bluuebunny/crossref_metadata_2025 huggingface dataset:
Robust Data-Driven Leak Localization in Water Distribution Networks Using Pressure Measurements and Topological Information
Authors: Alves Débora , Blesa Joaquim , Duviella Eric , Rajaoarisoa Lala
Published: November 2021

This article presents a new data-driven method for locating leaks in water distribution networks (WDNs). It is triggered after a leak has been detected in the WDN. The proposed approach is based on the use of inlet pressure and flow measurements, other pressure measurements available at some selected inner nodes of the WDN, and the topological information of the network. A reduced-order model structure is used to calculate non-leak pressure estimations at sensed inner nodes. Residuals are generated using the comparison between these estimations and leak pressure measurements. In a leak scenario, it is possible to determine the relative incidence of a leak in a node by using the network topology and what it means to correlate the probable leaking nodes with the available residual information. Topological information and residual information can be integrated into a likelihood index used to determine the most probable leak node in the WDN at a given instant k or, through applying the Bayes’ rule, in a time horizon. The likelihood index is based on a new incidence factor that considers the most probable path of water from reservoirs to pressure sensors and potential leak nodes. In addition, a pressure sensor validation method based on pressure residuals that allows the detection of sensor faults is proposed.
Machine Learning-Based Diagnosis in Laser Resonance Frequency Analysis for Implant Stability of Orthopedic Pedicle Screws
Authors: Mikami Katsuhiro , Nemoto Mitsutaka , Nagura Takeo , Nakamura Masaya , Matsumoto Morio , Nakashima Daisuke
Published: November 2021

Evaluation of the initial stability of implants is essential to reduce the number of implant failures of pedicle screws after orthopedic surgeries. Laser resonance frequency analysis (L-RFA) has been recently proposed as a viable diagnostic scheme in this regard. In a previous study, L-RFA was used to demonstrate the diagnosis of implant stability of monoaxial screws with a fixed head. However, polyaxial screws with movable heads are also frequently used in practice. In this paper, we clarify the characteristics of the laser-induced vibrational spectra of polyaxial screws which are required for making L-RFA diagnoses of implant stability. In addition, a novel analysis scheme of a vibrational spectrum using L-RFA based on machine learning is demonstrated and proposed. The proposed machine learning-based diagnosis method demonstrates a highly accurate prediction of implant stability (peak torque) for polyaxial pedicle screws. This achievement will contribute an important analytical method for implant stability diagnosis using L-RFA for implants with moving parts and shapes used in various clinical situations.
Future Trends in Semiconducting Gas-Selective Sensing Probes for Skin Diagnostics
Authors: Annerino Anthony , Gouma Pelagia-Irene (Perena)
Published: November 2021

This paper presents sensor nanotechnologies that can be used for the skin-based gas “smelling” of disease. Skin testing may provide rapid and reliable results, using specific “fingerprints” or unique patterns for a variety of diseases and conditions. These can include metabolic diseases, such as diabetes and cholesterol-induced heart disease; neurological diseases, such as Alzheimer’s and Parkinson’s; quality of life conditions, such as obesity and sleep apnea; pulmonary diseases, such as cystic fibrosis, asthma, and chronic obstructive pulmonary disease; gastrointestinal tract diseases, such as irritable bowel syndrome and colitis; cancers, such as breast, lung, pancreatic, and colon cancers; infectious diseases, such as the flu and COVID-19; as well as diseases commonly found in ICU patients, such as urinary tract infections, pneumonia, and infections of the blood stream. Focusing on the most common gaseous biomarkers in breath and skin, which is nitric oxide and carbon monoxide, and certain abundant volatile organic compounds (acetone, isoprene, ammonia, alcohols, sulfides), it is argued here that effective discrimination between the diseases mentioned above is possible, by capturing the relative sensor output signals from the detection of each of these biomarkers and identifying the distinct breath print for each disease.
Towards Understanding the Interconnection between Celestial Pole Motion and Earth’s Magnetic Field Using Space Geodetic Techniques
Authors: Modiri Sadegh , Heinkelmann Robert , Belda Santiago , Malkin Zinovy , Hoseini Mostafa , Korte Monika , Ferrándiz José M. , Schuh Harald
Published: November 2021

The understanding of forced temporal variations in celestial pole motion (CPM) could bring us significantly closer to meeting the accuracy goals pursued by the Global Geodetic Observing System (GGOS) of the International Association of Geodesy (IAG), i.e., 1 mm accuracy and 0.1 mm/year stability on global scales in terms of the Earth orientation parameters. Besides astronomical forcing, CPM excitation depends on the processes in the fluid core and the core–mantle boundary. The same processes are responsible for the variations in the geomagnetic field (GMF). Several investigations were conducted during the last decade to find a possible interconnection of GMF changes with the length of day (LOD) variations. However, less attention was paid to the interdependence of the GMF changes and the CPM variations. This study uses the celestial pole offsets (CPO) time series obtained from very long baseline interferometry (VLBI) observations and data such as spherical harmonic coefficients, geomagnetic jerk, and magnetic field dipole moment from a state-of-the-art geomagnetic field model to explore the correlation between them. In this study, we use wavelet coherence analysis to compute the correspondence between the two non-stationary time series in the time–frequency domain. Our preliminary results reveal interesting common features in the CPM and GMF variations, which show the potential to improve the understanding of the GMF’s contribution to the Earth’s rotation. Special attention is given to the corresponding signal between FCN and GMF and potential time lags between geomagnetic jerks and rotational variations.
Gradient-Descent-like Ghost Imaging
Authors: Yu Wen-Kai , Zhu Chen-Xi , Li Ya-Xin , Wang Shuo-Fei , Cao Chong
Published: November 2021

