bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of Trace Metals in Human Hair by Laser-Induced Breakdown Spectroscopy with a Compact Microchip Laser
Authors: Nakagawa Makoto , Matsuura Yuji
Published: May 2021

A laser-induced breakdown spectroscopy (LIBS) system using a microchip laser for plasma generation is proposed for in-situ analysis of trace minerals in human hair. The LIBS system is more compact and less expensive than conventional LIBS systems, which use flashlamp-excited Q-switched Nd:YAG lasers. Focusing optics were optimized using a Galilean beam expander to compensate for the low emitted pulse energy of the microchip laser. Additionally, hundreds of generated LIBS spectra were accumulated to improve the signal-to-noise ratio of the measurement system, and argon gas was injected at the irradiation point to enhance plasma intensity. LIBS spectra of human hair in the UV to near IR regions were investigated. Relative mass concentrations of Ca, Mg, and Zn were analyzed in hairs obtained from five subjects using the intensity of C as a reference. The results coincide well with those measured via inductively coupled argon plasma mass spectrometry. The lowest detectable concentrations of the measured LIBS spectra were 9.0 ppm for Mg, 27 ppm for Zn, and 710 ppm for Ca. From these results, we find that the proposed LIBS system based on a microchip laser is feasible for the analysis of trace minerals in human hair.
Flow-Through Electrochemical Biosensor for the Detection of Listeria monocytogenes Using Oligonucleotides
Authors: Armstrong Cheryl M. , Lee Joe , Gehring Andrew G. , Capobianco Joseph A.
Published: May 2021

Consumption of food contaminated by Listeria monocytogenes can result in Listeriosis, an illness with hospitalization rates of 94% and mortality rates up to 30%. As a result, U.S. regulatory agencies governing food safety retain zero-tolerance policies for L. monocytogenes. However, detection at such low concentrations often requires strategies such as increasing sample size or culture enrichment. A novel flow-through immunoelectrochemical biosensor has been developed for Escherichia coli O157:H7 detection in 1 L volumes without enrichment. The current work further augments this biosensor’s capabilities to (1) include detection of L. monocytogenes and (2) accommodate genetic detection to help overcome limitations based upon antibody availability and address specificity errors in phenotypic assays. Herein, the conjugation scheme for oligo attachment and the conditions necessary for genetic detection are laid forth while results of the present study demonstrate the sensor’s ability to distinguish L. monocytogenes DNA from L. innocua with a limit of detection of ~2 × 104 cells/mL, which agrees with prior studies. Total time for this assay can be constrained to <2.5 h because a timely culture enrichment period is not necessary. Furthermore, the electrochemical detection assay can be performed with hand-held electronics, allowing this platform to be adopted for near-line monitoring systems.
Merit-Based Motion Planning for Autonomous Vehicles in Urban Scenarios
Authors: Medina-Lee Juan , Artuñedo Antonio , Godoy Jorge , Villagra Jorge
Published: May 2021

Safe and adaptable motion planning for autonomous vehicles remains an open problem in urban environments, where the variability of situations and behaviors may become intractable using rule-based approaches. This work proposes a use-case-independent motion planning algorithm that generates a set of possible trajectories and selects the best of them according to a merit function that combines longitudinal comfort, lateral comfort, safety and utility criteria. The system was tested in urban scenarios on simulated and real environments, and the results show that different driving styles can be achieved according to the priorities set in the merit function, always meeting safety and comfort parameters imposed by design.
Machine Learning in Agriculture: A Comprehensive Updated Review
Authors: Benos Lefteris , Tagarakis Aristotelis C. , Dolias Georgios , Berruto Remigio , Kateris Dimitrios , Bochtis Dionysis
Published: May 2021

The digital transformation of agriculture has evolved various aspects of management into artificial intelligent systems for the sake of making value from the ever-increasing data originated from numerous sources. A subset of artificial intelligence, namely machine learning, has a considerable potential to handle numerous challenges in the establishment of knowledge-based farming systems. The present study aims at shedding light on machine learning in agriculture by thoroughly reviewing the recent scholarly literature based on keywords’ combinations of “machine learning” along with “crop management”, “water management”, “soil management”, and “livestock management”, and in accordance with PRISMA guidelines. Only journal papers were considered eligible that were published within 2018–2020. The results indicated that this topic pertains to different disciplines that favour convergence research at the international level. Furthermore, crop management was observed to be at the centre of attention. A plethora of machine learning algorithms were used, with those belonging to Artificial Neural Networks being more efficient. In addition, maize and wheat as well as cattle and sheep were the most investigated crops and animals, respectively. Finally, a variety of sensors, attached on satellites and unmanned ground and aerial vehicles, have been utilized as a means of getting reliable input data for the data analyses. It is anticipated that this study will constitute a beneficial guide to all stakeholders towards enhancing awareness of the potential advantages of using machine learning in agriculture and contributing to a more systematic research on this topic.
High-Temperature Monitoring in Central Receiver Concentrating Solar Power Plants with Femtosecond-Laser Inscribed FBG
Authors: Rodríguez-Garrido Roberto , Carballar Alejandro , Vera Jonathan , González-Aguilar José , Altamirano Adeodato , Loureiro Antonio , Pereira Daniel
Published: May 2021

