bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integration of Deep and Ensemble Learning for Detecting COVID-19 in Computed Tomography Images
Authors: Haidar Ali , Holloway Lois 
Published: September 2020

Abstract
This paper presents an approach for detecting covid-19 in Computed Tomography (CT) images by integrating deep convolutional neural networks and ensembles of decision trees. The proposed approach consisted of three steps. In the first step, the CT images slices were collected and processed. In the second step, a deep convolutional neural network was trained to predict covid-19 in the CT images. In the third step, deep features were extracted and were used to train an ensemble of decision trees. Six types/packages of ensembles of decision trees were investigated: extreme gradient boosting (XGBoost), bagged decision trees (BDT), random forest (RF), adaptive boosting decision trees (Adaboost), gradient boosting decision trees (GBDT), and dropouts meet multiple additive regression trees (DART). The accuracy, sensitivity, specificity, f1-score, precision, and area under the ROC curve (AUC) were calculated to compare the models against each other. The proposed approach revealed the highest performance with a RF that reported 0.87 accuracy, 0.87 f1-score, and 0.90 AUC. The developed models revealed similar performance when compared to previously published models. This highlights the efficiency of combining deep networks with ensembles of decision trees for detecting covid-19.
CASC15: A Tumor-Associated Long Non-Coding RNA
Authors: Wang Bei , Xu Wen , Cai Yuxuan , Guo Chong , Zhou Gang , Yuan Chengfu 
Published: September 2020

Background:
CASC15, one of long non-coding RNA, is involved in the regulation of many tumor biological
processes, and is expected to become a new biological therapeutic target. This paper aims to elucidate
the pathophysiological function of CASC15 in various tumors.

Methods:
The relationship between CASC15 and tumors was analyzed by searching references, and summarized
the specific pathophysiological mechanism of CASC15.

Results:
LncRNA CASC15 is closely related to tumor development, and has been shown to be abnormally high
expressed in all kinds of tumors, including breast cancer, cervical cancer, lung cancer, hepatocellular carcinoma,
gastric cancer, bladder cancer, colon cancer, colorectal cancer, cardiac hypertrophy, intrahepatic cholangiocarcinoma,
leukemia, melanoma, tongue squamous cell carcinoma and nasopharyngeal carcinoma. However,
CASC15 has been found to be down-expressed abnormally in ovarian cancer, glioma and neuroblastoma. Besides,
it is identified that CASC15 can affect the proliferation, invasion and apoptosis of tumors.

Conclusion:
LncRNA CASC15 has the potential to become a new therapeutic target or marker for a variety of
tumors.
Hydrogen Gas as an Exotic Performance-Enhancing Agent: Challenges and Opportunities
Authors: Ostojic Sergej M. 
Published: September 2020

Background:
Hydrogen gas (H2) has entered the world of experimental therapeutics approximately
four and a half decades ago. Over the years, this simple molecule appears to drive more scientific attention, perhaps
due to a dualism of H2 affirmative features demonstrated in numerous in vitro, animal and human studies
on one side, and still puzzling mechanism(s) of its biological activity on the other. Up to this point, H2 was scrutinized
for more than 170 different disease models and pathologies, and many research groups across the world
have lately started to dynamically investigate its conceivable performance-enhancing potential.

Methods:
We outlined here the studies indexed in leading research databases (PubMed, Web of Science, SCOPUS,
JSTORE) that explored the effects of hydrogen on exercise performance, and also addressed important restraints,
open questions, and windows of opportunities for forthcoming research and possible H2 enactment in
exercise physiology. About two dozen trials have been identified in this domain, with most of the trials published
during the past 5 years, while drinking hydrogen-rich water recognized as the most convenient method to
deliver H2 in both animal and human studies.

Results:
Either administered as an inhalational gas, enteral hydrogen-rich water, or intravenous hydrogen-rich
saline, H2 seems to favorably affect various exercise performance outcomes and biomarkers of exercise-associated
fatigue, inflammation, and oxidative stress. Not all studies have shown corroborative effects, and it appears
that the gold-standard protocol for applying H2 in the field of exercise science does not exist at the moment,
with studies markedly differ in the dose of H2 administered, the duration of treatment, and the source of
hydrogen.

