bluuebunny/crossref_metadata_2025 huggingface dataset:
Closed-Form UAV LoS Blockage Probability in Mixed Ground- and Rooftop-Mounted Urban mmWave NR Deployments
Authors: Begishev Vyacheslav , Moltchanov Dmitri , Gaidamaka Anna , Samouylov Konstantin
Published: January 2022

Unmanned aerial vehicles (UAV) are envisioned to become one of the new types of fifth/sixth generation (5G/6G) network users. To support advanced services for UAVs such as video monitoring, one of the prospective options is to utilize recently standardized New Radio (NR) technology operating in the millimeter-wave (mmWave) frequency band. However, blockage of propagation paths between NR base stations (BS) and UAV by buildings may lead to frequent outage situations. In our study, we use the tools of integral geometry to characterize connectivity properties of UAVs in terrestrial urban deployments of mmWave NR systems using UAV line-of-sight (LoS) blockage probability as the main metric of interest. As opposed to other studies, the use of the proposed approach allows us to get closed-form approximation for LoS blockage probability as a function of city and network deployment parameters. As one of the options to improve connectivity we also consider rooftop-mounted mmWave BSs. Our results illustrate that the proposed model provides an upper bound on UAV LoS blockage probability, and this bound becomes more accurate as the density of mmWave BS in the area increases. The closed-form structure allows for identifying of the street width, building block and BS heights, and UAV altitude as the parameters providing the most impact on the considered metric. We show that rooftop-mounted mmWave BSs allow for the drastic improvement of LoS blockage probability, i.e., depending on the system parameters the use of one rooftop-mounted mmWave BS is equivalent to 6–12 ground-mounted mmWave BSs. Out of all considered deployment parameters the street width is the one most heavily affecting the UAV LoS blockage probability. Specifically, the deployment with street width of 20 m is characterized by 50% lower UAV LoS blockage probability as compared to the one with 10 m street width.
Ex Vivo Evaluation of Mechanical Anisotropic Tissues with High-Frequency Ultrasound Shear Wave Elastography
Authors: Lee Seungyeop , Eun Lucy Youngmin , Hwang Jae Youn , Eun Yongsoon
Published: January 2022

The use of imaging devices to assess directional mechanics of tissues is highly desirable. This is because the directional mechanics depend on fiber orientation, and altered directional mechanics are closely related to the pathological status of tissues. However, measuring directional mechanics in tissues with high-stiffness is challenging due to the difficulty of generating localized displacement in these tissues using acoustic radiation force, a general method for generating displacement in ultrasound-based elastography. In addition, common ultrasound probes do not provide rotational function, which makes the measurement of directional mechanics inaccurate and unreliable. Therefore, we developed a high-frequency ultrasound mechanical wave elastography system that can accommodate a wide range of tissue stiffness and is also equipped with a motorized rotation stage for precise imaging of directional mechanics. A mechanical shaker was applied to the elastography system to measure tissues with high-stiffness. Phantom and ex vivo experiments were performed. In the phantom experiments, the lateral and axial resolution of the system were determined to be 144 μm and 168 μm, respectively. In the ex vivo experiments, we used swine heart and cartilage, both of which are considered stiff. The elastography system allows us to acquire the directional mechanics with high angular resolution in the heart and cartilage. The results demonstrate that the developed elastography system is capable of imaging a wide range of tissues and has high angular resolution. Therefore, this system might be useful for the diagnostics of mechanically anisotropic tissues via ex vivo tests.
Perception, Positioning and Decision-Making Algorithms Adaptation for an Autonomous Valet Parking System Based on Infrastructure Reference Points Using One Single LiDAR
Authors: Jiménez Felipe , Clavijo Miguel , Cerrato Alejandro
Published: January 2022

Autonomous parking valet systems improve users’ comfort, helping with the task of searching for a parking space and parking maneuvering; and due to the simple infrastructure design and low speeds, this maneuver is quite feasible for automated vehicles. Various demonstrations have been performed in both closed parking and in open air parking; scenarios that allow the use of specific technological tools for navigation and searching for a parking space. However, there are still challenges. The purpose of this paper was the integration of perception, positioning, decision-making, and maneuvering algorithms for the control of an autonomous vehicle in a parking lot with the support of a single LiDAR sensor, and with no additional sensors in the infrastructure. Based on a digital map, which was as simplified as possible, the driver can choose the range of parking spaces in which the vehicle must look for a space. From that moment on, the vehicle moves, looking for free places until an available one in the range selected by the driver is found. Then, the vehicle performs the parking maneuver, choosing between two alternatives to optimize the required space. Tests in a real parking lot, with spaces covered with metallic canopies, showed an accurate behavior.
Nonlinear Analytics for Electrochemical Biosensor Design Using Enzyme Aggregates and Delayed Mass Action
Authors: Martsenyuk Vasyl , Klos-Witkowska Aleksandra , Dzyadevych Sergei , Sverstiuk Andriy
Published: January 2022

