bluuebunny/crossref_metadata_2025 huggingface dataset:
Life Cycle Assessment of Households in Santiago, Chile: Environmental Hotspots and Policy Analysis
Authors: López-Eccher Camila , Garrido-Ramírez Elizabeth , Franchi-Arzola Iván , Muñoz Edmundo
Published: February 2021

The aim of this study is to assess the environmental impacts of household life cycles in Santiago, Chile, by household income level. The assessment considered scenarios associated with environmental policies. The life cycle assessment was cradle-to-grave, and the functional unit considered all the materials and energy required to meet an inhabitant’s needs for one year (1 inh/year). Using SimaPro 9.1 software, the Recipe Midpoint (H) methodology was used. The impact categories selected were global warming, fine particulate matter formation, terrestrial acidification, freshwater eutrophication, freshwater ecotoxicity, mineral resource scarcity, and fossil resource scarcity. The inventory was carried out through the application of 300 household surveys and secondary information. The main environmental sources of households were determined to be food consumption, transport, and electricity. Food consumption is the main source, responsible for 33% of the environmental impacts on global warming, 69% on terrestrial acidification, and 29% on freshwater eutrophication. The second most crucial environmental hotspot is private transport, whose contribution to environmental impact increases as household income rises, while public transport impact increases in the opposite direction. In this sense, both positive and negative environmental effects can be generated by policies. Therefore, life-cycle environmental impacts, the synergy between policies, and households’ socio-economic characteristics must be considered in public policy planning and consumer decisions.
Assessment of Cubic Equations of State: Machine Learning for Rich Carbon-Dioxide Systems
Authors: Truc George , Rahmanian Nejat , Pishnamazi Mahboubeh
Published: February 2021

Carbon capture and storage (CCS) has attracted renewed interest in the re-evaluation of the equations of state (EoS) for the prediction of thermodynamic properties. This study also evaluates EoS for Peng–Robinson (PR) and Soave–Redlich–Kwong (SRK) and their capability to predict the thermodynamic properties of CO2-rich mixtures. The investigation was carried out using machine learning such as an artificial neural network (ANN) and a classified learner. A lower average absolute relative deviation (AARD) of 7.46% was obtained for the PR in comparison with SRK (AARD = 15.0%) for three components system of CO2 with N2 and CH4. Moreover, it was found to be 13.5% for PR and 19.50% for SRK in the five components’ (CO2 with N2, CH4, Ar, and O2) case. In addition, applying machine learning provided promise and valuable insight to deal with engineering problems. The implementation of machine learning in conjunction with EoS led to getting lower predictive AARD in contrast to EoS. An of AARD 2.81% was achieved for the three components and 12.2% for the respective five components mixture.
Entrepreneurship Education as a Strategy to Build Regional Sustainability
Authors: Hagebakken Grete , Reimers Christian , Solstad Elsa
Published: February 2021

Entrepreneurship education (EE) is a means to create economic activity and is of importance in the development of rural regions. Entrepreneurship education is generally conducted by three different methods: (1) teaching students about entrepreneurial themes, (2) developing the capabilities of becoming a successful entrepreneur for enterprise and (3) developing capabilities through enterprise by which persons learn through experience and discovery. Our research question is; How does education through entrepreneurship fit as a way to meet the needs of start-ups in a rural context? We follow an entrepreneurial case programme in our study by conducting observations of and interviews with 26 persons involved in the programme. Our findings are that participants consider the programme as an important contribution to the local/regional entrepreneurial ecosystem. However, it is also described as a short-lived ecosystem, from which the participants mostly benefit while on the programme and to a lesser degree afterwards. Sustainability plays a part in attracting participants but to a lesser degree forms the educational content and evaluation parameters. Our study contributes to the discussion of how education through entrepreneurship is organised as an accelerator programme to help start-ups in a rural context.
Climate Change along the Silk Road and Its Influence on Scythian Cultural Expansion and Rise of the Mongol Empire
Authors: Che Ping , Lan Jianghu
Published: February 2021

Climate change and cultural exchange both influenced cultural development along the continental Silk Road during the late Holocene, but climate change and its influence on nomadic civilizations during that time has yet to be systematically assessed. In this study, we analyzed records of climate change along the Silk Road covering key periods in the late Holocene, based on multiproxies from various archives including lake sediments, shorelines/beach ridges, peatlands, ice cores, tree rings, aeolian sediments, moraines, and historical documents. Combined with archaeological data, we assessed the influence of climate on development and expansion of representative pastoral nomadism. Our results show that the most notable climate changes in Central Asia were characterized by decreasing temperature, expanding glaciers, increasing precipitation, and increasing humidity during transitions from the Sub-Boreal to Sub-Atlantic Period (ca. 9–8th century BC) and from the Medieval Warm Period to the Little Ice Age (ca. 13–14th century AD). The two periods coincided with Scythian Cultural expansion across the steppe landscape of Central Asia and rise of the Mongol Empire, respectively. These temporal coincidences are interpreted as causally related, where temperature fall and glacial advance may have forced the pastoral nomadism to southward migration. Coeval wetness and southward migration of steppe landscape in Central Asia were beneficial for these cultural expansions, which spanned the Eurasian arid and semi-arid zone westward. Therefore, during the historical period when productivity was underdeveloped, although expansions of pastoral nomadism were closely related to internal social structures, climate change was possibly the most critical controlling factor for sustainability development and collapse.
Does Corporate Financialization Have a Non-Linear Impact on Sustainable Total Factor Productivity? Perspectives of Cash Holdings and Technical Innovation
Authors: Wang Hui , Wang Qing , Sheng Xia
Published: February 2021

