bluuebunny/crossref_metadata_2025 huggingface dataset:
Foxtail Millet Ear Detection Method Based on Attention Mechanism and Improved YOLOv5
Authors: Qiu Shujin , Li Yun , Zhao Huamin , Li Xiaobin , Yuan Xiangyang
Published: October 2022

In the foxtail millet field, due to the dense distribution of the foxtail millet ears, morphological differences among foxtail millet ears, severe shading of stems and leaves, and complex background, it is difficult to identify the foxtail millet ears. To solve these practical problems, this study proposes a lightweight foxtail millet ear detection method based on improved YOLOv5. The improved model proposes to use the GhostNet module to optimize the model structure of the original YOLOv5, which can reduce the model parameters and the amount of calculation. This study adopts an approach that incorporates the Coordinate Attention (CA) mechanism into the model structure and adjusts the loss function to the Efficient Intersection over Union (EIOU) loss function. Experimental results show that these methods can effectively improve the detection effect of occlusion and small-sized foxtail millet ears. The recall, precision, F1 score, and mean Average Precision (mAP) of the improved model were 97.70%, 93.80%, 95.81%, and 96.60%, respectively, the average detection time per image was 0.0181 s, and the model size was 8.12 MB. Comparing the improved model in this study with three lightweight object detection algorithms: YOLOv3_tiny, YOLOv5-Mobilenetv3small, and YOLOv5-Shufflenetv2, the improved model in this study shows better detection performance. It provides technical support to achieve rapid and accurate identification of multiple foxtail millet ear targets in complex environments in the field, which is important for improving foxtail millet ear yield and thus achieving intelligent detection of foxtail millet.
Kinematic/Dynamic SLAM for Autonomous Vehicles Using the Linear Parameter Varying Approach
Authors: Vial Pau , Puig Vicenç
Published: October 2022

Most existing algorithms in mobile robotics consider a kinematic robot model for the the Simultaneous Localization and Mapping (SLAM) problem. However, in the case of autonomous vehicles, because of the increase in the mass and velocities, a kinematic model is not enough to characterize some physical effects as, e.g., the slip angle. For this reason, when applying SLAM to autonomous vehicles, the model used should be augmented considering both kinematic and dynamic behaviours. The inclusion of dynamic behaviour implies that nonlinearities of the vehicle model are most important. For this reason, classical observation techniques based on the the linearization of the system model around the operation point, such as the well known Extended Kalman Filter (EKF), should be improved. Consequently, new techniques of advanced control must be introduced to more efficiently treat the nonlinearities of the involved models. The Linear Parameter Varying (LPV) technique allows working with nonlinear models, making a pseudolinear representation, and establishing systematic methodologies to design state estimation schemes applying several specifications. In recent years, it has been proved in many applications that this advanced technique is very useful in real applications, and it has been already implemented in a wide variety of application fields. In this article, we present a SLAM-based localization system for an autonomous vehicle considering the dynamic behaviour using LPV techniques. Comparison results are provided to show how our proposal outperforms classical observation techniques based on model linearization.
Optical Rail Surface Crack Detection Method Based on Semantic Segmentation Replacement for Magnetic Particle Inspection
Authors: Kou Lei , Sysyn Mykola , Fischer Szabolcs , Liu Jianxing , Nabochenko Olga
Published: October 2022

Railway damage detection is of great significance in ensuring railway safety. The cracks on the rail surface play a key role in studying the formation and development process of rail damage, predicting the occurrence of rail defects, and then improving the service life of the rail. However, due to the small shape of the cracks, the typical detection method is relatively complicated, and the speed is quite slow. Although traditional magnetic particle inspection technology is fairly accurate at detection, it is costly and inconvenient to carry and install, while also limiting the detection speed and affecting the system’s operation. In this paper, a semantic segmentation detection method is developed by using various collected rail surface crack data and deep learning through a neural network. By comparing the inspection of the same rail surface with magnetic particle inspection technology, only inexpensive cameras are used and the inspection speed is increased while maintaining relatively high accuracy. In addition, the method can achieve fast detection speeds if it is extended to be combined with high-frequency cameras. It is an economical, efficient, and environmentally friendly method for future rail surface detection.
Implementation of a Low-Cost Data Acquisition System on an E-Scooter for Micromobility Research
Authors: Pérez-Zuriaga Ana María , Llopis-Castelló David , Just-Martínez Víctor , Fonseca-Cabrera Alejandra Sofía , Alonso-Troyano Carlos , García Alfredo
Published: October 2022

