bluuebunny/crossref_metadata_2025 huggingface dataset:
Day Ahead Optimal Dispatch Schedule in a Smart Grid Containing Distributed Energy Resources and Electric Vehicles
Authors: Fotopoulou Maria , Rakopoulos Dimitrios , Blanas Orestis
Published: November 2021

This paper presents a day ahead optimal dispatch method for smart grids including two-axis tracking photovoltaic (PV) panels, wind turbines (WT), a battery energy storage system (BESS) and electric vehicles (EV), which serve as additional storage systems in vehicle to grid (V2G) mode. The aim of the day ahead schedule is the minimization of fuel-based energy, imported from the main grid. The feasibility of the proposed method lies on the extensive communication network of the smart grids, including sensors and metering devices, that provide valuable information regarding the production of the distributed energy resources (DER), the energy consumption and the behavior of EV users. The day ahead optimal dispatch method is applied on a smart grid in order to showcase its effectiveness in terms of sustainability, full exploitation of DER production and ability of EVs to act as prosumers.
Learning a Transform Base for the Multi- to Hyperspectral Sensor Network with K-SVD
Authors: Hänel Thomas , Jarmer Thomas , Aschenbruck Nils
Published: November 2021

A promising low-cost solution for monitoring spectral information, e.g., on agricultural fields, is that of wireless sensor networks. In contrast to remote sensing, these can achieve more continuous monitoring due to their long-term deployment and are less impacted by the atmosphere, making them a promising solution for the calibration of satellite data. In this paper, we explore an alternative approach for processing data from such a network. Hyperspectral sensors were found to be too complex for such a network. While previous work considered fusing the data from different multispectral sensors in order to derive hyperspectral data, we shift the assessment of the hyperspectral modeling in a separate preprocessing step based on machine learning. We then use the learned data as additional input while using identical multispectral sensors, further reducing the complexity of the sensors. Despite requiring careful parametrization, the approach delivers hyperspectral data of similar and in some cases even better quality.
Flame-Made La2O3-Based Nanocomposite CO2 Sensors as Perspective Part of GHG Monitoring System
Authors: Andreev Matvey , Platonov Vadim , Filatova Darya , Galitskaya Elena , Polomoshnov Sergey , Generalov Sergey , Nikolaeva Anastasiya , Amelichev Vladimir , Zhdaneev Oleg , Krivetskiy Valeriy , Rumyantseva Marina
Published: November 2021

Continuous monitoring of greenhouse gases with high spatio-temporal resolution has lately become an urgent task because of tightening environmental restrictions. It may be addressed with an economically efficient solution, based on semiconductor metal oxide gas sensors. In the present work, CO2 detection in the relevant concentration range and ambient conditions was successfully effectuated by fine-particulate La2O3-based materials. Flame spray pyrolysis technique was used for the synthesis of sensitive materials, which were studied with X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), diffuse reflectance infrared Fourier transform spectroscopy (DRIFTs) and low temperature nitrogen adsorption coupled with Brunauer–Emmett–Teller (BET) effective surface area calculation methodology. The obtained materials represent a composite of lanthanum oxide, hydroxide and carbonate phases. The positive correlation has been established between the carbonate content in the as prepared materials and their sensor response towards CO2. Small dimensional planar MEMS micro-hotplates with low energy consumption were used for gas sensor fabrication through inkjet printing. The sensors showed highly selective CO2 detection in the range of 200–6667 ppm in humid air compared with pollutant gases (H2 50 ppm, CH4 100 ppm, NO2 1 ppm, NO 1 ppm, NH3 20 ppm, H2S 1 ppm, SO2 1 ppm), typical for the atmospheric air of urbanized and industrial area.
Towards Integration of Security and Safety Measures for Critical Infrastructures Based on Bayesian Networks and Graph Theory: A Systematic Literature Review
Authors: Pirbhulal Sandeep , Gkioulos Vasileios , Katsikas Sokratis
Published: November 2021

In recent times, security and safety are, at least, conducted in safety-sensitive or critical sectors. Nevertheless, both processes do not commonly analyze the impact of security risks on safety. Several scholars are focused on integrating safety and security risk assessments, using different methodologies and tools in critical infrastructures (CIs). Bayesian networks (BN) and graph theory (GT) have received much attention from academia and industries to incorporate security and safety features for different CI applications. Hence, this study aims to conduct a systematic literature review (SLR) for co-engineering safety and security using BN or GT. In this SLR, the preferred reporting items for systematic reviews and meta-analyses recommendations (PRISMA) are followed. Initially, 2295 records (acquired between 2011 and 2020) were identified for screening purposes. Later on, 240 articles were processed to check eligibility criteria. Overall, this study includes 64 papers, after examining the pre-defined criteria and guidelines. Further, the included studies were compared, regarding the number of required nodes for system development, applied data sources, research outcomes, threat actors, performance verification mechanisms, implementation scenarios, applicability and functionality, application sectors, advantages, and disadvantages for combining safety, and security measures, based on GT and BN. The findings of this SLR suggest that BN and GT are used widely for risk and failure management in several domains. The highly focused sectors include studies of the maritime industry (14%), vehicle transportation (13%), railway (13%), nuclear (6%), chemical industry (6%), gas and pipelines (5%), smart grid (5%), network security (5%), air transportation (3%), public sector (3%), and cyber-physical systems (3%). It is also observed that 80% of the included studies use BN models to incorporate safety and security concerns, whereas 15% and 5% for GT approaches and joint GT and BN methodologies, respectively. Additionally, 31% of identified studies verified that the developed approaches used real-time implementation, whereas simulation or preliminary analysis were presented for the remaining methods. Finally, the main research limitations, concluding remarks and future research directions, are presented
A Systematic Review of the Role of Road Network Pricing in Shaping Sustainable Cities: Lessons Learned and Opportunities for a Post-Pandemic World
Authors: Munir Tariq , Dia Hussein , Ghaderi Hadi
Published: November 2021

