bluuebunny/crossref_metadata_2025_split huggingface dataset:
Market segmentation analysis in hospitals: A literature review
Authors: Arista Herlin Ika Yuni , Suryawati Chriswardani , Sriatmi Ayun 
Published: February 2025

Background: Healthcare is undergoing a transformation in several key business units that require proper management. The growth of hospitals is accompanied by very high public demand for services, making hospitals compete in finding new opportunities and strategies to meet the needs of patients. To meet consumer expectations and desires, hospitals must design marketing combinations that provide value to the target consumer. Management planning serves the target market based on hospital market segmentation.
Purpose: To find out the analysis of the health service market segment so that it is expected to help the marketing process in hospitals.
Method: A literature review obtained through the internet, in the form of scientific research results from several sources. The population in this study is research with a focus on assessing hospital market segmentation in 2015-2023, obtained as many as 15 research articles sourced from scientific publications Science Direct, Scopus, ProQuest, Springer Link, Google Scholar, PubMed, JSTOR and Emerald Insight. The data obtained were then analyzed systematically.
Results: Based on the results of the article analysis, eight articles were found in the form of quantitative research, seven articles in the form of qualitative research, and one research in the form of mixed method research.
Conclusion: This study concludes that market segmentation analysis in hospitals divided by geography, demographic, psychographic, and behavioral and supported by the right marketing mix is an effective means to improve health services according to customer needs.
ANALISIS MAJAS DALAM LIRIK FLOWER OLEH MAEDA ATSUKO
Authors: Rabbani Ryan Ikmal 
Published: February 2025

Figure of speech changes the use of words from their usual literal meaning to a more creative, figurative or unconventional meaning. The purpose of using figure of speech is to enrich and beautify the language, as well as to create a stronger and more interesting impression in communication. This study aims to analyze the figure of speech contained in the lyrics of the Japanese song "Flower" sung by Maeda Atsuko. The study was conducted using a semantic approach to identify and understand the use of figure of speech in the lyrics. The research method involves a process of recording and direct analysis of the lyrics of the song "Flower". The figure of speech found were analyzed based on their literal and figurative meanings, as well as the context of their use in the lyrics. The results showed that the lyrics of this song contained 18 data or sentences containing various types of figure of speech, including metaphor, personification and hyperbole. The most common figure of speech found are 14 metaphors, 3 personification figure of speech and 1 hyperbole figure of speech. This research provides insight into Maeda Atsuko's creativity and artistic expression in composing the lyrics of the song "Flower". The analysis of figure of speech in these lyrics also provides a deeper understanding of the messages and feelings that singers want to convey to listeners. In addition, this research can be a contribution to literature and language studies, especially in understanding the use of figure of speech in the context of music and songs.

Keywords: figure of speech, Japanese songs, semantics
ANALISIS TANDA VERBAL MAKNA PERJUANGAN PADA TOKOH SEITA DALAM FILM ANIME HOTARU NO HAKA
Authors: Regita riang alamsyah  
Published: February 2025

Abstract
This research is entitled Analysis of Verbal Signs of the Meaning of Struggle in Seita's Character in the Hotaru No Haka Anime Film. Aims to identify verbal signs of the meaning of struggle in Seita's character in the Hotaru No Haka anime film using Ferdinand de Saussure's semiotic study. Uses the theory of Ferdinand de Saussure with the principle that every language is also a form of a sign system and each sign is divided into two parts which are a system of a sign and each sign consists of two parts, namely the signifier and the signified. This study used descriptive qualitative method. Data collection uses the listening method with the basic technique, namely Listening technique is free to engage in conversation. The analysis technique uses Saussure's theory of language signs, namely signified in the form of sound images and signifiers in the form of concepts. Then the presentation of the results of data analysis using formal methods and informal methods. The source of the data used is the Japanese anime film, Hotaru No Haka, with a duration of 1 hour 28 minutes which the author got from youtube. The theoretical basis used is the theory of semiotics which is a science that examines signs so as to produce a meaning. The results of this study, 14 verbal data data were found which contained the meaning of struggle for Seita's character. The conclusion that can be drawn from this study is that the verbal signs used by Seita's character use language that is easy to understand so that the audience can understand the meaning of the struggles carried out on Seita's character.
REVALIDAÇÃO DO DIPLOMA UNIVERSITÁRIO AO REFUGIADO NO BRASIL: A DIGNIDADE DO DIREITO FUNDAMENTAL AO TRABALHO
Authors: Costa Souza Nilson , De Andrade Barbosa Santos de Mesquita Alessandra , Diego Martarelli Fernandes Felipe 
Published: February 2025

