ethicalabs/Research-Intent-Collab huggingface dataset:
Legal harmonisation of Ukraine with European Union law: institutional and normative analysis of the implementation of 33 chapters of the acquis communautaire

In the context of Ukraine obtaining candidate status for membership in the European Union, the legal harmonisation of national legislation with the acquis communautaire has become particularly relevant. Given the institutional challenges, martial law, and complex geopolitical conditions, a comprehensive analysis of Ukraine’s progress in fulfilling its legal obligations within the framework of European integration is essential. Special attention is paid to both normative reforms and the actual steps toward legal implementation of EU standards across all 33 technical chapters of the acquis.  The purpose of the article is to conduct a systemic institutional and normative analysis of Ukraine’s implementation of the acquis communautaire based on the European Commission’s reports for 2023 and 2024, with a focus on legal adaptation mechanisms, institutional transformations, and the substantive dimension of legal approximation to EU law.  The research uses a comparative legal method, which made it possible to compare the state of acquis implementation over two consecutive periods. In addition, a normative-analytical approach was applied to assess the content of legislative changes in Ukraine and their compliance with the core requirements of EU law. The novelty of the study lies in its integrated legal analysis not only of the content of national reforms but also of the dynamics of institutional capacity-building for acquis implementation.  The study found that the most significant progress was achieved in the fields of public procurement, energy, competition, justice, customs policy, and common security policy. In many cases, the implementation of EU law has taken place not only at the legislative level but also through subordinate regulations, administrative instructions, and the establishment of specialised bodies. Meanwhile, such areas as the free movement of workers and capital, and regional policy demonstrate slower harmonisation due to legal and institutional barriers. The analysis confirms that Ukraine has transitioned from political declarations to the legally binding adaptation of the acquis, enhancing its readiness for accession negotiations.  In conclusion, the article argues that the success of Ukraine’s further legal approximation to the EU depends significantly on its ability to ensure sustainable implementation, effective institutional oversight, and the development of administrative and judicial review mechanisms. It is proposed that legal harmonisation be viewed not merely as a formal accession requirement but as a tool for deep transformation of public governance, rule of law, and the legal state in Ukraine.
All-optical Sudoku solver with photonic spiking neural network

Abstract   We proposed a Sudoku solver based on photonic spiking neural network (SNN) consisting of vertical-cavity surface-emitting lasers with an embedded saturable absorber (VCSELs-SA). Here,      N    2      neurons are adopted to solve the N   ×   N Sudoku puzzle with a unique solution. Values in Sudoku are temporally spike-encoded in different spiking times. The result is also achieved according to the spike timing information. In a network, for these VCSELs-SA belong to the same row or column or quadrant, they are inhibitory connected., i.e., from X polarization (XP) mode to Y polarization (YP) mode. Otherwise, they are excitatory connected, i.e., from XP mode to XP mode. Polarization mode competition (PMC) mechanism of VCSEL-SA is utilized to ensure the priority of inhibition behavior. With numerical simulations, 3 × 3 Sudoku puzzle is successfully solved with the help of inhibitory dynamics of VCSEL-SA. The results are represented by the output spike timing of XP mode of each VCSEL-SA. Furthermore, the photonic SNN is also extended to solve 4 × 4 Sudoku puzzle. This work may be interesting for the brain-inspired photonic neuromorphic information processing.
AlphaFold predicted protein structures from spiders

Predicted protein structures of ATP1B, OBP, DYNC2LI, RHOGDI and CAPON from Desis jiaxiangi (DEJI), Argyroneta aquatica (ARAQ) and Pardosa pseudoannulata (PAPS). Predicted protein structures of Sp spidroin from Desis jiaxiangi (DEJI) also have been uploaded.
Business and the Right to Health: Ensuring Access to Essential Medicines in the Context of Harmful Pricing Practices by Pharmaceutical Companies