The growing number of studies on road network pricing requires adoption of systematic methodologies to assess research outcomes and provide an unbiased summary of research findings and lessons learned. This paper aims to identify and analyse primary studies related to a set of research questions on road network pricing that primarily address the effectiveness of road network pricing as a travel demand management strategy. The paper achieves this by consolidating the fragmented evidence on the topic and identifying the role of transport pricing in steering our post-pandemic cities on a path of sustainable urban mobility. The paper uses a reliable and auditable systematic approach to examine past and current research trends, resulting in a rational assessment of the role and impacts of road network pricing as a travel demand management strategy. The paper achieves this by performing a bibliometric citation analysis that identifies 105 articles of valuable research contributions that represent fundamental knowledge in the development of research covering the period between 2007 and 2020. Importantly, the review identifies four main research themes in the literature, namely implementation impacts, innovations in technology, acceptability, and modelling methodologies for determining impacts, that are core elements of the research effort on the travel demand management and sustainability aspects of road pricing. Inductive reasoning is then used to address emerging issues, applications, and the effects of road network pricing in reducing congestion and enhancing urban centre environmental quality. The paper concludes with a discussion of policy directions for overcoming barriers to the implementation of road network pricing as an effective strategy for addressing modern-day urban mobility challenges such as rising urban populations, emissions, and pollution particularly amid and post COVID-19. Finally, the paper provides a roadmap of future research opportunities that can heighten the role of road network pricing in shaping the directions of sustainable urban transport policies and strategies.
Ethics and Sustainable Management. An Empirical Modelling of Carroll’s Pyramid for the Italian Landscape
Authors: D’Avanzo Ernesto , Franch Mariangela , Borgonovi Elio
Published: November 2021

Business management and, more generally, decision makers, are increasingly aware of the importance of corporate social responsibility and ethical choices within the strategic business vision. The number of tools (e.g., board of directors, organization actions), levers (e.g., cultural, social example of direct boss) and rules (e.g., protocols, certifications, law decrees) available, however, makes it difficult for management to identify the set of best practices to be adopted within its own organization. Further, the task is even more difficult when management is called upon to choose these tools for life-long learning programs intended for company staff as well as for new hires. The Italian Association for Managerial Training has promoted a survey that pays particular attention to the «ethical choices» and «behaviors» to be adopted in the organization’s management and their training programs. The results of the survey have been modelled through «Carroll’s conceptual framework» that, as known, is made of two parts: the most cited CSR pyramid and the least mentioned, but equally important, descriptive types of management. In this work, it has been employed a two steps multivariate analysis, employing an Exploratory Factor Analysis (EFA) and a Structural Equation Modelling (SEM). EFA has been used to identify Carroll’s descriptive types (or profiles), while SEMs were employed to verify the plausibility of the causal models that represent, in turn, thought experiments simulating «ethical dilemmas» useful for the company’s management during its decision making. The models identified, readable in the form of simple «heuristics», are interpreted in the light of Carroll’s «descriptive types» of management (i.e., moral, immoral and amoral). Thereby, any organization, even of a small size, interested in adopting «sustainable policies», can make use of the identified models to establish which guidelines can be adopted by the management during her/his decision making, and, according to Carroll, «to isolate the ethical or moral component of CSR and relate it to perspectives that reflect the three major ethical approaches to management», with the overall objective of managing with «stakeholders in an ethical or moral fashion».
Diversity of Endophytic Fungi in Huperzia serrata and Their Acetylcholinesterase Inhibitory Activity
Authors: Lu Ziyun , Ma Yangshuai , Xiao Liting , Yang Huilin , Zhu Du
Published: November 2021

