ethicalabs/Research-Intent-Collab huggingface dataset:
How Upper/Middle Managers' Ethical Leadership Activates Employee Ethical Behavior? The Role of Organizational Justice Perceptions Among Employees

Several studies have been conducted on ethical leadership and workplace ethical behavior but little is known about the role of organizational justice and each of its dimensions (procedural, distributive, interpersonal, informational) in this relationship. This study predicts that ethical leadership enhances organizational justice perceptions, including each of its specific dimensions, which in turn enhances employee ethical behavior. The results from two-wave survey data obtained from 270 employees in the Malaysian manufacturing industry confirm that ethical leadership has a positive impact on employee ethical behavior, and that organizational justice and each of its justice dimensions mediate this relationship, both individually and together. Importantly, interpersonal and informational dimensions show the strongest mediation effects. This paper highlights the actions and strategies that can help managers to effectively elevate the moral tone in their organizations. In particular, our findings show where managers must put more emphasis to foster an ethical workplace: on providing fair treatment (interpersonal justice) and honest information (informational justice).
A Novel Approach to Analyze Fashion Digital Archive from Humanities

Fashion styles adopted every day are an important aspect of culture, and style trend analysis helps provide a deeper understanding of our societies and cultures. To analyze everyday fashion trends from the humanities perspective, we need a digital archive that includes images of what people wore in their daily lives over an extended period. In fashion research, building digital fashion image archives has attracted significant attention. However, the existing archives are not suitable for retrieving everyday fashion trends. In addition, to interpret how the trends emerge, we need non-fashion data sources relevant to why and how people choose fashion. In this study, we created a new fashion image archive called Chronicle Archive of Tokyo Street Fashion (CAT STREET) based on a review of the limitations in the existing digital fashion archives. CAT STREET includes images showing the clothing people wore in their daily lives during the period 1970--2017, which contain timestamps and street location annotations. We applied machine learning to CAT STREET and found two types of fashion trend patterns. Then, we demonstrated how magazine archives help us interpret how trend patterns emerge. These empirical analyses show our approach's potential to discover new perspectives to promote an understanding of our societies and cultures through fashion embedded in consumers' daily lives.
The role of the Gadaa generational system of the Oromo in conflict resolution and peace building

This article explores the role of the gadaa generational system in conflict resolution among the West Guji Oromo in Southern Ethiopia. Conflict is an inevitable phenomenon in human day-to-day actual life interactions. In the pastoral area of Southern Ethiopia, it manifests itself in the form of violent and interethnic episodes of violence. People have their conflict handling mechanisms and peace restoring procedures through their own indigenous institutions. Gadaa is an all-encompassing institution of the Oromo people, recently recognized by UNESCO as representing a case of African democracy. Peace building and conflict resolution emanates from the central ritual and ceremonial activities of gadaa, its customary administrative and legal functions and the traditional religion, with the associated morality. The article is based on research conducted in Bulehora and Suro Berguda woreda, in the formerly Borana Zone of southern Ethiopia. Qualitative technic was employed. The results showed that the major source of conflict is competing interests in using water resources and grazing land, border expansion for grazing and border demarcation within the same ethnic groups. Those factors had an impact on economic, social, religious and political life. The abbaa gadaa is the most prominent customary leader. In order to manage conflicts and to build peace, the abbaa gadaa adopted a procedure based on 13 distinct steps. The research concluded that the gadaa generational institution is effective in conflict resolution and peace building in the area of research, and that it has a potential for replication at national level.
Turbulence in the Interstellar Medium: Energetics and Driving Mechanisms

Interstellar turbulence is expected to dissipate quickly in the absence of continuous energy input. I examine the energy available for driving the turbulence from six likely mechanisms: magnetorotational instability, gravitational instability, protostellar outflows, H II region expansion, stellar winds, and supernovae. I conclude that supernovae contribute far more energy than the other mechanisms, and so form the most likely drving mechanism.
Petrogenesis and porphyry metallogenic potential of the Jinmen pluton in the Nanling Range, South China: Insights from whole-rock geochemistry, zircon trace elements, and U-Pb-Hf isotopes

