bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation on Machine Learning Algorithms for Classification of Autism Spectrum Disorder (ASD)
Authors: Abdullah Azian Azamimi , Rijal Saroja , Dash Satya Ranjan 
Published: November 2019

Abstract
Autism Spectrum Disorder (ASD) was characterized by delay in social interactions development, repetitive behaviors and narrow interest, which usually diagnosed with standard diagnostic tools such as Autism Diagnostic Observation Schedule (ADOS) and Autism Diagnostic Interview-Revised (ADIR-R). Previous work has implemented machine-learning methods for the classification of ASD, however they used different types of dataset such as brain images for MRI and EEG, risk genes in genetic profiles and behavior evaluation based on ADOS and ADI-R. Here a trial on using Autism Spectrum Questions (AQ) to build models that have higher potential to classify ASD was developed. In this research, Chi-square and Least Absolute Shrinkage and Selection Operator (LASSO) have been selected as feature selection methods to select the most important features for 3 supervised machine learning algorithms, which are Random Forest, Logistic Regression and K-Nearest Neighbors with K-fold cross validation. The performance was evaluated in which results Logistic Regression scored the highest accuracy with 97.541% using model with 13 selected features based on Chi-square selection method.
Differentiate Characteristic EEG Tobacco Smoking and Non-smoking
Authors: Chin Lim Chee , Zazid Asmiedah Muhamad , Fook Chong Yen , Vijean Vikneswaran , Awang Saidatul Ardeenawatie , Affandi Marwan , Chee Lim Sin 
Published: November 2019

Abstract
Electroencephalogram (EEG) signal is non-stationary signal that have low frequency component and amplitude compared to stationary signal. Therefore, present of unwanted substance (nicotine) in Tobacco smoking will alter the brain electrical activity. This paper is proposed to investigate the changes of EEG signal with the present of nicotine and identify the difference brain signal between smoker and non-smoker. There are 20 males (10 smokers, 10 non-smokers) are selected. The subjects are chosen based on inclusion criteria (abstained from smoking within 6 hours before experiment, and do not take any medication and caffeine). The recorded EEG signal contain a lot of noise such as head moving, muscle movement, power line, eyes blinks and interference with other device. Butterworth filter are implemented to remove the unwanted noise present in the original signal. Bandpass filter is used to decompose the EEG signal into alpha, theta, delta and beta frequency. Then, eight features (mean, median, maximum, minimum, variance, standard deviation, energy and power) have been extracted by using Fast Fourier Transform (FFT) and Power Spectral Density (PSD) method. Then, four different type of kernel function (‘Linear’, ‘BoxConstraint’, ‘Polynomial’ and ‘RBF’) of SVM classifier are used to identify the best accuracy. As a result, PSD (97.50%) have higher performance accuracy than FFT (97.33%) by using Radial Basis Function (RBF) of Support Vector Machine (SVM). Smoking activity caused slightly increase theta and delta frequency. Smoking is activated of five electrode channels (Fp1, Fp2, F8, F3 and C3) and caused additional emotion such as deep rest, stress releasing and losing attention. The attention of smokers can be measure by using stroop test. After smoking activity, smokers become more energetic and increase the time response (1.77 s) of stroop test compared to non-smokers (2.96 s). The result is calculated by using statistical analysis (t-test). The p-value is 0.037 which is less than 0.05. Thus, the null hypothesis is rejected and conclude there is significant different between smokers and non-smoker performance before and after smoking task.
Classification of Benign and Malignant Breast Cancer using Supervised Machine Learning Algorithms Based on Image and Numeric Datasets
Authors: Ray Ratula , Abdullah Azian Azamimi , Mallick Debasish Kumar , Ranjan Dash Satya 
Published: November 2019