In recent years, cities are experiencing changes in the ways of moving around, increasing the use of micromobility vehicles. Bicycles are the most widespread transport mode and, therefore, cyclists’ behaviour, safety, and comfort have been widely studied. However, the use of other personal mobility vehicles is increasing, especially e-scooters, and related studies are scarce. This paper proposes a low-cost open-source data acquisition system to be installed on an e-scooter. This system is based on Raspberry Pi and allows collecting speed, acceleration, and position of the e-scooter, the lateral clearance during meeting and overtaking manoeuvres, and the vibrations experienced by the micromobility users when riding on a bike lane. The system has been evaluated and tested on a bike lane segment to ensure the accuracy and reliability of the collected data. As a result, the use of the proposed system allows highway engineers and urban mobility planners to analyse the behaviour, safety, and comfort of the users of e-scooters. Additionally, the system can be easily adapted to another micromobility vehicle and used to assess pavement condition and micromobility users’ riding comfort on a cycling network when the budget is limited.
Genotype and Environment Effects on Phytosterol and Tocopherol Contents in Almond Kernel Oil
Authors: Kodad Ossama , Fernandez-Cuesta Alvaro , Velasco Leonardo , Estopañán Gloria , El Baji Mina , Martínez-García Pedro José , Martínez-Gómez Pedro , i Company Rafel Socias
Published: October 2022

The phytosterol and tocopherol contents of almond kernel oil were evaluated in three almond cultivars, including the Spanish cultivar ‘Marcona’ and the French cultivars ‘Ferragnès’ and ‘Ferraduel’, grown under two different agro-climatic conditions, Zaragoza (Spain) and Meknès (Morocco). The analysis of variance showed significant effects of the genotype on kernel phytosterol content, Δ5-Avenasterol, Δ7-Campesterol, Stigmasterol and on the three tocopherol isomers. The location effect was significant on oil and kernel phytosterol contents, β-sitosterol,Δ5-avenasterol, Δ7-stigmastenol, Δ7-campesterol and α- and γ-tocopherol. The highest value of kernel and oil phytosterol contents were observed at Meknès (1.48 g kg−1 and 2.54 g kg−1, respectively), as compared to those obtained at Zaragoza (1.31 g kg−1 and 2.54 g kg−1, respectively).The highest values ofβ-sitosterol and Δ5-avenasterol were obtained at the Zaragoza location (81.93% and 10.55% of total phytosterols, respectively).The highest value of α-tocopherol was observed in the Morocco location (496 mg kg−1 oil). These results indicate that under warm climate conditions in Morocco, the almond cultivars tend to accumulate more phytosterol and tocopherol. However, the significance of the genotype × location interaction on the phytosterol and tocopherol contentindicates that the magnitude of variation in these traits mainly depends on the genotype.
Exploring Intersectional Variations in Sexual Pleasure, Sexual Autonomy, and Important Correlates
Authors: Alarcão Violeta , Stefanovska-Petkovska Miodraga , Candeias Pedro , Pascoal Patrícia M.
Published: October 2022

Research suggests that pressure to meet gender norms can limit social behaviors and ultimately promote poor health outcomes, such as disparities in decreased sexual pleasure, which are considered a central component of human rights and well-being. Previous studies have shown that sexual pleasure and sexual autonomy are gender-related, but little is known about these indicators in diverse populations. This study used data from a probabilistic sample of Cape Verdean immigrant (n = 127) and Portuguese native (n = 133) women and men who were in an intimate relationship enrolled in the FEMINA (Fertility, Migration and Acculturation) project to explore intersectional variations in sexual pleasure, sexual satisfaction, and distress considering their interplay with sexual autonomy and social representations regarding sexuality. For all participants and especially among men, sex is a very important part of life. Sexual autonomy was positively associated with sexual pleasure among Cape Verdean and Portuguese women and Portuguese men. Sexual distress was negatively associated with sexual pleasure among women, especially Cape Verdean women who reported higher sexual distress. This small-scale study is an example of an intersectional approach to sexual health and rights.
Is the Current Modelling of Litter Decomposition Rates Reliable under Limiting Environmental Conditions Induced by Ongoing Climate Change?
Authors: Ranucci Maddalena , Perez Martina , Lombardi Danilo , Vitale Marcello
Published: October 2022

Plant litter decomposition is a key process in the biogeochemical cycles of terrestrial ecosystems. The main goal of this work is to determine the impact of current climate change on the decomposition process of the litter of Palo Laziale Wood (Rome, Italy), one of the last remnants of the Tyrrhenian lowland forest. A time-dependent simulation of leaf litter decay was previously performed on a dynamic semi-empirical model based on Olson’s model (1963). It was also assumed that microbial activity depended on optimal temperature and moisture conditions simulated by Climatic Decomposition Index (CDI). The comparison between the observed and simulated leaf litter biomass reduction over time (t = −0.127, p = 0.901) highlighted the adequacy of CDI in reproducing biomass trends under limiting climatic conditions (high temperature and low precipitation). However, the decomposition model used here was not able to simulate the reduction of recalcitrant compounds (lignin) in strongly limiting conditions of water availability in the Palo Laziale Wood. These climatic conditions were attributable to climate change, which made the year 2020 representative of future years increasingly characterized by limiting climatic conditions. Therefore, it is necessary to carefully calibrate the CDI in order to consider the current and future changes in temperature and water availability in the Mediterranean area, and to, therefore, perform a better model-based foreseeing for leaf litter decomposition.
An Interval Valued Pythagorean Fuzzy AHP–TOPSIS Integrated Model for Ergonomic Assessment of Setup Process under SMED
Authors: Kose Yildiz , Civan Hatice Nida , Ayyildiz Ertugrul , Cevikcan Emre
Published: October 2022

