bluuebunny/crossref_metadata_2025 huggingface dataset:
Internationalization of Large Companies from Central and Eastern Europe or the Birth of New Stars
Authors: Çela Arjona , Hysa Eglantina , Voica Marian Catalin , Panait Mirela , Manta Otilia
Published: December 2021

With rapid globalization, firm internationalization has become an important corporate strategy as well as the necessity for the survival and growth of the business. In the last decade, there has been a growth in literature that studies this field, especially in emerging countries. However, there exists a gap in the literature in CEE countries. This study aims to fill that gap by conducting an analysis and providing insight regarding the factors that lead to an increase in firm internationalization in this region. This research paper studies the main determinants that have an impact on the firm internationalization of large companies in CEE countries using panel data empirical methods, such as the random effect model and generalized method of moments (GMM) model for a panel of 50 firms from 11 CEE countries and a time duration of 14 years. This study determines the main factors that positively influence firm internationalization in selected countries. These countries have experienced a radical transition from centrally planned economies to market economies, and although they have experienced economic growth and a rise in productivity, they are still facing several challenges. Therefore, it is important to know what facilitates and helps firms to expand in international markets. The main findings derived from this study show that firm characteristics, such as age, size and corporate performance, have a positive effect on the internationalization process. An increase in age, size and firm performance leads to higher levels of internationalization. Larger and relatively older firms have access to more resources and are more experienced in dealing with the environmental difficulties characteristic of these countries.
A Developed Data Envelopment Analysis Model for Efficient Sustainable Supply Chain Network Design
Authors: Moghaddas Zohreh , Tosarkani Babak Mohamadpour , Yousefi Samuel
Published: December 2021

In recent years, various organizations have focused on considering the sustainability concept in the supply chain (SC) design. Managers try to increase the sustainability of SCs to achieve a competitive advantage in today’s growing market. Designing a sustainable supply chain (SSC) by integrating economic, social, and environmental dimensions affects the SC’s overall performance. To achieve the SSC, decision makers (DMs) are required to evaluate different strategies and then apply the most effective one to design SC networks. This study proposes an assessment approach based on the network data envelopment analysis (DEA) to choose an efficient strategy for each stage of an SSC network. This approach seeks to provide a sustainable design with DMs to avoid imposing additional costs on SCs that result from noncompliance with environmental and social issues. To this end, we consider sustainability-concept-related inputs and outputs in the network DEA model to choose the most efficient strategy for SSC design. The strategy selection process can become an important issue, especially when SCs active in a competitive environment. Accordingly, a crucial feature of the presented model is considering the issue of competition to choose the efficient strategy. Furthermore, undesirable outputs and feedbacks and independent inputs and outputs for intermediate stages in the network system are considered to create a structure compatible with the real world. The output of the proposed approach enables DMs to select the appropriate strategy for each stage of the SSC network to maximize the aggregate efficiency of the network.
Moving-Vehicle Identification Based on Hierarchical Detection Algorithm
Authors: Yang Zhifa , Zhu Yu , Zhang Haodong , Yu Zhuo , Li Shiwu , Wang Chao
Published: December 2021

The vehicle detection method plays an important role in the driver assistance system. Therefore, it is very important to improve the real-time performance of the detection algorithm. Nowadays, the most popular method is the scanning method based on sliding window search, which detects the vehicle from the image to be detected. However, the existing sliding window detection algorithm has many drawbacks, such as large calculation amount and poor real-time performance, and it is impossible to detect the target vehicle in real time during the motion process. Therefore, this paper proposes an improved hierarchical sliding window detection algorithm to detect moving vehicles in real time. By extracting the region of interest, the region of interest is layered, the maximum and minimum values of the detection window in each layer are set, the flashing frame generated by the layering is eliminated by the delay processing method, and a method suitable for the motion is obtained: the real-time detection algorithm of the vehicle, that is, the hierarchical sliding window detection algorithm. The experiments show that the more layers are divided, the more time is needed, and when the number of detection layers is greater than 7, the time change rate increases significantly. As the number of layers decreases, the detection accuracy rate also decreases, resulting in the phenomenon of a false positive. Therefore, it is determined to meet the requirements of real time and accuracy when the image is divided into 7 layers. It can be seen from the experiment that when the images to be detected are divided into 7 layers and the maximum and minimum values of detection windows are 30 × 30 and 250 × 250, respectively, the number of sub-windows generated is one thirty-seventh of the original sliding window detection algorithm, and the execution time is only one-third of the original sliding window detection algorithm. This shows that the hierarchical sliding window detection algorithm has better real-time performance than the original sliding window detection algorithm.
Trade Policy Uncertainty, Innovation and Total Factor Productivity
Authors: Zhou Yuan , Ji Yao
Published: December 2021

