bluuebunny/crossref_metadata_2025_split huggingface dataset:
Brief, Real-Time Reflections: An Efficient, Contextual, and Familiar Variation of Narrative Medicine: A Mixed Methods Analysis
Authors: Hilgeman Brian , Kurtz Kevin , Hoeschen Mary , Hovis Zachary , Harrison Rachele , Minshew Lana 
Published: April 2024

Abstract

Background: Narrative medicine is a widely used pedagogic tool but can be detached from the clinic context and unfamiliar to students. Brief real-time reflections could be a method of narrative medicine that is contextual, familiar, and convenient.
Methods: Fourth year medical students completed 280-character reflections immediately after patient interactions while rotating in a primary care clinic serving complex patients. Three researchers used qualitative methods to develop a codebook to describe the reflections and an independent auditor verified codebook application. Student feedback regarding their experience writing reflections was elicited on a Likert scale to understand student perspectives on the tool about ease of use, empathy, and remembering patient interactions.
Results: Eighteen students completed 131 reflections during 64 clinics; an average of 2.04 reflections per clinic and spent an average of 4.39 minutes on each reflection. Three codes were elicited to describe the content of reflections: descriptive, emotional, and cognitive. The most frequently identified code was cognitive (n = 84, 41%), with descriptive (n = 69, 33%) and emotional (n = 53, 26%) being less frequent. Reflections could contain one or a combination of codes. The most common reflection was cognitive-only (n = 43, 33%) followed by a combination of descriptive and emotional (n=24; 18%). Most students agreed or strongly agreed that reflections helped them think more deeply about (9/9, 100%) and remember (8/9, 89%) patient interactions and were a good use of their time (7/9, 78%).
Conclusions: Brief, real-time reflections are a tool that allow medical students to reflect upon their clinical experiences in a complex and cognitive way and was well-received by students.
Proteomics analysis of extracellular vesicles for biomarkers of autism spectrum disorder
Authors: Moussa Houda Yasmine Ali , Shin Kyung Chul , Fuente Alberto de la , Bensmail Ilham , Abdesselem Houari B. , Ponraj Janarthanan , Mansour Said , Al-Shaban Fouad A. , Stanton Lawrence W , Abdulla Sara A. , Park Yongsoo 
Published: April 2024

Abstract
Background Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by symptoms that include social interaction deficits, language difficulties and restricted, repetitive behavior. Early intervention through medication and behavioral therapy can eliminate some ASD-related symptoms and significantly improve the life-quality of the affected individuals. Currently, the diagnosis of ASD is highly limited.
Methods To investigate the feasibility of early diagnosis of ASD, we tested extracellular vesicles (EVs) proteins obtained from ASD cases. First, plasma EVs were isolated from healthy controls (HCs) and ASD individuals and were analyzed using proximity extension assay (PEA) technology to quantify 1196 protein expression level. Second, machine learning analysis and bioinformatic approaches were applied to explore how a combination of EV proteins could serve as biomarkers for ASD diagnosis.
Results No significant differences in the EV morphology and EV size distribution between HCs and ASD were observed, but the EV number was slightly lower in ASD plasma. We identified the top five downregulated proteins in plasma EVs isolated from ASD individuals: WW domain-containing protein 2 (WWP2), Heat shock protein 27 (HSP27), C-type lectin domain family 1 member B (CLEC1B), Cluster of differentiation 40 (CD40), and folate receptor alpha (FRalpha). Machine learning analysis and correlation analysis support the idea that these five EV proteins can be potential biomarkers for ASD.
Conclusion We identified the top five downregulated proteins in ASD EVs and examined that a combination of EV proteins could serve as biomarkers for ASD diagnosis.
Porous Material Synthesis and Chromium (VI) Applications
Authors: Demiral Ilknur , Samdan Canan , CIN Hatice Hürrem 
Published: April 2024

