bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of machine learning to predict hospital visits for respiratory diseases using meteorological and air pollution factors in Linyi, China
Authors: Yang Jing , xu xin , Ma Xiaotian , Wang Zhaotong , You Qian , Shan Wanyue , Yang Ying , Bo Xin , Yin Chuansheng 
Published: March 2023

Abstract
Urbanization and industrial development have resulted in increased air pollution, which is concerning for public health. This study evaluated the effect of meteorological factors and air pollution on hospital visits for respiratory diseases (pneumonia, acute upper respiratory infections, and chronic lower respiratory diseases). The test dataset comprised meteorological parameters, air pollutant concentrations, and outpatient hospital visits for respiratory diseases in Linyi, China from January 1, 2016 to August 20, 2022. We used support vector regression (SVR) to build regression models to analyze the effect of meteorological factors and air pollutants on the number of outpatient visits for respiratory diseases. To evaluate the model performance, 70% of the dataset was used for training and 30% was used for testing. The Spearman correlation and SVR model results indicated that NO2, PM2.5, and PM10 were correlated with the occurrence of respiratory diseases, and the strongest correlation was for pneumonia. An increase in the daily average temperature and daily relative humidity decreased the number of patients with pneumonia and chronic lower respiratory diseases but increased the number of patients with acute upper respiratory infections. The SVR modeling showed potential for predicting the number of respiratory-related hospital visits. This work demonstrated that combining machine learning with meteorological and air pollution data can be used for disease prediction and can serve as a useful tool for policymakers to take preventive measures.
Synthesis and Performance of a Cathode Catalyst Derived from Bauhinia Accuminata Seed Pods in Single and Stacked Mfc
Authors: Ajit Karnapa , John Juliana , Krishnan Haribabu 
Published: March 2023

Abstract
It becomes important to simultaneously focus on the development of cost-effective electrode materials and catalysts as well as evaluating their performance on stacked systems in order to create scalable bio electrochemical systems for waste water treatment. Platinum group metal free biomass derived cathode catalysts have been observed to improve the microbial fuel cell performance in recent years. But their performance in scalable systems using Natural clay membrane – SS mesh electrode MEA needs to be evaluated for applying to real time systems. In the current work, a catalyst with intrinsic Fe-N-C coordination could be synthesised from the seedpods of biomass Bauhinia Accuminata. The elemental analysis and XPS results confirmed the intrinsic doping of heteroatoms N and P in the catalyst with atomic weight percentages of 4.5 and 3.5, respectively. The deconvolution of N1 and Fe2p spectra confirmed Fe-N-C coordination in the catalyst with pyridinic N and graphitic N content of 17.3% and 34.1%, favouring the ORR activity. The catalyst when coated on SS mesh and used in an MFC system with natural clay membrane - modified SS mesh electrode MEA, the maximum power density was 0.91 W/m3 compared to 0.02 W/m3 in plain SS electrode cell with COD removal efficiency of 93.3%. The study also demonstrated the stepping up of voltage, current and power achieved while stacking such single MFCs in series, parallel, parallel - series and fluidically connected configurations. Parallelly connected system outperformed other systems with a maximum power density of 1.54 W/m3 despite a high OCV of 4.15V attained in series connection. It was also notable that the fluidically connected parallel system achieved better power and current density (0.84W/m3 and 1.97A/m3) than the mixed parallel series circuitry (0.7W/m3 and 0.57A/m3).
Evaluation of SARS-CoV-2 isolation in cell culture from nasal/nasopharyngeal swabs or saliva specimens of patients with COVID-19
Authors: Yazawa Shunsuke , Yamazaki Emiko , Saga Yumiko , Itamochi Masae , Inasaki Noriko , Shimada Takahisa , Oishi Kazunori , Tani Hideki 
Published: March 2023