The paper is devoted to the extension of Brown’s model of enzyme kinetics to the case with distributed delays. Firstly, we construct a multi-substrate multi-inhibitor model using discrete and distributed delays. Furthermore, we consider simplified models including one substrate and one inhibitor, for which an experimental study has been performed. The algorithm of parameter identifications was developed which was tested on the experimental data of solution conductivity. Both the model and Kohlrausch’s law parameters are obtained as a result of the optimization procedure. Comparison of plots constructed with the help of the estimated parameters has shown that in such case the model with distributed delays is more chemically adequate in comparison with the discrete one. The methods of generalization of the results to the multi-substrate multi-inhibitor cases are discussed.
Interaction Design Patterns for Augmented Reality Fitting Rooms
Authors: Battistoni Pietro , Di Gregorio Marianna , Romano Marco , Sebillo Monica , Vitiello Giuliana , Brancaccio Alessandro
Published: January 2022

In this work, we explore the role of augmented reality as a meta-user interface, with particular reference to its applications for interactive fitting room systems and the impact on the related shopping experience. Starting from literature and existing systems, we synthesized a set of nine interaction design patterns to develop AR fitting rooms and to support the shopping experience. The patterns were evaluated through a focus group with possible stakeholders with the aim of evaluating and envisioning the effects on the shopping experience. The focus group analysis shows as a result that the shopping experience related to an AR fitting room based on the proposed patterns is influenced by three main factors, namely: the perception of the utility, the ability to generate interest and curiosity, and the perceived comfort of the interaction and environment in which the system is installed. As a further result, the study shows that the patterns can successfully support these factors, but some elements that emerged from the focus group should be more investigated and taken into consideration by the designers.
Rayleigh-Wave Dispersion Analysis and Inversion Based on the Rotation
Authors: Sun Lixia , Wang Yun , Qiu Xinming
Published: January 2022

Rotational observation is essential for a comprehensive description of the ground motion, and can provide additional wave-field information. With respect to the three typical layered models in shallow engineering geology, under the assumption of linear small deformation, we simulate the 2-dimensional radial, vertical, and rotational components of the wave fields and analyze the different characteristics of Rayleigh wave dispersion recorded for the rotational and translational components. Then, we compare the results of single-component inversion with the results of multi-component joint inversion. It is found that the rotational component has wider spectral bands and more higher modes than the translational components, especially at high frequencies; the rotational component has better anti-interference performance in the noisy data test, and it can improve the inversion accuracy of the shallow shear-wave velocity. The field examples also show the significant advantages of the joint utility of the translational and rotational components, especially when a low-velocity layer exists. Rotational observation shall be beneficial for shallow surface-wave exploration.
Fall Risk Assessment Using Wearable Sensors: A Narrative Review
Authors: Ferreira Rafael N. , Ribeiro Nuno Ferrete , Santos Cristina P.
Published: January 2022

Recently, fall risk assessment has been a main focus in fall-related research. Wearable sensors have been used to increase the objectivity of this assessment, building on the traditional use of oversimplified questionnaires. However, it is necessary to define standard procedures that will us enable to acknowledge the multifactorial causes behind fall events while tackling the heterogeneity of the currently developed systems. Thus, it is necessary to identify the different specifications and demands of each fall risk assessment method. Hence, this manuscript provides a narrative review on the fall risk assessment methods performed in the scientific literature using wearable sensors. For each identified method, a comprehensive analysis has been carried out in order to find trends regarding the most used sensors and its characteristics, activities performed in the experimental protocol, and algorithms used to classify the fall risk. We also verified how studies performed the validation process of the developed fall risk assessment systems. The identification of trends for each fall risk assessment method would help researchers in the design of standard innovative solutions and enhance the reliability of this assessment towards a homogeneous benchmark solution.
Knowledge Graph Based Hard Drive Failure Prediction
Authors: Chhetri Tek Raj , Kurteva Anelia , Adigun Jubril Gbolahan , Fensel Anna
Published: January 2022

The hard drive is one of the important components of a computing system, and its failure can lead to both system failure and data loss. Therefore, the reliability of a hard drive is very important. Realising this importance, a number of studies have been conducted and many are still ongoing to improve hard drive failure prediction. Most of those studies rely solely on machine learning, and a few others on semantic technology. The studies based on machine learning, despite promising results, lack context-awareness such as how failures are related or what other factors, such as humidity, influence the failure of hard drives. Semantic technology, on the other hand, by means of ontologies and knowledge graphs (KGs), is able to provide the context-awareness that machine learning-based studies lack. However, the studies based on semantic technology lack the advantages of machine learning, such as the ability to learn a pattern and make predictions based on learned patterns. Therefore, in this paper, leveraging the benefits of both machine learning (ML) and semantic technology, we present our study, knowledge graph-based hard drive failure prediction. The experimental results demonstrate that our proposed method achieves higher accuracy in comparison to the current state of the art.
Demonstrating the Potential of a Low-Cost Soil Moisture Sensor Network
Authors: Briciu-Burghina Ciprian , Zhou Jiang , Ali Muhammad Intizar , Regan Fiona
Published: January 2022

