bluuebunny/crossref_metadata_2025 huggingface dataset:
Mountain Landscape Dynamics after Large Wind and Bark Beetle Disasters and Subsequent Logging—Case Studies from the Carpathians
Authors: Falťan Vladimír , Petrovič František , Gábor Marián , Šagát Vladimír , Hruška Matej
Published: September 2021

High winds and the subsequent infestation of subcortical insect are considered to be the most extensive types of large natural disturbances in the Central European forests. In this paper, we focus on the landscape dynamics of two representative mountain areas of Slovakia, which have been affected by aforementioned natural disturbances during last two decades. For example, on 19 November 2004, the bora caused significant damage to more than 126 km2 of spruce forests in the Tatra National Park (TANAP). Several wind-related events also affected sites in the National Park Low Tatras (NAPALT). Monitoring of related land cover changes during years 2000–2019 was based on CORINE Land Cover data and methodology set up on satellite and aerial images interpretation, on detailed land cover interpretation (1:10,000) for the local case studies, as well as on the results of field research and forestry databases. The dynamics of forest recovery are different in the clear-cuts (usually with subsequent tree planting) and in the naturally developing forest. The area in the vicinity of Tatranská Lonmnica encroaching on the Studená dolina National Nature Reserve in TANAP represents a trend of the gradual return of young forest. The area of Čertovica on the border between NAPALT and its buffer zone are characterized by an increase in clear-cut sites with potentially increasing soil erosion risk, due to repeated wind disasters and widening of bark beetle. Proposed detailed, large-scale approach is being barely used, when considering recent studies dealing with the natural disturbances.
A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics
Authors: Huang Ziqi , Shen Yang , Li Jiayi , Fey Marcel , Brecher Christian
Published: September 2021

Digital twin (DT) and artificial intelligence (AI) technologies have grown rapidly in recent years and are considered by both academia and industry to be key enablers for Industry 4.0. As a digital replica of a physical entity, the basis of DT is the infrastructure and data, the core is the algorithm and model, and the application is the software and service. The grounding of DT and AI in industrial sectors is even more dependent on the systematic and in-depth integration of domain-specific expertise. This survey comprehensively reviews over 300 manuscripts on AI-driven DT technologies of Industry 4.0 used over the past five years and summarizes their general developments and the current state of AI-integration in the fields of smart manufacturing and advanced robotics. These cover conventional sophisticated metal machining and industrial automation as well as emerging techniques, such as 3D printing and human–robot interaction/cooperation. Furthermore, advantages of AI-driven DTs in the context of sustainable development are elaborated. Practical challenges and development prospects of AI-driven DTs are discussed with a respective focus on different levels. A route for AI-integration in multiscale/fidelity DTs with multiscale/fidelity data sources in Industry 4.0 is outlined.
Semantics Aware Dynamic SLAM Based on 3D MODT
Authors: Sualeh Muhammad , Kim Gon-Woo
Published: September 2021

The idea of SLAM (Simultaneous Localization and Mapping) being a solved problem revolves around the static world assumption, even though autonomous systems are gaining environmental perception capabilities by exploiting the advances in computer vision and data-driven approaches. The computational demands and time complexities remain the main impediment in the effective fusion of the paradigms. In this paper, a framework to solve the dynamic SLAM problem is proposed. The dynamic regions of the scene are handled by making use of Visual-LiDAR based MODT (Multiple Object Detection and Tracking). Furthermore, minimal computational demands and real-time performance are ensured. The framework is tested on the KITTI Datasets and evaluated against the publicly available evaluation tools for a fair comparison with state-of-the-art SLAM algorithms. The results suggest that the proposed dynamic SLAM framework can perform in real-time with budgeted computational resources. In addition, the fused MODT provides rich semantic information that can be readily integrated into SLAM.
Optical Transmission Properties of Si3N4 Add-Drop Micro-Ring Resonator Induced by a Fabry–Perot Resonance Effect
Authors: Chen Xinyang , Gu Linpeng , Huang Peijian , Gan Xuetao , Wang Ning , Zhu Yong , Zhang Jie
Published: September 2021

To resolve the problem of miscellaneous peaks and improve the accuracy of data processing in micro-ring resonators (MRRs), we propose an optical transmission model based on a Fabry–Perot (F-P) resonance effect in a Si3N4 add-drop MRR-waveguide structure, which is analyzed using a coupled mode theory and stationary interference method. The analysis indicates the experimentally obtained miscellaneous peaks are mainly induced by the multiple reflections between the two end grating couplers, which form a F-P cavity. In addition, an anti-reflection film on the interface of the grating couplers is proposed to reduce the F-P resonance effect. This work could be useful to analyze optical transmission properties of other MRR-based structures.
Detrending Technique for Denoising in CW Radar
Authors: Lee In-Seong , Park Jae-Hyun , Yang Jong-Ryul
Published: September 2021

