ethicalabs/Research-Intent-Collab huggingface dataset:
European Digital Sovereignty, Data Protection, and the Push toward Data Localization

Abstract                   This chapter will focus exclusively on concerns of the current trends toward “data localization” and the idea that “European data must be stored and processed in Europe.” Part I of this chapter will recall how certain influential political voices in Europe were pushing in favor of data localization even before the Schrems II Judgment of the Court of Justice of the European Union (CJEU). Part II will try to discern the exact reasons that motivated such calls for data localization. Part III will discuss in depth the major influence of the July 2020 Schrems II Judgment of the CJEU and will show that, ultimately, the numerous calls in favor of strict data localization of personal data as a response to this judgment, were not able to be balanced by those calling for the adoption of a “risk-based approach” to international data transfers. The chapter ends with a few thoughts about the necessity, for Europe, to study further the possible adverse effects of soft or strict data localization mandates and to find solutions that enable the main objective of data protection to be achieved without necessarily engaging in severe and disproportionate restrictions to transnational data flows that might be disruptive for European business and the global economy.
When Technology Meets Transparency &amp; Accountability: A Strategy to Prevent Corruption in Local Government

This study aims to develop an information technology–based transparency and accountability model to support corruption prevention in local government procurement in Batu City, East Java, Indonesia.  Adopting a qualitative approach, this study combines a literature review with data collected through Focus Group Discussions (FGDs) involving Batu City Government’s officials and village leaders. Data were analysed using NVivo 12 Plus to identify recurring patterns and key themes related to governance, technology, and integrity. The findings reveal that although Batu City has promoted digitalisation through agency-specific applications, the absence of an integrated cross-agency procurement system creates oversight gaps and accountability risks. The study highlights that effective IT-based procurement systems require not only data integration and open budget information but also reliable human resource integrity and ethical commitment. Advanced digital systems alone are insufficient without a robust anti-corruption culture. This study proposes an integrated information-technology model for goods and services procurement to help enhance budget transparency, accelerate anomaly detection, improve procurement traceability, and strengthen digital evidence for law enforcement. The proposed model serves as a strategic and sustainable oversight instrument, thereby reinforcing regional anti-corruption enforcement frameworks.
SCALE-TRACK: Asynchronous Euler-Lagrange particle tracking on heterogeneous computing architecture

Euler-Lagrange (EL) simulations provide a direct and robust framework for modeling disperse multiphase flows. However, they are computationally expensive. While various approaches have attempted to leverage heterogeneous computing architectures, they have encountered scalability limitations. We present SCALE-TRACK, a scalable two-way coupled EL particle tracking algorithm, designed to exploit heterogeneous exascale computing environments. With asynchronous coupling, cache-friendly data structures, and chunk-based partitioning, we address key limitations of existing EL implementations. Validations against an analytical solution and a conventional EL implementation demonstrate the accuracy of the proposed algorithms. On a local workstation, we simulated 1.4 billion particles in a test case featuring a single graphics processing unit (GPU). Scaling runs on an HPC (high-performance computing) cluster show excellent strong and weak scaling, with up to 256 billion particles being tracked on up to 256 GPUs. This represents a significant advancement for EL simulations, enabling high-fidelity simulations on local workstations and pushing the limits on HPC systems. The software is released as open source and is publicly available.
Natural Language Processing applied to electronic records: surveillance and detection of health events

Abstract Text fields in medical records are a valuable source for Public Health Surveillance but remain underutilized. This study describes the use of natural language processing (NLP) to enhance the identification of suspected cases and monitor disease trends in electronic records from the Urgency and Emergency Network (Rede de Urgência e Emergência - RUE), in the municipality of Rio de Janeiro (MRJ). Texts were pre-processed, and rules were applied to identify individual (measles and rubella) and collective (diarrhea and influenza-like syndrome) events, comparing the results with ICD-10 data from January 2023 to September 2024. A total of 28 suspected measles cases and 33 suspected rubella cases were identified through ICD, while the NLP technique detected an additional 30 suspected cases of measles and 17 of rubella based on patient complaints. Time series of diarrhea and influenza-like syndrome (síndrome gripal - SG), stemming from ICD and complaints, showed a cross-correlation above 0.93 at lag 0. Complaint analysis, particularly after the discontinuation of nonspecific SG ICD codes by RUE management, revealed a greater stability and expanded detection of suspected cases, demonstrating the potential of NLP in epidemiological surveillance in MRJ.
Voyager and Pioneer spacecraft measurements of cosmic ray intensities in the outer heliosphere: Toward a new paradigm for understanding the global solar modulation process: 1. Minimum solar modulation (1987 and 1997)