Soil moisture is a key parameter of the climate system as it relates to plant transpiration and photosynthesis and impacts land–atmosphere interactions. Recent developments have seen an increasing number of electromagnetic sensors available commercially (EM) for soil volumetric water content (θ). Their use is constantly expanding, and they are becoming increasingly used for agricultural, ecological, and geotechnical applications and climate research, providing decision support and high-resolution data for models and machine-learning algorithms. In this study, a soil moisture sensor network consisting of 10 Sense Cap capacitance-based sensors is evaluated. Analytical performance of the sensors was determined based on laboratory and field measurements with dielectric permittivity (ε) standards and soil media substrates. Sensor response normalisation to standards of known ε was found to reduce intersensor variability and provide robust estimates of θ in soil samples with known θ. Cross-comparison with a time-domain reflectometry (TDR) instrument carried out in two soil media demonstrates good agreement between the two probes throughout the tested range. The data communication performance of the network was evaluated in terms of packet drop rate at different ranges and sampling frequencies. It was noticed that the drop rate increased with distance from the gateway, while sampling frequency had no effect. Sources of errors associated with probe installation were identified and recommendations are provided for sensor deployment. The off-the-shelf all-in-one solution provided by Sense Cap is low cost, user friendly and suitable for implementation at temporal and spatial scales once the identified shortcomings are addressed. The evaluation presented aims to aid stakeholders and users involved in soil and land management practices including crop production, soil conservation, carbon sequestration and pollutants transport.
Multi-Path U-Net Architecture for Cell and Colony-Forming Unit Image Segmentation
Authors: Jumutc Vilen , Bļizņuks Dmitrijs , Lihachev Alexey
Published: January 2022

U-Net is the most cited and widely-used deep learning model for biomedical image segmentation. In this paper, we propose a new enhanced version of a ubiquitous U-Net architecture, which improves upon the original one in terms of generalization capabilities, while addressing several immanent shortcomings, such as constrained resolution and non-resilient receptive fields of the main pathway. Our novel multi-path architecture introduces a notion of an individual receptive field pathway, which is merged with other pathways at the bottom-most layer by concatenation and subsequent application of Layer Normalization and Spatial Dropout, which can improve generalization performance for small datasets. In general, our experiments show that the proposed multi-path architecture outperforms other state-of-the-art approaches that embark on similar ideas of pyramid structures, skip-connections, and encoder–decoder pathways. A significant improvement of the Dice similarity coefficient is attained at our proprietary colony-forming unit dataset, where a score of 0.809 was achieved for the foreground class.
An IoT-Aware Solution to Support Governments in Air Pollution Monitoring Based on the Combination of Real-Time Data and Citizen Feedback
Authors: Montanaro Teodoro , Sergi Ilaria , Basile Matteo , Mainetti Luca , Patrono Luigi
Published: January 2022

One of the main concerns of the last century is regarding the air pollution and its effects caused on human health. Its impact is particularly evident in cities and urban areas where governments are trying to mitigate its effects. Although different solutions have been already proposed, citizens continue to report bad conditions in the areas in which they live. This paper proposes a solution to support governments in monitoring the city pollution through the combination of user feedbacks/reports and real-time data acquired through dedicated mobile IoT sensors dynamically re-located by government officials to verify the reported conditions of specific areas. The mobile devices leverage on dedicated sensors to monitor the air quality and capture main roads traffic conditions through machine learning techniques. The system exposes a mobile application and a website to support the collection of citizens’ reports and show gathered data to both institutions and end-users. A proof-of-concept of the proposed solution has been prototyped in a medium-sized university campus. Both the performance and functional validation have demonstrated the feasibility and the effectiveness of the system and allowed the definition of some lessons learned, as well as future works.
A Distributed Localization Method for Wireless Sensor Networks Based on Anchor Node Optimal Selection and Particle Filter
Authors: Luo Qinghua , Liu Chao , Yan Xiaozhen , Shao Yang , Yang Kexin , Wang Chenxu , Zhou Zhiquan
Published: January 2022

In wireless sensor networks, due to the significance of the location information of mobile nodes for many applications, location services are the basis of many application scenarios. However, node state and communication uncertainty affect the distance estimation and position calculation of the range-based localization method, which makes it difficult to guarantee the localization accuracy and the system robustness of the distributed localization system. In this paper, we propose a distributed localization method based on anchor nodes selection and particle filter optimization. In this method, we first analyze the uncertainty of error propagation to the least-squares localization method. According to the proportional relation between localization error and uncertainty propagation, anchor nodes are selected optimally in real-time during the movement of mobile nodes. Then we use the ranging and position of the optimally selected anchor nodes to obtain the location information of the mobile nodes. Finally, the particle filter (PF) algorithm is utilized to gain the optimal estimation of the localization results. The experimental evaluation results verified that the proposed method effectively improves the localization accuracy and the robustness of the distributed system.
Position Control of a Pneumatic Drive Using a Fuzzy Controller with an Analytic Activation Function
Authors: Šitum Željko , Ćorić Danko
Published: January 2022