A detrending technique is proposed for continuous-wave (CW) radar to remove the effects of direct current (DC) offset, including DC drift, which is a very slow noise that appears near DC. DC drift is mainly caused by unwanted vibrations (generated by the radar itself, target objects, or surroundings) or characteristic changes in components in the radar owing to internal heating. It reduces the accuracy of the circle fitting method required for I/Q imbalance calibration and DC offset removal. The proposed technique effectively removes DC drift from the time-domain waveform of the baseband signals obtained for a certain time using polynomial fitting. The accuracy improvement in the circle fitting by the proposed technique using a 5.8 GHz CW radar decreases the error in the displacement measurement and increases the signal-to-noise ratio (SNR) in vital signal detection. The measurement results using a 5.8 GHz radar show that the proposed technique using a fifth-order polynomial fitting decreased the displacement error from 1.34 mm to 0.62 mm on average when the target was at a distance of 1 m. For a subject at a distance of 0.8 m, the measured SNR improved by 7.2 dB for respiration and 6.6 dB for heartbeat.
Transverse Growth of the Maxillo-Mandibular Complex in Untreated Children: A Longitudinal Cone Beam Computed Tomography Study
Authors: Yi Leah , Jeon Hyeran Helen , Li Chenshuang , Boucher Normand , Chung Chun-Hsi
Published: September 2021

The aim of this study is to evaluate the longitudinal transverse growth of the maxillo-mandibular complex in untreated children using the Cone Beam Computed Tomography (CBCT). Two sets of scans on 12 males (mean 8.75 years at T1 and 11.52 years at T2) and 18 females (mean 9.09 years at T1 and 10.80 years at T2) were analyzed using Dolphin 3D imaging. The transverse widths of various maxillary and mandibular skeletal landmarks and the dentoalveolar and dental landmarks at the level of first molars were measured. Overall, there were greater increases in the transverse dimension in the posterior than anterior portions of the maxilla and mandible. The increase in intergonial width of the mandible seems to be primarily due to the lengthening of the mandibular body. The dentoalveolar process at the first molar level increases at an equal rate corono-apically and is independent to the changes in molar inclination. When comparing maxillary dentoalveolar changes with that of the mandible, greater increases were noticed in the maxilla, which might be explained by the presence of sutural growth in the maxilla. Moreover, the first molars maintain their coordination with each other despite the differential increase in the maxillary and mandibular dentoalveolar processes.
PRASH: A Framework for Privacy Risk Analysis of Smart Homes
Authors: Bugeja Joseph , Jacobsson Andreas , Davidsson Paul
Published: September 2021

Smart homes promise to improve the quality of life of residents. However, they collect vasts amounts of personal and sensitive data, making privacy protection critically important. We propose a framework, called PRASH, for modeling and analyzing the privacy risks of smart homes. It is composed of three modules: a system model, a threat model, and a set of privacy metrics, which together are used for calculating the privacy risk exposure of a smart home system. By representing a smart home through a formal specification, PRASH allows for early identification of threats, better planning for risk management scenarios, and mitigation of potential impacts caused by attacks before they compromise the lives of residents. To demonstrate the capabilities of PRASH, an executable version of the smart home system configuration was generated using the proposed formal specification, which was then analyzed to find potential attack paths while also mitigating the impacts of those attacks. Thereby, we add important contributions to the body of knowledge on the mitigations of threat agents violating the privacy of users in their homes. Overall, the use of PRASH will help residents to preserve their right to privacy in the face of the emerging challenges affecting smart homes.
A Novel Transfer Function Based Ring-Down Suppression System for PMUTs
Authors: Wu Zhipeng , Liu Wenjuan , Tong Zhihao , Zhang Songsong , Gu Yuandong , Wu Guoqiang , Tovstopyat Alexander , Sun Chengliang , Lou Liang
Published: September 2021

In this paper, a novel ring-down suppression system based on transfer function is proposed for the first time to suppress the ring-down time and decrease the blind area of PMUTs (Piezoelectric Micromachined Ultrasonic Transducers). This suppression system includes a transfer function and a simple P (proportion) controller, which can reduce the ring-down time without degrading any performances of PMUTs. The transfer function serves as a virtual PMUT device, feeding its output into the P controller; then, the P controller generates a suppression signal to the actual PMUT device. The ring-down time of a 115-kHz PMUT array is demonstrated to be reduced by up to 93% through the suppression system. In addition, the P controller has been experimentally optimized, reducing the blind area of the PMUT array by about 40%. Moreover, a low ring-down PMUTs system design guideline is established, which is practical and straightforward for industrial scenarios. Finally, the system can be easily integrated into ASIC (Application Specific Integrated Circuit).
Polynomial, Neural Network, and Spline Wavelet Models for Continuous Wavelet Transform of Signals
Authors: Stepanov Andrey
Published: September 2021

