bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanisms of electrical energy management on different tariffs of industrial enterprises
Authors: Muratov Kh , Kodirov K , Kodirov D
Published: July 2020

This article addresses the issues of monitoring energy consumption modes to reduce production costs when tariffs that divide consumers’ electricity bills by day, weekdays, and seasons. Taking into account the aforementioned issue, the proper use of time-differentiated tariffs has led to some changes in the operating mechanisms of industrial enterprises to monitor their operating modes.
Algorithm for power systems mode optimization taking into account the frequency change in terms of probablistic nature of initial information
Authors: Gayibov T , Latipov Sh , Abdurashidov D , Pulatov B , Davirov A
Published: July 2020

The task of power systems mode optimization relates to the complex tasks of non-linear mathematical programming. Despite the development over the past few decades many methods and algorithms for solving this problem, questions of their improvement taking into account the current operating conditions of energy systems remain an important task. This article proposes a new algorithm for the optimization of short-term modes of power systems, taking into account frequency changes in terms of the probabilistic nature of initial information. A distinctive feature of the algorithm is associated with the elimination of the need to choose the single slack bus with balancing power plant in calculations, which is typical for many existing methods. It is shown that taking into account frequency change in the optimization of power system mode in terms of probabilistic nature of initial information can introduce significant changes in the calculation results and lead to a corresponding increase in the resulting economic effect.
Comparison of the reinforcing concrete structures performance of hydraulic structures with carbon fiber composite material
Authors: Maksudov I , Maksudova L , Abdukhalilov A , Bozorov A , Mirzaliev R
Published: July 2020

Today, in the construction field, high-strength textile materials are increasingly practiced with the external reinforcement of structural elements. For the manufacture of textile externally reinforcing materials, they are mainly used: fiberglass, basalt, carbon fiber, and other high-strength fibers and threads. In combination with an epoxy or polyester matrix, they form an unconventional building material - carbon fiber. Carbon fiber - in comparison with conventional building materials, it has a number of indisputable advantages, such as high tensile strength, low specific gravity, high ability to resist corrosion. Carbon fiber is currently listed as the most promising material used in construction. However, its use is often limited by high prices for reinforcing material, because of this, the use of such material in the designs of large structures is economically irrational. The conclusion is made that it is necessary to determine the best reinforcement method in which the least amount of material is spent without loss of quality.
Biomechanical Evaluation of Insole for Badminton Players: A Preliminary Study
Authors: Rashid Amir Mustakim Ab , Kadir Mohammed Rafiq Abdul , Ramlee Muhammad Hanif
Published: July 2020

Study in sports biomechanics is a demand field for any athletes due to the fact that it can contribute a lot for the improvement of sports performance. One of them is a study on badminton games where the athletes are normally perform many movements with a combination of usage of sport shoes and insoles. It should be noted that analysis on the badminton games and insoles are very limited in the literature. Therefore, this paper is presenting an art of development process of three-dimensional model of bone and insole in order to simulate the condition of badminton games via finite element method. Computed tomography images were used to reconstruct the bones using Mimics software whereas insole was developed using Gensole®. The bones were reconstructed by setting a Hounsfield Unit (226 to 3071) to differentiate the cortical bone. Anthropometric procedure was firstly used to develop the insole of Slazenger. For the preliminary analysis, the models were used to simulate the landing phase of the badminton player where the inferior part of the insole were lifted at 2° with a total of 2.57 times of body weight was applied from the bottom of insole. From the results, it is shown that the von Misses stress were observed at the contact point between bones and insole. From the preliminary results, the stress distribution on the insole is higher at certain points, might due to a larger contacted part. Nevertheless, a detail of foot and ankle joint should be developed in the future to mimic the real condition of the landing phase of athletes.
Automated badminton smash recognition using convolutional neural network on the vision based data
Authors: Rahmad N A , As’ari M A , Soeed K , Zulkapri I
Published: July 2020

Sport performance analysis in sports practice cannot be separable. It is important to help coach analyse and improve the performance of their athletes through training or game session. Due to the advancement of technology nowadays, the notational analysis of the video content using various software packages has become possible. Unluckily, the coach needs to recognize the actions manually before doing further analysis. The purpose of this study is to formulate an automated system for badminton smash recognition on widely available broadcasted videos using pre-trained Convolutional Neural Network (CNN) method. Smash and other badminton actions such as clear, drop, lift and net from the video were used to formulate the CNN models. Therefore, two experiments were conducted in this study. The first experiment is the study on the performance between four different existing pre-trained models which is AlexNet, GoogleNet, Vgg-16 Net and Vgg-19 Net in recognizing five actions. The results show that the pre-trained AlexNet model has the highest performance accuracy and fastest training period among the other models. The second experiment is the study on the performance of two different pre-trained models which is AlexNet and GoogleNet to recognize smash and non-smash action only. The results show that the pre-trained GoogleNet model produces the best performance in recognizing smash action. In conclusion, pre-trained AlexNet model is suitable to be used to automatically recognize the five badminton actions while GoogleNet model is excellent at recognizing smash action from the broadcasted video for further notational analysis.
Sustainable Supply of Hydrogen for Integrated Power Plant with Methanation via Pinch Analysis
Authors: Rudin S N F M , Muis Z Ab , Ramli A F , Shabri H A , Zailan R , Hashim H , Ho W S
Published: July 2020