Abstract
Breast cancer has been identified as the second leading cause of death among women worldwide after lung cancer and hence, it becomes extremely crucial to identify it at an early stage, which can considerably increase the chances of survival. The most important part in cancer detection is to be able to differentiate between benign and malignant tumors and this is where the work of Machine Learning comes in. Taking all the dependent features upon consideration, Supervised Machine Learning methods allow for classification with higher degree of accuracy and improve upon the misdiagnosis of the physicians, which might occur almost 20% of the time. In our paper, we are focusing towards understanding the shortcomings of digital mammograms in detection of breast cancer and utilize Machine Learning classifiers for the classification of benign and malignant tumors using image analysis. Apart from this, we are also looking into implementing Supervised Machine Learning classifiers such as Decision Tree, K Nearest Neighbour (KNN), Random Forest and Gaussian Naive Bayes classifiers for assessing the risks involved with breast cancer by analyzing the biomarkers that are involved with it. Our aim is to provide a comprehensive view on prediction of breast cancer through Machine Learning through both image and data analyses, which can play a pivotal role in prevention of misdiagnosis in future. Fig. 1. gives a layout for the breast cancer prediction using Supervised Machine learning classifiers.
Fibre based bioplastic film from Morus sp. (mulberry) leaves for medical purpose
Authors: Aziz Izzat Aiman , Robiah Mohamad Che Wan Sharifah , Adollah Robiyanti 
Published: November 2019

Abstract
New trend was shown the application of biodegradable plastic was used in the medicinal field especially as a template for the 3rd and 4th degree of burning is extensively studied. Currently, a bioplastic in medicinal applications for burning treatment comes from various materials based on fossil oil and synthetic chemical. Morus sp. among abundant plant and normally used for skin and inflammation treatment in traditional practices. The aim of this research is to synthesis bioplastic by using Polyvinyl alcohol (PVA) incorporates with Morus sp. leaves as the alternative of the skin template for a burning patient. With the phytochemical in the leaves such as phenolic, flavonoid and high content of antioxidant, hopefully, it will able to enhance the cell growth on the burning site without any contamination from the bacteria. 2 g Morus sp. leaves was blend with different concentration of the PVA (20%, 40%, 60%, 80%, and 100%) to produce plastic films. This mixture was stirred under constant magnetic stirring at 95°C for 1 hour. The mixtures are then pouring into a glass petri dish and dried in an oven at 50°C for 24 hours. The characterization of bioplastic is based on an antimicrobial test, tensile test, microstructure analysis using SEM and chemical composition analysed using FTIR. According to the results, a bioplastic made up from mixes Morus sp. leaves with 80% PVA has the best mechanical and antimicrobial properties. Therefore, the result showed a possible application of the film as an alternative for the medical purpose.
Effect of pressure and infill density parameter setting on morphological and mechanical properties of polycaprolactone printed scaffold using desktop 3D bioprinter
Authors: Fakhruddin Khalida , Abd Razak Saiful Izwan , Murad Muhammad ‘Ammar , Mat Nayan Nadirul Hasraf , Sa’adon Shafizah 
Published: November 2019

Abstract
Three dimensional (3D) bioprinting is the process of building a 3D construct containing biological cells. There are varies set of printing parameter involved in 3D bioprinting system that will affect the structure and the mechanical properties of the bioprinted construct. This study was done to investigated the effect of extrusion pressure and infill density on the polycaprolactone (PCL) 3D printed construct’s morphology, printing accuracy and compressive strength. Based on morphological evaluations using scanning electron microscope, the printed scaffold was suggested to be at the best condition at pressure 60psi using 80% infill setting. Besides, the mechanical testing revealed the printed scaffold was successfully fabricated without losing its mechanical integrity. This is a good indication for PCL as structural host material to obtain functionalized 3D scaffold using bioprinting method.
An Automated Intelligent Identification and Counting System Procedure for Tuberculosis
Authors: Rosli Fatin Atiqah , Mashor Mohd Yusoff , Noor Siti Suraya Md 
Published: November 2019