In this paper a modified wavelet synthesis algorithm for continuous wavelet transform is proposed, allowing one to obtain a guaranteed approximation of the maternal wavelet to the sample of the analyzed signal (overlap match) and, at the same time, a formalized representation of the wavelet. What distinguishes this method from similar ones? During the procedure of wavelets’ synthesis for continuous wavelet transform it is proposed to use splines and artificial neural networks. The paper also suggests a comparative analysis of polynomial, neural network, and wavelet spline models. It also deals with feasibility of using these models in the synthesis of wavelets during such studies like fine structure of signals, as well as in analysis of large parts of signals whose shape is variable. A number of studies have shown that during the wavelets’ synthesis, the use of artificial neural networks (based on radial basis functions) and cubic splines enables the possibility of obtaining guaranteed accuracy in approaching the maternal wavelet to the signal’s sample (with no approximation error). It also allows for its formalized representation, which is especially important during software implementation of the algorithm for calculating the continuous conversions at digital signal processors and microcontrollers. This paper demonstrates the possibility of using synthesized wavelet, obtained based on polynomial, neural network, and spline models, during the performance of an inverse continuous wavelet transform.
Methods of Precise Distance Measurements for Laser Rangefinders with Digital Acquisition of Signals
Authors: Muzal Michał , Zygmunt Marek , Knysak Piotr , Drozd Tadeusz , Jakubaszek Marcin
Published: September 2021

The article presents methods of long range distance measurements using pulsed lasers and the Time of Flight principle. Various algorithms of laser distance measurements with digital acquisition of echo pulses (acquisition of a signal’s full waveform) are presented. The main focus of work is concentrated on the method of distance measurements developed by the authors. With this method, during laboratory trials, a total measurement error of one centimeter was achieved using a 905 nm pulsed laser diode and pulse width of 39 ns. The maximum range of measurements with such high precision is limited only by a signal to noise ratio, duration of measurements and atmospheric conditions. All algorithms were implemented in a laser rangefinder module developed by the authors. Simulations and laboratory experiments were conducted and algorithm’s accuracy and precision were tested for various SNR conditions and changing distances.
Efficient Self-Supervised Metric Information Retrieval: A Bibliography Based Method Applied to COVID Literature
Authors: Moro Gianluca , Valgimigli Lorenzo
Published: September 2021

The literature on coronaviruses counts more than 300,000 publications. Finding relevant papers concerning arbitrary queries is essential to discovery helpful knowledge. Current best information retrieval (IR) use deep learning approaches and need supervised training sets with labeled data, namely to know a priori the queries and their corresponding relevant papers. Creating such labeled datasets is time-expensive and requires prominent experts’ efforts, resources insufficiently available under a pandemic time pressure. We present a new self-supervised solution, called SUBLIMER, that does not require labels to learn to search on corpora of scientific papers for most relevant against arbitrary queries. SUBLIMER is a novel efficient IR engine trained on the unsupervised COVID-19 Open Research Dataset (CORD19), using deep metric learning. The core point of our self-supervised approach is that it uses no labels, but exploits the bibliography citations from papers to create a latent space where their spatial proximity is a metric of semantic similarity; for this reason, it can also be applied to other domains of papers corpora. SUBLIMER, despite is self-supervised, outperforms the Precision@5 (P@5) and Bpref of the state-of-the-art competitors on CORD19, which, differently from our approach, require both labeled datasets and a number of trainable parameters that is an order of magnitude higher than our.
A Framework for Managing Device Association and Offloading the Transport Layer’s Security Overhead of WiFi Device to Access Points
Authors: Nofal Ramzi A. , Tran Nam , Dezfouli Behnam , Liu Yuhong
Published: September 2021

Considering the resource constraints of Internet of Things (IoT) stations, establishing secure communication between stations and remote servers imposes a significant overhead on these stations in terms of energy cost and processing load. This overhead, in particular, is considerable in networks providing high communication rates and frequent data exchange, such as those relying on the IEEE 802.11 (WiFi) standard. This paper proposes a framework for offloading the processing overhead of secure communication protocols to WiFi access points (APs) in deployments where multiple APs exist. Within this framework, the main problem is finding the AP with sufficient computation and communication capacities to ensure secure and efficient transmissions for the stations associated with that AP. Based on the data-driven profiles obtained from empirical measurements, the proposed framework offloads most heavy security computations from the stations to the APs. We model the association problem as an optimization process with a multi-objective function. The goal is to achieve maximum network throughput via the minimum number of APs while satisfying the security requirements and the APs’ computation and communication capacities. The optimization problem is solved using genetic algorithms (GAs) with constraints extracted from a physical testbed. Experimental results demonstrate the practicality and feasibility of our comprehensive framework in terms of task and energy efficiency as well as security.
Improving Human–Robot Interaction by Enhancing NAO Robot Awareness of Human Facial Expression
Authors: Filippini Chiara , Perpetuini David , Cardone Daniela , Merla Arcangelo
Published: September 2021