The increment of greenhouse gaseous emission increases the needs to find the best solution to reduce emission of its gaseous. Carbon dioxide is the main contributor which comes mainly from energy sector. Capturing CO2 from power plant does not fully solves the issue hence integrating power plant with methanation was proposed. In this paper, a pinch analysis technique is introduced to solve the challenge to implement the integrated power plant with methanation. The main drawback of the system is to deliver a sustainable and optimize capacity of hydrogen for methanation of carbon dioxide. Cascade pinch analysis is done which has been adopted from ESCA to calculate optimal hydrogen supply and hydrogen storage. From the analysis, after five iteration, the hydrogen supply capacity is obtained which is 281.38 Wh. The hydrogen storage capacity can also be determined which is 1352.52 Wh. Through the case study presented, it has proven that pinch analysis provides a simple methodology to solve the optimization issue of hydrogen supply and demand for integrated power plant with methanation system.
Solubility of Swietenia Macrophylla Seeds In Supercritical Carbon Dioxide Extraction
Authors: Hilmi Mohammad Lokman Bin , Salleh Liza Md , Jamaludin Roslina , Norodin Nur Salsabila Md , Zaidel Dayang Norulfairuz Abang
Published: July 2020

Swietenia macrophylla seeds oil has been claimed to possess anti-diabetic, antioxidant and other health benefit properties which have garnered the interest from food and pharmaceutical industries. This study aimed to determine solubility data of S. macrophylla seeds oil in order to understand the behaviour of the separation process which is fundamental in the designing process. Solubility of S. macrophylla seeds oil in supercritical carbon dioxide (SC-CO2) was determined by using dynamic method at 20-30 MPa and 40-60°C at fixed CO2 flowrate, 2 mL/min. The solubility of S. macrophylla seeds oil obtained were 1.93 to 4.77 mg (g CO2)−1 and was increased with pressure and temperature. In this study, the Chrastil, Adachi-Lu, del Valle-Aguilera, Gordillo and Sparks as semi-empirical models were tested to fit the experimental data. The Sparks model showed the best-fitted model for S. macrophylla seeds oil solubility data with an average absolute relative deviation (AARD) of 7.76% and a high coefficient of determination (R2) of 0.992. It can be concluded that the semi-empirical model give good correlation between observed value and predicted value.
Two-Stages Carbon Emission Pinch Analysis for Integrated System of Renewable Energy and Electric Vehicle
Authors: Ramli Ahmad F. , Idris Ahmad M. , Muis Zarina Ab. , Ho Wai S. , Sadikin Aziatul N. , Ahmad Syaza I.
Published: July 2020

The introduction of electric vehicles to the transportation fleet has merged the power generation and transportation sectors into an integrated system. Rather than fuel sources, electricity is used to charge electric vehicles, so these vehicles play a vital role as an important green technology that could reduce carbon emissions in the transportation sector. This study aimed to develop a multi-stage carbon emission pinch analysis for an integrated system to optimise the energy mix for electricity generation. In the first stage, the minimum number of electric vehicles required to reduce transportation emissions was determined. In the second stage, the optimal energy mix for power generation sector was determined while including the electricity demand for the electric vehicle. Four scenarios, namely the business-as-usual scenario (S1); the public transport utilization scenario (S2); the electrification of vehicle scenario (S3); and the Integrated-Policies scenario (S4) were developed based on Peninsular Malaysia as a case study, to analyse the impact of different mitigation strategies on the country’s economy. S1 was set as baseline for all the cases i.e., without any mitigation strategies. The results reveal that S4 was the best scenario, yielding a total cost saving percentage of 51.42 % compared to S1. For the power generation sector, 52 % of renewable energy (solar PV, biomass and biogas) utilisation would be needed in the energy mix to achieve the emission reduction target.
Assessment of Bridge Deck Movement under the Impact of Environmental Factors and Traffic Load
Authors: Ha Trung-Hieu , Chou Tien-Yin , Fang Yao-Min
Published: July 2020

The Bridge Health Monitoring (BHM) system has become crucial for long-span bridge structures. This study aims to assess the bridge deck movement based-on GPS time series data and environmental data obtained from BHM system. The correlation and regression analysis are utilized to find out the pairwise relationship between the bridge deck movement in all directions and environmental factors as well as traffic load. The result shows the highest correlations in bridge deck vertical movements, the symmetrical oscillation in different parts of bridge deck and it also reveals the impact of air temperature change, wind velocity and traffic vehicle on bridge deck movement in all directions.
Can Cold-Formed Steel Section Be Use As A Sustainable Structural Member in Building and Civil Engineering Constructions? A Mini Review
Authors: Lawan M M , Shek P N , Tahir M M
Published: July 2020

