bluuebunny/crossref_metadata_2025 huggingface dataset:
Supervised and Weakly Supervised Deep Learning for Segmentation and Counting of Cotton Bolls Using Proximal Imagery
Authors: Adke Shrinidhi , Li Changying , Rasheed Khaled M. , Maier Frederick W.
Published: May 2022

The total boll count from a plant is one of the most important phenotypic traits for cotton breeding and is also an important factor for growers to estimate the final yield. With the recent advances in deep learning, many supervised learning approaches have been implemented to perform phenotypic trait measurement from images for various crops, but few studies have been conducted to count cotton bolls from field images. Supervised learning models require a vast number of annotated images for training, which has become a bottleneck for machine learning model development. The goal of this study is to develop both fully supervised and weakly supervised deep learning models to segment and count cotton bolls from proximal imagery. A total of 290 RGB images of cotton plants from both potted (indoor and outdoor) and in-field settings were taken by consumer-grade cameras and the raw images were divided into 4350 image tiles for further model training and testing. Two supervised models (Mask R-CNN and S-Count) and two weakly supervised approaches (WS-Count and CountSeg) were compared in terms of boll count accuracy and annotation costs. The results revealed that the weakly supervised counting approaches performed well with RMSE values of 1.826 and 1.284 for WS-Count and CountSeg, respectively, whereas the fully supervised models achieve RMSE values of 1.181 and 1.175 for S-Count and Mask R-CNN, respectively, when the number of bolls in an image patch is less than 10. In terms of data annotation costs, the weakly supervised approaches were at least 10 times more cost efficient than the supervised approach for boll counting. In the future, the deep learning models developed in this study can be extended to other plant organs, such as main stalks, nodes, and primary and secondary branches. Both the supervised and weakly supervised deep learning models for boll counting with low-cost RGB images can be used by cotton breeders, physiologists, and growers alike to improve crop breeding and yield estimation.
Delay and Energy Consumption of MQTT over QUIC: An Empirical Characterization Using Commercial-Off-The-Shelf Devices
Authors: Jeddou Sidna , Fernández Fátima , Diez Luis , Baina Amine , Abdallah Najid , Agüero Ramón
Published: May 2022

The QUIC protocol, which was originally proposed by Google, has recently gained a remarkable presence. Although it has been shown to outperform TCP over a wide range of scenarios, there exist some doubts on whether it might be an appropriate transport protocol for IoT. In this paper, we specifically tackle this question, by means of an evaluation carried out over a real platform. In particular, we conduct a thorough characterization of the performance of the MQTT protocol, when used over TCP and QUIC. We deploy a real testbed, using commercial off-the-shelf devices, and we analyze two of the most important key performance indicators for IoT: delay and energy consumption. The results evince that QUIC does not only yield a notable decrease in the delay and its variability, over various wireless technologies and channel conditions, but it does not hinder the energy consumption.
Multi-End Physics-Informed Deep Learning for Seismic Response Estimation
Authors: Ni Peng , Sun Limin , Yang Jipeng , Li Yixian
Published: May 2022

As a structural health monitoring (SHM) system can hardly measure all the needed responses, estimating the target response from the measured responses has become an important task. Deep neural networks (NNs) have a strong nonlinear mapping ability, and they are widely used in response reconstruction works. The mapping relation among different responses is learned by a NN given a large training set. In some cases, however, especially for rare events such as earthquakes, it is difficult to obtain a large training dataset. This paper used a convolution NN to reconstruct structure response under rare events with small datasets, and the main innovations include two aspects. Firstly, we proposed a multi-end autoencoder architecture with skip connections, which compresses the parameter space, to estimate the unmeasured responses. It extracts the shared patterns in the encoder and reconstructs different types of target responses in varied branches of the decoder. Secondly, the physics-based loss function, derived from the dynamic equilibrium equation, was adopted to guide the training direction and suppress the overfitting effect. The proposed NN takes the acceleration at limited positions as input. The output is the displacement, velocity, and acceleration responses at all positions. Two numerical studies validated that the proposed framework applies to both linear and nonlinear systems. The physics-informed NN had a higher performance than the ordinary NN with small datasets, especially when the training data contained noise.
Can the Output of a Learned Classification Model Monitor a Person’s Functional Recovery Status Post-Total Knee Arthroplasty?
Authors: Emmerzaal Jill , De Brabandere Arne , van der Straaten Rob , Bellemans Johan , De Baets Liesbet , Davis Jesse , Jonkers Ilse , Timmermans Annick , Vanwanseele Benedicte
Published: May 2022