Abstract

Using chemical activation, carbonaceous porous material was produced from sunflower shells (SS). The study includes the effects of variation in the amount of chemical activation agent and carbonization temperature on various properties of carbonaceous porous materials. To thoroughly examine the carbonaceous porous materials that were produced, a range of analytical techniques were employed. The aim was to gain a comprehensive understanding of the materials' properties and to identify any potential applications for these carbonaceous porous materials. The carbonaceous porous material, produced with a 4:1 impregnation ratio and carbonized at 500 °C, had the highest surface area and pore volume. The specific surface area of this material was measured to be 1501 m2/g, and the pore volume of this material was found to be 0.842 cm3/g, indicating that it has a high capacity for adsorption and storage of gases and liquids. These properties make this carbonaceous porous material an ideal candidate for various applications, such as catalysis, gas storage, and water purification. After the carbonaceous porous materials were synthesized, experiments were conducted to evaluate their ability to remove Cr (VI) from aqueous solutions. After analyzing the results, it was concluded that the Langmuir isotherm provided a better fit than the other two isotherms. Furthermore, the kinetic analysis of the adsorption process indicated that it followed pseudo-second-order kinetics. In conclusion, the study demonstrated that carbonaceous porous material derived from SS has a high adsorption capacity and can effectively remove toxic substances such as Cr (VI).
Weight Analysis of Target Properties in Developing Aviation Comprehensive Surrogate Fuel
Authors: Huo Weiye , Zhao Mengmeng 
Published: April 2024

Abstract
In the development of comprehensive surrogate fuel that can simulate the pollution emissions of actual fuels, the weights of the target properties should be determined according to the importance that affects the pollution emissions from spray combustion. Based on the unique advantages of single-component fuel whose basic physical and chemical properties and chemical reaction mechanism can be accurately obtained, the pollution emissions of several single-component fuels, including NOx, CO, and UHC, were measured in the aero-engine combustor. The power-law relationships between fuel atomization particle size, vapor pressure, pollutant generation of gaseous fuel combustion, and the pollution emissions from spray combustion are analyzed based on the response surface methodology. The results show that for CO and NOx emissions from spray combustion, the importance of atomization particle size, vapor pressure, and pollutant generation of gaseous fuel combustion increases in turn. For UHC emissions, the importance of vapor pressure is significantly higher than that of atomization particle size, while pollutant generation of gaseous fuel combustion has little effect on UHC emissions. The weight ratios of target properties are determined by the coefficients of the coded factors of the power-law models.
Historic ocean seasonality and global fisheries
Authors: Hume Andrew , Ratledge Nathan , Wabnitz Colette C.C. , Palomares Maria L.D , Dunbar Robert 
Published: April 2024

Abstract
Rising ocean temperatures threaten marine ecosystems and food security worldwide. Yet, our current understanding of how climate change affects global marine fisheries often overlooks critical seasonal dynamics that govern ecosystem function. To address this gap, we compiled a global dataset for 187 countries between 1950 to 2018 and employed fixed effects regression to assess the effect of intra-annual sea surface temperature (SST) variation on annual marine fisheries catches. We detect a significant non-linear response with varied effects across the globe. Increases over 1°C in intra-annual SST variation estimated a 12% increase in catches for low and high latitude aseasonal countries, and a 30% decrease in catches in highly seasonal mid-latitude countries. Our analyses underscore the need to integrate ocean seasonality in efforts to better understand, mitigate and adapt to the impacts of climate change on marine fisheries, to support sustainable fisheries management as well as maintain global ocean health.
Near Real-Time Forecasting of Temperature Using Machine Learning Algorithms
Authors: Ramagalla Om Abhinav , V Subrahmanyam Kandula , G Srinivasa Rao 
Published: April 2024

