bluuebunny/crossref_metadata_2025 huggingface dataset:
An Intrusion Detection Model for Drone Communication Network in SDN Environment
Authors: Kou Liang , Ding Shanshuo , Wu Ting , Dong Wei , Yin Yuyu
Published: November 2022

Drone communication is currently a hot topic of research, and the use of drones can easily set up communication networks in areas with complex terrain or areas subject to disasters and has broad application prospects. One of the many challenges currently facing drone communication is the communication security issue. Drone communication networks generally use software defined network (SDN) architectures, and SDN controllers can provide reliable data forwarding control for drone communication networks, but they are also highly susceptible to attacks and pose serious security threats to drone networks. In order to solve the security problem, this paper proposes an intrusion detection model that can reach the convergence state quickly. The model consists of a deep auto-encoder (DAE), a convolutional neural network (CNN), and an attention mechanism. DAE is used to reduce the original data dimensionality and improve the training efficiency, CNN is used to extract the data features, the attention mechanism is used to enhance the important features of the data, and finally the traffic is detected and classified. We conduct tests using the InSDN dataset, which is collected from an SDN environment and is able to verify the effectiveness of the model on SDN traffic. The experiments utilize the Tensorflow framework to build a deep learning model structure, which is run on the Jupyter Notebook platform in the Anaconda environment. Compared with the CNN model, the LSTM model, and the CNN+LSTM hybrid model, the accuracy of this model in binary classification experiments is 99.7%, which is about 0.6% higher than other comparison models. The accuracy of the model in the multiclassification experiment is 95.5%, which is about 3% higher than other comparison models. Additionally, it only needs 20 to 30 iterations to converge, which is only one-third of other models. The experiment proves that the model has fast convergence speed and high precision and is an effective detection method.
Pruning Decision Rules by Reduct-Based Weighting and Ranking of Features
Authors: Stańczyk Urszula
Published: November 2022

Methods and techniques of feature selection support expert domain knowledge in the search for attributes, which are the most important for a task. These approaches can also be used in the process of closer tailoring of the obtained solutions when dimensionality reduction is aimed not only at variables but also at learners. The paper reports on research where attribute rankings were employed to filter induced decision rules. The rankings were constructed through the proposed weighting factor based on the concept of decision reducts—a feature reduction mechanism embedded in the rough set theory. Classical rough sets operate only in discrete input space by indiscernibility relation. Replacing it with dominance enables processing real-valued data. Decision reducts were found for both numeric and discrete attributes, transformed by selected discretisation approaches. The calculated ranking scores were used to control the selection of decision rules. The performance of the resulting rule classifiers was observed for the entire range of rejected variables, for decision rules with conditions on continuous values, discretised conditions, and also inferred from discrete data. The predictive powers were analysed and compared to detect existing trends. The experiments show that for all variants of the rule sets, not only was dimensionality reduction possible, but also predictions were improved, which validated the proposed methodology.
Smart Gas Network with Linepack Managing to Increase Biomethane Injection at the Distribution Level
Authors: Cavana Marco , Leone Pierluigi
Published: November 2022

The current situation in Europe calls for the need of urgent measures to find sustainable alternatives to its outer dependence on natural gas. Biomethane injection into the existing gas infrastructure is a fundamental opportunity to be promoted that, however, causes increasing complexities in the management of natural gas grids. At the gas distribution level, the lack of a monitoring system and suitable software for the simulation, management, and verification of gas networks may act as barriers to a widespread diffusion of a biomethane production and injection chain. A transient fluid-dynamic model of the gas network is developed to perform estimations of the natural gas grid capacity in situations of production-consumption mismatch, taking into account the linepack as a gas buffer stock. The model is applied to the gas distribution network of a small urban-rural area. The aim is to assess the role of the linepack in determining the gas network receiving capacity and to test smart management of pressure set-points and injection flow rate to minimize biomethane curtailment. Results show that biomethane unacceptability can be reduced to 10% instead of 27% (obtained when following the DSOs state-of-the-art current procedures), thus highlighting the importance of the implementation of transient simulation software but also underlining the need for smarter control systems, actuators, and data management platforms for a transition to smart digital gas grids.
A Computational Fluid Dynamics Study of Laminar Forced Convection Improvement of a Non-Newtonian Hybrid Nanofluid within an Annular Pipe in Porous Media
Authors: Moghadasi Hesam , Bayat Mohamad , Aminian Ehsan , Hattel Jesper H. , Bodaghi Mahdi
Published: November 2022

