ethicalabs/Research-Intent-Collab huggingface dataset:
The Situational Leadership Behavior, Organizational Culture and Human Resources Management Strategy in Increasing Productivity of Private Training Institutions

This study aims to analyze the relationship of situational leadership behavior with the organizational culture; the influence of situational leadership behavior and organizational culture on implementation of human resource management strategies; the effect of the implementation of the strategy of human resource management on productivity; the influence of situational leadership behavior, organizational culture and the implementation of human resource management strategies on the productivity of private vocational training institutes. While the type of research are descriptive and verificative using explanatory survey. The data collection is done using questionnaires, documentation and interviews, while the sampling technique used a Likert Summated Rating. The unit of analysis is the field of operation and delivery of training services and fields of administration. Data analysis is using path analysis. The results showed that the situational leadership behaviors significantly correlated with the organizational culture; the situational leadership behavior and organizational culture have a significant effect simultaneously and partially on the implementation of human resource management strategies in private vocational training institutions; the implementation of human resource management strategies have a significant effect on productivity improvement of private vocational training institutions; the situational leadership behavior, organizational culture and the implementation of human resource management strategy that have a significant effect simultaneously and partially to the increased productivity of private vocational training institutions in North Sumatera province.
On-the-fly fine-tuning of foundational neural network potentials: a Bayesian neural network approach

We introduce a workflow for data-efficient on-the-fly finetuning of foundational neural network potentials with enhanced trustworthiness by harnessing predictive uncertainty estimation extracted from a Bayesian transfer learning approach.
Figure 6 from Blood-Based Genomic Alteration Signature for Predicting Progression-Free Survival in &lt;i&gt;De Novo&lt;/i&gt; Metastatic Hormone-Sensitive Prostate Cancer: A Real-World Study

&lt;p&gt;Clinical significance of b.TRPC in patients undergoing different therapeutic regimens. &lt;b&gt;A,&lt;/b&gt; Kaplan–Meier curves of progression-free survival (PFS) in b.TRPC-positive vs. b.TRPC-negative patients receiving ADT monotherapy. &lt;b&gt;B,&lt;/b&gt; PFS outcomes in b.TRPC-positive and b.TRPC-negative patients treated with doublet therapy. &lt;b&gt;C,&lt;/b&gt; Kaplan–Meier analysis of PFS in b.TRPC-positive and b.TRPC-negative patients administered triplet therapy. Training set (top); validation set (bottom).&lt;/p&gt;
Heliospheric modulation of cosmic rays: model and observation

This paper presents the basic model of cosmic ray modulation in the heliosphere, developed in Yu.G. Shafer Institute of Cosmophysical Research and Aeronomy of the Siberian Branch of RAS. The model has only one free modulation parameter: the ratio of the regular magnetic field to the turbulent one. It may also be applied to the description of cosmic ray intensity variations in a wide energy range from 100 MeV to 100 GeV. Possible mechanisms of generation of the mentioned turbulence field are considered. The primary assumption about the electrical neutrality of the heliosphere appears to be wrong, and the zero potential needed to match the model with observations in the plane of the solar equator can be achieved if the frontal point of the heliosphere, which is flowed around by interstellar gas, lies near the mentioned plane. We have revealed that the abnormal rise of cosmic ray intensity at the end of solar cycle 23 is related to the residual modulation produced by the subsonic solar wind behind the front of a standing shock wave. The model is used to describe features of cosmic ray intensity variations in several solar activity cycles.
Antimicrobial Stewardship in Veterinary Ophthalmology: Making Antimicrobial Resistance Visible

ABSTRACT                   Antimicrobial resistance is increasingly recognized in veterinary ophthalmology, yet its development remains largely unnoticed in daily clinical practice. Although resistant ocular pathogens are reported worldwide, antimicrobial prescribing decisions are frequently made without feedback on local resistance patterns. This Viewpoint discusses aggregated antibiograms as a practical tool to improve situational awareness and support antimicrobial stewardship in veterinary ophthalmology. While antibiograms do not quantify reductions in antimicrobial resistance, their systematic use can provide contextual information that may help inform empirical treatment decisions and encourage reflection on routine prescribing. Using perioperative antibiotic use in cataract surgery as an example, we highlight how routine ophthalmic practices may benefit from re‐evaluation based on accumulated data. Making resistance patterns visible through aggregated antibiograms is a feasible, immediately actionable step toward more responsible antimicrobial use, with relevance to clinical and One Health considerations.
The Impact of Changes in Resolution on the Persistent Homology of Images