Osteoarthritis is a common musculoskeletal disorder. Classification models can discriminate an osteoarthritic gait pattern from that of control subjects. However, whether the output of learned models (probability of belonging to a class) is usable for monitoring a person’s functional recovery status post-total knee arthroplasty (TKA) is largely unexplored. The research question is two-fold: (I) Can a learned classification model’s output be used to monitor a person’s recovery status post-TKA? (II) Is the output related to patient-reported functioning? We constructed a logistic regression model based on (1) pre-operative IMU-data of level walking, ascending, and descending stairs and (2) 6-week post-operative data of walking, ascending-, and descending stairs. Trained models were deployed on subjects at three, six, and 12 months post-TKA. Patient-reported functioning was assessed by the KOOS-ADL section. We found that the model trained on 6-weeks post-TKA walking data showed a decrease in the probability of belonging to the TKA class over time, with moderate to strong correlations between the model’s output and patient-reported functioning. Thus, the LR-model’s output can be used as a screening tool to follow-up a person’s recovery status post-TKA. Person-specific relationships between the probabilities and patient-reported functioning show that the recovery process varies, favouring individual approaches in rehabilitation.
Machine Learning Approach to Support the Detection of Parkinson’s Disease in IMU-Based Gait Analysis
Authors: Trabassi Dante , Serrao Mariano , Varrecchia Tiwana , Ranavolo Alberto , Coppola Gianluca , De Icco Roberto , Tassorelli Cristina , Castiglia Stefano Filippo
Published: May 2022

The aim of this study was to determine which supervised machine learning (ML) algorithm can most accurately classify people with Parkinson’s disease (pwPD) from speed-matched healthy subjects (HS) based on a selected minimum set of IMU-derived gait features. Twenty-two gait features were extrapolated from the trunk acceleration patterns of 81 pwPD and 80 HS, including spatiotemporal, pelvic kinematics, and acceleration-derived gait stability indexes. After a three-level feature selection procedure, seven gait features were considered for implementing five ML algorithms: support vector machine (SVM), artificial neural network, decision trees (DT), random forest (RF), and K-nearest neighbors. Accuracy, precision, recall, and F1 score were calculated. SVM, DT, and RF showed the best classification performances, with prediction accuracy higher than 80% on the test set. The conceptual model of approaching ML that we proposed could reduce the risk of overrepresenting multicollinear gait features in the model, reducing the risk of overfitting in the test performances while fostering the explainability of the results.
NIR Instruments and Prediction Methods for Rapid Access to Grain Protein Content in Multiple Cereals
Authors: Chadalavada Keerthi , Anbazhagan Krithika , Ndour Adama , Choudhary Sunita , Palmer William , Flynn Jamie R. , Mallayee Srikanth , Pothu Sharada , Prasad Kodukula Venkata Subrahamanya Vara , Varijakshapanikar Padmakumar , Jones Chris S. , Kholová Jana
Published: May 2022

Achieving global goals for sustainable nutrition, health, and wellbeing will depend on delivering enhanced diets to humankind. This will require instantaneous access to information on food-source quality at key points of agri-food systems. Although laboratory analysis and benchtop NIR spectrometers are regularly used to quantify grain quality, these do not suit all end users, for example, stakeholders in decentralized agri-food chains that are typical in emerging economies. Therefore, we explored benchtop and portable NIR instruments, and the methods that might aid these particular end uses. For this purpose, we generated NIR spectra for 328 grain samples from multiple cereals (finger millet, foxtail millet, maize, pearl millet, and sorghum) with a standard benchtop NIR spectrometer (DS2500, FOSS) and a novel portable NIR-based instrument (HL-EVT5, Hone). We explored classical deterministic methods (via winISI, FOSS), novel machine learning (ML)-driven methods (via Hone Create, Hone), and a convolutional neural network (CNN)-based method for building the calibrations to predict grain protein out of the NIR spectra. All of the tested methods enabled us to build relevant calibrations out of both types of spectra (i.e., R2 ≥ 0.90, RMSE ≤ 0.91, RPD ≥ 3.08). Generally, the calibration methods integrating the ML techniques tended to enhance the prediction capacity of the model. We also documented that the prediction of grain protein content based on the NIR spectra generated using the novel portable instrument (HL-EVT5, Hone) was highly relevant for quantitative protein predictions (R2 = 0.91, RMSE = 0.97, RPD = 3.48). Thus, the presented findings lay the foundations for the expanded use of NIR spectroscopy in agricultural research, development, and trade.
The Wake at the Root: Understanding Racial Identity Refinement through Genetic Ancestry Testing and Theater Performance
Authors: Heyward Devin A.
Published: May 2022

The racial identity literature has operationalized identity formation as progressive stage models, usually triggered by the experience of a negative race-based event. With the advent of new genealogical technology, it is imperative to include experiences that participants elect to experience (i.e., self-initiated or agentic encounter events). By using this perspective, identity processes become fluid and more expansive. In the context of this study, genetic ancestry tests are operationalized as a self-initiated encounter event. Participants (n = 8) were enrolled in an arts-in-education program that uses theater to explore Black Americans’ identities and family histories. This study used theater performance and modified life narrative interviews to understand how participation informed understandings of the self and others. Subsequent interviews highlighted how participants internalized the genetic test results and their participation within the group. Results indicated that, while participants were deeply invested in learning more about their ancestral roots, there were concerns related to the test results and their meaning for individuals. This study highlights that for the Black diaspora, identity is informed by ancestry and family history, as well as by interactions with created community members. Overall, this study opens the possibility for deeper exploration of racial identity formation within critical social psychology.
Minding Mental Health: Clinicians’ Engagement with Youth Suicide Prevention
Authors: Klee Katherine , Bartkowski John P.
Published: May 2022

