bluuebunny/crossref_metadata_2025 huggingface dataset:
Noninvasive Electroencephalography Equipment for Assistive, Adaptive, and Rehabilitative Brain–Computer Interfaces: A Systematic Literature Review
Authors: Jamil Nuraini , Belkacem Abdelkader Nasreddine , Ouhbi Sofia , Lakas Abderrahmane
Published: July 2021

Humans interact with computers through various devices. Such interactions may not require any physical movement, thus aiding people with severe motor disabilities in communicating with external devices. The brain–computer interface (BCI) has turned into a field involving new elements for assistive and rehabilitative technologies. This systematic literature review (SLR) aims to help BCI investigator and investors to decide which devices to select or which studies to support based on the current market examination. This examination of noninvasive EEG devices is based on published BCI studies in different research areas. In this SLR, the research area of noninvasive BCIs using electroencephalography (EEG) was analyzed by examining the types of equipment used for assistive, adaptive, and rehabilitative BCIs. For this SLR, candidate studies were selected from the IEEE digital library, PubMed, Scopus, and ScienceDirect. The inclusion criteria (IC) were limited to studies focusing on applications and devices of the BCI technology. The data used herein were selected using IC and exclusion criteria to ensure quality assessment. The selected articles were divided into four main research areas: education, engineering, entertainment, and medicine. Overall, 238 papers were selected based on IC. Moreover, 28 companies were identified that developed wired and wireless equipment as means of BCI assistive technology. The findings of this review indicate that the implications of using BCIs for assistive, adaptive, and rehabilitative technologies are encouraging for people with severe motor disabilities and healthy people. With an increasing number of healthy people using BCIs, other research areas, such as the motivation of players when participating in games or the security of soldiers when observing certain areas, can be studied and collaborated using the BCI technology. However, such BCI systems must be simple (wearable), convenient (sensor fabrics and self-adjusting abilities), and inexpensive.
Object Detection and Depth Estimation Approach Based on Deep Convolutional Neural Networks
Authors: Wang Huai-Mu , Lin Huei-Yung , Chang Chin-Chen
Published: July 2021

In this paper, we present a real-time object detection and depth estimation approach based on deep convolutional neural networks (CNNs). We improve object detection through the incorporation of transfer connection blocks (TCBs), in particular, to detect small objects in real time. For depth estimation, we introduce binocular vision to the monocular-based disparity estimation network, and the epipolar constraint is used to improve prediction accuracy. Finally, we integrate the two-dimensional (2D) location of the detected object with the depth information to achieve real-time detection and depth estimation. The results demonstrate that the proposed approach achieves better results compared to conventional methods.
A Novel Robust Smart Energy Management and Demand Reduction for Smart Homes Based on Internet of Energy
Authors: Alhasnawi Bilal Naji , Jasim Basil H. , Rahman Zain-Aldeen S. A. , Siano Pierluigi
Published: July 2021

In residential energy management (REM), Time of Use (ToU) of devices scheduling based on user-defined preferences is an essential task performed by the home energy management controller. This paper devised a robust REM technique capable of monitoring and controlling residential loads within a smart home. In this paper, a new distributed multi-agent framework based on the cloud layer computing architecture is developed for real-time microgrid economic dispatch and monitoring. In this paper the grey wolf optimizer (GWO), artificial bee colony (ABC) optimization algorithm-based Time of Use (ToU) pricing model is proposed to define the rates for shoulder-peak and on-peak hours. The results illustrate the effectiveness of the proposed the grey wolf optimizer (GWO), artificial bee colony (ABC) optimization algorithm based ToU pricing scheme. A Raspberry Pi3 based model of a well-known test grid topology is modified to support real-time communication with open-source IoE platform Node-Red used for cloud computing. Two levels communication system connects microgrid system, implemented in Raspberry Pi3, to cloud server. The local communication level utilizes IP/TCP and MQTT is used as a protocol for global communication level. The results demonstrate and validate the effectiveness of the proposed technique, as well as the capability to track the changes of load with the interactions in real-time and the fast convergence rate.
Design of the UWB Positioning System Simulator for LOS/NLOS Environments
Authors: Paszek Krzysztof , Grzechca Damian , Becker Andreas
Published: July 2021

UWB is a rapidly developing technology characterised by high positioning accuracy, additional data transferability, and communication security. Low costs and energy demand makes it a system that meets the requirements of smart cities (e.g., smart mobility). The analysis of the positioning accuracy of moving objects requires a ground truth. For the UWB system, it should have an accuracy of the order of millimetres. The generated data can be used to minimize the cost and time needed to perform field tests. However, there is no UWB simulators which can consider the variable characteristics of operation along with distance to reflect the operation of real systems. This article presents a 2D UWB simulator for outdoor open-air areas with obstacles and a method of analysing data from the real UWB system under line-of-sight (LOS) and non-line-of-sight conditions. Data are recorded at predefined outdoor reference distances, and by fitting normal distributions to this data and modelling the impact of position changes the real UWB system can be simulated and it makes it possible to create virtual measurements for other locations. Furthermore, the presented method of describing the path using time-dependent equations and obstacles using a set of inequalities allows for reconstructing the real test scenario with moving tags with high accuracy.
Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future
Authors: Ahmedt-Aristizabal David , Armin Mohammad Ali , Denman Simon , Fookes Clinton , Petersson Lars
Published: July 2021

