bluuebunny/crossref_metadata_2025 huggingface dataset:
Measuring Intra-Urban Inequality with Structural Equation Modeling: A Theory-Grounded Indicator
Authors: Libório Matheus Pereira , Martinuci Oseias da Silva , Laudares Sandro , Lyrio Renata de Mello , Machado Alexei Manso Correa , Bernardes Patrícia , Ekel Petr
Published: October 2020

Composite indicators are almost always determined by methods that aggregate a reasonable number of manifest variables that can be weighted—or not—as new synthesis variables. A problem arises when these aggregations and weightings do not capture the possible effects that the various underlying dimensions of the phenomenon have on each other, and consequently distort the assessment of intra-urban inequality. In this paper, we explore the direct and indirect effects that the different underlying dimensions of intra-urban inequality have on indicators that represent this phenomenon. Structural equation modeling was used to build a composite indicator that captures the direct and indirect effects of the underlying dimensions of intra-urban inequality. From this modeling that combines confirmatory factor analysis with a system of simultaneous equations, the intra-urban inequality of the urban conurbation of Maringá–Sarandi–Paiçandu, Brazil was measured. The model comprises first- and second-order structures. The first-order structure is composed of non-observed variables that represent three underlying dimensions of intra-urban inequality. The second-order structure is the intra-urban inequality composite indicator that synthesizes the non-observed variables of the first-order structure. The model aims at demonstrating how to perform a theorized measurement of urban inequality so that it makes it possible to identify which dimensions most influence the others, as well as which dimensions are more relevant to this purpose.
Accessibility, Infrastructure Provision and Residential Land Value: Modelling the Relation Using Geographic Weighted Regression in the City of Rajkot, India
Authors: Munshi Talat
Published: October 2020

Amenities and infrastructure provision in urban areas are essential for the sustainable future of cities in developing countries like India. Indian cities have large development deficits and find it challenging to bridge the gap using traditional methods. Provision of these facilities costs money, which is often not available. However, access to amenities and infrastructure adds to land premium, which, if captured, can be used to finance the provision of these facilities. In India, very little information is available on the value of accessibility and infrastructure provision, and thus, these indirect benefits are primarily ignored by urban planners. This study fills the gap by identifying these benefits using Rajkot city in India as a case study. A geographic weighted regression model is used to model the relationship. It is found that land price variation is explained to a good extent using the model. Estimates show that infrastructure and amenities have a substantial impact on land value, much higher than the cost required to provide these.
An Examination of the Safety Impacts of Bus Priority Routes in Major Israeli Cities
Authors: Gitelman Victoria , Korchatov Anna , Elias Wafa
Published: October 2020

Bus priority routes (BPRs) promote public transport use in urban areas; however, their safety impacts are not sufficiently understood. Along with proven positive mobility effects, such systems may lead to crash increases. This study examines the safety impacts of BPRs, which have been introduced on busy urban roads in three major Israeli cities—Tel Aviv, Jerusalem and Haifa. Crash changes associated with BPR implementation are estimated using after–before or cross-section evaluations, with comparison-groups. The findings show that BPR implementation is generally associated with increasing trends in various crash types and, particularly, in pedestrian crashes at junctions. Yet, the results differ depending on BPR configurations. Center lane BPRs are found to be safer than curbside BPRs. The best safety level is observed when a center lane BPR is adjacent to a single lane for all-purpose traffic. Local public transport planners should be aware of possible negative implications of BPRs for urban traffic safety. Negative safety impacts can be moderated by a wider use of safety-related measures, as demonstrated in BPRs’ operation in Haifa. Further research is needed to delve into the reasons for the negative safety impacts of BPRs under Israeli conditions relative to the positive impacts reported in other countries.
The Impact of CEOs’ Transformational Leadership on Sustainable Organizational Innovation in SMEs: A Three-Wave Mediating Role of Organizational Learning and Psychological Empowerment
Authors: Begum Saira , Xia Enjun , Mehmood Khalid , Iftikhar Yaser , Li Yan
Published: October 2020

The sustainable organizational innovation is of paramount importance for enhancing productivity in firms and provides organizations with the strategic direction needed to allow them to perform at an international level. The leadership styles play a key role in their firms’ potential to consistently innovate. Using data from a time-lagged design with three waves, CEOs of Chinese small and medium-sized enterprises (SMEs) participated in the study. The findings reveal that psychological empowerment mediated the relationship between transformational leadership and sustainable organizational innovation. Organizational learning was found to indirectly effect the relationship between transformational leadership and sustainable organizational innovation. It also demonstrated that psychological empowerment had a positive impact on organizational learning. The findings indicate the strategic significance of transformational leadership and its influence on sustainable organizational innovation for SMEs. Theoretical contributions and practical implications were also discussed.
Relationships among Beliefs, Attitudes, Time Resources, Subjective Norms, and Intentions to Use Wearable Augmented Reality in Art Galleries
Authors: Jung Timothy , tom Dieck M. Claudia , Lee Hyunae , Chung Namho
Published: October 2020

