bluuebunny/crossref_metadata_2025 huggingface dataset:
Accurate Localization in Acoustic Underwater Localization Systems
Authors: Cario Gianni , Casavola Alessandro , Gagliardi Gianfranco , Lupia Marco , Severino Umberto
Published: January 2021

In underwater localization systems several sources of error may impact in different ways the accuracy of the final position estimates. Through simulations and statistical analysis it is possible to identify and characterize such sources of error and their relative importance. This is especially of use when an accurate localization system has to be designed within required accuracy prescriptions. This approach allows one to also investigate how much these sources of error influence the final position estimates achieved by an Extended Kalman Filter (EKF). This paper presents the results of experiments designed in a virtual environment used to simulate real acoustic underwater localization systems. The paper intends to analyze the main parameters that significantly influence the position estimates achieved by a Short Baseline (SBL) system. Specifically, the results of this analysis are presented for a proprietary localization system constituted by a surface platform equipped with four acoustic transducers used for the localization of an underwater target. The simulator here presented has the purpose of simulating the hardware system and modifying some of its design parameters, such as the base-line length and the errors on the GPS and Inertial Measurement Unit (IMU) units, in order to understand which parameters have to modify for improving the accuracy of the entire positioning system. It is shown that statistical analysis techniques can be of help in determining the best values of these parameters that permit to improve the performance of a real hardware system.
Activity Recognition for Ambient Assisted Living with Videos, Inertial Units and Ambient Sensors
Authors: Ranieri Caetano Mazzoni , MacLeod Scott , Dragone Mauro , Vargas Patricia Amancio , Romero  Roseli Aparecida Francelin
Published: January 2021

Worldwide demographic projections point to a progressively older population. This fact has fostered research on Ambient Assisted Living, which includes developments on smart homes and social robots. To endow such environments with truly autonomous behaviours, algorithms must extract semantically meaningful information from whichever sensor data is available. Human activity recognition is one of the most active fields of research within this context. Proposed approaches vary according to the input modality and the environments considered. Different from others, this paper addresses the problem of recognising heterogeneous activities of daily living centred in home environments considering simultaneously data from videos, wearable IMUs and ambient sensors. For this, two contributions are presented. The first is the creation of the Heriot-Watt University/University of Sao Paulo (HWU-USP) activities dataset, which was recorded at the Robotic Assisted Living Testbed at Heriot-Watt University. This dataset differs from other multimodal datasets due to the fact that it consists of daily living activities with either periodical patterns or long-term dependencies, which are captured in a very rich and heterogeneous sensing environment. In particular, this dataset combines data from a humanoid robot’s RGBD (RGB + depth) camera, with inertial sensors from wearable devices, and ambient sensors from a smart home. The second contribution is the proposal of a Deep Learning (DL) framework, which provides multimodal activity recognition based on videos, inertial sensors and ambient sensors from the smart home, on their own or fused to each other. The classification DL framework has also validated on our dataset and on the University of Texas at Dallas Multimodal Human Activities Dataset (UTD-MHAD), a widely used benchmark for activity recognition based on videos and inertial sensors, providing a comparative analysis between the results on the two datasets considered. Results demonstrate that the introduction of data from ambient sensors expressively improved the accuracy results.
Positional Differences in Pre-Season Scrimmage Performance of Division I Collegiate Football Players
Authors: Early Kate S. , Lemoine Nathan P. , Simoneaux Annie , Mullenix Shelly , Marucci Jack , MacLellan Michael J. , Johannsen Neil M.
Published: January 2021

This study aimed to describe the physical demands of American football players using novel performance analysis techniques. Heart rate (HR) and accelerometer-based activity levels were observed across two pre-season scrimmages in 23 Division I collegiate football players (age: 19 ± 1 y, height: 1.90 ± 0.06 m, weight: 116.2 ± 19.4 kg). Data were analyzed using a MATLAB program and inter-rater reproducibility assessed using inter-class correlations (ICC). Players were analyzed by side (offense/defense) and position (skill/non-skill). Performance variables assessed in bursts of activity included burst duration, HRmean and HRmax (bpm), and mean activity (vector magnitude units [vmu]). Exercise intensity was categorized as time spent in % HRmax in 5% increments. The burst duration (8.1±3.9 min, ICC = 0.72), HRmean (157 ± 12 bpm, ICC = 0.96) and mean activity (0.30 ± 0.05 vmu, ICC = 0.86) were reproducible. HRmean (p = 0.05) and HRmax (p = 0.001) were greater on defense. Offense spent more time at 65–70% HRmax (p = 0.01), 70–75% HRmax (p = 0.02) while defense spent more time 90–95% HRmax and ≥95% HRmax (p = 0.03). HRmean (p = 0.70) and HRpeak (p = 0.80) were not different between positions across both sides. Skilled players demonstrated greater mean activity (p = 0.02). The sport-specific analysis described HR and activity level in a reproducible manner. Automated methods of assessing HR may be useful in training and game time performance but ultimately provides support to coaching decision making.
Wearable Sensors for Assessing the Role of Olfactory Training on the Autonomic Response to Olfactory Stimulation
Authors: Tonacci Alessandro , Billeci Lucia , Di Mambro Irene , Marangoni Roberto , Sanmartin Chiara , Venturi Francesca
Published: January 2021

