bluuebunny/crossref_metadata_2025 huggingface dataset:
The Endemic Vascular Flora of Sardinia: A Dynamic Checklist with an Overview of Biogeography and Conservation Status
Authors: Fois Mauro , Farris Emmanuele , Calvia Giacomo , Campus Giuliano , Fenu Giuseppe , Porceddu Marco , Bacchetta Gianluigi
Published: February 2022

The vascular flora of Sardinia has been investigated for more than 250 years, with particular attention to the endemic component due to their phylogeographic and conservation interest. However, continuous changes in the floristic composition through natural processes, anthropogenic drivers or modified taxonomical attributions require constant updating. We checked all available literature, web sources, field, and unpublished data from the authors and acknowledged external experts to compile an updated checklist of vascular plants endemic to Sardinia. Life and chorological forms as well as the conservation status of the updated taxa list were reported. Sardinia hosts 341 taxa (15% of the total native flora) endemic to the Tyrrhenian Islands and other limited continental territories; 195 of these (8% of the total native flora) are exclusive to Sardinia. Asteraceae (50 taxa) and Plumbaginaceae (42 taxa) are the most representative families, while the most frequent life forms are hemicryptophytes (118 taxa) and chamaephytes (106 taxa). The global conservation status, available for 201 taxa, indicates that most endemics are under the ‘Critically Endangered’ (25 taxa), ‘Endangered’ (31 taxa), or ‘Least Concern’ (90 taxa) IUCN categories. This research provides an updated basis for future biosystematics, taxonomic, biogeographical, and ecological studies and in supporting more integrated and efficient policy tools.
Transgene Flow: Challenges to the On-Farm Conservation of Maize Landraces in the Brazilian Semi-Arid Region
Authors: Fernandes Gabriel Bianconi , Silva Ana Cláudia de Lima , Maronhas Maitê Edite Sousa , Santos Amaury da Silva dos , Lima Paola Hernandez Cortez
Published: February 2022

Brazil is one of the largest global producers of genetically modified crops and a center of origin and diversification of relevant species for agriculture and food. Transgenic monocultures occupy around 50 million hectares, whereas smallholder farmers, indigenous people, and traditional communities are responsible for in-situ/on-Farm conservation of local genetic resources. Based on 15 years of expertise in regulating GMOs and in cross-institutional agrobiodiversity conservation projects, this article discusses the challenges regarding the coexistence of these two agricultural models based on transgene flow detection in maize landraces. As part of a broad and unique participatory transgene-flow-monitoring process, 1098 samples of maize landraces were collected in the Brazilian Semi-arid Region between 2018 and 2021 and analyzed using immunochromatographic strips. The tests revealed 34% of samples with presence of GM proteins. It is concluded that the biosafety standards in force in Brazil do not allow the assurance of on-Farm conservation of maize. The sectors that contribute to agrobiodiversity conservation and do not benefit from using GM seeds are taking on the burden of this process. Transgene flow can be reduced by approving and enforcing more effective coexistence rules that consider maize landraces crop areas also as seed-producing areas added to full disclosure of commercial seeds origin.
Muslim Women in Interfaith Partnerships in Germany
Authors: Feise-Nasr Mona
Published: February 2022

The number of Muslim-interfaith couples in European countries has become significant due to transnational migration and a growing number of Muslims living in Muslim Minority countries. While the challenges for partners in such unions are complex, this article focuses on the lived experiences of Muslim women in interfaith intimate relationships in Germa ny. Drawing on field interviews with women in mixed-faith relationships, the following questions are central: How do Muslim women conceptualize religious identity and practices? Do they face challenges from different groups (Muslim communities, their families, friends, etc.) and if so, how do these challenges manifest? If respondents create concepts of being Muslim for themselves, how do these evolve in their narratives? How do they question, adapt or discard theological and social demands? Preliminary results illustrate that some respondents would appreciate a Muslim community that accepts their positionality as intermarried Muslim women. Looking at the narration of religious practices and concepts of Muslimness in the interviews, it becomes clear that a classification as haram, or legally forbidden, puts a simple categorical bar in front of a socially and theologically complex context. The inquiry combines interview analysis with situational mapping and is informed by Grounded Theory methodology.
Sensors and System for Vehicle Navigation
Authors: Stateczny Andrzej , Kazimierski Witold , Burdziakowski Pawel
Published: February 2022

In recent years, vehicle navigation, in particular autonomous navigation, has been at the center of several major developments, both in civilian and defense applications [...]
Improved 2D Ground Target Tracking in GPS-Based Passive Radar Scenarios
Authors: Gomez-del-Hoyo Pedro , del-Rey-Maestre Nerea , Jarabo-Amores María-Pilar , Mata-Moya David , Benito-Ortiz María-de-Cortés
Published: February 2022

