bluuebunny/crossref_metadata_2025_split huggingface dataset:
Flood forecasting using an improved NARX network based on wavelet analysis coupled with uncertainty analysis by Monte Carlo simulations: a case study of Taihu Basin, China
Authors: Jiang Feiqing , Dong Zengchuan , Wang Zeng'an , Zhu Yiqing , Liu Moyang , Luo Yun , Zhang Tianyan 
Published: June 2021

Abstract
Reliable flood forecasting can provide a scientific basis for flood risk assessment and water resources management, and the Taihu water level forecasting with high precision is essential for flood control in the Taihu Basin. To increase the prediction accuracy, a coupling model (DWT-iNARX) is established by combining the discrete wavelet transformation (DWT) with improved nonlinear autoregressive with exogenous inputs network (iNARX), for predicting the daily Taihu water level during the flood season under different forecast periods. And the DWT-iNARX model is compared with the back-propagation neural network (BP) and iNARX models to assess its capability in prediction. Meanwhile, we propose an uncertainty analysis method based on Monte Carlo simulations (MCS) for quantifying model uncertainty and performing probabilistic water level forecast. The results show that three models achieve good simulation results with higher accuracy when the forecast period is short, such as 1–3 days. In overall performance, iNARX and DWT-iNARX models show superiority in comparison with the BP model, while the DWT-iNARX model yields the best performance among all the other models. The research results can provide a certain reference for the water level forecast of the Taihu Lake.
A Case of Pulmonary Tuberculosis Mimicking as Diffuse Alveolar Hemorrhage: A Case Report
Authors: Chand Trilok , Thomas Georgie , Khan M. U. 
Published: June 2021

Background:
Pulmonary tuberculosis (TB) and diffuse alveolar hemorrhage (DAH) have some commonalities in several parts of the world. However, acute
hemoptysis with diffuse alveolar shadows while a patient is on anticoagulant and antiplatelet therapy for a specific reason suggests DAH over TB.

Case Presentation:
In this case, a patient was presented with acute respiratory symptoms with hypoxia and bilateral alveolar shadows. He was treated for DAH at the
initial encounter. However, on follow-up, he was confirmed having active pulmonary TB based on sputum acid-fast-bacilli culture.

Conclusion:
He was successfully treated with standard first-line anti-tubercular therapy and was subsequently declared cured. Pulmonary DAH with TB, in the
absence of an underlying autoimmune disorder, is rare.
Development of a Gene Expression Panel, for the Prediction of Protein Abundances in Cancer Cell Lines
Authors: Lee Gunhee , Chung Yeun-Jun , Lee Minho 
Published: June 2021

Background:
Due to the ease of quantifying mRNA expression in comparison with that of
protein abundances, many studies have utilized it to infer protein product quantification. However, the
mRNA expression values for a gene and its protein products are not known to have a strong relationship,
because of the complex mechanisms required to regulate the amounts of protein levels, from
translation to post-translational modifications.

Methods:
We have developed, in this study, models to predict protein levels from mRNA expression
levels using the transcriptome and reverse phase protein arrays (RPPA)-based on protein levels in pancancer
cell lines. When predicting the abundance of a protein expression, in addition to using RNA
expression of the corresponding gene, we also used RNA expression levels of a particular set of other
genes. By applying support vector regression, we have identified a 47-gene expression panel that contributes
to the improved performance of the prediction, and its optimal subsets specific to each protein
species.

Result and Conclusion:
Eventually, our final prediction models doubled the number of predictable
protein expressions (r > 0.7). Due to the weaknesses of RPPA, our model had some limitations, however,
we expect that these prediction models and the panel can be widely used in the future to infer
protein abundances.
PREDAIP: Computational Prediction and Analysis for Anti-inflammatory Peptide via a Hybrid Feature Selection Technique
Authors: Lin Dan , Yu Jialin , Zhang Ju , He Huan , Guo Xinyun , Shi Shaoping 
Published: June 2021

Background:
Anti-Inflammatory Peptides (AIPs) are potent therapeutic agents for inflammatory
and autoimmune disorders due to their high specificity and minimal toxicity under
normal conditions. Therefore, it is greatly significant and beneficial to identify AIPs for further
discovering novel and efficient AIPs-based therapeutics. Recently, three computational approaches,
which can effectively identify potential AIPs, have been developed based on machine learning
algorithms. However, there are several challenges with the existing three predictors.