Single-minute exchange of dies (SMED) is one of the most significant lean tools which reduces the required time for setup operations. The consideration of appropriate ergonomic interferences during the SMED implementation improves working conditions, productivity, and flexibility. The SMED literature has an opportunity for expansion with ergonomic assessment. Moreover, ergonomic assessment studies have various limitations in terms of a broad hierarchy of ergonomic factors and their weighting. Therefore, this study enriches the literature by providing the ergonomic assessment of the setup process through integrating multi-criteria decision-making (MCDM) into SMED. In this context, a wide hierarchy of ergonomic risk factors is compiled for ergonomic assessment. The Interval Valued Pythagorean Fuzzy Analytic Hierarchy Process (IVPF-AHP) method is used to determine the weights of factors. Then, Fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is used to prioritize setup tasks in terms of ergonomic factors by using the Interval Valued Pythagorean Fuzzy Sets (IVPFSs). The proposed model was validated by applying it to a real-life manufacturing system in the white goods supplier industry. The application results justify the proposed model with a setup time reduction of 58% and an ergonomic improvement of 19%.
Impact of Changes in Membership on Prices of a Unified Carbon Market: Case Study of the European Union Emissions Trading System
Authors: Xu Yue , Zhai Dayu
Published: October 2022

Using the event study methodology, the paper studies the effects of 22 key events in countries’ process of entering and exiting the European Union on returns of European Union Allowance (EUA) future prices in the EU Emissions Trading System (EU ETS). The events include 17 entry events concerning the signing of relevant agreements, becoming a candidate or potential candidate country, the process of a negotiation and formally entering the EU, and five exit events including the process of Brexit and the suspension of Iceland. The results show that two entry events involving Albania and Ukraine, respectively, have a significant positive impact, and five entry events have a significant negative impact. Among the exit events, the announcement of the Brexit referendum results causes significant negative market reaction. Most events regarding small carbon emitters entering the EU lead to negative cumulative abnormal returns (CAR) of EUA prices, and a significant negative correlation between the countries’ annual average carbon emissions and CAR is found, while the change of national allocation plans does not affect the market reaction notably. In the process of establishing a unified carbon market, regulators should carry out appropriate policy arrangements of emission allowances allocation when new members join, in order to guide market expectations and enhance market stability.
Carbon Neutrality in Shanxi Province: Scenario Simulation Based on LEAP and CA-Markov Models
Authors: Li Man , Zhang Yanfang , Liu Huancai
Published: October 2022

In the context of global climate governance and China’s carbon neutrality target, Shanxi Province, one of China’s major energy exporting regions, is under high pressure to achieve carbon neutrality. This paper sets up three carbon source scenarios and three carbon sink scenarios based on the Long-range Energy Alternatives Planning System (LEAP) and CA-Markov models to simulate the future change in carbon source and carbon sink of Shanxi from 2020 to 2060; it analyzes the achievement of the carbon peaking and carbon neutrality targets for each source–sink scenario. The results show that: (1) The total energy consumption and CO2 emissions have increased significantly, from 2000 to 2020, especially in heavy industry; (2) The CO2 emissions are predicted to peak at 381.6 Mt, 294.1 Mt and 282.7 Mt in 2040 (baseline scenario), 2030 (policy scenario), and 2025 (carbon neutrality scenario), respectively. The achievement of the carbon neutrality mainly depends on the reduction in CO2 emissions; (3) If Shanxi Province strives to reach the energy intensity of developed countries by 2060, with 80% of non-fossil energy generation, it has the potential to achieve the carbon neutrality target; (4) The popularization of carbon capture, utilization and storage (CCUS) technology will significantly accelerate the achievement of Shanxi Province’s carbon neutrality target.
Organic Leadership—Implicit Followership Interaction: Relations among Trust in Supervisor, Active Followership and OCB
Authors: Liu Sheng-Wen , Hsieh Ming-Tsang , Norcio Ralph , Rao Harika
Published: October 2022

