ethicalabs/Research-Intent-Collab huggingface dataset:
Assessing The Jurisdictional Legitimacy of International Criminal Court (ICC) in Arresting Head of State from Non-Party States to The Rome Statute (Case Study: The Problematics of Arresting Benjamin Netanyahu)

The issuance of an arrest warrant by the ICC for Israel Prime Minister Benjamin Netanyahu presents a fundamental juridical problem, given Israel's status as a non-State Party and Netanyahu's status as an active head of state. This research aims to (1) analyze the legal basis and legitimacy of the ICC's jurisdiction, and (2) analyze the resolution of the legal antinomy between the ICC's authority (Article 27) and the doctrine of head of state immunity (Customary International Law). This study employs a normative juridical methodology, utilizing statute, case, and conceptual approaches. The analysis reveals that the ICC's jurisdiction is legally valid, as it is not based on the perpetrator's nationality (ratione personae), but on the territorial delegation of jurisdiction (ratione loci) by Palestine as a State Party (Article 12(2)(a)), a basis confirmed by the 2021 Pre-Trial Chamber I decision. Furthermore, the study finds that the legal antinomy regarding immunity is resolved in favor of international criminal law. Head of state immunity (immunity ratione personae), rooted in the par in parem non habet imperium principle and the ICJ's 2002 Arrest Warrant case, is found to be inapplicable in the vertical relationship vis-à-vis an international court. This resolution is supported by Paragraph 61 of the Arrest Warrant decision itself and the ICC Appeals Chamber's 2019 judgment in the Al-Bashir (Jordan Referral) case. Thus, Article 27 (irrelevance of official capacity) prevails, and the ICC's legal basis for the arrest warrant is sound.
Projecting the response of the Greenland ice sheet to future climate change with the ice sheet model SICOPOLIS

Numerical modelling has become established as an important tool for understanding ice sheet dynamics in general, and in particular for assessing the contribution of the Greenland and Antarctic ice sheets to future sea level change under global warming conditions. In this paper, we review related work carried out with the ice sheet model SICOPOLIS (SImulation COde for POLythermal Ice Sheets). As part of a group of eight models, it was applied to a set of standardised experiments for the Greenland ice sheet defined by the SeaRISE (Sea-level Response to Ice Sheet Evolution) initiative. A main finding of SeaRISE was that, if climate change continues unabatedly, the ice sheet may experience a significant decay over the next centuries. However, the spread of results across different models was very large, mainly because of differences in the applied initialisation methods and surface mass balance schemes. Therefore, the new initiative ISMIP6 (Ice Sheet Modeling Intercomparison Project for CMIP6) was launched. An early sub-project is InitMIP-Greenland, within which we showed that two different initialisations computed with SICOPOLIS lead indeed to large differences in the simulated response to schematic future climate scenarios. Further work within ISMIP6 will thus focus on improved initialisation techniques. Based on this, refined future climate simulations for the Greenland ice sheet, driven by forcings derived from AOGCM (atmosphere-ocean general circulation model) simulations, will be carried out. The goal of ISMIP6 is to provide significantly improved estimates of ice sheet contribution to sea level rise in the coming years.
Dynamically Error-Corrected Gates for Universal Quantum Computation

Scalable quantum computation in realistic devices requires that precise control can be implemented efficiently in the presence of decoherence and operational errors. We propose a general constructive procedure for designing robust unitary gates on an open quantum system without encoding or measurement overhead. Our results allow for a low-level error correction strategy solely based on Hamiltonian engineering using realistic bounded-strength controls and may substantially reduce implementation requirements for fault-tolerant quantum computing architectures.
Biased Generalization in Diffusion Models

Generalization in generative modeling is defined as the ability to learn an underlying distribution from a finite dataset and produce novel samples, with evaluation largely driven by held-out performance and perceived sample quality. In practice, training is often stopped at the minimum of the test loss, taken as an operational indicator of generalization. We challenge this viewpoint by identifying a phase of biased generalization during training, in which the model continues to decrease the test loss while favoring samples with anomalously high proximity to training data. By training the same network on two disjoint datasets and comparing the mutual distances of generated samples and their similarity to training data, we introduce a quantitative measure of bias and demonstrate its presence on real images. We then study the mechanism of bias, using a controlled hierarchical data model where access to exact scores and ground-truth statistics allows us to precisely characterize its onset. We attribute this phenomenon to the sequential nature of feature learning in deep networks, where coarse structure is learned early in a data-independent manner, while finer features are resolved later in a way that increasingly depends on individual training samples. Our results show that early stopping at the test loss minimum, while optimal under standard generalization criteria, may be insufficient for privacy-critical applications.
Empirical study on the evolution of telecom fraud risks driven by artificial intelligence generated content

