bluuebunny/crossref_metadata_2025_split huggingface dataset:
OphthatomeTM: An integrated knowledgebase of ophthalmic diseases for translating vision research into the clinic
Authors: Raj Praveen , Tejwani Sushma , Sudha Dandayudhapani , B Muthu Narayanan , Thangapandi Chandrasekar , Das Sankar , J Somasekar , Mangalapudi Susmithasane , Kumar Durgesh , Pindipappanahalli Narendra , Shetty Rohit , Ghosh Arkashubra , Kumaramanickavel Govindasamy , Chaudhuri Amitabha , Nagaswamy Soumittra 
Published: October 2020

Abstract
Abstract
Background: Medical big data analytics has revolutionized the human healthcare system by introducing processes that facilitate rationale clinical decision making, predictive or prognostic modelling of the disease progression and management, disease surveillance, overall impact on public health and research. Although, the electronic medical records (EMR) system is the digital storehouse of rich medical data of a large patient cohort collected over many years, the data lack sufficient structure to be of clinical value for applying deep learning methods and advanced analytics to improve disease management at an individual patient level or for the discipline in general. Ophthatome TM captures data contained in retrospective electronic medical records between September 2012 and January 2018 to facilitate translational vision research through a knowledgebase of ophthalmic diseases.
Methods: The electronic medical records data from Narayana Nethralaya ophthalmic hospital recorded in the MS-SQL database was mapped and programmatically transferred to MySQL. The captured data was manually curated to preserve data integrity and accuracy. The data was stored in MySQL database management system for ease of visualization, advanced search functions and other knowledgebase applications.
Results: Ophthatome TM is a comprehensive and accurate knowledgebase of ophthalmic diseases containing curated clinical, treatment and imaging data of 581,466 ophthalmic subjects from the Indian population, recorded between September 2012 and January 2018. Ophthatome TM provides filters and Boolean searches with operators and modifiers that allow selection of specific cohorts covering 524 distinct ophthalmic disease types and 1800 disease sub-types across 35 different anatomical regions of the eye. The availability of longitudinal data for about 300,000 subjects provides additional opportunity to perform clinical research on disease progression and management including drug responses and management outcomes. The knowledgebase captures ophthalmic diseases in a genetically diverse population providing opportunity to study genetic and environmental factors contributing to or influencing ophthalmic diseases.
Conclusion: Ophthatome TM will accelerate clinical, genomic, pharmacogenomic and advanced translational research in ophthalmology and vision sciences.
Key words: Ophthatome, knowledge base, electronic medical records, curated clinical data, defined cohort, vision sciences
Sexual Function and Metabolic/Hormonal Changes in Women Using Long-Term Hormonal and Non-Hormonal Contraceptives: A pilot study.
Authors: Moreira Igor Fernando de aquino , Bianchini Maria Passos , Moreira Gabrielle Rodrigues Campos , Almeida Alessandra Maciel , Rezende Bruno Almeida 
Published: October 2020

Abstract
Background: Female sexual dysfunction is a common condition that negatively impacts the emotional health and quality of life of the affected individuals. Long-acting reversible contraceptives (LARCs) are becoming increasingly popular due to their effectiveness and convenience. LARCs can be hormonal (etonogestrel releasing implant—ENG and Levonorgestrel intrauterine system—LNG) or non-hormonal (copper intrauterine device—CuIUD and copper-silver intrauterine device—SIUD). There are very few studies that assess the influence on LARCS on sexual function are lacking. This study aimed to assess changes in sexual function as well as metabolic and hormonal parameters in women after implantation with LARCs.
Methods: In this prospective cohort study, we assessed 80 women who visited the Military Police Hospital in Brazil for LARCs placement. The study participants were divided into 4 groups according to the type of LARC received: ENG n=17; LNG n=22, CuIUD n=18 and SIUD n=23. The four groups were evaluated twice (prior to LARC placement and approximately 3 months later) for sexual function, using the Female Sexual Function Index (FSFI) and Female Sexual Quotient (QS-F) questionnaires. Metabolic and hormonal parameters were also assessed using blood tests.
Results: ENG worsened sexual function according to FSFI and QS-F, across all domains. A decrease in sex hormone-binding globulin (SHBG) between stages was observed for all groups. We observed an improvement in sexual function for non-hormonal LARCs, specially SIUD. However this improvement was not statistically significant.
Conclusion: The use of non-hormonal LARCS improved sexual function. Etonogestrel implants, had a negative influence on sexual function, probably by blocking ovarian function, and thus reducing the production of androgens and estrogens.
Successful outcome of disseminated candida tropicalis osteomyelitis on remission induction for childhood Philadelphia chromosome–positive acute lymphoblastic leukemia
Authors: Xie Lichun , Long Qingling , Zhou Guichi , Liu Si-xi , Wen Feiqiu 
Published: October 2020

