bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical features and treatment outcomes of rare genera of fungal keratitis in China
Authors: Wang Xin , Lu Xiuhai , Li Suxia , Wang Ting , Jia Yanni , Wang Shuting , Wang Jingting , Dong Chunxiao , Shi Weiyun 
Published: September 2019

Abstract
Background Fungal keratitis can cause severe corneal blindness, although the major fungal genera in China have been widely reported, however rare genera of fungal keratitis is little known. This study aimed to investigate the clinical features and treatment outcomes of rare genera of fungal keratitis in China.Methods This retrospective observational study included a total of 1608 patients infected with fungal keratitis and treated at the Shandong Eye Hospital. The risk factors, course of disease, clinical features, confocal microscopy images, histopathological features, in vitro drug sensitivity tests, and treatment outcomes of 16 patients with 8 rare fungal genera were evaluated.Results No immune rings were observed among the 8 fungal genera studied. Rhizopus and Pythium insidiosum keratitis presented as endothelial plaque and hypopyon. Curvularia crescentulum keratitis presented as endothelial plaque, feathery edges, and raised lesions. Purpureocillium lilacinum keratitis showed endothelial plaque, hypopyon, and raised lesions. Colletotrichum , Exserohilum, and Bipolaris keratitis had feathery edges, while Sarocladium keratitis had no typical fungal clinical characteristics. In 2/3 cases (12.5%) of Curvularia crescentulum keratitis, it was cured with medication, while in 14/16 cases (87.5%), surgery was required, including 3 cases of evisceration. The best-corrected visual acuity (BCVA, LogMAR) of 13 cases was 1.47±0.87 before treatment and 0.64 ±0.48 after treatment, and the difference was statistically significant [(95% CI, 0.26–1.40) ( P =0.006].Conclusions Curvularia crescentulum keratitis showed good results when treated with medicine, while for Rhizopus, Sarocladium, Colletotrichum, Exserohilum, Bipolaris, and Purpureocillium lilacinum keratitis, early surgical intervention shortened the course of the disease. The prognosis of Pythium insidiosum keratitis is poor, as medication failed and the recurrence cycle after surgery was short.
Risk factors analysis of HPS patients with acute Stanford A aortic dissection
Authors: Xie Qiuxia , Qin Haoling , Lin Ling , Guan Jian , Zhou Xuhui 
Published: September 2019

Abstract
Background: AAD refers to the blood flow into the middle membrane through the intimal rupture of the aorta. HPS is a common complication of Stanford-A AAD. The risk factors of HPS are remaining unclear
Methods: In this study, we have probed the potential risk factors of hepatopulmonary syndrome (HPS) patients with acute Stanford A aortic dissection. 18 HPS patients with acute Stanford A aortic dissection were selected as case group. 36 Normal people were considerate as control group. Demographic data, treatment methods, AD related disease history, clinical symptoms and Charlson comorbidity index (CCI) values of each patient were collected. Meanwhile, the values of maximum diameter of ascending aorta (mm), aortic dissection range, and main branch of aorta, pleural effusion/blood, and pericardial effusion/blood were measured by two experienced cardiovascular radiological physicians. Univariate and multivariate conditional logistic regression analysis were used in this study.
Results: CCI value and the branches of the brachiocephalus in case group were significant higher than that in control group (p<0.05). Univariate conditional logistic regression analysis showed CCI and branches of the brachiocephalus were associated with HPS. Multivariate conditional logistic regression analysis suggested that branches of the brachiocephalus was an independent risk factor for HPS (OR=7.02, 95%CI=1.28-38.62, p=0.025).
Conclusions: Branches of the brachiocephalus were an independent risk factor for HPS.
Elevated glycosylated hemoglobin levels and its interactive effects on hypertension risk in non-diabetic population: a cross-sectional survey in China
Authors: song jian , wei nana , zhao yingying , jiang yuhong , wu xuesen , gao huaiquan 
Published: September 2019