The application of knowledge graph and eventic graph technologies in the empirical study of telecom fraud cases driven by artificial intelligence generated content (AIGC) allows for a more intuitive tracing of the evolution of risks during the victimization process, which is of great significance for countering and early warning of new types of telecom fraud. Based on data from telecom fraud cases implemented using AIGC, semantic role labeling and dependency parsing were firstly performed during data preprocessing. Then, event element recognition and event relationship extraction were constructed to construct knowledge graphs and eventic graphs of the cases. Finally, the key stages and patterns of the evolution of telecom fraud risks were analyzed by combining mathematical statistics with graph technologies. The research revealed that, suspects using AIGC were able to more effectively exploit the phenomenon of confirmation bias to gain the victim’s trust. The evolution patterns of telecom fraud risks driven by AIGC were categorized into three types: the long-chain type evolution pattern systematically identifies complete risk events and their inter-event evolutionary trajectories within cases, while investigation of the star-shaped and composite type evolution patterns enable recognition of divergent risk behavioral patterns and localization of core risk event nodes across homogeneous case clusters, there by establishing a theoretical foundation for developing scientifically rational governance strategies in telecom fraud countermeasures.
Could the Road from Arusha Lead to London?: The Possible Role of the African Court of Human and Peoples’ Rights in Advancing Corporate Climate Accountability Efforts

Völkerrechtsblog
Transverse Beam Dynamics In Circular Particle Accelerators For High Energy Physics

Abstract                   Classical and superconducting magnets and conventional and superconductive high frequency cavities are the basic elements in any circular accelerator and collider. The magnets determine the particle or beam behaviour in the transverse plane, the cavities in the longitudinal. Specific beam oscillations, related to the interplay of both transverse and longitudinal phenomena, will not be considered. Since we are mainly interested in the quality and requirements on superconducting accelerator magnets, a short introduction to transverse beam dynamics and beam optics will be given. The success of any accelerator or collider for high energy physics will, among others, depend on a close harmonization and mutual matching between transverse beam dynamics requirements and the superconducting magnet performances from the design stage to the completion and operation of the accelerator.
Sequencing to Mitigate Catastrophic Forgetting in Continual Learning

To cope with real-world dynamics, an intelligent system needs to incrementally acquire, update, and exploit knowledge throughout its lifetime. This ability, known as Continual learning, provides a foundation for AI systems to develop themselves adaptively. Catastrophic forgetting is a major challenge to the progress of Continual Learning approaches, where learning a new task usually results in a dramatic performance drop on previously learned ones. Many approaches have emerged to counteract the impact of CF. Most of the proposed approaches can be categorized into five classes: replay-based, regularization-based, optimization-based, representation-based, and architecture-based. In this work, we approach the problem from a different angle, specifically by considering the optimal sequencing of tasks as they are presented to the model. We investigate the role of task sequencing in mitigating CF and propose a method for determining the optimal task order. The proposed method leverages zero-shot scoring algorithms inspired by neural architecture search (NAS). Results demonstrate that intelligent task sequencing can substantially reduce CF. Moreover, when combined with traditional continual learning strategies, sequencing offers enhanced performance and robustness against forgetting. Additionally, the presented approaches can find applications in other fields, such as curriculum learning.
ERA: A Dataset and Deep Learning Benchmark for Event Recognition in Aerial Videos

IEEE Geoscience and Remote Sensing Magazine. Project page: https://lcmou.github.io/ERA_Dataset/
Implementing the Provisions of the Rome Statute of the International Criminal Court in the National Legislation of European States

The process of implementation of the Rome Statute of the International Criminal Court into the national legislation of some European states is studied. It was analyzed that the implementation of the Rome Statute is one of the conditions for the proper implementation of certain rights and freedoms of a citizen, namely the right to judicial protection, etc. This is the organizational and legal activity of the state in the person of authorized subjects, which is carried out in a legally defined manner and consists of legal and other procedures aimed at ensuring the exercise of the jurisdiction of the ICC over persons responsible for particularly serious crimes in accordance with the definitions of the Rome e Statute.It is emphasized that the methods of implementation of the Rome Statute in the practice of foreign countries are determined by the following main approaches: 1) the adoption of a legislative act aimed at implementation, which will have priority over national laws and other legal acts in the event of contradictions regarding the jurisdiction of the ICC; 2) introduction of changes and additions to the constitution and other regulatory legal acts; 3) introduction of changes and additions to the relevant legislative acts, which is accompanied by the adoption of special legislation on cooperation with the ISS.The characteristic principles of the implementation of the Rome Statute and the recognition of the jurisdiction of the ICC, which arise from their legal nature and the peculiarities of the national legal system, are singled out and include: the principle of complementarity of the ICC with the national judicial system; “ne bis in idem”; the principle of non-extradition of one’s citizens; pardon; immunities of officials, etc. The Court’s jurisdiction’s contractual nature indicates that states’ right to administer justice under national law is primary.It has been considered which methods of ratification used by European states are effective, based on which it is possible to single out the most convenient and effective way of ratification of the Rome Statute by Ukraine.
Introduction of central bank digital currency – necessary legislative amendments