Global Positioning System (GPS) satellites offer promising opportunity for Passive Radar systems due to their global coverage and the availability of multiple satellites throughout the world. However, their low power at ground level limits system coverage. In this paper, a GPS based Passive Radar which exploits a single illumination source, and uses digital array processing for ground targets localization is presented. To face signal power problems, a processing scheme combining reconstructed reference signals, adaptive filtering techniques and spatial filtering is implemented. Conventional beamforming techniques are used to increase the level of the target echo before the detection stage, and high resolution DoA estimation techniques are applied to estimate targets azimuth. Ground target localization in local Cartesian space is performed taking into account the system geometry, range and azimuth information. Both synthetic and real radar data are used to analyse system operation. During the measurement campaign, a cooperative vehicle was used for validation purposes. Results confirm that ground targets detection and localization are feasible using a single GPS transmitter.
Three-Dimensional Measuring Device and Method of Underground Displacement Based on Double Mutual Inductance Voltage Contour Method
Authors: Shentu Nanying , Wang Feng , Li Qing , Qiu Guohua , Tong Renyuan , An Siguang
Published: February 2022

Landslide is a very common and destructive geo-hazard, and displacement monitoring of it is integral for risk assessment and engineering prevention. Given the shortcomings of current landslide displacement monitor technologies, a new three-dimensional underground displacement monitoring technology is proposed based on the double mutual inductance voltage contour method. The underground displacement measuring device mainly consists of an information processing unit and sensing array, connected by power and RS-485 communication lines. An underground displacement measurement model to convert the double mutual inductance voltages and the inter-axis angle into the relative displacement between adjacent sensing units is established based on the interval-interpolation and contour-modeling. Under the control of the information processing unit, the relative displacement between any two adjacent sensing units can be calculated through the underground displacement measurement model, so as to obtain the total displacement from underground depth to surface, and the measurement data can be further sent to the Internet of things cloud platform through the 4G module; thus the remote real-time monitoring of underground displacement three-dimensional measurement for the rock and soil mass from underground depth to the surface is realized. The measurement model is verified by building an experimental platform to simulate the underground displacement of rock and soil mass. The experimental results show that for each measuring unit, when the horizontal displacement and vertical displacement are within the measurement range of 0–50 mm, the maximum measurement error will not exceed 1 mm, which can meet the accuracy requirements of underground displacement monitoring of landslide.
Indirect-Neural-Approximation-Based Fault-Tolerant Integrated Attitude and Position Control of Spacecraft Proximity Operations
Authors: Alsaade Fawaz W. , Yao Qijia , Al-zahrani Mohammed S. , Alzahrani Ali S. , Jahanshahi Hadi
Published: February 2022

In this paper, a neural adaptive fault-tolerant control scheme is proposed for the integrated attitude and position control of spacecraft proximity operations in the presence of unknown parameters, disturbances, and actuator faults. The proposed controller is made up of a relative attitude control law and a relative position control law. Both the relative attitude control law and relative position control law are designed by adopting the neural networks (NNs) to approximate the upper bound of the lumped unknowns. Benefiting from the indirect neural approximation, the proposed controller does not need any model information for feedback. In addition, only two adaptive parameters are required for the indirect neural approximation, and the online calculation burden of the proposed controller is therefore significantly reduced. Lyapunov analysis shows that the overall closed-loop system is ultimately uniformly bounded. The proposed controller can ensure the relative attitude, angular velocity, position, and velocity stabilize into the small neighborhoods around the origin. Lastly, the effectiveness and superior performance of the proposed control scheme are confirmed by a simulated example.
Accuracy Assessment of Joint Angles Estimated from 2D and 3D Camera Measurements
Authors: Van Crombrugge Izaak , Sels Seppe , Ribbens Bart , Steenackers Gunther , Penne Rudi , Vanlanduit Steve
Published: February 2022

To automatically evaluate the ergonomics of workers, 3D skeletons are needed. Most ergonomic assessment methods, like REBA, are based on the different 3D joint angles. Thanks to the huge amount of training data, 2D skeleton detectors have become very accurate. In this work, we test three methods to calculate 3D skeletons from 2D detections: using the depth from a single RealSense range camera, triangulating the joints using multiple cameras, and combining the triangulation of multiple camera pairs. We tested the methods using recordings of a person doing different assembly tasks. We compared the resulting joint angles to the ground truth of a VICON marker-based tracking system. The resulting RMS angle error for the triangulation methods is between 12° and 16°, showing that they are accurate enough to calculate a useful ergonomic score from.
Human Control Model Estimation in Physical Human–Machine Interaction: A Survey
Authors: Scibilia Adriano , Pedrocchi Nicola , Fortuna Luigi
Published: February 2022

