bluuebunny/crossref_metadata_2025_split huggingface dataset:
Going Global and University Competitiveness: A framework for strategic leadership
Authors: Bakar Ahmad Naqiyuddin , Sardan Mohd Azim , Mahmud Mohammad Bastyian , Abdul Kadir Juliana Mohamed 
Published: April 2024

The terms “globalisation” and “internationalisation” of university have received a lot attention worldwide. Yet, being internationally visible does not mean that the university is properly internationalised. A university requires capacity to harnessing the power of strategic partnership and attracting renowned intellectuals to attain the global status and international appeal. University leadership must foster a holistic ecosystem in addressing community issues in line with SDGs. An integrative analytical framework for the strategic leadership combining three different areas of research: job related competencies, interpersonal competencies, and personal competencies is proposed, juxtaposing two dimensions – value and uniqueness – revealing different forms of university’s leadership.
Retrieval-Based Diagnostic Decision Support: Mixed Methods Study
Authors: Abdullahi Tassallah , Mercurio Laura , Singh Ritambhara , Eickhoff Carsten 
Published: April 2024

Background
Diagnostic errors pose significant health risks and contribute to patient mortality. With the growing accessibility of electronic health records, machine learning models offer a promising avenue for enhancing diagnosis quality. Current research has primarily focused on a limited set of diseases with ample training data, neglecting diagnostic scenarios with limited data availability.

Objective
This study aims to develop an information retrieval (IR)–based framework that accommodates data sparsity to facilitate broader diagnostic decision support.

Methods
We introduced an IR-based diagnostic decision support framework called CliniqIR. It uses clinical text records, the Unified Medical Language System Metathesaurus, and 33 million PubMed abstracts to classify a broad spectrum of diagnoses independent of training data availability. CliniqIR is designed to be compatible with any IR framework. Therefore, we implemented it using both dense and sparse retrieval approaches. We compared CliniqIR’s performance to that of pretrained clinical transformer models such as Clinical Bidirectional Encoder Representations from Transformers (ClinicalBERT) in supervised and zero-shot settings. Subsequently, we combined the strength of supervised fine-tuned ClinicalBERT and CliniqIR to build an ensemble framework that delivers state-of-the-art diagnostic predictions.

Results
On a complex diagnosis data set (DC3) without any training data, CliniqIR models returned the correct diagnosis within their top 3 predictions. On the Medical Information Mart for Intensive Care III data set, CliniqIR models surpassed ClinicalBERT in predicting diagnoses with <5 training samples by an average difference in mean reciprocal rank of 0.10. In a zero-shot setting where models received no disease-specific training, CliniqIR still outperformed the pretrained transformer models with a greater mean reciprocal rank of at least 0.10. Furthermore, in most conditions, our ensemble framework surpassed the performance of its individual components, demonstrating its enhanced ability to make precise diagnostic predictions.

Conclusions
Our experiments highlight the importance of IR in leveraging unstructured knowledge resources to identify infrequently encountered diagnoses. In addition, our ensemble framework benefits from combining the complementary strengths of the supervised and retrieval-based models to diagnose a broad spectrum of diseases.
A/B Testing of User Enrollment Forms to Enhance Diversity in the Biomedical Workforce via the National Research Mentoring Network: User-Centered Design Case Study
Authors: Syed Toufeeq Ahmed , Thompson Erika L , Johnson Jason , Latif Zainab , Kennedy Nan , Javier Damaris , Stinson Katie , Vishwanatha Jamboor K 
Published: April 2024

Abstract

Background
The National Research Mentoring Network (NRMN) is a National Institutes of Health–funded program for diversifying the science, technology, engineering, math, and medicine research workforce through the provision of mentoring, networking, and professional development resources. The NRMN provides mentoring resources to members through its online platform—MyNRMN.

Objective
MyNRMN helps members build a network of mentors. Our goal was to expand enrollment and mentoring connections, especially among those who have been historically underrepresented in biomedical training and the biomedical workforce.

Methods
To improve the ease of enrollment, we implemented the split testing of iterations of our user interface for platform registration. To increase mentoring connections, we developed multiple features that facilitate connecting via different pathways.

Results
Our improved user interface yielded significantly higher rates of completed registrations (P<.001). Our analysis showed improvement in completed enrollments that used the version 1 form when compared to those that used the legacy form (odds ratio 1.52, 95% CI 1.30-1.78). The version 2 form, with its simplified, 1-step process and fewer required fields, outperformed the legacy form (odds ratio 2.18, 95% CI 1.90-2.50). By improving the enrollment form, the rate of MyNRMN enrollment completion increased from 57.3% (784/1368) with the legacy form to 74.5% (2016/2706) with the version 2 form. Our newly developed features delivered an increase in connections between members.

