bluuebunny/crossref_metadata_2025_split huggingface dataset:
An integrated grey AHP-MOORA model for ameliorating public transport service quality
Authors: Moslem Sarbast , Çelikbilek Yakup 
Published: December 2020

Abstract
Introduction
Public transport systems provide essential mobility service to citizens who do not have access to private cars. Public transport also plays a significant role in minimizing road congestions, air pollution, journey time and energy consumption. Public transport service quality need efficient strategic plans to be able to increase user’s satisfaction and attract non-user’s.

Objectives
To achieve this target, a combined model of the Analytic Hierarchy Process (AHP) with Multi Objective Optimization Method by Ratio Analysis (MOORA) based on grey optimization has been adopted, as a case study, the public bus transport system in Budapest, Hungary has been opted.

Methods
The weight scores of the evaluation criteria are conducted based on transport experts' assessments. When the studies in the literature are reviewed, it is observed that the success of the MOORA technique about decision making is remarkable. Also, there is not an agreed and validated grey MOORA technique in the literature. Thus, an integrated grey AHP and grey MOORA technique is proposed in this study to evaluate the public transport service quality. Grey based multi-criteria decision making methods are very useful to decrease the subjectivity of the decision makers.

Results
The importance of criteria has been computed by conducting grey AHP approach while the alternatives that have been preferred mostly within the certain criteria have been estimated by adopting grey MOORA method. Finally, the findings of the proposed model shed the light on “Provide new buses” as the most desired alternative for developing the service quality of public bus transport in Budapest.

Conclusion
The proposed model provides reliable and robust results for improving public transport service quality. The local government representatives in Budapest may use the obtained results in their future strategic plans for developing public bus transport system.
Deep learning detection of informative features in tau PET for Alzheimer’s disease classification
Authors:   for the Alzheimer’s Neuroimaging Initiative, Jo Taeho , Nho Kwangsik , Risacher Shannon L. , Saykin Andrew J. 
Published: December 2020

AbstractBackgroundAlzheimer’s disease (AD) is the most common type of dementia, typically characterized by memory loss followed by progressive cognitive decline and functional impairment. Many clinical trials of potential therapies for AD have failed, and there is currently no approved disease-modifying treatment. Biomarkers for early detection and mechanistic understanding of disease course are critical for drug development and clinical trials. Amyloid has been the focus of most biomarker research. Here, we developed a deep learning-based framework to identify informative features for AD classification using tau positron emission tomography (PET) scans.ResultsThe 3D convolutional neural network (CNN)-based classification model of AD from cognitively normal (CN) yielded an average accuracy of 90.8% based on five-fold cross-validation. The LRP model identified the brain regions in tau PET images that contributed most to the AD classification from CN. The top identified regions included the hippocampus, parahippocampus, thalamus, and fusiform. The layer-wise relevance propagation (LRP) results were consistent with those from the voxel-wise analysis in SPM12, showing significant focal AD associated regional tau deposition in the bilateral temporal lobes including the entorhinal cortex. The AD probability scores calculated by the classifier were correlated with brain tau deposition in the medial temporal lobe in MCI participants (r = 0.43 for early MCI and r = 0.49 for late MCI).ConclusionA deep learning framework combining 3D CNN and LRP algorithms can be used with tau PET images to identify informative features for AD classification and may have application for early detection during prodromal stages of AD.
Auto3DCryoMap: an automated particle alignment approach for 3D cryo-EM density map reconstruction
Authors: Al-Azzawi Adil , Ouadou Anes , Duan Ye , Cheng Jianlin 
Published: December 2020

Abstract
Background
Cryo-EM data generated by electron tomography (ET) contains images for individual protein particles in different orientations and tilted angles. Individual cryo-EM particles can be aligned to reconstruct a 3D density map of a protein structure. However, low contrast and high noise in particle images make it challenging to build 3D density maps at intermediate to high resolution (1–3 Å). To overcome this problem, we propose a fully automated cryo-EM 3D density map reconstruction approach based on deep learning particle picking.

