bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine-Learning Functional Zonation Approach for Characterizing Terrestrial–Aquatic Interfaces: Application to Lake Erie
Authors: Enguehard Léa , Falco Nicola , Schmutz Myriam , Newcomer Michelle E. , Ladau Joshua , Brown James B. , Bourgeau-Chavez Laura , Wainwright Haruko M.
Published: July 2022

Ecosystems at coastal terrestrial–aquatic interfaces play a significant role in global biogeochemical cycles. In this study, we aimed to characterize coastal wetlands with particular focus on the co-variability between plant dynamics, topography, soil, and other environmental factors. We proposed a functional zonation approach based on machine learning clustering to identify the spatial regions, i.e., zones that capture these co-varied properties. This approach was applied to publicly available datasets along Lake Erie, in the Great Lakes Region. We investigated the heterogeneity of coastal ecosystem structures as a function of along-shore distance and transverse distance, based on the spatial data layers, including topography, wetland vegetation cover, and the time series of Landsat’s enhanced vegetation index (EVI) between 1990 and 2020. Results showed that the topographic metrics (elevation and slope), soil texture, and plant productivity influence the spatial distribution of wetland land-covers (emergent and phragmites). These results highlight a natural organization along the transverse axis, where the elevation and the EVI increase further away from the coastline. In addition, the clustering analysis allowed us to identify regions with distinct environmental characteristics, as well as the ones that are more sensitive to interannual lake-level variations.
Native Smartphone Single- and Dual-Frequency GNSS-PPP/IMU Solution in Real-World Driving Scenarios
Authors: Yi Ding , Yang Sihan , Bisnath Sunil
Published: July 2022

The Global Navigation Satellite System (GNSS) capability in smartphones has seen significant upgrades over the years. The latest ultra-low-cost GNSS receivers are capable of carrier-phase tracking and multi-constellation, dual-frequency signal reception. However, due to the limitations of these ultra-low-cost receivers and antennas, smartphone GNSS position solutions suffer significantly from urban multipath, poor signal reception, and signal blockage. This paper presents a novel sensor fusion technique using Precise Point Positioning (PPP) and the inertial sensors in smartphones, combined with a single- and dual-frequency (SFDF) optimisation scheme for smartphones. The smartphone is field-tested while attached to a vehicle’s dashboard and is driven in multiple real-world situations. A total of five vehicle experiments were conducted and the solutions show that SFDF-PPP outperforms single-frequency PPP (SF-PPP) and dual-frequency PPP (DF-PPP). Solutions can be further improved by integrating with native smartphone IMU measurements and provide consistent horizontal positioning accuracy of <2 m rms through a variety obstructions. These results show a significant improvement from the existing literature using similar hardware in challenging environments. Future work will improve optimising inertial sensor calibration and integrate additional sensors.
Improving Deforestation Detection on Tropical Rainforests Using Sentinel-1 Data and Convolutional Neural Networks
Authors: Ortega Adarme Mabel , Doblas Prieto Juan , Queiroz Feitosa Raul , De Almeida Cláudio Aparecido
Published: July 2022

Detecting early deforestation is a fundamental process in reducing forest degradation and carbon emissions. With this procedure, it is possible to monitor and control illegal activities associated with deforestation. Most regular monitoring projects have been recently proposed, but most of them rely on optical imagery. In addition, these data are seriously restricted by cloud coverage, especially in tropical environments. In this regard, Synthetic Aperture Radar (SAR) is an attractive alternative that can fill this observational gap. This work evaluated and compared a conventional method based on time series and a Fully Convolutional Network (FCN) with bi-temporal SAR images. These approaches were assessed in two regions of the Brazilian Amazon to detect deforestation between 2019 and 2020. Different pre-processing techniques, including filtering and stabilization stages, were applied to the C-band Sentinel-1 images. Furthermore, this study proposes to provide the network with the distance map to past-deforestation as additional information to the pair of images being compared. In our experiments, this proposal brought up to 4% improvement in average precision. The experimental results further indicated a clear superiority of the DL approach over a time series-based deforestation detection method used as a baseline in all experiments. Finally, the study proved the benefits of pre-processing techniques when using detection methods based on time series. On the contrary, the analysis revealed that the neural network could eliminate noise from the input images, making filtering innocuous and, therefore, unnecessary. On the other hand, the stabilization of the input images brought non-negligible accuracy gains to the DL approach.
Research on the Rotational Correction of Distributed Autonomous Orbit Determination in the Satellite Navigation Constellation
Authors: Zhou Wei , Cai Hongliang , Li Ziqiang , Tang Chengpan , Hu Xiaogong , Liu Wanke
Published: July 2022