Due to the impact of COVID-19, a large number of employees of organizations around the world have been forced to work remotely from home starting in 2020. As a result, leaders and followers face new communication and interaction challenges. If an enterprise is to be successful in the new wave of economic development, it must embrace the role of employee followers. However, there is currently no relevant research. Therefore, the purpose of this study is to analyze the interaction between organic leadership and implicit followers from the perspective of followers who are working remotely and further analyze their relationship with trust in their supervisor, organizational citizenship behavior, and active followership. Using the method of questionnaire measurement, multigroup analysis and ANCOVA and PLS-SEM analysis found the following. First, difference in leadership styles (IV) and implicit followers (IV) had significant effects on employees’ trust in supervisor (DV), organizational citizenship behavior (DV), and active followers (DV). Secondly, the influence of the leaders’ styles (IV) on employees’ trust in supervisor (DV), organizational citizenship behavior (DV), and active followership (DV) was significantly affected only when IFTs were anti-prototypical traits. Finally, organizational citizenship behavior (Med) had an indirect effect between trust in supervisor (DV) and active followership (DV). This article not only fills the gaps in the literature related to leaders and followers, but also provides analytical evidence and new thinking which will enable companies to propose management strategies more effectively for employees working remotely in the face of the impact of the epidemic.
Flood Damage Assessment: A Review of Microscale Methodologies for Residential Buildings
Authors: Aribisala Oluwatofunmi Deborah , Yum Sang-Guk , Adhikari Manik Das , Song Moon-Soo
Published: October 2022

Flood damage assessment (FDA) is an essential tool for evaluating flood damage, vulnerability, and risk to civil systems such as residential buildings. The outcome of an FDA depends on the spatial limits of the study and the complexity of the data. For microscale FDA, a high level of detail is required to assess flood damage. This study reviewed the existing methodologies in microscale FDA based on empirical and synthetic data selection methods for model development. The merits and challenges of these approaches are discussed. This review also proposes an integrated step for assessing the stages of FDA. This study contributes to the literature by providing insights into the methodologies adopted, particularly on a microscale basis, which has not been comprehensively discussed in the previous reviews. The findings of this study reveal that univariate modeling of flood damage is nevertheless popular among researchers. New advanced approaches, such as advanced machine learning and 3D models, are yet to gain prominence when compared with the univariate modeling that has recorded a high success. This review concludes that there is a need to adopt a combined empirical–synthetic approach in the selection of data for developing damage models. Further research is required in the areas of multivariate modeling (advanced machine learning), 3D BIM-GIS modeling, 3D visualization of damages, and projection of probabilities in flood damage predictions to buildings. These are essential for performance flood-based building designs and for promoting building resilience to flood damage.
Experimental Study of a Tubular Solar Distillation System with Heat Exchanger Using a Parabolic Trough Collector
Authors: Amin Muhammad , Umar Hamdani , Amir Fazri , Ginting Suma Fachruri , Sudarsana Putu Brahmanda , Septiadi Wayan Nata
Published: October 2022

One way to overcome the scarcity of clean water through sustainable approach is by utilizing a solar distillation system. This easy-to-use technology is adopting tubular solar distillation. The three main components, which are the most essential for producing the amount of permeate, are the solar collector, tubular and heat exchanger (HE). This study aims to determine the performance of a tubular solar distillation device equipped with HE using a parabolic trough collector (PTC). The PTC has an area of 5.1 m2 covered with a solar reflective chrome film. Aluminum tubular acts as the feedwater heater. The HE is placed inside the tubular, which acts as a coolant to convert the steam phase into freshwater/permeate and as a feedwater heater to flow into the tubular. In the present study, several parameters were tested: comprise temperature, solar radiation, pressure, humidity, mass flow rate, permeate productivity and efficiency. This study demonstrated the production of a sufficient amount of permeate, which was 5.32 L for 6 h. The efficiency of this device yielded a peak of 48.2% during solar radiation of 813 W/m2 in an average ambient temperature of 32 °C, with an overall average of 44.59%.
Identifying and Explaining Public Preferences for Renewable Energy Sources in Qatar
Authors: Nassar Ahmed K.
Published: October 2022

As a major natural gas and oil producer, Qatar has made significant strides towards its energy transition. This paper uses a survey research design with statistical tests to investigate citizens’ preferences for a wide range of energy resources. In this study, participants were asked to prioritize energy sources based on their environmental impact, price, benefits to Qatar’s economy, support of energy security, and ability to create jobs. The results showed that approximately two-thirds of the sample (n = 354) preferred renewable energy sources, particularly solar, which ranks first. Renewable energy sources were more likely to be favored by the group with greater knowledge of energy sources than those with limited knowledge, except for solar energy, which was preferred by both groups. Additionally, both natural gas and wind rank second in terms of preference, followed by hydropower. In contrast, nuclear power was not ranked, indicating a strong opposition to this type of energy. The study provides an evidence-based example of the tendency of citizens in a hydrocarbon-rich country to prefer renewable energy sources and natural gas. The energy policymakers need to collaborate with local communities so that citizens can participate in important future energy discussions to develop a personal connection to climate solutions.
Research on the Evaluation of Coordinated Development of Tourism–Economy–Ecological Environment along the Silk Road Economic Belt
Authors: Zhang Zhe , Qin Jianxiong , Luo Li , Feng Yaxin
Published: October 2022

