bluuebunny/crossref_metadata_2025 huggingface dataset:
Metamorphic Relation Generation: State of the Art and Research Directions
Authors: Li Rui , Liu Huai , Poon Pak-Lok , Towey Dave , Sun Chang-Ai , Zheng Zheng , Zhou Zhi Quan , Chen Tsong Yueh
Published: December 2024

Metamorphic testing has become one mainstream technique to address the notorious oracle problem in software testing, thanks to its great successes in revealing real-life bugs in a wide variety of software systems. Metamorphic relations, the core component of metamorphic testing, have continuously attracted research interests from both academia and industry. In the last decade, a rapidly increasing number of studies have been conducted to systematically generate metamorphic relations from various sources and for different application domains. In this article, based on the systematic review on the state of the art for metamorphic relations’ generation, we summarize and highlight visions for further advancing the theory and techniques for identifying and constructing metamorphic relations, and discuss promising research directions in related areas.
UPON: Urdu Poetry Generation Using Deep Learning: A Novel Approach and Evaluation
Authors: Tabassam Muhammad Rauf , Waheed Hajra , Safder Iqra , Sarwar Raheem , Aljohani Naif Radi , Nawaz Raheel , Hassan Saeed-Ul , Zaman Farooq , Ahsan Ahtazaz
Published: December 2024

Poetry represents the oldest and most esteemed literary form, allowing poets to convey ideas while carefully attending to elements such as meaning, coherence, poetic quality, and fluency. Notably, the creation of good poetry entails considerations of rhyme and meter. With the advent of artificial intelligence (AI), significant advancements have been made in automatic text generation, primarily within languages such as English and Chinese. However, the generation of Urdu poetry presents a unique challenge due to the language’s inherent ambiguity, cultural and historical nuances, and the demand for creativity. The existing body of literature has only marginally explored Urdu prose and has almost entirely overlooked the domain of Urdu poetry generation, primarily due to the scarcity of comprehensive training data. In response to this deficiency, this research endeavor addresses this challenge. It begins by introducing a specialized Urdu poetry dataset adhering to a specific meter, “behr-e-khafeef,” which incorporates approximately 20,000 couplets from the Rekhta repository. Subsequently, a character-based encoding methodology is proposed to transform these couplets into a numerical representation, assigning a distinct identifier to each character. The generation process initiates with the creation of the first verse through a character-level LSTM, followed by the application of a machine translation technique, specifically sequence-to-sequence learning, to formulate the second verse based on the first. The generated poetry is subjected to evaluation based on metrics, including BLEU scores. Additionally, an expert panel of Urdu poets is engaged to conduct a human assessment of the generated couplets, with the evaluation encompassing critical dimensions such as meaning, coherence, poetic quality, and fluency. Our findings are juxtaposed with existing poetry generation systems, demonstrating a notable advancement in the state-of-the-art, as evidenced by a BLEU score of 0.23. The research culminates with the presentation of prospective avenues for further exploration, aimed at inspiring the scholarly community to enhance the domain of poetry generation and augment existing contributions in this field.
Means of Hitting Times for Random Walks on Graphs: Connections, Computation, and Optimization
Authors: Xia Haisong , Xu Wanyue , Zhang Zuobai , Zhang Zhongzhi
Published: December 2024

For random walks on graph

\(\mathcal{G}\)

with

\(n\)

vertices and

\(m\)

edges, the mean hitting time

\(H_{j}\)

from a vertex chosen from the stationary distribution to vertex

\(j\)

measures the importance for

\(j\)

, while the Kemeny constant

\(\mathcal{K}\)

is the mean hitting time from one vertex to another selected randomly according to the stationary distribution. In this article, we first establish a connection between the two quantities, representing

\(\mathcal{K}\)

in terms of

\(H_{j}\)

for all vertices. We then develop an efficient algorithm estimating

\(H_{j}\)

for all vertices and

\(\mathcal{K}\)

in nearly linear time of

\(m\)

. Moreover, we extend the centrality

\(H_{j}\)

of a single vertex to

\(H(S)\)

of a vertex set

\(S\)

, and establish a link between

\(H(S)\)

and some other quantities. We further study the NP-hard problem of selecting a group

\(S\)

of

\(k\ll n\)

vertices with minimum

\(H(S)\)

, whose objective function is monotonic and supermodular. We finally propose two greedy algorithms approximately solving the problem. The former has an approximation factor

\((1-\frac{k}{k-1}\frac{1}{e})\)

and

\(O(kn^{3})\)

running time, while the latter returns a

\((1-\frac{k}{k-1}\frac{1}{e}-\epsilon)\)

-approximation solution in nearly-linear time of

\(m\)

, for any parameter

\(0{\lt}\epsilon{\lt}1\)

. Extensive experiment results validate the performance of our algorithms.
Online Worker Scheduling for Maximizing Long-Term Utility in Crowdsourcing with Unknown Quality
Authors: Wang Jiajun , Lin Pengfei , Ding Xingjian , Guo Jianxiong , Tang Zhiqing , Li Deying , Wu Weili
Published: December 2024

