bluuebunny/crossref_metadata_2025 huggingface dataset:
The Reinstatement of Returnees in District Swat, Pakistan: An Evaluative Study of the Rehabilitation Initiatives
Authors: Rafiq Muhammad , Hassan Asan Ali Golam , Saeed Muhammad
Published: December 2021

This study attempted to develop a happiness index tool for evaluating rehabilitation initiatives used to reinstate returnees at district Swat, Pakistan. The Happiness Index (HI) tool compares two periods, i.e., HI before rehabilitation (BR) and HI after rehabilitation (AR). The returnees’ happiness index (RHI) is also compared with Pakistan’s Happiness Index to identify the difference. Data for this study were elicited from 382 respondents through a structured survey questionnaire. The results show that after rehabilitation (AR), the returnees’ happiness index improved from 3.89 to 5.36, which is still less than the world happiness index of Pakistan, i.e., 5.65 in 2019. This study concluded that rehabilitation projects had a significantly positive impact on the HI of the returnees. However, more effective and sustainable initiatives are required to align the RHI to the HI of Pakistan. Further, the RHI tool adopted by this study is significant for measuring the happiness of the marginalized and affected people in Pakistan and beyond.
A Multi-Stage Stochastic Programming Model for the Multi-Echelon Multi-Period Reverse Logistics Problem
Authors: Azizi Vahid , Hu Guiping
Published: December 2021

Reverse logistics planning plays a crucial role in supply chain management. Stochasticity in different parameters along with time horizon can be a challenge in solving reverse logistics problems. This paper proposes a multi-stage, multi-period reverse logistics with lot sizing decisions under uncertainties. The main uncertain factors are return and demand quantities, and return quality. Moment matching method was adopted to generate a discrete set of scenarios to represent the original continuous distribution of stochastic parameters. Fast forward selection algorithm was employed to select the most representative scenarios and facilitate computational tractability. A case study was conducted and optimal solution of the recursive problem obtained by solving extensive form. Sensitivity analysis was implemented on different elements of stochastic solution. Results sow that solution of recursive problem (RP) outperforms the solution obtained from the problem with expected values of uncertain parameters (EEV).
On Comparing Cross-Validated Forecasting Models with a Novel Fuzzy-TOPSIS Metric: A COVID-19 Case Study
Authors: de Souza Dalton Garcia Borges , dos Santos Erivelton Antonio , Alves Júnior Francisco Tarcísio , Nascimento Mariá Cristina Vasconcelos
Published: December 2021

Time series cross-validation is a technique to select forecasting models. Despite the sophistication of cross-validation over single test/training splits, traditional and independent metrics, such as Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), are commonly used to assess the model’s accuracy. However, what if decision-makers have different models fitting expectations to each moment of a time series? What if the precision of the forecasted values is also important? This is the case of predicting COVID-19 in Amapá, a Brazilian state in the Amazon rainforest. Due to the lack of hospital capacities, a model that promptly and precisely responds to notable ups and downs in the number of cases may be more desired than average models that only have good performances in more frequent and calm circumstances. In line with this, this paper proposes a hybridization of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and fuzzy sets to create a similarity metric, the closeness coefficient (CC), that enables relative comparisons of forecasting models under heterogeneous fitting expectations and also considers volatility in the predictions. We present a case study using three parametric and three machine learning models commonly used to forecast COVID-19 numbers. The results indicate that the introduced fuzzy similarity metric is a more informative performance assessment metric, especially when using time series cross-validation.
Role of a Mine in Changing Its Surroundings—Land Use and Land Cover and Impact on the Natural Environment in Barapukuria, Bangladesh
Authors: Arifeen Hossain Mohammad , Chowdhury Md. Shahariar , Zhang Haoran , Suepa Tanita , Amin Nowshad , Techato Kuaanan , Jutidamrongphan Warangkana
Published: December 2021

Land use and land cover (LULC) change is considered among the most discussed issues associated with development nowadays. It is necessary to provide factual and up-to-date information to policymakers to fulfil the increasing population’s food, work, and habitation needs while ensuring environmental sustainability. Geographical Information System (GIS) and Remote sensing can perform such work adequately. This study aims to assess land use and land cover changes concerning the Barapukuria coal mine and its adjacent areas in Bangladesh by applying remote sensing and GIS (geographical information system) techniques. This research work used time-series satellite images from the Landsat 7 ETM+ satellite between 1999 and 2009 and the Landsat 8 OLI/TIRS satellite for 2019. Supervised classification maximum likelihood classifier matrix was implemented using ERDAS Imagine 2018. The images were categorised into four definite classes: settlement, agricultural land, forest land, and waterbody. Analytical results clearly indicated that settlements and agricultural land had increasing and decreasing trends over the past 20 years, respectively. Settlements increased from 22% to 34% between 1999 and 2019. However, agricultural land reduced from 69% to 59% in the same period. Settlements grew by more than 50% during this period. The research had an overall accuracy of 70%, while the kappa coefficient was more than 0.60. There were land subsidence issues because of mining activities, leading to 1.003 km2 area being depressed and 1500 houses cracked. This research depicts the present LULC scenario and the impact of the coalfield area. It is expected to reduce the burden on policymakers to prepare a proper and effective mines development policy in Bangladesh and meet sustainable development goal (SDG) 15 (Life on land).
Multi-Objective Optimization for Sustainable Supply Chain and Logistics: A Review
Authors: Jayarathna Chamari Pamoshika , Agdas Duzgun , Dawes Les , Yigitcanlar Tan
Published: December 2021

