bluuebunny/crossref_metadata_2025 huggingface dataset:
Sustainable Practices of Circular Economy in Operations Management
Authors: Kumar Anil , Yadav Gunjan
Published: August 2020

Because a multifaceted aspect of research allows us to answer critical queries and address broad issues; studying associative and collaborative fields is the need of hour. Therefore, the theme of this Special Issue was kept as “Sustainable Practices of Circular Economy in Operations Management”. After circulating the “Call for Papers” worldwide, the nine articles (from page numbers 1013 to 1139) in this special issue have been selected based on the technical quality of the work and their innovative approach.

The editors would like to acknowledge the help of all the people involved in this project and, more specifically, to the authors and reviewers that took part in the review process. Without their support, this special issue would not have become a reality. In particular, we would like to thank Prof. Jose Arturo Garza-Reyes, Dr. Sachin Kumar Mangla and Prof. Sunil Luthra. We would like to thank each one of the authors for their contributions. The editors wish to acknowledge the valuable contributions of the reviewers regarding the improvement of quality, coherence, and content presentation of the articles.

We are grateful to all members of International Journal of Mathematical, Engineering and Management Sciences for their assistance and timely motivation in producing this special issue. We hope the readers will share our excitement with this important scientific contribution the body of knowledge about various applications of Circular Economy for the Management of Operations.

Last but not the least we would like to thank Prof. Mangey Ram (Editor-in-Chief) for bringing out this special issue and all the researchers across the globe who have contributed for this issue.
Modeling Circular Economy Dimensions in Agri-Tourism Clusters: Sustainable Performance and Future Research Directions
Authors: Joshi Sudhanshu , Sharma Manu , Kler Rajnish
Published: August 2020

The purpose of this research is to identify the key Circular Economy dimensions (CE-D) in Agri-tourism industry and to determine the performance of these dimensions using AHP-TOPSIS method. The research is carried out in two stages, firstly 11 CE-D were identified using systematic literature review. In stage two, industrial experts validate and finalize 9 CE-D which can decide the overall performance of Agri-Tourism Networks. The AHP analysis shows that Destination Attractiveness is valued highest for making CE decisions, whereas, community contributions and sustainable livelihoods valued second and third as important dimensions. Moreover, TOPSIS shows that Pithoragarh is emerged as the best cluster among all Agri-tourism clusters selected for the study, whereas, Almora stood in second position. The Agri-food clusters are becoming more complex and flexible and started putting pressure on existing supply chains to re-design the existing value chain and incorporate more sustainable practices and performances. The identification of Circular Economy Dimensions (CE-D) to evaluate the performance of clusters can serve as guiding tool for the Agri-tourism Practioners and policy makers. Besides, the study examines relevant issues related to CE in Agri-tourism clusters, major advantages and challenges of building CE driven Agri-tourism clusters. The limitation of the study is the geographical coverage and limited demography of the respondents. The research study is among very few works on evaluating Agri-tourism supply chain practices in India, with the case reference of Uttarakhand.
Intellectual Capital and Operational Excellence: An Influential Assessment
Authors: Dhamija Pavitra
Published: August 2020

Competent intellectual capital is one of the most essential wealth that an organization requires in the present era of cutthroat competition. Operations management is nothing but management of operational processes in every big and small organization, and such activities constitute a major chunk of all organizational activities. Therefore, the present work targets to explore the association between intellectual capital and operational excellence, review of already conducted studies in the said area, and future directions through systematic literature review process. A total number of 165 articles provided by Scopus database (2010 to 2019) is used for analysis and interpretation. Bibliometric analysis and network analysis deliver significant clusters (operations management and optimization; intellectual capital and intellectual investment; knowledge management and decision support system; strategic planning and resource allocation; sustainable operations management and performance standards; behavioural research and change management), which is in turn a novel contribution of this article. The study concludes with a proposed conceptual model and key take away for researchers, academicians, and managers.
Corporate Governance Quality, Stakeholders’ Pressure, and Sustainable Development: An Integrated Approach
Authors: Almagtome Akeel , Khaghaany Maithm , Önce Saime
Published: August 2020

The goal of this paper is to explore the interrelated relationships between the quality of corporate governance, Stakeholder’s pressure, and Sustainability Reporting. We claim that sustainable development strategies are the result of the interaction of two variables: the standard of corporate governance and the pressure of stakeholders rather than the outcome of a single variable. The results indicate that the company size and corporate governance rating are positively correlated with sustainability reporting Scores disclosed by the Turkish companies. The analysis of 125 firm-year data suggest that the company provides more SRS if it has a better corporate governance rating; or larger total assets. The paper also reveals that social, environmental and economic indicators, as pillars of sustainable development, are not the result of corporate governance practices or of stakeholder pressure alone, but represent a holistic reflection of the accumulated effects of various factors related to both corporate governance practices and stakeholder theory. This paper extends the work of Taşkirmaz, and Gamze (2017) which examined the relationship between corporate governance and corporate social responsibility. Our results increase understanding of sustainable practices of the circular economy in Turkish industrial companies and indicate future trends for these applications. This research will help managers of manufacturing companies in formulating their plans to maximize the use of available resources and improve efficiency in the context of the circular economy.
Case Studies of Sustainable Road Transport Practices in Different Industry Sectors in India
Authors: Khandelwal Anoop
Published: August 2020