Cold-Formed Steel (CFS) section for several decades was not considered as a structural member in building and civil engineering constructions due to inadequate technical information available about its usage, despite the potentials it demonstrated as proven by current research studies. Therefore, this paper aimed at demonstrating the structural capability of CFS section as a sustainable structural member in building and civil engineering constructions. Some research studies conducted reported in this paper shows the possibility of CFS section to be utilized as a structural member in the construction industries. Results from the research studies reported shows that flexural capacities were found to be increased when the CFS section was integrated compositely. In conclusion, and as demonstrated in this paper based on the studies reported, the CFS section can be employed as a sustainable structural member in small and medium size buildings, civil engineering and in lightweight industrial constructions.
Performance of MR-De’Duster in Capturing Low Density Particulate
Authors: Hussein Norelyza , Yusof Mohd Rashid Mohd , Jamian Nor Ruwaida , Hashim Nor Hasyimah , Hassan Che Hafizan Che , Zaidi Nur Syamimi
Published: July 2020

A newly multi-cyclones named MR-deDuster is developed to capture particulate emission from potential industries. This study aims to assess the performance of MR-deDuster in capturing low density particulate. The tested particulate used in the study is PreKotTM (proprietary of AMR Sdn. Bhd), which is a low density particulate available in the market and commonly used as a pre-coating material with particulate density of 747 ± 2.2 kg/m3. Fractional collection efficiency, overall collection efficiency, cut diameter (dpc) and stack concentration were used to determine the performance of unit. The study indicates the unit able to capture about 88% of low density particulate at volumetric gas flow rate of 0.19 m3/s. The study has shown that collection efficiency of MR-deDuster increased as the volumetric gas flow rate increased. However, as the volumetric flow rate of gas was further increased to 0.21 m3/s, the collection efficiency of the unit was reduced. The optimum collection efficiency was observed to occur at volumetric gas flow rate of 0.19 m3/s.
An Ontology Development Architecture for Strategic Threat Intelligence of South China Sea Conflict (OntoSCSC)
Authors: Kamarudin Muhammad Fakhrul Syazwan , Othman Siti Hajar
Published: July 2020

The purpose of this study is to investigate the conflict of South China Sea area and develop an ontology architecture South China Sea conflict. The South China Sea is a marginal sea that is part of the Pacific Ocean, covering an area of about 3,500,000 square kilometres (1,400,000 sq mi) from the Karimata and Malacca Straits to the Taiwan Strait. Under its seabed are believed to be huge oil and gas reserves. In addition, several countries are subject to competing claims of sovereignty for the sea and its mostly uninhabited islands. The variety of names used for the islands and the sea also reflect these claims. The disputes within the South China Sea can possibly touch off an increasingly broad territorial conflagration. Various claimants fight about issues of sovereignty not defenceless to simple lawful goals. Other than that, the disputes are additionally discover by wild patriotism, as each inquirer joins symbolic motivation toward the South China Sea’s islands that deep exceed their aim material wealth. Furthermore, Ontology is the study of being’s philosophy. More broadly, its studies concepts that are directly related to becoming, existence, reality in particular, as well as the basic categories of being and their relationships. Traditionally listed as part of the major branch of philosophy known as metaphysics, ontology frequently deals with questions about what entities exist or can be said to exist and how these entities can be grouped, linked within a hierarchy, and subdivided by similarities and differences about South China Sea conflicts.
Junction-Centric Data Forwarding in Urban Vehicular Communication: Future Direction and Challenges
Authors: Aliyu A , Abdullah A H , Abdulrahman S , Joda U M , Abdulraheeem Z A
Published: July 2020

All Data packet transmission is a concept in vehicular communication for achieving road safety based on Intelligent Transportation System (ITS). The packet forwarding is carried out in two scenarios including road zone and junction zone forwarding in order to address the problem of intermittent disconnection that leads to packet loss and packet error. Several studies have been conducted considering these scenarios to achieve effective communication. These studies have been revisited to provide comprehensive understanding in order to further explore the existing solutions. However, the re-visitations of these studies have not considered some of the existing junction zone packet forwarding, which is based on video data transmission. To this end, this paper suggests a qualitative review on Junction-centric Data Packet Forwarding (JDPF) focusing on vehicular communication. Precisely, a review of various junction-centric approaches with their comparative assessment is presented. Major challenges in the junction- centric data packet forwarding are identified as future directions of research. The major issues include high traffic load, incorrect metric priority selection and link disconnection at the junction area. The review would be useful to practitioners and researchers, in terms of augmenting clarity in the junction-centric data packet forwarding literature.
Feature Engineering for Predicting MOOC Performance
Authors: Mohamad Nadirah , Ahmad Nor Bahiah , Jawawi Dayang Norhayati Abang , Hashim Siti Zaiton Mohd
Published: July 2020

Increasing data recorded in massive open online course (MOOC) requires more automated analysis. The analysis, which includes making student’s prediction requires better strategy to produce good features and reduces prediction error. This paper presents the process of feature engineering for predicting MOOC student’s performance utilizing deep feature synthesis (DFS) method. The experiment produces features which all the top features selected using principal component analysis (PCA) are the features that are generated from method. In terms of prediction comparing both based features and generated features, the result shows better accuracy for generated features proposed using k-nearest neighbours technique which shows the method potential to be used for future prediction model.
Analysis of Image Magnification in X-Ray fan beam Computed Tomography
Authors: Ishak Muhamad Noor Izwan , Sipaun Susan Maria , Rahman Mohd Fitri Abdul , Shari Mohamed Rabaie
Published: July 2020