With the advances of data-driven machine learning research, a wide variety of prediction problems have been tackled. It has become critical to explore how machine learning and specifically deep learning methods can be exploited to analyse healthcare data. A major limitation of existing methods has been the focus on grid-like data; however, the structure of physiological recordings are often irregular and unordered, which makes it difficult to conceptualise them as a matrix. As such, graph neural networks have attracted significant attention by exploiting implicit information that resides in a biological system, with interacting nodes connected by edges whose weights can be determined by either temporal associations or anatomical junctions. In this survey, we thoroughly review the different types of graph architectures and their applications in healthcare. We provide an overview of these methods in a systematic manner, organized by their domain of application including functional connectivity, anatomical structure, and electrical-based analysis. We also outline the limitations of existing techniques and discuss potential directions for future research.
Multi-Modal Adaptive Fusion Transformer Network for the Estimation of Depression Level
Authors: Sun Hao , Liu Jiaqing , Chai Shurong , Qiu Zhaolin , Lin Lanfen , Huang Xinyin , Chen Yenwei
Published: July 2021

Depression is a severe psychological condition that affects millions of people worldwide. As depression has received more attention in recent years, it has become imperative to develop automatic methods for detecting depression. Although numerous machine learning methods have been proposed for estimating the levels of depression via audio, visual, and audiovisual emotion sensing, several challenges still exist. For example, it is difficult to extract long-term temporal context information from long sequences of audio and visual data, and it is also difficult to select and fuse useful multi-modal information or features effectively. In addition, how to include other information or tasks to enhance the estimation accuracy is also one of the challenges. In this study, we propose a multi-modal adaptive fusion transformer network for estimating the levels of depression. Transformer-based models have achieved state-of-the-art performance in language understanding and sequence modeling. Thus, the proposed transformer-based network is utilized to extract long-term temporal context information from uni-modal audio and visual data in our work. This is the first transformer-based approach for depression detection. We also propose an adaptive fusion method for adaptively fusing useful multi-modal features. Furthermore, inspired by current multi-task learning work, we also incorporate an auxiliary task (depression classification) to enhance the main task of depression level regression (estimation). The effectiveness of the proposed method has been validated on a public dataset (AVEC 2019 Detecting Depression with AI Sub-challenge) in terms of the PHQ-8 scores. Experimental results indicate that the proposed method achieves better performance compared with currently state-of-the-art methods. Our proposed method achieves a concordance correlation coefficient (CCC) of 0.733 on AVEC 2019 which is 6.2% higher than the accuracy (CCC = 0.696) of the state-of-the-art method.
Assessment of Eutrophication and DOC Sources Tracing in the Sea Area around Dajin Island Using CASI and MODIS Images Coupled with CDOM Optical Properties
Authors: Ma Shuchang , Zhang Xiaoyu , Xiong Yixuan , Huang Guorong , Han Yachao , Funari Valerio
Published: July 2021

The sea area around Dajin Island in the Pearl River Estuary is the second-largest habitat in China for the Indo-Pacific humpback dolphin (Sousa Chinensis). However, the rapid economic development of this area brings potential threats to the aquatic ecology around Dajin Island. Real-time monitoring and evaluation of the ecological health of the sea area are urgent. In this study, band ratio and single-band inversion algorithms were performed to obtain Chlorophyll-a (Chl-a) and Suspended Sediment Concentration (SSC), relying on both Compact Airborne Spectrographic Imager (CASI) and Moderate resolution Imaging Spectrometer (MODIS) images. The CASI/Chl-a with high spatial resolution was adopted to assess the eutrophication status, while the dissolved organic carbon (DOC) concentration and chromophoric dissolved organic matter (CDOM) optical properties were used to derive the material composition and sources. The results suggest that the study area is under a low to medium eutrophication state with evenly distributed low Chl-a concentration. However, higher Chl-a is observed in the outer estuary with MODIS/Chl-a. The relatively high DOC concentration, especially in the north, where aquaculture is practiced, and near the estuary’s main axis, i.e., east Dajin Island, indicates that the eutrophication state might be underestimated using satellite chlorophyll alone. CDOM optical properties indicated that terrestrial materials are the DOC’s primary material sources, but the DOC derived from fishery aquaculture cannot be ignored. The low Chl-a concentration is likely due to the turbulent hydrodynamic regime caused by jet flow and reciprocating flow in this marine area. Comprehensive observation, including the assessment of different technological platforms, is suggested for the aquatic environment.
The Mediating Role of Major Sport Events in Visitors’ Satisfaction, Dissatisfaction, and Intention to Revisit a Destination
Authors: Škorić Sanela , Mikulić Josip , Barišić Petra
Published: July 2021