This work deals with the application of femtosecond-laser-inscribed fiber Bragg gratings (FsFBGs) for monitoring the internal high-temperature surface distribution (HTSD) in solar receivers of concentrating solar power (CSP) plants. The fiber-optic sensor system is composed of 12 FsFBGs measuring points distributed on an area of 0.4 m2, which leads to obtain the temperature map at the receiver by means of two-dimensional interpolation. An analysis of the FsFBG performance in harsh environment was also conducted. It describes the influence of calibration functions in high-temperature measurements, determines a required 10 nm spectral interval for measuring temperatures in the range from 0 to 700 °C, and reveals wavelength peak tolerances in the FsFBG fabrication process. Results demonstrate the viability and reliability of this measuring technique, with temperature measurements up to 566 °C.
Monitoring of a Highly Flexible Aircraft Model Wing Using Time-Expanded Phase-Sensitive OTDR
Authors: Soriano-Amat Miguel , Fragas-Sánchez David , Martins Hugo F. , Vallespín-Fontcuberta David , Preciado-Garbayo Javier , Martin-Lopez Sonia , Gonzalez-Herraez Miguel , Fernández-Ruiz María R.
Published: May 2021

In recent years, the use of highly flexible wings in aerial vehicles (e.g., aircraft or drones) has been attracting increasing interest, as they are lightweight, which can improve fuel-efficiency and distinct flight performances. Continuous wing monitoring can provide valuable information to prevent fatal failures and optimize aircraft control. In this paper, we demonstrate the capabilities of a distributed optical fiber sensor based on time-expanded phase-sensitive optical time-domain reflectometry (TE-ΦOTDR) technology for structural health monitoring of highly flexible wings, including static (i.e., bend and torsion), and dynamic (e.g., vibration) structural deformation. This distributed sensing technology provides a remarkable spatial resolution of 2 cm, with detection and processing bandwidths well under the MHz, arising as a novel, highly efficient monitoring methodology for this kind of structure. Conventional optical fibers were embedded in two highly flexible specimens that represented an aircraft wing, and different bending and twisting movements were detected and quantified with high sensitivity and minimal intrusiveness.
A Baseline for Cross-Database 3D Human Pose Estimation
Authors: Rapczyński Michał , Werner Philipp , Handrich Sebastian , Al-Hamadi Ayoub
Published: May 2021

Vision-based 3D human pose estimation approaches are typically evaluated on datasets that are limited in diversity regarding many factors, e.g., subjects, poses, cameras, and lighting. However, for real-life applications, it would be desirable to create systems that work under arbitrary conditions (“in-the-wild”). To advance towards this goal, we investigated the commonly used datasets HumanEva-I, Human3.6M, and Panoptic Studio, discussed their biases (that is, their limitations in diversity), and illustrated them in cross-database experiments (for which we used a surrogate for roughly estimating in-the-wild performance). For this purpose, we first harmonized the differing skeleton joint definitions of the datasets, reducing the biases and systematic test errors in cross-database experiments. We further proposed a scale normalization method that significantly improved generalization across camera viewpoints, subjects, and datasets. In additional experiments, we investigated the effect of using more or less cameras, training with multiple datasets, applying a proposed anatomy-based pose validation step, and using OpenPose as the basis for the 3D pose estimation. The experimental results showed the usefulness of the joint harmonization, of the scale normalization, and of augmenting virtual cameras to significantly improve cross-database and in-database generalization. At the same time, the experiments showed that there were dataset biases that could not be compensated and call for new datasets covering more diversity. We discussed our results and promising directions for future work.
Estimation of Motion and Respiratory Characteristics during the Meditation Practice Based on Video Analysis
Authors: Kashevnik Alexey , Othman Walaa , Ryabchikov Igor , Shilov Nikolay
Published: May 2021

Meditation practice is mental health training. It helps people to reduce stress and suppress negative thoughts. In this paper, we propose a camera-based meditation evaluation system, that helps meditators to improve their performance. We rely on two main criteria to measure the focus: the breathing characteristics (respiratory rate, breathing rhythmicity and stability), and the body movement. We introduce a contactless sensor to measure the respiratory rate based on a smartphone camera by detecting the chest keypoint at each frame, using an optical flow based algorithm to calculate the displacement between frames, filtering and de-noising the chest movement signal, and calculating the number of real peaks in this signal. We also present an approach to detecting the movement of different body parts (head, thorax, shoulders, elbows, wrists, stomach and knees). We have collected a non-annotated dataset for meditation practice videos consists of ninety videos and the annotated dataset consists of eight videos. The non-annotated dataset was categorized into beginner and professional meditators and was used for the development of the algorithm and for tuning the parameters. The annotated dataset was used for evaluation and showed that human activity during meditation practice could be correctly estimated by the presented approach and that the mean absolute error for the respiratory rate is around 1.75 BPM, which can be considered tolerable for the meditation application.
Congested Crowd Counting via Adaptive Multi-Scale Context Learning
Authors: Zhang Yani , Zhao Huailin , Duan Zuodong , Huang Liangjun , Deng Jiahao , Zhang Qing
Published: May 2021

