bluuebunny/crossref_metadata_2025 huggingface dataset:
Selection of the Right Undergraduate Major by Students Using Supervised Learning Techniques
Authors: Alsayed Alhuseen Omar , Rahim Mohd Shafry Mohd , AlBidewi Ibrahim , Hussain Mushtaq , Jabeen Syeda Huma , Alromema Nashwan , Hussain Sadiq , Jibril Muhammad Lawan
Published: November 2021

University education has become an integral and basic part of most people preparing for working life. However, placement of students into the appropriate university, college, or discipline is of paramount importance for university education to perform its role. In this study, various explainable machine learning approaches (Decision Tree [DT], Extra tree classifiers [ETC], Random forest [RF] classifiers, Gradient boosting classifiers [GBC], and Support Vector Machine [SVM]) were tested to predict students’ right undergraduate major (field of specialization) before admission at the undergraduate level based on the current job markets and experience. The DT classifier predicts the target class based on simple decision rules. ETC is an ensemble learning technique that builds prediction models by using unpruned decision trees. RF is also an ensemble technique that uses many individual DTs to solve complex problems. GBC classifiers and produce strong prediction models. SVM predicts the target class with a high margin, as compared to other classifiers. The imbalanced dataset includes secondary school marks, higher secondary school marks, experience, and salary to select specialization for students in undergraduate programs. The results showed that the performances of RF and GBC predict the student field of specialization (undergraduate major) before admission, as well as the fact that these measures are as good as DT and ETC. Statistical analysis (Spearman correlation) is also applied to evaluate the relationship between a student’s major and other input variables. The statistical results show that higher student marks in higher secondary (hsc_p), university degree (Degree_p), and entry test (etest_p) play an important role in the student’s area of specialization, and we can recommend study fields according to these features. Based on these results, RF and GBC can easily be integrated into intelligent recommender systems to suggest a good field of specialization to university students, according to the current job market. This study also demonstrates that marks in higher secondary and university and entry tests are useful criteria to suggest the right undergraduate major because these input features most accurately predict the student field of specialization.
Methods of Analyzing Microsized Plastics in the Environment
Authors: Woo Hyunjeong , Seo Kangmin , Choi Yonghyun , Kim Jiwon , Tanaka Masayoshi , Lee Keunheon , Choi Jonghoon
Published: November 2021

Microplastics are found in various environments with the increasing use of plastics worldwide. Several methods have been developed for the sampling, extraction, purification, identification, and quantification of microplastics in complex environmental matrices. This study intends to summarize recent research trends on the subject. Large microplastic particles can be sorted manually and identified through chemical analysis; however, sample preparation for small microplastic analysis is usually more difficult. Microplastics are identified by evaluating the physical and chemical properties of plastic particles separated through extraction and washing steps from a mixture of inorganic and organic particles. This identification has a high risk of producing false-positive and false-negative results in the analysis of small microplastics. Currently, a combination of physical (e.g., microscopy), chemical (e.g., spectroscopy), and thermal analyses is widely used. We aim to summarize the best strategies for microplastic analysis by comparing the strengths and limitations of each identification method.
A Survey of the Literature on Order-Picking Systems by Combining Planning Problems
Authors: Ahmadi Keshavarz Amir Reza , Jaafari Davood , Khalaj Mehran , Dokouhaki Parshang
Published: November 2021

Companies have been trying continuously to reduce their logistics costs in the current competitive markets. Warehouses are important components of the logistics systems and they must be managed effectively and efficiently to reduce the production cost as well as maintain customer satisfaction. Order-picking is the core of warehouse operations and an order-picking system (OPS) is essential to meet customer needs and orders. Failure to perform the OPS process properly results in high costs and customer dissatisfaction. This research aims to investigate the state of the art in the adoption of OPS and provide a broad systemic analysis on main operating strategies such as simultaneous consideration of order assignment, batching, sequencing, tardiness, and routing need. This study reviews 92 articles, classifies combinations of tactical and operational OPS problems, and provides guidelines on how warehouse managers can benefit from combining planning problems, in order to design efficient OPS and improve customer service. Combining multiple order-picking planning problems results in substantial efficiency benefits, which are required to face new market developments.
Positioning Evaluation of Single and Dual-Frequency Low-Cost GNSS Receivers Signals Using PPP and Static Relative Methods in Urban Areas
Authors: Romero-Andrade Rosendo , Trejo-Soto Manuel E. , Vega-Ayala Alejandro , Hernández-Andrade Daniel , Vázquez-Ontiveros Jesús R. , Sharma Gopal
Published: November 2021

