bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatial distribution and factors of ideal number of children among Ethiopian women: The Case of Ethiopia Demographic and Health Survey
Authors: Mengist Addisalem , Asmare Samson 
Published: July 2023

Abstract
Background
Fertility is one of the important subjects in public health studies which affects populationgrowth.Ideal number of children is one of the main indexes showing the fertility preferences of couples. The main objective of this study was to analyze the spatial distribution and factors of an ideal number of children among Ethiopian women using the multilevel count regression model.
Methods
The study design was a cross sectional study. About 14003 women’s ages of 15–49 who fulfill the inclusion criterion were considered in this study. The study was evaluated based on different statistical model such as NB regression model and cross level interaction between level-2 and level-1 predictors (model5). In the meantime, a model with the best fit of the data using AIC and BIC was found to be a Multilevel Negative Binomial regression model.
Results
From this study, 33% of the women had need more INC and the variance of the INC was higher than its mean, this indicates that there is over dispersion so NB regression models were considered to select the best fit for the data. The LRT suggested that, INC visits vary among zones Furthermore, the Ideal number of children was spatial clustered (Global Moran’s I = 0.1439, p < 0.00043). Significant hotspot clusters were found in the Somali region such as in Afder, Shabelle, Korahe, Doolo zone.
Conclusion
Our study investigated the spatial heterogeneity of an ideal number of children, and its association with women’s age, region, place of residence, women's education, contraception use, religion, family size, spatial variable (Si) and age at first birth were significant predictors of the ideal number of children by women at reproductive age. Significant hotspot clusters were found in the Somali region such as in Afder, Shabelle, Korahe, Doolo zone. Therefore, Spatial distribution of INC different across each zone of Ethiopia.
Hypergraph Reinforced Graph Collaborative Learning for Session-based Recommendation
Authors: ZHANG Jingwei , ZHANG Jingai , ZHANG Wenxiang , YANG Qing , HU Shiyan 
Published: July 2023

Abstract
Session-based recommendation(SBR) aims to provide more accurate recommendations to users based on anonymous behavior sequences. Almost all the existing graph neural networks for SBR models only focus on converting session sequences into a single type of graph, which can not provide effective and comprehensive item transformation relationships to improve the performance of capturing user preferences. In this paper, we propose a Hypergraph Reinforced Graph Collaborative Learning (HGL-SR) to compensate for the shortcomings of a single type in graph modeling. HGL-SR learns two levels of item embeddings from session graphs and hypergraphs. Specifically, we design a session graph channel and a hypergraph channel. In the session graph channel, we capture the low-order transition information of items using the contextual relationships in the session sequence. And for cross-session potential sequence aspects, we view each session as a collection of items, construct hypergraphs and learn higher-order transition information between items. To make the hypergraph learning results better for reinforcing session graph learning, we design a collaborative learning module to capture more accurate user preferences through item information. Extensive experiments conducted on two real datasets show that HGL-SR outperforms the state-of-the-art session-based recommendation methods consistently.
Integrating Deep Learning Algorithms with Satellite Images: Revolutionizing Earth Observation
Authors: Neyigapula Bheema Shanker 
Published: July 2023

Abstract
Earth observation using satellite images is a critical component of understanding our planet’s dynamics and monitoring environmental changes. The integration of deep learning algorithms with satellite images has revolutionized the field by enabling the extraction of valuable insights from these vast datasets. This research paper specifically focuses on the application of Graph Convolutional Networks (GCNs) in earth observation. GCNs provide a powerful framework for analyzing satellite images by leveraging the inherent spatial relationships among pixels. We explore the fundamentals of GCNs, their advantages in image analysis, and their applications in land cover classification, object detection, urban development monitoring, weather prediction, and climate modeling. Additionally, we discuss the challenges and limitations associated with integrating GCNs with satellite images and propose future research directions to enhance their performance and efficiency. The findings of this research highlight the transformative potential of GCNs in revolutionizing earth observation and offer new avenues for improving our understanding of the planet’s dynamics.
Predicting Mortality Risk in Hospitalized COVID-19 Patients: An Early Model Utilizing Clinical Symptoms
Authors: Hai Cong Nguyen , Duc Thanh Bui , Minh The Nguyen , Duc Loi Trinh , Quang Lich Ngo , Tung Son Luong Cao , Quy Sy Duong 
Published: July 2023