Abstract
Invasive fungal infection (IFI) is one of the most challenging complications in children with acute lymphoblastic leukemia (ALL) treatment, but acute fungal osteomyelitis (OM) is rarely encountered. Here, we describe a case of Candida tropicalis osteomyelitis in a 10-year-old patient with Philadelphia chromosome (Ph)–positive ALL. He was on remission induction therapy at the time of neutropenia, and abscess developed in the right arm. The blood and bone cultures were positive for Candida tropicalis. Antibiotics and anti-fungal were started. A magnetic resonance of the arm reveal in intraosseous abscess, suggestive of OM. Surgical irrigation and debridement of the bone were performed immediately. The patient was effectively treated with antifungal therapy and ALL treatment. Now he is full recovery, having complete clinical remission but with sequelae visible by MRI. He is taking oral posaconazole for consolidation until disappearance of the lesion shadows on MRI and having subsequent cycles of chemotherapy in parallel. The recommended treatment for candida osteomyelitis in Ph-positive ALL patients is fungicidal agent combined with surgery and modification chemotherapy with dasatinib. Using combined modalities of treatment seem to be crucial in the successful management of Ph-positive ALL.
A Survey on Generative Adversarial Networks for imbalance problems in computer vision tasks
Authors: Sampath Vignesh , Maurtua Iñaki , Martín Juan José Aguilar , Gutierrez Aitor 
Published: October 2020

Abstract
Any computer vision application development starts off by acquiring images and data, then preprocessing and pattern recognition steps to perform a task. When the acquired images are highly imbalanced and not adequate, the desired task may not be achievable. Unfortunately, the occurrence of imbalance problems in acquired image datasets in certain complex real-world problems such as anomaly detection, emotion recognition, medical image analysis, fraud detection, metallic surface defect detection, disaster prediction, etc., are inevitable. The performance of computer vision algorithms can significantly deteriorate when the training dataset is imbalanced. In recent years, Generative Adversarial Networks (GANs) have gained immense attention by researchers across a variety of application domains due to their capability to model complex real-world image data. It is particularly important that GANs can not only be used to generate synthetic images, but also its fascinating adversarial learning idea showed good potential in restoring balance in imbalanced datasets. In this paper, we examine the most recent developments of GANs based techniques for addressing imbalance problems in image data. The real-world challenges and implementations of synthetic image generation based on GANs are extensively covered in this survey. Our survey first introduces various imbalance problems in computer vision tasks and its existing solutions, and then examine key concepts such as deep generative image models and GANs. After that, we propose a taxonomy to summarize GANs based techniques for addressing imbalance problems in computer vision tasks into three major categories: 1. Image level imbalances in classification, 2. object level imbalances in object detection and 3. pixel level imbalances in segmentation tasks. We elaborate the imbalance problems of each group, and further provide GANs based solutions in each group. Readers will understand how GANs based techniques can handle the problem of imbalances and boost performance of the computer vision algorithms.
Ex vivo porcine model study on the treatment outcomes of scissor-type knife versus needle-type knife in endoscopic submucosal dissection performed by trainees
Authors: Ichijima Ryoji , Esaki Mitsuru , Yamakawa Shun , Minoda Yosuke , Suzuki Sho , Kusano Chika , Ikehara Hisatomo , Gotoda Takuji 
Published: October 2020

