ethicalabs/Research-Intent-Collab huggingface dataset:
The The Effect of Organizational Culture, Transformational Leadership, and Job Satisfaction of the National Library Republic of Indonesia on Organizational Citizenship Behavior (OCB): 1Ikawati Lestari, 2Setyo Riyanto 1Master of Management Student, Mercu Buana University, Jakarta, Indonesia 2Associate Professor at Mercu Buana University, Jakarta, Indonesia ikawatilestari@gmail.com; setyo.riyanto@mercubuana.ac.id

ABSTRACT&amp;nbsp;  The library is the builder of all libraries in Indonesia (Law No.43 of the Republic of Indonesia Year 2007). As a coach, the National Library of Indonesia faces challenges that must be met so that organizational performance needs to be improved. If every employee has organizational citizenship behavior (OCB), can achieve good government. The end of this study is to realize the effects of corporate culture, transformational leadership, and job satisfaction on organizational citizenship behavior (OCB) of the National Library of Indonesia. The resource persons in this study involved 280 ASN informants who had served at the National Library for at least three years—used linear regression method to analyze the data and SPSS version 17.0 for data analysis. The results of the analysis of this study instruct organizational culture, transformational leadership, and organizational citizenship behavior (OCB).  &amp;nbsp;  Keywords: Organizational Culture, Transformational Leadership, Job Satisfaction, Organizational Citizenship Behavior (OCB)
THE IMPACT OF TECHNOLOGY ON THE ENVIRONMENT OF BALOCHISTAN: AN INTERPLAY BETWEEN TECHNOLOGICAL INNOVATION AND SUSTAINABILITY DEVELOPMENT GOALS (SDGS) IN BALOCHISTAN AND THE INTEGRATION OF ENVIRONMENTAL IMPACT ASSESSMENT (EIA) IN PROPOSING A STRATEGIC MITIGATION FRAMEWORK FOR BALOCHISTAN

Technology based innovation and advancement would subsequently be the use of progressing information to practical applications accompanied by the design of smart devices/equipment. In the current era in Balochistan, it is a time of phenomenal transformation that mankind right now lives in-one in which technology upgradation reshapes our way of living but at the same times causes irreversible environmental changes and also results in resource depletion.The advent of new innovations was introduced with the industrial revolution resulting in a paradigm shift from conventional to new assembling approaches in Europe and the US during the period around 1760 to 1840. This has been proceeded with augmented industrialization and further technology design alterations across the globe including Balochistan, Pakistan. However the ramifications of these innovation to the climate, biotic/abiotic component of the environment, natural/non-renewable resources, regional communities etc have incorporated in the exploitation and harming of our mother nature and our planet Earth. These advancements have infact unfavourably impacted Balochistan in two primary ways; pollution and thedepletion of natural resources.Therefore, it is crucial to critically explore the impact of technology on the environment of Balochistan in order to comprehend and achieve the targets and goals of SDGs. In addition, it is crucial to implement Environmental Impact Assessment (EIA) which serves as an essential strategic tool to assess the likely natural outcomes of technology advancement, ensuring that both short-term and long-term impacts are understood and mitigated to attain sustainability for future generations.
Artificial intelligence in HFpEF: Diagnosis, prognosis, and management strategies

Heart failure with preserved ejection fraction (HFpEF) accounts for more than half of all HF cases and its incidence and prevalence continue to increase, with a substantial burden of morbidity and mortality. Despite advances in our understanding of heterogeneous pathophysiology underlying HFpEF, the diagnosis, risk assessment, and management of this disease entity remain challenging in everyday practice. Artificial intelligence (AI) algorithm can handle large amounts of complex data and machine learning (ML), a subfield of AI, allows for the identification of relevant patterns by learning from big data. Considering the vast datasets generated from patients with HFpEF over the course of their illness, the application of AI and ML algorithms in HFpEF has the potential to improve patient care through enhancing early and precise diagnosis, personalized treatment based on phenotypes, and efficient monitoring. In this review, we provide an overview of the use of AI and ML in patients with HFpEF, focusing on diagnosis, phenotyping, risk stratification and prognosis, and management. Additionally, we discuss the limitations in the clinical adaptability of AI and suggest the future research directions for developing novel and feasible AI-based HFpEF model.
sj-docx-3-css-10.1177_24705470231169106 - Supplemental material for Mental Health Among People Presenting for Care of Physical Symptoms: The Factors Associated with Suicidality and Symptoms of Depression and Anxiety are Similar Across Specialties