An intriguing challenge in the human–robot interaction field is the prospect of endowing robots with emotional intelligence to make the interaction more genuine, intuitive, and natural. A crucial aspect in achieving this goal is the robot’s capability to infer and interpret human emotions. Thanks to its design and open programming platform, the NAO humanoid robot is one of the most widely used agents for human interaction. As with person-to-person communication, facial expressions are the privileged channel for recognizing the interlocutor’s emotional expressions. Although NAO is equipped with a facial expression recognition module, specific use cases may require additional features and affective computing capabilities that are not currently available. This study proposes a highly accurate convolutional-neural-network-based facial expression recognition model that is able to further enhance the NAO robot’ awareness of human facial expressions and provide the robot with an interlocutor’s arousal level detection capability. Indeed, the model tested during human–robot interactions was 91% and 90% accurate in recognizing happy and sad facial expressions, respectively; 75% accurate in recognizing surprised and scared expressions; and less accurate in recognizing neutral and angry expressions. Finally, the model was successfully integrated into the NAO SDK, thus allowing for high-performing facial expression classification with an inference time of 0.34 ± 0.04 s.
Comprehensive mPoint: A Method for 3D Point Cloud Generation of Human Bodies Utilizing FMCW MIMO mm-Wave Radar
Authors: Zhang Guangcheng , Geng Xiaoyi , Lin Yueh-Jaw
Published: September 2021

In this paper, comprehensive mPoint, a method for generating 3D (range, azimuth, and elevation) point cloud of human targets using a Frequency-Modulated Continuous Wave (FMCW) signal and Multi-Input Multi-Output (MIMO) millimeter wave radar is proposed. Distinct from the TI-mPoint method proposed by TI technology, a comprehensive mPoint method considering both the static and dynamic characteristics of radar reflected signals is utilized to generate a high precision point cloud, resulting in more comprehensive information of the target being detected. The radar possessing 60–64 GHz FMCW signal with two sets of different dimensional antennas is utilized in order to experimentally verify the results of the methodology. By using the proposed process, the point cloud data of human targets can be obtained based on six different postures of the underlying human body. The human posture cube and point cloud accuracy rates are defined in the paper in order to quantitively and qualitatively evaluate the quality of the generated point cloud. Benefitting from the proposed comprehensive mPoint, evidence shows that the point number and the accuracy rate of the generated point cloud compared with those from the popular TI-mPoint can be largely increased by 86% and 42%, respectively. In addition, the noise level of multipath reflection can be effectively reduced. Moreover, the length of the algorithm running time is only 1.6% longer than that of the previous method as a slight tradeoff.
A Validated RP-HPLC Method for the Determination of Butamirate Citrate and Benzoic Acid in Syrup, Based on an Experimental Design Assessment of Robustness
Authors: Neofotistos Antonios-Dionysios , Gkountanas Kostas , Boutsikaris Haris , Dotsikas Yannis
Published: September 2021

A reversed-phase high-pressure liquid chromatography (RP-HPLC) method was developed and subsequently validated for the simultaneous determination of butamirate citrate (BC) and benzoic acid (BA) in cough syrup. The separation was performed employing a cyanopropyl column with a mobile phase consisting of 50%/50% v/v MeOH/NaH2PO4 * H2O 50 mM aqueous solution pH = 3.0. The quantitation was achieved with a diode array detector (DAD) at 210 nm. The method demonstrated a congenitally satisfactory separation, yet the acquired peaks were asymmetrical. This effect was eliminated by using 1% triethylamine in the buffer solution as a silanol blocker. In addition, the method was found to unequivocally assess the target analytes in the sample matrix and fulfilled the required specifications in relevance to specificity, linearity, accuracy, precision and stability of both the standard solutions and of the sample solutions. Lastly, an experimental design was designed in order to assess the robustness of the proposed assay. To this purpose, a graphical and a statistical approach were utilized and compared to identify the factors that should be strictly controlled during each execution of the method.
Olfactory Disorders in Post-Acute COVID-19 Syndrome
Authors: Araújo Laura , Arata Vanessa , Figueiredo Ricardo G.
Published: September 2021

Altered smell is one of the most prevalent symptoms in acute COVID-19 infection. Although most patients recover normal neurosensory function in a few weeks, approximately one-tenth of patients report long-term smell dysfunction, including anosmia, hyposmia, parosmia and phantosmia, with a particularly notable impact on quality of life. In this complex scenario, inflammation and cellular damage may play a key role in the pathogenesis of olfactory dysfunctions and may affect olfactory signaling from the peripheral to the central nervous system. Appropriate management of smell disturbances in COVID-19 patients must focus on the underlying mechanisms and the assessment of neurosensorial pathways. This article aims to review the aspects of olfactory impairment, including its pathophysiology, epidemiology, and clinical management in post-acute COVID-19 syndrome (PACS).
Bus Load Forecasting Method of Power System Based on VMD and Bi-LSTM
Authors: Tang Jiajie , Zhao Jie , Zou Hongliang , Ma Gaoyuan , Wu Jun , Jiang Xu , Zhang Huaixun
Published: September 2021

