ethicalabs/Research-Intent-Collab huggingface dataset:
Al-Haq position paper on issues arising from the Palestinian authority’s submission of a declaration to the Prosecutor of the International Criminal Court under Article 12(3) of the Rome Statute

In early 2009 the Palestinian Authority submitted a declaration under Article 12(3) of the Rome Statute recognizing the jurisdiction of the International Criminal Court ‘for the purpose of identifying, prosecuting and judging the authors and accomplices of acts committed on the territory of Palestine since 1 July 2002.’ In the first instance this paper argues that whereas the existence or otherwise of a state of Palestine remains moot at best for the purpose of international law and international relations broadly speaking, a compelling argument can be made that for the purposes of the Statute only, a determination by the Court that Palestine is a state that can engage with the Court would be valid and in line with the Court and the Statute’s statutory requirements. The paper, drawing on the criteria being relied upon by the Office of the Prosecutor in order to decide whether the PA, as an institution established by the PLO, has the necessary ‘capacity’ to transfer its jurisdiction to the Court, then addresses the extent of the PA’s jurisdiction over international crimes. It demonstrates that the PA can legitimately prosecute individuals responsible for crimes within the jurisdiction of the ICC regardless of the nationality of the individuals concerned and that the PA has the ability to enter into international agreements. It concludes by asserting that the ICC may validly consider Palestine to be a state for the purposes of Article 12(3) of the Rome Statute and may accept the transfer of jurisdiction from the PA to the Court in line with the Statute and the principles of international law
The State Duty to Protect from Business-Related Human Rights Violations in Water and Sanitation Services: Regulatory and BITs Implications

Fil: Martin, Liber Alexis. Universidad Nacional de Cuyo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina
Development of the Buckland Park Cosmic Ray Air Shower Array for Ultra High Energy Gamma Ray Astronomy

AbstractThe Buckland Park air shower array is being developed particularly for use as an ultra-high-energy gamma ray astronomy telescope. The properties of this instrument are described with an emphasis on improvements being made to its angular resolution. Some early data are presented to illustrate the way in which the data obtained will be used.
State-dependent Delay Differential Equations on $H^1$

Classically, solution theories for state-dependent delay equations are developed in spaces of continuous or continuously differentiable functions. The former can be technically challenging to apply in as much as suitably Lipschitz continuous extensions of mappings onto the space of continuous functions are required; whereas the latter approach leads to restrictions on the class of initial pre-histories. Here, we establish a solution theory for state-dependent delay equations for arbitrary Lipschitz continuous pre-histories and suitably Lipschitz continuous right-hand sides on the Sobolev space $H^1$. The provided solution theory is independent of previous ones and is based on the contraction mapping principle on exponentially weighted spaces. In particular, initial pre-histories are not required to belong to solution manifolds and the generality of the approach permits the consideration of a large class of functional differential equations even for which the continuity of the right-hand side has constraints on the derivative.
Physiological and Transcriptomic Analyses Reveal the Response of Medicinal Plant Bletilla striata (Thunb. ex A. Murray) Rchb. f. via Regulating Genes Involved in the ABA Signaling Pathway, Photosynthesis, and ROS Scavenging under Drought Stress

Bletilla striata is a valuable Chinese herbal medicinal plant widely used in various fields. To meet the market demand for this herb, the tissue culture technology of B. striata was developed. However, drought stress has been a significant threat to the survival of cultivated B. striata. To further understand the underlying mechanisms of B. striata under drought stress, its response was investigated at the physiological and transcriptional levels. Our photosynthesis results show that the decline of the net photosynthesis rate (Pn) in B. striata leaves was mainly caused by nonstomatal limitation factors. Using transcriptomic analysis 2398, differentially expressed genes (DEGs) were identified. KEGG enrichment analysis showed that DEGs involved in plant hormone signal transduction (ko04075) were significantly altered, especially the abscisic-acid signaling pathway. The up-regulations of the serine/threonine protein kinase (SnRK2) and S-type anion (SLAH2) channels might lead to stomatal closure, which is the reason for decline of photosynthesis. Moreover, the downregulation of cytochrome b6 and photosystem I reaction center subunit III/IV might be the major reason for nonstomatal limitation. In addition, B. striata enhanced the ability of ROS scavenging via activating the gene expression of superoxide dismutase, catalase, and peroxidase in response to drought stress. Our study enhanced the understanding of B. striata in response to drought stress.
INTERNET OF THINGS IN SPORTS: SECURITY OF SENSOR NETWORKS FOR HEALTH MONITORING

