bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Association between Psoriasis and Risk of ST-Elevation Myocardial Infarction among African American Patients
Authors: Krdi Ghena , Sparling Kennedy , Movahed Mohammad Reza , Hashemzadeh Mehrtash , Hashemzadeh Mehrnoosh 
Published: February 2025

AbstractBackground/ObjectivesSeveral studies have attempted to investigate the association between psoriasis and the incidence of cardiovascular disease (CVD) including ST-segment elevation myocardial infarction (STEMI), possibly making psoriasis a risk factor for the development of CVD. African American (AA) patients have a higher prevalence of cardiovascular disease risk factors, representing a racial health disparity. There are very limited studies on the association between psoriasis and STEMIs among this specific patient population. This study aims to explore if an association exists between a diagnosis of psoriasis and the incidence of STEMI among AA patients.MethodsPatients with specific ICD-10 codes for psoriasis and STEMI were included from the National Inpatient Sample (NIS) data. The rates of STEMI in patients with an established diagnosis of psoriasis were calculated and compared between AA and non-AA patients. An additional multivariate analysis was performed to adjust for CVD risk factors including age, gender, hypertension, hyperlipidemia, smoking, and diabetes.ResultsThe analysis revealed no significant association between a diagnosis of psoriasis and STEMI incidence among AA patients. However, there was a significant positive association between psoriasis and STEMIs with p-value <0.001 among the total population despite race. After adjusting for confounding variables, there remained no significant association between psoriasis and STEMI among AA patients, and there was a significant negative association between psoriasis and STEMI among non-AA patients.ConclusionThese findings suggest that psoriasis is not directly associated with STEMI among AA and non-AA patients, especially when controlling for confounding risks. Given the low prevalence of psoriasis among AA patients and the large burden of CVD in this patient population, further research will need to be conducted possibly guiding early CVD risk assessment and psoriasis management in AA patients.
Transferrin receptor-binding blood-brain barrier shuttle enhances brain delivery and efficacy of a therapeutic anti-Aβ antibody
Authors: Vega Marta Ramos , Hansen Henrik H. , Jensen Camilla Stampe , Alexiou Evdoxia , Madsen Martin R , Wichern Franziska , Skytte Jacob Lercke , Salinas Casper Graversen , Sotty Florence , Jensen Allan , Vergo Sandra , Hecksher-Sørensen Jacob 
Published: February 2025

ABSTRACTTransferrin receptor-1 (TfR1) transcytosis-mediated delivery of therapeutic monoclonal antibodies across the blood-brain barrier (BBB) is a promising concept in drug development for CNS disorders. We sought to investigate brain delivery and efficacy of Aducanumab (Adu), an anti-Aβ antibody, when fused to a mouse TfR1-binding Fab fragment as BBB shuttle (TfR1-Adu). Automated 3D light sheet fluorescence imaging coupled with computational analysis was applied to evaluate drug IgG distribution and plaque counts throughout the intact brain of transgenic APP/PS1 mice. TfR1-Adu demonstrated enhanced brain delivery and more homogeneous distribution after both acute and chronic dosing in transgenic APP/PS1 mice compared with unmodified Adu. Also, importantly, only unmodified Adu showed perivascular labelling. While high-dose Adu promoted Aβ plaque depletion in multiple brain regions, similar plaque-clearing efficacy was achieved with a five-fold lower dose of TfR1-Adu. Furthermore, low-dose TfR1-Adu demonstrated greater capacity to reduce congophilic plaque burden. Collectively, these observations strongly support the applicability of TfR1-enabled BBB shuttle strategies to improve brain delivery and plaque-clearing efficacy while mitigating the risk of vascular-associated amyloid-related imaging abnormalities (ARIA) adverse effects associated with current Aβ immunotherapeutics.
Mission imputable: Effects of missing data processing on infectious disease detection and prognosis
Authors: Roy Suravi Saha , Nguyen Ngoc Thi , Zuniga Agustin , Sarhaddi Fatemeh , Lagerspetz Eemil , Flores Huber , Nurmi Petteri 
Published: February 2025

