bluuebunny/crossref_metadata_2025_split huggingface dataset:
Basics of brand building in the banking industry
Authors: Morozova Nadiia , Denchyk Iryna 
Published: April 2024

This article explores the fundamentals of brand building in the banking industry, emphasizing the increasing importance of brand management in a globalized and competitive market. The study delves into the theoretical and practical aspects of brand formation, drawing on insights from scholars such as K. Keller, D. Aaker, and others. It highlights the role of relationship marketing strategies in cultivating customer loyalty and underscores the significance of employees in brand building, particularly in the retail banking sector.
The research reveals that service quality is a critical factor influencing customer satisfaction and loyalty, with a specific focus on electronic banking services. It discusses the challenges in building and promoting bank brands, including attracting consumer attention, promoting recall, and creating lasting relationships. The article also addresses the evolving landscape of the banking sector, emphasizing the impact of technology integration and heightened competition.
Corporate image and reputation emerge as key elements in ensuring sustainable business growth, with a positive image contributing to customer retention and loyalty. The study underscores the importance of factors such as reliability, quality, customer orientation, social responsibility, and ethical business conduct in shaping a bank's corporate reputation. Additionally, the article explores the complex nature of service branding in the financial sector, particularly in retail banking, and the challenges associated with valuation and risk assessment.
The quality of services, especially in electronic banking, plays a crucial role in customer satisfaction, loyalty, and retention. The article highlights the significance of meeting customer expectations and the role of emotional associations in shaping perceptions of service quality. It discusses the impact of trust on customer behavioral intentions, emphasizing the importance of security and risk considerations in electronic banking services.
In conclusion, the article provides insights into the multifaceted dynamics of brand building in the banking industry, shedding light on the interconnectedness of service quality, customer satisfaction, and brand loyalty.
IMPROVING COMMUNITY WELFARE THROUGH THE IMPLEMENTATION OF CORPORATE SOCIAL RESPONSIBILITY
Authors: Dwijatenaya Ida Bagus Made Agung , Aini  , Palinggi Yonathan , Musmuliadi  , Narulita Srikandini , Wijayanti Silvana Kardinar 
Published: April 2024

Objectives: This paper aimed to analyze the influence of corporate social responsibility (CSR) and social capital on community welfare and the influence of corporate social responsibility (CSR) through social capital on community welfare.

Theoretical Framework: The focus of this research was to examine the direct and indirect influence of CSR implementation on community welfare. The direct influence of social capital was community welfare. Some of the concepts used are welfare, social capital and CSR, as well as several empirical studies to support the model.

Research Methodology: This research applied a quantitative research design with an inferential statistical approach. Data was collected in the form of secondary and primary data. Data was collected through in-depth interviews based on questionnaires, observation and literature review. The sample used was 97 people. Data analysis applied SmartPLS version 3.

Findings: The study found that CSR has a positive and significant effect on community welfare and social capital. Social capital had a positive but insignificant effect on community welfare, and CSR had a positive but insignificant effect on community welfare through social capital.

Research, Practical & Social Implications: This research focused on community welfare, CSR and social capital that influence it.

Originality/Value: This study provided additional value for those who were active in improving welfare through community empowerment. CSR is a form of community empowerment that has a positive and significant effect on social capital and welfare. For this reason, social capital could be utilized optimally for the welfare of society.
Models of rental behavior of hospital patients (based on the results of a semi-formalized interview of doctors)
Authors: Tokareva Yu. M. , Alexandrina N. A. , Magomedova N. G. , Klimenko V. I. , Rudenko A. Yu. 
Published: April 2024

Currently, the problem of rental patients behavior is poorly understood in the sociology of medicine. The article discusses the concept of "rental behavior", differentiates the related categories of "rental motivation" and "rental attitude". Using the strategy of qualitative sociological research, a semi[1]formal interview of hospital doctors was conducted in order to identify typical behavioral patterns of rent-oriented patients. It is advisable to build interaction in the doctor-patient dyad taking into account the diagnosis of the rental behavior model. The results of the study can be used in the theory of sociology of medicine and in the development of applied sociological research programs.
CRiTical Race Information Theory as Innovative Pedagogy, Act Two: Still Harder Than You Think, and It Remains a Beautiful Thing
Authors: Dunbar Anthony W. , McFarland Rebekah , Grauel Elizabeth 
Published: April 2024