Wearable sensors are nowadays largely employed to assess physiological signals derived from the human body without representing a burden in terms of obtrusiveness. One of the most intriguing fields of application for such systems include the assessment of physiological responses to sensory stimuli. In this specific regard, it is not yet known which are the main psychophysiological drivers of olfactory-related pleasantness, as the current literature has demonstrated the relationship between odor familiarity and odor valence, but has not clarified the consequentiality between the two domains. Here, we enrolled a group of university students to whom olfactory training lasting 3 months was administered. Thanks to the analysis of electrocardiogram (ECG) and galvanic skin response (GSR) signals at the beginning and at the end of the training period, we observed different autonomic responses, with higher parasympathetically-mediated response at the end of the period with respect to the first evaluation. This possibly suggests that an increased familiarity to the proposed stimuli would lead to a higher tendency towards relaxation. Such results could suggest potential applications to other domains, including personalized treatments based on odors and foods in neuropsychiatric and eating disorders.
Land Subsidence and Its Relations with Sinkhole Activity in Karapınar Region, Turkey: A Multi-Sensor InSAR Time Series Study
Authors: Orhan Osman , Oliver-Cabrera Talib , Wdowinski Shimon , Yalvac Sefa , Yakar Murat
Published: January 2021

The Karapinar basin, located in the Central Anatolian part of Turkey, is subjected to land subsidence and sinkhole activity due to extensive groundwater withdrawal that began in the early 2000s. In this study, we use Interferometric Synthetic Aperture Radar (InSAR), Global Navigation Satellite System (GNSS), and groundwater level data to monitor and better understand the relations between groundwater extraction, land subsidence, and sinkhole formation in the Karapinar basin. The main observations used in the study are InSAR-derived subsidence velocity maps calculated from both Sentinel-1 (2014–2018) and COSMO-SkyMed (2016–2017) SAR data. Our analysis reveals broad areas of subsidence with rates exceeding 70 mm/yr. The InSAR-derived subsidence was compared with GNSS data acquired by a continuously operating GNSS station located in the study area, which show a similar rate of subsidence. The temporal characteristic of both InSAR and GNSS time series indicate a long-term subsidence signal superimposed by seasonal variability, which follows the overall groundwater level changes, with over 80% cross-correlation consistency. Our results also indicate that sinkhole activity is limited to slow subsidence areas, reflecting strong cohesion of near-surface rock layers that resist subsidence but yield to collapse in response to aquifer system deformation induced by groundwater extraction.
Spectral Analysis of Torsional Vibrations Measured by Optical Sensors, as a Method for Diagnosing Injector Nozzle Coking in Marine Diesel Engines
Authors: Drewing Sebastian , Witkowski Kazimierz
Published: January 2021

The study aimed to verify whether it is possible to diagnose the coking of a marine diesel engine injector nozzle by performing a spectral analysis of the crankshaft’s torsional vibrations. The measurements were taken using laser heads, clocked at 16 MHz. The reasons for selecting this type of optical sensors are described as well. The tests were carried out under laboratory conditions, using a test stand with a Sulzer 3AL 25/3 engine, operating under a load created by a Domel GD8 500–50/3 electric generator. A unique method is presented in the paper, which enables the measuring and calculation of torsional vibrations of engine crankshafts. The method was developed at the Chair of Marine Power Plants at the Maritime University of Gdynia. It has been proven that the distribution of differences in the values of individual harmonic components depends on the location of a defective injector nozzle in the cylinder.
Remote Patient Monitoring Using Radio Frequency Identification (RFID) Technology and Machine Learning for Early Detection of Suicidal Behaviour in Mental Health Facilities
Authors: Tao Xiaohui , Shaik Thanveer Basha , Higgins Niall , Gururajan Raj , Zhou Xujuan
Published: January 2021

Remote Patient Monitoring (RPM) has gained great popularity with an aim to measure vital signs and gain patient related information in clinics. RPM can be achieved with noninvasive digital technology without hindering a patient’s daily activities and can enhance the efficiency of healthcare delivery in acute clinical settings. In this study, an RPM system was built using radio frequency identification (RFID) technology for early detection of suicidal behaviour in a hospital-based mental health facility. A range of machine learning models such as Linear Regression, Decision Tree, Random Forest, and XGBoost were investigated to help determine the optimum fixed positions of RFID reader–antennas in a simulated hospital ward. Empirical experiments showed that Decision Tree had the best performance compared to Random Forest and XGBoost models. An Ensemble Learning model was also developed, took advantage of these machine learning models based on their individual performance. The research set a path to analyse dynamic moving RFID tags and builds an RPM system to help retrieve patient vital signs such as heart rate, pulse rate, respiration rate and subtle motions to make this research state-of-the-art in terms of managing acute suicidal and self-harm behaviour in a mental health ward.
Treadmill-to-Overground Mapping of Marker Trajectory for Treadmill-Based Continuous Gait Analysis
Authors: Jung Woo Chang , Lee Jung Keun
Published: January 2021

