bluuebunny/crossref_metadata_2025 huggingface dataset:
Proportional Trends of Continuous Rainfall in Indian Summer Monsoon
Authors: Kumar Vinay , Sunilkumar K. , Sinha Tushar
Published: January 2021

A comprehensive study on the Indian summer monsoonal rainfall (ISMR) is performed in the light of decadal changes in the continuous rainfall events and the number of rainy days using 68 years (1951–2018) of gridded rain gauge data. Non-parametric Mann–Kendall’s test is applied on total rainfall amount, the number of rainy days, number of continuous rainfall events, and rainfall magnitude to find trends over different climatic zones of India for the two periods, 1951–1984 and 1985–2018. Our results found a decreasing trend for more than 4-days of continuous rainfall events during the recent 34 years (1985–2018) compared to 1951–1984. The rate of increase/decrease in extreme/continuous rainfall events does not follow a similar trend in number of continuous rainfall events and magnitude. Moreover, the rainfall is shifted towards a lesser number of continuous rainfall days with higher magnitudes during 1985–2018. During the crop’s sow season (i.e., the first 45 days from the onset date of Indian monsoon), the total number of rainy days decreased by a half day during the last 34 years. Over the Central and North East regions of India, the number of rainfall days decreased by ~0.1 days/yr and ~0.3 days/yr, respectively, during 1985–2018. Overall, the decreasing trends in continuous rainfall days may escalate water scarcity and lead to lower soil moisture over rain-fed irrigated land. Additionally, an upsurge in heavy rainfall episodes will lead to an unexpected floods. On a daily scale, rainfall correlates with soil moisture and evaporation up to 0.87 over various land cover and land use regions of India. Continuous light-moderate rainfall seems to be a controlling factor for replenishing soil moisture in upper levels. A change in rainfall characteristics may force the monsoon-fed rice cultivation period to adopt changing rainfall patterns.
Monitoring of Power Towers’ Movement Using Persistent Scatterer SAR Interferometry in South West of Tehran
Authors: Tarighat Fereshteh , Foroughnia Fatemeh , Perissin Daniele
Published: January 2021

The Tehran basin has been increasingly affected by subsidence during the last few decades due to groundwater withdrawal. Hence, the study of the strength of the power towers (PTs) of transmission lines, as vital structures, is an important subject. In this paper, the persistent scatterer interferometry (PSI) method was applied on data stacks from two satellites (i.e., X-band COSMO-SkyMed (CSK) and C-band Sentinel-1A (S-1A)) obtained between 2014 and 2016 to investigate the deformation and the exact amount of displacement in each PT of the area of interest. Based on the results, during the same time interval (between October 2014 and February 2016), the vertical velocities calculated using CSK and S-1A were about −86 and −79 mm/y, respectively. Although the CSK data analysis resulted in a better displacement interpretation of PTs, due to its high resolution and shorter wavelength, the S-1 data analysis also demonstrated sufficient persistent scatterer (PS) points. The research proves that most of the PTs along a transmission line are affected by high land subsidence, which puts them in a serious jeopardy. They must be constantly monitored to ensure their safety and accurate operation. The results are in complete agreement with information of the existing global positioning system (GPS) station in our study area and also the observations of two piezometric wells with declining trends in the groundwater reservoir, which has the greatest effect on the subsidence rate in this area. The analysis revealed that the strength of PTs is at a high risk.
Detection of a Potato Disease (Early Blight) Using Artificial Intelligence
Authors: Afzaal Hassan , Farooque Aitazaz A. , Schumann Arnold W. , Hussain Nazar , McKenzie-Gopsill Andrew , Esau Travis , Abbas Farhat , Acharya Bishnu
Published: January 2021

This study evaluated the potential of using machine vision in combination with deep learning (DL) to identify the early blight disease in real-time for potato production systems. Four fields were selected to collect images (n = 5199) of healthy and diseased potato plants under variable lights and shadow effects. A database was constructed using DL to identify the disease infestation at different stages throughout the growing season. Three convolutional neural networks (CNNs), namely GoogleNet, VGGNet, and EfficientNet, were trained using the PyTorch framework. The disease images were classified into three classes (2-class, 4-class, and 6-class) for accurate disease identification at different growth stages. Results of 2-class CNNs for disease identification revealed the significantly better performance of EfficientNet and VGGNet when compared with the GoogleNet (FScore range: 0.84–0.98). Results of 4-Class CNNs indicated better performance of EfficientNet when compared with other CNNs (FScore range: 0.79–0.94). Results of 6-class CNNs showed similar results as 4-class, with EfficientNet performing the best. GoogleNet, VGGNet, and EfficientNet inference time values ranged from 6.8–8.3, 2.1–2.5, 5.95–6.53 frames per second, respectively, on a Dell Latitude 5580 using graphical processing unit (GPU) mode. Overall, the CNNs and DL frameworks used in this study accurately classified the early blight disease at different stages. Site-specific application of fungicides by accurately identifying the early blight infected plants has a strong potential to reduce agrochemicals use, improve the profitability of potato growers, and lower environmental risks (runoff of fungicides to water bodies).
A Practical Satellite-Derived Vegetation Drought Index for Arid and Semi-Arid Grassland Drought Monitoring
Authors: Chang Sheng , Chen Hong , Wu Bingfang , Nasanbat Elbegjargal , Yan Nana , Davdai Bulgan
Published: January 2021