Abstract
Background: Despite global efforts to control the COVID-19 pandemic, the emergence of new viral strains continues to pose a significant threat. Accurate patient stratification, optimized resource allocation, and appropriate treatment are crucial in managing COVID-19 cases. To address this, a simple and accurate prognostic tool capable of rapidly identifying individuals at high risk of mortality is urgently needed. Early prognosis facilitates predicting treatment outcomes and enables effective patient management. The aim of this study was to develop an early predictive model for assessing mortality risk in hospitalized COVID-19 patients, utilizing baseline clinical factors.
Methods: We conducted a descriptive cross-sectional study involving a cohort of 375 COVID-19 patients admitted and treated at the COVID-19 Patient Treatment Center in Military Hospital 175 from October 2021 to December 2022.
Results: Among the 375 patients, 246 and 129 patients were categorized into the survival and mortality groups, respectively. Our findings revealed six clinical factors that demonstrated independent predictive value for mortality in COVID-19 patients. These factors included age greater than 50 years, presence of multiple underlying diseases, dyspnea, acute confusion, oxygen saturation below 94%, and oxygen demand exceeding 5 liters per minute. We integrated these factors to develop the Military Hospital 175 scale (MH175), a prognostic scale demonstrating significant discriminatory ability with an area under the curve (AUC) of 0.87. The optimal cutoff value for predicting mortality risk using the MH175 score was determined to be ≥ 3 points, resulting in a sensitivity of 96.1%, specificity of 63.4%, positive predictive value of 58%, and negative predictive value of 96.9%.
Conclusions: The MH175 scale demonstrated a robust predictive capacity for assessing mortality risk in patients with COVID-19. Implementation of the MH175 scale in clinical settings can aid in patient stratification and facilitate the application of appropriate treatment strategies, ultimately reducing the risk of death. Therefore, the utilization of the MH175 scale holds significant potential to improve clinical outcomes in COVID-19 patients.
Trial registration: The participants were registered.
Association between echocardiography utilization and prognosis in patients with cardiac arrest: A retrospective study based on the MIMIC-IV database
Authors: Zhang Nan , Lin Qingting , Zhu Huadong 
Published: July 2023

Abstract
Background
Cardiac arrest is one of the main causes of adult mortality worldwide. However, the impact of the application of echocardiography on the prognosis of cardiac arrest patients is still lacking sufficient research.
Objectives
We aimed to explore the association between the echocardiography utilization and the prognosis of patients with cardiac arrest, which can offer some evidence to Improving the quality of diagnosis and treatment for patients with cardiac arrest.
Methods
This study was a retrospective study including adult patients aged over 18 with cardiac arrest diagnosis and hospitalized in the Intensive Care Unit (ICU) from the Medical Information Mart for Intensive Care IV (MIMIC-IV). Patients were grouped according to whether echocardiography was performed during the hospitalization, analysis models including dual robust estimation were used to evaluate the association between the application of echocardiography and the prognosis of patients with cardiac arrest.
Results
Compared with the control group without echocardiography, patients receiving echocardiography showed better outcomes in both hospitalization survival (Odds ratio = 0.94, 95% CI: 0.90–0.98, p = 0.007) and 28-day survival (p < 0.001).
Conclusions
In patients with cardiac arrest, the use of echocardiography was associated with a reduction in mortality rate.
Do Marketing Ethics Matter in formulating Consumer’s Purchase Intention? Evidence From the Sultanate of Oman
Authors: Abdelfattah Fadi , AlAlawi Abrar , Balushi Nabeela Imam Bakhsh AL , Salah Mohammed , AlWashahi Maryam 
Published: July 2023

Abstract
This study investigates the factors that affect customers’ purchasing intention to adopt shopping platforms in Oman. A conceptual model was developed after extensively reviewing related literature. An adapted questionnaire was developed and used to collect data from customers who have experience using digital platforms. One hundred and twelve responses were received through a convenient sampling method. The Partial Least Square (PLS) software analysed and validated the data. The findings showed that unethical marketing practices significantly affect the perceived risk of product scarcity and the intention to adopt digital platforms. As a result, several recommendations were made to the relevant authorities, including the Ministry of Commerce, Industry, and Investment Promotion, to understand and explore the aspects of deception that digital platforms use and develop and pass legislation in line with and ensure fair competition.
The effect of angiotensin-converting enzyme insertion/deletion polymorphism on severity and death rate of COVID-19 in Iranian patients
Authors: Samet Mohammad , Yazdi Mehran , Tajamolian Masoud , Beygi Mahdi , Sheikhha Mohammad Hasan , Hoseini Seyed Mehdi 
Published: July 2023

