bluuebunny/crossref_metadata_2025_split huggingface dataset:
Respiratory Severity Score and Oxygen Saturation Index during the first two hours of life as predictors for non-invasive respiratory support failure in moderate preterm infants with respiratory distress syndrome
Authors: Kaluarachchi Dinushan , Zapata Henry , Koueik Jack , Becker Heather , Lasarev Michael , Guthrie Scott 
Published: January 2024

Abstract
Background Noninvasive respiratory support (NRS) failure is common in preterm infants with respiratory distress syndrome (RDS). We evaluated the utility of Respiratory Severity Score (RSS) and Oxygen Saturation Index (OSI) during the first two hours of life (HOL) as a predictor for NRS failure.Methods We conducted a retrospective cohort study of infants born between 28 0/7 to 33 6/7 weeks with RDS. Univariate and multivariable logistic regression analysis were used to assess whether the RSS and OSI summary measures were associated with NRS failure.Results Among 282 infants included in the study 58 (21%) developed NRS failure. RSS and OSI summary measures in the first 2 HOL were associated with NRS failure within 72 HOL.Conclusion RSS and OSI during the first two HOL can predict NRS failure. Optimal RSS and OSI cutoffs for prediction of NRS failure need to be determined in large cohort studies.
Unemployment and health expenditures in China: New evidence on the unemployment insurance and disposable income
Authors: Xu Zhihao , Tan Jialong , Nicholas Stephen , Maitland Elizabeth , Zhong Yue , Han Lu , Wang Jian 
Published: January 2024

Abstract

Background Research consistently demonstrates that unemployment significantly increases individual health expenditures; However, those unemployed people often exhibit caution in utilizing medical services. The study of the relationship between unemployment and health services utilization is limited, especially in developing countries. Therefore, the objective of this research was to analyse and understand how unemployment influenced health services utilization in the context of unequal regional development in China.
Methods Provincial data spanning from 2007 to 2019 were obtained from multiple statistical yearbooks. Both ordinary least squares and fixed effectmodels were employed and adjusted to control for province-specific demographics and socioeconomic factors, ensuring a more accurate estimation. Furthermore, the study delved into the mediating role of unemployment insurance and household disposable income, examining how these factors influence the relationship between the unemployment rate and health expenditures. Rigorous robustness checks were also performed to validate the findings by replacing the explained variable and using instrumental variable method.
Results We found that the increasing unemployment rate had a substantial impact on health expenditures with a significant reduction observed in China's central and western regions but not in the eastern region. This phenomenon was linked to the dynamics of household economics, which means household disposable income experienced a corresponding decline as the unemployment rate increased, then in turn depressed health services utilization. Interestingly, the study also found that unemployment insurance acted as a critical financial buffer to offset the downward trend of health expenditures, indicating the positive externality of social security policy.
Conclusions Our results indicates that unemployed individuals in China exhibit a conservative approach to health services utilization, which is particularly evident in the central and western regions. During unemployment, policies should be implemented to support the low-income unemployed, especially in regions with an inadequate social security net.
Evaluation of integrated classification data for glacier terrain mapping using the Maximum likelihood classifier (MLC) approach: A case study of Kolahoi Glacier in Jammu &amp; Kashmir
Authors: Rawat kishan , Meer Mohammad Suhail , Ali Showkat , Qadir Junaid 
Published: January 2024