In semi-arid pasture areas, drought may directly influence livestock production, cause economic losses, and accelerate the processes of desertification along with destructive human activities (i.e., overgrazing). The aim of this article is to analyze the disadvantages of several drought indices derived from remote sensing data and develop a new vegetation drought index (VDI) for monitoring of grassland drought with high temporal frequency (dekad) and fine spatial resolution (1 km). The site-based soil moisture data from the field campaign in 2014 and the fenced biomass values at nine sites from 2000 to 2015 were adopted for validation. The results indicate that the proposed VDI would better reflect the extent, severity, and changes of drought compared with single drought indices or the vegetation health index (VHI); specifically, the VDI is more closely related to site-based soil moisture, with R human increasing to approximately 0.07 compared with the VHI; and with normalized fenced biomass (NFB) values, with average R human increasing to approximately 0.11 compared with the VHI. However, the correlations between VHI and VDI with NFB values are relatively lower in desert steppe regions. Furthermore, regional drought-affected data (RDA) are used to ensure spatial consistency of the evaluation; the VDI map is in good agreement with the RDA map based on field measurements. The presented VDI shows reliable and stable drought monitoring ability, which will play an important role in the future drought monitoring of inland grassland.
A New Machine Learning Algorithm for Numerical Prediction of Near-Earth Environment Sensors along the Inland of East Antarctica
Authors: Wang Yuchen , Dou Yinke , Yang Wangxiao , Guo Jingxue , Chang Xiaomin , Ding Minghu , Tang Xueyuan
Published: January 2021

Accurate short-term small-area meteorological forecasts are essential to ensure the safety of operations and equipment operations in the Antarctic interior. This study proposes a deep learning-based multi-input neural network model to address this problem. The newly proposed model is predicted by combining a stacked autoencoder and a long- and short-term memory network. The self-stacking autoencoder maximises the features and removes redundancy from the target weather station’s sensor data and extracts temporal features from the sensor data using a long- and short-term memory network. The proposed new model evaluates the prediction performance and generalisation capability at four observation sites at different East Antarctic latitudes (including the Antarctic maximum and the coastal region). The performance of five deep learning networks is compared through five evaluation metrics, and the optimal form of input combination is discussed. The results show that the prediction capability of the model outperforms the other models. It provides a new method for short-term meteorological prediction in a small inland Antarctic region.
Design and Experimental Evaluation of the Proactive Transmission of Replicated Frames Mechanism over Time-Sensitive Networking
Authors: Álvarez Inés , Furió Ignasi , Proenza Julián , Barranco Manuel
Published: January 2021

In recent years the Time-Sensitive Networking (TSN) Task Group (TG) has been working on proposing a series of standards to provide Ethernet with hard real-time guarantees, online management of the traffic and fault tolerance mechanisms. In this way the TG expects to create the network technology of future novel applications with real-time and reliability requirements. TSN proposes using spatial redundancy to increase the reliability of Ethernet networks, but using spatial redundancy to tolerate temporary faults is not a cost-effective solution. For this reason, we propose to use time redundancy to tolerate temporary faults in the links of TSN-based networks. Specifically, we have proposed the Proactive Transmission of Replicated Frames (PTRF) mechanism, which consists in transmitting several copies of each frame in a preventive manner. In this article we present for the first time a detailed description of the mechanism, with the three different approaches we have designed. We also present the implementation of PTRF in a real TSN prototype. Furthermore, we carry out a qualitative comparison of the different approaches of the mechanism and we experimentally evaluate the approaches of the mechanism in a quantitative manner from three perspectives: the end-to-end delay, the jitter and the bandwidth consumption.
An Efficient Plaintext-Related Chaotic Image Encryption Scheme Based on Compressive Sensing
Authors: Li Zhen , Peng Changgen , Tan Weijie , Li Liangrong
Published: January 2021