Millions of people die each year due to a lack of access to medicines.  Contributing to this crisis, pharmaceutical companies often raise the  prices of medicines beyond affordability. Pricing is a core factor for  access at an individual and national level. The right to access medicines  is well established as a component of the right to health under  international human rights law. However, scholarship has scarcely  considered the intersection of access to medicines and pricing.      This thesis investigates how access to medicines can be protected in the  context of harmful pricing practices by pharmaceutical companies. It  considers the nature of harmful pricing practices and examines the role of  states and pharmaceutical companies in respecting and protecting this  right. Employing a socio-legal methodology, I use a blended approach to  research methods. I draw on comparative, qualitative, and doctrinal  methods to examine the legal, social and ethical frameworks surrounding  state obligations and corporate responsibilities. Part One of my thesis  establishes the legal framework surrounding access to medicines in the  context of harmful pricing. Part Two and Part Three then address the  obligations and responsibilities of States and Pharmaceutical companies  respectively, exploring tools and mechanisms to protect access to  medicines.      Harmful pricing practices significantly impact access medicines at an  individual and systemic level. As the primary obligation holders, States  must use the maximum of available resources to protect against harmful  pricing practices and ensure access to medicines. Pharmaceutical companies  have responsibilities to respect, and at times fulfil, the right to  health. Companies demonstrate an understanding of these responsibilities,  yet harmful practices persist. The role of the state therefore remains  central. A significant number of tools are available for states and  corporations to protect access to medicines. It is critical these are  employed to the maximum extent to ensure access to medicines is protected.
Finality and Binding Force of Constitutional Court Decisions: An Analysis of Original Intent and Executory Problematics in the Judicial Review of Law

The final and binding nature of Constitutional Court decisions in the judicial review of Law was designed as a power-balancing instrument to limit the arbitrariness of lawmakers. This generally binding force, in reality, clashes with the absence of an executory apparatus instrument, thereby engendering an executory procedural law vacuum at the related Law level. This research aims to discover the essential meaning of the decision’s binding force by tracing constitutional history, while simultaneously conducting a juridical analysis of the executory problematics to formulate follow-up governance that guarantees legal certainty. This normative legal research employs the statutory, conceptual, and historical approaches to analyze legal materials deductively. The research results indicate that the original intent of the amendment framers placed constitutional court decisions as an absolute control tool against the domination of lawmaker institutions. However, the deletion of the decision follow-up time limit has legitimized institutional arrogance, culminating in the phenomenon of constitutional disobedience. Legislative and executive actions that deliberately revive unconstitutional norms prove the exploitation of loopholes in executive governance weaknesses. The resolution to this problem demands a comprehensive restructuring that integrates a progressive judicial order approach with legislative obligations. The conclusion of this research affirms the urgency of amending Law Number 12 of 2011 to insert the obligation to institutionalize constitutional court decisions into the National Legislative Program, with a maximum time limit of one year, in order to sever the chain of disobedience by positive lawmakers.
LAIgnd: Revolutionizing Drug Discovery with Advanced  AI-Driven Molecule Generation

