bluuebunny/crossref_metadata_2025 huggingface dataset:
Whole Body Cryotherapy and Hyperbaric Oxygen Treatment: New Biological Treatment of Depression? A Systematic Review
Authors: Krzystanek Marek , Romańczyk Monika , Surma Stanisław , Koźmin-Burzyńska Agnieszka
Published: June 2021

Treatment with antidepressants is often insufficiently effective, especially in treatment-resistant depression. In such a situation, it is possible to change the drug, add a second antidepressant, or use pharmacological and non-pharmacological methods of augmenting the effect of pharmacotherapy. New methods that may fall into the scope of multi-module depression treatment as an augmentation of depression treatment are whole body cryotherapy (WBC) and hyperbaric oxygen treatment (HBOT). 545 records were selected and analyzed for these two treatments and finally three clinical trials were selected for analysis. The review also includes data on the possibility of using WBC and HBOT in somatic indications and in organic mental syndromes. Despite the small number of studies on the effectiveness of WBC or HBOT in depression, the current data show that both methods may be effective in the treatment of depression. WBC may be effective in the augmentation of antidepressants, and additionally, it is a method in which a quick antidepressant effect is obtained. HBOT may be effective in endogenous depression, just as it is effective in the treatment of somatic depression symptoms. The results are very preliminary, but if confirmed in subsequent studies, both WBC and HBOT may become new treatment options in treating depression. The authors point to the need and directions for further research into these treatment methods as an augmentation strategy for pharmacological treatment of depression.
Molecular Dynamics Simulation of Clay Hydration Inhibition of Deep Shale
Authors: Zhang Yayun , Xiao Cong
Published: June 2021

In the process of the exploitation of deep oil and gas resources, shale wellbore stability control faces great challenges under complex temperature and pressure conditions. It is difficult to reflect the micro mechanism and process of the action of inorganic salt on shale hydration with the traditional experimental evaluation technology on the macro effect of restraining shale hydration. Aiming at the characteristics of clay minerals of deep shale, the molecular dynamics models of four typical cations (K+, NH4+, Cs+ and Ca2+) inhibiting the hydration of clay minerals have been established by the use of the molecular dynamics simulation method. Moreover, the micro dynamics mechanism of typical inorganic cations inhibiting the hydration of clay minerals has been systematically evaluated, as has the law of cation hydration inhibition performance in response to temperature, pressure and ion type. The research indicates that the cations can promote the contraction of interlayer spacing, compress fluid intrusion channels, reduce the intrusion ability of water molecules, increase the negative charge balance ability and reduce the interlayer electrostatic repulsion force. With the increase in temperature, the inhibition of the cations on montmorillonite hydration is weakened, while the effect of pressure is opposite. Through the molecular dynamics simulation under different temperatures and pressures, we can systematically understand the microcosmic dynamics mechanism of restraining the hydration of clay in deep shale and provide theoretical guidance for the microcosmic control of clay hydration.
Predicting Sooting Propensity of Oxygenated Fuels Using Artificial Neural Networks
Authors: Abdul Jameel Abdul Gani
Published: June 2021

The self-learning capabilities of artificial neural networks (ANNs) from large datasets have led to their deployment in the prediction of various physical and chemical phenomena. In the present work, an ANN model was developed to predict the yield sooting index (YSI) of oxygenated fuels using the functional group approach. A total of 265 pure compounds comprising six chemical classes, namely paraffins (n and iso), olefins, naphthenes, aromatics, alcohols, and ethers, were dis-assembled into eight constituent functional groups, namely paraffinic CH3 groups, paraffinic CH2 groups, paraffinic CH groups, olefinic –CH=CH2 groups, naphthenic CH-CH2 groups, aromatic C-CH groups, alcoholic OH groups, and ether O groups. These functional groups, in addition to molecular weight and branching index, were used as inputs to develop the ANN model. A neural network with two hidden layers was used to train the model using the Levenberg–Marquardt (ML) training algorithm. The developed model was tested with 15% of the random unseen data points. A regression coefficient (R2) of 0.99 was obtained when the experimental values were compared with the predicted YSI values from the test set. An average error of 3.4% was obtained, which is less than the experimental uncertainty associated with most reported YSI measurements. The developed model can be used for YSI prediction of hydrocarbon fuels containing alcohol and ether-based oxygenates as additives with a high degree of accuracy.
Modelling and Multi-Objective Optimization of the Sulphur Dioxide Oxidation Process
Authors: Zaker Mohammad Reza , Fauteux-Lefebvre Clémence , Thibault Jules
Published: June 2021