orges Bank has been running a central bank digital currency project since 2016. The project is now in its fourth phase, and as part of this phase an overview will be provided of required legislative amendments linked to the introduction of CBDC. For an overview of Norges Bank’s CBDC project, please see the web page on central bank digital currency (https://www.norges-bank.no/en/topics/financial-stability/central-bank-digital-currency/). This memo assesses the legislative amendments that are expected to be required in order to introduce CBDC.
Political Parties' Annual Accounts and the Impact of the Group of States against Corruption in 18 European States: Towards Enhanced Transparency?

Abstract This article investigates the impact of the Third Evaluation Round of the Group of States against Corruption (GRECO) on party finance laws in 18 Northern, Western, and Southern European states. It particularly focuses on the transparency stipulations regarding political parties' annual accounts. Five indicators are analyzed: (1) the obligation of parties to submit their accounts, (2) the availability of a standardized form, (3) the obligation to make the accounts public, (4) the independence of the auditor, and (5) the independence of the monitoring body. On the basis of this analysis, a global transparency score is calculated, allowing us to assess the impact of GRECO. Our study shows that GRECO had a significant impact: the legal frameworks of a large number of countries have been amended, in the sense that the level of transparency regarding the parties' accounts has considerably improved.
MASTER of the Cosmic Microwave Background Anisotropy Power Spectrum: A Fast Method for Statistical Analysis of Large and Complex Cosmic Microwave Background Data Sets

We describe a fast and accurate method for estimation of the cosmic microwave background (CMB) anisotropy angular power spectrum—Monte Carlo Apodized Spherical Transform Estimator (MASTER). Originally devised for use in the interpretation of the BOOMERANG experimental data, MASTER is both a computationally efficient method suitable for use with the currently available CMB data sets (already large in size, despite covering small fractions of the sky, and affected by inhomogeneous and correlated noise) and a very promising application for the analysis of very large future CMB satellite mission products.
Social Isolation, Social Media Use, and the Adolescent Mental Health Crisis: Exploring the Interaction of Risk Factors on Depression

Background                     Adolescence is a critical developmental period. Unfortunately, the US Surgeon General, Vivek Murthy, has declared teen mental health as a state of emergency. During this time, social connections and peer interactions play a crucial role in adolescent well-being.                                                           Methods                     In order to investigate potential risk factors for adolescent mental health outcomes such as depression, we ran hierarchical multiple regression models to explore the potential significant associations between both social media use and social isolation on depression symptoms. This was a cross-sectional study employing a large sample of teens from urban and rural schools across Southern Idaho (n=8,407 mean age=14.6). We then ran an interaction model to determine a potential interaction effect between social isolation and social media use on depression.                                                           Results                     We found that both social media use and social isolation were significantly associated with depression outcomes. Social isolation had a larger effect, accounting for a difference of 4.84 in depression scores for every one unit change in social isolation (p&lt;0.001). The interaction effect was significant.                                                           Discussion                     Although it is common for adults to point to social media use as a main risk factor for teen depression, experiencing social isolation poses greater risk. Additionally, findings suggest that the impact of social media use on depression depends on an adolescent’s level of social isolation.                                                           Conclusion                     Professionals who want to ameliorate the teen mental health crisis may need to focus attention on increasing social connection for adolescents they serve.
Essential but expensive? The World Health Organization, access to medicines and human rights

Now widely accepted as a component of the international human rights framework, the concept of access to medicines nonetheless continues to generate controversial questions as to its scope and application. Through critical analysis of relevant documentary materials, this article seeks to explore the conjunction between human rights and the list of essential medicines compiled biennially by the World Health Organization in the particular context of the recent expansion of this list to embrace a number of very costly medical interventions. Such extension is intended to stimulate access in the long run, but the expense of such medicines may limit accessibility in the short term, as governments struggling to ensure the sustainability of health systems choose to allocate finite resources elsewhere. This article therefore examines the compatibility of limitations to access on grounds of unaffordability, with international human rights obligations. It focuses especially upon Article 12 of the International Covenant on Economic, Social and Cultural Rights but also considers other human rights which may be engaged.
Combining Public Health Education and Disease Ecology Research: Using Citizen Science to Assess Chagas Disease Entomological Risk in Texas