A positional accuracy obtained by the Precise Point Positioning and static relative methods was compared and analyzed. Test data was collected using low-cost GNSS receivers of single- and dual-frequency in urban areas. The data was analyzed for quality using the TEQC program to determine the degree of affectation of the signal in the urban area. Low-cost GNSS receivers were found to be sensitive to the multipath effect, which impacts positioning. The horizontal and vertical accuracy was evaluated with respect to Mexican regulations for the GNSS establishment criteria. Probable Error Circle (CEP) and Vertical Positioning Accuracy (EPV) were performed on low cost GNSS receiver observation data. The results show that low-cost dual-frequency GNSS receivers can be used in urban areas. The precision was obtained in the order of 0.013 m in the static relative method. The results obtained are comparable to a geodetic receiver in a geodetic baseline of <20 km. The study does not recommend using single and dual frequencies low cost GNSS receivers based on results obtained by the Precise Point Positioning (PPP) method in urban areas. The inclusion of the GGM10 model reduces the vertical precision obtained by using low cost GNSS receivers in both methods, conforming to the regulations only in the horizontal component.
Simulation of On-Chip Broadband Photon Spin Router Base on Nondiffracting Surface Plasmon Beam Launching
Authors: Quan Zhiqiang , Liu Houquan , Yuan Libo
Published: November 2021

The development of a photonic device based on a non-diffracting surface plasmon polariton (SPP) beam can effectively improve the anti-interference ability. Furthermore, an easily adjustable on-chip routing device is highly desirable and extremely important in practical optical communication applications. However, no non-diffracting SPP-beam-based spin routing devices with high tunability in multiple degrees of freedom have been reported. In this study, we theoretically designed a simple micro-nano structure to realize a highly adjustable non-diffracting SPP-beam-based spin router using Finite-Difference Time-Domain (FDTD) simulation. The simulation results show that the structure enables spin-controlled nondiffracting SPP-beam directional launching. The launching direction of the nondiffracting SPP beam can be dynamically rotated counterclockwise or clockwise by changing the incident angle. Hence, the routing SPP beam can be coupled to different output waveguides to provide dynamic tunability. Moreover, this device shows good broadband response ability. This work may motivate the design and fabrication of future practical photon routing devices.
Preliminary Validation of a Low-Cost Motion Analysis System Based on RGB Cameras to Support the Evaluation of Postural Risk Assessment
Authors: Agostinelli Thomas , Generosi Andrea , Ceccacci Silvia , Khamaisi Riccardo Karim , Peruzzini Margherita , Mengoni Maura
Published: November 2021

This paper introduces a low-cost and low computational marker-less motion capture system based on the acquisition of frame images through standard RGB cameras. It exploits the open-source deep learning model CMU, from the tf-pose-estimation project. Its numerical accuracy and its usefulness for ergonomic assessment are evaluated by a proper experiment, designed and performed to: (1) compare the data provided by it with those collected from a motion capture golden standard system; (2) compare the RULA scores obtained with data provided by it with those obtained with data provided by the Vicon Nexus system and those estimated through video analysis, by a team of three expert ergonomists. Tests have been conducted in standardized laboratory conditions and involved a total of six subjects. Results suggest that the proposed system can predict angles with good consistency and give evidence about the tool’s usefulness for ergonomist.
Transdisciplinary Teaching and Learning in UX Design: A Program Review and AR Case Studies
Authors: Liu Wei , Lee Kun-Pyo , Gray Colin M. , Toombs Austin L. , Chen Kuo-Hsiang , Leifer Larry
Published: November 2021

Today’s user experience (UX) educators and designers can no longer just focus on creating more usable systems, but must also rise to the level of strategists, using design thinking and human–computer interaction (HCI) solutions to improve academic and business outcomes. Both psychological, designer, and engineering approaches are adopted in this study. An invited program review committee met to review progress of the UX program at the Beijing Normal University (BNUX). They considered issues and challenges facing the program today, and the steps that it could make to develop further. During a recent augmented reality (AR) project on designing future life experience on smart home and wearables, several experiential concepts and prototypes were generated to demonstrate HCI and UX research directions. The committee was impressed by BNUX with its energy, enthusiasm, and a sense of purpose on practicing transdisciplinary teaching and learning activities. Recommendations on the current organization of education, the relation between project-based learning and research, and opportunities for exposure and visibility are provided.
Vegetable Oil-Based Resins Reinforced with Spruce Bark Powder and with Its Hydrochar Lignocellulosic Biomass
Authors: Dinu Roxana , Bejenari Iuliana , Volf Irina , Mija Alice
Published: November 2021

A bio-based polymeric matrix was developed by the copolymerization of a vegetable oil-based epoxy, epoxidized linseed oil (ELO), with dodecenyl succinic anhydride (DDSA). To obtain eco-friendly bio-composites, this matrix was combined with a natural filler: spruce bark powder (SB) with its hydrochar (HC) in various proportions ranged from 1 to 30 wt.%. The reactivities of these formulations were studied by DSC analysis that highlighted that both fillers have a high catalytic effect on the ELO–DDSA crosslinking reaction. The complementary studies by TGA, DMA, tensile tests, water absorption and Shore tests had shown that both HC and SB bring improvements to the mechanical properties of the composites, fulfilling multiple roles: (i) Both act as co-reactants in the copolymerization mechanism; (ii) HC acts as reinforcement, consolidating the network and providing stiffness and rigidity; and (iii) SB acts as plasticizer for reducing the brittle character of the epoxy resins.
Analysis of Body-Slip and Buttock Pressure Characteristics during Operation of a Double-Sliding Reclining Wheelchair in Patients with Spinal Cord Injury
Authors: Chang Yunhee , Kang Jungsun , Jeong Bora , Kim Yongcheol , Hong Eung-Pyo , Kim Gyoosuk
Published: November 2021

