bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mathematical Modeling to Estimate the Reproductive Number and the Outbreak Size of COVID-19: The case of India and the World
Authors: Sinha Durgesh Nandini 
Published: May 2020

Abstract
Coronavirus disease (COVID-19) has become a global pandemic with more than 218,000 deaths in 211 different countries around the world. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus responsible for this deadliest disease. This paper describes a mathematical model for India, a country with the second highest population in the world with an extremely high population density of about 464 people per km2. This disease has multiphasic actions and reaction mode and our model SEIAQIm is based on six compartmental groups in the form of susceptible, exposed, infectious, asymptomatic, quarantine, and recovered immune factions. Latin Hypercube Sampling Partial Rank Correlation Coefficient method was used for the data analysis and model fitting. According to our model, India would reach its basic reproduction number R0=0.97 on May 14, 2020 with a total number of 73,800 estimated cases. Further, this study also equates the world's situation using the same model system and predicts by May 7, 2020 with a total number of 3,772,000 estimated confirmed cases. Moreover, the current mathematical model highlights the importance of social distancing as an effective method of containing spread of COVID-19.
Impact of rainfall properties on the performance of hydrological models for green roofs simulation
Authors: Mobilia Mirka , Longobardi Antonia 
Published: May 2020

Abstract
Green roofs (GR) are effective tools for the mitigation of the negative hydrological impact linked to uncontrolled urbanization. Models for runoff response of vegetated covers support planning decisions about the use of this technology in ever-expanding areas, but there is still large uncertainty in this research area. The goal of the present study was to define the accuracy of three selected models for the simulation of the hydrological behavior of a GR, with a particular focus on the precipitation pattern characteristics. The Nash cascade model, Storm Water Management Model (SWMM), and HYDRUS-1D models were selected. Each model was calibrated over 24 rainfall-runoff events collected at the experimental site located in Southern Italy. Rainfall events were characterized using several criteria and were divided into convective, stratiform, and tropical precipitation types according to the shape of the rainfall profile identified by the rainfall binary shape code. The models returned overall satisfactory performances with average Nash–Sutcliffe Efficiency index of 0.65 for the SWMM and HYDRUS and 0.73 for the Nash model. In general, the models were better performing for stratiform and tropical events. SWMM and HYDRUS predicted with higher accuracy the convective events while the Nash model appeared more suitable for stratiform events.
Design of an integration platform between the water-energy nexus and a business model applied for sustainable development
Authors: Mosalam Heba Ahmed , El-Barad Mohamed 
Published: May 2020

Abstract
Setting out an international standard schema for the water-energy-food (WEF) nexus and providing accurate data with realistic reports for investment through a simple application is essential for our real world. This research presents a tool to help anyone who wants to invest in environmental projects, especially water, energy, or food projects. The user can directly connect to a database of environmental data applying WEF nexus principles. This paper is looking for a mechanism to apply the WEF nexus concept through a web-based platform implementing unified concepts and terminology, setting basic criteria and standards, and making the data available, consistent, and homogeneous. Based on the problem statement, the purpose of this research is to implement a cross-application for sustainable development, including WEF nexus concepts, taking into consideration the interlinkage between the three resources integrated with a business model or financial study for projects. In addition, we have determined organizational perspectives of WEF nexus, including government entities, non-governmental organizations, and the private sector, and consolidated all the concepts into one set of WEF standards. Increasing the awareness of WEF nexus will help to establish a new generation of researchers who believe in the WEF nexus concepts and who will coordinate with developers and expert consultants to convert the WEF standards to programming coding.
Konferencja Wędrówki kultu relikwii w I tysiącleciu
Authors: Łaptaś Magdalena 
Published: May 2020

Sprawozdanie z Ogólnopolskiej konferencji naukowej poświęconej kultowi relikwii, która odbyła się 18 listopada 2014 r. na Uniwersytecie Kardynała Stefana Wyszyńskiego w Warszawie.
Revue report from the national conference “organized on 18th of November 2014 at the Kardinal Stefan Wyszyński Uniwersity in Warsaw, dedicated to the devotion for holy relics.
Effective Delivery of Nef-MPER-V3 Fusion Protein Using LDP12 Cell Penetrating Peptide for Development of Preventive/Therapeutic HIV-1 Vaccine
Authors: Sabaghzadeh Sahar , Sadat Seyed Mehdi , Rohollah Fatemeh , Bolhassani Azam 
Published: May 2020