Digital images enable quantitative analysis of material properties at micro and macro length scales, but choosing an appropriate resolution when acquiring the image is challenging. A high resolution means longer image acquisition and larger data requirements for a given sample, but if the resolution is too low, significant information may be lost. This paper studies the impact of changes in resolution on persistent homology, a tool from topological data analysis that provides a signature of structure in an image across all length scales. Given prior information about a function, the geometry of an object, or its density distribution at a given resolution, we provide methods to select the coarsest resolution yielding results within an acceptable tolerance. We present numerical case studies for an illustrative synthetic example and samples from porous materials where the theoretical bounds are unknown.
Robust subgroup discovery

We introduce the problem of robust subgroup discovery, i.e., finding a set of interpretable descriptions of subsets that 1) stand out with respect to one or more target attributes, 2) are statistically robust, and 3) non-redundant. Many attempts have been made to mine either locally robust subgroups or to tackle the pattern explosion, but we are the first to address both challenges at the same time from a global modelling perspective. First, we formulate the broad model class of subgroup lists, i.e., ordered sets of subgroups, for univariate and multivariate targets that can consist of nominal or numeric variables, including traditional top-1 subgroup discovery in its definition. This novel model class allows us to formalise the problem of optimal robust subgroup discovery using the Minimum Description Length (MDL) principle, where we resort to optimal Normalised Maximum Likelihood and Bayesian encodings for nominal and numeric targets, respectively. Second, finding optimal subgroup lists is NP-hard. Therefore, we propose SSD++, a greedy heuristic that finds good subgroup lists and guarantees that the most significant subgroup found according to the MDL criterion is added in each iteration. In fact, the greedy gain is shown to be equivalent to a Bayesian one-sample proportion, multinomial, or t-test between the subgroup and dataset marginal target distributions plus a multiple hypothesis testing penalty. Furthermore, we empirically show on 54 datasets that SSD++ outperforms previous subgroup discovery methods in terms of quality, generalisation on unseen data, and subgroup list size.
TECHNOLOGY-ENABLED IMPLEMENTATION OF INCLUSIVE EDUCATION POLICIES: A SYSTEMATIC REVIEW OF UDL, MTSS, AND LEARNING ANALYTICS

This article synthesises evidence on the implementation of inclusive education policies by examining the interplay of technology, pedagogical frameworks, and systemic support in shaping adoption, consistency, adherence, and feasibility across various school contexts. Design/methodology/approach: A Systematic Literature Review (SLR) was conducted in accordance with the PRISMA 2020 guidelines. Seventeen Scopus-indexed articles (2016–2024) were analysed, focusing on study characteristics, theoretical foundations, and implementation indicators. Quality was assessed using JBI checklists. Findings reveal that the combination of assistive technologies, learning management systems, and analytics dashboards enhances adoption and consistency when paired with teacher professional development and Leadership support. The UDL and MTSS frameworks strengthen coherence in curriculum adaptation and monitoring. Nevertheless, affordability, teacher readiness, and infrastructure gaps particularly in LMICs remain significant challenges. Temporal differences emerged: pre-COVID studies emphasised classroom level interventions, while post COVID research highlighted systemic digital infrastructure and accountability. Research limitations include reliance on English only sources, methodological heterogeneity, and potential publication bias. Implications: Policymakers must align inclusion mandates with funding and infrastructure, while school leaders should integrate teacher training and data driven monitoring to support inclusive practices. Researchers are encouraged to adopt mixed method and longitudinal designs across contexts. This study presents a comparative synthesis of pre and post COVID literature, highlighting systemic strategies and justice-oriented perspectives as crucial for sustaining inclusive education.
Dynamics and statistical mechanics of a one-dimensional model hamiltonian for structural phase transitions

We have studied thermodynamic and some dynamic properties of a one-dimensional-model system whose displacement field Hamiltonian is strongly anharmonic, and is representative of those used to study displacive phase transitions. By studying the classical equations of motion, we find important solutions (domain walls) which cannot be represented effectively by the usual phonon perturbation expansions. The thermodynamic properties of this system can be calculated exactly by functional integral methods. No Hartree or decoupling approximations are made nor is a temperature dependence of the Hamiltonian introduced artificially. At low temperature, the thermodynamic behavior agrees with that found from a phenomenological model in which both phonons and domain walls are included as elementary excitations. We then show that equal-time correlation functions calculated by both functional-integral and phenomenological methods agree, and that the dynamic correlation functions (calculated only phenomenologically) exhibit a spectrum with both phonon peaks and a central peak due to domain-wall motion.
Simulation of coupling between chemical reactions and ion transport in brown adipose tissue using network thermodynamics

Several cellular events associated with energy turnover in the mitochondria and at the Na+/K+ plasma membrane pump have been formulated in terms of network thermodynamics. The calorigenic role of the Na+/K+ pump is examined in terms of the relationship between the movement of sodium and potassium ions and the chemical reactions involved. In addition, attention is centered on the potential thermogenic role of three mitochondrial pathways involving proton fluxes--namely, one in which protons are transported from the matrix to the intermembrane space; a second in which protons are transferred back into the matrix in conjunction with the synthesis of ATP; and a third wherein protons re-enter the matrix without being coupled to any chemical reaction. (This latter pathway has been delineated by studies on isolated mitochondria and may be unique to brown fat.) At both sites (plasma membrane and mitochondria) the conversion of chemical energy to heat is considered.
Fullerenes in circumstellar and interstellar environments

