bluuebunny/crossref_metadata_2025 huggingface dataset:
A Vision-Based Collision Monitoring System for Proximity of Construction Workers to Trucks Enhanced by Posture-Dependent Perception and Truck Bodies’ Occupied Space
Authors: Shin Yoon-Soo , Kim Junhee
Published: June 2022

In the study, an automated visualization of the proximity between workers and equipment is developed to manage workers’ safety at construction sites using the convolutional-neural-network-based image processing of a closed-circuit television video. The images are analyzed to automatically transform a hazard index visualized in the form of a plane map. The graphical representation of personalized proximity in the plane map is proposed and termed as safety ellipse in the study. The safety ellipse depending on the posture of workers and the area occupied by the hazardous objects (trucks) enable to represent precise proximity. Collision monitoring is automated with computer vision techniques of artificial-intelligence-based object detection, occupied space calculation, pose estimation, and homography.
Forecasting Daytime Ground-Level Ozone Concentration in Urbanized Areas of Malaysia Using Predictive Models
Authors: Hashim NurIzzah M. , Noor Norazian Mohamed , Ul-Saufie Ahmad Zia , Sandu Andrei Victor , Vizureanu Petrica , Deák György , Kheimi Marwan
Published: June 2022

Ground-level ozone (O3) is one of the most significant forms of air pollution around the world due to its ability to cause adverse effects on human health and environment. Understanding the variation and association of O3 level with its precursors and weather parameters is important for developing precise forecasting models that are needed for mitigation planning and early warning purposes. In this study, hourly air pollution data (O3, CO, NO2, PM10, NmHC, SO2) and weather parameters (relative humidity, temperature, UVB, wind speed and wind direction) covering a ten year period (2003–2012) in the selected urban areas in Malaysia were analyzed. The main aim of this research was to model O3 level in the band of greatest solar radiation with its precursors and meteorology parameters using the proposed predictive models. Six predictive models were developed which are Multiple Linear Regression (MLR), Feed-Forward Neural Network (FFANN), Radial Basis Function (RBFANN), and the three modified models, namely Principal Component Regression (PCR), PCA-FFANN, and PCA-RBFANN. The performances of the models were evaluated using four performance measures, i.e., Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Index of Agreement (IA), and Coefficient of Determination (R2). Surface O3 level was best described using linear regression model (MLR) with the smallest calculated error (MAE = 6.06; RMSE = 7.77) and the highest value of IA and R2 (0.85 and 0.91 respectively). The non-linear models (FFANN and RBFANN) fitted the observed O3 level well, but were slightly less accurate compared to MLR. Nonetheless, all the unmodified models (MLR, ANN, and RBF) outperformed the modified-version models (PCR, PCA-FFANN, and PCA-RBFANN). Verification of the best model (MLR) was done using air pollutant data in 2018. The MLR model fitted the dataset of 2018 very well in predicting the daily O3 level in the specified selected areas with the range of R2 values of 0.85 to 0.95. These indicate that MLR can be used as one of the reliable methods to predict daytime O3 level in Malaysia. Thus, it can be used as a predictive tool by the authority to forecast high ozone concentration in providing early warning to the population.
Spatial Distribution and Driving Factors of Old and Notable Trees in a Fast-Developing City, Northeast China
Authors: Yang Yibo , Bao Guangdao , Zhang Dan , Zhai Chang
Published: June 2022

As a symbol of urban civilization and history, old and notable trees (ONTs) are facing challenges brought by rapid urbanization. Changchun is the fastest growing city in Northeast China, and throughout its development process of over 100 years it has preserved many ONTs. This study investigated all the ONTs in Changchun, and analyzed the species diversity, spatial distribution characteristics, dimension, age, and health status of trees by using ecological index and mathematical statistics, and trying to find out the underlying factors regulating their distribution. The results showed that there were 773 old trees belonging to 25 species and 2 notable trees from 1 species in Changchun. Pyrus ussuriensis was the dominant species, followed by Salix matsudana and Ulmus pumila. The urban area, population density, greening rate, and construction history did not influence the species and quantity of ONTs, while the types of land use and tree protection planning were important factors affecting the richness, diversity, and growth conditions of trees. To explore the potential reasons for their existence, the ONTs’ data in Changchun was compared with two nearby cities—Harbin and Shenyang. The comparison indicated that the geographical location and climatic conditions also controlled the distribution of ONTs. The number and dimensions of trees were driven by the history and development process of the city. Our findings suggested that preserving favorable living environments and maintaining a low intensity of human disturbance are critical factors for the survival of ONTs in cities.
The Impact of Government Intervention and Cap-and-Trade on Green Innovation in Supply Chains: A Social Welfare Perspective
Authors: Li Changhong , Wang Jialuo , Shi Yifan
Published: June 2022

