bluuebunny/crossref_metadata_2025 huggingface dataset:
A Wide Area Multiview Static Crowd Estimation System Using UAV and 3D Training Simulator
Authors: Shukla Shivang , Tiddeman Bernard , Miles Helen C.
Published: July 2021

Crowd size estimation is a challenging problem, especially when the crowd is spread over a significant geographical area. It has applications in monitoring of rallies and demonstrations and in calculating the assistance requirements in humanitarian disasters. Therefore, accomplishing a crowd surveillance system for large crowds constitutes a significant issue. UAV-based techniques are an appealing choice for crowd estimation over a large region, but they present a variety of interesting challenges, such as integrating per-frame estimates through a video without counting individuals twice. Large quantities of annotated training data are required to design, train, and test such a system. In this paper, we have first reviewed several crowd estimation techniques, existing crowd simulators and data sets available for crowd analysis. Later, we have described a simulation system to provide such data, avoiding the need for tedious and error-prone manual annotation. Then, we have evaluated synthetic video from the simulator using various existing single-frame crowd estimation techniques. Our findings show that the simulated data can be used to train and test crowd estimation, thereby providing a suitable platform to develop such techniques. We also propose an automated UAV-based 3D crowd estimation system that can be used for approximately static or slow-moving crowds, such as public events, political rallies, and natural or man-made disasters. We evaluate the results by applying our new framework to a variety of scenarios with varying crowd sizes. The proposed system gives promising results using widely accepted metrics including MAE, RMSE, Precision, Recall, and F1 score to validate the results.
Distinguishing Original and Non-Original Stands at the Zhanjiang Mangrove National Nature Reserve (P.R. China): Remote Sensing and GIS for Conservation and Ecological Research
Authors: Durango-Cordero Juan , Satyanarayana Behara , Chan Jonathan Cheung-Wai , Bogaert Jan , Dahdouh-Guebas Farid
Published: July 2021

The present research developed a novel methodological framework to differentiate natural mangrove stands (i.e., original), from stands which were planted and stands naturally established after interaction between planted and non-planted stands (e.g., through pollination, i.e., non-original). Ground-truth and remote sensing data were collected for Zhanjiang Mangrove National Nature Reserve (ZMNNR) in P.R. China. First, satellite images of Corona (1967) and GeoEye-1 (2009) were overlaid to identify original (1967) and non-original (2009) mangrove stands. Second, in both stands a total of 75 in situ plots (25 m2) were measured for ground-truthing of tree structural parameters including height, density, basal area and Complexity Index (CI). From temporal satellite data, we identify 236.12 ha of original mangrove and 567.88 ha of non-original mangrove in the reserve. Averaged measurements of the original mangrove stands, i.e., stem density (1164 nos. 0.1 ha−1), basal area (90.3 m2 0.1 ha−1) and CI (100.59), indicated that they were in a state of maturity and less disturbed compared to the non-original mangroves (density, 1241 nos. 0.1 ha−1; basal area, 4.92 m2 0.1 ha−1 and CI, 55.65). The Kruskal–Wallis test showed significant differentiation between the original and non-original mangrove tree structural parameters: Kandelia obovata’s density, X2 = 34.78, d.f. = 1, p = 0.001; basal area, X2 = 108.15, d.f. = 1, p = 0.001; Rizhopora stylosa’s density, X2 = 64.03, d.f. = 1, p = 0.001; basal area, X2 = 117.96, d.f. = 1, p = 0.001. The latter is also evident from the clustering plots generated from the Principal Component Analysis (PCA). Vegetation dynamics at the ZMNNR also enabled us to compare the species composition and distribution patterns with other Indo-West Pacific regions. Overall, the present study not only highlights the advantage of >50 years old satellite data but also provide a benchmark for future ecological research, conservation and management of the ZMNNR.
Deep Convolutional Neural Network for Large-Scale Date Palm Tree Mapping from UAV-Based Images
Authors: Gibril Mohamed Barakat A. , Shafri Helmi Zulhaidi Mohd , Shanableh Abdallah , Al-Ruzouq Rami , Wayayok Aimrun , Hashim Shaiful Jahari
Published: July 2021

Large-scale mapping of date palm trees is vital for their consistent monitoring and sustainable management, considering their substantial commercial, environmental, and cultural value. This study presents an automatic approach for the large-scale mapping of date palm trees from very-high-spatial-resolution (VHSR) unmanned aerial vehicle (UAV) datasets, based on a deep learning approach. A U-Shape convolutional neural network (U-Net), based on a deep residual learning framework, was developed for the semantic segmentation of date palm trees. A comprehensive set of labeled data was established to enable the training and evaluation of the proposed segmentation model and increase its generalization capability. The performance of the proposed approach was compared with those of various state-of-the-art fully convolutional networks (FCNs) with different encoder architectures, including U-Net (based on VGG-16 backbone), pyramid scene parsing network, and two variants of DeepLab V3+. Experimental results showed that the proposed model outperformed other FCNs in the validation and testing datasets. The generalizability evaluation of the proposed approach on a comprehensive and complex testing dataset exhibited higher classification accuracy and showed that date palm trees could be automatically mapped from VHSR UAV images with an F-score, mean intersection over union, precision, and recall of 91%, 85%, 0.91, and 0.92, respectively. The proposed approach provides an efficient deep learning architecture for the automatic mapping of date palm trees from VHSR UAV-based images.
Identifying and Mitigating Phishing Attack Threats in IoT Use Cases Using a Threat Modelling Approach
Authors: Abbas Syed Ghazanfar , Vaccari Ivan , Hussain Faisal , Zahid Shahzaib , Fayyaz Ubaid Ullah , Shah Ghalib A. , Bakhshi Taimur , Cambiaso Enrico
Published: July 2021