Conclusions
Our technical efforts expanded MyNRMN’s membership base and increased connections between members. Other platform development teams can learn from these efforts to increase enrollment among underrepresented groups and foster continuing, successful engagement.
Genesis and interpretation of the “precariat” concept in the countries of Western and Eastern Europe
Authors: Baranov N. V. 
Published: April 2024

The purpose of the article is to systematize a number of scientific works devoted to the conceptualization of the concept of the precariat, which received active theoretical elaboration at the beginning of the XX century. The relevance of the works devoted to the precariat is explained by the speeches of representatives of this social group in European countries at the beginning of the XXI century. One of the tasks of the article is to solve the “black box” G. Standing, which denoted the relationship of the newly formed social group with social processes outlined in the works of P. Bourdieu, J. Habermas and a number of other sociologists. The author also devotes a separate role to the analysis of the precariat by scientists in Western and Eastern Europe. Sociologists of Western Europe have focused on the designation of a newly formed social group in the socio-class structure of modern society. At the end of the article, the definition of two concepts, “precariat” and “precariatization”, which can contribute to the categorization of a social group in sociological theory, is given.
Confirmatory Factor Analysis for the Strategic Management Model of the Recovery of Smes Hotel Businesses During the COVID-19 Situation
Authors: Papamo Kanokwan , Naipinit Aree 
Published: April 2024

Objective: To examine the determinants of confirmatory factor analysis of business recovery strategy factors that affect expected business outcome after being affected by the COVID-19 situation of medium and small hotels.

Theoretical Framework: This study uses a Turnaround Theory, especially the theory of Crisis Management.

Method: This research uses a quantitative approach with a questionnaire as the tool to collect the data design using a sample of 298 with the Purposive Sampling technique. The data analysis technique used is Structural equation modeling (SEM); with the AMOS device to test the statistics of the goodness of fit of the measurement model with the empirical data.

Result: From examining the statistics of the goodness of fit of the measurement model with the empirical data, it was found that the business recovery strategy model that affects expected business outcomes had been consistent with the empirical data. This met the criteria for considering the harmony between the measurement model and the empirical data. Moreover, each question had demonstrated a statistical significance level of 0.01. The results of testing the influence of all 6 paths found that all the paths had had a positive influence, and the predictive power of the expected business outcome had been 67.1 percent.

Implications: The COVID-19 outbreak has had an impact on hotel operations and revenue. As a result, demand and service activities contracted significantly. Therefore, to alleviate this negative impact and business recovery.
Originality/Value: After reviewing the literature, it was found that. It was found that various strategies were used in response to this crisis. The researcher therefore analysis on strategies for business recovery So that it can be used as a model for restoring businesses after being affected by crisis situations.
Understanding the Efficiency Levels among Cryptocurrencies: Islamic, Green and Traditional
Authors: Dias Rui , Galvão Rosa , Iran Mohammad , Alexandre Paulo , Teixeira Nuno 
Published: April 2024

Background: Islamic cryptocurrencies are different from conventional ones in that they are backed by physical assets and are based on religious principles. After the COVID-19 pandemic, cryptocurrencies showed different behavior. However, there are not many studies on the efficiency, in its weak form, of these three typical families of cryptocurrencies (Islamic, green, and traditional).

Purpose: This study compares the efficiency levels of Islamic cryptocurrencies (HelloGold), green cryptocurrencies (Cardano, NANO, Stellar, IOTA), and traditional cryptocurrencies (BTC and ETH) in the preceding period and during the geopolitical conflict between Russia and Ukraine in 2022.

Methods: This research will use Lo and Mackinlay's (1988) variance ratio methodology, and the Detrended Fluctuation Analysis (DFA) model will be used.

Results: The results indicate that the Islamic currency HGT and the green currency XNO display significant information asymmetries, rejecting the random walk hypothesis for various time intervals. Similarly, other green currencies such as XLM, ADA, and MIOTA, as well as ETH and BTC, reject the hypothesis to varying degrees and time intervals. Furthermore, the Islamic cryptocurrency (HelloGold) was anti-persistent before and during the conflict. The digital currencies ADA and BTC are persistent in both periods. ETH is in equilibrium in the pre-conflict period and becomes persistent during the conflict (0.50 - 0.56), while MIOTA and XLM are persistent during the pre-conflict period and shift to equilibrium during the Russian invasion of Ukraine in 2022. Finally, the XNO eco-currency shows the same anti-persistence characteristics during the two sub-periods.