As a result of interactive and immersive technologies such as augmented reality, almost every service business has changed their ways of engaging with consumers. However, there has been little research on acceptance and use of wearable augmented reality (AR) in interactive services in museums and art galleries. Therefore, the aim of this study was to investigate the causal relationships among customers’ beliefs, evaluation, attitudes, perceived behavior control (time resources), subjective norms, and intentions to use wearable AR and visit a tourist attraction (an art gallery) using the theory of planned behavior. The results showed that time resources affected intention to visit an art gallery, while attitude toward wearable AR had an impact on intention to use wearable AR. Subjective norms were found to predict intentions, and the intention to use wearable AR was found to influence the intention to visit an art gallery.
Development of a New Green Indicator and Its Implementation in a Cyber–Physical System for a Green Supply Chain
Authors: Morella Paula , Lambán María Pilar , Royo Jesús , Sánchez Juan Carlos , Ng Corrales Lisbeth del Carmen
Published: October 2020

This work investigates Industry 4.0 technologies by developing a new key performance indicator that can determine the energy consumption of machine tools for a more sustainable supply chain. To achieve this, we integrated the machine tool indicator into a cyber–physical system for easy and real-time capturing of data. We also developed software that can turn these data into relevant information (using Python): Using this software, we were able to view machine tool activities and energy consumption in real time, which allowed us to determine the activities with greater energy burdens. As such, we were able to improve the application of Industry 4.0 in machine tools by allowing informed real-time decisions that can reduce energy consumption. In this research, a new Key Performance Indicator (KPI) was been developed and calculated in real time. This KPI can be monitored, can measure the sustainability of machining processes in a green supply chain (GSC) using Nakajima’s six big losses from the perspective of energy consumption, and is able to detect what the biggest energy loss is. This research was implemented in a cyber–physical system typical of Industry 4.0 to demonstrate its applicability in real processes. Other productivity KPIs were implemented in order to compare efficiency and sustainability, highlighting the importance of paying attention to both terms at the same time, given that the improvement of one does not imply the improvement of the other, as our results show.
A Strategy for Sustainable Development of Cooperatives in Developing Countries: The Success and Failure Case of Agricultural Cooperatives in Musambira Sector, Rwanda
Authors: Moon Sunghye , Lee Sang-ho
Published: October 2020

Many international aid agencies have been trying to utilize cooperatives as a strategic means for poverty reduction and rural community development in developing countries due to their characteristics, operational efficiency, and effectiveness. However, it is difficult to find a successful case due to various factors. This study tries to propose strategies that the aid agencies and local residents should use for the success of cooperatives in developing countries through an analysis of the success and failure cases of the two cooperatives established under the Saemaul ODA Program in Rwanda. While the length of the ODA program and scale of support significantly affect the cooperatives’ self-reliance, what support they receive from the aid agencies and whether it is a long-term support plan considering exit strategies are also important factors of their success. In addition to the support of the aid agencies, efforts of the cooperative members are essential. Cooperatives should reinforce their sense of ownership to achieve the long-term goals of self-reliance and sustainability by setting clear and feasible short-term goals and achieving them one by one through cooperation among members, as in the case of Korea’s Saemaul Undong.
Does the Environmental Kuznets Curve for CO2 Emissions Exist for Rwanda? Evidence from Bootstrapped Rolling-Window Granger Causality Test
Authors: Nutakor Felix , Bizumuremyi Sylvestre , Li Jinke , Liu Wei
Published: October 2020

This paper examined the causal relationship between economic growth and carbon dioxide emissions (CO2) in Rwanda using annual data from 1960–2014. The study was conducted within the framework of the environmental Kuznets curve (EKC) hypothesis using the rolling-window bootstrap Granger causality test approach with a rolling-window size of 15 years. The methodology allows for non-constancy in the parameters of the vector autoregression (VAR) model in the short run as well as in the long run. The study found bi-direction causality between the real gross domestic product (GDP) and CO2 emissions in metric tons per capita. The results from the rolling-window bootstrap Granger causality test show that GDP negatively influenced CO2 emissions in the 1976–1977, 1990–1993, 2005–2006, and 2007–2013 sub-sample periods. This result depicts a monotonically decreasing EKC, contrary to the standard EKC relationship. The downward-sloping EKC was explained by the transition of the Rwandan economy from an industrial-based economy to a service-based economy. Further, a feedback effect from CO2 emissions to the economy was established.
Transitioning Toward a Circular Economy: The Impact of Stakeholder Engagement on Sustainability Culture
Authors: Salvioni Daniela M. , Almici Alex
Published: October 2020