The article addresses the problem of ensuring the security of sensor networks used for athlete health monitoring within Internet of Things (IoT) ecosystems. It is demonstrated that the digitalisation of sports and the widespread adoption of wearable sensing devices connected to mobile gateways and cloud platforms create a new class of risks related to the confidentiality, integrity, and availability of biometric data. Based on an analysis of international standards and recommendations, including NIST SP 800-213/213A, ENISA guidelines, and ISO/IEC 27001, as well as contemporary research on sports IoT technologies, eHealth, BLE security, and authentication in IoT-enabled healthcare, a conceptual multi-layer security model for sports IoT systems is developed. The proposed approach distinguishes sensor, gateway, server, and application layers, each characterised by its functional role, typical threats, and specific mitigation mechanisms that take into account device resource constraints and real-time operational requirements. At the sensor layer, the study substantiates the use of energy-efficient cryptographic algorithms, BLE LE Secure Connections mode, secure boot, signed OTA firmware updates, and hardware security modules such as Secure Elements for protected key storage. At the gateway layer, the use of MQTT and HTTPS over TLS 1.3, mutual authentication (mTLS), as well as the implementation of edge analytics and on-device AI, is examined to reduce the volume of raw data transmitted and to enhance privacy. The server layer is described as a domain of scalable analytics and identity management, where data-at-rest encryption, centralised key management, short-lived and rotation-enabled JWT tokens, and key revocation mechanisms are applied. At the application layer, a role-based access model for physicians, coaches, analysts, and administrative personnel is proposed, along with multi-factor authentication, protected audit logging, and controlled firmware updates via Signed OTA. Particular attention is given to the confidentiality of geolocation data, the use of pseudonymisation and coordinate coarsening, as well as ethical and legal aspects of processing athletes’ biometric information. The results show that the proposed model can serve as a methodological foundation for designing, auditing, and standardising digital solutions in both professional and recreational sports, including the development of internal security policies in clubs and sports federations. The integration of technical, organisational, and regulatory measures, complemented by mechanisms for validating the reliability of AI-generated decisions and limiting the autonomy of algorithmic outputs, is identified as a prerequisite for building a robust, trustworthy, and resilient health monitoring ecosystem in sports based on the Internet of Things.
An exploration of the synergies between Six Sigma, total quality management, lean construction and sustainable construction

There have been many calls for the UK construction industry to improve its productivity and performance in order to exceed clients' ever-growing expectations and needs (DTI, 2003). One obstacle to achieving the required improvement has been the construction industry's reluctance to learn from other industries, hence causing time lags between the development of new technologies and management techniques, and their implementation within construction. Recent years have seen the wide acceptance of Total Quality Management and the emergence of Six Sigma in some industries. This paper examines the Six Sigma philosophy and investigates its potential application in construction by exploring the synergies that exists among Six Sigma, Total Quality Management (TQM), Lean Construction, and Sustainable Construction.
The Legal Basis for the Exercise of Jurisdiction by the International Criminal Court and the Preparatory Work of the Rome Statute (Ⅰ)

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Retracted: Efficient Multi-User Computation Offloading and Reducing Latency in Mobile-Edge Computing for IoT Applications

Mobile Edge Computing (MEC) is an inventive paradigm for computing that has the potential to notably diminish latency and energy consumption by transferring computationally demanding jobs to edge clouds near intelligent mobile users. This investigation aims to reduce offloading and latency between multiple users and edge computing in the context of Internet of Things (IoT) applications in the fifth generation (5G) by utilizing an optimization algorithm called the Bald Eagle Search Optimization Algorithm. Although employing deep learning methods might increase time consumption and computational complexity, an edge computing system enables devices to transfer their demanding jobs to edge servers, decreasing latency and conserving energy. The Bald Eagle Algorithm (BES) is an advanced optimization algorithm inspired by eagle hunting strategies and consists of select, search, and swoop stages. A resource estimation stage is introduced to select the most suitable resources to enhance the BES algorithm further. By transferring the most appropriate Internet of Things subtasks to edge servers, the edge system minimizes the anticipated execution time. To attain rapid and nearly optimal IoT device performance, a Bald Eagle Search Optimization Algorithm is suggested based on multiuser offloading. Edge computing effectively diminishes latency, surmounting the limitations of cloud-based processing. The BES algorithm outperforms existing methods, such as Deep-Q-Network (DQN) and Deep Deterministic Policy Gradient (DDPG), to lessen offloading latency. Finally, simulations are carried out to exhibit the attained power efficiency and stability by mitigating offloading latency.
AI-Based Database Index Optimization Model for Intelligent Query Performance Enhancement in Relational Database Systems