This paper explores the impact of trade policy uncertainty (TPU) shock on China’s total factor productivity. Using economic panel data for China, OECD countries, Hong Kong SAR, Macao SAR, and Singapore from the period 2003–2019, in this paper, we treat U.S.–China trade frictional events in 2016 and 2017 as a quasi-experiment to study the impact of TPU surge on China’s TFP under the synthetic control method (SCM) and generalized synthetic control method (GSCM), treating the OECD countries, Hong Kong SAR, Macao SAR, and Singapore as a control group. We found that TPU surge has a significantly negative causal effect on China’s TFP. SCM analysis, taking 2016 (2017) as the policy implementation time, showed that the average TFP loss borne by China due to trade policy uncertainty in 2017 and 2018 was 2.7% (3.5%). The VAR model showed that China’s trade policy uncertainty reduces China’s TFP through two channels: the shrinking channel of domestic R&D innovation, and the shrinking channel of the domestic sector’s use of foreign patents. This conclusion is robust according to the GSCM. To the best of the authors’ knowledge, this paper is the first attempt to examine the long-term technological impact of TPU surge during U.S.–China trade frictional events. Our findings suggest that trade friction harms technological progress, and reducing TPU can significantly enhance innovation and TFP.
Implementing and Monitoring Circular Business Models: An Analysis of Italian SMEs
Authors: Salvioni Daniela M. , Bosetti Luisa , Fornasari Tommaso
Published: December 2021

The transition from a linear to a circular economy (CE) is at the center of the debate among institutions, enterprises, practitioners, and scholars. Small- and medium-sized enterprises (SMEs), with their high presence in the business environment, play a pivotal role in the successful implementation of CE principles. Therefore, this paper aims to understand the state of the CE among Italian SMEs, considering both their different sizes and sectors. This study investigates CE knowledge and application, strategic relevance, benefits from and barriers to the transition towards circular business models, and the use of CE-related performance indicators in management control and external reporting. Through an online survey carried out in cooperation with the Italian Confederation of Craft Trades and Small- and Medium-Sized Enterprises (CNA), we collected primary data from 623 respondents. Findings revealed the existence of cultural, technological, market and financial barriers, which have hampered the adoption of circular practices among Italian SMEs. Poor understanding of CE potential, combined with difficulty in raising public and private funds to finance the transition from linear to circular, are the greatest problems. To overcome such issues, we recommend serious intervention by public institutions, trade and consumer associations, and the higher education system to develop a climate more favorable to the CE.
A Review of the Literature on Food Values and Their Potential Implications for Consumers’ Food Decision Processes
Authors: Femi-Oladunni Opeyemi Afolabi , Ruiz-Palomino Pablo , Martínez-Ruiz María Pilar , Muro-Rodríguez Ana Isabel
Published: December 2021

This article offers a semi-systematic literature review on the concept of food values. Specifically, 36 relevant research articles were analyzed. The results underscore the novelty and rapid popularity of this concept in different professional, scientific, and academic fields. Among the findings, the article highlights how the concept of food values has evolved to accommodate the features and behaviors of specific markets. Nonetheless, one can group food values into three distinct clusters. This article expands our understanding on the evolution of food values along different dimensions (various clusters and segments related to geographic regions and social classes). It also identifies several research gaps and translates them into different research proposals.
Sustainable Biodiesel Production by Transesterification of Waste Cooking Oil and Recycling of Wastewater Rich in Glycerol as a Feed to Microalgae
Authors: Paladino Ombretta , Neviani Matteo
Published: December 2021

The amount of solid and liquid organic waste and wastewater is continuously increasing all over the world. The necessity of their reuse and recycling is, therefore, becoming more and more pressing. Furthermore, the limited fossil fuel resources, in conjunction with the need to reduce greenhouse gas emissions, advocate the production of renewable fuels. In this work, we analyze a sustainable second-generation process to produce biodiesel by transesterification of waste cooking oil, coupled with a third-generation process in cascade for recycling the incoming wastewater. Since this latter is rich in glycerol, it is used as a feed for microalgae, from which oil can be extracted and added to the waste cooking oil to further produce biodiesel and close the cycle. We studied the influence of different factors like temperature, catalyst load, and reactants ratio on the kinetics of transesterification of the waste oil and estimated the kinetic parameters by different kinetic schemes. The obtained values of activation energies and pre-exponential factors at chosen conditions of T = 60 °C and catalyst load of 0.6% w/w in methanol are: Ea,direct = 35,661 J mol−1, Ea,reverse = 72,989 J mol−1, k0,direct = 9.7708 [dm3 mol−1]3 min−1, and k0,reverse = 24,810 [dm3 mol−1]3 min−1 for the global fourth-order reversible reaction scheme and Ea = 67,348 J mol−1 and k0 = 2.157 × 109 min−1 for the simplified pseudo-first-order irreversible reaction scheme; both in strong agreement with literature data. Furthermore, we designed very efficient conditions for discontinuous and continuous operating mode, both at lab-scale and pilot-scale. The quality of the biodiesel produced from waste cooking sunflower oil is compared with that of biodiesel produced by different kinds of virgin vegetable oils, showing that the former possesses acceptable quality standards (Cetane number = 48 and LHV = 36,600 kJ kg−1). Finally, the recycling of wastewater rich in glycerol as a nutrient for mixotrophic microalgae nurturing is discussed, and microalgae growing kinetics are evaluated (k1 about 0.5 day−1), endorsing the possibility of algae extraction each 4–5 days in a semi-continuous operating mode. The experimental results at the pilot scale finally confirm the quality of biodiesel, and the obtained yields for a two-stage process prove the competitiveness of this sustainable process on the global market.
Facing the Harsh Reality of Access and Benefit Sharing (ABS) Legislation: An Industry Perspective
Authors: Michiels Frank , Feiter Ulrich , Paquin-Jaloux Stéphanie , Jungmann Diana , Braun Axel , Sayoc Mary Ann P. , Armengol Ricard , Wyss Markus , David Bruno
Published: December 2021