To minimize body collapse due to repetitive reclining and repositioning when using a reclining wheelchair, reclining wheelchairs with a sliding backrest function have been developed. This study compared the differences in body-slip and buttock pressure according to the presence or absence of the sliding function of the backrest during reclining and repositioning motions in 10 patients with spinal cord injury. When reclining from 100° to 130°, backrest sliding and total body-slip in the double-sliding wheelchair were significantly decreased by 21.4 mm and 16.4 mm, respectively, compared to a non-sliding wheelchair, and the peak pressure on the ischial tuberosity was significantly decreased by 8.7 kPa. Upon comparison of the buttock pressure between the initial upright position before reclining and the return upright position after repositioning, the force and mean pressure with the double-sliding wheelchair were significantly reduced compared with those with the non-sliding wheelchair. It was confirmed that the double-sliding system improved body-slip and buttock pressure more effectively than the non-sliding system. This study’s results are expected to provide the basic data necessary for the prescription and selection of wheelchairs in clinical practice and to be utilized in the development of related devices.
Evaluation of the Adhesive Potential of Bacteria Isolated from Meat-Related Sources
Authors: Ning Zhenzhen , Xue Bei , Wang Huhu
Published: November 2021

Microbial adhesion constitutes the transition of microorganisms from a planktonic mode to a static one. It promotes the formation of biofilm which is responsible for spoilage, foodborne diseases, and corrosion in the food processing industry. In this study, the adhesive potential of fourteen meat-borne bacterial isolates belonging to seven different genera was investigated. All strains were found able to colonize polystyrene surfaces with different levels of firmness. Significant variations were determined in assays of bacterial hydrophobicity and motility. Among the 14 strains, Pseudomonas fragi, Aeromonas salmonicida II, Serratia liquefaciens, Citrobacter braakii, Pseudomonas putida, and Aeromonas veronii had a strong hydrophobic force, while the isolates of Lactobacillus genus showed the most hydrophilic property. In terms of motility, Citrobacter braakii and Escherichia coli exhibited exceptional swarming and swimming abilities, whilst conservatively weak performances were observed in the Lactobacillus strains. Furthermore, the majority of the isolates were predominantly electron donors and weak electron acceptors. Overall, a high level of correlation was observed between biofilm-forming ability with cell surface hydrophobicity and Lewis acid–base properties, whereas the contribution of motility in bacterial adhesion could not be confirmed. Research on the adhesive performance of foodborne bacteria is potentially conducive to developing novel control strategies, such as food processing equipment with specific surfaces, not facilitating attachment.
Special Issue “Extreme Sciences and Engineering”
Authors: Kaewunruen Sakdirat , Lu Xinzheng , Remennikov Alex M.
Published: November 2021

Due to uncertainties stemming from climate change, natural and man-made disasters, and extreme events, unexpected disruptions in the operation of our countries’ infrastructure may put the functioning of our societies and their economies at risk [...]
Improvement of Business Productivity by Applying Robotic Process Automation
Authors: Hyun Younggeun , Lee Dongseop , Chae Uri , Ko Jindeuk , Lee Jooyeoun
Published: November 2021

Digitalization has been bringing about various changes and innovations not only in our daily life but also in our business environment. In the manufacturing industry, robots have been used for automation for a long time, resulting in innovation in terms of the faster operation process and higher product quality. Robotics Process Automation (RPA) can be said to have brought this innovation in the productivity improvement of many industries into the business office. The purpose of this study is to improve business productivity by applying RPA named CoPA. It is based on Domain-Specific Languages (DSLs) and Model-Driven Engineering (MDE) coupled with MS Office. CoPA has been replaced to perform the repetitive patterned tasks (especially document work) done by many people in an office. For the applications of business productivity, CoPA has been implemented to revise five government project proposals requiring quite strict writing standards. The improvement of business productivity obtained by CoPA has been compared to the performance of 10 employees who are familiar with MS Office. The paper explains the method of CoPA coupled with MS Office as well as the agile method of human collaboration. It is clearly shown that CoPA as a business RPA can improve business productivity in terms of time consumption and document quality.
High-Intensity Conditioning for Combat Athletes: Practical Recommendations
Authors: Ruddock Alan , James Lachlan , French Duncan , Rogerson David , Driller Matthew , Hembrough David
Published: November 2021

Combat sports have been practiced for millennia and today are predominant sports at the Olympic games, with international organizations that host world, continental and national championships at amateur standard. There are also an increasing number of professional combat sports with global audiences. The growing popularity of professional combat sports and their importance at the Olympic games have led to an increase in scientific studies that characterize the physical, physiological, nutritional, biomechanical and training strategies of combat sports athletes. These studies characterize combat sports as high-intensity sports which require training strategies to develop the high-intensity capabilities of athletes. Therefore, the aim of this article is to (i) summarize the physiological demands of combat sports; (ii) present the primary considerations required to program high-intensity conditioning for athletes; (iii) define and present key high-intensity conditioning methods; and (iv) provide guidance for scientists and coaches to help prepare athletes under common but differing circumstances.
An Attention-Based Convolutional Neural Network for Acute Lymphoblastic Leukemia Classification
Authors: Zakir Ullah Muhammad , Zheng Yuanjie , Song Jingqi , Aslam Sehrish , Xu Chenxi , Kiazolu Gogo Dauda , Wang Liping
Published: November 2021