Spatiotemporal Mobile CrowdSourcing (MCS) is a new intelligent sensing paradigm for large-scale data acquisition where requesters can recruit a crowd of workers to perform data collection tasks. How to recruit suitable workers in a dynamic environment to maximize platform utility is a key issue and has become a research hotspot. Many past studies have made great efforts in this regard, but most of them either assume that the worker quality is known in advance or ignore the limitations of workers’ short-term ability to provide resources. In this article, we consider a platform-centered online spatiotemporal MCS system where mobile workers have both long-term and short-term constraints for providing resources, and their quality is unknown to the platform, while the platform has a long-term budget constraint for recruiting workers. We aim to find an online worker scheduling scheme to maximize the platform’s long-term utility without violating the constraints of both workers and the platform. To address this problem, we first transform the long-term utility maximization problem into a real-time utility maximization problem by leveraging the Lyapunov optimization, then design algorithms based on the Upper Confidence Bound (UCB) and Markov approximation to solve each real-time utility maximization problem with unknown worker quality. We demonstrate that our UCB-based algorithm has a sublinear regret and prove that our proposed framework has a performance guarantee for the addressed problem. Finally, we evaluate our design through numerical simulation experiments, and the results demonstrate the effectiveness of our algorithm.
Probabilistic Modelling of the Nonlinear Mapping between Voltammograms and the Grain Size of the Electrode Material in Li-Ion Batteries Using Optimally Tuned Gaussian Process Regression Models
Authors: Agrawal Anand Kumar , Swaminathan Narasimhan , Hussain Umair
Published: December 2024

The electrochemical response, and hence the performance, of lithium-ion batteries (LIBs) is heavily influenced by the microstructure of their electrode material, particularly grain size. Thus, a model that correlates electrode microstructure with electrochemical response can aid in optimizing these characteristics for better battery performance. However, no existing studies address this modeling problem. This study fills this gap by using data-driven probabilistic modeling to map the electrochemical response (voltammograms) to electrode grain size. The methodology is demonstrated on six datasets containing voltammograms from in-silico cyclic voltammetry experiments on LiMn2O4 electrode particles. Feature vectors created using seven features of the voltammogram were combined with the corresponding known grain size values to construct data-driven probabilistic models via Gaussian process regression (GPR) with five different kernels for each dataset. The hyperparameters of the kernels used in these GPR models were optimized using grid-search. Performance evaluation through bias-variance analysis demonstrated strong predictive accuracy of the developed models. Additionally, the comparisons across datasets and kernels showed the Gaussian and Rational Quadratic kernels’ effectiveness in modeling various relationships. The obtained results substantiate the efficacy of the proposed approach, revealing significant insights and encouraging further exploration.
Tracking the Evolution of Ionomer Film and Catalyst Material to Unravel PEMFC Performance Degradation
Authors: Chabot Florian , Lionel Porcar , Guétaz Laure , Rosini Sébastien , Morin Arnaud
Published: December 2024

Several characterization techniques were performed on a proton exchange membrane fuel cell (PEMFC) to relate the performance degradation induced by the membrane-targeted accelerated stress test (AST) to the evolution of electrochemical and physical properties of the electrode. This works investigated the ionomer structure and the proton transport properties. Electron microscopy and small angle neutron scattering analysis provided access to the electrode’s nanoscale structure, the distribution of the platinum particle size, the structure of the 2–3 nm thick ionomer film, as well as the location of the water uptake by the electrode. A newly-developed technique using proton desorption under diluted O2 allows to distinguish effectively used active sites for oxygen reduction reaction. Proton transport and dioxygen diffusivity properties were measured using impedance spectroscopy and limiting current technique respectively. The Membrane-AST leads to an increase in the water uptake of the electrode due to a modification of the global structure of the electrode, a reduced platinum surface area, and corrosion of carbon particles. However, it does not alter the ionomer structure. The decrease in performance is partially attributed to the increase in proton resistivity, but mainly due to the limitation of dioxygen transport fostered by the electrode structure modifications.
Management of Orofacial Infantile Haemangioma: A Case Report
Authors: Zuhir Othman , Muhd Noor Nurhidayah , Marsom Aminah
Published: December 2024

Infantile haemangioma (IH) is the most common childhood tumour, often developing in the head and neck region. It may cause disfigurement, functional impairment, or tooth developmental issues when it is present in the oral cavity. We report a case of a 2‐month‐old boy referred to the paediatric dentistry team with a segmental IH involving the left periorbital, cheek, and hard palate. The patient had a maculopapular rash in the periorbital area, a telangiectatic patch on his left cheek, and papules on the left posterior hard palate. He was comanaged with the paediatric, ophthalmology, dermatology, and cardiology teams. He was treated with oral propranolol, resulting in the lesions reducing in size. Early intervention is crucial to prevent severe complications affecting the patient’s appearance, function, speech, feeding, and dentition. Dentists should be familiar with the clinical presentations and preventative measures, as we may encounter such patients with oral cavity involvement.
Etiology and Prognostic Criteria for Liver Failure in Southeast China: A Multicenter Retrospective Cohort Study Between 2018 and 2020
Authors: Lyu Chunyan , Han Jun , Kang Naling , Zeng Dawu , Davgadorj Chantsalmaa , Ge Lina , Zhou Meifang , Mao Richeng , Yan Yan
Published: December 2024

Background: The prognosis of patients with liver failure (LF) depends significantly on the etiology and clinical indicators. This analysis of these basic indicators can help provide a basis for the study of predictive outcome indicators.

Methods: We collected the data from multiple centers in Southeast China, including subclasses of acute liver failure (ALF), subacute liver failure (SLF), acute‐on‐chronic liver failure (ACLF), subacute‐on‐chronic liver failure (SALF), and chronic liver failure (CLF). Multivariate logistic regression analysis was used to screen for clinical indicators of nonsurvivors. We analyzed receiver operating characteristic (ROC) curves and cutoff values to assess the prognostic criteria.