This study reviews actions taken by large companies in India to conform to environmental sustainability with a particular focus concerning road transport. The case study method was adopted. This entailed the researcher completing a questionnaire at face-to-face discussions with key informants in different companies across different industry sectors. The findings reveal significant congruence in adopting sustainability practices at business unit levels in general across diverse industry sectors but vary significantly in the transportation area due to segment-specific nuances. Further, it is seen that the sustainability steps are quite dependent on the nature of the products, cost of distribution related to the delivery points, and required reach of material. Research also shows that the stature of the companies expressly warrants that their policies and programs address the subject of sustainability in areas other than logistics and transportation. While this study is done across industry segments/verticals, it would be appropriate to investigate organizations within the same industry type to also establish if competition influences the width and depth of sustainability steps being taken by the Indian organizations.
Integration of Lean Approach with Energy Efficiency: Application in Kitchenware Manufacturing Company
Authors: Sagnak Muhittin , Ada Erhan , Kazancoglu Yigit , Mishra Atul
Published: August 2020

Energy efficiency in the industries is one of the leading problems of the 21st century. The main aim for the companies to deal with the energy efficiency paradigm is to save the resources in the manufacturing operations. Manufacturing opera-tions involve activities that creates wastes in any case; therefore, these wastes should be eliminated, or minimized as much as possible. In this paper, it is aimed to integrate the energy efficiency term with lean management principles. The barriers and the drivers of the energy efficiency was discussed, and the 8 wastes within lean perspective were translated into ener-gy counterparts. 8 wastes of lean approach were defined as energy efficiency perspective, and used as criteria. The study will reveal the important criteria using Fuzzy Analytic Network Process (Fuzzy ANP) method to make implications about how to eliminate these wastes.
COVID-19: A Bibliometric Analysis and Insights
Authors: Gautam Prerna , Maheshwari Sumit , Kaushal-Deep Singh Mathuria , Bhat Abdul Rashid , Jaggi Chandra K.
Published: August 2020

The current outbreak of the coronavirus disease has left the whole world traumatised. The illness triggered by the novel coronavirus is named as COVID-19. It is pre-fixed with the word “novel” because it comes under the new strain of the virus that has not been reported before. This virus outbreak has disrupted human life in the most petrifying way worldwide. The present study aims to analyse the work done in this field through a state-of-the-art review of articles based on COVID-19 and discuss the current trends in the epidemiology of this disease entity with special reference to India and the effects of this pandemic on the environment. The time frame selected for review is the beginning of this pandemic to April 10th, 2020. Scopus® database is used to carry out the analysis. Moreover, the most contributed authors, institutions, countries, etc. are showed through the analysis. The purpose of this review is to get an idea about the direction of the flow of current research, the association of various authors with each other, the role of collaboration between several institutions and the position of India in current explosive ongoing research.
Behavior of Curved Steel-Concrete Composite Beams Under Monotonic Load
Authors: Jaafer Abdulkhaliq A. , Kareem Saba L.
Published: August 2020

The paper develops a numerical investigation on the behavior of steel-concrete composite beam curved in plan to examine the effect of the various parameters. Three-dimensional finite element analysis (FEA) is employed using a commercial software, ABAQUS. The geometric and material nonlinearities are utilized to simulate the composite beam under a monotonic load. The FEA efficiency has been proved by comparing the numerical results with experimental tests obtained from previous literature, including load-deflection curves, ultimate load, ultimate and failure deflection, and cracks propagation. The validated models are used to assess some of the key parameters such the beam span/radius ratio, web stiffeners, partial interaction, concrete compressive strength, and steel beam yield stress. From the obtained results, it is noticed that the span/radius of curvature ratio influences the loading capacity, the beam yielding (i.e. the beam yield at an early stage) when the span/radius ratio increases and inelastic behavior developed early of the beam due to the torsional effect. The presence of web stiffeners with different locations in the curve composite beam affected the shear strength. The web twisting and vertical separation at the beam mid-span are observed to decrease as the number of the stiffeners increase due to the decrease in the beam torsion incorporating with transferring the failure to the concrete slab. Furthermore, the partial interaction and steel beam yield stress developed in this study appear to have a remarkable effect on beam capacity.
Blockwise and Low Density Key Error Correcting Codes
Authors: Das Pankaj Kumar , Kumar Subodh
Published: August 2020