Access and benefit sharing (ABS) is a framework which refers to a relatively recent type of legal requirements for access to and use of “genetic resources”. They are based on diverse national and regional laws and regulations, which mostly result from the implementation of the United Nations’ Convention on Biological Diversity (CBD) and its supplementary agreement, the Nagoya Protocol. Their ambition is to achieve fair and equitable sharing of benefits arising out of the use of genetic resources as an incentive to conserve and sustainably use them. This paper describes the experiences, practical constraints and complexities encountered by users of genetic resources when dealing with ABS legislation, with a focus on users from the private sector. We provide insights on how ABS laws have fundamentally changed the way of working with genetic resources, in the hope that it inspires re-thinking of the ABS framework, to better support the overall objectives of the CBD.
Farmers’ Contributions to Achieving Water Sustainability: A Meta-Analytic Path Analysis of Predicting Water Conservation Behavior
Authors: Abadi Bijan , Kelboro Girma
Published: December 2021

This article intends to summarize the findings of studies on the relationship between farmers’ behavioral intentions (BI) and water-conservation behavior (WCB) using the theory of planned behavior (TPB). A systematic review of transcripts obtained from Internet-based searching on reliable scientific databases (e.g., SID, ProQuest, Springer, Science Direct, John Wiley, Sage, Taylor & Francis, Emerald Insight, and Google Scholar) was followed by outfitting data for the Comprehensive Meta-Analysis (CMA) software. Data from a total of 28 studies on WCB were synthesized and analyzed through the CMA procedure. The resulting evidence demonstrates that the total and summarized estimate point (i.e., correlation) for the associations of attitude (ATT), subjective norms (SNs), and perceived behavioral control (PBC) with BI was 0.46, 0.36, and 0.26, respectively (r(t)PBC < r(t) SNs < r(t)ATT → BI). Furthermore, the effect size of the relationship between PBC and WCB was 0.27. The largest effect size pertained to the relationship between BI and WCB (BI → WCB) (r(t)BI = 0.52). The take-home message of the article is that hypothetical statements of the TPB are confirmed, as would be hypothesized. These findings should still be regarded in the field of WCB research; thus, policymakers need to provide solutions and adapt their policy initiatives for water resource management based on these findings. For example, one of the solutions to improve water resource management based on the research results is to examine the views and realities constructed by farmers of water resources and related management styles before carrying out water resource management projects. Identifying the potential capabilities of farmers and their economic and social background to expand water-conservation behavior and the tendency and acceptance of water resource management project to be implemented is also an important requirement in making resource management projects effective. The use of various methods of the individual, group, and collective communication to interact with farmers combined with provision of extension training, as well as mobilizing and organizing farmers to facilitate effective management of water resources are recommended.
An Integrated Analysis of GWR Models and Spatial Econometric Global Models to Decompose the Driving Forces of the Township Consumption Development in Gansu, China
Authors: Zhao Qianqian , Fan Qiao , Zhou Pengfei
Published: December 2021

The investigation of township consumption patterns has become highly significant in order to emphasize the importance of township consumption patterns in economic development and policy formulation. To attain township consumption development in underdeveloped areas is a significant way to meet the general criterion of “rich life” under China’s Rural Revitalization strategy. The primary objective of this study is to evaluate the driving forces that contribute to the development of township consumption in underdeveloped areas such as Gansu Province, China, and then scientifically design and implement a strategy for township consumption development in Gansu, all of which are related to the broader interests of rural revitalization. The study used 1233 township data of Gansu Province, China. The study integrated geographically weighted regression (GWR) and a spatial econometric global (SEG) model for data analysis and interpretation. The integration of these two models can comprehensively capture both spatial heterogeneity and spatial independence concurrently. First, we conducted integrated analyses of GWR and SEG models using consistent settings of spatial weight matrix elements, with GWR focusing on spatial heterogeneity and SEG models on spatial spillover. Second, the permanent resident population, the number of financial institution outlets, the types of townships, and the characteristics of townships had a substantial significant effect on the development of township consumption in Gansu, China. In addition, the ratio of residents with access to basic medical insurance was found to be negatively significant. The revitalization strategy for township consumption in Gansu Province, China should prioritize increasing the permanent resident population of townships, accelerating the development of township urbanization, accelerating the construction of township consumption infrastructures, and strengthening financial support from township financial institutions.
Agro-Morphological Characterization and Some Seed Characteristics of Wild Crambe (Brassicaceae) Species in Turkey
Authors: Subaşı Ilhan
Published: December 2021