Results
A perfect 2D particle mask is fully automatically generated for every single particle. Then, it uses a computer vision image alignment algorithm (image registration) to fully automatically align the particle masks. It calculates the difference of the particle image orientation angles to align the original particle image. Finally, it reconstructs a localized 3D density map between every two single-particle images that have the largest number of corresponding features. The localized 3D density maps are then averaged to reconstruct a final 3D density map. The constructed 3D density map results illustrate the potential to determine the structures of the molecules using a few samples of good particles. Also, using the localized particle samples (with no background) to generate the localized 3D density maps can improve the process of the resolution evaluation in experimental maps of cryo-EM. Tested on two widely used datasets, Auto3DCryoMap is able to reconstruct good 3D density maps using only a few thousand protein particle images, which is much smaller than hundreds of thousands of particles required by the existing methods.

Conclusions
We design a fully automated approach for cryo-EM 3D density maps reconstruction (Auto3DCryoMap). Instead of increasing the signal-to-noise ratio by using 2D class averaging, our approach uses 2D particle masks to produce locally aligned particle images. Auto3DCryoMap is able to accurately align structural particle shapes. Also, it is able to construct a decent 3D density map from only a few thousand aligned particle images while the existing tools require hundreds of thousands of particle images. Finally, by using the pre-processed particle images,
Auto3DCryoMap reconstructs a better 3D density map than using the original particle images.
Immunological biomarkers of the vitreous responsible for proliferative alteration in the different forms of retinal detachment
Authors: Balogh Anikó , Milibák Tibor , Szabó Viktória , Nagy Zoltán Zsolt , Kaarniranta Kai , Resch Miklós D. 
Published: December 2020

Abstract
Background
The purpose of the study was to explore the immunological components that are responsible for the proliferative alterations in the different forms of retinal detachment (RD).

Methods
Vitreous fluids were collected during 23G pars plana vitrectomy from 54 eyes of 54 patients with different RD types, such as rhegmatogenous RD (RRD) without proliferative vitreoretinopathy (PVR) (n = 30), PVR (n = 16) and proliferative diabetic retinopathy (PDR) with tractional RD (n = 8). Vitreous fluids were obtained from 19 eyes with epiretinal membrane (ERM), which were used as control samples. A multiplex chemiluminescent immunoassay was performed to evaluate the concentrations of 48 cytokines, chemokines and growth factors.

Results
The expression levels of eotaxin, IFN-gamma, IL-6, IL-8, IL-16, MCP-1, MIF and MIP-1 beta were significantly higher in all RD groups than in the ERM group. The levels of CTACK, IP-10, SCGF-beta, and SDF-1 alpha were significantly higher in patients with diabetic tractional RD and PVR than in other patients. The upregulation of VEGF and IL-18 was detected in PDR.

Conclusions
Our results indicate that complex and significant immunological mechanisms are associated with the pathogenesis of different forms of RD: selected cytokines, chemokines and growth factors are upregulated in the vitreous of eyes with RD. The detected proteins are present in different concentrations both in RRD and PVR. In the presence of PVR and PDR, the majority of cytokines are upregulated; thus, they may serve as biomarkers to estimate the progression or severity level of proliferation and later to develop personalized therapeutic strategies to slow down or prevent pathological changes.
Characterization of genome-wide association study data reveals spatiotemporal heterogeneity of mental disorders
Authors: Dai Yulin , O’Brien Timothy D. , Pei Guangsheng , Zhao Zhongming , Jia Peilin 
Published: December 2020

AbstractBackgroundPsychiatric disorders such as schizophrenia (SCZ), bipolar disorder (BIP), major depressive disorder (MDD), attention deficit-hyperactivity disorder (ADHD), and autism spectrum disorder (ASD) are often related to brain development. Both shared and unique biological and neurodevelopmental processes have been reported to be involved in these disorders.MethodsIn this work, we developed an integrative analysis framework to seek for the sensitive spatiotemporal point during brain development underlying each disorder. Specifically, we first identified spatiotemporal gene co-expression modules for four brain regions three developmental stages (prenatal, birth to 11 years old, and older than 13 years), totaling 12 spatiotemporal sites. By integrating GWAS summary statistics and the spatiotemporal co-expression modules, we characterized the risk genes and their co-expression partners for five disorders.ResultsWe found that SCZ and BIP, ASD and ADHD tend to cluster with each other and keep a distance from other psychiatric disorders. At the gene level, we identified several genes that were shared among the most significant modules, such asCTNNB1andLNX1, and a hub gene,ATF2,in multiple modules. Moreover, we pinpointed two spatiotemporal points in the prenatal stage with active expression activities and highlighted one postnatal point for BIP. Further functional analysis of the disorder-related module highlighted the apoptotic signaling pathway for ASD and the immune-related and cell-cell adhesion function for SCZ, respectively.ConclusionOur study demonstrated the dynamic changes of disorder-related genes at the network level, shedding light on the spatiotemporal regulation during brain development.
The International Conference on Intelligent Biology and Medicine (ICIBM) 2020: Data-driven analytics in biomedical genomics
Authors: Shi Xinghua , Zhao Zhongming , Wang Kai , Shen Li 
Published: December 2020

