bluuebunny/crossref_metadata_2025_split huggingface dataset:
Non-enzymatic glucose sensor with electrodeposited silver/carbon nanotubes composite electrode
Authors: Shabbir Syeda Ammara , Tariq Sana , Ashiq M. Gul Bahar , Khan Waqar A. 
Published: June 2019

AbstractDiabetes mellitus is a debilitating disease that affects each and every organ of human body. Hence it is important to continuously monitor the glucose level throughout the day and night. Glucose sensors are in great demand due to a rapid increase in diabetic community. A strategy has been implemented here to fabricate silver nanoparticles (AgNPs) with the support of functionalized carbon nanotubes (f-CNTs). Silver/carbon nanotubes (Ag/CNTs) nanocomposite electrode have been prepared by electrochemical process on Fluorine doped tin oxide (FTO) glass, by varying silver (Ag) concentrations for non-enzymatic glucose sensor. The variable Ag concentration in the morphology of Ag/CNTs nanocomposite has influenced the electrical conductivity, oxidation and reduction potential and electrochemical activity of glucose. Highest current density and good electrocatalytic activity for electrodes are obtained at 70 mM concentration of silver in Ag/CNTs composite. The present study indicates that the Ag/CNTs electrode is a possible substitute of the expensive glassy carbon electrode for enzyme-free glucose sensors.
Regulatory mechanisms of Robo4 and their effects on angiogenesis
Authors: Dai Chang , Gong Qiaoyun , Cheng Yan , Su Guanfang 
Published: June 2019

Abstract
Roundabout4 (Robo4) is a transmembrane receptor that belongs to the Roundabout (Robo) family of axon guidance molecules. Robo4 is an endothelial-specific receptor that participates in endothelial cell migration, proliferation, and angiogenesis and the maintenance of vasculature homeostasis. The purpose of this review is to summarize and analyze three main mechanisms related to the expression and function of Robo4 during developmental and pathological angiogenesis. In this review, static shear stress and the binding of transcription factors such as E26 transformation-specific variant 2 (ETV2) and Slit3 induce Robo4 expression and activate Robo4 during tissue and organ development. Robo4 interacts with Slit2 or UNC5B to maintain vascular integrity, while a disturbed flow and the expression of transcription factors in inflammatory or neoplastic environments alter Robo4 expression levels, although these changes have uncertain functions. Based on the mechanisms described above, we discuss the aberrant expression of Robo4 in angiogenesis-related diseases and propose antiangiogenic therapies targeting the Robo4 signaling pathway for the treatment of ocular neovascularization lesions and tumors. Finally, although many problems related to Robo4 signaling pathways remain to be resolved, Robo4 is a promising and potentially valuable therapeutic target for treating pathological angiogenesis and developmental defects in angiogenesis.
The emerging role of circular RNAs in breast cancer
Authors: Zhou Si-ying , Chen Wei , Yang Su-jin , Xu Zi-han , Hu Jia-hua , Zhang He-da , Zhong Shan-liang , Tang Jin-hai 
Published: June 2019

Abstract
Breast cancer (BCa) is one of the most frequently diagnosed cancers and leading cause of cancer deaths among females worldwide. Circular RNAs (circRNAs) are a new class of endogenous regulatory RNAs characterized by circular shape resulting from covalently closed continuous loops that are capable of regulating gene expression at transcription or post-transcription levels. With the unique structures, circRNAs are resistant to exonuclease RNase R and maintain stability more easily than linear RNAs. Recently, an increasing number of circRNAs are discovered and reported to show different expression in BCa and these dysregulated circRNAs were correlated with patients’ clinical characteristics and grade in the progression of BCa. CircRNAs participate in the bioprocesses of carcinogenesis of BCa, including cell proliferation, apoptosis, cell cycle, tumorigenesis, vascularization, cell invasion, migration as well as metastasis. Here we concentrated on biogenesis and function of circRNAs, summarized their implications in BCa and discussed their potential as diagnostic and therapeutic targets for BCa.
Deorphanizing NUDIX hydrolases from Trypanosoma: tantalizing links with metabolic regulation and stress tolerance
Authors: Matange Nishad 
Published: June 2019