With the development of mobile communication network, especially 5G today and 6G in the future, the security and privacy of digital images are important in network applications. Meanwhile, high resolution images will take up a lot of bandwidth and storage space in the cloud applications. Facing the demands, an efficient and secure plaintext-related chaotic image encryption scheme is proposed based on compressive sensing for achieving the compression and encryption simultaneously. In the proposed scheme, the internal keys for controlling the whole process of compression and encryption is first generated by plain image and initial key. Subsequently, discrete wavelets transform is used in order to convert the plain image to the coefficient matrix. After that, the permutation processing, which is controlled by the two-dimensional Sine improved Logistic iterative chaotic map (2D-SLIM), was done on the coefficient matrix in order to make the matrix energy dispersive. Furthermore, a plaintext related compressive sensing has been done utilizing a measurement matrix generated by 2D-SLIM. In order to make the cipher image lower correlation and distribute uniform, measurement results quantified the 0∼255 and the permutation and diffusion operation is done under the controlling by two-dimensional Logistic-Sine-coupling map (2D-LSCM). Finally, some common compression and security performance analysis methods are used to test our scheme. The test and comparison results shown in our proposed scheme have both excellent security and compression performance when compared with other recent works, thus ensuring the digital image application in the network.
Arduino-Based Myoelectric Control: Towards Longitudinal Study of Prosthesis Use
Authors: Wu Hancong , Dyson Matthew , Nazarpour Kianoush
Published: January 2021

Understanding how upper-limb prostheses are used in daily life helps to improve the design and robustness of prosthesis control algorithms and prosthetic components. However, only a very small fraction of published research includes prosthesis use in community settings. The cost, limited battery life, and poor generalisation may be the main reasons limiting the implementation of home-based applications. In this work, we introduce the design of a cost-effective Arduino-based myoelectric control system with wearable electromyogram (EMG) sensors. The design considerations focused on home studies, so the robustness, user-friendly control adjustments, and user supports were the main concerns. Three control algorithms, namely, direct control, abstract control, and linear discriminant analysis (LDA) classification, were implemented in the system. In this paper, we will share our design principles and report the robustness of the system in continuous operation in the laboratory. In addition, we will show a first real-time implementation of the abstract decoder for prosthesis control with an able-bodied participant.
Water Content of Polyelectrolyte Multilayer Films Measured by Quartz Crystal Microbalance and Deuterium Oxide Exchange
Authors: Kittle Joshua , Levin Jacob , Levin Nestor
Published: January 2021

Water content of natural and synthetic, thin, polymer films is of considerable interest to a variety of fields because it governs properties such as ion conductivity, rigidity, porosity, and mechanical strength. Measuring thin film water content typically requires either complicated and expensive instrumentation or use of multiple instrumental techniques. However, because a quartz crystal microbalance (QCM) is sensitive to changes in mass and viscosity, deuterated solvent exchange has emerged as a simple, single-instrument, in situ method to quantify thin film water content. Relatively few studies, though, have employed this technique to measure water content of polyelectrolyte multilayers formed by layer-by-layer (LbL) assembly. In this work, poly (allyl amine) (PAH) and poly (styrene sulfonate) (PSS) films of up to nine layers were formed and the water content for each layer was measured via QCM with deuterium oxide exchange. The well-characterized nature of PAH/PSS films facilitated comparisons of the technique used in this work to other instrumental methods. Water content results showed good agreement with the literature and good precision for hydrated films thicker than 20 nm. Collectively, this work highlights the utility, repeatability, and limitations of this deuterated exchange technique in measuring the solvent content of thin films.
Artificial-Intelligence-Enhanced Mobile System for Cardiovascular Health Management
Authors: Fu Zhaoji , Hong Shenda , Zhang Rui , Du Shaofu
Published: January 2021

The number of patients with cardiovascular diseases is rapidly increasing in the world. The workload of existing clinicians is consequently increasing. However, the number of cardiovascular clinicians is declining. In this paper, we aim to design a mobile and automatic system to improve the abilities of patients’ cardiovascular health management while also reducing clinicians’ workload. Our system includes both hardware and cloud software devices based on recent advances in Internet of Things (IoT) and Artificial Intelligence (AI) technologies. A small hardware device was designed to collect high-quality Electrocardiogram (ECG) data from the human body. A novel deep-learning-based cloud service was developed and deployed to achieve automatic and accurate cardiovascular disease detection. Twenty types of diagnostic items including sinus rhythm, tachyarrhythmia, and bradyarrhythmia are supported. Experimental results show the effectiveness of our system. Our hardware device can guarantee high-quality ECG data by removing high-/low-frequency distortion and reverse lead detection with 0.9011 Area Under the Receiver Operating Characteristic Curve (ROC–AUC) score. Our deep-learning-based cloud service supports 20 types of diagnostic items, 17 of them have more than 0.98 ROC–AUC score. For a real world application, the system has been used by around 20,000 users in twenty provinces throughout China. As a consequence, using this service, we could achieve both active and passive health management through a lightweight mobile application on the WeChat Mini Program platform. We believe that it can have a broader impact on cardiovascular health management in the world.
Distributed Fibre Optic Sensor-Based Continuous Strain Measurement along Semicircular Paths Using Strain Transformation Approach
Authors: Nagulapally Prashanth , Shamsuddoha Md , Rajan Ginu , Djukic Luke , B. Prusty Gangadhara
Published: January 2021