O presente artigo ira contemplar a sistematização que os refugiados enfrentam para revalidarem o diploma universitário no território nacional, eis que o cenário não somente implica o direito ao trabalho, e sim o direito humano da educação, sem contar, a aclamada dignidade da pessoa humana para continuarem seguir suas trajetórias ao novo pais. Neste âmbito, torna indiscutível atuação do governo federal na promoção e fortalecimento das politicas públicas de promover a boa acolhida aos refugiados, tal como, propor meios de vivencia digna para referida classe que a cada dia cresce o número significativamente, sendo a reavaliação um mecanismo de integração social e assim fortalecer as diretrizes humanitárias ao enredo em discussão.

PALAVRAS CHAVE: Refugiados, diploma universitário e trabalho.
ABSTRACT
This article will address the systematization that refugees face in order to revalidate their university diplomas in the national territory, since the scenario not only involves the right to work, but also the human right to education, not to mention the acclaimed dignity of the human person to continue following their paths to the new country. In this context, the federal government's role in promoting and strengthening public policies to promote a good welcome for refugees becomes indisputable, as well as proposing means of dignified living for this class, whose number is growing significantly every day, with reevaluation being a mechanism for social integration and thus strengthening the humanitarian guidelines for the subject under discussion.

Keywords: Refugees, university degree and work.
Editorial
Authors: Tavares Ujiie Nájela 
Published: February 2025

Neste segundo número, com publicação contínua e fatiada apresentamos por hora quatro artigos, um de autoria internacional e três nacionais, os quais possuem temáticas relevantes, sendo elas: a educação familiar na experiência cubana, a percepção de crianças com TEA acerca da escola e sua educação, vivências e ocupação espaço-tempo de crianças na cidade e atitudes sociais de professores da educação infantil acerca da inclusão.
AI-based biplane X-ray image-guided method for distal radius fracture reduction
Authors: Zha Qing , Shen Sizhou , Ma Ziyang , Yu Manqiu , Bi Hongzheng , Yang Hongbo 
Published: February 2025

BackgroundIn the course of manual reduction of distal radius fractures, many doctors rely on tactile perception to assess the displacement of the fracture. However, a more accurate determination of the severity of the fracture and the success of the reduction requires measurement software to annotate the fracture images, which is difficult to achieve real-timely in actual procedure of reduction. Which may lead to misdiagnosis when experienced doctors rely on their intuition. Therefore, it is necessary to develop an AI-based method for calculating fracture parameters to provide real-time display, particularly in fracture reduction machines.MethodsAn AI-based method for automatically calculating of radiographic parameters in distal radius fractures (DRF) was developed. Initially, anteroposterior (AP) and lateral (LAT) X-ray images of patients with distal radius fractures were collected from three hospitals and preprocessed. Subsequently, several neural network structures, UNet, DeeplabV3+, PSPNet, and TransUNet, are compared in terms of utility and accuracy, and finally, the models obtained from the UNet image segmentation algorithm are used for semantic segmentation of the radius and ulna. Following this, the contours of the radius and ulna were extracted using OpenCV, key points were detected, and the principal axes were calculated. Finally, the computed parameters including radial angle (RA), radial length (RL), ulnar variance (UV), and palmar tilt (PT) were calculated and displayed on the image.ResultsThe advantages and disadvantages of several models were considered, and finally the UNet neural network model was used as the core algorithm of the image segmentation model in this study. The segmentation accuracy for the radius and ulna in the AP and LAT X-ray images reached 91.31% and 88.63%, respectively. The average errors between the automated calculations of parameters RA, RL, UV, and PT and the manually annotated results by physicians were −1.36°, −1.7 mm, 0.66 mm, and −1.06°, respectively. The system has been initially deployed on the same computer that operates the radial fracture fracture repositioning robot.ConclusionThe automated parameter calculation method developed in this study accurately computes diagnostic parameters for assessing distal radius fractures and can be utilized in the image-guided reduction process of fracture rehabilitation robots. This method has the potential to evolve into an intelligent diagnostic tool for physicians, thereby enhancing the accuracy of distal radius fracture diagnosis.
Improving partnerships to improve outcomes for children and young people with special educational needs and disabilities: qualitative findings from a mixed methods systematic review
Authors: Tyldesley-Marshall Natalie , Johnson Rebecca , Parr Janette , Brown Anna , Ghosh Iman , Mehrabian Amin , Chen Yen-Fu , Grove Amy 
Published: February 2025

