bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adrenal Venous Sampling With or Without Adrenocorticotropic Hormone Stimulation: A Meta-Analysis
Authors: Laurent Irakoze , Astère Manirakiza , Zheng Fengfan , Chen Xiangjun , Yang Jun , Cheng Qingfeng , Li Qifu 
Published: November 2018

Abstract

Context
Adrenal venous sampling (AVS), with or without adrenocorticotropic hormone (ACTH) stimulation, is the test of choice to identify patients with a surgically curable subtype of primary aldosteronism (PA). Whether AVS with ACTH stimulation is more effective than AVS without ACTH stimulation remains controversial.

Objective
To compare the effectiveness of AVS with ACTH stimulation and AVS without ACTH stimulation in patients with PA.

Design
The Cochrane Library, PubMed, Embase, and Web of Science databases were searched to identify relevant articles. All cohort studies comparing the two techniques (AVS with ACTH stimulation and AVS without ACTH stimulation in a patient with PA) were included in the analysis.

Results
A total of 14 studies met the inclusion criteria, and they were analyzed. AVS with ACTH stimulation did not significantly reduce the number of incorrect lateralization more than AVS without ACTH stimulation in patients with PA (OR: 0.76; 95% CI: 0.36, 1.59; P = 0.47). AVS with ACTH stimulation significantly reduced the number of unsuccessful cannulations of both adrenal veins more than AVS without ACTH stimulation in patients with PA (OR: 0.26; 95% CI: 0.17, 0.40; P &lt; 0.00001). For subgroup analyses, it also significantly reduced the number of unsuccessful cannulations of left adrenal vein and right adrenal vein (OR: 0.14, 95% CI: 0.06, 0.33, P &lt; 0.00001; and OR: 0.30, 95% CI: 0.12, 0.71, P = 0.007, respectively).

Conclusion
AVS with ACTH stimulation can significantly reduce the number of unsuccessful cannulations, without significantly reducing the number of incorrect lateralization. Further studies are still needed to verify these findings.
Photoplethysmography Detection of Overreaching
Authors: BOURDILLON NICOLAS , NILCHIAN MASIH , MILLET GRÉGOIRE P. 
Published: November 2018

ABSTRACT

Introduction
Detecting the onset of functional overreaching (FOR) or nonfunctional overreaching in endurance athletes is of prior importance to ensure reactive amendment of the scheduled training program. The objective of this study was to assess photoplethysmography (PPG) in overloaded athletes and test whether 1) it would be affected differently in functional overreached (FOR) or nonoverreached acutely fatigued (AF) athletes and 2) specific PPG characteristics would allow for timely distinction of FOR and AF.

Methods
Fifteen athletes performed 2-wk baseline training followed by 3-wk overload (+45%; OVL) and 2-wk recovery (−20%). Three-thousand-meter time-trial running was used to assess performance at the end of baseline, OVL, and recovery and distinguish FOR and AF. PPG was recorded overnight using a wearable sensor, every third night. Overnight means and variances of systolic, diastolic, and dicrotic amplitudes and times as well as systolic and diastolic slopes were used to discriminate FOR and AF athletes.

Results
Performance was decreased in FOR and improved in AF at the end of OVL. Diastolic time was greater in AF than FOR, whereas systolic slope was smaller in AF than in FOR during OVL. The variances of systolic, diastolic, dicrotic amplitudes, systolic, diastolic slopes, and pulse areas were smaller in AF compared with FOR in the last week of OVL.