Supplemental material, sj-docx-3-css-10.1177_24705470231169106 for Mental Health Among People Presenting for Care of Physical Symptoms: The Factors Associated with Suicidality and Symptoms of Depression and Anxiety are Similar Across Specialties by Sina Ramtin, Kathleen Carberry, Maria Correa, David Ring, Carol Alter and Donna Shanor in Chronic Stress
Online Statistical Inference in Decision-Making with Matrix Context

The study of online decision-making problems that leverage contextual information has drawn notable attention due to their significant applications in fields ranging from healthcare to autonomous systems. In modern applications, contextual information can be rich and is often represented as a matrix. Moreover, while existing online decision algorithms mainly focus on reward maximization, less attention has been devoted to statistical inference. To address these gaps, in this work, we consider an online decision-making problem with a matrix context where the true model parameters have a low-rank structure. We propose a fully online procedure to conduct statistical inference with adaptively collected data. The low-rank structure of the model parameter and the adaptive nature of the data collection process make this difficult: standard low-rank estimators are biased and cannot be obtained in a sequential manner while existing inference approaches in sequential decision-making algorithms fail to account for the low-rankness and are also biased. To overcome these challenges, we introduce a new online debiasing procedure to simultaneously handle both sources of bias. Our inference framework encompasses both parameter inference and optimal policy value inference. In theory, we establish the asymptotic normality of the proposed online debiased estimators and prove the validity of the constructed confidence intervals for both inference tasks. Our inference results are built upon a newly developed low-rank stochastic gradient descent estimator and its convergence result, which are also of independent interest.
Impact of Building Design in BIM on the Carbon Footprint of Single-Family Houses: Life Cycle Assessment (LCA) and Case Study of Masonry and Timber Technology

Building carbon footprint analysis is a key instrument for assessing the impact of different constructions on climate change. Several standards and methodologies are available to calculate the footprint of buildings, including standards and norms, life cycle assessment (LCA), and dedicated software tools. The use of BIM software for these calculations is both scientifically justified and very practical. This scientific publication focusses on the application of a BIM-based research methodology for the analysis of the carbon footprint of a single-family house. The research process included the following steps: (i) design of a single-family house with timber frame construction using Archicad BIM software, (ii) simulation of the building energy performance using the EcoDesigner Star plug-in, (iii) life cycle assessment (LCA) using the plug-in for Archicad, (iv) preparation of a second model with traditional masonry construction for comparison, and (v) comparative analysis of the single-family house models with timber frame and masonry construction. Analysis of the results highlights significant differences in CO2e emissions between masonry and timber buildings and the varying impact of individual elements on the total CO2e emissions of the buildings studied. These findings are relevant for future work on sustainable building design and construction, which aims to minimise negative environmental impacts. The goal of minimising the cumulative carbon footprint of buildings is critical to achieving the Sustainable Development Goals and combating climate change.
Convergence of Regret Matching in Potential Games and Constrained Optimization

Regret matching (RM) -- and its modern variants -- is a foundational online algorithm that has been at the heart of many AI breakthrough results in solving benchmark zero-sum games, such as poker. Yet, surprisingly little is known so far in theory about its convergence beyond two-player zero-sum games. For example, whether regret matching converges to Nash equilibria in potential games has been an open problem for two decades. Even beyond games, one could try to use RM variants for general constrained optimization problems. Recent empirical evidence suggests that they -- particularly regret matching$^+$ (RM$^+$) -- attain strong performance on benchmark constrained optimization problems, outperforming traditional gradient descent-type algorithms.   We show that RM$^+$ converges to an $ε$-KKT point after $O_ε(1/ε^4)$ iterations, establishing for the first time that it is a sound and fast first-order optimizer. Our argument relates the KKT gap to the accumulated regret, two quantities that are entirely disparate in general but interact in an intriguing way in our setting, so much so that when regrets are bounded, our complexity bound improves all the way to $O_ε(1/ε^2)$. From a technical standpoint, while RM$^+$ does not have the usual one-step improvement property in general, we show that it does in a certain region that the algorithm will quickly reach and remain in thereafter. In sharp contrast, our second main result establishes a lower bound: RM, with or without alternation, can take an exponential number of iterations to reach a crude approximate solution even in two-player potential games. This represents the first worst-case separation between RM and RM$^+$. Our lower bound shows that convergence to coarse correlated equilibria in potential games is exponentially faster than convergence to Nash equilibria.
The Overlap between Dispute Settlement Mechanisms in World Trade Organization Agreements and Tax Treaties

The rapid expansion of the membership of the World Trade Organization (WTO) poses a significant challenge to the operation of tax treaties. This article examines the possible clash of jurisdiction and the potential conflict between the dispute resolution mechanisms provided for by the WTO and in tax treaties.
The association between wearable device metrics and clinical outcomes in oncology:A systematic review with evidence synthesis and meta-analysis