The autonomous orbit determination of the navigation constellation uses only bidirectional ranging data of the inter-satellite link for data processing. The lack of space-time benchmark information related to the Earth inevitably causes overall rotational uncertainty in the constellation, leading to a decrease in orbit accuracy and affecting user positioning accuracy. This study (1) introduces a method for rotation correction in distributed autonomous orbit determination based on inter-satellite bidirectional ranging; (2) conducts constellation autonomous orbit determination and time synchronization processing experiments based on inter-satellite ranging data for the 24 medium Earth orbit (MEO) satellites in the Beidou-3 global satellite navigation system (BDS-3); and (3) makes comparative analyses on the accuracy of autonomous orbit determination based on three rotation correction cases, including a no-rotation-correction case, independent satellite constraints case, and global satellite constraints case. The experimental results are described as follows. For the no-rotation-correction case, the prediction error of the orbital inclination angle (iot, i) for the entire constellation on the 30th day was 2.11 × 10−7/rad, the prediction error of the right ascension of the ascending point (Omega, Ω) was 2.25 × 10−7/rad, and the average root mean square (RMS) of the user range error (URE) for the entire constellation orbit was 1.41 m. In the autonomous orbit determination experiment with independent constraints on satellites, the prediction error of i for the entire constellation on the 30th day was 5.43 × 10−7/rad, the prediction error of Ω was 2.03 × 10−7/rad, and the average RMS of the orbital URE for the entire constellation was 1.09 m. In the autonomous orbit determination experiment with global satellite constraints, the prediction error of i for the entire constellation on the 30th day was 5.31 × 10−7/rad, the prediction error of Ω was 1.95 × 10−7/rad, and the RMS of the orbital URE for the entire constellation was 0.94 m. According to the analysis of the above experimental results, compared with the autonomous orbit determination under the no-rotation-correction case, the adoption of an algorithm for independent satellite constraints to correct the overall constellation rotation weakens the constellation rotation influence; however, it may destroy the overall constellation configuration, which affects the stability of autonomous orbit determination. Finally, the algorithm based on global satellite constraints both impairs the influence of constellation rotation and maintains the overall constellation configuration.
Double Effect of Urbanization on Vegetation Growth in China’s 35 Cities during 2000–2020
Authors: Miao Lijuan , He Yu , Kattel Giri Raj , Shang Yi , Wang Qianfeng , Zhang Xin
Published: July 2022

In recent decades, the trade-off between urbanization and vegetation dynamics has broken the balance between human activities and social-economic dimensions. Our understanding towards the complex human–nature interactions, particularly the gradient of vegetation growth pattern across different city size, is still limited. Here, we selected 35 typical cities in China and classified them into five categories according to their resident population (e.g., megacities, megapolis, big cities, medium cities, and small cities). The spatial-temporal dynamics of vegetation growth for all 35 cities were inferred from the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI). We found that averaged NDVI for all cities slightly decreased during 2000 and 2020, at a rate of 1.6 × 10−4 per year. Most cities were characterized with relatively lower NDVI in urban areas than its surrounding area (determined by a series of buffer zones, i.e., 1–25 km outside of the city boundary). The percentage of greening pixels increased from urban area to the 25 km buffer zone at a rate of 4.7 × 10−4 per km. We noticed that negative impact of urbanization on vegetation growth reduced as the distance to urban area increased, with an exception for megacities (e.g., Shanghai, Beijing, and Shenzhen). In megacities and megapolis, greening pixels were more concentrated at core urban area, implying that the positive urbanization effect on vegetation growth is much more apparent. We argue that urbanization in China might facilitate vegetation growth to a certain extent, for which an appropriate urban planning such as purposeful selection of city sizes could be a scientific guidance while targeting the city’s sustainable development goals in future.
Quantitative Analysis of Natural and Anthropogenic Factors Influencing Vegetation NDVI Changes in Temperate Drylands from a Spatial Stratified Heterogeneity Perspective: A Case Study of Inner Mongolia Grasslands, China
Authors: Li Shengkun , Li Xiaobing , Gong Jirui , Dang Dongliang , Dou Huashun , Lyu Xin
Published: July 2022

The detection and attribution of vegetation dynamics in drylands is an important step for the development of effective adaptation and mitigation strategies to combat the challenges posed by human activities and climate change. However, due to the spatial heterogeneity and interactive influences of various factors, quantifying the contributions of driving forces on vegetation change remains challenging. In this study, using the normalized difference vegetation index (NDVI) as a proxy of vegetation growth status and coverage, we analyzed the temporal and spatial characteristics of the NDVI in China’s Inner Mongolian grasslands using Theil–Sen slope statistics and Mann–Kendall trend test methods. In addition, using the GeoDetector method, a spatially-based statistical technique, we assessed the individual and interactive influences of natural factors and human activities on vegetation-NDVI change. The results show that the growing season average NDVI exhibited a fluctuating upward trend of 0.003 per year from 2000 to 2018. The areas with significant increases in NDVI (p < 0.05) accounted for 45.63% of the entire region, and they were mainly distributed in the eastern part of the Mu Us sandy land and the eastern areas of the Greater Khingan Range. The regions with a decline in the NDVI were mainly distributed in the central and western regions of the study area. The GeoDetector results revealed that both natural and human factors had significant impacts on changes in the NDVI (p < 0.001). Precipitation, livestock density, wind speed, and population density were the dominant factors affecting NDVI changes in the Inner Mongolian grasslands, explaining more than 15% of the variability, while the contributions of the two topography factors (terrain slope and slope aspect) were relatively low (less than 2%). Furthermore, NDVI changes responded to the changes in the level of specific influencing factors in a nonlinear way, and the interaction of two factors enhanced the effect of each singular factor. The interaction between precipitation and temperature was the highest among all factors, accounting for 39.3% of NDVI variations. Findings from our study may aid policymakers in better understanding the relative importance of various factors and the impacts of the interactions between factors on vegetation change, which has important implications for preventing and mitigating land degradation and achieving sustainable pasture use in dryland ecosystems.
A Lightweight Network Based on One-Level Feature for Ship Detection in SAR Images
Authors: Yu Wenbo , Wang Zijian , Li Jiamu , Luo Yunhua , Yu Zhongjun
Published: July 2022

