Reviewerly/exHarmony huggingface dataset:
Semi-supervised calibration of noisy event risk (SCANER) with electronic health records

Electronic health records (EHR), containing detailed longitudinal clinical information on a large number of patients and covering broad patient populations, open opportunities for comprehensive predictive modeling of disease progression and treatment response. However, since EHRs were originally constructed for administrative purposes not for research, in the EHR-linked studies, it is often not feasible to capture reliable information for analytical variables, especially in the survival setting, when both accurate event status and event times are needed for model building. For example, progression-free survival (PFS), a commonly used survival outcome for cancer patients, often involves complex information embedded in free-text clinical notes and cannot be extracted reliably. Proxies of PFS time such as time to the first mention of progression in the notes are at best good approximations to the true event time. This leads to difficulty in efficiently estimating event rates for an EHR patient cohort. Estimating survival rates based on error-prone outcome definitions can lead to biased results and hamper the power in the downstream analysis. On the other hand, extracting accurate event time information via manual annotation is time and resource intensive. The objective of this study is to develop a calibrated survival rate estimator using noisy outcomes from EHR data. In this paper, we propose a two-stage semi-supervised calibration of noisy event rate (SCANER) estimator that can effectively overcome censoring induced dependency and attains more robust performance (i.e., not sensitive to misspecification of the imputation model) by fully utilizing both a small-labeled set of gold-standard survival outcomes annotated via manual chart review and a set of proxy features automatically captured via EHR in the unlabeled set. We validate the SCANER estimator by estimating the PFS rates for a virtual cohort of lung cancer patients from one large tertiary care center and the ICU-free survival rates for COVID patients from two large tertiary care centers. In terms of survival rate estimates, the SCANER had very similar point estimates compared to the complete-case Kaplan Meier estimator. On the other hand, other benchmark methods for comparison, which fail to account for the induced dependency between event time and the censoring time conditioning on surrogate outcomes, produced biased results across all three case studies. In terms of standard errors, the SCANER estimator was more efficient than the KM estimator, with up to 50% efficiency gain. The SCANER estimator achieves more efficient, robust, and accurate survival rate estimates compared to existing approaches. This promising new approach can also improve the resolution (i.e., granularity of event time) by using labels conditioning on multiple surrogates, particularly among less common or poorly coded conditions.
A Study on the Step-wise SW Competency Model and Application: Focusing on the Case of an IT Company

Existing SW competency models and development platforms are fragmented, and researched and implemented mainly by suppliers such as elementary, middle and high schools and universities. This results in competency mismatches including weak connection with companies, which generate the biggest demand for SW workforce. From the perspective of companies which are desperate about proactive response to rapid technological changes in the era of the fourth industrial revolution, existing models and platforms failed to present appropriate alternatives for fostering SW talent and genuine competency. Backed by the cases of domestic IT companies (home appliances / information and communication/semiconductor fields), this paper presented the directions of cultivating SW workforce envisioned by companies. The proposed directions have been integrated into a corporate SW competency model to ensure the organic relationship in the process of talent development taken place in universities and companies. By applying the leadership pipeline, which was mainly used for succession planning, to a technology field of SW, this study also derived a differentiated SW competency model that blurs the boundary between technology and business management. In particular, it was possible to secure the practicality of the step-wise SW competency model by mapping out the necessary competencies based on the roles of SW workforce by growth stage and the ideal characteristics of talent required by the private sector. In addition, it was possible to verify its effectiveness by creating and applying a SW programming test based on the derived SW competency model.
Application and development of augmented reality in the medical field

This paper provides a systematic review of augmented reality (AR) technologies and their applications in medical diagnosis and treatment from 1988-2023.The paper is categorised by key technologies of augmented reality and medical diagnosis and treatment applications.For AR key technologies, 67 articles were researched.Among them, AR key technologies can be divided into three methods: display, calibration and tracking, with video perspective display technology dominating the field.For calibration technologies, 17 articles were included in the review, and we discussed methods based on graphic markers, optical markers and markerless calibration, respectively; for positional tracking technologies, 15 articles were counted, and we discussed methods based on markers, simultaneous localisation and map building, and optical flow-based tracking, respectively; for application areas of AR technologies, simulation teaching and training, surgical guidance and telemedicine were included in the review Scope.
IMPACT OF SCIENTIFIC PRODUCTIVITY ON DIFFERENT GEOGRAPHICAL AREAS