This paper discusses the impact of government intervention (greenness threshold limit) and cap-and-trade policy on green investment, stakeholder profits and social welfare under different power structure scenarios in the green supply chain. First, a two-level green supply chain system is constructed: a manufacturer that produces green products and complies with cap-and-trade policies and a retailer that sells green products. Based on the Stackelberg game and Cournot game, we compare the optimal solutions under the government intervention mechanism and cap-and-trade mechanism with manufacturer leadership, retailer leadership and equal power. The results are as follows: (1) both government intervention and the cap-and-trade mechanism are conducive to an increase in green technology innovation and profit, but excessive control will lead to a decline in social welfare. (2) The results in the concentrated scenario were better than those in the dispersed scenario. In the decentralized state, the result of equal power is the best, the result of retailer leadership is next, and the result of manufacturer leadership is the worst. (3) The lower cost of green investment will cause enterprises to give up purchasing carbon emission permits from the carbon market.
Approaching a Zero-Waste Strategy in Rapeseed (Brassica napus) Exploitation: Sustainably Approaching Bio-Based Polyethylene Composites
Authors: Aguado Roberto , Espinach Francesc Xavier , Vilaseca Fabiola , Tarrés Quim , Mutjé Pere , Delgado-Aguilar Marc
Published: June 2022

The current need to develop more sustainable processes and products requires the study of new materials. In the field of plastic materials, the need to develop 100% bio-based materials that meet market requirements is evident. In this sense, the present work aims to explore the potential of rapeseed waste as a reinforcement of a bio-based plastic matrix that does not generate new sub-waste. For this purpose, three types of processing of rapeseed residues have been studied: (i) milling; (ii) mechanical process; (iii) thermomechanical process. In addition, the reinforcing capacity of these materials, together with the need for an optimized coupling agent at 6 wt.%, has been verified. The micromechanics of the materials have been evaluated to determine the development of these fibers in the composite material. The results obtained show remarkable increases in mechanical properties, reaching more than 141% in tensile strength and 128% in flexural strength. There is a remarkable difference in the impact behavior between the materials with milled rapeseed and the fibers obtained by mechanical or thermomechanical processes. It was found that by sustainable design it is possible to achieve a 76.2% reduction in the amount of plastic used to manufacture material with the same mechanical properties.
Communicating the Resilience and Corporate Social Responsibility of SMEs during Lockdown in Spain: A Visual and Exploratory Study of Communication Mechanisms and Strategies
Authors: García-Santiago María-Dolores
Published: June 2022

The health crisis caused by COVID-19 has led to changes in the behaviour of businesses during lockdown, especially Small and Medium-sized enterprises (SMEs). This study aims to identify the capacity for reaction, resilience, and corporate social responsibility (CSR) from direct sources and from strategic communication categories. Firstly, to discover the communication mechanisms and strategies of innovative SMEs during lockdown in Spain for overcoming difficulties. And secondly, to confirm “Food and Drink”—sector SME resilience capacities through their communications, and the CSR capacity of the SMEs that supports the sustainability to the tourism sector. For this purpose, a qualitative analysis of the 2.0 messages communicated by the companies was carried out and a map generated from social network analysis to identify the most resilient SMEs based on strategic communication elements used. The results show an uneven business reaction that reflects the change of paradigm in communication with customers that is occurring heterogeneously. This study is original because few on this theme apply to SMEs in the Spanish context. We highlight they are all from the “Food and drink” sector and included in the list of enterprises with high growth rate through entrepreneurial spirit and innovation, allowing us to make certain comparisons and understand certain differences and respective resilience, including supply chains and CSR.
Has the Pandemic Altered Public Perception of How Local Green Spaces Affect Quality of Life in the United Kingdom?
Authors: Crossley Alexandra Jane , Russo Alessio
Published: June 2022

Green spaces unquestionably improve both physical and mental health, but there is little information on how they affect quality of life. This study investigates whether the public perception of how local green spaces and their impact on quality of life have altered as a result of restrictions imposed by the U.K.’s SARS-CoV-2 pandemic containment strategy. Qualitative data were collected using an online questionnaire distributed via social media platforms and postal flyers. The results clearly demonstrate that 90% of participants believe that green spaces improved their quality of life during the pandemic, with over 85% thinking that green spaces will continue to have a positive impact on their quality of life once the pandemic is over. Whether this is a permanent change in public thinking or a short-term adaptation to the stresses of the pandemic can be assessed in future research studies. More detailed research is required to understand more clearly the aspects and types of green spaces that are the most valuable for improving quality of life so that future ones can be designed to provide maximum benefits.
Adoption of Digital Technologies by SMEs for Sustainability and Value Creation: Moderating Role of Entrepreneurial Orientation
Authors: Vrontis Demetris , Chaudhuri Ranjan , Chatterjee Sheshadri
Published: June 2022

