bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anisotropic elastic strain in Pt-Co catalyst nanoparticles measured by correlated atomic resolution imaging and spectroscopy
Authors: Luo Xiaonan , Varambhia Aakash , Song Weixin , Shen Zhao , Sheader Alex , Ozkaya Dogan , Perez Sergio Lozano , Nellist Peter 
Published: August 2022

Abstract

Catalysts for the oxygen reduction reaction are crucial to the performance of fuel cell applications. Pt-based alloys have been shown to exhibit superior catalytic activities compared to pure Pt catalysts. Ligand and strain are two fundamental effects that have been proposed to explain the mechanistic origin of catalytic enhancement. It has been suggested that compressive strain leads to a shift of the d-band centre leading to improved reaction kinetics. Herein, we precisely quantify and correlate composition and strain variations from the same nanoparticle at an atomic scale within alloyed and dealloyed Pt-Co oxygen reduction reaction catalyst systems. Unlike the previously assumed effects of dealloying, we find that no compressive strain on the Pt-rich outer shell is imposed by the alloy core. Dilation strain is found to be distributed throughout the individual nanoparticles, with the radial dilation strain being much larger than the circumferential dilation strain at the surface. Remarkably, all the Pt-Co stoichiometries studied have a relatively invariant surface lattice parameter, which is smaller than that for pure Pt but larger than that predicted using the measured local surface composition, whether or not an acid de-alloying treatment is applied. These findings provide crucial insights to enable a full understanding of the origins of enhanced catalytic performance.
Using segmented linear regression under a Bayesian approach to detect climate change in different regions of the world
Authors: Achcar Jorge Alberto , Rodrigues Eliane R. , Oliveira Ricardo Puziol , Barili Emerson 
Published: August 2022

Abstract
In this work we study the behavior of some climate data (annual temperature and precipitation averages) obtained from climate stations in eleven countries in different regions of the world. One of the goals of the study is to determine whether the climate variables have change-points that could indicate the possible beginning of a change in climate. Another goal is to analyze the possible changes detected by the change-points in terms of the linear trends of the climate variables under investigation. Based on the information provided, differences between different regions in terms of the locations of the change-points and the changes they produce may also be inferred. The original data sets consist of monthly temperature and precipitation averages obtained over a period of time ranging from the end of the nineteenth century to the recent past. The annual averages were obtained and used in the analysis. The statistical methodology adopted to study the existence of the possible changes in the behavior of the climate variables, as well as the types of change produced, is that of segmented linear regression modeling.
Isolated long thoracic nerve palsy following COVID-19 vaccine: a case report.
Authors: Cutsem Gilles Van , Bolyn Serge 
Published: August 2022

Abstract
Introduction: We report an adult man who developed an isolated long thoracic nerve palsy three days following vaccination against COVID-19. To the best of our knowledge this is the first well-documented case of this association. Case presentation: A 46-year-old white man developed back pain, followed by pain in the right axilla and scapular region, clumsiness of the right arm and unusual position of his shoulder blade, three days after receiving a second dose of the Pfizer-BioNTech COVID-19 vaccine. When he consulted a neurologist six months later, the pain had subsided, but the other symptoms persisted despite physiotherapy. Main clinical findings were right scapular winging and marked amyotrophy of the serratus anterior, with preservation of the other muscles of the shoulder and scapula. Nerve conduction studies of the long thoracic nerve yielded a low amplitude with a slightly prolonged latency. Needle electromyography showed decreased compound motor action potentials on the right was normal with a few polyphasic waves on the left. Main diagnosis and interventions: A diagnosis of post-immunisation long thoracic neuritis was made. The patient was treated with physiotherapy. Conclusions: Clinicians should be aware of the possibility of neuritis of any nerve after COVID-19 vaccination.
Structural atlas of the most abundant human gut virus
Authors: Bayfield Oliver , Shkoporov Andrey , Yutin Natalya , Khokhlova Ekaterina , Smith Jake , Hawkins Dorothy , Koonin Eugene , Hill Colin , Antson Alfred 
Published: August 2022