Sport events represent a popular motive for travel and can bring a huge influx of visitors with multiple benefits for a destination. The purpose of this article is to analyze the effect of previous experience with the destination on future behavior in the form of intention to visit/revisit it and to shed more light on the relationship between visitors’ satisfaction and their future revisit intentions depending on their previous experience with the destination and the sporting event. The research setting was EuroBasket 2015, Zagreb, Croatia (EB), the largest and the most important basketball competition for national teams in Europe. A face-to-face survey with visitors of each of the 15 played games was conducted on site. In total, 765 questionnaires were collected. For the purpose of this paper, only foreign visitors (461 questionnaires) were included in the analysis. The connection between past experience and future intention to visit was tested with Pearson’s chi-squared test, differences in satisfaction levels—using the t-test for independent samples. In the next step of the analysis, we performed an analysis of impact asymmetry (IA) and of impact range (IR). The necessary input data were obtained through an OLS regression model with binary-coded dummy variables. The results showed that repeat visitors are more likely to express an intention to revisit the destination than first-time visitors, but the level of total satisfaction with EB was the same for both groups (first-time visitors and repeat visitors). The most influential event attributes for overall satisfaction were organization of EB in general, layout of the arena, and preparation of the city for the event. The study expanded the theoretical understanding of the visitors’ satisfaction with sporting event attributes as well their intention to revisit the destination.
Youth Violence and Human Security in Nigeria
Authors: Ezemenaka Kingsley Emeka
Published: July 2021

The failures of governance and statehood in Nigeria breed an anarchical or disruptive system in the state and provide a platform for youth violence and justification for disruptive behaviour against the state systems and structures. Contributing to the available research, this study shifts its focus to understand and address the linkage of disruptive behaviour by studying and discussing Human Security through the lens of youth violence in Nigeria. In doing so, this study adopts a mixed method approach of quantitative and qualitative data with Ted Robert Gurr’s theory of relative deprivation to investigate, analyse and discuss the issues herein. From the findings, cultism and ethnic factors were identified as major causes of youth violence among others. Thus, effective institutions, quality education, economic and security regional or geopolitical zones programs is noted as a means to address youth violence in Nigeria.
Do Tourism Activities and Urbanization Drive Material Consumption in the OECD Countries? A Quantile Regression Approach
Authors: Lasisi Taiwo Temitope , Eluwole Kayode Kolawole , Alola Uju Violet , Aldieri Luigi , Vinci Concetto Paolo , Alola Andrew Adewale
Published: July 2021

The United Nations Sustainable Development Goals (UNSDGs) elaborately encompass a global goal for sustainable consumption and production (Goal 12: SDGs), thus providing potential drivers and/or pathways to attaining sustainable consumption. In view of this global goal, this study examined the role of real income per capita, urbanization and especially inbound tourism in domestic material consumption for the panel of OECD countries. The study is conducted for the period of 1995 to 2016 by employing the panel quantile approach. Interestingly, an inverted U-shaped relationship between outbound tourism and domestic material consumption is established across the quantiles, thus indicating that sustainable domestic consumption is achievable after a threshold of domestic material consumption is attained. In addition, achieving sustainable consumption through economic or income growth is a herculean task for the OECD countries because the current reality indicates that income growth triggers higher consumption of domestic materials. However, the results suggest that urbanization is a recipe for sustainable domestic consumption since there is a negative and significant relationship between the two parameters across the quantiles. Nevertheless, the study presents relevant policy for efficient material and resources utilization and that is suitable to drive the SDGs for 2030 and other country-specific sustainable ambitions.
Social Sustainability as Social Learning: Insights from Multi-Stakeholder Environmental Governance
Authors: Hovardas Tasos
Published: July 2021

Social sustainability has for long been either neglected or downplayed in scientific literature and policy making and it remains an unsettled concept. The present paper critically examines several explanations for the unequal development of the social component of sustainability and suggests that social learning can serve as an insightful anchor for conceptualizing and operationalizing social sustainability. Collaborative governance is used to showcase this approach, specifically, a targeted review of multi-stakeholder schemes in natural resource management, wildlife conservation, and protected area governance. These schemes can exemplify a wide array of commonalities between the fields of social sustainability and social learning and reveal a fruitful cross-fertilization of the two concepts. The paper wishes to make two contributions. First, a specific dialectic between stakeholder collaboration and conflict under power asymmetries will be illustrated, which is characteristic in the operation of many multi-stakeholder governance schemes. Second, the need for scaffolding social learning in such schemes will be demonstrated so that a process-oriented account of social sustainability is attained. The way out offered by the present paper is that the dynamics between collaboration and conflict, properly managed by means of a toolkit with social learning templates for multi-stakeholder environmental governance schemes, may serve as a precondition for innovations sought.
On the Capability of the Epigeous Organs of Phragmites australis to Act as Metal Accumulators in Biomonitoring Studies
Authors: Baldantoni Daniela , Bellino Alessandro
Published: July 2021