Abstract
The study was designed to assess the association of ACE I/D polymorphism with the severity and prognosis of COVID-19 in Iranian population. Hence, 186 adult patients were categorized into three clinical groups based on the severity of COVID-19: 1) Outpatients or mild symptomatic patients as control; 2) Hospitalized patients or severe symptomatic cases; 3) Inpatients led to ICU/death or critically ill patients needed mechanical ventilation. The possible association of ACE I/D polymorphism with the risk of comorbidities and serum level of C-reactive protein was evaluated in two severe cases. The results showed that the frequency of D and I alleles are 69.35% and 30.65%, respectively, in total population. The analysis of allelic frequencies via Fisher's exact test confirmed significantly higher frequency of D allele in both severe groups than that in the mild one, 78.31% in Hospitalized patients (OR = 0.38; 95% CI = 0.22 to 0.68; p-value = 0.0011) and 74.19% in Inpatients led to ICU/death (OR = 0.48; 95% CI = 0.29 to 0.82; p-value = 0.0094) compared to 58.45% in Outpatients. The results of genotype proportions displayed an association between COVID-19 severity and DD genotype. Altogether, our findings in Iranian patients and other reports from different population lead us to the conclusion that despite the undoubted role of the DD genotype in the severity of the disease, the protective effect of the I allele is highly depended on the genetic pool of ethnicities.
Porphyrin based Ni/Co metal-organic framework: Preparation, characterization and photodegradation of 1,5-dihydroxynaphthalene
Authors: Bokaei Forough , Rahim Rahmatollah , Rabbani Mahboubeh 
Published: July 2023

Abstract
In this study, mixed-metal metal-organic frameworks (MM-MOFs) containing metal-based porphyrin moieties will be synthesized and characterized. Then, efficiency of MOFs with Co and Ni alone and Co/Ni together in the different molar ratios as nodes with Mn-TCPP and H2TCPP as a linker in the structure of bimetallic-MOFs were investigated for photodegradation of DHN to Juglone. Also, different effecting factors on photocatalytic activity containing solvent, oxidant, time, and type of lamp, were further optimized for the best MM-MOF. According to the results, Ni50%/Co50% TCPP-Mn with the molar ratio of 1:1 of Ni:Co shows the highest efficiency in the photocatalytic process which was up to 66.3% under xenon lamp irradiation with blowing of O2 as the source of oxidant. Therefore, the presence both of nickel and cobalt in the structure led to a synergistic effect in enhancement of photocatalytic activity application.
The synergic interplay between entropy, predictability, and informational efficiency of the Shanghai sectoral index
Authors: Fernandes Leonardo H S , de Araujo Fernando Henrique Antunes , Silva José W. L. , Filho Marcos C. M. , Tabak Benjamin 
Published: July 2023

Abstract
We explore the synergic interplay between entropy (disorder), predictability, and informational efficiency of the daily closing price time series of 13 sectoral economics components of the Shanghai index letter considering three non-overlapping periods (before and during COVID-19 and Russia-Ukraine war). Our findings reveal that the telecom services, financials, and consumer discretionary sectors are marked by higher informational efficiency. Otherwise, the industrials, utilities, and transportation sectors exhibit lower informational efficiency. These insights are relevant for financial agents to make informed decisions, manage risk, and seek opportunities in an ever-changing market environment.
Recent Advances in Selective C-H Bonds Functionalization through Aryl Radical-
Mediated Hydrogen Atom Transfer Strategy
Authors: Xing Linlin , Zhang Yong 
Published: July 2023