Abstract
Bacteriophages of the order Crassvirales (crassviruses) were originally discovered by cross-assembly of metagenomic sequences. They are the most abundant viruses in the human gut, are found in the majority of individual gut viromes and account for up to ~95% of the viral sequences in some individuals(1–4). Crassviruses are likely to play major roles in shaping the composition and functionality of the human microbiome, but the structures and roles of most of the phage-encoded proteins are unknown, with only generic predictions resulting from bioinformatic analyses(4,5). Here we present a cryo-electron microscopy structure of Bacteroides intestinalis bacteriophage ΦcrAss001(6), providing the structural basis for the functional assignment of most of its virion proteins. The muzzle protein forms a ~1 MDa assembly at the end of the tail and exhibits a previously unknown fold that we designate “crAss fold”, that likely serves as a gatekeeper to control ejection of cargoes. In addition to packing the ~103 kb virus DNA, the ΦcrAss001 virion encompasses extensive storage space for cargo proteins in the capsid and, most unusually, within the tail. One of the cargo proteins is present in both the capsid and the tail, suggesting a general mechanism for protein ejection, which involves partial unfolding of proteins during their extrusion through the tail. These findings provide the structural basis for understanding the mechanisms of assembly and infection of these hugely abundant crassviruses.
ASPP2 enhances hepatic inflammation through exosome CD40L release derived from hepatocyte in alcoholic liver disease
Authors: Zhang Wenyan , Zhou Xiao , Zhang Jing , Jiang Qiuzhu , Shi Honglin , Zhang Ying , Chen Dexi , Ma Yingmin , Yu Haibin , Shi Hongbo 
Published: August 2022

Abstract
ASPP2 plays an important role in regulating hepatic inflammation, but the mechanism has been unclear. Recent studies found that damaged hepatocytes can activate macrophages through releasing exosomes. Although there is no report that ASPP2 can regulate exosome release, some evidence suggests that ASPP2 may participate in exosome release by autophagy. Compared to wild type mice fed by EtOH diet, conditional ASPP2 gene knock out (ASPP2 ALB−/−) mice fed by EtOH diet showed decreased hepatic steatosis and inflammation. ASPP2 high expression promotes the exosome CD40L release in alcohol induction and vice versa. The expression of TNF- α, IL-1 β, IL-6 were increased in THP1 cells treated with exosome derived from 7702 cells with ASPP2 upregulation and vice versa. CD40L knockdown in hepatocytes reversed activated effect of ASPP2 on macrophages through exosomes CD40L derived from hepatocytes. ASPP2 enhanced exosome CD40L release through RAS-mTORC1-autophagy pathways in hepatocytes in alcohol induction. Compared to normal controls, the expression of ASPP2, TNF- α, IL-1 β, IL-6 in liver tissue and exosome CD40L in plasma increased significantly in patients with alcoholic liver cirrhosis. ASPP2 enhances hepatic inflammation and macrophages activation through exosome CD40L release from hepatocyte which is regulated by RAS-mTORC1-autophagy pathways in alcoholic liver disease.
3D Roughness Prediction Modeling and Evaluation of Textured Liner of Piston Component-cylinder System
Authors: Lü Yanjun , Liu Cheng , Zhang Yongfang , Jiang Cheng , Bai Xudong , Xing Zhiguo 
Published: August 2022

Abstract

In this study, a machine vision method is proposed to characterize 3D roughness of the textured surface on cylinder liner processed by plateau honing. The least absolute value (L∞) regression robust algorithm and Levenberg-Marquardt (LM) algorithm are employed to reconstruct image reference plane. On this basis, a single-hidden layer feedforward neural network (SLFNN) based on the extreme learning machine (ELM) is employed to model the relationship between high frequency information and 3D roughness. The characteristic parameters of Abbott-Firestone curve and 3D roughness measured by a confocal microscope are used to construct ELM-SLFNN prediction model for 3D roughness. The results indicate that the proposed method can effectively characterize 3D roughness of the textured surface of cylinder liner.
Risk factors of recurrent bacterial vaginosis among women of reproductive age: A cross-sectional study
Authors: Zeng Xianling , An Ruifang , Li Han , Zhang Yafei 
Published: August 2022