Results: Hepatitis B virus (HBV) infection is the leading etiology of patients with LF (64.52% (411/637)). SALF (41.36%) and CLF (32.30%) are the main subclasses of the hepatitis B virus–related liver failure (HBV‐LF) group and the non‐HBV–related LF group in Southeast China, respectively. Between 2018 and 2020, the incidence of HBV‐LF decreased significantly, ranging from 72.36% to 59.74%, and the spontaneous survival rates of patients with HBV‐LF were substantially lower than those of non‐HBV‐LF patients (36.43%~44.93% vs. 58.97%~63.64%). Infection and cirrhosis were the leading causes of death in both groups. The age and total bilirubin value of the nonsurvivors with HBV‐LF were significantly higher, and the number of days of hospitalization was significantly shorter than that of the survivors. The ages of the nonsurvivors in the non‐HBV‐LF group were significantly higher than those of the survivors. The prothrombin time–international normalized ratio (PT‐INR) is 2.05, 1.92, or 2.11, and antithrombin III (AT III) is 24.50%, which are proposed as prognostic criteria for the HBV‐SALF (hepatitis B virus–related subacute‐on‐chronic liver failure), non‐HBV‐SLF (non‐hepatitis B virus–related subacute liver failure), non‐HBV‐ACLF (non‐hepatitis B virus–related acute‐on‐chronic liver failure), and HBV‐ALF (hepatitis B virus–related acute liver failure) subclasses, respectively.

Conclusions: The incidence of HBV‐LF is decreasing annually. AT III, as an independent prognostic criterion, has excellent discriminative ability for the outcomes of the HBV‐ALF subclass.
Number of Prescription Medications and Overall Survival in Metastatic Castrate‐Resistant Prostate Cancer
Authors: Pickett Carley R. , Eaton Daniel B. , Karunanandaa Krishny , Cybulla Emily , Heiden Brendan T. , Chang Su-Hsin , Yan Yan , Subramanian Melanie P. , Puri Varun , Schoen Martin W.
Published: December 2024

Background: Assessment of comorbid diseases is essential to clinical research and may risk‐stratify patients for mortality independent of established methods such as the Charlson Comorbidity Index (CCI).

Methods: In a retrospective study of U.S. Veterans, we examined the association between the number of medications, 1‐year mortality, and overall survival in Veterans being treated for metastatic castration‐resistant prostate cancer (mCRPC) between 2011 and 2017.

Results: Among 8855 Veterans, a median of 11 medications and 6 medication classes were filled in the year prior to initial treatment of mCRPC with abiraterone or enzalutamide. The median patient age was 74 years, 25.7% of patients were Black, and the median CCI was 3. Despite being associated with fewer medications, increasing age was associated with an increased CCI. After adjusting for patient, tumor, and treatment factors, both the number of medications and the number of medication classes were associated with increased 1‐year mortality with adjusted OR (95% CI) of 1.03 (1.03, 1.04) and 1.08 (1.06, 1.11), respectively. Medications within Anatomic Therapeutic Class (ATC) N (nervous system) and ATC G (genitourinary and sex hormones) were associated with decreased OS, HR 1.18 (1.11, 1.25) and HR 1.15 (1.10, 1.20), respectively. Medications within ATC C (cardiovascular) were associated with increased OS, HR 0.91 (0.86, 0.97). Within a subgroup of patients with comparable age and CCI, the increased number of medications was associated with the increased risk of death.

Conclusions: The number and type of medications were independently associated with survival in patients undergoing treatment for mCRPC. With new therapies for treatment of advanced prostate cancer, patients are living longer, which increases the need for better understanding of the impact of comorbid diseases. Simple methods to assess disease burden and prognosticate survival have the potential to guide treatment decisions and improve the quality of life in this patient population.
Positional Differences in Jump Loads and Force and Velocity Metrics Throughout a 16‐Week Division I Volleyball Season
Authors: Sanders Gabriel J. , Skodinski Stacie , Cabarkapa Damjana V. , Howard Mason , Cabarkapa Dimitrije , Peacock Corey A.
Published: December 2024

The study quantified total and high‐intensity jump counts and assessed neuromuscular performance through countermovement jump (CMJ) force and velocity metrics by position. Twelve Division I female athletes (19.6 ± 1.3 years; 182.7 ± 6.5 cm) were included in the 16‐week study using wearable microsensors to monitor daily jump loads. CMJ tests were conducted twice weekly using dual force plates to measure force and velocity metrics. There were significant main effects of position (p ≤ 0.001) for jump and force plate metrics. Middle blockers accumulated significantly more jump counts of 38.1 cm or higher (jumps 38+; 65.4 ± 39.2 counts) and jump counts of 50.8 cm or higher (jumps 50+; 39.5 ± 32.7 counts) compared to outside hitters (jumps 38+; 39.4 ± 25.9 counts and jumps 50+; 15.0 ± 15.6 counts) and opposite hitters (jumps 38+; 47.9 ± 24.1 counts and jumps 50+; 29.7 ± 18.1 counts), while setters had the fewest high‐intensity jump counts (jumps 38+; 19.0 ± 16.6 counts and jumps 50+; 0.4 ± 0.8 counts). Middle blockers had the highest CMJ height (36.1 ± 6.4 cm), deepest CMJ depth (−41.7 ± 6.4 cm) and peak (2.75 ± 0.22 m/s) and average (1.49 ± 0.08 m/s) propulsion velocities (2.75 ± 0.22 m/s). Meanwhile, setters had significantly greater braking RFD (7839 ± 2617 N), average (1698 ± 223 N) and peak braking force (2061 ± 248 N), and average (1446 ± 88 N) and peak propulsion force (1994 ± 213 N), compared to all other positions. Opposite and outside hitters’ data fell between setters and middle blockers. Regardless of position, neuromuscular performance fluctuates during the season and there are noticeable positional differences in jump loads and force and velocity metrics.
CLK1 Activates YAP to Promote Intrahepatic Cholangiocarcinogenesis
Authors: Xue Shuai , Chen Xiangzheng , Qiu Guoteng , Liao Haotian , Qiang Zeyuan , Zhang Zheng , Feng Xuping , Xu Lin , Xie Rui , Zhou Hongyu , Huang Jiwei , Zeng Yong , Wang Haichuan
Published: December 2024