To protect the information from disturbances created by noisy channels, redundant symbols (called check symbols) with the information symbols are added. These extra symbols play important role for the efficiency of the communication system. It is always important to know how much these check symbols are required for a code designed for a specific purpose. In this communication, we give lower and upper bounds on check symbols needed to a linear code correcting key errors of length upto p which are confined to a single sub-block. We provide two examples of such linear codes. We, further, obtain those bounds for the case when key error occurs in the whole code length, but the number of disturbing components within key error is upto a certain number. Two examples in this case also are provided.
The Real Estate Market and Financial Stability
Authors: Nguyen My-Linh Thi , Bui Toan Ngoc
Published: August 2020

This paper investigates the relationship between the real estate market (REM) and financial stability in Vietnam. Financial stability is measured using stock market volatility. The research is performed in Vietnam, a developing country whose stock and real estate markets are considered to be nascent, so the data series is very short. To solve this problem, the autoregressive distributed lag (ARDL) approach, which generates more valid results than its counterparts, is adopted. Furthermore, the ARDL approach is appropriate for a model with non-stationary data series and especially allows the analysis of the impact between data series in the short run and the long run. The results reveal the positive relationship between the real estate market and stock market volatility. However, this correlation only exists in the short run, which is a difference between Vietnam and developed countries. The paper also obtains an unprecedented finding confirming that the global financial crisis exerted a negative impact on the REM in Vietnam in the short run and the long run.
Role of Environmental Concerns on the Startups Networking: A Study of Indian Startups
Authors: Sheoran Monika , Kumar Divesh
Published: August 2020

Environmental challenges are increasingly becoming central to businesses. The startups are also being increasingly influ-enced by environmental concerns. The present article attempts to understand the environmental concerns in the values guiding the management of the startups at two levels, i.e., start up’s internal as well as external operations. At the same time, it tries to correlate the same with the network size and networking frequency of the startups. A model has been pro-posed to show the relationship between start up’s environmental concerns and their networking efforts. To identify and understand these relations, a survey was conducted on the emerging startups from different fields. The incubation centres at different institutions of Rajasthan (India) were covered under the survey. The findings highlighted a significant relation-ship between the start up’s external environmental concern and networking, thereby suggesting the significance of these concerns for environmental issues in business operations. The startups having high environmental concern were found to be among the businesses which will get more attention and find themselves more scalable. Moreover, findings also re-vealed that the environmental orientation is a very crucial aspect of networking of startups, although the influence of ex-ternal and internal environment orientation has a contrasting impact on the networking of startups. So, researchers and academicians working in the field of environmentally oriented startups can use this differentiation for further researches. There have been studies on correlating the environmental concern with networking in established firms in developed country such as Dickel et al. (2018). Moreover, emerging economies like India, there have not been an attempt to study this kind of relationship in the context of startups. The current study tries to validate the results of the study conducted by Dickel et al. (2018) for the startups in Rajasthan (India).
Simulation Based Energy Control and Comfort Management in Buildings Using Multi-Objective Optimization Routine
Authors: Harish V. S. K. V. , Kumar Arun
Published: August 2020

Building energy management systems with high-level of sophistication have to control and manage a large set of actuators and other equipment and evaluate performance of each and every-subsystem on periodic basis. In the present study, a control algorithm has been developed as an engineered solution for intelligent energy control and comfort management in buildings. A hybrid genetic algorithm - particle swarm optimization based multi-objective optimization routine is developed to compute the optimal set-point level of heating, ventilation, and air conditioning and lighting systems with a view to balancing energy consumption and occupants' comfort. Occupants' comfort is evaluated for indoor air quality as CO2 concentration, thermal and visual comfort. Case studies with a different set of optimal parameters have been worked out to calculate the amount of energy consumed as well as comfort level achieved. Overall occupants' comfort was improved by 17% and daily, weekly and monthly building energy consumption was reduced by 2.5%, 7.7%, and 17.9%, respectively. The developed intelligent control strategy can be integrated with building automation systems to achieve finely tuned real-time optimized comfort management
Foundations of the Relative Constancy of Mean Velocity for Natural Streams: A General Principle of Steady State Anticipated by L. Prandtl and L. Leopold
Authors: Aragón Alfredo José Constaín , Peña-Guzmán Carlos , Peña-Olarte Gina Alexandra
Published: August 2020

Mean velocity is a key parameter for understanding, modeling and predicting the complex phenomena of advection and dispersion in natural watercourses, which are threatened by human intervention and river disasters. For this reason, the principles of relative constancy for the value of this parameter, established early by L. Prandtl and L. Leopold in the 20th century, are powerful theoretical tools for those who develop engineering tasks in this field. This article presents updated analyses of these principles, explaining how this constancy depends essentially on the existence of a steady state in the flow, which allows equiprobability in the system, and therefore, a minimum production of entropy. At the same time an equation is developed, as a function of macroscopic parameters, facilitating its interpretation and practical application. This hypothesis is contrasted by reviewing the relative values for those parameters and their effect on the formula, and defining the practical conditions of applicability of the formula. This method of validating the hypothesis is important in hydrometric practice, as flow velocity measurements are the starting point for their description, especially for large rivers where comprehensive assessments are impossible.
Mixture Designs Generated by Orthogonal Arrays Developed Using Difference Schemes
Authors: Singh Poonam , Sarin Vandana , Midha Neha
Published: August 2020