Recently, deep learning has greatly promoted the development of detection methods for ship targets in synthetic aperture radar (SAR) images. However, existing detection networks are mostly based on large-scale models and high-cost computations, which require high-performance computing equipment to realize real-time processing and limit their hardware transplantation to onboard platforms. To address this problem, a lightweight ship detection network via YOLOX-s is proposed in this paper. Firstly, we remove the computationally heavy pyramidal structure and build a streamlined network based on a one-level feature for higher detection efficiency. Secondly, to expand the limited receptive field and enhance the semantic information of a single-feature map, a residual asymmetric dilated convolution (RADC) block is proposed. Through four branches with different dilation rates, the RADC block can help the detector to capture various ships in complex backgrounds. Finally, to tackle the imbalance problem between ships of different scales in the training stage, we put forward a balanced label assignment strategy called center-based uniform matching. To verify the effectiveness of the proposed method, we conduct extensive experiments on the SAR Ship Detection Dataset (SSDD) and High-Resolution SAR Images Dataset (HRSID). The results show that our method can achieve comparable performance to general detection networks with much less computational cost.
SM-SegNet: A Lightweight Squeeze M-SegNet for Tissue Segmentation in Brain MRI Scans
Authors: Yamanakkanavar Nagaraj , Choi Jae Young , Lee Bumshik
Published: July 2022

In this paper, we propose a novel squeeze M-SegNet (SM-SegNet) architecture featuring a fire module to perform accurate as well as fast segmentation of the brain on magnetic resonance imaging (MRI) scans. The proposed model utilizes uniform input patches, combined-connections, long skip connections, and squeeze–expand convolutional layers from the fire module to segment brain MRI data. The proposed SM-SegNet architecture involves a multi-scale deep network on the encoder side and deep supervision on the decoder side, which uses combined-connections (skip connections and pooling indices) from the encoder to the decoder layer. The multi-scale side input layers support the deep network layers’ extraction of discriminative feature information, and the decoder side provides deep supervision to reduce the gradient problem. By using combined-connections, extracted features can be transferred from the encoder to the decoder resulting in recovering spatial information, which makes the model converge faster. Long skip connections were used to stabilize the gradient updates in the network. Owing to the adoption of the fire module, the proposed model was significantly faster to train and offered a more efficient memory usage with 83% fewer parameters than previously developed methods, owing to the adoption of the fire module. The proposed method was evaluated using the open-access series of imaging studies (OASIS) and the internet brain segmentation registry (IBSR) datasets. The experimental results demonstrate that the proposed SM-SegNet architecture achieves segmentation accuracies of 95% for cerebrospinal fluid, 95% for gray matter, and 96% for white matter, which outperforms the existing methods in both subjective and objective metrics in brain MRI segmentation.
A Comparative Analysis on Blockchain versus Centralized Authentication Architectures for IoT-Enabled Smart Devices in Smart Cities: A Comprehensive Review, Recent Advances, and Future Research Directions
Authors: Khalil Usman , Malik Owais Ahmed , Uddin Mueen , Chen Chin-Ling
Published: July 2022

Smart devices have become an essential part of the architectures such as the Internet of Things (IoT), Cyber-Physical Systems (CPSs), and Internet of Everything (IoE). In contrast, these architectures constitute a system to realize the concept of smart cities and, ultimately, a smart planet. The adoption of these smart devices expands to different cyber-physical systems in smart city architecture, i.e., smart houses, smart healthcare, smart transportation, smart grid, smart agriculture, etc. The edge of the network connects these smart devices (sensors, aggregators, and actuators) that can operate in the physical environment and collects the data, which is further used to make an informed decision through actuation. Here, the security of these devices is immensely important, specifically from an authentication standpoint, as in the case of unauthenticated/malicious assets, the whole infrastructure would be at stake. We provide an updated review of authentication mechanisms by categorizing centralized and distributed architectures. We discuss the security issues regarding the authentication of these IoT-enabled smart devices. We evaluate and analyze the study of the proposed literature schemes that pose authentication challenges in terms of computational costs, communication overheads, and models applied to attain robustness. Hence, lightweight solutions in managing, maintaining, processing, and storing authentication data of IoT-enabled assets are an urgent need. From an integration perspective, cloud computing has provided strong support. In contrast, decentralized ledger technology, i.e., blockchain, light-weight cryptosystems, and Artificial Intelligence (AI)-based solutions, are the areas with much more to explore. Finally, we discuss the future research challenges, which will eventually help address the ambiguities for improvement.
The Metaverse as a Virtual Form of Smart Cities: Opportunities and Challenges for Environmental, Economic, and Social Sustainability in Urban Futures
Authors: Allam Zaheer , Sharifi Ayyoob , Bibri Simon Elias , Jones David Sydney , Krogstie John
Published: July 2022

