bluuebunny/crossref_metadata_2025 huggingface dataset:
Cross-Modality Interaction Network for Equine Activity Recognition Using Imbalanced Multi-Modal Data
Authors: Mao Axiu , Huang Endai , Gan Haiming , Parkes Rebecca S. V. , Xu Weitao , Liu Kai
Published: September 2021

With the recent advances in deep learning, wearable sensors have increasingly been used in automated animal activity recognition. However, there are two major challenges in improving recognition performance—multi-modal feature fusion and imbalanced data modeling. In this study, to improve classification performance for equine activities while tackling these two challenges, we developed a cross-modality interaction network (CMI-Net) involving a dual convolution neural network architecture and a cross-modality interaction module (CMIM). The CMIM adaptively recalibrated the temporal- and axis-wise features in each modality by leveraging multi-modal information to achieve deep intermodality interaction. A class-balanced (CB) focal loss was adopted to supervise the training of CMI-Net to alleviate the class imbalance problem. Motion data was acquired from six neck-attached inertial measurement units from six horses. The CMI-Net was trained and verified with leave-one-out cross-validation. The results demonstrated that our CMI-Net outperformed the existing algorithms with high precision (79.74%), recall (79.57%), F1-score (79.02%), and accuracy (93.37%). The adoption of CB focal loss improved the performance of CMI-Net, with increases of 2.76%, 4.16%, and 3.92% in precision, recall, and F1-score, respectively. In conclusion, CMI-Net and CB focal loss effectively enhanced the equine activity classification performance using imbalanced multi-modal sensor data.
Simultaneous Burr and Cut Interruption Detection during Laser Cutting with Neural Networks
Authors: Adelmann Benedikt , Hellmann Ralf
Published: September 2021

In this contribution, we compare basic neural networks with convolutional neural networks for cut failure classification during fiber laser cutting. The experiments are performed by cutting thin electrical sheets with a 500 W single-mode fiber laser while taking coaxial camera images for the classification. The quality is grouped in the categories good cut, cuts with burr formation and cut interruptions. Indeed, our results reveal that both cut failures can be detected with one system. Independent of the neural network design and size, a minimum classification accuracy of 92.8% is achieved, which could be increased with more complex networks to 95.8%. Thus, convolutional neural networks reveal a slight performance advantage over basic neural networks, which yet is accompanied by a higher calculation time, which nevertheless is still below 2 ms. In a separated examination, cut interruptions can be detected with much higher accuracy as compared to burr formation. Overall, the results reveal the possibility to detect burr formations and cut interruptions during laser cutting simultaneously with high accuracy, as being desirable for industrial applications.
Optical Filter-Embedded Fiber-Optic Radiation Sensor for Ultra-High Dose Rate Electron Beam Dosimetry
Authors: Jeong Dong-Hyeok , Lee Manwoo , Lim Heuijin , Kang Sang-Koo , Lee Kyohyun , Lee Sang-Jin , Kim Hyun , Han Woo-Kyung , Kang Tae-Woo , Jang Kyoung-Won
Published: September 2021

FLASH radiotherapy is an emerging radiotherapy technique used to spare normal tissues. It employs ultra-high dose rate radiation beams over 40 Gy/s, which is significantly higher than those of conventional radiotherapy. In this study, a fiber-optic radiation sensor (FORS) was fabricated using a plastic scintillator, an optical filter, and a plastic optical fiber to measure the ultra-high dose rate electron beams over 40 Gy/s used in FLASH radiotherapy. The radiation-induced emissions, such as Cherenkov radiation and fluorescence generated in a transmitting optical fiber, were spectrally discriminated from the light outputs of the FORS. To evaluate the linearity and dose rate dependence of the FORS, the outputs of the fiber-optic radiation sensor were measured according to distances from an electron scattering device, and the results were compared with those of an ionization chamber and radiochromic films. Finally, the percentage depth doses were obtained using the FORS as a function of depth in a water phantom. This study found that ultra-high dose rate electron beams over 40 Gy/s could be measured in real time using a FORS.
Artificial Intelligence Technologies for Sign Language
Authors: Papastratis Ilias , Chatzikonstantinou Christos , Konstantinidis Dimitrios , Dimitropoulos Kosmas , Daras Petros
Published: September 2021

AI technologies can play an important role in breaking down the communication barriers of deaf or hearing-impaired people with other communities, contributing significantly to their social inclusion. Recent advances in both sensing technologies and AI algorithms have paved the way for the development of various applications aiming at fulfilling the needs of deaf and hearing-impaired communities. To this end, this survey aims to provide a comprehensive review of state-of-the-art methods in sign language capturing, recognition, translation and representation, pinpointing their advantages and limitations. In addition, the survey presents a number of applications, while it discusses the main challenges in the field of sign language technologies. Future research direction are also proposed in order to assist prospective researchers towards further advancing the field.
Personal Resilience Can Be Well Estimated from Heart Rate Variability and Paralinguistic Features during Human–Robot Conversations
Authors: Hsu Shin-Min , Chen Sue-Huei , Huang Tsung-Ren
Published: September 2021