Abstract
It has been revealed that SARS-CoV-2 can be efficiently isolated from clinical specimens such as nasal/nasopharyngeal swabs or saliva in cultured cells. In this study, we examined the efficiency of viral isolation including SARS-CoV-2 mutant strains between nasal/nasopharyngeal swab or saliva specimens. Furthermore, we also examined the comparison of viral isolation rates by sample species using simulated specimens for COVID-19. As a result, it was found that the isolation efficiency of SARS-CoV-2 in the saliva specimens was significantly lower than that in the nasal/nasopharyngeal swab specimens. In order to determine which component of saliva is responsible for the lower isolation rate of saliva specimens, we tested the abilities of lactoferrin, amylase, cathelicidin, and mucin, which are considered to be abundant in saliva, to inhibit the infection of SARS-CoV-2 pseudotyped viruses (SARS-CoV-2pv). Lactoferrin and amylase were found to inhibit SARS-CoV-2pv infection. In conclusion, even if the same number of viral genome copies was detected by the real-time RT-PCR test, infection of SARS-CoV-2 present in saliva is thought to be inhibited by inhibitory factors such as lactoferrin and amylase, compared to nasal/nasopharyngeal swab specimens.
Conservative management of double teeth in molar teeth with periapical periodontitis: A report of five cases and literature review
Authors: Chen Mengxi , Bai Xinna , Wang Xiangzhu , Xie Xiaoli , Chen Minmin 
Published: March 2023

Abstract
Background: Double teeth are usually the result of an abnormality in the developing tooth germ. Double teeth can occur in either the primary or permanent dentition, with the majority of cases concerning permanent teeth reported in the anterior teeth and less frequently in the molar teeth.
Case presentation: This report illustrates five cases of double teeth in molars with periapical periodontitis, including one case of geminated teeth and four cases of fused teeth. Radiographic findings revealed the presence of extra teeth on the buccal aspect of the molar in five cases, with or without communication between the two root canal systems. Root canal treatment was performed by using CBCT and a dental operating microscope. The treatment outcome was good in all five cases.
Conclusion: The diagnosis and treatment of double teeth requires special attention. The root canal system should be carefully explored to obtain a full understanding of the anatomy, allowing it to be fully cleaned and obturated. Proper anatomical structure analysis prior to treatment facilitates the development of an appropriate treatment plan, thereby increasing the likelihood of successful treatment both aesthetically and functionally.
Use of Routinely Collected Blood Donation Data for Expanded Hiv and Syphilis Surveillance in Blantyre District, Malawi
Authors: Singogo Emmanuel , Hartney Thomas , Bourdin Sarah , Chagomerana Maganizo , Kudowa Evaristar , Puerto-Meredith Sydney , M’baya Bridon , Kadewere Godfrey , Platt Lucy , Rice Brian , Hargreaves James R , Weir Sharon , Hosseinipour Mina C 
Published: March 2023

Abstract
Background
Although WHO recommends that all blood donations be screened for transfusion transmissible infections, these data are currently not incorporated into national surveillance. We set out to use routinely collected data from blood donors in Blantyre district, Malawi to explore HIV and syphilis prevalence and identify seroconversions among repeat donors.
Methods
We conducted a retrospective cohort analysis of blood donation data collected by the Malawi Blood Transfusion Service (MBTS) from October, 2015 to May, 2021. All blood donations were routinely screened for HIV and syphilis. We characterized donor demographics as well as screening outcomes, including identifying seroconversions among repeat donors who previously tested negative on their last donation. Log binomial regression was used to model the impact of individual level covariates on HIV and syphilis prevalence and risk of seroconversion.
Results
A total of 23,280 donations from 5,051 donors were recorded, with a median frequency of donations of 3 (IQR:2–6). At the time of their first donation, most donors were male (4,294; 85%) and students (3262; 64.6%). Of those screened for HIV and syphilis at first donation, 1.0%, (52/5,051) and 1.6% (80/5,051) tested positive, respectively. Among repeat donors who previously tested negative, 52 HIV seroconversions and 126 syphilis seroconversions were identified, indicating an incidence rate per 1,000 person-years of 5.9 (95% CI: 4.7, 7.4) and 13.3 (95% CI:11.4, 15.4) respectively. Prevalence of HIV (Prevalence ratio (PR) = 0.31: 95% CI: 0.15, 0.65) and syphilis (PR = 0.54: 95% CI:0.30, 0.94) were lower and risk of syphilis seroconversion (Risk ratio = 0.47: 95% CI:0.31, 0.70) was higher among students compared to other donors.
Conclusions
While blood donors are generally considered a low-risk population for HIV and syphilis, we were able to identify that there remain relatively high rates of undiagnosed HIV and syphilis infections among donors. The routinely collected data from national blood donation services may be used to better understand the epidemiology of HIV and syphilis in specific locations, with the potential to enhance existing population-level disease surveillance systems. In addition, these findings may be used to identify priority prevention areas and populations in Blantyre district that can inform targeted interventions for improved disease prevention, testing and treatment.
The Association Between Trial of Labor After Cesarean in Obese Patients and Adverse Maternal Outcomes
Authors: Jude Gabrielle , Fain Audra , Raker Christina , Rubenstein Shayna , Wagner Stephen , Bicocca Matthew , Gupta Megha 
Published: March 2023