This counterstory began with “CRiTical Race Information Theory as Innovative Pedagogy, Act One: Harder Than You Think, It's a Beautiful Thing.” In the first act, the authors introduced Critical Race information Theory (CRiT) as a rapidly developing iteration of Critical Race Theory (CRT) applied within information settings. The first act also introduced the CRiT frameworks and tenets as well as the CRiT's three-dimensional infrastructure: CRiT as pedagogy, CRiT as praxis, and CRiT as theory (including the process and nuances of theory building). In this article, the authors transition from the first act's “What is CRiT?” discussion to the second act's discussion of how to “Make it CRiT.” Whereas act one covered an approximately 15-year period, this second act moves at a more rapid pace, primarily because it covers a shorter period of time (2021–2023). In act two, the CRiT as pedagogy setting changes from the context of the pilot course launched within the Department of Information Studies at the University of California, Los Angeles to CRiT as pedagogy providing two offerings to Dominican University's School of Information Studies foundational course electives in its ALA-accredited curriculum. Before concluding, the second act offers inspiration and encouragement both to those who offer their critical race work as expressions of transformative, difference-making contributions and to those who aspire to develop and then offer their critical race creations.
Optimal weight support vector regression ensemble with cluster-based subsampling for electricity price forecasting
Authors: Li Yuerong , Zhang Yuhua , Che Jinxing 
Published: April 2024

Accurate prediction of short-term electricity price is the key to obtain economic benefit and also an important index of power system planning and management. Support vector regression (SVR) based ensemble works have gained remarkable achievements in terms of high accuracy and steady performance, but they are highly dependent on data representativeness and have a high computational complexity O (k * N 3) of data samples and parameter selection. To further improve the data representativeness and reduce its computational complexity, this paper develops a new approach to forecast electricity price via optimal weighted ensemble. In the model, the cluster-based subsampling algorithm is proposed to categorize the inputs being seasonally decomposed into several groups, and representative data are drawn from each group in a certain proportion to ensure that each subset trained with SVR has the same representativeness and features. Moreover, the optimal weighted combination method is presented to assign weights to the sub-SVRs to obtain the optimal support vector regression ensemble model (OWSSVRE). The experimental results show that the improved support vector regression ensemble model with the same features and representativeness of the subset has better performance in electricity price forecasting. As a result, it is suitable to support decision making in the energy and other sectors.
Transcriptomic profile of premature ovarian insufficiency with RNA-sequencing
Authors: Wu Jiaman , Feng Shiyu , Luo Yan , Ning Yan , Qiu Pingping , Lin Yanting , Ma Fei , Zhuo Yuanyuan 
Published: April 2024

IntroductionThis study aimed to explore the transcriptomic profile of premature ovarian insufficiency (POI) by investigating alterations in gene expression.MethodsA total of sixty-one women, comprising 31 individuals with POI in the POI group and 30 healthy women in the control group (HC group), aged between 24 and 40 years, were recruited for this study. The transcriptomic profiles of peripheral blood samples from all study subjects were analyzed using RNA-sequencing.ResultsThe results revealed 39 differentially expressed genes in individuals with POI compared to healthy controls, with 10 upregulated and 29 downregulated genes. Correlation analysis highlighted the relationship between the expression of SLC25A39, CNIH3, and PDZK1IP1 and hormone levels. Additionally, an effective classification model was developed using SLC25A39, CNIH3, PDZK1IP1, SHISA4, and LOC389834. Functional enrichment analysis demonstrated the involvement of these differentially expressed genes in the “haptoglobin-hemoglobin complex,” while KEGG pathway analysis indicated their participation in the “Proteoglycans in cancer” pathway.ConclusionThe identified genes could play a crucial role in characterizing the genetic foundation of POI, potentially serving as valuable biomarkers for enhancing disease classification accuracy.
Endometrial microbiota alteration in female patients with endometrial polyps based on 16S rRNA gene sequencing analysis
Authors: Zhao Yu , Liao Yun , Xu Gufeng , Wang Yue 
Published: April 2024