Huperzia serrata is a Huperzine A (HupA)-producing herb. HupA is a potent, reversible, highly specific, centrally active and selective acetylcholinesterase inhibitor, and is commonly used to improve Alzheimer’s disease.At present, H. serrata resources have been overexploited and their artificial cultivation has lagged behind the need, so the market demand cannot be met. In this study, the diversity of the endophytic fungi in H. serrata was studied by high-throughput sequencing and traditional culture methods. Furthermore, the ability of the isolated endophytic fungi to produce acetylcholinesterase-inhibiting activity was evaluated. The results related to the diversity of fungi between high-throughput sequencing and traditional culture methods were compared. With high-throughput sequencing, five phyla, 22 classes, 55 orders, 120 families, and 178 genera of fungi were detected in Hubei Province, and five phyla, 22 classes, 54 orders, 124 families, and 196 genera were detected in Fujian Province. After cultivation with traditional culture methods, two phyla, three classes, five orders, six families, and six genera were detected in Hubei, and one phylum, three classes, five orders, five families, and six genera in Fujian. The endophytic fungi of H. serrata are highly diverse, and the results of high-throughput sequencing comprehensively reflect their community compositions. When the acetylcholinesterase-inhibiting activity of the isolated and cultured endophytic fungi was determined, five and three endophytic fungi from Hubei and Fujian Provinces, respectively, had good inhibitory activity (inhibition rate > 50%). Most of them were separated from leaf tissue. The strain HBR-1 and strain FJL-5 had the strongest inhibitory effects on AChE, with inhibition rates of 72.34% and 60.54%, respectively. Although only a proportion of the endophytic fungi was isolated with traditional culture methods, metabolites with broad potential applications can be isolated from these fungal cultures. The combination of high-throughput sequencing and traditional culture methods can be used to isolate and purify endophytic fungi in a targeted manner, gain many endophytic fungi, and enrich the endophytic fungi resource library.
Can Current Earth Observation Technologies Provide Useful Information on Soil Organic Carbon Stocks for Environmental Land Management Policy?
Authors: Andries Ana , Morse Stephen , Murphy Richard J. , Lynch Jim , Mota Bernardo , Woolliams Emma R.
Published: November 2021

Earth Observation (EO) techniques could offer a more cost-effective and rapid approach for reliable monitoring, reporting, and verification (MRV) of soil organic carbon (SOC). Here, we analyse the available published literature to assess whether it may be possible to estimate SOC using data from sensors mounted on satellites and airborne systems. This is complemented with research using a series of semi-structured interviews with experts in soil health and policy areas to understand the level of accuracy that is acceptable for MRV approaches for SOC. We also perform a cost-accuracy analysis of the approaches, including the use of EO techniques, for SOC assessment in the context of the new UK Environmental Land Management scheme. We summarise the state-of-the-art EO techniques for SOC assessment and identify 3 themes and 25 key suggestions and concerns for the MRV of SOC from the expert interviews. Notably, over three-quarters of the respondents considered that a ‘validation accuracy’ of 90% or better would be required from EO-based techniques to be acceptable as an effective system for the monitoring and reporting of SOC stocks. The cost-accuracy analysis revealed that a combination of EO technology and in situ sampling has the potential to offer a reliable, cost-effective approach to estimating SOC at a local scale (4 ha), although several challenges remain. We conclude by proposing an MRV framework for SOC that collates and integrates seven criteria for multiple data sources at the appropriate scales.
Mapping Sustainable Diets: A Comparison of Sustainability References in Dietary Guidelines of Swiss Food Governance Actors
Authors: Teschner Ronja , Ruppen Jessica , Bornemann Basil , Emmenegger Rony , Sánchez Lucía Aguirre
Published: November 2021

With the growing recognition of the food system for a transformation toward sustainability, there is a need for future guidance on food consumption and policy. In particular, dietary guidelines (DGs) have received increasing attention as potential tools for enabling transformative change. This paper analyzes how and to what extent different state and non-state actors in Switzerland incorporate sustainability aspects in their dietary guidelines. It examines how these DGs account for different dimensions at the basis of sustainability thinking, including the classic environmental, economic, and social dimensions as well as issues of health and governance. Our analysis shows the explicit inclusion of sustainability aspects in all DGs of the chosen actors in Switzerland, addressing at least one sustainability category predominantly. Through the analysis of the different stakeholders, different areas of focus become apparent, with each stakeholder covering specific niches of sustainability. On this basis, the transformative role of non-state actors in developing the concept of sustainable diets is discussed.
Valuing User Preferences for Geospatial Fire Monitoring in Guatemala
Authors: Berenter Jared , Morrison Isaac , Mueller Julie M.
Published: November 2021