AbstractBackgroundMissing data in medical datasets poses significant challenges for developing effective AI/ML pipelines. Inaccurate imputation can lead to biased results, reduced model performance, and compromised clinical insights. Understanding how different imputation methods affect AI/ML model performance is crucial for ensuring accurate clinical findings.ObjectiveThis study systematically investigates the effects of different imputation methods on AI/ML model performance and the clinical implications of these methods.MethodsWe investigate the impact of four different missing data strategies on the performance of common classification algorithms for analyzing medical data. The performance was evaluated based on sensitivity and specificity metrics for the tasks of predicting COVID-19 diagnosis and patient deterioration. We also perform feature analysis to understand the clinical implications the choice of imputation method has.ResultsOur findings show that the choice of imputation method significantly affects the performance of AI/ML techniques and the clinical conclusions drawn from the data. The optimal handling of missing values depends on (i) the composition of the features with missing values, (ii) the rate of missing values, and (iii) the pattern of the missing features. Using COVID-19 diagnosis and patient deterioration as representative examples of clinical tasks, our results indicate that MICE imputation yields the best overall performance, resulting in a 26% improvement in accuracy compared to baseline methods. Specifically, for predicting COVID-19 diagnosis, we achieved a sensitivity of 81% and specificity of 98%, while for patient deterioration, the sensitivity was 65% and specificity was 99%.ConclusionThis study demonstrates the critical impact of missing data imputation on AI/ML model performance and the clinical insights derived from these models. Our findings underscore the importance of selecting appropriate imputation techniques tailored to the specific characteristics of medical data to ensure accurate and reliable AI/ML predictions.
Stability of emotional and behavioral problems in autistic children and adolescents during the COVID-19 pandemic
Authors: Boy Clemens , Truijens Femke L. , Louwerse Anneke , Visser Kirsten , Bastiaansen Dennis , Ester Wietske A. , Van Rijen Elisabeth H.M. , Van der Hallen Ruth , Dekker Linda P. 
Published: February 2025

Purpose
The lasting impact of the COVID-19 pandemic on autistic children and adolescents remains uncertain. Disruptions to routines, social communication and support systems presented unique challenges. The existing body of research has produced inconclusive results, necessitating further investigation to elucidate this ambiguity. This study aims to provide clarity regarding the emotional and behavioral functioning of autistic youth in response to COVID-19 related lockdowns. We further explore distinct subgroups of Autism Spectrum Disorder (ASD), investigating the socially inflexible and demand avoidant profile.

Design/methodology/approach
To surpass short-term outcomes, this study examined emotional and behavioral problems (EBPs) by means of the Brief Problem Monitor in 69 autistic youth before, during and after a national lockdown in the Netherlands. Using individualized measurement (Reliable Change Indices), group-level changes were discerned. An exploratory analysis compared individuals from the socially inflexible and demand avoidant profile.

Findings
Both on a group and individual level, this findings suggest stability of EBPs in response to the COVID-19 pandemic and its corresponding measures. However, while the demand avoidant profile showed significantly more EBPs compared to the socially inflexible profile prior to the pandemic, the two profiles showed similar EBPs levels during and post-pandemic. Taken together, autistic youth and their families may have exhibited unique adaption strategies toward challenges caused by the pandemic and managed them better than initially expected.

Originality/value
The findings urge to look beyond group level functioning, and rather into nuances in ASD profiles to tailor interventions and support to the needs of autistic youth and families. A novelty of the study consists in having identified two different autism profiles to explain differences among subgroups of ASD.
A light weight magnetic coupler structure for interoperability and robust misalignment with primary-side impedance tuning for wireless power transfer systems to electric vehicles
Authors: Yadav Ankur , Bera Tushar Kanti 
Published: February 2025

Purpose
Wireless power transfer (WPT) technology is explored as a promising solution for electric vehicle (EV) charging due to its convenience and potential to overcome traditional charging limitations. This study aims to present a novel lightweight magnetic coupler design, square grid structure (SGS), specifically aimed at enhancing interoperability and robustness in the presence of misalignments for primary-side impedance tuning WPT systems adapted for EVs.

Design/methodology/approach
The proposed coupler design uses the finite element analysis method through ANSYS Electronics Desktop software for optimization. A comprehensive comparative analysis is conducted, focusing on critical magnetic parameters such as coupling coefficient (k), mutual inductance (M) and self-inductance (L) for different air gaps. Three other coupler designs, including circular, rectangular and DD configurations, are considered in the evaluation process. Additionally, the performance of the proposed coupler is assessed through misalignment tolerance in different directions, magnetic flux density (B), magnetic field strength (H), Energy density, Quality factor (Q) with mesh generation and thermal analysis using ANSYS Icepak design software.

Findings
The study presents findings from the comprehensive analysis, highlighting the performance of the proposed SGS coupler in terms of different key magnetic parameters, misalignment tolerance in different directions and various operational conditions. To verify the result for Practical implementation, MATLAB Simulink demonstrates a remarkable power transfer efficiency (PTE) of 94\%, exceeding alternative coupler designs. These findings emphasize the potential of the lightweight magnetic coupler to enhance the performance and practicality of WPT systems for EVs.

