bluuebunny/crossref_metadata_2025 huggingface dataset:
Gait Variability to Phenotype Common Orthopedic Gait Impairments Using Wearable Sensors
Authors: Kushioka Junichi , Sun Ruopeng , Zhang Wei , Muaremi Amir , Leutheuser Heike , Odonkor Charles A. , Smuck Matthew
Published: November 2022

Mobility impairments are a common symptom of age-related degenerative diseases. Gait features can discriminate those with mobility disorders from healthy individuals, yet phenotyping specific pathologies remains challenging. This study aims to identify if gait parameters derived from two foot-mounted inertial measurement units (IMU) during the 6 min walk test (6MWT) can phenotype mobility impairment from different pathologies (Lumbar spinal stenosis (LSS)—neurogenic diseases, and knee osteoarthritis (KOA)—structural joint disease). Bilateral foot-mounted IMU data during the 6MWT were collected from patients with LSS and KOA and matched healthy controls (N = 30, 10 for each group). Eleven gait parameters representing four domains (pace, rhythm, asymmetry, variability) were derived for each minute of the 6MWT. In the entire 6MWT, gait parameters in all four domains distinguished between controls and both disease groups; however, the disease groups demonstrated no statistical differences, with a trend toward higher stride length variability in the LSS group (p = 0.057). Additional minute-by-minute comparisons identified stride length variability as a statistically significant marker between disease groups during the middle portion of 6WMT (3rd min: p ≤ 0.05; 4th min: p = 0.06). These findings demonstrate that gait variability measures are a potential biomarker to phenotype mobility impairment from different pathologies. Increased gait variability indicates loss of gait rhythmicity, a common feature in neurologic impairment of locomotor control, thus reflecting the underlying mechanism for the gait impairment in LSS. Findings from this work also identify the middle portion of the 6MWT as a potential window to detect subtle gait differences between individuals with different origins of gait impairment.
An Energy Efficient Load Balancing Tree-Based Data Aggregation Scheme for Grid-Based Wireless Sensor Networks
Authors: Wang Neng-Chung , Lee Chao-Yang , Chen Young-Long , Chen Ching-Mu , Chen Zi-Zhen
Published: November 2022

A wireless sensor network (WSN) consists of a very large number of sensors which are deployed in the specific area of interest. A sensor is an electronic device equipped with a small processor and has a small-capacity memory. The WSN has the functions of low cost, easy deployment, and random reconfiguration. In this paper, an energy-efficient load balancing tree-based data aggregation scheme (LB-TBDAS) for grid-based WSNs is proposed. In this scheme, the sensing area is partitioned into many cells of a grid and then the sensor node with the maximum residual energy is elected to be the cell head in each cell. Then, the tree-like path is established by using the minimum spanning tree algorithm. In the tree construction, it must meet the three constraints, which are the minimum energy consumption spanning tree, the network depth, and the maximum number of child nodes. In the data transmission process, the cell head is responsible for collecting the sensing data in each cell, and the collected data are transmitted along the tree-like path to the base station (BS). Simulation results show that the total energy consumption of LB-TBDAS is significantly less than that of GB-PEDAP and PEDAP. Compared to GB-PEDAP and PEDAP, the proposed LB-TBDAS extends the network lifetime by more than 100%. The proposed LB-TBDAS can avoid excessive energy consumption of sensor nodes during multi-hop data transmission and can also avoid the hotspot problem of WSNs.
Low-Complexity Hyperbolic Embedding Schemes for Temporal Complex Networks
Authors: Jiang Hao , Li Lixia , Zeng Yuanyuan , Fan Jiajun , Shen Lijuan
Published: November 2022

Hyperbolic embedding can effectively preserve the property of complex networks. Though some state-of-the-art hyperbolic node embedding approaches are proposed, most of them are still not well suited for the dynamic evolution process of temporal complex networks. The complexities of the adaptability and embedding update to the scale of complex networks with moderate variation are still challenging problems. To tackle the challenges, we propose hyperbolic embedding schemes for the temporal complex network within two dynamic evolution processes. First, we propose a low-complexity hyperbolic embedding scheme by using matrix perturbation, which is well-suitable for medium-scale complex networks with evolving temporal characteristics. Next, we construct the geometric initialization by merging nodes within the hyperbolic circular domain. To realize fast initialization for a large-scale network, an R tree is used to search the nodes to narrow down the search range. Our evaluations are implemented for both synthetic networks and realistic networks within different downstream applications. The results show that our hyperbolic embedding schemes have low complexity and are adaptable to networks with different scales for different downstream tasks.
Algorithm to Correct Measurement Offsets Introduced by Inactive Elements of Transducer Arrays in Ultrasonic Flow Metering
Authors: Massaad Jack , van Neer Paul L. M. J. , van Willigen Douwe M. , Pertijs Michiel A. P. , de Jong Nicolaas , Verweij Martin D.
Published: November 2022

