bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lab build Fully Automated microfluduic flow injection System
Authors: Al-Asady Ihsan A , Al-Sowdani K H 
Published: November 2021

Abstract
A fully automated microfluidic Flow Injection spectrophotometric system was designed in our laboratory with methylene blue used as an example. The device consists of a double-line microfluidic chip with dimensions (30 μl x 4 cm), each 15 μl volume intended to allow a very small volume of reagent and sample to be used. The microfluidic system also consists of two types of Arduino software. The first was the UNO of a type used to control the two mini peristaltic pumps to drive the water and methylene blue as carrier stream and sample respectively. The Mega type, which was equipped with homemade software, signal-to-peak, was the second Arduino which used as a data logger to record the results in the form of peaks using Microsoft Excel 2016. The peak’s height was corresponding to concentration. The linearity was in the range (0.025-0.125 μg/ml) with a five-point regression coefficient (0.9981), RSD% for ten replicates is 0.025 μg/mL. The detection limit was (0.001 μg/ml) and the sample throughput was 300 samples per hour and each sample required 25 μl of chemical reagents. Therefore, 240 samples need only (5.0 ml) from the chemical reagents, which clearly indicates that the consumed reagent and the waste were very low. Therefore, the method for determining methylene blue with a fully automated system is very environmentally friendly. save time, consumption regent, Improve quality, decrease cost-consumption reducing the consume of sample and inherited the reproducibility and accurate from flow injection analysis.
Evaluation of synergistic medicinal efficacy of four alkaloidic compounds isolated from Iraqi Allium porrum seeds against staphylococcus aureus bacteria
Authors: Al-Maliki Abbas D M , Ai-Maliki Ala’a A H , Hameed Maha A A 
Published: November 2021

Abstract
Medicinal plants are necessary benefit natural sources for chemical production of different therapies from secondary metabolism. Allium porrum is considered as one of sources of foods and drugs at the same time. So the current work focused on isolation and characterization of four alkaloids from seeds of this plant. These compounds are 2-piperidinone, 2-pyrrolidinone-4-methyl, adenosine-2-deoxy–N-methyl –N-(triflouro acetyl ) and maymarsine by using Gas Chromatography – Mass Spectroscopy (GC-MS) technique. The medicinal activity was achieved to investigate and evaluate the synergistic action of the mixture of the four alkaloidic compounds towards Staphylococcus aureus pathogen. The concentrations of alkaloidic mixture were prepared with values equal to 50,100,125,150,200,250,300,375,400 and 500 mg/ml and they revealed inhibition zones with diameters represented by 31,31,32,35,35,37,41,43,43and 45 mm. So the mixture of the four alkaloidic compounds can be used as natural therapy to treat various inflammatory caused by this pathogenic bacteria.
Synthesis, characterization and spectral studies of mononuclear and binuclear Fe(II), Co (II), Ni (II), Zn(II) complexes with 2,4-dinitrophenylhydrazine dithiocarbamate
Authors: Mohammed Enas Hazim , Ahmed Sahbaa Ali , Zedan Sariya Waleed 
Published: November 2021

Abstract
New complexes of dithiocarbamate of the general formula [M(2,4-dinitrphenhydra - dtc)2], [MM’(2,4-dinithrphenhydra-dtc)4] where: M=Fe (II), Co(II), Ni(II), M’=Zn(II), 2,4- dinitrphenhydra-dtc=2,4- di nitro phenyl hydrazine dithiocarbamate and [M(l,10-phen)3][M’(2,4 – dinitrphenhydra-dtc)4], [M(1,10- phen)3][M’2(2,4-dinitrphenhydra - dtc)6] Where: M=Co(II), Ni(II), M’=Zn(II), (1,10-phen)= 1,10-phenanthroline monohydrate. Have been prepared and characterized by atomic absorption spectroscopy infrared, conductance measurements, electronic absorption spectra, nuclear magnetic resonance and magnetic susceptibility measurements. Magnetic moments and electronic spectra indicate that the complexes of the type [M(2,-dinitrphenhydra-dtc)2], [MM’(2,4-dinitrphenhydra - dtc)4] are of square planner geometry while the complexes of the type [M(1,10-phen)3][M’(2,4-dinitrphenhydra-dtc)4] and [M(1,10 phen)3][M’2(2,4-dinitrphenhydra-dtc)6] have octahedral geometry.
Effect of infill density and raster angle on the mechanical properties of PLA
Authors: Tan M.A. , Yeoh C. K. , Teh P. L. , Rahim N. A. , Song C. C. , Mansor N. S. S. 
Published: November 2021