In recent years, the fullerene species C60 (and to a lesser extent also C70) has been reported in the mid-IR spectra of various astronomical objects. Cosmic fullerenes form in the circumstellar material of evolved stars, and survive in the interstellar medium (ISM). It is not entirely clear how they form or what their excitation mechanism is.
Islands of shape coexistence in proxy-SU(3) symmetry and in covariant density functional theory

Shape coexistence in even-even nuclei is observed when the ground state band of a nucleus is accompanied by another K=0 band at similar energy but with radically different structure. We attempt to predict regions of shape coexistence throughout the nuclear chart using the parameter-free proxy-SU(3) symmetry and standard covariant density functional theory. Within the proxy-SU(3) symmetry the interplay of shell model magic numbers, formed by the spin-orbit interaction, and the 3-dimensional isotropic harmonic oscillator magic numbers, leads to the prediction of specific horizontal and vertical stripes on the nuclear chart in which shape coexistence should be possible. Within covariant density functional theory, specific islands on the nuclear chart are found, in which particle-hole excitations leading to shape coexistence are observed. The role played by particle-hole excitations across magic numbers as well as the collapse of magic numbers as deformation sets in is clarified.
Concerning the connection between the Cℓ power spectrum of the cosmic microwave background and the Γm Fourier spectrum of rings on the sky

In this article we present and study a scaling law of the m m cosmic microwave background Fourier spectrum on rings that allows us to (i) combine spectra corresponding to different colatitude angles (e.g. several detectors at the focal plane of a telescope) and (ii) recover the C power spectrum once the m coefficients have been measured. This recovery is performed numerically below the 1 per cent level for colatitudes > 80 •. In addition, taking advantage of the smoothness of C and of m , we provide analytical expressions that allow the recovery of one of the spectra at the 1 per cent level, the other one being known.
The Adoption of Digital Ledger ‎Technology for Instant Auditing ‎and Accurate Financial Reporting in ‎Accounting

This study examines the adoption of Digital Ledger Technology (DLT) and its impact on the ‎accuracy of financial reporting and the efficiency of auditing processes within Jordanian ‎organizations. Using a quantitative research design, the study assesses how DLT enhances ‎financial data integrity and supports real-time auditing capabilities. Data were collected from ‎‎210 accounting and auditing professionals representing five major Jordanian institutions: the ‎Central Bank of Jordan, Jordan Customs Department, Arab Bank, Deloitte Jordan, and Ernst ‎&amp; Young Jordan. A structured questionnaire served as the primary data collection instrument, ‎employing a five-point Likert scale to measure perceptions across key constructs related to ‎DLT adoption. To improve response rates, the questionnaire was distributed through both ‎physical and digital channels. Descriptive statistics were used to analyze demographic data, ‎while multiple regression and independent samples t-tests were applied to test the study’s ‎hypotheses. The results revealed a statistically significant and positive relationship between ‎DLT adoption and both the accuracy and reliability of financial reporting, as well as between ‎DLT utilization and enhanced auditing speed and efficiency. Regression analysis indicated that ‎DLT adoption accounted for 52% of the variance in financial reporting accuracy, while t-test ‎results confirmed significant differences between DLT-based and traditional auditing methods. ‎The study complied with ethical standards, ensuring confidentiality and voluntary ‎participation. Overall, the findings demonstrate that DLT plays a transformative role in ‎improving accounting and auditing practices within a developing economy context‎.
Topological phases of non-interacting systems: A general approach based on states

In this work we provide a classification scheme for topological phases of certain systems whose observable algebra is described by a trivial $C^*$-bundles. The classification is based on the study of the homotopy classes of \emph{configurations}, which are maps from a \emph{quantum parameter space} to the space of pure states of a reference \emph{fiber} $C^*$-algebra. Both the quantum parameter space and the fiber algebra are naturally associated with the observable algebra. A list of various examples described in the last section shows that the common classification scheme of non-interacting topological insulators of type A is recovered inside this new formalism.
Climate-Resilient Education System (CRES): A Smart Low-Cost Adaptive Learning Infrastructure for Vulnerable Regions