Abstract
Back ground
Endoscopic submucosal dissection (ESD) for gastrointestinal neoplasms can be technically difficult for trainee endoscopists. Presently, there is no consensus for trainees to select the endo-knife type in ESD. Therefore, we conducted a comparison study of treatment outcomes between scissors-type and needle-type knives in ESD performed by trainees in an ex vivo porcine model.
Methods
This study was conducted on trainee endoscopists who participated in ESD hands-on seminars held in August 2018 and September 2019 . A total of 22 trainees from 13 institutions were divided into two groups according to their endoscopic experience. Under expert supervision, each trainee performed two ESDs in porcine models, namely, scissor-type knife (ESD-S) and needle-type knife (ESD-N). The efficacy and safety, including the procedure time and rates of self-completion, en bloc resection, and complications, were compared between ESD-S and ESD-N. In subgroup analysis, we also investigated the predictors associated with the difficulty of ESD for trainees using multivariate logistic regression analysis .
Results
Eight trainees had an experience of over 1,000 endoscopies (senior trainee: S-Trainee), whereas the others had an experience of less than 1,000 endoscopies (junior trainee: J-Trainee). Among the S-Trainees, no significant differences were observed in any treatment outcome between ESD-S and ESD-N. Among the J-Trainees, the total procedure and mucosal incision times were significantly shorter in ESD-S than in ESD-N [total procedure time: 16.5 min (range: 10.0–31.0) vs. 22.3 min (range: 10.0–38.0), P = 0.018; circumferential incision time: 10.0 min (range: 6-16) vs. 17.0 min (range: 5.0–31.5); P = 0.019]. Regarding complications, muscular injury occurred in two patients during ESD-N performed by J-Trainees; however, no muscular injury occurred during ESD-S. In subgroup analysis, ESD-N was an independent predictive factor of difficult ESD (odds ratio 5.28, 95% confidence interval 1.25 –22.30; p = 0.024).
Conclusions
This study revealed that trainees, particularly those who have experienced less than 1,000 endoscopies, should opt for the scissor-type knife to perform ESD.
Comparison of modified Mohr–Coulomb model and Bai–Wierzbicki model for constructing 3D ductile fracture envelope of AA6063
Authors: Gao Jianye , He Tao , Huo Yuanming , Song Miao , Yao Tingting , Yang Wanbo 
Published: October 2020

Abstract
The 3D ductile fracture envelope of AA6063-T6 were developed to predict and prevent its fracture. Smooth round bar tension tests were performed to characterize the flow stress, and a series of experiments were conducted to characterize the ductile fracture firstly, such as notched round bar tension tests, compression tests and torsion tests. These tests cover a wide range of stress triaxiality (ST) and Lode parameter (LP) to calibrate the ductile fracture criterion. Plasticity modeling was performed, and the predicted results were compared with corresponding experimental data to verify the plasticity model after these experiments. Then the relationship between ductile fracture strain and ST with LP was constructed using the modified Mohr–Coulomb (MMC) model and Bai-Wierzbicki (BW) model to develop the 3D ductile fracture envelope. Finally, two ductile damage models were proposed based on 3D fracture envolope of AA6063. Through the comparison of the two models, it was found that BW model had better fitting effect, and the sum of squares of residual error of BW model was 0.9901. The two models had relatively large errors in predicting the fracture strain of SRB tensile test and torsion test, but both of the predicting error of both two models were within the acceptable range of 15%. In the process of finite element simulation, the evolution process of ductile fracture can be well simulated by the two models. However, BW model can predict the location of fracture more accurately than MMC model.
An SDF-1α gene-activated collagen scaffold restores pro-angiogenic wound healing features in human diabetic adipose-derived stem cells
Authors: Laiva Ashang Luwang , O’Brien Fergal J. , Keogh Michael B. 
Published: October 2020

Abstract
Background

Diabetic foot ulcer is one of the leading causes of leg amputation and mortality in diabetic patients. Autologous stem cell therapy holds some potential to be a solution to this problem, however diabetic stem cells are relatively dysfunctional and restrictive in their wound healing abilities. This study sought to explore if a novel collagen-chondroitin sulfate (coll-CS) scaffold functionalized with polyplex nanoparticles carrying the gene encoding for stromal-derived factor-1 alpha (SDF-1α gene-activated scaffold) can enhance the regenerative functionality of human diabetic adipose-derived stem cells (ADSCs).

Methods

Gene-activated scaffolds were first prepared by soak-loading polyethyleneimine nanoparticles carrying the plasmid encoding for SDF-1α gene into a freeze-dried coll-CS scaffold. ADSCs from healthy and diabetic donors were then seeded on the gene-activated scaffold. The response of the ADSCs in the gene-activated scaffold was then compared against those of the healthy ADSCs cultured on the gene-free scaffold over 2 weeks period. Functional response in the ADSCs such as the activation of SDF-1α mediated signaling, production of bioactive factors, pro-angiogenic bioactivity of secreted factors, matrix deposition and remodeling was determined using proteome profiling, Matrigel assay, qRT-PCR and immunofluorescence.