There are several methods available for modeling sustainable supply chain and logistics (SSCL) issues. Multi-objective optimization (MOO) has been a widely used method in SSCL modeling (SSCLM), nonetheless selecting a suitable optimization technique and solution method is still of interest as model performance is highly dependent on decision-making variables of the model development process. This study provides insights from the analysis of 95 scholarly articles to identify research gaps in the MOO for SSCLM and to assist decision-makers in selecting suitable MOO techniques and solution methods. The results of the analysis indicate that economic and environmental aspects of sustainability are the main context of SSCLM, where the social aspect is still limited. More SSCLMs for sourcing, distribution, and transportation phases of the supply chain are required. Additionally, more sophisticated techniques and solution methods, including hybrid metaheuristics approaches, are needed in SSCLM.
Beyond Flood Preparedness: Effects of Experience, Trust, and Perceived Risk on Preparation Intentions and Financial Risk-Taking in China
Authors: Zhang Keshun , Parks-Stamm Elizabeth J. , Ji Yaqi , Wang Haiyan
Published: December 2021

Flooding, already the most damaging type of natural disaster in China, is expected to become increasingly costly around the world. However, few studies have examined residents’ flood-preparedness intentions and the effect of flood experience and other variables on general financial risk-taking. This study explored the effects of Chinese residents’ previous flood experiences, trust in public flood protection, and flood-risk perception on flood-preparedness intentions and attitudes towards financial risk-taking in general. Study 1 surveyed residents in a flooded area (n = 241) and a non-flooded area (n = 248); Study 2 surveyed a non-flooded area (n = 1599). The relations between the variables were tested through structural-equation modelling (SEM). Overall, the two studies found that residents’ flood experiences, trust in public protection, and flood-risk perception not only predicted their flood preparedness but also their financial risk aversion. This study highlights the importance of residents’ trust in public flood protection for flood risk management and communication, especially for those who have not yet experienced flooding.
Grey Wolf Optimizer-Based Array Reconfiguration to Enhance Power Production from Solar Photovoltaic Plants under Different Scenarios
Authors: Kumar Astitva , Rizwan Mohammad , Nangia Uma , Alaraj Muhannad
Published: December 2021

The extraction of maximum power is a big challenge in solar photovoltaic-based power plants due to varying atmospheric and meteorological parameters. The concept of array reconfiguration is applied for the maximum power extraction in solar PV plants. Using this approach, the occurrence of multiple peaks in P-V and I-V characteristics during partial shade can be smoothened and reduced significantly. Partial shading due to the movement of the cloud is considered in the research. The cloud movement mainly because of velocity and wind direction is used for creating various shading conditions. The main focus is to reduce the power losses during partial shading using a nature-inspired optimization approach to reconfigure the array for different types of shading conditions. A grey wolf optimizer-based bridge-linked total cross-tied (GWO-BLTCT) configuration is proposed in this paper. The performance of the proposed topology is compared with standard and hybrid topologies, namely, series-parallel, total cross-tied, BLTCT, and SuDoKu-BLTCT, based on performance indicators such as fill factor, performance ratio, power enhancement, and power loss. The proposed GWO-BLTCT outperforms the remaining topologies due to the least power loss and high fill factor. It also has the highest average power enhancement and performance ratio with 23.75% and 70.02% respectively.
Analysis of the Satisfaction Degree of Students at Spain’s Physiotherapy Universities in Relation to Online Teaching during the COVID-19 Pandemic
Authors: Escobio-Prieto Isabel , Sobrino-Sánchez Raquel , Mingorance José Antonio , García-Marín Manuel , Matas-Terrón Antonio , Albornoz-Cabello Manuel
Published: December 2021

Student satisfaction is a crucial aspect in the quality assessment of higher education. The aim of the present study was to assess the degree of satisfaction among students in the Faculties of physiotherapy throughout Spain concerning online teaching during the State of Emergency due to the COVID-19 pandemic. This was a quantitative study with a cross-sectional observational design. The online questionnaire DISFISCOVID was distributed to 24 physiotherapy faculties across Spain. A sample of 348 physiotherapy students from 14 Spanish universities completed the questionnaire. It showed high reliability evidence, achieving Cronbach’s alpha indices higher than 0.870, alongside a McDonald’s ωH of 0.876. On the whole, students were not satisfied with online learning during the State of Emergency, considering it unsuitable for their learning in either the theoretical or practical field of subjects in the degree of physiotherapy. In conclusion, the perception of physiotherapy students concerning the teaching they received, as far as practical contents and assessment methods are concerned, was not very satisfactory in those Faculties in which online learning platforms were not being used beforehand, and was more satisfactory when teaching was carried out in-person in the classroom.
Associations of Voluntary Exercise and Screen Time during the First Wave of COVID-19 Restrictions in Japan with Subsequent Grip Strength among University Students: J-Fit+ Study
Authors: Shen Shaoshuai , Suzuki Koya , Kohmura Yoshimitsu , Fuku Noriyuki , Someya Yuki , Miyamoto-Mikami Eri , Ke Dandan , Machida Shuich , Aoki Kazuhiro , Naito Hisashi
Published: December 2021