Objective:
A novel machine learning algorithm needs to be proposed to improve the AIPs prediction
accuracy.

Methods:
This study attempts to improve the recognition of AIPs by employing multiple primary
sequence-based feature descriptors and an efficient feature selection strategy. By sorting features
through four enhanced minimal redundancy maximal relevance (emRMR) methods, and then attaching
seven different classifiers wrapper methods based on the sequential forward selection algorithm
(SFS), we proposed a hybrid feature selection technique emRMR-SFS to optimize feature
vectors. Furthermore, by evaluating seven classifiers trained with the optimal feature subset, we
developed the Extremely Randomized Tree (ERT) based predictor named PREDAIP for identifying
AIPs.

Results:
We systematically compared the performance of PREDAIP with the existing tools on independent
test dataset. It demonstrates the effectiveness and power of the PREDAIP.

Conclusion:
The correlation criteria used in emRMR would affect the selection results of the optimal
feature subset at the SFS-wrapper stage, which justifies the necessity for considering different
correlation criteria in emRMR.
Informative Gene Selection Based on Cost-Sensitive Fast Correlation- Based Filter Feature Selection
Authors: Xiong Yueling , Li Qingqing , Wang Peipei , Ye Mingquan 
Published: June 2021

Background:
Informative gene selection is an essential step in performing tumor classification.
However, it is difficult to select informative genes related to tumors from large-scale gene
expression profiles because of their characteristics, such as high dimensionality, relatively small
samples, and class imbalance, and some genes are superfluous and irrelevant.

Objective:
Many researchers analyze and process gene expression data to obtain classified gene
subsets by using machine learning methods. However, the gene expression profiles of tumors often
have massive computational challenges. In addition, when improving feature importance and classification
accuracy, cost estimation is often ignored in traditional feature selection algorithms,
which makes tumor classification more difficult.

Methods:
In this study, a novel informative gene selection method based on cost-sensitive fast correlation-
based filter (CS-FCBF) feature selection is proposed.

Results:
First, the symmetric uncertainty index is used to evaluate the correlation between informativeFirst, the symmetric uncertainty index is used to evaluate the correlation between informative
genes and class labels, then a large number of irrelevant and redundant genes are quickly
filtered according to importance. Thereby, a candidate gene subset is generated. Second, costsensitive
learning, which introduces the misclassification cost matrix and support vector machine
attribute evaluation, is used to obtain the top-ranked gene subset with minimum misclassification
loss. Finally, the candidate gene subset is optimized.
genes and class labels, then a large number of irrelevant and redundant genes are quickly
filtered according to importance. Thereby, a candidate gene subset is generated. Second, costsensitive
learning, which introduces the misclassification cost matrix and support vector machine
attribute evaluation, is used to obtain the top-ranked gene subset with minimum misclassification
loss. Finally, the candidate gene subset is optimized.