Results

Overall, we found that SDF-1α gene-activated scaffold could restore pro-angiogenic regenerative response in the human diabetic ADSCs similar to the healthy ADSCs on the gene-free scaffold. Gene and protein expression analysis revealed that the SDF-1α gene-activated scaffold induced the overexpression of SDF-1α in diabetic ADSCs and engaged the receptor CXCR7, causing downstream signaling of β-arrestin as effectively as the transfected healthy ADSCs. The transfected diabetic ADSCs also effectively stimulated angiogenesis in endothelial cells while undergoing matrix remodeling characterized by reduction in deposition of fibronectin matrix and increase in the expression of basement membrane protein collagen IV. The SDF-1α gene-activated scaffold also induced a controlled pro- healing response in the healthy ADSCs by disabling the signaling of early developmental factors while promoting the expression of tissue remodeling components.

Conclusion

We show that the SDF-1α gene-activated scaffold can overcome the deficiencies associated with diabetic ADSCs paving the way for autologous patient stem cell therapies in combination with novel biomaterials to treat diabetic foot ulcers.
Impact of problem formulations, pipe selection methods, and optimization algorithms on the rehabilitation of water distribution systems
Authors: Wang Qi , Huang Wen , Yang Xueqiang , Wang Libing , Wang Zhihong , Wang Yuanjian 
Published: October 2020

AbstractGiven the continuous aging of pipeline infrastructure buried underground, water utilities need to make a strategic plan on how to maintain the entire water distribution systems (WDSs) to ensure the required standard of supply. This paper investigates the nexus of three key factors that have a significant impact on the decision-making process of the rehabilitation plan for WDSs. The factors considered include the problem formulations, the pipe selection methods for identifying critical components of WDSs, and the multi-objective evolutionary algorithms (MOEAs). The nexus was revealed by considering all the combinations of two variants for each factor. The optimal rehabilitation problem of the Exeter network was used as a case study. Results exhibit that the problem formulation determined the range of Pareto fronts essentially, which should give the highest priority in the decision-making process. The pipe selection method played a secondary role, mainly affecting the shape of Pareto fronts. Optimization algorithms also had a considerable impact on the optimality of solutions, subject to their characteristics and parameter settings. This paper also highlights that breakthroughs need to focus on these key factors to facilitate a more cost-effective solution to the rehabilitation of large WDSs.
GPCC catalyzed hydrogen peroxide for decolorization of C.I. Reactive Red 24 from simulated dyeing wastewater
Authors: Wang Jie , Wang Xueyan 
Published: October 2020

Abstract
A kind of gelatin protein copper complex (GPCC for short) was synthesized by us. GPCC acting as catalyst was applied to catalyzed hydrogen peroxide for decolorization of C.I. Reactive Red 24 from simulated dyeing wastewater. The influence of catalyzed hydrogen peroxide by GPCC on the decolorization of C.I. Reactive Red 24 from simulated dyeing wastewater was discussed. The optimum decolorization technology condition was optimized. And the effect of salt on decolorization of C.I. Reactive Red 24 in this catalytic system was also investigated. The results showed that hydrogen peroxide can be catalyzed by GPCC. In the catalytic system, the structure of C.I. Reactive Red 24 can be degraded and a high decolorization rate can be obtained in a wide pH range. In addition, the decolorization percentage and decolorization rate will be further improved when salt is present in the catalytic system.
Inovasi media pembelajaran game edukasi berbasis visual basic pada mata pelajaran pendidikan kewarganegaraan
Authors: Pratiwi Emy Yunita Rahma , Siswanto Muhammad Bambang Edi 
Published: October 2020