Sulphuric acid (H2SO4) is one of the most produced chemicals in the world. The critical step of the sulphuric acid production is the oxidation of sulphur dioxide (SO2) to sulphur trioxide (SO3) which takes place in a multi catalytic bed reactor. In this study, a representative kinetic rate equation was rigorously selected to develop a mathematical model to perform the multi-objective optimization (MOO) of the reactor. The objectives of the MOO were the SO2 conversion, SO3 productivity, and catalyst weight, whereas the decisions variables were the inlet temperature and the length of each catalytic bed. MOO studies were performed for various design scenarios involving a variable number of catalytic beds and different reactor configurations. The MOO process was mainly comprised of two steps: (1) the determination of Pareto domain via the determination a large number of non-dominated solutions, and (2) the ranking of the Pareto-optimal solutions based on preferences of a decision maker. Results show that a reactor comprised of four catalytic beds with an intermediate absorption column provides higher SO2 conversion, marginally superior to four catalytic beds without an intermediate SO3 absorption column. Both scenarios are close to the ideal optimum, where the reactor temperature would be adjusted to always be at the maximum reaction rate. Results clearly highlight the compromise existing between conversion, productivity and catalyst weight.
Backstepping Methodology to Troubleshoot Plant-Wide Batch Processes in Data-Rich Industrial Environments
Authors: Zuecco Federico , Cicciotti Matteo , Facco Pierantonio , Bezzo Fabrizio , Barolo Massimiliano
Published: June 2021

Troubleshooting batch processes at a plant-wide level requires first finding the unit causing the fault, and then understanding why the fault occurs in that unit. Whereas in the literature case studies discussing the latter issue abound, little attention has been given so far to the former, which is complex for several reasons: the processing units are often operated in a non-sequential way, with unusual series-parallel arrangements; holding vessels may be required to compensate for lack of production capacity, and reacting phenomena can occur in these vessels; and the evidence of batch abnormality may be available only from the end unit and at the end of the production cycle. We propose a structured methodology to assist the troubleshooting of plant-wide batch processes in data-rich environments where multivariate statistical techniques can be exploited. Namely, we first analyze the last unit wherein the fault manifests itself, and we then step back across the units through the process flow diagram (according to the manufacturing recipe) until the fault cannot be detected by the available field sensors any more. That enables us to isolate the unit wherefrom the fault originates. Interrogation of multivariate statistical models for that unit coupled to engineering judgement allow identifying the most likely root cause of the fault. We apply the proposed methodology to troubleshoot a complex industrial batch process that manufactures a specialty chemical, where productivity was originally limited by unexplained variability of the final product quality. Correction of the fault allowed for a significant increase in productivity.
Modelling of Applied Magnetic Field and Thermal Radiations Due to the Stretching of Cylinder
Authors: Tamoor Muhammad , Kamran Muhammad , Rehman Sadique , Farooq Aamir , Khan Rewayat , Lee Jung Rye , Shin Dong Yun
Published: June 2021

In this study, a numerical approach was adopted in order to explore the analysis of magneto fluid in the presence of thermal radiation combined with mixed convective and slip conditions. Using the similarity transformation, the axisymmetric three-dimensional boundary layer equations were reduced to a self-similar form. The shooting technique, combined with the Range–Kutta–Fehlberg method, was used to solve the resulting coupled nonlinear momentum and heat transfer equations numerically. When physically interpreting the data, some important observations were made. The novelty of the present study lies in finding help to control the rate of heat transfer and fluid velocity in any industrial manufacturing processes (such as the cooling of metallic plates). The numerical results revealed that the Nusselt number decrease for larger Prandtl number, curvature, and convective parameters. At the same time, the skin friction coefficient was enhanced with an increase in both slip velocity and convective parameter. The effect of emerging physical parameters on velocity and temperature profiles for a nonlinear stretching cylinder has been thoroughly studied and analyzed using plotted graphs and tables.
Application of RGB Images Obtained by UAV in Coffee Farming
Authors: Barbosa Brenon Diennevam Souza , Araújo e Silva Ferraz Gabriel , Mendes dos Santos Luana , Santana Lucas Santos , Bedin Marin Diego , Rossi Giuseppe , Conti Leonardo
Published: June 2021

The objective of this study was to evaluate the potential of the practical application of unmanned aerial vehicles and RGB vegetation indices (VIs) in the monitoring of a coffee crop. The study was conducted in an experimental coffee field over a 12-month period. An RGB digital camera coupled to a UAV was used. Nine VIs were evaluated in this study. These VIs were subjected to a Pearson correlation analysis with the leaf area index (LAI), and subsequently, the VIs with higher R2 values were selected. The LAI was estimated by plant height and crown diameter values obtained by imaging, which were correlated with these values measured in the field. Among the VIs evaluated, MPRI (0.31) and GLI (0.41) presented greater correlation with LAI; however, the correlation was weak. Thematic maps of VIs in the evaluated period showed variability present in the crop. The evolution of weeds in the planting rows was noticeable with both VIs, which can help managers to make the decision to start crop management, thus saving resources. The results show that the use of low-cost UAVs and RGB cameras has potential for monitoring the coffee production cycle, providing producers with information in a more accurate, quick and simple way.
Evaluation of the J-OFURO3 Sea Surface Net Radiation and Inconsistency Correction
Authors: Chen Hongkai , Jiang Bo , Li Xiuxia , Peng Jianghai , Liang Hui , Li Shaopeng
Published: June 2021