AbstractThis editorial summarizes eight research articles included in this supplement issue for the 2020 International Conference on Intelligent Biology and Medicine (ICIBM 2020) conference, that was held on August 9-10, 2020 (virtual conference), with a topic on data-driven analytics in biomedical genomics. These articles cover a wide range of topics in medical genomics that focus on integrative analysis of genomics data together with other types of data toward understanding complex human diseases, including cancer. With the growing importance of data analytics in biomedical science, we expect this collection of research articles provides scientific discussions in this direction.
Non-pharmacological labor pain management and associated factor among skilled birth attendants in Amhara Regional State health institutions, Northwest Ethiopia
Authors: Getu Almaz Aklilu , Getie Simegnew Asmer , Gela Getahun Belay , Maseresha Eleni Admassu , Feleke Birhanu Elifu , Muna Alemtsehay Mekonen 
Published: December 2020

Abstract
Background
Healthcare providers have a responsibility to provide pain management support to women during labor. Labor pain management in low and middle income countries primarily relies on non-pharmacological methods, as there is little access to pharmacologic pain management. This study aimed to determine the utilization of non-pharmacological labor pain management (NPLPM) and associated factors among skilled birth attendants (SBAs) in Amhara Regional State health institutions, Ethiopia.

Methods
A cross-sectional study was conducted on 592 SBAs working in the Amhara Region, Ethiopia. A multistage sampling was used to collect data using a pretested interview-administered questionnaire. Descriptive analysis was done to characterize the study population. Logistic regression was used to model predictors of NPLPM utilization among SBAs, including age, qualifications, type of medical institution, knowledge, attitudes, and the presence of a protocol.

Result
Nearly forty seven percent 277(46.8%) of SBAs in the study cohort utilized NPLPM. SBAs who had adequate knowledge of NPLPM had 2.8 times increased odds of using NPLPM than SBAs who had inadequate knowledge. (95%CI 1.89–4.014). SBAs who had a positive attitude had 4.12 times increased odds of using NPLPM than SBAs with a negative attitude (95%CI 2.36, 7.2). SBAs who had labor a pain management protocol in their facility had 3.98 times increased odds of using NPLPM than those who didn’t have a labor pain management protocol (95%CI 1.83, 8.62).

Conclusions
The analysis pointed to a gap in the utilization of NPLPM in the Amhara Region facilities studied. Less than half of SBAs used NPLPM when caring for laboring women. Professional factors related to use of NPLPM included the age of SBAs, their attitudes, level of education, and knowledge concerning pain management. NPLPM was also significantly associated with the availability of labor pain management protocols.
Analysis and validation of a highly sensitive one-step nested quantitative real-time polymerase chain reaction assay for specific detection of severe acute respiratory syndrome coronavirus 2
Authors: Zhang Yang , Dai Chunyang , Wang Huiyan , Gao Yong , Li Tuantuan , Fang Yan , Shen Zuojun , Chen Lichang , Chen Zhaowu , Ma Xuejun , Li Ming 
Published: December 2020

Abstract
Background
Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, is posing a serious threat to global public health. Reverse transcriptase real-time quantitative polymerase chain reaction (qRT-PCR) is widely used as the gold standard for clinical detection of SARS-CoV-2. Due to technical limitations, the reported positive rates of qRT-PCR assay of throat swab samples vary from 30 to 60%. Therefore, the evaluation of alternative strategies to overcome the limitations of qRT-PCR is required. A previous study reported that one-step nested (OSN)-qRT-PCR revealed better suitability for detecting SARS-CoV-2. However, information on the analytical performance of OSN-qRT-PCR is insufficient.

Method
In this study, we aimed to analyze OSN-qRT-PCR by comparing it with droplet digital PCR (ddPCR) and qRT-PCR by using a dilution series of SARS-CoV-2 pseudoviral RNA and a quality assessment panel. The clinical performance of OSN-qRT-PCR was also validated and compared with ddPCR and qRT-PCR using specimens from COVID-19 patients.

