bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment of wind energy potential of Hat Yai (Songkhla), Thailand
Authors: Kamdar I , Taweekun J 
Published: August 2021

Abstract
Due to environmental problems associated with fossil fuels and rising need for energy, wind power renewable energy will play a vital role in transformation of future energy structure in Thailand. Exploitation of wind energy for sustainable development, wind resource assessment plays an important role in wind power utilization. This case study presents wind resource assessment using the wind atlas analysis and application program (WAsP), in order to assess the potential of wind energy in Hat Yai, Thailand. Ten-minutes interval wind data observed by the Thai Meteorological Department recorded during the period 2017-2019, have been used to harness adequate wind power density and wind energy potential. The annual mean wind speed is 3.5 m/s at 10 m height above the ground. The prevailing direction southwest, south and northeast of the wind rose are very pronounced. The WAsP analysis estimates about 2,731.28 MWh of the total net annual energy production for the specific sites using the Enercon E-18 (80 kW) wind turbine of 1.92 MW capacity. The findings of this study indicate the possibility of the small-scale wind farm project for electricity generation in future.
Effect of pour point depressants and diluents on exergy destruction during pipeline transportation of crude oil
Authors: Kulkarni A D , Wani K S 
Published: August 2021

Abstract
Exergy destruction in pipeline flow of crude oils mixed with pour point depressants (PPD) and diluents has been investigated. Ethylene vinyl acetate with vinyl acetate content of 18% and 28% (EVA-18 and EVA-28) and Polymethyl methacrylate (PMMA) with concentrations of 200 ppm, 1000 ppm and 1500 ppm were chosen as the PPDs for this purpose. Four different diluents were considered viz. n-hexane, cyclohexane, n-butanol and toluene representing paraffins, naphthenes, alcohols and aromatics respectively. The viscosity reduction was found out experimentally. Using these results for a hypothetical pipeline, the effect of API gravity of crude oil, pipeline diameter, Reynolds number, PPD concentration and diluent type on exergy destruction was investigated. These findings would help in making a prudent choice of PPD and diluents for efficient transportation of crude oil through pipelines.
An Investigation of Factors Affecting Measurement Accuracy of Nanoparticles Real-time Sensor using Corona Discharge integrated with Quartz Crystal Microbalance
Authors: Vichayarom Nichakran , Jaruwongrangsri Kata , Tekasakul Perapong , Dejchanchaiwong Racha 
Published: August 2021

Abstract
A nanoparticles real-time sensor in the present study was designed using corona discharge integrated with quartz crystal microbalance (QCM) or Nano-QCM detector. We investigated the following factors affecting the measurement accuracy of the detector; needle to plate distance, flow rate, and number of particles on QCM. DC high voltage power supply of 7 kV was used to maintain the positive corona voltages difference in the charger. The mass sensitivity of 10 MHz AT-cut QCMs coated by plate rigid gold film were investigated. The monodisperse aerosol particles smaller than 300 nm were initially used for the testing of the system. They were charged with negative corona voltages and then deposited on the surface of QCM electrode. Sauerbrey equation was used to describe the frequency-mass relationship at the QCM surface. Results show that the above factors significantly affect the accuracy of the detector measurement. The particles can be collected on a QCM electrode using the partial breakdown high voltage (reach to breakdown points) in terms of needle-to-plate corona discharge. The optimal needle-to-plate distance is 6 mm with maximum mass change (frequency shift) on QCM electrode of 0.607μg/min. The QCM collection efficiency of nanoparticles on the QCM electrode surface using corona discharge technique can be as high as 95% of total particles. Collection efficiency of PM0.1 is under investigation.
Design of Fixture for Welding
Authors: Naksri Chanada , Chuchom Somchai , Chaiprapat Supapan 
Published: August 2021