Abstract
An explosion of sequence information in the genomics era has thrown up thousands of protein sequences without functional assignment. Though our ability to predict function based on sequence alone is improving steadily, we still have a long way to go. Proteins with common evolutionary origins carry telling sequence signatures, which ought to reveal their biological roles. These sequence signatures have allowed us to classify proteins into families with similar structures, and possibly, functions. Yet, evolution is a perpetual tinkerer, and hence, sequence signatures alone have proved inadequate in understanding the physiological activities of proteins. One such enigmatic family of enzymes is the NUDIX (nucleoside diphosphate linked to a moiety X) hydrolase family that has over 80000 members from all branches of the tree of life. Though MutT, the founding member of this family, was identified in 1954, we are only now beginning to understand the diversity of substrates and biological roles that these enzymes demonstrate. In a recent article by Cordeiro et al. in Bioscience Reports [Biosci. Rep. (2019)], two members of this protein family from the human pathogen Trypanosoma brucei were deorphanized as being polyphosphate hydrolases. The authors show that of the five NUDIX hydrolases coded by the T. brucei genomes, TbNH2 and TbNH4, show in vitro hydrolytic activity against inorganic polyphosphate. Through classical biochemistry and immunostaining microscopy, differences in their substrate specificities and sub-cellular localization were revealed. These new data provide a compelling direction to the study of Trypanosome stress biology as well as our understanding of the NUDIX enzyme family.
Extended halo of NGC 2682 (M 67) from Gaia DR2
Authors: Carrera R. , Pasquato M. , Vallenari A. , Balaguer-Núñez L. , Cantat-Gaudin T. , Mapelli M. , Bragaglia A. , Bossini D. , Jordi C. , Galadí-Enríquez D. , Solano E. 
Published: June 2019

Context. NGC 2682 is a nearby open cluster that is approximately 3.5 Gyr old. Dynamically, most open clusters are expected to dissolve on shorter timescales of ≈1 Gyr. That it has survived until now means that NGC 2682 was likely much more massive in the past and is bound to have an interesting dynamical history.
Aims. We investigate the spatial distribution of the stars in NGC 2682 to constrain dynamical evolution of the cluster. We particularly focus on the marginally bound stars in the cluster outskirts.
Methods. We used Gaia DR2 data to identify NGC 2682 members up to a distance of ∼150 pc (10°). The two methods Clusterix and UPMASK were applied to this end. We estimated distances to obtain 3D stellar positions using a Bayesian approach to parallax inversion, with an appropriate prior for star clusters. We calculated the orbit of NGC 2682 using the GRAVPOT16 software.
Results. The cluster extends up to 200′ (50 pc), which implies that its size is at least twice as large as previously believed. This exceeds the cluster Hill sphere based on the Galactic potential at the distance of NGC 2682.
Conclusion. The extra-tidal stars in NGC 2682 may originate from external perturbations such as disc-shocking or dynamical evaporation from two-body relaxation. The former origin is plausible given the orbit of NGC 2682, which crossed the Galactic disc ≈40 Myr ago.
Optimization of a Customized Mixed Model Assembly Using MATLAB/Simulink
Authors: Kuriakose R.B , Vermaak H.J 
Published: June 2019

Abstract
The relevance of assembly line balancing has never been more critical as it is now with the advent of Industry 4.0. This paper considers the case study of a Mixed Model Assembly Line in the form of a water bottling plant. The paper initially discusses the design consideration of the water bottling plant and how it was modelled in Simulink. Next the paper chooses an appropriate optimization technique and runs it on the model with real-time inputs. Finally, an analysis is done to test the impact of optimization and if it has improved the production time of the water bottling plant. The results of the study aim to add knowledge to the field of Mixed Model Assembly line balancing.
Prototype of Visible Light Communication Transceiver Using Array Photo Transistor for Real Time Digital Media Transfer
Authors: Wijayanto Inung , Hadiyoso Sugondo , Renggani Retno 
Published: June 2019