Abstract:
Selective C-H bond functionalization of organic molecules has developed as an
increasingly versatile platform that found wide applications in the synthesis of naturally occurring
compounds, functional group modification, material sciences, and chemical and pharmaceutical
industries. Apart from transition metal catalysis, which traditionally underwent a
two-electron mechanism, a recent renascence of radical chemistry based on the hydrogen atom
transfer (HAT) strategy has resulted in the rapid development of C-H bond functionalization.
While many methodologies involving heteroatom-based HAT have been widely studied during
the last decade, areas employing their carbon analogs were still challenging for chemists
and remained less explored. Recent progress has been made to generate aryl radical species
under relatively mild conditions, which can be utilized in the HAT step conveniently, and as a
result, motivated the advancements of remote C(sp3)-H functionalization of various organic compounds, including
amines, alcohols, amides and so on. This review will discuss the recent progresses in the functionalization of C-H
bonds characterized by a key aryl HAT process, and, at the same time, some emphases have been laid on selective
C-H functionalization catalyzed by photoredox chemistry.
Worldwide Prevalence of Polypharmacy: A Systematic Review
Authors: Januário Beatriz Dias , Mafra Natália Silva , de Souza Silva Humberto , Carvalho Isabella Monteiro , Sena Ana Luiza Sobreira , Pereira Ana Paula Gomes Soares , de Faria Júnior Newton Santos , Campos Helton Oliveira 
Published: July 2023

Introduction:
The present study has compiled the prevalence of polypharmacy worldwide and assessed
the prevalence of polypharmacy in different populations, including community-dwelling individuals, hospitalized
patients, and institutionalized patients.

Methods:
This systematic review was conducted and reported according to the guidelines outlined in the Preferred
Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. A systematic search of electronic
databases, including PubMed, Web of Science, and Scielo, was performed in March 2021 without any date and language
restrictions. Combinations of the following keywords were used for the search strategy: polypharmacy OR
multiple medications OR multiple medicines OR multiple drug AND prevalence. Based on the search and inclusion
criteria, two hundred and eight studies (73,076,167 individuals) were selected for inclusion in the systematic review.
It was observed that there is a wide variation in the prevalence of polypharmacy between studies.

Results:
The prevalence of polypharmacy was found to be 30.2%, 61.7%, and 56.9% for community-dwelling individuals,
hospitalized patients, and institutionalized patients, respectively.

Conclusion:
Based on the analyses, this systematic review has demonstrated a wide variation in the prevalence of
polypharmacy between studies and countries and a high prevalence of polypharmacy in institutionalized and hospitalized
patients.
Advances in Enzyme-responsive Supramolecular In situ Self-assembled
Peptide for Drug Delivery
Authors: Xu Wentao , Qin Xiaowen , Liu Yang , Chen Jun , Wang Yuguang 
Published: July 2023

Abstract:
Because of low immunogenicity, ease of modification, and inherent biosafety, peptides have
been well recognized as vehicles to deliver therapeutic agents to targeted regions with improved pharmacokinetic characteristics. Enzyme-responsive self-assembled peptides (ERSAPs) show superiority
over their naive forms due to their enhanced targeting efficacy and long-retention property. In this review, we have summarized recent advances in the therapeutic application of ERSAPs, mainly focusing
on their self-therapeutic properties and potential as vehicles to deliver different drugs.
Medicinal Applications of Selenium Nanoparticles Synthesized by Green
Methods
Authors: Martínez-Esquivias Fernando , Méndez-Robles María Dolores , Villagómez-Vega Alejandra , Segura-Almendárez Mayra Socorro , de la Cruz-Ahumada Claudia Jackelin , Guzman-Flores Juan Manuel 
Published: July 2023

Abstract:
Green’ methodologies have become the main route for producing selenium nanoparticles
(SeNPs), as they do not involve toxic substances that can increase the reactivity of the synthesized nanoparticles
and are practical and inexpensive. Extracts from plants, bacteria, fungi, yeasts, ascorbic
acid, and polysaccharides are used to produce these nanoparticles. Plant extracts contain phytochemicals
that act as reducing and stabilizing agents, while bacteria, fungi, and yeasts can synthesize SeNPs
from metabolites secreted during their development or via intracellular mechanisms. Ascorbic acid is
also an excellent agent for reducing precursor metal salts, and polysaccharides act as stabilizing agents
for the synthesized nanoparticles. The SeNPs synthesized by these routes have desirable characteristics
for clinical applications since they are safe, non-toxic, and stable, with high biocompatibility and
bioavailability. In addition, they have antimicrobial, anti-cancer, anti-diabetic, anti-mosquito, antioxidant,
and anti-inflammatory activities, as revealed by both in vitro and in vivo studies.
Impact of Prolonged Use of COVID-19 Drugs on the Human Neurological
System using Insilco Drug-gene Interaction
Authors: Naqvi Wayez , Garg Prekshi , Srivastava Prachi 
Published: July 2023

