ethicalabs/Research-Intent-Collab huggingface dataset:
Pengaruh Human Resource Information System (Hris) Terhadap Kinerja Sumber Daya Manusia Dengan Efektivitas Kerja Sebagai Variabel Intervening

Penerapan teknologi informasi dalam manajemen sumber daya manusia menjadi kebutuhan strategis bagi organisasi dalam meningkatkan efektivitas kerja dan kinerja karyawan. Salah satu bentuk penerapan tersebut adalah penggunaan Human Resource Information System (HRIS). Penelitian ini bertujuan untuk menganalisis pengaruh HRIS terhadap kinerja sumber daya manusia (SDM) dengan efektivitas kerja sebagai variabel intervening. Penelitian ini menggunakan pendekatan kuantitatif dengan metode survei terhadap karyawan yang telah menggunakan HRIS dalam aktivitas kerjanya. Data dianalisis menggunakan Structural Equation Modeling–Partial Least Squares (SEM-PLS). Hasil penelitian menunjukkan bahwa HRIS berpengaruh positif dan signifikan terhadap efektivitas kerja dan kinerja SDM. Selain itu, efektivitas kerja juga berpengaruh positif dan signifikan terhadap kinerja SDM serta terbukti memediasi pengaruh HRIS terhadap kinerja SDM. Temuan ini mengindikasikan bahwa implementasi HRIS yang efektif mampu meningkatkan kinerja SDM secara optimal melalui peningkatan efektivitas kerja karyawan. Penelitian ini memberikan implikasi penting bagi organisasi untuk mengoptimalkan pemanfaatan HRIS sebagai bagian dari strategi pengelolaan SDM berbasis teknologi informasi.
Root-Cause Investigation and Technical Reliability Analysis of the Starting-Air System Failure in a Marine Generator A Case Study of KM Sabuk Nusantara 101

The starting-air system of the 114-kW main generator aboard KM Sabuk Nusantara 101 experienced repeated start failures during a 14-day sea operation, resulting in delayed engine activation and reliability reduction. This study aims to identify the root causes of the failure and evaluate the system’s technical reliability performance. The investigation employed field observation, pressure measurement, functional testing, fault tracing, and logbook analysis, supported by Root-Cause Analysis (RCA) and reliability metrics (MTBF, MTTR, and failure rate). The results show three dominant failure sources: (1) air receiver leakage due to degraded flange seals, (2) solenoid valve contamination causing pilot pressure loss, and (3) starting-air valve seat wear leading to insufficient cylinder impulse pressure. Reliability calculation produced an MTBF of 112 hours, MTTR of 2.5 hours, and a failure rate of 0.00893 h⁻¹, indicating low operational reliability despite 97.8% availability. The findings conclude that the system failure is dominated by leakage, contamination, and single-point failures (SPF) in the pneumatic control circuit. Preventive actions recommended include condition-based monitoring, improved sealing and filtration, functional inspection intervals every 250 hours, and redundancy for critical pneumatic components. These measures are expected to increase operational readiness and reduce downtime on similar shipboard installations.
On Certified Generalization in Structured Prediction

In structured prediction, target objects have rich internal structure which does not factorize into independent components and violates common i.i.d. assumptions. This challenge becomes apparent through the exponentially large output space in applications such as image segmentation or scene graph generation. We present a novel PAC-Bayesian risk bound for structured prediction wherein the rate of generalization scales not only with the number of structured examples but also with their size. The underlying assumption, conforming to ongoing research on generative models, is that data are generated by the Knothe-Rosenblatt rearrangement of a factorizing reference measure. This allows to explicitly distill the structure between random output variables into a Wasserstein dependency matrix. Our work makes a preliminary step towards leveraging powerful generative models to establish generalization bounds for discriminative downstream tasks in the challenging setting of structured prediction.
Genetic discrimination and life insurance: a systematic review of the evidence