Conclusion
PPG is an efficient tool for the detection of overreaching because it distinguished FOR and AF athletes during OVL (prior performance decrement). This fast-responding method would therefore allow for adjusting the daily training content to prevent nonfunctional overreaching.
Effect of Clinical Pilates training on the fear of movement in patients with ankylosing spondylitis
Authors: Oskay Deran , Tuna Zeynep , Baglan-Yentur Songül 
Published: November 2018

Background/Aims: Exercise training has been shown to be beneficial in reducing symptoms in patients with ankylosing spondilitis. However, exercise effect on fear and avoidance of movement has not been assessed. The aim of this study was to evaluate the effect of Pilates training on kinesiophobia, disease activity, functional status and quality of life in patients with ankylosing spondilitis. Methods: A total of 21 patients with ankylosing spondilitis with stable medication participated in the study. Tampa Scale for Kinesiophobia, Bath Ankylosing Spondilitis Disease Activity Index, Bath Ankylosing Spondilitis Functional Index, ankylosing spondilitis Quality of Life Questionnaire and Beck Depression Inventory were completed by patients before and after a 6-week modified Pilates training programme. Findings: The patients were 41.6 ± 11.8 years old and the mean disease duration was 68 ± 87months. Mobility, disease acitivity and functional scores improved with exercise training (P<0.05). Moreover, quality of life, depression and kinesiophobia levels also showed significant improvement (P<0.05). Conclusions: The results of this study showed that 6-week supervised modified Pilates training programme improved clinical symptoms in patients with Aankylosing spondilitis. Moreover, patients benefited from this exercise method regarding quality of life, depression and fear of movement (kinesiophobia) considerably.
Staff experiences of working with patients with prolonged disorders of consciousness: a focus group analysis
Authors: Logeswaran Sophini , Papps Benjamin , Turner-Stokes Lynne 
Published: November 2018

Background/Aims: UK national clinical guidelines recommend assessment of patients in prolonged disorders of consciousness in specialist centres. Working in these centres can be challenging, but little is currently published about what staff experience or how best to support them. We explored the views of health care professionals working with prolonged disorders of consciousness patients in one specialist rehabilitation unit. Methods: Six focus groups were run with allied health professionals, medical and nursing staff in discipline-specific groups to explore the rewards and challenges of working with patients in prolonged disorders of consciousness, and what staff felt they needed to assist them. Transcribed data were analysed using thematic analysis. Findings: Five positive themes emerged: seeing change, supporting families, quality of the team and clinical input, work complexity and its personal impact. Three negative themes were identified: dealing with death and ‘living death’, dealing with family expectations and distress, and the negative professional and personal impact on staff. In terms of what would assist staff, three themes emerged: greater support with family communication, additional prolonged disorders of consciousness-specific training and further development of assessments of awareness. Conclusions: Staff recommendations on what would assist them could be used to inform the development of high-quality approaches to assessment and care in prolonged disorders of consciousness.
Antimicrobial assessment of a chitosan microfibre dressing: a natural antimicrobial
Authors: Edwards-Jones Val 
Published: November 2018

Objective: Chitosan is a natural biopolymer and is the main structural component of the cuticles of crustaceans, insects and molluscs and the cell walls of certain fungi. It is abundant in nature and is naturally antimicrobial. A natural fibre has been created with chitosan and is being used as a wound dressing, namely Kytocel. It is an absorbent fibre dressing that is claimed to be biodegradable and biocompatible. This study was undertaken to assess the antimicrobial properties of the microfibre wound dressing using a variety of methods commonly used to assess other antimicrobial dressings. Method: The zone of inhibition (ZOI) assay, challenge test (log reduction), time-to-kill and an in vitro wound model were all used in this report. Representative Gram-positive and Gram-negative bacteria were used and one yeast, Candida albicans. Results: The ZoI test showed no observable zones around the dressing but killed the organisms underneath the dressing. There was a >3 log reduction of Staphylococcus aureus and Escherichia coli within two hours and >3 log reduction against Pseudomonas aeruginosa and Candida albicans between four and 24 hours in the challenge test. In the wound model, there was a 2 log reduction of Escherichia coli within the wound model and in the sponge and culture medium below the dressing. Conclusion: The chitosan microfibre wound dressing gives wound care an additional dressing to use to help prevent and manage bioburden and wound infection.
Outcome of subtrochanteric femur resection in patients with spinal cord injuries
Authors: Ohlmeier Malte , Bode Annika , Suero Eduardo M. , Grasmücke Dennis , Aach Mirko , Meindl Renate , Schildhauer Thomas A. , Citak Mustafa 
Published: November 2018