This study aimed to examine the combined effect of voluntary exercise and screen time during the first wave of the coronavirus disease 2019 (COVID-19) restrictions on subsequent grip strength among health and sports science students in Japan. The participants performed grip strength tests and had their weight assessed on 21 October 2020. Furthermore, they completed an online survey between 21 October and 28 October 2020, which included participants’ current age, height, voluntary exercise, and screen time during the first wave of the COVID-19 pandemic (April and May 2020). In total, 380 participants provided complete data (mean age ± standard deviation [SD]: 18.8 ± 0.6 years; 233 males). Our results revealed that 87.6% of male students and 84.4% of female students performed voluntary exercise >1 day/week during the first wave of the pandemic. Moreover, 21.5% of male students and 23.1% of female students had >8 h/day of screen time. A trend toward greater grip strength was observed for both male and female students with high voluntary exercise and low screen time. In particular, grip strength (p < 0.05) was significantly greater in male students with high voluntary exercise and low screen time than those with low voluntary exercise and high screen time. In conclusion, this study revealed that during the first wave of COVID-19 restrictions, a combination of high voluntary exercise and low screen time positively affected the subsequent grip strength of health and sports science students.
Implications of Urban Land Management on the Cooling Properties of Urban Trees: Citizen Science and Laboratory Analysis
Authors: Ngao Jérôme , Cárdenas Macarena L. , Améglio Thierry , Colin Jérôme , Saudreau Marc
Published: December 2021

Trees participate in mitigating the urban heat island phenomenon thanks to their transpiration and shading. This cooling potential is highly dependent on leaf area. Nevertheless, leaf traits potentially vary across different land management practices in urban settings, thereby challenging the models used to estimate thermal budgets. The present study aims to investigate the variability of leaf area traits of linden (Tilia spp.) urban trees, and their effect on simulated tree transpiration. Reconstruction of the leaf area was undertaken at the tree scale at three different urban land management sites from three cities: London and Birmingham (UK) and Chantilly (France). The reconstruction combined allometric measurements at shoot and leaf scales, and a tree-scale 3D digitization with laboratory analysis using field data collected by citizen scientists. The management practices had a significant impact on leaf area, and on tree allometric relationships, which were propagated through the reconstruction process. Relative differences between the management practices ranged between 12% and 48% according to the city where the variable was considered (e.g., leaf area index, total leaf area, or tree transpiration). Trees in managed sites (i.e., individualized leaf crowns, frequent leaf litter removal, and standard thinning/pruning operations) develop a higher leaf area, thus promoting cooling potential. This study shows that the variability of leaf traits, and their responses to different land management, can be studied by comprehensive data collection through citizen science and lab-based modelling. It also highlights the importance of appropriate, well-designed urban planning, where landscaping using urban trees can play an even better role in climate proofing cities.
Comparative Analysis of Three Governance Modes for Resource-Based Urban Sustainability in China Based on Residents’ Perception: An Empirical Study of Pingdingshan City, Henan Province, China
Authors: Li Xiaofan , Yang Yongchun , Meng Qingmin
Published: December 2021

With the continuous improvement and deepened reform of institutional mechanisms in resource-based cities (RBCs) in China, mining areas have become significant urban brownfields with typical geological hazards that cause serious pollution and other disasters like landslides and subsidence. Therefore, the governance of mining areas becomes a grant challenge for local governments to sustain urban development, and different governance approaches could result in diverse effects on urban sustainability, which have not been studied in current research. In the last twenty years, the governance model of mining areas in RBCs in China can be classified into government governance model (GGM), joint governance model (JGM), and market governance model (MGM). Based on the traditional theories, we innovatively propose a structural measurement and mechanism analysis of mine management efficiency from the perspective of residents’ perceptions by designing structural equation modeling (SEM) for spatial distribution issues. The main objective is to disclose the comparative advantages of three different mine governance models and the prerequisites and considerations for the application of the three governance models in the institutional environment with Chinese characteristics, in addition to the answers of pros and cons of the three types of governance models. We find: (1) the GGM plays a necessary, positive, and effective role in guiding the governance process, and has a high level of resident satisfaction in relation to the public interest of the masses, but a problem is that the favorable groups in the implementation process mainly include the middle and senior officers. (2) The JGM as a transition and supplement to the GGM, and many large serious governance problems that cannot be solved by the GGM are reasonably solved by JGM. Lastly (3), the MGM is very different from the above two governance models, as it just concentrates on the governance of storage, transportation, and public lands within mining areas that are directly relevant to enterprises’ benefits. It indicates the urgent reforming needs of current governance models for efficient governance by integrating government, enterprise, and local communities.
Machine Learning Application to Eco-Friendly Concrete Design for Decarbonisation
Authors: Lavercombe Abigail , Huang Xu , Kaewunruen Sakdirat
Published: December 2021