In this paper, we propose a novel congested crowd counting network for crowd density estimation, i.e., the Adaptive Multi-scale Context Aggregation Network (MSCANet). MSCANet efficiently leverages the spatial context information to accomplish crowd density estimation in a complicated crowd scene. To achieve this, a multi-scale context learning block, called the Multi-scale Context Aggregation module (MSCA), is proposed to first extract different scale information and then adaptively aggregate it to capture the full scale of the crowd. Employing multiple MSCAs in a cascaded manner, the MSCANet can deeply utilize the spatial context information and modulate preliminary features into more distinguishing and scale-sensitive features, which are finally applied to a 1 × 1 convolution operation to obtain the crowd density results. Extensive experiments on three challenging crowd counting benchmarks showed that our model yielded compelling performance against the other state-of-the-art methods. To thoroughly prove the generality of MSCANet, we extend our method to two relevant tasks: crowd localization and remote sensing object counting. The extension experiment results also confirmed the effectiveness of MSCANet.
Research Trends and Future Perspectives in Marine Biomimicking Robotics
Authors: Aguzzi Jacopo , Costa Corrado , Calisti Marcello , Funari Valerio , Stefanni Sergio , Danovaro Roberto , Gomes Helena , Vecchi Fabrizio , Dartnell Lewis , Weiss Peter , Nowak Kathrin , Chatzievangelou Damianos , Marini Simone
Published: May 2021

Mechatronic and soft robotics are taking inspiration from the animal kingdom to create new high-performance robots. Here, we focused on marine biomimetic research and used innovative bibliographic statistics tools, to highlight established and emerging knowledge domains. A total of 6980 scientific publications retrieved from the Scopus database (1950–2020), evidencing a sharp research increase in 2003–2004. Clustering analysis of countries collaborations showed two major Asian-North America and European clusters. Three significant areas appeared: (i) energy provision, whose advancement mainly relies on microbial fuel cells, (ii) biomaterials for not yet fully operational soft-robotic solutions; and finally (iii), design and control, chiefly oriented to locomotor designs. In this scenario, marine biomimicking robotics still lacks solutions for the long-lasting energy provision, which presently hinders operation autonomy. In the research environment, identifying natural processes by which living organisms obtain energy is thus urgent to sustain energy-demanding tasks while, at the same time, the natural designs must increasingly inform to optimize energy consumption.
Design of a Plantar Pressure Insole Measuring System Based on Modular Photoelectric Pressure Sensor Unit
Authors: Ren Bin , Liu Jianwei
Published: May 2021

Accurately perceiving and predicting the parameters related to human walking is very important for man–machine coupled cooperative control systems such as exoskeletons and power prostheses. Plantar pressure data is rich in human gait and posture information and is an essential source of reference information as the input of the exoskeleton control system. Therefore, the proper design of the pressure sensing insole and validation is a big challenge considering the requirements such as convenience, reliability, no interference and so on. In this research, we developed a low-cost modular sensing unit based on the principle of photoelectric sensing and designed a plantar pressure sensing insole to achieve the purpose of sensing human walking gait and posture information. On the one hand, the sensor unit is made of economy-friendly commercial flexible circuits and elastic silicone, and the mechanical and electrical characteristics of the modular sensor unit are evaluated by a self-developed pressure-related calibration system. The calibration results show that the modular sensor based on the photoelectric sensing principle has fast response and negligible hysteresis. On the other hand, we analyzed the area where the plantar pressure is densely distributed. One benefit of the modular sensing unit design is that it is rather convenient to fabricate different insole solutions, so we fabricated and compared several pressure-sensitive insole solutions in this preliminary study. During the dynamic locomotion experiments of wearing the pressure-sensing insole, the time series signal of each sensor unit was collected and analyzed. The results show that the pressure sensing insole based on the photoelectric effect can sense the distribution of the plantar pressure by capturing the deformation of the insole caused by the foot contact during locomotion, and provide reliable gait information for wearable applications.
Moisture Computing-Based Internet of Vehicles (IoV) Architecture for Smart Cities
Authors: Tufail Ali , Namoun Abdallah , Abi Sen Adnan Ahmed , Kim Ki-Hyung , Alrehaili Ahmed , Ali Arshad
Published: May 2021