The fuzzy logic controller, which uses an analytic activation function for the defuzzification procedure, was applied to the position control of a servo pneumatic drive controlled by a proportional valve. The Gaussian shape of input fuzzy sets, with the possibility of their modification, was used to fuzzify the input signal. The control signal was determined by introducing an analytic function instead of defining the fuzzy rule base. In this way, a conventional 2-D fuzzy rule table base is modified into 1-D fuzzy defuzzification based on an analytic function to calculate the controller output. In this control algorithm, the problem of conventional fuzzy logic control, in terms of the exponential growth in rules as the number of input variables increases, is eliminated. The synthesis controller procedure is adjusted to the flow rate characteristic of the proportional valve. The developed control algorithms are verified by computer simulation and by testing on a real pneumatic rodless cylindrical drive.
A Simple Preparation Method of Graphene and TiO2 Loaded Activated Carbon Fiber and Its Application for Indoor Formaldehyde Degradation
Authors: Liu Fang , Gao Xuezhi , Peng Man
Published: January 2022

Formaldehyde has a significant impact on human health. This study used a simple dipping method to load graphene-titanium dioxide (GR-TiO2) on activated carbon fibers (ACFs). The microstructure of GR-TiO2/ACF hybrid material was observed by SEM, combined with XRD and BET analysis. The result showed that the GR-TiO2/ACF hybrid material had a specific surface area of 893.08 m2/g and average pore size of 2.35 nm. The formaldehyde degradation efficiency of the prepared material was tested under different conditions, such as ultraviolet (UV) radiation, air supply volume, relative humidity, initial mass concentration. The results showed that the UV radiation intensity, airflow and the initial mass concentration were positively correlated with the formaldehyde removal rate, and the relative humidity was negatively correlated with the formaldehyde removal rate. The GR-TiO2/ACF hybrid material had a maximum formaldehyde removal rate of 85.54% within 120 min.
MOF@chitosan Composites with Potential Antifouling Properties for Open-Environment Applications of Metal-Organic Frameworks
Authors: Jansen Christian , Tran-Cong Nam Michael , Schlüsener Carsten , Schmitz Alexa , Proksch Peter , Janiak Christoph
Published: January 2022

Metal-organic frameworks (MOFs) are promising materials for a myriad of applications because of their easy synthesis and large variability through the organic linker. For open-environment applications, the organic content can, however, give rise to fouling, that is, biofilm formation. Biofilms can destroy the MOF and reduce the sorption capacity. Therefore, it is necessary to formulate MOFs for open-environment application to avoid the growth of microorganisms. Chitosan is a polysaccharide biopolymer, obtained from chitin shells of shrimps by alkaline deacetylation, and has known fungistatic properties. Here, chitosan is used as a matrix for MOF@chitosan composites with different aluminum-based MOFs to implement the fungistatic effect of chitosan to MOFs. The obtained composites with the highest possible MOF loadings of up to 90% were tested according to DIN EN ISO 846 to examine the fungistatic material properties against the fungi Chaetomium globosum and Aspergillus falconensis.
Exploring Tourists’ Intentions to Purchase Homogenous Souvenirs
Authors: Wu Jianfeng , Zhang Lingyan , Lu Chunfu , Zhang Lekai , Zhang Yaya , Cai Qingli
Published: January 2022

In the context of people’s gradually rising consumption levels and the urgent need to upgrade the tourism market, the continuous homogenization of tourism souvenirs is beginning to seriously affect the shopping experience of tourism tourists. This study aims to explore how tourists perceive the phenomenon of the homogenization of tourism souvenirs and how this phenomenon affects tourists’ continuous purchase intention. This study constructs a hypothesis model of the relationship among perceived homogeneity, perceived value, and continuous purchase intention based on a perceived value perspective and validates the model using structural equations. These findings are as follows: (1) Tourists’ perceived product homogeneity and perceived service homogeneity have significant negative effects on perceived product value and continuous purchase intention. (2) Perceived service homogeneity has a significant negative effect on tourists’ perceived emotional value. (3) Perceived product value and perceived emotional value have significant positive effects on continuous purchase intention. The study also explores how to enhance tourists’ perceived value through innovative product design and service system construction. The findings can provide valuable insights for promoting the sustainable development of the tourism market and tourists’ continuous purchase intention.
How Many Electric Vehicles Are Needed to Reach CO2 Emissions Goals? A Case Study from Montreal, Canada
Authors: Laffont Pierre , Waygood E. Owen D. , Patterson Zachary
Published: January 2022