De novo molecular generation is crucial for advancing drug discovery and chemical research. This accelerates the search for new drug candidates and deepens our understanding of molecular diversity. The development of deep learning has propelled and expedited the de novo molecular generation. Generative networks, particularly Variational Autoencoders (VAEs), can randomly produce new molecules and modify molecular structures to enhance specific chemical properties, which are essential for advancing drug discovery. Although VAEs offer numerous advantages, they are hindered by limitations that affect their capacity to optimize properties and decode syntactically valid molecules. To address these challenges, we present LAIgnd, a de novo drug molecule generation model that implements a custom β-CVAE architecture conditioned on protein sequences and SELFIES input. Extensive experiments have shown that LAIgnd generates a wide variety of valid, novel, and effective molecules for complex and simple diseases, demonstrating its robustness and generalization capabilities. Additionally, by employing molecular docking, toxicity, similarity, and synthetic accessibility experiments, we demonstrated the drug-likeness and effectiveness of the generated molecules. The ability of our model to generate novel and diverse compounds was illustrated by a case study focusing on Lung Cancer. A total of four hundred (400) molecules were generated by LAIgnd, with a high number of molecules exhibiting strong inhibitory activity against the Epidermal Growth Factor receptor, as indicated by binding affinities. LAIgnd provides new insights into future directions to enhance therapeutics for complex and simple diseases by generating high-quality multi-target molecules for drug discovery.  Key words: De novo molecular generation, Drug discovery, Variational Autoencoders (VAEs), SELFIES,        Protein sequences.  CISDI Journal Reference Format Obi, E.D., Yentumi, J.A., Mbatuegwu, D., Omotuyi, O.I., Ajayi, O.O. &amp; Nwokoro, A. (2024): LAIgnd: Revolutionizing Drug Discovery with Advanced AI-Driven Molecule Generation. Computing, Information Systems, Development Informatics &amp; Allied Research Journal. Vol 15 No 4, Pp 1-10. Available online at www.isteams.net/cisdijournal.  dx.doi.org/10.22624/AIMS/CISDI/V15N3P4
The Physics of Plasma Wave Heating for Fusion Energy

AbstractThe general physics of plasma wave heating of magnetically confined plasma will be discussed. A presentation of the basic physical mechanism, theoretical models, and experimental results will be given. Emphasis will be placed on heating in the ion cyclotron range of frequencies, the use of lower-hybrid waves to generate current, and the use of electro-cyclotron heating in tandem mirrors. Additional applications will also be given.
Project management approach for HVDC topside: risk assessment analysis of spool  manufacturing

This paper aims to present how the risk assessment is conducted and to explore the main risks that could potentially disrupt the production flow of piping spool fabrication. From a management perspective, risk assessment may act as a foundation for a successful project. However, if it is not solid, consequences appear. For complex projects, such as HVDC topside, the operational team must be aware of the effects of risks that occur, and before any measures are implemented, the team must be capable of anticipating them. As a starting point, through a brainstorming session, it was assessed using a qualitative analysis of the risks, the probability of occurrence, and the impact they could produce. The process is associated with a variety of risks, from small ones (for instance, human errors that can be corrected) to larger ones (quality defects, contaminated materials, timeline constraints, non-compliance with standards, and safety risks). The paper also includes strategies of mitigation and associated actions. Moreover, in this paper are included methods proposed for further in-depth analisys.
Monitoring and Interpretation of Urban Land Subsidence Using Radar Interferometric Time Series and Multi-Source GIS Database

Subtle and gradual land subsidence in the Netherlands is a well-known phenomenon and it potentially involves a high risk of subsidence disaster in the densely populated areas. Based on the conventional geodetic techniques such as leveling, the slow deformations in urban areas are difficult to monitor due to low temporal and spatial sampling frequencies. We pre-sent the potential of Persistent Scatterer Interferometry (PSI) as an efficient satellite based technique of deformation monitoring. Time series of radar multi-epoch images (up-to 15 years) are analyzed to extract the tar-gets with a stable phase behavior over time. PSI is particularly useful in application to urban environment as the buildings and solid structures are favorable radar point targets.
An explicit finite-memory scheme for approximating and sampling invariant measures of stochastic functional differential equations with infinite delay

Efficient sampling and numerical approximation of invariant probability measures (IPMs) on infinite-dimensional function spaces are important problems in scientific computing. In this paper, we study the numerical approximation and sampling of IPMs associated with stochastic functional differential equations with infinite delay (SFDEswID). To this end, we develop a fully explicit ergodicity-preserving truncated Euler--Maruyama scheme for SFDEswID that requires only finite historical storage and accommodates superlinearly growing coefficients. We establish strong convergence of the numerical segment process and show that it admits a unique IPM and is exponentially ergodic in the Wasserstein distance. Building on these results, we prove the convergence of the numerical IPM to the exact one and derive an explicit convergence rate. As a consequence, we obtain a quantitative long-time sampling error estimate of order $O\left(e^{-λ_\varepsilon t_n}+Δ^{ρ_\varepsilon}\right)$. The results provide a rigorous and computationally efficient framework for sampling IPMs and quantifying long-time sampling errors for stochastic systems with infinite delay.
Great SCO2T! Rapid tool for carbon sequestration science, engineering, and economics