Ghost imaging is an indirect optical imaging technique, which retrieves object information by calculating the intensity correlation between reference and bucket signals. However, in existing correlation functions, a high number of measurements is required to acquire a satisfied performance, and the increase in measurement number only leads to limited improvement in image quality. Here, inspired by the gradient descent idea that is widely used in artificial intelligence, we propose a gradient-descent-like ghost imaging method to recursively move towards the optimal solution of the preset objective function, which can efficiently reconstruct high-quality images. The feasibility of this technique has been demonstrated in both numerical simulation and optical experiments, where the image quality is greatly improved within finite steps. Since the correlation function in the iterative formula is replaceable, this technique offers more possibilities for image reconstruction of ghost imaging.
Fusion of Unobtrusive Sensing Solutions for Sprained Ankle Rehabilitation Exercises Monitoring in Home Environments
Authors: Ekerete Idongesit , Garcia-Constantino Matias , Diaz-Skeete Yohanca , Nugent Chris , McLaughlin James
Published: November 2021

The ability to monitor Sprained Ankle Rehabilitation Exercises (SPAREs) in home environments can help therapists ascertain if exercises have been performed as prescribed. Whilst wearable devices have been shown to provide advantages such as high accuracy and precision during monitoring activities, disadvantages such as limited battery life and users’ inability to remember to charge and wear the devices are often the challenges for their usage. In addition, video cameras, which are notable for high frame rates and granularity, are not privacy-friendly. Therefore, this paper proposes the use and fusion of privacy-friendly and Unobtrusive Sensing Solutions (USSs) for data collection and processing during SPAREs in home environments. The present work aims to monitor SPAREs such as dorsiflexion, plantarflexion, inversion, and eversion using radar and thermal sensors. The main contributions of this paper include (i) privacy-friendly monitoring of SPAREs in a home environment, (ii) fusion of SPAREs data from homogeneous and heterogeneous USSs, and (iii) analysis and comparison of results from single, homogeneous, and heterogeneous USSs. Experimental results indicated the advantages of using heterogeneous USSs and data fusion. Cluster-based analysis of data gleaned from the sensors indicated an average classification accuracy of 96.9% with Neural Network, AdaBoost, and Support Vector Machine, amongst others.
Joint Feature-Space and Sample-Space Based Heterogeneous Feature Transfer Method for Object Recognition Using Remote Sensing Images with Different Spatial Resolutions
Authors: Hu Wei , Kong Xiyuan , Xie Liang , Yan Huijiong , Qin Wei , Meng Xiangyi , Yan Ye , Yin Erwei
Published: November 2021

To improve the classification results of high-resolution remote sensing images (RSIs), it is necessary to use feature transfer methods to mine the relevant information between high-resolution RSIs and low-resolution RSIs to train the classifiers together. Most of the existing feature transfer methods can only handle homogeneous data (i.e., data with the same dimension) and are susceptible to the quality of the RSIs, while RSIs with different resolutions present different feature dimensions and samples obtained from illumination conditions. To obtain effective classification results, unlike existing methods that focus only on the projection transformation in feature space, a joint feature-space and sample-space heterogeneous feature transfer (JFSSS-HFT) method is proposed to simultaneously process heterogeneous multi-resolution images in feature space using projection matrices of different dimensions and reduce the impact of outliers by adaptive weight factors in the sample space simultaneously to reduce the occurrence of negative transfer. Moreover, the maximum interclass variance term is embedded to improve the discriminant ability of the transferred features. To solve the optimization problem of JFSSS-HFT, the alternating-direction method of multipliers (ADMM) is introduced to alternatively optimize the parameters of JFSSS-HFT. Using different types of ship patches and airplane patches with different resolutions, the experimental results show that the proposed JFSSS-HFT obtains better classification results than the typical feature transferred methods.
Paper-Based Analytical Devices for Colorimetric and Luminescent Detection of Mercury in Waters: An Overview
Authors: Bendicho Carlos , Lavilla Isela , Pena-Pereira Francisco , la Calle Inmaculada de , Romero Vanesa
Published: November 2021