Using IMP, Voyager, and Pioneer spacecraft data, we have derived radial intensity profiles of cosmic rays in the heliosphere out to ∼70 AU as fractions of the expected interstellar intensities for five particle energies/species during the minimum solar modulation periods of 1987 and 1997. These radial profiles exhibit a markedly different behavior in the two periods of opposite solar magnetic polarity. In the negative polarity period (1987) the radial profiles for the highest‐rigidity particles extrapolate to the interstellar (IS) intensity at approximately the estimated location of heliospheric termination shock (TS) at 85–90 AU. The lower‐rigidity particle intensities extrapolate to only 0.45–0.60 of the IS intensity at this same location, indicating that a large part of the residual solar modulation for these particles at this time takes place at or beyond the location of the TS. In the 1997 positive polarity time period the fraction of the overall modulation that is occurring between the Earth and the TS is now much smaller, and since the intensity at the Earth is the same in both cycles, the consequence is that the extrapolated radial intensities at the TS location are now only 0.50 (at the highest rigidities) to 0.17 (at the lowest rigidities) of the respective IS intensities. Thus, at this time of minimum modulation most of the residual modulation apparently is taking place near to or beyond the TS. Also, the ratio of the fraction of the total residual modulation that is taking place between the Earth and the TS and that taking place beyond the TS changes dramatically between positive and negative modulation cycles. Viewed in this new way, contemporary modulation models including drifts, when they are assumed to occur within the TS, do not provide a satisfactory quantitative explanation of the modulation that is taking place at the minimum of solar activity. These models do not predict the large amount of modulation taking place near or beyond the termination shock. This outer heliospheric modulation dominates the overall residual modulation at low energies and is more effective in positive solar magnetic polarity periods. A new paradigm seems to be needed to interpret this large modulation that is taking place in the outer heliosphere.
Deep learning, Artificial Intelligence and machine learning in cancer: Prognosis, diagnosis and treatment

Thus, over the past years, the progress in AI, especially in machine learning and deep learning, has affected the area of oncology. It is in this context that this paper reviews the different changes in technologies for cancer prognosis, diagnosis, and treatment. Some of the ways that AI is helping improve cancer diagnosis and treatment are in the analysis of large clinical and genetic data to provide better forecast accuracy of cancer outcomes, the detailed image analysis to aid early cancer diagnosis, and the use of population, patient, and clinical data to create a custom-made treatment plan. For instance, ML performs well in prognostic evaluations where the algorithm tries to predict diseases’ progress and patients’ survival since it can recognize specific patterns in large databases; on the other hand, DL, particularly CNNs, are precise in interpreting medical images for early diagnosis. Also, AI assists in the application of enhanced therapies for genetic mutations as a form of precision medicine. During treatment strategy development, AI supports oncologists in determining the appropriate radiation doses and the proper combination of drugs; robotic systems increase the accuracy of operations due to AI. However, there is still information privacy and protection, algorithm and model bias, and implementation of AI applications in the context of clinical health care. These issues require special attention for the future development and adoption of AI in oncology. The present uses, advantages, and prospects of AI, ML, and DL in cancer treatment have been described in this paper, along with the focus on the capability of the interventions to transform the course of therapy and actual patient experience.
Hydroxycarbamide in children with sickle cell anaemia after first‐dose <i>vs</i>. chronic therapy: pharmacokinetics and predictive models for drug exposure