The effective prediction of bus load can provide an important basis for power system dispatching and planning and energy consumption to promote environmental sustainable development. A bus load forecasting method based on variational modal decomposition (VMD) and bidirectional long short-term memory (Bi-LSTM) network was proposed in this article. Firstly, the bus load series was decomposed into a group of relatively stable subsequence components by VMD to reduce the interaction between different trend information. Then, a time series prediction model based on Bi-LSTM was constructed for each sub sequence, and Bayesian theory was used to optimize the sub sequence-related hyperparameters and judge whether the sequence uses Bi-LSTM to improve the prediction accuracy of a single model. Finally, the bus load prediction value was obtained by superimposing the prediction results of each subsequence. The example results show that compared with the traditional prediction algorithm, the proposed method can better track the change trend of bus load, and has higher prediction accuracy and stability.
The Language of Risk and Vulnerability in Covering the COVID-19 Pandemic in Swedish Mass Media in 2020: Implications for the Sustainable Management of Elderly Care
Authors: Giritli Nygren Katarina , Klinga Maja , Olofsson Anna , Öhman Susanna
Published: September 2021

The consequences of the COVID-19 pandemic—in terms of climate, economy and social aspects—cannot yet be fully assessed, but we can already see how the pandemic is intensifying already existing socio-economic inequalities. This applies to different population groups, particularly the elderly. In this article, our goal is to identify the linguistic constructions of elderly citizens in Swedish mass media coverage of the COVID-19 pandemic in 2020 from a sociological and corpus linguistics perspective. More specifically, our aim is to explore the discursive formations of the elderly in Swedish media during the pandemic and how these formations relate to risk as well as the discursive constructions of in- and out-groups. Drawing on corpus-assisted discourse studies (CADS), inspired by discourse–historical analysis (DHA), we examine the media coverage of COVID-19 by three Swedish newspapers published during 2020: Aftonbladet, a national tabloid; Svenska Dagbladet, a national morning newspaper; and Dalademokraten, a regional morning newspaper. In this article, the news articles and their messages are considered performative to the extent that—for example, at the same time as a story is expressed—the elderly are at risk of becoming seriously ill due to COVID-19; moreover, a position of vulnerability for the elderly is simultaneously created. The result reveals that the elderly were constructed as an at-risk group, while visitors, personnel and nursing homes were constructed as being risky or a threat to the elderly.
Corporate Social Responsibility and Employee Green Behavior in the Hospitality Industry: A Cross-Country Study
Authors: Rahman Khattak Sajid Rahman , Nouman Muhammad , Fayaz Muhammad , Cismaș Laura Mariana , Negruț Lucia , Negruț Constantin Viorel , Salem Sultan
Published: September 2021

This study empirically investigates the role of employees’ perceptions of CSR in improving their green behavior in the hospitality industry. In addition, this study investigates the mediating role of employee well-being and the moderating role of hotels’ environmental strategy in this relationship. Empirical analysis is performed in a cross-country setting using evidence from Pakistan and Italy. The study model is tested through PLS-SEM using survey data of 485 hotel employees. Findings from the overall sample and country-specific samples reveal that CSR is positively and significantly related to employee green behavior. Moreover, employee well-being serves as a significant mediator in the relationship between corporate social responsibility and employee green behavior, while hotels’ environmental strategy significantly moderates this relationship in the overall and country-specific samples. These results suggest that paradoxically, though the selected countries have different tourism implementation levels, economic development, and cultures, the employees’ perceptions of CSR and its effect on their green behavior do not vary significantly across both countries.
Business Survival of Small and Medium-Sized Restaurants through a Crisis: The Role of Government Support and Innovation
Authors: Najib Mukhamad , Abdul Rahman Abdul Aziz , Fahma Farah
Published: September 2021

This study aimed to investigate the effects of government support for the business survival of SME restaurants in Indonesia. In this study, we analyzed the impact of government support on the innovation of SME restaurants as well as the impact of entrepreneurial self-efficacy on innovation. Furthermore, this study analyzed the impact of entrepreneurial self-efficacy and innovation on business survival. A total of 120 owners or managers of SME restaurants participated in this study. The sample was collected based on a purposive method. To analyze the relationship among latent variables, we implemented structural equation modeling (SEM). The results show that government support has a positive impact on business survival through marketing and process innovation. In addition, the business survival of SMEs is affected by marketing innovation, process innovation, and entrepreneurial self-efficacy. In this study, the entrepreneurial factor had the highest impact on SMEs’ survival. This study established the body of knowledge related to the positive effect of government support on innovation in the perspective of small and medium-sized restaurants in the emerging market countries and developed a model of business survival of SMEs during pandemic crises by integrating external factors (government support) and an internal factor (entrepreneurial self-efficacy) through marketing and process innovation in the food processing industry.
Research on Innovative Training on Smart Greenhouse Technologies for Economic and Environmental Sustainability
Authors: Kavga Angeliki , Thomopoulos Vasileios , Barouchas Pantelis , Stefanakis Nikolaos , Liopa-Tsakalidi Aglaia
Published: September 2021