Lab-on-paper technologies, also known as paper-based analytical devices (PADs), have received increasing attention in the last years, and nowadays, their use has spread to virtually every application area, i.e., medical diagnostic, food safety, environmental monitoring, etc. Advantages inherent to on-field detection, which include avoiding sampling, sample preparation and conventional instrumentation in central labs, are undoubtedly driving many developments in this area. Heavy metals represent an important group of environmental pollutants that require strict controls due to the threat they pose to ecosystems and human health. In this overview, the development of PADs for Hg monitoring, which is considered the most toxic metal in the environment, is addressed. The main emphasis is placed on recognition elements (i.e., organic chromophores/fluorophores, plasmonic nanoparticles, inorganic quantum dots, carbon quantum dots, metal nanoclusters, etc.) employed to provide suitable selectivity and sensitivity. The performance of both microfluidic paper-based analytical devices and paper-based sensors using signal readout by colorimetry and luminescence will be discussed.
A Novel Approach of Heat Rate Enhancement in Rectangular Channels with Thin Porous Layer at the Channel Walls
Authors: Saghir Mohamad Ziad
Published: November 2021

Heat transfer enhancement is a topic of great interest nowadays due to its different applications in industries. A porous material also known as metallic foam plays a major role in heat enhancement at the expense of pressure drop. The flow in channels demonstrates the usefulness of this technology in heat extraction. In our current study, a porous strip attached to the walls of the channels is proposed as an alternative for heat enhancement. The thickness of the porous strip was varied for different Reynolds numbers. By maintaining a laminar regime and using water as a fluid, we determined an optimum thickness of porous material leading to the highest performance evaluation criterion. In our current study, with the aspect ratio being the porous strip thickness over the channel width, an aspect ratio of 0.2 is found to be the alternative. A 40% increase in heat enhancement is detected in the presence of a porous strip when compared to a clear channel case for a Reynolds number equal to 200, which improves further as the Reynolds number increases accordingly.
Monitoring of Gold Biodistribution from Nanoparticles Using a HPLC-Visible Method
Authors: Chaigneau Thomas , Pallotta Arnaud , Benaddi Fatima Zahra , Sancey Lucie , Chakir Said , Boudier Ariane , Clarot Igor
Published: November 2021

There is intensive research using gold nanoparticles for biomedical purposes, which have many advantages such as ease of synthesis and high reactivity. Their possible small size (<10 nm) can lead to the crossing of biological membranes and then to problematic dissemination and storage in organs that must be controlled and evaluated. In this work, a simple isocratic HPLC method was developed and validated to quantify the gold coming from nanoparticles in different biological samples. After a first carbonization step at 900 °C, the nanoparticles were oxidized by dibroma under acidic conditions, leading to tetrachloroaurate ions that could form ion pairs when adding rhodamine B. Finally, ion pairs were extracted and rhodamine B was evaluated to quantify the corresponding gold concentration by reversed-phase HPLC with visible detection. The method was validated for different organs (liver, spleen, lungs, kidneys, or brain) and fluids (plasma and urine) from rats and mice. Lastly, the developed method was used to evaluate the content of gold in organs and fluids after intravenous (IV) injection of nanoparticles.
An Evaluation of the Equilibrium Properties in Hexane and Ethanol Extractive Systems for Moringa oleifera Seeds and Fatty Acid Profiles of the Extracts
Authors: Arguelles-Peña Karina , Olguín-Rojas José Arturo , Acosta-Osorio Andrés Antonio , Carrera Ceferino , Barbero Gerardo F. , García-Alvarado Miguel Ángel , Rodríguez-Jimenes Guadalupe del Carmen
Published: November 2021

Until the present, oilseed extractions have been mainly performed using hexane: a toxic, non-sustainable solvent. Extraction methods using ethanol have recently been proposed and, to evaluate the suitability of ethanol as an alternative solvent, Moringa seeds with an oil content as high as 40% have been chosen to determine the equilibrium properties in solid–liquid ethanol extractions. The equilibrium constant (Keq) and the specific retained solution (M) of the extractive systems seeds–oil–hexane and seeds–oil–ethanol were determined and validated, following a counter-current multi-stage extraction model. The extractions were carried out at 40 and 50 °C, the mass to solvent ratios used were 1:5, 1:10 and 1:20, and shelled and unshelled seeds (kernels) were tested. The Keq and M of the different kinetics revealed that Keq was not infinite in the hexane systems, whereas the ethanol systems registered slightly lower values. Regarding M, although the seed powder allowed more rapid extractions, particle size was increased to reduce M for an easier phase preparation. Finally, a counter-current multi-stage extraction system was simulated and applied under suitable conditions. The fatty acid profiles for both types of extract were similar regarding their main components. definition:
Correction: Vukovic et al. COVID-19 Pandemic: Is the Crypto Market a Safe Haven? The Impact of the First Wave. Sustainability 2021, 13, 8578
Authors: Vukovic Darko , Maiti Moinak , Grubisic Zoran , Grigorieva Elena M. , Frömmel Michael
Published: November 2021

The authors would like to make the following corrections to the published paper [...]
Organic Food Consumption among Households in Hanoi: Importance of Situational Factors
Authors: Tran Anh Thi Van , Nguyen Nhung Thi
Published: November 2021