Abstract
Background: Bacterial vaginosis (BV) is the most common cause of vaginitis and is associated with an increased risk of health problems. Our study aims to explore risk factors of recurrent BV (RBV) among women of reproductive age and offer references for clinical prevention and treatment of BV.Methods: This cross-sectional study was carried out in Gynecology Outpatient Clinic of the First Affiliated Hospital of Xi’an Jiaotong University from June 2016 to June 2019 in real-world conditions. Women with RBV were selected，and simultaneously uncomplicated BV (UBV) patients and those who underwent routine gynecological examination and had normal vaginal microflora (NVM) were also recruited as the control. We conducted a face-to-face questionnaire survey and a multivariate logistic regression analysis to uncover the related risk factors of RBV and UBV.Results: Totally, 316 participants were enrolled in the present study, including 68 RBV patients, 135 UBV patients and 113 NVM women. Univariate analysis showed that unemployment, desserts and wiping were the risk factors for UBV (P2<0.05), while education, high BMI index, smoking and sedentary lifestyle were risk factors for both RBV and UBV (P1<0.05). In addition, history of HPV infection, contraceptive methods, age at FSI and not cleaning vulva during sexual actvity were the risk factors for UBV (P2<0.05), while history of other vaginitis and number of sexual partners in the previous year were risk factors for both RBV and UBV (P1<0.05). Multivariate Logistic regression analysis revealed that lower educational level increased the risk of suffering RBV (OR =2.842, 95% CI = 1.177-6.859, P =0.020). Interestingly, no smoking was a protective factor (OR =0.371, 95% CI = 0.152-0.885, P =0.026). Moreover, absence of other vaginitis and exclusive sexual partner could also weaken the risk of incurring RBV. However, there was no statistical difference between non-sedentary lifestyle, BMI and RBV.Conclusions: Risk factors of RBV are various, involving women's socioeconomic status, hygienic habits, disease history and other aspects. It is necessary to take corresponding measures to avoid risk factors and to help lessening the prevalence of RBV among women of reproductive age.This study was registered in the Thai Clinical Trials Registry (www.clinicaltrials.in.th) on 24 February 2018, and the registered number was, TCTR20180223002, retrospectively registered
Spatial Disparity and Factors Associated with Dementia Mortality: A Cross-Sectional Study in Zhejiang Province, China
Authors: Heng Xiaotian , Liu Xiaoting , Li Na , Lin Jie , Zhou Xiaoyan 
Published: August 2022

Abstract
BackgroundThere is evidence of spatial disparity in mortality from Alzheimer’s disease and other forms of dementia in China. Regional factors of physical and social features may be influencing this spatial disparity. However, there are few reports on dementia mortality in China, and the true extent of spatial disparity in dementia mortality across small regional localities is unclear. The majority of people who die from dementia are over 60 years old. This study aims to explore the geographical variations in dementia mortality, estimate the relative risk and identify districts at higher risk for intervention and further study.Methods We used surveillance data on deaths from Alzheimer’s disease and other forms of dementia in Zhejiang province from 2015–2019 to estimate the spatial risk of death from dementia using a Bayesian spatial model. We mapped predicted relative risk to visualize the risk of death from Alzheimer’s disease and other forms of dementia and to identify risk factors associated with dementia.ResultsA total of 30,398 deaths attributable to dementia as the underlying or related cause (multiple causes) were reported in 2015–2019. Counties and districts located in the southeast and west of Zhejiang province had significantly higher standard mortality ratios than others. The predicted mean relative risk was 0.98, with a range of 0.14 ~ 4.37. Counties and districts with a smaller proportion of residents aged 60 years or older, poorer economic status, inferior health resources and worse pollution had a higher risk of dementia death.ConclusionsThere is spatial disparity in dementia mortality across different districts in Zhejiang. Our study adds new evidence on the association between social and environmental factors and the risk of dementia death. Appropriate preventive health strategies can be developed to reduce such spatial disparity in the risk of dementia mortality.
Effects of chemical additives and mature compost on reducing nitrogen loss during food waste composting
Authors: Xiong Shangao , Liu Yongdi , Zhang Hao , Xu Shaoqi , Li Songrong , Fan Xinqi , Chen Rui , Ding Guochun , Li Ji , Wei Yuquan 
Published: August 2022