Suicidal ideation and deaths among children and adolescents have seen an unprecedented rise over the last ten years, recently further exacerbated by the COVID-19 pandemic. This research explores mental health professionals’ approaches to delivering suicide prevention treatment services. Using insights from Giddens’ structuration theory, the study examines licensed mental health professionals’ (1) reflections on suicide prevention trainings for those in their profession, (2) appraisals of available treatment options, and (3) assessments of postvention services provided to professionals who encounter a client suicide. Additional attention was given to the structural impacts of the COVID-19 pandemic on intervention services. Data were collected through qualitative interviews with youth mental health clinicians in the state of Texas. Results underscore the interplay between structural influences and practitioner innovations in the delivery of these essential services to a vulnerable population. This study underscores the agency of mental health professionals in navigating the demands of a difficult profession.
Changes in the Mental Health Indicators and Training Opportunities for Estonian Elite Athletes Compared to the COVID-19 Isolation Period
Authors: Tamm Anna-Liisa , Parm Ülle , Aluoja Anu , Tomingas Tuuli
Published: May 2022

Background: In spring 2020, two-thirds of Estonian elite athletes had symptoms of emotional distress. The aim of this study was to evaluate the mental health indicators and training opportunities for elite Estonian athletes a year after the complete COVID-19 isolation period compared to June 2020. Methods: In both cross-sectional studies, athletes completed self-reported questionnaires, including the Emotional State Questionnaire. Descriptive statistics, t-tests, and Chi2 tests were applied to compare the study groups (p < 0.05). Results: A total of 172 out of approximately 600 elite Estonian athletes participated in the survey (102 in 2020 and 70 in 2021). More than a year after the COVID-19 lockdown period, the mental health problems of elite athletes (particularly the symptoms of depression and fatigue) are even greater concern than in June 2020, despite the recovery in training conditions and competition. Of all of the subjects, 80% had high levels of distress in 2021 compared to 36% in 2020. According to the athletes, the availability of health care services was good (78.6%), but there was a lack of close cooperation with the coach. However, the athletes considered their coaches to be their main supporters, along with their family members and partners. Only 4.3% of the respondents considered a sports psychologist to be their main supporter (n = 6). Conclusions: More than a year after the COVID-19 lockdown period, the mental health indicators of Estonian elite athletes were worrisome. Most of subjects had high levels of distress even though their training conditions had returned to normal (i.e., to as they had been before COVID-19).
Getting Started with Positive Energy Districts: Experience until Now from Maia, Reykjavik, Kifissia, Kladno and Lviv
Authors: Fatima Zarrin , Vacha Tomas , Swamygowda Kavyashree , Qubailat Reef
Published: May 2022

Cities are at the centre of the debate to mitigate climate change. A considerable number of cities have already made commitments to sustainability transitions through the introduction and integration of green strategies. Moreover, in the past few years, Europe has witnessed an increase in the development of smart cities and advancement towards creating more sustainable cities. At the moment, an innovative concept in smart city development involves Positive Energy Districts (PEDs) that further encourage districts and cities to become carbon neutral. This paper looks at the five cities of Maia, Reykjavik, Kifissia, Kladno and Lviv that are a part of an ongoing H2020 project. The purpose of the paper was to understand the status quo of energy transition in these five cities as they embarked on the PEDs journey and identify associated challenges and benefits that PEDs brought to each city. The information was collected through a knowledge gap survey, City Vision 2050 workshop, discussions during the City Forum and individual interviews with city representatives. Cities across Europe and beyond may find themselves in a similar situation, and therefore, this paper also provides brief set of checkpoints to prepare new cities for the PED journey, thus enabling them to transition towards PEDs more efficiently.
Comprehensive Measurement, Spatiotemporal Evolution, and Spatial Correlation Analysis of High-Quality Development in the Manufacturing Industry
Authors: Wang Meijuan , Yu Donghua , Chen Haiqian , Li Yang
Published: May 2022