Mental health is as crucial as physical health, but it is underappreciated by mainstream biomedical research and the public. Compared to the use of AI or robots in physical healthcare, the use of AI or robots in mental healthcare is much more limited in number and scope. To date, psychological resilience—the ability to cope with a crisis and quickly return to the pre-crisis state—has been identified as an important predictor of psychological well-being but has not been commonly considered by AI systems (e.g., smart wearable devices) or social robots to personalize services such as emotion coaching. To address the dearth of investigations, the present study explores the possibility of estimating personal resilience using physiological and speech signals measured during human–robot conversations. Specifically, the physiological and speech signals of 32 research participants were recorded while the participants answered a humanoid social robot’s questions about their positive and negative memories about three periods of their lives. The results from machine learning models showed that heart rate variability and paralinguistic features were the overall best predictors of personal resilience. Such predictability of personal resilience can be leveraged by AI and social robots to improve user understanding and has great potential for various mental healthcare applications in the future.
Efficient 3D Object Recognition from Cluttered Point Cloud
Authors: Li Wei , Cheng Hongtai , Zhang Xiaohua
Published: September 2021

Recognizing 3D objects and estimating their postures in a complex scene is a challenging task. Sample Consensus Initial Alignment (SAC-IA) is a commonly used point cloud-based method to achieve such a goal. However, its efficiency is low, and it cannot be applied in real-time applications. This paper analyzes the most time-consuming part of the SAC-IA algorithm: sample generation and evaluation. We propose two improvements to increase efficiency. In the initial aligning stage, instead of sampling the key points, the correspondence pairs between model and scene key points are generated in advance and chosen in each iteration, which reduces the redundant correspondence search operations; a geometric filter is proposed to prevent the invalid samples to the evaluation process, which is the most time-consuming operation because it requires transforming and calculating the distance between two point clouds. The introduction of the geometric filter can significantly increase the sample quality and reduce the required sample numbers. Experiments are performed on our own datasets captured by Kinect v2 Camera and on Bologna 1 dataset. The results show that the proposed method can significantly increase (10–30×) the efficiency of the original SAC-IA method without sacrificing accuracy.
A Lightweight Pedestrian Detection Engine with Two-Stage Low-Complexity Detection Network and Adaptive Region Focusing Technique
Authors: Que Luying , Zhang Teng , Guo Hongtao , Jia Conghan , Gong Yuchuan , Chang Liang , Zhou Jun
Published: September 2021

Pedestrian detection has been widely used in applications such as video surveillance and intelligent robots. Recently, deep learning-based pedestrian detection engines have attracted lots of attention. However, the computational complexity of these engines is high, which makes them unsuitable for hardware- and power-constrained mobile applications, such as drones for surveillance. In this paper, we propose a lightweight pedestrian detection engine with a two-stage low-complexity detection network and adaptive region focusing technique, to reduce the computational complexity in pedestrian detection, while maintaining sufficient detection accuracy. The proposed pedestrian detection engine has significantly reduced the number of parameters (0.73 M) and operations (1.04 B), while achieving a comparable precision (85.18%) and miss rate (25.16%) to many existing designs. Moreover, the proposed engine, together with YOLOv3 and YOLOv3-Tiny, has been implemented on a Xilinx FPGA Zynq7020 for comparison. It is able to achieve 16.3 Fps while consuming 0.59 W, which outperforms the results of YOLOv3 (5.3 Fps, 2.43 W) and YOLOv3-Tiny (12.8 Fps, 0.95 W).
A Redundant Configuration of Four Low-Cost GNSS-RTK Receivers for Reliable Estimation of Vehicular Position and Posture
Authors: Morales Jesús , Martínez Jorge L. , García-Cerezo Alfonso J.
Published: September 2021

This paper proposes a low-cost sensor system composed of four GNSS-RTK receivers to obtain accurate position and posture estimations for a vehicle in real-time. The four antennas of the receivers are placed so that every three-antennas combination is optimal to get the most precise 3D coordinates with respect to a global reference system. The redundancy provided by the fourth receiver allows to improve estimations even more and to maintain accuracy when one of the receivers fails. A mini computer with the Robotic Operating System is responsible for merging all the available measurements reliably. Successful experiments have been carried out with a ground rover on irregular terrain. Angular estimates similar to those of a high-performance IMU have been achieved in dynamic tests.
Performance and Characteristics of Wearable Sensor Systems Discriminating and Classifying Older Adults According to Fall Risk: A Systematic Review
Authors: Kristoffersson Annica , Du Jiaying , Ehn Maria
Published: September 2021