Leukemia is a kind of blood cancer that influences people of all ages and is one of the leading causes of death worldwide. Acute lymphoblastic leukemia (ALL) is the most widely recognized type of leukemia found in the bone marrow of the human body. Traditional disease diagnostic techniques like blood and bone marrow examinations are slow and painful, resulting in the demand for non-invasive and fast methods. This work presents a non-invasive, convolutional neural network (CNN) based approach that utilizes medical images to perform the diagnosis task. The proposed solution consisting of a CNN-based model uses an attention module called Efficient Channel Attention (ECA) with the visual geometry group from oxford (VGG16) to extract better quality deep features from the image dataset, leading to better feature representation and better classification results. The proposed method shows that the ECA module helps to overcome morphological similarities between ALL cancer and healthy cell images. Various augmentation techniques are also employed to increase the quality and quantity of training data. We used the classification of normal vs. malignant cells (C-NMC) dataset and divided it into seven folds based on subject-level variability, which is usually ignored in previous methods. Experimental results show that our proposed CNN model can successfully extract deep features and achieved an accuracy of 91.1%. The obtained findings show that the proposed method may be utilized to diagnose ALL and would help pathologists.
Vector Optical Beam with Controllable Variation of Polarization during Propagation in Free Space: A Review
Authors: Wang Wen-Yue , Cheng Tian-Yu , Bai Zhen-Xu , Liu Shuo , Lü Jia-Qi
Published: November 2021

The vector optical beam with longitudinally varying polarization during propagation in free space has attracted significant attention in recent years. Compared with traditional vector optical beams with inhomogeneous distribution of polarization in the transverse plane, manipulating the longitudinal distribution of polarization provides a new dimension for the expansion of the applications of vector optical beams in volume laser machining, longitudinal detection, and in vivo micromanipulation. Two theoretical strategies for achieving this unique optical beam are presented in the way of constructing the longitudinally varying phase difference and amplitude difference. Relevant generation methods are reviewed which can be divided into the modulation of complex amplitude in real space and the filtering of the spatial spectrum. In addition, current problems and prospects for vector optical beams with longitudinally varying polarization are discussed.
Designing and Simulating the Control Process of a Feed Pusher Robot Used on a Dairy Farm
Authors: Pavkin Dmitriy Yu. , Shilin Denis V. , Nikitin Evgeniy A. , Kiryushin Ivan A.
Published: November 2021

Feeding cattle on livestock farms is a labor-intensive operation that requires considerable capital investments to purchase equipment and cover labour costs. The global trends in developing technological equipment for feeding cattle include the robotization of various processes. The operation of feed pushing on the feeding table is an integral part of the feeding process, which has a significant impact on livestock productivity. This study concentrates on the simulation modeling of a feed pusher robot using Simulink tools in the Matlab environment to facilitate robot modernization or optimize the final cost for artificial testing of typical system elements and reduce production costs. Based on a simulation model, an experimental sample was designed with a controlled dispenser of feed additives, which can significantly facilitate the feeding process and optimize the dosing of concentrated additives.
Design and Analysis of the Rolling and Jumping Compound Motion Robot
Authors: Wu Huaisong , Li Bingyang , Wang Futao , Luo Bin , Jiao Zhiwei , Yu Yuan , Wang Pengfei
Published: November 2021

Complex and unknown areas in deep space exploration present major challenges to the motion ability of current space robots. Different from the traditional single-mode motion space robot, a compound motion robot with flexible movement and strong obstacle surmounting ability is proposed. Through the highly integrated structure design, the lightweight robot has the ability of rolling and jumping, and the kinematic characteristics of the robot under two motion modes are analyzed. This work provides a reference for the design of deep space exploration equipment with high motion capability in the future.
A Mechanical Feedback Classification of Linear Mechanical Control Systems
Authors: Nowicki Marcin , Respondek Witold
Published: November 2021

We give a classification of linear nondissipative mechanical control system under mechanical change of coordinates and feedback. First, we consider a controllable case that is somehow a mechanical counterpart of Brunovský classification, then we extend the result to all linear nondissipative mechanical systems (not necessarily controllable) which leads to a mechanical canonical decomposition. The classification of Lagrangian systems is given afterwards. Next, we show an application of the classification results to the stability and stabilization problem and illustrate them with several examples. All presented results in this paper are expressed in terms of objects on the configuration space Rn only, while the state-space of a mechanical control system is Rn×Rn consisting of configurations and velocities.
Anti-Yeast Synergistic Effects and Mode of Action of Australian Native Plant Essential Oils
Authors: Alderees Fahad , Mereddy Ram , Were Stephen , Netzel Michael E. , Sultanbawa Yasmina
Published: November 2021