Result
The limit of detection (copies/ml) of qRT-PCR, ddPCR, and OSN-qRT-PCR were 520.1 (95% CI: 363.23–1145.69) for ORF1ab and 528.1 (95% CI: 347.7–1248.7) for N, 401.8 (95% CI: 284.8–938.3) for ORF1ab and 336.8 (95% CI: 244.6–792.5) for N, and 194.74 (95% CI: 139.7–430.9) for ORF1ab and 189.1 (95% CI: 130.9–433.9) for N, respectively. Of the 34 clinical samples from COVID-19 patients, the positive rates of OSN-qRT-PCR, ddPCR, and qRT-PCR were 82.35% (28/34), 67.65% (23/34), and 58.82% (20/34), respectively.

Conclusion
In conclusion, the highly sensitive and specific OSN-qRT-PCR assay is superior to ddPCR and qRT-PCR assays, showing great potential as a technique for detection of SARS-CoV-2 in patients with low viral loads.
Bayesian stochastic multi-scale analysis via energy considerations
Authors: Sarfaraz Muhammad S. , Rosić Bojana V. , Matthies Hermann G. , Ibrahimbegović Adnan 
Published: December 2020

AbstractMulti-scale processes governed on each scale by separate principles for evolution or equilibrium are coupled by matching the stored energy and dissipation in line with the Hill-Mandel principle. We are interested in cementitious materials, and consider here the macro- and meso-scale behaviour of such a material. The accurate representations of stored energy and dissipation are essential for the depiction of irreversible material behaviour, and here a Bayesian approach is used to match these quantities on different scales. This is a probabilistic upscaling and as such allows to capture, among other things, the loss of resolution due to scale coarsening, possible model errors, localisation effects, and the geometric and material randomness of the meso-scale constituents in the upscaling. On the coarser (macro) scale, optimal material parameters are estimated probabilistically for certain possible behaviours from the class of generalised standard material models by employing a nonlinear approximation of Bayes’s rule. To reduce the overall computational cost, a model reduction of the meso-scale simulation is achieved by combining unsupervised learning techniques based on a Bayesian copula variational inference with functional approximation forms.
Probabilistic seismic response analysis of coastal highway bridges under scour and liquefaction conditions: does the hydrodynamic effect matter?
Authors: Wang Xiaowei , Pang Yutao , Ye Aijun 
Published: December 2020

AbstractCoastal highway bridges are usually supported by pile foundations that are submerged in water and embedded into saturated soils. Such sites have been reported susceptible to scour hazard and probably liquefied under strong earthquakes. Existing studies on seismic response analyses of such bridges often ignore the influence of water-induced hydrodynamic effect. This study assesses quantitative impacts of the hydrodynamic effect on seismic responses of coastal highway bridges under scour and liquefaction potential in a probabilistic manner. A coupled soil-bridge finite element model that represents typical coastal highway bridges is excited by two sets of ground motion records that represent two seismic design levels (i.e., low versus high in terms of 10%-50 years versus 2%-50 years). Modeled by the added mass method, the hydrodynamic effect on responses of bridge key components including the bearing deformation, column curvature, and pile curvature is systematically quantified for scenarios with and without liquefaction across different scour depths. It is found that the influence of hydrodynamic effect becomes more noticeable with the increase of scour depths. Nevertheless, it has minor influence on the bearing deformation and column curvature (i.e., percentage changes of the responses are within 5%), regardless of the liquefiable or nonliquefiable scenario under the low or high seismic design level. As for the pile curvature, the hydrodynamic effect under the low seismic design level may remarkably increase the response by as large as 15%–20%, whereas under the high seismic design level, it has ignorable influence on the pile curvature.
Correlates of poor medication adherence in chronic psychotic disorders
Authors: Sajatovic Martha , Mbwambo Jessie , Lema Isaac , Blixen Carol , Aebi Michelle E. , Wilson Betsy , Njiro Godwin , Burant Christopher J. , Cassidy Kristin A. , Levin Jennifer B. , Kaaya Sylvia 
Published: December 2020

Background
Chronic psychotic disorders (CPDs) occur worldwide and cause significant burden. Poor medication adherence is pervasive, but has not been well studied in sub-Saharan Africa.