Sensor-based fall risk assessment (SFRA) utilizes wearable sensors for monitoring individuals’ motions in fall risk assessment tasks. Previous SFRA reviews recommend methodological improvements to better support the use of SFRA in clinical practice. This systematic review aimed to investigate the existing evidence of SFRA (discriminative capability, classification performance) and methodological factors (study design, samples, sensor features, and model validation) contributing to the risk of bias. The review was conducted according to recommended guidelines and 33 of 389 screened records were eligible for inclusion. Evidence of SFRA was identified: several sensor features and three classification models differed significantly between groups with different fall risk (mostly fallers/non-fallers). Moreover, classification performance corresponding the AUCs of at least 0.74 and/or accuracies of at least 84% were obtained from sensor features in six studies and from classification models in seven studies. Specificity was at least as high as sensitivity among studies reporting both values. Insufficient use of prospective design, small sample size, low in-sample inclusion of participants with elevated fall risk, high amounts and low degree of consensus in used features, and limited use of recommended model validation methods were identified in the included studies. Hence, future SFRA research should further reduce risk of bias by continuously improving methodology.
A Coverage Optimization Method for WSNs Based on the Improved Weed Algorithm
Authors: Zhu Fang , Wang Wenhao
Published: September 2021

Wireless sensor networks (WSNs) is a multi-hop wireless network composed of a group of static or mobile sensor nodes in the form of self-organization. Uneven distribution of nodes often leads to the problem of over coverage and incomplete coverage of monitoring areas. To solve this problem, this paper establishes a network coverage optimization model and proposes a coverage optimization method based on an improved hybrid strategy weed algorithm (LRDE_IWO). The improvement of the weed algorithm includes three steps. Firstly, the standard deviation of normal distribution based on the tangent function is used as the seed’s new step size in the seed diffusion stage to balance the ability of the global search and local search of weed algorithm. Secondly, to avoid the problem of premature convergence, a disturbance mechanism combining enhanced Levy flight and the adaptive random walk strategy is proposed in the process of seed breeding. Finally, in competition of invasive weed stage, the differential evolution strategy is introduced to optimize the competition operation process and speed up convergence. The improved weed algorithm is applied to coverage optimization of WSNs. The simulation results show that the coverage rate of LRDE_IWO is increased by about 1% to 6% compared with the original invade weed algorithm (IWO) and the differential evolution invasive weed optimization algorithm (DE_IWO), and the coverage rate of the LRDE_IWO algorithm is increased by 4.10%, 2.73% and 1.19%, respectively, compared with the antlion optimization algorithm (ALO), the fruit fly optimization algorithm (FOA) and the gauss mutation weed algorithm (IIWO). The results prove the superiority and validity of the improved weed algorithm for coverage optimization of wireless sensor networks.
Assessment of Grain Harvest Moisture Content Using Machine Learning on Smartphone Images for Optimal Harvest Timing
Authors: Yang Ming-Der , Hsu Yu-Chun , Tseng Wei-Cheng , Lu Chian-Yu , Yang Chin-Ying , Lai Ming-Hsin , Wu Dong-Hong
Published: September 2021

Grain moisture content (GMC) is a key indicator of the appropriate harvest period of rice. Conventional testing is time-consuming and laborious, thus not to be implemented over vast areas and to enable the estimation of future changes for revealing optimal harvesting. Images of single panicles were shot with smartphones and corrected using a spectral–geometric correction board. In total, 86 panicle samples were obtained each time and then dried at 80 °C for 7 days to acquire the wet-basis GMC. In total, 517 valid samples were obtained, in which 80% was randomly used for training and 20% was used for testing to construct the image-based GMC assessment model. In total, 17 GMC surveys from a total of 201 samples were also performed from an area of 1 m2 representing on-site GMC, which enabled a multi-day GMC prediction. Eight color indices were selected using principal component analysis for building four machine learning models, including random forest, multilayer perceptron, support vector regression (SVR), and multivariate linear regression. The SVR model with a MAE of 1.23% was the most suitable for GMC of less than 40%. This study provides a real-time and cost-effective non-destructive GMC measurement using smartphones that enables on-farm prediction of harvest dates and facilitates the harvesting scheduling of agricultural machinery.
Statistical Extraction Method for Revealing Key Factors from Posture before Initiating Successful Throwing Technique in Judo
Authors: Kato Satoshi , Yamagiwa Shinichi
Published: September 2021

Many methods such as biomechanics and coaching have been proposed to help people learn a certain movement. There have been proposals for methods to discover characteristics of movement based on information obtained from videos and sensors. Especially in sports, it is expected that these methods can provide hints to improve movement skills. However, conventional methods focus on individual movements, and do not consider cases where external factors influence the movement, such as combat sports. In this paper, we propose a novel method called the Extraction for Successful Movement method (XSM method). Applying the method, this paper focuses on throwing techniques in judo to discover key factors that induce successful throwing from the postures right before initiating the throwing techniques. We define candidate factors by observing the video scenes where the throwing techniques are successfully performed. The method demonstrates the significance of the key factors according to the predominance of factors by χ2 test and residual analysis. Applying the XSM method to the dataset obtained from the videos of the Judo World Championships, we demonstrate the validity of the method with discussing the key factors related to the successful throwing techniques.
The Deformation Behavior and Bending Emissions of ZnO Microwire Affected by Deformation-Induced Defects and Thermal Tunneling Effect
Authors: Shi Linlin , Wang Hong , Ma Xiaohui , Wang Yunpeng , Wang Fei , Zhao Dongxu , Shen Dezhen
Published: September 2021