A treadmill was used to perform continuous walking tests in a limited space that can be covered by marker-based optical motion capture systems. Most treadmill-based gait data are analyzed based on gait cycle percentage. However, achieving continuous walking motion trajectories over time without time normalization is often required, even if tests are performed under treadmill walking conditions. This study presents a treadmill-to-overground mapping method of optical marker trajectories for treadmill-based continuous gait analysis, by adopting a simple concept of virtual origin. The position vector from the backward moving virtual origin to a targeted marker within a limited walking volume is the same as the position vector from the fixed origin to the forward moving marker over the ground. With the proposed method, it is possible (i) to observe the change in physical quantity visually during the treadmill walking, and (ii) to obtain overground-mapped gait data for evaluating the accuracy of the inertial-measurement-unit-based trajectory estimation. The accuracy of the proposed method was verified from various treadmill walking tests, which showed that the total travel displacement error rate was 0.32% on average.
Train-Induced Vibration Monitoring of Track Slab under Long-Term Temperature Load Using Fiber-Optic Accelerometers
Authors: Zhang Jianxiang , Huang Wenzhu , Zhang Wentao , Li Fang , Du Yanliang
Published: January 2021

The train-induced vibration response provides a flexible solution for the real-time monitoring deformation of high-speed railway track slab in actual operation. This paper proposes a long-term real-time monitoring method for track slab deformation based on wavelet packet energy (WPE) using fiber optic accelerometers to record train-induced vibration. We found that the vibration response law of track slab deformation could be established by using the WPE of the frequency band covering the first- and second-order frequencies induced by the adjacent carriages. A field test was carried out for more than one year on the Beijing–Shanghai high-speed railway to investigate the train-induced vibration response law of track slab that was continuously deformed under a long-term temperature load. The maximum values of the WPE characteristic index appeared in winter and summer, and they were positively correlated with the temperature difference between the air environment and the track slab under the daily temperature load. These results were demonstrated to be consistent with the track slab deformation law for long-term and daily temperature loads. The novel method based on fiber optic accelerometers and WPE provides a new method for the long-term and real-time monitoring of track slab deformation.
Power-Oriented Monitoring of Clock Signals in FPGA Systems for Critical Application
Authors: Drozd Oleksandr , Nowakowski Grzegorz , Sachenko Anatoliy , Antoniuk Viktor , Kochan Volodymyr , Drozd Myroslav
Published: January 2021

This paper presents a power-oriented monitoring of clock signals that is designed to avoid synchronization failure in computer systems such as FPGAs. The proposed design reduces power consumption and increases the power-oriented checkability in FPGA systems. These advantages are due to improvements in the evaluation and measurement of corresponding energy parameters. Energy parameter orientation has proved to be a good solution for detecting a synchronization failure that blocks logic monitoring circuits. Key advantages lay in the possibility to detect a synchronization failure hidden in safety-related systems by using traditional online testing that is based on logical checkability. Two main types of power-oriented monitoring are considered: detecting a synchronization failure based on the consumption and the dissipation of power, which uses temperature and current consumption sensors, respectively. The experiments are performed on real FPGA systems with the controlled synchronization disconnection and the use of the computer-aided design (CAD) utility to estimate the decreasing values of the energy parameters. The results demonstrate the limited checkability of FPGA systems when using the thermal monitoring of clock signals and success in monitoring by the consumption current.
A Brain-Inspired Decision-Making Linear Neural Network and Its Application in Automatic Drive
Authors: Sun Tianjun , Gao Zhenhai , Gao Fei , Zhang Tianyao , Chen Siyan , Zhao Kehan
Published: January 2021

Brain-like intelligent decision-making is a prevailing trend in today’s world. However, inspired by bionics and computer science, the linear neural network has become one of the main means to realize human-like decision-making and control. This paper proposes a method for classifying drivers’ driving behaviors based on the fuzzy algorithm and establish a brain-inspired decision-making linear neural network. Firstly, different driver experimental data samples were obtained through the driving simulator. Then, an objective fuzzy classification algorithm was designed to distinguish different driving behaviors in terms of experimental data. In addition, a brain-inspired linear neural network was established to realize human-like decision-making and control. Finally, the accuracy of the proposed method was verified by training and testing. This study extracts the driving characteristics of drivers through driving simulator tests, which provides a driving behavior reference for the human-like decision-making of an intelligent vehicle.
Learning-Based End-to-End Path Planning for Lunar Rovers with Safety Constraints
Authors: Yu Xiaoqiang , Wang Ping , Zhang Zexu
Published: January 2021