Based on China’s provincial panel data from 2007 to 2017, this paper constructs a comprehensive indicator system for high-quality development of manufacturing from eight dimensions. Using the composite entropy weights method, kernel density estimation (KDE) and exploratory spatial data analysis (ESDA) to investigate its spatiotemporal evolution and spatial correlation characteristics. The results show that: (1) The high-quality development of the manufacturing industry shows a steady upward trend, but each dimension (subsystem) is quite different and can be divided into three types: growth type, flat type, and attenuation type. (2) The spatial distribution of the high-quality development of the manufacturing industry is highly consistent with the “Hu Huanyong Line”, and the overall layout is “high in the east and low in the west, high in the south and low in the north”. Seventy percent of the provinces are below the average level, with large interprovincial differences and significant spatial imbalance. (3) The high-quality development of the interprovincial manufacturing industry shows obvious spatial positive correlation. The hot spots are more active, and the spatial spillover effect is stronger—the Yangtze River Delta is the core, spreading outward in circles, and the main direction of diffusion is “from north to south”. In contrast, the cold spot area develops slowly and moves from south to north. Therefore, China should pay more attention to the “Botai Line”, which is perpendicular to the Hu Huanyong Line, and formulate differentiated development strategies to promote the coordinated development of the manufacturing industry.
Sustainable Circular Economy Strategies: An Analysis of Brazilian Corporate Sustainability Reporting
Authors: Sanches Julia Romano , Trevisan Adriana Hofmann , Seles Bruno Michel Roman Pais , Castro Camila Gonçalves , Piao Roberta Souza , Rozenfeld Henrique , Mascarenhas Janaina
Published: May 2022

Corporate Sustainability Reporting provides essential data for academic and empirical research on sustainability and the still-growing adoption of the circular economy by companies. Despite the wide attention that the circular economy receives from the academy, a systematization and hierarchy of the strategies that embrace the sustainable circular economy are still necessary. In addition, there is a limitation of research on the analysis of Corporate Sustainability Reporting in emerging economies. In this study, fifty sustainable circular economy strategies emerged from a systematic literature review, arranged among nine categories. The differential of the identified strategies is the expansion of strategies for a sustainable circular economy vision. Then, 51 Corporate Sustainability Reporting from 17 multinational companies operating in Brazil in 2016, 2018 and 2020 were analyzed to identify companies’ adoption of these strategies. The Corporate Sustainability Reporting analysis results suggest that companies operating in Brazil are directing significant efforts toward a sustainable circular economy. Based on these two results and the theory of business process management, we proposed the Business Process for Sustainable Circular Economy framework.
The Effects of the Crisis Management Skills and Distance Education Practices of Universities on Student Satisfaction and Organizational Image
Authors: Toklucu Ekrem , Silman Fatoş , Turan Selahattin , Atasoy Ramazan , Kalkan Ümit
Published: May 2022

In the present study, the purpose was to determine the direct and indirect effects of the crisis management skills and distance education practices of universities on student satisfaction and organizational image in the continuing Coronavirus pandemic. To conduct the study, a questionnaire was applied to 467 students who had to receive compulsory distance education at TRNC universities during the pandemic process. The relation levels between the crisis management and distance education practices of universities, corporate image, student satisfaction, and direct and indirect effects between the variables, were designed with a structural equation modeling by forming hypotheses according to the sub-dimensions of the student satisfaction scale. The findings of the study showed that as the crisis management of the university administrations in the pandemic process was perceived positively by the students, their organizational image and satisfaction increased. However, it was detected that there was a lower level of relationship between attitudes towards distance learning and crisis management, and that this had a limited effect on student satisfaction. It was concluded that the structural equation model can be used to explain the causal relationship between the variables. The study also showed that the determinants of organizational image and student satisfaction in education must be understood better and that universities must review their crisis management and distance education practices and develop new service plans.
Moderating Effect of Structural Holes on Absorptive Capacity and Knowledge-Innovation Performance: Empirical Evidence from Chinese Firms
Authors: Zhou Xiaomin
Published: May 2022

Under open innovation, the position of the innovation subject in the knowledge network plays a vital role. The purpose of this paper was to identify the role of structural holes in the relationship between the knowledge-absorption capacity and the innovation performance. Previous studies have ignored the role of structural holes in this relationship. Moreover, there are differences between structural-hole theory and weak-relationship theory on the mechanism of the network location on the innovation performance. A hierarchical regression model was applied to test the hypothesis. The findings from a study of 74 Chinese-listed integrated-circuit companies confirm the positive effect that the absorptive capacity has on the innovation performance, as well as the moderating role of structural holes in this relationship. By benefiting from the advantages of information and control, structural-hole spanners often have stronger knowledge-absorption abilities, and they thus achieve higher innovation performances. The results suggest that the synergy of structural holes should be taken seriously by those enterprises that are trying to strengthen their knowledge-absorption abilities to improve their innovation performances.
Emotional Artificial Neural Networks and Gaussian Process-Regression-Based Hybrid Machine-Learning Model for Prediction of Security and Privacy Effects on M-Banking Attractiveness
Authors: Cavus Nadire , Mohammed Yakubu Bala , Gital Abdulsalam Ya’u , Bulama Mohammed , Tukur Adamu Muhammad , Mohammed Danlami , Isah Muhammad Lamir , Hassan Abba
Published: May 2022