The seeds of wild Crambe species have potential to be used as a source of industrial oil and animal feed. In this study, 48 genotypes of three Crambe species collected from the flora of Turkey were grown under field conditions in Ankara/Turkey in 2014–2016. The seed protein ratio, plant height, number of branches per plant, number of seeds per plant, seed yield per plant, thousand seed weight and hulless/hulled seed ratio (H/H) were determined. The highest protein ratio was determined as 26.02% in the t18 accession of Crambe tataria species. Variations in the characteristics were analyzed using principal component analysis. In the factor analysis of Crambe maritima, Crambe orientalis, Crambe tataria and the mean of these three species, the first two principal components accounted for 100%, 58.06%, 59.93% and 100% of the total variations, respectively. There were positive correlations between the plant height and number of seeds per plant, seed yield per plant for C. orientalis, and number of branches per plant for C. tataria. Although seed yield per plant was high in C. tataria and C. orientalis, they are not suitable for conventional agriculture due to shell thickness, inhomogeneous plant emergence and shooting. Conventional cultivation of wild Crambe species can be made possible by eliminating these negative features with breeding and agronomic studies.
Microwave-Assisted Solid Sampling Analysis Coupled to Flame Furnace Atomic Absorption Spectrometry for Cd and Pb Determination in Food-Contact Polymers
Authors: Henn Alessandra Schneider , Frohlich Angelica Chaiani , Pedrotti Matheus Felipe , Cauduro Vitoria Hagemann , Oliveira Marcos Leandro Silva , Flores Erico Marlon de Moraes , Bizzi Cezar Augusto
Published: December 2021

Microwave-assisted solid sampling analysis coupled to flame furnace atomic absorption spectrometry (MW-SS-FF-AAS) was used for Cd and Pb determination in food-contact polymer samples, with the aim of minimizing reagents and laboratory waste. Operational parameters, such as the FF tube design, the oxygen flow rate, the flame stoichiometry, the sample mass, among others, were evaluated and optimized. Calibration was performed using only reference solutions, and the limits of quantification were 1.7 and 4.6 μg g−1 for Cd and Pb, respectively. Accuracy was assessed by the analysis of certified reference materials (CRMs), and by comparison with the results obtained by inductively coupled plasma mass spectrometry after microwave-assisted wet digestion. The MW-SS-FF-AAS results for the CRMs showed no statistical difference with the certified values, and good agreement was observed with the results of the digestion method. The MW-SS-FF-AAS method was considered suitable for Cd and Pb determination in food-contact polymers. The concentrations of Cd and Pb in the analyzed samples varied from <1.7 to 628 μg g−1, and from <4.6 to 614 μg g−1, respectively. As sample digestion is not necessary, the use of concentrated acids can be avoided by using the proposed MW-SS-FF-AAS method, greatly reducing waste generation.
A Hybrid Multi-Objective Optimizer-Based SVM Model for Enhancing Numerical Weather Prediction: A Study for the Seoul Metropolitan Area
Authors: Deif Mohanad A. , Solyman Ahmed A. A. , Alsharif Mohammed H. , Jung Seungwon , Hwang Eenjun
Published: December 2021

Temperature forecasting is an area of ongoing research because of its importance in all life aspects. However, because a variety of climate factors controls the temperature, it is a never-ending challenge. The numerical weather prediction (NWP) model has been frequently used to forecast air temperature. However, because of its deprived grid resolution and lack of parameterizations, it has systematic distortions. In this study, a gray wolf optimizer (GWO) and a support vector machine (SVM) are used to ensure accuracy and stability of the next day forecasting for minimum and maximum air temperatures in Seoul, South Korea, depending on local data assimilation and prediction system (LDAPS; a model of local NWP over Korea). A total of 14 LDAPS models forecast data, the daily maximum and minimum air temperatures of in situ observations, and five auxiliary data were used as input variables. The LDAPS model, the multimodal array (MME), the particle swarm optimizer with support vector machine (SVM-PSO), and the conventional SVM were selected as comparison models in this study to illustrate the advantages of the proposed model. When compared to the particle swarm optimizer and traditional SVM, the Gray Wolf Optimizer produced more accurate results, with the average RMSE value of SVM for T max and T min Forecast prediction reduced by roughly 51 percent when combined with GWO and 31 percent when combined with PSO. In addition, the hybrid model (SVM-GWO) improved the performance of the LDAPS model by lowering the RMSE values for T max Forecast and T min Forecast forecasting from 2.09 to 0.95 and 1.43 to 0.82, respectively. The results show that the proposed hybrid (GWO-SVM) models outperform benchmark models in terms of prediction accuracy and stability and that the suggested model has a lot of application potentials.
Investigation of the Influence of Gas Turbine Power Stations on the Quality of Electric Energy in the Associated Petroleum Gas Utilization
Authors: Petrochenkov Anton , Romodin Aleksandr , Leyzgold Dmitriy , Kokorev Andrei , Kokorev Aleksandr , Lyakhomskii Aleksandr , Perfil’eva Evgenia , Gagarin Yuri , Shapranov Ruslan , Brusnitcin Pavel , Ilyushin Pavel
Published: December 2021