Cdc2-like kinase 1 (CLK1) has dual-specificity kinase ability to phosphorylate tyrosine and serine/threonine protein residues. CLK1 regulates many physiological processes and has been shown to contribute to multiple types of cancer. Here, we investigated the functional role of CLK1 during intrahepatic cholangiocarcinoma (ICC) development. The expression of CLK1 was elevated in ICC tumors, and patients with high expression of CLK1 demonstrated poor prognosis. In hydrodynamically transfected mouse models, CLK1 alone was insufficient to induce ICC, whereas CLK1 cooperated with AKT (AKT/CLK1) to trigger ICC initiation. In addition, overexpression of CLK1 in ICC cells facilitated proliferation in vitro and tumor growth in vivo, while loss of CLK1 elicited the opposite effects. Moreover, RNAseq analysis indicated that high levels of CLK1 corresponded with activation of the Hippo-YAP signaling pathway. Consistently, the AKT/CLK1 murine tumors displayed upregulation of YAP as well as its downstream targets. Furthermore, loss or pharmacological inhibition YAP in ICC cells inhibited CLK1-induced growth, and deletion of Yap completely retarded the induction of AKT/CLK1 tumors. Mechanistically, 4D-label free mass spectrometry and co-immunoprecipitation assays revealed WWC2 as a potential mediator of CLK1-YAP cascade. Collectively, the current findings identify a critical role for CLK1 in promoting ICC development and indicate that inhibiting YAP might be an effective approach for perturbing CLK1-mediated tumorigenesis.
Data from DeePathNet: A Transformer-Based Deep Learning Model Integrating Multiomic Data with Cancer Pathways
Authors: Cai Zhaoxiang , Poulos Rebecca C. , Aref Adel , Robinson Phillip J. , Reddel Roger R. , Zhong Qing
Published: December 2024

Abstract
Multiomic data analysis incorporating machine learning has the potential to significantly improve cancer diagnosis and prognosis. Traditional machine learning methods are usually limited to omic measurements, omitting existing domain knowledge, such as the biological networks that link molecular entities in various omic data types. Here, we develop a transformer-based explainable deep learning model, DeePathNet, which integrates cancer-specific pathway information into multiomic data analysis. Using a variety of big datasets, including ProCan-DepMapSanger, Cancer Cell Line Encyclopedia, and The Cancer Genome Atlas, we demonstrate and validate that DeePathNet outperforms traditional methods for predicting drug response and classifying cancer type and subtype. Combining biomedical knowledge and state-of-the-art deep learning methods, DeePathNet enables biomarker discovery at the pathway level, maximizing the power of data-driven approaches to cancer research. DeePathNet is available on GitHub at https://github.com/CMRI-ProCan/DeePathNet.
Significance:
DeePathNet integrates cancer-specific biological pathways using transformer-based deep learning for enhanced cancer analysis. It outperforms existing models in predicting drug responses, cancer types, and subtypes. By enabling pathway-level biomarker discovery, DeePathNet represents a significant advancement in cancer research and could lead to more effective treatments.
Drug utilization research in a municipality in the state of Espírito Santo: findings and implications related to the practice of polypharmacy
Authors: Bazoni Patrícia Silva , Faria Ronaldo José , Silva Alciellen Mendes da , Horsth Ana Luisa , Meira Eduardo Frizzera , Santos Jéssica Barreto Ribeiro dos , Silva Michael Ruberson Ribeiro da
Published: December 2024

Objetivo: Estimar a prevalência, o perfil e os fatores associados à polifarmácia durante a pandemia por COVID-19 em moradores da região Sul do Espírito Santo. Métodos: Realizou-se um estudo transversal, no município de Alegre, entre os meses de novembro e dezembro de 2021. Foi realizada análise descritiva para as características sociodemográficas e clínicas dos entrevistados, bem como dos medicamentos mais utilizados. A ocorrência da polifarmácia menor foi definida como o uso de dois a quatro medicamentos e a polifarmácia maior como o uso de cinco ou mais medicamentos. Modelos de regressão logística multinomial foram utilizados para analisar a associação das variáveis sociodemográficas e clínicas com a ocorrência da polifarmácia. Resultados: Os medicamentos mais utilizados foram os do sistema cardiovascular, seguido do sistema nervoso central e trato alimentar e metabolismo, sendo os cinco medicamentos mais utilizados representados pela dipirona, losartana, hidroclorotiazida, sinvastatina e metformina. A prevalência da polifarmácia menor foi de 44,9% e da polifarmácia maior de 20,2%. Os fatores associados significativamente à polifarmácia menor foram: maior faixa etária, sexo feminino, se autodeclarar branco, pior qualidade de vida, consultas médicas no último ano, uso da Farmácia Básica Municipal e presença de comorbidades. Além disso, renda mais elevada, autopercepção de saúde regular e ruim/muito ruim, não se automedicar, problemas de adesão ao tratamento e não usar plantas medicinais foram fatores associados à ocorrência da polifarmácia maior. Conclusão: Foram identificados diversos fatores sociodemográficos e clínicos relacionados a ocorrência de polifarmácia. O conhecimento desses fatores irá contribuir para a proposição de medidas de educação em saúde, para auxiliar na promoção do uso racional de medicamentos e melhorar a segurança e experiência do paciente com o uso dos medicamentos.
Construção e Validação de um Questionário sobre conhecimentos dos farmacêuticos para trabalhar no Cuidado ao Paciente no Sistema Público de Saúde Brasileiro
Authors: Silva Luanna Gabriella Resende da , Souza Samara Ribeiro de , Tinoco Marlon Silva , Fernandes Mayra Rodrigues , Oliveira William Neves , Obreli-Neto Paulo Roque , Belo Vinicius Silva , Pereira Mariana Linhares , Baldoni André Oliveira
Published: December 2024