X-ray computed tomography (CT) is a non-destructive measurement method that allows inspection into both external and internal geometry of a scanned sample. This work is mainly concerned with industrial X-ray CT and its 2D image reconstruction parameters. The purpose of our study was to investigate how image magnification in 2D X-ray CT is influenced by the object position for a 50.5 mm x 50.5 mm cuboid. Using a standard definition of magnification, equations were derived to enable geometrical magnification to be determined from its position and vice versa knowing the diameter and machine parameters. Experimental data are compared and observed with regard to geometrical magnification. Results from experimental data showed a strong correlation between geometrical magnification and image magnification obtained from the reconstructed CT image. Derived sizes of cuboid from magnification were more consistent horizontally with geometrical magnification than vertically.
A Statistical Data Selection Approach for Short-Term Load Forecasting Using Optimized ANFIS
Authors: Mustapha M , Mustafa M W , Salisu S , Abubakar I , Hotoro A Y
Published: July 2020

Volume of the forecasting data and good data analysis are the key factors that influence the accuracy of forecasting algorithm because it depends on data identification and model parameters. This paper focuses on data selection approach for short-term load forecasting. It involves formulating data selection algorithm to identify factors (variables) that influence energy demand at utility level. Correlation Analysis (CA) and Hypothesis Test (HT) are used in the selection, where Wavelet Transform (WT) is applied to bridge the gap between the forecasting variables. This results to three groups of data; data without CA, HT and WT, data with CA, HT but without WT and data with CA, HT and WT. An optimized adaptive neuro-fuzzy inference system (ANFIS) using Cuckoo Search Algorithm (CS) is used to conduct the forecasting. The essence is to reduce the computational difficulty associated with the gradient descent (GD) algorithm in traditional ANFIS. With the three data groups, it is observed that CHW data can give satisfactory results more than the NCNHNW and NCNHW data. Also the numerical results shows that CHW data selection approach can give a MAPE of 0.63 against the bench-mark approach with MAPE of 3.55. This indicates that it is good practice to select the actual data and process it before the forecasting.
Performance Comparison between SVM and K-Means for Vehicle Counting
Authors: El-Khoreby Mohamed A , Abu-Bakar Syed Abd Rahman , Mokji Musa Mohd , Omar Syaril Nizam
Published: July 2020

Support vector machine (SVM) and K-means have been two well known methods used in classification. Choosing an accurate classifier for good features to differentiate between the foreground and background has a significant effect in increasing the accuracy of the detection. This paper presents and analyzes performance comparison between SVM and K-means classifiers for vehicle counting targeted for intelligence transportation systems (ITS) application. In particular, precision and recall have been used for the comparison between the two methods. Five videos from different weather conditions have been used for the testing purposes. SVM shows a better performance in terms of precision and recall.
Automated Classification of Stroke Lesion Using Bagged Tree Classifier
Authors: Saad N M , Abdullah A R , Syafeeza A R , Noor N S M , Ali N H , Muda A S
Published: July 2020

Stroke is a “brain attack” that often causes paralysis, resulted from either bleeding in the brain (hemorrhagic) or the blockage of blood flow to the brain (ischemic). It posed a big challenge to Malaysian healthcare services with at least 32 deaths per day, while survivors were burdened with multiple problems. Conventionally, the diagnosis is performed manually by neuroradiologists during a highly subjective and time consuming tasks. Therefore, this paper intends to diagnose and classify stroke by investigating diffusion- weighted imaging (DWI) of brain stroke images using Bagged Tree classification. Stroke is classified into three main types which are acute stroke, chronic stroke and hemorrhage stroke. The performance of the proposed method is then verified using accuracy and Area Under the Curve (AUC). Based on the results, the overall accuracy for the classification is 96.7%. The AUC of each type of stroke for acute stroke, chronic stroke and hemorrhage stroke is 97%, 100% and 99%, respectively. This outcome could serve as an insight to improve the healthcare of the community by providing better solutions using such intelligent system.
Effects of Approximation in Computation on the Accuracy and Performance of Deep Neural Network Inference
Authors: Ow Hui Nee , Sheikh Usman Ullah , Mokji Musa Mohd
Published: July 2020

Recently, deep learning is at the forefront of the state-of-the-art machine learning algorithms and has shown excellent results in a variety of applications such as medical field, consumer as well as autonomous vehicles. Convolutional Neural Network (CNN) – is the leading deep learning architecture that is mostly applied. However, huge dataset is needed to train with complex architecture to achieve precise learning. Inference can be performed when given a ready CNN model and its weight file to another user. Inference takes time with precise weights and huge dataset. To overcome this problem, and enhance the inference system, approximation computation will be applying in terms of weight for changed of decimal place. The smaller size of the dataset is used in the inference process to reduce the inference time. MobileNetV2 architecture is used with the new weight for inference. Also, open source libraries such as TensorFlow, Keras and python is used. GPU (NVIDIA GeForce GTX 1060 6GB 64 Bit) is used as training and inference platform. Inference time is shortened, and the accuracy of performance for new weights compare with the precise weight only has a small gap which still has a great performance for classification. This work has proved that with 4 decimal places is able to obtain the same accuracy for inference when compared to benchmark with 9 decimal places. Inference time for 4 decimal places is also less than benchmark time.
Ship systems synthesis and analysis using holistic design approach: The QFD-AD method
Authors: Khairuddin J , Maimun A , Siow C L
Published: July 2020