Objective: To analyse the clinical outcome of subtrochanteric femur resection in patients with infected hip joints caused by pressure ulcers (PUs) in patients following spinal cord injury (SCI). Method: A retrospective cohort study, carried out between January 2004 and December 2015. Only patients receiving a subtrochanteric femur resection were included. SCI patients were treated for a hip joint infection caused by a PU. Primary outcome measures were to work out the revision rates and the rate of heterotopic ossification occurrence. Results: At the time of admission, 37 out of the 56 participating patients (66.1%) showed a category IV PU with the ischium being most commonly affected (n=25, 44.6%). The subtrochanteric femur resection was combined either with a direct wound closure (n=29; 51.8%) or a myocutaneous flap (n=27; 48.2%). The mean number of surgeries was 2.6 (1–4; SD=1.6) and 21 patients were successfully treated by a single surgery. Of the patients, 28 had wound healing disorders (50%) and required a revision surgery, and 24 (42.9%) developed a postoperative heterotopic ossification. Conclusion: Hip joint infection caused by PUs can be treated with subtrochanteric femur resection. However, the number of postoperative complications is still high.
La aplicación de las nuevas tecnologías apps en el sistema financiero ecuatoriano. Un factor que contribuye a su desarrollo
Authors: Jiménez Silva Erlinda Elisabeth 
Published: November 2018

El constante avance tecnológico del siglo XXI y la globalización de los mercados exigen al sector empresarial que sus actividades se enmarquen en un alto nivel de innovación y competitividad, de manera especial las organizaciones que ofrecen servicios, donde el grado de percepción sobre oportunidad, comodidad y facilidad es muy apreciado por sus clientes o usuarios. El presente artículo es el resultado de una investigación en el sistema financiero ecuatoriano sobre el uso de las nuevas tecnologías, de manera particular las apps, como herramienta tecnológica en sus actividades tanto con clientes internos como externos, durante el año 2017, con la finalidad de conocer el verdadero aporte de esta herramienta en su desarrollo económico, a través del incremento de su participación de mercado y mejora en la satisfacción del cliente. A través de una investigación cuantitativa, y mediante la aplicación de encuestas administradas a una muestra de directivos de las instituciones financieras entre bancos del sector privado, sector público, cooperativas y mutualistas, sobre el uso de la tecnología y de manera particular de las apps por parte de los clientes externos e internos y con el afianzamiento de información documental, se buscó analizar y comprender el efectivo aporte de las apps en su crecimiento económico. Se obtuvo así que las entidades que han logrado mayor participación en el mercado financiero son los bancos y son los que utilizan en mayor escala esta herramienta tecnológica, lo que les ha permitido disminuir costos y gastos operativos. Con ello han logrado mayor cobertura de mercado, por lo que notablemente es uno de los factores que aportan en la rentabilidad de estas entidades.
Developing a Conceptual Framework using Exploratory Testing to Improve Software Quality in SME's
Authors: Thangiah Murugan , Basri Shuib , Durai Dominic Dhanapal 
Published: November 2018

In order to create quality software with standards and agreeing principles, the Small and Medium Software Enterprises (SME’s) faces many challenges and issues due to variety of reasons. Starting from the requirement analysis phase, the challenges emerge and continue until the project nears its completion, before being released to the customers or stakeholders. Various issues surfaced during the SDLC phases are identified and analyzed in the study. A Conceptual Framework using Exploratory Testing has been developed based on the study and the quantitative analyses were conducted using survey questionnaire. In this research paper the data analysis of the quantitative survey is conducted using Partial Least Square Structural Equation Modeling. The reliability and validity of the data is evaluated and presented in this paper which is essential to develop the conceptual framework. Further analysis of the survey questionnaire will be carried on and it will be reported in future work.
Optimization on the Credit Risk of Companies in Malaysia With Data Envelopment Analysis Model
Authors: X. Agnes Lai J. , H. Lam J. , S. Lam W. 
Published: November 2018