Conclusion:
H2 is a newfangled and rather effective performance-enhancing agent, yet its promising ergogenic
potency has to be further validated and characterized in more well-controlled, appropriately sampled and longterm
mechanistic trials. Also, appropriate regulation of hydrogen utilization in sport as an exotic medical gas
may require distinctive legislative actions of relevant regulatory agencies in the future.
Bronchospasmolytic and Adenosine Binding Activity of 8-(Proline / Pyrazole)- Substituted Xanthine Derivatives
Authors: Singh Sneha , Ojha Madhwi , Yadav Divya , Kachler Sonja , Klotz Karl-Norbert , Yadav Rakesh 
Published: September 2020

Background:
8-Phenyltheophylline derivatives exhibit prophylactic effects at a specific
dose but do not produce the cardiovascular or emetic side effects associated with xanthines, thereby
exhibiting unique characteristics of potential therapeutic importance.

Methods:
Novel series of 8-(proline/pyrazole)-substituted xanthine analogs has been synthesized. The affinity and selectivity of compounds to adenosine receptors have been assessed by radioligand binding studies. The synthesized compounds also
showed good bronchospasmolytic properties (increased onset of bronchospasm; decreased duration of jerks) with 100% survival of animals in comparison to the standard drug. Besides, compound 8f & 9f showed good binding affinity in comparison to other synthesized compounds in the micromolar range.

Results:
The maximum binding affinity of these compounds was observed for A2B receptors,
which was ~ 7 or 10 times higher as compared to A1, A2A and A3 receptors. The newly synthesized
derivatives 8f, 9a-f, 17g-m, and 18g-m displayed significant protection against histamine
aerosol induced bronchospasm in guinea pigs.

Conclusion:
Newly synthesized proline/pyrazole based xanthines compounds showed a satisfactory
binding affinity for adenosine receptor subtypes. Replacement or variation of substituted proline
ring with substituted pyrazole scaffold at the 8th-position of xanthine moiety resulted in the reduction
of adenosine binding affinity and bronchospasmolytic effects.
Knowledge of Non-communicable Disease Risk Factors among Community Health Workers in South Africa
Authors: Onagbiye Sunday O. , Tsolekile Lungiswa P. , Puoane Thandi 
Published: September 2020

Introduction:
Community Health Workers play an important role in supporting patients with chronic non-communicable diseases (NCDs), therefore they need to be constantly updated with current knowledge to enable them to perform their activities effectively. The purpose of this study was to assess the knowledge of NCDs risk factors among Community Health Workers (CHWs) in South Africa.

Methodology:
A triple “A” approach (assessment, analysis, and action) was used among 40 CHWs working with patients with chronic non-communicable diseases. All CHWs gave voluntary, informed consent in writing and verbally before they were allowed to participate in the study. For the initial assessment, CHWs completed a questionnaire to assess knowledge about the knowledge of NCDs. The questionnaire was analysed to determine their baseline performance. The findings of the assessment identified shortcomings in the knowledge of CHWs, specifically on diabetes and hypertension knowledge. Feedback was given to the CHWs followed by a short training on healthy living, focusing on the risk factors associated with NCDs (diabetes and hypertension). Training of CHWs was conducted using an adapted national training programme together with CHW prevention of healthy lifestyle modules designed by experts from the School of Public Health, University of the Western Cape. All statistical tests were two-tailed, and p<.05 was considered statistically significant.

Results:

The majority (97.5%) of the CHWs who had their knowledge assessed were women. Fifty-five percent (55%) were within age 30-45 years, while 45% were between the ages 46-60 years. The majority of the participants had secondary school education (92.5%) and 1-15 years of experience (97.5%) as CHWs. The results of the post-training assessment revealed that 48.5%, 63.6%, 42.4%, 72.7%, 42.5%, 57.6%, and 18.2% had poor knowledge of diabetes, hypertension, diabetes complications, hypertension complications, advice for diabetic patient, advice for hypertension, and nutrition advice of NCDs, respectively. Regression analysis showed that those with higher education levels were significantly highly likely to be knowledgeable about hypertension complications (OR=19.6, CI=1.14, 336.0).