Distributed fibre optic sensors (DFOS) are popular for structural health monitoring applications in large engineering infrastructure because of their ability to provide spatial strain measurements continuously along their lengths. Curved paths, particularly semicircular paths, are quite common for optical fibre placement in large structures in addition to straight paths. Optical fibre sensors embedded in a curved path configuration typically measure a component of strain, which often cannot be validated using traditional approaches. Thus, for most applications, strain measured along curved paths is ignored as there is no proper validation tool to ensure the accuracy of the measured strains. To overcome this, an analytical strain transformation equation has been developed and is presented here. This equation transforms the horizontal and vertical strain components obtained along a curved semicircular path into a strain component, which acts tangentially as it travels along the curved fibre path. This approach is validated numerically and experimentally for a DFOS installed on a steel specimen with straight and curved paths. Under tensile and flexural loading scenarios, the horizontal and vertical strain components were obtained numerically using finite element analysis and experimentally using strain rosettes and then, substituted into the proposed strain transformation equation for deriving the transformed strain values. Subsequently, the derived strain values obtained from the proposed transformation equation were validated by comparing them with the experimentally measured DFOS strains in the curved region. Additionally, this study has also shown that a localised damage to the DFOS coating will not impact the functionality of the sensor at the remaining locations along its length. In summary, this paper presents a valid strain transformation equation, which can be used for transforming the numerical simulation results into the DFOS measurements along a semicircular path. This would allow for a larger scope of spatial strains measurements, which would otherwise be ignored in practice.
Have Sustained Acidic Deposition Decreases Led to Increased Calcium Availability in Recovering Watersheds of the Adirondack Region of New York, USA?
Authors: Lawrence Gregory , Siemion Jason , Antidormi Michael , Bonville Donald , McHale Michael
Published: January 2021

Soil calcium depletion has been strongly linked to acidic deposition in eastern North America and recent studies have begun to document the recovery of soils in response to large decreases in acidic deposition. However, increased calcium availability has not yet been seen in the B horizon, where calcium depletion has been most acute, but mineral weathering is critically important for resupplying ecosystem calcium. This study provides new data in seven watersheds in the Adirondack region (New York, USA), where acidic deposition impacts on soils and surface waters have been substantial and recovery remains slow. Initial sampling in 1997–1998 and 2003–2004 was repeated in 2009–2010, 2014, 2016 and 2017. Exchangeable calcium concentrations increased by an average of 43% in the Oe horizon of three watersheds where this horizon was sampled (10.7–15.3 cmolc kg−1). Changes in calcium were not seen in the individual watersheds of the Oa and B horizons, but as a group, a significant increase in calcium was measured in the upper B horizon. Liming of a calcium-depleted watershed also tripled calcium concentration in the upper B horizon in 5 years. However, stream calcium in unlimed watersheds decreased over the study period. Small increases in B-horizon calcium may be underway.
A Life Cycle Engineering Perspective on Biocomposites as a Solution for a Sustainable Recovery
Authors: Fitzgerald Amy , Proud Will , Kandemir Ali , Murphy Richard J. , Jesson David A. , Trask Richard S. , Hamerton Ian , Longana Marco L.
Published: January 2021

Composite materials, such as carbon fibre reinforced epoxies, provide more efficient structures than conventional materials through light-weighting, but the associated high energy demand during production can be extremely detrimental to the environment. Biocomposites are an emerging material class with the potential to reduce a product’s through-life environmental impact relative to wholly synthetic composites. As with most materials, there are challenges and opportunities with the adoption of biocomposites at the each stage of the life cycle. Life Cycle Engineering is a readily available tool enabling the qualification of a product’s performance, and environmental and financial impact, which can be incorporated in the conceptual development phase. Designers and engineers are beginning to actively include the environment in their workflow, allowing them to play a significant role in future sustainability strategies. This review will introduce Life Cycle Engineering and outline how the concept can offer support in the Design for the Environment, followed by a discussion of the advantages and disadvantages of biocomposites throughout their life cycle.
From Drive-By-Wire to Autonomous Vehicle: Urban Freight Vehicle Perspectives
Authors: Masood Khayyam , Zoppi Matteo , Fremont Vincent , Molfino Rezia M.
Published: January 2021