Abstract
Tuberculosis (TB) is an infectious disease caused by Mycobacterium Tuberculosis or TB Bacilli. Currently, the classification of TB bacilli is carried out by microbiologist by using Ziehl-Nielsen (ZN) stained smear sputum slide under a light microscopy. However, the manual evaluation is time-consuming and lead to slow decision. Furthermore, the sensitivity is less due to incline of human error which lead to inaccurate conclusion. Therefore, this study proposes an intelligence identification and counting system to detect the presence of TB bacilli in the ZN-stained smear sputum image. This system is designed to identify the presence of TB bacilli and count the number of TB bacilli by applying digital image processing and artificial intelligence techniques. In image acquisition, there are 70 samples images of ZN-stained smear sputum image were collected from Hospital Universiti Sains Malaysia (HUSM) Kubang Kerian, Kota Bharu, Kelantan, Malaysia. The image processing technique consists of contrast enhancement, segmentation, and feature extraction. The contrast of original image was enhanced by the combination of global enhancement, local enhancement and Contrast Limited Adaptive Histogram Equalization (CLAHE). Then, the enhanced image was segmented using color thresholding and the features were extracted consists of on 18 colour features, 15 shape features and 5 texture features. Afterward, the features underwent feature selection to select the relevant features by using Neighborhood Component Analysis (NCA) and ReliefF Analysis. The study showed that there are relevant features were chosen by ReliefF at feature weight more than 0.004 including (8 colour features, 11 shape feature and 3 texture features) for improving the performance and accuracy of Multilayer Perceptron (MLP) trained by Scaled Conjugate Gradient (SCG). For classification process, MLP, k-Nearest Neighborhood (k-NN) and Support Vector Machine (SVM) are used with 6 folds cross-validation. It was found that MLP has the highest of accuracy, sensitivity and specificity with 93.8%, 93.4% and 94.1% respectively.
Antibacterial Ability of Mesoporous Carbonated Hydroxyapatite
Authors: Mohammad Nur Farahiyah , Fadzli Farah Syazana Ahmad , Saleh Siti Shuhadah Md , Mohamad Che Wan Sharifah Robiah , Taib Mustafa Ali Azhar 
Published: November 2019

AbstractMesoporous carbonated hydroxyapatite (Meso-CHA) is a bioceramic materials that offer good biocompatibility and bioactivity properties that suitable for bone defects or diseases treatment and therapy. Antibacterial study is very important to ensure that materials is biocompatible enough to be used on or inside the human body. The aim of this study is to investigate the antibacterial ability of the Meso-CHA (without addition of antibacterial agents) towards Escherichia coli (E. coli) bacteria. Meso-CHA samples were synthesized using chemical precipitation method where surfactant P-123 was used to introduce pores within nanoparticles structure. X-ray Diffraction (XRD) and Fourier Transform Infrared (FTIR) analysis proved that pure phase of Meso-CHA was obtained. Synthesized Meso-CHA demonstrated higher pore properties (surface area = 146.92 m2g−1, pore size = 2.35 nm, and pore volume = 0.2437 cm3g−1) compared to commercial HA (surface area = 7.84 m2g−1, pore size = 2.05 nm, and pore volume = 0.0085 cm3g−1). The antibacterial study demonstrated that Meso-CHA has low antibacterial properties with Minimum Inhibitory Concentration (MIC) of 200 mg.ml−1compared to HA. Carbonate ion addition into the Meso-CHA structure does not improve the antibacterial ability of the materials.
The cure and tensile properties of montmorillonite-natural rubber composites in the incorporation of alkanolamide
Authors: Surya I , Ginting M 
Published: November 2019

Abstract
Effects of alkanolamide incorporation on cure and tensile properties of montmorillonite (MMT)-natural rubber (NR) composites were studied. The material of alkanolamide was synthesized from the waste of cooking oil production which was used as a rubber additive and incorporated into the NR compounds at 0, 1, 3, 5, 7 and 9 parts per hundred rubber (phr.). From the results, the alkanolamide decreased the times to scorch and cure but increased elongation at break. It was also found that the alkanolamide improved difference in torque, tensile strength and tensile moduli up to a five phr. of alkanolamide and decreased those properties with further increasing the alkanolamide loading. From the swelling test; the five phr. of alkanolamide loading was the optimum loading which causing the highest density of crosslink of the MMT composite of NR.
The Crystallization Process of Zr-Based Metallic Glass by the Influence of Heating Rate and Alloy Composition
Authors: Triwikantoro  , Kriswandono Y , Munawaroh F 
Published: November 2019

Abstract
A study of the crystallization process of Zr-based Metallic Glass by the influence of the heating rate and variation of alloy composition was investigated. The alloys used were Zr68Cu14Ni11Al7, Zr64.5Cu17Ni11Al7.5, and Zr69.5Cu12Ni11Al7.5. Thermal stability was analyzed using DSC (Differential Scanning Calorimetry) with a heating rate of 5°C/min and 10°C/min until the temperature reached 500°C. The three samples were heated with temperature variations of 400°C, 425°C, and 450°C for one hour in air. Crystal growth was observed by XRD test. The DSC curve of the three samples shows that the higher the rate of heating, the shift of the crystallization peak temperature shifts to a higher temperature. At higher temperatures, the crystallization process occurs faster than at lower temperatures. The composition of zirconium contributes to the resistance properties of crystallization. The alloy with the highest zirconium composition has a high resistance to crystallization. The crystalline phase formed is ZrO2 tetragonal in all samples heated at a temperature of 450°C, and there is an intermetallic phase of Zr2Ni identified on Zr64.5Cu17Ni11Al7.5
Thickness and Resistivities of Cu/Ni Film Resulted by Electroplating on the Various Electrolyte Temperature
Authors: Wustha Jumratul , Toifur Moh. , Khusnani Azmi 
Published: November 2019