Abstract
Purpose: We hypothesized that among obese patients with a history of cesarean birth, a TOLAC is associated with decreased composite maternal adverse outcomes (CMAO) compared to planned repeat low transverse cesarean section (RLTCS).
Methods: In this population-based cross-sectional study using the National Birth Certificate database from 2016-2020, we compared obese patients who attempted TOLAC at term (³37 weeks estimated gestational age) to planned RLTCS. The primary outcome was a CMAO, defined as delivery complications, including intensive care unit (ICU) admission, uterine rupture, unplanned hysterectomy, or maternal blood transfusion.
Results: 794,278 patients met inclusion criteria for the study; 126,809 underwent a TOLAC, and 667,469 had a planned RLTCS. The overall CMAO was significantly higher for patients undergoing TOLAC (9.0 per 1,000 live births) compared to RLTCS (5.3 per 1,000 live births; aRR 1.64, 95% CI 1.53-1.75).
Conclusions: This data demonstrates that in obese patients with prior cesarean birth , a trial of labor is associated with increased maternal morbidity when compared to a planned repeat cesarean birth.
Expressions of pandemic fatigue on digital platforms: A thematic analysis of sentiment and narratives for infodemic insights
Authors: White Becky K , Ishizumi Atsuyoshi , Lavery Lucy , Wright Amy , Foley Tom , O’Neill Rhys , Rambaud Kimberly , Sreen Ravi Shankar , Salvi Cristiana , Takahashi Ryoko , D’Agostino Marcelo , Nguyen Tim , Briand Sylvie , Purnat Tina D 
Published: March 2023

Abstract
Background
The infodemic accompanying the COVID-19 pandemic has led to an overwhelming amount of information, including questions, concerns and misinformation. Pandemic fatigue has been identified as a concern from early in the pandemic. With new and ongoing health emergencies in 2022, it is important to understand how pandemic fatigue is being discussed and expressed by users on digital channels.
Methods
This paper describes the collection of publicly available data over a 3-month period from multiple online sources using Meltwater, CrowdTangle to source data from Twitter, Facebook, Instagram, YouTube, TikTok, Pinterest, Product Reviews, Twitch, blogs & forums. A comprehensive search strategy was developed and tested. A total of 1,484,042 social media posts were identified during the time-period that included the defined search terms for pandemic fatigue. These data were initially sorted by highest levels of engagement and from this dataset, analysts reviewed the mentions to isolate and remove irrelevant content and identify dominant narratives. A thematic analysis was carried out on these narratives to identify themes related to expression of pandemic fatigue. Two researchers reviewed the data and themes.
Results
The thematic analysis of narratives identified six main themes relating to expression of pandemic fatigue, and one theme of counter narratives against pandemic fatigue. Data volume increased concurrent with the time of the mpox emergency announcement. Emergent themes showed the different ways users expressed pandemic fatigue and how it was interlaced with issues of trust, preventative measure acceptance and uptake, misinformation, and being overwhelmed with multiple or sustained emergencies.
Conclusions
This paper has identified the different ways users express pandemic fatigue on digital channels over a 3-month period. Better understanding the implications of the infodemic ecosystem on user’s perceptions, questions, and concerns regarding pandemic and more broadly emergency fatigue is vital in identifying relevant interventions and, in the longer term, strengthening the global architecture for health emergency preparedness, prevention, readiness and resilience, as evidenced in this paper. There are clear pathways for further research, including incorporating additional languages and reviewing these themes over longer time periods.
Health status of inhabitants from the period of the Funnel-beaker Culture from Modřice (Brno-Country District, Czechia)
Authors: Vargová Lenka , Tvrdý Zdeněk , Vymazalová Kateřina 
Published: March 2023