Porous inserts and nanofluids are among the conventional methods for the amelioration of heat transfer in industrial systems. The heat transfer rate could also be improved by utilizing porous substances with a higher thermal conductivity in these systems. This research work presents a two-dimensional (2D) numerical examination of the laminar forced convection of an Al2O3-CuO-carboxy methyl cellulose (CMC) non-Newtonian hybrid nanofluid within an annular pipe in a porous medium. The porous medium was inserted within two inner or outer wall cases. For hybrid nanofluid flow modeling in porous media, a Darcy–Brinkman–Forchheimer formulation was employed. Additionally, a power-law technique was utilized as a fluid viscosity model for the considered non-Newtonian fluid. The governing equations were discretized according to the finite volume method (FVM) using the computational fluid dynamics (CFD) software package ANSYS-FLUENT. The cylinder walls’ thermal boundary conditions were exposed to a constant heat flux. For various Darcy numbers, the impacts of different volume fractions of the hybrid nanofluid (0% to 5%), the total Nusselt number, the pressure drop, and the performance number (PN) were evaluated. The outcomes indicate that the heat transfer coefficient increases considerably with a decrease in the Darcy number (0.1 to 0.0001), as well as with an increase in the porous thickness ratio. Moreover, it was found that the nanoparticles’ increased volume fraction would ameliorate the heat transfer and, more considerably, the PN factor. Furthermore, according to the outcomes in both cases I and II for a constant porous thickness ratio and Darcy number (rp=1,Da=0.0001) and a high volume fraction (φ=5%), the maximum total Nusselt number reached 1274.44. Moreover, applying a volume fraction of 5% with Da=0.1 and rp=1 reached the highest value of the PN index equal to 7.61, which is augmented as roughly 88% compared to the case of a zero volume fraction.
A Universal PSpice Simulation Model of a Switched Buck Voltage Regulator
Authors: Kováč Dobroslav , Vince Tibor , Bereš Matej , Molnár Ján , Dziak Jozef , Jacko Patrik , Kováčová Irena
Published: November 2022

The article describes the design of a universal simulation model of a voltage regulator for applications compatible with the globally used PSpice program. Users can create a model of any type of integrated switching voltage regulator that is currently available on the market by setting its individual parameters. The proposed connection of the regulator was applied in the connection of the buck DC–DC converter. The accuracy of the model was verified by comparing the results obtained by the simulation to other official models and to practical measurements taken on a real sample of the converter. The versatility of the model was proven by comparison with another type of converter with different parameters.
Solar Power Forecasting Using CNN-LSTM Hybrid Model
Authors: Lim Su-Chang , Huh Jun-Ho , Hong Seok-Hoon , Park Chul-Young , Kim Jong-Chan
Published: November 2022

Photovoltaic (PV) technology converts solar energy into electrical energy, and the PV industry is an essential renewable energy industry. However, the amount of power generated through PV systems is closely related to unpredictable and uncontrollable environmental factors such as solar radiation, temperature, humidity, cloud cover, and wind speed. Particularly, changes in temperature and solar radiation can substantially affect power generation, causing a sudden surplus or reduction in the power output. Nevertheless, accurately predicting the energy produced by PV power generation systems is crucial. This paper proposes a hybrid model comprising a convolutional neural network (CNN) and long short-term memory (LSTM) for stable power generation forecasting. The CNN classifies weather conditions, while the LSTM learns power generation patterns based on the weather conditions. The proposed model was trained and tested using the PV power output data from a power plant in Busan, Korea. Quantitative and qualitative evaluations were performed to verify the performance of the model. The proposed model achieved a mean absolute percentage error of 4.58 on a sunny day and 7.06 on a cloudy day in the quantitative evaluation. The experimental results suggest that precise power generation forecasting is possible using the proposed model according to instantaneous changes in power generation patterns. Moreover, the proposed model can help optimize PV power plant operations.
Flexible Power Point Tracking Using a Neural Network for Power Reserve Control in a Grid-Connected PV System
Authors: Gomez Jishu Mary , Shanmugam Prabhakar Karthikeyan
Published: November 2022