Ultrasonic flow meters (UFMs) based on transducer arrays offer several advantages. With electronic beam steering, it is possible to tune the steering angle of the beam for optimal signal-tonoise ratio (SNR) upon reception. Moreover, multiple beams can be generated to propagate through different travel paths, covering a wider section of the flow profile. Furthermore, in a clamp-on configuration, UFMs based on transducer arrays can perform self-calibration. In this manner, userinput is minimized and measurement repeatability is increased. In practice, transducer array elements may break down. This could happen due to aging, exposure to rough environments, and/or rough mechanical contact. As a consequence of inactive array elements, the measured transit time difference contains two offsets. One offset originates from non-uniform spatial sampling of the generated wavefield. Another offset originates from the ill-defined beam propagating through a travel path different from the intended one. In this paper, an algorithm is proposed that corrects for both of these offsets. The algorithm also performs a filtering operation in the frequency-wavenumber domain of all spurious (i.e., flow-insensitive) wave modes. The advantage of implementing the proposed algorithm is demonstrated on simulations and measurements, showing improved accuracy and precision of the transit time differences compared to the values obtained when the algorithm is not applied. The proposed algorithm can be implemented in both in-line and clamp-on configuration of UFMs based on transducer arrays.
MWA Performed at 5.8 GHz through ‘Side Firing’ Approach: An Exploratory Study
Authors: Bottiglieri Anna , Brace Christopher , O’Halloran Martin , Farina Laura
Published: November 2022

Recent studies have shown that ablation techniques have the potential to eradicate adrenal adenomas while preserving the functionalities of the adrenal gland and the surrounding anatomical structures. This study explores a new microwave ablation (MWA) approach operating at 5.8 GHz and using anatomical and dielectric characteristics of the target tissue to create directional heating patterns. Numerical simulations are executed in planar and 3D adrenal models, considering two energy doses. The numerical study is refined accounting for the vaporization of the tissue water content. Ex vivo experimental evaluations on porcine adrenal models complete the study. The numerical and experimental results show that spherical ablation zones are able to cover the target for both energy doses considered. Nonetheless, most of the non-targeted tissues can be preserved from excessive heating when low energy level is used. Numerical models accounting for water vaporization are capable to foresee the experimental temperature values. This study shows that the proposed MWA directional approach operating at 5.8 GHz can be considered for creating effective and selective ablation zones.
Machine Learning-Based Ensemble Classifiers for Anomaly Handling in Smart Home Energy Consumption Data
Authors: Kasaraneni Purna Prakash , Venkata Pavan Kumar Yellapragada , Moganti Ganesh Lakshmana Kumar , Kannan Ramani
Published: November 2022

Addressing data anomalies (e.g., garbage data, outliers, redundant data, and missing data) plays a vital role in performing accurate analytics (billing, forecasting, load profiling, etc.) on smart homes’ energy consumption data. From the literature, it has been identified that the data imputation with machine learning (ML)-based single-classifier approaches are used to address data quality issues. However, these approaches are not effective to address the hidden issues of smart home energy consumption data due to the presence of a variety of anomalies. Hence, this paper proposes ML-based ensemble classifiers using random forest (RF), support vector machine (SVM), decision tree (DT), naive Bayes, K-nearest neighbor, and neural networks to handle all the possible anomalies in smart home energy consumption data. The proposed approach initially identifies all anomalies and removes them, and then imputes this removed/missing information. The entire implementation consists of four parts. Part 1 presents anomaly detection and removal, part 2 presents data imputation, part 3 presents single-classifier approaches, and part 4 presents ensemble classifiers approaches. To assess the classifiers’ performance, various metrics, namely, accuracy, precision, recall/sensitivity, specificity, and F1 score are computed. From these metrics, it is identified that the ensemble classifier “RF+SVM+DT” has shown superior performance over the conventional single classifiers as well the other ensemble classifiers for anomaly handling.
Optimal-Damage-Effectiveness Cooperative-Control Strategy for the Pursuit–Evasion Problem with Multiple Guided Missiles
Authors: Ma Xiang , Dai Keren , Li Man , Yu Hang , Shang Weichen , Ding Libo , Zhang He , Wang Xiaofeng
Published: November 2022

In this paper, an optimal-damage-effectiveness cooperative-control strategy based on a damage-efficiency model and a virtual-force method is proposed to solve the pursuit–evasion problem with multiple guided missiles. Firstly, different from the overly ideal assumption in the traditional pursuit–evasion problem, an optimization problem that maximizes the damage efficiency is established and solved, making the optimal-damage-effectiveness strategy more meaningful for practical applications. Secondly, a modified virtual-force method is proposed to obtain this optimal-damage-effectiveness control strategy, which solves the numerical solution challenges brought by the high-complexity damage function. Thirdly, adaptive gain is designed in this strategy based on guidance-integrated fuze technology to achieve robust maximum damage efficiency in unpredictable interception conditions. Finally, the effectiveness and robustness of the proposed strategy are verified by numerical simulations.
The Resilience of Tourism Recreation Companies in a Pandemic Context: The Case of Canyoning in the Azores
Authors: Silva Francisco , Lopes Tiago , Silva Mário
Published: November 2022