This paper presents an algorithm for constructing mixture designs based on orthogonal arrays developed using difference schemes. The algorithm can also be applied to constrained mixture experiments. The algorithm allows the generation of efficient mixture designs for Scheffé canonical polynomials.
Quality Improvement of Recycled Aggregate Concrete using Six Sigma DMAIC Methodology
Authors: Patil Suhas Vijay , Rao K. Balakrishna , Nayak Gopinatha
Published: August 2020

Recycled aggregates (RA) are obtained from construction and demolished waste, laboratory crushed concrete and concrete waste at RMC plants. The concrete made from recycled aggregate is known as recycled aggregate concrete. The use of recycled aggregate is very beneficial to the environment in civil works. Its usage also helps in financial saving as the cost of transportation and production energy cost of natural coarse aggregate (NCA) is reduced. In India, the recycled aggregate application in lower grade concrete work is observed. However, the effect of recycled aggregate on the strength and durability of concrete restricts its use in higher-grade work. This paper presents a series of tests carried out on recycled coarse aggregate (RCA) and recycled coarse aggregate concrete (RCAC) and test results are compared with the NCA and parent concrete made from NCA. Tests were carried out as per IS code and concrete was prepared using a two-stage mixing approach in the concrete mix design. M30 concrete mix of four RCAC samples was tested at 28 days of curing and in comparison with parent concrete, it is found that on an average compressive strength is decreased by 12.89% at 28 days curing. Adhered mortar increases the porosity of the recycled aggregate and forms a weak zone between aggregate surface and mortar. In addition, test results showed the defects in recycled aggregate and helped to identify the area where concentration is necessary to improve the quality of recycled aggregate using six sigma DMAIC methodology. Total of 12 defects were found in the process and raw material. Statistical analysis was used to evaluate the performance of all the mix made with RCA.
Multiclass Recognition of Offline Handwritten Devanagari Characters using CNN
Authors: Bisht Mamta , Gupta Richa
Published: August 2020

The handwriting style of every writer consists of variations, skewness and slanting nature and therefore, it is a stimulating task to recognise these handwritten documents. This article presents a study on various methods available in literature for Devanagari handwritten character recognition and performs its implementation using Convolutional neural network (CNN). Available methods are studied on different parameters and a tabular comparison is also presented which concludes superiority of CNN model in character recognition task. The proposed CNN model results in well acceptable accuracy using dropout and stochastic gradient descent (SGD) optimizer.
Comparative Analysis of Background Subtraction and CNN Algorithms for Mid-Block Traffic Data Collection and Classification
Authors: Illahi Ubaid , Mir Mohammad Shafi
Published: August 2020

Classification of vehicles in the traffic stream is a pre-requisite for planning and designing the facilities for road-users. Considering the importance and gaining popularity of automated systems in this field, the aim of this article is to compare two algorithms- one using the Background Subtraction (BS) technique and the other using Convolutional Neural Network (CNN) with a primary focus on an increased number of vehicle classifications. To check the reliability of these algorithms, the outputs produced were validated against the data obtained from Kachkoot Toll Plaza, India. The results were analyzed using drop-line diagrams and confusion matrices. The overall efficiency of the CNN-based algorithm (0.98) was found to be better than the BS-based algorithm (0.95). The comparison presented in this paper will be useful for transportation professionals and agencies.
Radial Basis Function Pseudospectral Method for Solving Standard Fitzhugh-Nagumo Equation
Authors: Arora Geeta , Bhatia Gurpreet Singh
Published: August 2020

In this article, a pseudospectral approach based on radial basis functions is considered for the solution of the standard Fitzhugh-Nagumo equation. The proposed radial basis function pseudospectral approach is truly mesh free. The standard Fitzhugh-Nagumo equation is approximated into ordinary differential equations with the help of radial kernels. An ODE solver is applied to solve the resultant ODEs. Shape parameter which decides the shape of the radial basis function plays a significant role in the solution. A cross-validation technique which is the extension of the statistical approach leave-one-out-cross-validation is used to find the shape parameter value. The presented method is demonstrated with the help of numerical results which shows a good understanding with the exact solution. The stability of the proposed method is demonstrated with the help of the eigenvalues method numerically.
Concept for a Supply Chain Digital Twin
Authors: Barykin Sergey Yevgenievich , Bochkarev Andrey Aleksandrovich , Kalinina Olga Vladimirovna , Yadykin Vladimir Konstantinovich
Published: August 2020