The Jinmen pluton is situated on the southern margin of the Nanling metallogenic belt. A skarn-type Cu-Fe-Mo-Au polymetallic deposit has been recently discovered in proximity to the pluton. However, there have been no systematic studies on its emplacement age, petrological classification, or its relationship with mineralization. This study focuses on the Jinmen pluton, characterized by a lithological assemblage of biotite monzogranite alongside minor granite dikes and mafic microgranular enclaves (MMEs). These rocks display distinct whole-rock geochemical characteristics, yet share similar emplacement ages, mineral assemblages, and isotopic compositions. Zircon LA-ICP-MS U–Pb dating yields weighted mean ages of 161.6 ± 0.6 Ma to 158.7 ± 0.6 Ma for three biotite monzogranite samples, 161.1 ± 0.6 Ma for one granite dike sample, and 161.0 ± 0.8 Ma for one MME sample, indicating consistent emplacement ages within error. Four molybdenite Re–Os model ages ranging from 163.0 to 156.2 Ma further confirm synchronous magmatism and mineralization during the late Jurassic. Zircon εHf(t) values show negative variations (–7.17 to –1.69), with corresponding two-stage model ages (1.32–1.66 Ga), indicating derivation from partial melting of pre-existing crustal material, while MMEs were formed by magmatic mixing processes. Most biotite monzogranites exhibit low Y and Yb contents coupled with high Sr and Ba concentrations, characteristic of adakitic signatures. Comprehensive analyses reveal the Jinmen pluton as I-type granite generated by crustal anatexis of Proterozoic igneous rocks. The pluton additionally exhibits high oxygen fugacity (ΔFMQ = +0.9 to +3.4) and water-rich magmatic features. The biotite monzogranite is characterized by high V/Sc ratios. A negative correlation between ΔFMQ and log[104×(Eu/Eu*)/YbN] of biotite monzogranite suggest significant potential for porphyry copper mineralization.
An Activity Analysis to Investigate the Root Causes of Worker Productivity Losses in Sri Lankan Building Construction Project

Construction workers are the basic unit of the construction industry. The behaviour of construction workers varies with the time, which impacts on worker productivity. Therefore, obtaining the highest levels of performance is crucial in order to be competitive in the construction industry. The scarcity of skilled workers, increase of high rise building projects and changes in the economic and political conditions aggravated the need of seeking strategies to improve the performances of construction workers. Therefore, it is essential to investigate the productivity pitfalls, and root causes behind the worker performance losses when developing productivity improvement frameworks. Under this study, a detailed workforce assessment framework was developed for building construction projects using the Activity Analysis technique. A worker performance benchmarking was carried out for different trades to identify the differences in contract strategies of the workers. Further, root causes for worker productivity losses were identified and mapped those with the responsible parties.
International treaties on legal assistance in law enforcement activities of the Customs authorities of the Russian Federation

The most important task of the customs authorities of the Russian Federation is to protect national security, prevent, detect and suppress crimes and administrative offenses, cooperate with customs and other competent authorities of foreign states, international organizations dealing with customs issues. One of the means of solving this problem is international treaties on mutual assistance in customs matters. The article considers the state of international legal regulation of law enforcement activities of the customs authorities of the Russian Federation by international treaties on legal assistance. Using formal legal and comparative legal methods, the relevant international treaties in which the Russian Federation participates are analyzed. В В  The forms of legal assistance used in international cooperation in law enforcement activities of the Federal Customs Service are highlighted. The system of legal aid treaties under study is heterogeneous in its structure and does not cover relations with all States with which this cooperation may be necessary. As a solution to the problem, the systematization of international acts regulating issues of international cooperation of customs authorities in the law enforcement sphere is presented and proposals are presented to the legislator: to conclude agreements with those states with which an agreement on mutual legal assistance in criminal and administrative matters has already been concluded, but no agreement on mutual assistance in customs matters has been concluded.
Dynamic formation and breaking of disulfide bonds in molecular dynamics simulations with the UNRES force field

Many proteins contain disulfide bonds that are usually essential for maintaining function and a stable structure. Several algorithms attempt to predict the arrangement of disulfide bonds in the context of protein structure prediction, but none can simulate the entire process of oxidative folding, including dynamic formation and breaking of disulfide bonds. In this work, a potential function developed to model disulfide bonds is coupled with the united-residue (UNRES) force field, and used in both canonical and replica exchange molecular dynamics simulations to produce complete oxidative folding pathways. The potential function is obtained by introducing a transition barrier that separates the bonded and nonbonded states of the half-cystine residues. Tests on several helical proteins show that improved predictions are obtained when dynamic disulfide-bond formation and breaking are considered. The effect of the disulfide bonds on the folding kinetics is also investigated, particularly their role in stabilizing folding intermediates, resulting in slower folding.
An embodied perspective of open educational resources (OERs) collaborative design supporting self-determined and autonomous learning.