Recently, the concept of combining ‘things’ on the Internet to provide various services has gained tremendous momentum. Such a concept has also impacted the automotive industry, giving rise to the Internet of Vehicles (IoV). IoV enables Internet connectivity and communication between smart vehicles and other devices on the network. Shifting the computing towards the edge of the network reduces communication delays and provides various services instantly. However, both distributed (i.e., edge computing) and central computing (i.e., cloud computing) architectures suffer from several inherent issues, such as high latency, high infrastructure cost, and performance degradation. We propose a novel concept of computation, which we call moisture computing (MC) to be deployed slightly away from the edge of the network but below the cloud infrastructure. The MC-based IoV architecture can be used to assist smart vehicles in collaborating to solve traffic monitoring, road safety, and management issues. Moreover, the MC can be used to dispatch emergency and roadside assistance in case of incidents and accidents. In contrast to the cloud which covers a broader area, the MC provides smart vehicles with critical information with fewer delays. We argue that the MC can help reduce infrastructure costs efficiently since it requires a medium-scale data center with moderate resources to cover a wider area compared to small-scale data centers in edge computing and large-scale data centers in cloud computing. We performed mathematical analyses to demonstrate that the MC reduces network delays and enhances the response time in contrast to the edge and cloud infrastructure. Moreover, we present a simulation-based implementation to evaluate the computational performance of the MC. Our simulation results show that the total processing time (computation delay and communication delay) is optimized, and delays are minimized in the MC as apposed to the traditional approaches.
A Lean UX Process Model for Virtual Reality Environments Considering ADHD in Pupils at Elementary School in COVID-19 Contingency
Authors: Cardona-Reyes Héctor , Muñoz-Arteaga Jaime , Villalba-Condori Klinge , Barba-González María Lorena
Published: May 2021

Today, the world is experiencing the COVID-19 health contingency, which prevents people from being exposed to one another and restricts physical contact. Under this context, the use of technology has become an essential tool to face the challenges of daily life, and virtual reality can be an alternative in the development of solutions that effectively support the acquisition of learning skills and knowledge transmission through the execution of tasks designed by multi-disciplinary groups. In addition, it can encourage the user to continue with the acquisition of learning skills in a friendly and fun way in a health and education context. This work proposes the use of virtual reality environments as an alternative to support the learning process in children with special educational needs such as Attention Deficit Hyperactivity Disorder (ADHD) and other associated disorders that occur in basic education. These proposed reality environments are designed under the Lean UX process model and their contents are designed according to expert therapeutic guidelines. As a result of this proposal, a case study is presented in which the user experience is evaluated through the use of an interactive environment to support the special educational needs of elementary school children attending an educational institution in Mexico.
The Protraction and Retraction Angles of Horse Limbs: An Estimation during Trotting Using Inertial Sensors
Authors: Sapone Marie , Martin Pauline , Ben Mansour Khalil , Chateau Henry , Marin Frédéric
Published: May 2021

The protraction and retraction angles of horse limbs are important in the analysis of horse locomotion. This study explored two methods from an IMU positioned on the canon bone of eight horses to estimate these angles. Each method was based on a hypothesis in order to define the moment corresponding with the verticality of the canon bone: (i) the canon bone is in a vertical position at 50% of the stance phase or (ii) the verticality of the canon bone corresponds with the moment when the horse’s withers reach their lowest point. The measurements were carried out on a treadmill at a trot and compared with a standard gold method based on motion capture. For the measurement of the maximum protraction and retraction angles, method (i) had average biases (0.7° and 1.7°) less than method (ii) (−1.3° and 3.7°). For the measurement of the protraction and retraction angles during the stance phase, method (i) had average biases (4.1° and −3.3°) higher to method (ii) (2.1° and −1.3°). This study investigated the pros and cons of a generic method (i) vs. a specific method (ii) to determine the protraction and retraction angles of horse limbs by a single IMU.
High Accuracy WiFi-Based Human Activity Classification System with Time-Frequency Diagram CNN Method for Different Places
Authors: Sharma Lokesh , Chao Chung-Hao , Wu Shih-Lin , Li Mei-Chen
Published: May 2021

Older people are very likely to fall, which is a significant threat to the health. However, falls are preventable and are not necessarily an inevitable part of aging. Many different fall detection systems have been developed to help people avoid falling. However, traditional systems based on wearable devices or image recognition-based have many disadvantages, such as user-unfriendly, privacy issues. Recently, WiFi-based fall detection systems try to solve the above problems. However, there is a common problem of reduced accuracy. Since the system is trained at the original signal collecting/training place, however, the application is at a different place. The proposed solution only extracts the features of the changed signal, which is caused by a specific human action. To implement this, we used Channel State Information (CSI) to train Convolutional Neural Networks (CNNs) and further classify the action. We have designed a prototype to test the performance of our proposed method. Our simulation results show an average accuracy of same place and different place is 93.2% and 90.3%, respectively.
Cavity Enhanced Multi-Channels Gases Raman Spectrometer
Authors: Yang Dewang , Liu Qingsheng , Guo Jinjia , Wu Lulu , Kong Andong
Published: May 2021