This study explores the conditions under which financialization may foster sustainable total factor productivity (TFP). We examine the inverted U-shaped relationship between corporate financialization and TFP by employing a panel threshold model using microeconomic non-financial panel data from Chinese firms in the 2007 to 2018 period. Our results suggest that the turning point is more significant in holding short-term financial assets and state-owned enterprises. The threshold effect suggests that technical innovation determines the optimal threshold at which TFP is affected by financialization. Further, financialization is considered an alternative to cash in order to increase the value of capital, leading to a positive effect on TFP. Contrary to their positive effects below the optimal thresholds, financialization exceeds a certain level, displaces technical innovation, and becomes detrimental to TFP. Our analysis thus establishes the importance of sustainable growth of TFP and minimize the adverse effect of financialization.
Preferences and Tourism Development under Uncertainty: An Empirical Study
Authors: Lu Zhou , Li Haiwei , Lau Chi Keung Marco , Isah Aliyu Buhari
Published: February 2021

Using the Global Preferences Survey dataset, this paper examines the effects of six measures of preferences (altruism, negative reciprocity, patience, positive reciprocity, risk-taking, and trust) on the per capita international tourist arrivals and the per capita incoming tourist receipts. The data focus on 74 countries for the period from 1995 to 2019. The paper finds that citizens’ trust is positively related to tourism development, and its impact is statistically significant. This evidence indicates that a country with a higher level of trust in other nations’ people attracts more tourists and generates higher tourism receipts.
Intentions to Participate in Carsharing: The Role of Self- and Social Identity
Authors: Derikx Loes , van Lierop Dea
Published: February 2021

Carsharing is becoming an increasingly popular mode of transportation in many cities around the world. Previous research has revealed that users tend to be young, are highly educated, have high incomes and live in densely populated neighbourhoods. However, this does not explain why people who have similar socioeconomic characteristics do not adopt carsharing when residing in comparable urban contexts. To assess the critical differences between users and non-users of carsharing, the current research uses the theory of planned behaviour as a theoretical framework to analyse how aspects of an individual’s social and self-identity determine their intentions to participate in carsharing. In-person intercept questionnaire data were collected in the Berlin neighbourhoods Schloßstraße, Steglitz and Glasower Straße, Neukölln in the fall of 2019 (N = 216). Exploratory and confirmatory factor analysis and structural equation modelling were used to analyse the collected data. The model results suggest that having a pro-technology self-identity and negative pro-car identity are significantly associated with the intention to participate in carsharing. These associations are present in both the structural and alternative models. Moreover, both models indicate a negative relationship between individuals’ degree of environmental self-identity and the degree of their pro-car identity. The results suggest that, in order to promote carsharing, regional governments should focus on attracting new users who are currently already using mobility technology. The findings can be used by regional governments to identify potential carsharing users and to specifically target individuals who are likely to be willing to adopt and participate in carsharing.
Algorithmic Pricing and Price Gouging. Consequences of High-Impact, Low Probability Events
Authors: Sánchez-Cartas Juan Manuel , Tejero Alberto , León Gonzalo
Published: February 2021

Algorithmic pricing may lead to more efficient and contestable markets, but high-impact, low-probability events such as terror attacks or heavy storms may lead to price gouging, which may trigger injunctions or get sellers banned from platforms such as Amazon or eBay. This work addresses how such events may impact prices when set by an algorithm and how different markets may be affected. We analyze how to mitigate these high-impact events by paying attention to external (market conditions) and internal (algorithm design) features surrounding the algorithms. We find that both forces may help in partially mitigating price gouging, but it remains unknown which forces or features may lead to complete mitigation.
Exploring the Impact of the COVID-19 Pandemic on University Students’ Learning Life: An Integrated Conceptual Motivational Model for Sustainable and Healthy Online Learning
Authors: Al-Kumaim Nabil Hasan , Alhazmi Abdulsalam K. , Mohammed Fathey , Gazem Nadhmi A. , Shabbir Muhammad Salman , Fazea Yousef
Published: February 2021