With a view of shedding light on the accumulation capability of the epigeous organs of common reed (Phragmites australis), employed worldwide in metal biomonitoring, an accumulation study of Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn was performed, focusing on leaves belonging to different whorls and culms. To this end, in five sampling sites on the littoral zone of the volcanic Lake Averno (Italy), and in one occasion (autumn) before plant senescence, leaves of different ages and culms were collected and analyzed for metal concentrations. In terms of the suitability for biomonitoring, culms demonstrated poor performances in relation to the low metal accumulation and the difficulties in sampling and processing, whereas leaves proved their effectiveness in highlighting whole plant exposure. Since the accumulation degree of Cr, Cu, Fe and Zn is unaffected by leaf age, the pooling of leaves from different whorls is advisable to improve the representativeness of samplings. This strategy becomes mandatory in the case of Ni, the non-monotonic age-dependent variations of which would affect the derivation of contamination gradients otherwise. For Mn, Cd and Pb, the accumulation patterns strictly dependent on age can instead be exploited in selecting the sensitivity of biomonitoring by focusing on the organs where they are preferentially accumulated: old leaves for Mn and young leaves for Cd and Pb.
Contextualization of the Bioeconomy Concept through Its Links with Related Concepts and the Challenges Facing Humanity
Authors: Barañano Leire , Garbisu Naroa , Alkorta Itziar , Araujo Andrés , Garbisu Carlos
Published: July 2021

The concept of bioeconomy is a topic of debate, confusion, skepticism, and criticism. Paradoxically, this is not necessarily a negative thing as it is encouraging a fruitful exchange of information, ideas, knowledge, and values, with concomitant beneficial effects on the definition and evolution of the bioeconomy paradigm. At the core of the debate, three points of view coexist: (i) those who support a broad interpretation of the term bioeconomy, through the incorporation of all economic activities based on the production and conversion of renewable biological resources (and organic wastes) into products, including agriculture, livestock, fishing, forestry and similar economic activities that have accompanied humankind for millennia; (ii) those who embrace a much narrower interpretation, reserving the use of the term bioeconomy for new, innovative, and technologically-advanced economic initiatives that result in the generation of high-added-value products and services from the conversion of biological resources; and (iii) those who stand between these two viewpoints. Here, to shed light on this debate, a contextualization of the bioeconomy concept through its links with related concepts (biotechnology, bio-based economy, circular economy, green economy, ecological economics, environmental economics, etc.) and challenges facing humanity today is presented.
A Simple Way to Increase the Prediction Accuracy of Hydrological Processes Using an Artificial Intelligence Model
Authors: Meidute-Kavaliauskiene Ieva , Jabehdar Milad Alizadeh , Davidavičienė Vida , Ghorbani Mohammad Ali , Sammen Saad Sh.
Published: July 2021

Rainfall and evaporation, which are known as two complex and unclear processes in hydrology, are among the key processes in the design and management of water resource projects. The application of artificial intelligence, in comparison with physical and empirical models, can be effective in the face of the complexity of hydrological processes. The present study was prepared with the aim of increasing the accuracy in monthly prediction of rainfall (R) and pan evaporation (EP) by providing a simple solution to determining new inputs for forecasting scenarios. Initially, the prediction of two parameters, R and EP, for the current and one–three lead times, by determining the different input modes, was developed with the SVM model. Then, in order to increase the accuracy of the predictions, the month number (τ) was added to all scenarios in predicting both the R and EP parameters. The results of the intelligent model using several statistical indices (i.e., root mean square error (RMSE), Kling–Gupta (KGE) and correlation coefficient (CC)), with the help of case visual indicators, were compared. The month number (τ) was able to greatly improve the prediction accuracy of both the R and EP parameters under the SVM model and overcome the complexities within these two hydrological processes that the scenarios were not initially able to solve with high accuracy. This is proven in all time steps. According to the RMSE, KGE and CC indices, the highest increase in the forecast accuracy for the upcoming two months of rainfall (Rt+2) for Ardabil station in scenario 2 (SVM-2) was 19.1, 858 and 125%, and for the current month of pan evaporation (EPt) for Urmia station in scenario 6 (SVM-6), this occurred at the rates of 40.2, 11.1 and 7.6%, respectively. Finally, in order to investigate the characteristic of the month number in the SVM model under special conditions such as considering the highest values of the R and EP time series, it was proved that by using the month number of the SVM model, again, the accuracy could be improved (on average, 17% improvement for rainfall, and 13% for pan evaporation) in almost all time steps. Due to the wide range of effects of the two variables studied in the hydrological discussion, the results of the present study can be useful in agricultural sciences and in water management in general and will help owners.
Solar Home Systems in South Asia: Examining Adoption, Energy Consumption, and Social Practices
Authors: Ojong Nathanael
Published: July 2021