The promotion of sustainable consumption plays an extremely important role in Vietnam’s National Green Growth Strategy. However, despite an increase in concerns about environmental issues, eco-friendly buying behaviors in general and organic food consumption in particular are still unpopular among Vietnamese consumers, leading to a question about the importance of situational factors, which this article focuses on. Based on attitudes; subjective norms; perceived norms, which are mentioned in the theory of planned behavior (TPB) and consumer choice theory; and social norms from social categorization theory, the research created a questionnaire and then sent it to respondents who were in charge of buying food for their family in Hanoi. Then, 423 of the 570 responses received were used to create the structural equation model (SEM) with four distinct stages in AMOS statistical software, which evidences the crucial role of situational factors. Subjective norms and social norms have the highest positive impact on organic food purchase among households in Hanoi. Moreover, households’ organic food purchase is also positively affected by perceived behavior control and the availability of products but negatively affected by the price of products, which strongly fits with TPB, social categorization theory, and other studies. In particular, there is no evidence about relationships between knowledge of or attitude toward organic food and family income and organic food purchase among households in Hanoi. In addition, age and education status do not have any impact on respondents’ behavior in organic food purchase in this city. Finally, the authors propose some suggestions to promote organic food consumption among households in Hanoi. First is that businesses specializing in the production and supply of organic products should focus on customer care activities, innovate business models, and advertise to attract customers to use organic products. Second is that the government should issue regulations to encourage businesses to invest in the research and production of organic products as well as implement strict regulations to penalize violations in the production and supply of organic products.
Simulating the Impacts of Hybrid Campus and Autonomous Electric Vehicles as GHG Mitigation Strategies: A Case Study for a Mid-Size Canadian Post-Secondary School
Authors: Saha Bijoy , Fatmi Mahmudur Rahman
Published: November 2021

This paper presents how a post-secondary institution like University of British Columbia’s Okanagan (UBCO) campus can reduce its carbon footprint and be aligned with the government’s target through promoting virtual campus and autonomous electric vehicles (AEVs). Different virtual campus scenarios are developed: online classes only, working-from-home only, and a hybrid of both. In the case of AEVs, alternative penetration rates for levels 2 and 5 are considered. A total of 50 scenarios are tested using a sub-area transport simulation model for UBCO, which is extracted from the regional travel demand forecasting model. The results suggest that a 40% AEV penetration rate coupled with fully in-person classes reduces GHG by ~36% compared to the 2018-level, which will help UBCO to achieve their 2030 emission reduction target and be aligned with the provincial target. The 50% AEV and 10% hybrid virtual campus reduces emissions by ~48%, which is aligned with the 2040 provincial target. A fully virtual campus will help to reach the 2050 provincial target by reducing GHG by ~76%. The results further demonstrate that level 5 AEVs produce lesser emissions than level 2 at a lower AEV penetration rate for the fully in-person campus scenario. At higher penetration rates, level 5 performs better only if it is coupled with 10% of students, faculties and staffs attending virtual campus scenario.
Barriers and Facilitators for the Romanian Older Adults in Enjoying Physical Activity Health-Related Benefits
Authors: Urzeala Constanta , Popescu Veronica , Courteix Daniel , Mitrache Georgeta , Roco Mihaela , Teodorescu Silvia
Published: November 2021

Older adults are considered a vulnerable category within the population, which is exposed to an accelerated risk of functional degeneration. The purpose of this study was to explore different facilitating factors and possible existing barriers to being physically active in older age in urban areas of Romania. A cross-sectional survey was conducted among 172 participants who were asked to assess their health, on a scale from 1 to 3, and to fill out two questionnaires: 1. Physical Activity Scale for the Elderly; 2. Depression, Anxiety, and Stress Scale. Participants were also asked to specify to what extent they performed different leisure activities during the last week. SPSS was used for data analysis. The chi-squared test, t-test, ANOVA, and MANOVA emphasised the differences between participants, at p < 0.05. Regarding health condition, 27.3% of participants responded that their health was good, 53.5%—satisfactory, and 19.2%—not so good. The results showed significant differences between older adults participating in Elderly Clubs and non-participants, only in terms of PASE leisure. There were significant multivariate effects of the variables Gender and Stable life partner regarding PASE leisure. Weak negative correlations were identified between leisure physical activities and emotional state. Among the proposed leisure activities, watching TV and listening to music represented the most frequent preferences of the participants. The older adults participating in this study preferred to become involved with different physical activities, in conjunction with their habits, health, age, sex, stable life partner, and Elderly Club participation.
Environmental Regulation, Technological Innovation, and Industrial Transformation: An Empirical Study Based on City Function in China
Authors: Xu Jing , Chen Dong , Liu Rongrong , Zhou Maoxian , Kong Yunxiao
Published: November 2021