Research limitations/implications
Although the study offers valuable insights into the proposed SGS coupler design, there might be restrictions due to their hardware design being complex compared to other couplers and particular operating circumstances or environmental elements that were not considered during the investigation. Future studies could investigate these areas, focusing more on the shielding method to provide a more thorough knowledge of the coupler’s functionality.

Originality/value
This work advances WPT technology by presenting a novel SGS coupler design, which provides a robust and efficient solution for EV charging. The suggested lightweight magnetic coupler’s novelty and value in addressing the growing need for sustainable transportation solutions are highlighted by the significant improvement of 94% PTE.
Determining optimal installation of renewable distributed generators in the radial distribution system considering technical-economic aspects by using energy valley optimizer algorithm
Authors: Chinh Nguyen Cong , Tung Nguyen Nhat 
Published: February 2025

Purpose
This study aims to introduce an effective optimization algorithm for finding the suitable penetration of renewable distributed generators (RDGs) in the power system. The target of this research is to minimize the total costs, including the cost of emissions, the cost of purchasing electricity from the primary grid and the cost of branch power losses.

Design/methodology/approach
Energy valley optimizer (EVO) is applied to solve the optimization problem for determining the integration of photovoltaic units and wind turbine units in the system. This study considers the time variation of load demand and output power of units to improve the quality of the found solution. Simulation results are collected for evaluating the performance of the used methods in the same conditions.

Findings
The results indicated the huge economic and technical benefits from adopting the optimal solution of placement and sizing of RDGs in the power system. Besides, the outstanding efficiency of EVO is also proven through comparison with sunflower optimizer, drawer algorithm, osprey optimization algorithm, genetic algorithm, particle swarm optimization and artificial bee colony algorithm.

Originality/value
The mathematical models for the objective function and the constraints are appropriately described for the optimization problem. A simulation program for applying the optimization algorithms to the above problem is developed in the MATLAB software. The simulation results demonstrated the excellent benefits not only economically but also technically for the hybrid distribution system.
The roadblocks to success: exploring challenges faced by BA-level students in practicum experiences in Jordan
Authors: Altakhaineh Abdel Rahman Mitib , AlTalafeeh Asma , Al-Ziadat Mariam 
Published: February 2025

PurposeThis study aims to explore the challenges faced by BA students in the Applied English program at the University of Jordan during their practicum experience, focusing on the first semester of the academic year 2022/2023. It seeks to shed light on training environment issues and workplace skills while considering the cultural and economic context of Arab countries, particularly Jordan.Design/methodology/approachThe study employed a qualitative research design using semi-structured focus group discussions. A sample of 24 students were selected through convenient sampling, ensuring accessibility as the researchers are also instructors at the same university. Data collection emphasized ethical considerations, including informed consent and ensuring privacy and confidentiality.FindingsThe study identified significant challenges related to the training environments and the alignment of tasks with learning objectives. Familial and cultural factors were found to influence the students’ experiences, highlighting the importance of context-specific support. Recommendations were provided to enhance the practicum experience by improving training site selection, refining tasks and offering targeted support systems. Additionally, the study highlights the potential of virtual training environments as a future area of exploration.Originality/valueThis research is among the first to address practicum challenges faced by BA students in the Arab region, with a specific focus on Jordan. By situating findings within the cultural and economic contexts of the region, the study provides unique insights for tailoring support systems and training programs. The results contribute to a better understanding of how to prepare graduates for successful careers in similar contexts.
Integrating skill knowledge and multimodal information to enhance 3C assembly skills
Authors: Liu Liqun , Xie Yupeng , Liu Ting 
Published: February 2025

Purpose
To solve the 3C assembly task, the traditional robot needs a lot of manual coding and the skills learned are faced with the problems of adapting to the scene and task diversity, lack of generalization ability and so on. This paper aims to propose a skill knowledge and multimodal information fusion algorithm (SKMIF).

Design/methodology/approach
This method combines skill knowledge and multimodal information in large language model to enhance 3C assembly task skills. The SKMIF algorithm is used to conduct experiments in simulated and real 3C assembly tasks, which verifies the effectiveness of the method in single-task and multi-task scenarios, and solves the problem of insufficient generalization ability of automated programming.

Findings
Through the transfer from simulation to reality, the assembly strategy learned in the virtual environment is applied to the real scene, which significantly improves the assembly accuracy and success rate in the real environment. The verification of the enhanced 3C soft-row line assembly task shows that the success rate is 96%.

Originality/value
This paper proposes a new algorithm to enhance 3C assembly skills, to improve generalization ability and adaptability to multitasking environments.
Optimizing office space: the role of passive occupancy
Authors: Einola Kiia Aurora , Dooley Ken 
Published: February 2025

Purpose
This study aims to examine how active occupancy, passive occupancy and clean desk policy impact the optimal size of a desk-sharing office. Passive occupancy refers to a situation where a desk remains occupied because workers have left personal items on it, even though they are not present. This occupancy state makes it unavailable for others, but presence sensors do not detect it as occupied. Clean desk policy defines how long these workers may be absent without cleaning their desks.