Abstract
Background Abnormal glucose metabolism have been suggested to be involved in the development of hypertension. The present study aimed to investigate the associations and potential interactions of hemoglobin A1c (HbA1c) with other factors on the risk of hypertension among Chinese non-diabetic adults. Methods As a cross-sectional survey, the current work provided questionnaire survey, anthropometric tests and biochemical measure for each of the eligible participants. The HbA1c levels were quantified and grouped by quartiles. The correlation between HbA1c and hypertension risk in non-diabetic were investigated by univariate and multivariate analyses. For evaluating the interactive effects, the parameters of Relative Excess Risk due to Interaction (RERI), Attributable Proportion due to Interaction (AP) and Synergy Index (SI) were calculated, respectively. Results In the current study, 1462 non-diabetic subjects were enrolled. Totally, the prevalence of hypertension was 22.4% (n=327) in the individuals without diabetes. When the HbA1c levels were grouped by quartiles, it was revealed that the prevalence of hypertension substantially elevated across groups ( P for trend <0.001). In the multivariable logistic regression analyses, in comparison with the first quartile of HbA1c, the normalized OR for hypertension risk were 1.90 (95% CI:1.28-2.80) for the highest quartile. Besides, the ROC curve analysis indicated that the best threshold of HbA1c as the predictor for hypertension risk was 4.95 in non-diabetic subjects, with the AUC of 0.60 (0.58-0.63). Eventually, it was demonstrated from the interactive effect analysis that the HbA1c significantly interacted with abdominal obesity (RERI: 1.48, 95% CI: 0.38- 2.58; AP: 0.37, 95% CI: 0.14-0.60 and SI: 1.96, 95% CI: 1.06-3.62) and family history of hypertension (AP: 0.37, 95% CI: 0.05-0.70) on the risk of hypertension in non-diabetic participants. Conclusion The risk of hypertension was aggravated by the up-regulated HbA1c in an independent and synergistic manner with abdominal obesity and family history of hypertension in Chinese subjects without diabetes.
DNA extraction from resin producing Boswellia tree
Authors: Khan Adil , Khan Abdul Latif , Asaf Sajjad , Al-Harrasi Ahmed , Al-Rawahi Ahmed 
Published: September 2019

Abstract
Wild and medicinal plants producing resin and ladle with phenolic and polysaccharides have been found a major hurdle to extract high quality of genomic DNA. These contaminants co -precipitate with DNA and inhibit enzymatic modification of DNA. Previously reported protocols yielded highly viscous DNA regimen that were not amicable to down-stream analysis. We tried several commonly used protocols but were unable to isolate high quality DNA from frankincense producing Boswellia sacra. We extensively optimized the Cetyl Trimethyl Ammonium Bromide (CTAB) based protocol used for Commiphora wightii and Passiflora foetida previously. The current methos involves changes in buffer conditions, handling methods, and cycles of steps to remove resin at earlier stages of extracton. The obtained gDNA can be used for genetic diversity, DNA barcoding and next generation sequencing approaches. To our knowledge, this is the first optimized protocol which a rapid and less laborious for the extraction of DNA from Boswellia species.
DECOMPOSITION OF GENDER WAGE GAP IN POLAND USING COUNTERFACTUAL DISTRIBUTION WITH SAMPLE SELECTION
Authors: Landmesser Joanna Małgorzata 
Published: September 2019

Abstract
In the paper, we compare income distributions in Poland taking into account gender differences. The gender pay gap can only be partially explained by differences in men’s and women’s characteristics. The unexplained part of the gap is usually attributed to the wage discrimination. The objective of this study is to extend the Oaxaca-Blinder decomposition procedure to different quantile points along the income distribution. We use the RIF-regression method to describe differences between the incomes of men and women along the two distributions and to evaluate the strength of the influence of personal characteristics on the various parts of the income distributions. As the sample selection is a serious issue for the study, therefore our decomposition approach will be adjusted for sample selection problems. The results suggest not only differences in the income gap along the income distribution (in particular sticky floor and glass ceiling), but also differences in the contribution of selection effects to the pay gap at different quantiles. The analysis is based on data from the EU-SILC data for Poland in 2014.
Brachial Plexopathy as a Complication of Radiotherapy: A Systematic Review
Authors: Shabeeb Dheyauldeen , Musa Ahmed E. , Keshavarz Mansoor , Mihandoust Ehsan , Hassanzadeh Gholamreza , Hadian Mohammad R. , Shirazi Alireza , Najafi Masoud 
Published: September 2019

Background:
Radiotherapy is a commonly used cancer treatment modality. However,
radiation-induced complications are major drawbacks, especially at high doses. Radiation-induced
brachial plexopathy (RIBP) is mostly observed in breast and lung cancer patients some months to
years after radiotherapy. RIBP symptoms have negative effects on patients’ quality of life. The
aim of this study was to review RIBP according to the preferred reporting items for systematic
reviews and meta-analyses (PRISMA) guidelines.