The Chinese economy has now transitioned from rapid expansion to high-quality growth. The issue of achieving synergy between environmental conservation and economic growth has become a serious concern. Based on the panel data of 120 prefecture-level cities in China from 2008 to 2017, we used the panel threshold regression model to investigate the influences of environmental regulation (ER) and technological innovation (TI) on urban industrial transformation. Further, we examined the threshold characteristics of four types of functional cities—resource-based, industry-oriented, comprehensive regional, and other types of cities. Our results show that ER and TI have varied effects on the industrial transformation of the four categories of functional cities. Both ER and TI have significant nonlinear threshold impacts on industrial transformation in resource-based cities. The inhibitory effect of ER on industrial structure rationalization decreases as the severity of ER increases. There is a shift from the promotion to the restriction of industrial structure rationalization due to TI increase. In contrast, TI strengthens the optimization of industrial structure. The promotion effects of ER and TI on industrial structure optimization improve as the former and latter increase in comprehensive regional cities. The influence of TI on the industrial transformation of industry-oriented cities is consistent with its impact on resource-based cities. These findings provide theoretical guidance and inspiration for urban industrial transformation in response to ER and TI based on their functional roles.
A Distributed Mix-Context-Based Method for Location Privacy in Road Networks
Authors: Ullah Ikram , Shah Munam Ali , Khan Abid , Maple Carsten , Waheed Abdul , Jeon Gwnaggil
Published: November 2021

Preserving location privacy is increasingly an essential concern in Vehicular Adhoc Networks (VANETs). Vehicles broadcast beacon messages in an open form that contains information including vehicle identity, speed, location, and other headings. An adversary may track the various locations visited by a vehicle using sensitive information transmitted in beacons such as vehicle identity and location. By matching the vehicle identity used in beacon messages at various locations, an adversary learns the location history of a vehicle. This compromises the privacy of the vehicle driver. In existing research work, pseudonyms are used in place of the actual vehicle identity in the beacons. Pseudonyms should be changed regularly to safeguard the location privacy of vehicles. However, applying simple change in pseudonyms does not always provide location privacy. Existing schemes based on mix zones operate efficiently in higher traffic environments but fail to provide privacy in lower vehicle traffic densities. In this paper, we take the problem of location privacy in diverse vehicle traffic densities. We propose a new Crowd-based Mix Context (CMC) privacy scheme that provides location privacy as well as identity protection in various vehicle traffic densities. The pseudonym changing process utilizes context information of road such as speed, direction and the number of neighbors in transmission range for the anonymisation of vehicles, adaptively updating pseudonyms based on the number of a vehicle neighbors in the vicinity. We conduct formal modeling and specification of the proposed scheme using High-Level Petri Nets (HPLN). Simulation results validate the effectiveness of CMC in terms of location anonymisation, the probability of vehicle traceability, computation time (cost) and effect on vehicular applications.
Application of Soil Washing and Thermal Desorption for Sustainable Remediation and Reuse of Remediated Soil
Authors: Lee Sang-Hwan , Kim Soon-Oh , Lee Sang-Woo , Kim Min-Suk , Park Hyun
Published: November 2021

Global governance of soil resources as well as revitalizations and remediation of degraded areas seem to be necessary actions for sustainable development. A great deal of effort has gone into developing remediation technologies to remove or reduce the impact of these contaminants in the environment. However, contaminated soil remediations in stringent conditions deteriorate soil properties and functions and create the need for efficient soil revitalization measures. Soil washing (SW) and thermal desorption (TD) are commonly used to remediate contaminated soil and can significantly reduce the contaminant, sometimes to safe levels where reuse can be considered; however, the effects of treatment on soil quality must be understood in order to support redevelopment after remediation. In this review, we discussed the effects of SW and TD on soil properties, including subsequent soil quality and health. Furthermore, the importance of these techniques for remediation and reclamation strategies was discussed. Some restoration strategies were also proposed for the recovery of soil quality. In addition, remediated and revitalized soil can be reused for various purposes, which can be accepted as an implementation of sustainable remediation. This review concludes with an outlook of future research efforts that will further shift SW and TD toward sustainable remediation.
Optimal Ordering Policy for Retailers with Bayesian Information Updating in a Presale System
Authors: Quan Jinxian , Cho Sung-Won
Published: November 2021

In this study, we investigate inventory allocation and pricing strategies for retailers by incorporating demand information into the issue of inventory allocation during the presale period. In a presale system, retailers offer presale goods at a price lower than the retail price. By offering products at a discount, retailers may attract additional demand. In addition, this system enables retailers to reduce the uncertainty of market demand and establish a strategy for inventory allocation based on the results of presales. A Bayesian approach was employed to analyze and update demand information, and inventory allocation was formulated as a newsvendor problem to determine the optimal policy that maximizes retailer profit. A numerical analysis was conducted to validate the effectiveness of the proposed strategy. Results suggest that the proposed strategies can support retailers by more accurately predicting demand and achieving higher profits with less inventory. Furthermore, retailers can experience greater benefits from risk-averse customers than from risk-neutral customers.
Predictors of Viewing YouTube Videos on Incheon Chinatown Tourism in South Korea: Engagement and Network Structure Factors
Authors: Yoo Woohyun , Kim Taemin , Lee Soobum
Published: November 2021