Conclusion:
There was poor knowledge of risk factors for NCDs among CHWs. An association exists between the knowledge of risk factors for NCDs and education levels among the participants. There is a need for regular refresher training programs for CHWs to upscale their knowledge about NCDs, coupled with frequent review of CHWs program and curriculum.
Nurses’ Knowledge, Attitude, and Performance about Disaster Management: A Case of Iran
Authors: Far Sedighe S. T. , Marzaleh Milad A. , Shokrpour Nasrin , Ravangard Ramin 
Published: September 2020

Background:
Iran is a disaster-prone country in which many natural and man-made disasters happen every year. Because the health sector is vital due to its nature of treatment and rehabilitation of the injured after the disasters, all health care providers, especially hospital nurses, should be prepared to provide the services they need.

Objective:
The present study aimed to determine the level of knowledge, attitude, and performance of nurses about disaster management in teaching hospitals affiliated to Iran, Shiraz University of Medical Sciences in 2019.

Methods:
This cross-sectional and descriptive-analytical study was conducted on a sample of 230 nurses working in the teaching hospitals of Iran, Shiraz University of Medical Sciences, who were selected using the stratified sampling proportional to size and simple random sampling methods. The data were collected using a valid and reliable questionnaire containing 20 questions in three dimensions of knowledge, attitude, and performance. Then, the collected data were analyzed using SPSS 25.0 through independent samples t-test, ANOVA and Tukey tests at the significance level of 5%.

Results:
The results showed that the highest and lowest mean scores were related to the attitude (2.38±0.19) and knowledge (1.70±0.50) of the nurses, respectively. However, all three dimensions were at a moderate level. The results showed significant relationships between the mean score of performance and the gender, marital status, age, and work experience of the nurses. In addition, statistically significant relationships were found between the mean score of knowledge and their age and work experience (p<0.05).

Conclusion:
According to the findings, the following suggestions can be made to increase the knowledge and performance of the nurses for being prepared in critical situations: reducing the duration and increasing the quality of training classes and workshops on disaster preparedness; providing some incentives for nurses, especially female, married, older, and more experienced ones to attend these classes; and improving the methods of training materials related to disaster management.
A Review on Machine-learning Based Code Smell Detection Techniques in Object-oriented Software System(s)
Authors: Kaur Amandeep , Jain Sushma , Goel Shivani , Dhiman Gaurav 
Published: September 2020

Background:
Code smells are symptoms that something may be wrong in software systems
that can cause complications in maintaining software quality. In literature, there exist many
code smells and their identification is far from trivial. Thus, several techniques have also been proposed
to automate code smell detection in order to improve software quality.

Objective:
This paper presents an up-to-date review of simple and hybrid machine learning-based
code smell detection techniques and tools.

Methods:
We collected all the relevant research published in this field till 2020. We extracted the
data from those articles and classified them into two major categories. In addition, we compared the
selected studies based on several aspects like code smells, machine learning techniques, datasets,
programming languages used by datasets, dataset size, evaluation approach, and statistical testing.

Results:
A majority of empirical studies have proposed machine-learning based code smell detection
tools. Support vector machine and decision tree algorithms are frequently used by the researchers.
Along with this, a major proportion of research is conducted on Open Source Softwares (OSS)
such as Xerces, Gantt Project and ArgoUml. Furthermore, researchers pay more attention to Feature
Envy and Long Method code smells.