Data infrastructures, economic processes, and governance models of digital platforms are increasingly pervading urban sectors and spheres of urban life. This phenomenon is known as platformization, which has in turn given rise to the phenomena of platform society, where platforms have permeated the core of urban societies. A recent manifestation of platformization is the Metaverse, a global platform project launched by Meta (formerly Facebook) as a globally operating platform company. The Metaverse represents an idea of a hypothetical “parallel virtual world” that incarnate ways of living and working in virtual cities as an alternative to smart cities of the future. Indeed, with emerging innovative technologies—such as Artificial Intelligence, Big Data, the IoT, and Digital Twins—providing rich datasets and advanced computational understandings of human behavior, the Metaverse has the potential to redefine city designing activities and service provisioning towards increasing urban efficiencies, accountabilities, and quality performance. However, there still remain ethical, human, social, and cultural concerns as to the Metaverse’s influence upon the quality of human social interactions and its prospective scope in reconstructing the quality of urban life. This paper undertakes an upper-level literature review of the area of the Metaverse from a broader perspective. Further, it maps the emerging products and services of the Metaverse, and explores their potential contributions to smart cities with respect to their virtual incarnation, with a particular focus on the environmental, economic, and social goals of sustainability. This study may help urban policy makers to better understand the opportunities and implications of the Metaverse upon tech-mediated practices and applied urban agendas, as well as assess the positives and negatives of this techno-urban vision. This paper also offers thoughts regarding the argument that the Metaverse has disruptive and substantive effects on forms of reconstructing reality in an increasingly platformized urban society. This will hopefully stimulate prospective research and further critical perspectives on the topic.
Forest Soils: Functions, Threats, Management
Authors: von Wilpert Klaus
Published: July 2022

The specific characteristic of forest soils is their long-term development under a more-or-less continuous vegetation cover [...]
Environmental Impact Evaluation of University Integrated Waste Management System in India Using Life Cycle Analysis
Authors: Jaglan Amit Kumar , Cheela Venkata Ravi Sankar , Vinaik Mansi , Dubey Brajesh
Published: July 2022

Decarbonization of university campuses by integrating scientific waste approaches and circular economy principles is the need-of-the-hour. Universities, the maximum energetic corporations and places for clinical studies and social activities, have a duty to assemble low-carbon campuses and play a vital function in lowering CO2 emissions. An environmental life cycle assessment was conducted to compare proposed municipal solid waste (MSW) treatment systems with the existing system in the residential university campus (RUC) in Kharagpur, West Bengal (India). The results show the existing MSW disposal practice in RUC (baseline scenario has the highest GWP (1388 kg CO2 eq), which can potentially be reduced by adopting integrated waste management system with source segregation as represented in futuristic scenarios (S2—50% sorting) and (S3—90% sorting)). Compared to S1, GHG emission was reduced by 50.9% in S2 and by 86.5% in S3. Adopting anaerobic digestion and engineered landfill without energy recovery offsets the environmental emissions and contributes to significant environmental benefits in terms of ecological footprints. Capital goods play a pivotal role in mitigation the environmental emissions. The shift towards S2 and S3 requires infrastructure for waste collection and sorting will contribute to reduction of associated environmental costs in the long-term.
Renewable Energy Acceptance by Households: Evidence from Lithuania
Authors: Štreimikienė Dalia , Lekavičius Vidas , Stankūnienė Gintare , Pažėraitė Aušra
Published: July 2022

Although renewable energy adoption in the residential sector has increased significantly in the EU due to the governmental policies, aiming to reduce the barriers of renewable energy penetration, the full potential of renewable energy deployment in households is still not realized due to the behavioral and other barriers. One of the most important factors in the adoption of renewable energy technologies in households is the decision-making to implement renewables; therefore, the behavioral economics insights should be taken into account during the analysis of renewable energy acceptance by households. The paper provides a systematic literature review on renewable energy use in households by analyzing policies and measures, which could increase the use of renewable energy in households by overcoming the major barriers. The dynamics of renewable energy consumption in EU households was performed by applying Eurostat data, and the empirical case study was conducted in Lithuania to understand the main reasons of renewable energy acceptance by the household. Even though the use of renewable energy sources has increased significantly in the EU member states during the recent years, the study has found the following most common barriers that the traditional policies are unable to overcome: (1) high upfront cost and long pay-back period, (2) a lack of information and knowledge, (3) low priority of environmental concern, (4) resistance to change; human habits. The case study shows that the majority of Lithuanian households would like to use renewable energy technologies in their homes, but they encounter financial difficulties and lack of infrastructure. The policy recommendations were developed based on the results of the conducted study.
Digitalisation as the Indicator of the Evidence of Sustainability in the European Union
Authors: Burinskienė Aurelija , Seržantė Milena
Published: July 2022