Path planning is an essential technology for lunar rover to achieve safe and efficient autonomous exploration mission, this paper proposes a learning-based end-to-end path planning algorithm for lunar rovers with safety constraints. Firstly, a training environment integrating real lunar surface terrain data was built using the Gazebo simulation environment and a lunar rover simulator was created in it to simulate the real lunar surface environment and the lunar rover system. Then an end-to-end path planning algorithm based on deep reinforcement learning method is designed, including state space, action space, network structure, reward function considering slip behavior, and training method based on proximal policy optimization. In addition, to improve the generalization ability to different lunar surface topography and different scale environments, a variety of training scenarios were set up to train the network model using the idea of curriculum learning. The simulation results show that the proposed planning algorithm can successfully achieve the end-to-end path planning of the lunar rover, and the path generated by the proposed algorithm has a higher safety guarantee compared with the classical path planning algorithm.
Recognition of Blinks Activity Patterns during Stress Conditions Using CNN and Markovian Analysis
Authors: Korda Alexandra I. , Giannakakis Giorgos , Ventouras Errikos , Asvestas Pantelis A. , Smyrnis Nikolaos , Marias Kostas , Matsopoulos George K.
Published: January 2021

This paper investigates eye behaviour through blinks activity during stress conditions. Although eye blinking is a semi-voluntary action, it is considered to be affected by one’s emotional states such as arousal or stress. The blinking rate provides information towards this direction, however, the analysis on the entire eye aperture timeseries and the corresponding blinking patterns provide enhanced information on eye behaviour during stress conditions. Thus, two experimental protocols were established to induce affective states (neutral, relaxed and stress) systematically through a variety of external and internal stressors. The study populations included 24 and 58 participants respectively performing 12 experimental affective trials. After the preprocessing phase, the eye aperture timeseries and the corresponding features were extracted. The behaviour of inter-blink intervals (IBI) was investigated using the Markovian Analysis to quantify incidence dynamics in sequences of blinks. Moreover, Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) network models were employed to discriminate stressed versus neutral tasks per cognitive process using the sequence of IBI. The classification accuracy reached a percentage of 81.3% which is very promising considering the unimodal analysis and the noninvasiveness modality used.
Does Sociology Need Open Science?
Authors: Breznau Nate
Published: January 2021

Reliability, transparency, and ethical crises pushed many social science disciplines toward dramatic changes, in particular psychology and more recently political science. This paper discusses why sociology should also change. It reviews sociology as a discipline through the lens of current practices, definitions of sociology, positions of sociological associations, and a brief consideration of the arguments of three highly influential yet epistemologically diverse sociologists: Weber, Merton, and Habermas. It is a general overview for students and sociologists to quickly familiarize themselves with the state of sociology or explore the idea of open science and its relevance to their discipline.
The Competences from the Perception and Practice of University Students
Authors: Sáez-López José-Manuel , Domínguez-Garrido María-Concepción , Medina-Domínguez María-del-Castañar , Monroy Fuensanta , González-Fernández Raúl
Published: January 2021

There is a growing importance of competences as an essential curricular element in higher education since they allow for the transfer of knowledge to diverse academic and professional contexts. For the foundation, taxonomy and classification of this study, we obtained ratings from 543 students at two prestigious Spanish universities. The different competences were grouped by management and planning, higher cognitive skills, quality management and innovation, expression and communication and knowledge acquisition. We evaluated the attitudes of university students regarding competences in a pedagogical design; it was expected that students valued the importance of competencies in pedagogical contexts and the skill in these competences. Students highlighted the importance of management and planning, higher cognitive skills, quality management and innovation, expression and communication, knowledge society and teamwork. A correlation analysis between the importance of and skill in the studied competences was also included. Obtained data detail the importance that students give to competences. The participants also detailed the deficiencies in their skill on most competences. The lack of correlation between importance and skill is detailed, as well as the importance of management and planning competences in curricular design in higher education.
The Relationship between Suggestibility, Fabrication, Distortion, and Trauma in Suspected Sexually Abused Children
Authors: Vagni Monia , Maiorano Tiziana , Giostra Valeria
Published: January 2021