With recent advances in mobile and internet technologies, the digital payment market is an increasingly integral part of people’s lives, offering many useful and interesting services, e.g., m-banking and cryptocurrency. The m-banking system allows users to pay for goods, services, and earn money via cryptotrading using any device such as mobile phones from anywhere. With the recent trends in global digital markets, especially the cryptocurrency market, m-banking is projected to have a brighter future. However, information stored or conveyed via these channels is more vulnerable to different security threats. Thus, the aim of this study is to examine the influence of security and confidentiality on m-banking patronage using artificial intelligence ensemble methods (ANFIS, GPR, EANN, and BRT) for the prediction of safety and secrecy effects. AI models were trained and tested using 745 datasets obtained from the study areas. The results indicated that AI models predicted the influence of security with high precision (NSE > 0.95), with the GPR model outperformed the other models. The results indicated that security and privacy were key influential parameters of m-payment system patronage (m-banking), followed by service and interface qualities. Unlike previous m-banking studies, the study results showed ease of use and culture to have no influence on m-banking patronage. These study results would assist m-payment system stakeholders, while the approach may serve as motivation for researchers to use AI techniques. The study also provides directions for future m-banking studies.
The Spatio-Temporal Evolution of the Soil Conservation Function of Ecosystems in the North–South Transition Zone in China: A Case Study of the Qinling-Daba Mountains
Authors: Li Zhengyang , Lu Yafeng , Wang Yukuan , Liu Jia
Published: May 2022

Maintaining and improving the soil conservation function of an ecosystem is of positive significance to the sustainable and stable development of that ecosystem. We used the RUSLE model to evaluate the soil conservation function of the Qinling-Daba Mountains from 1982, 1995, 2005, and 2015 in order to analyze the spatio-temporal evolution characteristics of soil conservation. Our conclusions are as follows: (1) During the study period, the amount of average actual soil erosion in the Qinling-Daba Mountains was 955.39 × 108 t, the amount of actual soil erosion fluctuated greatly from year after year, there were obvious spatial aggregation and temporal and spatial transfer phenomena, and there was serious soil nutrient loss in the east. (2) From 1982 to 2015, soil conservation in the Qinling-Daba Mountains increased by 27.75 × 108 t during fluctuations. The soil conservation was negatively correlated with elevation and slope, and was positively correlated with vegetation coverage. (3) The average soil conservation of forest ecosystems and farmland ecosystems accounts for 78.11% of the total soil conservation, but there are differences in the ways in which to achieve soil conservation function. The order for soil conservation function of different vegetation types is crops > shrub > broad-leaved forest > coniferous forest > grass > meadow > grassland > coniferous and broad-leaved mixed forest > alpine plant > swamp. (4) The average retention of N, P and K elements in soil were 75.57 × 104 t, 25.35 × 104 t and 737.28 × 104 t, respectively. The soil elements had the consistency of spatial difference in spatial distribution and were time scaled. The soil nutrient loss in the eastern region is serious. Shrubs, broadleaf forests and crops have the greatest effect on soil nutrient retention. Alpine plants retain the greatest amount of soil nutrients per unit area. Therefore, the establishment of reasonable soil conservation strategies and scientific vegetation interplanting measures will help to enhance the soil conservation function of the Qinling-Daba Mountains ecosystem and improve the ecosystem production capacity.
Understanding the Customer Experience and Satisfaction of Casino Hotels in Busan through Online User-Generated Content
Authors: Fu Wei , Wei Shengnan , Wang Jue , Kim Hak-Seon
Published: May 2022

Casinos contribute huge sums of tax revenues to local government, and influence the local economy greatly. Customer satisfaction of casino hotels is a key factor that affects overnight customers, when evaluating the casino as a whole. To find out the determinants of customer satisfaction, along with the relationship between the key factors, this study is based on 2897 reviews, focusing on casino hotels in the Busan area, and performs a series analysis. First, text mining techniques are utilized, in order to elucidate which words were mentioned most often in online reviews. Furthermore, the semantic network method as well as factor and regression analysis were conducted. According to the findings, the top 70 ranked keywords are grouped into four clusters: “Entertainment”, “Service”, “Facilities”, and “Atmosphere”. The results of exploratory factor analysis are grouped in five factors: “Location”, “Outdoor Facilities”, ”Indoor Facilities”, “Services”, and “Entertainment”. Within these five factors, “Location” and “Outdoor Facilities” showed significantly positive impact on customer satisfaction, while “Indoor Facilities” and “Entertainment” have a significant negative influence on customer satisfaction. As a result of these findings, theoretical suggestions and practical recommendations have been made, for helping to launch the future marketing strategies of Busan casino hotels.
A Field Study on the Law of Spatiotemporal Development of Rock Movement of Under-Sea Mining, Shandong, China
Authors: Liu Jia , Ma Fengshan , Guo Jie , Li Guang , Song Yewei , Wan Yang
Published: May 2022