Aims
This cross-sectional survey of 100 poorly adherent Tanzanian patients with CPD characterised clinical features associated with poor adherence.

Method
Descriptive statistics characterised demographic and clinical variables, including barriers to adherence, adherence behaviours and attitudes, and psychiatric symptoms. Measures included the Tablets Routine Questionnaire, Drug Attitudes Inventory, the Brief Psychiatric Rating Scale, the Clinical Global Impressions scale, the Alcohol Use Disorders Identification Test and Alcohol, Smoking and Substance Involvement Screening Test. The relationship between adherence and other clinical variables was evaluated.

Results
Mean age was 35.7 years (s.d. 8.8), 61% were male and 80% had schizophrenia, with a mean age at onset of 22.4 (s.d. 7.6) years. Mean proportion of missed CPD medication was 64%. One in ten had alcohol dependence. Most individuals had multiple adherence barriers. Most clinical variables were not significantly associated with the Tablets Routine Questionnaire; however, in-patients with CPD were more likely to have worse adherence (P ≤ 0.01), as were individuals with worse medication attitudes (Drug Attitudes Inventory, P < 0.01), higher CPD symptom severity levels (Brief Psychiatric Rating Scale, P < 0.001) and higher-risk use of alcohol (Alcohol Use Disorders Identification Test, P < 0.001).

Conclusions
Poorly adherent patients had multiple barriers to adherence, including poor attitudes toward medication and treatment, high illness acuity and substance use comorbidity. Treatments need to address adherence barriers, and consider family supports and challenges from an intergenerational perspective.
Autistic traits and mental health in women with the fragile-X premutation: maternal status versus genetic risk
Authors: White Sarah J. , Gerber Denise , Sanchez Hernandez Romina D. , Efiannayi Anthonia , Chowdhury Ishita , Partington Hannah , Moss Joanna F. 
Published: December 2020

BackgroundResearch on women with the fragile-X premutation (FX-p) has been underrepresented within the field of behavioural phenotypes.AimsTo understand whether the FX-p confers risk for autistic traits, depression and anxiety, independent of maternal status.MethodIn study 1, mothers of children with fragile-X syndrome (M-FXp; n = 51, mean age 43 years (s.d. = 5.80)) were compared with mothers of autistic children (M-ASD; n = 59, mean age 42 (s.d. = 5.80)), mothers of children with Smith-Magenis syndrome (M-SMS; n = 27, mean age 39 (s.d. = 7.20)) and mothers of typically developing children (M-TD; n = 44, mean age 40 (s.d. = 4.90)). In study 2, the M-FXp group were compared with non-mothers with the FX-p (NM-FXp; n = 17, mean age 32 (s.d. = 9.20)), typically developed non-mothers (NM-TD; n = 28, mean age 31 (s.d. = 6.80)) and the M-TD group. All participants completed an online survey, including measures of IQ, autistic traits, anxiety, depression and positive affect.ResultsIn study 1: the M-FXp group reported more autistic traits than the M-TD group (P < 0.05, η2 = 0.046). Anxiety and parental stress were elevated in the M-FXp, M-SMS and M-ASD groups relative to the M-TD group (all P ≤ 0.003, η2 = 0.079–0.322). In study 2: a main effect of premutation status indicated that women with the FX-p report elevated autistic traits and anxiety (P ≤ 0.007, η2 = 0.055–0.060); this did not interact with maternal status.ConclusionsThe findings indicate that women with the FX-p show an increased risk for autistic traits and anxiety. This risk is specific to the presence of the FX-p and is not fully accounted for by maternal status or the stress of caring for children with neurodevelopmental disorders.
White Swan: On Possible Further Additions to the Oeuvre of a Crow Warrior-Artist
Authors: Lycett Stephen J. , Keyser James D. 
Published: December 2020

Abstract
Crow warrior-artist White Swan authored more biographic images than any other Historic-period Crow artist. It has even been suggested that he drew one rock art scene at the historically important petroglyphs at Joliet, Montana. Here, the authors evaluate the likelihood that the Joliet scene is a White Swan drawing, and they also evaluate the possibility that one of the “anonymous” ledger drawings in the Barstow collection was drawn by him. Unfortunately, neither drawing has sufficient similarities to known White Swan drawings to be classified as such. Instead, these drawings indicate there were likely far many more Crow men who could execute pictographic narratives of style and content similar to those produced by White Swan than has so far been reported in the anthropological literature.