Great advancements in technologies such as big data analytics, robots, remote sensing, the Internet of Things, decision support systems and artificial intelligence have transformed the agricultural sector. In the greenhouse sector, these technologies help farmers increase their profits and crop yields while minimizing the production costs, produce in a more environmentally friendly way and mitigate the risks caused by climate change. In greenhouse farming, especially in the Mediterranean region, a lack of knowledge and qualified personnel able to uptake new knowledge, the small size of farms, etc., make it difficult to implement new technologies. Although it is necessary to demonstrate the advantages of innovations related to sustainable agriculture, there is a little opportunity for specific training on greenhouse production in cutting-edge technologies. To gain insight into this problem, questionnaires for greenhouse farmers and intermediaries were developed in multiple choice format and filled in by the stakeholders. A statistical analysis was performed, and the results are presented in graphical form. In most cases, the findings confirmed that producers who run small farms, in most cases, have a lack of knowledge, especially on how to manage climate control systems or fertigation systems. The majority of farmers were elderly with a low level of education, which makes it difficult to be aware of the training issues, due to distrust and a lack of innovation culture. Therefore, their strategy was usually survival with cost control. However, young graduates have been recently returning to agriculture, and they are open to training activities and innovation. The most desirable training offer should be related to sustainable agriculture and precision agriculture technologies.
The Good, the Bad and the Future: A SWOT Analysis of the Ecosystem Approach to Governance in the Baltic Sea Region
Authors: Jetoo Savitri , Lahtinen Varvara
Published: September 2021

The ecosystem approach has been used extensively as a guiding principle in water policies of the Baltic Sea Region since the 1970s. In addition to its operationalization as a management framework in this region, it also has expansive theoretical underpinnings. However, despite extensive literature on this approach, there has not yet been any systematic assessment of the internal and external factors that influence its implementation. This kind of assessment could form the basis for improved thinking around the concept and better implementation actions. As such, this article presents a Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis of the ecosystem approach in the Baltic Sea Region by using content analysis on Baltic Sea documents. This study found that key strengths of the principle are its interdisciplinary focus and its acceptance as a framework for conservation, whilst resource intensiveness and its operational complexity are key weaknesses. The SWOT analysis revealed that a key opportunity in the external environment is the ease of alignment with other policies whilst the key external threat is the difficulty integrating disciplines. This study showed that with a streamlined allocation of resources, more stakeholder engagement through capacity building and political leadership, the ecosystem approach could facilitate interdisciplinary knowledge pooling to achieve a good ecological status of the Baltic Sea.
The Effects of Rock Index Tests on Prediction of Tensile Strength of Granitic Samples: A Neuro-Fuzzy Intelligent System
Authors: Li Yan , Hishamuddin Fathin Nur Syakirah , Mohammed Ahmed Salih , Armaghani Danial Jahed , Ulrikh Dmitrii Vladimirovich , Dehghanbanadaki Ali , Azizi Aydin
Published: September 2021

Rock tensile strength (TS) is an essential parameter for designing structures in rock-based projects such as tunnels, dams, and foundations. During the preliminary phase of geotechnical projects, rock TS can be determined through laboratory works, i.e., Brazilian tensile strength (BTS) test. However, this approach is often restricted by laborious and costly procedures. Hence, this study attempts to estimate the BTS values of rock by employing three non-destructive rock index tests. BTS predictive models were developed using 127 granitic rock samples. Since the simple regression analysis did not yield a meaningful result, the development of models that integrate multiple input parameters were considered to improve the prediction accuracy. The effects of non-destructive rock index tests were examined through the use of multiple linear regression (MLR) and adaptive neuro-fuzzy inference system (ANFIS) approaches. Different strategies and scenarios were implemented during modelling of MLR and ANFIS approaches, where the focus was to consider the most important parameters of these techniques. As a result, and according to background and behaviour of the ANFIS (or neuro-fuzzy) model, the predicted values obtained by this intelligent methodology are closer to the actual BTS compared to MLR which works based on linear statistical rules. For instance, in terms of system error and a-20 index, values of (0.84 and 1.20) and (0.96 and 0.80) were obtained for evaluation parts of ANFIS and MLR techniques, which revealed that the ANFIS model outperforms the MLR in forecasting BTS values. In addition, the same results were obtained through ranking systems by the authors. The neuro-fuzzy developed in this study is a strong technique in terms of prediction capacity and it can be used in the other rock-based projects for solving relevant problems.
Research on the Impact of Urban Rail Transit on the Financing Constraints of Enterprises from the Perspective of Sustainability
Authors: Yang Rong , Tjia Linda Yin-nor , Finger Matthias
Published: September 2021