Being a victim of abuse in childhood can lead to the development of trauma-related psychopathology, which could affect the testimony of the child victim. Post-traumatic stress disorder (PTSD) is a factor that can increase both the levels of suggestibility and the production of memory errors, such as confabulations, which can be identified in distortions and fabrications. No studies have analyzed the relationship between suggestibility, fabrications, distortions, and PTSD on samples of children and adolescents suspected of being sexually abused. This study aims to verify in a sample of 221 sexually abused children and adolescents the effect of PTSD, measured by Trauma Symptoms Checklist for Children, in increasing the levels of immediate and delayed suggestibility and the production of fabrications and distortions in immediate and delayed memory tasks, obtained by Gudjonsson Suggestibility Scale 2, controlling age and non-verbal intelligence. Our results show that PTSD increases the levels of immediate and delayed suggestibility, but it has no effect on memory recall in immediate recall tasks. Moreover, PTSD leads to a greater number of distorted and fabricated information inserted in delayed memory. Forensic implications of PTSD consequences on memory tasks and suggestibility levels of sexually abused children are discussed.
The Penetration of New Generation Information Technology and Sustainable Development of Regional Economy in China—Moderation Effect of Institutional Environment
Authors: Cheng Long , Zhang Shiyuan , Lou Xuming , Yang Yang , Jia Weifeng
Published: January 2021

Sustainable economic development is an important force to enhance the comprehensive national strength. It mainly depends on the breakthrough and innovation of science and technology. The new generation of information technology (NGIT) is the most active field in scientific and technological innovation. It is of great significance to deeply consider the relationship between the new generation of information technology and the sustainable development of a regional economy. In this study, 29 provinces and cities in China from 2009 to 2018 were selected and use the feasible generalized least squares (FGLS) method to empirically analyze the impact of the new generation of information technology on the sustainable development of regional economy. Simultaneously, it analyzes the differences between NGIT and economy sustainable development of the regional economy under different institutional environments. According to the research results, there is a positive correlation between new-generation information technology and the sustainable development of a regional economy. There is a positive U-shaped relationship between the penetration depth of NGIT and the sustainable development of a regional economy. Simultaneously, the higher the institutional environment’s level, the stronger the positive relationship between the penetration of NGIT and the sustainable development of a regional economy.
Individual-Level Determinants of the Public Acceptance of Policy Measures to Improve Urban Air Quality: The Case of the Barcelona Low Emission Zone
Authors: Oltra Christian , Sala Roser , López-Asensio Sergi , Germán Silvia , Boso Àlex
Published: January 2021

A variety of policy instruments that impose restrictions on traffic are being put in place across European cities to improve urban air quality. These measures include various schemes such as congestion charges, low emission zones (LEZs) and other traffic calming measures. In this paper, we are interested in the public acceptance of LEZs. Recent studies show high levels of public support for LEZs across Europe. However, specific research on public attitudes towards LEZs is limited. We conducted a self-administered survey (online) among residents in Barcelona, Spain. Based on a previous analytical model, bivariate and path analysis modelling was used to examine the association between key independent variables and acceptance. The results showed that most surveyed residents had a positive attitude towards implementing the LEZ, perceiving this policy instrument as a fair and effective measure to reduce air pollution. Perceived process legitimacy, perceived global impacts and affect had a significant direct effect on acceptance. Prior attitudes and personal orientations and, to a lesser extent, personal characteristics, were indirectly associated with levels of acceptance.
A New Approach for Assessing Secure and Vulnerable Areas in Central Urban Neighborhoods Based on Social-Groups’ Analysis
Authors: Shach-Pinsly Dalit , Ganor Tamar
Published: January 2021

Current urban planning of central neighborhoods is focused on mobility transformation towards more sustainable methods of public transportation and walkability that increase social interactions. Central urban neighborhoods in many cities may suffer from deterioration due to lack of personal security that result in diminished walkability. The lack of personal security might exclude residents from those areas and create a troublesome circle of deterioration, and may emphasize spatial inequality. It may also establish different patterns of the neighborhood infrastructure usage for different social groups, such as using specifically more secure streets and public spaces. The main goal of this paper is to define the routes and spaces where people walk and use in their neighborhoods in which they feel safe, and to understand how different social groups walk-through and use the same urban environment. This is analyzed by the security rating index (SRI) model, a GIS-based mapping model, which is used to identify and rate secure urban areas for better walkability. The SRI results are compared to an interview, which was given to different social-group representatives, urban data that was collected using a mobile application, and to vandalism data analysis from the municipality. The security and walkability analysis assessment took place in the Hadar neighborhood in Haifa, Israel.
Non-Financial Disclosure and Intra-Industry Comparability: A Macro, Meso and Micro Analysis
Authors: Cerioni Eva , D’Andrea Alessia , Giuliani Marco , Marasca Stefano
Published: January 2021