Abstract
This study aims to investigate the effect of adding different types of mature compost amendments and sulfur powder on nitrogen loss and compost maturity of food waste. High-throughput sequencing was used to analyze the bacterial community during composting. Results showed that the secondary fermentation mature compost mixed with sulfur powder group had the most reduction of ammonia emission (56.3%) and the primary fermentation mature compost amendments were the most effective for nitrous oxide emission reduction (36.9%). The temperature, pH well as the nitrogen forms transformation of the pile significantly affect the nitrogen loss during composting. Firmicutes helped to promote the rapid warming of the pile and Actinobacteria and Proteobacteria played an important role in decomposition of organic matter. Thermobifida and Ureibacillus had main contribution to the rapid degradation of organic matter in the process of composting. The relative abundance of nitrogen-fixing bacteria were higher and the relative abundance of predominantly ammonifying and denitrifying bacteria were lower than control group, with different additives addition.
Prenatal magnetic resonance imaging of cerebellar dysplasia or malformations and coexistent malformations: A retrospective study in a single institution
Authors: Yu Fei , Zhou Qing , Huang Xiaowei , Xu Chengjie , Xiao Xirong , Zhang Guofu , Zhang He 
Published: August 2022

Abstract
Purpose: To clarify the prenatal magnetic resonance (MR) imaging characteristics of foetal cerebellar dysplasia/hypoplasia and developmental malformations and evaluate their diagnostic value. Methods: We retrospectively reviewed MR images of foetuses with suspected intracranial anomalies on screening ultrasound (US) on picture archiving communication system (PACS) servers within a five-year period in our institution. The main abnormal findings and coexistent anomalies were recorded by two experienced radiologists with census reading. The MRI and US results were paired and compared in each case. Results: We recruited 121 cases (average gestational week, 24.5 ± 4.7 weeks) with prenatal MR imaging, including sixty-two cases with simple cerebellar dysplasia or hypoplasia, thirty-one cases with other anomalies and twenty-eight cases with normal MR imaging findings. Cerebellar anomalies included intracranial haemorrhage, arachnoid cysts, Blake’s pouch cysts, Dandy-Walker malformation, cerebellar tonsil hernia and vermis absence. Coexistent cerebral malformations included hydrocephalus, cerebral haemorrhage, holoprosencephaly, brainstem/gyri malformation, ventriculomegaly and agenesis of the corpus callosum. Other detected systemic malformations included tethered cord syndromes (9 cases), club foot (1 case), cardiac malformation (1 case) and lip-palate cleft (1 case). Among 49 cases with both prenatal MR and US, MR imaging confirmed the diagnosis and/or provided more abnormal findings than US in 12 cases. Two dead babies after birth were recorded in cerebellar malformation group. Conclusion: Prenatal MR imaging could better show cerebellar anomalies and coexistent systemic malformations. As a complementary tool of US, MR imaging could help prenatal counselling and treatment selection at term.
Online Diagnosis-Treatment Department Recommendation based on Machine Learning in China
Authors: zhang shuangzhu , Ju Chunhua 
Published: August 2022

Abstract
[Background] As a supplement to the traditional medical service mode, online medical mode provides services of online appointment, consultation, online remote treatment, etc. Due to the complexity of online medical service application scenarios and the necessity of professional knowledge, the accuracy of the department during patient online consultation is limited, and traditional recommendation methods in the medical field face problems such as low computational efficiency and poor effectivenessMachine learning has been widely and successfully applied in medical fields. Hence, this study applies machine learning technology to intelligent department recommendation for online diagnosis-treatment services.[Objective] This paper compares the accuracy rate of different machine learning algorithms utilized for intelligent medical department recommendation at online diagnosis-treatment platforms, aiming to extract new features from the research data to improve recommendation effect. [Method] Based on online diagnosis-treatment data from 20 second-level departments at WeDoctor platform, the accuracy rates of two text vectorization methods in implementing intelligent department recommendation pairing with four classifiers, namely support-vector machine, random forest, multinomial Bayes and logistic regression, were compared from the perspective of hierarchy classification of department and secondary department. Furthermore, the paper also introduces variable of gender and age to improve accuracy rate of department recommendation. [Results] The recommendation accuracy rate is the best when text vectorization method is word2vec and classification algorithm is support-vector machine. The accuracy rate is 79.40% after adding age and gender into the model. The accuracy rate of intelligent recommendation was only about 52.7% for general surgery department and the reason behind is probably that online consultations from patients are usually so complicated that department functions are prone to be confused. [Conclusion] The effect of machine learning for online diagnosis-treatment platforms’ intelligent department recommendation is particularly significant. And the recommendation accuracy rate can be further improved by integrating age and gender into the algorithm. Moreover, considering the fact that some disease symptoms are confusing and can affect the recommendation accuracy rate to some extent, multiple departments shall be recommended to improve patients' online diagnosis-treatment experience and satisfaction.Fund program: National Natural Science Foundation of China(71571162)
Geo-Spatial Analysis of Drought in The Gambia Using Multiple Models
Authors: Bayo Bambo , Mahmood Shakeel 
Published: August 2022