The COVID-19 pandemic has forced many organizations around the world to make full use of a variety of emerging online communication platform technologies. Universities are among the organizations that have asked students, tutors, and lecturers to use a number of different online communication platforms to ensure the education process remains uninterrupted. However, the COVID-19 pandemic has generated considerable challenges for the global higher education community while using such emerging technologies. This research has two main goals. First, this paper will begin by investigating whether the online learning platforms used by university students during the COVID-19 period have presented any challenges to their learning. Second, the paper will then go on to address proposed solutions by developing a conceptual model to reduce the impact of such challenges. This research uses an exploratory qualitative research approach, supported by literature content analysis techniques. The data set for this study was collected during the first peak of the pandemic period in Malaysia, between the 16th of May 2020 and the 5th of June 2020. We used SPSS to conduct a descriptive analysis and NVivo12 to analyse data collected from 486 students from different universities in Malaysia. These students disclosed various obstacles they encountered when they used IT platform applications for online learning. These obstacles include (a) work and information overload received from instructors, (b) inadaptability and unfamiliarity of the new online learning environment, and (c) personal health challenges related to stress and anxiety. Based on previous relevant research, this study introduced a set of motivational factors and developed a conceptual motivational model for sustainable and healthy online learning.
A Systematic Literature Review of the IT-Based Supply Chain Management System: Towards a Sustainable Supply Chain Management Model
Authors: Chiang Chang-Tang , Kou Tun-Chih , Koo Tian-Lih
Published: February 2021

The concept of sustainability has been highly valued by all aspects of life, while the supply chain plays a critical role in production and logistics. Supply chain management (SCM) is continuously transformed by information technology (IT). The purpose of this study is to review and discuss the effect of information technology-based SCM on sustainability. This paper conducted a systematic literature review by collecting author-anchored keywords from peer-reviewed articles on IT-based supply chain management. A total of 1264 articles and 2575 keywords from eleven supply chain-related journals were analysed with social network analysis. A knowledge map with ten research hot topics was identified. Additionally, a sustainable supply chain management (SSCM) model is developed not only to guide researchers to further understand IT-based SCM topical and structural meanings but also to contribute to enlightening a coherent and rigorous body of theories relevant to academics and supply chain and logistics managers interested in SSCM.
Digital Certificate Verification Scheme for Smart Grid using Fog Computing (FONICA)
Authors: Mahmood Shahid , Gohar Moneeb , Choi Jin-Ghoo , Koh Seok-Joo , Alquhayz Hani , Khan Murad
Published: February 2021

Smart Grid (SG) infrastructure is an energy network connected with computer networks for communication over the internet and intranets. The revolution of SGs has also introduced new avenues of security threats. Although Digital Certificates provide countermeasures, however, one of the issues that exist, is how to efficiently distribute certificate revocation information among Edge devices. The conventional mechanisms, including certificate revocation list (CRL) and online certificate status protocol (OCSP), are subjected to some limitations in energy efficient environments like SG infrastructure. To address the aforementioned challenges, this paper proposes a scheme incorporating the advantages and strengths of the fog computing. The fog node can be used for this purpose with much better resources closer to the edge. Keeping the resources closer to the edge strengthen the security aspect of smart grid networks. Similarly, a fog node can act as an intermediate Certification Authority (CA) (i.e., Fog Node as an Intermediate Certification Authority (FONICA)). Further, the proposed scheme has reduced storage, communication, processing overhead, and latency for certificate verification at edge devices. Furthermore, the proposed scheme reduces the attack surface, even if the attacker becomes a part of the network.
Carbon Footprint Comparative Analysis of Cardboard and Plastic Containers Used for the International Transport of Spanish Tomatoes
Authors: Lo-Iacono-Ferreira Vanesa G. , Viñoles-Cebolla Rosario , Bastante-Ceca María José , Capuz-Rizo Salvador F.
Published: February 2021

Agricultural packaging has a direct impact on the environmental performance of food. The carbon footprint (CF) of two of the most used packaging systems for international transport by road of fruit and vegetables is assessed and compared. Corrugated cardboard boxes (CCB) and polypropylene foldable boxes (PPB) in two different sizes are the object of this study. For the reusable boxes, three different scenarios are considered regarding the number of uses of each box (20, 50, and 100 uses). Product CF ISO 14067:2018 standard is applied, and requirements of ISO 14026:2017 and ISO 14044:2006 are met for a cradle-to-grave CF analysis. Product distribution and return of the empty box are the stages with the most significant impact for PPB over the manufacturing stage. CCB that does not have any returning stage or requirements of sanitation has its main impact in manufacturing. The comparison between both packaging systems of the same size, considering the functional unit and defined scope, points out CCB has a lower CF than PPB.
Effects of Grassland Conversion in the Chinese Chernozem Region on Soil Carbon, Nitrogen, and Phosphorus
Authors: Li Chunli , Dong Guotao , Sui Biao , Wang Hongbin , Zhao Lanpo
Published: February 2021