Abstract
Defects commonly found in welding include distortion, overlapping, warping, and misalignment. Welders probably observe more frequent problems as such if lacking proper fixturing devices. Existing fixture designs are tedious to use, and they could induce even more defects. In this study, four design alternatives of a welding fixture were initially conceptualized from a survey of 25 experienced welders before the best one was selected based on reliability, rigidity, and ease of use. The design was made of SS400 steel because of its exceptional mechanical and thermal properties. A structural analysis was performed using the finite element method to evaluate the strength and stability of the design while in use. Experimental results revealed that this fixturing device could withstand forces exerted vertically from screw clamping. It could also tolerate high temperature from a welding arc and restrain the workpiece as deformed by the heat. This novel design will minimize set-up time, chances of defect formation, and a need for post-welding quality improvement.
Optimization of operating parameters for rubber sheet fast drying in a forced-convection rubber smoking room
Authors: Intararak Pennung , Dejchanchaiwong Racha , Tekasakul Perapong 
Published: August 2021

Abstract
A new design of a rubber smoking room for fast drying based on conventional rubber smoking room was tested. Effects of the operating parameters for the fast drying of rubber in a forced-convection rubber smoking room were investigated. Temperature distribution, moisture content, thermal efficiency, specific fuelwood, electricity and energy consumption were evaluated for drying of 1,500 rubber sheets. The suitable operating condition from the experiment is 60°C and 12 m/s for the temperature and velocity. The rubber sheet moisture content was reduced to 0.4% db within 36 hours, i.e. 36 hours less than conventional smoke drying. The variation temperature inside the rubber smoking room was near uniform with a maximum of 8.0°C. The temperatures ranges were 38.9-64.6°C at the front plane, 40.4-65.0°C at the middle plane, and 36.7-62.9°C at the rear plane. A new rubber smoking room can save up to 49.3% in fuelwood consumption as compared to conventional rubber smoking room. Hence, the new rubber smoke drying system is capable of enhancing thermal efficiency and saving energy compared to existing rubber smoking room.
Preparing Fluorescent Conjugated Polymers through One Pot Enzymatic Polymerization for Sensing Applications
Authors: Kiratitanavit W 
Published: August 2021

AbstractFluorescence based polymeric sensors are simple, extremely sensitive, versatile and adaptable for detection of different types of analysts. However, the multi-step synthesis using toxic chemicals followed by purification is often required for obtaining these fluorophores. Here the possibility of utilizing enzymes as the catalyst, for the one step polymerization of naturally occurring monomers to yield fluorescent conjugated polymers is presented. Four monomers, 4- Hydroxyphenylacetic acid (HPA), Hydroxytyrosol (HDT), Chlorogenic acid (CGA) and Serotonin (Sero) were polymerized using Horseradish peroxidase as the biocatalyst. The broad peaks of IR spectrum were obtained from all polymers comparing with the sharp peaks of monomers. The decrease of UV-Vis intensity at significant wavelength of each monomer was found when the polymer was formed. These polymers exhibit fluorescence with significant stokes shift around 100 nm rendering them useful in fluorescence quenching-based sensors. In the detection of lead ion, DNT and TNT in solution through fluorescence-quenching are studied. Both nitro aromatic compounds were detected from electron interaction between phenol and nitro-aromatic compound structures that poly(HPA) and poly(Sero) detected at 1 ppm level. From having carboxylic group, poly(HPA) detected lead at 50 ppb at neutral pH.
An Assessment of the Implications of Biodiesel Consumption Promotion in the Transportation Sector for Thailand
Authors: Purathanang T , Wattana S 
Published: August 2021