Like many landscapes across Central America, forests in Guatemala’s Maya Biosphere Reserve (MBR) are increasingly susceptible to forest fire, with most forest fires resulting from untended agricultural fires. Fire damage poses significant risk to the MBR’s natural resources and cultural heritage, but budget challenges limit the capacity of national, regional, and local institutions to effectively detect, monitor, and control forest fires. The Geospatial Information System for Fire Management (SIGMA-I) is a United States government-subsidized suite of geospatial fire management tools that are widely disseminated, free of charge, to land managers and other users in Guatemala for on-the-ground fire prevention and response. Provision of SIGMA-I geospatial data and tools such as daily thermal “hotspot” maps provide positive benefits for sustainable fire management. However, little research exists supporting the nonmarket monetary value of geospatial fire monitoring tools and their component features. We used a choice experiment to estimate land managers’ willingness to pay for individual attributes of SIGMA-I hotspot mapping in Guatemala. We found quantitative evidence of positive willingness to pay for geospatial data, demonstrating positive nonmarket value of geospatial data for sustainable fire management in developing countries and regions where agricultural fires are common. Our results indicate strong preferences from Guatemala’s forest fire management community for improving the frequency of hotspot reporting and reducing detection of erroneous hotspots. As the availability of geospatial data increases, use of tools like SIGMA-I has the potential to significantly improve fire management, especially in regions where funding and resources for fire management are scarce. Our results support continued multinational funding for tools like SIGMA-I for forest fire management in Guatemala and other developing countries.
Can the Current State Support Mechanisms Help the Growth of Renewable Energies in Wind Markets?
Authors: Morea Donato , Bittucci Lucilla , Cafaro Arturo , Mango Fabiomassimo , Murè Pina
Published: November 2021

The aim of this paper is to provide evidence on the effectiveness of the current state support mechanism incentive adopted by the Italian government in the wind market. In particular, this paper intends to investigate the effectiveness of the auction mechanism as an incentive tool for renewable sources as required by the transposition of Directive 2009/28/EC. In order to demonstrate the economic and financial feasibility of a typical wind-sector investment, we performed a scenario analysis (Monte Carlo simulation) determining a 52,500 Net Present Value (NPV) by varying the key underlying variables of the investment. The results show that with the mechanism currently in place the percentage of positive leveraged NPV is approximately equal to 70%. Despite the state contribution provided through the “Feed-in tariff” mechanism, the profitability of wind projects is not always successful, and this problem could be amplified by the slowness of the authorization procedures. The article offers prime reflections for scholars and policy makers who have long been committed to promoting sustainable development and important considerations on the introduction of further incentive models.
Development Path of Industrial Heritage Tourism: A Case Study of Kitakyushu (Japan)
Authors: Zhao Zhengyuan , Liu Zhigao
Published: November 2021

Industrial heritage tourism is aimed at promoting sustainable development in the regional social economy. Japan published Heritage Constellations of Industrial Modernization in 2007 and 2008, and treated them as an important resource to promote the activation of the local economy. Evolutionary economic geography offers a useful framework for studying the evolution of industries and has already been applied to study the different types of tourism destinations, what is often unclear, however, is under what conditions declining industrial cities can be transformed into an industrial heritage tourism destination and by whom. Thus, this article tries to employ the EEG approach to understand the development of industrial heritage tourism in Japan, using Kitakyushu City as a case. The case of Kitakyushu City illustrates the importance of initial conditions and stakeholder collaboration in promote the development of industrial heritage tourism. The results of this study also showed that participation of community residents and the application of new technologies, strong support from national and local governments are critical to the new path creation.
Sustainability Transition through Dynamics of Circular Construction Projects
Authors: Kooter Elonie , Uden Mart van , Marrewijk Alfons van , Wamelink Hans , Bueren Ellen van , Heurkens Erwin
Published: November 2021

The aim of this paper is to better understand the dynamics of circular construction projects and how these interorganizational projects contribute to the transition towards a circular economy. It is essential that the construction sector develops and adopts interorganizational initiatives to support the transition to a circular and low-carbon construction economy. A benefit of being involved in such initiatives is that organizations reflect on the emergence and acceptance of new practices related to changing organizational roles and responsibilities. In this paper, we study eight circular construction projects within the context of an interorganizational initiative to stimulate the transition towards a circular economy by exploring insights from evaluations thereof. We build upon literature from Sustainability Transitions Research (STR), circular construction research, and interorganizational project studies. Our findings show three clusters of dynamics that are relevant in the realization of circular ambitions in interorganizational construction projects: (1) prerequisites, (2) temporal dynamics in interorganizational projects, and (3) contextual influences. These insights highlight factors that enable the realization of circular ambitions in construction projects and contribute to our understanding of the dynamics of interorganizational construction projects and their role in the context of STR.
Revealing the Contribution of Informal Settlements to Climate Change Mitigation in Latin America: A Case Study of Isidro Fabela, Mexico City
Authors: Reyes Ariadna
Published: November 2021