Converting natural vegetation to other types of land utilization is presently the most common land use change around the world. Conversion of grassland plays an important role in estimating the regional nutrients budget and assessing ecological effects. However, few studies have estimated the impacts of grassland conversion on soil nutrients under different soil pedogenic horizons. This study selected three sites, which were covered by grassland, shelterbelt, and cropland. The study evaluated the effects of grassland conversion and soil pedogenic horizon (to a depth of 100 cm) on the soil organic carbon (SOC), soil total nitrogen (STN), and soil total phosphorus (STP) concentrations and stocks in the Chinese Chernozem region. The results revealed that significant (p < 0.05) differences were seen after grassland conversion for concentrations and stocks of SOC, STN, and STP. The transformation from grassland to shelterbelt and cropland plantations caused soil carbon and soil nitrogen losses but caused soil phosphorus accumulations. Moreover, conversion of grassland made SOC, STN, and STP all drop below the Bk-horizon. Changes in the SOC and STP on an area basis were the greatest after conversion of grassland to cropland, for concentrations of −16% and 26% and for stocks of −15% and 32%, respectively. Land use change and soil pedogenic horizon primarily influenced the distribution patterns of nutrients concentrations and stocks. However, grassland conversion effects on nutrients were mainly at surface horizons. Soil properties, such as calcium carbonate (CaCO3) and soil texture, affected the nutrients from the Bk-horizon to the C-horizon. This study indicates that land use management policies should protect natural grasslands to minimize losses of SOC, STN, and STP.
Hazardous Solid Waste Confined in Closed Dump of Morelia: An Urgent Environmental Liability to Attend in Developing Countries
Authors: González-Arqueros M. Lourdes , Domínguez-Vázquez Gabriela , Alfaro-Cuevas-Villanueva Ruth , Israde-Alcántara Isabel , Buenrostro-Delgado Otoniel
Published: February 2021

In developing countries, landfills of urban solid waste (USW) are a major source of contamination. One reason is the common practice of the illegal confinement of hazardous waste (HW). The contamination is mainly due to deficitary design location, operation and lack of liner, which enables the dispersion of pollutants. The aim of our work is to demonstrate the presence of heavy metals (HM) and arsenic (As) in USW of the closed dump of Morelia, which clandestinely confined HW for 20 years. Solid samples of USW were collected from eight opencast wells with different age of confinement. Composition, degradation status, physical-chemical characterization and analysis of HM and As were carried out. The results showed the presence of Pb, Cu, Ni, Zn, Cr, Fe and high concentrations of As. This study provides evidence about the usual and illegal practice of landfill HW together with USW; the hazard due to the presence of HM and As; the deficiency in the operation and closure; and, the lack of competent legislation on the subject. This information is essential to establish background information for improving laws and help decision makers in territorial planning to improve public and environment health.
Influences on Teachers’ Intention to Apply Classroom Management Strategies for Students with ADHD: A Model Analysis
Authors: Strelow Anna Enrica , Dort Martina , Schwinger Malte , Christiansen Hanna
Published: February 2021

Students with attention deficit/hyperactivity disorder (ADHD) show reduced on-task behavior at school and educational problems due to the symptoms associated with this diagnosis. Classroom management strategies (CMS) are important to reduce impairment due to ADHD symptoms but are not yet well implemented. In this study we analyzed whether the facilitators and barriers regarding the intention to apply CMS identified for pre-service teachers are replicable in a sample of teachers in service. Overall, 599 teachers in service completed an online survey on the intention to apply CMS, their attitude towards CMS and towards students with ADHD, direct experiences, individual differences, and social influences. We calculated path models that significantly clarified variance in the intention to apply CMS (R2intention to use effective CMS = 0.47, p < 0.01 and R2intention to use ineffective CMS = 0.39, p < 0.01). It turns out that similar variables are relevant to teachers in service as well as pre-service teachers. A models’ extension to include variables that do justice to the difference between the two groups, such as work experience, shows a better model fit. Especially, attitude towards CMS, attitude towards students with ADHD, strain, perceived behavioral control and teachers’ affiliation with primary or special needs schools are important variables regarding the intention to apply CMS. The implementation of effective and elimination of ineffective CMS should thus be addressed by targeting teacher’s attitudes towards children with ADHD. Furthermore, strain prevention and education might enhance the application of effective CMS.
Optimization Model for the Pavement Pothole Repair Problem Considering Consumable Resources
Authors: Liu Shu-Shun , Budiwirawan Agung , Arifin Muhammad Faizal Ardhiansyah , Chen Wei Tong , Huang Ying-Hua
Published: February 2021

When heavy rain strikes Taiwan, it always results in cracks in road pavement, and damages arising from potholes. Tremendously compromising road safety, road users may have fatal accidents caused by untimely repair actions. The road maintenance department needs to take the responsibilities for road sections in the form of inspections and faces the decision about how to properly allocate available resources to repair pavement damages immediately. When performing pavement repair works, we need to consider the resource consumption behavior and explore the mechanism of replenishing resources and calculating the return time. Therefore, in order to help maintenance units to deal with consumable resource issues, this study proposes a novel approach to offer the mechanism of consumable resource calculation, which is difficult to solve through the traditional vehicle routing problem (VRP) approach. This proposed model treats the pothole repair problem as a resource-constrained project scheduling problem (RCPSP), which is capable of resolving such consumable resource considerations. The proposed model was developed by adopting constraint programming (CP) techniques. Research results showed that the proposed model is capable of providing the optimal decisions of pavement pothole repair tasks and also meets practical requirements to make appropriate adjustment, and helps the maintenance unit to shorten total repair duration and optimize resource assignment decisions of pavement maintenance objectives.
New Theorems for Oscillations to Differential Equations with Mixed Delays
Authors: Santra Shyam Sundar , Majumder Debasish , Bhattacharjee Rupak , Bazighifan Omar , Khedher Khaled Mohamed , Marin Marin
Published: February 2021