Conclusion: These results highlight the complexity and dynamics of cryptocurrency markets, indicating that different digital currencies can exhibit different temporal behaviors regarding information efficiency and persistence or anti-persistence patterns.
The Impact of International Accounting and Auditing Standards on the Quality of Financial Reporting
Authors: Kadhim Luay Taqi , Bougatef Khemaies 
Published: April 2024

Objective: This study aims to measure the impact of applying international standards for financial reporting and auditing on the quality of financial reports for a sample of Iraqi joint-stock companies.

Methodology: The study goal is achieved by developing a special form to examine financial reports in addition to a special form to examine the reports of auditors and the extent of compliance with the adopted international standards. To achieve the research objectives, a content analysis method was used for the financial reports of a sample consisting of 18 companies listed on the Iraq Stock Exchange distributed across 8 different sectors of activity.

Results: Our findings reveal that most of these companies do not adopt international accounting standards and financial reporting, except for the banking sector. Additionally, statutory auditors do not follow international auditing standards, except for those auditing companies that apply international financial reporting standards.

Conclusion: The non-compliance to International Accounting and Auditing Standardsfor the most of listed companies could affect negatively the quality and reliability of financial information provided by them.
The Antecedents of Successful Competency Test of Indonesia Family Planning Counselors
Authors: Yuliatin Rurul , Said Laila Refiana 
Published: April 2024

Purpose: This study investigated several selected antecedents that affect the result of competency tests of family planning counselors in South Kalimantan Province, namely motivation, social environment, the institution role, self-efficacy, and job satisfaction.

Method/design/approach: This research was conducted in South Kalimantan, Indonesia, involving 330 active family planning counselors from 13 regencies/cities who had taken the competency test between 2017 and 2020. The study employed the census technique, which means all counselors were included in the sample. Data was analyzed using the 'Smart-PLS 3.0' software.

Results and conclusion: Data analysis with SmartPLS showed that Job Satisfaction, Institutional Role, and Self-efficacy significantly affect the success of the Competency Test. There were significant influences of motivation and social environment on self-efficacy. Among these antecedents, the Institution’s Role was the most substantial factor affecting the Competency Test’s success.

Research implications: Policies and human resource development strategies of the Indonesia National Family Planning Coordinating Agency were discussed as part of the research implications.

Originality/value: The research analysis yielded valuable findings regarding the key determinants that exert a substantial influence on the efficacy of competency assessments administered to family planning counselors. The results of this study can be utilized to provide valuable insights for the formulation of policies and the development of human resource strategies within the Indonesia National Family Planning Coordinating Agency.
Personalized opioid-sparing pain relief protocol for advanced robot-assisted pelvic surgery
Authors: Lifanova A. D. , Grazhdankin A. A. , Mironov P. I. , Lutfarakhmanov I. I. 
Published: April 2024

The objective was to study the safety and efficacy of a personalized opioid-sparing pain relief protocol in the context of enhanced rehabilitation after advanced robot-assisted pelvic surgery.Materials and methods. The prospective study included 19 patients who underwent surgery under combined thoracic epidural anesthesia/analgesia: general anesthesia was administered with propofol or sevoflurane/desflurane with ketamine + 6–8 ml/hour of 0.25% ropivacaine, in the postoperative period 0.125% bupivacaine was administered at a rate of 8–15 ml/hour. In the comparison group (n = 21), opioids were used as a component of general anesthesia and multimodal analgesia. Intra- and postoperative opioid consumption, pain severity, opioid-related side effects, and timing of postoperative rehabilitation were evaluated.Results. In the study group, the median milligram equivalents of morphine were significantly lower than in the control group (103 versus 148 and 91 versus 404, respectively; p = 0.001 for both comparisons). The values of the numerical pain scale did not differ significantly between the groups. Side effects were significantly lower in the treatment group (26% vs. 62%; p = 0.026). There were significant differences in the timing of intestinal function recovery, initiation of regular diet and transfer from the recovery room in favor of opioid-sparing pain relief (p = 0.037; p = 0.046; and p = 0.023; respectively).Conclusions. The use of a personalized opioid-sparing pain relief protocol in the context of enhanced rehabilitation of patients underwent the advanced robot-assisted pelvic surgery helped to reduce opioid consumption, side effects, and postoperative rehabilitation without affecting the severity of pain.
Safe and Scalable Real-Time Trajectory Planning Framework for Urban Air Mobility
Authors: Taye Abenezer G. , Valenti Roberto , Rajhans Akshay , Mavrommati Anastasia , Mosterman Pieter J. , Wei Peng 
Published: April 2024