There is currently a discussion going on in the scientific community about using digital twins and modeling to manage risks in the supply chains. This need for constructing digital twins is caused by the low reliability and stability of supply chains due to the faults in their operation. These faults are a result of risks in the supply chains which can be consolidated into two types. The first type is operational risks. These are the current risks of the supply chain itself caused by an uncer-tainty of supply and demand as well as by an obstructed flow of information along the supply chain. The second type is critical risks caused by force majeure. These risks disrupt the normal operation of the supply chain and critically reduce the most important performance indicators of the company such as annual income and profits. Risks happen due to natural or man-made causes such as fires and floods in the distribution centers or at production facilities, legal disputes with sup-pliers, strikes, terrorist attacks on logistics facilities and others. Dynamic simulation and analytical optimization are two dominant technologies for managing risks of the supply chains, which helps to increase their reliability and stability if failures occur. Through optimizing and simulating of the supply chains, companies can generate new information about the impact of failure and influence the supply chain and its performance by looking at various scenarios that simulate the locations of failures, the duration and recovery policies. An analysis of the literary sources shows that there is no single approach to build the concept for a supply chain digital twin. This article gives an overview of the literature according to this problem and offers the author's point of view on the concept for a supply chain digital twin.
A Hybrid Genetic Algorithm-Based Fuzzy Markovian Model for the Deterioration Modeling of Healthcare Facilities
Authors: Ahmed Reem , Zayed Tarek , Nasiri Fuzhan
Published: August 2020

Healthcare facilities are constantly deteriorating due to tight budgets allocated to the upkeep of building assets. This entails the need for improved deterioration modeling of such buildings in order to enforce a predictive maintenance approach that decreases the unexpected occurrence of failures and the corresponding downtime elapsed to repair or replace the faulty asset components. Currently, hospitals utilize subjective deterioration prediction methodologies that mostly rely on age as the sole indicator of degradation to forecast the useful lives of the building components. Thus, this paper aims at formulating a more efficient stochastic deterioration prediction model that integrates the latest observed condition into the forecasting procedure to overcome the subjectivity and uncertainties associated with the currently employed methods. This is achieved by means of developing a hybrid genetic algorithm-based fuzzy Markovian model that simulates the deterioration process given the scarcity of available data demonstrating the condition assessment and evaluation for such critical facilities. A nonhomogeneous transition probability matrix (TPM) based on fuzzy membership functions representing the condition, age and relative deterioration rate of the hospital systems is utilized to address the inherited uncertainties. The TPM is further calibrated by means of a genetic algorithm to circumvent the drawbacks of the expert-based models. A sensitivity analysis was carried out to analyze the possible changes in the output resulting from predefined modifications to the input parameters in order to ensure the robustness of the model. The performance of the deterioration prediction model developed is then validated through a comparison with a state-of-art stochastic model in contrast to real hospital datasets, and the results obtained from the developed model significantly outperformed the long-established Weibull distribution-based deterioration prediction methodology with mean absolute errors of 1.405 and 9.852, respectively. Therefore, the developed model is expected to assist decision-makers in creating more efficient maintenance programs as well as more data-driven capital renewal plans.
Audio Feedback for Device-Supported Balance Training: Parameter Mapping and Influencing Factors
Authors: Fuchs Dominik , Knauer Martin , Egger Marion , Friedrich Petra
Published: August 2020

Recent studies suggest that real-time auditory feedback is an effective method to facilitate motor learning. The evaluation of the parameter mapping (sound-to-movement mapping) is a crucial, yet frequently neglected step in the development of audio feedback. We therefore conducted two experiments to evaluate audio parameters with target finding exercises designed for balance training. In the first experiment with ten participants, five different audio parameters were evaluated on the X-axis (mediolateral movement). Following that, in a larger experiment with twenty participants in a two-dimensional plane (mediolateral and anterior-posterior movement), a basic and synthetic audio model was compared to a more complex audio model with musical characteristics. Participants were able to orient themselves and find the targets with the audio models. In the one-dimensional condition of experiment one, percussion sounds and synthetic sound wavering were the overall most effective audio parameters. In experiment two, the synthetic model was more effective and better evaluated by the participants. In general, basic sounds were more helpful than complex (musical) sound models. Musical abilities and age were correlated with certain exercise scores. Audio feedback is a promising approach for balance training and should be evaluated with patients. Preliminary evaluation of the respective parameter mapping is highly advisable.
Vision-Based Spacecraft Pose Estimation via a Deep Convolutional Neural Network for Noncooperative Docking Operations
Authors: Phisannupawong Thaweerath , Kamsing Patcharin , Torteeka Peerapong , Channumsin Sittiporn , Sawangwit Utane , Hematulin Warunyu , Jarawan Tanatthep , Somjit Thanaporn , Yooyen Soemsak , Delahaye Daniel , Boonsrimuang Pisit
Published: August 2020