AimsThe purposes of this work were to: (1) compare pharmacokinetic (PK) parameters for hydroxycarbamide in children receiving their first dose (HCnew) vs. those receiving chronic therapy (HCchronic), (2) assess the external validity of a published PK dosing strategy, and (3) explore the accuracy of dosing strategies based on a limited number of HC measurements.MethodsUtilizing data from two prospective, multicenter trials of hydroxycarbamide (Pharmacokinetics of Liquid Hydroxyurea in Pediatric Patients with Sickle Cell Anemia; NCT01506544 and Single‐Dose (SD) and Steady‐State (SS) Pharmacokinetics of Hydroxyurea in Children and Adolescents with Sickle Cell Disease), plasma drug concentration vs. time profiles were evaluated with a model independent approach in the HCnew and HCchronic groups. Various predictive scenarios were analysed to evaluate whether systemic exposure with hydroxycarbamide could be accurately predicted.ResultsAbsorption of hydroxycarbamide was rapid, variable and dose independent. Dose‐normalized peak plasma concentrations and drug exposure (AUC) were higher, and weight‐normalized apparent oral clearance was lower in the HCnew group. We assessed a PK‐guided dosing strategy along with other predictive scenarios and found that inclusion of plasma samples only slightly improved the accuracy of AUC predictions when compared to a population‐based method.ConclusionsChildren naïve to hydroxycarbamide exhibit a different PK profile compared to children receiving chronic therapy. Accuracy of population‐based dosing is sufficient to target AUCs in individual patients. Further clearance/bioavailability studies are needed to address the factors responsible for variability in the disposition of hydroxycarbamide.
Field Theoretic Aspects of Condensed Matter Physics: An Overview

In this chapter I discuss the impact of concepts of Quantum Field Theory in modern Condensed Physics. Although the interplay between these two areas is certainly not new, the impact and mutual cross-fertilization has certainly grown enormously with time, and Quantum Field Theory has become a central conceptual tool in Condensed Matter Physics. In this chapter I cover how these ideas and tools have influenced our understanding of phase transitions, both classical and quantum, as well as topological phases of matter, and dualities.
Specifics of the Distribution of Orbits of Long-Period Comets in the Inner Part of the Oort Cloud

Abstract—We investigate statistical patterns in the distribution of the orbits of long-period comets that belong to the inner region of the Oort cloud (with aphelion distances, Q, lying in the 50–2000 AU interval). We show that the distribution of aphelia is not random and such patterns can be due, in particular, to the presence of hypothetical massive bodies in the region considered. We varied the orbital parameters of such bodies to obtain two orbits such that each of them has the aphelia of 40 comets located within the 20-degree neighborhood of the orbit. This number is statistically significant. The orbits have the following parameters in the ecliptic coordinate system: P1: ΩP = 297°, iP = 24°, ωP = 322°, eP = 0.6, aP = 510 AU; P2: ΩP =92°, iP = 80°, ωP =327°, eP = 0.3, aP =1000 AU. For the adopted masses of these bodies we determined the minimum distances between their orbits and the orbits of the comets and estimated the number of aphelia located within the spheres of influence of these bodies. We found that the greatest number of aphelia are located near orbit P1. However, their number is insufficient to conclude that massive bodies actually move in the inferred orbits. It is remarkable that the planes of orbits P1 and P2 in the Galactic coordinate system have the same inclinations (40°) and longitudes of their ascending nodes are equal to 10° and 170°, i.e., the orbital planes are almost symmetric with respect to the direction toward the Galactic center. The concentration of orbital aphelia of the comets considered found in this study can therefore be due to the attraction from the Galactic center and/or complex motion of the Solar system.
Promoting Food Security in Rwanda Through Sustainable Agricultural Productivity: Meeting the Challenges of Population Pressure, Land Degradation, and Poverty