Abstract
Climate change has made The Gambia vulnerable to drought hazard. Variability and negative trends in rainfall quantity and mid-season dry spells mainly attributed to the impacts of climate change. The inadequacy in hydrometeorological information puts the agricultural sector at a high risk which employs over 70% of the population. The aim of this study was to establish the intensity and spatiotemporal pattern of drought in The Gambia from 2000–2020 using multiple drought indices. Rainfall data, satellite images, and government policy documents were analyzed to determine the state of drought in The Gambia. Rainfall data, using Standardized Precipitation Index (SPI) and Precipitation Anomaly Percentage (PAP) were calculated and interpolated, and satellite images were processed using Vegetation Condition Index (VCI) to determine drought intensity and spatial distribution. The findings revealed that drought exists in The Gambia at moderate levels of SPI values (-1.00 to -1.49), (35% of PAP), and VCI of no drought intensity of more than 35%. The most drought prone areas in The Gambia are North Bank Region and Eastern parts of country in both north and south of the Gambia River banks. Recommendations of adaptation practice both on-farm and off-farm such as damming and economic diversification was drawn from other parts of the world, to reduce the negative effects of drought hazard in The Gambia.
How to establishing an indicators framework for evaluating the performances in primary TB control institutions under the new TB control model？Based on a Delphi Study conducted in Guangxi, China
Authors: Wu Tengyan , He Huimin , Wei Suosu , Zhu Pinghua , Feng Qiming , Tang Zhong 
Published: August 2022

Abstract

Background In China, the new TB control model of trinity form had been implemented in all parts, and the comprehensively evaluation to the Performances in primary TB control institutions were closely related to the working capacity and quality of TB service, but there was still no an unified evaluation indicators framework in practice and few relevant studies. The purpose of this study was to establish an indicators framework for comprehensively evaluating the performances in primary TB control institutions under the new TB control model of trinity form in Guangxi, China. Methods The Delphi method was used to establish an indicators framework for comprehensively evaluating the performances in primary TB control institutions under the new TB control model of trinity form, and the analytic hierarchy process(AHP) was used to determine the weights of all levels of indicators, from September 2021 to December 2021 in Guangxi, China. Results A total of 14 experts who had at least 10 years working experience and engaged in TB prevention and control and public health management from health committee, CDC, TB designated hospitals and university of Guangxi were consulted in two rounds. The average age of the experts were (43.3 ± 7.549) years old, and the effective recovery rate of the questionnaire was 100.0%. The average value of authority coefficient of experts (Cr) in the two rounds of consultation was above 0.800. The Kendall's harmony coefficient (W) of experts' opinions on the first-level indicators, the second-level indicators and the third-level indicators were 0.786, 0.201 and 0.169, respectively, which were statistically significant (P < 0.05). Finally, an indicators framework was established, which includes 2 first-level indicators, 10 second-level indicators and 37 third-level indicators. The results of analytic hierarchy process (AHP) show that the consistency test of all levels of indicators were CI < 0.10, which indicating that the weight of each indicator was acceptable. Conclusion The indicators framework established in this study was in line with the reality, had reasonable weights, and could provide a scientific evaluation tool for comprehensively evaluating the performances in primary TB control institutions under the new TB control model of trinity form in Guangxi, China.