This paper presents a real-time trajectory planning framework for urban air mobility (UAM) that is both safe and scalable. The proposed framework employs a decentralized, free-flight concept of operation in which each aircraft independently performs separation assurance and conflict resolution, generating safe trajectories by accounting for the future states of nearby aircraft. The framework consists of two main components: a data-driven reachability analysis tool and an efficient Markov-decision-process-based decision maker. The reachability analysis overapproximates the reachable set of each aircraft through a discrepancy function learned online from simulated trajectories. The decision maker, on the other hand, uses a 6-degree-of-freedom guidance model of fixed-wing aircraft to ensure collision-free trajectory planning. Additionally, the proposed framework incorporates reward shaping and action shielding techniques to enhance safety performance. The proposed framework was evaluated through simulation experiments involving up to 32 aircraft in a generic city-scale area with a 15 km radius, with performance measured by the number of near-midair collisions (NMAC) and computational time. The results demonstrate the planner’s ability to generate safe trajectories for the aircraft in polynomial time, showing its scalability. Moreover, the action shielding and reward shaping strategies show up to a 78.71 and 85.14% reduction in NMAC compared to the baseline planner, respectively.
A Novel Workflow for Predicting Seismic Reservoir Characterizations - OBN Case Study - Western Offshore, India
Authors: El Mawla Walid Abd , Goswami Saumya , Hassan Rania , Mishra Uday Shanker , Sengupta Souvik , Aly Omar , Mukherjee Anubrati , Basu S. , Mohapatra S. , Prakash Anand , Saluja Vikash 
Published: April 2024

Objectives & Scope
To identify the extend and improve the hydrocarbon productivity of the reservoirs in the area, seismic inversion study was carried out with the latest seismic image data to characterize the lithology and identify the potential reservoir distribution in the area. Advantage of OBN multi-component seismic data is the capability of providing PP & PS datasets as it helped to conduct PP-PS joint inversion enhancing the inverted shear impedance and density followed by seismic stochastic inversion for better vertical resolution.

Challenges & Procedures
Challenge #1: The presence of un-delineated karst features within H3B reservoir unit causing lots of water break through, mud loss while drilling and losing the control on the newly drilling wells. Challenge #2: To locate new save optimized candidates for infill wells securing the production plateau and minimizing the risks behind the reservoir facies/quality. To meet the objectives a seismic reservoir characterization study was carried out by conditioning seismic dataset followed by angle stack generation of PP & PS datasets. Seismic velocity from imaging product was used to trend the low frequency model building after calibration with the well logs. All the information was then used to conduct pre-stack PP-PS joint inversion to generate several attributes such as P-Impedance, S-Impedance, VpVs ratio, density. This was followed by seismic stochastics inversion to enhance the vertical resolution beyond the seismic band-limit and to reduce the uncertainties, P10, P50 & P90 cases of elastic/Petro-elastic properties have been provided. Also, a full seismic attribute analysis has been performed to help locate the potential sweet spots for better well optimization processes. In addition to that the petro-elastic attributes have been used to trend the rock-models and compensate for the environmental model in 3D mode away from the well locations.
Does retensioning of adjustable-loop cortical suspension devices improve performance: A systematic review and meta-analysis
Authors: Campbell Seth Theodore , Liu Joseph , Gowd Anirudh K. , Amin Nirav , Sardelli Matthew , Morrison Martin 
Published: April 2024

Objectives:
To date, there is conflicting evidence when comparing fixed-loop cortical suspension devices (FLDs) to adjustable-loop devices (ALDs). Some studies indicate that ALDs are inferior to FLD in regard to displacement and failure load while others show that they are biomechanically similar. The purpose of this study is to use a meta-analysis of biomechanical data to compare FLDs to ALDs with and without retensioning. It is hypothesized that retensioning the ALD will allow these devices to be biomechanically equivalent to the FLD in total unloaded displacement and failure load.

Materials and Methods:
This study sought to identify all biomechanical studies that compared fixed loops to ALD. A meta-analysis was performed to find the standardized mean difference with retensioning as a covariate.

Results:
The analysis of isolated tests showed that retensioning reduced the cyclic ALD displacement in comparison to non-retensioned ALD; however, both the ALD with and without retensioning had significantly higher cyclical displacement and significantly lower failure load compared to the FLD. In the meta-analysis of the animal model data, there was no significant difference between the ALD with retensioning and the FLD.

Conclusion:
This analysis suggests that retensioning reduces displacement of an ALD, with displacements measured in animal bone testing showing no significant difference as compared to FLD. However, in the device-only model, the ALD with retensioning and the ALD without retensioning had significantly higher cyclical displacement and significantly lower load to failure compared to the FLD. These data suggest that retensioning may be beneficial. However, there is significant heterogeneity in the pooled studies which limit the strength of this conclusion.