The study of human–machine interaction as a unique control system was one of the first research interests in the engineering field, with almost a century having passed since the first works appeared in this area. At the same time, it is a crucial aspect of the most recent technological developments made in application fields such as collaborative robotics and artificial intelligence. Learning the processes and dynamics underlying human control strategies when interacting with controlled elements or objects of a different nature has been the subject of research in neuroscience, aerospace, robotics, and artificial intelligence. The cross-domain nature of this field of study can cause difficulties in finding a guiding line that links motor control theory, modelling approaches in physiological control systems, and identifying human–machine general control models in manipulative tasks. The discussed models have varying levels of complexity, from the first quasi-linear model in the frequency domain to the successive optimal control model. These models include detailed descriptions of physiologic subsystems and biomechanics. The motivation behind this work is to provide a complete view of the linear models that could be easily handled both in the time domain and in the frequency domain by using a well-established methodology in the classical linear systems and control theory.
Fiber-Optic System for Monitoring Pressure Changes on Mine Support Elements
Authors: Yugay Vyacheslav , Mekhtiyev Ali , Madi Perizat , Neshina Yelena , Alkina Aliya , Gazizov Farit , Afanaseva Olga , Ilyashenko Svetlana
Published: February 2022

The paper presents the developed fiber-optic sensors for monitoring pressure measurement on the elements of mine supports. The sudden destruction of the support leads to the collapse of the mine workings and poses a serious threat to the life and safety of underground workers. A fiber-optic system for monitoring changes in pressures on the elements of mine supports will increase the share of mining automation and reduce the share of manual labor, as well as eliminate measurement errors associated with the human factor. Systematic monitoring of the state of the working elements of the support will allow timely tracking of their deformations caused by an increase in rock pressure on them. Implementation of the system at mining enterprises will expand the use of digital technologies in mining. Timely warning of a mine collapse threat will significantly increase the level of safe mining operations, as well as reduce the cost of supporting mine workings, since elimination of the consequences of destruction is associated with significant material costs. This work presents a developed laboratory testbench that simulates a mine working and elements of an arch support on which are installed the fiber-optic sensors connected to an automated measuring system. The developed hardware and software complex provides the processing of a light spot falling on the surface of a television matrix that is installed at the exit from the optical fiber. The results of visual processing are converted into numerical values, which are used to make a decision about the state of the considered object. In addition to automatic monitoring of the structural integrity condition of the considered object, the system is equipped with a function of a visual display for monitoring results, which makes it possible to track sharp fluctuations and bursts of pressure parameters, based on which the prediction of pre-emergency and emergency situations is performed.
Developmental Trends in the Application and Measurement of the Bidirectional Reflection Distribution Function
Authors: Zou Yangyang , Zhang Liu , Zhang Jian , Li Bonan , Lv Xueying
Published: February 2022

The bidirectional reflection distribution function (BRDF) is among the most effective means to study the phenomenon of light–object interaction. It can precisely describe the characteristics of spatial reflection of the target surface, and has been applied to aerial remote sensing, imaging technology, materials analysis, and computer rendering technology. This study provides a comprehensive review of the development of devices to measure the BRDF. We gathered research in the area by using the Web of Science Core Collection, and show that work on the BDRF has been ongoing in the last 30 years. We also describe some typical measurement devices for the BRDF proposed in the literature. Finally, we summarise outstanding problems related to BRDF measurement and propose directions of future research in the area.
Hardware Efficient Massive MIMO Systems with Optimal Antenna Selection
Authors: Aredo Shenko Chura , Negash Yalemzewd , Marye Yihenew Wondie , Kassa Hailu Belay , Kornegay Kevin T. , Diba Feyisa Debo
Published: February 2022

An increase in the number of transmit antennas (M) poses an equivalent rise in the number of Radio Frequency (RF) chains associated with each antenna element, particularly in digital beamforming. The chain exhibits a substantial amount of power consumption accordingly. Hence, to alleviate such problems, one of the potential solutions is to reduce the number of RFs or to minimize their power consumption. In this paper, low-resolution Digital to Analogue Conversion (DAC) and transmit antenna selection at the downlink are evaluated to favour reducing the total power consumption and achieving energy efficiency in mMIMO with reasonable complexity. Antenna selection and low-resolution DAC techniques are proposed to leverage massive MIMO systems in free space and Close In (CI) path-loss models. The simulation results show that the power consumption decreases with antenna selection and low-resolution DAC. Then, the system achieves more energy efficiency than without low-resolution of DAC and full array utilization.
Prediction of Neonatal Respiratory Distress Biomarker Concentration by Application of Machine Learning to Mid-Infrared Spectra
Authors: Ahmed Waseem , Veluthandath Aneesh Vincent , Rowe David J. , Madsen Jens , Clark Howard W. , Postle Anthony D. , Wilkinson James S. , Murugan Ganapathy Senthil
Published: February 2022