Digital business transformation is considered an effective business strategy that appears to have gained attention since the enterprises are challenged to continuously improve their business practices as well as capabilities. The use of digital technologies could reduce the influence of external crises and could introduce massive changes in business operations by providing better business models. Moreover, adopting digital technology can influence both economic sustainability and social value of enterprises and can improve regional socio-economic conditions. There are few recent studies on how technology can empower enterprises at different phases of growth and sustainability; furthermore, very few studies are available that determine how adopting different modern digital technologies can create value for small and medium enterprises (SMEs). Therefore, this study aims to close this gap and investigate the moderating role of entrepreneurial orientation. With the support of resource-based view (RBV) and dynamic capability view (DCV) theories, along with a literature review, a theoretical model has been developed. It was then validated using the PLS-SEM technique considering 319 respondents who are SME employees in India. The findings show that adopting digital technologies has a significant impact on the creation of economic sustainability and social value for SMEs. The study also found a significant moderating impact of entrepreneurial orientation on the relationship between social and economic value creation and SME performance.
Assessing Resource Efficiency of City Neighbourhoods: A Methodological Framework for Structuring and Practical Application of Indicators in Urban Planning
Authors: Schebek Liselotte , Lützkendorf Thomas
Published: June 2022

Today, changing framework conditions of living and working in cities drive urban planning processes for refurbishment, notably at the level of neighbourhoods, and provide a window of opportunity to enhance resource efficiency and sustainable urban development. Indicators, as part of sustainability assessment methods, may support the identification of the most beneficial planning alternatives or the selection of measures. However, the fact that a multitude of indicators are proposed in the literature discourages their actual use and hampers a sound application for decision support. To tackle these challenges, a manual has been developed proposing a framework for the use of indicators in urban planning. In this contribution, the theoretical foundations of the proposed framework are analysed. A conceptual outline of the framework is presented, which as its core has a typology of indicators, and its embedding in urban planning processes is discussed. The framework combines a theoretically concise unifying structure with a flexible practical approach for application in diverse areas of resource efficiency. Thus, it shall enhance transparency as well as comparability in the use of indicators, foster communication between stakeholders and in the long run support the application of indicators and use of sustainability assessment methods as regular parts of urban planning.
Review on Water and Energy Integration in Process Industry: Water-Heat Nexus
Authors: Castro Oliveira Miguel , Iten Muriel , Matos Henrique A.
Published: June 2022

The improvement of water and energy use is an important concern in the scope of improving the overall performance of industrial process plants. The investment in energy efficiency comprehended by the most recent sustainability policies may prove to be an effective response to the fall of energy intensity rates associated with the economic crisis brought by the COVID-19 pandemic. The improvement in water efficiency may also prove to be a potential approach due to its interdependencies to energy use, whose exploitation comprises part of the study of the water-energy nexus. Waste heat recovery and water reclamation practices have been exploited to improve water and energy efficiency. A specific method designated “Combined Water and Energy Integration” has been applied to water recycling as both an additional water source and a heat recovery source in a set of water-using processes. In scientific and industrial domains, there is still a need for integrated approaches of water-using and combustion-based processes for overall water and energy efficiency improvements in industrial plants. In this work, an innovative approach for a simultaneous improvement of water and energy use is proposed based on process integration and system retrofitting principles. This proposal is based on the delineation of two innovative concepts: Water and Energy Integration Systems (WEIS) and Water-Heat Nexus (WHN). A review on existing technologies for waste heat recovery, thermal energy storage and heat-driven wastewater treatment is performed, following a conceptualisation design.
An Artificial Neural Network for Simulation of an Upflow Anaerobic Filter Wastewater Treatment Process
Authors: McCormick Mark
Published: June 2022

The purpose of this work was to develop a problem-solving approach and a simulation tool that is useful for the specification of wastewater treatment process equipment design parameters. The proposition of using an artificial neural network (ANN) numerical model for supervised learning of a dataset and then for process simulation on a new dataset was investigated. The effectiveness of the approach was assessed by evaluating the capacity of the model to distinguish differences in the equipment design parameters. To demonstrate the approach, a mock dataset was derived from experimentally acquired data and physical effects reported in the literature. The mock dataset comprised the influent flow rate, the bed packing material dimension, the type of packing material and the packed bed height-to-diameter ratio as predictors of the calorific value reduction. The multilayer perceptron (MLP) ANN was compared to a polynomial model. The validation test results show that the MLP model has four hidden layers, each having 256 units (nodes), accurately predicts calorific value reduction. When the model was fed previously unseen test data, the root-mean-square error (RMSE) of the predicted responses was 0.101 and the coefficient of determination (R2) was 0.66. The results of simulation of all 125 possible combinations of the 3 mechanical parameters and identical influent wastewater flow profiles were ranked according to total calorific value reduction. A t-test of the difference between the mean calorific value reduction of the two highest ranked experiments showed that the means are significantly different (p-value = 0.011). Thus, the model has the capacity to distinguish differences in the equipment design parameters. Consequently, the values of the three mechanical feature parameters from the highest ranked simulated experiment are recommended for use in the design of the industrial scale upflow anaerobic filter (UAF) for wastewater treatment.
A Fog-Cluster Based Load-Balancing Technique
Authors: Singh Prabhdeep , Kaur Rajbir , Rashid Junaid , Juneja Sapna , Dhiman Gaurav , Kim Jungeun , Ouaissa Mariya
Published: June 2022