In the province of Quebec, Canada where the electricity is nearly carbon-free, the road transport sector represents 35.6% of all emissions. As such, electric vehicles (EVs) have been proposed as a means to reduce such emissions. However, it is not clear how many conventional vehicles (CVs) would need to change to electric in order to meet the greenhouse gas (GHG) emissions reduction target of reducing 1990 CO2 emissions by 37.5% by 2030 in the province. In fact, various considerations exist such as which vehicles will change and how those vehicles are used. This articleaddresses this issue in the case of Montreal, Canada. First, to create a baseline, direct emissions by all personal vehicles in Montreal in 2018 are calculated using data from the 2018 origin-destination (OD) survey and provincial vehicle registration. Next, five scenarios are studied to calculate the variations in the number of EVs needed in the fleet in order to achieve provincial targets. The most optimistic scenario shows that roughly 49% of the fleet would need to change. The most pessimistic scenario estimates that almost 73% of the fleet would need to be converted to EVs. It can be concluded that the strategy used can have a great impact on how many vehicles need to be replaced in the fleet. However, all simulations show that the necessary replacements are far from negligible. It must surely be coupled with other actions such as reducing veh.km travelled (vkmt) or increasing public transport use.
Solar Chimney Power Plants: A Review of the Concepts, Designs and Performances
Authors: Cuce Erdem , Cuce Pinar Mert , Carlucci Salvatore , Sen Harun , Sudhakar Kumarasamy , Hasanuzzaman Md. , Daneshazarian Reza
Published: January 2022

This research presents a comprehensive review of solar chimney power plants (SCPP) as a reliable source of renewable electricity generation. Solar chimney power plants differ from other renewable energy technologies because thermal and momentum effects result in 24-h electricity generation. However, they are influenced by a wide range of design, geometrical and operational parameters, and environmental conditions. This review evaluates the design aspects and the theoretical, numerical, experimental, and performance findings in previous works holistically and concisely. The study also extensively discusses the various optimization strategies, advantages, disadvantages, and limitations of solar chimney power plants. Energy storage aspects and hybrid system designs are also addressed in the present review in order to overcome the known handicaps and limitations of solar chimney power plants. The performance figures of the technology are clearly demonstrated as a function of the design and operational conditions, and future prospects are discussed in detail. It is hoped that designers and policymakers will gain valuable insight into the technological features and advancements of solar chimney power plants, assisting them in making a better-informed decision.
Relation between Globe Latitude and the Quality of Life: Insights for Public Policy Management
Authors: Pawliczek Adam , Kurowska-Pysz Joanna , Smilnak Richard
Published: January 2022

Life quality and its determinants represent a topic which is essential to all civilizations, past and present. This paper employs common methods for inspecting factors of correlation with the aim of assessing the influence of geographical location on life quality and happiness. After setting a stable theoretical cornerstone, the article works with the measures reported by the Human Development Index (HDI) and the World Happiness Score (WHS). The work finds and proves ties between the globe latitude of one’s dwelling and their reported life quality measures, with the main conclusion being that the quality of life measured by the HDI and WHS is spread around the globe asymmetrically regarding latitude. Following the results of the research, possible reasons such as enhanced strategic thinking and an emphasis on sounder plans for living embedded in public policy are discussed. Recommendations point toward the possibility of the global north issuing aid to the global south, not in the form of financial capital, but in the form of a knowledge transfer through technology-enabled learning as a means for uplifting global well-being.
Consumption-Based CO2 Emissions on Sustainable Development Goals of SAARC Region
Authors: Rahman Mohammad Mazibar , Ahmed Rafiuddin , Mashud Abu Hashan Md. , Malik Asif Iqbal , Miah Sujan , Abedin Mohammad Zoynul
Published: January 2022

Consumption-based CO2 emission (CBE) accounting shows the possibility of global carbon leakage. Very little attention has been paid to the amount of emissions related to the consumption of products and services and their impact on sustainable development goals (SDGs), especially in the SAARC region. This study used a CBE accounting method to measure the CO2 emissions of five major SAARC member countries. Additionally, a Fully Modified Ordinary Least Square (FMOLS) and a causality model were used to investigate the long-term effects of the CBE and SDG variables between 1972 and 2015. The results showed that household consumption contributed more than 62.39% of CO2 emissions overall in the SAARC region. India had the highest household emissions, up to 37.27%, and Nepal contributed the lowest, up to 0.61%. The total imported emissions were the greatest in India (16.88 Gt CO2) and Bangladesh (15.90 Gt CO2). At the same time, the results for the long-term relationships between the CBEs and SDGs of the SAARC region showed that only the combustible renewables and waste (CRW) variable is significant for most of these countries. The sharing of the responsibility for emissions between suppliers and customers could encourage governments and policymakers to make global climate policy and sustainable development decisions, which are currently stalled by questions over geographical and past emission inequities.
A Study on Growth Engines of Middle Market Enterprise (MME) of Korea Using Meta-Analysis
Authors: Kim Minseo , Lim Seongbae , Sawng Yeong-wha
Published: January 2022