Cement replacement materials can not only benefit the workability of the concrete but can also improve its compressive strength. Reducing the cement content of concrete can also lower CO2 emissions to mitigate the impact of the construction industry on the environment and improve energy consumption. This paper aims to predict the compressive strength (CS) and embodied carbon (EC) of cement replacement concrete using machine learning (ML) algorithms, i.e., deep neural network (DNN), support vector regression (SVR), gradient boosting regression (GBR), random forest (RF), k-nearest neighbors (kNN), and decision tree regression (DTR). Not only is producing an optimal ML model helpful for predicting accurate results, but it also saves time, energy, and costs, compared to conducting experiments. Firstly, 367 pieces of experimental datasets from the open literature were collected, in which cement was replaced with any of the cementitious materials. Secondly, the datasets were imported into the ML models, whose parameters were tuned by the grid search algorithm (GSA). Then, the prediction performance, the coefficient of determination (R2), the prediction accuracy, and the root mean square error (RMSE) were employed to indicate the prediction ability of the ML models. The results demonstrate that the GBR models perform the best prediction of the CS and EC. The R2 of the GBR models for predicting the CS and EC are 0.946 and 0.999, respectively. Thus, it can be concluded that the GBR models have promising abilities for design assistance in cement replacement concrete. Finally, a sensitivity analysis (SA) was conducted in this paper to analyse the effects of the inputs on the CS and EC of the cement replacement concrete. Pulverised fuel ash (PFA), blast-furnace slag (GGBS), Expanded perlite (EP), and Silica fume (SF) were noticed to affect the CS and EC of cement replacement concrete significantly.
Artificial Intelligence-Driven Digital Technologies to the Implementation of the Sustainable Development Goals: A Perspective from Brazil and Portugal
Authors: Pigola Angélica , da Costa Priscila Rezende , Carvalho Luísa Cagica , Silva Luciano Ferreira da , Kniess Cláudia Terezinha , Maccari Emerson Antonio
Published: December 2021

Innovativeness is a characteristic of digital technologies (DT), and they have been assuming an important role in economic, social, and environmental dimensions. Therefore, DT are relevant contributors for sustainable development goal (SDG) achievements. This study aims to compare the preference for artificial intelligence-driven digital technologies (AI-Driven DT) to achieve SDGs in Brazil and Portugal. An independent sample t-test analysis and Levene test are performed to identify potential artificial intelligence-driven digital technologies (AI-Driven DT) as favorable facilitators for SDG achievements in Brazil and Portugal. Based on the findings, a broader analysis is provided, to (i) indicate potential favorable SDGs, (ii) discuss differences between the countries in AI-Driven DT preferences in each SDG, and (iii) make recommendations for potential technologies that could receive more attention and investments in both regions to make emergent digital technologies succeed, with a particular emphasis on cleaner production. The analysis is organized into three dimensions: economic, social, and environment. At the end, a closing discussion is provided about the key guidelines and prospects that could be adopted to keep a strong and positive shift of AI-Driven DT developments and applications towards fully supporting the attainment of the SDG of United Nations Organization (ONU) Agenda 2030.
Examining Emotional Labor in COVID-19 through the Lens of Self-Efficacy
Authors: Yao Lixia , Gao Jie
Published: December 2021

The ongoing COVID-19 pandemic has dealt a significant blow to the restaurant industry, with many restaurants suspending operations or closing altogether. This study was aimed to investigate the effects of emotional labor on employees’ well-being and the mediating role of self-efficacy in the context of chain restaurants. Data were collected in 2020 through an online survey in China, and results revealed that emotional labor had a significant impact on well-being that was measured in life and job satisfaction. Self-efficacy not only had a significant positive impact on employees’ job- and life-related well-being but also played a fully mediating role between deep acting and life satisfaction, with a partial mediating role between deep acting and job satisfaction. Job-related well-being also played a fully mediating role between deep acting and life satisfaction, with a partial mediating role between deep acting and job satisfaction. It is important for restaurant employees to develop deep acting skills and improve self-efficacy and job satisfaction Restaurant managers must establish a healthy working environment by providing better job support and creating a more relaxed working atmosphere.
Effect of Chief Executive Officer’s Sustainable Leadership Styles on Organization Members’ Psychological Well-Being and Organizational Citizenship Behavior
Authors: Choi Hyun-ju
Published: December 2021