The circular economy transition increasingly points to the need for a change in corporate culture, namely toward sustainability. This change can be supported by improving relations with relevant stakeholders, engaging comprehensively with them, and creating strong awareness about issues such as ecosystem protection, health-related safeguards, and the careful use of resources. In this regard, through stakeholder engagement and a review of traditional business models, the circular economy can contribute to transforming the corporate culture to ensure the concurrent enhancement of economic, social, and environmental dimensions. This study verified the role of stakeholder engagement in establishing and strengthening the sustainability culture in a company transitioning toward a circular economy. The case study research methodology was applied, referencing a single firm—operating in the oil and energy industry—representing one of the best practices in the international context, even if some efforts are still required to reduce downstream emissions. The findings underline the contributing role played by stakeholder engagement in establishing values and principles compliant with environmental protection and community wellbeing. Thus, this study contributes to the existing stakeholder engagement literature and sheds light on the practical implications and emerging issues.
Sustainable Policy Measures Based on Implementation of Digital Technologies in Corrections: Exploratory Study from Slovakia and Beyond
Authors: Borseková Kamila , Klátik Jaroslav , Koróny Samuel , Krištofík Peter , Mihók Peter , Orviský Martin
Published: October 2020

Across the world, millions of people are incarcerated every year, while hundreds of thousands of them are released back into their home communities. Despite several alternatives within the criminal justice system, incarceration is still considered as the most natural method of correction. This can lead to different types of unsustainable pathways within a society. Despite the growing importance and increasing use of digital technologies, there are relatively few scientific studies related to the implementation of digital technologies in corrections. Therefore, the present paper aims to assess the sustainable policy measures based on the implementation of digital technologies in corrections, namely electronic monitoring (EM). The originality of our paper is supported by unique primary data gathered during the first national survey on the assessment of sustainability measures of EM in Slovakia. Our research reveals that EM implementation contributes to individual and institutional resilience in a socio-economic context; the requirements for a conditional release of serious offenders with mandatory EM seem to have created sustainable conditions for the use of this form of the EM “back door” scheme. EM programs are aimed at suppressing crime through increased accountability and monitoring, which leads to their sustainability. Maintaining social and family ties, reducing risk of imprisonment and undesirable new ties, and keeping working habits are the main sustainable policy measures of EM that support better social inclusion of offenders. Assessment of the sustainable policy measures based on the implementation of digital technologies in corrections, namely electronic monitoring (EM) uncovered in the present paper, creates space for further research and policy implications. Data protection, automated data processing and artificial intelligence in the implementation of digital technologies in corrections are important topics that deserve much more attention in research.
Multiobjective Optimization of a Residential Grid-Tied Solar System
Authors: Vaz Warren S.
Published: October 2020

Residential customers are increasingly turning to solar energy as they are becoming more climate-conscious and solar energy is becoming more cost-effective. However, customers are often faced with myriad choices from retailers. The current retail landscape features several solar panel sizes, battery storage sizes, and technologies, and all of them come in a range of prices. The present study aims to present a strategy to optimize the choice for the customer taking two conflicting objectives into account: minimizing the cost and minimizing the carbon footprint. By presenting multiple nondominated (optimal) solutions based on the individual’s unique parameters, customers can make the optimal choice. Two disparate locations are examined: New York City, NY, USA and Phoenix, AZ, USA. Several variations are examined, including no battery storage, battery storage, and charging of an electric vehicle. The strategy was found to suitably highlight a variety of options that gave the best tradeoff between carbon emissions and cost. Metrics to compare nondominated fronts showed that a variable season charging time for the electric vehicle produced fronts that dominated a fixed season strategy by 6%. This strategy can be easily implemented by customers to avoid choosing improperly sized and priced residential solar systems.
Exploring E-Commerce Big Data and Customer-Perceived Value: An Empirical Study on Chinese Online Customers
Authors: Liu Chunting , Wang Shanshan , Jia Guozhu
Published: October 2020

The purpose of this study is to make good use of the massive amount of online user comment data to explore and analyze the dimensions of customer-perceived value and the importance of each dimension, given the background of China’s huge e-commerce market. We compiled a web crawler program to collect online comment data from online reviews. The crawled data were pre-processed and content analysis were performed. A customer-perceived value dictionary was constructed based on the extraction of frequent terms, literature review, and expert opinions. We re-identified the dimensions of customer-perceived value to include four key dimensions and corresponding subdivisions. Both the rationality and operability of the dimension model of customer-perceived value were validated and applied. Thereafter, the importance of various dimensions and the impacts of customer-perceived value dimensions on customer loyalty were analyzed and discussed. The empirical research results reveal that all four dimensions of customer-perceived value play an important role in customer-perceived value and that the patterns and degrees of the role of each dimension are rather different. Further, only certain parts of the dimensions of customer-perceived value have an impact on customer loyalty, and the degree of the impact differs substantially.
Sustainable Cornelian Cherry Production in Montenegro: Importance of Local Genetic Resources
Authors: Jaćimović Vučeta , Božović Djina , Ercisli Sezai , Bosančić Borut , Necas Tomas
Published: October 2020