Background: The emerging study of wearable devices (WDs) in patients with cancer provides opportunities to harness real-time patient data for predicting clinical outcomes. We conducted a systematic review with best evidence synthesis to examine the association between WD metrics and clinical outcomes in patients with cancer. Methods: MEDLINE and Embase were searched from inception until June 2022. Risk of bias assessment and best evidence synthesis were performed and, If possible, meta-analysis was conducted. Results: A total of 34 studies was included. We found moderate-to-strong evidence for associations between circadian rest-activity metrics and OS. Disrupted I&lt;O was associated with increased hazard for death (HR 2.08; 95 %CI: 1.50–2.88). For most associations there was insufficient evidence due to lack of studies (n = 32) or inconsistent results (n = 14). Conclusion: Meta-analysis was greatly hampered due to heterogeneity and different methodology used between studies. Studies primarily designed to investigate the association between WD metrics and clinical outcomes are warranted.
Business Ethics, Corporate Social Responsibility and Sustainability in management master programs : A qualitative study on the EQUIS-accredited business schools in four Nordic countries

With today’s public debates concerning the environmental and social issues there is a need to educate the future business leaders how to run a business in a way that can contribute to sustainability and the protection of the world’s natural resources. Therefore, the aim of this study is to investigate to what extent management master programs at the EQUIS-accredited business schools in the Nordic countries include courses which address the concepts of Business Ethics, CSR and Sustainability. This is interesting to study since existing theories suggest that there is a possibility that higher education could be a resource for sustainability since it will increase the students’ awareness about global sustainability issues, such as environmental, economical and social issues. Also since the world’s business schools educate management students how to manage businesses in the best possible way in order to maximize profit and shareholder value, and may not focus on the ethical part of the business governance. For this study a qualitative research strategy has been used to investigate the content of several descriptions for programs and courses offered to management master students. By doing this we found which programs and courses that included the concepts Business Ethics, CSR and Sustainability or concepts resembling to these and which programs that did not include any of the concepts. The empirical findings facilitated our possibility to understand and analyze the content of the investigated management master programs. The study is based on secondary data collected from nine Nordic EQUIS-accredited business schools’ websites. The findings suggest that programs and courses including one or more of the concepts Business Ethics, CSR and Sustainability are available at all of the investigated business schools to a varying extent. Out of 40 investigated management master programs we found 19 programs that specifically mentioned one or more of the concepts Business Ethics, CSR and Sustainability in their program descriptions. The reasons why barely 50 percent of the programs include one or more of the concepts might be due to low demand from applicants, prioritization of other subjects and courses or that the schools do not consider these concepts to be important. Key words: Business Ethics, Corporate Social Responsibility, Sustainability, Sustainable Development, Sustainable Consumption, Management Master Programs
Plasma physics: A review and applications with special reference to inertial confinement fusion energy

A brief description of plasma, its types and fundamental requirements necessary to study the physics of plasma has been presented through this article. Information given here would be useful to those who have the basic knowledge of physics. Mathematical complications have been avoided to suit the purpose. Varied applications of plasma have been introduced. A little detail has been devoted to one of the major applications of plasma physics known as theoretical thermonuclear fusion studies. Physics of inertial confinement together with the role of self-generated magnetic field in the design of fusion targets have also been described.&#x0D; &#x0D; Himalayan Journal of Sciences 1(1): 21-24, 2003
Evaluation of occupational health and safety in formal and informal sectors, 2024 - Freetown, Sierra Leone: A workplace-base survey

Abstract         Background: In Sierra Leone, poor access to health and safety measures remains among the causes of occupational hazards. More knowledge is needed on how to support workplace safety and well-being. This study aims to assess occupational health and safety (OHS) measures in both formal and informal sectors, while adjusting for sociodemographic characteristics and compliance by sectors. Methods: A cross-sectional study of 516 workers (238 formal; 278 informal) assessed occupational health and safety (OHS) practices. Data was collected on safety policy, safety measures, and ergonomics. At 95% significance a logistic regression was computed for statistical analysis to compere compliance level with health and safety measures. Results: Significantly more formal-sector (76.9%) had safety policies than informal sector (23.7%). Most participants (81.8%) recognized the importance of emergency exits, though recognition was higher in the formal than informal sector (92.9% vs. 72.3%), respectively. Poor ergonomics were prevalent (54.5%), especially in the formal sector (62.9%). Male were significantly associated with lower odds of OHS compliance compared to female (OR = 0.1; 95% CI: 0.02–0.38; p&lt; 0.001). Regression analysis identified key factors associated with OHS compliance: formal sector employment (aOR=4.9; 95%CI: 0.91-25.90, p=0.064), and awareness of national OHS policy in the workplace (aOR=8.4; 95%CI: 1.78-39.73, p&lt;0.01). Conclusion: The study revealed a significant disparity in OHS measures between formal and informal sectors, with formal sectors showing better compliance with OHS procedures. We recommend that employers establish inclusive workplace policies and tailor training programs, and that the Ministry of Labour and Social Security implement comprehensive OHS policies.
Small State, Great Power? An Analysis of Norway’s Influence on the United Nations Security Council, 1979-80.