Background:
Coronavirus disease (COVID-19) was an infectious illness brought on by the
SARS-CoV-2 virus. The first known SARS-CoV-2 infection was detected in the Wuhan District of China.
The diagnostic and therapeutic management of COVID-19 requires an immediate response, as an alternative,
quicker in-silico techniques can be used, which can serve as a filter before wet lab validation.

Objective:
A pharmaceutical drug, also known as a medication or medicine, is a chemical substance that
is used to treat, cure, prevent, or diagnose a disease or to promote overall health. When a particular class
of drugs is used to treat a diseased gene, it can also affect the various healthy non-diseased genes in the
body, resulting in altered gene expression and gene function.

Methods:
The adverse effects of medications prescribed to COVID-19 patients form the basis of this
study, which genes were being targeted, and what disorders or traits were caused as a result of this activity.

Results:
COVID-19 is said to cause inflammation of the brain's tissues; inflammation of brain tissue is
also a risk factor for Alzheimer's disease. The SARS-CoV-2 infection activates the inflammasome pathway,
which is seen in patients with neurodegenerative diseases such as Alzheimer's and Parkinson's.

Conclusion:
SARS-CoV-2 can enter the brain via the olfactory system or can be transferred through infected
immune cells. The virus could enter the body by infecting endothelial cells of the brain. The presence
of ACE2 receptors, SARS-CoV-2 receptors, interleukin (IL)-6, IL-1b, tumour necrosis factor (TNF),
and IL-17 disrupts the Blood Brain Barrier, allowing the virus to enter the brain.
Urgensi pendidikan karakter di institusi pendidikan kesehatan di Indonesia
Authors: Yani Lasiyati Yuswo 
Published: July 2023

Tenaga kesehatan harus memiliki karakter yang kuat, yakni memiliki etos kerja sesuai dengan kode etik dengan selalu mengedepankan pelayanan kesehatan kepada masyarakat. Dalam menjalankan tugasnya, tenaga kesehatan profesional harus dapat memenuhi tugas dan tanggung jawabnya sesuai dengan prinsip kode etik profesi dan peraturan perundang-undangan yang berlaku. Personal karakter yang kuat ini dimulai dari masa pendidikan, termasuk juga pendidikan tinggi. Penelitian ini bertujuan menganalisis pentingnya upaya penanaman nilai karakter bagi calon tenaga kesehatan khususnya bidan dan perawat dalam menghadapi era globalisasi. Penelitian ini menggunakan metode literature review dari beberapa sumber yang berupa artikel jurnal dan website dengan menggunakan pendekatan deduktif kuantitatif dengan cara menganalisis data yang digunakan sesuai dengan tema yang dibahas. Hasil penelitian ini menunjukkan bahwa penanaman pendidikan karakter penting dan sangat dibutuhkan bagi calon tenaga kesehatan. Bagi tenaga kesehatan, pembentukan karakter ini memerlukan pembinaan untuk membentuk karakter yang baik agar terbentuk tenaga kesehatan yang memiliki pemikiran maju tidak hanya mampu dalam keilmuan, tetapi juga dapat terampil yang holistik dalam memberikan pelayanan kesehatan.Health workers must have a strong character, namely having a work ethic in accordance with a code of ethics by always prioritizing health services to the community. In carrying out their duties, health professionals must be able to fulfill their duties and responsibilities in accordance with the principles of the professional code of ethics and applicable laws and regulations. This strong personal character starts from the time of education, including higher education. This research aims to analyze the importance of cultivating character values for prospective health workers, especially midwives and nurses in facing the globalization era. This study uses the literature review method from several sources in the form of journal articles and websites by using a quantitative deductive approach by analyzing the data used in accordance with the themes discussed. The results of this research show that the cultivation of educational character is important and much needed for prospective health workers. For health workers, the formation of this character requires coaching to form a good character to form health workers who have advanced thinking not only capable in science, but also holistically skilled in providing health services.