Background:
There is no effective and safe preventive/therapeutics vaccine against
HIV-1 worldwide. Different viral proteins such as Nef, and two regions of Env including; variable
loop of gp120 (V3) and membrane proximal external region of gp41 (MPER) are particularly
important for vaccine development in different strategies and they are also the primary targets of
cellular and humoral immune responses. On the other side, LDP12 is a new cell-penetrating
peptide (CPP) which is capable of therapeutic application and cargoes delivery across the cellular
membrane.

Objective:
In current study, we designed and produced Nef-MPER-V3 fusion protein harboring LDP12
that has the capability of being used in future vaccine studies.

Methods:
The CPP-protein was expressed in E. coli Rosseta (DE3) strain and purified through
Ni-NTA column. Characterization of cellular delivery and toxicity of the recombinant protein were
evaluated by western blotting and MTT assay.

Results:
Our results showed that the CPP-protein was successfully expressed and purified with
high yield of 5 mg/L. Furthermore, non-cytotoxic effect was observed and specific band (~ 37
KDa) in western blotting indicated the capability of LDP12 to improve the rate of penetration into
HEK-293T cells in comparison with a control sample.

Conclusion:
Altogether, the data indicated that LDP12 CPP could be utilized to internalize HIV-1
Nef-MPER-V3 protein into eukaryotic cell lines without any toxicity and represented a valuable
potential vaccine candidate and this guarantees the further evaluation towards the assessment of its
immunogenicity in mice, which is currently under process.
Structural Insights into the Molecular Design of ROS1 Inhibitor for the Treatment of Non-Small Cell Lung Cancer (NSCLC)
Authors: Adhikary Ritu , Khandelwal Ravina , Hussain Tajamul , Nayarisseri Anuraj , Singh Sanjeev K. 
Published: May 2020

Background:
Non-Small Cell Lung Cancer (NSCLC) alone is the leading cause of deaths
worldwide. ROS1 is a receptor tyrosine kinase (RTK), eminently recognized as the stereotyped oncogenic
driver. These RTKs trigger an array of physiological regulations via cellular signal transduction
pathways, which are crucial for cancer development. This attributed ROS1 as an appealing and potential
target towards the targeted cancer therapy. The present research aims to propound out an effective
contemporary inhibitor for targeting ROS1 with a high affinity.

Methods:
Molegro Virtual Docker (MVD) provided a flexible docking platform to find out the bestestablished
drug as an inhibitor for targeting ROS1. A similarity search was accomplished against the
PubChem database to acquire the corresponding inhibitor compounds regarding the Entrectinib (Pub-
Chem ID: 25141092). These compounds were docked to procure the high-affinity inhibitor for the target
protein via virtual screening. A comparative study between the control molecule (PubChem ID:
25141092)and the virtual screened compound(PubChem ID-25175866) was performed for the relative
analysis of their salient features, which involved pharmacophore mapping, ADMET profiling, and
BOILED-Egg plot.

Results:
The virtual screened compound (PubChem ID-25175866) possesses the lowest rerank score
(-126.623), and the comparative ADMET analysis also shows that it is a potential and effective inhibitor
for ROS1 among the selected inhibitors.

Conclusion:
The present study provided a scope for the ROS1 inhibitor as significant prevention for nonsmall
cell lung cancer (NSCLC). It can be upheld for future studies as a promising support via in vivo studies.
Sphingosine Analogs and Protein Phosphatase 2A as a Molecular Targeted Cancer Therapy: A Mini Systematic Review
Authors: Mayerhofer Thomas , Jha Rajesh Kumar 
Published: May 2020

Background:
Regulation of protein phosphatase 2A (PP2A) plays an important role in hematologic
and solid neoplasms. Therefore, the use of sphingosine analogs as anti-neoplastic drugs has
shown potential due to their role as PP2A activators.

Objective:
Investigation of whether sphingosine analogs bind to endogenous inhibitor proteins of
PP2A, such as I2 PP2A/SET and/or CIP2A, and whether this binding reactivates PP2A, allowing it to resume
its role as a tumor suppressor.