Internet of things (IoT) is a technology that enables our daily life objects to connect on the Internet and to send and receive data for a meaningful purpose. In recent years, IoT has led to many revolutions in almost every sector of our society. Nevertheless, security threats to IoT devices and networks are relentlessly disruptive, because of the proliferation of Internet technologies. Phishing is one of the most prevalent threats to all Internet users, in which attackers aim to fraudulently extract sensitive information of a user or system, using fictitious emails, websites, etc. With the rapid increase in IoT devices, attackers are targeting IoT devices such as security cameras, smart cars, etc., and perpetrating phishing attacks to gain control over such vulnerable devices for malicious purposes. In recent decades, such scams have been spreading, and they have become increasingly advanced over time. By following this trend, in this paper, we propose a threat modelling approach to identify and mitigate the cyber-threats that can cause phishing attacks. We considered two significant IoT use cases, i.e., smart autonomous vehicular system and smart home. The proposed work is carried out by applying the STRIDE threat modelling approach to both use cases, to disclose all the potential threats that may cause a phishing attack. The proposed threat modelling approach can support the IoT researchers, engineers, and IoT cyber-security policymakers in securing and protecting the potential threats in IoT devices and systems in the early design stages, to ensure the secure deployment of IoT devices in critical infrastructures.
3D Reconstruction with Single-Shot Structured Light RGB Line Pattern
Authors: Li Yikang , Wang Zhenzhou
Published: July 2021

Single-shot 3D reconstruction technique is very important for measuring moving and deforming objects. After many decades of study, a great number of interesting single-shot techniques have been proposed, yet the problem remains open. In this paper, a new approach is proposed to reconstruct deforming and moving objects with the structured light RGB line pattern. The structured light RGB line pattern is coded using parallel red, green, and blue lines with equal intervals to facilitate line segmentation and line indexing. A slope difference distribution (SDD)-based image segmentation method is proposed to segment the lines robustly in the HSV color space. A method of exclusion is proposed to index the red lines, the green lines, and the blue lines respectively and robustly. The indexed lines in different colors are fused to obtain a phase map for 3D depth calculation. The quantitative accuracies of measuring a calibration grid and a ball achieved by the proposed approach are 0.46 and 0.24 mm, respectively, which are significantly lower than those achieved by the compared state-of-the-art single-shot techniques.
Blur Kernel Estimation and Non-Blind Super-Resolution for Power Equipment Infrared Images by Compressed Sensing and Adaptive Regularization
Authors: Zhao Hongshan , Liu Bingcong , Wang Lingjie
Published: July 2021

Infrared sensing technology is more and more widely used in the construction of power Internet of Things. However, due to cost constraints, it is difficult to achieve the large-scale installation of high-precision infrared sensors. Therefore, we propose a blind super-resolution method for infrared images of power equipment to improve the imaging quality of low-cost infrared sensors. If the blur kernel estimation and non-blind super-resolution are performed at the same time, it is easy to produce sub-optimal results, so we chose to divide the blind super-resolution into two parts. First, we propose a blur kernel estimation method based on compressed sensing theory, which accurately estimates the blur kernel through low-resolution images. After estimating the blur kernel, we propose an adaptive regularization non-blind super-resolution method to achieve the high-quality reconstruction of high-resolution infrared images. According to the final experimental demonstration, the blind super-resolution method we proposed can effectively reconstruct low-resolution infrared images of power equipment. The reconstructed image has richer details and better visual effects, which can provide better conditions for the infrared diagnosis of the power system.
Systematic Review of Diagnostic Sensors for Intra-Abdominal Pressure Monitoring
Authors: Liao Chien-Hung , Cheng Chi-Tung , Chen Chih-Chi , Wang Yu-Hsin , Chiu Hsin-Tzu , Peng Cheng-Chun , Jow Uei-Ming , Lai Yen-Liang , Chen Ya-Chuan , Ho Dong-Ru
Published: July 2021

Intra-abdominal pressure (IAP) is defined as the steady-state pressure within the abdominal cavity. Elevated IAP has been implicated in many medical complications. This article reviews the current state-of-the-art in innovative sensors for the measurement of IAP. A systematic review was conducted on studies on the development and application of IAP sensors. Publications from 2010 to 2021 were identified by performing structured searches in databases, review articles, and major textbooks. Sixteen studies were eligible for the final systematic review. Of the 16 articles that describe the measurement of IAP, there were 5 in vitro studies (31.3%), 7 in vivo studies (43.7%), and 4 human trials (25.0%). In addition, with the advancement of wireless communication technology, an increasing number of wireless sensing systems have been developed. Among the studies in this review, five presented wireless sensing systems (31.3%) to monitor IAP. In this systematic review, we present recent developments in different types of intra-abdominal pressure sensors and discuss their inherent advantages due to their small size, remote monitoring, and multiplexing.
Lane Following Method Based on Improved DDPG Algorithm
Authors: He Rui , Lv Haipeng , Zhang Sumin , Zhang Dong , Zhang Hang
Published: July 2021