CO2 capture and storage (CCS) technology is likely to be widely deployed in coming decades in response to major climate and economics drivers: CCS is part of every clean energy pathway that limits global warming to 2C or less and receives significant CO2 tax credits in the United States. These drivers are likely to stimulate capture, transport, and storage of hundreds of millions or billions of tonnes of CO2 annually. A key part of the CCS puzzle will be identifying and characterizing suitable storage sites for vast amounts of CO2. We introduce a new software tool called SCO2T (Sequestration of CO2 Tool, pronounced Scott) to rapidly characterizing saline storage reservoirs. The tool is designed to rapidly screen hundreds of thousands of reservoirs, perform sensitivity and uncertainty analyses, and link sequestration engineering (injection rates, reservoir capacities, plume dimensions) to sequestration economics (costs constructed from around 70 separate economic inputs). We describe the novel science developments supporting SCO2T including a new approach to estimating CO2 injection rates and CO2 plume dimensions as well as key advances linking sequestration engineering with economics. Next, we perform a sensitivity and uncertainty analysis of geology combinations (including formation depth, thickness, permeability, porosity, and temperature) to understand the impact on carbon sequestration. Through the sensitivity analysis we show that increasing depth and permeability both can lead to increased CO2 injection rates, increased storage potential, and reduced costs, while increasing porosity reduces costs without impacting the injection rate (CO2 is injected at a constant pressure in all cases) by increasing the reservoir capacity.
Additional file 2 of How are ontologies implemented to represent clinical practice guidelines in clinical decision support systems: protocol for a systematic review

Additional file 2. Search strategy MEDLINE
From Humanitarian Intervention to the Responsibility to Protect: Normative Evolution, Political Selectivity and The Crisis of Implementation

This article examines the transformation from humanitarian intervention to the doctrine of the Responsibility to Protect (R2P) by analyzing its normative evolution, political selectivity and persistent implementation crisis. It addresses the following central research question: Does R2P constitute a genuine normative advancement in international law or does it merely reproduce the structural dilemmas of humanitarian intervention under a new terminology? Drawing on an analytical and interpretive approach, the study integrates theoretical debates with a comparative assessment of three key cases - Kosovo (1999), Libya (2011) and Syria (2011- ). The article first explores the conceptual and legal foundations of humanitarian intervention, then evaluates how R2P was institutionalized through the 2001 International Commission on Intervention and State Sovereignty (ICISS) Report, the 2005 World Summit Outcome Document, UN Secretary-General reports and relevant Security Council resolutions. The empirical analysis demonstrates that Kosovo served as the moral catalyst of the R2P debate, Libya represented its first formal application but simultaneously triggered a legitimacy crisis due to the shift toward regime change and Syria constituted the most visible failure of the doctrine, revealing the paralyzing effects of geopolitical rivalries and Security Council vetoes. The findings suggest that while R2P redefined sovereignty through the lens of responsibility and sought to reconcile human rights protection with international peace and security, its implementation has remained highly selective and politically instrumentalized. The article concludes that R2P represents a partially realized normative project whose effectiveness is constrained by power politics and institutional asymmetries. Strengthening the future of the doctrine requires restoring the balance between legitimacy and effectiveness and ensuring that humanitarian imperatives are not overshadowed by strategic interests.
Adjoint computations by algorithmic differentiation of a parallel solver for time-dependent PDEs