The COVID-19 pandemic had an enormous impact on the tourism sector. Economies with a large weight of external tourism were especially affected, as was the case with the Azores region. This paper aims to analyse the level of this crisis and the resilience of tourism recreation companies specializing in canyoning in the Azores region, and whether these reactions led to more sustainable business models. The adopted methodology considered the analysis of recent statistical data on tourism and the available information on COVID-19 pandemic-related impacts. In parallel, questionnaires were applied to all tourism recreation companies in Portugal, and semi-structured interviews were conducted with all the canyoning providers in the Azores region. Results show that all companies survived the crisis, and some have made significant changes to their business models. Furthermore, some degree of success was observed in how services adapted to new demand characteristics, given the small size of most of these businesses and the specialization of their products.
Using Computer Vision for Monitoring the Quality of 3D-Printed Concrete Structures
Authors: Senthilnathan Shanmugaraj , Raphael Benny
Published: November 2022

Concrete 3D printing has the potential to reduce material and process waste in construction. Thus, it contributes to making the construction industry more sustainable through the use of digital-fabrication technologies. While concrete 3D printing is attractive due to its potential to realize complex designs, practical challenges include an increased chance of defects and deformities. Quality assessment of 3D-printed elements is essential for large-scale implementation. Workability of concrete is known to decrease with printing time and it impacts extrudability. It is usually visible in 3D-printed elements, with the lower layers having a smooth finish, while the top layers have cracks and discontinuities. A computer-vision-based quality assessment method is proposed in this paper using a two-bin Linear Binary Pattern textural analysis. Information entropy is used as the metric for measuring the texture variation within each layer and its changes over the layers are studied. A higher entropy value is found for layers having deformities. Finally, through the error-minimization technique, a threshold entropy value is calculated and, using this, the printed layers can be assessed and corrective actions taken. This paper contributes to developing a non-intrusive quality assessment technique for concrete 3D-printed elements.
The Impact of COVID-19 Outbreak on Health Emergency and Disaster in Japan
Authors: Ishimaru Tomohiro , Shimizu Shoichi , Teshima Ayaka , Ibayashi Koki , Arikado Mihoko , Tsurugi Yoko , Tateishi Seiichiro , Okawara Makoto
Published: November 2022

The coronavirus disease 2019 (COVID-19) pandemic highlighted the importance of health emergency and disaster risk management (EDRM) to reduce the risks and impacts of infectious disease outbreaks. We investigated Japan’s response to the COVID-19 pandemic, focusing on changes made to the current health EDRM. Findings from document analysis and semi-structured interviews with six experts were integrated to provide insights into Japan’s health EDRM to improve outcomes in future health emergencies. Relevant information was extracted from COVID-19 policy documents published by the Japanese government, and the interviews validated and expanded on the data already collected. Challenges faced in the country’s response to COVID-19 and the changes made to the health EDRM framework are summarised. Findings were grouped into human resource topics (including essential health EDRM positions and safety of personnel), health service delivery topics (including public health and hospital primary care services), and logistical topics (including vaccination, personal protective equipment, patient transport, and telecommunications). These responses to the pandemic could serve as an example of good practice for other countries developing strategies for future health emergencies and disasters.
How Do Innovation-Driven Policies Help Sports Firms Sustain Growth? The Mediating Role of R&D Investment
Authors: Ding Yang , Chen Gang
Published: November 2022

The sports industry features low energy intensity and low emissions through which it has played an important role in realizing sustainable development. This study aims to examine the driving factors that help sports firms improve their innovation development and sustain growth. Using a panel of 95 sports firms listed on the New Third Board in China from 2015 to 2021 with 582 observations, this study evaluated the effect of innovation-driven policies on sports firms’ long-term growth, measured by market value, and the mediating effect of R&D investment on this relationship. The results showed that innovation subsidies and the deduction of R&D expenses can effectively encourage sports firms’ engagement in innovation development and finally help improve the firms’ market value. Furthermore, we found that the effect of R&D subsidies on sports firms’ market values increases with firm size. This study provides new insights into the literature on the long-term growth of sports firms by showing that policy support for sports firms’ innovation activities enables them to invest more resources into research and development activities, which finally reinforce their potential of long-term growth. Furthermore, the findings provide practical suggestions for policymakers on enhancing the development of the sports industry and helping sports firms sustain growth.
An Intelligent Wildfire Detection Approach through Cameras Based on Deep Learning
Authors: Wei Changan , Xu Ji , Li Qiqi , Jiang Shouda
Published: November 2022