Conclusion:
This experiment was verified in eight independent tumor datasets. By comparing and
analyzing CS-FCBF with another three hybrids of typical gene selection algorithms combined with
cost-sensitive learning, we found that the method proposed in this study has a better classification
performance with fewer selected genes, which might provide guidance in tumor diagnosis and research.
Revisiting the Antiviral Efficacy of Terpenoids: Plausible Adjunct Therapeutics
for Novel SARS-CoV-2?
Authors: Ahmad Afza , Tiwari Rohit Kumar , Ansari Irfan Ahmad 
Published: June 2021

:
Presently the world is witnessing the most devastating pandemic in the history of
mankind caused by Severe Acute Respiratory Syndrome or SARS-CoV-2. This dreaded pandemic
is responsible for escalated mortality rates across the globe and this is the worst catastrophe in the
history of mankind. Since its outbreak, substantial scientific explorations focusing on the formulation
of novel therapeutical and/or adjunct intervention against the disease are continuously in the
pipeline. However, till date, no effective therapy has been approved and hence the present alarming
situation urges the necessity of exploring novel, safe and efficient interventional strategies. Functionally,
terpenoids are a class of secondary plant metabolites having multi facet chemical structures
and are categorically documented to be the largest reservoir of bioactive constituents, predominant
in nature. Intriguingly, very little is scientifically explored or reviewed in regards to the anti-CoV-2
attributes of terpenoids. The present article thus aims to revisit the antiviral efficacy of terpenoids
by reviewing the current scientific literature and thereby provide an opinion on the plausibility of
exploring them as potential therapeutical intervention to deal with ongoing CoV-2 pandemic.
Research on Electrochemical Machining of Small Deep Holes with Positive
and Negative Pulse Power
Authors: Li Zhaolong , Cao Bingren 
Published: June 2021

Background:
High-temperature alloys, such as the nickel-based alloy, have become the
main materials for core components in the aerospace field because of their high strength and good
toughness. Therefore, how to improve the machining accuracy and stability of electrochemical machining
(ECM) of small deep holes on nickel-based alloy is an important topic for studies. The instantaneous
high-density current during the pulse width of pulse ECM is beneficial to the dissolution
of nickel-based alloy. Many experts and scholars have studied pulse ECM of small deep holes.

Objective:
The purpose of this article is to propose and design a positive and negative pulse (PANP)
power supply to study the accuracy and stability of ECM of small deep holes on the nickel-based
alloy.

Methods:
First of all, an H-bridge composed of four MOSFET switches is designed to achieve
PANP output in the main circuit of the power supply. Then, this article discusses the influence of
the ratio of positive and negative pulses on short circuits, the influence of the ratio of positive and
negative pulses on the mass removal rate, and the influence of the electrolyte concentration and
pulse width on the mass removal rate. Finally, according to the obtained optimal parameters, the influence
of the electrolyte pressure on the average radial overcut of hole depth is analyzed.

Results:
The experimental results show that the short-circuit frequency is reduced by more than
50% compared with non-negative pulses power supply; the ratio of positive and negative pulses,
pulse width, and electrolyte concentration and pressure were optimized by experiments in order to
improve the mass removal rate of the workpiece and the average radial overcut of hole depth.

Conclusion:
The designed PANP power supply can improve the machining accuracy and stability
of ECM of small deep holes on the nickel-based alloy.
2D and Layered Ti-based Materials for Supercapacitors and Rechargeable
Batteries: Synthesis, Properties, and Applications
Authors: Ni Wei , Shi Lingying 
Published: June 2021

:
Titanium-based two-dimensional (2D) and layered compounds with open and stable crystal
structures have attracted increasing attention for energy storage and conversion purposes, e.g., rechargeable
alkali-ion batteries and hybrid capacitors, due to their superior rate capability derived from
the intercalation-type or pseudocapacitive kinetics. Various strategies, including structure design, conductivity
enhancement, surface modification, and electrode engineering, have been implemented to
effectively overcome the intrinsic drawbacks while simultaneously maintaining their advantages as
promising and competitive electrode materials for advanced energy storage and conversion. Here, we
provide a comprehensive overview of the recent progress on Ti-based compound materials for highrate
and low-cost electrochemical energy storage applications (mainly on rechargeable batteries and
supercapacitors). The energy storage mechanisms, structure-performance relations, and performanceoptimizing
strategies in these typical energy storage devices are discussed. Moreover, major challenges
and perspectives for future research and industrial application are also illustrated.
Pengaruh Kecepatan Pengadukan pada Proses Stircasting terhadap Sifat Mekanik pada Paduan Aluminium
Authors: Jauhari Mochamad Helmi , Darmadi Djarot B , Widodo Teguh Dwi 
Published: June 2021