The inadequacy of financial reports for meeting the information needs of stakeholders has prompted companies to adopt non-financial communication systems (also called non-financial disclosure—NFD). Comparability of NFD is an issue as it allows making sense of the information. Nevertheless, while some argue that comparability is particularly difficult to pursue in practice on a general level, it can be achieved among companies belonging to the same industry. This study aims to understand whether, at the empirical level, the comparability of NFD is achieved and to what extent (macro, meso or micro). To achieve this aim, a text analysis of the NFD was performed. The object of analysis is represented by the NFD published by the listed companies belonging to the energy and banking industries, and that is part of the Dow Jones sustainability index. The main results are the following. First, there is a de facto comparability in terms of adopted standards, but not in terms of how the standards are applied. Second, the phenomenon of label creativity represents a relevant barrier. Third, although content standardization is lacking, common information dimensions in the reports seem to emerge. This appears to be an invitation to policymakers to transpose virtuous behavior and to implement the desired harmonization of jure.
Coming in from the Cold: A Longitudinal Analysis of SDG Reporting Practices by Spanish Listed Companies Since the Approval of the 2030 Agenda
Authors: Curtó-Pagès Ferran , Ortega-Rivera Enrique , Castellón-Durán Marc , Jané-Llopis Eva
Published: January 2021

Despite the apparent commitment of large Spanish corporations to the SDGs, information about their documented contribution to the 2030 Agenda is still scarce. This article aims to explore this gap by investigating the extent to which Spanish listed companies have been reporting on the SDGs since the approval of the 2030 Agenda. The paper contributes to the country-level analysis of SDG reporting by performing a longitudinal analysis over the 4-year period encompassing 2016 to 2019. It contributes to management science by assessing Corporate Sustainability performance through adherence to the SDGs and testing what the facilitators of SDG reporting have been during the first 4 years since the adoption of the 2030 Agenda. Findings reveal a low commitment of Spanish listed companies to sustainability reporting. Nevertheless, they also uncover how those companies that publish non-financial reports are increasingly reporting on the SDGs. Additionally, there is also a growing tendency among CEOs to mention the SDGs in their letters to stakeholders. Furthermore, a positive link is established between the adoption of GRI reporting standards or being a signatory of the UN Global Compact and SDG reporting. Similarly, those companies that publish Integrated Reports are more likely to consider the SDGs in their disclosures than those that publish Standalone Reports or Annual Reports. Nonetheless, there is a growing tendency to gravitate from producing Integrated Reports to producing Annual Reports. Owing to the breadth of these results and their relevance to academics and practitioners alike, this study can help build future evidence-based accountability literature and policy on the SDGs at the Spanish and European levels.
Online Tools for the Creation of Personal Learning Environments in Engineering Studies for Sustainable Learning
Authors: Rus-Casas Catalina , La Rubia M.Dolores , Eliche-Quesada Dolores , Jiménez-Castillo Gabino , Aguilar-Peña Juan D.
Published: January 2021

This work describes an educational experience in which personal learning environments (PLEs) were created as a tool for the acquisition of subject contents in the science, technology, engineering, and mathematics (STEM) areas. For this, the same methodology was developed for different subjects in order to teach the use of some digital tools, learn about the concepts related to the PLE, and apply the PLE to educational content promoting sustainable learning. Two questionnaires were designed to obtain information about the tools, activities, and subjects. The results of the questionnaires were analyzed using the Kaiser–Meyer–Olkin test and Pearson’s correlation. Then, several factors and the relationships between them were defined. In addition, this paper shows that because the PLE is based on a learning model in which the learner is the protagonist, its use is linked to sustainable learning. Therefore, the use of PLEs allows the development of the competences of “collaborative work” and “information management and organization”, which are both related to sustainable learning. In addition, the use of PLEs promotes understanding of the subjects and academic results in the subjects.
Learning and Teaching Interdisciplinary Skills in Sustainable Urban Development—The Case of Tampere University, Finland
Authors: Taylor Jonathon , Jokela Salla , Laine Markus , Rajaniemi Juho , Jokinen Pekka , Häikiö Liisa , Lönnqvist Antti
Published: January 2021

Developing the economic, environmental, and social sustainability of urban environments is challenging due to the complex and interconnected nature of the context and objectives. In order to be successful in this challenging environment, professionals working in the urban development arena should have a holistic understanding of the different pillars of sustainable development, as well as various competencies and skills. This paper looks at sustainable urban development (SUD) from the perspective of the skills and competencies required and identifies effective pedagogic practices that could help educate future professionals. In particular, we explore interdisciplinary and transdisciplinary learning, reflective thinking, and experiential learning, which are needed for understanding various aspects of a complex phenomenon, collaborating with professionals from different fields and coming up with novel and constructive ways of solving complex problems. We first examine these through reviewing and analyzing relevant literature on education for sustainable development, with a focus on SUD. Then, we explore the application of these approaches in practice by describing and analyzing a newly introduced degree program at Tampere University, Finland.
A Structure Landmark-Based Radio Signal Mapping Approach for Sustainable Indoor Localization
Authors: Liu Tao , Zhang Xing , Zhang Huan , Tahir Nadeem , Fang Zhixiang
Published: January 2021