This study aims to relate the impact of scientific productivity through research and the development of different geographic areas considering the relation of variables of per capita income, education, consumption, and trade between countries, belonging to the Organization for Economic Cooperation and Development.The impact of scientific productivity relates to the policies that countries invest in through their universities.Therefore, it has focused on allocating resources that the countries delivered for research and development.The research showed classification by geographical area, showing the relevance of geographical location in scientific development by a critical analysis of the number of citable documents on Eastern Europe, Middle East, Northern America, Pacific, and Western Europe shown in the regression model, realized in the methodology for the hypothesis test of the parameter estimation (slope) p-values, determining that is significant.On the other hand, in the countries grouped in the Organization for Economic Cooperation and Development, the hypothesis test showed a significant result, implying a direct relationship between the number of citable documents and the countries with higher economic development.Finally, countries with higher economic development conduct more research that generates an impact on scientific production and economic development.
IMPACT OF STRATEGIC CAPABILITIES AND ORGANIZATIONAL STRUCTURE ON ENTREPRENEURSHIP IN PALESTINIAN TELECOMMUNICATIONS COMPANIES

Palestine Telecommunications Companies (PTC) have experienced significant growth in recent years.The industry has become increasingly competitive, forcing companies to develop strategic capabilities to succeed in the market.In addition, the organizational structure of these companies plays a critical role in their ability to innovate and pursue entrepreneurial activities.However, this study aims to examines the impact of strategic capabilities and organizational structure on entrepreneurship in PTC.The study used a quantitative approach, using a survey design to gather data from 187 executives in the PTC industry.The participants' perceptions of strategic capabilities, organizational structure, and entrepreneurship was collected through close-ended questions using a five-point Likert scale.SmartPLS4 was used to analyze the data.The results indicate that both strategic capabilities and organizational structure positively impact entrepreneurship and the competitive advantage in PTCs.Furthermore, entrepreneurship has a mediator effect between the variables.These findings highlight the importance of fostering an entrepreneurial culture in PTCs to leverage strategic capabilities and organizational structure for the sustained competitive advantage.This study has significant implications for managers and policymakers in the telecommunications industry, emphasizing the need to support innovation and creativity.However, this paper provides evidence that the integration of entrepreneurship into the strategic management process can enhance a company's ability to compete and succeed in a rapidly changing business environment.As such, policymakers and industry practitioners should pay more attention to foster an entrepreneurial mindset and creating an environment that supports innovation and creativity in Palestinian telecommunications companies.
OPTIMIZED MULTI-CRITERIA HYBRID MATCHING METHOD (MCHMM) USING CRITIC, AHP, AND GALE-SHAPLEY ALGORITHMS: MATCHING PEOPLE WITH COVID-19 VACCINATION CENTERS

The Covid-19 vaccination process faced many problems; "who gets vaccinated" and "where is the nearest vaccination center" are two questions that entail a multi-Criteria problem.Such problems arise in the most inopportune time of the Covid-19 pandemic.The matching process depended on many variables: the current health state of the person, insurance company, location, and residency.Such variables are not static and differ from one country to another.Hence, this paper presents a new Multi-Criteria Hybrid Matching Method (MCHMM).MCHMM is a hybrid matching method extended from three multi-Criteria decision-making methods.MCHMM uses the strengths of three methods: Analytic Hierarchy Process (AHP), and Gale-Shapley algorithm.To fully automate the decision-making process of matching the MCHMM, which relies on CRITIC to develop the weight of Criteria, the weights are then used in AHP to develop the preference list of the Gale-Shapley algorithm (GS).Then the GS algorithm will produce the matched sets, eliminating the human factor and interference like favoritism in deciding.Such elimination is essential to reduce long waiting queues, proclivities, tendencies, biases, preconceptions, prejudices, and predispositions.Hence, reason and logic will guide the decision process, ridding it of impurities.MCHMM will match the person with the vaccination center most suited to her/his case, not based on distance only but also based on the Criteria s/he chooses.MCHMM is a unique hybrid algorithm that solves a multi-Criteria problem taking advantage of other algorithms.Furthermore, MCHMM can be generalized and can be used in any similar situation.
THE ROLE OF LITERATURE AND ART IN CONSTRUCTING SOCIAL THOUGHTS