A computational fluid dynamics code is differentiated using algorithmic differentiation (AD) in both tangent and adjoint modes. The two novelties of the present approach are 1) the adjoint code is obtained by letting the AD tool Tapenade invert the complete layer of message passing interface (MPI) communications, and 2) the adjoint code integrates time-dependent, non-linear and dissipative (hence physically irreversible) PDEs with an explicit time integration loop running for ca. $10^{6}$ time steps. The approach relies on using the Adjoinable MPI library to reverse the non-blocking communication patterns in the original code, and by controlling the memory overhead induced by the time-stepping loop with binomial checkpointing. A description of the necessary code modifications is provided along with the validation of the computed derivatives and a performance comparison of the tangent and adjoint codes.
End-to-End Automation for Cross-Database DevOps Deployments: CI/CD Pipelines, Schema Drift Detection, and Performance Regression Testing in the Cloud

Cloud computing systems are increasingly based on heterogeneous databases that combine SQL and NoSQL databases such as Oracle, SQL Server, PostgreSQL, MongoDB, and Cassandra. Although the principles of DevOps have revolutionized the application delivery process, system workflows that involve databases are usually ineffective, performed manually, and extremely vulnerable to failure. The fact that schema updates must be performed manually, cross-engine inconsistencies, and undetected performance regressions create high operational risks, especially in pre-production deployments. Current database DevOps solutions are partially automated but lack full-end solutions that can be used to address schema drift, performance degradation, and deployment reliability of various database systems. In this study, we propose a completely automated and cloud-based DevOps architecture that combines Continuous Integration and Continuous Delivery (CI/CD) and automated schema drift detection and performance regression testing within a multi-database setup. The design-science research methodology was used to design and test the pipeline, and then controlled experiments of schema variation, migration path, and workload patterns across the chosen database engines were conducted. The initial results show that the use of automated schema drift detection can greatly minimize inconsistent releases and the late detection of structural anomalies. Automated performance regression testing revealed throughput decreases, latency spikes, and resource inefficiencies with statistically significant confidence levels. Overall, the system minimizes manual intervention and deployment risk, enhances reproducibility, and offers sound performance insights before rolling out production. The findings provide both theoretical and practical value in the emerging discipline of cross-database DevOps automation and useful advice to organizations interested in scalable, cloud-native delivery workflows of databases.
Examining the Impact of <scp>ACA</scp> Medicaid Expansion on Insurance Coverage, Access to Care and Health of Low‐Income Parents

ABSTRACTObjectiveTo examine longer‐term effects of Medicaid expansion on insurance coverage, access to care, and health, and investigate heterogeneous effects across demographic characteristics of low‐income parents.Study Setting and DesignWe estimated linear probability models for having healthcare coverage and access to care and reporting days of not good physical and mental health in the past 30 days. We adjusted for individual‐ and state‐level factors, and state and year fixed effects. Our treatment group included low‐income parents residing in Medicaid expansion states, and our control group included high‐income parents residing in Medicaid expansion states and ineligible for any Affordable Care Act (ACA) subsidies. We used difference‐in‐differences and event‐study designs.Data Sources and Analytic SampleNationally representative secondary data on self‐reported insurance, access, and health status from the core component (2011–2019) of the Behavioral Risk Factor Surveillance System (BRFSS) among respondents aged 26–54 with at least one child living in the household.Principal FindingsMedicaid expansion was associated with a 13.4 percentage point (pp) increase in the probability of reporting any health insurance (p &lt; 0.001), an 11.3 pp decline in the probability of reporting a cost barrier (p &lt; 0.001), and a 2.4 pp decrease in the probability of reporting days in poor mental health (p = 0.028) among low‐income parents. Our results also suggest parents who were married and those identifying as non‐Hispanic white (relative to Hispanic and non‐Hispanic other/multiple race) experienced the largest increases in health insurance coverage.ConclusionsWhile Medicaid expansions improved insurance coverage, access to care, and health status among low‐income parents, disparities persisted and, in some cases, widened. These findings have significant implications for policymakers as they consider policies aimed at increasing access to care.