Abstract
Polylactic acid (PLA) is derived from natural aliphatic polyester resources for instance sugarcane or starch based plants. PLA also known as a biocompatible and biodegradable thermoplastic and found widely in multiple applications like electronic and electrical devices, biomedical, food packaging and the engineering field. PLA have attracted attention in production potential due to its superior attributes like ease of processing, high strength and high modulus. Infill density, raster angle and infill pattern can influence the mechanical characteristics of materials like PLA, acrylonitrile-butadiene-styrene (ABS), polyetheretherketone (PEEK). In this paper, the relationship between infill density and raster angle was studied to investigate the mechanical performances of PLA by using 3D printers. 3D printing is used to fabricate more complex 3D design objects. The tensile test was involved to evaluate the properties of pure PLA. For pure PLA, 0° raster angles with 100% infill density show the highest tensile strength and Young’s modulus which are 28.926MPa and 1262.7MPa respectively. However, a decreasing trend of break elongation reveals in PLA as infill density increases for both 0° and 90° raster angle. Optimization of printing parameters become crucial to provide high quality materials for 3D printing in order for education, packaging, engineering and biomedical applications.
Water Absorption Behaviour of Epoxy/Acrylated Epoxidized Palm Oil (AEPO) Reinforced Hybrid Kenaf/Glass Fiber Montmorillonite (HMT) Composites
Authors: Mustapha Rohani , Mustapha Siti Noor Hidayah , Suriani M. J , Ruzaidi C. M. , Awang M 
Published: November 2021

Abstract
The use of fiber-reinforced vegetable oil - polymer composites has increased in various technical fields. However, the long-term operating performance of these materials is still not well understood, limiting the development of these composites. In this study, the water absorption performance of hybrid composites, which consist of kenaf fiber and glass fiber as reinforcement, epoxy resin and acrylated epoxidized palm oil (AEPO) as a matrix, and montmorillonite (MMT) nano clays as a filler was evaluated with the function of different fibers layering order. The hand lay-up method is used to produce the composites with the variable number of kenaf fibers and glass fibers layer sequences. The water absorption kinetics of epoxy/AEPO reinforced hybrid kenaf/glass fiber-filled MMT composites are described in this paper. It has been observed that the water absorption rate of the composites depends on the fiber layering sequences. The alternative sequence of Glass-Kenaf-Kenaf-Glass and Kenaf-Glass-Kenaf-Glass composites layers exhibited the lowest moisture absorption rates of 7.61% and 7.63%, respectively.
Relationship between morphology analysis and durability of geopolymer paste
Authors: Razak Siti Aisyah , Zainal Farah Farhana , Shamsudin Shaiful Rizam , Nordin MohdNashaAin 
Published: November 2021

Abstract
Geopolymer may improve corrosion protection by slowing the corrosion of steel in concrete or paste. When the alkalinity of the paste is reduced, the passivating layer is destroyed. If the paste is more pores, it can be easily absorbed by NaCl solution or moisture. The improved properties of the geopolymer paste increase its durability by preventing corrosive elements from harming the steel contained within the geopolymer paste. Two types of paste were used in this research which geopolymer paste and Ordinary Portland Cement (OPC) paste. A Scanning Electron Microscope (SEM) was used to determine the surface morphology of geopolymer paste and OPC paste. Based on the result of this investigation, the morphology characterisation is related to the concrete’s endurance. The formation of an aluminosilicate gel during the geopolymerisation process is critical for stability, increasing the geopolymer matrix’s density. As a result, this can increase the durability of geopolymer paste compared to OPC paste which geopolymer also can improve corrosion protection of steel in paste.
Preparation of Composite Banana Peel-TiO2for Methyl Orange Dyes Removal
Authors: Teoh Hui Ling , Ibrahim Siti Aida , Ainuddin Ainun Rahmahwati , Hussin Rosniza , Zakiah Kamdi 
Published: November 2021