Abstract
Accurate predictions are vital for various applications, such as weather, climate, energy supply, transportation, and agriculture. The estimates of air temperature have been considered a crucial parameter in climate impact, and its prediction is challenging due to random changes and the non-linear relationship with other meteorological parameters such as wind speed, humidity, pressure, and soil moisture. Traditionally, Numerical Weather Prediction models serve the purpose of weather predictions, but they have their constraints and limitations. In recent years, the use of artificial intelligence (AI) technology has grown leaps and bounds in understating data-driven Earth systems. The present study employed two machine learning algorithms, namely extreme gradient boosting (XGBoost) and k-nearest neighbour (KNN), to predict the half-hourly temperature over Shadnagar (Latitude: 17.0713° N, Longitude: 78.2059° E), a semi-urban location in India. We utilized half-hourly meteorological parameters for training and testing data from January 1, 2016, to December 31, 2019. After the successful training of both models, predictions were made by taking the previous 72 hours of meteorological parameters for the prediction of 72 hours of temperature. The XGBoost and KNN models were evaluated using mean square error (MAE) and root mean square error (RMSE). The results showed that both models had similar MSE and RMSE values of around 2 and 1.4, respectively. The correlation coefficients for both models were high, approximately 0.95. Overall, both models performed well in predicting temperature values, with the KNN model exhibiting better accuracy after 24 hours. The results of the study can be helpful for developing more accurate temperature prediction models for near-real-time forecasting. Further, we have developed a Synergetic Machine learning Algorithms for near Real-time forecasting of Temperature (SMART), a GUI based application for near-real time temperature forecasting and provided the multi-model mean temperature predictions.
Predictors of Septic Shock Mortality at a Tertiary Hospital in Ethiopia: A Prospective Observational Study
Authors: Zeleke Amanuel , Sitotaw Alazar , Arega Balew , Tewabe Elias , Solela Gashaw , Teshome Haileyesus , Hailemichael Hanna , Legese Seble , Ahmed Sebrina , Bogale Selam , Hailemichael Simret , Mitiku Anteneh , Endazenaw Getabalew , Tsegaye Eyuel , Eshetu Anteneh 
Published: April 2024

Abstract

Background: Septic shock causes significant mortality, ranging from 30% to 50%, with a slight difference in developing and developed countries. There is insufficient evidence in Ethiopia regarding septic shock mortality. Therefore, we aimed to determine the in-hospital mortality rate and its predictors among septic shock patients admitted to a tertiary hospital in Ethiopia.
Methods: A hospital-based prospective observational study was conducted among septic shock patients admitted to Yekatit 12 Hospital Medical College (Y12HMC) from January to September 2023. All patients with septic shock who fulfilled the inclusion criteria were included and followed until discharge or death. We collected sociodemographic characteristics, clinical and laboratory parameters, microbiologic findings, and treatment-related data from eligible patients using a standardized data extraction format. Data entry and analysis were done using Statistical Package for Social Sciences (SPSS) version 25. The multivariable analysis using the Cox regression model was used to determine the predictors of in-hospital mortality, with P < 0.05 representing statistical significance.
Results: A total of 144 septic shock patients were included in the study. The mean age was 46 ± 19 years, with a range of 15 to 95 years. The overall in-hospital mortality of septic shock patients was 66.7%. The multivariable Cox regression analysis revealed that low Glasgow coma scale (GCS) [adjusted hazard ratio: 2.23, 95% CI: 1.35-3.69, P = 0.01] and low peripheral oxygen saturation (SpO2) [adjusted hazard ratio: 8.74, 95% CI: 1.18-14.84, P = 0.03] at diagnosis were independently associated with a higher risk of in-hospital mortality.
Conclusion: Septic shock mortality was found significantly higher in our study. Septic shock patients with low GCS and SpO2 at the time of diagnosis require a vigilant care. Early identification of high-risk patients, applying appropriate and compressive management could reduce the mortality.
Childcare Deserts Impede Scientists’ Career Development and Undermine Gender Equity
Authors: Li Jun 
Published: April 2024