YouTube has become an increasingly popular source of tourism information. The purpose of this study is to explore the network structures of YouTube videos about Incheon’s Chinatown in South Korea and investigate the potential factors that can predict the viewing of these videos. The analysis of 104 videos about Incheon Chinatown revealed that the engagement factors assessed by the number of comments and likes, and the running time of content, were significant predictors of viewing. However, network structure factors did not predict viewing. These findings make valuable contributions to sustainable tourism research and provide practical guidance for tourism management.
An Investigation on Shenzhen Urban Green Space Changes and Their Effect on Local Eco-Environment in Recent Decades
Authors: Liu Yue , Li Hui , Li Chang , Zhong Cheng , Chen Xueye
Published: November 2021

Rapid urbanization and population growth impact enormous pressures on urban natural, economic and social environments. The quantitative analysis of urban green space (UGS) landscape dynamics and their impact on the urban eco-environment is of great significance for urban planning and eco-environment protection. Taking Shenzhen as an example, the UGS landscape changes and their impact on urban heat islands (UHI), surface wetness, air pollution and carbon storage were comprehensively investigated with Landsat and MODIS images. Results showed a large number of lands transferring from UGS to non-UGS from 1978 to 2018, especially for cropland. Built-up regions have adverse influences on eco-environment factors, and then they suffer high SUHI and AOD and low humidity and carbon storage. The growth of built-up areas not only enlarges the area of SUHI, but also enhances the intensity of heat islands. On the contrary, UGS patches have beneficial influences on all eco-environment factors and then enjoy a better eco-environment, including low SUHII, high surface wetness, high carbon storage and low AOD. It is expected that this study could provide scientific support for UGS plans and for conserving and sustainable urban development for developing cities.
Integrating Corporate Social Responsibility into Corporate Strategy: The Role of Formal Tools
Authors: Maccarrone Paolo , Contri Anna Maria
Published: November 2021

This paper contributes to the literature debate on the role that formal tools used in the management of CSR activities can play in the integration of CSR into corporate strategy. In particular, the purpose of this research is two-fold: firstly, to investigate if a high degree of formalisation of CSR activities is needed to reach a high degree of integration of CSR into corporate strategy; secondly, to understand what roles CSR formal tools play in this integration process. In order to answer these research questions, eleven case studies of large multinational companies operating in Italy were developed. The results of the empirical analysis show that a high degree of integration is often coupled with intensive use of formalization, with some interesting exceptions. This result can be explained by the active role that almost all CSR formalisation elements play in the integration process of CSR in the overall corporate strategy.
From Corporate Social Responsibility to Stock Price Crash Risk: Modelling the Mediating Role of Firm Performance in an Emerging Market
Authors: Thuy Cao Thi Mien , Trung Trinh Quoc , Khuong Nguyen Vinh , Liem Nguyen Thanh
Published: November 2021

The literature on the link between corporate social responsibility (CSR) disclosure and stock price crash risk suggests that it is far more complicated than a plain one-to-one relationship. In this study, we examine how CSR disclosure affects the stock price crash risk and whether firm performance acts as a mediating variable in this relationship. The CSR disclosure index is built using the content analysis technique and the GRI criteria. We choose 225 businesses in Vietnam, comprising 159 firms listed on HOSE and 66 firms listed on HNX. Using the techniques of OLS, LOGIT, GMM, and the Sobel test and replacing different measures of dependent and mediator variable to enhance the robustness of our findings, we reach two important results. To begin with, CSR disclosure has a negative influence on the stock price crash risk of Vietnam’s listed firms. Second, in the aforementioned relationship, firm performance serves as an intermediate. Our results imply that listed firms should engage in CSR practices and disclosure in order to raise the firm’s performance and lower the stock price crash risk.
Vehicle Door Opening Control Model Based on a Fuzzy Inference System to Prevent Motorcycle–Vehicle Door Crashes
Authors: Huang Cheng-Yong
Published: November 2021

The goal of this research is to develop a fuzzy logic-based vehicle door control system to avoid motorcycle–vehicle door crash accidents. Accidents of this nature usually occur when the driver has parked the car, opens the door getting out of the car and collides with a motorcycle approaching from the rear, causing injury to the motorcyclist. In order to prevent such accidents, the fuzzy logic control system inputs the speed (MS) and safety distance (SD) of the motorcycle approaching from the rear, and then the fuzzy inference unit (FIU) calculates the clear output (Crisp) defuzzification Vehicle Door Opening Model (VDOM) value for the central locking system of the car, which can be used to trigger three modes, namely Danger Mode, Caution Mode and Warning Mode. In this study, the VDOM system is designed to trigger reasonable, reliable and consistent door control under different speeds of motorcycles coming from the rear and will be effectively applied to the door control of semi-automatic cars in the future.
The Impact of Thin Asphalt Layers as a Road Traffic Noise Intervention in an Urban Environment
Authors: Grangeiro de Barros Ablenya , Kampen Jarl K. , Vuye Cedric
Published: November 2021