The authors of this study developed the use of attenuated total reflectance Fourier transform infrared spectroscopy (ATR–FTIR) combined with machine learning as a point-of-care (POC) diagnostic platform, considering neonatal respiratory distress syndrome (nRDS), for which no POC currently exists, as an example. nRDS can be diagnosed by a ratio of less than 2.2 of two nRDS biomarkers, lecithin and sphingomyelin (L/S ratio), and in this study, ATR–FTIR spectra were recorded from L/S ratios of between 1.0 and 3.4, which were generated using purified reagents. The calibration of principal component (PCR) and partial least squares (PLSR) regression models was performed using 155 raw baselined and second derivative spectra prior to predicting the concentration of a further 104 spectra. A three-factor PLSR model of second derivative spectra best predicted L/S ratios across the full range (R2: 0.967; MSE: 0.014). The L/S ratios from 1.0 to 3.4 were predicted with a prediction interval of +0.29, −0.37 when using a second derivative spectra PLSR model and had a mean prediction interval of +0.26, −0.34 around the L/S 2.2 region. These results support the validity of combining ATR–FTIR with machine learning to develop a point-of-care device for detecting and quantifying any biomarker with an interpretable mid-infrared spectrum.
Are You Wearing a Mask? Detecting If a Person Wears a Mask Using a Wristband
Authors: Msigwa Constantino , Baek Seungwoo , Bernard Denis , Yun Jaeseok
Published: February 2022

Coronavirus 2019 (COVID-19) has posed a serious threat to the lives and health of the majority of people worldwide. Since the early days of the outbreak, South Korea’s government and citizens have made persistent efforts to provide effective prevention against further spread of the disease. In particular, the participation of individual citizens in complying with the necessary code of conduct to prevent spread of the infection, through measures such as social distancing and mask wearing, is as instrumental as the geographical tracking of the trajectory of the infected. In this paper, we propose an activity recognition method based on a wristband equipped with an IR array and inertial measurement unit (IMU) to detect individual compliance with codes of personal hygiene management, such as mask wearing, which are recommended to prevent the spread of infectious diseases. The results of activity recognition were comparatively analyzed by applying conventional machine learning algorithms and convolutional neural networks (CNNs) to the IMU time series and IR array thermal images collected from 25 subjects. When CNN and 24 × 32 thermal images were used, 97.8% accuracy was achieved (best performance), and when 6 × 8 low-resolution thermal images were used, similar performance with 97.1% accuracy was obtained. In the case of using IMU, the performance of activity recognition was lower than that obtained with the IR array, but an accuracy of 93% was achieved even in the case of applying machine learning algorithms, indicating that it is more suitable for wearable devices with low computational capability.
Concurrent-Mode CMOS Detector IC for Sub-Terahertz Imaging System
Authors: Lee Moon-Jeong , Lee Ha-Neul , Lee Ga-Eun , Han Seong-Tae , Yang Jong-Ryul
Published: February 2022

A CMOS detector with a concurrent mode for high-quality images in the sub-terahertz region has been proposed. The detector improves output-signal coupling characteristics at the output node. A cross-coupling capacitor is added to isolate the DC bias between the drain and gate. The detector is designed to combine a 180° phase shift based on common source operation and an in-phase output signal based on the drain input. The circuit layout and phase shift occurring in the cross-coupled capacitor during phase coupling are verified using an EM simulation. The detector is fabricated using the TSMC 0.25-μm mixed-signal 1-poly 5-metal layer CMOS process, where the size, including the pad, is 1.13 mm × 0.74 mm. The detector IC comprises a folded dipole antenna, the proposed detector, a preamplifier, and a voltage buffer. Measurement results using a 200-GHz gyrotron source demonstrate that the proposed detector voltage responsivity is 14.13 MV/W with a noise-equivalent power of 34.42 pW/√Hz. The high detection performance helps resolve the 2-mm line width. The proposed detector exhibits a signal-to-noise ratio of 49 dB with regard to the THz imaging performance, which is 9 dB higher than that of the previous CMOS detector core circuits with gate-drain capacitors.
Quality of Service Aware Orchestration for Cloud–Edge Continuum Applications
Authors: Orive Adrián , Agirre Aitor , Truong Hong-Linh , Sarachaga Isabel , Marcos Marga
Published: February 2022