The realization of electrically pumped emitters at micro and nanoscale, especially with flexibility or special shapes is still a goal for prospective fundamental research and application. Herein, zinc oxide (ZnO) microwires were produced to investigate the luminescent properties affected by stress. To exploit the initial stress, room temperature in situ elastic bending stress was applied on the microwires by squeezing between the two approaching electrodes. A novel unrecoverable deformation phenomenon was observed by applying a large enough voltage, resulting in the formation of additional defects at bent regions. The electrical characteristics of the microwire changed with the applied bending deformation due to the introduction of defects by stress. When the injection current exceeded certain values, bright emission was observed at bent regions, ZnO microwires showed illumination at the bent region priority to straight region. The bent emission can be attributed to the effect of thermal tunneling electroluminescence appeared primarily at bent regions. The physical mechanism of the observed thermoluminescence phenomena was analyzed using theoretical simulations. The realization of electrically induced deformation and the related bending emissions in single microwires shows the possibility to fabricate special-shaped light sources and offer a method to develop photoelectronic devices.
Optimum Parameters for Extracting Three Kinds of Carotenoids from Pepper Leaves by Response Surface Methodology
Authors: Li Nenghui , Li Jing , Ding Dongxia , Xie Jianming , Zhang Jing , Li Wangxiong , Ma Yufeng , Gao Feng , Niu Tianhang , Wang Cheng , Bakpa Emily Patience
Published: September 2021

To determine the optimum parameters for extracting three carotenoids including zeaxanthin, lutein epoxide, and violaxanthin from pepper leaves by response surface methodology (RSM), a solvent of acetone and ethyl acetate (1:2) was used to extract carotenoids with four independent factors: ultrasound time (20–60 min); ratio of sample to solvent (1:12–1:4); saponification time (10–50 min); and concentration of saponification solution (KOH–methanol) (10–30%). A second-order polynomial model produced a satisfactory fitting of the experimental data with regard to zeaxanthin (R2 = 75.95%, p < 0.0197), lutein epoxide (R2 = 90.24%, p < 0.0001), and violaxanthin (R2 = 73.84%, p < 0.0809) content. The optimum joint extraction conditions of zeaxanthin, lutein epoxide, and violaxanthin were 40 min, 1:8, 32 min, and 20%, respectively. The optimal predicted contents for zeaxanthin (0.823022 µg/g DW), lutein epoxide (4.03684 µg/g dry; DW—dry weight), and violaxanthin (16.1972 µg/g DW) in extraction had little difference with the actual experimental values obtained under the optimum extraction conditions for each response: zeaxanthin (0.8118 µg/g DW), lutein epoxide (3.9497 µg/g DW), and violaxanthin (16.1590 µg/g DW), which provides a theoretical basis and method for cultivating new varieties at low temperatures and weak light resistance.
Moderating Effect of Demographic Variables by Analyzing the Motivation and Satisfaction of Visitors to the Former Presidential Vacation Villa: Case Study of Cheongnam-Dae, South Korea
Authors: Seong Bo-Hyun , Hong Chang-Yu
Published: September 2021

This study aims to verify whether there is a difference in groups vis-à-vis gender and age in the relationship between the motivation and satisfaction of visiting the former presidential villa, Cheongnam-dae. Using structural equation models, we examined that Relaxation has a positive effect on satisfaction in all groups. However, the relationship between motivation and satisfaction, such as Convenience, Historicity, and Fellowship, reveals gender and age differences, while the relationship among three motivation factors differs by gender and age. Four motivational factors, i.e., Relaxation, Convenience, Historicity, and Satisfaction, significantly affected the youth (n = 171), while the three factors, i.e., Relaxation, Convenience, and Fellowship, significantly affected the elderly (n = 143). Our analysis encourages expanding ecotourism infrastructure to enhance the ecological value of Cheongnam-dae. It is also necessary to replenish related facilities and contents to enhance the effectiveness of ecological experiences and environmental education. Therefore, this work is significant as it contributes to the development of an analytic framework by discussing the difference between motivation and satisfaction.
A Smart Right to the City—Grounding Corporate Storytelling and Questioning Smart Urbanism
Authors: Strüver Anke , Saltiel Rivka , Schlitz Nicolas , Hohmann Bernhard , Höflehner Thomas , Grabher Barbara
Published: September 2021