The phenomenon of rock movement in mining areas has always been a difficult problem in mining engineering, especially under complicated geological conditions. Although the backfilling method mitigates the destruction of the surrounding rock, deformation can still exist in the mining area. In order to ensure the safety of under-sea mining, it is necessary to study the rock movement laws and the mechanisms. This paper focuses on a settlement analysis of the monitoring data of the No. 55 prospecting profile. By analyzing the shape of the settlement curves, the spatial distribution characteristics of settlements of different mining sublevels are summarized. Additionally, the fractal characteristics of the settlement rate under different space–time conditions are studied. We also discuss the relationship between the fractal phenomenon and the self-organized criticality (SOC) theory. The findings are of great theoretical value for the further study of mining settlements to better understand the physical mechanisms of internal movement and rock mass failures through the fractal law of the settlement. Furthermore, elucidating the rock movement law is an urgent task for the safety of seabed mining.
Bridging Actors and Their Role in Co-Managing Lakes: Cases from Greater Bengaluru Metropolitan Region (GBMR)
Authors: Lakshmisha Arvind , Thiel Andreas
Published: May 2022

Co-management is seen as a means to effectively manage common-pool resources, especially collaborations based on sharing of roles and responsibilities between state and non-state actors. Collaborations depend on certain key intermediary bridging actors who facilitate and coordinate links between these actors. In this paper, we aim to understand the role of these bridging actors in shaping networks of co-management by developing a framework based on certain characteristics such as initiation, position, and facilitation of interactions whose application we illustrate for three lakes situated across a rural–urban gradient in Greater Bengaluru Metropolitan Region (GBMR). Drawing on concepts from co-management and social network analysis, we analyse data collected from documents, key informant interviews, and FGDs to identify that bridging actors play a critical role in resource gathering, enhancing mutual trust, and promoting innovation through information exchange irrespective of the social-ecological context. Beyond mere description, we highlight that state sponsorship plays an important role in establishment of bridging actors in urban and peri-urban areas due to heterogeneity in perceptions, actors, lack of trust and credibility in comparison to rural lakes where state sponsorship is less important and community engagement is stronger. We conclude that irrespective of the context, position of bridging actors plays an important role in facilitation of interactions within networks.
Consumers’ Change in Trust and Security after a Personal Data Breach in Online Shopping
Authors: Strzelecki Artur , Rizun Mariia
Published: May 2022

This research is dedicated to one of the significant problems connected with purchasing online: consumers’ personal data security. The purpose of the paper is to present the results of a study of an incident of a personal data breach from the Morele.net online store that occurred in Poland. The current gap in the literature is the lack of research done among consumers who suffered from a data breach. Data from 826 people affected by this incident were collected and used for drawing conclusions regarding the changes that took place after the incident. The data obtained are both qualitative and quantitative. The data set was analyzed using the IBM SPSS software package. The evolution in consumers’ trust towards the store was studied and results reveal that it has strongly decreased, although this did not influence consumers’ attitudes towards online shopping in general. The main finding of the research is that one out of three affected consumers will discontinue online shopping on Morele.net; however, they will not tend to change their online shopping behavior in general—they will just purchase in other online stores. Moreover, even though consumers were disappointed, and many were considering no longer purchasing from this site, the store still had significant opportunities to regain consumers’ trust and save its competitiveness in the market. The results suggest several improvements that should help online stores stay secure and trustworthy for their consumers. It was revealed that consumers had not previously been greatly concerned about their data being protected by the store; this incident, however, had changed this fact, and now consumers had become much more conscious about providing any of their data to any website.
Systems Thinking Accident Analysis Models: A Systematic Review for Sustainable Safety Management
Authors: Delikhoon Mahdieh , Zarei Esmaeil , Banda Osiris Valdez , Faridan Mohammad , Habibi Ehsanollah
Published: May 2022

Accident models are mental models that make it possible to understand the causality of adverse events. This research was conducted based on five major objectives: (i) to systematically review the relevant literature about AcciMap, STAMP, and FRAM models and synthesize the theoretical and experimental findings, as well as the main research flows; (ii) to examine the standalone and hybrid applications for modeling the leading factors of the accident and the behavior of sociotechnical systems; (iii) to highlight the strengths and weaknesses of exploring the research opportunities; (iv) to describe the safety and accident models in terms of safety-I-II-III; and finally, to investigate the impact of the systemic models’ applications in enhancing the system’s sustainability. The systematic models can identify contributory factors, functions, and relationships in different system levels which helps to increase the awareness of systems and enhance the sustainability of safety management. Furthermore, their hybrid extensions can significantly overcome the limitations of these models and provide more reliable information. Applying the safety II and III concepts and their approaches in the system can also progress their safety levels. Finally, the ethical control of sophisticated systems suggests that further research utilizing these methodologies should be conducted to enhance system analysis and safety evaluations.
Three-Dimensional Urban Morphology Transformation of Coal Mining Cities: Case Study of Tangshan
Authors: Xu Chen , Zhang Lufeng , Lan Jun , Hong Yijun
Published: May 2022