Methods:
Online databases (PubMed, Scopus, Web of Science and Embase) were searched to
retrieve relevant studies on brachial plexopathy as a complication of radiotherapy.

Results:
Initial search results yielded a total of 657 articles. After careful screening of their titles
and abstracts, according to the inclusion and exclusion criteria, 31 articles were finally included in
this study. Findings from these 31 papers showed that a total of 9192 cancer patients had undergone
radiotherapy for different regions including chest, axillary area, thoracic outlet, neck and
breast. 26.4% of these patients had RIPB (associated with symptoms such as paresthesia, pain,
weakness, and/or motor dysfunction, organ pathology/dysfunction etc.) with different follow up
times, where 8.2% of patients had RIPB after a mean time of 1.2 years, 15.8% after 2.6 years,
51% after 5 years, 14% after 7.8 years, and 11% after 10.5 years.

Conclusion:
From our findings, we can conclude that the issue of radiation-induced brachial
plexus complication in human is of great concern. Common symptoms associated with this complication
include paresthesia, numbness, pain and weakness. We recommend the use of individual
dose planning and computer-assisted image segmentation techniques that support rapid and reliable
contouring of the brachial plexus. Also, the radiation dose to the brachial plexus should be
limited as much as possible to reduce the risk of brachial plexopathy.
Computer-Based versus Paper-Based Insulin Infusion Algorithms in Diabetic Ketoacidosis
Authors: Younis Moustafa , Pham John , Asad Hussein , Hamarshi Majdi S. 
Published: September 2019

Background::
Paper-based and computer-based insulin infusion algorithms facilitate appropriate
glycemic therapy. The data comparing these algorithms in the management of diabetic ketoacidosis
in the intensive care unit (ICU) setting are limited. We aimed to determine the differences in time to
diabetic ketoacidosis resolution and incidence of hypoglycemia between computer and paper-based insulin
infusion.

Methods::
Single-institution retrospective review of patients admitted to the ICU with diabetic ketoacidosis
between 4/1/2015 and 7/20/2018. Our institution introduced computer-based insulin infusion
(Glucommander) to the intensive care unit on 3/28/2016. Patients were grouped into either paper-based
group (preintervention) or a computer-based group (postintervention). Summary and univariate analyses
were performed.

Results::
A total of 620 patients (paper-based=247; computer-based=373) with a median (IQR) age of 40
(26-56) years were included; 46% were male. Patients in the computer-based group were significantly
older (p=0.003); otherwise, there were no significant differences in gender, race, body mass index and
HbA1c. The mean (±SD) time to diabetic ketoacidosis resolution in the computer-based group was significantly
lower than the paper-based group (p=0.02). The number of patients in the paper-based group
who developed severe hypoglycemia (<50 mg/dl) was significantly higher 8% vs 1%; p<0.0001.

Conclusions::
Our analyses demonstrate statistically significant decreases in time to DKA resolution and
hypoglycemic events in DKA patients who were managed using a computer-based insulin infusion algorithm
providing a more effective and safer option when compared to paper-based insulin infusion.
PNN and BP Neural Network Fault Diagnosis Research on Electronic Accelerator Pedal Detection
Authors: Jiang Yuxiu , Zhao Xiaohuan 
Published: September 2019

Background:
The working state of electronic accelerator pedal directly affects the safety
of vehicles and drivers. Effective fault detection and judgment for the working state of the accelerator
pedal can prevent accidents.

Methods:
Aiming at different working conditions of electronic accelerator pedal, this paper used
PNN and BP diagnosis model to detect the state of electronic accelerator pedal according to the
principle and characteristics of PNN and BP neural network. The fault diagnosis test experiment of
electronic accelerator pedal was carried out to get the data acquisition.

Results:
After the patents for electronic accelerator pedals are queried and used, the first measured
voltage, the upper limit of first voltage, the first voltage lower limit, the second measured voltage,
the upper limit of second voltage and the second voltage lower limit are tested to build up the data
samples. Then the PNN and BP fault diagnosis models of electronic accelerator pedal are established.
Six fault samples are defined through the design of electronic accelerator pedal fault classifier
and the fault diagnosis processes are executed to test.