Fire is one of the most serious disasters in the wild environment such as mountains and jungles, which not only causes huge property damage, but also may lead to the destruction of natural ecosystems and a series of other environmental problems. Considering the superiority and rapid development of computer vision, we present a novel intelligent wildfire detection method through video cameras for preventing wildfire hazards from becoming out of control. The model is improved based on YOLOV5S architectures. At first, we realize its lightweight design by incorporating the MobilenetV3 structure. Moreover, the improvement of detection accuracy is achieved by further improving its backbone, neck, and head layers. The experiments on a dataset containing a large number of wild flame and wild smoke images have demonstrated that the novel model is suitable for wildfire detection with excellent detection accuracy while meeting the requirements of real-time detection. Its wild deployment will help detect fire at the very early stage, effectively prevent the spread of wildfires, and therefore significantly contribute to loss prevention.
How Do K–12 Students’ Perceptions of Online Learning Environments Affect Their Online Learning Engagement? Evidence from China’s COVID-19 School Closure Period
Authors: Ma Yunpeng , Zuo Mingzhang , Yan Yujie , Wang Kunyu , Luo Heng
Published: November 2022

A learning environment’s quality has crucial influence on a student’s engagement. In this study, we utilized a structural equation modeling approach to explore the structural relationships between students’ perceptions of an online learning environment and their online learning engagement during China’s COVID-19 school closure period by focusing on an online learning environment and the specific features that facilitate student engagement. The online learning environment was conceptualized as a multidimensional structure consisting of four elements: pedagogy, social interaction, technology, and the consideration of home learning conditions. Student engagement was conceptualized as a multifaceted construct comprising behavioral, emotional, and cognitive engagement. The results showed that teaching presence significantly predicted deep behavioral engagement (β = 0.246), emotional engagement (β = 0.110), and cognitive engagement (β = 0.180). Social presence significantly positively predicted cognitive engagement (β = 0.298) and emotional engagement (β = 0.480), whereas its effect on behavioral engagement was not significant. The perceived ease of technology use significantly predicted only emotional engagement (β = 0.324), and the family learning presence significantly predicted only behavioral engagement (β = 0.108). The results also indicated that emotional and cognitive engagement had indirect effects on the predictive power of the online learning environment for behavioral engagement. These findings provide valuable guidelines and effective strategies for teachers and parents to design suitable online learning environments to enhance K–12 student engagement.
Upgrading Anaerobic Sludge Digestion by Using an Oil Refinery By-Product
Authors: Alimohammadi Mahsa , Demirer Goksel N.
Published: November 2022

Carbon-based conductive additives have been studied for their positive effects on anaerobic digestion (AD) using synthetic substrates, but their importance in wastewater sludge digestion has not been sufficiently explored. This research investigated and compared the effects of two conductive materials (graphene and petroleum coke) with and without trace metal supplementation. The results indicated that supplementing reactors with graphene and petroleum coke could significantly improve biogas production. The supplementation of 1 g/L petroleum coke and 2 g/L graphene, without trace metal addition, led to an increase in the biogas production by 19.10 ± 1.04% and 16.97 ± 5.00%, respectively. Thus, it can be concluded that petroleum coke, which is an oil refinery by-product, can be used to enhance biogas production in a similar way to other carbon-based conductive materials that are currently available on the market. Moreover, using petroleum coke and graphene, the average chemical oxygen demand (COD) removal was 42.84 ± 1.23% and 42.80 ± 0.45%, respectively, without the addition of trace metals. On the other hand, supplementation of the reactors with trace elements resulted in a COD removal of 34.65 ± 0.43% and 34.05 ± 0.45% using petroleum coke and graphene, respectively.
Streamliners, Switchmen and Bridge Builders: About the Mechanisms and Uniqueness of Accelerator Programs
Authors: Ulmer Thomas , Pape Ulrich
Published: November 2022

Accelerators are a new and fast-growing element in entrepreneurial ecosystems. However, our understanding about their impact on the development of startups remains limited. Utilizing a grounded theory approach and in-depth interviews with 21 entrepreneurs, this study investigates the value-adding mechanisms of accelerators. Our analysis, however, is not limited to financial capital, which allows us to highlight the relative importance of different forms of capital in the context of accelerators. We aim to understand how accelerators stimulate the development of participants and extend the support landscape for early-stage startups. Our results are threefold. First, we demonstrate that accelerators facilitate every step in the resource mobilization by reducing uncertainties and compensating for deficiencies. Second, the founding process becomes more structured, as participants build a founder identity and the process itself is professionalized. Third, accelerators support startups in building a resource base, by providing immediate resources and building bridges to various other resources.
The Role of Employees’ Technology Readiness, Job Meaningfulness and Proactive Personality in Adaptive Performance
Authors: Abdul Hamid Roshayati
Published: November 2022