In an autonomous vehicle, the lane following algorithm is an important component, which is a basic function of autonomous driving. However, the existing lane following system has a few shortcomings: first, the control method it adopts requires an accurate system model, and different vehicles have different parameters, which needs a lot of parameter calibration work. The second is that it may fail on road sections where the lateral acceleration requirements of vehicles are large, such as large curves. Third, its decision-making system is defined based on rules, which has disadvantages: it is difficult to formulate; human subjective factors cannot guarantee objectivity; coverage is difficult to guarantee. In recent years, the deep deterministic policy gradient (DDPG) algorithm has been widely used in the field of autonomous driving due to its strong nonlinear fitting ability and generalization performance. However, the DDPG algorithm has overestimated state action values and large cumulative errors, low training efficiency and other issues. Therefore, this paper improves the DDPG algorithm based on the double critic networks and priority experience replay mechanism. Then this paper proposes a lane following method based on this algorithm. Experiment shows that the algorithm can achieve excellent following results under various road conditions.
Trajectory Planner CDT-RRT* for Car-Like Mobile Robots toward Narrow and Cluttered Environments
Authors: Kwon Hyunki , Cha Donggeun , Seong Jihoon , Lee Jinwon , Chung Woojin
Published: July 2021

In order to achieve the safe and efficient navigation of mobile robots, it is essential to consider both the environmental geometry and kinodynamic constraints of robots. We propose a trajectory planner for car-like robots on the basis of the Dual-Tree RRT (DT-RRT). DT-RRT utilizes two tree structures in order to generate fast-growing trajectories under the kinodynamic constraints of robots. A local trajectory generator has been newly designed for car-like robots. The proposed scheme of searching a parent node enables the efficient generation of safe trajectories in cluttered environments. The presented simulation results clearly show the usefulness and the advantage of the proposed trajectory planner in various environments.
Using Embedded Feature Selection and CNN for Classification on CCD-INID-V1—A New IoT Dataset
Authors: Liu Zhipeng , Thapa Niraj , Shaver Addison , Roy Kaushik , Siddula Madhuri , Yuan Xiaohong , Yu Anna
Published: July 2021

As Internet of Things (IoT) networks expand globally with an annual increase of active devices, providing better safeguards to threats is becoming more prominent. An intrusion detection system (IDS) is the most viable solution that mitigates the threats of cyberattacks. Given the many constraints of the ever-changing network environment of IoT devices, an effective yet lightweight IDS is required to detect cyber anomalies and categorize various cyberattacks. Additionally, most publicly available datasets used for research do not reflect the recent network behaviors, nor are they made from IoT networks. To address these issues, in this paper, we have the following contributions: (1) we create a dataset from IoT networks, namely, the Center for Cyber Defense (CCD) IoT Network Intrusion Dataset V1 (CCD-INID-V1); (2) we propose a hybrid lightweight form of IDS—an embedded model (EM) for feature selection and a convolutional neural network (CNN) for attack detection and classification. The proposed method has two models: (a) RCNN: Random Forest (RF) is combined with CNN and (b) XCNN: eXtreme Gradient Boosting (XGBoost) is combined with CNN. RF and XGBoost are the embedded models to reduce less impactful features. (3) We attempt anomaly (binary) classifications and attack-based (multiclass) classifications on CCD-INID-V1 and two other IoT datasets, the detection_of_IoT_botnet_attacks_N_BaIoT dataset (Balot) and the CIRA-CIC-DoHBrw-2020 dataset (DoH20), to explore the effectiveness of these learning-based security models. Using RCNN, we achieved an Area under the Receiver Characteristic Operator (ROC) Curve (AUC) score of 0.956 with a runtime of 32.28 s on CCD-INID-V1, 0.999 with a runtime of 71.46 s on Balot, and 0.986 with a runtime of 35.45 s on DoH20. Using XCNN, we achieved an AUC score of 0.998 with a runtime of 51.38 s for CCD-INID-V1, 0.999 with a runtime of 72.12 s for Balot, and 0.999 with a runtime of 72.91 s for DoH20. Compared to KNN, XCNN required 86.98% less computational time, and RCNN required 91.74% less computational time to achieve equal or better accurate anomaly detections. We find XCNN and RCNN are consistently efficient and handle scalability well; in particular, 1000 times faster than KNN when dealing with a relatively larger dataset-Balot. Finally, we highlight RCNN and XCNN’s ability to accurately detect anomalies with a significant reduction in computational time. This advantage grants flexibility for the IDS placement strategy. Our IDS can be placed at a central server as well as resource-constrained edge devices. Our lightweight IDS requires low train time and hence decreases reaction time to zero-day attacks.
Distributed Event Triggering Algorithm for Multi-Agent System over a Packet Dropping Network
Authors: Bemani Ali , Björsell Niclas
Published: July 2021