A new satellite-based product containing daily sea surface net radiation (Rn) values at a spatial resolution of 0.25° from 1988 to 2013, named the Japanese Ocean Flux Data Sets with Use of Remote Sensing Observations, version 3 (J-OFURO3), was recently generated and released. In this letter, the performance of the J-OFURO3 sea-surface Rn product was fully evaluated by using observations from 55 global moored buoy sites. The overall accuracy was satisfactory, with root-mean-square difference (RMSD) of 24.05 and 10.76 Wm−2 at daily and monthly scales, respectively. However, an inconsistency issue was found in the long-term variations in the J-OFURO3 sea-surface Rn values in approximately 2000; this inconsistency may be due to the replacement of the input dataset. To address this issue, a simple but effective inconsistency correction method was developed and conducted in this study. The analysis results demonstrated that the variations in the corrected J-OFURO3 sea-surface Rn data were more reasonable and that its daily validation accuracy was significantly improved by decreasing the bias from 4.67 to 0.27 Wm−2 before the year 2000. Thereby, it is suggested that the inconsistency correction method should be applied before using the J-OFURO3 sea-surface Rn data. However, the data users still should be cautious about another discontinuity issues caused by the quality of the input dataset itself.
Enhanced Neural Network Model for Worldwide Estimation of Weighted Mean Temperature
Authors: Long Fengyang , Gao Chengfa , Yan Yuxiang , Wang Jinling
Published: June 2021

Precise modeling of weighted mean temperature (Tm) is critical for realizing real-time conversion from zenith wet delay (ZWD) to precipitation water vapor (PWV) in Global Navigation Satellite System (GNSS) meteorology applications. The empirical Tm models developed by neural network techniques have been proved to have better performances on the global scale; they also have fewer model parameters and are thus easy to operate. This paper aims to further deepen the research of Tm modeling with the neural network, and expand the application scope of Tm models and provide global users with more solutions for the real-time acquisition of Tm. An enhanced neural network Tm model (ENNTm) has been developed with the radiosonde data distributed globally. Compared with other empirical models, the ENNTm has some advanced features in both model design and model performance, Firstly, the data for modeling cover the whole troposphere rather than just near the Earth’s surface; secondly, the ensemble learning was employed to weaken the impact of sample disturbance on model performance and elaborate data preprocessing, including up-sampling and down-sampling, which was adopted to achieve better model performance on the global scale; furthermore, the ENNTm was designed to meet the requirements of three different application conditions by providing three sets of model parameters, i.e., Tm estimating without measured meteorological elements, Tm estimating with only measured temperature and Tm estimating with both measured temperature and water vapor pressure. The validation work is carried out by using the radiosonde data of global distribution, and results show that the ENNTm has better performance compared with other competing models from different perspectives under the same application conditions, the proposed model expanded the application scope of Tm estimation and provided the global users with more choices in the applications of real-time GNSS-PWV retrival.
The Extraction of Street Curbs from Mobile Laser Scanning Data in Urban Areas
Authors: Zhao Leyang , Yan Li , Meng Xiaolin
Published: June 2021

The demand for mobile laser scanning in urban areas has grown in recent years. Mobile-based light detection and ranging (LiDAR) technology can be used to collect high-precision digital information on city roads and building façades. However, due to the small size of curbs, the information that can be used for curb detection is limited. Moreover, occlusion may cause the extraction method unable to correctly capture the curb area. This paper presents the development of an algorithm for extracting street curbs from mobile-based LiDAR point cloud data to support city managers in street deformation monitoring and urban street reconstruction. The proposed method extracts curbs in three complex scenarios: vegetation covering the curbs, curved street curbs, and occlusion curbs by vehicles, pedestrians. This paper combined both spatial information and geometric information, using the spatial attributes of the road boundary. It can adapt to different heights and different road boundary structures. Analyses of real study sites show the rationality and applicability of this method for obtaining accurate results in curb-based street extraction from mobile-based LiDAR data. The overall performance of road curb extraction is fully discussed, and the results are shown to be promising. Both the completeness and correctness of the extracted left and right road edges are greater than 98%.
A More Accurate Field-to-Field Method towards the Wind Retrieval of HY-2B Scatterometer
Authors: Shi Xinjie , Duan Boheng , Ren Kaijun
Published: June 2021

In this paper, we present a method for retrieving sea surface wind field (SSWF) from HaiYang-2B (HY-2B) scatterometer data. In contrast to the conventional algorithm, i.e., using a point-to-point (P2P) method based on geophysical model functions (GMF) to retrieve SSWF by spaceborne scatterometer, we introduce a more accurate field-to-field (F2F) retrieval method based on convolutional neural network (CNN). We fully consider the spatial correlation and continuity between adjacent observation points, and input the observation data of continuous wind field within a certain range into the neural network to construct the neural network model, and then synchronously obtain the wind field within the range. The wind field obtained by our retrieval method maintains its continuity and solves the problem of ambiguity removal in traditional wind direction retrieval methods. Comparing the retrieval results with the buoy data, the results show that the root mean square errors (RMSE) of wind direction and wind speed are less than 0.18 rad (10.31°) and 0.75 m/s, respectively. The retrieval accuracy is better than the L2B product of HY-2B.
Learning Polynomial-Based Separable Convolution for 3D Point Cloud Analysis
Authors: Yu Ruixuan , Sun Jian
Published: June 2021