In the framework of the EULALIA project (Enhancing University Language courses with an App powered by game-based Learning and tangible user Inter-faces Digital Creativity Enhanced in Teacher education) the authors develop a blended embodied approach to cultural competence education by using scenario based and multisensorial methodologies applying Tangible User Interfaces (TUIs) and Mobile Learning. Combining virtual and multisensorial physical dimensions thanks to the application TUIs and VR elements, situational affordances are distributed across a network of Learning Objects (Smart) storing a variety of digital contents. Exploring a physical map the user experiment learning scenarios constructing personal meanings, self-directing and serf regulating their learning path. In this view, the students and teachers are able to creatively, and collaboratively design Open Educational Resource (OER), co-creating their Language Learning Strategy (LLS), in the form of a game scenario. The paper explores the potential of OERs co-design approach in the in the educational context presenting the EULALIA workshops experience.
Dynamic Knowledge Graphs: Revolutionizing Skill Analytics through Graph Neural Networks

The dynamic nature of workforce skills and their interrelationships necessitates sophisticated systems for understanding, classifying, and predicting skill evolution. This article introduces a novel framework for Dynamic Knowledge Graph Evolution in the Skills Domain, leveraging Graph Neural Networks to model hierarchical skill relationships, analyze temporal trends, and automate taxonomy generation. Our architecture incorporates a hierarchical GNN model that captures parent-child relationships among skills, enabling accurate skill classification and clustering. Temporal article is integrated into the framework to identify emerging skills and trends, providing actionable insights for dynamic workforce planning. Furthermore, we propose an automated taxonomy generation algorithm that leverages unsupervised clustering and natural language processing to continuously update the graph structure. Experiments on real-world datasets demonstrate the framework's ability to model skill evolution with high precision, generate interpretable taxonomies, and predict workforce demands effectively. Applications in talent management, career planning, and learning systems showcase the system's ability to adapt to the rapidly evolving landscape of workforce skills.
Climate change uncertainty, irreversibility and the precautionary principle

This paper begins with a critique of the option value argument used by economists to explain and justify the precautionary principle. The argument is shown to misrepresent both uncertainty and irreversibility. An alternative justification of the precautionary principle is discussed, under conditions of Keynesian uncertainty, and irreversibility interpreted in terms of incommensurability. Recent formal decision theories under Keynesian uncertainty are reviewed and their limitations explored, with particular reference to the insights that decision theory can bring to understanding the precautionary principle. Throughout, the decision problems under consideration are those faced by climate change policy makers. Copyright , Oxford University Press.
A Dual Digital Twin Framework for Reinforcement Learning: Bridging Webots and MuJoCo with Generative AI and Alignment Strategies

Deep reinforcement learning (DRL) has shown potential for robotic training in virtual environments; however, challenges remain in bridging simulation and real-world deployment. This paper introduces an extended reinforcement learning framework that advances beyond traditional single-environment approaches by proposing a dual digital twin concept. Specifically, we suggest creating a digital twin of the robot in Webots and a corresponding twin in MuJoCo, enabling policy training in MuJoCo’s optimized physics engine and subsequent transfer back to Webots for validation. To ensure consistency across environments, we introduce a digital twin alignment methodology, synchronizing sensors, actuators, and physical model characteristics between the two simulators. Furthermore, we propose a novel testing framework that conducts controlled experiments in both virtual environments to quantify and manage divergence, thereby improving robustness and transferability. To address the cost and complexity of maintaining two high-fidelity models, we leverage generative AI agents to automate the creation of the secondary digital twin, significantly reducing engineering overhead. The proposed framework enhances scalability, accelerates training, and improves the reliability of sim-to-real transfer, paving the way for more efficient and adaptive robotic systems.
Inventory management in supply chains with consideration of Logistics, green investment and different carbon emissions policies

Abstract   This study investigates the effects that carbon policies and green technologies may have on the integrated inventory of a two-echelon supply chain with consideration of carbon emissions during the processes of product production, transportation, and storage. The three carbon emissions policies: limited total carbon emissions, carbon taxation, and cap-and-trade, are considered in the study. The proposed model can assist firms in determining their corresponding optimal production quantity, delivery quantity, and green investment amount with an aim of minimizing the costs under different carbon emissions policies. Moreover, this study also provides practical implications for the government to make appropriate policies and regulations in balancing the trade-off between environmental protection and economic growth. Finally, the results indicate that firms adopting the carbon tax policy would prefer to invest in a relatively efficient green technology. With regard to the sources of carbon emissions, the effects of unit carbon emissions during production and unit distance of transportation are the most dramatic, and the cap limit has greater effects than the carbon emissions reduction factor of the green technology. Besides, the government should set the limit of carbon emissions within a reasonable range under the cap-and-trade policy to avoid suppliers overly trading their quotas of carbon emissions.
Simulation Model for the Dynamics Analysis of a Surgical Assistance Robot