BackgroundEffective collaboration between different services is recommended by government policy for children and young people (CYP) with Special Educational Needs and Disabilities (SEND) across many countries. In the UK, despite significant shifts in policy towards partnership working, there remains a scarcity of scientific evidence on how this should be achieved. This mixed methods systematic review examined interventions leading to improved service outcomes for multiagency working for CYP with SEND.MethodEleven databases generated a total of 7,473 results. Data from 137 selected studies were analysed. However, only qualitative research findings from thematic synthesis regarding key ingredients of effective partnership are reported.ResultsFrom these, five key ingredients for effective partnership working in SEND services were identified: (1) participation, and legitimacy to participate in a partnership; (2) personalisation and consultation with children, young people, and their families in designing and delivering services; (3) respectful communication, and feeling that involvement is valued; (4) preparation to be an effective member of a partnership; and (5) working across professional and organisational boundaries.Conclusion and implicationsTo facilitate practical application of the findings, three exemplar cases of effective partnership are explored. A framework to support partnership design, collaboration, and the development of evidence-based recommendations, is presented.Systematic review registrationThe study protocol for this study was registered in PROSPERO CRD42022352194.
Ultrasonic radiomics in predicting pathologic type for thyroid cancer: a preliminary study using radiomics features for predicting medullary thyroid carcinoma
Authors: Zhang Dai , Yang Fan , Hou Wenjing , Wang Ying , Mu Jiali , Wang Hailing , Wei Xi 
Published: February 2025

IntroductionMedullary thyroid carcinoma (MTC) is aggressive and difficult to distinguish from papillary thyroid carcinoma (PTC) using traditional ultrasound. Objective to establish a standard-based ultrasound imaging model for preoperative differentiation of MTC from PTC.MethodsA retrospective study was conducted on the case data of 213 thyroid cancer patients (82 MTC, 90 lesions; 131 PTC, 135 lesions) from the Department of Diagnostic and Therapeutic Ultrasonography, Tianjin Medical University Cancer Institute and Hospital. We constructed clinical model, radiomics model and comprehensive model by executing machine learning algorithms based on baseline clinical, pathological characteristics and ultrasound image data, respectively.ResultsThe study showed that the comprehensive model observed the highest diagnostic efficacy in differentiating MTC from PTC with AUC, sensitivity, specificity, positive predictive value, negative predictive value and accuracy of 0.93, 0.88, 0.82, 0.77, 0.91, 85.8%. Delong test results showed that the comprehensive model was significantly better than the clinical model (Z=-3.791, P&lt;0.001) and the radiomics model (Z=-2.017, P=0.044). Calibration curves indicated the comprehensive model and the radiomics model exhibited better stability than the clinical model. Decision curves analysis (DCA) demonstrated that the comprehensive model had the highest clinical net benefit.DiscussionsRadiomics model is effective in identifying MTC and PTC preoperatively, and the comprehensive model is better. This approach can aid in identifying the pathologic types of thyroid nodule before clinical operation, supporting personalized medicine in the decision-making process.
A novel glycolysis-related gene signature for predicting prognosis and immunotherapy efficacy in breast cancer
Authors: Huang Rui , Li Yi , Lin Kaige , Zheng Luming , Zhu Xiaoru , Huang Leqiu , Ma Yunhan 
Published: February 2025