Shape classification and segmentation of point cloud data are two of the most demanding tasks in photogrammetry and remote sensing applications, which aim to recognize object categories or point labels. Point convolution is an essential operation when designing a network on point clouds for these tasks, which helps to explore 3D local points for feature learning. In this paper, we propose a novel point convolution (PSConv) using separable weights learned with polynomials for 3D point cloud analysis. Specifically, we generalize the traditional convolution defined on the regular data to a 3D point cloud by learning the point convolution kernels based on the polynomials of transformed local point coordinates. We further propose a separable assumption on the convolution kernels to reduce the parameter size and computational cost for our point convolution. Using this novel point convolution, a hierarchical network (PSNet) defined on the point cloud is proposed for 3D shape analysis tasks such as 3D shape classification and segmentation. Experiments are conducted on standard datasets, including synthetic and real scanned ones, and our PSNet achieves state-of-the-art accuracies for shape classification, as well as competitive results for shape segmentation compared with previous methods.
Utterance Level Feature Aggregation with Deep Metric Learning for Speech Emotion Recognition
Authors: Mocanu Bogdan , Tapu Ruxandra , Zaharia Titus
Published: June 2021

Emotion is a form of high-level paralinguistic information that is intrinsically conveyed by human speech. Automatic speech emotion recognition is an essential challenge for various applications; including mental disease diagnosis; audio surveillance; human behavior understanding; e-learning and human–machine/robot interaction. In this paper, we introduce a novel speech emotion recognition method, based on the Squeeze and Excitation ResNet (SE-ResNet) model and fed with spectrogram inputs. In order to overcome the limitations of the state-of-the-art techniques, which fail in providing a robust feature representation at the utterance level, the CNN architecture is extended with a trainable discriminative GhostVLAD clustering layer that aggregates the audio features into compact, single-utterance vector representation. In addition, an end-to-end neural embedding approach is introduced, based on an emotionally constrained triplet loss function. The loss function integrates the relations between the various emotional patterns and thus improves the latent space data representation. The proposed methodology achieves 83.35% and 64.92% global accuracy rates on the RAVDESS and CREMA-D publicly available datasets, respectively. When compared with the results provided by human observers, the gains in global accuracy scores are superior to 24%. Finally, the objective comparative evaluation with state-of-the-art techniques demonstrates accuracy gains of more than 3%.
A Semantic and Knowledge-Based Approach for Handover Management
Authors: Vivas Fulvio Yesid , Caicedo Oscar Mauricio , Nieves Juan Carlos
Published: June 2021

Handover Management (HM) is pivotal for providing service continuity, enormous reliability and extreme-low latency, and meeting sky-high data rates, in wireless communications. Current HM approaches based on a single criterion may lead to unnecessary and frequent handovers due to a partial network view that is constrained to information about link quality. In turn, HM approaches based on multicriteria may present a failure of handovers and wrong network selection, decreasing the throughput and increasing the packet loss in the network. This paper proposes SIM-Know, an approach for improving HM. SIM-Know improves HM by including a Semantic Information Model (SIM) that enables context-aware and multicriteria handover decisions. SIM-Know also introduces a SIM-based distributed Knowledge Base Profile (KBP) that provides local and global intelligence to make contextual and proactive handover decisions. We evaluated SIM-Know in an emulated wireless network. When the end-user device moves at low and moderate speeds, the results show that our approach outperforms the Signal Strong First (SSF, single criterion approach) and behaves similarly to the Analytic Hierarchy Process combined with the Technique for Order Preferences by Similarity to the Ideal Solution (AHP-TOPSIS, multicriteria approach) regarding the number of handovers and the number of throughput drops. SSF outperforms SIM-Know and AHP-TOPSIS regarding the handover latency metric because SSF runs a straightforward process for making handover decisions. At high speeds, SIM-Know outperforms SSF and AHP-TOPSIS regarding the number of handovers and the number of throughput drops and, further, improves the throughput, delay, jitter, and packet loss in the network. Considering the obtained results, we conclude that SIM-Know is a practical and attractive solution for cognitive HM.
Measurement of Ankle Joint Movements Using IMUs during Running
Authors: Kim Byong Hun , Hong Sung Hyun , Oh In Wook , Lee Yang Woo , Kee In Ho , Lee Sae Yong
Published: June 2021