Low cost and high reproducible is a key issue for sustainable location-based services. Currently, Wi-Fi fingerprinting based indoor positioning technology has been widely used in various applications due to the advantage of existing wireless network infrastructures and high positioning accuracy. However, the collection and construction of signal radio map (a basis for Wi-Fi fingerprinting-based localization) is a labor-intensive and time-cost work, which limit their practical and sustainable use. In this study, an indoor signal mapping approach is proposed, which extracts fingerprints from unknown signal mapping routes to construct the radio map. This approach employs special indoor spatial structures (termed as structure landmarks) to estimate the location of fingerprints extracted from mapping routes. A learning-based classification model is designed to recognize the structure landmarks along a mapping route based on visual and inertial data. A landmark-based map matching algorithm is also developed to attach the recognized landmarks to a map and to recover the location of the mapping route without knowing its initial location. Experiment results showed that the accuracy of landmark recognition model is higher than 90%. The average matching accuracy and location error of signal mapping routes is 96% and 1.2 m, respectively. By using the constructed signal radio map, the indoor localization error of two algorithms can reach an accuracy of 1.6 m.
Assessment of Online Deliberative Quality: New Indicators Using Network Analysis and Time-Series Analysis
Authors: Shin Bokyong , Rask Mikko
Published: January 2021

Online deliberation research has recently developed automated indicators to assess the deliberative quality of much user-generated online data. While most previous studies have developed indicators based on content analysis and network analysis, time-series data and associated methods have been studied less thoroughly. This article contributes to the literature by proposing indicators based on a combination of network analysis and time-series analysis, arguing that it will help monitor how online deliberation evolves. Based on Habermasian deliberative criteria, we develop six throughput indicators and demonstrate their applications in the OmaStadi participatory budgeting project in Helsinki, Finland. The study results show that these indicators consist of intuitive figures and visualizations that will facilitate collective intelligence on ongoing processes and ways to solve problems promptly.
Allocation and Scheduling of Handling Resources in the Railway Container Terminal Based on Crossing Crane Area
Authors: Ren Gang , Wang Xiaohan , Cai Jiaxin , Guo Shujuan
Published: January 2021

The integrated allocation and scheduling of handling resources are crucial problems in the railway container terminal (RCT). We investigate the integrated optimization problem for handling resources of the crane area, dual-gantry crane (GC), and internal trucks (ITs). A creative handling scheme is proposed to reduce the long-distance, full-loaded movement of GCs by making use of the advantages of ITs. Based on this scheme, we propose a flexible crossing crane area to balance the workload of dual-GC. Decomposing the integrated problem into four sub-problems, a multi-objective mixed-integer programming model (MIP) is developed. By analyzing the characteristic of the integrated problem, a three-layer hybrid heuristic algorithm (TLHHA) incorporating heuristic rule (HR), elite co-evolution genetic algorithm (ECEGA), greedy rule (GR), and simulated annealing (SA) is designed for solving the problem. Numerical experiments were conducted to verify the effectiveness of the proposed model and algorithm. The results show that the proposed algorithm has excellent searching ability, and the simultaneous optimization scheme could ensure the requirements for efficiency, effectiveness, and energy-saving, as well as the balance rate of dual-GC.
Determinants of Consumers’ Willingness to Buy Counterfeit Luxury Products: An Empirical Test of Linear and Inverted U-Shaped Relationship
Authors: Wu Qiong , Zhao Shukuan
Published: January 2021

The proliferation of counterfeit luxury goods poses a great threat to the sustainable development of the luxury goods industry; it also disturbs the order of economic development, causes the aggravation of environmental pollution, and is contrary to the principle of global sustainable development. How to effectively weaken consumers’ willingness to buy counterfeit luxury products has become a focal issue. This research explores the impact of value consciousness, social risk perception, and face consciousness on the purchase intention of counterfeit luxury. In addition, this study explores the different mediating roles played by attitude. The results show that value consciousness has a significant positive impact on the counterfeit luxury purchase intention through the full mediation of attitudes. Perceived social risk not only exerts a direct negative impact on the purchase intention of counterfeit luxury products but can also indirectly influence intention through the partial mediation of attitudes. Besides, there is an inverted U-shaped relationship between face consciousness and counterfeit luxury purchase intention, and attitudes play a partially mediating role in this inverted U-shaped path. This research also has certain management implications for the government and luxury products companies to formulate relevant policies and marketing strategies to curb consumers’ willingness to purchase counterfeit luxury products.
Sustainable Design and Prototyping Using Digital Fabrication Tools for Education
Authors: Soomro Sohail Ahmed , Casakin Hernan , Georgiev Georgi V.
Published: January 2021