The oscillation of differential equations plays an important role in many applications in physics, biology and engineering. The symmetry helps to deciding the right way to study oscillatory behavior of solutions of this equations. The purpose of this article is to establish new oscillatory properties which describe both the necessary and sufficient conditions for a class of nonlinear second-order differential equations with neutral term and mixed delays of the form p(ι)w′(ι)α′+r(ι)uβ(ν(ι))=0,ι≥ι0 where w(ι)=u(ι)+q(ι)u(ζ(ι)). Furthermore, examining the validity of the proposed criteria has been demonstrated via particular examples.
Plant Age Has a Minor Effect on Non-Destructive Leaf Area Calculations in Moso Bamboo (Phyllostachys edulis)
Authors: Huang Lichao , Niinemets Ülo , Ma Jianzhong , Schrader Julian , Wang Rong , Shi Peijian
Published: February 2021

Leaf area is among the most important leaf functional traits, and it determines leaf temperature and alters light harvesting. The calculation of individual leaf area is the basis of calculating the leaf area index (i.e., the total leaf area per unit ground area) that is directly associated with the ability of plants to intercept light for photosynthesis. It is valuable to provide a fast and reliable approach to measuring leaf area. Here, we examined the validity and calculation accuracy of the Montgomery equation (ME), which describes the area of a leaf as a product of leaf length, width and a specific coefficient referred to as the Montgomery parameter, MP. Using ME, we calculated leaf areas of different age groups of bamboo culms. For most broad-leaved plants, leaf area is proportional to the product of leaf length and width, and MP falls within a range of 1/2 to π/4, depending on leaf shape. However, it is unknown whether there is an intra-specific variation in MP resulting from age structure and whether such a variation can significantly reduce the predictability of ME in calculating leaf area. This is relevant as a population of perennial plants usually composes of different age groups. We used Moso bamboos as model as this species is of ecological and economic importance in southern China, and pure stands can cover six to seven plant age groups. We used five age groups of moso bamboo and sampled 260–380 leaves for each group to test whether ME holds true for each group and all groups combined, whether there are significant differences in MP among different age groups, and whether the differences in MP can lead to large prediction errors for leaf area. We observed that for each age group and all groups combined, there were significant proportional relationships between leaf area and the product of leaf length and width. There were small but significant differences in MP among the five age groups (MP values ranged from 0.6738 to 0.7116 for individual plant ages; MP = 0.6936 for all age groups combined), which can be accounted for by the minor intergroup variation of leaf shape (reflected by the leaf width/length ratio). For all age classes, MP estimated for the pooled data resulted in <4% mean absolute percentage error, indicating that the effect of variation in MP among different age groups was small. We conclude that ME can serve as a useful tool for accurate calculations of leaf area in moso bamboo independent of culm age, which is valuable for estimation of leaf area index as well as evaluating the productivity and carbon sequestration capacity of bamboo forests.
Non-Destructive Fast Estimation of Tree Stem Height and Volume Using Image Processing
Authors: Coelho João , Fidalgo Beatriz , Crisóstomo Manuel M. , Salas-González Raúl , Coimbra A. Paulo , Mendes Mateus
Published: February 2021

Measuring biometric tree characteristics to estimate the volume of wood in a forest area is a time consuming task. It is usually performed by a team of two or more people, who measure the diameter and height of several trees in sampling plots. The results are then extrapolated for the forest stand. The present paper describes a method which facilitates estimating tree biometric parameters using computational techniques. A camera takes two pictures of each sample tree, with an especially designed target placed close to the tree, to facilitate image processing and camera calibration steps. Taking advantage of the trees’ natural shape and assuming a symmetric stem, the diameter and height of the tree stems are estimated from the images and the volumes of the tree stems are calculated. Experimental trials show promising results, exhibiting errors similar to the traditional methods used currently, in the range of 10%, showing that the method is suitable for forest inventory.
An Inertial Algorithm for Solving Hammerstein Equations
Authors: Chidume Charles E. , Adamu Abubakar , Nnakwe Monday O.
Published: February 2021

An inertial algorithm for solving Hammerstein equations is presented. This algorithm is obtained as a consequence of a new inertial algorithm proposed and studied for solving nonlinear equations involving operators that are m-accretive. Some strong convergence theorems are proved in real Banach spaces that are uniformly smooth. Furthermore, comparisons of the numerical performance of our algorithms with the numerical performance of some recent important algorithms are presented.
A Primer on Design Aspects and Recent Advances in Shuffle Exchange Multistage Interconnection Networks
Authors: Amodu Oluwatosin Ahmed , Othman Mohamed , Yunus Nur Arzilawati Md , Hanapi Zurina Mohd
Published: February 2021