Abstract
The presented work is focused on the palaeopathological analysis of the skeletal remains of 22 individuals (11 adults, 2 subadults, 9 children) from Modřice (Brno-Country District, Czechia) dated to the period of the Funnel-beaker Culture (3700-4000 BC). It represents a group of settled farmers. There are clear signs on the skeletons of physical activity. These inhabitants subsisted mainly on plant-based food. Compared to similar Neolithic groups, the Modřice skeletons had a very high rate of tooth decay. Of the congenital malformations, skeletal (scaphocephaly) and spinal (vertebral synostosis, spondylolysis) disabilities were found here. Most of the inflammatory changes on the bones were observed in connection with dental diseases, two cases of otitis media and inflammatory foci on the cranial vault of one of the females were also recorded. Although the presented research was limited by the small number of examined skeletons, it presents new information about the health status of the studied population group and enriches the existing knowledge about this important Neolithic population.
Long-term Causal Effects of Redlining on Environmental Risk Exposure
Authors: Conzelmann Claire , Salazar-Miranda Arianna , Phan Toan , Hoffman Jeremy 
Published: March 2023

Abstract
We provide new evidence that policies implemented nearly a century ago have significant causal effects on the exposure of 9 urban communities in the U.S. to climate-related risks. Using a boundary design, we show that redlining, a discriminatory federal housing policy pursued in the 1930s and outlawed in the 1960s, has resulted in persistent inequality in climate risk exposure. Locations in neighborhoods assigned lower credit grades have significantly higher exposure to flooding and higher air temperatures than comparable locations with higher grades. We attribute these disparities to lower measures of environmental capital, specifically tree coverage and ground surface perviousness, in these neighborhoods. Our findings underscore the ongoing causal effects of historical housing policies on present-day exposure to climate risks, and highlight the need to address the legacies of past policies in adapting to future climate risks.
Isolation and genomic characterization of one novel goose astrovirus causing acute gosling gout in China
Authors: Peng Zhifeng , Gao Dongsheng , Song Xinghui , Huang Huimin , Zhang Xiaozhan , Jiang Zenghai , Qiao Hongxing , Bian Chuanzhou 
Published: March 2023

Abstract
Novel goose astrovirus (NGAstV) is a member of the genus Avastrovirus and the family Astroviridae. NGAstV-associated gout disease has caused huge economic losses to the goose industry worldwide. Since early 2020, NGAstV infections characterized by articular and visceral gout emerged continuously in China. Herein, we isolated a GAstV strain from goslings with fatal gout disease and sequenced its full-length genome. Then we conducted systematic genetic diversity and evolutionary analysis. The results demonstrated that two genotypic species of GAstV were circulating in China, and GAstV-II sub-genotype IId had become the dominant one. Multiple alignments of amino acid sequences of GAstV capsid protein revealed several characteristic mutations (E456D, A464N, and L540Q) in GAstV-II d strains, as well as additional residues in the new isolate which varied over time. These findings enrich the understanding of the genetic diversity and evolution of GAstV and may facilitate the development of effective preventive strategies.
Identification of fasciclin-like arabinogalactan protein family genes associated with fruit ripening in tomato
Authors: Hu Jiahui , Wang Jun , Tuerdiyusufu Diliaremu , Yang Tao , Li Ning , Yang Haitao , Wang Baike , Yu Qinghui 
Published: March 2023