The escalating utilization of digital technology has created new challenges and therefore calls for modifications in organizational culture, technology infrastructure and job structure. However, there is still a lack of research studies that view digital technology from the perspective of how challenges of digital technology can be addressed at the employee level. Transformation toward digitalization requires employees’ readiness to adapt to the new job structure. Adaptability is the employees’ ability to adapt to changes. Employees with adaptive performance can solve problems creatively, manage volatile situations and handle pressure effectively. Adaptive performance can be enhanced when employees are ready to adopt the utilization of digital technology or technology readiness. Technology readiness is the tendency of employees to use new technology to achieve goals related to their lives and work. However, an individual’s tendency to utilize digital technology varies depending on their perception of their job’s meaningfulness and the personality that the person has. Therefore, the objective of this study is to investigate the relationship between employees’ technology readiness and adaptive performance, and to examine the role of job meaningfulness as a mediator and proactive personality as a moderator. Data was analyzed using the PLS-SEM. The results showed that employees with the tendency to utilize technology in their jobs have higher adaptive performance. Furthermore, the relationship is mediated by job meaningfulness and is enhanced by employees with highly proactive personalities. The findings from this study can drive organizations to motivate their employees and provide a flexible job structure to encourage the employees to utilize technology more effectively.
Performance Evaluation of Environmentally Sustainable Precast Cement Concrete Paver Blocks Using Fly Ash and Polypropylene Fibre
Authors: Sundaramurthy Suresh , Bala Shashi , Sharma Anil Kumar , Verma Jyoti , Zahmatkesh Sasan , Arisutha S. , Verma Sarika , Sillanpaa Mika , Ravichandran Nagavinothini , Panneerselvam Balamurugan
Published: November 2022

Paver blocks are manufactured from zero-slump plain concrete, which is small element used for outdoor applications and flexible road surfaces. IS:15658 (2006) permits the use of 33- grade ordinary Portland cement (OPC) as the minimum for manufacturing paver blocks, but the usage of this type of cement is restricted in India nowadays. In this context, we have studied OPC 43-grade cement replaced by 30% Class F-grade fly ash and the addition of 0.0% and 0.5% polypropylene fibre (PPF) to evaluate the suitability of paver blocks in terms of the climatic conditions, movement of vehicles and road surfaces in India. The synergistic effect of the mechanical properties of paver blocks revealed that a 30% replacement of OPC with fly ash and 0.3% PPF is more suitable for the manufacturing of paver blocks. The obtained results from the reference mixes indicated that the mechanical properties of paver blocks have increased with respect to the age of the blocks. The present study is important for paver block manufacturers as it fulfils the mix design, strength and durability requirements for Indian roads associated with the utilization of waste materials such as fly ash. Additionally, the study will help the national economy increase by 20% in the future, along with the sustainability of virgin materials.
Manifold Design in a PEM Fuel Cell Stack to Improve Flow Distribution Uniformity
Authors: Rahimi-Esbo Mazaher , Sangtabi Ahmad Rezaei , Alizadeh Ebrahim
Published: November 2022

In this paper, a numerical study was performed to investigate the flow distribution in a 52-cell proton exchange membrane (PEM) fuel cell stack. The non-uniformity factor and standard deviation parameters were used to determine the flow distribution uniformity. Flow channels of each bipolar plate were replaced with straight parallel channels filled with porous media to reduce computational costs. The effect of external and integrated humidifiers on the gas distribution among the channels was investigated. Using integrated humidifiers improved the non-uniformity factor and standard deviation by 35% and 19%, respectively. Two methods were employed to improve the flow distribution: gradual reduction of the manifold height, and installing a bump at the bottom wall of the inlet manifold. Reducing the height of the inlet manifold in the stack with integrated and external humidifiers decreased the non-uniformity factor by 62% and 44%, respectively. The installation of the bump on the manifold wall enhanced flow distribution in the stack with the external humidifier. The results show that by using an integrated humidifier in this method, the flow distribution became more non-uniform. The best flow distribution in the stack was obtained with an integrated humidifier and a 90% reduction in manifold height. In this case, the flow rate passing through each channel was more than 99% of the average mass flow rate passing through the entire channel.
Investigation of the Phycoremediation Potential of Freshwater Green Algae Golenkinia radiata for Municipal Wastewater
Authors: Sisman-Aydin Goknur , Simsek Kemal
Published: November 2022

Recent developments in the removal of pollutants from wastewater show that phycoremediation to wastewater treatment and reuse wastewater may provide sustainable biosolutions. This work investigated the performance of the green microalgae Golenkinia radiata Chodat 1984 (Chlorophyceae) in terms of N, P, and COD removal at different treatment stages of municipal wastewater, reusability of remediated wastewater and wastewater-based biomass production. Water samples were taken from different wastewater units (presettling basin effluent, active sludge basin effluent, and discharge channel) of a municipal wastewater treatment plant (İzmir, Turkey). In the 7-day experiments, Chl-a, Chl-b, DO, pH, and T (°C) were also measured alongside the pollutant analyses. The results in Chl-a (1803 ± 75.9 µg L−1) and biomass yield (7.66 ± 0.05 g L−1) in the primary effluent (P) were quite impressive. Additionally, the results showed that the correlation between the increase in Chl-a and the residual concentrations of pollutants was remarkable. NH4-N, NO3-N, NO2-N, PO4-P, and COD treatment efficiencies were in the ranges of (74.6–83.0%), (15.35–70.4%), (0.00–47.22%), (80.67–86.27%), and (77.22–87.53%), respectively. The final concentrations of pollutants (E) were found to comply with EU legislation. The results also reveal that green microalgae G. radiata may be a strong candidate for microalgae-based wastewater treatment.
Simulation and Prediction of Land Use/Cover Changes Based on CLUE-S and CA-Markov Models: A Case Study of a Typical Pastoral Area in Mongolia
Authors: Sun Changqing , Bao Yulong , Vandansambuu Battsengel , Bao Yuhai
Published: November 2022