The capture of a target spacecraft by a chaser is an on-orbit docking operation that requires an accurate, reliable, and robust object recognition algorithm. Vision-based guided spacecraft relative motion during close-proximity maneuvers has been consecutively applied using dynamic modeling as a spacecraft on-orbit service system. This research constructs a vision-based pose estimation model that performs image processing via a deep convolutional neural network. The pose estimation model was constructed by repurposing a modified pretrained GoogLeNet model with the available Unreal Engine 4 rendered dataset of the Soyuz spacecraft. In the implementation, the convolutional neural network learns from the data samples to create correlations between the images and the spacecraft’s six degrees-of-freedom parameters. The experiment has compared an exponential-based loss function and a weighted Euclidean-based loss function. Using the weighted Euclidean-based loss function, the implemented pose estimation model achieved moderately high performance with a position accuracy of 92.53 percent and an error of 1.2 m. The in-attitude prediction accuracy can reach 87.93 percent, and the errors in the three Euler angles do not exceed 7.6 degrees. This research can contribute to spacecraft detection and tracking problems. Although the finished vision-based model is specific to the environment of synthetic dataset, the model could be trained further to address actual docking operations in the future.
Differential Response to Water Deficit in Chili Pepper (Capsicum annuum L.) Growing in Two Types of Soil Under Different Irrigation Regimes
Authors: Macias-Bobadilla Israel , Vargas-Hernandez Marcela , Guevara-Gonzalez Ramon G. , Rico-Garcia Enrique , Ocampo-Velazquez Rosalia V. , Torres-Pacheco Irineo
Published: August 2020

Chili pepper (Capsicum spp.) is one of the most economically important horticultural crops in the world; its production for the food and pharmaceutical industries has been increasing worldwide. The economic importance of this crop is due, in part, to the nutraceutical properties derived from its secondary metabolism. Drought is the main environmental factor that affects crop production. Nevertheless, studies involving water deficit have considered short-term responses to sharp water deficit rather than long-term acclimation processes through moderate and gradually increasing water deficits, which omitted the dynamics and profile of the secondary metabolism that are part of the plant’s defence system against this stress factor. The present study aimed to identify the different mechanisms that chili pepper plants use to cope with drought stress using a progressive decrease and increase of water availability, conditions that commonly occur for crops in open fields. Four treatments were applied as follows: gradual water deficit (GWD), initial waterlogging with gradual water deficit (IWGD), sudden water deficit with gradual recovery (SWDR), and no deficit of water (NDW). These conditions should represent a more real situation similar to that faced by plants in the agricultural environment. In order to evaluate the response mechanisms associated with these water deficits, changes in phenological variables, proline accumulation, and the gene expression of phenylalanine ammonia-lyase (PAL), chalcone synthase (CHS), peroxidase (POD), and superoxide dismutase (SOD) were measured in chili pepper plants growing on land under different irrigation regimes in two contrasting soil types in areas where chili pepper plants are cultivated in central Mexico. The variables evaluated showed a differentiated response of the mechanisms in plants growing under different levels of water deficit. Given the differential response observed for the gene expression and morphological and biochemical variables studied in chili pepper plants against different water regimes, in this work, this may have implications for more efficient use of water in crops with high nutraceutical content, in addition to prospects for using products derived from secondary metabolism in the pharmaceutical industry.
A Deep Learning Approach for Weed Detection in Lettuce Crops Using Multispectral Images
Authors: Osorio Kavir , Puerto Andrés , Pedraza Cesar , Jamaica David , Rodríguez Leonardo
Published: August 2020

Weed management is one of the most important aspects of crop productivity; knowing the amount and the locations of weeds has been a problem that experts have faced for several decades. This paper presents three methods for weed estimation based on deep learning image processing in lettuce crops, and we compared them to visual estimations by experts. One method is based on support vector machines (SVM) using histograms of oriented gradients (HOG) as feature descriptor. The second method was based in YOLOV3 (you only look once V3), taking advantage of its robust architecture for object detection, and the third one was based on Mask R-CNN (region based convolutional neural network) in order to get an instance segmentation for each individual. These methods were complemented with a NDVI index (normalized difference vegetation index) as a background subtractor for removing non photosynthetic objects. According to chosen metrics, the machine and deep learning methods had F1-scores of 88%, 94%, and 94% respectively, regarding to crop detection. Subsequently, detected crops were turned into a binary mask and mixed with the NDVI background subtractor in order to detect weed in an indirect way. Once the weed image was obtained, the coverage percentage of weed was calculated by classical image processing methods. Finally, these performances were compared with the estimations of a set from weed experts through a Bland–Altman plot, intraclass correlation coefficients (ICCs) and Dunn’s test to obtain statistical measurements between every estimation (machine-human); we found that these methods improve accuracy on weed coverage estimation and minimize subjectivity in human-estimated data.
Effect of Organic Amendments on the Productivity of Rainfed Lowland Rice in the Kilombero Floodplain of Tanzania
Authors: Kwesiga Julius , Grotelüschen Kristina , Senthilkumar Kalimuthu , Neuhoff Daniel , Döring Thomas F. , Becker Mathias
Published: August 2020