Efficient query processing is a fundamental requirement in relational database management systems (RDBMS), particularly in large-scale enterprise and cloud environments. Database indexing plays a crucial role in improving query performance; however, traditional index tuning methods rely heavily on manual intervention and static heuristics, which are inefficient for dynamic workloads. This paper proposes an AI-Based Database Index Optimization Model (AIDIOM) that leverages machine learning and reinforcement learning to automatically generate, evaluate, and optimize database indexes. The system continuously monitors workload patterns, extracts query features, predicts index utility using supervised learning models, and refines decisions using reinforcement learning feedback. Experimental evaluation using standard benchmarks such as TPC-H demonstrates significant improvements in query execution time, throughput, and resource utilization compared to traditional indexing methods. The results confirm that AI-driven index optimization provides a scalable and adaptive solution for modern database systems.
Epistemologia coletiva: crença, justificação e conhecimento de grupo = Collective epistemology: group belief, justification and knowledge

Neste artigo iremos sistematizar os conceitos-chave da chamada epistemologia coletiva, apontando as diferentes teorias que explicam nossa prática de atribuição de estados cognitivos (tais como crença, justificação e/ou conhecimento) a grupos. Na introdução levantaremos o problema central que motiva a área, a saber: a atribuição de estados cognitivos a grupos tem como referente o grupo enquanto grupo ou os indivíduos que o compõe? Na primeira seção apresentaremos os melhores argumentos em favor do individualismo, aqueles que defendem que as atribuições se reduzem aos indivíduos. Na segunda, terceira e quarta seções apresentaremos modelos coletivistas, que defendem uma certa autonomia do grupo frente aos indivíduos, o conjunto de membros que o compõe. Na quinta e sexta seções apresentaremoscomo modelos coletivistas explicam a atribuição de justificação e conhecimento a grupos. Nós concluímos notando que os ataques coletivistas ao individualismo são bastante efetivos, fazendo com que essa abordagem seja difícil de sustentar, e apontando outros elementos que são necessários para a construção de um modelo coletivista completo
Contexts in a paper recommendation system with collaborative filtering

Making personalized paper recommendations to users in an educational domain is not a trivial task of simply matching users’ interests with a paper topic. Therefore, we proposed a context-aware multidimensional paper recommendation system that considers additional user and paper features. Earlier experiments on experienced graduate students demonstrated the significance of this approach using modified collaborative filtering techniques. However, two key issues remain: (1) How would the modified filtering perform when target users are inexperienced undergraduate students who have a different pedagogical background and contextual information-seeking goals, such as task- and course-related goals, from those of graduate students?; (2) Should we combine graduates and undergraduates in the same pool, or should we separate them? We conducted two studies aimed at addressing these issues and they showed that (1) the system can be effectively used for inexperienced learners; (2) recommendations are less effective for different learning groups (with different pedagogical features and learning goals) than they are for the same learning groups. Based on the results obtained from these studies, we suggest several context-aware filtering techniques for different learning scenarios.&lt;br /&gt;&lt;br /&gt;
Predicting plasma profiles following oral dosing for drug liver transporter substrates using physiologically based pharmacokinetic modeling

The aim of this work was to assess the prediction of oral plasma profiles utilizing a previously developed physiologically based pharmacokinetic (PBPK) approach using in vitro sandwich cultured hepatocytes (SCHH) to predict intravenous plasma profiles for seven liver transporter substrates (Jones et al., 2012).                   Utilizing physicochemical, in vitro passive permeability and solubility inputs, descriptors of oral absorption were predicted using a physiologically based gastrointestinal tract model. These inputs were then incorporated into the published transporter PBPK model with a single compartment for oral absorption.                   The validity of these absorption predictions were shown to be satisfactory when assessed by combining them with the transporter parameters obtained from fitting the intravenous plasma data. Prospective predictions based on SCHH utilizing scaling factors developed in the literature and predicted oral absorption parameters were performed as a test of both aspects in predicting oral plasma time course. The average fold errors for the seven compounds increased somewhat to 2.5, 3.3, and 2.4, respectively.                   An early prediction method has been developed using physicochemical and in vitro inputs to estimate plasma profiles and pharmacokinetic parameters for intravenous and oral dosing drugs that are substrates for liver transporters.
Designing and Implementing a Customer Data Platform (CDP) for Omnichannel Businesses in the Fashion Industry: A Strategic Framework

The fashion industry is experiencing significant transformation driven by rapidly changing trends and consumer preferences. Customers, equipped with smartphones and numerous options, require personalized and consistent experiences across all touchpoints. This paper examines the implementation of a Customer Data Platform (CDP) designed for omnichannel businesses in this dynamic sector. It not only outlines a technical solution but also develops a strategic framework. This study examines fundamental challenges, including isolated data, transient trends, and the nuanced equilibrium of personalization versus privacy. We suggest a phased implementation strategy. We prioritize the activation of data to establish authentic connections with customers, enhance loyalty, and improve financial performance in a highly competitive market. A specific instance comes to mind in which a small boutique effectively employed a basic version of this approach. The application of data, when combined with human insight, demonstrates significant potential. This encapsulates our broader objectives.
In-Situ TEM Electrochemistry of Anode Materials in Lithium-Ion Batteries