<p class="Abstract">The composite material is a material composed of a mixture or combination of two or more of the major elements that macro differ in shape and material composition that basically can not be separated. In this research, the aluminum used was the outcome of production cesspool with the addition of volcanic dust from Mount Kelud by 2% as reinforcement. The stir casting process is the casting process by adding a material (powder form) in pure metal (aluminum), which has been melted and then stirring constantly. After that, the composite materials (the volcanic dust from Mount Kelud) were mixed slowly into the stirred liquid material. In this research, the variations of stirring speed were 0,200,300,400,500 and 600 rpm. The stirring each time for 4 minutes. In this study, the stirring speed in the casting process was 0, 200, 300, 400, 500, and 600 rpm. Tensile test, Impact test, and microstructure observations were carried out on the casting results. From these tests, the highest modulus of elasticity and impact value was obtained at the 600rpm stirring process. It may due to globular grains are more evenly distributed. And the result of metallographic testing was stirring speed could affect the amount and density of composite grain structure. The faster the stirring, the grain structure was getting smaller and close.</p>
Development and evaluation of a complex of studies to increase the frequency of bending vibrations of modern passenger car bodies
Authors: Skachkov A. N. , Samoshkin S. L. , Korshunov S. D. , Nikiforov D. A. , Romashov D. A. 
Published: June 2021

Investigations of the frequency of bending vibrations of the car bodies of 61-4440 model range, which includes compartment cars, staff cars, non-compartment cars, coach cars, restaurant cars and others, are described. The bodies of all cars of this model range have the same overall dimensions and are made of corrosionresistant steels (stainless) with flat corrugated sheathing of the lower (under the window) belt.To assess the influence of the design features of stainless steel bodies on its bending stiffness and the parameters of bending vibrations in the vertical plane, a computational and experimental complex of works was carried out.After analyzing the calculation results and experimental data, proposals were developed and implemented to increase the bending stiffness of the metal body structure with stainless steel skin. To check the implemented proposals, complex tests were carried out to determine the parameters of bending vibrations of the metal structure of the experimental body. The tests were carried out according to the combined method developed by the authors. For this, a vibrator, installed in the console parts of the body, and impulse excitation were used.The results of testing the metal structure of the experimental body in comparison with the results of testing the car bodies of 61-4440 model range showed the effectiveness of the implemented proposals, namely: increasing the frequency of the first tone of bending vibrations by 18 %; decrease in the amplitude of vertical vibrations of the body structure at the frequency of the first tone from 12 to 50 %; decrease in the amplitude of the vertical accelerations of the metal structure of the body during oscillations at the frequency of the first tone approximately by 2 times; significant reduction in horizontal acceleration in the area of the middle section walls. The effectiveness of the implemented proposals for increasing the bending stiffness of the metal structure of the experimental body allows recommending them for the entire model range of 61-4440 cars.
Mucinous Cystadenoma of the Ovary Associated with Hyperplasia of Stromal Leydig Cells in Pregnant Woman
Authors: Bartoš Vladimír 
Published: June 2021

Background: The hormonally induced non-neoplastic lesions of ovarian stroma during pregnancy must be recognized by pathologist in order to avoid mistaking them for true tumors.
Case report: A 28-year-old woman was delivered of a healthy infant by cesarean section. As an incidental finding, a multicystic tumor in the left ovary was found and resected. Histopathology was consistent with benign mucinous cystadenoma. In addition, within the stroma beneath the lining mucinous epithelium, a dense population of cohesive polygonal cells with abundant eosinophilic cytoplasm, typically resembling the Leydig cells, was seen. They were uniform without atypia, accompaning by minimal proliferative activity. They strongly expressed vimentin, inhibin, CD99 and calretinin. The final diagnosis of mucinous cystadenoma associated with hyperplasia of stromal Leydig cells was made.
Conclusions: Leydig cell hyperplasia belongs to the specific changes of ovarian stroma associated with pregnancy. The present case stresses that in such situation the pathologists should be aware of it and not confuse it with a tumor.
Conceptualizing Usability for the eHealth Context: Content Analysis of Usability Problems of eHealth Applications
Authors: Broekhuis Marijke , van Velsen Lex , Peute Linda , Halim Meilani , Hermens Hermie 
Published: June 2021