Renewable electricity generation from solar energy has rapidly increased in South Asia. This paper presents a systematic review of 79 scholarly papers on the topic of solar home system adoption, energy consumption, and social practices in South Asia. Using an intersectionality lens, the paper demonstrates that various categories of difference, such as gender, age, class, and ethnicity, intersect and shape the adoption of this technology in South Asia. Utilizing a social practice theory lens, the paper shows that solar home systems shape the spatial and temporal arrangements and practices of members of households that have adopted the technology, as well as their counterparts who have not. This technology has a practical but also symbolic function; the symbolic function and social meaning are derived from the economic and socio-cultural contexts. As this renewable energy technology is embedded in economic and socio-cultural contexts, people reconfigure it in creative ways to meet their everyday energy needs. The paper identifies research gaps and suggests future research agendas.
Spatiotemporal Assessment of Land Marketization and Its Driving Forces for Sustainable Urban–Rural Development in Shaanxi Province in China
Authors: Wei Xindong , Wang Ning , Luo Pingping , Yang Jie , Zhang Jian , Lin Kangli
Published: July 2021

In recent years, market-oriented allocation of land has been promoted to support rural revitalization and urban–rural integrated development. To follow the path of sustainable development, it is necessary to improve the efficiency of resource utilization and to rationally allocate and use resources on the premise of ensuring the sustainable use of resources. This study aims to measure the degree of land marketization in Shaanxi Province, China during the period 2008–2019 and analyze its driving forces. The methods used include Gray Relation Analysis and Hot Spot Analysis. The MK trend method was used to analyze the average area of land acquired through Bidding–Listing–Auction (B-L-A), protocol, and allocation methods. The results show that the land marketization level in Shaanxi declined from 2008 to 2014 and fluctuated upwards from 2014 to 2019. In addition, B-L-A transactions increased across the province. There was little spatial heterogeneity of land marketization, but southern Shaanxi had less land marketization than the other key areas. Urbanization, non-agricultural output, and foreign direct investment were found to be the main driving factors of land marketization, while the influence of fixed asset investment and per capita disposable income declined each year. Based on these findings, we suggest that there is a need for land management reforms and urbanization efforts to encourage land marketization in southern Shaanxi. Further, we suggest that northern Shaanxi would benefit from optimizing the land use structure and focusing on the energy land market. This study also provides theoretical support for realizing the reform of the marketization of national land elements, the healthy operation of urban land marketization, and sustainable urban and rural development.
Does Physical Activity Influence Consumer Acceptance of Gene Edited Food?
Authors: Pruitt J. Ross , Melton Kaitlyn M. , Palma Marco A.
Published: July 2021

Consumer acceptance of new and emerging food production technologies is tied to their understanding of costs and benefits of the product. Advances in bioengineering not only provide direct nutritional benefits to the consumer, but also environmental benefits that improve sustainability. Improved consumer understanding of the benefits of innovative bioengineered food products can aid in the adoption process. We track participants’ physical activity level to determine whether this trait impacts willingness to pay for bioengineered foods. Additionally, we determine whether consumers are willing to pay a premium for gene edited food relative to genetically modified food. The results indicate that there is no link between physical activity and willingness to pay for genetically edited food. Additional results suggest that there is a premium among Asian and other respondents but not by gender.
Power Distribution Network Expansion and Location Optimization of Additional Facilities: A Case Study
Authors: Javed Urooj , Ullah Saif , Imran Muhammad , Malik Asif Iqbal , Khan Nokhaiz Tariq
Published: July 2021

Planning the power distribution network is critical and challenging; the main challenges include the multiple costs involved, selecting the appropriate locations of different nodes of the network at minimal cost, and minimizing the cost of energy loss for both the primary and secondary networks. Literature on the power distribution network presents different approaches, however, lacks to address the several issues of the complex power distribution networks and many aspects are yet to be explored; for example, the uncertain cost of energy loss. This study intends to address the gaps in the literature by proposing a four-phased approach. In doing so, first, an integer linear programming model is formulated with the objective of cost minimization. Secondly, fuzzy variables are used to tackle the parameters with uncertainty; cost of energy loss. In the third phase, a fine-tuned genetic algorithm (FT-GA) that uses the Taguchi Orthogonal Array is introduced to solve the mathematical model. It is worth mentioning that during the design of the experiment, the input parameters are crossover rate, elite count, and population size. In the last phase, a pragmatic approach is adopted and a Pakistan-based case study is used to validate the proposed model and its implication in real-life scenarios. The results exhibit that our proposed approach outperforms traditional methods like the genetic algorithm (GA) and inter-point methods in terms of fitness function value, number of generations, and computational time. This research contributes at both theoretical and managerial levels and may help decision-makers to design networks more efficiently and cost-effectively in Pakistan, Asia, and beyond.
Land Use/Land Cover Changes in the Tlemcen Region (Algeria) and Classification of Fragile Areas
Authors: Bardadi Abdelkader , Souidi Zahira , Cohen Marianne , Amara Mohamed
Published: July 2021