BackgroundPrevious studies have shown that glycolysis-related genes (GRGs) are associated with the development of breast cancer (BC), and the prognostic significance of GRGs in BC has been reported. Considering the heterogeneity of BC patients, which makes prognosis difficult to predict, and the fact that glycolysis is regulated by multiple genes, it is important to establish and evaluate new glycolysis-related prediction models in BC.MethodsIn total, 170 GRGs were selected from the GeneCards database. We analyzed data from the Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) database as a training set and data from the Gene Expression Omnibus (GEO) database as a validation cohort. Based on the overall survival data and the expression levels of GRGs, Cox regression analyses were applied to develop a glycolysis-related prognostic gene (GRPGs)-based prediction model. Kaplan (KM) survival and ROC analyses were performed to assess the performance of this model. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to identify the potential biological functions of GRPGs. cBioPortal database was used to explore the tumor mutation burden (TMB). The tumor immune dysfunction and exclusion indicator (TIDE) was used to estimate the patient response to immune checkpoint blockade (ICB). The levels of tumor-infiltrating immune cells (TICs) and stromal cells were quantitatively analyzed based on gene expression profiles.ResultsWe constructed a prediction model of 10 GRPGs (ADPGK, HNRNPA1, PGAM1, PIM2, YWHAZ, PTK2, VDAC1, CS, PGK1, and GAPDHS) to predict the survival outcomes of patients with BC. Patients were divided into low- and high-risk groups based on the gene signature. The AUC values of the ROC curves were 0.700 (1-year OS), 0.714 (3-year OS), 0.681 (5-year OS). TMB and TIDE analyses showed that patients in the high-risk group might respond better to ICB. Additionally, by combining the GRPGs signature and clinical characteristics of patients, a novel nomogram was constructed. The AUC values for this combined prediction model were 0.827 (1-year OS), 0.792 (3-year OS), and 0.783 (5-year OS), indicating an outstanding predictive performance.ConclusionA new GRPGs based prediction model was built to predict the OS and immunotherapeutic response of patients with BC.
Association of systemic inflammation response index with latent tuberculosis infection and all-cause mortality: a cohort study from NHANES 2011-2012
Authors: Wang Lin , Kuang Yi , Zeng Yan , Wan Zhihui , Yang Sha , Li Renliang 
Published: February 2025

BackgroundThe Systemic Inflammatory Response Index (SIRI) is a promising inflammatory marker; however, the relationship between SIRI and latent tuberculosis infection (LTBI), as well as its association with mortality rates, remains unclear. The present study aimed to explore the associations of the SIRI with LTBI and all-cause mortality.MethodsWe conducted a prospective cohort study using data from National Health and Nutrition Examination Survey (NHANES) cycles from 2011 to 2012. We explored the association between SIRI and LTBI prevalence using Multiple logistic regression models. We used Multivariate Cox proportional hazards model to analyze the association between SIRI and all-cause mortality. In addition, Kaplan-Meier curves, restricted cubic splines (RCS), stratified analysis, and interaction tests were performed.ResultsThe study included a total of 4,983 adults who participated in NHANES 2011-2012. The mean follow-up period was 92.35 ± 16.82 months, and there were 525 deaths, representing a mortality rate of 10.54%. The occurrence of LTBI is significantly associated with low SIRI levels(OR=0.76, 95% CI: 0.66-0.89), after adjusting for confounders. Among LTBI patients, elevated SIRI levels are significantly correlated with an increased risk of all-cause mortality (adjusted HR = 1.48, 95% CI: 1.01-2.15). RCS revealed a linear relationship between SIRI and all-cause mortality in patients with LTBI (P =0.059[overall] and P = 0.391 [Nonlinear]). Furthermore, within the LTBI population, the area under the curve (AUC) of SIRI for all-cause mortality are 0.731 (1-year), 0.640 (3-year), and 0.634 (5-year).ConclusionThe findings of this study indicate that elevated SIRI levels are independently associated with an increased risk of all-cause mortality in patients with LTBI. Notably, SIRI was significantly inversely associated with the incidence of LTBI. Therefore, SIRI may serve as an effective tool for risk stratification in adults with LTBI in the United States. Further research is needed to elucidate the underlying mechanisms and to explore any therapeutic implications of these findings.
Enhancing patient satisfaction and reducing nurse workload: the impact of multimedia health education in a prospective single-center randomized controlled trial
Authors: Yang Liping , Qin Zilan , Yao Jia , Xu Huan , Tian Jinhui , Ren Yanxian , Wang Haiping , Meng Wenbo 
Published: February 2025