Since the late 1980s, genetic discrimination has remained one of the major concerns associated with genetic research and clinical genetics. Europe has adopted a plethora of laws and policies, both at the regional and national levels, to prevent insurers from having access to genetic information for underwriting. Legislators from the United States and the United Kingdom have also felt compelled to adopt protective measures specifically addressing genetics and insurance. But does the available evidence really confirm the popular apprehension about genetic discrimination and the subsequent genetic exceptionalism?This paper presents the results of a systematic, critical review of over 20 years of genetic discrimination studies in the context of life insurance.The available data clearly document the existence of individual cases of genetic discrimination. The significance of this initial finding is, however, greatly diminished by four observations. First, the methodology used in most of the studies is not sufficiently robust to clearly establish either the prevalence or the impact of discriminatory practices. Second, the current body of evidence was mostly developed around a small number of 'classic' genetic conditions. Third, the heterogeneity and small scope of most of the studies prevents formal statistical analysis of the aggregate results. Fourth, the small number of reported genetic discrimination cases in some studies could indicate that these incidents took place due to occasional errors, rather than the voluntary or planned choice, of the insurers.Important methodological limitations and inconsistencies among the studies considered make it extremely difficult, at the moment, to justify policy action taken on the basis of evidence alone. Nonetheless, other empirical and theoretical factors have emerged (for example, the prevalence and impact of the fear of genetic discrimination among patients and research participants, the (un)importance of genetic information for the commercial viability of the private life insurance industry, and the need to develop more equitable schemes of access to life insurance) that should be considered along with the available evidence of genetic discrimination for a more holistic view of the debate.
The recovery phase of galactic cosmic ray modulation in the outer heliosphere

Energetic hydrogen and helium nuclei from the galaxy (cosmic rays) enter the solar system with varying degrees of difficulty during the 11‐year solar magnetic cycle, resulting in spatial and temporal variations of particle intensities in the heliosphere. We report observations of these variations from the ISEE‐3, Voyager 1 and 2, and Pioneer 10 spacecraft during the period from early 1981 to early 1986 and for heliocentric distances ranging from 1 to 37 AU. During this time the high energy intensities in the outer heliosphere have been increasing exponentially at a rate of approximately 20%/year with occasional interruptions due to enhanced solar activity. There are long delays (∼3 years) in the recovery of the intensity of low energy particles relative to high energy particles that significantly alter the energy spectra. The radial intensity gradients measured in the ecliptic plane are observed to remain constant or to decrease at the time of the reversal of the solar magnetic poles in 1980.
Science in the Swiss Public. The State of Science Communication and Public Engagement with Science in Switzerland

Science communication and public engagement with science have repeatedly been called for in recent years, particularly during the COVID-19 pandemic. Therefore, die Swiss Academies of the Arts and Sciences have set up an expert group to assess the state of science communication in Switzerland, and to provide recommendations for how to improve it. The expert group report is based on a comprehensive review of the available interdisciplinary scholarship analyzing science communication and public engagement with science in Switzerland. Selectively, it also incorporates original data, international findings, and secondary analyses where little or no published scholarly work was available. The report covers a wide range of facets of science communication and public engagement in Switzerland, from public attitudes towards science over individuals and organizations engaging in science communication and engagement formats to news and social media representations of science. On this basis, it formulates 20 recommendations for improving science communication in Switzerland.
Validation of a Wearable Sensor Prototype for Measuring Heart Rate to Prescribe Physical Activity: Cross-Sectional Exploratory Study