Situational leadership theory and the contingency approach of leadership were utilized and applied based on situational theory. Based on a total of four foundational theories, that is, bottom-up spillover theory, theories of prosocial behavior, and so on, this study empirically analyzed what influence a chief executive officer’s (CEO’s) sustainable leadership styles (servant, ethical, and authentic leadership) have on the psychological well-being and organizational citizenship behaviors of organization members. The study was conducted on adult employees of midsized or larger companies (including subsidiaries) across four countries: South Korea, the United Kingdom, the United States, and South Africa. Data were obtained from 649 adult employees. SmartPLS was used to conduct structural equation modeling analysis of the data. The results were as follows: (1) CEOs’ servant and authentic leadership styles had statistically significant positive (+) effects on employees’ psychological well-being; however, ethical leadership did not. (2) CEOs’ ethical leadership had a statistically significant (+) effect on employees’ organizational citizenship behavior; however, servant and authentic leadership did not. (3) Employees’ psychological well-being had a statistically significant (+) effect on organizational citizenship behavior. CEOs are attracting more attention than ever, leading companies in today’s rapidly changing times. This suggests that it is necessary to comprehend principles that show when, where, and how important leaders are and sustainable leadership styles that can increase their chances of success. Moreover, this study derived constructive implications that a leader can overcome today’s challenges through sustainable leadership styles.
Zeroth-Order Nucleation Transition under Nanoscale Phase Separation
Authors: Yukalov Vyacheslav I. , Yukalova Elizaveta P.
Published: December 2021

Materials with nanoscale phase separation are considered. A system representing a heterophase mixture of ferromagnetic and paramagnetic phases is studied. After averaging over phase configurations, a renormalized Hamiltonian is derived describing the coexisting phases. The system is characterized by direct and exchange interactions and an external magnetic field. The properties of the system are studied numerically. The stability conditions define the stable state of the system. At a temperature of zero, the system is in a pure ferromagnetic state. However, at finite temperature, for some interaction parameters, the system can exhibit a zeroth-order nucleation transition between the pure ferromagnetic phase and the mixed state with coexisting ferromagnetic and paramagnetic phases. At the nucleation transition, the finite concentration of the paramagnetic phase appears via a jump.
Functional Model of a Self-Driving Car Control System
Authors: Sviatov Kirill , Yarushkina Nadejda , Kanin Daniil , Rubtcov Ivan , Jitkov Roman , Mikhailov Vladislav , Kanin Pavel
Published: December 2021

The article describes a structural and functional model of a self-driving car control system, which generates a wide class of mathematical problems. Currently, control systems for self-driving cars are considered at several levels of abstraction and implementation: Mechanics, electronics, perception, scene recognition, control, security, integration of all subsystems into a solid system. Modern research often considers particular problems to be solved for each of the levels separately. In this paper, a parameterized model of the integration of individual components into a complex control system for a self-driving car is considered. Such a model simplifies the design and development of self-driving control systems with configurable automation tools, taking into account the specifics of the solving problem. The parameterized model can be used for CAD design in the field of self-driving car development. A full cycle of development of a control system for a self-driving truck was implemented, which was rub in the “Robocross 2021” competition. The software solution was tested on more than 40 launches of a self-driving truck. Parameterization made it possible to speed up the development of the control system, expressed in man-hours, by 1.5 times compared to the experience of the authors of the article who participated in the same competition in 2018 and 2019. The proposed parameterization was used in the development of individual CAD elements described in this article. Additionally, the implementation of specific modules and functions is a field for experimental research.
A Novel System-Theoretic Matrix-Based Approach to Analysing Safety and Security of Cyber-Physical Systems
Authors: Liew Lin-Shen , Sabaliauskaite Giedre , Kandasamy Nandha Kumar , Wong Choong-Yew William
Published: December 2021

Cyber-Physical Systems (CPSs) are getting increasingly complex and interconnected. Consequently, their inherent safety risks and security risks are so intertwined that the conventional analysis approaches which address them separately may be rendered inadequate. STPA (Systems-Theoretic Process Analysis) is a top-down hazard analysis technique that has been incorporated into several recently proposed integrated Safety and Security (S&S) analysis methods. This paper presents a novel methodology that leverages not only STPA, but also custom matrices to ensure a more comprehensive S&S analysis. The proposed methodology is demonstrated using a case study of particular commercial cloud-based monitoring and control system for residential energy storage systems.
Diastolic Cardiac Function by MRI—Imaging Capabilities and Clinical Applications
Authors: Ibrahim El-Sayed H. , Dennison Jennifer , Frank Luba , Stojanovska Jadranka
Published: December 2021

Most cardiac studies focus on evaluating left ventricular (LV) systolic function. However, the assessment of diastolic cardiac function is becoming more appreciated, especially with the increasing prevalence of pathologies associated with diastolic dysfunction like heart failure with preserved ejection fraction (HFpEF). Diastolic dysfunction is an indication of abnormal mechanical properties of the myocardium, characterized by slow or delayed myocardial relaxation, abnormal LV distensibility, and/or impaired LV filling. Diastolic dysfunction has been shown to be associated with age and other cardiovascular risk factors such as hypertension and diabetes mellitus. In this context, cardiac magnetic resonance imaging (MRI) has the capability for differentiating between normal and abnormal myocardial relaxation patterns, and therefore offers the prospect of early detection of diastolic dysfunction. Although diastolic cardiac function can be assessed from the ratio between early and atrial filling peaks (E/A ratio), measuring different parameters of heart contractility during diastole allows for evaluating spatial and temporal patterns of cardiac function with the potential for illustrating subtle changes related to age, gender, or other differences among different patient populations. In this article, we review different MRI techniques for evaluating diastolic function along with clinical applications and findings in different heart diseases.
Degradation-Aware Deep Learning Framework for Sparse-View CT Reconstruction
Authors: Sun Chang , Liu Yitong , Yang Hongwen
Published: December 2021