Methods:
Literature from the PubMed database was searched and those articles related to PP2A and
sphingosine analogs were reviewed.

Results:
Utilization of sphingosine analogs in hematologic and solid neoplasms revealed numerous
mechanisms of inducing cell death. Regulation of PP2A through modulation of I2
PP2A/SET and/or
CIP2A was demonstrated in a variety of neoplastic processes; however, unique mechanisms such as
cell necrosis via the production of reactive oxygen species was also appreciated.

Conclusion:
Only certain malignancies expressed endogenous inhibitor proteins, yet sphingosine analogs
were able to induce cell death in neoplasms that did not express these proteins. This suggests that
sphingosine analogs may be utilized for anti-neoplastic therapy via reactivation of PP2A however, it
is not the exclusive mechanism for inducing cell death. Further investigation of sphingosine analogs
as a novel or adjunctive chemotherapeutic treatment is warranted.
Spelling Errors and Shouting Capitalization Lead to Additive Penalties to Trustworthiness of Online Health Information: Randomized Experiment With Laypersons
Authors: Witchel Harry J , Thompson Georgina A , Jones Christopher I , Westling Carina E I , Romero Juan , Nicotra Alessia , Maag Bruno , Critchley Hugo D 
Published: May 2020

Background
The written format and literacy competence of screen-based texts can interfere with the perceived trustworthiness of health information in online forums, independent of the semantic content. Unlike in professional content, the format in unmoderated forums can regularly hint at incivility, perceived as deliberate rudeness or casual disregard toward the reader, for example, through spelling errors and unnecessary emphatic capitalization of whole words (online shouting).

Objective
This study aimed to quantify the comparative effects of spelling errors and inappropriate capitalization on ratings of trustworthiness independently of lay insight and to determine whether these changes act synergistically or additively on the ratings.

Methods
In web-based experiments, 301 UK-recruited participants rated 36 randomized short stimulus excerpts (in the format of information from an unmoderated health forum about multiple sclerosis) for trustworthiness using a semantic differential slider. A total of 9 control excerpts were compared with matching error-containing excerpts. Each matching error-containing excerpt included 5 instances of misspelling, or 5 instances of inappropriate capitalization (shouting), or a combination of 5 misspelling plus 5 inappropriate capitalization errors. Data were analyzed in a linear mixed effects model.

Results
The mean trustworthiness ratings of the control excerpts ranged from 32.59 to 62.31 (rating scale 0-100). Compared with the control excerpts, excerpts containing only misspellings were rated as being 8.86 points less trustworthy, those containing inappropriate capitalization were rated as 6.41 points less trustworthy, and those containing the combination of misspelling and capitalization were rated as 14.33 points less trustworthy (P<.001 for all). Misspelling and inappropriate capitalization show an additive effect.

Conclusions
Distinct indicators of incivility independently and additively penalize the perceived trustworthiness of online text independently of lay insight, eliciting a medium effect size.
Associations Between Parent Self-Reported and Accelerometer-Measured Physical Activity and Sedentary Time in Children: Ecological Momentary Assessment Study
Authors: de Brito Junia N , Loth Katie A , Tate Allan , Berge Jerica M 
Published: May 2020

Background
Retrospective self-report questionnaires are the most common method for assessing physical activity (PA) and sedentary behavior (SB) in children when the use of objective assessment methods (eg, accelerometry) is cost prohibitive. However, self-report measures have limitations (eg, recall bias). The use of real-time, mobile ecological momentary assessment (EMA) has been proposed to address these shortcomings. The study findings will provide useful information for researchers interested in using EMA surveys for measuring PA and SB in children, particularly when reported by a parent or caregiver.

Objective
This study aimed to examine the associations between the parent’s EMA report of their child’s PA and SB and accelerometer-measured sedentary time (ST), light-intensity PA (LPA), and moderate-to-vigorous–intensity PA (MVPA) and to examine if these associations differed by day of week, sex, and season.