Against the backdrop of multiple ongoing crises in European cities related to socio-spatial injustice, inequality and exclusion, we argue for a smart right to the city. There is an urgent need for a thorough account of the entrepreneurial mode of technocapitalist smart urbanism. While much of both affirmative and critical research on Smart City developments equate or even reduce smartness to digital infrastructures, we put actual smartness—in the sense of social justice and sustainability—at centre stage. This paper builds on a fundamental structural critique of (1) the entrepreneurial city (Harvey) and (2) the capitalist city (Lefebvre). Drawing upon Lefebvre’s right to the city as a normative framework, we use Smart City developments in the city of Graz as an illustration of our argument. Considering strategies of waste and mobility management, we reflect on how they operate as spatial and technical fixes—fixing the limits of capitalism’s growth. By serving specific corporate interests, these technocapitalist strategies yet fail to address the underlying structural causes of pressing urban problems and increasing inequalities. With Lefebvre’s ongoing relevant argument for the importance of use value of urban infrastructures as well as his claim that appropriation and participation are essential, we discuss common rights to the city: His framework allows us to envision sustainable and just—actually smart—alternatives: alternatives to technocapitalist entrepreneurial urbanisation. In this respect, a smart right to the city is oriented towards the everyday needs of all inhabitants.
A Tool to Assess Architectural Education from the Sustainable Development Perspective and the Students’ Viewpoint
Authors: Martínez-Ventura Jordi , de-Miguel-Arbonés Eduardo , Sentieri-Omarrementería Carla , Galan Juanjo , Calero-Llinares María
Published: September 2021

Architectural education plays a fundamental role in achieving sustainable development by training future professionals who can contribute to sustainability through their practice. Nevertheless, to ensure the introduction of sustainable development in the education of future architects, it is fundamental to understand what is being done and what could be improved. Despite this, a big gap has been detected in the assessment of architectural education in Spain and worldwide. Thus, a close-ended questionnaire for students has been designed based on the outcomes from a literature review, exploratory interviews with specialists, and the qualitative analysis of two schools of architecture. Additionally, it has been revised by experts, through the pilot study of a preliminary version, and with the supplementary analysis of the answers to a final test with students from different schools from Spain. In particular, this questionnaire allows for comprehensively measuring the students’ perception of their sustainability learning outcomes, their learning experience, and the connection between, with the aim of facilitating the adjustment of Spanish architectural education towards the introduction or enhancement of sustainable development by education managers, teachers, policymakers, and professional associations.
Measurement of Indoor Air Pollution in Bhutanese Households during Winter: An Implication of Different Fuel Uses
Authors: Khumsaeng Thipsukon , Kanabkaew Thongchai
Published: September 2021

Measurements of indoor air pollution in Bhutanese households were conducted in winter with regards to the use of different fuels. These measurements were taken in Thimphu, Bhutan, for PM1, PM2.5, PM10, CO, temperature, air pressure and relative humidity in houses and offices with various fuels used for heaters and classified as the hospital, NEC, kerosene, LPG and firewood. The objective of this study was to measure the pollutant concentrations from different fuel uses and to understand their relationship to the different fuel uses and meteorological data using a time series and statistical analysis. The results revealed that the average values for each pollutant for the categories of the hospital, NEC, kerosene, LPG and firewood were as follows: CO (ppm) were 6.50 ± 5.16, 3.65 ± 1.42, 31.04 ± 18.17, 33.93 ± 26.41, 13.92 ± 17.58, respectively; PM2.5 (μg·m−3) were 7.24 ± 4.25, 4.72 ± 0.71, 6.01 ± 3.28, 5.39 ± 2.62, 18.31 ± 11.92, respectively; PM10 (μg·m−3) was 25.44 ± 16.06, 10.61 ± 4.39, 11.68 ± 6.36, 22.13 ± 9.95, 28.66 ± 16.35, respectively. Very coarse particles of PM10 were identified by outdoor infiltration for the hospital, NEC, kerosene and LPG that could be explained by the stable atmospheric conditions enhancing accumulation of ambient air pollutions during the measurements. In addition, high concentrations of CO from kerosene, LPG and firewood were found to be mainly from indoor fuel combustion. Firewood was found to the most polluting fuel for particulate matter concentrations. For the relationships of PM and meteorological data (Temp, RH and air pressure), they were well explained by linear regression while those for CO and the meteorological data, they were well explained by polynomial regression. Since around 40% of houses in Thimphu, Bhutan, use firewood for heating, it is recommended that ventilation should be improved by opening doors and windows in houses with firewood heaters to help prevent exposure to high concentrations of PM1, PM2.5, and PM10.
Sustainable Public Procurement and Human Rights: Barriers to Deliver on Socially Sustainable Road Infrastructure Projects in Mexico
Authors: Treviño-Lozano Laura
Published: September 2021

Public procurement involves a process through which the public sector buys goods, services and works from private suppliers to accomplish its functions, including road infrastructure projects. Sustainability, both within the procurement process and the infrastructure outcome, comprises economic, environmental and social dimensions. Sustainable Public Procurement (SPP) is acknowledged as a core dimension of sustainable development goal 12 (SDG12) on sustainable consumption by States and production by businesses, and as a State-business nexus within Pilar I of the UN Guiding Principles on Business and Human Rights (UNGPs). Clearly, SPP delivering sustainable infrastructure involves broad positive effects and benefits for involved stakeholders and leveraging power over business suppliers to include social sustainable criteria within the procurement process is in the State’s hands. However, SPP has been little implemented in developing States such as Mexico resulting in unsustainable infrastructure outcomes. This article explores, through two case studies, the barriers of socially sustainable public procurement of road infrastructure developed by businesses contracted by the State in Mexico. By identifying such barriers, the Mexican State could be able to implement measures to tackle them and deliver on social sustainable infrastructure aligned with its commitments on sustainable development goals and its international obligations on human rights.
Feedback to Minimize Household Waste a Field Experiment in The Netherlands
Authors: van der Werff Ellen , Lee Chieh-Yu
Published: September 2021