Prototyping physical artifacts is a fundamental activity for both product development in industrial and engineering design domains and the development of digital fabrication skills. Prototyping is also essential for human-centric problem-solving in design education. Digital fabrication assists in rapid prototype development through computer-aided design and manufacturing tools. Due to the spread of makerspaces like fabrication laboratories (FabLabs) around the world, the use of digital fabrication tools for prototyping in educational institutes is becoming increasingly common. Studies on the social, environmental, and economic sustainability of digital fabrication have been carried out. However, none of them focus on sustainability and prototyping-based digital fabrication tools or design education. To bridge this research gap, a conceptual framework for sustainable prototyping based on a five-stage design thinking model is proposed. The framework, which is based on a comprehensive literature review of social, economic, and environmental sustainability factors of digital fabrication, is applied to evaluate a prototyping process that took place in a FabLab in an education context aimed at enhancing sustainability. Three case studies are used to evaluate the proposed framework. Based on the findings, recommendations are presented for sustainable prototyping using digital fabrication tools.
Main Agro-Morphological and Biochemical Berry Characteristics of Wild-Grown Sea Buckthorn (Hippophae rhamnoides L. ssp. caucasica Rousi) Genotypes in Turkey
Authors: Ilhan Gülçe , Gundogdu Muttalip , Karlović Ksenija , Židovec Vesna , Vokurka Aleš , Ercişli Sezai
Published: January 2021

Sea buckthorn (Hippophae rhamnoides L. ssp. caucasica Rousi) is one of the most important wild edible fruits, grown in Turkey for centuries without any chemical treatments. The plant is extremely resistant to adverse environmental conditions. In this study, the main agro-morphological and biochemical berry traits and, to a lesser extent, other plant morphological traits of 10 sea buckthorn genotypes sampled from the eastern Anatolia (Sivas province) region were assessed. Among the 10 genotypes, five of them presented a shrub growth habit, whereas five of them presented tree growth habit, with leaf area ranging from 2.56 to 4.22 cm2. The majority of genotypes had an oblong berry shape with variable berry skin color ranging from dark orange to orange, light orange, and yellow. The weight of 100 berries varied from 13.85 to 23.87 g, while juice yield and vitamin C content was found to be 44.87–57.15% and 37.45–62.85 mg/100 g fresh berry base, respectively. Soluble solid content (SSC) was in the range of 12.56–14.67%. The genotypes exhibited a great variability in total anthocyanin content (from 9.1 to 38.7 mg/L), with relatively dark-orange sea buckthorn berries containing more anthocyanin than orange, light-orange, and yellow berries. Linoleic acid was the main fatty acid detected in the pulp of sea buckthorn berries, ranging from 24.11% to 36.37%, depending on the genotype. Investigated genotypes proved also to be rich in total phenolic content, showing at the same time great variability in this trait. The results obtained from the relatively limited number of genotypes show promising traits for further valorization of both horticultural and nutritional traits, suggesting potentially even higher variability, if more genotypes are going to be considered in the future.
Energy, Economic, and Environmental Performance of a Single-Family House in Chile Built to Passivhaus Standard
Authors: Bravo-Orlandini Camilo , Gómez-Soberón José M. , Valderrama-Ulloa Claudia , Sanhueza-Durán Francisco
Published: January 2021

The energy consumption of buildings accounts for 22% of total global energy use and 13% of global greenhouse gas emissions. In this context, this study aims to evaluate the energy, economic, and environmental performance of housing in Chile built according to the Passivhaus (PH) standard. The standard was applied to housing in eight representative climate zones with a single-family residence as reference. The analysis incorporated passive strategies, which are considered as pillars of the PH. The energy performance was analyzed using the Passive House Planning Package software (PHPP), version 9.6a. The results showed that when every passive strategy is implemented, the heating energy demand decreases by 93%, while the refrigeration demand is nonexistent. These results were achieved through a 37% increase in the overall initial budget investment, which will be amortized over an 11-year period. In this way, the primary energy consumption is reduced by 32% and, correspondingly, CO2 emissions are reduced by 39%. In modern Chile, it is difficult (but not impossible) to incorporate PH. However, governmental programs and aids could represent an initial step. Therefore, this research will help to identify strategies for incorporating PH in Chile, with the aim of improving the energy performance of housing.
The Climate Just City
Authors: Granberg Mikael , Glover Leigh
Published: January 2021

Cities are increasingly impacted by climate change, driving the need for adaptation and sustainable development. Local and global economic and socio-cultural influence are also driving city redevelopment. This, fundamentally political, development highlights issues of who pays and who gains, who decides and how, and who/what is to be valued. Climate change adaptation has primarily been informed by science, but the adaptation discourse has widened to include the social sciences, subjecting adaptation practices to political analysis and critique. In this article, we critically discuss the just city concept in a climate adaptation context. We develop the just city concept by describing and discussing key theoretical themes in a politically and justice-oriented analysis of climate change adaptation in cities. We illustrate our arguments by looking at recent case studies of climate change adaptation in three very different city contexts: Port Vila, Baltimore City, and Karlstad. We conclude that the social context with its power asymmetries must be given a central position in understanding the distribution of climate risks and vulnerabilities when studying climate change adaptation in cities from a climate justice perspective.