The Internet of Things has recently been a popular topic of study for developing smart homes and smart cities. Most IoT applications are very sensitive to delays, and IoT sensors provide a constant stream of data. The cloud-based IoT services that were first employed suffer from increased latency and inefficient resource use. Fog computing is used to address these issues by moving cloud services closer to the edge in a small-scale, dispersed fashion. Fog computing is quickly gaining popularity as an effective paradigm for providing customers with real-time processing, platforms, and software services. Real-time applications may be supported at a reduced operating cost using an integrated fog-cloud environment that minimizes resources and reduces delays. Load balancing is a critical problem in fog computing because it ensures that the dynamic load is distributed evenly across all fog nodes, avoiding the situation where some nodes are overloaded while others are underloaded. Numerous algorithms have been proposed to accomplish this goal. In this paper, a framework was proposed that contains three subsystems named user subsystem, cloud subsystem, and fog subsystem. The goal of the proposed framework is to decrease bandwidth costs while providing load balancing at the same time. To optimize the use of all the resources in the fog sub-system, a Fog-Cluster-Based Load-Balancing approach along with a refresh period was proposed. The simulation results show that “Fog-Cluster-Based Load Balancing” decreases energy consumption, the number of Virtual Machines (VMs) migrations, and the number of shutdown hosts compared with existing algorithms for the proposed framework.
Mechanization of Small-Scale Agriculture in China: Lessons for Enhancing Smallholder Access to Agricultural Machinery
Authors: Liao Wangda , Zeng Fusheng , Chanieabate Meseret
Published: June 2022

Developing countries with small-scale agriculture have yet to exploit the untapped potential of agricultural mechanization. This is because of the misconception that mechanization is often seen as unworthy in small-scale agriculture. The purpose of this paper is to examine the development of agricultural mechanization in China and to provide evidence on how smallholder farmers can access agricultural machinery. A narrative approach was employed to conduct an in-depth analysis of the policies, strategies, and trends associated with agricultural mechanization development. The findings showed that: (1) the establishment and development of mechanization for smallholder agriculture is an evolutionary process that strongly opposes leapfrogging (technocratic behavior) and making large jumps; (2) the foundation of mechanization development should rely on a self-reliance system; (3) an appropriate mechanization theory is the key to inducing the rapid growth of mechanization in small-scale agriculture; (4) the successful application of agricultural machinery requires strong, target-oriented, and pro-farmer policies with effective leadership strategies. We present the key lessons on policy and institutional aspects for countries with small-scale agriculture and who are in the initial stages of agricultural mechanization.
Study-GNN: A Novel Pipeline for Student Performance Prediction Based on Multi-Topology Graph Neural Networks
Authors: Li Ming , Wang Xiangru , Wang Yi , Chen Yuting , Chen Yixuan
Published: June 2022

Student performance prediction has attracted increasing attention in the field of educational data mining, or more broadly, intelligent education or “AI + education”. Accurate performance prediction plays a significant role in solving the problem of a student dropping out, promoting personalized learning and improving teaching efficiency, etc. Traditional student performance prediction methods usually ignore the potential (underlying) relationship among students. In this paper, we use graph structure to reflect the students’ relationships and propose a novel pipeline for student performance prediction based on newly-developed multi-topology graph neural networks (termed MTGNN). In particular, we propose various ways for graph construction based on similarity learning using different distance metrics. Based on the multiple graphs of different topologies, we design an MTGNN module, as a key module in the pipeline, to deal with the semi-supervised node classification problem where each node represents a student (and the node label is the student’s performance, e.g., Pass/Fail/Withdrawal). An attention-based method is developed to produce the unified graph representation in MTGNN. The effectiveness of the proposed pipeline is verified in a case study, where a real-world educational dataset and several existing approaches are used for performance comparison. The experiment results show that, compared with some traditional machine learning methods and the vanilla graph convolutional network with only a single graph topology, our proposed pipeline works effectively and favorably in student performance prediction.
Frameworks for Urban Green Infrastructure (UGI) Indicators: Expert and Community Outlook toward Green Climate-Resilient Cities in Pakistan
Authors: Rayan Muhammad , Gruehn Dietwald , Khayyam Umer
Published: June 2022