Renewable energy penetration in the global energy sector is in a state of steady growth. A major criterion imposed by the regulatory boards in the wake of electronic-driven power systems is frequency regulation capability. As more rooftop PV systems are under installation, the inertia response of the power utility system is descending. The PV systems are not equipped inherently with inertial or governor control for unseen frequency deviation scenarios. In the proposed method, inertial and droop frequency control is implemented by creating the necessary power reserve by the derated operation of the PV system. While, traditionally, PV systems operate in normal MPPT mode, a derated PV system follows a flexible power point tracking (FPPT) algorithm for creating virtual energy storage. The point of operation for the FPPT of the PV is determined by using a neural network block set available in MATLAB. For the verification of the controller, it is applied to a PV array in a modified IEEE-13 bus system modeled in the MATLAB/Simulink platform. The simulation results prove that when the proposed control is applied to the test network with renewable energy penetration, there is an improved system inertia response.
Demand Response in HEMSs Using DRL and the Impact of Its Various Configurations and Environmental Changes
Authors: Amer Aya , Shaban Khaled , Massoud Ahmed
Published: November 2022

With smart grid advances, enormous amounts of data are made available, enabling the training of machine learning algorithms such as deep reinforcement learning (DRL). Recent research has utilized DRL to obtain optimal solutions for complex real-time optimization problems, including demand response (DR), where traditional methods fail to meet time and complex requirements. Although DRL has shown good performance for particular use cases, most studies do not report the impacts of various DRL settings. This paper studies the DRL performance when addressing DR in home energy management systems (HEMSs). The trade-offs of various DRL configurations and how they influence the performance of the HEMS are investigated. The main elements that affect the DRL model training are identified, including state-action pairs, reward function, and hyperparameters. Various representations of these elements are analyzed to characterize their impact. In addition, different environmental changes and scenarios are considered to analyze the model’s scalability and adaptability. The findings elucidate the adequacy of DRL to address HEMS challenges since, when appropriately configured, it successfully schedules from 73% to 98% of the appliances in different simulation scenarios and minimizes the electricity cost by 19% to 47%.
Preventive Maintenance Strategy Optimization in Manufacturing System Considering Energy Efficiency and Quality Cost
Authors: Yang Liang , Liu Qinming , Xia Tangbin , Ye Chunming , Li Jiaxiang
Published: November 2022

Climate change is a serious challenge facing the world today. Countries are already working together to control carbon emissions and mitigate global warming. Improving energy efficiency is currently one of the main carbon reduction measures proposed by the international community. Within this context, improving energy efficiency in manufacturing systems is crucial to achieving green and low-carbon transformation. The aim of this work is to develop a new preventive maintenance strategy model. The novelty of the model is that it takes into account energy efficiency, maintenance cost, product quality, and the impact of recycling defective products on energy efficiency. Based on the relationship between preventive maintenance cost, operating energy consumption, and failure rate, the correlation coefficient is introduced to obtain the variable preventive maintenance cost and variable operating energy consumption. Then, the cost and energy efficiency models are established, respectively, and finally, the Pareto optimal solution is found by the nondominated sorting genetic algorithm II (NSGAII). The results show that the preventive maintenance strategy proposed in this paper is better than the general maintenance strategy and more relevant to the actual situation of manufacturing systems. The scope of the research in this paper can support the decision of making energy savings and emission reductions in the manufacturing industry, which makes the production, maintenance, quality, and architecture of the manufacturing industry optimized.
Identification and Construction of Ecological Nodes in the Fuzhou Ecological Corridors
Authors: Lin Jiqing , Yang Wufa , Yu Kunyong , Geng Jianwei , Liu Jian
Published: November 2022