The fast growth in the amount of connected devices with computing capabilities in the past years has enabled the emergence of a new computing layer at the Edge. Despite being resource-constrained if compared with cloud servers, they offer lower latencies than those achievable by Cloud computing. The combination of both Cloud and Edge computing paradigms can provide a suitable infrastructure for complex applications’ quality of service requirements that cannot easily be achieved with either of these paradigms alone. These requirements can be very different for each application, from achieving time sensitivity or assuring data privacy to storing and processing large amounts of data. Therefore, orchestrating these applications in the Cloud–Edge computing raises new challenges that need to be solved in order to fully take advantage of this layered infrastructure. This paper proposes an architecture that enables the dynamic orchestration of applications in the Cloud–Edge continuum. It focuses on the application’s quality of service by providing the scheduler with input that is commonly used by modern scheduling algorithms. The architecture uses a distributed scheduling approach that can be customized in a per-application basis, which ensures that it can scale properly even in setups with high number of nodes and complex scheduling algorithms. This architecture has been implemented on top of Kubernetes and evaluated in order to asses its viability to enable more complex scheduling algorithms that take into account the quality of service of applications.
Design and Control of Multi-Plate MR Clutch Featuring Friction and Magnetic Field Control Modes
Authors: Park Jin-Young , Oh Jong-Seok , Kim Young-Choon
Published: February 2022

A magnetorheological (MR) multi-plate clutch was proposed with both mechanical friction mode and magnetic field control modes. The magnetic field control mode was based on an MR fluid coupler that changed its viscous properties according to the density of an applied magnetic field. This mode was used in the early stage of clutch operation to reduce the impact of friction between the disc and plate, and eliminate to the extent possible the difference in their relative speeds when contacting each other in later stages. Once the rotational speed difference between the disc and plate was reduced, the clutch was operated in mechanical friction mode by compressing the friction surfaces together. A torque modeling equation was then derived for each mode based on the Bingham model of the MR fluid, and the transmission torque of the proposed multi-plate clutch was derived using these equations as well as magnetic field analysis results obtained using ANSYS Maxwell. A multi-plate MR clutch was then fabricated, and its torque transmission characteristics were evaluated in the magnetic field control and mechanical friction modes. The results confirmed that the model-based torque calculations were consistent with the observed transmission torque. Finally, control algorithms for mechanical friction only and mixed mechanical friction/magnetic field control torque tracking of the proposed MR multi-plate clutch were designed, and their performances were evaluated when applying unit step command, half-sine-wave command, and rotational speed changes. The results indicated that the torque tracking control was performed smoothly, demonstrating the advantages of the proposed clutch.
A Novel Methodology for the Synchronous Collection and Multimodal Visualization of Continuous Neurocardiovascular and Neuromuscular Physiological Data in Adults with Long COVID
Authors: Xue Feng , Monaghan Ann , Jennings Glenn , Byrne Lisa , Foran Tim , Duggan Eoin , Romero-Ortuno Roman
Published: February 2022

Background: Reports suggest that adults with post-COVID-19 syndrome or long COVID may be affected by orthostatic intolerance syndromes, with autonomic nervous system dysfunction as a possible causal factor of neurocardiovascular instability (NCVI). Long COVID can also manifest as prolonged fatigue, which may be linked to neuromuscular function impairment (NMFI). The current clinical assessment for NCVI monitors neurocardiovascular performance upon the application of orthostatic stressors such as an active (i.e., self-induced) stand or a passive (tilt table) standing test. Lower limb muscle contractions may be important in orthostatic recovery via the skeletal muscle pump. In this study, adults with long COVID were assessed with a protocol that, in addition to the standard NCVI tests, incorporated simultaneous lower limb muscle monitoring for NMFI assessment. Methods: To conduct such an investigation, a wide range of continuous non-invasive biomedical sensing technologies were employed, including digital artery photoplethysmography for the extraction of cardiovascular signals, near-infrared spectroscopy for the extraction of regional tissue oxygenation in brain and muscle, and electromyography for assessment of timed muscle contractions in the lower limbs. Results: With the proposed methodology described and exemplified in this paper, we were able to collect relevant physiological data for the assessment of neurocardiovascular and neuromuscular functioning. We were also able to integrate signals from a variety of instruments in a synchronized fashion and visualize the interactions between different physiological signals during the combined NCVI/NMFI assessment. Multiple counts of evidence were collected, which can capture the dynamics between skeletal muscle contractions and neurocardiovascular responses. Conclusions: The proposed methodology can offer an overview of the functioning of the neurocardiovascular and neuromuscular systems in a combined NCVI/NMFI setup and is capable of conducting comparative studies with signals from multiple participants at any given time in the assessment. This could help clinicians and researchers generate and test hypotheses based on the multimodal inspection of raw data in long COVID and other cohorts.
The Increasing Replication of Territorial and Social Inequalities in Public Education in Hungary—Causes, Components, Practices and Mechanisms
Authors: Velkey Gábor
Published: February 2022