Yeasts are the most common group of microorganisms responsible for spoilage of soft drinks and fruit juices due to their ability to withstand juice acidity and pasteurization temperatures and resist the action of weak-acid preservatives. Food industries are interested in the application of natural antimicrobial compounds as an alternative solution to the spoilage problem. This study attempts to investigate the effectiveness of three Australian native plant essential oils (EOs) Tasmanian pepper leaf (TPL), lemon myrtle (LM) and anise myrtle (AM) against weak-acid resistant yeasts, to identify their major bioactive compounds and to elucidate their anti-yeast mode of action. The minimum inhibitory concentration (MIC), minimum fungicidal concentration (MFC) and minimum bactericidal concentration (MBC) were assessed for EOs against weak-acid resistant yeasts (Candida albicans, Candida krusei, Dekkera anomala, Dekkera bruxellensis, Rhodotorula mucilaginosa, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Zygosaccharomyces bailii and Zygosaccharomyces rouxii) and bacteria (Staphylococcus aureus and Escherichia coli). The EOs showed anti-yeast and antibacterial activity at concentrations ranging from 0.03–0.07 mg/mL and 0.22–0.42 mg/mL for TPL and 0.07–0.31 mg/mL and 0.83–1.67 mg/mL for LM, respectively. The EOs main bioactive compounds were identified as polygodial in TPL, citral (neral and geranial) in LM and anethole in AM. No changes in the MICs of the EOs were observed in the sorbitol osmotic protection assay but were found to be increased in the ergosterol binding assay after the addition of exogenous ergosterol. Damaging of the yeast cell membrane, channel formation, cell organelles and ion leakage could be identified as the mode of action of TPL and LM EOs. The studied Australian native plant EOs showed potential as natural antimicrobials that could be used in the beverage and food industry against the spoilage causing yeasts.
Stress Analysis in Damaged Pipeline with Composite Coating
Authors: Dutkiewicz Maciej , Dalyak Taras , Shatskyi Ivan , Venhrynyuk Tetyana , Velychkovych Andrii
Published: November 2021

This paper studied the distribution of stresses near damage in the form of axial surface cracks in a pipeline reinforced with a spiral-wound composite coating. The authors applied the homogenization method to determine the effective elastic characteristics of a structurally anisotropic layered package. By means of the classical momentless theory of shells, it was established that the stress state of the coated intact pipe under the pressure of the pumped product depends on the parameters of the geometry of the capacity strip, as well as on the component composition of the heterogeneous coating. The finite element method was applied to solve the problem of plane deformation of a piecewise homogeneous ring with an internal crack perpendicular to the interface. This problem assumes the linearity of the materials and the ideal mechanical contact with the layers. The effect of the composite coating and the size of the damage on the magnitudes of the energy flow into the crack tip, and on the stress intensity factor, was studied in detail. Various variants of the coating were considered, namely, winding of the coating on an unloaded pipe and reinforcement of the pipe under repair pressure.
Material Thickness Classification Using Scattering Parameters, Dielectric Constants, and Machine Learning
Authors: Hien Pham-The , Hong Ic-Pyo
Published: November 2021

Wall-thinning in building structures due to corrosion and surface erosion occurs due to the severe operating conditions and the changing of the surrounding environment, or it can result from poor workmanship and a lack of systematic monitoring during construction. Hence, the continuous monitoring of structures plays an important role in decreasing unexpected accidents. In this paper, a novel method based on the deep neural network and support vector machine approaches is investigated to build up a thickness classification model by incorporating different input features, including the dielectric constants of the material under test, which are extracted from the scattering parameters proceeded by the National Institute of Standards and Technology iterative method. The attained classification results from both machine learning algorithms are then compared and show that both of the models have a good prediction ability. While the deep neural network is the better solution with a large amount of data, the support vector machine is the more appropriate solution when employing small dataset. It can be stated that the proposed method is able to support systematic monitoring as it can help to improve the accuracy of the prediction of material thickness.
Multi-Objective Design of Profit Volumes and Closeness Ratings Using MBHS Optimizing Based on the PrefixSpan Mining Approach (PSMA) for Product Layout in Supermarkets
Authors: Kaewyotha Jakkrit , Songpan Wararat
Published: November 2021