Gait analysis has historically been implemented in laboratory settings only with expensive instruments; yet, recently, efforts to develop and integrate wearable sensors into clinical applications have been made. A limited number of previous studies have been conducted to validate inertial measurement units (IMUs) for measuring ankle joint kinematics, especially with small movement ranges. Therefore, the purpose of this study was to validate the ability of available IMUs to accurately measure the ankle joint angles by comparing the ankle joint angles measured using a wearable device with those obtained using a motion capture system during running. Ten healthy subjects participated in the study. The intraclass correlation coefficient (ICC) and standard error of measurement were calculated for reliability, whereas the Pearson coefficient correlation was performed for validity. The results showed that the day-to-day reliability was excellent (0.974 and 0.900 for sagittal and frontal plane, respectively), and the validity was good in both sagittal (r = 0.821, p < 0.001) and frontal (r = 0.835, p < 0.001) planes for ankle joints. In conclusion, we suggest that the developed device could be used as an alternative tool for the 3D motion capture system for assessing ankle joint kinematics.
Core Temperature during Cold-Water Triathlon Swimming
Authors: Høiseth Lars Øivind , Melau Jørgen , Bonnevie-Svendsen Martin , Nyborg Christoffer , Eijsvogels Thijs M. H. , Hisdal Jonny
Published: June 2021

Triathlon and other endurance races have grown in popularity. Although participants are generally fit and presumably healthy, there is measurable morbidity and mortality associated with participation. In triathlon, most deaths occur during the swim leg, and more insight into risk factors, such as hypothermia, is warranted. In this study, we measured the core temperature of 51 participants who ingested temperature sensor capsules before the swim leg of a full-distance triathlon. The water temperature was 14.4–16.4 °C, and the subjects wore wetsuits. One subject with a low body mass index and a long swim time experienced hypothermia (<35 °C). Among the remaining subjects, we found no association between core temperature and swim time, body mass index, or sex. To conclude, the present study indicates that during the swim leg of a full-distance triathlon in water temperatures ≈ 15–16 °C, subjects with a low body mass index and long swim times may be at risk of hypothermia even when wearing wetsuits.
Low-Powered Photodetector Based on Two-Dimensional InS0.3Se0.7/WS2 Heterostructure
Authors: Zhang Kaiting , Chang Jie , Tan Chaoyang , Han Hui
Published: June 2021

Photodetectors based on two-dimensional (2D) materials have great potential applications in the field of new energy, such as fuel cells, solar cells, and other fields. Van der Waals (vdW) heterojunction photodiodes are expected to be one of the promising applications of two-dimensional materials due to the photoelectric properties without consideration of lattice mismatch. High-efficiency photoelectric sensors based on two-dimensional materials have great significance to reducing the energy consumption of devices. Here, we build a complex vdW heterostructure by combining InS0.3Se0.7 with another suitable 2D material WS2. Few-layer graphite was used as electrodes to enhance the optoelectronic performance of indium monochalcogenides. Evident photocurrent is observed in the InS0.3Se0.7/WS2 vdW heterostructure device arising from the formed p–n junction at the interface. The uniformity and photoresponse of the InS0.3Se0.7/WS2 vdW heterostructure has been further investigated by the photocurrent mapping. It shows that the entire photovoltaic current was originated from the InS0.3Se0.7/WS2 vdW heterojunction by scanning photocurrent microscope images. Furthermore, the response speed is enhanced at small bias voltage. The transient photoresponse can be well reproduced in almost 100 cycles, indicating the good repeatable optoelectronic performance. Our study indicates that the as-prepared InS0.3Se0.7/WS2 vdW heterostructures are attractive building blocks for photodetectors application. Our findings will open up a new way to further develop high-performance, low-power, and energy-efficient photodetectors based on indium monochalcogenides.
CoVid Key Figures and New Challenges in the HoReCa Sector: The Way towards a New Supply-Chain
Authors: García-Madurga Miguel-Ángel , Esteban-Navarro Miguel-Ángel , Morte-Nadal Tamara
Published: June 2021

The profound impact of the coronavirus pandemic on global tourism activity and the hospitality industry has rendered statistical approaches on tourism-demand forecasting obsolete. Furthermore, literature review shows the absence of studies on the supply chain in the HoReCa (hotel, restaurant, catering) sector from a sustainability perspective that also addresses economic and social aspects, and not only environmental ones. In this context, the objective of this article is to carry out a prospective analysis on how the changes in the behaviour of consumers during the pandemic and the uncertainties regarding the exit from the health emergency can give rise to social trends with a high impact on the HoReCa sector in the coming years and, specifically, how they will affect the HoReCa supply chain. In the absence of investigations due to the proximity of what has happened, public sources and reports of international relevance have been identified and analysed from the future studies and strategic and competitive intelligence disciplines. The HoReCa sector in Spain has been chosen as field of observation. This analysis draws the future of the HoReCa sector, describes the changes in customer behaviour regarding food and beverages, explains the changes in distribution chains, and reflects on the impact of potential scenarios on the sector. The confluence of all these changes and trends can even configure a new supply chain in the hospitality sector with the emergence of new actors and the increase of access routes to a new final customer for whom security prevails in all its dimensions: physical, emotional, economic, and digital.
Moped Scooter Sharing: Citizens’ Perceptions, Users’ Behavior, and Implications for Urban Mobility
Authors: Aguilera-García Álvaro , Gomez Juan , Sobrino Natalia , Vinagre Díaz Juan José
Published: June 2021