Abstract

Efficiently addressing challenges in mapping spectrally similar classes and overcoming limitations imposed by the restricted spectral sensitivity of remote sensing data is crucial for accurate image processing. In this context, the significance of the Maximum Likelihood Classifier (MLC) becomes apparent in optimizing classification accuracy. This study focuses on classifying glacierized terrain surrounding the Kolahoi glacier in the Kashmir Valley, integrating a diverse set of data sources, including Digital Elevation Model (DEM)-derived topographic attributes and transformed spectral data. The integration of ancillary sources, such as slope, aspect, plane, and profile curvatures derived from DEM, along with spectral information extracted from the LISS-III image using Red/SWIR ratio, NIR/SWIR ratio, and Normalized Difference Snow Index (NDSI), is explored to classify nine distinct glacier terrain classes. These classes encompass a range of features, including snow, ice, mixed-ice, debris, supraglacial debris, periglacial debris, water, vegetation, bare land, and shadow.To optimize the classification process, various scenarios are examined by combining each ancillary data source with the four spectral bands. The MLC is employed as the classification algorithm, and the resulting glacier terrain maps are validated against an ASTER image of Area of Interest (AOI). Notably, the study reveals that the glacier terrain map achieving the highest overall accuracy, an impressive 90.75%, emerges when incorporating the Red/SWIR ratio with the spectral data. This outcome underscores the effectiveness of the proposed classification approach in accurately mapping diverse glacier terrain classes.The successful application of the Maximum Likelihood Classifier in this study holds promising implications for applications such as glacier monitoring and environmental assessment in glacierized regions. The optimized classification approach presented here demonstrates its potential to contribute significantly to remote sensing applications, offering a valuable tool for understanding and monitoring complex terrain features in glacierized environments.
Study on production and utilization of a reference material for determination of multi-residue pesticides in tomato matrix
Authors: Tran Thi Thu Trang , Nguyen Linh Trang , Dinh Hoang Anh , Nguyen Thi Thao Nguyen , Le Thi Phuong Thao , Le Thi Hong Hao , Nguyen Thi Anh Huong , Nguyen Thi Minh Hoa 
Published: January 2024

Abstract
Controlling pesticide residues in food has been always a concern globally. It is recommended to use certified reference materials (CRM) or reference materials (RM) in pesticide analysis to validate analytical methods and assess the quality of the measurement results. A comprehensive study on production, storage, transportation, and utilization of an RM of pesticide residues (Difenoconazole, Imidacloprid, Acetamiprid, Indoxacarb, Profenofos, Buprofezin) in tomato was conducted. After comparing two production processes of freezing and freeze-drying, the freeze-drying production process was concluded to be superior. The RM production and characterization process is in accordance with ISO 17034:2016 and ISO guide 35:2017-08. The concentrations of 6 pesticides in the RM are around their Codex maximum residue limits. At a storage temperature of 4°C, freeze-dried RM are predicted to be stable for all six pesticides for at least 548 days, while at a temperature of − 20°C, the shelf life was at least 696 days.
The effect of wearing an N95 face mask on intraocular pressure
Authors: Nilforushan Naveed , Najafzadeh Farhad , Bakhsh Samira Chai , Sharfinejad Masoume 
Published: January 2024

Abstract

Purpose
To evaluate the effect of wearing N95 mask on intraocular pressure
Methods
This cross-sectional study enrolled 34 medical staff volunteer. After baseline eye examinations, all participants were asked to wear an N95 mask for one hour. Then O2 saturation, pulse rate and blood pressure evaluation and sequential IOP measurements with Icare and Goldmann applanation tonometer were performed. Then one hour after removal of the mask all measurements were taken again. Finally, all information was collected for statistical analysis.
Results
A total of 34 participants (68 eyes) were included with mean (±SD) age of 38.97(12.41) years. The mean value of IOP/GAT increased significantly by 1.20 (mmHg) after wearing the mask (12.50 to 13.70, p-value<0.001) and then decreased significantly by 1.27 (mmHg) after removing the mask (13.70 to 12.43, p-value<0.001). The O2 saturation increased significantly from 96.4 with mask to 97.05 after mask removal (p-value<0.001). Although the mean Pulse Rate decreased about 1.5 unit after removing the mask but it was not significant. The mean Blood Pressure decreased after removing the mask but the change was not significant. Also, no significant relationship between IOP change and O2 saturation was found.
Conclusion
The use of N95 face masks could cause a marked increase in IOP and decrease in O2 saturation.
Artificial Intelligence Techniques for Dynamic Security Assessments – A Survey
Authors: Cuevas Miguel , Alvarez-Malebrán Ricardo , Rahmann Claudia , Ortiz Diego , Peña José , Rozas-Valderrama Rodigo 
Published: January 2024