Tourism is currently one of the important development industries in many countries and regions, and a healthy environment is an important basis and carrier for the sustainable development of the tourism economy. Ensuring a harmonious relationship between tourism, the economy, and the environment has become one of the keys to achieving sustainable development of tourism destinations. Based on panel data on tourism, the economy, and the environment from nine provinces along the Silk Road Economic Belt from 2015 to 2019, this study has built a comprehensive evaluation index system of the tourism–economy–ecological environment (TEE). The entropy evaluation method, comprehensive evaluation model, and coupling and coordination degree model were used for quantitative analysis of the coordination development level and for assessing the spatial–temporal evolution patterns of coupling coordination for the TEE system in nine provinces along the Silk Road Economic Belt. The results show that the value of the TEE system is generally on the rise. Still, the growth rate of tourism and the economy subsystem is significantly higher than that of the environment subsystem. The coupling coordinating the development of the TEE system shows an increasing trend with a high degree of coupling. The coordination degree is relatively low, with significant gradient differences and apparent polarization. The main constraint to the coordinated development of the Silk Road Economic Belt is tourism and the economy.
Dynamic Estimation of Urban Land Use Efficiency and Sustainability Analysis in China
Authors: Cheng Huifang , Yu Ting , Zhang Hao , Duan Kaifeng , Zhu Jianing
Published: October 2022

With rapid urbanization in China, land use efficiency (LUE) and related sustainability should be reasonably evaluated and improved. Studies have rarely investigated urban LUE and lack an analysis from the sustainability perspective. Long-term analysis can help identify the weaknesses in LUE and obtain a more stable evaluation. Hence, in this paper we develop a dynamic data envelopment analysis (DEA) model to assess urban LUE considering the time dimension. Differing from studies on traditional static DEA models, this study connects the observed periods by creating a common objective function. In addition, a method for estimating the sustainability of urban LUE is proposed under the DEA framework. The proposed method was applied to 34 major Chinese cities over a 3-year period, from 2015 to 2017. The results reveal that urban LUE still has potential for improvement in most cities. There was a distinct difference in efficiency among eastern, central, and western cities during the observed period. The average efficiency was higher in eastern cities than in central and western cities. The potential to optimize the land area and GDP should be realized with more efforts by most cities to strengthen LUE. Additionally, most inefficient cities have weak performance regarding the sustainability of LUE. The proposed approach enriches the sustainable measurement of LUE. Some management implications are provided to improve urban LUE. The empirical findings provide important support for sustainable land use in practice, and the proposed model is an important empirical extension of the DEA method in the land management field.
Architects’ Perceptions about Sustainable Design Practice and the Support Provided for This by Digital Tools: A Study in Australia
Authors: Yu Rongrong , Gu Ning , Ostwald Michael J.
Published: October 2022

The fundamental goal of sustainable design for the built environment is to optimise the performance of buildings to minimise their impact on the environment. To achieve this goal, contemporary architects use a range of digital design environments, such as Computer-aided Design (CAD) or Building Information Modelling (BIM) tools. These allow architects to implement sustainable design principles and make optimal decisions about the ecological and energy properties of the building or environment being designed. Past research about architects’ uses of these tools for sustainable design have been focused on their capacity for optimising building performance and meeting architects’ design needs. In parallel, other studies have identified technological barriers and readiness factors for implementing sustainable design in several countries, including Australia. Researchers have suggested that presently, most architects are unlikely to perceive Building Performance Analysis (BPA) as their responsibility. It has also been found that the digital design tools need to more effectively support sustainable design. However, despite this body of past research, to date there is a lack of a more holistic understanding regarding architects’ perceptions about the alignment between sustainability practices and the capacity of digital design environments for supporting these, particularly in Australia. This paper addresses this knowledge gap, by presenting findings derived from semi-structured interviews with 18 professional architects in Australia, each with experiences in sustainable design and the use of digital design tools. The results are used to establish a conceptual model, which illustrates the relationships between a variety of factors affecting architects’ sustainable design practices. The findings suggest that in Australia, architects have more negative than positive experiences regarding their sustainable design practices, due to factors ranging from those related to the practice itself, to the digital design technologies and budget available for supporting their goals. This study also identifies an urgent need to enhance and better align the capabilities of digital design technologies with sustainable outcomes and associated organisational objectives, which the new model can assist in understanding and facilitating.
Assessment of Sustainable Maintenance Strategy for Manufacturing Industry
Authors: Ighravwe Desmond Eseoghene
Published: October 2022