IntroductionThe potential role of the endometrial microbiota in the pathogenesis of endometrial polyps (EPs) warrants further investigation, given the current landscape of limited and inconclusive research findings. We aimed to explore the microecological characteristics of the uterine cavity in patients with EPs and investigate the potential of endometrial microbiota species as novel biomarkers for identifying EPs.MethodsEndometrial samples were collected from 225 patients who underwent hysteroscopies, of whom 167 had EPs, whereas 58 had non- hyperproliferative endometrium status. The endometrial microbiota was assessed using 16S rRNA gene sequencing. We characterized the endometrial microbiota and identified microbial biomarkers for predicting EPs.ResultsThe endometrial microbial diversity and composition were significantly different between the EP and control groups. Predictive functional analyses of the endometrial microbiota demonstrated significant alterations in pathways involved in sphingolipid metabolism, steroid hormone biosynthesis, and apoptosis between the two groups. Moreover, a classification model based on endometrial microbial ASV-based biomarkers along with the presence of abnormal uterine bleeding symptoms achieved powerful classification potential in identifying EPs in both the discovery and validation cohorts.ConclusionOur study indicates a potential association between altered endometrial microbiota and EPs. Endometrial microbiota-based biomarkers may prove valuable for the diagnosis of EPs.Clinical trial registrationChinese Clinical Trial Registry (ChiCTR2100052746).
More frequent utilization of evidence-based teaching practices leads to increasingly positive student outcomes
Authors: Reeves Philip M. , Bauer Melanie , Gill Julia C. , Wang Cong , Hanauer David I. , Graham Mark J. 
Published: April 2024

IntroductionEvidence-based teaching (EBT) practices benefit students, yet our understanding of how frequently these strategies should be utilized in STEM courses is less established.MethodsIn this study, students (n = 894) of faculty who learned about how to implement EBTs from the Summer Institutes for Scientific Teaching were surveyed. The students rated the frequency of implementation of six types of EBTs after the course and completed a follow-up survey one year later to examine long-term outcomes.ResultsClass and student-level analyses indicated that students who reported being exposed to EBTs every couple of classes also reported that they learned more and had a higher ability to work in groups when compared to students who were exposed to EBTs less frequently.DiscussionThe results will help instructors and faculty development professionals understand how frequently EBTs should be incorporated when designing and modifying courses.
Case report: Novel NUS1 variant in a Chinese patient with tremors and intellectual disability
Authors: Li Ruolin , Yang Jiayi , Ma Jinfeng , Zhang Aimei , Li Hongfang 
Published: April 2024

Introduction:Nuclear undecaprenyl pyrophosphate synthase 1 (NUS1) gene variants are associated with a range of phenotypes, including epilepsy, intellectual disability, cerebellar ataxia, Parkinson’s disease, dystonia, and congenital disorders of glycosylation. Additionally, cases describing genotypes and clinical features are rare.Case Presentation:Herein, we report the case of a 23-year-old Chinese female patient who presented with tremors, intellectual disability, and epilepsy. A history of carbon monoxide exposure, brain trauma, or encephalitis was not present in this case. Trio whole-exome sequencing analysis revealed a de novo pathogenic variant of c.750del in exon 4, leading to p.Leu251* amino acid substitution. Genetic analysis failed to identify the identical mutations in the remaining family members who underwent screening. The patient was diagnosed with a rare congenital disease, “congenital glycosylation disorder, type 1aa, autosomal dominant, type 55, with seizures (MRD-55).”Conclusion:We provide further evidence for the role of variants in NUS1 in the development of tremors, epilepsy, and intellectual disabilities. These findings expand our understanding of the clinical phenotypes of NUS1 variants.
Experts' view on the role of oestrogens in combined oral contraceptives: emphasis on oestetrol (E4)
Authors: Creinin M. D. , Cagnacci A. , Spaczyński R. Z. , Stute P. , Chabbert-Buffet N. , Korver T. , Simoncini T. 
Published: April 2024