Given the implications of energy use in housing units for global warming, life cycle assessment (LCA) has been used to examine greenhouse gas (GHG) emissions. Although informal settlements, currently known as colonias populares, or barrios, house most of the urban population in Latin America, there is a poor understanding of how people in these communities use energy and contribute to GHG emissions. This investigation provides a comprehensive analysis of resource consumption in Mexico City’s colonia popular, including self-help housing, household energy consumption, and transportation. As there is no spatially specific data on energy use, the author conducted field research in the informal community of Isidro Fabela, founded in the 1960s. Isidro Fabela is an illuminating community that helps understand the energy use of informal settlements at advanced stages of urban consolidation. A mixed-method research approach served to collect empirical data through observations, household surveys, and in-depth interviews. Research sheds light on the efficient and sustainable ways in which families use energy, materials, and resources during self-help construction, and through their daily lives, in their community. The community-based LCA assessment finds that the contribution of Isidro Fabela to GHG emissions is 50% of the average impact in Mexico City. Natural gas or liquefied petroleum gas (LPG) consumption for water heating is the most significant contributor to GHG emissions because families use inefficient heaters. Interestingly, by using public transportation and even walking, residents moderate the contribution of work commutes to GHG emissions. Therefore, climate change policy should enhance low-energy practices in informal settlements, by improving access to energy-efficient technologies and public transportation, to help families contribute further to GHG mitigation in Mexico City and elsewhere in Latin America.
The Future of Agricultural Jobs in View of Robotization
Authors: Marinoudi Vasso , Lampridi Maria , Kateris Dimitrios , Pearson Simon , Sørensen Claus Grøn , Bochtis Dionysis
Published: November 2021

Robotics and computerization have drastically changed the agricultural production sector and thus moved it into a new automation era. Robots have historically been used for carrying out routine tasks that require physical strength, accuracy, and repeatability, whereas humans are used to engage with more value-added tasks that need reasoning and decision-making skills. On the other hand, robots are also increasingly exploited in several non-routine tasks that require cognitive skills. This technological evolution will create a fundamental and an unavoidable transformation of the agricultural occupations landscape with a high social and economic impact in terms of jobs creation and jobs destruction. To that effect, the aim of the present work is two-fold: (a) to map agricultural occupations in terms of their cognitive/manual and routine/non-routine characteristics and (b) to assess the susceptibility of each agricultural occupation to robotization. Seventeen (17) agricultural occupations were reviewed in relation to the characteristics of each individual task they entail and mapped onto a two-dimensional space representing the manual versus cognitive nature and the routine versus non-routine nature of an occupation. Subsequently, the potential for robotization was investigated, again concerning each task individually, and resulted in a weighted average potential adoption rate for each one of the agricultural occupations. It can be concluded that most of the occupations entail manual tasks that need to be performed in a standardised manner. Considering also that almost 81% of the agricultural work force is involved with these activities, it turns out that there is strong evidence for possible robotization of 70% of the agricultural domain, which, in turn, could affect 56% of the total annual budget dedicated to agricultural occupations. The presented work silhouettes the expected transformation of occupational landscape in agricultural production as an effort for a subsequent identification of social threats in terms of unemployment and job and wages polarization, among others, but also of opportunities in terms of emerged skills and training requirements for a social sustainable development of agricultural domain.
An AHP-Based Procedure for Model Selection for Eco-Efficiency Assessment
Authors: Xavier Belem Maria Julia , Vieira Junior Milton , Mummolo Giovanni , Facchini Francesco
Published: November 2021

Modelling eco-efficiency is becoming a wide field of research shown by a large body of scientific literature on the subjects concerned. This paper, after performing a systematic literature review (SLR) to identify existing models for process eco-efficiency assessments, provides a methodology, based on the analytic hierarchy process (AHP) method, for choosing the eco-efficiency assessment model to be used for a given application (process, product, or service). For the SLR, papers from the databases Scopus, Web of Science and Science Direct were used. Forty articles were considered for this study, using as the main selection criterion articles that present an eco-efficiency assessment model, since the purpose was to survey the types of existing models that are used to assess processes, products or services for eco-efficiency. With the systematic review carried out, it was possible to identify the types of models that exist and how they are used in different sectors, always aiming to identify if what was analyzed is eco-efficient and what points need to be improved. The proposed AHP-based methodology was applied to a numerical model to outline how to apply the methodology. The approach was easy to use and effective in identifying the proper eco-efficiency model.
Structural, Magnetic, and Optical Properties of Mn2+ Doping in ZnO Thin Films
Authors: Sharma Monika , Bera Kakoli , Mishra Ruby , Kuanr Alka V.
Published: November 2021

MnxZn1−xO thin films (x = 0%, 1%, 3%, and 5%) were grown on corning glass substrates using sol–gel technique. Single-phase hexagonal wurtzite structure was confirmed using X-ray diffraction. Raman analysis revealed the presence of Mn content with an additional vibrational mode at 570 cm−1. The surface morphology of the samples was observed by scanning electron microscopy which suggested that the grain size increases with an increase in Mn concentration. The optical bandgap increases with increasing Mn concentration due to a significant blueshift in UV–visible absorption spectra. The alteration of the bandgap was verified by the I–V measurements on ZnO and Mn-ZnO films. The various functional groups in the thin films were recorded using FTIR analysis. Magnetic measurements showed that MnxZn1−xO films are ferromagnetic, as Mn induces a fully polarised state. The effect of Mn2+ ions doping on MnxZn1−xO thin films was investigated by extracting various parameters such as lattice parameters, energy bandgap, resistivity, and magnetisation. The observed coercivity is about one-fifth of the earlier published work data which indicates the structure is soft in nature, having less dielectric/magnetic loss, and hence can be used as ultra-fast switching in spintronic devices.
A Prabhakar Fractional Approach for the Convection Flow of Casson Fluid across an Oscillating Surface Based on the Generalized Fourier Law
Authors: Sarwar Noman , Asjad Muhammad Imran , Sitthiwirattham Thanin , Patanarapeelert Nichaphat , Muhammad Taseer
Published: November 2021