The horror of genocide and civil war have turned the world's attention to Rwanda over the last year. But before and beyond that conflict, there was hunger and the slow grinding poverty of small holder agriculture meeting with severe land scarcity and degradation. This report is about reversing the spiraling decline of the land and the economy in rural Rwanda. Three things conspire to accelerate this decline: unsustainable land use practices, insufficient non-farm employment, and rapid population growth. We focus on the forces behind productivity decline in Rwandan agriculture. This report examines how erosion, organic input use, soil conservation investments, use of fertilizer and lime, and land use strategies affect productivity. We then examine what determines farmers; productivity and conservation investments. The results are based on collaborative research between the Rwandan Ministry of Agriculture (MINAGRI) and Michigan State University. The data derive from a detailed farm-level survey, one of the most comprehensive in Africa, conducted by the Division des Statistiques Agricoles (DSA/MINAGRI). The survey covered a nationwide random sample of 1248 households, and was undertaken of 11 years, from 1984-1994. DSA has been, and we hope will be again, one of the national treasures of Rwanda. Our key findings are that Rwandan framers need to sustainable intensify their farming by protecting the soil against erosion, and by enhancing soil fertility through the use of organic matter, and chemical fertilizer, and lime. Without more input access and use, inevitable intensification of farming, as holding grow smaller, will be based only on adding more labor and cropping more intensely, both of which will degrade soils and lead to greater hardship. Where farmers are now making these investments, we report successes. We find success is often predicted on confidence in the future, knowledge from extension services, cash and labor resources from off-farm earnings, holding livestock that provides manure, and planting perennial cash crops. The contributions of this report are: (1) in underscoring and focusing on priority strategies and questions regarding the many issues that have come in and out of development debate in the highland tropics of Africa, and (2) in the systematic application of detailed, nationwide survey data to these key questions. Moreover, the report points to the great value of excellent national agricultural statistics services and national capacity to analyze data and provide insights for policy debate.
Development of a layer-wise in-situ laser-based dimensional monitoring system with post-mechanical characterization of synthesized polylactic acid 3D prints in FDM additive manufacturing

High-dimensional accuracy is difficult to obtain in 3D printing techniques such as Fused Deposition Modeling (FDM). The study was conducted in two phases. In the first phase, the causes of dimensional inaccuracy in FDM printing were reviewed and a new Laser-Based Dimensional Measurement System (LDMS) was produced. Two FDM printers, Ultimaker Extended and Creality Ender 3 Pro, were used in experiments to investigate the impacts of material deposition, over-extrusion, print speed, under-extrusion, mechanical vibrations, and temperature variation on dimensional accuracy. The third stage involved the synthesis of PLA material, which was then extruded into a capillary and used for 3D printing by the LDMS system. The printed samples were characterized using tensile, hardness, and flexural tests, as well as XRD, FTIR, SEM, and TG/DA analyses. It was also demonstrated that the LDMS provides in-situ layer-wise dimensional monitoring during intermediate stages of the building process. The obtained PLA polymers were biodegradable and amorphous. It was also noted that the printed parts could withstand lateral loads better than longitudinal loads, and, in compression, they were stronger than in tension.This research work supports SDG 12 (Responsible Consumption and Production) by improving material efficiency and promoting biodegradable PLA.
Climate change adaptation on public lands: policy, vulnerability assessments, and resilience in the U.S. Forest Service

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From Scripts to Platforms-as-Code: The Role of Terraform and Ansible in Declarative Infrastructure Rollouts

Between 2000 and 2020, the evolution of infrastructure provisioning reflected a decisive shift from manual, script-based administration toward fully declarative, code-driven automation enabled by Infrastructure-as-Code (IaC) principles. As enterprises embraced virtualization and later cloud-native architectures, the demand for scalable, reproducible, and policy-governed rollouts grew exponentially. IaC frameworks emerged as the foundation for this transformation, allowing infrastructure to be version-controlled, tested, and deployed through automated pipelines. Tools such as Terraform and Ansible became pivotal in unifying provisioning and configuration, enabling platform teams to define entire environments as reusable modules governed by CI/CD and GitOps workflows. This article contextualizes their role in institutionalizing automation and governance across hybrid and multi-cloud platforms, tracing the lineage from early configuration management systems like CFEngine, Puppet, and Chef to modern self-auditing architectures that integrate compliance, rollback, and continuous validation. Together, these advances redefined infrastructure delivery as an engineering discipline turning once-manual deployment tasks into programmable, secure, and verifiable platform lifecycle operations.
Analisis terhadap Artificial Intelligence sebagai Subjek Hukum Pidana