Digitalisation provides access to an integrated network of information that can benefit society and businesses. However, the evidence of sustainability in business is less researched. In our paper, by building up the research approach, we address the relevant gap by investigating how sustainable development goals represent the interrelationship between digitalisation and sustainability. Such research is particularly important because understandings of digitalisation and sustainability determine how different actors, including business managers and policymakers, act in response to those imperatives to develop future employees skills starting from school age. Following a multi-method approach, we have combined our analysis into two steps examining the relationship between digitalisation and sustainability. Building digital networks, business managers and policy makers using digital means can create some unique opportunities to strategically address sustainable development challenges for the United Nations Targets (SDG) to ensure higher productivity, education, and an equality-oriented society. This point of view describes the potential of digitalisation for society and businesses of the future. The authors revise the links between digitalisation and sustainability in the European Union countries by using data available in Eurostat and UNECE public databases. The two-stage methodology for the identification of the relationship between ICT and sustainability is used in the paper and a linear regression model is applied. The results showed tiers with five SDGs, focusing on business, and all these tiers are fixed in the constructed equations for each SDG. The recommended solution is statistically valid and proves the novelty of this research. Among digitalisation indicators, only mobile-cellular subscriptions and fixed-broadband sub-basket prices in part do not affect researched sustainable development indicators.
Does Digital Transformation in Manufacturing Affect Trade Imbalances? Evidence from US–China Trade
Authors: Zu Wenjing , Gu Guoda , Lei Sihan
Published: July 2022

In the new era of the Fourth Industrial Revolution, digitalization has progressively transformed manufacturing and further affected the balance in international trade patterns. This study assesses whether and how the digital transformation in manufacturing contributes to trade imbalances. Using detailed industry-level data from the US, this study constructs an integrated evaluation to measure the level of digital transformation in manufacturing and investigates the ways in which digital transformation in manufacturing affects the US–China trade imbalance. Empirical results show that the US digital transformation in manufacturing is positively associated with the US–China total trade imbalance, which in turn is negatively associated with their related-party trade imbalance. The further analysis presents a moderated mediation model that includes the US-imported intermediate input from China (mediator for the US–China total trade imbalance), foreign direct investment in China by the US multinationals (mediator for the US–China related-party trade imbalance), and Chinese important manufacturing policy (moderator) simultaneously. The results reveal that the Chinese important manufacturing policy moderates the mediation process and the moderated mediation effect is stronger for the industries which are not involved with this policy. Our findings are informative for developing digital transformation strategies for both manufacturing firms and government authorities.
Assessing Durability Properties and Economic Potential of Shellfish Aquaculture Waste in the Construction Industry: A Circular Economy Perspective
Authors: Peceño Begoña , Bakit José , Cortes Niris , Alonso-Fariñas Bernabé , Bonilla Enzo , Leiva Carlos
Published: July 2022

The construction industry’s high demand for natural resources, combined with the waste generated by agriculture, creates an opportunity for the circular economy. This experiment used the CaCO3 found in scallop shells as an ingredient for the manufacture of fire-resistant materials, replacing gypsum in compositions of 40% and 50% by weight. The mechanical compressive strength was estimated for both freeze-thaw cycles and acid and sulfate attacks. The cost of disposing of scallop shell waste in landfills, savings from substitution, and the payback period relative to the amount of production were determined. The compressive strength of the materials decreased by 80% when subjected to freeze-thaw cycles and sulfate attack. In response to acid attack, they showed a 100% increase in strength during the first three weeks and a decrease thereafter. The savings amounted to $46.36 (22.4%) for 40% replacement and $58.93 (28.4%) for 50%. Respectively, return on investment is achieved at 800- and 630-per-metric ton produced. The difference between the costs of waste disposal (in aquaculture) and the potential savings from using CaCO3 as a raw material (in construction) creates an opportunity for commercialization between the two industries, serves as a reference for decision-makers, and complies with circular economy principles, reducing both inputs of raw materials and outputs of waste.
Issues and Needs of Elderly in Community Facilities and Services: A Case Study of Urban Housing Projects in Bangkok, Thailand
Authors: Somsopon Wiruj , Kim Sohee Minsun , Nitivattananon Vilas , Kusakabe Kyoko , Nguyen Thi Phuoc Lai
Published: July 2022