Organic amendments can reportedly sustain and increase lowland rice productivity in smallholder systems. Few studies have assessed locally-available substrates in hydrologically variable floodplain environments. We investigated the effects of green and farmyard manures on rice yields, and total soil C and N in the Kilombero floodplain, Tanzania. At both the fringe and the middle positions, five treatments were applied in 2016 and 2017, comprising (1) non-amended control, (2) farmyard manure, (3) pre-rice legumes, (4) post-rice legumes and (5) a combination of green and farmyard manures. Residual treatment effects were assessed in 2018 when rice plots were uniformly non-amended. Depending on the year and the position, organic amendments increased rice grain yields by 0.7–3.1 Mg ha–1 above the non-amended control. Sole green and farmyard manure applications had similar effects on grain yield, while a combination of green and farmyard manure led to a significant increase in grain yield above both the control and sole applications of organic amendments in both years. The contribution from biological N2 fixation by legumes ranged from 4 to 61 kg N ha–1. Despite partial N balances being mostly negative, we observed positive residual effects on the yield of the non-amended rice in the third year. Such effects reached up to 4 Mg ha−1 and were largest with post-rice legumes, sole or combined with farmyard manure. Irrespective of the position in the floodplain, manures significantly increased soil C and N contents after two years, hence enhancing soil fertility and resulting in increased rice grain yields. Comparable benefits may be obtained along the hydrological gradients of other large river floodplains of the region and beyond.
Antioxidant Purple Corn Protein Concentrate from Germinated Andean Purple Corn Seeds
Authors: Vilcacundo Edgar , García Antón , Vilcacundo Mario , Morán Roberto , Samaniego Iván , Carrillo Wilman
Published: August 2020

Ecuador Andean purple corn (Zea mays L.) was subjected to a germination process at 15–40 °C for 24–168 incubation hours. Purple corn protein concentrates (PCPCs) were obtained by alkaline extraction at pH 8.0 and pH 10.0, followed by an isoelectric precipitation process at pH 4.0, pH 5.0 and pH 6.0. Proteins and phenolic content of PCPCs was calculated. PCPC antioxidant properties were determined by the ferric-reducing antioxidant power (FRAP) in vitro method and by the 2,2-azinobis, 3-ethyl-benzothiazoline-6-sulfonic acid, (ABTS) in vitro method. Andean purple corn seeds were able to germinate under the germination conditions tested in this study. The higher percentage of germination was of 63.33% at 168 h/25 °C. The PCPCs protein profile was characterized for the presence of six bands with molecular weights of 14.50 kDa, 20.12 kDa, 25.18 kDa, 41.85 kDa, 59.59 kDa, and 65.87 kDa. Germinated PCPC presented a high TPC content with ranges of 605.71–1820.00 mg gallic acid equivalents (GAE)/g PCPC dry weight (DW), germinated PCPC/72 h/25 °C presented a higher value of 1820.00 mg GAE/g PCPC, DW. All germinated PCPCs samples assayed presented strong antioxidant activity when measured by the ABTS and FRAP methods. Germinated PCPC/144 h/35 °C presented high antioxidant activity by ABTS with 804.35 µmol Trolox equivalents (TE)/g PCPC DW and germinated PCPC/144 h/30 °C presented a high value by the FRAP method, 987.83 µmol TE/g PCPC DW.
Resistance of Maize Hybrids to Fusarium graminearum, F. culmorum, and F. verticillioides Ear Rots with Toothpick and Silk Channel Inoculation, as Well as Their Toxin Production
Authors: Mesterhazy Akos , Toldine Toth Eva , Szel Sandor , Varga Monika , Toth Beata
Published: August 2020

Testing Fusarium resistance to ear rots in maize requires a well-supported methodology and tests for toxin responses. In this study, commercial hybrids were tested for resistance to Fusarium graminearum, Fusarium culmorum, and Fusarium verticillioides (kernel and silk channel), as well as their toxin response. One third of the hybrids tested showed a similar resistance or susceptibility to the three pathogens and their toxin response, but there is no proof for their genetic background being the same or different. The performance of the remaining hybrids was highly variable and supports the idea of different genetic regulation. The mean ear rot severity of the kernel resistance was doubled compared with the silk channel resistance data. The ear rot and toxin tests displayed significant positive correlations, verifying the decisive role of resistance in toxin regulation. Several hybrids, termed toxigenic hybrids, showed significant extra toxin production, indicating an additional food safety risk. The toothpick method gave more reliable results and a better differentiation of genotypes. The resistance to different Fusarium spp. in a specific growing region should be analyzed separately in independent resistance tests. Through this, the food safety risks could be better identified. Susceptible hybrids should not be used for commercial production.
Improving Access to Antimicrobial Prescribing Guidelines in 4 African Countries: Development and Pilot Implementation of an App and Cross-Sectional Assessment of Attitudes and Behaviour Survey of Healthcare Workers and Patients
Authors: Olaoye Omotayo , Tuck Chloe , Khor Wei Ping , McMenamin Roisin , Hudson Luke , Northall Mike , Panford-Quainoo Edwin , Asima Derrick Mawuena , Ashiru-Oredope Diane
Published: August 2020