Abstract
Previous research about low cost visible light communication (VLC) transceiver prototype was conducted which able to reach 98 cm, 70° and 19200 bps of transmitting distance, maximum transmission angle and transmission rate, respectively. The next prototype is built to get better performance by adding a reflector to the array phototransistor and split the power of the transceiver in order to maximize the light of the LED. This new prototype surpasses our target by reaching 134 cm of transmission distance. The system is also able to send digital multimedia files such as text, images, video in MPEG format and audio files in WAV and Mp3 format. The maximum bit rate of our prototype is 9600 bps and acceptance angle is 87°.
Quality Assessment of DEM Generated from SAR Radargrammetry Based on Cross-Correlation and Spatial Resolution Setting
Authors: Arief R , Setiyoko A , Maulana R , Ali S , Sudiana D , Arymurthy A M 
Published: June 2019

Abstract
DEM as a model of earth’s surface model plays an important role in the environmental analysis. The most common recent technology in producing DEM is SAR. Even though it has advantages compared to optical approach, DEM generated from SAR still has issues regarding process setting regarding cross-correlation and spatial resolution determination. Both aspects will affect the volume of output data and computational effort. This research project is aimed to analyze the effects of cross-correlation and spatial resolution determination in DEM generation process to its accuracy. Several experiment scenarios of cross-correlation and spatial resolution setting had been applied to TerraSAR-X data. Overall output is shown that determination of cross-correlation threshold and spatial resolution in processing stages will have a significant effect on the accuracy of DEM generated. Gaps of data often occur in several sets of both aspects.
Towards Personalization to support Learners’ Motivation on Gamified MOOC Platform
Authors: Saputro Rujianto Eko , Salam Sazilah , Zakaria Mohd. Hafiz , Septiadi Abednego Dwi 
Published: June 2019

Abstract
Online learning expands along with the development of information technology. One model of online education that widely used because it is open and massive today is the Massive Open Online Courses (MOOCs). However, the problems that arise at the MOOC are related to the high drop out rate caused by the lack of motivation of users to complete the course. Various approaches are taken to deal with this, one of which is by utilising elements of the game through gamification and personalisation to understand the factors needed by learners in the learning environment. This research proposes a personalised design through self-determination. The results of the study have implemented on a new Gamified MOOC platform that pays attention to learner personalisation regarding competency, autonomy and relatedness.
Drone Tracking Modelling Ontology for Tourist Behavior
Authors: Rusdi Jack Febrian , Salam Sazilah , Abu Nur Azman , Sahib Shahrin , Naseer Muchammad , Abdullah Abdul Aziz 
Published: June 2019

Abstract
Availability of internet access is one of the needs for tourists when traveling. Unfortunately, the availability of access is quite limited when in a tourist destination, usually Wi-Fi also generally uses a closed system that cannot be accessed by just anyone, except those who get access keys only. This paper provides a solution for the model of internet access for tourists provided by Tourism Service Providers, by utilizing drone technology as an access point. In addition, this model also provides services to track the position of tourists who spread and facilities for communication between tourists, especially for certain conditions, such as the occurrence of saturation for tourists while in one of the tourist destinations.
Analysis Of Alpha And Beta EEG Signal Pattern In Trypophobia Condition With Wavelet Method
Authors: Herdaning Jehan Pratama , Hadiyoso Sugondo , Wijayanto Inung 
Published: June 2019

Abstract
A phobia is a human fear of things that are sometimes very simple for some people. One of them is Trypophobia which is a fear of visualizing small holes. The effect of the trypophobia effect can we analyze his brain waves using an Electroencephalograph. In this study, a system was developed to classify a person’s condition without Trypophobia (normal) and the condition of a person with Trypophobia based on analysis of alpha and beta EEG signals. In this study, the Artificial Neural Network (ANN) used for classifying conditions. Discrete Wavelet Transform (DWT) is used to reduce the raw dimensions of EEG signals and retrieve signal features. The test results show that the best performance obtained in beta signals which have the highest diagnostic parameter accuracy, namely Maximum, Standard Deviation and Variance with 100% accuracy, with computation time 0.027 and 0.037 seconds. While for alpha signals obtained with Variance and Interquartile Range parameters of 96.42% with a time of 0.03 and 0.032 seconds.
Linear Congruential Method for Randomization of Test Item in Computer-Based Psychological Edwards Personal Preference Schedule (EPPS) Test
Authors: Sesari E G , Dirgantoro B , Setianingsih C 
Published: June 2019