Abstract not Available.
State Building Interventions in Post Cold War Period: A Critique of ‘Responsibility to Protect’ and ‘Humanitarianism’

This paper explores the concepts of humanitarianism and responsibility to protect, which have most influentially guided state building interventions in the post Cold War period. With more than fifty states intervened in the guise of ‘responsibility to protect,’ this paper attempts to analyze why interventionist state building has developed as a major concern for the international state system. It further delves into the impacts of such interventionist rationale on the nature and functioning of the international state system. This paper argues the rise of sovereignty as responsibility and humanitarianism challenged the inviolable sovereignty of states by making it conditional on the government’s exercise of monopoly over violence within its territory and extension of protection to its citizens against war, crimes, violence and bloodshed. The paper further argues that the selective application of the principle of human security and non-intervention by major powers in crucial conflicts makes the moral ground of this principle very dubious. It also highlights that in post 9/11 period, the mixed successes of these concepts in practice, resulting form a large number of political, institutional and operational challenges, underlie the need to use non-military diplomatic, political and economic means for conflict resolution.
Use of high throughput sequencing to observe genome dynamics at a single cell level

With the development of high throughput sequencing technology, it becomes possible to directly analyze mutation distribution in a genome-wide fashion, dissociating mutation rate measurements from the traditional underlying assumptions. Here, we sequenced several genomes of Escherichia coli from colonies obtained after chemical mutagenesis and observed a strikingly nonrandom distribution of the induced mutations. These include long stretches of exclusively G to A or C to T transitions along the genome and orders of magnitude intra- and inter-genomic differences in mutation density. Whereas most of these observations can be explained by the known features of enzymatic processes, the others could reflect stochasticity in the molecular processes at the single-cell level. Our results demonstrate how analysis of the molecular records left in the genomes of the descendants of an individual mutagenized cell allows for genome-scale observations of fixation and segregation of mutations, as well as recombination events, in the single genome of their progenitor.
Experimental adaptive on‐line optimization of cellular productivity of a continuous bakers' yeast culture

AbstractAn adaptive on‐line optimization method that utilizes dynamic model identification has been applied to maximize the cellular productivity of a continuous bakers' yeast culture. Experiments were conducted on a sophisticated computerized fermentation system. Experimental results show that the adaptive on‐line optimization method requires very little a priori information, is easy to implement, converges quickly, adapts to changes in the process, and is stable even when operational difficulties are encountered.
Data driven theory for knowledge discovery in the exact sciences with applications to thermonuclear fusion

AbstractIn recent years, the techniques of the exact sciences have been applied to the analysis of increasingly complex and non-linear systems. The related uncertainties and the large amounts of data available have progressively shown the limits of the traditional hypothesis driven methods, based on first principle theories. Therefore, a new approach of data driven theory formulation has been developed. It is based on the manipulation of symbols with genetic computing and it is meant to complement traditional procedures, by exploring large datasets to find the most suitable mathematical models to interpret them. The paper reports on the vast amounts of numerical tests that have shown the potential of the new techniques to provide very useful insights in various studies, ranging from the formulation of scaling laws to the original identification of the most appropriate dimensionless variables to investigate a given system. The application to some of the most complex experiments in physics, in particular thermonuclear plasmas, has proved the capability of the methodology to address real problems, even highly nonlinear and practically important ones such as catastrophic instabilities. The proposed tools are therefore being increasingly used in various fields of science and they constitute a very good set of techniques to bridge the gap between experiments, traditional data analysis and theory formulation.
Diffusion models for Handwriting Generation

17 figures, 17 pages
Generative Artificial Intelligence and Introductory Programming Education at Universities: Content, Assignments, Assessment

This paper briefly outlines the content, tasks and methodology of teaching programming in introductory university subjects, traditionally used teaching tools, systems and methods of assessment. It then describes how generative artificial intelligence (GenAI) can be used to improve programming teaching and learning in introductory university courses. The following themes are reviewed: content and assignments of introductory programming courses, learning tools, assessment systems and methods, advancing learning with GenAI, formative assessment with GenAI. Particular attention is paid to formative assessment, the main goal of which is to help the student quickly and efficiently learn from their mistakes. To provide good feedback, special pre-prompts have to be developed to ensure GenAI's responses are accurate, helpful, friendly, and educational.