Freight Urban RoBOTic vehicle (FURBOT) is a complete drive-by-wire vehicle expected to perform autonomously in an urban setting. This upgrading has raised issues that need to be resolved/addressed for the vehicle to achieve a higher level of autonomy. This research addresses two of these main issues. The First is the legal framework/licensing issue necessary to be addressed for the vehicle to be insured and legally drive on public roads. The second is the changes and upgrading the vehicle must go through to become a complete autonomous freight handling vehicle. The outcome of this research led to the decision for correct categorization of the vehicle for resolving its licensing issue and its legal status on the European roads by understanding the limitations of the vehicle, which includes vehicle current state and its structural properties. An additional contribution of this research is identifying the software and hardware changes the vehicle has to go through to be fully autonomous. This includes identification of correct sensors and their placement and quantities. In addition, in-depth study for software identification for the vehicle is provided resulting in favorable choice for an off-the-shelf software. Additionally, foreseeable issues, expectations from the vehicle and requirements (considering its demonstration as an autonomous vehicle) that need to be fulfilled are also highlighted. For demonstration site, use cases and site dynamics are also studied for achieving autonomy. Fulfillment of these requirements is necessary for the vehicle to demonstrate autonomous navigation and freight handling for SHOW (SHared automation Operating models for Worldwide adoption) H2020 project for delivering freight in an urban setting.
A Step-by-Step Process towards an Evolutionary Policy Encouraging the Adoption of Sustainable Business Models
Authors: Paletta Angelo , Foschi Eleonora , Alimehmeti Genc , Bonoli Alessandra
Published: January 2021

The increasing awareness on environmental issues and their implications for society and economy, has led policymakers to rethink the legislative and financial measures supporting companies to innovate their business. As a result, companies are encouraged to integrate corporate sustainability (CS) into their value creation. Different from the past approaches, the current policy making process has been inspired by a multi-value creation system, aimed to deeply analyze the present situation, and identify the bottlenecks to design further steps to be taken. In this context, regional authorities cover a pivotal role in financing the pre-competitive phase of innovative and sustainable business models (SBMs). A survey was launched in the Emilia Romagna Region (ERR), analyzing the main factors contributing to maximizing CS. This paper investigates supply chain, welfare, environmental management as well as planning, control and communication strategy together with ecological footprints such as materials, energy, water, plastics, and waste ecological footprints. It gives a twofold contribution: first, it sets the stage for the construction of a theoretical model representing an SBM, and second, it gives a practical contribution by supporting the public administration decision-making in adopting a breakthrough roadmap facilitating the value transfer from industry to society.
Information Technology for Business Sustainability: A Literature Review with Automated Content Analysis
Authors: Vidmar Doroteja , Marolt Marjeta , Pucihar Andreja
Published: January 2021

An extremely dynamic and fast-moving environment is pushing enterprises to continuous innovation and change. Managing sustainability in a digitalized environment seems to be of central importance for policy makers, as information technologies (IT), in combination with sustainability objectives, offer a wide range of opportunities for positive change. Through a systematic literature review and the application of automated content analysis, this study aims to provide insights into the latest research in the interdisciplinary field of sustainable business models and information systems. The results of the analysis, combined with a researcher’s perspective, suggest that IT, which can be used to achieve sustainability objectives, are already in place and have an infinite number of potential implications in the future. The results suggest that positive economic, social, and environmental changes can be achieved by using IT as long as they are used to identify unsustainable actions and enable positive change. The analysis of research trends revealed a discrepancy between the research in the European Union and the rest of the world and pointed to several avenues for future research.
Digital Storytelling in Cultural Heritage: Audience Engagement in the Interactive Documentary New Life
Authors: Podara Anna , Giomelakis Dimitrios , Nicolaou Constantinos , Matsiola Maria , Kotsakis Rigas
Published: January 2021

This paper casts light on cultural heritage storytelling in the context of interactive documentary, a hybrid media genre that employs a full range of multimedia tools to document reality, provide sustainability of the production and successful engagement of the audience. The main research hypotheses are enclosed in the statements: (a) the interactive documentary is considered a valuable tool for the sustainability of cultural heritage and (b) digital approaches to documentary storytelling can provide a sustainable form of viewing during the years. Using the Greek interactive documentary (i-doc) NEW LIFE (2013) as a case study, the users’ engagement is evaluated by analyzing items from a seven-year database of web metrics. Specifically, we explore the adopted ways of the interactive documentary users to engage with the storytelling, the depth to which they were involved along with the most popular sections/traffic sources and finally, the differences between the first launch period and latest years were investigated. We concluded that interactivity affordances of this genre enhance the social dimension of cultural, while the key factors for sustainability are mainly (a) constant promotion with transmedia approach; (b) data-driven evaluation and reform; and (c) a good story that gathers relevant niches, with specific interest to the story.
The Origin of Proactive Environmental Corporate Social Responsibility (ECSR) of Large Firms: Institutional Embeddedness—Driven, Family Involvement-Promoted, or Resource-Dependent?
Authors: Hu Shilei , Wang Xiaohong
Published: January 2021