In recent years, moped-style scooter sharing is gaining increasing attention in many urban areas worldwide. Nevertheless, research contributions are still limited, unlike other shared mobility systems. This paper is aimed at providing a first insight on moped sharing demand by exploring the usage and opinions towards this new mobility alternative. To that end, the research exploits the data from a web-based survey conducted in Spain, one of the countries with the largest implementation around the world in terms of the shared e-mopeds fleet. Kruskal–Wallis tests were conducted to identify the segment of the urban population that is more likely adopted moped sharing, and additional statistical mean differences in specific variables concerning moped sharing were carried out. The paper also provides a better understanding of the shared mopeds market and some implications for urban mobility, such as the potential role of shared mopeds in reducing vehicle ownership and its effect on urban modal shift. Furthermore, two discrete choice models were developed to (i) analyze the key drivers determining the willingness to use moped sharing, and (ii) explore individuals’ opinions on whether owning a private vehicle will not be a need in the future. The results indicate that age, occupation, income, and environmental awareness seem to be among the main reasons behind the potential use of these services in the future. The results may be useful for both operators and transport planners when designing actions and policy efforts addressing this mobility option and urban mobility in general.
Synchronization-Free RadChat for Automotive Radar Interference Mitigation
Authors: Aydogdu Canan , Wymeersch Henk , Eriksson Olof , Herbertsson Hans , Rydström Mats
Published: June 2021

Automotive radar interference mitigation is expected to be inherent in all future ADAS and AD vehicles. Joint radar communications is a candidate technology for removing this interference by coordinating radar sensing through communication. Coordination of radars requires strict time synchronization among vehicles, and our formerly proposed protocol (RadChat) achieves this by a precise absolute time, provided by GPS clocks of vehicles. However, interference might appear if synchronization among vehicles is lost in case GPS is spoofed, satellites are blocked over short intervals, or GPS is restarted/updated. Here we present a synchronization-free version of RadChat (Sync-free RadChat), which relies on using the relative time for radar coordination, eliminating the dependency on the absolute time provided by GPS. Simulation results obtained for various use cases show that Sync-free RadChat is able to mitigate interference without degrading the radar performance.
An Empirical Analysis of Mode Choice Decision for Utilitarian and Hedonic Trips: Evidence from Iran
Authors: Mirzaei Enayat , Mignot Dominique
Published: June 2021

A sizeable body of literature reveals a strong relationship between mode choice and health status. Therefore, society would benefit from travel if transportation and urban planners motivated more individuals to satisfy their desire for travel by active transportation rather than motorized transportation. Despite rich existing literature about the relations between the built environment and travel, we still need to address some research gaps in explaining travel mode choice. As a shortcoming, identifying and measuring the primary motivations for trips, and then incorporating such motivations into travel mode choice modelling, has received less attention in previous research. In this regard the current paper follows two main goals. It aims to differentiate between trips by determining the main utility of travelers and then analyzes the impact of the built environment measurements and subjective attributes on mode choice decision. Using data from a survey of 515 participants who reside in Isfahan, Iran, we conducted a series of binary logistic models to explore how the built environment influences mode choice decisions for different trips, controlling for socio-economics and subjective attributes. The results show that the number of hedonic trips were sizably more than utilitarian trips. It was found that travel mode choice for utilitarian and hedonic trips is influenced by travel habits and subjective attitudes, but the built environment also matters. Specifically, two built environment characteristics, including density and diversity, can substitute walking/cycling for driving for utilitarian trips. In addition, car use for hedonic trips is not influenced by built environment measurements. It seems that the utility and desire of hedonic driving depends on mode of travel. It is concluded that driving and walking/biking for hedonic and utilitarian trips are not single behaviors and differentiating between trips according to their main utility and considering both objective and subjective attributes helps urban and transportation planners prescribe appropriate spatial and nonspatial strategies to encourage walking/biking.
Agro-Food Innovation and Sustainability Transition: A Conceptual Synthesis
Authors: Jia Xiangping
Published: June 2021

The global community faces the challenge of feeding a growing population with declining resources, making transformation to sustainable agriculture and food systems all the more imperative and ‘innovation’ all the more crucial. In this study, agro-food system innovation (re)defines sustainability transition with a complexity construct of cross-scale interaction and an adaptive cycle of system change. By taking a panarchical view, top-down and bottom-up pathways to innovation can be reconciled and are not contradictory, enabling and constraining innovation at every level. This study breaks down the structure of the agricultural innovation system into four components based on multi-level perspectives of sustainability transition, namely: actors and communities, interaction and intermediaries, coherence and connectedness and regimes rules and landscape. Meanwhile, this research frames the functional construct of system innovation for food and agriculture with five perspectives drawing on broad inputs from different schools of thought, namely: knowledge management, user sophistication, entrepreneurial activities’ directionality and reflexive evaluation. This research advocates for an ecosystem approach to agricultural innovation that gives full play to niche-regime interactions using social-technical perspectives.
Evaluation and Analysis of CFI Schemes with Different Length of Displaced Left-Turn Lanes with Entropy Method
Authors: Pan Binghong , Luo Shasha , Ying Jinfeng , Shao Yang , Liu Shangru , Li Xiang , Lei Jiaqi
Published: June 2021