Financial institutions provide financial services to their clients or retail customers where money is managed. Credit risk has been identified as one of the dominant risks that affect the performance of a company. A firmâ€™s efficiency with different credit risk management practices is still unknown. This research aims to evaluate the credit risk management and efficiency of the financial institutions that are publicly listed in Bursa Malaysia from year 2013-2016 with the Data Envelopment Analysis (DEA) model. Based on the financial ratios, the DEA model allows the relative efficiency of a set of companies to be assessed by solving a linear programming model. The results show that ALLIANZ, APEX, BURSA, ECM, LPI and TAKAFUL are efficient in terms of their credit risk management. This study identifies the efficient and inefficient financial companies in Malaysia.Â Â
Genre Classification of Traditional Malay Music Using Spectrogram Correlation
Authors: A. Samad S. , B. Huddin A. 
Published: November 2018

A method to classify the genre of traditional Malay music using spectrogram correlation is described.Â The method can be divided into three distinct parts consisting of spectrogram construction that retains the most salient feature of the music, template construction that takes into account the variations in music within a genre as well as the music progresses, and template matching based on spectrogram image cross-correlation with unconstrained minimum average correlation energy filters. Experiments conducted with seven genres of traditional Malay music show that the recognition accuracy is dependent on the number of segments used to construct the filter templates, which in turn is related to the length of music segment used. Despite using a small dataset, an average recognition rate of 61.8 percent was obtained for music segments lasting 180 seconds using six relatively short excerpts.Â Â
EEG Calmness Index Establishment Using Computational of Z-Score
Authors: A. M. Aris S. , A. Bani N. , N.Muhtazaruddin M. , N. Taib M. 
Published: November 2018

A lot of useful information can be obtained through observation of the electroencephalogram (EEG) signal such as the human psychophysiology. It has been proven that EEG is handy in human diagnosis and tools to observe the brain condition. The study aims to establish a calmness index, which can differentiate the calmness level of an individual. Alpha waves were selected as the data features and computed into asymmetry index. The data features were clustered using Fuzzy C-Means (FCM) and resulted in three clusters. Wilcoxon Signed Ranks test was applied to determine the significance of the data features clustered by FCM. The Z-score obtained successfully distinguish three level of calmness index from the lower index until the higher index. With the advancement of signal processing techniques, the feature extractions for calmness index establishment computation is achievable.Â Â
VGG16 for Plant Image Classification with Transfer Learning and Data Augmentation
Authors: Aqib Haqmi Abas Mohamad , Ismail Nurlaila , Ihsan Mohd Yassin Ahmad , Nasir Taib Mohd 
Published: November 2018

This paper discusses the potential of applying VGG16 model architecture for plant classification. Flower images are used instead of leaves as in other plant recognition model because the structure of shape and color of leaves are similar in nature. This might be disadvantageous when we want to use only leaves images as a sole feature of plants to classify the species. Previous work has demonstrated the effectiveness of using transfer learning, dropout and data augmentation as a method to reduce overfitting problem of convolutional neural network model when applied in limited amount of images data. We have successfully build and train the VGG16 model with 2800 flower images. The model able to achieve a classification accuracy score of 96.25% for training set, 93.93% for validation set and 89.96% for testing set.Â Â
Identifying High Impact Disaster Triggers on Computer Networks in Asia Pacific Region
Authors: Alayham Abbas Helmi Rabab , Jamal Arshad , Abdul Hameed Ashour Marwan 
Published: November 2018

This paper aims to study various aspects of Asia Pacific region in order to identify the most common disasters as well as disasters with the largest impact. It represents a first step in developing a strategy to face topological network failure that is triggered by an accidental disaster. The study of Asia-Pacific region is crucial, firstly because in order to properly address a problem it is very important to properly define the problem at hand and its surroundings. Secondly, because disasters include in their impacts various aspects of the society those aspects have their own further effect on the society, therefore, it is of great importance to address all aspects of the region that can have a cross effect with disasters. The main focus in this paper is this cross effect with computer network infrastructure; due to their important role in the societyâ€™s way of life, as well as their fatal role during disasters and crisis.Â Â
Animation Effectiveness for E-Learning with Progressive Web App Approach: a Narrative Review
Authors: Wijaya Hadi , Alayham Abbas Rabab , . . 
Published: November 2018