The availability of wireless networked control systems (WNCSs) has increased the interest in controlling multi-agent systems. Multiple feedback loops are closed over a shared communication network in such systems. An event triggering algorithm can significantly reduce network usage compared to the time triggering algorithm in WNCSs, however, the control performance is insecure in an industrial environment with a high probability of the packet dropping. This paper presents the design of a distributed event triggering algorithm in the state feedback controller for multi-agent systems, whose dynamics are subjected to the external interaction of other agents and under a random single packet drop scenario. Distributed event-based state estimation methods were applied in this work for designing a new event triggering algorithm for multi-agent systems while retaining satisfactory control performance, even in a high probability of packet drop condition. Simulation results for a multi-agent application show the main benefits and suitability of the proposed event triggering algorithm for multi-agent feedback control in WNCSs with packet drop imperfection.
Creating a Child-Friendly Environment: An Interpretation of Children’s Drawings from Planned Neighborhood Parks of Lucknow City
Authors: Agarwal Mohit Kumar , Sehgal Vandana , Ogra Aurobindo
Published: July 2021

The urban environment is a product of many tangible and intangible factors for communities, involving activities, spaces, and users of different age groups. Stakeholder consultation has become an essential part of envisaging any urban space. In general practice, mostly adults’ opinions and suggestions are taken into account, and children are sidelined, even if the issues are related to children. Children are an integral part of the present urbanizing world and are some of its most sensitive and affected users. The United Nations Convention on the Rights of the Child recognizes three P’s: provision, protection, and participation. The third, participation, is a crucial dimension of creating a healthier environment, but it has largely been neglected. The drawing technique is among the methods to gather information directly through the children’s participatory approach. It has been observed that children prefer to express themselves by drawing rather than answering questions and find it easy and enjoyable. This research incorporates drawing as a methodological tool for identifying children’s expectations and understanding their preferences about their ideal neighborhood park. A total of 80 children aged between 6 and 15 years from planned zones of Lucknow city were selected for the research. The results derived from the content and co-relation data analysis techniques highlight that children emphasized physical, perceptional, cognitive, emotional, and social parameters for developing a child-friendly environment in parks and open spaces.
Impact of In-School Suspension on Black Girls’ Math Course-Taking in High School
Authors: Ibrahim Habiba , Barnes David L. , Butler-Barnes Sheretta T. , Johnson Odis
Published: July 2021

Black girls are more likely to receive in-school suspension (ISS) in comparison to their non-Black peers. However, research on the effect of in-school suspension on students’ academic achievement, specifically math achievement of Black girls, is still very limited. Mathematics is an important foundational component of science, technology, and engineering fields, which are domains in which Black girls are underrepresented. Using the nationally representative Educational Longitudinal Study of 2002 (ELS:2002), this study explores the relationship between in-school suspension and the highest math course completed in a multi-level analysis of 860 Black female participants from 320 high schools. Our findings revealed that in-school suspension was associated with lower mathematics course-taking. Implications for policy, practice, and research are discussed.
Changes in Physical Activity during the COVID-19 Pandemic—An Analysis of Differences Based on Mitigation Policies and Incidence Values in the Federal States of Germany
Authors: Beck Franziska , Mutz Michael , Engels Eliane Stephanie , Reimers Anne Kerstin
Published: July 2021

Measures to slow down the spread of coronavirus SARS-CoV-2 have had an impact on the daily life and physical activity (PA) of many people. Nevertheless, in Germany, mitigation policies and incidence values vary widely across the federal states (Länder). Thus, the aim of the present study was to investigate regional differences in PA during the coronavirus pandemic. This study is based on the SPOVID project (Examining physical activity and sports behavior in the face of COVID-19 pandemic: a social inequality perspective) that incorporates a large-scale, representative cross-sectional survey representing the German population (≥14 years). Based on the survey that took place in October 2020 (N = 1477), we investigated the relationships between the COVID-19 incidence values as well as the mitigation policies across the federal states in Germany and changes in PA. Pearson correlations indicated a strong negative relationship between PA change and 7-day incidence values (r = −0.688 **, p = 0.009) and a moderate negative relationship between PA changes and an index of mitigation policies (r = −0.444, p = 0.112). Higher 7-day incidence values and stricter mitigation policies were associated with a stronger decline in PA levels. Therefore, it is important to support people to stay active even if there are restrictions. In particular, in federal states and regions with high incidences and stricter mitigation policies, measures to promote health-enhancing PA are necessary.
Natural Environment and Cultural Heritage in the City, a Sustainability Perspective
Authors: Kazak Jan K. , Hodor Katarzyna , Wilkosz-Mamcarczyk Magdalena
Published: July 2021

The 21st century urges us to analyze urban problems and revise its components [...]
Open and Consistent Geospatial Data on Population Density, Built-Up and Settlements to Analyse Human Presence, Societal Impact and Sustainability: A Review of GHSL Applications
Authors: Ehrlich Daniele , Freire Sergio , Melchiorri Michele , Kemper Thomas
Published: July 2021