Why are some firms in China highly engaged in proactive environmental corporate social responsibility (ECSR) while others are not? Knowledge of the determinants of proactive ECSR is a key research question among academics and practitioners. This study seeks to advance the ECSR literature by suggesting a configuration way of integrating institutional embeddedness, family involvement, and the resource base factors of firms to predict proactive ECSR investment, a proxy for proactive ECSR. Specifically, this study explores how the combination of institutional embeddedness, family involvement, and the resource base factors of firms jointly shape the proactive ECSR investment of large firms. Using fuzzy-set qualitative comparative analysis (fsQCA) on a sample of 162 large private firms in China, this study finds that no condition alone is sufficient to account for high proactive ECSR investment. Institutional embeddedness, family involvement, and the resource base factors of firms must interact with one another to produce highly proactive ECSR investments. There exist two distinctive configurations that provide a nuanced picture of the drivers of proactive ECSR investment. These findings provide meaningful insights for theory and practice and pave the way for future research in the domain of ECSR.
Sustainable Alternate Materials for Concrete Production from Renewable Source and Waste
Authors: Ramasubramani R. , Gunasekaran K.
Published: January 2021

Natural resources are being continuously extracted for the production of concrete which leads to degradation of the ecosystem. This is also a challenge for sustainability to save Nature. This study seeks to identify a suitable replacement material for river sand and stone aggregate for the sustainable utilization of renewable sources. Manufactured sand (M-sand) from industrial by-products and coconut shell (CS), an agricultural waste, are the resources selected as replacement materials for sustainability. This study uses M-sand as fine aggregate and CS coarse aggregate in place of river sand (R-sand) and crushed stone aggregate (CSA) for concrete production, respectively. To prove that M-sand and CS are sustainable alternate materials, this study focused on the microstructural characteristics on concrete constituents and CS aggregate and also conducted on concrete produced using R-sand, M-sand and CS. Also, this study focused on the microstructural characteristics and properties of conventional concrete (CC) and coconut shell concrete (CSC) produced using both R-sand and M-sand. Since this study aims to find sustainable alternative materials for R-sand and CSA by M-sand and CS, its properties are studied and compared since microstructural characterization is very significant for concrete compatibility. Microstructural studies revealed that the use of M-sand does not affect the microstructural properties of concrete compared to R-sand concrete and rather it improves the strength of concrete. A similar same trend was observed when CS was used with M-sand compared to CS used with R-sand. Hence, this study strongly suggests that the use of M-sand in its place of R-sand and CS in its place of CSA are sustainable alternatives for the production of concrete so that natural resources can be saved and hence sustainability could be sustained.
A Model of Stress Change under the First COVID-19 Pandemic among the General Public in Japanese Major Cities and Rural Areas
Authors: Uehara Misato , Fujii Makoto , Kobayashi Kazuki
Published: January 2021

Research on stress related to the COVID-19 pandemic has been dominated by the cases of healthcare workers, students, patients, and their stress during the COVID-19 pandemic. This study examined the relationship between the amount of stress change under the COVID-19 pandemic and demographic factors (age, sex, occupation, etc.) in residents of a large city and a rural area of Japan. A total of 1331 valid responses were received in June 2020 from residents of Tokyo, Osaka, and Nagano registered with a private research firm. We were able to identify 15 statistically significant variables out of 36 explanatory variables, which explained the significant increase in stress compared to the pre-pandemic period. Multiple-factor analysis showed that the relationship with people is a more significant explanatory variable for the level of increase in stress than the difference in environment between big cities (Tokyo, Osaka) and rural areas (Nagano), the type of housing, and the decrease in income compared to the pre-pandemic period.
The Role of Social Media in the Luxury Tourism Business: A Research Review and Trajectory Assessment
Authors: Thirumaran K , Jang Haejin , Pourabedin Zahra , Wood Jacob
Published: January 2021

The luxury tourism industry immediately conjures up thoughts of exclusivity, with access to it confined to a small and elite group of travelers often located within their own social bubble. Our systematic literature review seeks to understand how tourism scholarship has addressed the issue of luxury travel based on social media pronouncements and the areas of concentration in which earlier studies have been conducted. Literature was sourced using the following key terms “luxury tourism”, “elite travel”, “social media”, and “sustainability” in various combinations using the OneSearch online platform, the Proquest Database, and Google Scholar. Only peer-reviewed journals were used for the critical analysis. Three main thematic areas were identified and reviewed: (1) the role of social media in luxury tourism; (2) the behavioral attributes of luxury travelers’ when using social media; and (3) the methodologies employed in the extant literature, given the limitations of accessing specific data for the luxury tourism market. The selected period for the journals and articles reviewed was the last ten years, from March 2010 to March 2020. NVivo version 12 was used to decipher the themes and focus areas as well as quantify the significance of social media to luxury tourism. Drawing from these literature review outcomes, the study explores future research areas and issues that require new theoretical and methodological frameworks to further our understanding of the intersection between social media and the luxury tourism business.
The Commitment of Spanish Local Governments to Sustainable Development Goal 11 from a Multivariate Perspective
Authors: Martínez-Córdoba Pedro-José , Amor-Esteban Víctor , Benito Bernardino , García-Sánchez Isabel-María
Published: January 2021