Cornelian cherries has been grown Balkan peninsula no apparent disease and pest problems for centuries. The most important pomological and technological properties of cornelian cherry genetic resources (eleven local and introduced varieties and selections) in Gornje Polimlje, Montenegro were studied in four-year periods. Fruit weight, stone weight, and mesocarp/stone ratio shows great variation and varied between 1.89 to 6.16 g, 0.32 to 0.64 g and between 76.66 and 90.59%, respectively. Genotypes significantly differed each other in terms of yield determined as per trunk cross section area (TCSA). For better visualization of the agronomical traits important to the yield, i.e., yield per TCSA and fruit weight data is presented in combination as measured in the years of study. The best promising genotypes are Vladimirskiy, Chisinau yellow, and Krupnoplodni NS, which had consistently higher yield and large fruits for sustainable fruit production. Dry matter, total sugars, reducing sugars, sucrose, total acidity, Ca–pectate, vitamin C, total anthocyanins, total polyphenols, and ash content of cornelian cherry cultivars and selections were found between 19.81–24.46%, 10.94–14.47%, 10.44–13.09%, 0.24–1.23%, 1.92–2.51%, 2.76–4.43%, 41.09–101.27 mg/100 g, 0–157.06 mg/100 g, 183.91–307.9 mg/100 g, and 0.89–1.16%, respectively. The amount of potassium, which predominates in percentage of minerals in the ash, ranged from 2888 to 3574 mg/kg. The extensiveness of the study leads, therefore, to several clear conclusions and recommendations. Consistently, the best balance of biochemical elements in combination with good yield and fruit size measurements is found in selection Krupnoplodi NS. If consider fruit size and yield efficiency are priority, Vladimirskiy, Chisinau yellow, Kosten 3, and Krupnoplodni NS have clear advantage over the other genotypes. The study highlights the importance of local cornelian cherry selections for sustainable cornelian cherry production in Montenegro.
Sustainable Strategic Management Model for Hotel Companies: A Multi-Stakeholder Proposal to “Walk the Talk” toward SDGs
Authors: Rubio-Mozos Ernestina , García-Muiña Fernando E. , Fuentes-Moraleda Laura
Published: October 2020

As we reach the fifth anniversary of the Declaration of the United Nations 2030 Agenda for Sustainable Development, the tourism sector responsible for over 10% of the world’s GDP still does not have an open-source, sustainable management criteria that would enable and empower them to “walk the talk” to contribute to the Sustainable Development Goals (SDGs). The purpose of this paper is to fill the gap in the social sciences and business management literature by providing a theoretical Sustainable Strategic Management Model (SSMM) proposal for the Fourth Sector (4S), Small- and Medium-sized (SMEs) Hotel companies (4S-SM-HCs), which are committed and have the will to contribute firmly to the 2030 Agenda. Based on their corporate purpose and aligned with the SDGs, this article provides a holistic proposal with a multi-stakeholder approach, adding the SDG perspective. Through a qualitative research methodology based on two focus groups in which the main stakeholders and the management team of the 4S-SM-HC under examination took part, a theoretical SSMM is co-defined so that the hotel company can make significant contributions to the five areas of the SDGs. Basing their structure on the internationally recognized Global Sustainable Tourism Council (GSTC) Criteria and co-created through social learning, this SSMM proposes four strategic management axis and develops ten principles of ethical performance (PEP). The main contributions of this article are two: (1) to provide an ecosystemic SSMM proposal to the 4S-SM-HCs to allow them to make significant contributions to the SDGs, and (2) to facilitate a methodological framework with a multi-stakeholder approach and SDG perspective to enable them to contribute to the wellbeing of people, the community and the planet.
Effects of Land Use Change from Natural Forest to Livestock on Soil C, N and P Dynamics along a Rainfall Gradient in Mexico
Authors: Figueroa Daniela , Ortega-Fernández Patricia , Abbruzzini Thalita F. , Rivero-Villlar Anaitzi , Galindo Francisco , Chavez-Vergara Bruno , Etchevers Jorge D. , Campo Julio
Published: October 2020

The effects of converting native forests to livestock systems on soil C, N and P contents across various climatic zones are not well understood for the tropical region. The goal of this study was to test how soil C, N and P dynamics are affected by the land-use change from natural forests to livestock production systems (extensive pasture and intensive silvopastoral systems) across a rainfall gradient of 1611–711 mm per year in the Mexican tropics. A total of 15 soil-based biogeochemical metrics were measured in samples collected during the dry and rainy seasons in livestock systems and mature forests for land-use and intersite comparisons of the nutrient status. Our results show that land-use change from natural forests to livestock production systems had a negative effect on soil C, N and P contents. In general, soil basal respiration and C-acquiring enzyme activities increased under livestock production systems. Additionally, reduction in mean annual rainfall affected moisture-sensitive biogeochemical processes affecting the C, N and P dynamics. Our findings imply that land-use changes alter soil C, N and P dynamics and contents, with potential negative consequences for the sustainability of livestock production systems in the tropical regions of Mexico investigated.
Talent Goes Social: Online Corporate Networking and Business Performance
Authors: Paniagua Jordi , Peris-Ortiz Marta , Korzynski Pawel
Published: October 2020