Smartphone apps have proven to be an effective and acceptable resource for accessing information on antimicrobial prescribing. The purpose of the study is to highlight the development and implementation of a smartphone/mobile app (app) for antimicrobial prescribing guidelines (the Commonwealth Partnerships for Antimicrobial Stewardship—CwPAMS App) in Ghana, Tanzania, Uganda and Zambia and to evaluate patients’ and healthcare providers’ perspectives on the use of the App in one of the participating institutions. Two structured cross-sectional questionnaires containing Likert scale, multiple-choice, and open-ended questions were issued to patients and healthcare workers six months after the introduction of the app at one of the hospital sites. Metrics of the use of the app for a one-year period were also obtained. Download and use of the app peaked between September and November 2019 with pharmacists accounting for the profession that the most frequently accessed the app. More than half of the responding patients had a positive attitude to the use of the app by health professionals. Results also revealed that more than 80% of health care workers who had used the CwPAMS App were comfortable using a smartphone/mobile device on a ward round, considered the app very useful, and found it to improve their awareness of antimicrobial stewardship, including documentation of the indication and duration for antimicrobials on the drug chart. It also encouraged pharmacists and nurses to challenge inappropriate antimicrobial prescribing. Overall, our findings suggest that its use as a guide to antimicrobial prescribing sparked positive responses from patients and health professionals. Further studies will be useful in identifying the long-term consequences of the use of the CwPAMS App and scope to implement in other settings, in order to guide future innovations and wider use.
Candida auris Bloodstream Infections in Russia
Authors: Barantsevich Natalia E. , Vetokhina Antonina V. , Ayushinova Natalia I. , Orlova Olga E. , Barantsevich Elena P.
Published: August 2020

Candida auris—a fungus (yeast) that can cause hospital outbreaks was first recognized in 2009. The authors report data on 38 cases of C. auris bloodstream infections in multidisciplinary hospitals situated in two distantly located regions of Russia, considering predisposing factors, antifungal susceptibility of isolates, treatment, and outcomes. Interhospital transfers of patients and labor migration contributed to the spread of C. auris. The South Asian lineage of the studied strains was indicated by K143R substitution in ERG11 gene and phylogenetic analysis of internal transcribed spacer and D1-D2 domain. All isolates from C. auris candidemia cases were susceptible to echinocandins. High-level resistance to fluconazole and resistance to amphotericin B were present in the majority of strains. The overall all-cause mortality rate in C. auris bloodstream infections was 55.3% and the 30-day all-cause mortality rate 39.5%. The attributable mortality was 0%. Eradication of C. auris from blood was associated with the favourable outcomes in patients. It was achieved irrespective of whether antifungal preparations within or outside the susceptibility range were administered. Further international surveillance and studies providing consensus guidelines for the management of C. auris infections are needed.
Utilizing Energy Storage for Operational Adequacy of Wind-Integrated Bulk Power Systems
Authors: Shrestha Tej Krishna , Karki Rajesh
Published: August 2020

Renewable energy resources like wind generation are being rapidly integrated into modern power systems. Energy storage systems (ESS) are being viewed as a game-changer for renewable integration due to their ability to absorb the variability and uncertainty arising from the wind generation. While abundant literature is available on system adequacy and operational reliability evaluation, operational adequacy studies considering wind and energy storage have received very little attention, despite their elevated significance. This work presents a novel framework that integrates wind power and energy storage models to a bulk power system model to sequentially evaluate the operational adequacy in the operational mission time. The analytical models are developed using a dynamic system state probability evaluation approach by incorporating a system state probability estimation technique, wind power probability distribution, state enumeration, state transition matrix, and time series analysis in order to quantify the operational adequacy of a bulk power system integrated with wind power and ESS. The loss of load probability (LOLP) is used as the operational adequacy index to quantify the spatio-temporal variation in risk resulting from the generation and load variations, their distribution on the network structure, and the operational strategies of the integrated ESS. The proposed framework is aimed to serve as a guideline for operational planning, thereby simplifying the decision-making process for system operators while considering resources like wind and energy storage facilities. The methodology is applied to a test system to quantify the reliability and economic benefits accrued from different operational strategies of energy storage in response to wind generation and other operational objectives in different system scenarios.