Households can reduce environmental problems by minimizing their waste. Studies suggest that feedback may promote waste minimization. We propose that the effectiveness of feedback depends on the standard to which the feedback is compared. We tested the effect of feedback on waste minimization compared to a personal goal (goal comparison feedback), the behaviour of others (social comparison feedback), or one’s past behaviour (historical comparison feedback). Furthermore, the underlying process explaining the effect of feedback on behaviour is yet unclear. We tested the influence of feedback on environmental self-identity, self-efficacy, and descriptive social norms to minimize waste. We conducted a field study in the Netherlands. Households received feedback during six months on the number of residual waste bags they produce. The results show that all intervention groups reduced their number of waste bags including the control group that only received information on how to reduce waste. Yet, a comparison neighbourhood did not reduce their actual waste during the same time period. We did not find clear differences between the different feedback comparison standards. Furthermore, the feedback did not influence any of the process variables. We found that environmental self-identity was most consistently related to self-reported waste behaviours.
Insights into the Mobility Pattern of Australians during COVID-19
Authors: Munawar Hafiz Suliman , Khan Sara Imran , Qadir Zakria , Kiani Yusra Sajid , Kouzani Abbas Z. , Mahmud M. A. Parvez
Published: September 2021

Coronavirus disease 2019 (COVID-19) is an infectious disease characterised by symptoms that are like the common cold. The current pandemic situation in anticipation of a vaccine has posed serious threats to the health and economic sectors of countries worldwide. To overcome the quick transmission of the virus, the government of Australia has also taken drastic measures to prevent its spread. These policies include an international and interstate travel ban, social distancing rules, lockdown, shutdown of educational institutes and work-from-home policies. Such rules have affected people on both behavioural and psychological levels. This study aims to analyse the effect of COVID-19 on Australian citizens, and therefore, the changed behaviour of citizens concerning their mobility patterns, transport preferences and shopping methods under the pandemic have been studied. A detailed literature search was adopted for gathering data related to the study theme, along with real-time evidence of changes in the behaviour of people following the pandemic. The socioeconomic impact of the pandemic on social inequality and thereby the effect on the vulnerable people of the population are also studied. Authentic surveys and statistical data are consulted to figure out how the new lifestyle choices of people will linger in the post-pandemic era. It was found that people in Australia have adopted the work-from-home regime, and new habits suiting the nationwide restrictions have become routine for many people.
Effectiveness of Green Infrastructure Location Based on a Social Well-Being Index
Authors: Ko Sanghyeon , Lee Dongwoo
Published: September 2021

Urban Green Infrastructure (GI) provides promising opportunities to address today’s pressing issues in cities, mainly resulting from uncurbed urbanization. GI has the potential to make significant contributions to make cities more sustainable by satisfying the growing appetite for higher standards of living as well as helping cities adapt to extreme climate events. To leverage the potentials of GI, this article aims to investigate the effectiveness of GI that can enhance social welfare benefits in the triple-bottom line of urban sustainability. First, publicly available data sets representing social demographic, climate, and built environmental elements are collected and indexed to normalize its different scales by the elements, which is termed as the “Social Well-being Index.” Second, a random forest regressor was applied to identify the impacts of variables on the indexed scores by region. As a result, both the Seoul and Gyeonggi-do models found the most significant relationship with the type of GI to prevent pollutants and disasters, followed by GI types to conserve and improve the environment in Seoul and GI types to serve activity spaces in Gyeonggi-do. Furthermore, variables such as population, number of pollutants, and employment rate in Seoul were found significant and employment rate, population, and air pollution were significant in Gyeonggi-do. Finally, a scenario analysis is conducted to investigate the impacts of the overall index score with additional GI facilitation according to the model’s findings. This article can provide effective strategies for implementing policies about GI by considering regional conditions. The analytical processes in this article can provide useful insights into preparing effective ecological and environmental improvement policies accordingly.
Heritage Engagement and Subjective Well-Being in the European Union
Authors: Ateca-Amestoy Victoria , Villarroya Anna , Wiesand Andreas Joh.
Published: September 2021