The commitment of governments to sustainable development was materialised in the Millennium Development Goals (MDGs) and later in the Sustainable Development Goals (SDGs), the latter being a more ambitious project that positions local governments as the main agents for its implementation. With the aim of improving the sustainability of cities, this research analyses the commitment of Spanish local governments to the SDG-11, indicating possible improvements with the aim of complying with Agenda 2030. We use the X-STATIS study technique with graphic representations. The results indicate a positive trend towards achieving SDG-11, in which progressive governments are concerned with issues of inclusive and sustainable urbanisation as a result of increased citizen participation, and conservative governments focus on slum upgrading and safety in inclusive and accessible public spaces. In addition, the ideological coincidence between different administrative levels is an impetus to the fulfilment of SDG-11.
Food Security and Climate Stabilization: Can Cereal Production Systems Address Both?
Authors: Liang Long , Ridoutt Bradley G. , Wang Liyuan
Published: January 2021

There is abundant evidence that greenhouse gas (GHG) emissions of cereal products, expressed per ton of grain output, have been trending downward over the past 20 years. This has largely been achieved through agricultural intensification that has concurrently increased area-based GHG emissions. The challenge is for agriculture to increase grain yields to meet the food demands of a growing world population while also contributing to climate stabilization goals by reducing net GHG emissions. This study assessed yield-based and area-based emissions and efficiencies for the winter wheat–summer maize (WWSM) rotation system over the period 1996 to 2016 using long-term, longitudinal, farm survey data and detailed soil emission data in Huantai county, Shandong Province, which is an archetype for cereal production across the North China Plain (NCP). In this region, yields have been increasing over time. However, nitrogen fertilizer inputs have decreased substantially with greater adoption of soil nutrient testing. In addition, there has been widespread adoption of residue incorporation into soils. As such, since 2002, the product carbon footprints of wheat and maize have reduced by 25% and 30%, respectively. Meanwhile, area-based carbon footprints for the rotation system have reduced by around 15% over the same period. These findings demonstrate the importance of detailed assessment of soil N2O emissions and rates of soil organic carbon sequestration. They also show the potential for net reductions in GHG emissions in cropping without loss of grain yields.
The Impact of an Environmental Way of Customer’s Thinking on a Range of Choice from Transport Routes in Maritime Transport
Authors: David Andrej , Mako Peter , Lizbetin Jan , Bohm Patrik
Published: January 2021

The paper deals with the impact that an environmental way of thinking has on shipping and transport company customers regarding their preferences in choosing a transport route. Nowadays, maritime transport plays a very important role mainly in transoceanic container transport. It also deals with the statistics focused on container shipping, especially between North America and Europe. These statistics contribute to a general description of the development of container shipping on the route that is applicated in this case study. The significant impact of this kind of transport also reflects the estimation of the future development of container transport on the selected transport route. In this view, the least square method is used in this paper. This method can present the trend of development according to statistics. Thanks to these materials, this paper estimates a slight increase of the number of containers transported between North America and Europe in the near future. This increase will have a certain effect on the environment. Thus, as part of their business policy of sustainability and environment protection, customers will prefer a mode of transport and transport routes featuring a smaller effect on the environment in the future. The relevance of such a change in preferences in planning transport routes for the customer is reflected in the case study presented in this paper. So, one part of this paper is also dedicated to information about the impact of maritime transport on the environment. This part also explains the impact according to different studies that have been published in the last few years. The main contribution of this paper is also to point out the importance of this factor for the preferences of customers via the multi-criteria decision method. Using a multi-criteria decision method, it outlines how the factor of the impact on the environment can significantly change the offer made by a transport or shipping company, and thus how it represents a key element of whether the customer would prefer the given offer or focus on a competitor’s offer.
Navigation of Autonomous Light Vehicles Using an Optimal Trajectory Planning Algorithm
Authors: Valera Ángel , Valero Francisco , Vallés Marina , Besa Antonio , Mata Vicente , Llopis-Albert Carlos
Published: January 2021

Autonomous navigation is a complex problem that involves different tasks, such as location of the mobile robot in the scenario, robotic mapping, generating the trajectory, navigating from the initial point to the target point, detecting objects it may encounter in its path, etc. This paper presents a new optimal trajectory planning algorithm that allows the assessment of the energy efficiency of autonomous light vehicles. To the best of our knowledge, this is the first time in the literature that this is carried out by minimizing the travel time while considering the vehicle’s dynamic behavior, its limitations, and with the capability of avoiding obstacles and constraining energy consumption. This enables the automotive industry to design environmentally sustainable strategies towards compliance with governmental greenhouse gas (GHG) emission regulations and for climate change mitigation and adaptation policies. The reduction in energy consumption also allows companies to stay competitive in the marketplace. The vehicle navigation control is efficiently implemented through a middleware of component-based software development (CBSD) based on a Robot Operating System (ROS) package. It boosts the reuse of software components and the development of systems from other existing systems. Therefore, it allows the avoidance of complex control software architectures to integrate the different hardware and software components. The global maps are created by scanning the environment with FARO 3D and 2D SICK laser sensors. The proposed algorithm presents a low computational cost and has been implemented as a new module of distributed architecture. It has been integrated into the ROS package to achieve real time autonomous navigation of the vehicle. The methodology has been successfully validated in real indoor experiments using a light vehicle under different scenarios entailing several obstacle locations and dynamic parameters.
Influence of Complex Occupant Behavior Models on Cooling Energy Usage Analysis
Authors: Mun Sun-Hye , Kwak Younghoon , Huh Jung-Ho
Published: January 2021