Modeling and predicting land use/cover change (LUCC) and identifying its drivers have been a focus of research over the past few decades. In order to solve the problem of land resource degradation in typical pastoral areas, reveal the temporal and spatial evolution characteristics of LUCC, and the contradiction between man and land in sustainable development, we analyze the Gurvanbulag area of Bulgan province, Mongolia, where grassland degradation is relatively serious. The LUCC data in 2000, 2010 and 2019 were obtained through interpreting human-computer interaction. On this basis, the same binary logistic regression (BLR) results were input into the multi-criteria evaluation analytic hierarchy process (MCE_AHP) of CLUE-S and CA_Markov models. The Current Trends (CT) and Ecological Protection (EP) development scenarios were used to predict the temporal and spatial evolution characteristics of LUCC in 2030 and 2040. The results show: (1) both models can effectively simulate the LUCC in 2019, and the CLUE-S model was significantly better than the CA_Markov model. (2) From 2000 to 2019, the LUCC in this region was dominated by a decrease in water and the growth of grassland and other land, indicating that the region is at the risk of land resource degradation. (3) In a multi-scenario development study, by 2030 and 2040, both models predicted that the EP development scenario is more effective in protecting the local ecological environment and it is easier to achieve the sustainability of land resources, than the CT development scenario. Combined with local policy demands and the prediction results of restraining land resource degradation, CLUE-S was significantly higher than the CA_Markov model, indicating that in typical pastoral areas, the former is more in line with the need for sustainable development of the local ecological environment than the latter.
Evaluation and Choice Criteria of Sustainable Suppliers in the Construction Industry: A Comparative Study in Brazilian Companies
Authors: Castro e Silva Andreia de , Seleme Robson , de Assis Silva Wiliam , Zattar Izabel Cristina , Nara Elpidio Oscar Benitez , Júnior Osiris Canciglieri , Benitez Lisianne Brittes
Published: November 2022

This article seeks to develop criteria for evaluating sustainable suppliers in civil construction and to contribute to improving the understanding of the factors that influence the selection of sustainable suppliers. Organizations should develop strategies that motivate suppliers to participate in green supply-chain initiatives, as supplier selection can directly interfere with sustainability performance at work. However, there is a gap in the research that addresses the selection of sustainable suppliers in the Brazilian context of civil construction related to certifications for sustainable construction. To fill this gap, the present article used literature-review methodologies, content analysis, data triangulation, and field research through a survey. The literature review identifies the certifiable standards for sustainable construction most cited in the literature: LEED, AQUA, BREEAM, and CASBEE. The standards analysis allows us to identify seven similar supply criteria for sustainable construction certifications. The parameters of each certification were analyzed to define those related to the selection of suppliers, identifying those that qualify a supplier as environmentally sustainable. We found that 60.7% of respondents work in companies without certifications, 75% know sustainable procurement, 50% of companies had established a sustainable procurement policy, and 83% of companies had a strategy for selecting suppliers. The results of this research contribute to construction companies being able to rank the importance of these criteria when choosing a supplier, in addition to having access to the mapping of essential criteria, allowing a search for greater interaction between the links of the green supply chain and rendering buildings and supplies more sustainable.
Scale Compromise: Three Challenges of Large-Scale but Citizen-Driven Urban Planning
Authors: Filip Artur Jerzy
Published: November 2022

Amongst various urban crises, some fundamental ones require long-term policies and large-scale developments to be effectively mitigated. Since multiple government-led large-scale projects raised more and more public opposition, the question whether such grand endeavors can be approached by citizen-driven initiatives became urgent. However, large-scale urban planning issues are still believed to be too big, too complex, and too difficult to be solved from the bottom up. This paper examines such recurring belief—here termed the “scale compromise”—and conceptualizes it across two essential dimensions of urban planning: spatial and political. The scale compromise is presented twofold, as each side of the compromise is embedded within a separate strand of urban planning practice: large-scale urban planning as traditionally associated with the authority-led approach, and citizen-driven urbanism as traditionally linked with locality. Regarding each approach, respectively, the causes, consequences, and difficulties of the scale compromise are discussed from both perspectives. Finally, by breaking down the resulting compromise across three integral aspects of planning—the socio-economic, organizational, and technical—the “scale compromise” conceptual framework indicates three scale-related challenges. Accordingly, this paper argues why all the three challenges must be met concurrently, as failing at one squanders the efforts made for the others. Finally, some recent experience in the development of urban greenway projects in the U.S. are discussed as promising points of reference for dealing with the scale compromise and for seeking new solutions to fundamental urban crisis.
The Impact of Traffic Information Provision and Prevailing Policy on the Route Choice Behavior of Motorcycles Based on the Stated Preference Experiment: A Preliminary Study
Authors: Fadilah Siti Raudhatul , Nishiuchi Hiroaki , Ngoc An Minh
Published: November 2022