The Tlemcen region is characterized by very diverse and steep areas exposed to gravity hazards, especially in high and medium mountain areas. Tlemcen National Park was chosen for this study, the main objective of which is to map fragile areas in close relation to reduced vegetation cover due to land-use changes and forest fires. Multi-source data were used to monitor land use/land cover (LULC)patterns in the study area between 1987 and 2017. The methodology is based on an object-oriented classification of the Landsat images, using the K nearest neighbor method for mapping the major LULC classes at the national park level. The results show that LULC is constantly changing in the study area. In 1987, the landscape was made up of (16.5%) oak forests (holm oak, cork oak, zean oak) and Aleppo pine, which then deteriorated following repeated fires in the nineties to barely represent 7.22% of the surface in 1995, followed by a fast forest reclamation, with the forest area doubling in 10 years (13.46% of the area in 2005), and a near stabilization of the forest cover in 2017 with 14.68% of the area. These mutations are mainly due to fluctuations in anthropogenic action. Despite past declines and disturbances, the current forested area in the Tlemcen area represents significant forest capital classified as a national park to be protected and developed.
The Role of B Companies in Tourism towards Recovery from the Crisis COVID-19 Inculcating Social Values and Responsible Entrepreneurship in Latin America
Authors: Acevedo-Duque Ángel , Gonzalez-Diaz Romel , Vega-Muñoz Alejandro , Fernández Mantilla Mirtha Mercedes , Ovalles-Toledo Luiz Vicente , Cachicatari-Vargas Elena
Published: July 2021

One of the particularities of companies with a social purpose is that, through their business model of B companies, they have incorporated into their processes the necessary mechanisms to obtain, simultaneously, the profits to ensure the existence of the organization in the market. At the same time, social value is generated, which is necessary to address the problems of the social crisis caused by COVID-19 and the environmental problems affecting the community. The current global health and economic crisis has opened up the possibility of adopting business model B and focusing more on the individual. Based on the grounded theory method, we have examined 3500 B Corporations in Latin America, of which 57 were examined in 10 countries listed in the Directory of B Corporations for Latin America. The main conclusions are that B Corporations dedicated to tourism through responsible entrepreneurship develop a more inclusive, sustainable and environmentally friendly economy for the benefit of society, go beyond the notion of CSR and move away from traditional business, as B Corporations combine social development and economic growth.
A Virtuous Circle of Governance Contests with Externalities
Authors: Park Sung-Hoon , Shogren Jason F.
Published: July 2021

Governments create contests to allocate resources to stakeholders, e.g., grants, contracts. The actions of these stakeholders can generate a positive externality for themselves—the contest winner can attract additional outside funding and donations from third-parties who want to jump on the winner’s bandwagon. Herein we examine the externalities arising from these contests created by governance and their impact on a virtuous circle of governance contests. Among various conditions that make governance virtuous, we focus on the equilibrium expected payoffs of stakeholders, the difference in them, and the rent-dissipation rates. Our study shows that the impact of externalities on the efficiency of governance depends on two key factors: (i) the choice of governance contests, the player-externality and the winner-externality, and (ii) the relative efficiency of stakeholders’ efforts.
Shade-Grown Coffee in Colombia Benefits Soil Hydraulic Conductivity
Authors: Lozano-Baez Sergio Esteban , Domínguez-Haydar Yamileth , Di Prima Simone , Cooper Miguel , Castellini Mirko
Published: July 2021

Secondary tropical forests and coffee agroforestry systems contain fewer trees than native forests but can positively impact soil hydrological functions, such as water infiltration compared to the pasture land that they replace. However, for both land uses it remains in how far the soil hydraulic characteristics are comparable to that of native forest. Therefore, we investigated the saturated hydraulic conductivity (Ks) and some hydrophysical soil attributes in four land-use types: (i) a shade-grown coffee; (ii) a natural regenerated forest 15 years ago; (iii) a pasture; and (iv) a reference forest, in the municipality of La Jagua de Ibirico, César department, Colombia. We determined historical land use and conducted soil sampling, using the Beerkan method to determine the Ks values. We also measured canopy cover, vegetation height, diameter at breast height and total number of trees in the forest covers. Our results indicate that Ks values were similar for the coffee and the reference forest, reflecting the positive effect of trees on soil hydrological functioning in agroforestry systems. Our results suggest that 15 years of forest regeneration after land abandonment in Sub-Andean Forest, can improve the soil hydraulic attributes. Additionally, soil water repellency was observed for the reference forest soil.
Multi-Objective Optimization to Support the Design of a Sustainable Supply Chain for the Generation of Biofuels from Forest Waste
Authors: Gutierrez-Franco Edgar , Polo Andres , Clavijo-Buritica Nicolas , Rabelo Luis
Published: July 2021