The individual"s thought is a socio-psychological construction that has rendered them a submissive subject through systematic procedures that have taken place throughout history.These practices have been vitally maintained and supported by power holders solely because having a subordinate individual would guaranty the continuation of protecting their interests.Many aspects of life, including art and literature, have a crucial influence on developing a submissive individual.However, Marxists, in particular deviant Marxists, made significant efforts to subvert and disrupt the established and conservative modes of thought by which individuals were instilled.The methodical or scientific novelty of this work lies in its analysis of the social and psychological ways that have influenced the formation of a submissive individual.By investigating the historical practices that have reinforced this construction, the work provides insight into the ways in which power is maintained and perpetuated in society.Moreover, the trajectory in which the discussion accounts primarily for the efforts made by Marxists to disrupt these practices and challenge established modes of thought represents a significant contribution to our understanding of social change.In a word, the provided analysis of the role of power and ideology in shaping the individual"s thought offers a helpful assessment regarding the ways that are needed by individuals to resist and subvert overpowering ideologies.
JOB SATISFACTION IN THE CONTEXT OF COVID-19: EVIDENCE FROM THE JORDANIAN PUBLIC AND PRIVATE SECTORS

The purpose of this paper is to identify employee perceptions regarding the following variables: physical, economic, and social environments, job load, stress, and job satisfaction in both Jordanian private and public sectors.Using structured questionnaires, primary data were collected from 230 employees of public and private organizations, working from home (WFH) during and after the COVID-19 pandemic.Structural equation modeling (SEM) was conducted using SmartPLS-3 software and SPSS, multiple regression, independent sample t-test, and descriptive statistics to analyze the data.The results indicate that the most important determinants include both economic and social environments, in addition to job load and stress, which all have a statistically significant effect on job satisfaction among employees.Moreover, there are statistical differences in the level of job satisfaction, specifically in the physical environment, job load, and stress, in favor of private sector employees.This study recommends that the public sector support WFH employees, clarify the general employment terms, and master new online office abilities and virtual work communication skills.
Financial Fraud of Listed Companies: The Case of the Luckin Coffee Incident

The rapid development of China's economy has increased the number of listed companies.Some listed companies use accounting information to carry out targeted financial fraud.This behavior distorts the financial information of listed companies, seriously misleads investors' investment judgments, endangers the vital interests of investors, and undermines the fairness of the trading market.This article takes Luckin Coffee as the research object, and conducts a case study on its financial fraud.
Automatically identifying the motivations of Facebook mention to scholarly outputs based on Light GBM

Purpose/Significance] The article investigated the automatic identification of the motivation of Facebook mention to scholarly outputs based on Light GBM algorithm, in order to achieve more in-depth usage of Facebook mention on a large scale.[Methodology/Procedure] Based on three types of contextual data, including mentioned scholarly outputs, Facebook users who post scholarly outputs, and text of Facebook posts to scholarly outputs, promising relevant features were extracted, and machine learning algorithms were used to automatically identify the motivations.[Results/Conclusions] (1) Features significantly correlated to the motivation of Facebook mention are identified in all three types of contextual data.In particular, relevant features are the altmetric attention score, the number of collaborative countries, the number of followers, the number of likes, the identities of Facebook users who post scholarly outputs and the number of comments on Facebook posts; (2) The prediction precision of the Light GBM classification model for motivation of Facebook mention was 0.31.In comparison, the classification precision without the text features of Facebook posts was 0.35, which was higher than the overall feature combination.The classification precision with only the post text features was 0.27.After combining the length and language of posts, the precision was improved to 0.30;(3) The classification precision of Facebook motivation has a positive correlation with users' activity.After combining all features, the classification precision of the first quartile users in terms of productivity reached 1, the classification precision of the second quartile was 0.36, and for the third quartile, the classification precision was 0.32.In conclusion, considering the high complexity of automatic classification of motivation of Facebook mentions, the study has achieved relatively high classification precision and could provide reference for future studies.
Identification of potential interdisciplinary cooperative topics based on co-word network: Taking LIS and computer science as an example

Purpose/significance] Interdisciplinary knowledge fusion plays a key role in promoting the development of interdisciplinary integration and providing new ideas for interdisciplinary cooperative research.This study sets out to identify potential interdisciplinary cooperative topics between Library and Information Science (LIS) and Computer Science.[Method / Process] We built an interdisciplinary co-word network to identify potential interdisciplinary cooperative topics by closed and opened irrelevant knowledge discovery methods.We also constructed the topic interdisciplinary cooperation potential index (TICPI) to calculate the interdisciplinary cooperation potential of the topic and found the best contact path of the cooperation topic by constructing the practicable value (PV) of the contact patch.[Result / Conclusion] The experimental data suggested that both methods can identify the same potential interdisciplinary cooperative topics, such as knowledge service & matrix decomposition, online comments & social media processing, academic text & generative adversarial network, network public opinion & smart home.Exploiting the cooperation potential of these topics can help the knowledge fusion between disciplines.
Application of article-level metrics and comparison with journal-level metrics in differentiated document recommendation: An empirical study in artificial intelligence field