It is anticipated that the prevalence of motorcycles in Asian countries will continue to increase, causing congestion and network imbalances concerning the nature of motorcycles. Literature demonstrates Variable Message Signs (VMSs) as an effective measure for addressing this issue. Understanding route choice behavior may thus aid in determining the appropriate traffic information to broadcast. This study aims to identify the impact of VMS messages related to traffic conditions and regulations on the route choice of motorcycle riders. In this instance, the core concept of ramp metering is adapted for non-highways to manage the proportion of motorcycles entering the traffic stream of the mainline. Two predetermined routes were offered through a stated preference survey to capture the responses to VMS. A binary logit model was initially introduced, further improved by including the individual characteristics and accommodating the unobserved factors across a series of observations (panel effects) by applying the mixed binary logit. It was revealed that traffic flow conditions significantly affect route preference; therefore, motorcycles tend to choose routes with lower volumes. However, waiting time at a ramp meter has no impact. The present research is a preliminary investigation for further implications in proposing traffic management strategies under mixed traffic situations.
Glycerol-Based Deep Eutectic Solvents for Simultaneous Organosolv Treatment/Extraction: High-Performance Recovery of Antioxidant Polyphenols from Onion Solid Wastes
Authors: Bozinou Eleni , Palaiogiannis Dimitrios , Athanasiadis Vassilis , Chatzilazarou Arhontoula , Lalas Stavros I. , Makris Dimitris P.
Published: November 2022

Onion solid wastes (OSW) are a food side-stream with high polyphenolic load and distinguished polyphenolic profile. This study was conducted in order to explore a novel methodology of production of polyphenol-enriched extracts with antioxidant properties from OSW, using glycerol and green deep eutectic solvents (DES), composed of glycerol/citric acid and glycerol/sodium acetate. The organosolv process developed was appraised by establishing models based on severity, but also response surface methodology. Using a linear model, it was, for the first time, proposed that there is a direct correlation between the yield of the process in total polyphenols and the combined severity factor. Furthermore, response surface optimization enabled the establishment of linear models to predict the effects of time and temperature on the total polyphenol extraction yield. Out of the solvents tested, the DES composed of citric acid and glycerol was found to provide the highest yield in total polyphenols (87.90 ± 3.08 mg gallic acid equivalents per g dry mass) at significantly higher combined severity. However, the extraction efficiency of this solvent was virtually equal to that of the two other solvents tested. On the other hand, the polyphenolic composition of the extract obtained with the glycerol/citric acid DES was characterized by exceptionally high quercetin concentration. This extract also displayed the highest antioxidant activity. Based on the evidence emerged, it was proposed that OSW polyphenol extraction with the DES glycerol/citric acid could be used for production of extracts enriched in the bioactive flavonoid quercetin, with enhanced antioxidant activity. Moreover, using this green methodology, 27.59 ± 0.09 g of pure quercetin could be recovered out of 1 kg OSW. Thus, this methodology could be employed as a sustainable means of producing quercetin, through valorization of food wastes in a biorefinery context.
Longitudinal Predictors of Perceived Climate Change Importance and Worry among Italian Youths: A Machine Learning Approach
Authors: Prati Gabriele , Tzankova Iana , Albanesi Cinzia , Cicognani Elvira
Published: November 2022

The current study aimed to investigate the longitudinal predictors of perceived importance of climate change and personal worry among Italian youths. Specifically, we used machine learning techniques to examine the predictive importance of a wide range of socio-demographic factors, political perceptions, attitudes on a national and European level (identity, attitudes, tolerance, support for democracy, authoritarianism, nationalism, political trust), efficacy beliefs, social well-being, political interest, and different forms of participation on perceived importance of climate change and personal worry. In this longitudinal study, we collected data using a questionnaire in two waves at a one-year interval—in 2016 and 2017. Participants were 1288 Italian young adults (61.3% were female; 38.7% were male) whose mean age was 19.18 (SD = 3.29) ranging between 15 and 30 years. Breiman’s random forest algorithm performed better than Friedman’s gradient boosting machines algorithm. The random forest algorithm revealed that age, tolerance toward migrants, and tolerance toward refugees were the most important predictors of perceived importance of climate change and personal worry. Other important predictors were national/European identity, political interest, internal political efficacy, nationalism, social well-being, self-efficacy, authoritarianism, anti-democratic attitudes, EU warmth, and online and civic participation.
Changes in Agri-Food Export Competitiveness Based on the Sophistication Analysis: The Case of Xinjiang, China
Authors: Wang Jingjing , Zhang Yan , Mustafa Zeeshan , Canavari Maurizio
Published: November 2022