The problem of the quality of electric energy in the utilization of petroleum gas is considered. The article presents the results of the development of a mathematical description of power supply systems with gas turbine power stations based on two-shaft gas turbine units. The typical power distribution scheme of a gas turbine power station is given. The joint analysis of the generation modes of the gas turbine power station and the detected deviations of the power quality indicators values was carried out. The influence of the used mode on the power quality indicators is determined. As a result, the factors of operation of a gas turbine power station that affects power quality are identified, and recommendations for their elimination are given.
Learning in Troubled Times: Parents’ Perspectives on Emergency Remote Teaching and Learning
Authors: Seabra Filipa , Abelha Marta , Teixeira António , Aires Luísa
Published: December 2021

The COVID-19 pandemic triggered profound social consequences, affecting all aspects of human activity, including education. The process of remote teaching that was implemented in response to this crisis is known as emergency remote teaching and learning (ERTL). The present study focuses on Portuguese parents’ perspectives about this process. Data were gathered through an online questionnaire, answered by 203 parents of preschool, basic, and secondary education students (ages 3–18), focusing on self-perceived digital competence, satisfaction with ERTL, and pedagogical activities developed with their children. Parents were moderately satisfied with ERTL but expressed a marked increase in their workload, particularly those working from home. Parents of children in the second cycle of basic education (ages 10–12) were less satisfied with the process. A variety of activities was promoted, responding to different educational levels’ characteristics. Results show the importance of promoting parents’ digital competence and directing support policies, particularly to parents of younger children (ages 3–12), and raise concerns about equity.
A Wider Impedance Bandwidth Dual Filter Symmetrical MIMO Antenna for High-Speed Wideband Wireless Applications
Authors: Sharma Manish , Vashist Prem Chand , Alsukayti Ibrahim , Goyal Nitin , Anand Divya , Mosavi Amir H.
Published: December 2021

This research article reports a compact fractal 4 × 4 UWB extended bandwidth MIMO antenna with physical dimensions of 44 × 44 mm2 for high-speed wireless applications. The reported antenna comprises four fractal radiating elements that are symmetrical and placed orthogonal to each other with a respective rectangular ground printed on the opposite plane. A higher isolation is achieved between the radiating elements by the placement of a fractal patch orthogonally and no separate decoupling structure is required. The antenna offers a −10 dB transmission capacity of 2.84–15.88 GHz. The fractal radiating element, which is embedded by an inverted T-type stub placed within a rectangular slot and an etched rotated C-type slot, provides band-stop filters for WiMAX (Worldwide inter-operability for Microwave Access) and WLAN (wireless local area network)-interfering bands. The key parameters of diversity performance are compared by simulation and measurement (fabricated prototype) of ECC (envelope correlation coefficient), DG (directive gain), TARC (total active reflection coefficient) and CCL (channel capacity loss). The antenna offers an omnidirectional radiation pattern with an average gain of 3.52 dBi.
Self-Optimizing Path Tracking Controller for Intelligent Vehicles Based on Reinforcement Learning
Authors: Ma Jichang , Xie Hui , Song Kang , Liu Hao
Published: December 2021