This study examines the effect of online social talent on business performance. The paper uses data from a selected sample of 296 companies from the S&P 500 list with active corporate profiles on LinkedIn. The empirical design consists of non-linear techniques to test the hypothesis that financial performance (i.e., revenue) and online social talent (i.e., employee online profile and skills) have a positive and non-linear relationship. The findings show that internal online social talent measured by employees’ online profiles, and their skills are positively associated with companies’ financial performance. The study provides insights into talent management in the digital age and elucidates the role of online corporate social networking in business performance.
Cross-Sectoral Inter-Country Linkages under the Belt and Road Initiative: Chinese ICT Services Value Added Inflows to Manufacturing Exports in the New Eurasian Land Bridge Economies
Authors: Cieślik Ewa
Published: October 2020

The article presents the New Eurasian Land Bridge (NELB) of the Belt and Road Initiative (BRI) and China, with a special focus on the role of these countries in global value chains (GVCs), to investigate the intensification of the Chinese ICT services’ value-added inflows to the NELB countries’ manufacturing, especially to transport equipment and computers, electronic and electrical equipment. The central question is how strong the linkages between the Chinese ICT services and the selected NELB countries’ manufacturing are. We hypothesized that: (1) As a result of the introduction of the BRI, the role of the Chinese ICT services’ value-added diverted to the NELB countries’ manufacturing gross exports increased; (2) The growth rate of the Chinese ICT services’ value-added directed to the NELB manufacturing gross exports exceeds the growth rate of the non-services’ value-added diverted to their manufacturing; (3) The NELB economies became more dependent on the Chinese ICT services’ value-added embodied in their manufacturing gross exports.
Burrows–Wheeler Transform Based Lossless Text Compression Using Keys and Huffman Coding
Authors: Rahman Md. Atiqur , Hamada Mohamed
Published: October 2020

Text compression is one of the most significant research fields, and various algorithms for text compression have already been developed. This is a significant issue, as the use of internet bandwidth is considerably increasing. This article proposes a Burrows–Wheeler transform and pattern matching-based lossless text compression algorithm that uses Huffman coding in order to achieve an excellent compression ratio. In this article, we introduce an algorithm with two keys that are used in order to reduce more frequently repeated characters after the Burrows–Wheeler transform. We then find patterns of a certain length from the reduced text and apply Huffman encoding. We compare our proposed technique with state-of-the-art text compression algorithms. Finally, we conclude that the proposed technique demonstrates a gain in compression ratio when compared to other compression techniques. A small problem with our proposed method is that it does not work very well for symmetric communications like Brotli.
Axle Temperature Monitoring and Neural Network Prediction Analysis for High-Speed Train under Operation
Authors: Hao Wei , Liu Feng
Published: October 2020

Predicting the axle temperature states of the high-speed train under operation in advance and evaluating working states of axle bearings is important for improving the safety of train operation and reducing accident risks. The method of monitoring the axle temperature of a train under operation, combined with the neural network prediction method, was applied. A total of 36 sensors were arranged at key positions such as the axle bearings of the train gearbox and the driving end of the traction motor. The positions of the sensors were symmetrical. Axle temperature measurements over 11 days with more than 38,000 km were obtained. The law of the change of the axle temperature in each section was obtained in different environments. The resultant data from the previous 10 days were used to train the neural network model, and a total of 800 samples were randomly selected from eight typical locations for the prediction of axle temperature over the following 3 min. In addition, the results predicted by the neural network method and the GM (1,1) method were compared. The results show that the predicted temperature of the trained neural network model is in good agreement with the experimental temperature, with higher precision than that of the GM (1,1) method, indicating that the proposed method is sufficiently accurate and can be a reliable tool for predicting axle temperature.
POISE: Efficient Cross-Domain Chinese Named Entity Recognization via Transfer Learning
Authors: Sheng Jiabao , Wumaier Aishan , Li Zhe
Published: October 2020