Introdução: A maior parte dos farmacêuticos comunitários brasileiros não possuem a devida qualificação para exercer o Cuidado Farmacêutico junto aos pacientes com Diabetes Mellitus (DM). Assim, faz-se necessário construir e validar um questionário para medir conhecimento de farmacêuticos inseridos no Brazilian Public Health System (SUS). Métodos: Estudo metodológico, desenvolvido em quatro etapas: elaboração do questionário construído com base na literatura; validação de conteúdo por meio da técnica Delphi; pré-teste com farmacêuticos SUS; e estudo piloto, em que o questionário foi aplicado aos farmacêuticos do SUS que participaram da capacitação antes e após o término de um curso de capacitação. Para avaliar o conhecimento do farmacêutico no curso, realizou-se as médias antes (T0) e após (T1) a realização do curso, considerando-se dois grupos: Grupo A (Farmacêuticos com ≥ 75% de participação no curso) e Grupo B (Farmacêuticos com participação < 75%). Resultados: Foi necessária apenas uma rodada entre os 31 especialistas pela Técnica de Delphi (Cálculo para Validade de Conteúdo total = 98%). O questionário final apresentou 13 questões, sendo que 10 foram elaboradas e validadas pelos autores e três questões são de um questionário validado. Houve diferença entre as médias do Grupo A (média inicial 7,50 e final 9,90, p = 0,000), o que não foi observado no grupo B (média inicial 6,63 versus final 6,06, p=0,120). Conclusão: O questionário sobre DM e comorbidades associadas permitiu a mensuração do conhecimento de farmacêuticos do SUS.-
Análise epidemiológica das anomalias congênitas prioritárias para fins de vigilância ao nascimento em uma regional de saúde do Maranhão
Authors: Silva Hidário Lima da , Dias Ismália  Cassandra Costa Maia , Santos Floriacy Stabnow S , Santos Leonardo Hunaldo dos , Pascoal Lívia Maia , Santos Neto Marcelino , Bezerra Janaína Miranda
Published: December 2024

Introdução: As anomalias congênitas prioritárias para fins de vigilância ao nascimento constituem um grupo de anomalias definidas pelo Ministério da Saúde do Brasil que podem ser identificadas oportunamente após o parto, principalmente por apresentarem características que facilitam a identificação pós-parto, bem como a tomada de condutas de forma precoce e a realização de terapêuticas adequadas. Objetivo: Determinar a tendência da incidência e caracterizar os casos de anomalias congênitas prioritárias para fins de vigilância ao nascimento em uma regional de saúde do sudoeste do Maranhão, Brasil. Métodos: Estudo ecológico, de séries temporais, realizado com dados sobre nascidos vivos com anomalias na Regional de Saúde de Imperatriz, Maranhão (2011-2020), a partir de dados do Sistema de Informações sobre Nascidos Vivos. A análise de tendência temporal das taxas de incidência foi realizada por regressões lineares de Prais-Winsten, por meio do software SPSS, na versão 24.0, a 5% de significância. Resultados: Foram 222 casos de anomalias prioritárias. Os defeitos de membros apresentaram maior incidência (0,88/1.000), com taxa de variação anual de -5,6 (IC95%: -15,7; 5,7) e p-valor estável de 0,35. Predominaram-se mulheres solteiras (69,36%), de até 29 anos de idade (72,98%), gestação a termo (77,03%) e única (95,94%). A maioria dos recém-nascidos eram do sexo masculino (60,81%), com peso adequado (70,72%) e cor parda (79,28%). Conclusão: A ocorrência de anomalias congênitas prioritárias no sudoeste do Maranhão apresentou-se estável, com predomínio dos defeitos de membros. A atenção ao pré-natal oportuniza o diagnóstico precoce, embora os dados demonstrem que as anomalias congênitas ainda são prevalentes.
Fatores associados à depressão pós-parto: uma análise de agregação
Authors: Netto Larissa Reisen , Mousinho Pietra Sardinha Silvestre , Matta Julia Surrage da , Batista Thainá Gomes , Cypreste Adriana Marchon Zago , Bubach Susana , Santos Andréia Soprani dos , Poton Wanêssa Lacerda
Published: December 2024