In the present work, an unsteady convection flow of Casson fluid, together with an oscillating vertical plate, is examined. The governing PDEs corresponding to velocity and temperature profile are transformed into linear ODEs with the help of the Laplace transform method. The ordinary derivative model generalized to fractional model is based on a generalized Fourier law. The solutions for energy and velocity equations are obtained after making the equations dimensionless. To check the insight of the physical parameters, especially the symmetric behavior of fractional parameters, it is found that for small and large values of time, fluid properties show dual behavior. Since the fractional derivative exhibits the memory of the function at the chosen value of time, therefore the present fractional model is more suitable in exhibiting memory than the classical model. Such results can be useful in the fitting of real data where needed. In the limiting case when fractional parameters are taken β=γ = 0 and α = 1 for both velocity and temperature, we get the solutions obtained with ordinary derivatives from the existing literature.
Ferrohydrodynamic and Magnetohydrodynamic Effects on Jet Flow and Heat Transfer of Fe3O4-H2O Nanofluid in a Microchannel Subjected to Permanent Magnets
Authors: Xie Yunfeng , Jiang Changwei , Zheng Peijia , Cao Zhichao , Luo Minghong
Published: November 2021

In the present study, the two-dimensional jet flow of Fe3O4-H2O nanofluid was numerically investigated in a microchannel. The main objective of this article was to study the impact of permanent magnets on both ferromagnetic hydrodynamic and thermal behavior. A ferromagnetic hydrodynamic model, which includes the Brown effect and thermophoretic effect, was applied to simulate the problem through solving momentum, energy, and volume fraction equations. In this regard, different results, including the velocity vector, temperature distribution, and Nusselt number, were analyzed. Moreover, the influence of Kelvin force, inlet opening, permanent magnets position, and Reynolds number were studied on the jet flow and heat transfer. The obtained results demonstrate these factors significantly affect the jet flow and heat transfer of Fe3O4-H2O nanofluid in the microchannel. Moreover, it was found that the magnetic field originating from permanent magnets can effectively solve the problem of local high temperature on the wall at low inlet opening. The heat transfer gain was the most obvious when the position of the permanent magnet was close to the microchannel entrance. When inlet opening and permanent magnets position are 1/4 and 1, respectively, the heat transfer gain was largest, reaching 35.2%.
PQMLE of a Partially Linear Varying Coefficient Spatial Autoregressive Panel Model with Random Effects
Authors: Li Shuangshuang , Chen Jianbao , Chen Danqing
Published: November 2021

This article deals with asymmetrical spatial data which can be modeled by a partially linear varying coefficient spatial autoregressive panel model (PLVCSARPM) with random effects. We constructed its profile quasi-maximum likelihood estimators (PQMLE). The consistency and asymptotic normality of the estimators were proved under some regular conditions. Monte Carlo simulations implied our estimators have good finite sample performance. Finally, a set of asymmetric real data applications was analyzed for illustrating the performance of the provided method.
Information Limits for Community Detection in Hypergraph with Label Information
Authors: Zhao Xiaofeng , Zhao Wei , Yuan Mingao
Published: November 2021

In network data mining, community detection refers to the problem of partitioning the nodes of a network into clusters (communities). This is equivalent to identifying the cluster label of each node. A label estimator is said to be an exact recovery of the true labels (communities) if it coincides with the true labels with a probability convergent to one. In this work, we consider the effect of label information on the exact recovery of communities in an m-uniform Hypergraph Stochastic Block Model (HSBM). We investigate two scenarios of label information: (1) a noisy label for each node is observed independently, with 1−αn as the probability that the noisy label will match the true label; (2) the true label of each node is observed independently, with the probability of 1−αn. We derive sharp boundaries for exact recovery under both scenarios from an information-theoretical point of view. The label information improves the sharp detection boundary if and only if αn=n−β+o(1) for a constant β>0.
Adjustments in the Range of Angular Motion during Walking after Amputation of the Toes: A Case Report
Authors: Forczek-Karkosz Wanda , Taylor Simon , Kicka Anna , Cappellini Germana , Dewolf Arthur H. , Ivanenko Yury
Published: November 2021

The forefoot plays an important role in providing body support and propulsion during walking. We investigated the effect of forefoot dysfunction on the gait pattern of a young adult with partial bilateral amputation of the toes. We measured our participant’s gait kinematics during barefoot and shod overground walking and analysed time-distance and joint range of motion (RoM) parameters against a group of healthy adults. Forefoot dysfunction gait is improved by footwear and walking experience; however, this improvement was still remarkably different (exceeded 95% CI) when compared to healthy gait at matching walking speed. Compared to healthy gait, walking barefoot had a slower speed and a 30% reduction in ankle and knee joint RoM, but a larger hip RoM. Shod gait resulted in a remarkable increase in ankle RoM and walking speed compared to barefoot gait. These results are consistent with the important role of the forefoot (tarsals and metatarsophalangeal joints) and suggest that footwear can facilitate gait function following toe amputation.
On Nonlinear Forced Impulsive Differential Equations under Canonical and Non-Canonical Conditions
Authors: Santra Shyam Sundar , Alotaibi Hammad , Noeiaghdam Samad , Sidorov Denis
Published: November 2021