Raman spectroscopy has the advantages of multi-component detection, with a simple device and wide concentration ranges, and it has been applied in environmental monitoring and gas logging. However, its low sensitivity has limited its further applications. In fact, the Raman signal is not weak, but the utilization efficiency of the Raman signal is low, and most of the signal is wasted. Given this, in this paper we report a cavity-enhanced multi-channel gas Raman spectrometer with an eight-sided cuvette. First, we simulated the Raman scattering intensity at angles from 30 degrees to 150 degrees. The simulation results showed that the signal intensity at an angle of 45° is 1.4 times that observed at 90°. Based on the simulation results, we designed a three-channel sample cell for higher sensitivity. The results of these experiments showed that the sensitivity could be increased by adding all signal together, and the limit of detection (LOD) for CO2 was 75 ppm, which is better than that of each channel. This paper thus presents a new method to enhance the Raman signal, which can be used in field applications.
Energy Solutions for Wearable Sensors: A Review
Authors: Rong Guoguang , Zheng Yuqiao , Sawan Mohamad
Published: May 2021

Wearable sensors have gained popularity over the years since they offer constant and real-time physiological information about the human body. Wearable sensors have been applied in a variety of ways in clinical settings to monitor health conditions. These technologies require energy sources to carry out their projected functionalities. In this paper, we review the main energy sources used to power wearable sensors. These energy sources include batteries, solar cells, biofuel cells, supercapacitors, thermoelectric generators, piezoelectric and triboelectric generators, and radio frequency (RF) energy harvesters. Additionally, we discuss wireless power transfer and some hybrids of the above technologies. The advantages and drawbacks of each technology are considered along with the system components and attributes that make these devices function effectively. The objective of this review is to inform researchers about the latest developments in this field and present future research opportunities.
Learning from, through and about Differences: A Multiple Case Study on Schools as Practice Grounds for Citizenship
Authors: Rinnooy Kan Willemijn F. , März Virginie , Volman Monique , Dijkstra Anne Bert
Published: May 2021

Learning to relate to others that differ from you is one of the central aims of citizenship education. Schools can be understood as practice grounds for citizenship, where students’ citizenship is not only influenced by the formal curriculum, but also by their experiences in the context of teacher–student and student–student relations. In this article we therefore investigate how the practice of dealing with difference is enacted in schools. Data were collected through an exploratory multiple case study in four secondary schools, combining interviews and focus groups. Despite the differences between the schools in terms of population and location, in all schools the reflection on the enactment of ‘dealing with differences’ was limited in scope and depth. ‘Being different’ was understood primarily in terms of individual characteristics. Furthermore, in all schools there was limited reflection on being different in relation to teachers and the broader community. Finally, relevant differences for citizenship were confined to the category of ‘ethnic and cultural diversity’. This article calls for preparing teachers to consider a broader array of differences to practice dealing with differences with their students and to support students in reflecting on the societal implications of being different from each other.
Maximum Strength Benchmarks for Difficult Static Elements on Rings in Male Elite Gymnastics
Authors: Schärer Christoph , Huber Sarina , Bucher Pascal , Capelli Claudio , Hübner Klaus
Published: May 2021

On rings, in men’s artistic gymnastics, the general strength requirements for important static elements remain elusive. Therefore, the aim was to describe the relationship between a new conditioning strength test and a maximum strength test of static elements on rings in order to determine the minimal strength level (benchmarks) required to maintain these elements with one’s own body weight. Nineteen elite gymnasts performed a concentric (1RM isoinertial) and eccentric (isokinetic: 0.1 m/s) conditioning strength test for swallow/support scale (supine position) and inverted cross (seated position) on a computer-controlled device and a maximum strength test maintaining these elements for 5 s on rings with counterweight or additional weight. High correlation coefficients were found between the conditioning maximum strength for swallow/support scale (r: 0.65 to 0.92; p < 0.05) and inverted cross (r: 0.62 to 0.69; p > 0.05) and the maximum strength of the elements on rings. Strength benchmarks varied between 56.66% (inverted cross concentric) and 94.10% (swallow eccentric) of body weight. Differences in biomechanical characteristics and technical requirements of strength elements on rings may (inter alia) explain the differences between correlations. Benchmarks of conditioning strength may help coaches and athletes systematize the training of strength elements on rings.
Local Agri-Food Systems as a Cultural Heritage Strategy to Recover the Sustainability of Local Communities. Insights from the Spanish Case
Authors: Espluga-Trenc Josep , Calvet-Mir Laura , López-García Daniel , Di Masso Marina , Pomar Ariadna , Tendero Guillem
Published: May 2021