Background                     Wearable sensors are rapidly evolving, particularly in health care, due to their ability to facilitate continuous or on-demand physiological monitoring.                                                           Objective                     This study aimed to design and validate a wearable sensor prototype incorporating photoplethysmography (PPG) and long-range wide area network technology for heart rate (HR) measurement during a functional test.                                                           Methods                     We conducted a transversal exploratory study involving 20 healthy participants aged between 20 and 30 years without contraindications for physical exercise. Initially, our laboratory developed a pulse wearable sensor prototype for HR monitoring. Following this, the participants were instructed to perform the Incremental Shuttle Walk Test while wearing the Polar H10 HR chest strap sensor (the reference for HR measurement) and the wearable sensor. This test allowed for real-time comparison of HR responses between the 2 devices. Agreement between these measurements was determined using the intraclass correlation coefficient (ICC3.1) and Lin concordance correlation coefficient. The mean absolute percentage error was calculated to evaluate reliability or validity. Cohen d was used to calculate the agreement’s effect size.                                                           Results                     The mean differences between the Polar H10 and the wearable sensor during the test were –2.6 (95% CI –3.5 to –1.8) for rest HR, –4.1 (95% CI –5.3 to –3) for maximum HR, –2.4 (95% CI –3.5 to –1.4) for mean test HR, and –2.5 (95% CI –3.6 to –1.5) for mean recovery HR. The mean absolute percentage errors were –3% for rest HR, –2.2% for maximum HR, –1.8% for mean test HR, and –1.6% for recovery HR. Excellent agreement was observed between the Polar H10 and the wearable sensor for rest HR (ICC3.1=0.96), mean test HR (ICC3.1=0.92), and mean recovery HR (ICC3.1=0.96). The agreement for maximum HR (ICC3.1=0.78) was considered good. By the Lin concordance correlation coefficient, the agreement was found to be substantial for rest HR (rc=0.96) and recovery HR (rc=0.96), moderate for mean test HR (rc=0.92), and poor for maximum HR (rc=0.78). The power of agreement between the Polar H10 and the wearable sensor prototype was large for baseline HR (Cohen d=0.97), maximum HR (Cohen d=1.18), and mean recovery HR (Cohen d=0.8) and medium for mean test HR (Cohen d= 0.76).                                                           Conclusions                     The pulse-wearable sensor prototype tested in this study proves to be a valid tool for monitoring HR at rest, during functional tests, and during recovery compared with the Polar H10 reference device used in the laboratory setting.
301MO Genomic HLA as a predictive biomarker for survival among non-small cell lung cancer patient treated with single agent immunotherapy

We aimed to assess the role of genomic HLA-I/II homozygosity in the overall survival benefit in patients with unresectable locally advanced, metastatic non-small lung cancer treated by single agent PD1/PDL1 inhibitors...
A self‐contained and portable density functional theory library for use in <i>Ab Initio</i> quantum chemistry programs

AbstractA major unresolved problem of density functional theory is the yet unknown exchange‐correlation functional, which leads to a proliferation of its less or more successful approximations. A practical implementation of these numerous functionals can present a substantial challenge particularly if the higher order functional derivatives are required. We present a systematic method of functional implementation. The method allows a clean handling of a large number of functionals in a mutually independent way. We developed an extensive set of automatic test routines to facilitate functional and derivative testing with respect to the implementation correctness and numerical stability. An integral part of the presented solution is a program for automatic code generation from analytical formulas that uses only freely available tools. Code for evaluation of functionals and their first, second, third, and fourth derivatives can be generated, which accelerates the development, implementation, and testing of new functionals. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2007
Advanced Edge Computing Frameworks for Optimizing Data Processing and Latency in IoT Networks

The advent of edge computing has been revolutionary in improving data processing efficiency and reducing latency in IoT networks. By decentralizing computational tasks, edge computing enables real-time analytics and scalability while reducing reliance on centralized cloud infrastructures. This paper explores advanced frameworks, including hierarchical and decentralized architectures, that integrate AI and machine learning to enhance predictive optimization and resource management. It also addresses challenges such as protocol compatibility, energy efficiency, and operational complexities. The review provides insights into current advancements and identifies future opportunities for improving IoT network performance and supporting latency-sensitive applications like smart cities and industrial automation.
Dissecting Serverless Computing for AI-Driven Network Functions: Concepts, Challenges, and Opportunities