Low-noise thin asphalt layers (TALs) are a feasible solution to mitigate road traffic noise in urban environments. Nevertheless, the impacts of this type of noise intervention are reported mostly regarding noise levels, while non-acoustic aspects influencing the population perception are still little-known. This study investigates the implementation of TALs in two streets of Antwerp, Belgium. The effectiveness of the intervention was measured via noise modelling and acoustic measurements of road traffic noise. A reduction of 2.8 dB in noise exposure was observed in Lden and Lnight, while SPB measurements showed decreases up to 5.2 dB on the roadside. The subjective impacts of the TALs were evaluated via self-administered surveys and compared to results from control streets. The annoyance indicators were positively impacted by the TALs implementation, resulting in annoyance levels similar or lower than in the control streets. The TALs did not impact the reported physical complaints, sleep quality, and comfort level to perform activities.
Marine Sites and the Drivers of Wellbeing: Ecosystem vs. Anthropic Services
Authors: Cavalletti Barbara , Corsi Matteo , Lagomarsino Elena
Published: November 2021

Coastal sites offer a range of services that contribute to human wellbeing. While some of the services are entirely human-made (e.g., parasol and sunbed rental), others are produced thanks to the contribution of marine ecosystems (e.g., water clarity). The purpose of this paper is to investigate the preferences of a sample of beachgoers for these two categories of services that policymakers have to balance when designing management strategies for coastal sites. We consider a marine site in the north of Italy that partially falls within the boundaries of a protected area but that is characterized by a medium-to-high level of anthropization. The results of a discrete choice experiment show that in the current state of things, the ecosystem services proposed for the sample have, on average, a higher marginal utility, suggesting that actions increasing those services have a larger effect on well-being.
Higher Perceived Design Thinking Traits and Active Learning in Design Courses Motivate Engineering Students to Tackle Energy Sustainability in Their Careers
Authors: Milovanovic Julie , Shealy Tripp , Katz Andrew
Published: November 2021

Engineers play an important role in implementing the Sustainable Development Goals defined by the United Nations, which aim to provide a more sustainable environment for future generations. Through design thinking, creativity, and innovation, sustainable engineering solutions can be developed. Future engineers need to acquire skills in their engineering curriculum to feel equipped to address sustainable design challenges in their career. This paper focuses on the impact of perceived design thinking traits and active learning strategies in design courses to increase senior engineering students’ motivation to engage in energy sustainability in their career. A national survey was distributed to senior engineering students in the United States (n = 4364). The survey asked students about their motivation to engage in sustainable design, their perceived design thinking traits (i.e., integrative feedback, collaboration), and if they experienced active learning strategies in design courses (i.e., learning by doing). The results highlight that higher perceived design thinking ability increases senior engineering students’ interests in designing solutions related to energy sustainability. Active learning experiences positively influence senior engineering students’ interests in designing solutions related to energy sustainability. These findings show the importance of teaching design thinking in engineering courses to empower future engineers to address sustainable challenges through design and innovation.
Use of Pyrolyzed Soybean Hulls as Fillers in Polypropylene and Linear Low Density Polyethylene
Authors: Coben Collin , Sancaktar Erol
Published: November 2021

In the competitive market of plastic fillers, inexpensive and reliable materials are always sought after. Using a method of thermal conversion called pyrolysis, a potential contender was created from a plant biomass known as soybean hulls (SBH). SBH are a byproduct of the soybean farming industry and represent an abundant and inexpensive feedstock. The thermal conversion of SBH material gives rise to a lightweight carbon-rich filler called pyrolyzed soybean hulls (PSBH). We created two separate lots, lots A and B, with lot A corresponding to SBH pyrolyzed at 450 °C (PSBH-A) and lot B corresponding to SBH pyrolyzed at 500 °C (PSBH-B). Both lots of PSBH were also milled to reduce their particle size and tested against the as-received PSBH fillers. These milled materials were designated as ground soybean hulls (GSBH). Two different polyolefins, linear low-density polyethylene (LLDPE) and polypropylene (PP), were used for this study. The PSBH fillers were added to the polyolefins in weight percentages of 10%, 20%, 30%, 40%, and 50%, with the resulting plastic/PSBH composites being tested for their mechanical, thermal, and water absorption properties. In general, the addition of filler increased the maximum stress of the LLDPE/PSBH composites while reducing maximum stress of the PP/PSBH composites. The strain at maximum stress was reduced with increasing amounts of the PSBH filler for all composites. The modulus of elasticity generally increased with increasing filler amount. For thermal properties, the addition of the PSBH filler increased the heat distortion temperature, increased the thermal decomposition temperature, and reduced the heat of fusion of the composites compared to the neat polyolefins. The liquid absorption and thickness swelling in the materials were small overall but did increase with increasing amounts of the PSBH filler and with the time spent submerged in liquid. Milling the PSBH material into GSBH generally had small effects on the various tested material properties and led to easier mixing and a smoother finish on the surface of processed samples. The differences observed between lot A and lot B composites were often small or even negligible.
Brain Immunoinformatics: A Symmetrical Link between Informatics, Wet Lab and the Clinic
Authors: Papageorgiou Ismini , Bittner Daniel , Psychogios Marios Nikos , Hadjidemetriou Stathis
Published: November 2021