This study creates a framework to aid in the sustainability of maintenance strategies. The framework was created using expertise from the industry and academia. Using this knowledge, three multi-criteria tools were chosen for the maintenance strategies evaluation. The tools include grey relational analysis (GRA) techniques, additive ratio assessment (ARAS), and step-wise weight assessment ratio analysis (SWARA). In a production system, they were used to assess four planned maintenance strategies. The strategies are periodic maintenance (S1), meter-based maintenance (S2), predictive maintenance (S3) and prescriptive maintenance (S4). The ARAS approach was used to obtain the strategy rating for the various requirements. This study used the SWARA method to determine the requirements’ importance using an intuitionistic fuzzy triangular number. The ARAS results were combined using the GRA method. This study observed that the criteria utilised to choose a maintenance strategy for equipment depend on the information collected from six specialists in a manufacturing organisation. For instance, it was discovered that S3 was the maintenance approach that best suited the system’s technical needs. At the same time, S2 was found to be less effective. The economic needs analysis showed that S1 is the maintenance strategy that is most appropriate for the system, while S3 is the least appropriate. S1 is the most appropriate maintenance method for the system, given the social requirements, whereas S2 is the least effective. According to the results of the environmental requirements, S2 is the best maintenance plan for the system, while S4 is the worst. According to the GRA approach, the system’s best and least appropriate maintenance strategies are S2 and S4, respectively.
A Torque-Compensated Fault-Tolerant Control Method for Electric Vehicle Traction Motor with Short-Circuit Fault
Authors: Hou Feiyu , Yao Fei , Li Zheng
Published: October 2022

The development of traditional vehicles which consume fossil carbon-based fuels is constrained by environmental pollution and the energy crisis, and it has become a social consensus to develop electric vehicles with new energy resources and low emissions. The drive system of electric vehicles should be able to reliably operate over a long period. When a short-circuit fault occurs in the driving motor, the current in the winding will increase sharply and threaten driving safety. This paper proposed a short-circuit fault-tolerant control strategy for a dual three-phase permanent magnet synchronous traction motor (DT-PMSTM) which can resolve the problem of short-circuit faults. The current in non-short-circuit fault windings has been reconstructed to offset the interference of the short-circuit current and output a stable torque. Based on the principle of constant composited magnetic motive force (MMF), the dimension-reduced orthogonal transformation matrix was derived. The compensation currents were designed according to the interference effect of the short-circuit current to the normal MMF of the motor. Consequently, the lost torque component caused by the lack of the short-circuit winding was compensated, and the torque pulsation was also reduced. The performance of the topologies with neutral point-isolated mode and neutral point-connected mode were both investigated and compared. The validity of the proposed short-circuit fault-tolerant control strategy was proved by the simulation results.
Injury Severity Analysis of Rear-End Crashes at Signalized Intersections
Authors: Sharafeldin Mostafa , Farid Ahmed , Ksaibati Khaled
Published: October 2022

Signalized intersections are common hotspots for rear-end crashes, causing severe injuries and property damage. Despite recent attempts to determine the contributing causes to injury severity in this crash type, the frequency of severe rear-end crashes is still significant. Therefore, exploring commonly omitted potential risk factors is essential to proper detection of contributing factors to these crashes and planning appropriate countermeasures. This research incorporated the examination of intersection crash data in Wyoming to examine injury severity risk factors in this crash type. The study examined a set of potential roadway, driver, crash, and environmental risk factors, including pavement surface friction, which is a commonly omitted factor in relevant studies. A random-parameters ordinal probit model was developed for the analysis. The findings demonstrated that two crash attributes (motorcycle involvement and improper seat belt use), three driver’s attributes (driver’s condition, age, and gender), and two environmental and roadway characteristics (road condition and pavement friction) impacted the injury severity of rear-end crashes at signalized intersections.
Dynamic Evaluation and Regional Differences Analysis of the NEV Industry Development in China
Authors: Liang Yanhua , Lu Hongjuan
Published: October 2022

In the transportation sector, new energy vehicles (NEVs) are critical to reduce CO2 emissions in the context of carbon neutralization. The study of dynamic evaluation and regional difference analysis is helpful to the NEV industry development in policy design and industrial planning. In this study, based on the provincial data in China from 2016 to 2020, the grey target model and Dagum Gini coefficient method are employed for the dynamic evaluation and regional differences of the NEV industry development. The results were as follows: (1) The overall and provincial level of the NEV industry development showed an increasing pattern. The bull’s eye degrees of Guangdong, which had the best development, were 0.4884, 0.5361, 0.6067, 0.6787, and 0.7047 during the study period. (2) The regional differences in the NEV industry development were significant. The east region had the best development, followed by the middle, the west, and the northeast regions. The intra-regional differences were expanding with different annual growth rates. (3) The inter-regional differences between the east and the other three regions were the largest. The regional differences in the NEV development are mainly derived from inter-regional dereference. (4) The D1, D2, and D3 dimensions all contributed significantly to provinces with higher levels of development, while the D4 dimension contributed significantly to provinces with lower levels of development. Based on these results, different provinces should take differentiated development strategies and enhancement paths to promote their NEV industry development.
Comparing Law Enforcement Performance of Forest Stations at Pu Hu Nature Reserve, Vietnam
Authors: Khac Dong Le , Hoa Ao Xuan , Nguyen Nha Thi Huynh , Thu Hue Ha Thi , Techato Kuaanan
Published: October 2022