Interconnection networks provide an effective means by which components of a system such as processors and memory modules communicate to provide reliable connectivity. This facilitates the realization of a highly efficient network design suitable for computational-intensive applications. Particularly, the use of multistage interconnection networks has unique advantages as the addition of extra stages helps to improve the network performance. However, this comes with challenges and trade-offs, which motivates researchers to explore various design options and architectural models to improve on its performance. A particular class of these networks is shuffle exchange network (SEN) which involves a symmetric N-input and N-output architecture built in stages of N/2 switching elements each. This paper presents recent advances in multistage interconnection networks with emphasis on SENs while discussing pertinent issues related to its design aspects, and taking lessons from the past and current literature. To achieve this objective, applications, motivating factors, architectures, shuffle exchange networks, and some of the performance evaluation techniques as well as their merits and demerits are discussed. Then, to capture the latest research trends in this area not covered in contemporary literature, this paper reviews very recent advancements in shuffle exchange multistage interconnection networks within the last few years and provides design guidelines as well as recommendations for future consideration.
Spatial Moduli of Non-Differentiability for Time-Fractional SPIDEs and Their Gradient
Authors: Wang Wensheng
Published: February 2021

High order and fractional PDEs have become prominent in theory and in modeling many phenomena. In this paper, we study spatial moduli of non-differentiability for the fourth order time fractional stochastic partial integro-differential equations (SPIDEs) and their gradient, driven by space-time white noise. We use the underlying explicit kernels and spectral/harmonic analysis, yielding spatial moduli of non-differentiability for time fractional SPIDEs and their gradient. On one hand, this work builds on the recent works on delicate analysis of regularities of general Gaussian processes and stochastic heat equation driven by space-time white noise. On the other hand, it builds on and complements Allouba and Xiao’s earlier works on spatial uniform and local moduli of continuity of time fractional SPIDEs and their gradient.
Detecting Tourism Typologies of Regional Destinations Based on Their Spatio-Temporal and Socioeconomic Performance: A Correlation-Based Complex Network Approach for the Case of Greece
Authors: Tsiotas Dimitrios , Krabokoukis Thomas , Polyzos Serafeim
Published: February 2021

Within the context that tourism-seasonality is a composite phenomenon described by temporal, geographical, and socio-economic aspects, this article develops a multilevel method for studying time patterns of tourism-seasonality in conjunction with its spatial dimension and socio-economic dimension. The study aims to classify the temporal patterns of seasonality into regional groups and to configure distinguishable seasonal profiles facilitating tourism policy and development. The study applies a multilevel pattern recognition approach incorporating time-series assessment, correlation, and complex network analysis based on community detection with the use of the modularity optimization algorithm, on data of overnight-stays recorded for the time-period 1998–2018. The analysis reveals four groups of seasonality, which are described by distinct seasonal, geographical, and socio-economic profiles. Overall, the analysis supports multidisciplinary and synthetic research in the modeling of tourism research and promotes complex network analysis in the study of socio-economic systems, by providing insights into the physical conceptualization that the community detection based on the modularity optimization algorithm can enjoy to the real-world applications.
Imaging Techniques to Study Plant Virus Replication and Vertical Transmission
Authors: Sánchez Pina María Amelia , Gómez-Aix Cristina , Méndez-López Eduardo , Gosalvez Bernal Blanca , Aranda Miguel A.
Published: February 2021

Plant viruses are obligate parasites that need to usurp plant cell metabolism in order to infect their hosts. Imaging techniques have been used for quite a long time to study plant virus–host interactions, making it possible to have major advances in the knowledge of plant virus infection cycles. The imaging techniques used to study plant–virus interactions have included light microscopy, confocal laser scanning microscopy, and scanning and transmission electron microscopies. Here, we review the use of these techniques in plant virology, illustrating recent advances in the area with examples from plant virus replication and virus plant-to-plant vertical transmission processes.
RNA Helicase A Regulates the Replication of RNA Viruses
Authors: Shi Rui-Zhu , Pan Yuan-Qing , Xing Li
Published: February 2021

The RNA helicase A (RHA) is a member of DExH-box helicases and characterized by two double-stranded RNA binding domains at the N-terminus. RHA unwinds double-stranded RNA in vitro and is involved in RNA metabolisms in the cell. RHA is also hijacked by a variety of RNA viruses to facilitate virus replication. Herein, this review will provide an overview of the role of RHA in the replication of RNA viruses.
Rescue of Infectious Rotavirus Reassortants by a Reverse Genetics System Is Restricted by the Receptor-Binding Region of VP4
Authors: Falkenhagen Alexander , Huyzers Marno , van Dijk Alberdina A. , Johne Reimar
Published: February 2021