The path tracking control system is a crucial component for autonomous vehicles; it is challenging to realize accurate tracking control when approaching a wide range of uncertain situations and dynamic environments, particularly when such control must perform as well as, or better than, human drivers. While many methods provide state-of-the-art tracking performance, they tend to emphasize constant PID control parameters, calibrated by human experience, to improve tracking accuracy. A detailed analysis shows that PID controllers inefficiently reduce the lateral error under various conditions, such as complex trajectories and variable speed. In addition, intelligent driving vehicles are highly non-linear objects, and high-fidelity models are unavailable in most autonomous systems. As for the model-based controller (MPC or LQR), the complex modeling process may increase the computational burden. With that in mind, a self-optimizing, path tracking controller structure, based on reinforcement learning, is proposed. For the lateral control of the vehicle, a steering method based on the fusion of the reinforcement learning and traditional PID controllers is designed to adapt to various tracking scenarios. According to the pre-defined path geometry and the real-time status of the vehicle, the interactive learning mechanism, based on an RL framework (actor–critic—a symmetric network structure), can realize the online optimization of PID control parameters in order to better deal with the tracking error under complex trajectories and dynamic changes of vehicle model parameters. The adaptive performance of velocity changes was also considered in the tracking process. The proposed controlling approach was tested in different path tracking scenarios, both the driving simulator platforms and on-site vehicle experiments have verified the effects of our proposed self-optimizing controller. The results show that the approach can adaptively change the weights of PID to maintain a tracking error (simulation: within ±0.071 m; realistic vehicle: within ±0.272 m) and steering wheel vibration standard deviations (simulation: within ±0.04°; realistic vehicle: within ±80.69°); additionally, it can adapt to high-speed simulation scenarios (the maximum speed is above 100 km/h and the average speed through curves is 63–76 km/h).
Spatial-Temporal 3D Residual Correlation Network for Urban Traffic Status Prediction
Authors: Bao Yin-Xin , Shi Quan , Shen Qin-Qin , Cao Yang
Published: December 2021

Accurate traffic status prediction is of great importance to improve the security and reliability of the intelligent transportation system. However, urban traffic status prediction is a very challenging task due to the tight symmetry among the Human–Vehicle–Environment (HVE). The recently proposed spatial–temporal 3D convolutional neural network (ST-3DNet) effectively extracts both spatial and temporal characteristics in HVE, but ignores the essential long-term temporal characteristics and the symmetry of historical data. Therefore, a novel spatial–temporal 3D residual correlation network (ST-3DRCN) is proposed for urban traffic status prediction in this paper. The ST-3DRCN firstly introduces the Pearson correlation coefficient method to extract a high correlation between traffic data. Then, a dynamic spatial feature extraction component is constructed by using 3D convolution combined with residual units to capture dynamic spatial features. After that, based on the idea of long short-term memory (LSTM), a novel architectural unit is proposed to extract dynamic temporal features. Finally, the spatial and temporal features are fused to obtain the final prediction results. Experiments have been performed using two datasets from Chengdu, China (TaxiCD) and California, USA (PEMS-BAY). Taking the root mean square error (RMSE) as the evaluation index, the prediction accuracy of ST-3DRCN on TaxiCD dataset is 21.4%, 21.3%, 11.7%, 10.8%, 4.7%, 3.6% and 2.3% higher than LSTM, convolutional neural network (CNN), 3D-CNN, spatial–temporal residual network (ST-ResNet), spatial–temporal graph convolutional network (ST-GCN), dynamic global-local spatial–temporal network (DGLSTNet), and ST-3DNet, respectively.
The Impact of Perceived Interactivity and Intrinsic Value on Users’ Continuance Intention in Using Mobile Augmented Reality Virtual Shoe-Try-On Function
Authors: Jiang Qianling , Sun Jie , Yang Chun , Gu Chao
Published: December 2021

In response to the rapid growth of mobile Internet, online retailers have created better shopping experiences through new technologies. These shopping experiences are the product of the new interaction methods created by new technologies and the intrinsic value of these technologies. To achieve a better understanding of how new technologies improve consumers’ intention to use them continuously, this study established a theoretical model of how consumers’ perceived interactivity affects intrinsic value, which then affects attitudes, and ultimately contributes to the theoretical model. Within the perceived interactivity construct, there is perceived control, personalization and responsiveness, and as part of the intrinsic value construct there is playfulness and aesthetics. The results demonstrate that intrinsic value and perceived interactivity play important roles in predicting consumers’ attitudes and continuance intention to use new technologies applied to mobile e-commerce, but do not include perceived control in perceived interactivity. To highlight the results of this study, relevant enterprises or practitioners may use the findings to design or improve the features of existing mobile apps to provide better services and experiences to consumers based on their internal perceptions.
Artwork Style Recognition Using Vision Transformers and MLP Mixer
Authors: Iliadis Lazaros , Nikolaidis Spyridon , Sarigiannidis Panagiotis , Wan Shaohua , Goudos Sotirios
Published: December 2021

Through the extensive study of transformers, attention mechanisms have emerged as potentially more powerful than sequential recurrent processing and convolution. In this realm, Vision Transformers have gained much research interest, since their architecture changes the dominant paradigm in Computer Vision. An interesting and difficult task in this field is the classification of artwork styles, since the artistic style of a painting is a descriptor that captures rich information about the painting. In this paper, two different Deep Learning architectures—Vision Transformer and MLP Mixer (Multi-layer Perceptron Mixer)—are trained from scratch in the task of artwork style recognition, achieving over 39% prediction accuracy for 21 style classes on the WikiArt paintings dataset. In addition, a comparative study between the most common optimizers was conducted obtaining useful information for future studies.
Phosphating Modification with Metal Ions of Carbon Steel Surface to Improve the Influence of Anticorrosion Properties
Authors: Samardžija Marina , Alar Vesna , Špada Vedrana , Kapor Frankica
Published: December 2021