Climate-induced pressures spur on the need for urban green infrastructure (UGI) planning. This approach offers a possible way to improve ecosystem functionality and human well-being in adversely affected urban regions, wherein UGI is perceived as a green and nature-based climate change mitigation/adaptation strategy. In Pakistan, the Khyber Pakhtunkhwa (KP) province lacks such urban landscape and greening policies (ULGP) or legislative frameworks for transitioning to green action plans (GAP), to alleviate the risk of multi-climatic hazards. Thus, this study aims to investigate a sustainable UGI-indicator-based framework model, based on the due inclusion of the concerned stakeholders. The relative importance index (RII) and inter-quartile range (IQR) techniques are employed for field data analysis. The findings proclaim excellent reliability (α > 0.7) and internal consistency, wherein sustainable UGI indicators are grouped based on their importance. The results portray the ecological and economic sustainability dimensions as being important (RII = 0.835 and RII = 0.807, respectively), socio-cultural dimensions as being moderately important (RII = 0.795), and a set of UGS elements (RII ≥ 0.77) as vital for bolstering individual UGI indicators. The main UGS elements emerging in each category can be grouped as follows: ecological category—“reducing rainwater runoff” (RII = 0.94); socio-cultural category—“enhancement of mental and physical health” (RII = 0.90); and eco category—“minimizing the risk of flood disasters” (RII = 0.96). The simulation results demonstrate the need for an inclusive perspective when building the urban green space (UGS) infrastructure (and standards) that will be most suitable for ensuring climate-resilient urban regions. This study contributes to putting the scientific research knowledge of the natural green-landscape-based (NBLB) approach into practice. The study calls for the establishment of an effective, pragmatic relationship between the urban landscape and greening policies, alongside a constructive relationship with the native inhabitants to ensure eco-friendly and resilient settlements.
Experimental Investigation of an Adaptive Fuzzy-Neural Fast Terminal Synergetic Controller for Buck DC/DC Converters
Authors: Babes Badreddine , Hamouda Noureddine , Albalawi Fahad , Aissa Oualid , Ghoneim Sherif S. M. , Abdelwahab Saad A. Mohamed
Published: June 2022

This study proposes a way of designing a reliable voltage controller for buck DC/DC converter in which the terminal attractor approach is combined with an enhanced reaching law-based Fast Terminal Synergetic Controller (FTSC). The proposed scheme will overcome the chattering phenomena constraint of existing Sliding Mode Controllers (SMCs) and the issue related to the indefinite time convergence of traditional Synergetic Controllers (SCs). In this approach, the FTSC algorithm will ensure the proper tracking of the voltage while the enhanced reaching law will guarantee finite-time convergence. A Fuzzy Neural Network (FNN) structure is exploited here to approximate the unknown converter nonlinear dynamics due to changes in the input voltage and loads. The Fuzzy Neural Network (FNN) weights are adjusted according to the adaptive law in real-time to respond to changes in system uncertainties, enhancing the increasing the system’s robustness. The applicability of the proposed controller, i.e., the Adaptive Fuzzy-Neural Fast Terminal Synergetic Controller (AFN-FTSC), is evaluated through comprehensive analyses in real-time platforms, along with rigorous comparative studies with an existing FTSC. A dSPACE ds1103 platform is used for the implementation of the proposed scheme. All results confirm fast reference tracking capability with low overshoots and robustness against disturbances while comparing with the FTSC.
Characterizations of Well-Posedness for Generalized Hemivariational Inequalities Systems with Derived Inclusion Problems Systems in Banach Spaces
Authors: Ceng Lu-Chuan , Li Jian-Ye , Wang Cong-Shan , Zhang Fang-Fei , Hu Hui-Ying , Cui Yun-Ling , He Long
Published: June 2022

In real Banach spaces, the concept of α-well-posedness is extended to the class of generalized hemivariational inequalities systems consisting of two parts which are of symmetric structure mutually. First, certain concepts of α-well-posedness for generalized hemivariational inequalities systems are put forward. Second, certain metric characterizations of α-well-posedness for generalized hemivariational inequalities systems are presented. Lastly, certain equivalence results between strong α-well-posedness of both the system of generalized hemivariational inequalities and its system of derived inclusion problems are established.
Formulation, Solution’s Existence, and Stability Analysis for Multi-Term System of Fractional-Order Differential Equations
Authors: Ahmad Dildar , Agarwal Ravi P. , ur Rahman Ghaus
Published: June 2022

In the recent past, multi-term fractional equations have been studied using symmetry methods. In some cases, many practical test problems with some symmetries are provided to demonstrate the authenticity and utility of the used techniques. Fractional-order differential equations can be formulated by using two types of differential operators: single-term and multi-term differential operators. Boundary value problems with single- as well as multi-term differential operators have been extensively studied, but several multi-term fractional differential equations still need to be formulated, and examination should be done with symmetry or any other feasible techniques. Therefore, the purpose of the present research work is the formulation and study of a new couple system of multi-term fractional differential equations with delay, as well as supplementation with nonlocal boundary conditions. After model formulation, the existence of a solution and the uniqueness conditions will be developed, utilizing fixed point theory and functional analysis. Moreover, results related to Ulam’s and other types of functional stability will be explored, and an example is carried out to illustrate the findings of the work.
Symmetric Bernstein Polynomial Approach for the System of Volterra Integral Equations on Arbitrary Interval and Its Convergence Analysis
Authors: Abdul Karim Samsul Ariffin , Khan Faheem , Basit Muhammad
Published: June 2022

In this paper, a new numerical technique is introduced to find the solution of the system of Volterra integral equations based on symmetric Bernstein polynomials. The use of Bernstein polynomials to find the numerical solutions of differential and integral equations increased due to its fast convergence. Here, the numerical solution of the system of Volterra integral equations on any finite interval [m,n] is obtained by replacing the unknown functions with the generalized Bernstein basis functions. The proposed technique converts the given system of equations into the system of algebraic equations which can be solved by using any standard rule. Further, Hyers–Ulam stability criteria are used to check the stability of the given technique. The comparison between exact and numerical solution for the distinct nodes is demonstrated to show its fast convergence.
On Codazzi Couplings on the Metric (E4 = I)−Manifolds
Authors: Turanli Sibel , Gezer Aydin
Published: June 2022