This review analyses peer-reviewed scientific publications and policy documents that use built-up density, population density and settlement typology spatial grids from the Global Human Settlement Layer (GHSL) project to quantify human presence and processes for sustainability. Such open and free grids provide detailed time series spanning 1975–2015 developed with consistent approaches. Improving our knowledge of cities and settlements by measuring their size extent, as well as the societal processes occurring within settlements, is key to understanding their impact on the local, regional and global environment for addressing global sustainability and the integrity of planet Earth. The reviewed papers are grouped around five main topics: Quantifying human presence; assessing settlement growth over time; estimating societal impact, assessing natural hazard risk and impact, and generating indicators for international framework agreements and policy documents. This review calls for continuing to refine and expand the work on societal variables that, when combined with essential variables including those for climate, biodiversity and ocean, can improve our understanding of the societal impact on the biosphere and help to monitor progress towards local, regional and planetary sustainability.
A Framework for Urban Flood Resilience Assessment with Emphasis on Social, Economic and Institutional Dimensions: A Qualitative Study
Authors: Ghasemzadeh Behnam , Zarabadi Zahra Sadat Saeideh , Majedi Hamid , Behzadfar Mostafa , Sharifi Ayyoob
Published: July 2021

In recent years, the effects of climate change have become more noticeable in Iran, especially in big cities. In particular, climate-related flood risk is increasingly recognized as a potential threat in the capital city of Tehran. Accordingly, the present study aimed to provide a framework/assessment tool to measure Tehran’s resilience to flood risks. To this end, 21 professionals from different disciplines were selected through a purposive sampling procedure and were interviewed using semi-structured interviews. The analysis procedure resulted in the identification of 3 themes, 15 categories, 40 subcategories, and 235 codes. The themes were social, economic, and organizational; The identified categories were culture and education (since culture is something to be learned through formal and informal education this component has two features: culture and education), participation, trust, attitude, solidarity, resources, empowerment, flexibility, credit, supervision, intercommunication, rules, specialization, and research. Validation of the indicators and their usability based on the opinions of local experts was used to calibrate the assessment tool and ensure its context-sensitivity. The results of this research can help planners and policymakers to increase their awareness of flood resilience. The approach taken in this research may also be useful for developing flood resilience assessment tools in other Iranian cities as well as in other cities of the Global South with similar conditions.
Contribution of Supportive Local Communities to Sustainable Event Tourism
Authors: Li Xiubai , Kim Jinok Susanna , Lee Timothy J.
Published: July 2021

The importance of community attitude and participation for the success and sustainability of cultural festivals has been steadily increasing in recent years. The Chuncheon Puppet Festival (CPF) is an international festival that has been held every year since 1989 in Chuncheon, Korea. The festival has several distinctive characteristics as a sustainable event because: (a) it maintains its single genre of puppet performances based on modern cultural art; (b) it is well-established as the festival for the local residents of Chuncheon City and is planned by local community residents and local small companies, not by government agencies or global large entrepreneurs; (c) it helps children to have an interesting cultural experience in the local environment; and (d) it is regularly hosted in August, an off-season for festivals in Korea that was chosen by residents as it is a school holiday season. However, there is still room for improvement to secure its place as a successful sustainable festival. The following might be considered: (i) increased exchange of human resources among the festival executive members, community groups, and the public staff in Chuncheon City; (ii) local residents should maintain full control of the festival; and (iii) a local cultural trust should be established by cultural art professionals, local resident organizations, puppet show professionals, and public agency staff. The CPF is a typical example of a successful sustainable festival with proactive and supportive community participation and a large number of volunteers that help to increase local competitiveness and sustainable local development. This case report delivers insightful lessons and messages to guide what needs to be preconditioned for local cultural festivals to be sustainable and successful for a long time in many destinations, where they can contribute as efficient catalysts for regional tourism development.
Design for Deconstruction Using Integrated Lean Principles and BIM Approach
Authors: Marzouk Mohamed , Elmaraghy Ahmed
Published: July 2021

Existing buildings are characterized by the continuous change in the functional requirements of their end-users. As such, they are subjected to renovation or reconstruction, which is associated with total or partial demolition of the buildings, leading to an increase in construction and demolition waste. In addition, the materials abandoning the circular loop leave an adverse impact on the environment. This research integrates the building information modeling (BIM) approach and lean principles to ensure the early involvement of key participants in the decision-making process. This approach aids in planning the sequencing of deconstruction planning phases required before actual demolition activities take place. The paper presents the practical implementation of a BIM plug-in Tool. The assumptions and the scope based on which the plug-in was designed are briefly discussed. A case study for a mechanical, electrical, and plumbing (MEP) BIM model is introduced to illustrate the practical features of the proposed BIM plug-in Tool. The results encourage the selective dismantling of building elements based on the customers’ needs. Building information modeling capabilities in deconstruction planning were also investigated. The proposed tool aids in decreasing the uncertainties involved in demolition projects. The tool can be implemented on a national level to automate the deconstruction projects and optimize the extraction of salvaged building elements. The recovery option for such elements and their final destiny can be secured with sufficient time before their dismantling from their original locations.
Perceived Value and Its Predictive Relationship with Satisfaction and Loyalty in Ecotourism: A Study in the Posets-Maladeta Natural Park in Spain
Authors: Carrascosa-López Conrado , Carvache-Franco Mauricio , Carvache-Franco Wilmer
Published: July 2021