MODICAS (modular interactive Computer Assisted Surgery) represents an integral solution for the software-based combination of a surgical planning software, an optical localization device and a haptic sensor with a mechatronic manipulator in order to support surgical interventions. One key feature of the integral system is to accurately and precisely align any surgical instrument, according to the preoperative planning, in relation to the bony structure of the patient and to intraoperatively ensure the alignment to remain constant all the time. This is made possible due to the automatically controlled tracking of small patient movements in real time. As a result of developed calibration algorithms, the stationary precision and accuracy of the whole system is mainly defined by the measurement characteristics of the applied localization device. Moreover, the actual exploratory focus lies on the enhancement of the dynamic behaviour, especially on the reduction of the dynamic tracking error without concurrently degrading the stationary properties. The following chapter describes the development and use of an offline simulation environment for the analysis and the enhancement of the MODICAS patient tracking system dynamics. At first, the functional principle of the tracking procedure is discussed. Furthermore, the physical modelling of all relevant system characteristics and the identification of the system parameters are described. Additionally, the model behaviour is verified against measurements from the real surgical assistance system. It is shown, that the offline model properly simulates the behaviour of the real system. As an example of use, a comparison of three tracking control strategies is shown on the basis of the developed and identified model. In the future, further simulations will be performed, in order to understand how various system parameters like lags, measurement noise or calibration errors may influence the overall tracking performance. The results will lead to a conclusion about the actual technical constraints and to an outlook on how such system can be further advanced in the future.
Energy equipartition between stellar and dark matter particles in cosmological simulations results in spurious growth of galaxy sizes

ABSTRACT                The impact of 2-body scattering on the innermost density profiles of dark matter haloes is well established. We use a suite of cosmological simulations and idealized numerical experiments to show that 2-body scattering is exacerbated in situations where there are two species of unequal mass. This is a consequence of mass segregation and reflects a flow of kinetic energy from the more to less massive particles. This has important implications for the interpretation of galaxy sizes in cosmological hydrodynamic simulations, which nearly always model stars with less massive particles than are used for the dark matter. We compare idealized models as well as simulations from the eagle project that differ only in the mass resolution of the dark matter component, but keep subgrid physics, baryonic mass resolution, and gravitational force softening fixed. If the dark matter particle mass exceeds the mass of stellar particles, then galaxy sizes – quantified by their projected half-mass radii, R50 – increase systematically with time until R50 exceeds a small fraction of the redshift-dependent mean interparticle separation, l (${\rm R_{50}} \gtrsim 0.05\times l$). Our conclusions should also apply to simulations that adopt different hydrodynamic solvers, subgrid physics, or adaptive softening, but in that case may need quantitative revision. Any simulation employing a stellar-to-dark matter particle mass ratio greater than unity will escalate spurious energy transfer from dark matter to baryons on small scales.
Bound on quantum computation time: Quantum error correction in a critical environment

4 pages (revised title, following PRA request)
Cephalopods: fisheries science, stock assessment and management in the fast lane

Peer reviewed
Federated Continual Learning with Adaptive Differential Privacy and Client-Side Drift Detection for Evolving Medical Imaging Datasets

Abstract                 This paper presents a novel Federated Continual Learning framework for medical imaging that enables continuous model updates across multiple hospitals without central data sharing. Our approach addresses critical challenges in healthcare AI: data privacy, catastrophic forgetting, and distribution drift. We demonstrate the framework on OrganAMNIST with three hospitals learning sequential tasks. Results show successful federated collaboration but reveal significant catastrophic forgetting, highlighting the need for advanced continual learning techniques in privacy-constrained environments. The integrated drift detection and differential privacy mechanisms provide a foundation for practical clinical deployment.
A Measurement of the Cosmic Microwave Background $B$-Mode Polarization Power Spectrum at Sub-Degree Scales from 2 years of POLARBEAR Data

We report an improved measurement of the cosmic microwave background (CMB) $B$-mode polarization power spectrum with the POLARBEAR experiment at 150 GHz. By adding new data collected during the second season of observations (2013-2014) to re-analyzed data from the first season (2012-2013), we have reduced twofold the band-power uncertainties. The band powers are reported over angular multipoles $500 \leq \ell \leq 2100$, where the dominant $B$-mode signal is expected to be due to the gravitational lensing of $E$-modes. We reject the null hypothesis of no $B$-mode polarization at a confidence of 3.1$σ$ including both statistical and systematic uncertainties. We test the consistency of the measured $B$-modes with the $Λ$ Cold Dark Matter ($Λ$CDM) framework by fitting for a single lensing amplitude parameter $A_L$ relative to the Planck best-fit model prediction. We obtain $A_L = 0.60 ^{+0.26} _{-0.24} ({\rm stat}) ^{+0.00} _{-0.04}({\rm inst}) \pm 0.14 ({\rm foreground}) \pm 0.04 ({\rm multi})$, where $A_{L}=1$ is the fiducial $Λ$CDM value, and the details of the reported uncertainties are explained later in the manuscript.
Cosmological Simulations of Multicomponent Cold Dark Matter

6 pages, 4 figures