Let Mk be a metric E4=I−manifold equipped with electromagnetic-type structure E, a pseudo-Riemannian metric g and a nondegenerate 2−form ω^. The paper deals with Codazzi couplings of an affine connection ∇ with E, g and ω^. We present some results concerning the relationship of these Codazzi couplings. In addition, we construct the connection between Codazzi couplings and e−(E4=I) Kaehler manifolds.
A Novel Integrated Method for Harmonic Suppression and Reactive Power Compensation in Distribution Network
Authors: Wang Yifei , Yin Kaiyang , Liu Huikang , Yuan Youxin
Published: June 2022

Aiming at the serious harmonic pollution and the low power factor in the distribution network of industrial enterprises, this paper develops an integrated method for harmonic suppression and reactive power compensation suitable for the distribution network of industrial enterprises. The integrated method realizes the dual functions of harmonic filtering and reactive power compensation, and filters out the harmonic current to get a symmetrical current waveform while ensuring safe operation of the power compensator. In addition, it solves the problems of high harmonic content, small power factor in the distribution network, and device burnout caused by direct input of reactive power compensator. The main contributions of this paper are as follows: (1) According to the demand for the integration of harmonic suppression and reactive power compensation, the steps of integrated method for harmonic suppression and reactive power compensationare proposed, and then the methods for harmonic filtering and reactive power compensation are investigated; (2) a method for designing the capacity of a filter capacitor and the rated parameter of an electromagnetic coupling reactance converter is proposed, and an optimization simulation system is constructed to design the parameters of the filter; (3) a simulation system is developed, followed by parameter design and simulation analysis of harmonic filtering subsystem (HFSS), reactive power compensation subsystem (RPCSS) and the integrated system of harmonic suppression and reactive power compensation. Simulation results verify that the HFSS is put into operation first and then switched off later to ensure the normal operation of other equipment in the distribution network. After the treatment, the power factor, harmonic current content and total distortion rate all meet the national standards. The integrated method can dynamically track harmonics and reactive power changes, filter out harmonics, improve power factor and the symmetry level of the power source, and ensure the normal operation of other equipment in the distribution network. The research results lay a certain theoretical and technical foundation for the harmonic filtering and reactive power compensation theory, technology and its device innovation to achieve effective suppression of power harmonics and reactive power compensation.
Efficacy of Botulinum Toxin Type-A I in the Improvement of Mandibular Motion and Muscle Sensibility in Myofascial Pain TMD Subjects: A Randomized Controlled Trial
Authors: De la Torre Canales Giancarlo , Poluha Rodrigo Lorenzi , Pinzón Natalia Alvarez , Da Silva Bruno Rodrigues , Almeida Andre Mariz , Ernberg Malin , Manso Ana Cristina , Bonjardim Leonardo Rigoldi , Rizzatti-Barbosa Célia Marisa
Published: June 2022

This study assessed the effects of botulinum toxin type A (BoNT-A) in mandibular range of motion and muscle tenderness to palpation in persistent myofascial pain (MFP) patients (ReBEC RBR-2d4vvv). Eighty consecutive female subjects with persistent MFP, were randomly divided into four groups (n = 20): three BoNT-A groups with different doses and a saline solution group (placebo control group). Treatments were injected bilaterally in the masseter and anterior temporalis muscle in a single session. Clinical measurements of mandibular movements included: pain-free opening, maximum unassisted and assisted opening, and right and left lateral excursions. Palpation tests were performed bilaterally in the masseter and temporalis muscle. Follow-up occurred 28 and 180 days after treatment. For the statistical analysis the Mann–Whitney U-test with Bonferroni correction was used for groups comparisons. Regardless of dose, all parameters of mandibular range of motion significantly improved after 180 days in all BoNT-A groups, compared with the control group. Palpation pain over the masseter and temporalis muscles were significantly reduced in all BoNT-A groups regardless of dose, compared with the control group, after 28 and 180 days of treatment. Independent of doses, BoNT-A improved mandibular range of motion and muscle tenderness to palpation in persistent MFP patients.
Riding the Pandemic Waves—Lessons to Be Learned from the COVID-19 Crisis Management in Romania
Authors: Túri Gergő , Kassay János , Virág Attila , Dózsa Csaba , Horváth Krisztián , Lorenzovici László
Published: June 2022