The rotavirus species A (RVA) capsid contains the spike protein VP4, which interacts with VP6 and VP7 and is involved in cellular receptor binding. The capsid encloses the genome consisting of eleven dsRNA segments. Reassortment events can result in novel strains with changed properties. Using a plasmid-based reverse genetics system based on simian RVA strain SA11, we previously showed that the rescue of viable reassortants containing a heterologous VP4-encoding genome segment was strain-dependent. In order to unravel the reasons for the reassortment restrictions, we designed here a series of plasmids encoding chimeric VP4s. Exchange of the VP4 domains interacting with VP6 and VP7 was not sufficient for rescue of viable viruses. In contrast, the exchange of fragments encoding the receptor-binding region of VP4 resulted in virus rescue. All parent strains and the rescued reassortants replicated efficiently in MA-104 cells used for virus propagation. In contrast, replication in BSR T7/5 cells used for plasmid transfection was only efficient for the SA11 strain, whereas the rescued reassortants replicated slowly, and the parent strains failing to produce reassortants did not replicate. While future research in this area is necessary, replication in BSR T7/5 cells may be one factor that affects the rescue of RVAs.
The Role of the Host Ubiquitin System in Promoting Replication of Emergent Viruses
Authors: Valerdi Karl M. , Hage Adam , van Tol Sarah , Rajsbaum Ricardo , Giraldo Maria I.
Published: February 2021

Ubiquitination of proteins is a post-translational modification process with many different cellular functions, including protein stability, immune signaling, antiviral functions and virus replication. While ubiquitination of viral proteins can be used by the host as a defense mechanism by destroying the incoming pathogen, viruses have adapted to take advantage of this cellular process. The ubiquitin system can be hijacked by viruses to enhance various steps of the replication cycle and increase pathogenesis. Emerging viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), flaviviruses like Zika and dengue, as well as highly pathogenic viruses like Ebola and Nipah, have the ability to directly use the ubiquitination process to enhance their viral-replication cycle, and evade immune responses. Some of these mechanisms are conserved among different virus families, especially early during virus entry, providing an opportunity to develop broad-spectrum antivirals. Here, we discuss the mechanisms used by emergent viruses to exploit the host ubiquitin system, with the main focus on the role of ubiquitin in enhancing virus replication.
An Innovative Hourly Water Demand Forecasting Preprocessing Framework with Local Outlier Correction and Adaptive Decomposition Techniques
Authors: Hu Shiyuan , Gao Jinliang , Zhong Dan , Deng Liqun , Ou Chenhao , Xin Ping
Published: February 2021

Accurate forecasting of hourly water demand is essential for effective and sustainable operation, and the cost-effective management of water distribution networks. Unlike monthly or yearly water demand, hourly water demand has more fluctuations and is easily affected by short-term abnormal events. An effective preprocessing method is needed to capture the hourly water demand patterns and eliminate the interference of abnormal data. In this study, an innovative preprocessing framework, including a novel local outlier detection and correction method Isolation Forest (IF), an adaptive signal decomposition technique Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), and basic forecasting models have been developed. In order to compare a promising deep learning method Gated Recurrent Unit (GRU) as a basic forecasting model with the conventional forecasting models, Support Vector Regression (SVR) and Artificial Neural Network (ANN) have been used. The results show that the proposed hybrid method can utilize the complementary advantages of the preprocessing methods to improve the accuracy of the forecasting models. The root-mean-square error of the SVR, ANN, and GRU models has been reduced by 57.5%, 27.8%, and 30.0%, respectively. Further, the GRU-based models developed in this study are superior to the other models, and the IF-CEEMDAN-GRU model has the highest accuracy. Hence, it is promising that this preprocessing framework can improve the performance of the water demand forecasting models.
Selection of Optimum Pollution Load Reduction and Water Quality Improvement Approaches Using Scenario Based Water Quality Modeling in Little Akaki River, Ethiopia
Authors: Angello Zelalem , Behailu Beshah , Tränckner Jens
Published: February 2021

The collective impacts of rapid urbanization, poor pollution management practices and insufficient sanitation infrastructure have driven the water quality deterioration in Little Akaki River (LAR), Ethiopia. Water quality modeling using QUAL2Kw was conducted in the LAR aimed at selecting the optimal water quality improvement and pollution load reduction approaches based on the evaluation of five scenarios: modification of point sources (PS) load (S1), modification of nonpoint sources (NPS) load (S2), simultaneous modification of PS and NPS load (S3), application of local oxygenators and fish passages using cascaded rock ramps (S4), and an integrated scenario (S5). Despite the evaluation of S1 resulting in an average load reduction of Biochemical Oxygen Demand (BOD) (17.72%), PO4-P (37.47%), NO3-N (19.63%), the water quality objective (WQO) in LAR could not be attained. Similarly, though significant improvement of pollution load was found by S2 and S3 evaluation, it did not secure the permissible BOD and PO4-P pollution load in the LAR. Besides, as part of an instream measure, a scenario evaluated using the application of rock ramps (S4) resulted in significant reduction of BOD load. All the individual scenarios were not successful and hence an integration of scenarios (S5) was evaluated in LAR that gave a relatively higher pollutant load reduction rate and ultimately was found a better approach to improve pollution loads in the river. In conclusion, pollution load management and control strategy integrally incorporating the use of source-based wastewater treatment, control of diffuse pollution sources through the application of best management practices and the application of instream measures such as the use of cascaded rock ramps could be a feasible approach for better river water quality management, pollution reduction, aquatic life protection and secure sustainable development in the LAR catchment.
Water Leak Localization Using High-Resolution Pressure Sensors
Authors: Levinas Daniel , Perelman Gal , Ostfeld Avi
Published: February 2021