IntroductionHealth education is an important part of nursing care. Verbal health education is a common practice in surgical wards, which is time-consuming and laborious. Thus, this study aims to evaluate whether multimedia health education reduces nurses’ workload without compromising patient and family satisfaction in a surgical context.MethodsWe conducted a parallel-group, prospective randomized controlled trial at the Hepatobiliary Surgery Institute of Lanzhou University’s First Hospital between July 2019 and May 2022. Eligible patients (≥18 years) with general surgical conditions and acceptable for surgery were randomly assigned (1:1) to receive a multi-media health education group or a standard health education group. Randomization was performed by an independent statistician using a computer-generated randomization list. The nurses’ workload and satisfaction were the main outcomes; the anxiety level of patients and the variables affecting nurse workload were the secondary outcomes.ResultsA total of 184 eligible participants were randomly assigned to receive multimedia health education and standard health education. The results showed that multimedia health education can shorten the time [15.21 (0.63)vs.16.94 (3.96)] nurses spend on health education during patient admissions, the difference being statistically significant (p &lt; 0.001), but it did not lower the satisfaction levels of nurses [73.46 (2.36) vs. 67.16 (5.52)], patients [53.35 (2.09) vs. 47.86 (5.00)], their families [53.35 (2.28) vs. 47.86 (4.53)] and doctors [73.33 (2.40) vs. 68.07 (4.92)] regarding health education (p &lt; 0.001); in fact, it increased their satisfaction.ConclusionMulti-media health education could reduce nurses’ workload and enhance patient satisfaction but not increase complications.Clinical trial registrationhttps://www.clinicaltrials.gov/, identifier [NCT03989401].
Network analysis of adverse event patterns following immunization with mRNA COVID-19 vaccines: real-world data from the European pharmacovigilance database EudraVigilance
Authors: Ferreira-da-Silva Renato , Lobo Mariana Fernandes , Pereira Ana Margarida , Morato Manuela , Polónia Jorge Junqueira , Ribeiro-Vaz Inês 
Published: February 2025

ObjectiveTo analyses real-world safety data of mRNA COVID-19 vaccines within the European Economic Area (EEA), using Individual Case Safety Reports (ICSR), and to evaluate the variability in safety profiles between different vaccine versions.MethodsWe utilized EudraVigilance data from 1 January 2020, to 31 December 2023, focusing on Moderna (Spikevax) and Pfizer/BioNTech (Comirnaty) vaccines against COVID-19. We performed descriptive statistics, co-occurrence analysis, and correspondence analysis to identify patterns and clusters of adverse events following immunization (AEFI).ResultsWe retrieved 993,199 ICSR (Moderna: 394,484; Pfizer: 605,794), with most reports related to women patients (69%) and non-healthcare professionals (65%). A total of 10,804 distinct AEFI terms were described across the retrieved ICSR, with a cumulative occurrence frequency of 3,558,219 (Moderna: 1,555,638; Pfizer: 2,031,828). The most prominent serious clusters included headache, fatigue, pyrexia, myalgia, arthralgia, malaise, nausea, and chills, which frequently co-occurred with vaccination failure. Specific AEFI like fever, chills, malaise, arthralgia, injection site pain, inflammation, and warmth were more often linked to Moderna, while Pfizer was more commonly associated with vaccination failure, menstrual disorders (heavy menstrual bleeding and dysmenorrhea), and hypoesthesia. In older adults, serious clusters included confusional states, cerebrovascular accidents, and myocardial infarctions, while myocarditis and pericarditis were noted in younger males. Although rare, serious systemic AEFI, like anaphylactic reactions, were identified but require further causality evaluation.ConclusionThe overall safety of mRNA COVID-19 vaccines for mass vaccination is supported, but continuous pharmacovigilance remains essential. Identified clusters of AEFI, particularly serious and systemic ones, although rare and potentially influenced by other underlying causes, underscore the need for continuous monitoring and further epidemiological investigations to explore potential causal relationships.