Conclusion:
We identified several areas of open research like the need for code smell detection
techniques using hybrid approaches, the need for employing valid industrial datasets, etc.
Big Data Analytics for MANET Based Sustainable Smart Healthcare Solution
Authors: Gautam Ashu , Mahajan Rashima , Zafar Sherin 
Published: September 2020

Objective:
Collaboration of most promising upcoming technologies like big data and Internet
of Things (IoT) plays a significant role in the sustainable development of the smart world. One
of the important applications is the amalgamation of such technology in the e-healthcare sector,
where private information is being transferred from one end device to other equipment. Sensors and
different other instruments engaged in the e-healthcare sector, for transferring important vital information
of the patients, are categorized as Wireless Mesh Networks (WMN). An attacker can introduce
many malicious activities via different types of attacks; ultimately, such activities can produce
an outturn in Denial of Service (DoS) of important routines which need to be completed in stipulated
time. Therefore, it is important to showcase the effect of various attacks affecting the routing methodology
of the protocols of such networks.

Methods:
In this research study, the most suitable routing protocol to handle DDoS attacks is simulated
and estimated for the Quality of Service (QoS) in smart network infrastructure in terms of energy
consumption and jitter in changing nodes scenario, which aids in providing implications to enhance
existing protocols and alleviate the consequence of DDoS instigated by such attacks.

Results:
The performance of AODV (Adhoc on Demand Vector), SAODV (Secured Adhoc On Demand)
and HWMP (Hybrid Wireless Mesh Protocol) is compared and tabularized, which are the
most popularly utilized protocols in the healthcare environment.

Conclusion:
The simulation results show that the HWMP outperformed well than the other two routing
protocols in terms of evaluation metrics, namely energy consumption and jitter, which could be
considered much less vulnerable against DDoS attacks prevailing in the sustainable healthcare sector.
Feasibility of Using a Single Heart Rate–Based Measure for Real-time Feedback in a Voluntary Deep Breathing App for Children: Data Collection and Algorithm Development
Authors: Petersen Christian L , Görges Matthias , Todorova Evgenia , West Nicholas C , Newlove Theresa , Ansermino J Mark 
Published: September 2020

Background
Deep diaphragmatic breathing, also called belly breathing, is a popular behavioral intervention that helps children cope with anxiety, stress, and their experience of pain. Combining physiological monitoring with accessible mobile technology can motivate children to comply with this intervention through biofeedback and gaming. These innovative technologies have the potential to improve patient experience and compliance with strategies that reduce anxiety, change the experience of pain, and enhance self-regulation during distressing medical procedures.

Objective
The aim of this paper was to describe a simple biofeedback method for quantifying breathing compliance in a mobile smartphone app.

Methods
A smartphone app was developed that combined pulse oximetry with an animated protocol for paced deep breathing. We collected photoplethysmogram data during spontaneous and subsequently paced deep breathing in children. Two measures, synchronized respiratory sinus arrhythmia (RSAsync) and the corresponding relative synchronized inspiration/expiration heart rate ratio (HR-I:Esync), were extracted from the photoplethysmogram.

Results
Data collected from 80 children aged 5-17 years showed a positive RSAsync effect in all participants during paced deep breathing, with a median (IQR; range) HR-I:Esync ratio of 1.26 (1.16-1.35; 1.01-1.60) during paced deep breathing compared to 0.98 (0.96-1.02; 0.82-1.18) during spontaneous breathing (median difference 0.25, 95% CI 0.23-0.30; P<.001). The measured HR-I:Esync values appeared to be independent of age.

Conclusions
An HR-I:Esync level of 1.1 was identified as an age-independent threshold for programming the breathing pattern for optimal compliance in biofeedback.
Construction of a Digestive System Tumor Knowledge Graph Based on Chinese Electronic Medical Records: Development and Usability Study
Authors: Xiu Xiaolei , Qian Qing , Wu Sizhu 
Published: September 2020

Background
With the increasing incidences and mortality of digestive system tumor diseases in China, ways to use clinical experience data in Chinese electronic medical records (CEMRs) to determine potentially effective relationships between diagnosis and treatment have become a priority. As an important part of artificial intelligence, a knowledge graph is a powerful tool for information processing and knowledge organization that provides an ideal means to solve this problem.

Objective
This study aimed to construct a semantic-driven digestive system tumor knowledge graph (DSTKG) to represent the knowledge in CEMRs with fine granularity and semantics.