Design complexity is generally experienced in the design development and production of large and complex systems. It is viewed as the key element that would determine the design development cycle and quality. In this context, a study was conducted to demonstrate the ROPAX ship design and development processes applying the QFD-AD method. It is proposed to synthesise and analyse the ship systems design and configurations at the early design phase. This study explored the method applicability to facilitate concurrent design and decision-making, alternative to the conventional ship design spiral model. Moreover, it presented the potential method to support holistic design approach in exploring ship design as large and complex systems.
Potential of range extender electric vehicles (REEVS)
Authors: Veza I , Roslan M F , Said M F M , Latiff Z A
Published: July 2020

Battery Electric Vehicles (BEVs) is a promising technology. However, it suffers from low range characteristics thus increasing the anxiety to prospect customers and hindering its market penetration. To overcome this challenge, a range extender that can generate additional power to charge the battery could be the solution. This brief review article will highlight the prospects and challenges of range extender technology for electric vehicles. A number of automobile manufacturers have launched their Range Extended Electric Vehicles (REEVs) models and the detailed comparison will be given. Several types of range extenders will be discussed, including the internal combustion engine, microturbine, and fuel cell. Lastly, this report will suggest the use of Low Temperature Combustion (LTC) i.e Homogeneous Charge Compression Ignition (HCCI) engine be utilised as range extenders for electric vehicles.
Design and fabrication of an ergonomic sitting stool with storage capability
Authors: Wessam H
Published: July 2020

The paper presents design, development, and fabrication of a modern and ergonomic sitting stool with storage capability, for the Electronic Learning Center (ELC) of Jerudong International School (JIS), Brunei Darussalam. Dimensions of the stool are based on anthropometric data of teenage students of 18 years of age. It is fabricated using readily available materials that can be reused and recycled which makes the stool environmentally friendly. It is designed and developed after analyzing the available stools in the market. The analysis is performed based on product specifications such as aesthetics, cost, function, size, materials, environment-friendliness, and safety. The stool is termed a better solution by the supervisor and senior students of the ELC that could solve the problem of limited desk space at ELC, provide comfortable seating for students, and also provide the students with enough space to store their books, folders, bags, pencil case, and their water bottle in the storage compartment of the stool.
Complex geometry automotive muffler sound transmission loss measurement by experimental method and 1D simulation correlation
Authors: Mohammad M , Muhamad Said M F , Khairuddin M H , A Kadir M K , Dahlan M A A , Zaw T
Published: July 2020

A muffler is a device to attenuate noise from the exhaust. The muffler performance determined by the acoustic performance is called sound transmission loss (STL). This paper aims to measure the STL experimentally and correlated with the 1D simulation result. STL was measured using the impedance tube. Four-pole method (microphone) and two-load method were applied to measure the STL. The STL was also determined through the 1D simulation tools software. Three types of mufflers STL were measured; small expansion chamber, big expansion chamber and complex muffler. The respective error between simulation and experiment were 0.17%, 7.89%, and 11.40%. Hence, the STL experiment result was well correlated with the 1D simulation model.
Ignition Characteristics of Supersonic Combustion
Authors: Elhawary Shehab , Saat Aminuddin , Mazlan Mohammad Amri , Wahid Mazlan Abdul
Published: July 2020

Detonation may be initiated by two different modes, direct initiation or deflagration-to- detonation transition (DDT). Direct initiation can occur by a strong source such as using exploding wire or high-voltage discharge jets. Nevertheless, this method required a significant amount of energy in order to ensure that the generated blast wave will not separate and decay. A good alternative to direct initiation is Pre-detonator initiation, it depends on initiate the detonation in an ancillary small tube connected to the main tube then the detonation waves propagate to achieve detonation in the main tube. The pre-detonator is one of the most used methods to initiate the detonation due to the high reliability and design simplicity. This article is used to present a short review on experimental studies of supersonic combustion using various types of pre-detonator together with preliminary experimental work on single supersonic combustion experiment by using methane-oxygen and propane-oxygen mixtures. From this initial work, it is shows that equivalence ratio of Propane-Oxygen mixture at 0.6 shows smaller size of the supersonic combustion wave front as compared to the Methane-Oxygen mixture at 0.6 and 0.8.
Implementation of the PDCA continuous improvement cycle (Plan-D0-Check-Act) as a tool for improving the quality of the cast AA5083 alloy produced in the foundry laboratory
Authors: Al-Bakoosh Abdelaisalam Ali , Ahmad Zamani , Idris Jamaliah
Published: July 2020