Sparse-view CT reconstruction is a fundamental task in computed tomography to overcome undesired artifacts and recover the details of textual structure in degraded CT images. Recently, many deep learning-based networks have achieved desirable performances compared to iterative reconstruction algorithms. However, the performance of these methods may severely deteriorate when the degradation strength of the test image is not consistent with that of the training dataset. In addition, these methods do not pay enough attention to the characteristics of different degradation levels, so solely extending the training dataset with multiple degraded images is also not effective. Although training plentiful models in terms of each degradation level can mitigate this problem, extensive parameter storage is involved. Accordingly, in this paper, we focused on sparse-view CT reconstruction for multiple degradation levels. We propose a single degradation-aware deep learning framework to predict clear CT images by understanding the disparity of degradation in both the frequency domain and image domain. The dual-domain procedure can perform particular operations at different degradation levels in frequency component recovery and spatial details reconstruction. The peak signal-to-noise ratio (PSNR), structural similarity (SSIM) and visual results demonstrate that our method outperformed the classical deep learning-based reconstruction methods in terms of effectiveness and scalability.
Safety Risks of Plant Fiber/Plastic Composites (PPCs) Intended for Food Contact: A Review of Potential Hazards and Risk Management Measures
Authors: Zhang Hong , Weng Yunxuan
Published: December 2021

Plant fiber/plastic composites (PPCs), with the benefits of low cost and easy processing, have been widely used in the production of various food contact products. They are generally considered to be economical and environmentally friendly because of their natural raw materials (plant fibers) and recommended to be one of the ideal alternatives to traditional petrochemical-based plastics. However, in addition to plastic resins and plant fibers, some indispensable additives are involved in the production process of PPCs, which may pose food safety risks. To date, excessive migration of hazardous substances (such as melamine) has been reported in some products made of PPCs, and the safety and applicability of PPCs as food contact materials need to be further studied. In this paper, the main raw materials of PPCs used for food contact are taken as the pointcut to analyze the possible hazards, sources of hazards, and existing risk management measures in various countries. The conclusion shows that PPCs used for food contact may have potential safety risks at present. However, systematic research on migration methods and safety assessment are still insufficient, and further studies are needed regarding the main safety risks and migration patterns.
RETRACTED: Combined Toxicity of Xenobiotics Bisphenol A and Heavy Metals on Zebrafish Embryos (Danio rerio)
Authors: Di Paola Davide , Capparucci Fabiano , Lanteri Giovanni , Cordaro Marika , Crupi Rosalia , Siracusa Rosalba , D’Amico Ramona , Fusco Roberta , Impellizzeri Daniela , Cuzzocrea Salvatore , Spanò Nunziacarla , Gugliandolo Enrico , Peritore Alessio
Published: December 2021

Environmental pollutants may cause adverse effects on the immune system of aquatic organisms. This study revealed that combination of environmental pollutants and Bisphenol A(BPA) could cause an acute inflammatory response in zebrafish larvae as shown by body alterations, which may imply a common immunotoxicity mechanism for most environmental pollutants. In the present study we evaluated the toxicity after co-exposure of BPA and Cd or Cr (III) in zebrafish embryos and larvae, and the oxidative stress pathway involved. Evaluation of lethal and developmental endpoints such as hatching, edema, malformations, abnormal heart rate and survival rate were evaluated after 96 h of exposure. Combination of BPA at 10 μM with Cd or Cr at 0.5 μM exposure induce malformations at 96 hpf in zebrafish larvae, as well as significantly increases oxidative stress and induce apoptosis on larvae. Our study suggested how environmental pollutant showed a synergistic effect at common not-effective doses, promoting decrease of antioxidant defense and contrasted fish development.
Correction: Nonin-Lecomte et al. Bacterial Type I Toxins: Folding and Membrane Interactions. Toxins 2021, 13, 490
Authors: Nonin-Lecomte Sylvie , Fermon Laurence , Felden Brice , Pinel-Marie Marie-Laure
Published: December 2021

The authors wish to make the following corrections to their paper [...]
Perspectives on the Pseudomonas aeruginosa Type III Secretion System Effector ExoU and Its Subversion of the Host Innate Immune Response to Infection
Authors: Hardy Kierra S. , Tessmer Maxx H. , Frank Dara W. , Audia Jonathon P.
Published: December 2021

Pseudomonas aeruginosa is an opportunistic, Gram-negative pathogen and an important cause of hospital acquired infections, especially in immunocompromised patients. Highly virulent P. aeruginosa strains use a type III secretion system (T3SS) to inject exoenzyme effectors directly into the cytoplasm of a target host cell. P. aeruginosa strains that express the T3SS effector, ExoU, associate with adverse outcomes in critically ill patients with pneumonia, owing to the ability of ExoU to rapidly damage host cell membranes and subvert the innate immune response to infection. Herein, we review the structure, function, regulation, and virulence characteristics of the T3SS effector ExoU, a highly cytotoxic phospholipase A2 enzyme.
Searching for Magnetospheres around Herbig Ae/Be Stars
Authors: Pogodin Mikhail , Drake Natalia , Beskrovnaya Nina , Pavlovskiy Sergei , Hubrig Swetlana , Schöller Markus , Järvinen Silva , Kozlova Olesya , Alekseev Ilya
Published: December 2021