Abstract
Psychological tests are used to determine human’s attitude and behavior. In its application, psychological tests still use the old method. Objects are asked to answer questions and then the answers will be collected again to be calculated, and then conclusion will be drawn from the result. It will be time consuming and impractical. Computer-based psychological test have an answer to these deficiencies. By utilizing the ease of test item management in computer, this paper discusses the application of linear congruential method for randomization of test item in computer-based psychological edwards personal preference schedule (EPPS) test developed by web-based programming. According to expert, the difference in the number of respondents who have the largest and smallest raw score aspects that are the same and not the same is considered not too significant that in this case randomization of test item can be applied to the EPPS test because the change in test results is not too significant and the scoring process is still valid
Detecting Hand, Foot and Mouth Disease in Earlier Stage Using C4.5 Algorithm as Expert System Based on Android
Authors: Syahrial Farisa Hafida , Irawan Budhi , Prasasti Anggunmeka Luhur 
Published: June 2019

Abstract
Hand, Foot and Mouth Disease (HFMD) is an infectious diseases caused by enterovirus virus 71 (EV 71). The symptoms of HFMD is similar to several other disease that caused by a virus, especially disease that have a fever and rash symptoms which people usually underestimate diseases that have early symptoms like that. Therefore, in this system we classify the HFMD with the intention of detecting the disease from an earlier stage. And we use Android based application since at this present time, smartphone is the closest device that is always used by many people. The classification used in this paper is Decision Tree C4.5 Algorithm. Dataset used in this research is as many as 256 which divided into training data and testing data, that formed based on symptoms that had previously been validated by the doctor. The result shows that data partitions of 90%:10%, 80%:20% and 70%:30% has accuracy, precision and recall value are 100%. Thus, data partition 70%:30% has the best result because this partition has less training data but can still classify diseases effectively.
Item delivery simulation using genetic algorithm
Authors: Switrayana I Nyoman , Osmond Andrew Brian , Aditsania Annisa 
Published: June 2019

Abstract
In sending items, time and costs can be minimized by selecting the shortest path. The problem of choosing the shortest path is often known as Travelling Salesman Problem (TSP). TSP in this study was not only concerned with distance but also the priority of places to be visited. Priority parameters in this research are a sign that each place has a value to be visited first than another place. This priority can also be assumed as a type of delivery service that can be chosen by the customer. Priority is divided into three groups, but it can also be more than that according to the needs of a shipping service provider. Delivery of multiple destinations in one area can be delivered with a single trip based on their priority. Search optimization of the shortest path is modeled with genetic algorithms. Hamilton path is the output of the simulation.
Seizure Type Classification on EEG Signal using Support Vector Machine
Authors: Dwi Saputro Inggi Ramadhani , Maryati Nita Dwi , Solihati Siti Rizqia , Wijayanto Inung , Hadiyoso Sugondo , Patmasari Raditiana 
Published: June 2019

Abstract
One instrument to record the activity of brainwave in a specific time is called Electroencephalography (EEG). EEG signal can be used to analyze the epilepsy disease. Brainwave of seizure patient has a low frequency with a tighter pattern than brainwave of normal people. We use data from Temple University Hospital Seizure Corpus (TUSZ) that represents an accurate clinical condition characterization. Based on neurologist report, several types of seizure can be found in the dataset. In this research, we classify three types of seizure, Generalized Non-Specific Seizure (GNSZ), Focal Non-Specific Seizure (FNSZ) and Tonic-Clonic Seizure (TCSZ). We added a normal EEG signal, so we have four classes to be classified using Support Vector Machine (SVM). The training dataset consists from 120 data (20 GNSZ, 50 FNSZ, 25 TCSZ and 25 Normal), while the evaluation dataset is 90 datasets (20 GNSZ, 50 FNSZ, 5 TCSZ and 15 Normal). We observe the combination of three feature extraction method, Mel Frequency Cepstral Coefficients (MFCC), Hjorth Descriptor and Independent Component Analysis (ICA). The best result obtained by combining MFCC and Hjorth descriptor that can detect seizure type with 90.25%, 97.83%, and 91.4% of average sensitivity, average specificity, and accuracy respectively.
An advanced comparison on big data world computing frameworks
Authors: Deshai N , Venkataramana S , Sekhar B V D S , Srinivas K , Sundhar Singh P , NagaKrishna L 
Published: June 2019