Production of the high-quality alloy sample using the casting process it is not an easy and simple matter, it is one of the critical difficulties faced by the foundry technologist and researchers. Since the PDCA continuous improvement cycle is a key tool to achieve quality improvement of the product. Therefore, it was applied as an attempt to produce a high-quality cast AA5083 alloy. The main purpose of this paper is to avoid the defects that occur during the production of cast AA5083 alloy using the casting technique, which leads to minimizing product quality. The defects that may take place during the casting process of aluminium alloys have been identified through the literature reviews and taken into consideration to avoid them. The cause-effect diagram (Fishbone-Diagram) was constructed to show the root cause of the defects to avoid them, as well as the PDCA cycle was used to minimize the defects effectively. The results obtained showed that by applying the PDCA continuous improvement cycle and using the quality control tools, the quality of the cast AA5083 alloy can be improved.
Steel Wire Cleaning using Cold Plasma
Authors: Zainal Muhamad Nor Firdaus , Redzuan Norizah , Misnal Mohd Fadthul Ikmal , Ahmad Norhayati , Ibrahim Raja Kamarulzaman Raja
Published: July 2020

Current galvanizing process used hydrochloric acid to remove oxide layer and mild acidic bath to remove oil on metal wire surface. These cleaning processes are compulsory before steel wire coated with zinc. These chemicals cleaning technique cause ecological harm and produce toxic waste. To consider of minimizing these problems, cold plasma was introduced for metal wire cleaning. Previous research already proves that cold plasma capable to remove oil by using dielectric barrier discharge (DBD) and remove oxide layer on copper by using RF plasma discharge. Therefore, in this research, the same plasma discharge system that is DBD was used to remove oil and oxide layer on steel wire. 8kV of voltage and air was used to generate plasma. By using copper and steel wire as electrode, it can remove oil around 82% and oxide layer around 54%.
Thousands of reactants and transition states for competing E2 and S

N

2 reactions
Authors: von Rudorff Guido Falk , Heinen Stefan N , Bragato Marco , von Lilienfeld O Anatole
Published: July 2020

Reaction barriers are a crucial ingredient for first principles based computational retro-synthesis efforts as well as for comprehensive reactivity assessments throughout chemical compound space. While extensive databases of experimental results exist, modern quantum machine learning applications require atomistic details which can only be obtained from quantum chemistry protocols. For competing E2 and S

N

2 reaction channels we report 4,466 transition state and 143,200 reactant complex geometries and energies at MP2/6-311G(d) and single point DF-LCCSD/cc-pVTZ level of theory, respectively, covering the chemical compound space spanned by the substituents NO2, CN, CH3, and NH2 and early halogens (F, Cl, Br) and hydrogen as nucleophiles and early halogens as leaving groups. Reactants are chosen such that the activation energy of the competing E2 and S

N

2 reactions are of comparable magnitude. The correct concerted motion for each of the one-step reactions has been validated for all transition states. We demonstrate how quantum machine learning models can support data set extension, and discuss the distribution of key internal coordinates of the transition states.
Reprocessing of electrophysiology material in EHRA countries: an EHRA Young EP survey
Authors: Duncker David , Svetlosak Martin , Guerra Federico , Nagy Klaudia Vivien , Vanduynhoven Philippe , Mikhaylov Evgeny N , Kosiuk Jedrzej
Published: July 2020

Data on reprocessing of electrophysiology (EP) materials are sparse. Reprocessing of catheters and other materials in daily routine varies through countries and may depend on specific material characteristics, supplier, or federal law. The aim of this study was to collect data on reprocessing usage through EHRA countries. An online survey consisting of 27 questions was distributed to EHRA Young EP members and members of national EP working groups. Two hundred and two participants from 34 EHRA countries completed the survey. One hundred and seven respondents (53.0%) reported having used and using reprocessed EP material, 30 (14.9%) respondents have used reprocessed EP material in the past but not at the time of the survey, 65 (32.2%) had never used reprocessed EP material. The most reprocessed EP materials include cables (70%), diagnostic EP catheters with deflectable (64%) or fixed curve (63%), non-irrigated ablation catheters (51%), and other conventional diagnostic catheters (41%). The most durable material was diagnostic EP catheters with a fixed curve (61%), the most sensitive material was ablation catheters with contact force sensors (21%). Important benefits were seen in reducing costs for the providing hospital (65%) and the healthcare provider (42%) and making EP procedures available for a greater number of patients (42%). Main concerns were on quality aspects (58%), contamination (52%), and loss of precision (47%). Reprocessing of EP materials is heterogeneously managed among EHRA countries. The present survey shows that European electrophysiologists consider the use of reprocessed EP material as generally safe and cost-effective.
Context Matters: Hawaiian Monk Seals Switch Between Feeding Strategies Depending on Ecological Context
Authors: Kienle Sarah S , Powers Jezebel , Kendall Traci , Richter Beau , Castle Leann , Lentes Gwen , Costa Daniel , Mehta Rita S
Published: July 2020