The purpose of this study is to comprehensively review previous studies and discover implications for the sustainable growth engines of middle market enterprise (MME) of Korea using meta-analysis. Since Germany’s hidden champion companies are considered as benchmarking targets because their economic environment and size are similar to those of Korean MMEs, a meta-analysis was conducted on the previous studies of them. As a result of integrating the effect sizes of input and output factors according to the process of the Program Logic model from the viewpoint of dynamic capabilities, 198 in Germany and 229 in Korea were derived. It was found that, unlike Korean companies, the number of skilled workers, labor productivity, CEO experience, and Innovation activities within the firm had a significant impact on Germany’s hidden champion companies. In addition, industry and region-oriented innovation networks and family businesses were identified as important variables. Meta-analysis collects a large number of individual studies in order to integrate the results and statistically assess the data. As a result, it will be used as basic data for developing models for academic research in the future. In addition, it will provide implications for sectors in which Korean MMEs should concentrate their efforts in order to create an innovative ecosystem.
Impact of China’s Provincial Government Debt on Economic Growth and Sustainable Development
Authors: Yang Wanping , Zhang Zhenya , Wang Yajuan , Deng Peidong , Guo Luyao
Published: January 2022

Macroeconomic stability is the core concept of sustainable development. However, the coronavirus disease (COVID-19) pandemic has caused government debt problems worldwide. In this context, it is of practical significance to study the impact of government debt on economic growth and fluctuations. Based on panel data of 30 provinces in China from 2012 to 2019, we used the Mann–Kendall method and Kernel Density estimation to analyze the temporal and spatial evolution of China’s provincial government debt ratio and adopted a panel model and HP filtering method to study the impact of provincial government debt on economic growth and fluctuation. Our findings indicate that, during the sample period, China’s provincial government debt promoted economic growth and the regression coefficient (0.024) was significant. From different regional perspectives, the promotion effect of the central region (0.027) is higher than that of the eastern (0.020) and western regions (0.023). There is a nonlinear relationship between China’s provincial government debt and economic growth, showing an inverted “U-shaped” curve. Fluctuations in government debt aggravate economic volatility, with a coefficient of 0.009; tax burden fluctuation and population growth rate aggravate economic changes. In contrast, the optimization of the province’s industrial structure and the improvement of the opening level of provinces slow down economic fluctuations.
Planning Perspectives on Rural Connected, Autonomous and Electric Vehicle Implementation
Authors: Walters Joseph G. , Marsh Stuart , Rodrigues Lucelia
Published: January 2022

Connected, autonomous and electric vehicles (CAEV) are a powerful combined transport technology looking to disrupt the automotive sector and drive the transition to safe, accessible, clean and sustainable transport systems. The trialling of private, public and shared CAEV technologies is occurring in cities around the world; however, historically isolated and transport-poor rural communities may have the most to gain from CAEV implementation. Despite the accessibility and transport safety needs of rural communities, rural CAEV trials are few in the UK. Therefore, this paper investigates the hypothesis that the lack of rural implementation research and trials means that rural transport planners are ill-informed and uncertain of both the potential of CAEVs and their implementation requirements to meet rural community transport needs. This investigation consists of consultations with UK-based transport planning professionals to establish their perspectives on CAEV technologies and their rural implementation potential. The findings show that 96% of transport planners lack sufficient understanding of CAEV technology and its implementation challenges. However, the findings also highlight a willingness, given the opportunity, for transport planners to engage with CAEV technologies and apply them to specifically rural scenarios.
Evaluating Evaporative Cooling Assisted Solid Desiccant Dehumidification System for Agricultural Storage Application
Authors: Hussain Ghulam , Aleem Muhammad , Sultan Muhammad , Sajjad Uzair , Ibrahim Sobhy M. , Shamshiri Redmond R. , Farooq Muhammad , Usman Khan Muhammad , Bilal Muhammad
Published: January 2022