To improve the performance of deep learning methods in case of a lack of labeled data for entity annotation in entity recognition tasks, this study proposes transfer learning schemes that combine the character to be the word to convert low-resource data symmetry into high-resource data. We combine character embedding, word embedding, and the embedding of the label features using high- and low-resource data based on the BiLSTM-CRF model, and perform the feature-transfer and parameter-sharing tasks in two domains of the BiLSTM network to annotate with zero resources. Before transfer learning, we must first calculate the label similarity between two different domains and select the label features with large similarity for feature transfer mapping. All training parameters of the source domain in the model are shared during the BiLSTM network processing and CRF layer. In addition, we also use the method of combining characters and words to reduce the problem of word segmentation across domains and reduce the error rate in label mapping. The results of experiments show that in terms of the overall F1 score, the proposed model without supervision was superior by 9.76 percentage points to the general parametric shared transfer learning method, and by 9.08 and 12.38 percentage points, respectively, to two recent high–low resource learning methods. The proposed scheme improves performance in terms of transfer learning between the high- and low-resource data and can identify the predicted data in the target domain.
Internet of Things and Its Applications: A Comprehensive Survey
Authors: Hassan Rosilah , Qamar Faizan , Hasan Mohammad Kamrul , Aman Azana Hafizah Mohd , Ahmed Amjed Sid
Published: October 2020

With the evolution of the fifth-generation (5G) wireless network, the Internet of Things (IoT) has become a revolutionary technique that enables a diverse number of features and applications. It can able a diverse amount of devices to be connected in order to create a single communication architecture. As it has significantly expanded in recent years, it is fundamental to study this trending technology in detail and take a close look at its applications in the different domains. It represents an enabler of new communication possibilities between people and things. The main asset of this concept is its significant influence through the creation of a new world dimension. The key features required for employing a large-scale IoT are low-cost sensors, high-speed and error-tolerant data communications, smart computations, and numerous applications. This research work is presented in four main sections, including a general overview of IoT technology, a summary of previous correlated surveys, a review regarding the main IoT applications, and a section on the challenges of IoT. The purpose of this study is to fully cover the applications of IoT, including healthcare, environmental, commercial, industrial, smart cities, and infrastructural applications. This work explains the concept of IoT and defines and summarizes its main technologies and uses, offering a next-generation protocol as a solution to the challenges. IoT challenges were investigated to enhance research and development in the fields. The contribution and weaknesses of each research work cited are covered, highlighting eventual possible research questions and open matters for IoT applications to ensure a full analysis coverage of the discussed papers.
A Fast Non-Linear Symmetry Approach for Guaranteed Consensus in Network of Multi-Agent Systems
Authors: Abdulghafor Rawad , Almotairi Sultan
Published: October 2020

There has been tremendous work on multi-agent systems (MAS) in recent years. MAS consist of multiple autonomous agents that interact with each order to solve a complex problem. Several applications of MAS can be found in computer networks, smart grids, and the modeling of complex systems. Despite numerous benefits, a significant challenge for MAS is achieving a consensus among agents in a shared target task, which is difficult without applying certain mathematical equations. Non-linear models offer better possibility of resolving consensus for MAS; however, existing non-linear models are considerably complicated and present no guarantees for achieving consensus. This paper proposes a non-linear mathematical model of semi symmetry quadratic operator (SSQO) in order to resolve the issue of consensus in networks of MAS. The model is based on stochastic quadratic operator theory, with added new notations. An important feature for the proposed model is low complexity, fast consensus, and a guaranteed capability to reach a consensus. We present an evaluation of the proposed SSQO model and comparison with other existing models. We demonstrate that an average consensus can be achieved with our model in addition to the emulation effects for the MAS consensus.
Maritime Autonomous Surface Ship’s Path Approximation Using Bézier Curves
Authors: Miller Anna , Walczak Szymon
Published: October 2020

This work is devoted to the second order rational Bézier curve coefficients estimation. We present the methodology of unique coefficients for each type of ship computation. In the presented formulas of ship’s length, a draft and angular path combined with a drift path are used. This approach leads to the simplest and most accurate Maritime Autonomous Surface Ships (MASS) path modeling. Three rational curve control points are waypoints (WPT). Using WPTs as curve control points allows integrating a trajectory intuitive for the navigator with a path predicting model used as a reference in the control system. Research was done based on real-time data originating from the MASS autonomous trajectory tracking system. The presented mathematical modeling tool may be treated as the best way of future trajectory prediction due to low computation power required.
Relationship between the Shear Strength and Microscopic Pore Parameters of Saline Soil with Different Freeze-Thaw Cycles and Salinities
Authors: Wang Jiaqi , Wang Qing , Lin Sen , Han Yan , Cheng Shukai , Wang Ning
Published: October 2020