Over the past decade, the approach to socio-spatial inequalities has increasingly focused on references to the complexity of this phenomenon and on the role of its trans-economic components (mechanisms of reproduction, institutional frameworks, local specificities). Among the institutional structures of social reproduction, public services play a prominent role, including the system of education and training. In my analysis, in addition to reviewing the inequalities within the education system and their causes, I focus on a detailed exploration of the mechanisms that shape people’s access to services. In Hungary, according to the unanimous opinion of domestic analyses, changes in school inequalities (especially in the last decade) have been in the opposite direction in comparison with similar countries. Inequalities between schools have increased significantly and school segregation has become increasingly common (and accepted). My study first reviews the general structural features of the education system and its most important changes, then takes a case study approach, conducting a detailed analysis of primary school education in four municipalities in Hungary in order to explore the specific mechanisms of operation from a bottom-up perspective. The analysis of the local context also allows the specificities of the ‘place’ and the effects of hierarchies and networks beyond it to be isolated, and permits the interpretation of diverse local practices.
Mindfulness in Health Education: From Physical to Virtual Presence during the Pandemic, an Anthropological Study in Spain
Authors: Tellez Infantes Anastasia , Antón Hurtado Fina , Sánchez Vera Fulgencio , Martínez Guirao Javier Eloy
Published: February 2022

Research on traditional mindfulness-based interventions supports the position that they are effective in treating psychological problems and benefiting healthy people. However, more research is needed on the effectiveness of online interventions, a field that is growing and developing rapidly, especially with the onset of the pandemic, as many meditation groups have moved into cyberspace. There is little research on the difficulties that these groups face and the effectiveness of online mindfulness practice. In this work, we analyze the effects of the transition from training with physical presence to virtual training in mindfulness during the lockdown and subsequent period of social distancing due to SARS-CoV-2. Specifically, we analyze the changes in the means and the methodology and the effects of the transition to virtual presence; finally, we evaluate the results obtained through both training models. The investigation was carried out in a center where face-to-face training has been provided for twelve years and that, with the onset of the pandemic, moved its practice groups to cyberspace. The methodology is anthropological and is supported by quantitative and qualitative techniques. The results show that online training breaks the traditional chrono-topo complex and opens up new access possibilities, but limits bodily practices, decreases the intensity of the experience, and slows down the pace of learning. However, the effectiveness is maintained by showing equivalent result rates at the end of the training.
Power Management and Control of a Hybrid Electric Vehicle Based on Photovoltaic, Fuel Cells, and Battery Energy Sources
Authors: Mohamed Naoui , Aymen Flah , Altamimi Abdullah , Khan Zafar A. , Lassaad Sbita
Published: February 2022

This paper deals with an energy management problem to ensure the best performance of the recharging tools used in electric vehicles. The main objective of this work is to find the optimal condition for controlling a hybrid recharging system by regrouping the photovoltaic cells and fuel cells. The photovoltaic and fuel cell systems were connected in parallel via two converters to feed either a lithium battery bank or the main traction motor. This combination of energy sources resulted in a hybrid recharging system. The mathematical model of the overall recharging system and the designed power management loop was developed, taking into account multiple aspects, including vehicle loading, the stepwise mathematical modelling of each component, and a detailed discussion of the required electronic equipment. Finally, a simplistic management loop was designed and implemented. Multiple case studies were simulated, statistical approaches were used to quantify the contribution of each recharging method, and the benefits of the combination of the two sources were evaluated. The energetic performance of an electric vehicle with the proposed hybrid recharging tool under various conditions, including static and dynamic modes, was simulated using the MATLAB/Simulink tool. The results suggest that despite the additional weight of PV panels, the combination of the PV and FC systems improves the vehicle’s energetic performance and provides a higher charging capacity instead of using an FC alone. A comparison with similar studies revealed that the proposed model has a higher efficiency. Finally, the benefits and drawbacks of each solution are discussed to emphasise the significance of the hybrid recharging system.
Erasmus Students’ Experiences as Cultural Visitors: Lessons in Destination Management
Authors: Marin-Pantelescu Andreea , Tăchiciu Laurențiu , Oncioiu Ionica , Ștefan-Hint Mihaela
Published: February 2022

Destination management is an important instrument in promoting tourism as a factor of economic development. Its usefulness in planning and developing infrastructures and services especially dedicated to tourism, such as holidays, sports, or balneal resorts, is well established. In the context of increasing the mobility of people at a national and international level, the flows of visitors whose trips are related to jobs, business, studies, conferences have constantly increased, and—as a result—the importance of large cities among tourist destinations is increasing. The management of destinations must also contribute in such cases to the creation of a greater attractiveness for potential visitors, the facilitation of their activities, and the production of culturally enriched and pleasant experiences. There is still a need to better understand how big cities are perceived as a destination by visitors, especially when it comes to longer stays. As a result, this paper proposes an approach to explore the visitors’ perception of their own experiences with the destination city. The subjects of the study are Erasmus students, while the destinations considered are university cities where the mobility programs were carried out. The aim of the research carried out by the focus-group method was to identify the elements that contributed to the coagulation of the experience associated with a certain destination city, in the sense of a more favorable or less favorable image of the destination in question. The results highlight that where visitors interact for a longer period of time and at deeper levels with the host community, they share the conditions of local life. The more pleasant these conditions are for the residents, the more open and welcoming they are to foreigners, and the more appreciated one’s personal experience of that city is.
Business Models and Sustainable Development Goals
Authors: Ensign Prescott C.
Published: February 2022