The study aims to investigate Maisotsenko cycle evaporative cooling assisted solid desiccant air-conditioning (M-DAC) system for agricultural storage application. Conventional air-conditioning (AC) systems used for this application are refrigeration-based which are expensive as they consume excessive amount of primary-energy. In this regard, the study developed a lab-scale solid silica gel-based desiccant AC (DAC) system. Thermodynamic performance of the developed system was investigated using various adsorption/dehumidification and desorption/regeneration cycles. The system possesses maximum adsorption potential i.e., 4.88 g/kg-DA at higher regeneration temperature of 72.6 °C and long cycle time i.e., 60 min:60 min. Moreover, the system’s energy consumption performance was investigated from viewpoints of maximum latent, sensible, and total heat as well as latent heat ratio (LHR), which were found to be 0.64 kW, 1.16 kW, and 1.80 kW, respectively with maximum LHR of 0.49. Additionally, the study compared standalone DAC (S-DAC), and M-DAC system thermodynamically to investigate the feasibility of these systems from the viewpoints of temperature and relative humidity ranges, cooling potential (Qp), and coefficient of performance (COP). The S-DAC system showed temperature and relative humidity ranging from 39 °C to 48 °C, and 35% to 66%, respectively, with Qp and COP of 17.55 kJ/kg, and 0.37, respectively. Conversely, the M-DAC system showed temperature and relative humidity ranging from 17 °C to 25 °C, and 76% to 98%, respectively, with Qp and COP of 41.80 kJ/kg, and 0.87, respectively. Additionally, the study investigated respiratory heat generation rate (Qres), and heat transfer rate (Qrate) by agricultural products at different temperature gradient (∆T) and air velocity. The Qres and Qrate by the products were increased with ∆T and air velocity, respectively, thereby generating heat loads in the storage house. Therefore, the study suggests that the M-DAC system could be a potential AC option for agricultural storage application.
Assessment of Final Space Cooling Consumption in the European Transportation Sector
Authors: Quaglini Giulio , Pezzutto Simon , Grotto Andrea , Wilczynski Eric
Published: January 2022

The current study aims to investigate one of the most underexplored energy fields in scientific research, i.e., final energy consumption (FEC) of space cooling (SC) in the European (EU27+UK) transportation sector with 2019 as a baseline. The fundamentals of this study include a comprehensive literature review as well as the creation of a dataset characterized by completeness and reliability. Different essential input parameters have been investigated and the encountered data and information gaps have been filled. The transportation sector has been broken down into three main categories, namely, light, medium, and heavy vehicles. Throughout the EU27+UK, the number of vehicles, equivalent full load hours (EFLHs), system power capacities, and their related energy efficiency levels have been collected. The collected data and information have been computed and the EU27+UK FEC for space cooling in the transportation sector resulted in more than 125 TWh/year. It is worth underlining that the light vehicles category accounted for the majority of the total FEC, followed by the medium and heavy vehicle categories, respectively.
The Relationships between the Pillars of TPM and TQM and Manufacturing Performance Using Structural Equation Modeling
Authors: Al-Refaie Abbas , Lepkova Natalija , Camlibel Mehmet Emre
Published: January 2022

This paper examines the direct and indirect relationships between the pillars of total quality management (TQM) and total productive maintenance (TPM) and investigates their effects on manufacturing performance (MPR) using structural equation modeling. Three structural models were developed with their corresponding hypotheses. Data were then collected from thirty industrial firms in Jordan. A descriptive statistical analysis was followed by an analysis of variance (ANOVA). The structural models were analyzed to draw conclusions about the model hypotheses and identify the most influential TPM and TQM pillars on MPR. Significant variations were noticed among firms in the implementation levels of the TPM, TQM, and MPR pillars. Further, it was found that TPM directly and indirectly influences MPR. Furthermore, TPM pillars have a larger impact on MPR than TQM. Research hypotheses are suggested to be tested individually on small-, middle-, and large-sized firms. This research provides valuable information on top management in the industrial sector, on the significant relationships between the pillars of TPM, TQM, and MPR and supports them in identifying important TQM/TPM pillars which they should focus on in order to enhance MPR.
Research on the Connotation and Dimension of Consumers’ Quantified-Self Consciousness
Authors: Jin Hong , Peng Ying , Chen Jian , Park Seong Taek
Published: January 2022

Quantified-self practice has penetrated into people’s daily life. Academic circles have begun to study it, but at present, scholars have not raised quantified-self practice to the level of consciousness. In order to explore the structural connotation of quantified-self consciousness and then provide management reference for enterprises offering quantified-self services, this study conducted in-depth interviews with self-trackers with the method of grounded theory. The conceptual model of quantified-self consciousness is formed through step-by-step coding, and the theoretical saturation is tested by reserving original sentences and crawling relevant online comments. The model shows that quantified-self consciousness can be divided into three dimensions: individual thinking, social projection, and data sensitivity.
How Are Leadership, Virtues, HRM Practices, and Citizenship Related in Organizations? Testing of Mediation Models in the Light of Positive Organizational Studies
Authors: Demo Gisela , Coura Karla , Fogaça Natasha , Costa Ana Carolina , Scussel Fernanda , Montezano Lana
Published: January 2022