AbstractComposite banana peel activated carbon-TiO2has successfully prepared using the sol-gel method. In this research, banana peel was activated using KOH activator. This study aimed to compose biomass wastes (banana peels) with TiO2 catalyst for Methyl Orange (MO) dye removal. The banana peel-activated carbon (BPAC) composition varied from 20, 50 and 70 wt. %. The prepared samples were calcined at 400°C for 4 h. The structure and properties of the prepared samples were characterized by X-ray Diffraction (XRD), Fourier Transmission Infra-Red (FTIR), Scanning Electron Microscope (SEM) and Ultraviolet-Visible Spectrophotometer (UV-Vis). The results obtained from XRD showed the presence of anatase, rutile and potassium formate. The morphological analysis TiO2 showed agglomeration whereas pores were observed in BPAC. FTIR results indicated a C-O stretching and CH functional group formation through a modification that it does not exhibit in pure TiO2. The sample with 50 wt% BPAC-TiO2has the highest MO removal (72.5%) within 3 h of irradiation time. From the current finding, banana peel-activated carbon-TiO2can be commercialized for wastewater remediation especially in treating dye pollution.
Magnetic-Based Coreshell Nanoparticles as Potential Adsorbents for the Removal of Cu2+ Under Ultraviolet (UV) Light
Authors: Husni Hazreen Nadihah , Mahmed Norsuria , Ge Yanling , Norizan Mohd Natashah , Halin Dewi Suriyani Che , Razak Kamrosni Ab , Mohamad Ili Salwani 
Published: November 2021

Abstract
The magnetite (Fe3O4) and maghemite (γFe2O3) nanopartides, magnetite-silica-silver chloride (Fe3O4-SiO2-AgCl) and maghemite-silica-silver chloride (γFe2O3-SiO2-AgCl) coreshell structures have successfully been synthesized by using a simple wet chemistry method. The efficiency of these particles as the adsorbents for the removal of copper ion, Cu2+ in aqueous solution under UV light was investigated. Two different parameters were studied, namely the adsorbents contact time (60, 120, 180, 240 and 300s) and the solution-stirring rate (100, 200 and 300 rpm). From the results, the removal percentage of the copper ions from the solution were above 90% after 5 hours of adsorption process at 300 rpm by using Fe3O4 (94%) and γFe2O3 (92%) nanoparticles. The maximum removal of copper ions was nearly 100% when yFe2O3-SiO2-AgCl & Fe3O4-SiO2-AgCl coreshell particles were used. The samples that were prepared without magnetic core such as AgCl-SiO2, AgCl and SiO2 particles, showed lower percentage of the copper ions removal (78%, 60% and 20%, respectively). This situation shows that the magnetic nanoparticles plays and important role during the adsorption process due to their large active sites for the adsorption to occur.
The Modelling of Heteroscedastics IDR-USD Exchange Rate with Intervention and Outlier Factors
Authors: Mukhaiyar Utriweni , Yudistira Dhika , Indratno Sapto Wahyu , Yaacob Wan Fairos Wan 
Published: November 2021

AbstractThe nonstationary in time series data may be caused by the existence of intervention, outliers, and heteroscedastic effects. The outliers can represent an intervention so that it creates a heteroscedastic process. This research investigates the involvements of these three factors in time series data modelling. It is also reviewed how long the effects of the intervention and outliersfactors will last. The weekly IDR-USD exchange rate in period of May 2015 to April 2020 be evaluated. It is obtained that ARIMA model with the intervention factor gives the best re-estimation result, with smallest average of errors squared. Meanwhile for prediction, the heteroscedastic effect combined with outlier factors gives better results with the lowest percentage of errors. One of the phenomenal interventions in this data is the Covid-19 pandemic, which was started in Indonesia on March 2020. It is found that the effect of the intervention lasts less than five months and the prediction shows that the volatility of IDR-USD exchange rate starts to decline. This shows the stability of the process is starting to be maintained.
Box-Jenkins and State Space Model in Forecasting Malaysia Road Accident Cases
Authors: Husin Wan Zakiyatussariroh Wan , Afdzal Adlina Sofia , Azmi Nur Lisa Hashim , Hamadi Siti Auni Taqiah Sheikh 
Published: November 2021