In our analysis, we assessed how Romania dealt with the numerous challenges presented by the COVID-19 pandemic during 2021. In that year, the government had to deal with two waves of COVID-19 pandemics caused by the new variants, the low vaccination rate of the population, the overload of the healthcare system and political instability at the same time. Based on publicly available databases and international literature, we evaluated government measures aimed at reducing the spread of the pandemic and ensure the operation of the healthcare workforce and infrastructure. In addition, we evaluated measures to provide health services effectively and the government’s pandemic responses regarding excess mortality in 2021. In the absence of a complex monitoring system, limited information was available on the spread of the pandemic or the various risk factors at play. Due to incomplete and inadequate management systems, the government was unable to implement timely and adequate measures. Our analysis concludes that the management of a pandemic can only be successful if data are collected and evaluated using complex systems in a timely manner, and if members of society adhere to clearly communicated government measures due to high levels of trust in the government.
Post-Mortem Diagnosis of Pediatric Dengue Using Minimally Invasive Autopsy during the COVID-19 Pandemic in Brazil
Authors: Melo Deborah N. , Lima Giovanna R. P. , Fernandes Carolina G. , Teixeira André C. , Filho Joel B. , Araújo Fernanda M. C. , Araújo Lia C. , Siqueira André M. , Farias Luís A. B. G. , Monteiro Renata A. A. , Ordi Jaume , Martinez Miguel J. , Saldiva Paulo H. N. , Cavalcanti Luciano P. G.
Published: June 2022

We report the first pediatric disease in which the use of minimally invasive autopsy (MIA) confirmed severe dengue as the cause of death. During the COVID-19 pandemic, a previously healthy 10-year-old girl living in north-eastern Brazil presented fever, headache, diffuse abdominal pain, diarrhoea, and vomiting. On the fourth day, the clinical symptoms worsened and the patient died. An MIA was performed, and cores of brain, lungs, heart, liver, kidneys, and spleen were collected with 14G biopsy needles. Microscopic examination showed diffuse oedema and congestion, pulmonary intra-alveolar haemorrhage, small foci of midzonal necrosis in the liver, and tubular cell necrosis in the kidneys. Dengue virus RNA and NS1 antigen were detected in blood and cerebrospinal fluid samples. Clinical, pathological, and laboratory findings, in combination with the absence of other lesions and microorganisms, allowed concluding that the patient had died from complications of severe dengue.
Molecular Characterization of a Novel Polerovirus Infecting Soybean in China
Authors: Xu Tengzhi , Lei Lei , Fu Yong , Yang Xiaolan , Luo Hao , Chen Xiangru , Wu Xiaomao , Wang Yaqin , Jia Meng-ao
Published: June 2022

Poleroviruses are positive-sense, single-stranded viruses. In this study, we describe the identification of a novel polerovirus isolated from soybean displaying curled leaves. The complete viral genome sequence was identified using high-throughput sequencing and confirmed using rapid amplification of cDNA ends (RACE), RT-PCR and Sanger sequencing. Its genome organization is typical of the members of genus Polerovirus, containing seven putative open reading frames (ORFs). The full genome is composed of single-stranded RNA of 5822 nucleotides in length, with the highest nucleotide sequence identity (79.07% with 63% coverage) for cowpea polerovirus 2 (CPPV2). Amino acid sequence identities of the protein products between the virus and its relatives are below the threshold determined by the International Committee of Taxonomy of Viruses (ICTV) for species demarcation, and this strongly supports this virus’ status as a novel species, for which the name soybean chlorotic leafroll virus (SbCLRV) is proposed. Recombination analysis identified a recombination event in the ORF5 of the 3’ portion in the genome. Phylogenetic analyses of the genome and encoded protein sequences revealed that the new virus is closely related to phasey bean mild yellows virus, CPPV2 and siratro latent polerovirus. Subsequently, we demonstrated the infectivity of SbCLRV in Nicotiana benthamiana via infectious cDNA clone generation and agroinoculation.
Isolation of Genetically Diverse H5N8 Avian Influenza Viruses in Poultry in Egypt, 2019–2021
Authors: Salaheldin Ahmed H. , Elbestawy Ahmed R. , Abdelkader Abdelkader M. , Sultan Hesham A. , Ibrahim Awad A. , Abd El-Hamid Hatem S. , Abdelwhab Elsayed M.
Published: June 2022

The global spread of avian influenza virus (AIV) of clade 2.3.4.4b since 2016 has caused severe losses in wild birds and poultry and has posed a risk for the infection of mammals including humans. The vaccination of poultry has been used to limit the spread of the virus and mitigate its socioeconomic impact. Here, we describe H5N8 epidemics in chickens, turkeys and ducks from different localities in Egypt from 2019 to 2021. About 41.7% (n = 88/211) flocks were tested positive by RT-qPCR for H5N8 viruses with prevalence rates of 45.1% (n = 65/144) and 34.3% (n = 23/67) in vaccinated and non-vaccinated flocks, respectively. A sequence analysis of the hemagglutinin and neuraminidase genes indicated not only the multiple introduction events of H5N8 viruses in Egypt but also the establishment of endemic viruses in commercial poultry in 2020/2021. The recent H5N8 viruses in poultry in Egypt are genetically distinct from the majority of licensed vaccines used in the field. Together, our findings indicate that poultry in Egypt is an endemic center for clade 2.3.4.4b in the Middle East. The efficiency of current vaccines should be regularly evaluated and updated to fully protect poultry flocks in Egypt against H5N8 viruses.
Retrospective Detection and Complete Genomic Sequencing of Canine morbillivirus in Eurasian Otter (Lutra lutra) Using Nanopore Technology
Authors: Lanszki Zsófia , Lanszki József , Tóth Gábor Endre , Zeghbib Safia , Jakab Ferenc , Kemenesi Gábor
Published: June 2022