Methods
A total of 140 parent-child dyads (mean child age 6.4 years, SD 0.8; n=66 girls; n=21 African American; n=24 American Indian; n=25 Hispanic/Latino; n=24 Hmong; n=22 Somali; and n=24 white) participated in this study. During an 8-day period, parents reported child PA and SB via multiple daily signal contingent EMA surveys, and children wore a hip-mounted accelerometer to objectively measure ST, LPA, and MVPA. Accelerometer data was matched to the time period occurring before parent EMA-report of child PA and SB. Generalized estimating equations with interaction-term analyses were performed to determine whether the relationship between parent-EMA report of child PA and SB and accelerometer-measured ST and LPA and MVPA outcomes differed by day of the week, sex and season.

Results
The parent’s EMA report of their child’s PA and SB was strongly associated with accelerometer-measured ST, LPA, and MVPA. The parent’s EMA report of their child’s PA was stronger during the weekend than on weekdays for accelerometer-measured ST (P≤.001) and LPA (P<.001). For the parent’s EMA report of their child’s SB, strong associations were observed with accelerometer-measured ST (P<.001), LPA (P=.005), and MVPA (P=.008). The findings related to sex-interaction terms indicated that the association between the parent-reported child’s PA via EMA and the accelerometer-measured MVPA was stronger for boys than girls (P=.02). The association between the parent’s EMA report of their child’s PA and SB and accelerometer-measured ST and PA was similar across seasons in this sample (all P values >.31).

Conclusions
When the use of accelerometry-based methods is not feasible and in contexts where the parent is able to spend more proximate time observing the child’s PA and SB, the parent’s EMA report might be a superior method for measuring PA and SB in young children relative to self-report, given the EMA’s strong associations with accelerometer-measured PA and ST.
The Development of a Practical Artificial Intelligence Tool for Diagnosing and Evaluating Autism Spectrum Disorder: Multicenter Study
Authors: Chen Tao , Chen Ye , Yuan Mengxue , Gerstein Mark , Li Tingyu , Liang Huiying , Froehlich Tanya , Lu Long 
Published: May 2020

Background
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with an unknown etiology. Early diagnosis and intervention are key to improving outcomes for patients with ASD. Structural magnetic resonance imaging (sMRI) has been widely used in clinics to facilitate the diagnosis of brain diseases such as brain tumors. However, sMRI is less frequently used to investigate neurological and psychiatric disorders, such as ASD, owing to the subtle, if any, anatomical changes of the brain.

Objective
This study aimed to investigate the possibility of identifying structural patterns in the brain of patients with ASD as potential biomarkers in the diagnosis and evaluation of ASD in clinics.

Methods
We developed a novel 2-level histogram-based morphometry (HBM) classification framework in which an algorithm based on a 3D version of the histogram of oriented gradients (HOG) was used to extract features from sMRI data. We applied this framework to distinguish patients with ASD from healthy controls using 4 datasets from the second edition of the Autism Brain Imaging Data Exchange, including the ETH Zürich (ETH), NYU Langone Medical Center: Sample 1, Oregon Health and Science University, and Stanford University (SU) sites. We used a stratified 10-fold cross-validation method to evaluate the model performance, and we applied the Naive Bayes approach to identify the predictive ASD-related brain regions based on classification contributions of each HOG feature.

Results
On the basis of the 3D HOG feature extraction method, our proposed HBM framework achieved an area under the curve (AUC) of >0.75 in each dataset, with the highest AUC of 0.849 in the ETH site. We compared the 3D HOG algorithm with the original 2D HOG algorithm, which showed an accuracy improvement of >4% in each dataset, with the highest improvement of 14% (6/42) in the SU site. A comparison of the 3D HOG algorithm with the scale-invariant feature transform algorithm showed an AUC improvement of >18% in each dataset. Furthermore, we identified ASD-related brain regions based on the sMRI images. Some of these regions (eg, frontal gyrus, temporal gyrus, cingulate gyrus, postcentral gyrus, precuneus, caudate, and hippocampus) are known to be implicated in ASD in prior neuroimaging literature. We also identified less well-known regions that may play unrecognized roles in ASD and be worth further investigation.