Urban rail transit (URT) is closely related to the sustainable development of the city. In addition to the traffic improvements, it also brings social and economic benefits. From the perspective of sustainability, we discuss the effect of urban rail transit on financing constraints of companies listed on the China A-share stock market (A-share, common stocks issued by companies registered in China for domestic institutions, organizations or individuals to subscribe and trade in RMB) and further explore whether the level of financial development has an effect on the above relationship. The results show that: (1) Financing constraints are common among sample enterprises, and the later the opening year of urban rail transit, the greater the degree of financing constraints; (2) The development of urban rail transit is beneficial to alleviate the level of financing constraints of listed companies, and this mitigating effect mainly exists in the samples with high relevance to urban rail transit; (3) The higher the level of financial development, the smaller the degree of corporate financing constraints; (4) Financial development may influence the relationship between financing constraints and urban rail transit. With the improvement of the financial development level, the alleviating effect of urban rail transit on corporate financing constraints is less pronounced. This study gives some references to improve the financing constraints of listed companies and for promoting the sustainable development of urban rail transit.
Employment or Development in a Semi-Peripheral Region: The Roadrunner Paradigm
Authors: Gómez-Moreno María-Luisa
Published: September 2021

This study observes the relationship between employment policies and the evolution of the productive system, applying the theoretical framework of local development to an average-sized town in a semi-peripheral area of the European Union, during the period from 1975 to 2015. To do so, a case analysis was made of the outcomes of employment policies via their effects on the variables impacting on the productive fabric. The following data sources were used: grey literature related to public policies; published statistics on demographic variables and economic activity; and local press reports. The following results were obtained: (a) the responses of economic agents owe more to the changes in the international scenario than to employment policies; (b) it is essential to analyse the evolution of demographic factors to properly interpret the relationship between labour supply and demand. We conclude that (a) corporate culture significantly influences the success or otherwise of employment policies, and (b) in the semi-peripheral area discussed, unemployment is an endemic problem that successive cohesion and employment policies have failed to resolve. Therefore, the use of innovation-oriented theoretical and practical approaches should be reconsidered.
Pretreatment of Automotive Shredder Residues, Their Chemical Characterisation, and Pyrolysis Kinetics
Authors: Vijayan Sandhya Kuruvalan , Kibria Mahmud Arman , Uddin Md Hemayet , Bhattacharya Sankar
Published: September 2021

Automotive Shredder Residue (ASR), a waste when metals are mostly removed from end-of-life vehicles, has constituents similar to municipal solid waste (MSW) consisting of plastics, rubber, textiles, and some metals. The processing of ASR is a challenge due to its heterogeneous nature, making feeding to a reactor difficult. In this work, a new procedure of ASR pretreatment is proposed to bring particulate nature in the sample for easier feeding during pyrolysis. The thermal breakdown characteristics of the pretreated ASR solids under slow pyrolysis conditions were assessed in a thermogravimetric analyser following the International Confederation for Thermal Analysis and Calorimetry (ICTAC) kinetics committee recommendations. The effect of particle sizes and heating rates were studied at temperatures up to 800 °C at different heating rates of 2, 5, and 10 °C/min for three particle sizes, 38–63 µm, 63–90 µm, and 90–106 µm, and the kinetic data were derived. The volatiles emitted during pyrolysis were characterized by Diffuse Reflectance Infrared Spectroscopy (DRIFTS). We also developed an algorithm for the selection of heating rate during the pyrolysis of the pretreated ASR. The DRIFTS results, kinetic data, and heating rate for the selected particle sizes are useful for the development of a pyrolysis process for pretreated ASR.
The Impact of Nautical Activities on the Environment—A Systematic Review of Research
Authors: Ukić Boljat Helena , Grubišić Neven , Slišković Merica
Published: September 2021

As nautical tourism and recreational activities involving boats have become highly popular, research interest on various effects of nautical tourism is also increasing. This paper aims to analyze the main scientific contributions in the field of nautical tourism and its impact on the environment. The focus of the analysis is on the methods used to estimate and model recreational boating activities. Since nautical tourism plays a crucial role in the context of the growth and development of the economy, it is necessary to consider the environmental component of its development. The background objective of the paper is to provide a representation of environmental descriptors, i.e., to highlight in particular the environmental impact of nautical tourism. A search on the Web of Science Core Collection, touching on this topic, is composed of scientific papers published in the period 2010–2021. The papers examined are divided into five categories according to the impact of nautical tourism they study: Environmental, Economic, Social, Technical or Other. The results show that most papers were published in the area of environmental impacts of nautical tourism, with most papers examining invasive species, antifouling and impacts on species. The analysis showed that the negative impacts were mainly studied individually. Based on the analysis and evaluation of the scientific publications, a basic recommendation is given for the construction of a model to estimate recreational boating activities and its impact on the environment.
Local Energy Communities in Spain: Economic Implications of the New Tariff and Variable Coefficients
Authors: Manso-Burgos Álvaro , Ribó-Pérez David , Alcázar-Ortega Manuel , Gómez-Navarro Tomás
Published: September 2021