In this paper, we explore the relationship between different ways of getting engaged with cultural heritage and life satisfaction. Using data from a representative sample of the population of the 28 members of the European Union in 2017 collected in the Eurobarometer 88.1 (2017), we explore the relationship between use and non-use values and individual subjective well-being measured as life satisfaction. We present the results derived from the estimation of an ordered probit model where life satisfaction is a function of living near to heritage resources to represent non-use values, different ways of heritage participation (tangible, intangible, digital, and volunteering), and the usual explanatory variables that have been found to be predictors of life satisfaction. Our results indicate that the chances of being more satisfied with ones’ life increase with volunteering activities, with visits to heritage institutions, and with digital engagement. These findings contribute to a better understanding of the multifaceted values of heritage.
Biological Indicators of Soil Quality under Different Tillage Systems in Retisol
Authors: Vilkiene Monika , Mockeviciene Ieva , Karcauskiene Danute , Suproniene Skaidre , Doyeni Modupe Olufemi , Ambrazaitiene Dalia
Published: September 2021

Soil microorganism diversity has a close relation with soil function, and the changes in the composition of the soil microbial population can directly affect it. The aim of this study was to identify the bacterial community composition and determine the main soil chemical and physical properties formed by the different tillage systems. In the experiment, we analyzed the combination of three tillage systems and four organic fertilizers. Soil samples were taken from the two layers of the soil profile: the upper 0–10 cm and the lower 10–20 cm. The composition and diversity of soil bacterial communities were assessed by the sequencing of 16S rRNA genes. Results revealed that the highest biodiversity was found in the soil with shallow ploughless tillage and enriched with farmyard manure. Actinobacteria and Proteobacteria were the dominant bacterial species across all treatments. Their total abundance varied between 26% and 36% in the different analyzed agroecosystems. For the Dystric Bathygleyic Glossic Retisol, shallow ploughless tillage is the most suitable tillage system, as it creates favorable conditions for the accumulation of organic carbon in the soil under the Western Lithuania climate conditions.
Synergising Research and Service Activities at Swiss Research Institutions to Accelerate Sustainable Development
Authors: Saric Jasmina , Käser Fabian , Lys Jon-Andri , Utzinger Jürg , Breu Thomas
Published: September 2021

Research that takes a pro-active role in bridging science and practice holds promise to accelerate progress towards the Sustainable Development Goals. While passing on best practices outside of academia, inspiration can be drawn from pressing global challenges. Using Swiss research institutions that maintain partnerships with low- and middle-income countries as a case study, the purpose of this study was to identify synergies between research and services for development (R&S4D). We mapped Swiss research institutions that host both types of activities and identified the strengths, weaknesses, opportunities, and threats (SWOT) linked to their hybrid models. Semi-structured interviews were conducted with representatives from the identified institutions, and data were analysed using the Framework Method. Strengths of combining R&S4D were observed on four levels: (i) individual (i.e., high employability outside academia); (ii) project (i.e., higher quality and practical relevance); (iii) entity (i.e., flexibility regarding funders, resources, and partners); and (iv) sustainable development (i.e., more impactful work). The main weaknesses were named as a decrease in the scientific quality of research projects specifically and inefficiency/lack of feasibility of implementation services. A lack of career paths and positions for individuals who wish to pursue academic research alongside services was identified as a threat. The Universities of Applied Sciences account for the largest share of hybrid positions in Switzerland; increasing their currently limited funding for research and international activities represents an opportunity. Our reserch adds a unique viewpoint to the discussion on the role of academia in supporting society to move towards sustainable development. It does so by exploring whether and how the concept of multisectoriality can work as an integral part of academia at the individual and the institutional level.
Influence of Wind Turbines on Farmlands’ Value: Exploring the Behaviour of a Rural Community through the Decision Tree
Authors: Ottomano Palmisano Giovanni , De Boni Annalisa , Roma Rocco , Acciani Claudio
Published: September 2021

The relationship between wind energy and rural areas leads to the controversial debate on the effects declared by rural communities after wind farms or single turbines are operative. The literature on this topic lacks dedicated studies analysing how the behaviour of rural communities towards wind turbines can affect the market value of farmlands. This research aims to examine to the extent to which the easement of wind turbines can influence the market value of farmlands in terms of willingness to pay (WTP) by a small rural community, and to identify the main factors affecting the WTP. Starting from data collected via face-to-face interviews, a decision tree is then applied to investigate the WTP for seven types of farmland in a rural town of Puglia Region (Southern Italy) hosting a wind farm. Results of the interviews show a broad acceptance of the wind farm, while the decision tree classification shows a significant reduction of WTP for all farmlands. The main factors influencing the WTP are the education level, the possibility to increase the income, the concerns for impacts on human health and for maintenance workmen. National and local policy measures have to be put in place to inform rural communities about the ‘magnitude’ of the effects they identified as crucial, so that policy-makers and private bodies will contribute to make the farmland market more equitable.
Determinants of Selection of R&D Cooperation Partners: Insights from Korea
Authors: Hong Sung Hyo
Published: September 2021