The Xinjiang Uygur Autonomous Region is a major agri-food export contributor within China. Growing quality requirements for agri-food export, increasing green trade barriers, and a desire to emphasize sustainable trade at regional levels have prompted Xinjiang to pay increased attention to agri-food export competitiveness. The paper uses the export sophistication index to investigate the overall and classificatory export competitiveness of Xinjiang’s Agricultural Products (APs). The results are compared to the national average within China by calculating the relative export sophistication. The research finds that (1) Xinjiang’s APs exports are predominant in medium and medium-low-sophistication products. Along with the expanding scale, its structure has been optimized overall. (2) Horticultural products keep a leading position, not having strong competitiveness in Xinjiang but also far exceeding the national average. However, the bulk APs, livestock products, aquatic products, beverages and tobacco, and other APs have no significant export competitiveness compared to the national average. (3) The export structure of Xinjiang’s APs is highly concentrated in horticultural products, showing an adverse trend in export competitiveness distribution—”the strong getting stronger and the weak getting weaker,” and a slower upgrading than the national average since the outbreak of COVID-19, which requires the attention of policymakers.
Obtaining bioLPG via the HVO Route in Brazil: A Prospect Study Based on Life Cycle Assessment Approach
Authors: Menezes Natália de Almeida , Cunha Isadora Luiza Clímaco , dos Santos Moisés Teles , Kulay Luiz
Published: November 2022

BioLPG is a partially renewable fuel that can be produced by different conversion routes, with vegetable oil hydrotreatment (HVO) being one of the most promising processes. This study uses the Life Cycle Assessment (LCA) approach to assess the environmental impacts associated with this processing. The analysis considered the conditions practiced in Brazil with soybean oil (SO) as raw material, different hydrogen sources, and raw materials’ feed rates in the reaction system. The model was based on secondary data collected for the 2020–2021 biennium, and the environmental impacts were determined for Global Warming Potential, Primary Energy Demand, Terrestrial Acidification, Fine Particulate Matter Formation, Terrestrial Ecotoxicity, and direct Land Use Change. The results show that the SO produced by soybeans grown in Paraná/BR and hydrotreated with H2 obtained by electrolysis ([SO/H2]mol/mol = 1:30) had the best environmental performance in four of the six impact categories analyzed. A complementary analysis also identified the best environmental performances for bioLPG obtained from blending SO from different sources to avoid supplier dependence. Even accumulating worse environmental performance than fossil LPG, renewable fuel has promising prospects for deployment in Brazil. Nevertheless, for this to occur, some actions must be implemented in its production cycle.
Building with Nature—Ecosystem Service Assessment of Coastal-Protection Scenarios
Authors: Schernewski Gerald , Voeckler Lars Niklas , Lambrecht Leon , Robbe Esther , Schumacher Johanna
Published: November 2022

The aim of this study is to assess existing conventional and hypothetical nature-based coastal-protection schemes using a comparative ecosystem service assessment, based on quantitative data and literature as well as on stakeholder views. We assessed three conventional groin systems and three building-with-nature scenarios including an expanded beach area, a mussel farm and seagrass beds. Stakeholders perceived the nature-based scenarios as positive and assumed an overall increase in the ecosystem service provision. The quantitative data-based approach showed similar results. Building-with-nature approaches were considered to provide economical and/or environmental benefits to human beings, beyond coastal protection and safety. Especially for the combination of coastal-protection measures with submerged vegetation in shallow waters, a strong increase in ecosystem service potential is assumed, e.g., on nature restoration as well as on touristic and landscape attractiveness. Our approach turned out to be suitable for assessing different coastal-protection scenarios with reasonable effort. Our methodology can help to catch the views of people, raise awareness on the multiple consequences of these measures and enable an improved and structured participatory dialogue with locals and stakeholders. Our approach may support coastal-protection planning and help to reduce local resistance against measures and their implementation.
Sustainable Gardening for Economic Inclusion, Poverty Reduction, and Culture Preservation
Authors: Rivas-Aceves Salvador , Schmidt Sarah
Published: November 2022

Sustainable gardening activities can be the basis to reduce poverty while preserving culture. By generating economic inclusion, gardening can provide the entry point into society for vulnerable communities. Community stakeholders in Mexico City and Northeast Ohio were studied to analyze whether sustainable gardening can generate economic inclusion while preserving culture. Through in-depth interviews, the relationship between these three components is analyzed. In particular, topics such as gardening experience, family traditions, institutional support, economic barriers, use of technology, cropping methods, and social integration were explored. From conception to implementation and analysis, the goal of agency building reinforced social sustainability. In addition to interpretive qualitative interviews, experiential research was conducted through a “working-with” model where the communities in reference contributed intellectual resources to the project-based research design. Primary results fall into three primary categories including gardening methods, cultural preservation, and economic factors. In each analyzed case, implications of cultural preservation emerge as a foundational motivation to maintain the particular agricultural practice. Despite significant economic barriers, including high poverty rates, the cases in reference nonetheless maintain traditions, thus highlighting the importance of culture. Negative economic implications suggest an absence of institutional support, which contribute to issues of poverty and low quality of life. Social implications indicate a level of marginalization that contributes to the aforementioned economic and institutional barriers.