In 2015, all 193 member countries of the United Nations adopted the 2030 Agenda for Sustainable Development. It includes 17 Sustainable Development Goals (SDGs). Building on the principle of “leaving no one behind,” it emphasizes a holistic approach to achieving sustainable development [1]. The 2020 environmental, social and governance (ESG) scoring and reporting document from the Organization for Economic Co-operation and Development (OECD) notes that sustainability investing has grown, primarily due to the number of funds and investors that have added ESG approaches to their overall agenda. Corporations, central banks and the public sector are placing a new emphasis on a greener environment and low-carbon economy [2]. The 2020s was to be a decade of action but progress has been slow, stalled or reversed in meeting the 17 SDG targets [3]. OECD’s quantitative analysis provides an indication of the progress made and challenges still ahead with regard to sustainable development. The wide variety of metrics, methodologies, and approaches indicate a high number of disparate outcomes that are open to interpretation [4].
Promotional Activities of Selected National Tourism Organizations (NTOs) in the Light of Sustainable Tourism (Including Sustainable Transport)
Authors: Olszewski-Strzyżowski Dariusz Jacek
Published: February 2022

The dynamic development and evolution that tourism has recently undergone and its growing importance made it become an important element of the policy of today’s countries in various walks of social, economic and political life. As tourism is one of the largest industries in the world, most countries recognized the leading role in their economies, establishing in this regard the administrative structure of the national tourism organizations (NTOs). NTOs are responsible for the marketing and promotion of countries, improving the tourist image of a given country and supporting existing or developing new tourism products. At the same time, governments are increasingly realizing that tourism should develop in accordance with the principles of sustainable development and be integrated with the natural, cultural and social environment of these countries. This article presents the activities of selected national tourism organizations (NTOs) in terms of their role in developing the potential of sustainable tourism (and within it sustainable transport) in their countries. The aim of the article is to review the promotional activities undertaken by NTOs operating in countries such as Austria, Cyprus, Grenada, Guatemala, Norway and Indonesia. The article is an overview, and the following sources were used to prepare it: official websites of the organizations, reports, promotional materials and any documents related to the operation of the studied NTOs in the field of sustainable tourism and sustainable transport development (e.g., tourism development strategies, tourism product development strategies, projects and programs). The choice of these countries for the analysis was dictated by the fact that they have outstanding natural and cultural assets that make up the product potential for sustainable tourism and the very responsible, diverse and long-term promotional and marketing activities undertaken by the NTOs (e.g., promotional campaigns). Such prudent treatment of own resources and sustainable potential may also contribute to these countries gaining a competitive advantage over other destinations in the world (e.g., increase in interest from tourists). The activities and promotional campaigns cited in the article as well as the solutions proposed by NTOs can also become excellent examples of good practice for other destinations in the world. The research has also shown that the studied countries (and their national tourism organizations) clearly support the development of sustainable tourism and sustainable transport through their national tourism policies.
Exploration of Copula Models Use in Risk Assessment for Freezing and Snow Events: A Case Study in Southern China
Authors: Li Qian , Chen Liutong , Yan Zhengtao , Xu Yingjun
Published: February 2022

Due to cold waves, low and extremely low temperatures occur every winter. Sudden cooling can cause freezing and snow disasters, which seriously affect transportation, power, safety, and other activities, resulting in serious economic losses. Based on precipitation and average temperature data from 258 national meteorological stations over the past 70 years, this study established a historical freezing and snow event data set, extracting the accumulated precipitation intensity (API) and accumulated temperature intensity (ATI). We selected the optimal distribution function and joint distribution function for each station and calculated the univariate and bivariate joint return periods. The return period accuracy plays an important role in risk assessment results. By comparing the calculations with the real return period for historical extreme events, we found that the bivariate joint return period based on a copula model was more accurate than the univariate return period. This is important for the prediction and risk assessment of freezing and snow disasters. Additionally, a risk map based on the joint return period showed that Jiangsu and Anhui, as well as some individual stations in the central provinces, were high-risk areas; however, the risk level was lower in Chongqing and the southern provinces.
Analysis of the Vulnerability and Resilience of the Tourism Supply Chain under the Uncertain Environment of COVID-19: Case Study Based on Lijiang
Authors: Bai Haixia , Ran Wenxue
Published: February 2022