We describe four different approaches for the detection of magnetospheric accretion among Herbig Ae/Be stars with accretion disks. Studies of several unique objects have been carried out. One of the objects is the Herbig Ae star HD 101412 with a comparatively strong magnetic field. The second is the early-type Herbig B6e star HD 259431. The existence of a magnetosphere in these objects was not recognized earlier. In both cases, a periodicity in the variation of some line parameters, originating near the region of the disk/star interaction, has been found. The third object is the young binary system HD 104237, hosting a Herbig Ae star and a T Tauri star. Based on the discovery of periodic variations of equivalent widths of atmospheric lines in the spectrum of the primary, we have concluded that the surface of the star is spotted. Comparing our result with an earlier one, we argue that these spots can be connected with the infall of material from the disk onto the stellar surface through a magnetosphere. The fourth example is the Herbig Ae/Be star HD 37806. Signatures of magnetospheric accretion in this object have been identified using a different method. They were inferred from the short-term variability of the He i λ5876 line profile forming in the region of the disk/star interaction.
Nucleocapsid (N) Gene Mutations of SARS-CoV-2 Can Affect Real-Time RT-PCR Diagnostic and Impact False-Negative Results
Authors: Lesbon Jéssika , Poleti Mirele , de Mattos Oliveira Elisângela , Patané José , Clemente Luan , Viala Vincent , Ribeiro Gabriela , Giovanetti Marta , de Alcantara Luiz , Teixeira Olivia , Nonato Maria , de Lima Loyze , Martins Antonio , dos Santos Barros Claudia , Marqueze Elaine , de Souza Todão Bernardino Jardelina , Moretti Debora , Brassaloti Ricardo , de Lello Rocha Campos Cassano Raquel , Mariani Pilar , Slavov Svetoslav , dos Santos Rafael , Rodrigues Evandra , Santos Elaine , Borges Josiane , de La Roque Debora , Kitajima Joao , Santos Bibiana , Assato Patricia , da Silva da Costa Felipe , Banho Cecilia , Sacchetto Livia , Moraes Marilia , Palmieri Melissa , da Silva Fabiana , Grotto Rejane , Souza-Neto Jayme , Nogueira Mauricio , Coutinho Luiz , Calado Rodrigo , Neto Raul , Covas Dimas , Kashima Simone , Elias Maria , Sampaio Sandra , Fukumasu Heidge
Published: December 2021

The current COVID-19 pandemic demands massive testing by Real-time RT-PCR (Reverse Transcription Polymerase Chain Reaction), which is considered the gold standard diagnostic test for the detection of the SARS-CoV-2 virus. However, the virus continues to evolve with mutations that lead to phenotypic alterations as higher transmissibility, pathogenicity or vaccine evasion. Another big issue are mutations in the annealing sites of primers and probes of RT-PCR diagnostic kits leading to false-negative results. Therefore, here we identify mutations in the N (Nucleocapsid) gene that affects the use of the GeneFinder COVID-19 Plus RealAmp Kit. We sequenced SARS-CoV-2 genomes from 17 positive samples with no N gene detection but with RDRP (RNA-dependent RNA polymerase) and E (Envelope) genes detection, and observed a set of three different mutations affecting the N detection: a deletion of 18 nucleotides (Del28877-28894), a substitution of GGG to AAC (28881-28883) and a frameshift mutation caused by deletion (Del28877-28878). The last one cause a deletion of six AAs (amino acids) located in the central intrinsic disorder region at protein level. We also found this mutation in 99 of the 14,346 sequenced samples by the Sao Paulo state Network for Pandemic Alert of Emerging SARS-CoV-2 variants, demonstrating the circulation of the mutation in Sao Paulo, Brazil. Continuous monitoring and characterization of mutations affecting the annealing sites of primers and probes by genomic surveillance programs are necessary to maintain the effectiveness of the diagnosis of COVID-19.
New Approaches to Multi-Parametric HIV-1 Genetics Using Multiple Displacement Amplification: Determining the What, How, and Where of the HIV-1 Reservoir
Authors: Patro Sean , Niyongabo Aurelie , Maldarelli Frank , Kearney Mary
Published: December 2021