Thailand is projected to become a “super-aged” society in 2050, with more than 35 percent of the population aged 60 or above. The aging population represents enormous challenges in supporting the elderly’s needs in terms of living environment and well-being. Providing community facilities and services that foster healthy aging in urban residential areas ensures that older adults feel comfortable aging in their homes or communities. Therefore, this research study includes a comprehensive assessment of the needs of elderly people that used community facilities and services using a focus group interview, a site investigation, and a questionnaire survey in five urban housing projects in Bangkok. The study reveals that the need for community facilities and services, such as green spaces, safety facilities, and medical services, was prioritized by the majority of elderly respondents, especially those who were ambulant and active. Elderly people’s income and health status, the provision of community facilities and services for the elderly, and the usability and accessibility of community facilities were found to be key factors that affected elderly people’s satisfaction and participation in social activities. As reported in the literature, an elderly-friendly living environment should support social activities in the open spaces of residential areas. It is revealed by the study that green spaces, safety facilities, elderly clubs, medical and long-term care services, and social activity arrangement services were instrumental for elderly people’s social and health status; therefore, these should be considered by housing developers and facility managers.
Response of Bread Wheat Cultivars Inoculated with Azotobacter Species under Different Nitrogen Application Rates
Authors: El-Sorady Gawhara A. , El-Banna Aly A. A. , Abdelghany Ahmed M. , Salama Ehab A. A. , Ali Hayssam M. , Siddiqui Manzer H. , Hayatu Nafiu Garba , Paszt Lidia Sas , Lamlom Sobhi F.
Published: July 2022

A field trial was conducted to investigate the productivity of three bread wheat cultivars, namely Giza-168, Shandawel-1, and Misr-2, under different fertilization treatments, i.e., azotobacter inoculation, 25% nitrogen (N) + azotobacter, 50%N + azotobacter, 75%N + azotobacter, and 100%N of the recommended level (180 kg/ha). The treatments were laid in a split-plot design, and each was replicated three times. The findings showed that wheat cultivars examined in the two seasons exhibited significant variations (p ≤ 0.05) in plant height (PH, cm), number of tillers m−2 (NTM), number of spikelets per spike (NSS), 1000-grain weight (TGW, g), spike length (SL, cm), biological yield (BY, ton ha−1), grain yield (GY, ton ha−1), straw yield (SY, ton ha−1), harvest index (HI, %), protein content (PC, %), days to 50% heading (DTH), and chlorophyll content (CC, SPAD). As a result, Giza-168 had a higher GY (14%), HI (27%), and TGW (10%) than any of the other two cultivars in both growing seasons. Furthermore, Misr-2 exhibited the highest PH (16%), NTM (26%), NSS (28%), SL (10%), BY (30%), SY (46%), and CC (3%). The application of the two treatments of 100%N and N75% + azotobacter exhibited high and statistically similar performance, resulting in an increase in all studied traits by greater than 30–50% compared to the other three treatments. According to the findings of the current investigation, the application of N fertilizer combined with azotobacter increased wheat yield more than either solely azotobacter or N application. We concluded that the application of nitrogen combined with azotobacter reduced the quantity of applied nitrogen by 25%.
Digital Winescape and Online Wine Tourism: Comparative Insights from Crete and Santorini
Authors: Alebaki Maria , Psimouli Maria , Kladou Stella , Anastasiadis Foivos
Published: July 2022

In the pursuit of sustainability and competitiveness, digital aspects of the tourism experience become increasingly more significant and wine tourism is no exception to this. Still, studies building on established concepts and sustainable practices in the corporate environment often prioritize physical attributes. One such example refers to winescape frameworks, which are yet to explicitly incorporate the digital experience, despite the growing importance of the digital servicescape. This study contributes to this area by commenting on available data on winery websites and adopting the winescape concept to analyze social media activity during the first year of the COVID-19 pandemic. The population of the study includes 53 wineries, located in two well-known Greek wine tourism destinations, namely Crete and Santorini. The results identify the most common winescape components that wineries emphasize, revealing similarities and differences across the two destinations. Implications highlight the winescape dimensions that (should) matter the most when considering digital experiences, and provide insights for wine tourism scholars and businesses alike towards a more sustainable wine supply chain.
The Role of NO in the Amelioration of Heavy Metal Stress in Plants by Individual Application or in Combination with Phytohormones, Especially Auxin
Authors: Ganguly Retwika , Sarkar Anik , Acharya Krishnendu , Keswani Chetan , Minkina Tatiana , Mandzhieva Saglara , Sushkova Svetlana , Chakraborty Nilanjan
Published: July 2022