Ecotourism involves visiting natural areas to carry out environmentally friendly activities, contributing to environmental care. The present study aims to: (i) establish the dimensions of the perceived value in ecotourism applied to a natural park, (ii) analyze the dimensions of perceived value that predict ecotourism satisfaction, and (iii) identify the dimensions of perceived value that predict ecotourists’ intentions to return, recommend, and provide positive word of mouth about the ecotourism destination as loyalty variables. The research was conducted in the Posets-Maladeta Natural Park in Spain. The sample taken in situ consisted of 341 questionnaires. For data analysis, factor analysis and the stepwise multiple regression method were used. The results showed three dimensions of perceived value: economic, functional, and social and emotional. The “functional” value was the most significant predictor of ecotourists’ satisfaction, intentions to return, and to provide positive word of mouth. Likewise, the “functional” and the “social and emotional” dimensions were important predictors of tourists’ intentions to recommend these places. These findings will serve as management guides for different institutions and tourism service providers of protected areas to develop products according to tourists’ perceived value.
Labor Contracts, Wages and SME Failure
Authors: Dewaelheyns Nico , Van Hulle Cynthia , Van Landuyt Yannick , Verreydt Mathias
Published: July 2021

Although employment protection and employee remuneration has been shown to affect many aspects of a firm’s performance, evidence of their ability to explain firm failure is very limited. This paper examines the effect of different types of labor contracts and wages on the probability of corporate failure between 2012 and 2019 using a sample of 29,596 Belgian SMEs. Using discrete time hazard regression models, we find that the use of contract types with lower employment protection and paying lower wages are significant predictors of failure.
Multi-Objective Energy Management and Charging Strategy for Electric Bus Fleets in Cities Using Various ECO Strategies
Authors: Hasan Mohammed Mahedi , Avramis Nikos , Ranta Mikaela , Saez-de-Ibarra Andoni , El Baghdadi Mohamed , Hegazy Omar
Published: July 2021

The paper presents use case simulations of fleets of electric buses in two cities in Europe, one with a warm Mediterranean climate and the other with a Northern European (cool temperate) climate, to compare the different climatic effects of the thermal management strategy and charging management strategy. Two bus routes are selected in each city, and the effects of their speed, elevation, and passenger profiles on the energy and thermal management strategy of vehicles are evaluated. A multi-objective optimization technique, the improved Simple Optimization technique, and a “brute-force” Monte Carlo technique were employed to determine the optimal number of chargers and charging power to minimize the total cost of operation of the fleet and the impact on the grid, while ensuring that all the buses in the fleet are able to realize their trips throughout the day and keeping the battery SoC within the constraints designated by the manufacturer. A mix of four different types of buses with different battery capacities and electric motor specifications constitute the bus fleet, and the effects that they have on charging priority are evaluated. Finally, different energy management strategies, including economy (ECO) features, such as ECO-comfort, ECO-driving, and ECO-charging, and their effects on the overall optimization are investigated. The single bus results indicate that 12 m buses have a significant battery capacity, allowing for multiple trips within their designated routes, while 18 m buses only have the battery capacity to allow for one or two trips. The fleet results for Barcelona city indicate an energy requirement of 4.42 GWh per year for a fleet of 36 buses, while for Gothenburg, the energy requirement is 5 GWh per year for a fleet of 20 buses. The higher energy requirement in Gothenburg can be attributed to the higher average velocities of the bus routes in Gothenburg, compared to those of the bus routes in Barcelona city. However, applying ECO-features can reduce the energy consumption by 15% in Barcelona city and by 40% in Gothenburg. The significant reduction in Gothenburg is due to the more effective application of the ECO-driving and ECO-charging strategies. The application of ECO-charging also reduces the average grid load by more than 10%, while shifting the charging towards non-peak hours. Finally, the optimization process results in a reduction of the total fleet energy consumption of up to 30% in Barcelona city, while in Gothenburg, the total cost of ownership of the fleet is reduced by 9%.
Cadmium Uptake, In Vivo Metastasis and Subcellular Environmental Response of Five Wetland Plants Using DFT Method
Authors: Zeng Zheng , Luo Wei-Ge , Yi Fa-Cheng , Wang Zhe
Published: July 2021