This study is connected with the nonoscillatory and oscillatory behaviour to the solutions of nonlinear neutral impulsive systems with forcing term which is studied for various ranges of of the neutral coefficient. Furthermore, sufficient conditions are obtained for the existence of positive bounded solutions of the impulsive system. The mentioned example shows the feasibility and efficiency of the main results.
Functional Inequalities for Metric-Preserving Functions with Respect to Intrinsic Metrics of Hyperbolic Type
Authors: Mocanu Marcelina
Published: November 2021

We obtain functional inequalities for functions which are metric-preserving with respect to one of the following intrinsic metrics in a canonical plane domain: hyperbolic metric or some restrictions of the triangular ratio metric, respectively, of a Barrlund metric. The subadditivity turns out to be an essential property, being possessed by every function that is metric-preserving with respect to the hyperbolic metric and also by the composition with some specific function of every function that is metric-preserving with respect to some restriction of the triangular ratio metric or of a Barrlund metric. We partially answer an open question, proving that the hyperbolic arctangent is metric-preserving with respect to the restrictions of the triangular ratio metric on the unit disk to radial segments and to circles centered at origin.
Identification and Characterization of mRNA Biomarkers for Sodium Cyanide Exposure
Authors: Kim Min , Jee Seung-Cheol , Kim Soee , Hwang Kyung-Hwa , Sung Jung-Suk
Published: November 2021

Biomarkers in exposure assessment are defined as the quantifiable targets that indicate the exposure to hazardous chemicals and their resulting health effect. In this study, we aimed to identify, validate, and characterize the mRNA biomarker that can detect the exposure of sodium cyanide. To identify reliable biomarkers for sodium cyanide exposure, critical criteria were defined for candidate selection: (1) the expression level of mRNA significantly changes in response to sodium thiocyanate treatment in transcriptomics results (fold change > 2.0 or <0.50, adjusted p-value < 0.05); and (2) the mRNA level is significantly modulated by sodium cyanide exposure in both normal human lung cells and rat lung tissue. We identified the following mRNA biomarker candidates: ADCY5, ANGPTL4, CCNG2, CD9, COL1A2, DACT3, GGCX, GRB14, H1F0, HSPA1A, MAF, MAT2A, PPP1R10, and PPP4C. The expression levels of these candidates were commonly downregulated by sodium cyanide exposure both in vitro and in vivo. We functionally characterized the biomarkers and established the impact of sodium cyanide on transcriptomic profiles using in silico approaches. Our results suggest that the biomarkers may contribute to the regulation and degradation of the extracellular matrix, leading to a negative effect on surrounding lung cells.
Nuclear Matter in 1 + 1 Dimensions
Authors: Pisarski Robert D. , Lajer Marton , Tsvelik Alexei M. , Konik Robert M.
Published: November 2021

We review the solution of QCD in two spacetime dimensions. Following the analysis of Baluni, for a single flavor, the model can be analyzed using Abelian bosonization. The theory can be analyzed in strong coupling, when the quarks are much lighter than the gauge coupling. In this limit, the theory is given by a Luttinger liquid.
Urban Expansion Simulated by Integrated Cellular Automata and Agent-Based Models; An Example of Tallinn, Estonia
Authors: Mozaffaree Pour Najmeh , Oja Tõnu
Published: November 2021

From 1990 to 2018, built-up areas in Tallinn, Estonia’s capital city, increased by 25.03%, while its population decreased by −10.19%. Investigating the factors affecting urban expansion and modeling it are critical steps to detect future expansion trends and plan for a more sustainable environment. Different models have been used to investigate, predict, and simulate urban expansion in recent years. In this paper, we coupled the cellular automata, agent-based, and Markov models (CA–Agent model) in a novel manner to address the complexity of the dynamic simulation, generate heterogeneity in space, define more complicated rules, and employ the suitability analysis. In the CA–Agent model, cells are dynamic agents, and the model’s outcome emerges from cellular agents’ interactions over time using the rules of behavior and their decisions concerning the adjacent neighboring cells and probabilities of spatial changes. We performed the CA–Agent model run two times for 2018 and 2030. The first simulated results were used to validate the performance of the model. Kappa showed 0.86, indicating a relatively high model fit, so we conducted the second 12-year run up to the year 2030. The results illustrated that using these model parameters, the overall built-up areas will reach 175.24 sq. km with an increase of 30.25% in total from 1990 to 2030. Thus, implementing the CA–Agent model in the study area illustrated the temporal changes of land conversion and represented the present spatial planning results requiring regulation of urban expansion encroachment on agricultural and forest lands.
A Review of COVID-19 Modelling Strategies in Three Countries to Develop a Research Framework for Regional Areas
Authors: Rahman Azizur , Kuddus Md Abdul , Ip Ryan H. L. , Bewong Michael
Published: November 2021