Abstract
Road accident is one of the main causes of death and injury worldwide in this fast-paced modern world. Many developing countries, including Malaysia, are facing serious road accident problems. Forecasting road accident cases has become an important step towards setting the road safety target. Hence, this study aims to develop forecasting models and forecast future trends of monthly road accident cases in Malaysia. The data set on monthly number of accident cases from January 2001 to December 2019 was provided by Polis Diraja Malaysia (PDRM). Box-Jenkins and State space models were developed using the data under study. The models were then evaluated based on in-sample and out-sample evaluation using lowest root mean square error, mean absolute percentage error and mean absolute error. The results show that the basic structural state space model with trend and seasonal component was the most appropriate model in forecasting road accident cases in Malaysia. The 10-year ahead forecast from January 2020 to December 2030 shows that monthly road accident cases in Malaysia have a constant inclining pattern for each year. It is hoped that the finding from this study could become a reference for the authorities of Malaysia in making recommendations in order to improve road safety and reduce road traffic accidents in Malaysia.
The Geometric Brownian Motion of Indosat Telecommunications Daily Stock Price During the Covid-19 Pandemic in Indonesia
Authors: Edriani Tiara Shofi , Pasaribu Udjianna Sekteria , Afrianti Yuli Sri , Astute Ni Nyoman Wahyu 
Published: November 2021

Abstract
One of the major telecommunication and network service providers in Indonesia is PT Indosat Tbk. During the coronavirus (COVID-19) pandemic, the daily stock price of that company was influenced by government policies. This study addresses stock data movement from February 5, 2020 to February 5, 2021, resulted in 243 data, using the Geometric Brownian motion (GBM). The stochastic process realization of this stock price fluctuates and increases exponentially, especially in the 40 latest data. Because of this situation, the realization is transformed into log 10 and calculated its return. As a result, weak stationary in variance is obtained. Furthermore, only data from December 7, 2020 to February 5, 2021 fulfill the GBM assumption of stock price return, as

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. The main idea of this study is adding datum one by one as much as 10% – 15% of the total data

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, starting from December 4, 2020 backwards. Following this procedure, and based on the 3% < p-value < 10%, the study shows that its datum can be included in

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is selected for modelling. Thus, GBM succeeded in representing the stock price movement of the second most popular Indonesian telecommunication company during COVID-19 pandemic.
Irregular Symmetrical Object Designed By Using Lambda Miu B-Spline Degree Four
Authors: Sukri Nursyazni Binti Mohamad , Mohd Puteri Ainna Husna Binti Megat , Nor-Al-Din Siti Musliha Binti , Razali Noor Khairiah Binti 
Published: November 2021

Abstract
In Computer Aided Geometry Design (CAGD), B-splines curves are piecewise polynomial parametric curves that play an important role. CAGD involves the interpolation and approximation curves and surfaces. CAGD has been widely used which brings good impact of computers to industries in manufacturing. There are many improved methods in the B-spline curve such as extended cubic B-spline, trigonometric B-spline, quasi trigonometric B-spline, and λμ-B-spline. Each of the methods has its behaviour and advantage. In this paper, λμ-B-spline was used to be implemented in generating irregular symmetrical objects. λμ-B-spline has a shape parameter that can change the global shape by manipulating the value of the shape parameter. The bottle has been chosen as an irregular symmetrical object. The 2-dimensional symmetrical curves of Bottle design were formed by using λμ-B-spline degree 4. The curves designed are dependent on the shape parameter which can be adjusted. Then, the curves generated were revolved using the Sweep Surface method to form 3-dimensional objects. Every object has its volume and this research focused on the numerical method which was Simpson’s 3/8 to compute the volume. The volumes obtained were compared to the actual volume to determine the best shape parameter used. The results show that the λμ-B-spline curve with a shape parameter of 1 is the best shape parameter in designing symmetrical irregular objects with the desired volume.
University Students’ Readiness for Job Opportunities in Big Data Analytics
Authors: Yusoff Sarah , Noh Nur Hidayah Md , Isa Norulhidayah 
Published: November 2021