This thesis is a contribution to the understanding of small state power in the United Nations Security Council. The Security Council has always been a prestigious organ of the UN, and Norway has served several times since its creation in 1945. Norway was elected to sit in the Council for the period from 2021-2022, and the debate on whether it was beneficial for a small state such as Norway to sit on the Security Council surrounded by great power was ongoing. Questions of what Norway would stand to gain and spend on such an endeavour were central. This thesis analyses Norway’s third term in the Security Council from 1979-1980. The focus is on how Norway managed to influence the Council and how allied interests played a part in determining what room for manoeuvre Norway had from case to case. In 1979 Norway entered its third term in the Security Council. Norway’s term on the Security Council from 1979-1980 was characterized by severe cases where Norway often had to take its allies’ interests into account. This thesis divides the cases in the Security Council into two categories where Norway’s allies had strong interests of their own and secondly where their interests were relatively weaker. The cases being examined where allies had strong interest are the Iranian Revolution of 1979, the Soviet Invasion of Afghanistan, the Iran-Iraq War and Israeli settlements in Arab areas. The second part of cases examined are the apartheid regimes in Southern Africa, the Vietnamese invasion of Cambodia, and the Lebanese Civil War and subsequent UN peacekeeping mission though UNIFIL. Norwegian influence in the Security Council depended on three main factors: allied interests in the conflicts being debated, Soviet interest in conflicts being debated, and Norwegian self-restriction in cases where Norway was concerned about damaging its relationship with either the US or the USSR.
Tutorial in Medical Decision Modeling Incorporating Waiting Lines and Queues Using Discrete Event Simulation

In most decision-analytic models in health care, it is assumed that there is treatment without delay and availability of all required resources. Therefore, waiting times caused by limited resources and their impact on treatment effects and costs often remain unconsidered. Queuing theory enables mathematical analysis and the derivation of several performance measures of queuing systems. Nevertheless, an analytical approach with closed formulas is not always possible. Therefore, simulation techniques are used to evaluate systems that include queuing or waiting, for example, discrete event simulation. To include queuing in decision-analytic models requires a basic knowledge of queuing theory and of the underlying interrelationships. This tutorial introduces queuing theory. Analysts and decision-makers get an understanding of queue characteristics, modeling features, and its strength. Conceptual issues are covered, but the emphasis is on practical issues like modeling the arrival of patients. The treatment of coronary artery disease with percutaneous coronary intervention including stent placement serves as an illustrative queuing example. Discrete event simulation is applied to explicitly model resource capacities, to incorporate waiting lines and queues in the decision-analytic modeling example.
Should Species Distribution Models Account for Spatial Autocorrelation? A Test of Model Projections Across Eight Millennia of Climate Change

Aim: The distributions of many organisms are spatially autocorrelated, but it is unclear whether including spatial terms in species distribution models (SDMs) improves projections of species distributions under climate change. We provide one of the first comparative evaluations of the ability of a purely spatial SDM, a purely non-spatial SDM and a SDM that combines spatial and environmental information to project species distributions across eight millennia of climate change. Location: Eastern North America. Methods: To distinguish between the importance of climatic versus spatial explanatory variables we fit three Bayesian SDMs to modern occurrence data for Fagus and Tsuga, two tree genera whose distributions can be reliably inferred from fossil pollen: a spatially varying intercept model, a non-spatial model with climatic variables and a spatially varying intercept plus climate model. Using palaeoclimate data with a high temporal resolution, we hindcasted the SDMs in 1000-year time steps for 8000 years, and compared model projections with palynological data for the same periods. Results: For both genera, spatial SDMs provided better fits to the calibration data, more accurate predictions of a hold-out validation dataset of modern trees and higher variance in current predictions and hindcasted projections than non-spatial SDMs. Performance of non-spatial and spatial SDMs according to the area under the receiver operating curve varied by genus. For both genera, false negative rates between non-spatial and spatial models were similar, but spatial models had lower false positive rates than non-spatial models. Main conclusions: The inclusion of computationally demanding spatial random effects in SDMs may be warranted when ecological or evolutionary processes prevent taxa from shifting their distributions or when the cost of false positives is high.