Serverless computing represents a transformative paradigm in cloud architecture that is fundamentally changing how network functions are deployed and managed. This article examines the intersection of serverless computing and artificial intelligence in the context of network functions, highlighting how this convergence enables more efficient, scalable, and intelligent network operations. The serverless model abstracts infrastructure management while offering automatic scaling and consumption-based pricing, creating an ideal environment for deploying AI-driven network capabilities. The architectural components of serverless platforms are explored, including event sources, function runtimes, scaling mechanisms, state management systems, and integration layers, with particular attention to how these components support AI workloads. Despite compelling advantages, several challenges must be addressed, including cold start latency, state management in stateless environments, and resource limitations for complex AI models. Mitigation strategies such as provisioned concurrency, external state stores, and model optimization have proven effective in overcoming these obstacles. Integration with complementary cloud-native technologies like Kubernetes, Knative, and service meshes further enhances the capabilities of serverless network functions. Practical applications in intelligent DDoS mitigation, network configuration management, predictive maintenance, and dynamic traffic optimization demonstrate the real-world value of this approach, while economic and security assessments reveal significant benefits in cost reduction, operational efficiency, and security posture.
Review of Smith, K.L., &amp; Dickson, K.A. (Eds.).(2016).Open access and the future of scholarly communication: Policy and infrastructure. NY: Rowan and Littlefield.

Review of Smith, K.L., &amp; Dickson, K.A. (Eds.). (2016). Open access and the future of scholarly communication: Policy and infrastructure. NY: Rowan and Littlefield
<i>Fusarium incarnatum</i>                     : a paradigm for One Health pathogen dynamics across humans, animals, and the environment

ABSTRACT                                                                                    The                       Fusarium incarnatum-equiseti                       species complex (FIESC) is a harmful plant pathogen responsible for diseases, such as root rot, fruit rot, leaf blight, and wilt, in various crops. Recently, it has been increasingly associated with both superficial and invasive infections in humans and animals. Additionally, this pathogen produces mycotoxins, posing significant risks to public health. This study aims to characterize the molecular and morphological characteristics of FIESC isolates obtained from various sources, including human, veterinary, and plant samples. Molecular identification was performed using multilocus sequence typing (MLST), targeting the internal transcribed spacer (ITS) rDNA, the second-largest subunit of the RNA polymerase gene (RPB2), and translation elongation factor 1 alpha (TEF-1α). Based on MLST analysis, all FIESC isolates were found to belong to the Incarnatum clade and were classified into two species:                       F. irregulare                       and                       F. pernambucanum                       . Furthermore, these isolates demonstrated the ability to penetrate and colonize human nails, porcine skin, and muskmelon fruits. In this study, we report members of FIESC as a newly identified pathogens in Taiwan capable of cross-infection among humans, animals, and plants. These findings highlight the dual significance of                       Fusarium                       : it poses a serious threat to agriculture by compromising plant health and crop yields while also representing a public health risk due to its ability to infect humans and animals.                                                                                IMPORTANCE                                            The                       Fusarium incarnatum-equiseti                       species complex (FIESC) is a significant plant pathogen affecting a wide range of crops, leading to substantial agricultural losses worldwide. In this study, we report that                       Fusarium                       isolates belonging to                       F. pernambucanum                       and                       F                       .                       irregulare                       obtained from various sources, including respiratory specimens from human, cat, rabbit, and turtle, along with plant samples from muskmelon fruits, represent newly identified pathogens in Taiwan. Our findings suggest that these isolates possess the potential for cross-infection among plants, animals, and humans, underscoring their importance in both agricultural and medical contexts. Notably, the plant isolates PLMF1 and BDMF7 demonstrate the ability to transition from plant pathogens to zoonotic pathogens, highlighting a concerning adaptability.
CLIMATE VULNERABILITY AND LOCAL ADAPTATION STRATEGY: UNDERSTANDING CLIMATE CHANGE NORM ADAPTATION AND DYNAMICS COMMUNITY RESILIENCE IN BATULAPISI DALAM, GOWA REGENCY, SOUTH SULAWESI