The uncertainty environment brought about by COVID-19 has broken the original stable hierarchical network structure and the whole supply and demand system of the tourism supply chain (TSC), which has brought heavy losses to the tourism industry. Using the case research and consensual qualitative research (CQR) method, taking the real situation and perception of individual supply chain members as a window, supplemented by the narrative insertion of Lijiang Yulong Tourism Co., Ltd., Lijiang Old Town and Yulong Snow Mountain scenic areas, the general laws of the vulnerability and resilience of the TSC were glimpsed. The results show that there are vulnerability factors in the TSC including the supply side, demand side, government side, destination economic structure and supply chain attributes, which lead to the interruption and damage of the TSC after the outbreak of the pandemic. At the same time, China’s overall economic environment, tourism demand side, supply side, government side and market participants all have resilience elements. Behind the vulnerability, there is a power of recovery and opportunities for innovation and change. The TSC shows a trend of restorative growth. Theoretically, it helps to enrich theories of TSC and supply chain management under an emergency crisis. In practice, the response behavior of participants at different levels of the supply chain is also the basis for TSC risk management and formulation of optimization strategies in the future, which helps tourism sustainable development in the uncertain environment.
Suitability Zoning for Sustainable Drainage Systems (SuDSs): Application in a Basin in Southern Brazil
Authors: Failache Moises , Pons Nívea , Pejon Osni , Zuquette Lázaro
Published: February 2022

The objective of this study was to propose a set of procedures to assess areas regarding the suitability of sustainable drainage systems (SuDSs) with application in a basin in the urban area of São Carlos (Brazil). The assessment was based on an analysis of 39 attributes reflecting the infiltration conditions that control the functional and constructive aspects of the systems, including subsurface drainability, stability, and groundwater contamination potential, which control the degree of suitability of each plot of land. The data obtained through engineering geological mapping procedures and physical principles were used to characterize the area, which resulted in the division of the basin into five SuDS suitability zones, ranging from favorable to restrictive. The proposed procedures proved to be efficient for analyzing the suitability of different SuDS types and the zoning of an area into terrain units. This approach can help planners identify the most appropriate SuDS types for a given unit, optimize the efficiency/cost relationship, and foresee potential environmental and construction-related challenges. In other words, this procedure enables the assessment of the suitability of SuDSs for different unit terrain types with inexpensive and environmentally efficient technological procedures and resources and can be applied at a fine geographic scale.
Conventional RVS Methods for Seismic Risk Assessment for Estimating the Current Situation of Existing Buildings: A State-of-the-Art Review
Authors: Bektaş Nurullah , Kegyes-Brassai Orsolya
Published: February 2022

Developments in the field of earthquake engineering over the past few decades have contributed to the development of new methods for evaluating the risk levels in buildings. These research methods are rapid visual screening (RVS), seismic risk indexes, and vulnerability assessments, which have been developed to assess the levels of damage in a building or its structural components. RVS methods have been proposed for the rapid pre- and/or post-earthquake screening of existing large building stock in earthquake-prone areas on the basis of sidewalk surveys. The site seismicity, the soil type, the building type, and the corresponding building characteristic features are to be separately examined, and the vulnerability level of each building can be identified by employing the RVS methods. This study describes, evaluates, and compares the findings of previous investigations that utilized conventional RVS methods within a framework. It also suggests the methods to be used for specific goals and proposes prospective enhancement strategies. Furthermore, the article discusses the time-consuming RVS methods (such as FEMA 154, which requires from 15 to 30 min, while NRCC requires one hour), and provides an overview of the application areas of the methods (pre-earthquake: FEMA 154, NRCC, NZEE, etc.; postearthquake: GNDT, EMS, etc.). This review of the traditional RVS methods offers a comprehensive guide and reference for field practitioners (e.g., engineers, architects), and recommends enhancement techniques (e.g., machine learning, fuzzy logic) for researchers to be used in future improvements.
A Cost-Effective Solution for Non-Convex Economic Load Dispatch Problems in Power Systems Using Slime Mould Algorithm
Authors: Kamboj Vikram Kumar , Kumari Challa Leela , Bath Sarbjeet Kaur , Prashar Deepak , Rashid Mamoon , Alshamrani Sultan S. , AlGhamdi Ahmed Saeed
Published: February 2022

Slime Mould Algorithm (SMA) is a newly designed meat-heuristic search that mimics the nature of slime mould during the oscillation phase. This is demonstrated in a unique mathematical formulation that utilizes adjustable weights to influence the sequence of both negative and positive propagation waves to develop a method to link food supply with intensive exploration capacity and exploitation affinity. The study shows the usage of the SM algorithm to solve a non-convex and cost-effective Load Dispatch Problem (ELD) in an electric power system. The effectiveness of SMA is investigated for single area economic load dispatch on large-, medium-, and small-scale power systems, with 3-, 5-, 6-, 10-, 13-, 15-, 20-, 38-, and 40-unit test systems, and the results are substantiated by finding the difference between other well-known meta-heuristic algorithms. The SMA is more efficient than other standard, heuristic, and meta-heuristic search strategies in granting extremely ambitious outputs according to the comparison records.