Abstract
This paper assesses the implications of the promotion of biodiesel consumption in the Thai transportation sector in terms of energy, environment and agriculture. In order to analyse the implications, scenarios are modelled quantitatively to assess their impacts for the period 2019-2037. Scenarios developed in this paper represent various percentages of biodiesel blending mandates including REF (7% biodiesel blend), B10 (10% biodiesel blend) and B20 (20% biodiesel blend). The analytical tool employed to assess the scenario impacts is the Low Emissions Analysis Platform (LEAP) model. The analyses suggest that an increase in percentage share of biodiesel blend would contribute to a reduction in diesel consumption and hence crude oil requirement. Consequently, it would generate less CO2 emissions and especially less Fine Particulate Matter (PM2.5) - an issue of contemporary environmental health concerns. It is, further, revealed that higher shares of biodiesel in diesel would result in an increase demand for oil palm production in order to meet a rising growth in biodiesel production. Such an increase in demand for oil palm feedstock would result in higher commodity prices and therefore higher income for farmers. However, a high oil palm production demand would require a substantial crop cultivation area. The effort to increase palm planting and productivity to meet the growing demand is a challenging task. In order to overcome this challenge, this paper suggests the implementation of agricultural zoning and the advancement of crop species and biodiesel conversion technology.
Progressive Web App for Crop Field Data Collection
Authors: Koysawat Phunon , Boonprakob Chayanon , Saengprachatanarug Khwantri , Chaosakul Arnut , Wanjantuk Panupong , Wongphati Mahisorn , Santiteerakul Santawat , Chinapas Adulwit , Saikaew Kanda Runapongsa 
Published: August 2021

Abstract
General farming needs to have a matter of data collection. For efficient cultivation planning and harvesting, information must be collected for evaluation and analysis to make each harvest decision. For example, we need to assess plants’ ages, changes in size, color, and other senses (sweetness, smell, etc.) to plan for different crop field growth phases. Also, data collection problems occur due to the need to collect data in multiple locations simultaneously. Collecting information manually in the form of documents makes the process challenging to analyze. There is a need to collect field data more efficiently. Thus, this article proposes developing a web application to replace manual note-taking to reduce errors in recording and gathering data and missing data. Users can locate and modify crop field locations using latitude and longitude and work seamlessly with the Google Earth application. Furthermore, to accommodate practical use in real-life, the web application developed using Progressive Web Application (PWA) can perform without the Internet. Besides, PWA web applications are as fast as using an application on a smartphone without downloading and saving space. Based on the experimental result, compared with the process without using the application, it was found that the proposed application could reduce time in collecting sugarcane sampling data by about 45.28%
Prediction of Vegetarian Food Preferences for the Aging Society
Authors: Kengpol Athakorn , Punyota Wilaitip 
Published: August 2021

Abstract
The objective of this research is to predict vegetarian food preferences from chronic disease among the elderly by using a hybrid method that includes both an artificial neural network (ANN) and particle swarm optimization (PSO), called ANN-PSO. ANN is a mathematical model that mimics the human brain that is intelligent in learning, prediction, recognition, classification by practice, and solving complex problems. In this study, data collection of vegetarian food preferences, including gender (male and female), a chronic disease selected from the diseases that are common among the elderly, and a vegetarian menu suitable for the chronic disease. Data were collected by interviewing 100 elderly people. Then, the data were analysed using artificial neural networks and applied the particle swarm optimization method to determine the appropriate parameters (weights) for the neural network. The results indicate that the application of PSO along with ANN can accurately predict vegetarian preferences for the aging society. The accurate vegetarian prediction model resulted in increasing consumption of vegetarian food and allowed manufacturers to produce meals or present menus tailored to the individual preferences of the elderly.
Comparison of machine learning algorithms for mortality prediction in intensive care patients on multi-center critical care databases
Authors: Pattalung Thanakron Na , Chaichulee Sitthichok 
Published: August 2021

AbstractCurrent scoring systems for mortality prediction in intensive care patients are usually applied once after 24 hours of admission, as all parameters needed for scoring are not yet available. In addition, several parameters are dynamic and may change according to patient conditions. It is hypothesized that mortality prediction should be made at the earliest when relevant information becomes available and continuously during patient stay. This study focuses on the development of algorithms for mortality prediction from vital signs and laboratory results based on the data from three recent critical care databases, i.e. the eICU collaborative research database, the Multiparameter Intelligent Monitoring in Intensive Care III (MIMIC-III) database, and the MIMIC-IV database. We employed logistic regression, κ-nearest neighbours, neural networks and tree-based classifiers for such problem. Our models had the area under the receiver operating characteristic curve (AUROC) ranging from 0.67 – 0.95. Reliable mortality prediction can be made as early as the first 4 hours after ICU admission. We provided comprehensive analysis on different time frames used for prediction, models trained with top attributes, models trained with data combination, and missing values. Our results provide guidelines and benchmarks for the development of such algorithm in local narratives.
Quantification of climate change mitigation potential at Novi Sad landfill
Authors: Milovanovic D , Zivancev M , Ubavin D , Bezanovic V , Petrovic M 
Published: August 2021