The main purpose of this study is to analyze whether Cd2+ affects the absorption of Ca2+ and Fe2+ by the roots of five wetland plants and the toxic mechanism of cadmium on the subcellular structure. Five wetland plant samples were collected from the constructed wetland in the upper reaches of the Yangtze River. Based on the experiment and density function theory (DFT), we measured the Cd2+ content in the root, stem, and leaf, the morphological dimensions of plants, and in the subcellular structure the electronic activity of Cd compound was calculated to describe the stability and activity of the products. In general, Zephyranthes candida,Cynodon dactylon, Arundo donax, and Pontederia cordata have distinct cadmium uptake characteristics, while Phragmites communis does not. The results indicated tolerance to cadmium in all but Phragmites communis, which was due to cadmium distribution through the process of transpiration and a mechanical interception. The simulation results showed that Cd2+ imposed no obvious inhibition on the absorption of Ca2+ and Fe2+ in plants, as the energy barrier of the process is about 1–3 eV. Cd2+ could improve the amount of pyruvate and glucose by 30% via spd orbital hybridization, making them more chemically reactive. At the same time, Cd2+ could replace Mg2+ in chlorophyll through a copper substitution reaction, making the electron energy of chlorophyll more concentrated. As a result, the valence-band electron at −40 eV was vacant. In conclusion, we determined that Cd2+ has no obvious inhibitory effect on Ca2+ and Fe2+ in root absorption and that Cd2+ could affect the properties of compounds of the subcellular structure and thus produce physiological toxicity.
Blood, Hair and Feces as an Indicator of Environmental Exposure of Sheep, Cow and Buffalo to Cobalt: A Health Risk Perspectives
Authors: Hussain Muhammad Iftikhar , Iqbal Khan Zafar , Naeem Majida , Ahmad Kafeel , Awan Muhammad Umer Farooq , Alwahibi Mona S. , Elshikh Mohamed Soliman
Published: July 2021

Exposure to toxic metals (TMs) such as cobalt (Co) can cause lifelong carcinogenic disorders and mutagenic outcomes. TMs enter ground water and rivers from human activity, anthropogenic contamination, and the ecological environment. The present study was conducted to evaluate the influence of sewage water irrigation on cobalt (Co) toxicity and bioaccumulation in a soil-plant environment and to assess the health risk of grazing livestock via forage consumption. Cobalt is a very necessary element for the growth of plants and animals; however, higher concentrations have toxic impacts. Measurement of Co in plant, soil and water samples was conducted via wet digestion method using an atomic absorption spectrophotometer. The Co pollution severity was examined in soil, forage crops (Sorghum bicolor Kuntze, Sesbania bispinosa (Jacq.) W. Wight, Cynodon dactylon (L.) Pers., Suaeda fruticosa (L.) Forssk. and Tribulus terrestris L.) in blood, hair and feces of sheep, cow and buffalo from district Toba-Tek-Singh, Punjab, Pakistan. Three sites were selected for investigation of Co level in soil and forage samples. Highest concentration of Co was 0.65 and 0.35 mg/kg occurring in S. bicolor at site I. The sheep blood, cow hair and sheep feces samples showed highest concentrations of 0.545, 0.549 and 0.548 mg/kg, respectively at site I and site II. Bioconcentration factor, pollution load index, enrichment factor and daily intake were found to be higher (0.667, 0.124, 0.12 and 0.0007 mg/kg) in soil, S. bicolor, S. fruticosa and in buffalo, respectively, at site I. It was concluded that forage species irrigated with wastewater are safe for consumption of livestock. However, though the general values were lower than the permissible maximum limit, it was observed that the bioaccumulation in the forage species was higher. Therefore, soil and food chain components should be avoided from trace metal contamination, and other means of nonconventional water resources should be employed for forages irrigation.
Performance Evaluation of a Prestressed Belitic Calcium Sulfoaluminate Cement (BCSA) Concrete Bridge Girder
Authors: Markosian Nick , Tawadrous Raed , Mastali Mohammad , Thomas Robert J. , Maguire Marc
Published: July 2021

Belitic calcium sulfoaluminate (BCSA) cement is a sustainable alternative to Portland cement that offers rapid setting characteristics that could accelerate throughput in precast concrete operations. BCSA cements have lower carbon footprint, embodied energy, and natural resource consumption than Portland cement. However, these benefits are not often utilized in structural members due to lack of specifications and perceived logistical challenges. This paper evaluates the performance of a full-scale precast, prestressed voided deck slab bridge girder made with BCSA cement concrete. The rapid-set properties of BCSA cement allowed the initial concrete compressive strength to reach the required 4300 psi release strength at 6.5 h after casting. Prestress losses were monitored long-term using vibrating wire strain gages cast into the concrete at the level of the prestressing strands and the data were compared to the American Association of State Highway and Transportation Officials Load and Resistance Factor Design (AASHTO LRFD) predicted prestress losses. AASHTO methods for prestress loss calculation were overestimated compared to the vibrating wire strain gage data. Material testing was performed to quantify material properties including compressive strength, tensile strength, static and dynamic elastic modulus, creep, and drying and autogenous shrinkage. The material testing results were compared to AASHTO predictions for creep and shrinkage losses. The bridge girder was tested at mid-span and at a distance of 1.25 times the depth of the beam (1.25d) from the face of the support until failure. Mid-span testing consisted of a crack reopening test to solve for the effective prestress in the girder and a flexural test until failure. The crack reopen effective prestress was compared to the AASHTO prediction and AASHTO appeared to be effective in predicting losses based on the crack reopen data. The mid-span failure was a shear failure, well predicted by AASHTO LRFD. The 1.25d test resulted in a bond failure, but nearly developed based on a moment curvature estimate indicating the AASHTO bond model was conservative.
How Green Trust, Consumer Brand Engagement and Green Word-of-Mouth Mediate Purchasing Intentions
Authors: Guerreiro João , Pacheco Mariana
Published: July 2021