In Vietnam, most protected areas are guarded and their natural resources are conserved by forest rangers, who carry out their law enforcement duties from forest stations. Previous research projects have been undertaken on law enforcement performance during traditional patrolling in most protected areas; however, insights into patrolling efforts at the local level, as a part of protection activities, have been significantly missing. The aim of this paper was to compare the law enforcement performance of rangers at two forest stations in the Pu Hu Nature Reserve (NR). These forest rangers face different challenges and illegal activities, depending on local conditions, which means that their law enforcement activities can vary widely. The results provided initial insights into the different variables of law enforcement performance and illegal encounters at the local level. The number of illegal encounters and distance walked were not significantly different between the two forest stations, unlike other variables, such as relative altitude, walking speed, and patrol hours. The ratios of illegal encounters to relative altitude and to speed at the Nam Tien Forest Station were higher than the equivalent findings at the Trung Thanh Forest Station due to differences in terms of the patrolling hours and distance walked between the two forest stations. Action to improve conservation is essentially a matter of implementing conservation planning in parallel with the current situation. Undoubtedly, the successful management of forests by stations in a protected area will be indicated by a positive law enforcement performance.
Life Cycle Assessment of Cynara cardunculus L. -Based Polygeneration and Biodiesel Chains
Authors: Barros Lovate Temporim Ramoon , Cavalaglio Gianluca , Petrozzi Alessandro , Coccia Valentina , Cotana Franco , Nicolini Andrea
Published: October 2022

Given the current scenario of increasing environmental problems associated with the need for rapid energy transition, this article aimed to investigate the implementation of Cynara cardunculus L. (cardoon), a plant with high environmental performance, as a source of energy resources. This study presented thLife Cycle Assessment of two energy production chains—for the polygeneration of power, heat, and cooling; and to produce biodiesel—fed with cardoon seeds, in addition to comparing these chains with the use of the traditional Italian grids (power and gas) and with the production of diesel based on palm, soybean, and rapeseed. Approximately 49 t of seeds were cultivated and processed, yielding 8.5 t of oil. The system boundaries encompass three main macro-phases, cardoon production, oil extraction, and, depending on the application, energy generation (polygeneration) or transesterification (biodiesel). The models were developed using the software SimaPro V9.3.0.2, and the inventory was based on the database ecoinvent V3.8. The Life Cycle Impact Assessment was performed using the ReCiPe V1.06 method at the midpoint (H) and endpoint (H/A) levels. Crude cardoon oil showed a global warming of 20–55% lower than other vegetable oils (palm, soybean, and rapeseed). In the case of biodiesel production, cardoon-based biodiesel presented a reduction in the impact burden by 12–57% compared to biodiesel based on palm, soybean, and rapeseed. With the use of oil in Polygeneration, a subtle increase in the impact burden was observed, with 13% more impact than the use of Italian power and gas grids.
Early Identification of Significant Patents Using Heterogeneous Applicant-Citation Networks Based on the Chinese Green Patent Data
Authors: Liu Xipeng , Li Xinmiao
Published: October 2022

With the deterioration of the environment and the acceleration of resource consumption, green patent innovation focusing on environmental protection fields has become a research hot-spot around the world. Previous researchers constructed homogeneous information networks to analyze the influence of patents based on citation ranking algorithms. However, a patent information network is a complex network containing multiple pieces of information (e.g., citation, applicant, inventor), and the use of a single information network will result in incomplete information or information loss, and the obtained results are biased. In addition, scholars constructed centrality indicators to assess the importance of patents with less consideration of the age bias problem of algorithms and models, and the results obtained are inaccurate. In this paper, based on the Chinese green patent (CNGP) dataset from 1985 to 2020, a CNGP heterogeneous applicant-citation network is constructed, and the rescaling method and normalization procedure are used to solve the age bias. The results illustrate that the method proposed in this paper is able to identify significant patents earlier, and the performance of the rescaled indegree (R_ID) works best such as the IR score is 17.32% in the top 5% of the rankings, and it is the best in the constructed dynamic heterogeneous networks as well. In addition, the constructed heterogeneous information network has better results compared with the traditional homogeneous information network, such as the NIR score of R_ID metrics can be improved by 2% under the same condition. Therefore, the analysis method proposed in this paper can reasonably evaluate the quality of patents and identify significant patents earlier, thus providing a new method for scientists to measure the quality of patents.
Prediction of Waterway Cargo Transportation Volume to Support Maritime Transportation Systems Based on GA-BP Neural Network Optimization
Authors: Jin Guangying , Feng Wei , Meng Qingpu
Published: October 2022