Abstract
Unsanitary landfills and inadequate waste management system represent the 3rd largest global anthropogenic source of methane emissions in the environment. Waste management system in Novi Sad, the second largest city in Serbia, significantly contributes to the national carbon footprint. Unsanitary Municipal solid waste landfill in Novi Sad receives and deposits mixed waste without any treatment, thus causing the organic waste to biodegrade within the landfill body, and produce and emit the landfill gas (mostly CH4 and CO2) in the environment. Other potential sources of greenhouse gas emissions from waste management system include vehicles used for waste collection, machinery used at the landfill and landfill fires. The purpose of this study is to determine total baseline emissions of relevant greenhouse gases from the waste management system in Novi Sad, and to estimate and quantify the emission reduction potential for defined organic waste treatment scenario. The potential scenarios for organic waste diversion and treatment from the landfill include composting, anaerobic digestion, mechanical biological treatment, waste to energy, etc. Quantification of baseline emissions and climate change mitigation potential are estimated using the Solid Waste Emissions Estimation Tool, the model developed by Climate and Clean Air Coalition.
Performance Evaluation of Vertical Axis Wind Turbine on Highways
Authors: Shoib Abdul Rashid , Binti Azhar Siti Khadijah , Didane Djamal Hissein , Mohammed Akmal Nizam , Ogab Mohammed , Afolabi Lukmon Owolabi 
Published: August 2021

Abstract
The consumption of electricity at highways is increasing over time, consequently, more fossil fuel is burned to generate more electrical energy. However, this expensive cost of burning fossil fuels can be saved by replacing them with renewable energy sources such as wind energy. Wind energy can be generated by using a wind turbine. Therefore, this study aims to develop a vertical axis wind turbine (VAWT) that can work effectively in highway wind speed conditions while evaluating its performance in terms of torque and power by using a simulation approach. The simulation involves the use of K-omega shear-stress transport (SST) as the turbulence viscosity model. The VAWT undergoes two types of tests during the simulation process. In Test 1, the wind turbine is tested with a various number of blades at constant wind speed to find which model has the best performance in terms of torque and power output. Then, the selected model with the better output proceeds to Test 2 where it is tested with different sizes of blade radius. The results have shown that a Savonius wind turbine with five blades produces more torque and power output compared to the other rotors with two, three and four blades reaching the maximum at 140 RPM. In terms of blade radius, the model with a 400 mm radius has a better performance and capable of producing higher torque and power output than the other blade sizes.
Cluster decomposition principle and two-electron wave function of the Cooper pair in the BCS superconducting state
Authors: Higuchi Katsuhiko , Higuchi Masahiko 
Published: August 2021

Abstract
We present the explicit forms of the maximum eigenvalue and the corresponding eigenfunction for the second-order reduced density matrix (RDM2) of the BCS superconducting state (SS). Using these quantities, we deal with two topics in the present paper. As the first topic, it is shown that the cluster decomposition principle holds in the BCS-SS. This proof gives a theoretical foundation that the abnormal density can be chosen as the order parameter of the SS. As the second topic, it is shown that such an eigenfunction is spin singlet and spatially extends isotopically, and further that the mean distance of two electrons which consists of the above eigenfunction is in a good agreement with Pippard’s coherence length. This means that maximum geminal of the RDM2 of the BCS-SS can be regarded as the Cooper pair itself which are condensed to the same energy level in a number of

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Discourses between the Public and the Private: Transnational Families at the Crossroads
Authors: Purkarthofer Judith , Lanza Elizabeth , Berg Mina Finstad 
Published: August 2021