Understanding the content of a subject is the most fundamental thing a student should do to acquire the skills and knowledge. Animation is one way to provide an interesting way of learning. ALETRIA project is the reason to support the students for use animation methods that developed in novel e-learning concept. As a first step, the study of animation and e-learning development became the basis of this narrative literature. Terms of search that used in this paper is animation for learning, engagement and learnerâ€™s motivation. E-learning development with Progressive Web Apps (PWAs) were excluded from the search terms. 29 papers were selected for review as they are relevant to the criteria. The combined results of these papers recommend that there is reason to confident that the development of e-learning animations with the PWA approach might be effective to use.Â Â
The Impact of Using Gamification in Learning Computer Science for Students in University
Authors: Oktaviati Risna , Amril Jaharadak Adam 
Published: November 2018

The utilization of technology can be implemented in education. Gamification is a new technology that used elements such as badges, level, and point of game play that implemented in a non-game context. In this research, the researcher analyzes some of the literature to establish in the extent of gamification to assist studentâ€™s motivation and engagement among Computer Science related subject. The researcher found that the most common element that implemented in learning Computer Science related subject were badges, point, level, and leaderboards. Implementing gamification elements in learning can be a tool that can motivate and engage the student in learning Computer Science.Â Â
Impact of News Sentiment Analysis on Market Price Movement During the Dividend Period
Authors: L. Hor W. , X. Goh W. , H. Ow S. 
Published: November 2018

This study presents development of a system for analysing the polarity of stock market news to guide traders in making better decision when buying, selling or holding stocks during the dividend period. It will also help traders by reducing the risk of making inaccurate decision in trading. Trusted and reliable data such as dividend news, daily share market price, company news and announcements from Bursa Malaysia and The Edge Market will be used for performing news sentiment analysis using Azure Text Analytics. The results show that company news and announcements do not have significant effect on the Malaysia stock prices as the prices move within the range of 0-1%, which is the benchmark of the normal range of daily price movement.Â Â
Early Detection of Diabetic Retinopathy by Using Deep Learning Neural Network
Authors: Hazim Johari Mohamad , Abu Hassan Hasliza , Ihsan Mohd Yassin Ahmad , Md Tahir Nooritawati , Zabidi Azlee , Ismael Rizman Zairi , Baharom Rahimi , Abdul Wahab Norfishah 
Published: November 2018

This project presents a method to detect diabetic retinopathy on the fundus images by using deep learning neural network. Alexnet Convolution Neural Network (CNN) has been used in the project to ease the process of neural learning. The data set used were retrieved from MESSIDOR database and it contains 1200 pieces of fundus images. The images were filtered based on the project needed.Â There were 580 pieces of images types .tif has been used after filtered and those pictures were divided into 2, which is Exudates images and Normal images. On the training and testing session, the 580 mixed of exudates and normal fundus images were divided into 2 sets which is training set and testing set. The result of the training and testing set were merged into a confusion matrix. The result for this project shows that the accuracy of the CNN for training and testing set was 99.3% and 88.3% respectively.Â Â Â
Convolutional Neural Network (CNN) based Gait Recognition System using Microsoft Kinect Skeleton Features
Authors: Shahrum Md Guntor Mohd , Sahak Rohilak , Zabidi Azlee , Md Tahir Nooritawati , Mohd Yassin Ihsan , Ismael Rizman Zairi , Baharom Rahimi , Abdul Wahab Noorfishah 
Published: November 2018

Biometric identification systems have recently made exponential advancements in term of complexity and accuracy in recognition for security purposes and a variety of other application. In this paper, a Convolutional Neural Network (CNN) based gait recognition system using Microsoft Kinect skeletal joint data points is proposed for human identification. A total of 23 subjects were used for the experiments. The subjects were positioned 45 degrees (oblique view) from Kinect. A CNN based on the modified AlexNet structure was used to fit the different input data size. The results indicate that the training and testing accuracies were 100% and 69.6% respectively.Â Â