The measurement indexes of literature include citation frequency, H index, etc.The evaluation of core journals mainly relies on the indexes such as impact factor or comprehensive evaluation method.With the in-depth development of research, these indicators are not comprehensive and accurate for literature and journals.Therefore, according to various literature needs for different researchers, "core literature" in this study was divided into three types: classical, popular and frontier; and measurement system of document value was constructed with comprehensive use of entropy weight method and principal component analysis from the perspective of Article-Level Metrics.In the case study of artificial intelligence (AI), three types of document sets were acquired with the threshold value of specific indicators, and then measured by a combination of multi-index, achieving identification and recommendation of core documents for different research needs.At the same time, this paper further calculates the total score of the journals according to the literature score, and finds that the journal distribution of different types of core literature is quite different.The difference between the ranking of journal scores and the ranking of impact factor after literature classification is relatively large, but the ranking of journal normalized Eigenfactor and the ranking of impact factor are similar.These research directions, loading journals, selected indicators, and temporal effects in three types of core documents were revealed in the study, which can provide a certain reference for promoting scientific research in AI and launching scientific research management services.
Potential influential topics in information science based on citation structural variation approach

This study aims to identify potential influential literature and potential influential topics in the field of information science (IS).Using citation structural variation approach, provided by CiteSpace, we discerned the potential influential theses in IS.Then, we proposed an analyzing framework based on"citation network-citation structural variation-citation cluster," which is used to discern the potential influential topics in IS.Using the structural variation approach, we analyzed the contents and features of potential influential theses.The potential influential topics, discerned by the "citation network-citation structural variation-citation cluster" framework, corroborated the existing knowledge base to some extent and seemed to be divergent and intermingled.Such potential impact literature and potential impact research topics are of certain reference value for future frontier research.
Using online tools to measure digital competence of foreign language teachers

The context of the study is the global crisis caused by the COVID-19 pandemic and by the war in Europe on the territory of Ukraine, which actualized significant digital transformations in the educational processes.This article substantiates the need for measuring the digital competence of future teachers of foreign languages as an important component of their professional competence.Taking into account the theoretical research of Ukrainian and foreign scientists on the problem under study, the concept of "digital competence of foreign language teachers" is specified; the areas and levels of digital competence are described according to the Professional Teacher's Standard and the Description of the teacher's digital competence.Three broad directions for measuring digital competence are orientation in the information space, use of electronic (digital) educational resources, and application of digital technologies in the educational process.The major method for evaluating digital competence level of a teacher is self-assessment and self-reflection by means of online tools that can be used in combination.The following online tools for measuring digital competence of foreign language teachers are described in the article: the national test "Digital chart for teachers", The Digital Competence Wheel, My Digital Skills.Each online tool is characterized in terms of its components, aspects of digital competence under testing, peculiarities of usage, and results obtained after testing.It is concluded that it is important to give the teacher freedom in choosing self-assessment tools and their further use for their own professional needs, such as for building a trajectory of professional self-improvement and self-development.Further research can be focused on the methodology of enhancing English teachers' digital competence.
On solutions of the distributional Bellman equation

&lt;abstract&gt;&lt;p&gt;In distributional reinforcement learning (RL), not only expected returns but the complete return distributions of a policy are taken into account. The return distribution for a fixed policy is given as the solution of an associated distributional Bellman equation. In this note, we consider general distributional Bellman equations and study the existence and uniqueness of their solutions, as well as tail properties of return distributions. We give necessary and sufficient conditions for the existence and uniqueness of return distributions and identify cases of regular variation.&lt;/p&gt; &lt;p&gt;We link distributional Bellman equations to multivariate affine distributional equations. We show that any solution of a distributional Bellman equation can be obtained as the vector of marginal laws of a solution to a multivariate affine distributional equation. This makes the general theory of such equations applicable to the distributional reinforcement learning setting.&lt;/p&gt;&lt;/abstract&gt;