The purpose of this research is to investigate the influence of the phosphatizing process with Ni2+, Ce3+, and Ti2+ ions on the properties of the coating to obtain better corrosion protection of the metal. Steel corrosion occurs through physicochemical interaction between the metal and its surrounding environment. This leads to a change in the metal’s physical, mechanical, and optical properties that can cause damage to the functionality of the metal, which in turn may result in accidents or other malfunctions. Carbon steel grade has limited resistance to corrosion, depending on the carbon content and alloying element, the microstructure, and the surrounding environment of the material. This paper present tests that have been carried out on some of the physicochemical properties of protective epoxy and polyurethane coating on carbon steel grade. Coatings represent one of the methods available to protect metal surfaces from corrosion. Coating properties such as thickness, hardness, and adhesion were investigated. The same properties were tested by exposing the sample plates to corrosive conditions of the humid chamber and seawater. Their anticorrosion properties were explored by electrochemical impedance spectroscopy (EIS) techniques under immersion in 3.5 wt.% NaCl solutions as a corrosive medium. Part of the samples prior to application of the coatingwere modified with a phosphate solution containing metal ions: Ni2+, Ce3+, and Ti2+ to further investigate the effects of phosphatization on the properties of the coating. After exposure of the plates to the salt and moist chamber conditions, no traces of corrosion products, cracking or peeling of the coating were found on the surfaces. The adhesion properties were tested by the pull-off adhesion test. It was found that metal/polymer adhesion was satisfied according to EN ISO 4624:2016 and had the same value for all samples. However, a detailed EIS analysis showed a higher resistance of phosphate samples with Ce3+ ions than samples that were phosphated with Ni2+ and Ti2+ ions and those that did not have a sparingly soluble phosphate salt layer.
From Extrapolation to Precision Chemical Hazard Assessment: The Ecdysone Receptor Case Study
Authors: Ruivo Raquel , Sousa João , Neuparth Teresa , Geffard Olivier , Chaumot Arnaud , Castro L. , Degli-Esposti Davide , Santos Miguel
Published: December 2021

Hazard assessment strategies are often supported by extrapolation of damage probabilities, regarding chemical action and species susceptibilities. Yet, growing evidence suggests that an adequate sampling of physiological responses across a representative taxonomic scope is of paramount importance. This is particularly relevant for Nuclear Receptors (NR), a family of transcription factors, often triggered by ligands and thus, commonly exploited by environmental chemicals. Within NRs, the ligand-induced Ecdysone Receptor (EcR) provides a remarkable example. Long regarded as arthropod specific, this receptor has been extensively targeted by pesticides, seemingly innocuous to non-target organisms. Yet, current evidence clearly suggests a wider presence of EcR orthologues across metazoan lineages, with unknown physiological consequences. Here, we address the state-of-the-art regarding the phylogenetic distribution and functional characterization of metazoan EcRs and provide a critical analysis of the potential disruption of such EcRs by environmental chemical exposure. Using EcR as a case study, hazard assessment strategies are also discussed in view of the development of a novel “precision hazard assessment paradigm.
GEMS Embeddings of Schwarzschild and RN Black Holes in Painlevé-Gullstrand Spacetimes
Authors: Hong Soon-Tae , Kim Yong-Wan , Park Young-Jai
Published: December 2021

Making use of the higher dimensional global embedding Minkowski spacetime (GEMS), we embed (3 + 1)-dimensional Schwarzschild and Reissner-Nordström (RN) black holes written by the Painlevé-Gullstrand (PG) spacetimes, which have off-diagonal components in metrics, into (5 + 1)- and (5 + 2)-dimensional flat ones, respectively. As a result, we have shown the equivalence of the GEMS embeddings of the spacetimes with the diagonal and off-diagonal terms in metrics. Moreover, with the aid of their geodesic equations satisfying various boundary conditions in the flat embedded spacetimes, we directly obtain freely falling temperatures. We also show that freely falling temperatures in the PG spacetimes are well-defined beyond the event horizons, while they are equivalent to the Hawking temperatures, which are obtained in the original curved ones in the ranges between the horizon and the infinity. These will be helpful to study GEMS embeddings of more realistic Kerr, or rotating BTZ black holes.
Lessons from New York High Line Green Roof: Conserving Biodiversity and Reconnecting with Nature
Authors: Salih Kawar , Saeed Zaid O. , Almukhtar Avar
Published: December 2021