Methods
This paper focuses on the knowledge graph schema and semantic relationships that were the main challenges for constructing a Chinese tumor knowledge graph. The DSTKG was developed through a multistep procedure. As an initial step, a complete DSTKG construction framework based on CEMRs was proposed. Then, this research built a knowledge graph schema containing 7 classes and 16 kinds of semantic relationships and accomplished the DSTKG by knowledge extraction, named entity linking, and drawing the knowledge graph. Finally, the quality of the DSTKG was evaluated from 3 aspects: data layer, schema layer, and application layer.

Results
Experts agreed that the DSTKG was good overall (mean score 4.20). Especially for the aspects of “rationality of schema structure,” “scalability,” and “readability of results,” the DSTKG performed well, with scores of 4.72, 4.67, and 4.69, respectively, which were much higher than the average. However, the small amount of data in the DSTKG negatively affected its “practicability” score. Compared with other Chinese tumor knowledge graphs, the DSTKG can represent more granular entities, properties, and semantic relationships. In addition, the DSTKG was flexible, allowing personalized customization to meet the designer's focus on specific interests in the digestive system tumor.

Conclusions
We constructed a granular semantic DSTKG. It could provide guidance for the construction of a tumor knowledge graph and provide a preliminary step for the intelligent application of knowledge graphs based on CEMRs. Additional data sources and stronger research on assertion classification are needed to gain insight into the DSTKG’s potential.
Effect of a Text Messaging–Based Educational Intervention on Cesarean Section Rates Among Pregnant Women in China: Quasirandomized Controlled Trial
Authors: Su Yanfang , Heitner Jesse , Yuan Changzheng , Si Yafei , Wang Dan , Zhou Zhiying , Zhou Zhongliang 
Published: September 2020

Background
Consensus exists that appropriate regional cesarean rates should not exceed 15% of births, but China’s cesarean rate exceeds 50% in some areas, prompting numerous calls for its reduction. At present, China’s 2016 two-child policy has heightened the implications of national cesarean section trends.

Objective
This study leveraged pervasive cellular phone access amongst Chinese citizens to test the effect of a low-cost and scalable prenatal advice program on cesarean section rates.

Methods
Participants were pregnant women presenting for antenatal care at a clinic in Xi’an, China. Assignment was quasirandomized and utilized factorial assignment based on the expecting mother’s birthday. Participants were assigned to one of the following four groups, with each receiving a different set of messages: (1) a comparison group that received only a few “basic” messages, (2) a group receiving messages primarily regarding care seeking, (3) a group receiving messages primarily regarding good home prenatal practices, and (4) a group receiving text messages of all groups. Messages were delivered throughout pregnancy and were tailored to each woman’s gestational week. The main outcome was the rates of cesarean delivery reported in the intervention arms. Data analysts were blinded to treatment assignment.

Results
In total, 2115 women completed the trial and corresponding follow-up surveys. In the unadjusted analysis, the group receiving all texts was associated with an odds ratio of 0.77 (P=.06), though neither the care seeking nor good home prenatal practice set yielded a relevant impact. Adjusting for potentially confounding covariates showed that the group with all texts sent together was associated with an odds ratio of 0.67 (P=.01). Notably, previous cesarean section evoked an odds ratio of 11.78 (P<.001), highlighting that having a cesarean section predicts future cesarean section in a subsequent pregnancy.

Conclusions
Sending pregnant women in rural China short informational messages with integrated advice regarding both care-seeking and good home prenatal practices appears to reduce women’s likelihood of undergoing cesarean section. Reducing clear medical indications for cesarean section seems to be the strongest potential pathway of the effect. Cesarean section based on only maternal request did not seem to occur regularly in our study population. Preventing unnecessary cesarean section at present may have a long-term impact on future cesarean section rates.

Trial Registration
ClinicalTrials.gov NCT02037087; https://clinicaltrials.gov/ct2/show/NCT02037087.

International Registered Report Identifier (IRRID)
RR2-10.1136/bmjopen-2015-011016