Abstract

For decades, the United States grappled with a childcare crisis that left American families struggling to secure quality childcare, compromising both children's development and parental career progress. Here we investigate the impact of childcare availability---and the lack thereof---on US scientists' career advancement and gender equity in science. We construct a longitudinal database of childcare facilities and their capacities spanning the last twenty years. Leveraging the biennial survey of US scientists and engineers sponsored by the National Science Foundation (NSF) and the National Institutes of Health (NIH), we uncover that over half of US scientists and engineers employed at universities and research institutions work in childcare deserts, that is, areas where the supply of childcare falls significantly short of demand. Despite equivalent exposure to these deserts, the career consequences for male and female scientists are starkly different. Childcare deserts disproportionally reduce women scientists’ likelihood of achieving tenure by 6.8 percentage points, with no noticeable impact on men’s tenure attainment. The lack of childcare explains almost the entire gender tenure gap among scientists with children. Furthermore, this impact is largest in engineering (-19.0 percentage points), followed by that in science and health (-8.2 and -4.9 percentage points, respectively). Our findings highlight the critical role of expanding childcare availability in maintaining research and innovation workforce’s productivity and in reducing the gender gap in science.
Enhanced Electrochemical Activity of NiAl Cathode for Hydrogen Production
Authors: Latreche Sofiane , Boutarek-Zaourar Naïma , Bencherifa Ismail , Messaoud Faouzi , Mossang Eric , Mansour Samir , Trari Mohamed 
Published: April 2024

Abstract

This work is devoted to the elaboration of Ni68%Al32% wt. (NiAl) intermetallic compound highly electro-active and cost-effective electrode materials using an induction furnace utilized as cathodes in alkaline water reduction into hydrogen. The XRD analysis showed the formation of the NiAl phase with an average crystallite size of 44.13 nm. The SEM/EDS results confirm the XRD results with an average grain size of 50 µm. The chemical activation of Aluminum from NiAl was carried out on NaOH (25%) solution at 353 K for 72 h. The Optical Profilometry and UV-visible spectrophotometry confirmed the formation of Ni-Raney-type electrodes with high specific surface area. The activated NiAl electrodes resulted in remarkable efficiency for the hydrogen evolution reaction (HER), 13 times higher than the non-activated electrode. The comparison with literature data reveals that the efficiency of the NiAl cathode has increased by 120% compared to pure Ni.
Diet Adjustment Before Colonoscopy Can Improve the Quality of Bowel Preparation in Patients with Schizophrenia
Authors: Li Yuan-Rung , Chang Wei-En , Huang Ying-Che , Wang Chih-Feng , Tsay Feng-Woei 
Published: April 2024

Abstract

Background: Quality of bowel preparation is crucial in colonoscopy. However, patients with schizophrenia are prescribed antipsychotic medicines, which may influence the effect of bowel preparation for colonoscopy. Poor quality of bowel preparation can reduce the benefit of colonoscopy, and increase the risk of overlooking possible colorectal cancers.
Aim: This study aimed to employ diet adjustment before colonoscopy to improve the quality of bowel preparation.
Method: Since January 2022, patients with schizophrenia at our institute requiring colonoscopy examination were divided into a standard group and a diet-modified groups. The standard group was initiated with a low-residue diet two days before and a clean liquid diet the day before the colonoscopy examination. The diet-modified group was initiated with a low-residue diet four days before and a clean liquid diet two days before the colonoscopy examination. Both groups were administered bowel cleansing medicines the day before and the morning of the examination. We used the Aronchick bowel preparation scale to evaluate the quality of bowel preparation.
Result: From January 2022 to September 30, 2022, the quality of bowel preparation was poor in 25/325 (7.69%) non-schizophrenic patients and 32/135 (23.70%) patients with schizophrenia (p < 0.001). The quality of bowel preparation was poor in 20/59 (33.90%) and 12/76 (15.79%) patients of the standard and the diet-modified groups, respectively (p = 0.014).
Conclusions: Diet adjustment before colonoscopy can be used to improve the quality of bowel preparation in patients with schizophrenia.
Exploring the Relationship Between Dietary Intake and Clinical Outcomes in Peritoneal Dialysis Patients
Authors: Ma Liantao , Wu Yueying , Gao Junyi , Tang Wen , Su Chunyan , Zhu Yinghao , Wang Tianlong , Liao Weibin , Chu Xu , Harrison Ewen , Wang Yasha 
Published: April 2024