As an unconventional design to alleviate the conflict between left-turn and through vehicles, Continuous Flow Intersection (CFI) has obvious advantages in improving the sustainability of roadway. So far, the design manuals and guidelines for CFI are not enough sufficient, especially for the displaced left-turn lane length of CFI. And the results of existing research studies are not operational, making it difficult to put CFI into application. To address this issue, this paper presents a methodological procedure for determination and evaluation of displaced left-turn lane length based on the entropy method considering multiple performance measures for sustainable transportation, including traffic efficiency index, environment effect index and fuel consumption. VISSIM and the surrogate safety assessment model (SSAM) were used to simulate the operational and safety performance of CFI. The multi-attribute decision-making method (MADM) based on an entropy method was adopted to determine the suitability of the CFI schemes under different traffic demand patterns. Finally, the procedure was applied to a typical congested intersection of the arterial road with heavy traffic volume and high left-turn ratio in Xi’an, China, the results showed the methodological procedure is reasonable and practical. According to the results, for the studied intersection, when the Volume-to-Capacity ratio (V/C) in the westbound and eastbound lanes is less than 0.5, the length of the displaced left-turn lanes can be selected in the range of 80 to 170 m. Otherwise, other solutions should be considered to improve the traffic efficiency. The simulation results of the case showed CFI can significantly improve the traffic efficiency. In the best case, compared with the conventional intersection, the number of vehicles increases by 13%, delay, travel time, number of stops, CO emission, and fuel consumption decrease by 41%, 29%, 25%, 17%, and 17%, respectively.
Railway Corridors in Croatian Cities as Factors of Sustainable Spatial and Cultural Development
Authors: Jurković Željka , Hadzima-Nyarko Marijana , Lovoković Danijela
Published: June 2021

Transport and mobility in cities are important factors in the sustainability of the urbanized world. This article investigates one type of intra-urban transport: railway transport and the surrounding areas along the railway, i.e., whether railway corridors can be a factor in the sustainable development of cities in the 21st century. The aim of the article is to determine specific characteristics of railway corridors and identify problems and cultural-historical specifics related to the industrial cultural heritage of the railway. The article examines the importance of an integrated approach to the planning of railway corridors and emphasizes the importance of multicriteria analyses in the decision-making process for corridor areas. As a case study, the city of Osijek is selected because in the past the railway strongly influenced its economical and urban development. Concretization and specification methods applied to the city of Osijek prove that railway corridors can become factors of the sustainable development of cities. The article proves that railway corridors have the potential to transform sustainable urban development because they pass through central, often historical, city areas, they occupy large surfaces and have a long linear spatial continuity. The scientific contribution of the article is the identification and systematization of the contribution of the transformation of railway corridors to the sustainable development of cities.
An Integrated Decision Support Model Based on BWM and Fuzzy-VIKOR Techniques for Contractor Selection in Construction Projects
Authors: Naghizadeh Vardin Aziz , Ansari Ramin , Khalilzadeh Mohammad , Antucheviciene Jurgita , Bausys Romualdas
Published: June 2021

Sustainable development of any country to some extent depends on successful accomplishment of construction projects, particularly infrastructures. Contractors have a key role in the success of these projects. Hence, the selection of a competent contractor as a complicated and hard decision process has a vital importance in the destiny of any construction project. Contractor selection is in essence a multicriteria decision-making that ought to encompass so many aspects of the project and the client’s requirements on one hand and the capabilities and past records of the contractors on the other hand. Failure in selecting a competent contractor may cause time and cost overruns; quality shortcomings; increasing in claims, disputes and change orders; and even failure of the project. In spite of deficiencies of selecting a contractor by the rule of “the lowest bid price”, it still prevails in many countries including Iran. In this paper, a new contractor selection model based on the best-worst method (BWM) and well-known Fuzzy-VIKOR techniques is proposed as a solution to overcome the deficiencies of the traditional “lowest bid price” rule. An illustrative example of a water channel construction project verified the applicability of the proposed model in practice.
Resident Support for Tourism Development: Application of a Simplified Resident Empowerment through Tourism Scale on Developing Destinations in Flanders
Authors: Neuts Bart , Kimps Senne , van der Borg Jan
Published: June 2021