IntroductionThe evolution of contraception has been crucial for public health and reproductive well-being. Over the past 60 years, combined oral contraceptives (COCs) have remained an important part of the contraceptive landscape worldwide; continued development has worked toward maintaining efficacy and improving safety.MethodsSeven global experts convened to discuss the clinical relevance of the oestrogen in COCs, focusing on the impact of the new oestrogen, oestetrol (E4). Participants then commented through an online forum on the summary content and other participants' feedback. We prepared this report to describe the experts' views, their follow-up from the open forum and the evidence supporting their views.ResultsEthinylestradiol (EE) and oestradiol (E2) affect receptors similarly whereas E4 has differential effects, especially in the liver and breast. Adequate oestrogen doses in COCs ensure regular bleeding and user acceptability. EE and E4 have longer half-lives than E2; accordingly, COCs with EE and E4 offer more predictable bleeding than those with E2. Oestrogen type and progestin influence VTE risk; E2 poses a lower risk than EE; although promising, E4/DRSP VTE risk is lacking population-based data. COCs alleviate menstrual symptoms, impact mental health, cognition, libido, skin, and bone health.ConclusionOestrogens play an important role in the contraceptive efficacy, bleeding patterns, and overall tolerability/safety of COCs. Recent studies exploring E4 combined with DRSP show promising results compared to traditional formulations, but more definitive conclusions await further research.
A bioinformatic approach to identify confirmed and probable CRISPR–Cas systems in the Acinetobacter calcoaceticus–Acinetobacter baumannii complex genomes
Authors: Mancilla-Rojano Jetsi , Flores Víctor , Cevallos Miguel A. , Ochoa Sara A. , Parra-Flores Julio , Arellano-Galindo José , Xicohtencatl-Cortes Juan , Cruz-Córdova Ariadnna 
Published: April 2024

IntroductionThe Acinetobacter calcoaceticus–Acinetobacter baumannii complex, or Acb complex, consists of six species: Acinetobacter baumannii, Acinetobacter calcoaceticus, Acinetobacter nosocomialis, Acinetobacter pittii, Acinetobacter seifertii, and Acinetobacter lactucae. A. baumannii is the most clinically significant of these species and is frequently related to healthcare-associated infections (HCAIs). Clustered regularly interspaced short palindromic repeat (CRISPR) arrays and associated genes (cas) constitute bacterial adaptive immune systems and function as variable genetic elements. This study aimed to conduct a genomic analysis of Acb complex genomes available in databases to describe and characterize CRISPR systems and cas genes.MethodsAcb complex genomes available in the NCBI and BV-BRC databases, the identification and characterization of CRISPR-Cas systems were performed using CRISPRCasFinder, CRISPRminer, and CRISPRDetect. Sequence types (STs) were determined using the Oxford scheme and ribosomal multilocus sequence typing (rMLST). Prophages were identified using PHASTER and Prophage Hunter.ResultsA total of 293 genomes representing six Acb species exhibited CRISPR-related sequences. These genomes originate from various sources, including clinical specimens, animals, medical devices, and environmental samples. Sequence typing identified 145 ribosomal multilocus sequence types (rSTs). CRISPR–Cas systems were confirmed in 26.3% of the genomes, classified as subtypes I-Fa, I-Fb and I-Fv. Probable CRISPR arrays and cas genes associated with CRISPR–Cas subtypes III-A, I-B, and III-B were also detected. Some of the CRISPR–Cas systems are associated with genomic regions related to Cap4 proteins, and toxin–antitoxin systems. Moreover, prophage sequences were prevalent in 68.9% of the genomes. Analysis revealed a connection between these prophages and CRISPR–Cas systems, indicating an ongoing arms race between the bacteria and their bacteriophages. Furthermore, proteins associated with anti-CRISPR systems, such as AcrF11 and AcrF7, were identified in the A. baumannii and A. pittii genomes.DiscussionThis study elucidates CRISPR–Cas systems and defense mechanisms within the Acb complex, highlighting their diverse distribution and interactions with prophages and other genetic elements. This study also provides valuable insights into the evolution and adaptation of these microorganisms in various environments and clinical settings.
Machine learning techniques based on 18F-FDG PET radiomics features of temporal regions for the classification of temporal lobe epilepsy patients from healthy controls
Authors: Liao Kai , Wu Huanhua , Jiang Yuanfang , Dong Chenchen , Zhou Hailing , Wu Biao , Tang Yongjin , Gong Jian , Ye Weijian , Hu Youzhu , Guo Qiang , Xu Hao 
Published: April 2024