Conclusion:
The fault diagnosis results were analyzed and the comparisons between the PNN and
the BP research results show that BP neural network is an effective method for fault detection of
electronic throttle pedal, which is obviously superior to PNN neural network based on the experiment
data.
Study of the Fluorescence based Applications of Water Soluble (N, P) Doped Carbon Dots Synthesized via Microwave Assisted Green Pyrolysis
Authors: Singh Rajshree , Singh Shikha , Senapati Sudipta , Mitra Kheyanath , Singh Jaydeep , Gupta Susanta K.S. , Misra Nira , Maiti Pralay , Ray Biswajit 
Published: September 2019

Background:Water soluble nitrogen and phosphorus doped carbon dots (CD) have been synthesized using citric acid, tris(2-aminoethyl)amine and orthophosphoric acid via one step microwave assisted pyrolytic method.Methods:The CD synthesized has been characterized using FTIR, UV-Vis, fluorescence spectroscopy and EDAX coupled with SEM techniques.Results:SEM study has shown the formation of nanosized CD with an average size of ~18 nm. Elemental analysis via EDAX has confirmed successful incorporation of nitrogen (30.8% wt) and phosphorus (5.7% wt) atoms in it. The steady state and 3D fluorescence spectroscopic studies have shown its efficient fluorescence emission with emission maxima in the region of ~450 nm. It has shown efficient “turn off” fluorescence behaviour towards transition metal ions like Fe2+ and Co2+ ions and toxic nitrophenolic compounds like p-nitrophenol and picric acid. Its efficient interaction with BSA has been revealed in terms of fluorescence quenching of BSA by steady state, synchronous and 3D fluorescence spectroscopy. It has shown very good in vitro biocompatibility and enhanced cell adhesion properties towards NIH 3T3 fibroblast cells. Moreover, fluorescence microscopy has shown significant uptake of CD by the tested cell line.Conclusion:Such bio-compatible nitrogen and phosphorous doped CD can be potentially useful to estimate metal ions, p-nitrophenol and picric acid using fluorescence spectroscopy and for fluorescence based bio-imaging.
Website Quality Analytics Using Metaheuristic Based Optimization
Authors: Kumar Akshi , Arora Anshika 
Published: September 2019

Background::
Studies are indicative of the fact that high-quality websites get better rankings
on the search engines. A good website is the one which provides reliable content, has good design
and user interface and can address global audience. But the end-users struggle with the predicament
of selecting qualitative websites. Although “Quality” is fairly a subjective term, there is an
obvious need for a useful and valid model which evaluates the quality attributes of a website. “A
Website quality model essentially consists of a set of criteria used to determine if a website reaches
certain levels of fineness”.

Objective::
The quality of a website must be assured in terms of technicality, the accuracy of information,
response time, design of website, ease of use, and many more. The aim is to identify features of
a website that determines its quality and build an automatic website quality prediction model.

Method::
We conduct an empirical study on 700 websites and run 6 baseline classifiers to categorize
websites into good, average and poor using quality attributes. Subsequently, metaheuristic-based algorithms
(Particle Swarm Optimization, Elephant Search Algorithm and Wolf Search Algorithm) for
optimal feature selection have been implemented to get an optimal subset of quality attributes that is
able to predict the quality of websites more accurately.

Result::
The study confirms that the proposed implementation of metaheuristics for feature selection
in website quality classification improves the performance of the supervised learning algorithms. An
average 12.74% improvement in accuracy was observed using the features selected by Particle
Swarm Optimization, 5.56% average improvement in accuracy using Elephant Search Algorithm for
feature selection while an average improvement of 5.77% was observed using Wolf Search Algorithm
for feature selection.

Conclusion::
The study validates that Particle Swarm Optimization for feature selection in website
quality analytics task outperforms Wolf Search Algorithm and Elephant Search Algorithm.
Performance Analysis of TCP Variants Using AODV and DSDV Routing Protocols in MANETs
Authors: Singh Rajnesh , Singh Neeta , Dinker Aarti Gautam 
Published: September 2019

Background:
TCP is the most reliable transport layer protocol that provides reliable data
delivery from source to destination node. The background of TCP suggests that it works well in
wired networks but it is assumed that TCP is less preferred for ad-hoc networks. However, for application
in ad-hoc networks, TCP can be modified to improve its performance. Various researchers
have proposed improvised variants of TCP by only one or two measures.