While the potential macro-economic benefits of tourism development have been well-established, the negative social effects of uninhibited growth have received increased attention in the last decade, emphasizing the central role of communities in the search for a sustainable balance in tourism. This paper focuses on the relatively underdeveloped Scheldeland region in Flanders (Belgium), where a strategic goal is to leverage cultural and natural heritage to boost development. Via a resident questionnaire based on a simplified version of the Resident Empowerment through Tourism Scale (RETS), we identified support for tourism development and deconstructed the drivers of this support. The objective was to empirically validate the research instrument and underlying theory in a situation of relative ‘undertourism’ and prospective future growth. The questionnaire collected 2058 responses, and the partial least squares-structural equation modeling (PLS-SEM) results indicated that support for tourism, which was generally high across the seven municipalities, was mainly affected by social, psychological, and political empowerment, with personal economic benefits not playing a significant role. These results show that social exchange theory (SET) as a theoretical basis for potential tourism support has limited validity in currently underdeveloped destinations. Secondly, comparatively speaking, the municipalities with the lowest tourism development were least supportive of tourism growth, with an increase in tourism intensity seemingly leading to increasing support due to a higher awareness of accrued benefits through tourism.
Optimization of Conventional and Green Vehicles Composition under Carbon Emission Cap
Authors: Islam Md. Anisul , Gajpal Yuvraj
Published: June 2021

The CO2 emission of transportation is significantly reduced by the employment of green vehicles to the existing vehicle fleet of the organizations. This paper intends to optimize the composition of conventional and green vehicles for a logistics distribution problem operating under a carbon emission cap imposed by the government. The underlying problem involves product delivery by the vehicles starting from a single depot to geographically distributed customers. The delivery occurs within specified time windows. To solve the proposed problem, we design a hybrid metaheuristic solution based on ant colony optimization (ACO) and variable neighborhood search (VNS) algorithms. Extensive computational experiments have been performed on newly generated problem instances and benchmark problem instances adopted from the literature. The proposed hybrid ACO is proven to be superior to the state-of-the-art algorithms available in the literature. We obtain 21 new best-known solutions out of 56 benchmark instances of vehicle routing problem with time windows (VRPTW). The proposed mixed fleet model obtains the best composition of conventional and green vehicles with a 6.90% reduced amount of CO2 emissions compared to the case when the fleet consists of conventional vehicles only.
LEED Scores of Residential Buildings in Poor Cities: Kabul City Case
Authors: Sabory Najib Rahman , Senjyu Tomonobo , Momand Adina Hashemi , Waqfi Hadya , Saboor Nilofar , Mobarez Rabia , Razeqi Farida
Published: June 2021

Urbanization and technology have proven to be detrimental to the environment. Buildings contribute a significant portion of this damage. This issue motivated governments, builders, engineers, and architects to seek ways to reduce buildings’ environmental footprints. Leadership in Energy and Environmental Design (LEED), developed by the U.S. Green Building Council (USGBC), is one of the most widely used strategies to ensure energy efficiency and a clean environment in buildings. In Afghanistan, where there are no active regulatory frameworks for energy saving and efficiency for the building sector, it is imperative to promote the transformation of the building industry and practices towards sustainability. In this regard, the role of the residential building sector is of utmost importance due to its major share in the country’s energy consumption and GHG emissions profile. Thus, this study assesses the energy efficiency and environmental impact of existing buildings in Kabul city concerning the LEED rating system. This research suggests practical steps to improve the sustainability of the residential building stock in Kabul city. Robust sets of data on existing residential buildings in Kabul are collected, classified, evaluated, and compared to LEED standards. This research reveals and concludes that most of the existing buildings in Kabul city are in poor conditions and do not meet the minimum requirements to be a candidate for LEED certification. A detailed analysis of the results has led to recommendations on how these buildings could improve to meet the LEED criteria. This is the first study of its kind conducted for Kabul city residential building. Considering the cross-sectoral nature of the building industry, the findings of this study will contribute to many other areas such as water, transportation, ICT, health, energy and the environment.
Indicators of the Tourist Attractiveness of Urban–Rural Communes and Sustainability of Peripheral Areas
Authors: Świdyńska Natalia , Witkowska-Dąbrowska Mirosława
Published: June 2021

The elements which determine a peripheral area’s level of tourist attractiveness, such as tourist infrastructure and tourist values, should be developed in urban–rural communes in peripheral areas, where tourism may be one of the forces capable of stimulating sustainable development. This study covered urban–rural communes of the province of Warmia and Mazury in Poland. Urban–rural communes are specific areas where urban–rural linkages are often important. The research was carried out in accordance with Hellwig’s taxonomic development pattern method. The study found no complementary relationship between tourism values and tourism infrastructure with regards to creating tourism attractiveness. Tourism attractiveness was found to be more affected by tourism infrastructure. However, in units with larger urban centers, tourist values were found to significantly contribute to tourist attractiveness. The presented results provide a good basis for further research on the impact of global trends on regional development. At the same time, the analyzed framework provides guidance for ensuring the development of local tourism, and the study’s suggested priorities and measures could lead to the development of tourism in peripheral regions, which should in turn attract new investments, create new jobs, and thus develop the economy and the welfare of the population.