The production and supply chain management of biofuels from organic waste as raw material has been identified as a promising strategy in the field of renewable energies and circular economy initiatives. This industry involves complex tasks such as strategic land use, feedstock purchasing, production plant location, production capacity strategy, and material flows, which can be solved by mathematical modeling. The study proposed a multi-objective mixed-integer linear programming model to design a sustainable supply chain of biofuels with forest residues from its triple function: economic, environmental, and social. The trade-offs between the proposed objectives were determined with computational results. The proposed objectives were profit maximization, CO2 minimization, and employment generation maximization. Thus, the proposed model serves as a tool for decision-making, allowing the projection of a long-term structure of the biofuel supply chains and contribute to the United Nations Sustainable Development Goals.
The Effects of the Social Influence Approach on Swift Guanxi, Trust and Repurchase Intention When Considering Buyer Dependence
Authors: Wu Wen-Kuei , Huang Shu-Chin , Wu Hsiao-Chung , Shyu Maw-Liann
Published: July 2021

This study explores how social influence approaches alter buyer–seller swift guanxi, trust in the seller and repurchase intention when considering the influence of buyer dependence. Based on the results of an online survey in three cities of Taiwan, we empirically test the research model using partial least squares analysis. We found that buyer dependence exerts different but positive effects on each social influence approach usage and only the identification approach contributes to buyer–seller swift guanxi, trust in the seller and repurchase intention. The buyer–seller swift guanxi also mediates the effects of the identification approach and trust in the seller on repurchase intention. This study clarifies the role of buyer dependence on the seller’s social influence approaches and buyer–seller swift guanxi in the online C2C marketplace context. A seller should exploit buyer dependence, learn how to use each social influence approach and develop close buyer-seller swift guanxi, then repurchase intention can be secured.
DEXiAqua, a Model to Assess the Sustainability of Aquaculture Systems: Methodological Development and Application to a French Salmon Farm
Authors: Le Féon Samuel , Dubois Théo , Jaeger Christophe , Wilfart Aurélie , Akkal-Corfini Nouraya , Bacenetti Jacopo , Costantini Michele , Aubin Joël
Published: July 2021

Aquaculture is increasingly considered a major contributor to the growing demand for worldwide seafood production. Sustainability is becoming a key issue for aquaculture systems, with the objective to produce seafood with lower environmental impacts and that is economically viable and socially fair. In the context of the SIMTAP project, a multi-attribute model called DEXiAqua was developed. DEXiAqua uses the DEX method to assess the sustainability of aquaculture systems via indicators from technical domains and reference methods (i.e., life cycle assessment, life cycle costing, social life cycle assessment, and emergy accounting) selected and organized by the partners in the SIMTAP project. The DEX method consists of building an attribute tree that is organized to characterize a complex problem. Qualitative or quantitative indicators are measured at the end of each branch of the tree. The value of each indicator is translated into a qualitative scale for the associated attribute via threshold values. Weighted utility functions are used to build attributes from sub-attributes until the attribute of overall sustainability is reached. DEXiAqua was applied to a case study of salmon farming in France, which illustrated its ability to assess overall sustainability and help identify ways to improve the production system by identifying environmental, social, and economic hotspots. More case studies are required to apply DEXiAqua to a variety of systems with technical and contextual differences, which could result in changing attribute weights to adapt it better to different contexts.
Where Are the Best European Road Runners and What Are the Country Variables Related to It?
Authors: Thuany Mabliny , Pereira Sara , Hill Lee , Santos Jean Carlos , Rosemann Thomas , Knechtle Beat , Gomes Thayse Natacha
Published: July 2021

Background: The environment can play a relevant role in performance in runners. This study aimed to verify the distribution of the best European road runners across the continent, and to investigate variables related to country representatives in the European Senior outdoor top list 2019. Methods: The sample comprised 563 European runners, aged 18–48 years, ranked in the European Senior outdoor top list 2019 for distances of 10–42 km. Country-related variables were gross domestic product (GDP), competition place, population size, and sports investment. The countries were categorized as “top ten countries” or “other countries”. Binary logistic regression was used for analysis. Results: The United Kingdom showed the highest prevalence of runners in the ranking (men—17.6%; women—23.0%), followed by Spain (male ranking—12.1%) and Germany (female ranking—8.6%). For men, sports investment (OR = 1.13; CI95% = 1.03–1.28) and country GDP (OR = 0.96; CI95% = 0.93–0.98) showed an association with the chances of the athlete to reach the Top 10 ranking, while among women, the only variable significantly related was the competition venue (OR = 3.97; CI95% = 1.40–11.23). Conclusion: As in other sports considered “non-expensive”, the economic and demographic characteristics of the place where athletes train can provide advantages in performance.
Experimental Study on the Effect of Fulvic Acid in Waste Slurry on Flocculation and Zeta Potential
Authors: Yang Yi , Wu Silin , Huang Xianwen
Published: July 2021