Abstract
Background: Tomato (Solanum lycopersicum) is a model plant for fruit ripening, of which contains a series of complex physiological and biochemical process. Fasciclin-like arabinogalactan proteins (FLAs) are a subclass of arabinogalactan proteins (AGPs) involved in cell wall formation and intracellular signal transduction. However, its functional mechanism in plant development including fruit ripening is rarely studied. In the present study, we identified four species tomatoes’ FLAs and analyzed their structural characteristics, evolutionary history and expression patterns during fruit development to mine candidate genes and determine their potential role in tomato fruit ripening.
Results: In the present study, 18 ,21, 22 and 22 FLAs were identified from the S. lycopersicum, S. pimpinellifolium, S. pennellii, and S. lycopersicoides, respectively. These proteins were divided into four groups by evolutionary and structural characteristics, and each group of FLAs in FAS structure domain, glycosylphosphatidylinositol (GPI) and the number there are similarities. The FLAs in four species are relatively conserved, and most of them are distributed at both ends of chromosomes. The FLA family members are amplified and evolved mainly by means of segmental duplication and purifying selection. Similar transcripts and expression patterns analysis among them revealed their regulatory roles in tomato fruit ripening. More intresting, in the WGCNA module constructed by the combination of tomato fruit transcriptome and targeted carotenoid metabolome, several SlFLAs co-expressed with genes enriched in secondary metabolism.
Conclusion: The FLAs gene family found in four species tomatoes and provides valid information in their little-studied studies on the regulation of fruit ripening. Combined with the detection of a key metabolite of tomato fruit ripening, carotenoids, which broadens the idea of biological functional analysis of SlFLAs and provides a theoretical basis and candidate genes for improving tomato fruit quality.
Prediction of vancomycin trough concentration using machine learning in the intensive care unit
Authors: Igarashi Yutaka , Osawa Shuichiro , Akaiwa Mari , Sato Yoshiki , Saito Takuma , Nakanishi Hatsumi , Yamanaka Masanori , Nishimura Kan , Ogawa Kei , Isoe Yuto , Miura Yoshihiko , Miyake Nodoka , Ohwada Hayato , Yokobori Shoji 
Published: March 2023

Abstract
Background: It is difficult to predict vancomycin trough concentrations in critically ill patients as their pharmacokinetics change with the progression of both organ failure and medical intervention. This study aims to develop a model to predict vancomycin trough concentration using machine learning (ML) and to compare its prediction accuracy with that of the population pharmacokinetic (PPK) model.
Methods: A single-center retrospective observational study was conducted. Patients who had been admitted to the intensive care unit, received intravenous vancomycin, and had undergone therapeutic drug monitoring between 2013 and 2020,were included. Thereafter, ML models were developed with random forest, LightGBM, and ridge regression using 42 features. Mean absolute errors (MAE) were compared and important features were shown using LightGBM.
Results: Among 335 patients, 225 were included as training data and 110 were used for test data. A significant difference was identified in the MAE by each ML model compared with PPK;4.13 ± 3.64 for random forest, 4.18 ± 3.37 for LightGBM, 4.29 ± 3.88 for ridge regression, and 6.17 ± 5.36 for PPK. The highest importance features were pH, lactate, and serum creatinine.
Conclusion: This study concludes that ML may be able to more accurately predict vancomycin trough concentrations than the currently used PPK model in ICU patients.
Carbon reduction assessment of public buildings based on Apriori algorithm and intelligent big data analysis
Authors: Shen Xu 
Published: March 2023

Abstract
Today, with the continuous progress of urbanization, public buildings have many environmental problems. Their high carbon emissions and energy consumption have caused considerable environmental pollution. Based on the analysis of the whole life cycle of public buildings, it can be seen from the results that due to its long time span, the service life will cause more pollution to the environment, high energy consumption and carbon emissions. In this environment, this paper completes the design and construction of carbon reduction measurement system for public buildings by combining intelligent big data technology and Apriori algorithm. The system mainly analyzes the whole life cycle of the building to calculate all energy consumption projects of the building, converts them into carbon footprint indicators, and uses the indicators to complete the quantitative assessment of environmental pollution level for public buildings in the whole life cycle, and obtains the carbon reduction assessment data of the building in the operating cycle in combination with the carbon emission factors of energy and electricity. The results of quantitative data analysis can be used for the design and arrangement of energy conservation and emission reduction policies, which can be realized by changing the lighting and ventilation, peripheral protection, shape coefficient and rainwater circulation of buildings. This paper conducts carbon reduction assessment for public buildings by integrating intelligent big data and Apriori algorithm.