The behavior of building occupants has been studied by researchers for building control as well as for predicting energy use. In this study, we analyzed the effect of the application of single and complex behavior models on the simulation results of residential buildings. Two occupant behaviors—window opening and closing and air conditioner (AC) usage—were simulated, which are known to be interconnected. This study had two purposes: The first was to integrate data analysis tools (R in this study) and building simulation tools (EnergyPlus in this study) so that two behaviors with interconnectivity could be reflected in building simulation analysis. The second purpose was to apply the behavior models in residential buildings to an integrated simulation environment in stages to analyze their relative influence on the building energy and indoor environment. The results of the study prove that the application of complex behavior is important for research regarding the prediction of actual energy consumption. The results help identify the gap between reality and the existing simulation methods; thereby, they can help improve methods related to energy consumption analysis. We hope that this study and its results will serve as a guide for researchers looking to study occupants’ behavior in the future.
Quotients of Euler Equations on Space Curves
Authors: Duyunova Anna , Lychagin Valentin , Tychkov Sergey
Published: January 2021

Quotients of partial differential equations are discussed. The quotient equation for the Euler system describing a one-dimensional gas flow on a space curve is found. An example of using the quotient to solve the Euler system is given. Using virial expansion of the Planck potential, we reduce the quotient equation to a series of systems of ordinary differential equations (ODEs). Possible solutions of the ODE system are discussed.
Kirkiin: A New Toxic Type 2 Ribosome-Inactivating Protein from the Caudex of Adenia kirkii
Authors: Bortolotti Massimo , Maiello Stefania , Ferreras José M. , Iglesias Rosario , Polito Letizia , Bolognesi Andrea
Published: January 2021

Ribosome-inactivating proteins (RIPs) are plant toxins that irreversibly damage ribosomes and other substrates, thus causing cell death. RIPs are classified in type 1 RIPs, single-chain enzymatic proteins, and type 2 RIPs, consisting of active A chains, similar to type 1 RIPs, linked to lectin B chains, which enable the rapid internalization of the toxin into the cell. For this reason, many type 2 RIPs are very cytotoxic, ricin, volkensin and stenodactylin being the most toxic ones. From the caudex of Adenia kirkii (Mast.) Engl., a new type 2 RIP, named kirkiin, was purified by affinity chromatography on acid-treated Sepharose CL-6B and gel filtration. The lectin, with molecular weight of about 58 kDa, agglutinated erythrocytes and inhibited protein synthesis in a cell-free system at very low concentrations. Moreover, kirkiin was able to depurinate mammalian and yeast ribosomes, but it showed little or no activity on other nucleotide substrates. In neuroblastoma cells, kirkiin inhibited protein synthesis and induced apoptosis at doses in the pM range. The biological characteristics of kirkiin make this protein a potential candidate for several experimental pharmacological applications both alone for local treatments and as component of immunoconjugates for systemic targeting in neurodegenerative studies and cancer therapy.
Return of the Neurotropic Enteroviruses: Co-Opting Cellular Pathways for Infection
Authors: Peters Christine E. , Carette Jan E.
Published: January 2021

Enteroviruses are among the most common human infectious agents. While infections are often mild, the severe neuropathogenesis associated with recent outbreaks of emerging non-polio enteroviruses, such as EV-A71 and EV-D68, highlights their continuing threat to public health. In recent years, our understanding of how non-polio enteroviruses co-opt cellular pathways has greatly increased, revealing intricate host–virus relationships. In this review, we focus on newly identified mechanisms by which enteroviruses hijack the cellular machinery to promote their replication and spread, and address their potential for the development of host-directed therapeutics. Specifically, we discuss newly identified cellular receptors and their contribution to neurotropism and spread, host factors required for viral entry and replication, and recent insights into lipid acquisition and replication organelle biogenesis. The comprehensive knowledge of common cellular pathways required by enteroviruses could expose vulnerabilities amenable for host-directed therapeutics against a broad spectrum of enteroviruses. Since this will likely include newly arising strains, it will better prepare us for future epidemics. Moreover, identifying host proteins specific to neurovirulent strains may allow us to better understand factors contributing to the neurotropism of these viruses.