Saline soil is a widely distributed special soil with poor engineering properties. In seasonally frozen regions, the poor properties of saline soil will cause many types of engineering damage such as road boiling, melt sinking, and subgrade instability. These engineering failures are closely related to the shear strength of saline soil. However, there are relatively few studies on saline soil in cold regions. The strength of the soil is always determined by its microstructure; therefore, the study aims to investigate the relationship between the shear strength and microscopic pore structure of saline soil with different freeze–thaw cycles and salinities. The shear strength characteristics of saline soil with different salinities subjected to different freeze–thaw cycles were obtained by triaxial tests. In addition, the microstructure of the soil samples was investigated by scanning electron microscopy (SEM) tests, and the microscopic pore parameters of the soil samples, including porosity (N), average pore diameter (D¯), average shape coefficient (K), surface fluctuation fractal dimension (F), and orienting probability entropy (Hm), were obtained by image processing software quantitatively. Based on the experimental results, the influence of freeze–thaw cycles and salinity on the shear strength characteristics and microstructure of the soil samples were analyzed. Besides that, in order to effectively eliminate the collinearity between independent variables and obtain a stable and reasonable regression model, principal component regression (PCR) analysis was adopted to establish the relationship between the microscopic pore parameters and the failure strength of the soil samples. The fitting results demonstrated that the failure strength of saline soil is mainly related to the size and direction of the pores in the soil, and it has little correlation with pore shape. The failure strength of the soil was negatively correlated with the average pore diameter (D¯) and porosity (N), and it was positively correlated with the orienting probability entropy of the pores (Hm). This study may provide a quantitative basis for explaining the variation mechanism of the mechanical properties of saline soil from a microscopic perspective and provide references for the symmetry between the changes of the macroscopic properties and microscopic pore structure of the saline soil in cold regions.
Nordhaus–Gaddum-Type Results for the Steiner Gutman Index of Graphs
Authors: Wang Zhao , Mao Yaping , Das Kinkar Chandra , Shang Yilun
Published: October 2020

Building upon the notion of the Gutman index SGut(G), Mao and Das recently introduced the Steiner Gutman index by incorporating Steiner distance for a connected graph G. The Steiner Gutman k-index SGutk(G) of G is defined by SGutk(G)=∑S⊆V(G),|S|=k∏v∈SdegG(v)dG(S), in which dG(S) is the Steiner distance of S and degG(v) is the degree of v in G. In this paper, we derive new sharp upper and lower bounds on SGutk, and then investigate the Nordhaus-Gaddum-type results for the parameter SGutk. We obtain sharp upper and lower bounds of SGutk(G)+SGutk(G¯) and SGutk(G)·SGutk(G¯) for a connected graph G of order n, m edges, maximum degree Δ and minimum degree δ.
A Novel Framework Using Neutrosophy for Integrated Speech and Text Sentiment Analysis
Authors: Mishra Kritika , Kandasamy Ilanthenral , Kandasamy W. B. Vasantha , Smarandache Florentin
Published: October 2020

With increasing data on the Internet, it is becoming difficult to analyze every bit and make sure it can be used efficiently for all the businesses. One useful technique using Natural Language Processing (NLP) is sentiment analysis. Various algorithms can be used to classify textual data based on various scales ranging from just positive-negative, positive-neutral-negative to a wide spectrum of emotions. While a lot of work has been done on text, only a lesser amount of research has been done on audio datasets. An audio file contains more features that can be extracted from its amplitude and frequency than a plain text file. The neutrosophic set is symmetric in nature, and similarly refined neutrosophic set that has the refined indeterminacies I1 and I2 in the middle between the extremes Truth T and False F. Neutrosophy which deals with the concept of indeterminacy is another not so explored topic in NLP. Though neutrosophy has been used in sentiment analysis of textual data, it has not been used in speech sentiment analysis. We have proposed a novel framework that performs sentiment analysis on audio files by calculating their Single-Valued Neutrosophic Sets (SVNS) and clustering them into positive-neutral-negative and combines these results with those obtained by performing sentiment analysis on the text files of those audio.
Oxidative Damage of Mussels Living in Seawater Enriched with Trace Metals, from the Viewpoint of Proteins Expression and Modification
Authors: Kournoutou Georgia G. , Giannopoulou Panagiota C. , Sazakli Eleni , Leotsinidis Michalis , Kalpaxis Dimitrios L. , Dinos George P.
Published: October 2020

The impact of metals bioaccumulation in marine organisms is a subject of intense investigation. This study was designed to determine the association between oxidative stress induced by seawater enriched with trace metals and protein synthesis using as a model the mussels Mytilus galloprovincialis. Mussels were exposed to 40 μg/L Cu, 30 μg/L Hg, or 100 μg/L Cd for 5 and 15 days, and the pollution effect was evaluated by measuring established oxidative biomarkers. The results showed damage on the protein synthesis machine integrity and specifically on translation factors and ribosomal proteins expression and modifications. The exposure of mussels to all metals caused oxidative damage that was milder in the cases of Cu and Hg and more pronounced for Cd. However, after prolonged exposure of mussels to Cd (15 days), the effects receded. These changes that perturb protein biosynthesis can serve as a great tool for elucidating the mechanisms of toxicity and could be integrated in biomonitoring programs.
Water Thermodynamics of Peptide Toxin Binding Sites on Ion Channels
Authors: Shah Binita , Sindhikara Dan , Borrelli Ken , Leffler Abba E.
Published: October 2020