Development of potential HIV-1 curative interventions requires accurate characterization of the proviral reservoir, defined as host-integrated viral DNA genomes that drive rebound of viremia upon halting ART (antiretroviral therapy). Evaluation of such interventions necessitates methods capable of pinpointing the rare, genetically intact, replication-competent proviruses within a background of defective proviruses. This evaluation can be achieved by identifying the distinct integration sites of intact proviruses within host genomes and monitoring the dynamics of these proviruses and host cell lineages over longitudinal sampling. Until recently, molecular genetic approaches at the single proviral level have been generally limited to one of a few metrics, such as proviral genome sequence/intactness, host-proviral integration site, or replication competency. New approaches, taking advantage of MDA (multiple displacement amplification) for WGA (whole genome amplification), have enabled multiparametric proviral characterization at the single-genome level, including proviral genome sequence, host-proviral integration site, and phenotypic characterization of the host cell lineage, such as CD4 memory subset and antigen specificity. In this review, we will examine the workflow of MDA-augmented molecular genetic approaches to study the HIV-1 reservoir, highlighting technical advantages and flexibility. We focus on a collection of recent studies in which investigators have used these approaches to comprehensively characterize intact and defective proviruses from donors on ART, investigate mechanisms of elite control, and define cell lineage identity and antigen specificity of infected CD4+ T cell clones. The highlighted studies exemplify how these approaches and their future iterations will be key in defining the targets and evaluating the impacts of HIV curative interventions.
Model-Based Planning and Delivery of Mass Vaccination Campaigns against Infectious Disease: Application to the COVID-19 Pandemic in the UK
Authors: Ibrahim Dauda , Kis Zoltán , Tak Kyungjae , Papathanasiou Maria M. , Kontoravdi Cleo , Chachuat Benoît , Shah Nilay
Published: December 2021

Vaccination plays a key role in reducing morbidity and mortality caused by infectious diseases, including the recent COVID-19 pandemic. However, a comprehensive approach that allows the planning of vaccination campaigns and the estimation of the resources required to deliver and administer COVID-19 vaccines is lacking. This work implements a new framework that supports the planning and delivery of vaccination campaigns. Firstly, the framework segments and priorities target populations, then estimates vaccination timeframe and workforce requirements, and lastly predicts logistics costs and facilitates the distribution of vaccines from manufacturing plants to vaccination centres. The outcomes from this study reveal the necessary resources required and their associated costs ahead of a vaccination campaign. Analysis of results shows that by integrating demand stratification, administration, and the supply chain, the synergy amongst these activities can be exploited to allow planning and cost-effective delivery of a vaccination campaign against COVID-19 and demonstrates how to sustain high rates of vaccination in a resource-efficient fashion.
Cross-Reactivity Conferred by Homologous and Heterologous Prime-Boost A/H5 Influenza Vaccination Strategies in Humans: A Literature Review
Authors: Kok Adinda , Fouchier Ron A. M. , Richard Mathilde
Published: December 2021

Avian influenza viruses from the A/H5 A/goose/Guangdong/1/1996 (GsGd) lineage pose a continuing threat to animal and human health. Since their emergence in 1997, these viruses have spread across multiple continents and have become enzootic in poultry. Additionally, over 800 cases of human infection with A/H5 GsGd viruses have been reported to date, which raises concerns about the potential for a new influenza virus pandemic. The continuous circulation of A/H5 GsGd viruses for over 20 years has resulted in the genetic and antigenic diversification of their hemagglutinin (HA) surface glycoprotein, which poses a serious challenge to pandemic preparedness and vaccine design. In the present article, clinical studies on A/H5 influenza vaccination strategies were reviewed to evaluate the breadth of antibody responses induced upon homologous and heterologous prime-boost vaccination strategies. Clinical data on immunological endpoints were extracted from studies and compiled into a dataset, which was used for the visualization and analysis of the height and breadth of humoral immune responses. Several aspects leading to high immunogenicity and/or cross-reactivity were identified, although the analysis was limited by the heterogeneity in study design and vaccine type used in the included studies. Consequently, crucial questions remain to be addressed in future studies on A/H5 GsGd vaccination strategies.
Analyses of Safety Profile and Homologous Antibody Responses to a Mammalian Cell-Based, MF59-Adjuvanted, A/H5N1, Pandemic Influenza Vaccine across Four Phase II/III Clinical Trials in Healthy Children, Adults, and Older Adults
Authors: Versage Eve , van Twuijver Esther , Jansen Wim , Theeuwes Ad , Sawlwin Daphne , Hohenboken Matthew
Published: December 2021

Modern cell culture-based technology eliminates vaccine manufactures reliance on embryonated chicken eggs, which may become compromised during an avian influenza pandemic. Four studies (total N = 6230) assessed the immunogenicity and safety of mammalian cell-based, MF59®-adjuvanted, A/H5N1 vaccine (aH5N1c; AUDENZ™) as two doses administered on Days 1 and 22 in children (NCT01776554), adults (NCT01776541; NCT02839330), and older adults (NCT01766921; NCT02839330). Immunogenicity of formulations at 7.5 μg and 3.75 μg antigen per dose were assessed by hemagglutination inhibition and microneutralization assays on Days 1, 22, 43, and 183 or 387. Solicited local and systemic adverse events (AEs) were recorded for 7 days after each vaccination. Unsolicited AEs were collected for 21 days after each vaccination, and serious and other selected AEs were recorded for one year. Antibody responses after two 7.5 μg doses met CBER licensure criteria in all age groups. Overall, an age-related response was evident, with the highest responses observed in children <3 years old. In children, antibody titers met seroconversion criteria 12 months after vaccination. MF59 allowed for antigen dose sparing. Solicited AEs were mild to moderate in nature, of short duration, and less frequent after the second dose than the first, demonstrating a favorable risk-benefit profile.