Abstract

The rise of converter interface generation (CIGs) technologies with fast response times has introduced new challenges for the stability of electrical power systems. Traditional dynamic security assessment (DSA) methods of power systems are based on dynamic simulations within a time domain. Because of the high computational efforts and human resources required to carry out these kinds of simulations, they are performed for a limited number of adverse (critical) operational conditions in terms of their stability. However, further incorporation of CIGs in power systems not only results in a shift of the critical operating conditions that may threaten the system’s stability, but also the number of critical conditions increases. Consequently, there is an urgent need to develop new methods for evaluating system stability in a wide range of operating conditions with a reasonable amount of human and computational effort. A complementary 1 strategy to the traditional methods for DSA is to use artificial intelligence (AI) techniques. Unlike traditional methods, AI techniques use a data set that captures the non-linear relationships between the system’s operational conditions and their stability, without needing to solve the algebraic-differential equations modeling the power system. Once these relationships are established, the system’s stability can be evaluated for other operational conditions much faster (within the order of the hundreds of milliseconds) and accurately. This, in turn, allows for the consideration of an extended range of operational conditions for DSA studies. This article surveys the state of the art regarding the use of AI techniques for DSA in electrical power systems. Focus is made on algorithms, the kind of stability being addressed, data processing and applications. Finally, limitations, challenges, and future trends are discussed.
Efficiency of pneumatic conveying system improve with the help of heat recycling in Graphite manufacturing industry
Authors: Yadav Ranjana , Sharma Ashok Kumar , Sharma Sarita 
Published: January 2024

Abstract

In the pneumatic conveying system the graphite powder conveyed from furnace to silos with the help of compressed air but presence of moisture in this air creates lumps formation in mild steel pipe result choking and system under breakdown. In this paper a practical modification has been done in graphite manufacturing industry to improve the system efficiency of compressor unit by recycling heat with an additional heat exchanger and improve cost control of pneumatic conveying system. This study investigates that potential of heat recycling to enhance the efficiency of pneumatic conveying systems in the graphite manufacturing industry. Coefficient of performance improves (COP) up to 75.2% ,with reduction in down time 75%,increasing availability of pneumatic conveying 23.7% and reduces in cost of steel pipe material up to 66.67% & labour cost 90%. Effectiveness of heat exchanger and heat transfer rate found 63.51% and 16.907 KW respectively.
Integration of Routine Immunization and COVID-19 Vaccination in Ekiti State Primary Health Care Facilities: A Qualitative Assessment of the Enablers and Barriers
Authors: Jimoh Akolade Uthman , Filani Oyebanji , Awobeku Dapo , Isiaka Saheed Dipo , Dauda Mahfus , Adeshina Esther Opeyemi , Samuel Olugbemisola Wuraola , Ayodeji Oluwafisayo Azeez , Adenipekun Segun , Okoh Chukwudinma , Adediran Kehinde , Atobatele Sunday , Sampson Sidney , Tinuoye Tobiloba , Seluwa Ayodele , Ojo Nicholas , Omoya Sunday 
Published: January 2024