Peptide toxins isolated from venomous creatures, long prized as research tools due to their innate potency for ion channels, are emerging as drugs as well. However, it remains challenging to understand why peptide toxins bind with high potency to ion channels, to identify residues that are key for activity, and to improve their affinities via mutagenesis. We use WaterMap, a molecular dynamics simulation-based method, to gain computational insight into these three questions by calculating the locations and thermodynamic properties of water molecules in the peptide toxin binding sites of five ion channels. These include an acid-sensing ion channel, voltage-gated potassium channel, sodium channel in activated and deactivated states, transient-receptor potential channel, and a nicotinic receptor whose structures were recently determined by crystallography and cryo-electron microscopy (cryo-EM). All channels had water sites in the peptide toxin binding site, and an average of 75% of these sites were stable (low-energy), and 25% were unstable (medium or high energy). For the sodium channel, more unstable water sites were present in the deactivated state structure than the activated. Additionally, for each channel, unstable water sites coincided with the positions of peptide toxin residues that previous mutagenesis experiments had shown were important for activity. Finally, for the sodium channel in the deactivated state, unstable water sites were present in the peptide toxin binding pocket but did not overlap with the peptide toxin, suggesting that future experimental efforts could focus on targeting these sites to optimize potency.
Prevalent Human Gut Bacteria Hydrolyse and Metabolise Important Food-Derived Mycotoxins and Masked Mycotoxins
Authors: Daud Noshin , Currie Valerie , Duncan Gary , Farquharson Freda , Yoshinari Tomoya , Louis Petra , Gratz Silvia W.
Published: October 2020

Mycotoxins are important food contaminants that commonly co-occur with modified mycotoxins such as mycotoxin-glucosides in contaminated cereal grains. These masked mycotoxins are less toxic, but their breakdown and release of unconjugated mycotoxins has been shown by mixed gut microbiota of humans and animals. The role of different bacteria in hydrolysing mycotoxin-glucosides is unknown, and this study therefore investigated fourteen strains of human gut bacteria for their ability to break down masked mycotoxins. Individual bacterial strains were incubated anaerobically with masked mycotoxins (deoxynivalenol-3-β-glucoside, DON-Glc; nivalenol-3-β-glucoside, NIV-Glc; HT-2-β-glucoside, HT-2-Glc; diacetoxyscirpenol-α-glucoside, DAS-Glc), or unconjugated mycotoxins (DON, NIV, HT-2, T-2, and DAS) for up to 48 h. Bacterial growth, hydrolysis of mycotoxin-glucosides and further metabolism of mycotoxins were assessed. We found no impact of any mycotoxin on bacterial growth. We have demonstrated that Butyrivibrio fibrisolvens, Roseburia intestinalis and Eubacterium rectale hydrolyse DON-Glc, HT-2 Glc, and NIV-Glc efficiently and have confirmed this activity in Bifidobacterium adolescentis and Lactiplantibacillus plantarum (DON-Glc only). Prevotella copri and B. fibrisolvens efficiently de-acetylated T-2 and DAS, but none of the bacteria were capable of de-epoxydation or hydrolysis of α-glucosides. In summary we have identified key bacteria involved in hydrolysing mycotoxin-glucosides and de-acetylating type A trichothecenes in the human gut.
Gradual and Discrete Ontogenetic Shifts in Rattlesnake Venom Composition and Assessment of Hormonal and Ecological Correlates
Authors: Schonour Richard B. , Huff Emma M. , Holding Matthew L. , Claunch Natalie M. , Ellsworth Schyler A. , Hogan Michael P. , Wray Kenneth , McGivern James , Margres Mark J. , Colston Timothy J. , Rokyta Darin R.
Published: October 2020

Ontogenetic shifts in venom occur in many snakes but establishing their nature as gradual or discrete processes required additional study. We profiled shifts in venom expression from the neonate to adult sizes of two rattlesnake species, the eastern diamondback and the timber rattlesnake. We used serial sampling and venom chromatographic profiling to test if ontogenetic change occurs gradually or discretely. We found evidence for gradual shifts in overall venom composition in six of eight snakes, which sometimes spanned more than two years. Most chromatographic peaks shift gradually, but one quarter shift in a discrete fashion. Analysis of published diet data showed gradual shifts in overall diet composition across the range of body sizes attained by our eight study animals, while the shifts in abundance of different prey classes varied in form from gradual to discrete. Testosterone concentrations were correlated with the change in venom protein composition, but the relationship is not strong enough to suggest causation. Venom research employing simple juvenile versus adult size thresholds may be failing to account for continuous variation in venom composition lifespan. Our results imply that venom shifts represent adaptive matches to dietary shifts and highlight venom for studies of alternative gene regulatory mechanisms.