One of the factors threatening the sustainability of rural territories is the hegemonic agro-industrial model, whose environmental and social impacts strongly limit rural life. Here, we want to call attention to the opportunities provided by alternative agri-food systems, based on agroecology and food sovereignty, as a cultural heritage to support sustainable local development. We have carried out exploratory research to draft the main agroecological initiatives in Spain, particularly those having explicit support or encouragement from public administrations. An on-line questionnaire (n = 40) was delivered, and in-depth interviews (n = 15) were carried out among a sample of people working in the Spanish agroecology sector (public and private). The results demonstrate how the recovery and promotion of traditional ecological knowledge can help to increase the capacity of the social-ecological systems to cope with shocks and disturbances and maintain long-term resilience. In addition, agroecological practices allow collective identities to emerge around the characteristics of the territory strengthening local life, placing the society-ecosystem coevolution at the center of local identity. In conclusion, although still a minority, we have showed how several types of policies conceiving agroecological practices as an intangible collective heritage, with significant transformative potential towards local sustainability, have already been implemented.
The Effects of Urban and Economic Development on Coastal Zone Management
Authors: Pasquali Davide , Marucci Alessandro
Published: May 2021

The land transformation process in the last decades produced the urbanization growth in flat and coastal areas all over the world. The combination of natural phenomena and human pressure is likely one of the main factors that enhance coastal dynamics. These factors lead to an increase in coastal risk (considered as the product of hazard, exposure, and vulnerability) also in view of future climate change scenarios. Although each of these factors has been intensively studied separately, a comprehensive analysis of the mutual relationship of these elements is an open task. Therefore, this work aims to assess the possible mutual interaction of land transformation and coastal management zones, studying the possible impact on local coastal communities. The idea is to merge the techniques coming from urban planning with data and methodology coming from the coastal engineering within the frame of a holistic approach. The main idea is to relate urban and land changes to coastal management. Then, the study aims to identify if stakeholders’ pressure motivated the deployment of rigid structures instead of shoreline variations related to energetic and sedimentary balances. The influence of coastal protection (described by an indicator taking into account the linear density of the rigid protection extension alongshore) measures have been considered. Finally, the economical performances in the period just after the land transformation have been studied by means of a dimensionless index based on the concept of the local unit. The method has been applied to the case study of the Abruzzo Region. Results reveal a large urbanization growth and a generalized over-protection of the coast with a resulting spatial alternation of shoreline retreat and advance. On the other hand, the analysis of the local economy reveals that the presence of tourism activities does not necessarily lead to an increase in the local economy. Indeed, the most important improvement in local economies in the region can be associated with coastal stretches characterized by a high environmental value.
Sustainable Competitiveness of Tourism in the Algarve Region. Critical Stakeholders’ Perception of the Supply Sector
Authors: Farinha Fátima , Bienvenido-Huertas David , Duarte Pinheiro Manuel , Silva Elisa M. J. , Lança Rui , José Oliveira Miguel , Batista Ricardo
Published: May 2021

The Algarve region, located in the south of Portugal, is a well-known tourism destination that seeks to be sustainable and competitive. The local administration looks to establish a collaborative network, where stakeholders take a crucial role. The research aims to appeal to the accommodations and food services stakeholders to have a shared vision of the issues and priorities related to sustainable tourism development. Their perception is a critical factor in making decisions regarding the region’s competitiveness. Algarve’s two major and leading associations of the tourism supply sector AIHSA and AHETA were invited to participate in the study. Based on the responses of an online questionnaire, an artificial intelligence algorithm was applied to the data to identify the common and divergent aspects. The conceptual model developed is based on a simplified model of psychological ownership. The results highlight a convergent perspective regarding sustainability challenges, namely, natural resources and biodiversity, safety, and supply chain. However, hotels and restaurants do not reflect the same perception regarding sustainability initiatives, e-tourism, or free internet access. These divergences are essential results since they indicated which issues require local authorities’ priority intervention.
Cost Analysis of a Novel Method for Ecological Compensation—A Study of the Translocation of Dead Wood
Authors: Lindroos Ola , Söderlind Malin , Jensen Joel , Hjältén Joakim
Published: May 2021

Translocation of dead wood is a novel method for ecological compensation and restoration that could, potentially, provide a new important tool for biodiversity conservation. With this method, substrates that normally have long delivery times are instantly created in a compensation area, and ideally many of the associated dead wood dwelling organisms are translocated together with the substrates. However, to a large extent, there is a lack of knowledge about the cost efficiency of different methods of ecological compensation. Therefore, the costs for different parts of a translocation process and its dependency on some influencing factors were studied. The observed cost was 465 SEK per translocated log for the actual compensation measure, with an additional 349 SEK/log for work to enable evaluation of the translocation’s ecological results. Based on time studies, models were developed to predict required work time and costs for different transportation distances and load sizes. Those models indicated that short extraction and insertion distances for logs should be prioritized over road transportation distances to minimize costs. They also highlighted a trade-off between costs and time until a given ecological value is reached in the compensation area. The methodology used can contribute to more cost-efficient operations and, by doing so, increase the use of ecological compensation and the benefits from a given input.
Managing Sustainable Transitions: Institutional Innovations from India
Authors: Chebrolu Shambu Prasad , Dutta Deborah
Published: May 2021