An increasing interest in environmental problems around the world has significantly expanded the demand for green goods, transforming green marketing into an effective tool for businesses to achieve competitive advantage. Yet, as more firms become aware of this strategic advantage, greenwashing activities can also flourish, and customers grow more cautious about green efforts by firms. The present research examines how greenwashing expectations of customers affect their green buying decisions by studying how green trust, consumer brand engagement and green word-of-mouth mediate this relationship. A total of 302 subjects participated in a survey to study greenwashing effects using a high involvement green ad and a low involvement green ad. Results were analyzed using a PLS-SEM approach. The findings show that the greenwashing expectations of customers have no direct effect on green purchase decisions, but that green trust and green word-of-mouth mediate this relationship. Likewise, greenwashing perception significantly affects customer brand engagement indirectly through green trust and there is a full mediation between greenwashing perception and green purchasing intention through green trust, customer brand engagement and green word of mouth. Therefore, the study shows that having a low perception of greenwashing is not enough to increase purchases. For that to occur, companies need to ensure that WOM communicates such efforts and that consumers trust these green initiatives.
Agent-Based Modeling for By-Product Metal Supply—A Case Study on Indium
Authors: Cao Jinjian , Choi Chul Hun , Zhao Fu
Published: July 2021

With rapid development and deployment of clean energy technology, demand for certain minor metals has increased significantly. However, many such metals are by-products of various host metals and are economically infeasible to extract independently. Meanwhile, by-product metals present in the mined ores may not be extracted even if they are sent to smelters along with host metal concentrates if it is not economically favorable for the producers. This dependency poses potential supply risks to by-product metals. Indium is a typical by-product metal, mainly from zinc mining and refining, and is important for flat panel displays, high efficiency lighting, and emerging thin-film solar panel production. Current indium supply–demand forecast models tend to overlook the volatile and competitive nature of minor metal market and are mostly based on top-down approaches. Therefore, a bottom-up agent-based model can shed new light on the market dynamics and possible outcome of future indium supply–demand relationship. A multi-layered model would also be helpful for identifying possible bottlenecks of indium supply and finding solutions. This work takes indium as an example of minor metal market and sets up an agent-based model to predict future market situation and supply–demand balance. The market is modeled as a Cournot competition oligopolistic market by refineries with capacity restriction based on host metal production. The model maintains active Nash equilibrium each year to simulate competitions between suppliers. The model is validated and verified by historical data and sensitivity analysis. Several scenarios are also explored to illustrate possible uncertainties of the market.
The Impact of Indoor Living Wall System on Air Quality: A Comparative Monitoring Test in Building Corridors
Authors: Shao Yiming , Li Jiaqiang , Zhou Zhiwei , Zhang Fan , Cui Yuanlong
Published: July 2021

Living wall systems have been widely recognized as one of the promising approaches for building applications due to their aesthetic value and ecological benefits. Compared with outdoor living wall systems, indoor living wall systems (ILWS) play a more vital role in indoor air quality. The aim of this study is to investigate the effects of ILWS on indoor air quality. In an office building, two parallel corridors were selected as comparative groups. A 10.6 m2 ILWS was installed on the sidewall of the west corridor while the east corridor was empty. Some important parameters, including indoor air temperature, relative humidity, concentrations of carbon dioxide (CO2), and particulate matter (PM) were obtained based on the actual environment monitoring. According to the statistical analysis of the data, there were significant differences in the concentrations of CO2 and PMs in the corridors with and without ILWS, which indicated that CO2 and PM2.5 removal rate ranged from 12% to 17% and 8% to 14%, respectively. The temperature difference is quite small (0.13 °C on average), while relative humidity slightly increased by 3.1–6.4% with the presence of the ILWS.
Intellectual Capital and Sustainable Economic Performance in the Public Sector: The Context of the New Public Management in Malaysia
Authors: Kamaruddin Kardina , Abeysekera Indra
Published: July 2021

The New Public Management allows us to reflect upon whether intellectual capital helps public sector organisations meet their performance benchmarks. Sustainable economic performance gains importance from the public sector’s service ideal. Although there have been empirical endeavours using intellectual capital as operational variables, this study examines the theoretically informed relationship between the intellectual capital construct and its construct dimensions and the sustainable economic performance construct and its construct dimensions. The decision-making inputs of senior officials in the Malaysian public sector are vital for evaluating the relationship, as these officials are the individual strategists of the collective organisational strategy. The study conducted a survey that received 1092 usable responses and analysed them using the structural equation modelling research method. The findings showed a robust theoretical relationship between intellectual capital and sustainable economic performance. Furthermore, the study identified intellectual capital items that play a vital role in supporting public sector sustainable economic performance in Malaysia under New Public Management. The findings provide useful knowledge for public sector officials and policymakers, and for further research.