Background
Usability tests can be either formative (where the aim is to detect usability problems) or summative (where the aim is to benchmark usability). There are ample formative methods that consider user characteristics and contexts (ie, cognitive walkthroughs, interviews, and verbal protocols). This is especially valuable for eHealth applications, as health conditions can influence user-system interactions. However, most summative usability tests do not consider eHealth-specific factors that could potentially affect the usability of a system. One of the reasons for this is the lack of fine-grained frameworks or models of usability factors that are unique to the eHealth domain.

Objective
In this study, we aim to develop an ontology of usability problems, specifically for eHealth applications, with patients as primary end users.

Methods
We analyzed 8 data sets containing the results of 8 formative usability tests for eHealth applications. These data sets contained 400 usability problems that could be used for analysis. Both inductive and deductive coding were used to create an ontology from 6 data sets, and 2 data sets were used to validate the framework by assessing the intercoder agreement.

Results
We identified 8 main categories of usability factors, including basic system performance, task-technology fit, accessibility, interface design, navigation and structure, information and terminology, guidance and support, and satisfaction. These 8 categories contained a total of 21 factors: 14 general usability factors and 7 eHealth-specific factors. Cohen κ was calculated for 2 data sets on both the category and factor levels, and all Cohen κ values were between 0.62 and 0.67, which is acceptable. Descriptive analysis revealed that approximately 69.5% (278/400) of the usability problems can be considered as general usability factors and 30.5% (122/400) as eHealth-specific usability factors.

Conclusions
Our ontology provides a detailed overview of the usability factors for eHealth applications. Current usability benchmarking instruments include only a subset of the factors that emerged from our study and are therefore not fully suited for summative evaluations of eHealth applications. Our findings support the development of new usability benchmarking tools for the eHealth domain.
Development and Evaluation of Acceptability and Feasibility of a Web-Based Intervention for Patients With Bipolar Disorder in Iran: Implementation Study
Authors: Ashrafi Agaah , Tabatabaee Maryam , Sharifi Vandad 
Published: June 2021

Background
Psychoeducation for bipolar disorder has a significant impact on symptoms and treatment adherence. In Iran, as a low-resource setting, infrastructural barriers, such as inadequate mental health professionals, difficulties in transportation, and costs of care, may hinder optimum delivery of this evidence-based intervention to patients.

Objective
This study sought to explore the acceptability and feasibility of a web-based intervention for bipolar patients in Iran.

Methods
A website has been developed as a platform for providing psychoeducational content about bipolar disorder. Patients were chosen via a convenient sampling method in 2018-2019. The main component of the intervention included streaming 7 weekly video clips after attending a single in-person meeting, as well as a medication self-monitoring application. Information was collected about the feasibility and acceptability of the intervention.

Results
We invited 45 patients from the day center and the outpatient clinic of Roozbeh psychiatric hospital and some private clinics in Tehran. Of the 23 patients (51%) who attended the first in-person session and provided informed consent, 14 patients dropped out during the study. While 9 patients completed the course (attended 4 or more online sessions), only 5 watched all the video sessions. The rate of adherence to the intervention and frequency of exposure to the website were much higher for those recruited from the private and outpatient clinics.

Conclusions
This web-based intervention can be feasible and acceptable only for a subgroup of patients with specific educational status and socioeconomic level.