The concept of sustainable urban design has appeared in different perspectives to minimize and reduce the negative impacts of urban expansion in terms of climatic and environmental drawbacks. One of the undeniable approaches of sustainable urban design is the adoption of green urban roofs. Green roofs are seen to have a substantial role in addressing and resolving environmental issues in the context of climate change. Research investigations have indicated that green roofs have a remarkable impact on decreasing rainwater runoff, reducing the heat island effect in urban spaces, and increasing biodiversity. Nevertheless, green roofs in urban spaces as a competent alternative to nature remains a standing question. To what extent can green roofs mimic the biodiversity that is seen in nature? Moreover, to what level is this approach practical for achieving a tangible reconnection with nature, or so-called biophilia? This study attempts to discuss the essence and impact of green roofs in urban spaces based on a case study approach. The study reflected lessons from the New York High Line Green Roof regarding biophilia and biodiversity in this case study. It concludes with key lessons that can be transferred to other urban spaces with similar settings.
The Bacteriophage Pf-10—A Component of the Biopesticide “Multiphage” Used to Control Agricultural Crop Diseases Caused by Pseudomonas syringae
Authors: Kazantseva Olesya A. , Buzikov Rustam M. , Pilipchuk Tatsiana A. , Valentovich Leonid N. , Kazantsev Andrey N. , Kalamiyets Emilia I. , Shadrin Andrey M.
Published: December 2021

Phytopathogenic pseudomonads are widespread in the world and cause a wide range of plant diseases. In this work, we describe the Pseudomonas phage Pf-10, which is a part of the biopesticide “Multiphage” used for bacterial diseases of agricultural crops caused by Pseudomonas syringae. The Pf-10 chromosome is a dsDNA molecule with two direct terminal repeats (DTRs). The phage genomic DNA is 39,424 bp long with a GC-content of 56.5%. The Pf-10 phage uses a packaging mechanism based on T7-like short DTRs, and the length of each terminal repeat is 257 bp. Electron microscopic analysis has shown that phage Pf-10 has the podovirus morphotype. Phage Pf-10 is highly stable at pH values from 5 to 10 and temperatures from 4 to 60 °C and has a lytic activity against Pseudomonas strains. Phage Pf-10 is characterized by fast adsorption rate (80% of virions attach to the host cells in 10 min), but has a relatively small number of progeny (37 ± 8.5 phage particles per infected cell). According to the phylogenetic analysis, phage Pf-10 can be classified as a new phage species belonging to the genus Pifdecavirus, subfamily Studiervirinae, family Autographiviridae, order Caudovirales.
Severity Biomarkers in Puumala Hantavirus Infection
Authors: Outinen Tuula K. , Mäkelä Satu , Pörsti Ilkka , Vaheri Antti , Mustonen Jukka
Published: December 2021

Annually, over 10,000 cases of hemorrhagic fever with renal syndrome (HFRS) are diagnosed in Europe. Puumala hantavirus (PUUV) causes most of the European HFRS cases. PUUV causes usually a relatively mild disease, which is rarely fatal. However, the severity of the infection varies greatly, and factors affecting the severity are mostly unrevealed. Host genes are known to have an effect. The typical clinical features in PUUV infection include acute kidney injury, thrombocytopenia, and increased vascular permeability. The primary target of hantavirus is the endothelium of the vessels of different organs. Although PUUV does not cause direct cytopathology of the endothelial cells, remarkable changes in both the barrier function of the endothelium and the function of the infected endothelial cells occur. Host immune or inflammatory mechanisms are probably important in the development of the capillary leakage. Several immunoinflammatory biomarkers have been studied in the context of assessing the severity of HFRS caused by PUUV. Most of them are not used in clinical practice, but the increasing knowledge about the biomarkers has elucidated the pathogenesis of PUUV infection.
COVID-19 Vaccination Compliance and Associated Factors among Medical Students during an Early Phase of Vaccination Rollout—A Survey from Israel
Authors: Katz Maayan , Azrad Maya , Glikman Daniel , Peretz Avi
Published: December 2021

COVID-19 is “a once-in-a-century” pandemic, bringing with it unparalleled health, social, and economic ramifications. As part of the world’s efforts to restrain the pandemic, vaccine development has been expedited. This population-representative survey in Israel aimed to investigate whether the knowledge, attitudes, and vaccination status of medical students affect their intention to recommend COVID-19 vaccination (as well as reasons for refusal and acceptance of the vaccine). The questionnaire was anonymous, via Google Forms app in December 2021. One-hundred and four medical students completed the survey. Overwhelmingly, (91.3%) COVID-19 vaccination status and intention to receive the vaccine were positively associated with intention to recommend. Twenty-five percent of the students replied that they lacked knowledge regarding the vaccine. A statistically significant association was found between experiencing quarantine and the intention to be vaccinated (p = 0.034). There was a significant positive relationship between the number of symptoms from previous vaccines and the fear of COVID-19 (rs = 0.272, p < 0.01). Prior vaccination did not have an effect on COVID-19 vaccine hesitancy. This first study evaluating COVID-19 vaccine hesitancy among Israeli medical students highlighted the need for medical programs to emphasize the benefits of COVID-19 vaccination in the protection of healthcare workers and patient safety. Education, awareness campaigns, and regulation of vaccine trials could further decrease COVID-19 vaccine hesitancy and increase vaccine rates among medical students.