Design/methodology/approach
Desk-level occupancy data from 10 sites in the Nordics was collected and used to calculate office utilisation with different clean desk policy time delays. The data was gathered over 6 months from 7,522 sensors.

Findings
Clean desk policy time delay had a significant impact on the office utilisation. Considering passive occupancy with a 120-min clean desk policy time delay added, on average, 86.4% on the calculated utilisation, almost doubling it.

Research limitations/implications
Data was focused on three Nordic countries. The implications should be tested in other regions as well.

Practical implications
If organisations neglect passive occupancy, they may consider their office less occupied than it is. Accurate data can help organisations to confidently right-size their office space.

Originality/value
Passive occupancy has not been considered in terms of office sizing, despite its significant impact on desk availability. Clean desk policy has been discussed in previous literature, but its impact on office sizing remains unknown.
CEO career variety and ESG disclosure: evidence from Indonesia
Authors: Rahmatulloh Sahrian Aditya , Anridho Nadia , Ningsih Sri , Fitriani Nurul , Lee Siew Peng 
Published: February 2025

Purpose
This study aims to investigate the influence of CEO career variation as one of the internal factors influencing the decision-making in environmental, social and governance (ESG) disclosure.

Design/methodology/approach
Using data from Indonesian nonfinancial companies publicly listed on the Indonesia Stock Exchange from 2018 to 2021, this study uses a quantitative analysis approach to explore the relationship between CEO career variation and ESG reporting decisions.

Findings
This study reveals that CEOs who have greater career variety exhibit reduced involvement in ESG disclosure, in which a relationship is particularly pronounced in young firms but reversed in older ones where CEO career variety correlates positively with ESG disclosure.

Research limitations/implications
This study is limited to nonfinancial companies in Indonesia, and the voluntary nature of ESG reporting during the chosen period may impact the generalizability of findings. Future research could explore other contextual factors and extend the investigation to different industries or regions.

Practical implications
This study finds that CEOs with diverse career backgrounds tend to disclose less ESG information, implying that shareholders should consider candidates’ backgrounds and experiences when selecting future CEOs. This highlights the importance of choosing CEOs with relevant experience to ensure a strong commitment to sustainable business practices and social and environmental goals.

Originality/value
This study applies the upper echelon theory to investigate the previously unexplored relationship between ESG disclosure and CEO careers in a variety of industries, employers, functions and countries.
“Everything is figure-out-able”: challenges of Aer Cosmetics, Inc
Authors: Singh Nitin Kumar , Rossetti Federica , Byrne Erin 
Published: February 2025

Research methodology
The case describes a real company, real people and real situations. The authors have used real names other than the name of the cosmetic formulation company and the product design company – which the authors address as “the Florida company” and “the product design company,” respectively. The authors used both secondary and primary data to develop this case study. The case originated from the guest lecture given by Paige in one of the author’s classes. Following her guest lecture, the authors asked her permission to develop her story into a case study, and she graciously consented. The authors obtained background information about the company – Aer Cosmetics, from the company website, news articles and the TEDx talk delivered by Paige. The authors followed it with Paige’s interview, which the authors recorded and transcribed. Based on this interview and the information collected from the other sources, the authors developed the final version of the case study. Paige read and approved the final version for its factualness and sequence of events. The case was then informally reviewed by professors who have published their case studies in the target journal. The authors revised the case study based on this feedback and again obtained Paige’s approval on the case text before submission to the journal.

Case overview/synopsis
This case is set in May 2024. Paige DeAngelo, the CEO of Aer Cosmetics, was disappointed with the sales of her newly launched sustainable mascara product. She had been a student entrepreneur at Drexel University for the last three years. She developed her product with the help of the university incubator and other entrepreneurial support systems available at Drexel and outside. Paige had graduated in December 2023. Drexel University allowed its students to remain in their incubator program only up to one year after graduation. Thus, with seven months remaining, it is time for Paige to decide how she would manage the next growth phase of her business. The students are put into the shoes of Paige DeAngelo. They are asked to decide whether to extend their stay in the incubator program, venture out and be an independent business entity, pitch the company for acquisition by corporations, or leverage other entrepreneurial support systems in the environment to grow the company. Students need to craft a strong argument, either supporting the options they advocate for or opposing those they reject.

Complexity academic level
This case was written primarily for upper-division undergraduate courses but is also suitable for MBA courses.