Product layout significantly impacts consumer demand for purchases in supermarkets. Product shelf renovation is a crucial process that can increase supermarket efficiency. The development of a sequential pattern mining algorithm for investigating the correlation patterns of product layouts, solving the numerous problems of shelf design, and the development of an algorithm that considers in-store purchase and shelf profit data with the goal of improving supermarket efficiency, and consequently profitability, were the goals of this research. The authors of this research developed two types of algorithms to enhance efficiency and reach the goals. The first was a PrefixSpan algorithm, which was used to optimize sequential pattern mining, known as the PrefixSpan mining approach. The second was a new multi-objective design that considered the objective functions of profit volumes and closeness rating using the mutation-based harmony search (MBHS) optimization algorithm, which was used to evaluate the performance of the first algorithm based on the PrefixSpan algorithm. The experimental results demonstrated that the PrefixSpan algorithm can determine correlation rules more efficiently and accurately ascertain correlation rules better than any other algorithms used in the study. Additionally, the authors found that MBHS with a new multi-objective design can effectively find the product layout in supermarket solutions. Finally, the proposed product layout algorithm was found to lead to higher profit volumes and closeness ratings than traditional shelf layouts, as well as to be more efficient than other algorithms.
Biochar-Improved Growth and Physiology of Ehretia asperula under Water-Deficit Condition
Authors: Hoang Thi-Lan-Huong , Jang Dong-Cheol , Nguyen Quang-Tin , Na Won-Ho , Kim Il-Seop , Vu Ngoc-Thang
Published: November 2021

Ehretia asperula’s physiological responses to growth performance following oak-wood biochar application under water stress conditions (WSC) and no water stress conditions (non-WSC) were investigated in a pot experiment. Biochar (WB) was incorporated into the soil at concentrations of 0, 5, 10, 15, and 20 tons ha−1 before transplanting Ehretia asperula in the pots. One month after transplanting, Ehretia asperula plants were put under water stress by withholding water for ten days. Water stress significantly decreased the growth and physiology of Ehretia asperula. Under WSC, the application of WB at the concentrations of 15 and 20 tons ha−1 to the soil increased the plant height; number of leaves; fresh and dry weight of the roots, shoots, and leaves; Fv/Fm; chlorophyll content; leaf relative water content; and soil moisture as well as decreased the relative ion leakage. The application of WB enhanced drought tolerance in Ehretia asperula plants by lowering the wilting point. The findings suggest that WB application at the concentration of 15 tons ha−1 could be recommended for ensuring the best physiological responses and highest growth of Ehretia asperula plants.
Calculation of Surface Offset Gathers Based on Reverse Time Migration and Its Parallel Computation with Multi-GPUs
Authors: Liu Dingjin , Li Bo , Liu Guofeng
Published: November 2021

As an important method for seismic data processing, reverse time migration (RTM) has high precision but involves high-intensity calculations. The calculation an RTM surface offset (shot–receiver distance) domain gathers provides intermediary data for an iterative calculation of migration and its velocity building. How to generate such data efficiently is of great significance to the industrial application of RTM. We propose a method for the calculation of surface offset gathers (SOGs) based on attribute migration, wherein, using migration calculations performed twice, the attribute profile of the surface offsets can be obtained, thus the image results can be sorted into offset gathers. Aiming at the problem of high-intensity computations required for RTM, we put forth a multi-graphic processing unit (GPU) calculative strategy, i.e., by distributing image computational domains to different GPUs for computation and by using the method of multi-stream calculations to conceal data transmission between GPUs. Ultimately, the computing original efficiency was higher relative to a single GPU, and more GPUs were used linearly. The test with a model showed that the attributive migration methods can correctly output SOGs, while the GPU parallel computation can effectively improve the computing efficiency. Therefore, it is of practical importance for this method to be expanded and applied in industries.
Traffic Signal Optimization for Multiple Intersections Based on Reinforcement Learning
Authors: Gu Jaun , Lee Minhyuck , Jun Chulmin , Han Yohee , Kim Youngchan , Kim Junwon
Published: November 2021

In order to deal with dynamic traffic flow, adaptive traffic signal controls using reinforcement learning are being studied. However, most of the related studies are difficult to apply to the real field considering only mathematical optimization. In this study, we propose a reinforcement learning-based signal optimization model with constraints. The proposed model maintains the sequence of typical signal phases and considers the minimum green time. The model was trained using Simulation of Urban MObility (SUMO), a microscopic traffic simulator. The model was evaluated in the virtual environment similar to a real road with multiple intersections connected. The performance of the proposed model was analyzed by comparing the delay and number of stops with a reinforcement learning model that did not consider constraints and a fixed-time model. In a peak hour, the proposed model reduced the delay from 3 min 15 s to 2 min 15 s and the number of stops from 11 to 4.7 compared to the fixed-time model.
Latin American Art, Visual and Material Culture in the Long Eighteenth Century: An Introduction
Authors: Beck Lauren , Robin Alena
Published: November 2021

The temporal frame of this Special Issue of Arts—the long eighteenth century—comprises a complex period of development in the Spanish colonies of Latin America that reverberates throughout the region’s visual culture [...]
Quantitative Model for the Value of the 3D Product Model Use in Production Processes
Authors: Kirpes Carl , Sly Dave , Hu Guiping
Published: November 2021