Since the time of the Industrial Revolution, the accumulation of various heavy metals (HMs), such as cadmium (Cd), arsenic (As), lead (Pb), chromium (Cr), mercury (Hg), copper (Cu), zinc (Zn), nickel (Ni), etc., has increased substantially in the soil, causing a real risk to all kinds of consumers in the food chain. Moreover, excess HM accumulation is considered a major factor in decreasing plant growth and productivity. A number of recent studies have exhibited the astonishing impact of nitric oxide (NO), a multifunctional, gaseous signal molecule, on alleviating the destructive effects of HMs. Many reports revealed the noteworthy contribution of NO in reducing HM uptake and toxicity levels. In the present review, focus is given to the contribution of NO to decrease the toxicity levels of different HMs in a variety of plant species and their accumulation in those species. Simultaneously, this review also demonstrates the effects of NO on HM-stressed species, by its use both individually and along with auxin, a plant-growth-promoting phytohormone. Different perspectives about the reaction to the co-application of NO and auxin, as well as the differential role of NO to overcome HM stress, have been expanded.
Identification of Embodied Environmental Attributes of Construction in Metropolitan and Growth Region of Melbourne, Australia to Support Urban Planning
Authors: Rydlewski James , Rajabi Zohreh , Tariq Muhammad Atiq Ur Rehman , Muttil Nitin , Sidiqui Paras , Shah Ashfaq Ahmad , Khan Nasir Abbas , Irshad Muhammad , Alam Arif , Butt Tayyab Ashfaq , Ng Anne Wai Man
Published: July 2022

As growth regions evolve to accommodate the increasing population, they need to develop a wider variety of residential properties to accommodate the varying needs of the residents. As a result, the new accommodation is denser which involves higher embodied water carbon and energy. This research compares the construction differences in metropolitan and growth regions of Melbourne to identify embodied carbon, water, and energy. Representative areas of 25 km2 are selected from both regions. The growth region has 80% of the built area comprised of 2nd generation low-rise residential buildings whereas the prolific construction type in the Metropolitan region is mixed purpose industrial with 30% of the built area comprising of this type. The methodology implies open-source satellite imagery to build a spatial dataset in QGIS. The visual identification of the constructions in the study areas enables to identity the materials used in their construction. The total embodied carbon, water, and energy for the Metropolitan region are 32,895 tonnes, 4192 mL, and 3,694,412 GJ, respectively, whereas in the growth region, the totals are 179,376 tonnes carbon, 2533 mL water, and 2,243,571 GJ. Whilst Metropolitan has a significantly higher overall footprint when this is compared to the population of each region, it is shown that the growth region with its current construction type has a higher embodied carbon, water, and energy per head. The total per head for Metropolitan is 226.7 GJ energy, 257 kL water, and 20 tonnes carbon, whereas in the growth region, the embodied energy, water, and carbon, respectively, per head is 287.4 GJ, 324.6 kL, and 22 tonnes. The current performance per head of the growth region is considerably lower than that of Metropolitan. Using diverse residential construction types and efficient materials can serve the demanding needs of denser populated areas.
A Life Cycle Analysis to Optimally Manage Wasted Plastic Pesticide Containers
Authors: Garbounis Georgios , Karasali Helen , Komilis Dimitrios
Published: July 2022

Wasted Plastic Pesticide Containers (WPPC) represent the end-of-life cycle of used agrochemicals. Optimal treatment of these containers is necessary to protect both human health and the environment. In Europe, WPPC are typically rinsed after use and landfilled along with commingled Municipal Solid Waste (MSW). There seems to be no Life Cycle Assessment (LCA) methodology in the international literature to compare the environmental impacts of the WPPC management methods. The goal of this work was to perform an LCA to quantify the environmental impacts of seven alternative scenarios to treat and dispose of Wasted Plastic Pesticide Containers and rank them according to their environmental footprints. Thirty-one WPPCs were sampled, triple-rinsed and an analysis of their residual active pesticide was performed. Those residuals amounts were included in the LCA when assembling the WPPC unit. The scenario in which WPPC are separately collected and recycled resulted in the lowest net environmental impacts. Scenario 5 (50% recycling and 50% incineration) and scenario 6 (50% recycling and 50% landfilling) were the next environmentally optimal technologies, while the landfilling scenario resulted in the highest environmental impacts. A sensitivity analysis was performed, using different impact assessment methods, different transportation distances and different types of landfills and incinerators. The residual pesticide amount did not alter the ranking of the management scenarios. Triple rinsing was found to render all wasted containers as non-hazardous wastes.
Fuzzy-Energy-Management-Based Intelligent Direct Torque Control for a Battery—Supercapacitor Electric Vehicle
Authors: Oubelaid Adel , Alharbi Hisham , Humayd Abdullah S. Bin , Taib Nabil , Rekioua Toufik , Ghoneim Sherif S. M.
Published: July 2022

This paper presents a proposed fuzzy energy management strategy developed for a battery−super capacitor electric vehicle. In addition to providing different driving modes, the proposed strategy delivers the suitable type and amount of power to the vehicle. Furthermore, the proposed strategy takes into account possible failures in vehicle power sources. The speed and torque of the HEV traction machine are simultaneously controlled using a genetic algorithm that provides simultaneous tuning via the use of newly proposed cost functions that give the designer the ability to tradeoff and prioritize between the design variables to be minimized. The simulation results show that the intelligent speed and torque control and the fuzzy power management strategy improved the vehicle’s performance in terms of ripple minimization. The real-time simulation is conducted using the RT LAB simulator, and the results obtained correspond to those obtained in the numerical simulation using MATLAB/Simulink.
Determination of the Risk on Human Health of Heavy Metals Contained by Ship Source Bilge and Wastewater Discharged to the Sea on the Mediterranean by Monte Carlo Simulation
Authors: Özkaynak Ömer Harun , İçemer Gönül Tuğrul , Merdun Hasan
Published: July 2022

