social life. The caste system in Hinduism and, therefore, in the Hindu-majored nation in India is a strong social discriminatory hierarchy that has been exercised for more than two millenniums. Mulk Raj Anand, with a firm belief in the dignity and equality of all human beings, attempts to project a panoramic scene of the caste system by beckoning a single day from the diary of Bakha, an untouchable boy who is a sweeper in profession. The present paper attempts to address the curse and discrimination triggered by the caste system, which is prevalent in Mulk Raj Anand’s Untouchable. Though the scenes of the novel belong to a small, interior town in Punjab, the happenings are pan-Indian in nature. This paper also argues how the caste system paves the way for inter-caste conflict and exploitation and, apart from several caste discrimination, why changing the upper caste’ outlook is the sole way out to wipe out the stigma of the caste system.
Evaluating traditional Chinese medicine using modern clinical trial design and statistical methodology: application to a randomized controlled acupuncture trial

AbstractTraditional Chinese medicine (TCM), used in China and other Asian counties for thousands of years, is increasingly utilized in Western countries. However, due to inherent differences in how Western medicine and this ancient modality are practiced, employing the so‐called Western medicine‐based gold standard research methods to evaluate TCM is challenging. This paper is a discussion of the obstacles inherent in the design and statistical analysis of clinical trials of TCM. It is based on our experience in designing and conducting a randomized controlled clinical trial of acupuncture for post‐operative dental pain control in which acupuncture was shown to be statistically and significantly better than placebo in lengthening the median survival time to rescue drug. We demonstrate here that PH assumptions in the common Cox model did not hold in that trial and that TCM trials warrant more thoughtful modeling and more sophisticated models of statistical analysis. TCM study design entails all the challenges encountered in trials of drugs, devices, and surgical procedures in the Western medicine. We present possible solutions to some but leave many issues unresolved. Copyright © 2011 John Wiley &amp; Sons, Ltd.
The quality of end of life care for Danish cancer patients who have received specialized palliative: a national survey using the Danish version of VOICES-SF

National recommendations state that Danish patients with complex palliative needs should have access to specialized palliative care but little is known about the perceived quality of this care or end of life care in general.To assess how end of life care was evaluated by the bereaved spouses and to investigate whether the perceived quality was associated with (1) quantity of specialized palliative care provided, (2) place of death, and (3) emotional state when completing the questionnaire.The bereaved spouses of 1584 cancer patients who had received specialized palliative care were invited to answer the Views Of Informal Carers - Evaluation of Services - Short Form (VOICES-SF) and the Hospital Anxiety and Depression Scale (HADS) approximately 3-9 months after the patient's death.A total of 787 (50%) of the invited spouses participated. In the last 3 months of the patient's life, the quality of all services taken together was rated as good, excellent, or outstanding in 83% of the cases and it was significantly associated with place of death (p = 0.0051, fewest considered it "fair" or "poor" if the patient died at home). In total, 93% reported that the patient died at the right place although only 74% died at the patient's preferred place. Higher levels of anxiety (p = 0.01) but not depression at the time of questionnaire completion was associated with lower satisfaction with the overall quality of care.The quality of care was rated very highly by bereaved spouses of patients receiving specialized palliative care.