Introduction: Postpartum depression (PPD), according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), is a multifactorial disease, which occurs during pregnancy until the fourth week postpartum. Objective: To assess whether family support, depression and/or anxiety before or during pregnancy, alcohol consumption and/or smoking during pregnancy, and age (<20 or >35 years), together or separately, in puerperal women influence the occurrence of PPD. Methods: A longitudinal and multicenter study, called “Projeto Viver”, with 3435 women who gave birth in three maternity hospitals in Espírito Santo. At the last follow-up, at the end of the neonatal period, 1818 puerperae were interviewed by telephone (52.9%). Poisson analysis with robust variance adjustment was performed for one, two, three and even four grouped factors, and adjusted for covariates. Results: The prevalence of PPD was 7.3% (95% CI 6.1% - 8.5%) in the first month after delivery. Most puerperae with PPD were between 20 and 34 years old (71.2%; 95%CI 62.8% - 78.3%), more than 12 years of education (60.7%; 95%CI 51.5% - 69.2%), non-white skin color (77.3%; 95%CI 69.2% - 83.8%) and social class C (51.5%; 95%CI 42.9% - 60.0%). The most prevalent risk factor in puerperae with PPD was the lack of family support (34.1%; 95%CI 26.4% - 42.6%) and the least was depression and/or anxiety before or during pregnancy (3.8%; 95%CI 1.6% - 8.8%). Women without family support, who smoked and/or drank during pregnancy had 98% and 60% risk for PPD, respectively. The presence of two and three risk factors doubled and tripled the risk for PPD among puerperae, respectively. In puerperae with two concurrent factors, such as lack of family support and smoking/ethylism, as well as those with depression and/or anxiety before or during pregnancy and age extremes, the risk for PPD was 2.1 (95% CI 1.2 - 3.9) and 3.7 (95% CI 1.2 - 11.7), respectively. Conclusion: The result of this study allowed the knowledge of the risk of aggregate factors, and can contribute to public health actions that minimize them in pregnant women, in order to reduce the occurrence of depression after childbirth.
Desenvolvimento de uma aplicação móvel baseada em jogos para o ensino da Anatomia de estudantes da área da saúde
Authors: Nascimento José Vitor de Sousa , Mendes Victor Hugo da Silva , Rodrigues Vandilson Pinheiro
Published: December 2024

Introduction: Game-based mobile applications have become powerful tools to aid the learningprocess. In the study of human anatomy, the use of apps has shown promise, providing studentswith an interactive and accessible way to explore and understand the complexity of the humanbody. Objective: This study describes the performance on digital platforms of an application developed to help healthcare students learn human anatomy content. Methods: This mobile application was developed in the Dart programming language and made available for Android and iOS systems. The Anatomania App presented a multifaceted approach to teaching human anatomy, including resources such as quizzes, text lessons, explanatory videos, and flashcards. These screens offer options for adjusting individual preferences and settings. Results: This mobile application had a total of 85,807 downloads and 82,839 registered users. This application had a high frequency of users from Portuguese-speaking countries such as Brazil, Angola, Portugal, and Mozambique. Conclusion: This educational application has shown the potential to promote a more effective and interactive approach to learning anatomy.
Prognostic Implications of Right Ventricular Dysfunction in Severe Degenerative Mitral Regurgitation
Authors: Bohbot Yohann , Essayagh Benjamin , Benfari Giovanni , Bax Jeroen J. , Le Tourneau Thierry , Topilsky Yan , Antoine Clemence , Rusinaru Dan , Grigioni Francesco , Ajmone Marsan Nina , van Wijngaarden Aniek , Hochstadt Aviram , Roussel Jean Christian , Diouf Momar , Thapa Prabin , Michelena Hector I. , Enriquez‐Sarano Maurice , Tribouilloy Christophe
Published: December 2024

Background

The prevalence and impact of right ventricular dysfunction (RVD) in degenerative mitral regurgitation (DMR) is unknown. We aimed to determine whether RVD assessed by echocardiography in routine clinical practice is independently associated with mortality in patients with DMR.

Methods and Results

We used data from the MIDA‐Q (Mitral Regurgitation International DAtabase‐Quantitative) registry, which included patients with isolated DMR due to mitral valve prolapse from January 2003 to January 2020 from 5 tertiary centers across North America, Europe, and the Middle East. A cohort of 2917 (mean age: 66 years, 70.8% male patients, follow‐up: 5.2 [3.3–8.3] years) consecutive patients with severe DMR was included and long‐term mortality was analyzed. RVD, identified in 426 (14.6%) patients, was associated with reduced 8‐year survival (55%±3% versus 77%±1%;
P
<0.001), overall and in all subgroups of patients, even after comprehensive adjustment including left ventricular dilatation and dysfunction, DMR severity, pulmonary pressures, and surgery (adjusted hazard ratio, 1.44 [95% CI, 1.17–1.77];
P
<0.001). This excess mortality was observed under medical management (adjusted hazard ratio, 1.57 [95% CI, 1.20–2.05];
P
=0.001) and after surgical correction of mitral regurgitation (adjusted hazard ratio, 1.45 [95% CI, 1.02–2.05];
P
=0.039). Patients with RVD undergoing surgery within 3 months of diagnosis experienced a better 8‐year survival (73%±4% versus 43%±4%;
P
<0.001), even after adjustment (adjusted hazard ratio, 0.44 [95% CI, 0.29–0.67];
P
<0.001) despite an increase of 1‐month postoperative mortality (7.1% versus 0.5% for patients without RVD;
P
<0.001).