Abstract
Synthesis of Cu/Ni thin films has been carried out by electroplating method assisted by magnetic fields at variations in the temperature of the solution. The use of magnetic fields in the deposition process is to accelerate mass transport, reduce the reaction effect of hydrogen evolution, improve surface morphology. An increase in the temperature of the solution can accelerate the rate of Ni ions from the anode to the cathode. The electroplating process is carried out at a DC voltage of 1.5 volts, a magnetic field of 200 gauss that is perpendicular to the electric field, within 5 seconds, and the electrode distance is 4 cm. The solution temperature varied from 40°C – 80°C at intervals of 10 °C. Characterization is done by testing the thickness and resistivity of the Ni layer. Thickness test is done with the help of calculations from the results of weighing Ni. The test of sheet resistivity is done by means of a 4 point probe.
The results showed that the greater the temperature of the solution the thicker the Ni layer. The thickness of the Ni layer ranges from (0.09 ± 0.001) μm to (0.38 ± 0.006) μm which is the opposite to the resistivity of the chip, namely the higher the temperature of the solution the smaller the sheet resistivity. The size of the sheet resistivity is from (1.31 ± 0.02) Ω/sq. To (1.38 ± 0.06) Ω/sq to identify relevant articles in literature searches, great care should be taken in constructing both.
Production and Optimization of Lipase by Aspergillus niger using Coconut Pulp Waste in Solid State Fermentation
Authors: Suyanto E , Soetarto E S , Cahyanto M N 
Published: November 2019

Abstract
Lipase has high economical value and an attribute that treasures wide range applications. Among the microbes, fungi to be the best source for lipase production in agro-industrial residue using solid state fermentation (SSF). One of agro-industrial residue is coconut pulp waste. The aims of this study is to explore the possibility of coconut pulp waste for producing of lipase using fungi isolate, Aspergillus niger and find the partial optimum condition of lipase production based on 2 parameters only. The crude enzyme was extracted by mixing fermented substrate with 50 mL sterile aquades pH 7 containing 0.01% Tween-80. The protein concentrations are determined by Bradford method using spectrophotometric. Lipase activity was followed the titrimetric method. The SSF was carried out with variation of initial spore concentration of 1×105, 1×106, 1×107, and 1×108 (spores.mL−1) and crude enzyme was harvested by adding 25, 50, 75, 100, and 125 (mL) of extract solution. The result showed that initial spore concentration and extract solution affected of lipase production. The SSF in coconut pulp waste using A. niger has successfully produced lipase with optimum condition were achieved by adding spore concentration inoculum 1×106 spore.mL−1 in acidic condition at 30°C for 7 days and extracted by 75 mL of extract solution that was result 72.5 mL of crude enzyme with lipase activity 10.83 U.mL−1 and protein content 0.074 mg/mL−1.
Biosorption of Synthetic Dye from Batik Wastewater Using Trichoderma viride Immobilized on Ca-Alginate
Authors: Rahmaniah G , Mahdi C , Safitri A 
Published: November 2019

Abstract
Batik and textile industry is one of the sources of liquid waste derived from the staining process. One of the color substances commonly used is remazol brilliant violet which is an azotype substance that is difficult to be degraded in the environment and is toxic pollutants. A method that can be used to decolorize of synthetic dye is biosorption. Trichoderma viride can be used as biosorbent, since it is resistant to toxic compound. The immobilization of T. viride is applied to increase their stability and to minimize cellular damage. Calcium alginate can be used for immobilization matrix because it is affordable, non-toxic and biocompatible. This study focused on determining the optimum conditions on biosorption process of remazol brilliant violet using immobilized T. viride. Remazol brilliant violet solution were absorbed at pH 4, 5, 6, 7, 8, and 9, contact time for 10, 20, 30, 50, 60, 70, and 90 min, and the amount of adsorbent used were varied at 0.3; 0.4; 0.6; 0.8; and 1 g. The optimum condition was obtained at 60 min biosorption time, at pH 4 with the amount of adsorbent was 1 g, with percent of adsorption was 8.76%. The adsorption capacity of remazol brilliant violet using T. viride immobilized with Ca-alginate was 0.089 mg/g. FTIR spectra results indicated functional groups that involved in immobilization of T. viride were O-H and C=O carboxylic, while in biosorption process violet were C-H sp3, C=O carboxylic, C=O amide and C=C benzene.
The effect of kaffir lime (Citrus hystrix DC) essential oil on bioplastic derived from cassava peel waste
Authors: Masruri M , Azhar A Z , Rosyada I , Febrianto A 
Published: November 2019