Discharge of bilge and wastewater from ships into the sea poses a risk to human health due to the heavy metals. In this study, shipborne bilgewater and wastewater carcinogenic and non-carcinogenic human health risks determine by using the measured and literature values of heavy metals copper, iron, vanadium, chromium, manganese, cobalt, nickel, zinc, arsenic, cadmium, and mercury in the shipborne bilgewater and wastewater. The heavy metal contents of seawater were selected from 11 points determined in Antalya Bay, wastewater, and bilge samples taken from two ships. The human health risk was determined using the Monte Carlo Simulation (MCS) method using these measured values and the heavy metal concentrations in the Mediterranean Sea in the literature. The risk of carcinogenicity of heavy metals from wastewater by dermal route, ingestion, and from bilge water by dermal way and ingestion were evaluated. The wastewater is dermal Ni > As > Cr, the wastewater is Ni > Cr > As by ingestion, the dermal Ni > As > Cr in the bilge, and the risk of ingestion is Ni > Cr > As. It has been determined that the non-carcinogenic Cr, Co, Hg, and As values in the wastewater and bilge water are above the acceptable 1 and therefore expose a risk to human health. The human health carcinogenic risk caused by heavy metals generating from the bilge and wastewater is much higher than the standard values determined by the WHO. For the first time in this study, it was determined that bilge water exposes a high risk for both swimmers and ship personnel in the health risk assessment of shipborne wastewater and bilge water.
Combining Tradable Credit Schemes with a New Form of Road Pricing: Producing Liveable Cities and Meeting Decarbonisation Goals
Authors: Pattinson Jo-Ann , Harrison Gillian , Mullen Caroline , Shepherd Simon
Published: July 2022

This paper considers how the implementation of a tradable credit scheme (TCS) may be used to reduce road traffic and to contribute to the formation of liveable cities and global climate change commitments. The concept of applying TCS to individual road transport is familiar to transport researchers as a measure to regulate congestion and reduce transport-related emissions. Yet, it is not a strategy currently being considered by policy makers in the UK, despite the electrification of the road vehicle fleet and the associated loss of tax revenue presenting a rare opportunity to alter the economic instruments, which apply to road traffic. We consider how transport researchers can capitalise on this unique moment in transport history to shape transport policy. Our study uses qualitative methods, including a thematic analysis of semi-structured interviews with transport stakeholders and experts, in addition to a literature review and document analysis. Data analysis is inductive, permitting the formation of new ideas about the potential benefits of TCS and the barriers to the application of TCS to real-world policy. Building upon the results of TCS experiments and the results of our analysis, we propose a novel potential form of TCS combined with road pricing to maintain government revenue, which incentivises road users to decrease road vehicle kilometres travelled and reduce pollution and congestion. The proposal contributes to the discussion on the governance of road transport and taxation.
Majorization Results Based upon the Bernardi Integral Operator
Authors: Al-Shbeil Isra , Srivastava Hari Mohan , Arif Muhammad , Haq Mirajul , Khan Nazar , Khan Bilal
Published: July 2022

By making use of some families of integral and derivative operators, many distinct subclasses of analytic, starlike functions, and symmetric starlike functions have already been defined and investigated from numerous perspectives. In this article, with the help of the one-parameter Bernardi integral operator, we investigate several majorization results for the class of normalized starlike functions, which are associated with the Janowski functions. We also give some particular cases of our main results. Finally, we direct the interested readers to the possibility of examining the fundamental or quantum (or q-) extensions of the findings provided in this work in the concluding section. However, the (p,q)-variations of the suggested q-results will provide relatively minor and inconsequential developments because the additional (rather forced-in) parameter p is obviously redundant.
JLcoding Language Tool for Early Programming Learning
Authors: Li Wei-Ying , Lu Tzu-Chuen
Published: July 2022

This paper proposes a symmetry language of block-based to design novel educational programming called the JLcoding system. JLcoding system helps students convert from a block-based language to a text-based programming language. The interface and function of the system are block-based programs such as Scratch, but it is designed with text-based architecture. The system contains graphic teaching to teach the basic knowledge of programming, such that students can maintain interest and confidence when learning computational thinking. The system simultaneously combines the advantages of block-based and text-based programming. This research engaged 41 students who learned block-based programming language as the research objects. The experimental results show that the students can obtain higher post-test scores than the pre-test scores after learning the JLcoding system. The degree of learning progress was not affected by their gender. Additionally, it was discovered that male students have higher confidence in their programming abilities, and students who have learning interests are more motivated to continue learning the program.