Abstract

Background
The development of the COVID-19 vaccine influenced the discussion on the importance of exploring the interaction between COVID-19 vaccination and routine immunization. Subsequently, the WHO Strategic Advisory Group Experts (SAGE) on immunization plausibly advised countries to leverage the COVID-19 vaccination rollout as a transformative opportunity to establish a resilient immunization system, through the integration of routine immunization, resulting in strengthened primary healthcare services.
Objective
This study assesses the enablers and barriers to integrating COVID-19 vaccination and routine immunization in Ekiti state, Nigeria.
Methods
This study adopted a qualitative research approach to obtain information from 40 participants selected purposively across the primary healthcare facilities, LGA, and state levels. A three-tier approach was used in selecting the LGAs. At the same time, In-depth interviews were conducted to elicit relevant information on the assessment of enablers and barriers to integrating COVID-19 vaccination and routine immunization through an interview guide. All audio interview files were transcribed in the English language, coded, and presented using a thematic approach (inductive and deductive approaches)
Results
A total of 40 healthcare workers across Ekiti state were selected to participate in this study. Our study found the enablers of integrating COVID-19 into routine immunization to include demand generation and social mobilization, health education, health workers training, data validation, financing, and supervision. However, rumors, demand for palliatives, Adverse Events Following Immunization (AEFI), manpower shortage, poor network services, and bad road networks were reported as barriers to integrating COVID-19 vaccination and routine immunization in Ekiti state.
Conclusion
While the enablers of integrating COVID-19 and routine immunization may outweigh its barriers, it is pertinent to know that the efforts towards integrating COVID–19 vaccination on RI is a call to all stakeholders. The identified barriers in the study must be addressed to ensure a strengthened health system. Therefore, achieving a successful integration and uptake of vaccination/immunization is anchored on driving demand generation, social mobilization, health education, availability of healthcare workers, integrated supervision, and financing.
Machine Learning Model Based Prediction of Risk Factors for Hypertension in Elderly HIV/AIDS Patients Using Electronic Medical Records
Authors: An Mingyang , Wang Chunjie , Pan Wei , Wang Xiao , Cai Qiong , Zhao Qian , Yi Li , Sun Yan , Zhang Chunming , Zhang Xianhui , Pan Xilong 
Published: January 2024

Abstract
Objective: This study used electronic medical record information and machine learning methods to develop a model predicting the risk of hypertension in HIV/AIDS patients.
Method: This study focused on HIV/AIDS patients admitted to the Henan Infectious Disease Hospital in China from September 2017 to October 2022. The researchers extracted 84 clinical features from electronic medical records. Feature selection was performed using mutual information, Recursive Feature Elimination, Lasso regression, and Principal Component Analysis. Five machine learning prediction models (eXtreme Gradient Boosting [XGBoost], Logistic Regression, Support Vector Machine [SVM], Back Propagation Neural Network [BPNN], and Decision Tree [DT]) were trained using these selected features. These models were tested using 20% of the data. Model performance was assessed using metrics including the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, precision, and F1 score. The optimal predictive model interpreted the feature values using Shapley Additive Explanations (SHAP).
Result: After evaluating five machine learning models, the XGBoost prediction model demonstrated superior predictive capability. According to the SHAP interpretation of this model, CD4/CD3 (percentage of CD4 cells to CD3 cells), NE (Neutrophil Count), CRP (C-Reactive Protein), GLU (Glucose), PLT (Platelets), LDD-c (Low-Density Lipoprotein Cholesterol), ApoA1 (Apolipoprotein A1), TC (Total Cholesterol) were identified as the most crucial predictive features. Additionally, MCHC (Mean Corpuscular Hemoglobin Concentration), UCB (Unconjugated Bilirubin), TP (Total Protein), CK-MB (Creatine Kinase-MB), GT (Gamma-Glutamyl Transferase), PCV (Packed Cell Volume) have a significant impact on the occurrence of hypertension in HIV/AIDS patients.
Conclusion: The predictive model is significant for the rational management and formulation of personalized treatment plans for hospitalized HIV/AIDS patients.
Multidirectional myocardial function in bicuspid aortic valve stenosis patients: a three-dimensional speckle tracking analysis
Authors: Deng Wenhui , Li Yuman , Zhang Li , Yang Yali , Lv Qing , Tan Yuting , He Shukun , Zhang Yichan , Xie Mingxing , Wang Jing 
Published: January 2024