Abstract
Kaffir lime essential oil is reported contain a biologically active secondary metabolite from the class of terpenoid. It was reported active as antibacterial, antioxidant, and anticancer. Combination of this bioactive essential oil to afford bioplastic or biodegradable plastic will open their future applications in industry and medicine. This paper report the characteristic of the combining of kaffir lime essential with starch from cassava peel waste to produce bioplastic. The FTIR spectroscopy, SEM, XRD and elasticity test was reported to the bioplastic produced. In short, bioplastic prepared from both starting materials are able to be made. The appearance is clear and transparent. The FTIR spectra also provide a combination of both functional groups, and some fractures found to the bioplastic without addition of kaffir lime essential oil. Interestingly, elasticity improves for bioplastic composed of essential oil.
Antioxidant activity of vacuum column chromatography fractions of ethanol extract of sarang banua (Clerodenrum fragrans vent willd) leaves
Authors: Simorangkir M , Nainggolan B , Silaban S 
Published: November 2019

Abstract
Sarang banua plants are found in Simalungun, North Sumatra, Indonesia, which have been used by the community as traditional medicinal plants. The result of plant determination, sarang banua plant is a type of Clerodendrum fragrans Vent Willd, including the family Verbenaceae. The antioxidant activity of vacuum column chromatography fractions of ethanol extract of C. fragrans leaves was completed. This study aims to find a pure fraction through vacuum column chromatography from the ethanol extract of C. fragrans leaves which has antioxidant activity. Purification of ethanol extract of C. Fragrans was carried out using vacuum column chromatography with silica gel 1.07733.1000 stationary phase and n-hexane, ethyl acetate and methanol as mobile phase. The antioxidant activity test of the fractions were carried out by DPPH free radical reduction method. The antioxidant test results using the DPPH free radical scavenging method showed that the F5 fraction had higher antioxidant activity than F4 and F3 fractions with IC50 values in a row 19.80; 24.65 and 84.02 ppm. The IC50 value of vitamin C as a positive control is 22.25 ppm. The F5 fraction has antioxidant activity higher than Vitamin C (positive control) and includes a very strong category of antioxidants.
Interaction of cadmium-cysteine binding and oxidation of protein causes of blood thrombosis
Authors: Marisa D , Aflanie I , Muthmainah N , Suhartono E 
Published: November 2019

Abstract
Thrombosis occurs if the balance between thrombogenic factors and protective mechanisms is disrupted. These disorders can be caused by endothelial disorders due to the presence of heavy metals such as cadmium (Cd). These amino acid residues can bind Cd metal covalently with the -S-S-, -C-S-, -SH, and phenyl groups, which are present in the amino acid residues. This situation causes changes in the structure of the protein, so that it becomes modified and forms a blood clot (thrombosis). However, the spectroscopic interaction of cadmium-cysteine as causes of thrombosis has not been widely studied. Therefore, this research needs to be done. The research conducted was an experimental study with posttest control with group design. This study used healthy blood obtained from PMI Banjar regency. This study used one control group and three treatment groups, namely P0 = control group, blood without Cd; P1 = blood group with Cd 0.003 mg/l; P2 = blood group with Cd 0.03 mg/l; P3 = blood group with Cd 0.3 mg/l; P4 = blood group with Cd 3 mg/l. Furthermore, each group was incubated for 45 minutes at 37°c. Then cloth weight, AOPP levels, and absorbance were measured at wavelengths 253 nm. The results showed that an increase in cadmium levels caused an increase in the rate of thrombosis. This increase is associated with an increase in AOPP levels. Cadmium can bind covalently with cysteine and other amino acids which results in the breakdown of peptide bonds. The study concluded that cd accelerated the rate of thrombosis due to increased protein oxidation (aopp). This oxidation is caused by binding cd to cysteine with kbind = 0.355.