Conclusions

RVD is observed in 14.6% of severe DMR and exhibits a powerful and independent association with excess mortality partially attenuated by mitral surgery. Therefore, assessment of right ventricular systolic function should be included in routine DMR evaluation and in the clinical decision‐making process.
Dose–response of tDCS effects on motor learning and cortical excitability: A preregistered study
Authors: Hsu Gavin , Jafari Zhenous Hadi , Ahmed Abdelrahman , Edwards Dylan J. , Cohen Leonardo G. , Parra Lucas C.
Published: December 2024

Multiple studies have demonstrated that transcranial direct current stimulation (tDCS) of the primary motor cortex (M1) can influence corticospinal excitability and motor skill acquisition. However, the evidence for these effects is inconsistent, and a common neural substrate for these effects has not been directly demonstrated. To address this, we hypothesized that higher tDCS intensities would produce more robust effects, and uncover their relationship. In this preregistered study, 120 participants engaged in a motor skill learning task while receiving tDCS with posterior-to-anterior currents through M1. We employed a double-blind, between-subjects design, with groups of 4 mA, 6 mA, or sham stimulation, while ensuring balanced groups in terms of typing speed. Cortical excitability was assessed via motor-evoked potentials (MEPs) and TMS-evoked potentials (TEPs) before and after motor skill learning with concurrent tDCS. tDCS at these higher intensities was well tolerated, and motor learning correlated with pretraining typing speed. Planned analyses found no dose–response effect of tDCS on motor skill performance or MEP amplitude. This suggests that, under our experimental conditions, tDCS did not significantly modulate motor skill learning or corticospinal excitability. Furthermore, there was no correlation between motor performance and MEP, and thus no evidence for a common neural substrate. Exploratory analyses found an increase in MEP and TEP amplitudes following the sequence learning task. Motor skill gains positively correlated with TEP changes over the stimulated M1, which were more negative with increasing tDCS intensity. The effects of tDCS on motor skill learning and MEPs, if they exist, may require particular experimental conditions that have not been tested here. Preregistration: https://osf.io/jyuev (in-principle acceptance: 2024/06/05)
Macrovascular contributions to resting-state fMRI signals: A comparison between EPI and bSSFP at 9.4 Tesla
Authors: Ramadan Dana , Mueller Sebastian , Stirnberg Ruediger , Bosch Dario , Ehses Philipp , Scheffler Klaus , Bause Jonas
Published: December 2024

The draining-vein bias of T2*-weighted sequences, like gradient echo echo-planar imaging (GRE-EPI), can limit the spatial specificity of functional MRI (fMRI). The underlying extravascular signal changes increase with field strength (B0) and the perpendicularity of draining veins to the main axis of B0, and are, therefore, particularly problematic at ultra-high field (UHF). In contrast, simulations showed that T2-weighted sequences are less affected by the draining-vein bias, depending on the amount of rephasing of extravascular signal. As large pial veins on the cortical surface follow the cortical folding tightly, their orientation can be approximated by the cortical orientation to B0→. In our work, we compare the influence of the cortical orientation to B0→ on the resting-state fMRI signal of three sequences aiming to understand their macrovascular contribution. While 2D GRE-EPI and 3D GRE-EPI (both T2*-weighted) showed a high dependence on the cortical orientation to B0→, especially on the cortical surface, this was not the case for 3D balanced steady-state free precession (bSSFP) (T2/T1-weighted). Here, a slight increase of orientation dependence was shown in depths closest to white matter (WM). And while orientation dependence decreased with increased distance to the veins for both EPI sequences, no change in orientation dependence was observed in bSSFP. This indicates the low macrovascular contribution to the bSSFP signal, making it a promising sequence for layer fMRI at UHF.
Using bibliometrics to detect questionable authorship and affiliation practices and their impact on global research metrics: A case study of 14 universities
Authors: Meho Lokman I. , Akl Elie A.
Published: December 2024

From 2019 to 2023, a subset of 80 highly published universities demonstrated research output increases exceeding 100%, compared to the global average of 20%. Among these, 14 institutions showed significant declines in first authorship rates, raising questions about their authorship and affiliation practices. We employed bibliometric analysis to examine shifts in authorship and affiliation dynamics at these universities. Key findings include a 234% rise in total publications, a 23 percentage point drop in first authorship rates, and an increase in hyperprolific authors from 23 to 177. International collaborations surged, and several universities exhibited sharp rises in multiaffiliated publications. Additionally, the proportion of articles published in top 10% journals increased by 11 percentage points, and the proportion of articles ranked among the world’s top 10% most cited grew by 12 percentage points. These trends raise concerns about the integrity of authorship and affiliation practices, as they deviate from normative behavior, far exceeding those observed nationally and at top-ranked universities—Caltech, MIT, Princeton, and UC Berkeley. The study emphasizes the need for collaborative reforms by universities, ranking agencies, publishers, and other entities, highlighting the importance of each entity’s role in preserving academic integrity and ensuring the reliability of global research metrics.
Exploration and exploitation: Which research strategy are you better at?
Authors: Huang Shengzhi , Lu Wei , Cheng Qikai , Zhang Li , Huang Yong
Published: December 2024

This study quantifies and analyzes the individual-level abilities of scientists utilizing either an exploration or an exploitation strategy. Specifically, we present a Research Strategy Q model, which untangles the coupling effect of scientists’ research ability (Qα) and research strategy ability (Eαπ) on research performance. Qα indicates scientists’ fundamental ability to publish high-quality papers, while Eαπ indicates scientists’ proficiency in terms of exploration and exploitation strategies. Five research strategies proposed by our previous study are employed. We generate synthetic data and collect empirical data as our experimental data set. We show that these research strategies present different benefit and risk characteristics. Adopting some exploitation strategies tends to stifle research performance, while exploration strategies are high risk and high yield. Qα and Eαπ have predictive power for research performance. Moreover, we find that, first, scholars who prefer to execute a research strategy, π, may not necessarily be better at executing π. Second, some scholars have differences in their abilities towards different strategies, while other scholars have differences in their abilities towards the same strategy. Third, exploration and exploitation are not contradictory but complementary from the perspective of proficiency, while they are mutually exclusive from the perspective of selection preference.
Amazigh-Arabic Code-Switching in Radio Talk Shows
Authors: Driouch Aziz , Hermas Abdelkader
Published: December 2024