Pada umumnya peserta didik merasa enggan untuk mempelajari pendidikan kewarganegaraan. Beberapa problematikanya adalah pembelajaran pendidikan kewarganegaraan yang cenderung tidak menarik, membosankan, kekeliruan mahasiswa dalam memaknai dan memahami nilai-nilai yang terkandung dalam pendidikan kewarganegaraan, terbatasnya waktu yang digunakan untuk membuat media pembelajaran, kurangnya keterampilan yang dimiliki dalam membuat media pembelajaran berbasis TIK, dan tidak tersedianya biaya. Oleh karena itu, perlu adanya upaya untuk meningkatkan pembelajaran pendidikan kewarga-negaraan. Tujuan penelitian ini adalah untuk menghasilkan suatu media yang siap untuk diisi konten dan skenario penggunaanya, sehingga menjadi media yang menarik dan dapat meningkatkan motivasi belajar mahasiswa. Metode penelitian ini berbentuk kuantitatif dan kualitatif. Data kuantitatif data yang diperoleh dengan menggunakan kuesioner atau angket, sedangkan data kualitatif berupa: 1.) Data awal mengenai hasil observasi dan wawancara dengan dosen mata kuliah pendidikan kewarganegaraan terhadap pelaksanaan pembelajaran di kelas; dan 2.) Data komentar dan saran dari para validator. Target capaian dalam penelitian ini adalah untuk menghasilkan produk berupa media pembelajaran game edukasi dengan Microsoft Power Point berbasis Visual Basic pada mata pelajaran pendidikan kewarganegaraan yang digunakan untuk meningkatkan proses pem-belajaran maupun kompetensi peserta didik. AbstractIn general, students feel reluctant to study civic education. Some of the problems are civic education learning which tends to be unattractive, boring, student mistakes in interpreting and understanding the values contained in civic education, limited time spent making learning media, lack of skills in making ICT-based learning media, unavailability cost. Therefore, there is a need for efforts to improve civic education learning. The purpose of this research is to produce a media that is ready to be filled with content and scenarios for its use so that it becomes an attractive medium and can increase student motivation to learn. This research method is quantitative and qualitative. Quantitative data are data obtained using a questionnaire/questionnaire. While the qualitative data is in the form of 1) preliminary data regarding the results of observations and interviews with lecturers of civic education courses on the implementation of learning in class, 2) data on comments and suggestions from the validators. The target of the achievement is to produce a product in the form of learning media for educational games with Visual Basic-Based Microsoft PowerPoints in citizenship education subjects that are used to improve the learning process and the competence of students.
Use of Patient-Reported Symptoms from an Online Symptom Tracking Tool for Dementia Severity Staging: Development and Validation of a Machine Learning Approach
Authors: Shehzad Aaqib , Rockwood Kenneth , Stanley Justin , Dunn Taylor , Howlett Susan E 
Published: October 2020

Background
SymptomGuide Dementia (DGI Clinical Inc) is a publicly available online symptom tracking tool to support caregivers of persons living with dementia. The value of such data are enhanced when the specific dementia stage is identified.

Objective
We aimed to develop a supervised machine learning algorithm to classify dementia stages based on tracked symptoms.

Methods
We employed clinical data from 717 people from 3 sources: (1) a memory clinic; (2) long-term care; and (3) an open-label trial of donepezil in vascular and mixed dementia (VASPECT). Symptoms were captured with SymptomGuide Dementia. A clinician classified participants into 4 groups using either the Functional Assessment Staging Test or the Global Deterioration Scale as mild cognitive impairment, mild dementia, moderate dementia, or severe dementia. Individualized symptom profiles from the pooled data were used to train machine learning models to predict dementia severity. Models trained with 6 different machine learning algorithms were compared using nested cross-validation to identify the best performing model. Model performance was assessed using measures of balanced accuracy, precision, recall, Cohen κ, area under the receiver operating characteristic curve (AUROC), and area under the precision-recall curve (AUPRC). The best performing algorithm was used to train a model optimized for balanced accuracy.

Results
The study population was mostly female (424/717, 59.1%), older adults (mean 77.3 years, SD 10.6, range 40-100) with mild to moderate dementia (332/717, 46.3%). Age, duration of symptoms, 37 unique dementia symptoms, and 10 symptom-derived variables were used to distinguish dementia stages. A model trained with a support vector machine learning algorithm using a one-versus-rest approach showed the best performance. The correct dementia stage was identified with 83% balanced accuracy (Cohen κ=0.81, AUPRC 0.91, AUROC 0.96). The best performance was seen when classifying severe dementia (AUROC 0.99).

Conclusions
A supervised machine learning algorithm exhibited excellent performance in identifying dementia stages based on dementia symptoms reported in an online environment. This novel dementia staging algorithm can be used to describe dementia stage based on user-reported symptoms. This type of symptom recording offers real-world data that reflect important symptoms in people with dementia.