Conclusions
Our research suggested that it is possible to identify neuroimaging biomarkers that can distinguish patients with ASD from healthy controls based on the more cost-effective sMRI images of the brain. We also demonstrated the potential of applying data-driven artificial intelligence technology in the clinical setting of neurological and psychiatric disorders, which usually harbor subtle anatomical changes in the brain that are often invisible to the human eye.
A Cross-Cultural Comparison of an Extended Planned Risk Information Seeking Model on Mental Health Among College Students: Cross-Sectional Study
Authors: Niu Zhaomeng , Willoughby Jessica Fitts , Mei Jing , Li Shaochun , Hu Pengwei 
Published: May 2020

Background
Approximately 42.5 million adults have been affected by mental illness in the United States in 2013, and 173 million people have been affected by a diagnosable psychiatric disorder in China. An increasing number of people tend to seek health information on the Web, and it is important to understand the factors associated with individuals’ mental health information seeking. Identifying factors associated with mental health information seeking may influence the disease progression of potential patients.

Objective
This study aimed to test the planned risk information seeking model (PRISM) in China and the United States with a chronic disease, mental illness, and two additional factors, ie, media use and cultural identity, among college students.

Methods
Data were collected in both countries using the same online survey through a survey management program (Qualtrics). In China, college instructors distributed the survey link among university students, and it was also posted on a leading social media site called Sina Weibo. In the United States, the data were collected in a college-wide survey pool in a large Northwestern university.

Results
The final sample size was 235 for the Chinese sample and 241 for the US sample. Media use was significantly associated with mental health information–seeking intentions in the Chinese sample (P<.001), and cultural identity was significantly associated with intentions in both samples (China: P=.02; United States: P<.001). The extended PRISM had a better model fit than the original PRISM.

Conclusions
Cultural identity and media use should be considered when evaluating the process of mental health information seeking or when designing interventions to address mental health information seeking.
Deep Learning Neural Networks to Predict Serious Complications After Bariatric Surgery: Analysis of Scandinavian Obesity Surgery Registry Data
Authors: Cao Yang , Montgomery Scott , Ottosson Johan , Näslund Erik , Stenberg Erik 
Published: May 2020

BackgroundObesity is one of today’s most visible public health problems worldwide. Although modern bariatric surgery is ostensibly considered safe, serious complications and mortality still occur in some patients.ObjectiveThis study aimed to explore whether serious postoperative complications of bariatric surgery recorded in a national quality registry can be predicted preoperatively using deep learning methods.MethodsPatients who were registered in the Scandinavian Obesity Surgery Registry (SOReg) between 2010 and 2015 were included in this study. The patients who underwent a bariatric procedure between 2010 and 2014 were used as training data, and those who underwent a bariatric procedure in 2015 were used as test data. Postoperative complications were graded according to the Clavien-Dindo classification, and complications requiring intervention under general anesthesia or resulting in organ failure or death were considered serious. Three supervised deep learning neural networks were applied and compared in our study: multilayer perceptron (MLP), convolutional neural network (CNN), and recurrent neural network (RNN). The synthetic minority oversampling technique (SMOTE) was used to artificially augment the patients with serious complications. The performances of the neural networks were evaluated using accuracy, sensitivity, specificity, Matthews correlation coefficient, and area under the receiver operating characteristic curve.ResultsIn total, 37,811 and 6250 patients were used as the training data and test data, with incidence rates of serious complication of 3.2% (1220/37,811) and 3.0% (188/6250), respectively. When trained using the SMOTE data, the MLP appeared to have a desirable performance, with an area under curve (AUC) of 0.84 (95% CI 0.83-0.85). However, its performance was low for the test data, with an AUC of 0.54 (95% CI 0.53-0.55). The performance of CNN was similar to that of MLP. It generated AUCs of 0.79 (95% CI 0.78-0.80) and 0.57 (95% CI 0.59-0.61) for the SMOTE data and test data, respectively. Compared with the MLP and CNN, the RNN showed worse performance, with AUCs of 0.65 (95% CI 0.64-0.66) and 0.55 (95% CI 0.53-0.57) for the SMOTE data and test data, respectively.ConclusionsMLP and CNN showed improved, but limited, ability for predicting the postoperative serious complications after bariatric surgery in the Scandinavian Obesity Surgery Registry data. However, the overfitting issue is still apparent and needs to be overcome by incorporating intra- and perioperative information.