Despite the widespread disruptions of lives and livelihoods due to the COVID-19 pandemic, it could also be seen as a gamechanger. The post-pandemic recovery should address fundamental questions concerning our food systems. Is it possible to reset existing ecologically unsustainable production systems towards healthier and more connected systems of conscious consumers and ecologically oriented farmers? Based on three illustrative cases from different parts of India, we show how managing transitions towards sustainability require institutional innovations and new intermediaries that build agency, change relations, and transform structures in food systems. Lessons from three diverse geographies and commodities in India are presented: urban farming initiatives in Mumbai, conscious consumer initiatives in semi-urban Gujarat for pesticide-free mangoes, and resource-poor arid regions of Andhra Pradesh. Through these examples, we show that, beyond the technological solutions, institutional innovations such as urban community-supported farming models, Participatory Guarantee Schemes, and Farmer Producer Organisations (FPOs) can enable sustainable transitions. Sustainable lifestyles in a post COVID-19 world, as the cases show, require collective experimentation with producers that go beyond changed consumer behaviour to transform structures in food systems.
Assessment of Ecological Vulnerability on Northern Sand Prevention Belt of China Based on the Ecological Pressure–Sensibility–Resilience Model
Authors: Li Xiufen , Song Lining , Xie Zunbo , Gao Tian , Wang Tingting , Zheng Xiao , Liu Jiang , Liu Limin
Published: May 2021

Quantitative assessment of ecological vulnerability is of great significance for ecological protection and restoration in ecologically vulnerable regions. Here, the ecological vulnerability of the northern sand prevention belt (NSPB) of China was assessed using an ecological pressure–sensibility–resilience model from 2000 to 2015. Results showed that the ecological vulnerability index (EVI) displayed low values in the eastern part and high values in the western part of the study region. The EVI ranged from 0.29 to 1.32 in 2000, with the mean value of 0.88, whereas it averaged 0.78 in 2015, ranging from 0.21 to 1.26. Decreasing EVI from 2000 to 2015 indicated that the ecological status has been improved. Moreover, the area proportion of moderately, heavily, and extremely ecological vulnerability levels occupied approximately 87% in both 2000 and 2015, indicating a high ecological vulnerability level. Furthermore, the change in area proportion of different ecological vulnerability levels were associated with the change in the spatial distribution of vegetation coverage, indicating that eco-environmental protection projects were indeed effective. These findings indicated that differential strategies in different restoration zones should be adopted, especially in the western parts of the study region, and eco-environmental protection projects should be reinforced to improve the ecological restoration.
Research on Supplier Selection of Prefabricated Building Elements from the Perspective of Sustainable Development
Authors: Song Yinghui , Wang Junwu , Guo Feng , Lu Jiequn , Liu Sen
Published: May 2021

Prefabricated building is an efficient building mode. Compared with the traditional building mode, the prefabricated building has advantages of less pollution, high construction efficiency, being more labor-saving, and economy, which is in line with China’s sustainable development strategy. This paper proposes a supplier selection evaluation model based on the mechanism equation model (SEM) and intuitionistic fuzzy analytic hierarchy process (IFAHP). Based on a detailed literature review, 300 structured questionnaires were distributed to the relevant enterprises, and an evaluation index system of prefabricated building element suppliers was built. With the fitting and modification process using a structural equation model, and assist of a path factor, an evaluation index system for evaluating the prefabricated building element suppliers was finally obtained. Finally, the intuitionistic fuzzy analytic hierarchy process was used to establish a selection model of prefabricated element suppliers, and the prefabricated element suppliers of Shuangyashan prefabricated construction projects were analyzed as a case study. The results show that the following factors have the most significant impact on supplier selection (from high to low): quality, economy, long-term cooperation, after-sales, and transportation. This study had a comprehensive consideration of the influencing factors existing in the whole selection process and should provide a valuable reference for the sustainable development of prefabricated construction engineering.
The Reuse of Excavated Soils from Construction and Demolition Projects: Limitations and Possibilities
Authors: Hale Sarah E. , Roque Antonio José , Okkenhaug Gudny , Sørmo Erlend , Lenoir Thomas , Carlsson Christel , Kupryianchyk Darya , Flyhammar Peter , Žlender Bojan
Published: May 2021