Prior research has shown qualitatively that organizations can increase the value created in their production and assembly processes through the implementation of three-dimensional (3D) product models in those processes. This paper moves beyond qualitative value to develop and calibrate a quantitative model for the value of 3D product model use in production and assembly processes. The principal contributions of this research are development of the quantitative model and determination of the quantitative value of deploying the 3D product model in assembly and production processes; findings developed through interviews with industry experts in industrial and systems engineering to gather the model inputs, calculate the outputs, and then calibrate the model with those industry experts. These results are then compared against the qualitative value categories from prior research to determine the alignment in order and magnitude with the quantitative model results. This paper concludes with a recommendation of where both industry and academia focus future implementation efforts and research based upon the associated results demonstrated in both the qualitative and quantitative model on the value of 3D product model use in assembly and production processes.
Viability of Bacillus subtilis Cells in Airborne Bioaerosols on Face Masks
Authors: Lee Eun-Hee , Chang Yunsoo , Lee Seung-Woo
Published: November 2021

The coronavirus disease 2019 (COVID-19) pandemic is a general health crisis and has irreversible impacts on human societies. Globally, all people are at risk of being exposed to the novel coronavirus through transmission of airborne bioaerosols. Public health actions, such as wearing a mask, are highly recommended to reduce the transmission of infectious diseases. The appropriate use of masks is necessary for effectively preventing the transmission of airborne bioaerosols. The World Health Organization (WHO) suggests washing fabric masks or throwing away disposable masks after they are used. However, people often use masks more than once without washing or disposing them. The prolonged use of a single mask might—as a result of the user habitually touching the mask—promote the spread of pathogens from airborne bioaerosols that have accumulated on the mask. Therefore, it is necessary to evaluate how long the living components of bioaerosols can be viable on the masks. Here, we evaluated the viability of airborne Bacillus subtilis (B. subtilis) in bioaerosols filtered on woven and anti-droplet (non-woven) face masks. As a simulation of being simultaneously exposed to sand dust and bioaerosols, the viability rates of bioaerosols that had accumulated on masks were also tested against fine dust and airborne droplets containing bacteria. The bioaerosols survived on the masks immediately after the masks were used to filter the bioaerosols, and the bacteria significantly proliferated after one day of storage. Thereafter, the number of viable cells in the filtered bioaerosols gradually decreased over time, and the viability of B. subtilis in bioaerosols on the masks varied, depending on the mask material used (woven or non-woven). Despite the reduction in viability, bioaerosols containing living components were still found in both woven and anti-droplet masks even after six days of storage and it took nine days not to have found them on masks. The number of viable cells in bioaerosols on masks significantly decreased upon exposure of the masks to fine dust. The results of this study should provide useful information on how to appropriately use masks to increase their duration of effectiveness against bioaerosols.
Interdimensionality
Authors: Svozil Karl
Published: November 2021

In this speculative analysis, interdimensionality is introduced as the (co)existence of universes embedded into larger ones. These interdimensional universes may be isolated or intertwined, suggesting a variety of interdimensional intrinsic phenomena that can only be understood in terms of the outer, extrinsic reality.
Going Forward and Back: The Complex Evolutionary History of the GPx
Authors: Trenz Thomaz Stumpf , Delaix Camila Luiza , Turchetto-Zolet Andreia Carina , Zamocky Marcel , Lazzarotto Fernanda , Margis-Pinheiro Márcia
Published: November 2021

There is large diversity among glutathione peroxidase (GPx) enzymes regarding their function, structure, presence of the highly reactive selenocysteine (SeCys) residue, substrate usage, and reducing agent preference. Moreover, most vertebrate GPxs are very distinct from non-animal GPxs, and it is still unclear if they came from a common GPx ancestor. In this study, we aimed to unveil how GPx evolved throughout different phyla. Based on our phylogenetic trees and sequence analyses, we propose that all GPx encoding genes share a monomeric common ancestor and that the SeCys amino acid was incorporated early in the evolution of the metazoan kingdom. In addition, classical GPx and the cysteine-exclusive GPx07 have been present since non-bilaterian animals, but they seem to have been lost throughout evolution in different phyla. Therefore, the birth-and-death of GPx family members (like in other oxidoreductase families) seems to be an ongoing process, occurring independently across different kingdoms and phyla.
MaNmrA, a Negative Transcription Regulator in Nitrogen Catabolite Repression Pathway, Contributes to Nutrient Utilization, Stress Resistance, and Virulence in Entomopathogenic Fungus Metarhizium acridum
Authors: Li Chaochuang , Zhang Qipei , Xia Yuxian , Jin Kai
Published: November 2021

The NCR pathway plays an important regulatory role in the nitrogen metabolism of filamentous fungi. NmrA, a central negative regulatory protein in the NCR pathway and a key factor in sensing to the carbon metabolism, plays important roles in pathogenic fungal nutrition metabolism. In this study, we characterized the functions of MaNmrA in the insect pathogenic fungus M. acridum. Multiple sequence alignments found that the conserved domain (NAD/NADP binding domain) of MaNmrA was highly conservative with its homologues proteins. Deletion of MaNmrA improved the utilization of multiple carbon sources (such as glucose, mannose, sucrose, and trehalose) and non-preferred nitrogen sources (such as NaNO3 and urea), significantly delayed the conidial germination rate and reduced the conidial yield. The MaNmrA-disruption strain (ΔMaNmrA) significantly decreased tolerances to UV-B and heat-shock, and it also increased the sensitivity to the hypertonic substance sorbitol, oxygen stress substance H2O2, and cell wall destroyer calcofluor white, indicating that loss of MaNmrA affected cell wall integrity, tolerances to hypertonic and oxidative stress. Bioassays demonstrated that disruption of MaNmrA decreased the virulence in both topical inoculation and intrahemocoel injection tests. Further studies revealed that the appressorium formation, turgor pressure, and colonization in hemolymph were significantly reduced in the absence of MaNmrA. Our work will deepen the functional cognition of MaNmrA and make a contribution to the study of its homologous proteins.
Assessment of the Spatial Invasion Risk of Intentionally Introduced Alien Plant Species (IIAPS) under Environmental Change in South Korea
Authors: Adhikari Pradeep , Lee Yong-Ho , Park Yong-Soon , Hong Sun-Hee
Published: November 2021