Coal mining cities in China are in a significant era of urban spatial transformation. However, most of the existing studies have ignored the three-dimensional built environment and the impact of subsidence areas on the whole city, which has made it difficult to grasp the spatial development process of coal mining cities. In this study, we defined the subsidence areas and seismic zones as unstable regions and the other areas as stable regions. On this basis, a framework of cognition and evaluation of the transformation of both regions was constructed, by using three-dimensional urban morphology types (3D-UMTs), a landscape expansion index (LEI), and an urban transformation evaluation system. Lunan District and Lubei District of Tangshan were selected as the study area, and the time range was set from 2000 to 2018. The results indicated that the whole study area had experienced inefficient urban spatial transformation during the time span. This study also proved that considering unstable regions made the evaluation of the spatial form transformation of coal mining cities more accurate. The urban transformation evaluation system is helpful to visualize and evaluate the implementation of existing policies and assist decision-makers with delineating key areas for future urban development.
Analysis of Hospital’s Emergency and Disaster Preparedness Using Hospital Safety Index in Indonesia
Authors: Lestari Fatma , Paramitasari Debby , Fatmah  , Yani Hamid Achir , Suparni  , EL-Matury Herlina J. , Wijaya Oktomi , Rahmadani Meilisa , Ismiyati Avinia , Firdausi Rizka Asshafaa , Kadir Abdul
Published: May 2022

Indonesia is country with abundant high-risk areas for various disasters that can affect both the structural and non-structural safety of various vital establishments, particularly hospitals. This present study aims to examine the level of the hospital safety index in nine hospitals in four provinces based on the guidelines from the WHO/PAHO (World Health Organization/Pan American Health Organization). The Hospital Safety Index (HSI) guidelines consist of four parameters that include the types of hazards, structural safety, non-structural safety, disasters and emergency managements. This study was a cross-sectional study on data obtained through interviews, focus group discussions (FGDs), observations, and document reviews to assess the parameters of the HSI. Data were calculated for the HSI score, and descriptive statistics and multiple correspondence analysis (MCA) were carried out. The SPSS software version 25.0 was used for the statistical analysis. Results show that the overall safety index was 0.673 (Level A), meaning that it is likely the hospital will maintain functionality in emergencies and disasters. By province, the level A index was identified in DKI Jakarta (0.76), Yogyakarta (0.709), and West Java (0.673), showing that hospitals in these provinces will maintain functionality in emergency and disaster situations; however, in North Sumatera, the index was categorized in B category (0.507), demonstrating that the hospital’s ability to function during and after emergencies and disasters is potentially at risk. The multiple correspondence analysis shows that the hospitals in the provinces of Yogyakarta and West Java tend to achieve similar categories in almost all assessment modules; therefore, control measures of preparedness should be considered, such as improvements in equipment and facilities; hospital emergency and disaster response and recovery planning; communication and information management; training; and relevant stakeholders awareness.
Evaluation of Energy Potential from Coffee Pulp in a Hydrothermal Power Market through System Dynamics: The Case of Colombia
Authors: Martínez-Ruiz Yessenia , Manotas-Duque Diego Fernando , Osorio-Gómez Juan Carlos , Ramírez-Malule Howard
Published: May 2022

Colombia has abundant solar, wind, and biomass resources for energy production with non-conventional renewable energy (NCREs) sources. However, the current participation of NCREs is negligible in the electricity mix of the country, which has historically depended on hydroelectric plants. Meteorological phenomena, such as the El Niño–Southern Oscillation (ENSO), threaten the energy supply during periods of drought, and the generation of energy using fossil fuels is necessary to offset the hydric deficit. Since Colombia is one of the largest coffee producers in the world, this study used system dynamics to evaluate the energy potential from cherry coffee pulp and analyze trends in the energy supply for different energy sources in scenarios of climatic vulnerability. First, the causal relationship of the system was identified, and the key variables of the model were projected. Then, the behavior of the system was evaluated by simulating a 120-month period. The results showed a generation potential from coffee pulp of 177 GWh per year and a power generation of 11,250 GWh and 7537 GWh with solar and wind resources, respectively, by 2030. Finally, it was confirmed that including new renewable resources is a key factor in supporting hydraulic generation in the warm phase of ENSO while reducing thermal generation dependence.
Decoupling Analysis of Net Carbon Emissions and Economic Growth of Marine Aquaculture
Authors: Guan Hongjun , Sun Zhenzhen , Wang Jingyi
Published: May 2022

Decoupling carbon emissions from economic growth is the key for the sustainable development of developing countries. Based on the panel data of marine aquaculture in China from 2010 to 2019, this paper employs the Tapio decoupling index model to analyze the decoupling characteristics of net carbon emissions and the economic growth of marine aquaculture. The logarithmic average weight decomposition method (LMDI model) and Tapio decoupling effort index model are also introduced to explore the contribution of various areas, provinces, and factors to the decoupling of net carbon emissions and the economic growth of marine aquaculture. Empirical results show that: (1) Net carbon emissions have a decoupling trend from the economic growth of marine aquaculture, but there is a large regional difference. (2) Regarding the degree of decoupling efforts, it is much stronger in the eastern and southern ocean economic zones than that in the northern ocean economic zone. (3) In terms of the decoupling contributions of various factors, carbon emission intensity > aquaculture scale > aquaculture efficiency > aquaculture structure, but there is heterogeneity among the different regions. Among the reasons for the inter-regional differences, carbon emission intensity > aquaculture scale > aquaculture structure > aquaculture efficiency. A further redundancy efficiency analysis explains the source of the differences. On this basis, strategies are proposed to improve the efficiency of marine aquaculture, including the construction of a modern three-dimensional aquaculture system, the improvement of the market-oriented mechanism, and the establishment of a modern marine aquaculture economic system.
Investigating into the Coupling and Coordination Relationship between Urban Resilience and Urbanization: A Case Study of Hunan Province, China
Authors: Xiong Yanni , Li Changyou , Zou Mengzhi , Xu Qian
Published: May 2022