Synopsis

The ability to expand the behavioral repertoire past seemingly rigid morphological features enables animals to succeed in a variety of ecological contexts. The integration of morphology, performance, and behavior produces diverse animal feeding strategies. These different strategies reflect trade-offs between specialization, prey choice, and energetic expenditure, which have important consequences for understanding individual and population-level flexibility in response to environmental change. Here we examined the feeding strategies used by the Hawaiian monk seal (Neomonachus schauinslandi), an endangered marine predator. We tested how Hawaiian monk seal feeding strategies change in response to ecological context, specifically prey size and prey location at different depths. Seven captive Hawaiian monk seals were fed five prey types across a continuum of sizes, and prey were presented at three depths to represent surface, pelagic, and benthic feeding. Hawaiian monk seals used suction feeding and biting strategies, and these strategies were associated with significant differences in behavior and kinematic performance. Hawaiian monk seals used suction feeding most frequently when targeting small to medium prey (0–79% of the seal’s head length) but switched to biting when consuming large prey (>80% of the seal’s head length). These results demonstrate that prey size drives the transition between suction feeding and biting strategies. Seals also switched strategies based on prey position in the water column, primarily using suction feeding when prey were benthic and pelagic, and biting when prey were at the water’s surface. Overall, suction feeding was three to five times faster than biting, required a smaller gape, and used fewer jaw movements, allowing seals to quickly consume numerous small to medium sized prey. In contrast, biting was slower but resulted in the ability to target larger, potentially more energy rich prey. Our results show that Hawaiian monk seals exhibit flexibility in their use of different feeding strategies, which likely facilitates increased foraging success when feeding in spatially and temporally dynamic marine environments.
Characteristics of fungal community structure during the decomposition of mixed foliage litter from Pinus massoniana and broadleaved tree species in southwestern China
Authors: Zhang Yan , Li Xun , Zhang Danju , Qin Yu , Zhou Yang , Song Simeng , Zhang Jian
Published: July 2020

Aims

The conifer litter is fairly recalcitrant and nutrient poor, and broadleaved litter promotes coniferous litter decomposition by increasing degradable nutrients and promoting microbial metabolism. Mixing Pinus massoniana litter and three broadleaved litters may increase the diversity and abundance of fungal decomposers compared with those in P. massoniana litter and vary depending on the number and proportion of broadleaved species included.

Methods

We analysed the composition and diversity of fungal communities during mixed litter decomposition in southwestern China with 35 treatments (P. massoniana, Toona sinensis, Cinnamomum camphora and Sassafras tzumu litter) using Illumina high-throughput sequencing.

Important Findings

The mixed litters increased fungal diversity and richness compared with those in the single-species litter, except in the following treatments: P. massoniana litter accounting for 70%–80% in the P. massoniana + T. sinensis, P. massoniana + S. tzumu + T. sinensis and P. massoniana + S. tzumu + C. camphora combinations, and P. massoniana + S. tzumu + C. camphora + T. sinensis combination with small proportion of T. sinensis litter. The diversity and richness of the 7:1:2 combination of P. massoniana + C. camphora + T. sinensis were significantly higher than those in the other treatments. Ascomycota and Basidiomycota were the dominant phyla, and Aspergillus was the most abundant genus. The decomposition of litters from one needleleaf and one broadleaved species (6:4) and one needleleaf species and two broadleaved species (broadleaved litter accounting for 30%–40%) exhibited synergistic interactions throughout the decomposition process, and the relative abundance of fungi that decompose refractory substances increased. The P. massoniana + C. camphora + T. sinensis combination and a 30%–40% broadleaf litter proportion increased fungal diversity and accelerated the decomposition of recalcitrant coniferous litter. Therefore, C. camphora and T. sinensis are a potential candidate species for mixed planting with P. massoniana.
Balancing Scientific Rigor With Urgency in the Coronavirus Disease 2019 Pandemic
Authors: Spec Andrej , Schwartz Ilan S
Published: July 2020

Knowledge dissemination during COVID19 has been notable for the rise of pre-prints and publication by press release, favoring speed over accuracy. We stress the importance of journals in this landscape and highlight the value of editorial judgment and peer review.
Internet Searches About Infectious Diseases Training During the Coronavirus Disease 2019 Pandemic
Authors: Birabaharan Morgan , Smith Davey M , Wooten Darcy
Published: July 2020

The COVID- 19 pandemic has showcased the field of Infectious Diseases (ID). We used Google Trends to find that this newfound attention has led to higher interest in ID training.
Out of Sight but Not Out of Mind: Caring for Patients Receiving OPAT During the SARS-CoV-2 Pandemic
Authors: Rivera Christina G , Mahoney Monica V , Stevens Ryan W , Abu Saleh Omar
Published: July 2020

In an effort to “flatten the curve” of SARS-CoV-2, society is urged to practice social distancing. However, the management of other disease states may require some patients to undergo outpatient parenteral antimicrobial therapy (OPAT). Practical considerations for OPAT management during an infectious pandemic are reviewed. These include shortening durations of therapy, utilizing the oral route, avoiding medications requiring therapeutic drug monitoring, selecting antimicrobials with long durations, decreasing frequency of laboratory blood draws, and performing tele-health visits.
Physics of parameter correlations around the solar-scale enhancement in neutrino theory with unitarity violation
Authors: Martinez-Soler Ivan , Minakata Hisakazu
Published: July 2020