Objective:
These one or two measures do not seem to be sufficient for proper analysis of improvised
version of TCP. Therefore, in this paper, our objective is to evaluate the performance of different
TCP variants and their results are investigated with DSDV and AODV routing protocols.

Methods:
Our methodology includes the analysis of various performance measures such as
throughput, delay, packet drop, packet delivery ratio and number of acknowledgements. The simulation
results are carried out by varying number of nodes in network simulator tool NS2.

Results:
It is observed in results that TCP Newreno achieved higher throughput and packet delivery
ratio with both AODV and DSDV routing protocols. Whereas TCP Vegas achieved minimum
delay and packet loss with both DSDV and AODV protocol. However TCP sack achieved minimum
acknowledgment with both AODV and DSDV routing protocols.

Conclusion:
The comparison of all these TCP variants helps in drawing conclusion that, TCP
Newreno provides better performance with both AODV and DSDV protocols.
Comparative Study of Cryptography for Cloud Computing for Data Security
Authors: Mathur Priya , Gupta Amit K. , Vashishtha Prateek 
Published: September 2019

Background:
Cloud computing is an emerging technique by which anyone can access the
applications as utilities over the internet. Cloud computing is the technology which comprises of all
the characteristics of the technologies like distributed computing, grid computing, and ubiquitous
computing. Cloud computing allows everyone to create, to configure as well as to customize the
business applications online. So the cloud computing techniques need security of information communicated
between the sending and receiving entities.

Objective:
The secure data storage disadvantage of Cloud computing can be resolve up to some extent
with the help of the implementation of the cryptographic algorithms during the storing and accessing
of the data from the cloud servers.

Method:
In this paper we have compared four different recently implemented Cryptographic Algorithms
which are Modified RSA (SRNN), Elliptic Curve Cryptography Algorithm, Client Side Encryption
Technique and Hybrid Encryption Technique.

Conclusion:
Client Side Encryption Technique and Hybrid Encryption Technique are better than
Modified RSA and Elliptic Curve Cryptography because Client Side Encryption Technique has an
advantage that in this data is encrypted prior to upload the data on the cloud i.e. encryption at the client
side which provides an additional layer of security to the data on the cloud. On the other hand,
Hybrid Encryption Technique has an advantage that it uses the rapidity of the processing time of
Symmetric Key Cryptography and robustness in key length of the Asymmetric Key Cryptography.
Dual Data Selection Using Multi-Objective Micro-CHC
Authors: Rathee Seema , Ratnoo Saroj 
Published: September 2019

Objective:
Redundant and superfluous features or instances reduce the efficiency and efficacy
of data mining algorithms. Hence, selecting relevant and significant features and instances is
very important for a data mining process to be able to discern some meaning information. Dual selection
deals with the problem of generating a small subset of non-redundant features as well as instances
simultaneously from a large and noisy data set. The two main objectives for dual selection
are to maximize the classification accuracy and to bring as much as possible data reduction. The two
objectives, accuracy and data reduction rate, are conflicting because maximizing the data reduction
rate generally results in a lower accuracy rate and vice versa. These objectives are mutually dependent
and must be tackled simultaneously. Therefore, the problem of dual data selection ought to be
naturally approached with multi-objective optimization techniques which give a set of nondominated
solutions instead of a single best solution. The problem of dual selection has exhaustively
large search space and has been addressed through single and Multi-Objective Genetic Algorithms
(MOGAs). More often, evolutionary approaches may it be single or multi-objective work with large
population sizes and take unacceptably long execution times due to computationally expensive fitness
functions. These approaches also suffer from premature convergence.

Methods:
This paper proposes a hybrid Multi-Objective Micro-CHC (MO-Micro-CHC) to address
the task of dual selection. The suggested approach uses a population of only a few individuals and
elitism advised in Micro Genetic Algorithm (Micro-GA), Heterogeneous Uniform Recombination
(HUX) and Cataclysmic mutation inspired by CHC, and non-dominated sorting of NSGA-II- a most
popular and widely implemented multi-objective genetic algorithm.

Results:
We have conducted extensive experimentation using numerous datasets from the UCI data
repository. Analysis of results approves that Mo-Micro-CHC achieves high accuracy and competing
reduction rate in comparison to similar approaches. In addition, it takes far less execution time as
compared to many of its counterparts.