This paper presents the Climate-Resilient Education System (CRES), an original low-cost adaptive learning infrastructure designed for vulnerable regions. The system integrates environmental sensing, decision-making, and continuity-based learning modes to maintain educational access during climate disruptions such as floods, heatwaves, and power outages.  The design combines engineering logic with education policy, introducing a readiness score and modular architecture that allows schools to detect risk, switch learning modes, and preserve continuity. CRES emphasizes affordability, local repairability, and offline functionality, making it suitable for resource-constrained environments.  This work is an original student research project developed for academic and scholarship purposes.
Social Sciences and Humanities Framework Report. Framing the research, development and design processes when building a prototype of a citizen-centred interoperable health-data exchange platform

The objective of Deliverable 1.1 is to provide a general Social Sciences and Humanities (SSH) framework for the Horizon 2020 project Smart4Health . This project aims to build the prototype of an interoperable health-data platform – the 4HealthPlatform – and a corresponding user portal – the 4HealthNavigator – in order to empower citizens to proactively engage in managing their health. Embracing a citizen centred approach, the project will engage in a co-creation process predominantly involving citizen-users. This SSH framework will outline both the main approach and the kinds of questions that need to be asked during the research, development and design processes. Our report testifies to the consortium’s awareness that the challenges of building such a health-data platform are never solely technical but are also always social. The report starts with outlining the Responsible Research and Innovation approach and the corresponding processes of co-creation. In the following three chapters the challenges of infrastructuring health, the ways in which users and non-users should be understood and integrated and questions of governance of health-data infrastructures are addressed. Each of the chapter end with a set of questions that need to be addressed in the multiple processes of esearch, development and design.
The Assertion of a Regional Specificity of the Right of Peoples to Self-determination by the African Court on Human and Peoples’ Rights

Abstract                In the judgment of Bernard Anbataayela Mornah v. Republic of Benin and others on 22 September 2022, the African Court on Human and Peoples’ Rights made a significant step forward regarding the justiciability of the right to self-determination. Traditionally viewed as part of international relations and thus non-justiciable, the right to self-determination was, in this case, brought into the legal domain by the Court, which affirmed its justiciable dimension. The Court paved the way for the justiciability of a right that has historically been treated as a political principle rather than a legal norm. Until now, claims of self-determination were largely perceived as matters of state sovereignty and inter-state relations, beyond the direct reach of international and regional courts. This decision represents a paradigm shift as it contributes to the consolidation of the right to self-determination as an imperative and justiciable right. Furthermore, the Court recognized the possibility of an actio popularis, meaning the ability of an individual to file a complaint in defense of the right to self-determination, even if not personally affected by the violation of this right. This approach allows for the defense of the right to self-determination beyond individual interests. The decision is based on the imperative nature of the right to self-determination, which the Court identifies as a jus cogens norm.
Self-error-corrected hyperparallel photonic quantum computation working with both the polarization and the spatial-mode degrees of freedom

Usually, the hyperparallel quantum computation can speed up quantum computing, reduce the quantum resource consumed largely, resist to noise, and simplify the storage of quantum information. Here, we present the first scheme for the self-error-corrected hyperparallel photonic quantum computation working with both the polarization and the spatial-mode degrees of freedom of photon systems simultaneously. It can prevent bit-flip errors from happening with an imperfect nonlinear interaction in the nearly realistic condition. We give the way to design the universal hyperparallel photonic quantum controlled-NOT (CNOT) gate on a two-photon system, resorting to the nonlinear interaction between the circularly polarized photon and the electron spin in the quantum dot in a double-sided microcavity system, by taking the imperfect interaction in the nearly realistic condition into account. Its self-error-corrected pattern prevents the bit-flip errors from happening in the hyperparallel quantum CNOT gate, guarantees the robust fidelity, and relaxes the requirement for its experiment. Meanwhile, this scheme works in a failure-heralded way. Also, we generalize this approach to achieve the self-error-corrected hyperparallel quantum CNOT$^N$ gate working on a multiple-photon system. These good features make this scheme more useful in the photonic quantum computation and quantum communication in the future.
Realizing the full potential of electronic health records: the role of natural language processing

Meaningful use of electronic health records (EHRs) for patient care or for research requires data to be comparable. Many portions of EHRs continue to be unstructured, presenting significant challenges for biomedical informatics. This issue of the journal displays several solutions to this problem that are based on natural language processing (NLP) techniques. A high-level review by Nadkarni ( see page 544 ) is intended to introduce the main components of NLP for the novice, and to briefly describe machine learning methods that are successfully being employed in the field. It includes a discussion on Watson, a contestant on ‘Jeopardy!,’ a popular question-and-answer TV show, and the ensuing speculations about its potential extensions to medical NLP. However, despite some notable examples of successful NLP applications in clinical care, progress in the field has been relatively slow.  Chapman and colleagues ( see page 540 ) discuss the need to steer current NLP research efforts so that new developments can be accelerated, and research products can become readily usable in healthcare applications. The authors advocate for a concerted, collaborative effort to develop open-source software components and infrastructure to share annotated data and tools. The guest editorial raises important questions …