The waste slurry produced by the dredging of urban rivers needs to be dewatered before being reused sustainably. As a large amount of plant debris accumulates in sediment, humus-like substances become one of main components in waste slurry. In light of the lack of research on the effect of fulvic acid (FA) in waste slurry on flocculation and separation, this paper carried out experimental research, including the effect of FA content on flocculation and filtration, as well as flocculation and filtration experiments of eight different sources of waste slurry. The results show that if only the FA content in the slurry is changed, the effect of FA on flocculation and separation is significant when the FA content is 0~3%, but it is not obvious when the FA content exceeds 3%. The flocculation and filtration results of eight different sources of river-dredged waste slurry are obviously different; the D10 increment can differ by nearly 10 times, and the specific resistance to filtration (SRF) differs by 2 orders of magnitude. However, FA is not a sensitive factor affecting the flocculation results. FA mainly affects the results by affecting the zeta potential of the slurry. Therefore, in the dewatering design of waste slurry, only the zeta potential needs to be considered.
Bacteria Isolated from Wastewater Irrigated Agricultural Soils Adapt to Heavy Metal Toxicity While Maintaining Their Plant Growth Promoting Traits
Authors: Ajmal Abdul Wahab , Saroosh Saleha , Mulk Shah , Hassan Muhammad Nadeem , Yasmin Humaira , Jabeen Zahra , Nosheen Asia , Shah Syed Muhammad Usman , Naz Rabia , Hasnain Zuhair , Qureshi Tariq Mahmood , Waheed Abdul , Mumtaz Saqib
Published: July 2021

The present study explored the plant growth promotion and bioremediation potential of bacteria inhabiting wastewater irrigated agricultural soils. Thirty out of 75 bacterial isolates (40%), 29/75 (39%) and 28/75 (37%) solubilized Zn, K and PO4 during plate essays respectively. Fifty-six percent of the isolates produced siderophores, while 30% released protease in vitro. Seventy-four percent of bacteria resisted Pb, Ni and Cd at various concentrations added to the culture media plates. Sixteen out of 75 (26%) isolates were able to fix N in Nbf medium. Among these 16 N fixers, N fixing nifH, nifD and nifK genes was detected through PCR in 8, 7 and 1 strain respectively using gene specific primers designed in the study with Enterobacter sp. having all three (nifHKD) genes. Isolated bacteria showed resemblance to diverse genera such as Bacillus, Pseudomonas, Enterobacter, Citrobacter, Acinetobacter, Serratia, Klebsiella and Enterococcus based on 16S rRNA gene sequence analysis. In addition to showing the best mineral solubilization and metal resistance potential, Citrobacter sp. and Enterobacter sp. also removed 87%, 79% and 43% and 86%, 78% and 51% of Ni, Cd and Pb, respectively, from aqueous solution. These potent bacteria may be exploited both for bioremediation and biofertilization of wastewater irrigated soils leading to sustainable agriculture.
Interactive Advertising on HbbTV: An Experimental Analysis of Emotions
Authors: Fondevila-Gascón Joan-Francesc , Vidal-Portés Eduard , Muñoz-Sánchez Omar , Polo-López Marc
Published: July 2021

Interactivity in television (and sustainability, thanks to virtualization) is a growing phenomenon, driven especially by the implementation of the HbbTV (hybrid broadcast broadband television) standard. Networks, media agencies and advertisers are trying to adapt to and profit from the options generated by the interaction with the viewer. Through an experimental methodology including the viewing of an advertising block which included conventional and interactive advertisements, the emotions of the viewer were collected. It was concluded that the order of the announcements is not decisive, that the emotions of anger and sadness predominate over those of joy due to a negative predisposition towards viewing advertising proposals and the content of the advertisement itself, and that less intrusive formats are more accepted.
Environmental Particulate Matter (PM) Exposure Assessment of Construction Activities Using Low-Cost PM Sensor and Latin Hypercubic Technique
Authors: Khan Muhammad , Khan Numan , Skibniewski Miroslaw J. , Park Chansik
Published: July 2021

Dust generation is generally considered a natural process in construction sites; ergo, workers are exposed to health issues due to fine dust exposure during construction work. The primary activities in the execution of construction work, such as indoor concrete and mortar mixing, are investigated to interrogate and understand the critical high particulate matter concentrations and thus health threats. Two low-cost dust sensors (Sharp GP2Y1014AU0F and Alphasense OPC N2) without implementing control measures to explicitly evaluate, compare and gauge them for these construction activities were utilized. The mean exposures to PM10, PM2.5 and PM1 during both activities were 3522.62, 236.46 and 47.62 µg/m3 and 6762.72, 471.30 and 59.09 µg/m3, respectively. The results show that PM10 and PM2.5 caused during the concrete mixing activity was approximately double compared to the mortar. The Latin Hypercube Sampling method is used to analyze the measurement results and to predict the exposure concentrations. The high dust emission and exposure from mixing activities fail to meet the World Health Organization and Health and Safety Commission standards for environmental exposure. These findings will leverage the integration of low-cost dust sensors with Building Information Modelling (BIM) to formulate a digital twin for automated dust control techniques in the construction site.
Enhancing Sustainable Inclusive Education
Authors: Lakkala Suvi , Óskarsdóttir Edda
Published: July 2021

In recent decades, inclusive education has been the focal point of many international declarations related to children’s and young people’s educational rights [...]