Abstract
Today’s internet world becomes really introducing a landmark between Peta to Exa byte which is significantly generating an enormous size of data while computing the digital things including the format of each datasets which signifies highly unstructured because which could be generating from different social sites, IOT, Google engine, Twitter, Yahoo, monitoring and controlling through sensors essentially called big data. Because of this fast era, we apply just contemporary techniques with common tools regarding having focused performing, smooth process and to execute computations on huge data. Though such tremendous universal data has some shortcomings for getting effective processing, analyzing the universe immense datasets and scalability techniques. Apache open free source Hadoop does the latest big data weapon which can process Zetta byte dimensions of databases by its most developed and popular components as hdfs and Map Reduce, to make up vast storage facility plus great administration in the sense to process zettabyte of datasets as powerfully, flexible. MR likes more famous software popular structure for handling big-data existing issues with full parallel, highly distributed and most scalable manner. However, public and unrestricted source tools on Hadoop, map reduces become major limitations like poor allocate process on needy resources working regarding stream-oriented processing, Shortage significant viewpoints like latency, dynamic manner execution, optimization, computing as online and diverse logical solutions. We consider significant various complex data computing orientated techniques. This study paper address Apache fastest spark tool, online-oriented tool public and unrestricted source and Flink are in Apache project are efficient frameworks to conquer that limitation.
AES encryption and decryption standards
Authors: Devi SistlaVasundhara , Kotha Harika Devi 
Published: June 2019

Abstract
Over the last years there has been massive changes that lead to the growth of information in technology, that brought significant changes in the part of cryptography and its applications like confidentiality of data and many such. Privacy and secrecy is what everyone desires for their data or accounts. Encryption is one such method to achieve it. Advanced Encryption Standard (AES), can be used to protect the information. The primary preferred standpoint of AESis, it very well may be can be reproduced or worked with unadulterated equipment. In this paper, Xilinx 9.2i is utilized for recreation and improvement of VHDL code. Integrating and execution of the code is completed on Xilinx - Project Navigator ISE 9.2i suite. Xilinx XC3S500 gadget of Spartan Family and is utilized for equipment usage. This undertaking proposes a strategy to coordinate the AES encrypter and the AES descrypter.
A. Amalgamative sentiment analysis framework on social networking site
Authors: ArunaSafali M , Satya Prasad R , Sastry KBS 
Published: June 2019

Abstract
Sentiment analysis is the most widely used in many applications. Knowing the sentiment analysis for any of the dataset becomes most important to know the sentiment for the given inputs. In this paper, the amalgamative sentiment analysis framework developed for dividing the positive and negative emotions taken from the user’s tweets. In this system, an integrated social networking is developed which is integrated with ASAF. Results show the classification of these tweets.
Acceptability analysis method for evaluate data on twitter using support vector machine
Authors: Swathi K , Naga deepthi P 
Published: June 2019

Abstract
The first model centres around believability at the client level, tackling different elements of information stream into a registered validity rating. The next model specifies a methodology to find believability score for singular tweets. We built up the system for validity on Face book by evaluating the validity of: (i) the reliability of the web sources discussing a case, (ii) the dialect style of the articles revealing the case and, (iii) their position. We at that point gathered the preparation information for making a model utilizing Support Vector Machine (SVM). Furthermore the standardization technique is essential advance for purifying information before utilizing the machine learning strategy to order information. The outcome demonstrate that Naïve Bayes to identify the Fake news has precision 96.08%. We distinguish basic examples of transiently agent discussion subgraphs and speak to their subjects utilizing Latent Dirichlet Allocation (LDA) demonstrating. We break down how the information had proliferated, and the moves were made in light of the source. The component retweet was considered as a proportion of examination to upgrade the reliability of the spread information. The performance of our positioning calculation essentially upgraded when we connected re-positioning system.