We discuss the physics of the three neutrino flavor transformation with non-unitary mixing matrix, with particular attention to the correlation between the $\nu$SM- and the $\alpha$ parameters which represent the effect of unitarity-violating (UV) new physics. Towards this goal, a new perturbative framework is created to illuminate the effect of non-unitarity in the region of the solar-scale enhanced oscillations. We refute the skepticism about the physical reality of the $\nu$Standard Model CP phase $\delta$–$\alpha$ parameter phase correlation by analysis with the SOL convention of $U_{{\tiny MNS}}$, in which $e^{\pm i \delta}$ is attached to $s_{12}$. Then, a comparative study between the solar- and atmospheric-scale oscillation regions allowed by the framework reveals a dynamical $\delta$–(blobs of the $\alpha$ parameters) correlation in the solar oscillation region, in sharp contrast to the “chiral”-type phase correlation $[e^{- i \delta} \bar{\alpha}_{\mu e},\ e^{- i \delta} \bar{\alpha}_{\tau e},\ \bar{\alpha}_{\tau \mu}]$ in the Particle Data Group convention seen in the atmospheric oscillation region. An explicit perturbative calculation to the first order in the $\nu_{\mu} \rightarrow \nu_{e}$ channel allows us to decompose the UV related part of the probability into the unitary evolution part and the genuine non-unitary part. We observe that the effect of non-unitarity tends to cancel between these two parts, as well as between the different $\alpha_{\beta \gamma}$ parameters.
Getting better without memory
Authors: Halilova Julia G , Addis Donna Rose , Rosenbaum R Shayna
Published: July 2020

Does the tendency to adjust appraisals of ourselves in the past and future in order to maintain a favourable view of ourselves in the present require episodic memory? A developmental amnesic person with impaired episodic memory (HC) was compared with two groups of age-matched controls on tasks assessing the Big Five personality traits and social competence in relation to the past, present and future. Consistent with previous research, controls believed that their personality had changed more in the past 5 years than it will change in the next 5 years (i.e. the end-of-history illusion), and rated their present and future selves as more socially competent than their past selves (i.e. social improvement illusion), although this was moderated by self-esteem. Despite her lifelong episodic memory impairment, HC also showed these biases of temporal self-appraisal. Together, these findings do not support the theory that the temporal extension of the self-concept requires the ability to recollect richly detailed memories of the self in the past and future.
Genome-wide investigation of DNA methylation dynamics reveals a critical role of DNA demethylation during the early somatic embryogenesis of Dimocarpus longan Lour
Authors: Chen Xiaohui , Xu Xiaoping , Shen Xu , Li Hansheng , Zhu Chen , Chen Rongzhu , Munir Nigarish , Zhang Zihao , Chen Yukun , Xuhan Xu , Lin Yuling , Lai Zhongxiong
Published: July 2020

DNA methylation plays essential roles in gene regulation, chromatin structure stability, gene imprinting, X chromosome inactivation and embryonic development. However, the dynamics and functions of DNA methylation during the early stage of longan (Dimocarpus longan) somatic embryogenesis (SE) are still unclear. In this study, we carried out whole genome bisulphite sequencing and transcriptome sequencing analyses for embryogenic callus (EC), incomplete compact pro-embryogenic cultures (ICpEC) and globular embryos (GE) in an early SE system. At a global level, the DNA 5-methylcytosine content in EC, ICpEC and GE was 24.59, 19.65 and 19.74%, respectively, suggesting a global decrease in DNA methylation from EC to ICpEC and then a slight increase from ICpEC to GE. Differentially methylated region (DMR) analysis showed that hypomethylation mainly occurred in CHH contexts. Gene ontology and Kyoto encyclopedia of genes and genomes analysis of hypomethylated-CHH-DMR-associated genes revealed that zein biosynthesis, fatty acid biosynthesis, circadian rhythm and mitophagy pathways were involved in longan early SE. Expression patterns of DNA methyltransferase and demethylase genes during longan early SE suggested that the decrease in DNA methylation was probably regulated by DNA methyltransferase genes and the DNA demethylase gene REPRESSOR OF SILENCING 1 (ROS1). The correlation between DNA hypomethylation and gene expression revealed that decreased DNA methylation did not cause extensive changes in gene expression during early longan SE and that gene expression may be affected by methylation changes in gene and downstream regions. Inhibiting DNA methylation with 5-azacytidine treatment in EC promoted the formation of GE and enhanced the capability of longan SE. Our results suggest that DNA demethylation has important roles in longan SE development.
Acute abdominal pain in the first trimester of pregnancy
Authors: Gostigian Amanda
Published: July 2020

Pregnant women presenting to the ED with abdominal pain or vomiting are likely to be evaluated for problems with the pregnancy. Although pregnancy-related pathology is common, patients may have intra-abdominal pathology that requires prompt evaluation and possible surgical intervention.
Recognizing and limiting syphilis to prevent congenital syphilis
Authors: Sanchez Lucia , Harris Toni , Duford Amie , Duran Nelson
Published: July 2020

Syphilis is on the rise in every age and ethnicity group across the United States. The rate of congenital syphilis has started to rise as well, increasing the need for syphilis screening before pregnancy occurs. Raising awareness for syphilis screening, especially among sexually active women, is important, as the implications of this disease have lifelong effects for mother and child.