The Eurasian otter (Lutra lutra) is a piscivorous apex predator in aquatic habitats, and a flagship species of conservation biology throughout Europe. Despite the wide distribution and ecological relevance of the species, there is a considerable lack of knowledge regarding its virological and veterinary health context, especially in Central Europe. Canine morbillivirus (Canine distemper virus (CDV)) is a highly contagious viral agent of the family Paramyxoviridae with high epizootic potential and veterinary health impact. CDV is present worldwide among a wide range of animals; wild carnivores are at particular risk. As part of a retrospective study, lung-tissue samples (n = 339) from Eurasian otters were collected between 2000 and 2021 throughout Hungary. The samples were screened for CDV using a real-time RT-PCR method. Two specimens proved positive for CDV RNA. In one sample, the complete viral genome was sequenced using a novel, pan-genotype CDV-specific amplicon-based sequencing method with Oxford Nanopore sequencing technology. Both viral sequences were grouped to a European lineage based on the hemagglutinin-gene phylogenetic classification. In this article, we present the feasibility of road-killed animal samples for understanding the long-term dynamics of CDV among wildlife and provide novel virological sequence data to better understand CDV circulation and evolution.
How Humoral Response and Side Effects Depend on the Type of Vaccine and Past SARS-CoV-2 Infection
Authors: Stępień Monika , Zalewska Małgorzata , Knysz Brygida , Świątoniowska-Lonc Natalia , Jankowska-Polańska Beata , Łaczmański Łukasz , Piwowar Agnieszka , Kuźniarski Amadeusz
Published: June 2022

Since the end of December 2020, it has been possible to vaccinate against COVID-19. Our aim was to evaluate and compare the effectiveness of the vaccines available at the time of the mass vaccination program in Poland and also to look into the most common adverse side effects. Patients’ anti-SARS-CoV-2 antibodies levels were checked before vaccination and after the first and after the second/last dose by the anti-SARS-CoV-2 QuantiVac ELISA (IgG) (EUROIMMUN MedicinischeLabordiagnostica AG; Luebeck; Germany) test. Before each blood collection, all patients filled out a questionnaire regarding experienced side effects. We observed that 100% of patients responded to the vaccinations. After the first dose, convalescents had much higher levels of anti-SARS-CoV-2 antibodies than naive patients, although after the second dose, 61 out of 162 convalescents (37.7%) had lower results than before. The comparison of immunological responses in the convalescents group after the first dose and in the naive group after the second dose showed that convalescents had higher antibody titers, which may suggest the possibility of changing the vaccination schedule for convalescents. The highest antibody titers after both the first and second doses were observed after Moderna shots. Fever was identified as a significant factor regarding higher levels of antibodies after the first and second doses of the vaccine.
A Diagnostic Strategy for Gauging Individual Humoral Ex Vivo Immune Responsiveness Following COVID-19 Vaccination
Authors: Kuechler Anna Sabrina , Weinhold Sandra , Boege Fritz , Adams Ortwin , Müller Lisa , Babor Florian , Bennstein Sabrina B. , Pham T.-X. Uyen , Hejazi Maryam , Reusing Sarah B. , Hermsen Derik , Uhrberg Markus , Schulze-Bosse Karin
Published: June 2022

Purpose: We describe a diagnostic procedure suitable for scheduling (re-)vaccination against severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) according to individual state of humoral immunization. Methods: To clarify the relation between quantitative antibody measurements and humoral ex vivo immune responsiveness, we monitored 124 individuals before, during and six months after vaccination with Spikevax (Moderna, Cambridge, MA, USA). Antibodies against SARS-CoV-2 spike (S1) protein receptor-binding domain (S1-AB) and against nucleocapsid antigens were measured by chemiluminescent immunoassay (Roche). Virus-neutralizing activities were determined by surrogate assays (NeutraLISA, Euroimmune; cPass, GenScript). Neutralization of SARS-CoV-2 in cell culture (full virus NT) served as an ex vivo correlate for humoral immune responsiveness. Results: Vaccination responses varied considerably. Six months after the second vaccination, participants still positive for the full virus NT were safely determined by S1-AB levels ≥1000 U/mL. The full virus NT-positive fraction of participants with S1-AB levels <1000 U/mL was identified by virus-neutralizing activities >70% as determined by surrogate assays (NeutraLISA or cPas). Participants that were full virus NT-negative and presumably insufficiently protected could thus be identified by a sensitivity of >83% and a specificity of >95%. Conclusion: The described diagnostic strategy possibly supports individualized (re-)vaccination schedules based on simple and rapid measurement of serum-based SARS-CoV-2 antibody levels. Our data apply only to WUHAN-type SARS-CoV-2 virus and the current version of the mRNA vaccine from Moderna (Cambridge, MA, USA). Adaptation to other vaccines and more recent SARS-CoV-2 strains will require modification of cut-offs and re-evaluation of sensitivity/specificity.