In the context of accelerated urbanization, constructing resilient cities is an effective approach to tackling risks, such as extreme weather, and various urban challenges. The coupling and coordinated development of urbanization and urban resilience is a prominent embodiment of urban sustainable development and high-quality development capacity. In this study, Hunan Province, China, which is frequently affected by various disasters, is selected as a representative for examining the coupling and coordination relationship between urban resilience and urbanization level. The panel data are adopted to construct a dual-system evaluation framework integrating urban resilience and urbanization level based on the entropy weight-coefficient of variation (CV)-CRITIC method. The coupling coordination degree of this dual-system evaluation framework is calculated with the coupling model in physics and GM (1, 1) grey prediction model. Additionally, the spatial–temporal evolution characteristics of the coupling coordination degree are investigated and analyzed by ArcGIS and Geoda software. The following are indicated from the results: (1) The resilience of all cities is related to their geographical location and is characterized by a decrease from east to west; in addition, the resilience level of most cities presents a downward trend with time. (2) The urbanization level of most cities develops stably with time, but there is a growing gap in the urbanization level between regions. (3) There is a strong correlation between urban resilience and urbanization level in all cities; the unbalanced coupling and coordinated development emerge, specifically manifested by the polarization phenomenon. Eventually, a circle-difference spatial distribution pattern that starts from the central urban agglomeration and gradually decreases to the periphery is formed. (4) The prediction results of the coupling coordination degree suggest that there is an increasingly distinct polarization trend for the coupling and coordinated development between cities, and it is necessary to pay attention to those cities with a declined predicted value. (5) There is a significant positive spatial autocorrelation and agglomeration effects in the distribution of the coupling coordination degree of all cities, and the correlation is getting stronger with each passing year; the correlation mode is mainly characterized by homogeneity and supplemented by heterogeneity. Finally, several suggestions are proposed in this paper, in an attempt to lead the coordinated development of regions by novel urbanization and thus promote the sustainable development of cities. The methods and insights adopted in this study contribute to investigating the relationship between urban resilience and urbanization in China and other regions worldwide.
Laplace Transform for Solving System of Integro-Fractional Differential Equations of Volterra Type with Variable Coefficients and Multi-Time Delay
Authors: Amin Miran B. M. , Ahmad Shazad Shawki
Published: May 2022

This study is the first to use Laplace transform methods to solve a system of Caputo fractional Volterra integro-differential equations with variable coefficients and a constant multi-time delay. This technique is based on different types of kernels, which we will explain in this paper. Symmetry kernels, which have properties of difference kernels or simple degenerate kernels, are able to compute analytical work. These are demonstrated by solving certain examples and analyzing the effectiveness and precision of cause techniques.
Temporal Dynamics of the Ruminant Type I IFN-Induced Antiviral State against Homologous Parainfluenza Virus 3 Challenge In Vitro
Authors: Sun Min , Hao Fei , Li Wenliang , Cheng Zilong , Zhang Wenwen , Yang Leilei , Mao Li , Liu Maojun
Published: May 2022

Viruses have evolved diverse strategies to evade the antiviral response of interferons (IFNs). Exogenous IFNs were applied to eliminate the counteracting effect and possess antiviral properties. Caprine parainfluenza virus 3 (CPIV3) and bovine parainfluenza virus type 3 (BPIV3) are important pathogens associated with respiratory diseases in goat and cattle, respectively. To explore the feasibility of type I IFNs for control of CPIV3 and BPIV3 infection, the activated effects of IFN-stimulated genes (ISGs) and the immunomodulation responses of goat IFN-α were detected by transcriptomic analysis. Then, the antiviral efficacy of goat IFN-α and IFN-τ against CPIV3 and BPIV3 infection in MDBK cells was evaluated using different treatment routes at different infection times. The results showed that CPIV3 infection inhibited the production of type I IFNs, whereas exogenous goat IFN-α induced various ISGs, the IFN-τ encoding gene, and a negligible inflammatory response. Consequently, goat IFN-α prophylaxis but not treatment was found to effectively modulate CPIV3 and BPIV3 infection; the protective effect lasted for 1 week, and the antiviral activity was maintained at a concentration of 0.1 μg/mL. Furthermore, the antiviral activity of goat IFN-τ in response to CPIV3 and BPIV3 infection is comparable to that of goat IFN-α. These results corroborate that goat IFN-α and IFN-τ exhibit prophylactic activities in response to ruminant respiratory viral infection in vitro, and should be further investigated for a potential use in vivo.