BackgroundThis study aimed to investigate the clinical application of 18F-FDG PET radiomics features for temporal lobe epilepsy and to create PET radiomics-based machine learning models for differentiating temporal lobe epilepsy (TLE) patients from healthy controls.MethodsA total of 347 subjects who underwent 18F-FDG PET scans from March 2014 to January 2020 (234 TLE patients: 25.50 ± 8.89 years, 141 male patients and 93 female patients; and 113 controls: 27.59 ± 6.94 years, 48 male individuals and 65 female individuals) were allocated to the training (n = 248) and test (n = 99) sets. All 3D PET images were registered to the Montreal Neurological Institute template. PyRadiomics was used to extract radiomics features from the temporal regions segmented according to the Automated Anatomical Labeling (AAL) atlas. The least absolute shrinkage and selection operator (LASSO) and Boruta algorithms were applied to select the radiomics features significantly associated with TLE. Eleven machine-learning algorithms were used to establish models and to select the best model in the training set.ResultsThe final radiomics features (n = 7) used for model training were selected through the combinations of the LASSO and the Boruta algorithms with cross-validation. All data were randomly divided into a training set (n = 248) and a testing set (n = 99). Among 11 machine-learning algorithms, the logistic regression (AUC 0.984, F1-Score 0.959) model performed the best in the training set. Then, we deployed the corresponding online website version (https://wane199.shinyapps.io/TLE_Classification/), showing the details of the LR model for convenience. The AUCs of the tuned logistic regression model in the training and test sets were 0.981 and 0.957, respectively. Furthermore, the calibration curves demonstrated satisfactory alignment (visually assessed) for identifying the TLE patients.ConclusionThe radiomics model from temporal regions can be a potential method for distinguishing TLE. Machine learning-based diagnosis of TLE from preoperative FDG PET images could serve as a useful preoperative diagnostic tool.
Gait-modifying effects of augmented-reality cueing in people with Parkinson’s disease
Authors: Hoogendoorn Eva M. , Geerse Daphne J. , van Dam Annejet T. , Stins John F. , Roerdink Melvyn 
Published: April 2024

IntroductionExternal cueing can improve gait in people with Parkinson’s disease (PD), but there is a need for wearable, personalized and flexible cueing techniques that can exploit the power of action-relevant visual cues. Augmented Reality (AR) involving headsets or glasses represents a promising technology in those regards. This study examines the gait-modifying effects of real-world and AR cueing in people with PD.Methods21 people with PD performed walking tasks augmented with either real-world or AR cues, imposing changes in gait speed, step length, crossing step length, and step height. Two different AR headsets, differing in AR field of view (AR-FOV) size, were used to evaluate potential AR-FOV-size effects on the gait-modifying effects of AR cues as well as on the head orientation required for interacting with them.ResultsParticipants modified their gait speed, step length, and crossing step length significantly to changes in both real-world and AR cues, with step lengths also being statistically equivalent to those imposed. Due to technical issues, step-height modulation could not be analyzed. AR-FOV size had no significant effect on gait modifications, although small differences in head orientation were observed when interacting with nearby objects between AR headsets.ConclusionPeople with PD can modify their gait to AR cues as effectively as to real-world cues with state-of-the-art AR headsets, for which AR-FOV size is no longer a limiting factor. Future studies are warranted to explore the merit of a library of cue modalities and individually-tailored AR cueing for facilitating gait in real-world environments.