At the end of December 2019, an outbreak of COVID-19 occurred in Wuhan city, China. Modelling plays a crucial role in developing a strategy to prevent a disease outbreak from spreading around the globe. Models have contributed to the perspicacity of epidemiological variations between and within nations and the planning of desired control strategies. In this paper, a literature review was conducted to summarise knowledge about COVID-19 disease modelling in three countries—China, the UK and Australia—to develop a robust research framework for the regional areas that are urban and rural health districts of New South Wales, Australia. In different aspects of modelling, summarising disease and intervention strategies can help policymakers control the outbreak of COVID-19 and may motivate modelling disease-related research at a finer level of regional geospatial scales in the future.
Autophagy Inhibits Intercellular Transport of Citrus Leaf Blotch Virus by Targeting Viral Movement Protein
Authors: Niu Erbo , Liu Huan , Zhou Hongsheng , Luo Lian , Wu Yunfeng , Andika Ida Bagus , Sun Liying
Published: November 2021

Autophagy is an evolutionarily conserved cellular-degradation mechanism implicated in antiviral defense in plants. Studies have shown that autophagy suppresses virus accumulation in cells; however, it has not been reported to specifically inhibit viral spread in plants. This study demonstrated that infection with citrus leaf blotch virus (CLBV; genus Citrivirus, family Betaflexiviridae) activated autophagy in Nicotiana benthamiana plants as indicated by the increase of autophagosome formation. Impairment of autophagy through silencing of N. benthamiana autophagy-related gene 5 (NbATG5) and NbATG7 enhanced cell-to-cell and systemic movement of CLBV; however, it did not affect CLBV accumulation when the systemic infection had been fully established. Treatment using an autophagy inhibitor or silencing of NbATG5 and NbATG7 revealed that transiently expressed movement protein (MP), but not coat protein, of CLBV was targeted by selective autophagy for degradation. Moreover, we identified that CLBV MP directly interacted with NbATG8C1 and NbATG8i, the isoforms of autophagy-related protein 8 (ATG8), which are key factors that usually bind cargo receptors for selective autophagy. Our results present a novel example in which autophagy specifically targets a viral MP to limit the intercellular spread of the virus in plants.
Mental Health and Substance Use Associated with Hospitalization among People with COVID-19: A Population-Based Cohort Study
Authors: Velásquez García Héctor Alexander , Wilton James , Smolina Kate , Chong Mei , Rasali Drona , Otterstatter Michael , Rose Caren , Prystajecky Natalie , David Samara , Galanis Eleni , McKee Geoffrey , Krajden Mel , Janjua Naveed Zafar
Published: November 2021

This study identified factors associated with hospital admission among people with laboratory-diagnosed COVID-19 cases in British Columbia. The study used data from the BC COVID-19 Cohort, which integrates data on all COVID-19 cases with data on hospitalizations, medical visits, emergency room visits, prescription drugs, chronic conditions and deaths. The analysis included all laboratory-diagnosed COVID-19 cases in British Columbia to 15 January 2021. We evaluated factors associated with hospital admission using multivariable Poisson regression analysis with robust error variance. Of the 56,874 COVID-19 cases included in the analysis, 2298 were hospitalized. Factors associated with increased hospitalization risk were as follows: male sex (adjusted risk ratio (aRR) = 1.27; 95% CI = 1.17–1.37), older age (p-trend < 0.0001 across age groups increasing hospitalization risk with increasing age [aRR 30–39 years = 3.06; 95% CI = 2.32–4.03, to aRR 80+ years = 43.68; 95% CI = 33.41–57.10 compared to 20–29 years-old]), asthma (aRR = 1.15; 95% CI = 1.04–1.26), cancer (aRR = 1.19; 95% CI = 1.09–1.29), chronic kidney disease (aRR = 1.32; 95% CI = 1.19–1.47), diabetes (treated without insulin aRR = 1.13; 95% CI = 1.03–1.25, requiring insulin aRR = 5.05; 95% CI = 4.43–5.76), hypertension (aRR = 1.19; 95% CI = 1.08–1.31), injection drug use (aRR = 2.51; 95% CI = 2.14–2.95), intellectual and developmental disabilities (aRR = 1.67; 95% CI = 1.05–2.66), problematic alcohol use (aRR = 1.63; 95% CI = 1.43–1.85), immunosuppression (aRR = 1.29; 95% CI = 1.09–1.53), and schizophrenia and psychotic disorders (aRR = 1.49; 95% CI = 1.23–1.82). In an analysis restricted to women of reproductive age, pregnancy (aRR = 2.69; 95% CI = 1.42–5.07) was associated with increased risk of hospital admission. Older age, male sex, substance use, intellectual and developmental disability, chronic comorbidities, and pregnancy increase the risk of COVID-19-related hospitalization.