Chagas disease is a zoonotic parasitic disease well-documented throughout the Americas and transmitted primarily by triatomine 'kissing bug' vectors. In acknowledgment of the successful history of vector control programs based on community participation across Latin America, we used a citizen science approach to gain novel insight into the geographic distribution, seasonal activity, and Trypanosoma cruzi infection prevalence of kissing bugs in Texas while empowering the public with information about Chagas disease.We accepted submissions of kissing bugs encountered by the public in Texas and other states from 2013-2014 while providing educational literature about Chagas disease. In the laboratory, kissing bugs were identified to species, dissected, and tested for T. cruzi infection. A total of 1,980 triatomines were submitted to the program comprised of at least seven species, of which T. gerstaeckeri and T. sanguisuga were the most abundant (85.7% of submissions). Triatomines were most commonly collected from dog kennels and outdoor patios; Overall, 10.5% of triatomines were collected from inside the home. Triatomines were submitted from across Texas, including many counties which were not previously known to harbor kissing bugs. Kissing bugs were captured primarily throughout April-October, and peak activity occurred in June-July. Emails to our dedicated account regarding kissing bugs were more frequent in the summer months (June-August) than the rest of the year. We detected T. cruzi in 63.3% of tested bugs.Citizen science is an efficient approach for generating data on the distribution, phenology, and infection prevalence of kissing bugs-vectors of the Chagas disease parasite-while educating the public and medical community.
Night-sky brightness monitoring in Hong Kong - a city-wide light pollution assessment

Results of the first comprehensive light pollution survey in Hong Kong are presented. The night-sky brightness was measured and monitored around the city using a portable light sensing device called the Sky Quality Meter over a 15-month period beginning in March 2008. A total of 1,957 data sets were taken at 199 distinct locations, including urban and rural sites covering all 18 Administrative Districts of Hong Kong. The survey shows that the environmental light pollution problem in Hong Kong is severe - the urban night-skies (sky brightness at 15.0 mag per arcsec square) are on average ~100 times brighter than at the darkest rural sites (20.1 mag per arcsec square), indicating that the high lighting densities in the densely populated residential and commercial areas lead to light pollution. In the worst polluted urban location studied, the night-sky at 13.2 mag per arcsec square can be over 500 times brighter than the darkest sites in Hong Kong. The observed night-sky brightness is found to be affected by human factors such as land utilization and population density of the observation sites, together with meteorological and/or environmental factors. Moreover, earlier night-skies (at 9:30pm local time) are generally brighter than later time (at 11:30pm), which can be attributed to some public and commercial lightings being turned off later at night. On the other hand, no concrete relationship between the observed sky brightness and air pollutant concentrations could be established with the limited survey sampling. Results from this survey will serve as an important database for the public to assess whether new rules and regulations are necessary to control the use of outdoor lightings in Hong Kong.
An Empirical Study of the Accuracy and Completeness of Large Language Model(LLM)-Generated Privacy Notices under the European General Data Protection Regulation (GDPR)

As Large Language Models (LLMs) become more integrated into software development workflows, balancing rapid code deployment with strict privacy regulations, such as the General Data Protection Regulation (GDPR), remains a significant challenge. The existing literature reveals a notable gap in understanding the relationship between LLM use and the generation of compliant privacy notices. This study presents a systematic empirical evaluation of three frontier LLMs: ChatGPT, Claude, and Gemini, to assess their ability to generate GDPR-compliant privacy notices. Specifically, the study investigates: (1) the extent to which frontier LLMs produce GDPR-compliant privacy notices; (2) comparative performance differences among frontier LLMs in terms of GDPR compliance; (3) the impact of prompt personas on accuracy and completeness; and (4) the potential legal implications of relying on LLM-generated privacy notices. Performance was evaluated using sentence-transformer-based semantic similarity analysis to measure accuracy, alongside a point-based grading rubric grounded in GDPR Articles 13 and 14 to assess completeness. The results indicate that ChatGPT demonstrates the highest level of compliance, particularly with GPT-5, while Claude and Gemini exhibit notable deficiencies in completeness and reliability.A key limitation of this study is the exclusion of GDPR Article 12 (transparency), due to its inherently subjective nature. Consequently, while high completeness scores were observed, the findings do not fully capture all dimensions of GDPR compliance. Future work is needed to develop robust methodologies for evaluating transparency and to assess whether LLM-generated privacy notices can meet the full spectrum of regulatory requirements.