This study considers code-switching (CS) in the discourse of multilingual Amazigh speakers. The corpus consists of live Amazigh radio talk shows in Morocco (North Africa). The study examines the frequency and nature of CS between Amazigh (Tashelhit variety) and Arabic and identifies the conversational functions of CS. The analysis shows a substantial use of Arabic in Amazigh radio discourse; 72 % of the utterances attest to Arabic CS. The two languages play the role of the matrix and embedded language. Standard Arabic (92 %) is more activated than Moroccan Arabic (8 %). As for the conversational functions of CS, the majority of the functions in Gumperz (1982) are instantiated in the corpus: quotation, interjection, reiteration, message qualification, and personalization and objectivization, but new functions emerged: the principle of economy, cultural items, lexical and semantic gaps, and discourse fillers. Finally, we claim that Amazigh-Arabic CS has led to the inception of a third code that mixes verb stems with morphology of the two languages.
A Model for the Development of Learning in a Virtual Geological Field Trip as a Modified Novelty Space
Authors: Choi Yoon-Sung
Published: December 2024

The purpose of this study is to propose a “modified novelty space” model for learning in virtual geological field trips. To do so, three field sites in Busan National Geopark were selected to explore geological characteristics. VR-based virtual field trips (VFTs) were developed for participation. These VFTs consisted of basic, plus, and advanced steps. The modified novelty space model redefines the novelty space for the context of virtual learning environments (VLEs) by subdividing it into cognitive, geographic, psychological, technical, and social factors. The cognitive domain refers to the curriculum content in geology. The geographic domain involves contextual interpretations of places. The psychological domain increases familiarity based on methods to provide stability. The technical domain refers to the ability to handle skills. The social domain refers to emotional sharing among people in relationships. This model proposes five elements with the aim of decrease in modified novelty space ultimately contributing positively to virtual learning.
A Database of Early Modern Tax Registers of the White Forest (Central Poland)
Authors: Jasiński Cezary , Związek Tomasz
Published: December 2024

This article presents a database focusing on settlement patterns, demographics, and economic transformations within one of the largest forested areas of early modern Poland, the White Forest, situated at the confluence of two significant rivers, the Narew and Bug. These waterways historically facilitated the export of grain and forest products from eastern Poland and certain regions of the Grand Duchy of Lithuania. This database was compiled according to the guidelines established by the “Historical Atlas of Poland” which gathers spatially-oriented data pertinent to the historical geography of Polish lands. The database pertains to a region that was somewhat peripheral in terms of the overall national development, rendering it suitable for comparative analysis with other European regions that exhibit similar trends—intensive settlement expansion, environmental pressure in the early modern era, and a degree of distance from contemporary political and economic hubs.
Examining the Impact of ict Use and Related Attitudes on Students’ Achievements in Science Using the pls-sem Model
Authors: Eksail Fuad Ali Ahmed
Published: December 2024

Investigations were conducted into the relationships between science achievement and ict use in and out of the classroom, as well as the mediating effects of students’ interest in and perceptions of their ict proficiency. The primary focus of this study has been the association between ict and scientific achievement among Singaporean students as measured by the Programme for International Student Assessment (pisa) 2018. This study examined pisa 2018 data using partial least squares structural equation modeling (pls-sem) to evaluate the effect of ict use on students’ achievements in science. Complex cause-and-effect relationships in path models with latent variables can be estimated using the structural equation modeling method known as pls-sem. 6,676 15-year-old Singaporean students who participated in the 2018 Programme for International Student Assessment (pisa) were examined. Students’ interest in ict, their assessment of their ict competency, and their accomplishment in science were found to be correlated with how they used ict both inside and outside of the classroom. The findings also imply that the association between ict use and science accomplishment may be mediated by students’ perceived ict proficiency and interest. This research can contribute to advancing the theoretical knowledge of technology, learning, and the cultural environment, in addition to practical ict implementations in scientific classes that consider the variances in ict affects.
Resistance to Epoetin-Stimulating Agents in Children Receiving Renal Replacement Therapy
Authors: Kaya Mehtap , Cicek Neslihan , Guven Sercin , Alpay Harika , Gokce Ibrahim
Published: December 2024

The incidence of anemia increases with the stage of chronic kidney disease (CKD). Erythropoietin (EPO) deficiency is a common cause of anemia in CKD. Erythropoietin-stimulating agents (ESAs) are the mainstay of the treatment. Treatment can be challenging due to erythropoietin resistance (ER), which can be assessed using the erythropoietin resistance index (ERI). Our aim was to investigate the factors contributing to high ERI levels in children receiving renal replacement therapy (RRT). Thirty-three children receiving RRT for at least 3 months were included. The mean ERI value was 15.7 IU/kg/w/g/dL. A significant association was observed between serum phosphorus levels and ERI ( P = .016, r = 0.41). The mean parathormone (PTH) level was also higher in the high ERI group (599 ± 351 vs 392 ± 320 pg/mL, P = .088). An association, approaching statistical significance, was found between ERI and hypertension ( P = .06, r = 0.32). Our study indicated a potential relationship between hyperphosphatemia, possibly secondary hyperparathyroidism, and ERI in children undergoing RRT.