Abstract

This study investigates the relationship between dietary intake and mortality risk among patients with End-Stage Renal Disease (ESRD), a population for whom nutritional management is crucial yet challenging due to the disease's complexity and the limitations of existing dietary guidelines. Recognizing the gaps in current research, particularly the lack of detailed evidence-based recommendations for micronutrient intake and a focus predominantly on the early stages of chronic kidney disease, our work seeks to provide evidence-based dietary guidance tailored to the needs of ESRD patients. Through the collection of long-term, longitudinal, and fine-grained dietary records linked with extensive electronic health records (EHR) data over a 12-year period, we have constructed a dataset that offers a detailed view of dietary nutrient intake across 26 types of nutrients. Utilizing a two-stage model, we have analyzed the association between dietary intake and mortality risk. Our model provides comprehensive dietary recommendations for 26 nutrients, with 13 out of these nutrients showing a significant correlation with mortality risk while currently lacking specific guidelines for ESRD patients. This research not only challenges and refines the current dietary recommendations but also highlights the importance of considering non-linear relationships between nutrient intake and health outcomes. By offering a comprehensive perspective on dietary management for ESRD patients, this study contributes to the optimization of nutritional care strategies, aiming to improve patient prognosis and quality of life.
Pressure Vessel Mass Estimation for High Altitude PEM Unmanned Aircraft System
Authors: Albayati Ibrahim M. , Ali Rashid , Al-Bayati Abdulrahman Muataz 
Published: April 2024

Abstract

The power to weight ratio of the power plant is an important consideration, especially in design of Unmanned Aircraft System (UAS). In this paper, a UAS with an MTOW of 35.3 kg, equipped with a fuel cell as a prime power supply to provide electrical power to the propulsion system is being considered. A pressure vessel design is proposed that can estimate and determine the total size and weight of the combined power-plant of a fuel cell stack with hydrogen and air/oxygen vessels and the propulsion system of the UAS for high altitude operation. Two scenarios are adopted in determining the size and weight of pressure vessels required to supply oxygen to the fuel cell stack. Different types of stainless-steel materials are used in the design of the pressure vessel in order to find an appropriate material that provides low size and weight advantages. Also, hydrogen pressure vessel design and mass estimation are also considered. The estimated sizes and weights of hydrogen and oxygen vessels of the power-plant and propulsion system in this research offers a maximum of four hours of flying time for the UAS mission; this is based on a Horizon (H-1000) PEM stack.
Insect herbivory on Acer rubrum varies across income and urbanization gradients in the D.C. metropolitan area
Authors: Blake Elizabeth , Bennett Shelley , Hruska Amy , Komatsu Kimberly J 
Published: April 2024

Abstract

Urbanization has increased wealth disparity within the United States, impacting the urban landscape and species interactions. In particular, the interactions between street trees and the arthropod communities that live among them may be modified by both human population densities across urban to suburban locations, as well as income levels within these areas. We examined the effect of land use type (urban vs suburban) and median household income on variation in leaf damage and arthropod abundance of red maples (Acer rubrum) in the District of Columbia metropolitan region. We compared these levels of leaf damage to rates observed in a nearby natural forest. We predicted leaf damage would be positively correlated with urbanization (forested < suburban < urban) and a negative relationship between leaf damage and neighborhood income level (low > medium > high). Instead, we observed higher levels of leaf damage on trees in the forest environment compared to the urban and suburban areas. Leaves from urban medium and high-income areas were less likely to exhibit herbivore damage than those from suburban areas. Of the leaves with any damage, those in urban high-income and suburban low-income areas exhibited the most leaf area missing. These trends may be related to specific factors associated with urbanization and income level, such as tree and impervious surface coverage and pesticide use. This study highlights differences in biotic interactions across individual neighborhoods and the importance of including socio-economic variables (e.g., household income) when examining species interactions in developed environments.