The European Union advocates for legislative support to local energy communities. Measures include the promotion of dynamic energy allocation and discriminatory electricity tariffs such as the recent Spanish framework. However, the impact of these normative changes is not yet evaluated. This paper inquires into the impact of dynamic allocation coefficient and different electricity tariffs on the profitability of local energy communities. To do so, a linear optimisation model is developed and applied to real consumer data in Spain around a variable capacity photovoltaic generation plant. Comparing the economic performance of the static or variable power allocation under the effect of changing electricity tariffs. While both measures are beneficial, the new electricity tariffs result in larger profitability increases than the planned variable coefficients. The combination of measures allows for profitability improvements of up to 25% being complementary measures. However, installations that maximise the potential for electricity generation are still not as profitable due to the low purchase price of surplus energy. While discriminatory electricity price tariffs and variable allocation coefficients are positive measures, further measures are needed for these communities to install generation plants as large as the potential that each case allows.
Legal Disputes under Time Charter in Connection with the Stranding of the MV Ever Given
Authors: Cha Jaeung , Lee Jinwoo , Lee Changhee , Kim Yulseong
Published: September 2021

The MV Ever Given’s stranding in the Suez Canal in March 2021 prompted renewed awareness of the heightened risk of marine accidents in narrow channels as global shipping companies continuously expand vessel sizes. However, there has been limited consideration of ways to improve accident response, and little analysis of future-oriented liabilities and damage compensation schemes for similar maritime accidents. First, key issues related to the Suez Canal stranding accident were analyzed based on web crawling using the R studio program (Version: R-4.0.5) to extract text data from unstructured format text (HTML tags). We designed the research questions to address the key issues/disputes, such as definitions of legal terms related to the Ever Given’s stranding accident and the declaration of a general average (G/A), liability for maintaining seaworthiness, source of command authority over the captain, and liability for compensation for delay in delivery. Then, the liability of stakeholders was legally interpreted through causal inductive reasoning based on relevant legal theories and precedents. To help secure safe and sustainable shipping routes, this study demystifies the problems resulting from the side effects of the trend of ultra-large vessels based on technology bias, and will contribute to responses to similar accidents in the future.
Ecology Projects and Participatory Budgeting: Enhancing Citizens’ Support
Authors: Gherghina Sergiu , Tap Paul
Published: September 2021

In contemporary times, a large number of ecology projects are put on the public agenda through participatory budgeting. There is variation in the support they receive from citizens, but until now we have not known what drives this support. This article aims to identify the factors that could determine the support for ecology projects in participatory budgeting. It includes all 36 projects on ecology, which passed the technical eligibility check, submitted to the participatory budgeting in Cluj-Napoca (Romania) between 2017 and 2019. We use quantitative analysis to test the extent to which five project characteristics have an effect on the public support for the ecology projects: the requested budget, the type of project, the number of arguments, the use of jargon, and images and videos in addition to text descriptions. The results show that citizens take the environmental matters seriously and do not vote for schematic projects that are limited in scope and which have limited contribution to the general welfare.
Understanding the Regional Engagement of Universities from a Stakeholders’ Perspective: The Case of the University of Thessaly, Greece
Authors: Adamakou Maria , Niavis Spyros , Kallioras Dimitris , Petrakos George
Published: September 2021

International literature pays vast attention to the role and the regional engagement of universities as a facilitator of sustainable regional development. Most papers use top-down approaches by looking at how well conceptual models of a university’s role fit any case study considered or by measuring predefined dimensions of university engagement. The present paper prioritizes the stakeholder views and provides a framework for revealing the critical dimensions of the university’s regional engagement from a bottom-up perspective. The region of Thessaly is selected as a case study, and the university’s engagement is conceptualized by a four-dimensional framework that considers the university’s contributions, student roles, beneficiaries, and barriers. Then, through a survey, relevant items are provided to stakeholders to formulate any potential engagement factors. The factors are extracted using the principal component analysis, and then the consensus of different stakeholders on their response patterns is then also evaluated with relevant statistical tests. In practical terms, the analysis shows that a capable number of factors could be formulated under each dimension of the framework and that there are not many significant differences in stakeholder perceptions, regardless of their institutional role. In theoretical terms, the identified factors may act as a baseline for any future relevant evaluation.