A new method for identifying a leaking pipe within a pressurized water distribution system is presented. This novel approach utilizes transient modeling to analyze water networks. Urban water supply networks are important infrastructure that ensures the daily water consumption of urban residents and industrial sites. The aging and deterioration of drinking water mains is the cause of frequent burst pipes, thus making the detection and localization of these bursts a top priority for water distribution companies. Here we describe a novel method based on transient modeling of the water network and produces high-resolution pressure response under various scenarios. Analyzing this data allows the prediction of the leaking pipe. The transient pressure data is classified as leaking pipes or no leak clusters using the K-nearest neighbors (K-NN) algorithm. The transient model requires a massive computation effort to simulate the network’s performance. The classification model presented good performance with an overall accuracy of 0.9 for the basic scenarios. The lowest accuracy was obtained for interpolated scenarios the model had not been trained on; in this case, the accuracy was 0.52.
Living and Prototyping Digital Twins for Urban Water Systems: Towards Multi-Purpose Value Creation Using Models and Sensors
Authors: Pedersen Agnethe N. , Borup Morten , Brink-Kjær Annette , Christiansen Lasse E. , Mikkelsen Peter S.
Published: February 2021

In this paper, we review the emerging concept of digital twins (DTs) for urban water systems (UWS) based on the literature, stakeholder interviews and analyzing the current DT implementation process in the utility company VCS Denmark (VCS). Here, DTs for UWS are placed in the context of DTs at the component, unit process/operation or hydraulic structure, treatment plant, system, city, and societal levels. A UWS DT is characterized as a systematic virtual representation of the elements and dynamics of the physical system, organized in a star-structure with a set of features connected by data links that are based on standards for open data. This allows the overall functionality to be broken down into smaller, tangible units (features), enabling microservices that communicate via data links to emerge (the most central feature), facilitated by application programing interfaces (APIs). Coupled to the physical system, simulation models and advanced analytics are among the most important features. We propose distinguishing between living and prototyping DTs, where the term “living” refers to coupling observations from an ever-changing physical twin (which may change with, e.g., urban growth) with a simulation model, through a data link connecting the two. A living DT is thus a near real-time representation of an UWS and can be used for operational and control purposes. A prototyping DT represents a scenario for the system without direct coupling to real-time observations, which can be used for design or planning. By acknowledging that different DTs exist, it is possible to identify the value-creation from DTs achieved by different end-users inside and outside a utility organization. Analyzing the DT workflow in VCS shows that a DT must be multifunctional, updateable, and adjustable to support potential value creation across the utility company. This study helps clarify key DT terminology for UWS and identifies steps to create a DT by building upon digital ecosystems (DEs) and open standards for data.
Climate Change Patterns of Wild Blueberry Fields in Downeast, Maine over the Past 40 Years
Authors: Tasnim Rafa , Drummond Francis , Zhang Yong-Jiang
Published: February 2021

Maine, USA is the largest producer of wild blueberries (Vaccinium angustifolium Aiton), an important native North American fruit crop. Blueberry fields are mainly distributed in coastal glacial outwash plains which might not experience the same climate change patterns as the whole region. It is important to analyze the climate change patterns of wild blueberry fields and determine how they affect crop health so fields can be managed more efficiently under climate change. Trends in the maximum (Tmax), minimum (Tmin) and average (Tavg) temperatures, total precipitation (Ptotal), and potential evapotranspiration (PET) were evaluated for 26 wild blueberry fields in Downeast Maine during the growing season (May–September) over the past 40 years. The effects of these climate variables on the Maximum Enhanced Vegetation Index (EVImax) were evaluated using Remote Sensing products and Geographic Information System (GIS) tools. We found differences in the increase in growing season Tmax, Tmin, Tavg, and Ptotal between those fields and the overall spatial average for the region (state of Maine), as well as among the blueberry fields. The maximum, minimum, and average temperatures of the studied 26 wild blueberry fields in Downeast, Maine showed higher rates of increase than those of the entire region during the last 40 years. Fields closer to the coast showed higher rates of warming compared with the fields more distant from the coast. Consequently, PET has been also increasing in wild blueberry fields, with those at higher elevations showing lower increasing rates. Optimum climatic conditions (threshold values) during the growing season were explored based on observed significant quadratic relationships between the climate variables (Tmax and Ptotal), PET, and EVImax for those fields. An optimum Tmax and PET for EVImax at 22.4 °C and 145 mm/month suggest potential negative effects of further warming and increasing PET on crop health and productivity. These climate change patterns and associated physiological relationships, as well as threshold values, could provide important information for the planning and development of optimal management techniques for wild blueberry fields experiencing climate change.