Water transportation is an important part of comprehensive transportation and plays a critical role in a country’s economic development. The world’s cargo transportation is dominated by waterway transportation, and maritime transportation Systems (MTS) are the main part of the waterway transportation system. The flow of goods plays a key role in the economic development of the ports along the route. The sustainable development of maritime transportation, the maritime transportation economy and the environment have great practical significance. In this paper, the principle of the BP (back propagation) neural network is used to predict the freight transportation volume of China’s waterways, and the genetic algorithm (GA) is used to optimize the BP neural network, so as to construct the GA-BPNN (back propagation neural network) prediction model. By collecting and processing the data of China’s water cargo transport volume, the experimental results show that prediction accuracy is significantly improved, which proves the reliability of the method. The experimental methods and results can provide certain reference information for the optimization, upgrade, and more scientific management of sustainable MTS in China and internationally, provide key information for port cargo handling plans, help optimize port layout, and improve transportation capacity and efficiency.
A New Regional Distributed Photovoltaic Power Calculation Method Based on FCM-mRMR and nELM Model
Authors: Zhu Honglu , Jiang Tingting , Sun Yahui , Sun Shuang
Published: October 2022

As the proportion of distributed photovoltaic (DP) increases, improving the accuracy of regional distributed photovoltaic power calculation is crucial to making full use of PV and ensuring the safety of the power system. The calculation of regional power generation is the key to power prediction, performance evaluation, and fault diagnosis. Distributed photovoltaic plants (DPP) are characterized by scattered distribution and small installed capacity, lots of DPPs are not fully monitored, and their real-time output power is difficult to obtain. Therefore, to improve the observability of DPPs and increase the accuracy of calculation, a new method that combines with fuzzy c-means (FCM), Max-Relevance and Min-Redundancy (mRMR) and Extreme Learning Machine(ELM), which can calculate the regional DPP output power without meteorological data is proposed, and validated using actual operational data of regional DPPs in China. The calculations results show good robustness in different months. The innovation of this study is the combination of the benchmark DPP selection method FCM-mRMR and the power calculation method nELM, and the mean absolute error (MAPE) of the proposed method is 0.198 and the coefficient of determination (R2) is 0.996.
How to Effectively Promote Eco-Friendly Behaviors: Insights from Contextual Behavioral Science
Authors: Stapleton Alison , McHugh Louise , Karekla Maria
Published: October 2022

The rapidly increasing rate of climate change is a major threat of our time. Human behaviors contribute to climate change. These behaviors are malleable. To change human behavior in significant and sustainable ways, we need a scientific understanding of motivation and behavior change. One area in psychological science that provides precision, scope, and depth to our understanding of human behavior and motivation is contextual behavioral science (CBS). The current article provides an account of how CBS can provide real-world solutions to promoting positive behavior change to reduce human-induced climate issues. Specifically, we will outline six evidence-based considerations for organizations aiming to promote pro-environmental behaviors through messaging, advertising, and social marketing. Practical examples are provided across all six considerations to promote behavior change to reduce the rapidly increasing rate of climate change.
Roles of Medicinal Mushrooms as Natural Food Dyes and Dye-Sensitised Solar Cells (DSSC): Synergy of Zero Hunger and Affordable Energy for Sustainable Development
Authors: Ahmad Nurfadzilah , Vunduk Jovana , Klaus Anita , Dahlan Nofri Yenita , Ghosh Soumya , Muhammad-Sukki Firdaus , Dufossé Laurent , Bani Nurul Aini , Wan-Mohtar Wan Abd Al Qadr Imad
Published: October 2022

In 2015, approximately 195 countries agreed with the United Nations that by 2030, they would work to make the world a better place. There would be synergies in accomplishing the 17 Sustainable Development Goals (SDGs). Synergy using a single sustainable resource is critical to assist developing nations in achieving the SDGs as cost-effectively and efficiently possible. To use fungal dye resources, we proposed a combination of the zero hunger and affordable energy goals. Dyes are widely used in high-tech sectors, including food and energy. Natural dyes are more environment-friendly than synthetic dyes and may have medicinal benefits. Fungi are a natural source of dye that can be substituted for plants. For example, medicinal mushrooms offer a wide range of safe organic dyes that may be produced instantly, inexpensively, and in large quantities. Meanwhile, medicinal mushroom dyes may provide a less expensive choice for photovoltaic (PV) technology due to their non-toxic and environmentally friendly qualities. This agenda thoroughly explains the significance of pigments from medicinal mushrooms in culinary and solar PV applications. If executed effectively, such a large, unwieldy and ambitious agenda may lead the world towards inclusive and sustainable development.