Breakthrough advances in informatics over the last decade have thoroughly influenced the field of immunology. The intermingling of machine learning with wet lab applications and clinical results has hatched the newly defined immunoinformatics society. Immunoinformatics of the central neural system, referred to as neuroimmunoinformatics (NII), investigates symmetrical and asymmetrical interactions of the brain-immune interface. This interdisciplinary overview on NII is addressed to bioscientists and computer scientists. We delineate the dominating trajectories and field-shaping achievements and elaborate on future directions using bridging language and terminology. Computation, varying from linear modeling to complex deep learning approaches, fuels neuroimmunology through three core directions. Firstly, by providing big-data analysis software for high-throughput methods such as next-generation sequencing and genome-wide association studies. Secondly, by designing models for the prediction of protein morphology, functions, and symmetrical and asymmetrical protein–protein interactions. Finally, NII boosts the output of quantitative pathology by enabling the automatization of tedious processes such as cell counting, tracing, and arbor analysis. The new classification of microglia, the brain’s innate immune cells, was an NII achievement. Deep sequencing classifies microglia in “sensotypes” to accurately describe the versatility of immune responses to physiological and pathological challenges, as well as to experimental conditions such as xenografting and organoids. NII approaches complex tasks in the brain-immune interface, recognizes patterns and allows for hypothesis-free predictions with ultimate targeted individualized treatment strategies, and personalizes disease prognosis and treatment response.
Parking and Ride Induction Methods for Drivers in Commuting Scenes
Authors: Zheng Lili , Xie Zifang , Ding Tongqiang , Xi Jianfeng , Meng Fanyun
Published: November 2021

Parking and ride is a very effective method to improve the traffic condition of commuter channels, and it is necessary to develop effective parking guidance strategies. In this study, considering the travel time, walking distance, parking cruise time, parking fee, and personal attributes of drivers, a probability model of parking and ride selection in commuter scenarios was proposed, and a dynamic price adjustment method based on the equilibrium of parking occupancy in the region was constructed. The parking price was adjusted by determining the target occupancy, thus affecting the parking choice behavior to guide the commuter to park. The example analysis showed that this method adjusted the selection probability of the parking lot by using the dynamic price adjustment method from the perspective of regional parking occupancy equilibrium, solved the model by symmetric duality algorithm and formulated a reasonable parking replacement induction scheme to achieve the goal of occupancy equilibrium. Compared with parking guidance under static pricing, it can avoid the crowding of commuter vehicles into the city center effectively to reduce the congestion of commuter channels.
Digital Twin-Enabled Decision Support in Mission Engineering and Route Planning
Authors: Lee Eugene Boon Kien , Van Bossuyt Douglas L. , Bickford Jason F.
Published: November 2021

This article presents a Model-Based Systems Engineering (MBSE) methodology for the development of a Digital Twin (DT) for an Unmanned Aerial System (UAS) with the ability to demonstrate route selection capability with a Mission Engineering (ME) focus. It reviews the concept of ME and integrates ME with a MBSE framework for the development of the DT. The methodology is demonstrated through a case study where the UAS is deployed for a Last Mile Delivery (LMD) mission in a military context where adversaries are present, and a route optimization module recommends an optimal route to the user based on a variety of inputs including potential damage or destruction of the UAS by adversary action. The optimization module is based on Multiple Attribute Utility Theory (MAUT) which analyzes predefined criteria which the user assessed would enable the successful conduct of the UAS mission. The article demonstrates that the methodology can execute a ME analysis for route selection to support a user’s decision-making process. The discussion section highlights the key MBSE artifacts and also highlights the benefits of the methodology which standardizes the decision-making process thereby reducing the negative impact of human factors which may deviate from the predefined criteria.
An Alternative Method to Develop Embroidery Textile Strain Sensors
Authors: Martínez-Estrada Marc , Gil Ignacio , Fernández-García Raúl
Published: November 2021

In this paper, a method to develop embroidered textile strain resistive sensors is presented. The method is based on two overlapped zigzag conductive yarn patterns embroidered in an elastic textile. To demonstrate the functionality of the proposed configuration, a textile sensor embroidered with a conductor yarn composed of 99% pure silver-plated nylon yarn 140/17 dtex has been experimentally characterised for an elongation range from 0% to 65%. In order to show the sensor applicability, a second test with the sensor embroidered in a knee-pad has been done to evaluate the flexion knee angle from 180° to 300°. The experimental results show the usefulness of the proposed method to develop fabric strain sensors that can help to manufacture commercial applications on the healthcare sector.