Studies show that Human Resource Management (HRM) practices, the role of leadership, organizational citizenship behavior, and organizational virtues influence the greater involvement of professionals at work and, consequently, the organizational performance. However, there is a lack of investigations encompassing these four variables in the same research model. Thus, the main objective of this study was to identify the relationship between leadership, organizational virtues, HRM practices, and organizational citizenship behaviors in a sample of employees of Brazilian companies. A printed questionnaire was administered to a valid sample of 659 subjects, who participated voluntarily, from public and private organizations in a Brazilian State. A total of seven hypotheses were tested using confirmatory factor analysis to assess the fit of the measurement models of the four studied variables, in addition to path analysis, using structural equation modeling to specify and estimate the mediation models. All hypotheses were confirmed, attesting to the positive predictive associations between the variables. We also confirm the partial mediation of HRM practices in the relationship between leadership and citizenship and the total mediation in the relationship between virtues and citizenship. This research advances the efforts to test more complex and unexplored structural models in which HRM practices are mediating variables, fulfilling a gap in the literature, as well as providing investigations of antecedents and consequents of the variables adopted in the research. As practical implications, the findings constitute a diagnosis for managers to understand how these relationships happen, supporting decision-making towards an increasingly effective, strategic, and humanized HRM.
Optimal Control for a Class of Riemann-Liouville Fractional Evolution Inclusions
Authors: Yang He , Ren Qian
Published: January 2022

In this paper, under symmetric properties of multivalued operators, the existence of mild solutions as well as optimal control for the nonlocal problem of fractional semilinear evolution inclusions are investigated in abstract spaces. At first, the existence results are proved by applying the theory of operator semigroups and the fixed-point theorem of multivalued mapping. Then the existence theorem on the optimal state-control pair is proved by constructing the minimizing sequence twice. An example is given in the last section as an application of the obtained conclusions.
Potential Energy Surfaces for Noble Gas (Ar, Kr, Xe, Rn)–Propylene Oxide Systems: Analytical Formulation and Binding
Authors: Palazzetti Federico , Coletti Cecilia , Marrone Alessandro , Pirani Fernando
Published: January 2022

Multidimensional potential energy surfaces for heavy noble gas–propylene oxide systems are obtained by applying the phenomenological method successfully used to describe homologous systems involving He and Ne atoms. Such potential energy surfaces, where the interaction exclusively arises from the anisotropic van der Waals interaction components, are given in an analytical form. Therefore, they can be easily used as force fields to carry out molecular simulations to evaluate spectroscopic features and the dynamical selectivity of weakly bound complexes formed by propylene oxide (a prototype chiral species) with a noble gas atom (a prototype isotropic partner) by two-body collisions under a variety of conditions. Several potential energy minima are identified on the surfaces, which are confirmed and characterized by high level ab initio calculations. The next step to further generalize this methodology is its extension to systems involving propylene oxide-diatomic molecules (as H2, O2 and N2), as well as to propylene oxide dimers.
Laser Based Navigation in Asymmetry and Complex Environment
Authors: Zhao Yuchen , Xie Keying , Liu Qingfei , Li Yawen , Wu Tian
Published: January 2022

For collision-free navigation in unstructured and cluttered environments, deep reinforcement learning (DRL) has gained extensive successes for being capable of adapting to new environments without much human effort. However, due to its asymmetry, the problems related to its lack of data efficiency and robustness remain as challenges. In this paper, we present a new laser-based navigation system for mobile robots, which combines a global planner with reinforcement learning-based local trajectory re-planning. The proposed method uses Proximal Policy Optimization to learn an efficient and robust local planning policy with asynchronous data generation and training. Extensive experiments have been presented, showing that the proposed system achieves better performance than previous methods including end-to-end DRL, and it can improve the asymmetrical performance. Our analysis show that the proposed method can efficiently avoid deadlock points and achieves a higher success rate. Moreover, we show that our system can generalize to unseen environments and obstacles with only a few shots. The model enables the warehouse to realize automatic management through intelligent sorting and handling, and it is suitable for various customized application scenarios.
Ultrasound Imaging of the Facial Muscles and Relevance with Botulinum Toxin Injections: A Pictorial Essay and Narrative Review
Authors: Wu Wei-Ting , Chang Ke-Vin , Chang Hsiang-Chi , Chen Lan-Rong , Kuan Chen-Hsiang , Kao Jung-Ting , Wei Ling-Ying , Chen Yunn-Jy , Han Der-Sheng , Özçakar Levent
Published: January 2022

High-resolution ultrasound is preferred as the first-line imaging modality for evaluation of superficial soft tissues, such as the facial muscles. In contrast to magnetic resonance imaging and computed tomography, which require specifically designated planes (axial, coronal and sagittal) for imaging, the ultrasound transducer can be navigated based on the alignment of facial muscles. Botulinum toxin injections are widely used in facial cosmetic procedures in recent times. Ultrasonography is recognized as a useful tool for pre-procedure localization of target muscles. In this pictorial review, we discuss the detailed sonoanatomy of facial muscles and their clinical relevance, particularly with regard to botulinum toxin injections. Furthermore, we have summarized the findings of clinical studies that report ultrasonographic imaging of facial muscles.
Correction: Batković et al. Axion-like Particle Searches with IACTs. Universe 2021, 7, 185
Authors: Batković Ivana , De Angelis Alessandro , Doro Michele , Manganaro Marina
Published: January 2022

The authors wish to make the following corrections to their paper [...]