Climate change presents ecological and social challenges for rural areas, including Batulapisi Dalam, Tinggimoncong District, Gowa Regency, South Sulawesi. The region faces specific vulnerabilities that demand strategic responses to ensure the sustainability of residents’ livelihoods. This research seeks to understand the dynamics of community resilience models through adaptive transformation approaches and the localization of climate norms. A qualitative case study was conducted at the research site using data collection techniques that include in-depth interviews, participatory observation, focus group discussions, and policy document analysis. Our study shows that, despite the intensification of climate impacts displacing planting and harvesting cycles, adaptation to climate-change norms at community levels remains limited. The agrarian pressures brought about by land conflicts and the conversion of agricultural areas into ecotourism sites have further exacerbated these challenges. As a response, farmers have employed agronomic adaptation strategies, especially crop rotation applied to the changing state of groundwater availability. This study proposes a hybrid model for adaptation strategy, integrating socio-ecological capital through livelihood diversification at the rural community level. We argue that linking local policy to national and international frameworks such as the Paris Agreement and the Village SDGs is important and must be pursued together with strengthening norm entrepreneurs who can promote greater local sustainable climate adaptation capacity.
Thermal-hydraulics, physical chemistry, and technology at nuclear power stations equipped with fast-neutron sodium-cooled reactors

Main results of investigations aimed at developing a verified system of computer codes that take into account the interrelation among nuclear-physical, thermal-hydraulic, physicochemical, thermal-mechanical, mass-transfer, and technological processes in nuclear power installations and at substantiating the models used as the core of these codes are presented together with the results of tests carried out to obtain data for verifying the codes.
The Influence of Human Resource Information System (HRIS) Effectiveness on Employees’ Performance at Brankas

Since the 21st century, the use of data makes it possible to assist in making decision and business strategies. Human Resource Information System (HRIS) is an excellent example of utilizing savings in administrative costs and also taking strategies that can benefit companies or organizations by gathering information, processing and sharing. The purpose of this research was to understand the influence of HRIS effectiveness on employees’ performance at Brankas. The method used in this research was a quantitative method with data collection technique through the distribution of questionnaires. The type of analysis used is descriptive and causal with the data analysis used descriptive analysis, simple linear regression, determination coefficient, and hypothesis testing. The results of this study showed that HRIS has significant influence on employees’ performance at Brankas. The results of this study should be used as input for Brankas through developing and improving the system of HRIS to help the company more efficient in terms of time management by the time set up.
A molecular dynamics study of water-soluble polymers: analysis of force fields from atomistic simulations

A force field (FF) analysis was performed on three water-soluble polymers (PAM, PNIPAAm, and PEO), that are of significant interest for biomedical applications, by measuring the polymer radius of gyration (Rg), solvent accessible surface area (SASA), radial distribution functions (g(r)), and relative shape anisotropy (κ2) in dilute conditions. Three generalised FFs were utilised to model PAM and PNIPAAm (DREIDING, GAFF, and GAFF2) in conjunction with five water models: SPC, SPC/E, TIP3P, TIP4P, and TIP4P/2005. It was found that the DREIDING FF showed better agreement with PAM experimental data reported for Rg, irrespective of the water model. For PNIPAAm, the DREIDING FF was also the best performing among the FFs studied; however, the choice of water model played an important role in the predicted properties. The trends in SASA and κ2 are consistent with Rg. For PEO modelled with the CHARMM C35r FF, all water models except TIP3P resulted in good agreement with experimental and previous simulation data. These results highlight the considerable impact that polymer and water FFs can have on sampling appropriate polymer conformations in solvated systems.