The construction and demolition of infrastructure can produce a surplus of excavated soils that ends up at landfills. This practice is not sustainable, and approaches are needed to reduce soil waste and minimize environmental and human health hazards. The “Reuse of urban soils and sites” Working Group in the European Large Geotechnical Institute Platform (ELGIP) works towards a safe and resource efficient use of excavated soils for construction. By considering relevant literature and practicals based on experience in the participating ELGIP countries (France, Norway, Portugal, Slovenia and Sweden), this study presents current practice related to the reuse of excavated soils, and the main barriers (regulatory, organizational, logistical and material quality) to effectively reuse them. Results show that there is no consensus on the best strategies to manage excavated soils in urban areas. This paper provides suggestions of ways in which stakeholders can increase reuse of excavated soils.
Energy and Exergy Analyses on Seasonal Comparative Evaluation of Water Flow Cooling for Improving the Performance of Monocrystalline PV Module in Hot-Arid Climate
Authors: Sohani Ali , Shahverdian Mohammad Hassan , Sayyaadi Hoseyn , Hoseinzadeh Siamak , Memon Saim , Piras Giuseppe , Astiaso Garcia Davide
Published: May 2021

Solar irradiation in hot-arid climatic countries results in increased temperatures, which is one of the major factors affecting the power generation efficiency of monocrystalline photovoltaic (PV) systems, posing performance and degradation challenges. In this paper, the efficiency of a water-flow cooling system to increase the output of a monocrystalline PV module with a rated capacity of 80 W is studied from both energy and exergy perspectives. The energy and exergy tests are performed for each season of the year, with and without cooling. The energy and exergy efficiencies, as well as the commodity exergy values, are used to compare the photovoltaic device with and without cooling. The findings are based on the experimental data that were collected in Tehran, Iran as an investigated case study in a country with a hot-arid climate. The findings show that when water-flow cooling is used, the values of the three efficiency metrics change significantly. In various seasons, improvements in regular average energy efficiency vary from 7.3% to 12.4%. Furthermore, the achieved increase in exergy efficiency is in the 13.0% to 19.6% range. Using water flow cooling also results in a 12.1% to 18.4% rise in product exergy.
Using Individualised HDI Measures for Predicting Educational Performance of Young Students—A Swedish Case Study
Authors: Türk Umut , Östh John , Toger Marina , Kourtit Karima
Published: May 2021

HDI is a frequently used quantitative index of human potential and welfare, developed as a comprehensive measure for the cross-sectional and temporal comparison of socioeconomic performance. The HDI is a standardised quantitative estimation of welfare comprising indicators of health, knowledge and standard of living, enabling assessment over countries, regions or time periods, in case of limited data access. The index highlights critical conditions for equity and socioeconomic development outside the group of stakeholders and researchers. The HDI provides a learning potential that may be harnessed to enhance insights into the magnitude of human potential at super-local levels. In this paper we design, implement and test the validity of a super-local variant of HDI in the context of pedagogical performance of young pupils. We compare whether HDI is a good predictor for school grades among all ninth-grade students in Sweden during the year 2014. Our results show that a super-local HDI index is performing equal to or better than the one related to standard measures of human potential, while the index can be generated on individual levels using k-nearest neighbour approaches during the index creation process.
The Role of Communication and Engagement in Airport Noise Management
Authors: Heyes Graeme , Hooper Paul , Raje Fiona , Flindell Ian , Dimitriu Delia , Galatioto Fabio , Burtea Narcisa E. , Ohlenforst Barbara , Konovalova Olena
Published: May 2021

Research suggests that non-acoustic factors can have a considerable effect on community attitudes and opinions towards aviation noise and that these can be influenced through processes of communication and engagement. This paper reviews literature from various fields to identify the key elements of effective practice, using them as a lens through which to assess case study noise management actions conducted at European airports. This analysis found that communication and engagement holds significant potential for noise management, but that this remains largely unfulfilled due to such methods being used as an ancillary management activity, rather than as a powerful tool to aid in the design and delivery of noise management actions. A series of recommendations and research priorities are proposed that could shape the future of noise management, including potential changes to European policy that more explicitly advocate for communication and engagement as a noise management tool in its own right.
Patterns for Resilient Value Creation: Perspective of the German Electrical Industry during the COVID-19 Pandemic
Authors: Neumann Konstantin , van Erp Tim , Steinhöfel Erik , Sieckmann Felix , Kohl Holger
Published: May 2021

The COVID-19 pandemic represents a massive, often unanticipated, external disruption for many companies. As a concept for responding to such disruption, organizational resilience has recently received great attention. In the organizational context, the overriding question is how companies can become more resilient. This study aims to contribute to answering this question by identifying, categorizing, and providing specific business model patterns for achieving resilience on the corporate level. For this purpose, a review of publications by major consulting firms was conducted. Patterns were extracted from publications until a convergence criterion indicated that no new pattern could be identified considering further publications. The 110 extracted unique patterns were clustered into 13 objectives, and additionally categorized according to resilience phases, as well as business model elements, to support the application in practice. The final catalog of patterns was validated through expert interviews and thus provides organizations, such as those in the electrical industry, with an overview and specific approaches on how to tackle industrial resilience through the adaption of their business model.