AbstractRaising a child is a challenging venture, regardless of where one lives in the world. Most children are raised in their families; however, many states have welfare services if the child’s well-being is at stake. Scandinavian countries follow a rather strict policy in placing the child’s individual rights above those of the family, and Norway has child welfare legislation that applies to all children in the country, regardless of their status, nationality or citizenship. This institutional structure has raised issues about how family life is negotiated in society. In this article, we analyze the ways in which language and culture are used to address expectations of (good) normal family life in both private and public discourses with implications for transnational families. We thus problematize the notion of the family as a private domain or space. Furthermore, by examining institutional involvement in child-rearing, we extend research on family language policy to contexts of foster care. We thereby raise the discussion to a societal level about private and public expectations towards family life in a late-modern society.
Genome sequencing data analysis for rare disease gene discovery
Authors: Umlai Umm-Kulthum Ismail , Bangarusamy Dhinoth Kumar , Estivill Xavier , Jithesh Puthen Veettil 
Published: August 2021

AbstractRare diseases occur in a smaller proportion of the general population, which is variedly defined as less than 200 000 individuals (US) or in less than 1 in 2000 individuals (Europe). Although rare, they collectively make up to approximately 7000 different disorders, with majority having a genetic origin, and affect roughly 300 million people globally. Most of the patients and their families undergo a long and frustrating diagnostic odyssey. However, advances in the field of genomics have started to facilitate the process of diagnosis, though it is hindered by the difficulty in genome data analysis and interpretation. A major impediment in diagnosis is in the understanding of the diverse approaches, tools and datasets available for variant prioritization, the most important step in the analysis of millions of variants to select a few potential variants. Here we present a review of the latest methodological developments and spectrum of tools available for rare disease genetic variant discovery and recommend appropriate data interpretation methods for variant prioritization. We have categorized the resources based on various steps of the variant interpretation workflow, starting from data processing, variant calling, annotation, filtration and finally prioritization, with a special emphasis on the last two steps. The methods discussed here pertain to elucidating the genetic basis of disease in individual patient cases via trio- or family-based analysis of the genome data. We advocate the use of a combination of tools and datasets and to follow multiple iterative approaches to elucidate the potential causative variant.
qTeller: a tool for comparative multi-genomic gene expression analysis
Authors: Woodhouse Margaret R , Sen Shatabdi , Schott David , Portwood John L , Freeling Michael , Walley Justin W , Andorf Carson M , Schnable James C 
Published: August 2021

Abstract

Motivation
Over the last decade, RNA-Seq whole-genome sequencing has become a widely used method for measuring and understanding transcriptome-level changes in gene expression. Since RNA-Seq is relatively inexpensive, it can be used on multiple genomes to evaluate gene expression across many different conditions, tissues and cell types. Although many tools exist to map and compare RNA-Seq at the genomics level, few web-based tools are dedicated to making data generated for individual genomic analysis accessible and reusable at a gene-level scale for comparative analysis between genes, across different genomes and meta-analyses.

Results
To address this challenge, we revamped the comparative gene expression tool qTeller to take advantage of the growing number of public RNA-Seq datasets. qTeller allows users to evaluate gene expression data in a defined genomic interval and also perform two-gene comparisons across multiple user-chosen tissues. Though previously unpublished, qTeller has been cited extensively in the scientific literature, demonstrating its importance to researchers. Our new version of qTeller now supports multiple genomes for intergenomic comparisons, and includes capabilities for both mRNA and protein abundance datasets. Other new features include support for additional data formats, modernized interface and back-end database and an optimized framework for adoption by other organisms’ databases.

Availability and implementation
The source code for qTeller is open-source and available through GitHub (https://github.com/Maize-Genetics-and-Genomics-Database/qTeller). A maize instance of qTeller is available at the Maize Genetics and Genomics database (MaizeGDB) (https://qteller.maizegdb.org/), where we have mapped over 200 unique datasets from GenBank across 27 maize genomes.

Supplementary information
Supplementary data are available at Bioinformatics online.