These days, small and medium-sized enterprises (SMEs) face more severe competition in foreign markets due to the globalization of the economy (e.g., FTA). They usually lack technological capabilities and often depend on external R&D activities. Thus, it is worth exploring what factors facilitate SMEs’ R&D collaboration with partners. This paper empirically analyzes the determinants of SMEs’ selections of R&D cooperation partners in Korea. According to the regression results, SMEs with a larger labor force in R&D, larger sales, younger CEOs, more advanced technologies, and less R&D equipment are more likely to cooperate with external R&D partners. When SMEs produce a product that is not easily imitated by others, they are more willing to cooperate with universities or research institutions but not with suppliers or customers. In sum, for Korean SMEs, the arguments of appropriability and resource complementarity appear to work in their R&D activities. However, the former is more important for collaborations with universities or research institutions, and the latter is more influential to those with suppliers and customers. This paper contributes to the literature in two aspects—quantitative studies on the collaborative innovation of SMEs are still limited, and the differences in cooperation determinants across types of partners are explored due to the richness of the dataset.
Development of Road Freight Transport Indicators Focused on Sustainability to Assist Shippers: An Analysis Conducted in France through the FRET 21 Programme
Authors: Touratier-Muller Nathalie , Jaussaud Jacques
Published: September 2021

The transport procurement process is based on criteria selected by shippers when soliciting tenders from carriers. Although sustainable transport indicators are not yet a formal selection criterion in France, some indicators are starting to be gradually considered in freight transport contracts between shippers and carriers. Dispersed information can be gathered regarding Euro 5 and Euro 6 standards compliance for trucks, their fuel consumption, the number of signatory shippers to the CO2 reduction charter, and the search for less-polluting alternative freight solutions. However, these elements are difficult to quantify, and it is often hard to formalise and evaluate their related performance. Therefore, the objective of this article is to draw up, at the request of ADEME (the French Environment and Energy Management Agency), a series of reliable, operational sustainable transport indicators that can be applied to all shippers regardless of their size or industry sector. As part of the FRET 21 charter deployment in France, this article proposes a list of measurable sustainability indicators to support transport buyers when selecting freight carriers.
Assessing Peruvian University Students’ Preferences for Labor Conditions in Mining Site
Authors: Mikami Shuto , Ito Yutaka , Oyola Gonzales Hernan Gabriel
Published: September 2021

The mining industry is one of the biggest industries and has a strong impact in Peru. Despite the mining industry’s importance, it faces labor shortages and environmental risks. For these situations, mining students are important sources of workers not only as labor forces but also as skilled workers who can contribute to solving the environmental issues of mining companies. Thus, the purpose of this paper is to assess Peruvian university mining students’ preferences for labor conditions in mining sites using a discrete choice experiment in order to promote efficient improvements in labor conditions in mining sites that contribute to stable employment and address environmental concerns. The number of respondents was 222 in two Peruvian universities, including males and females aged 16–35 years. The analysis’s findings indicate that labor conditions at mining sites can be optimized by adjusting them to specific individual characteristics of potential mining workers, resulting in a more efficient working environment for companies and workers.
Training, Education, and Research in COVID-19 Times: Innovative Methodological Approaches, Best Practices, and Case Studies
Authors: Lytras Miltiadis , Alsaywid Basim , Housawi Abdulrahman
Published: September 2021

The recent pandemic of COVID-19 challenges the delivery of training and education worldwide [...]
Assessment of the Socioeconomic Vulnerability to Seismic Hazards in the National Capital Region of India Using Factor Analysis
Authors: Agrawal Navdeep , Gupta Laxmi , Dixit Jagabandhu
Published: September 2021

The seismicity of the National Capital Region (NCR) of India increased significantly over the last decade. Communities in the NCR face significant exposure to damaging seismic events, and the seismic risk arises not only from the region’s proximity to the Himalayan mountains, but also from the socioeconomic vulnerabilities in its communities and the current capacities of different localities to respond to and recover from any unforeseen large seismic event. GIS-based spatial distribution of exposure to seismic hazards (SH) can help decision-makers and authorities identify locations with populations at high seismic risk, and to prepare risk-mitigation plans. Socioeconomic vulnerability (SeV) studies serve as a basis for quantifying qualitative measures. For this purpose, in the present study, the hazard of place (HoP) model is used to assess SeV to seismic hazards in the NCR. Social indicators like age, gender, literacy, family size, built environment, etc., comprising a total of 36 variables, are used to assess a socioeconomic vulnerability index (SeVI) based on factor and principal component (PCA) analyses. Based on PCA, 20 variables were retained and grouped into four factors: socioeconomic status, employment status, building typology, and family size. Ground-motion parameters, estimated from probabilistic seismic hazard assessment, are integrated with the socioeconomic vulnerability index to quantify exposure to seismic hazards. The spatial distributions in the produced socioeconomic-vulnerability index and seismic–hazard–exposure maps highlight the critical areas. The results reveal that areas of low literacy, high unemployment, and poor housing condition show moderate-to-high vulnerability. The south-eastern region of the study area is assessed as a high-risk zone by an integrated SeV–SH risk matrix. The results of this study emphasize the importance of the socioeconomic vulnerability component of disaster risk–reduction programs, from a holistic perspective, for the areas with high seismicity.