Abstract
Purpose
The effects of aortic stenosis (AS) progression on multidirectional myocardial function in BAV patients has still not elucidated, although early left ventricular longitudinal myocardial dysfunction is known to be presented in BAV patients with normal function. The aim of the study was to evaluate the multidirectional myocardial functions of BAV patients.
Methods
A total of 86 BAV patients (age 46.71 ± 13.62 years, 69.4% men) with normally functioning (BAV-nf), mild AS, moderate AS, and severe AS with preserved left ventricular ejection fraction (LVEF ≥ 50%) were included. 30 healthy volunteers were recruited as the control group. Multidirectional strain and volume analysis were performed by three-dimensional speckle tracking echocardiography(3D-STE).
Results
Global longitudinal strain (GLS), and global radial strain (GRS) were reduced in BAV-nf patients compared with the controls. With each categorical the increase of AS severity from BAV-nf to severe AS, there was an associated progressive impairment of GLS and GRS (all P < 0.001). The global circumferential strain (GCS) did not change significantly from BAV-nf to mild AS but was starting damaged from moderate AS. Multiple linear regressions indicated that indexed aortic valve area (AVA/BSA), as a measure of AS severity, was an independent determinant of GLS, GCS and GRS.
Conclusions
Left ventricular myocardial damage occurs earlier in BAV patients. With each categorical increase in the grade of AS severity from normally functioning to severe aortic stenosis, there was an associated progressive impairment of longitudinal myocardial. Furthermore, circumferential myocardial function was starting damaged from moderate AS. AVA/BSA was independently associated with multidirectional myocardial function injuries.
Comprehensive Analysis of PSME2 and Its Significant Role in Non- small cell lung cancer
Authors: Ma Xuemei , Jiang XiaoLi , Han Yu , Zhou Binjian , Song Mengxue , Wu Qingtian , Hou Xia 
Published: January 2024

Abstract
Non-small cell lung cancer (NSCLC) is the most common subtype of lung cancer, but its mechanisms of occurrence and development remain incompletely understood. The proteasome activator complex subunit 2 (PSME2) is a member of the family of protease-activating subgenes and is strongly associated with the emergence of several cancer types. However, the role of PSME2 in NSCLC is unclear. In this study, we investigated the clinical significance and prognostic value of PSME2 expression in NSCLC progression. We utilized data from The Cancer Genome Atlas (TCGA) database for bioinformatic analyses. We carried out experimental validation at both the tissue and cellular levels. Gene set enrichment analysis (GSEA) and various databases, such as Kaplan-Meier Plotter (KM), STRING, Tumor Immune Estimation Resource (TIMER), TIMER2.0, were used to investigate the role of PSME2 in NSCLC. Statistical analysis was performed using R (v.4.3.1). Our findings revealed the predictive significance of PSME2 in NSCLC patients. PSME2 is highly expressed in pathological tissues and cell lines of NSCLC patients. PSME2 expression was associated with patient's age, sex, tumor stage, lymph node stage, pathological stage. GSEA analysis identified associations between PSME2 and extracellular matrix organization, as well as immune-related pathways. Immunological analysis revealed a positive correlation between the level of immune cell permeation, the activation of anti-tumor immune cycle stages, and the level of PSME2 expression. Identifying PSME2 as a novel biomarker for NSCLC could shed light on the promotion of NSCLC development by the immune environment.
Neural patterning of P19 cells derived embryoid bodies: an analogic perspective
Authors: Sadaghiani Sahar , Sardar Reza , Hassanzadeh Sajad , Namjoo Zeinab 
Published: January 2024

Abstract

Research conducted on neuron differentiation from different cells is very limited. This research examined the patterning of differentiated neural cells in embryoid bodies (EBs) of two groups, hanging drop cells and aggregate cells obtained from P19 cells. P19 cells are a type of mouse embryonic carcinoma cells that can irreversibly differentiate into nerve cells by retinoic acid. P19 cell line was cultured in Minimum Essential Medium Alpha Medium in two hanging drop and aggregation methods. After 4 days, the EBs obtained from both methods were suspended into control and 1μM RA groups. A Real-Time PCR method and an inverted microscope were applied to evaluate neurons 8 days after induction. Using both hanging drop and aggregation methods, long and branched processes emerged from different parts of the cells by the end of the eighth day. Evaluation and comparison of the expression level of neural differentiation markers, including Nes, TUB βIII, and Map2, showed no significant difference between the two groups. However, aggregation group neurons exhibited higher levels of Nes mRNA. Neuronal identity markers, which represent the identity of the resulting neurons in EBs, revealed no significant difference between hanging drop and aggregation groups. The two above-mentioned methods can result in significant and similar differentiation of EBs into motor neuron-like neurons with spatial identity along the rostro-caudal axis under RA induction. This can be considered as a basis for nerve cell differentiation and transplantation in vitro and in vivo.