This article discusses issues related to the existence of artificial intelligence as a legal subject, and criminal liability when artificial intelligence commits criminal acts. The purpose of this study is to find out the categorization of artificial intelligence as a legal object or legal subject, and to find out to whom criminal responsibility is assigned when artificial intelligence commits a crime. The research method used in writing this article is normative legal research, with a conceptual approach. The results of this study are that artificial intelligence is not a legal subject, because the actions carried out by artificial intelligence are only orders from its users, and for criminal acts committed by artificial intelligence, those who must be responsible are the creators of artificial intelligence or users of artificial intelligence
Studies of physics conditions for aneutronic and/or nonradioactive nuclear energy generation in 3He-induced fission of 6Li and 3He fusion in a steady state migma plasma

Abstract   The physical properties of a steady state migma plasma consisting of reacting  3 He,  6 Li, and d nuclei with densities  n  ∼ 10 14  cm −3  and energies of 0.1–10 MeV, which corresponds to  β  ≥ 0.9, were studied using a zero-dimensional collisional model and simulated by an iterative code on a CRAY computer (β does not have the same physical meaning here as in thermal plasmas). We conclude that if migma plasma can achieve the density currently attained in thermal plasma devices (n ∼ 10 14  cm −3 ), it will produce net energy through radionuclide-free aneutronic nuclear reactions with a power density of ∼ 20 MW th /m 3 . Specifically: synchrotron radiation looses from multi-MeV migma are ∼10 3  times lower than those from thermal plasma of the same density  n  ∼ 10 14  cm −3 . We obtained a positive energy balance for the neutronless and radionuclide-free quasi-chain fission of  6 Li, and the pure  3 He fusion, with a “scientific” power output-to-input ratio  Q  = 1.7, as compared to the  Q  ∼ 10 −3  obtained in thermal plasma. The radionuclide fraction or “radioactivity”  R  =  I  rad / I  t  and a neutron power fraction or “neutronicism”  N  =  P  n / P  nuc  are  R  = 0.5%,  N  = 2% for (a) and  R  = N = 0.0% for (b). For in migma, we obtain  Q  ∼ ∞,  R  = 0.5%, and  N  = 3.5%. Our results suggest that in the next stage of simulation, the 3-component fuel d +  3 He +  6 Li should be used to obtain high  Q  and, simultaneously, low  R  and  N . For nonradioactive aneutronic migma: (a) bitemperature migma is essential; ignition is  not  possible in a Maxwellian system; (b) nor is ignition possible in a closed system (end looses are essential); (c) the diamagnetic well is essential; (d) the system must confine ions up to  E  i  = 10 MeV (15 MeV for D- 3 He protons); and (e) migma does not become thermalized, which makes a steady state reactor operation feasible.
The Concept of Resilience and Protection of Critical Infrastructure against Natural and Man-made Disasters in Republic of Macedonia

The paper argues that if Macedonia is about to enhance resilience to natural and man made disasters it must consider effective critical infrastructure protection. Identifying critical infrastructures that need to be protected, among others, will enable Macedonian society to withstand, absorb, adapt to the new situation and to bounce back effectively. During the research we have identified two problems. First there is no national consensus of what resilience means. Second there is no identified list of critical infrastructures that need protection through the concept of “all hazards approach” embedded in the national disaster risk and reduction concept. Therefore the paper first discusses the concept of resilience as seen by different branches of science in order to establish a framework for further examination in Macedonian context. In the second part we examine how the concept of critical infrastructure protection against all types of hazards could be placed in Macedonia. In the third part of the paper we argue that without coherent state strategy for critical infrastructure protection Macedonia risks to endanger disaster/crisis management system’s resilience. Finally we provide some recommendation.