Abstract
This study aims to explore the students’ level of readiness in taking up job opportunities in big data analytics and determine the contributing factors to students’ readiness. In addition, the crucial factors that need to be resolved are identified. This job field requires some significant criteria such as, willing to work as a team, self-effort, and specialised skills such as data visualisations and data storytelling, big data analysis, and basic knowledge on tools for big data analytics. Intellipaat.com, a platform that offers various professional online training courses, has ranked position in big data analytics and data science as the highest paying jobs in 2019. However, from 2019 onwards, Malaysia has been predicted to suffer a shortfall of data analysis professionals of up to 7,000-15,000. Our educational institutions are being encouraged to create more graduates to meet this need. The question arises on whether students are prepared and willing to work in this sector once they graduate. An online survey was constructed and distributed to all UiTM students enrolled in various bachelor’s degrees and master’s programmes. One hundred and thirty-nine students participated in this survey. A graphical tool for data tabulation was presented using a box-and-whisker plot. Additionally, correlation analysis and multiple regression were used to determine the relationship and factors that can contribute the students’ readiness for job opportunities in big data analytics. The results from the box-and-whisker plot have discovered an excellent sign of students’ readiness towards job opportunities in big data analytics. Correlation analyses has shown a weak to moderate relationship among factors and multiple linear regression analyses revealed the data visualisation including storytelling skill (DVSS) and teamwork (TW) have significantly given some impacts on the students’ opportunity in big data analytics career. The results of this study are expected to provide insights into students’ readiness for job opportunities in big data analytics.
Age Group Classification using Convolutional Neural Network (CNN)
Authors: Mustapha Muhammad Firdaus , Mohamad Nur Maisarah , Osman Ghazali , Ab Hamid Siti Haslini 
Published: November 2021

Abstract
Age group classification is a complex task that is used to classify facial images or videos into predetermined age categories. It is an important task due to its numerous applications such as health, security, authentication system, recruitment, and also in intelligent social robots. Convolutional Neural Network (CNN) has recently shown excellent performance in analysing human face images and videos. This paper proposed an age group classification task using CNN that trained and tested with an All-Age Face (AAF) dataset. FaceNet deep learning model that uses CNN was applied in this study to compute a 128-d embedding that quantifies the face of the age group. The experiment included two age groups: Adolescence and Mature Adulthood. The proposed age group classification model achieved 84.90% accuracy for the training images and 85.12% accuracy for the test images. The experimental results showed that CNN is capable of achieving competitive classification accuracy throughout two age groups in the AAF dataset with unbalanced data distribution.
Design of a compact reconfigurable bandpass filter using interdigital capacitor, DMS slots and varactor diode for wireless RF systems
Authors: Belmajdoub A. , Jorio M. , Bennani S. , Das S. , Madhav B.T.P. 
Published: November 2021

Abstract
This paper proposes a new design of a reconfigurable
bandpass filter based on an interdigital capacitor and varactor
diode for wireless and mobile applications. The designed
reconfigurable bandpass filter has been implemented on an RT 6010
substrate with a relative dielectric constant of 10.2, thickness of
1.27 mm, and loss tangent of 0.0023. In order to reduce the filter
size, the defected microstrip structure (DMS) is used due to its
easy design, high compactness, high quality factor and easy
integration with other RF devices. The suggested reconfigurable
filter has a simple structure with a very attractive compact size of
4.7 × 8.4 mm2, low insertion loss than -1 dB, and
tuning range (2–2.6 GHz).
The role of seafood in sustainable diets
Authors: Koehn J Zachary , Allison Edward H , Golden Christopher D , Hilborn Ray 
Published: November 2021

Abstract
Recent discussions of healthy and sustainable diets encourage increased consumption of plants and decreased consumption of animal-source foods (ASFs) for both human and environmental health. Seafood is often peripheral in these discussions. This paper examines the relative environmental costs of sourcing key nutrients from different kinds of seafood, other ASFs, and a range of plant-based foods. We linked a nutrient richness index for different foods to life cycle assessments of greenhouse gas (GHG) emissions in the production of these foods to evaluate nutritional benefits relative to this key indicator of environmental impacts. The lowest GHG emissions to meet average nutrient requirement values were found in grains, tubers, roots, seeds, wild-caught small pelagic fish, farmed carp and bivalve shellfish. The highest GHG emissions per nutrient supply are in beef, lamb, wild-caught prawns, farmed crustaceans, and pork. Among ASFs, some fish and shellfish have GHG emissions at least as low as plants and merit inclusion in food systems policymaking for their potential to support a healthy, sustainable diet. However, other aquatic species and production methods deliver nutrition to diets at environmental costs at least as high as land-based meat production. It is important to disaggregate seafood by species and production method in ‘planetary health diet’ advice.