Predicting the regions at risk of invasion from IIAPS is an integral horizon-scanning activity that plays a crucial role in preventing, controlling, and eradicating invasive species. Here, we quantify the spatial distribution area and invasion risk of IIAPS using a species distribution model under different levels of environmental change in South Korea. From the model predictions, the current average spatial extent of the 10 IIAPS is 33,948 km2, and the individual spatial extents are estimated to change by −7% to 150% by 2050 and by −9% to 156% by 2070. The spatial invasion risk assessment shows that, currently, moderate-to-high invasion risk is limited to coastal areas and densely populated metropolitan cities (e.g., Seoul, Busan, and Gwangju), but that the area with this level of risk is expected to spread toward the central and northern regions of the country in the future, covering 86.21% of the total area of the country by 2070. These results demonstrate that the risk of invasion by IIAPS is estimated to enlarge across the whole country under future environmental changes. The modeling system provided in this study may contribute to the initial control and strategic management of IIAPS to maintain the dynamic ecosystems of South Korea.
Mitochondria-Endoplasmic Reticulum Crosstalk in Parkinson’s Disease: The Role of Brain Renin Angiotensin System Components
Authors: Sunanda Tuladhar , Ray Bipul , Mahalakshmi Arehally M. , Bhat Abid , Rashan Luay , Rungratanawanich Wiramon , Song Byoung-Joon , Essa Musthafa Mohamed , Sakharkar Meena Kishore , Chidambaram Saravana Babu
Published: November 2021

The past few decades have seen an increased emphasis on the involvement of the mitochondrial-associated membrane (MAM) in various neurodegenerative diseases, particularly in Parkinson’s disease (PD) and Alzheimer’s disease (AD). In PD, alterations in mitochondria, endoplasmic reticulum (ER), and MAM functions affect the secretion and metabolism of proteins, causing an imbalance in calcium homeostasis and oxidative stress. These changes lead to alterations in the translocation of the MAM components, such as IP3R, VDAC, and MFN1 and 2, and consequently disrupt calcium homeostasis and cause misfolded proteins with impaired autophagy, distorted mitochondrial dynamics, and cell death. Various reports indicate the detrimental involvement of the brain renin–angiotensin system (RAS) in oxidative stress, neuroinflammation, and apoptosis in various neurodegenerative diseases. In this review, we attempted to update the reports (using various search engines, such as PubMed, SCOPUS, Elsevier, and Springer Nature) demonstrating the pathogenic interactions between the various proteins present in mitochondria, ER, and MAM with respect to Parkinson’s disease. We also made an attempt to speculate the possible involvement of RAS and its components, i.e., AT1 and AT2 receptors, angiotensinogen, in this crosstalk and PD pathology. The review also collates and provides updated information on the role of MAM in calcium signaling, oxidative stress, neuroinflammation, and apoptosis in PD.
The Membrane-Bound Notch Regulator Mnr Supports Notch Cleavage and Signaling Activity in Drosophila melanogaster
Authors: Nagel Anja C. , Müller Dominik , Zimmermann Mirjam , Preiss Anette
Published: November 2021

The Notch signaling pathway is pivotal to cellular differentiation. Activation of this pathway involves proteolysis of the Notch receptor and the release of the biologically active Notch intracellular domain, acting as a transcriptional co-activator of Notch target genes. While the regulation of Notch signaling dynamics at the level of ligand–receptor interaction, endocytosis, and transcriptional regulation has been well studied, little is known about factors influencing Notch cleavage. We identified EP555 as a suppressor of the Notch antagonist Hairless (H). EP555 drives expression of CG32521 encoding membrane-bound proteins, which we accordingly rename membrane-bound Notch regulator (mnr). Within the signal-receiving cell, upregulation of Mnr stimulates Notch receptor activation, whereas a knockdown reduces it, without apparent influence on ligand–receptor interaction. We provide evidence that Mnr plays a role in γ-secretase-mediated intramembrane cleavage of the Notch receptor. As revealed by a fly-eye-based reporter system, γ-secretase activity is stimulated by the overexpression of Mnr, and is inhibited by its knockdown. We conclude that Mnr proteins support Notch signaling activity by fostering the cleavage of the Notch receptor. With Mnr, we identified a membrane-bound factor directly augmenting Notch intra-membrane processing, thereby acting as a positive regulator of Notch signaling activity.