Ecological corridor construction is an important support of the current pursuit of high-quality urbanization. Fuzhou is a mountain–water city characterized by a unique spatial structure. However, rapid urbanization has exacerbated the rate of ecosystem fragmentation, negatively impacting the livable living environment. The construction of ecological corridors is of great significance for efforts to restore the broken landscape and form the urban ecosystem as an organic whole in Fuzhou. In the present study, Fuzhou was considered as the study area, and the water, green, and ventilation corridors, as well as surface temperature data, were analyzed using the kernel density analysis method to generate surface-temperature-based ecological nodes. The impacts of various corridors and surface temperatures on the construction of the Fuzhou ecological corridors were assessed using ecological theory, and the ecological resistance surfaces of the influencing factors were obtained. We constructed ecological corridors for the mitigation of the urban heat island in Fuzhou using the MCR model with four levels and then evaluated the network connectivity of the corridors. The results revealed the following findings: (1) The study area comprises 32 ecological nodes, including nine in Minhou County and Changle District, four in Mawei and Cangshan Districts, and two in Gulou, Taijiang, and Jin’an Districts. (2) Fuzhou contains 63 ecological corridors with a total length of approximately 494.65 km. These include 31 first-level (201.16 km), 11 second-level (98.56 km), 14 third-level (129.12 km), and 7 fourth-level (65.81 km) corridors. (3) The degree of closure (α), the point rate of lines (β), the degree of connectivity (γ), and the degree of connectivity (Cr) indexes of the network structure for the ecological corridors were 0.27, 2.03, 0.72, and 0.87, respectively. They indicate that the overall ecological effectiveness of the network is high and can provide a theoretical basis for the construction of ecological corridors in the future.
Pharmacodynamics of Dracorhodin Perchlorate and Its Inflammation-Targeting Emulsion Gel for Wound Healing
Authors: Wang Xiaojie , Guo Xue , Yu Ran , Yue Mingxing , Li Xingjuan , Liu Bo , Pan Zhiquan
Published: November 2022

The mechanism of dracorhodin perchlorate for the repair of rat skin wounds was investigated. In order to screen a more favorable drug delivery system for wound repair, the therapeutic effect of dracorhodin perchlorate inflammation-targeted emulsion gel was compared with that of non-targeted emulsion gel on rat wounds. Compared with non-targeted emulsion gels, inflammation-targeted emulsion gels had a better transdermal penetration and lower potentials (−51.6 mV and −17.1 mV, respectively). The recovery of the wound from the dracorhodin perchlorate inflammation targeted emulsion gel group was better than that of the dracorhodin perchlorate inflammation non-targeted emulsion gel group and the positive drug group. Compared with the no-target emulsion gel group, the bFGF expression on day 7 and the EGF expression on day 14 in the targeted emulsion group showed 45.5% and 49.9% improvement, respectively. Pathological tissue slices showed that the epidermis, dermis, and basal layer inflammatory cells in the inflammation-targeted emulsion gel group and non-targeted emulsion gel group were significantly reduced, the granulation tissue proliferation was obvious, and the inflammation-targeted emulsion gel group was more effective. The results proved that dracorhodin perchlorate had a repairing effect on rat skin wounds, and its mechanism might be related to the promotion of the expression of EGF and bFGF in tissues.
Prenatal Genetic Testing in the Era of Next Generation Sequencing: A One-Center Canadian Experience
Authors: Almubarak Asra , Zhang Dan , Kosak Mackenzie , Rathwell Sarah , Doonanco Jasmine , Eaton Alison J. , Kannu Peter , Lazier Joanna , Lui Monique , Niederhoffer Karen Y. , MacPherson Melissa J. , Sorsdahl Melissa , Caluseriu Oana
Published: November 2022

The introduction of next generation sequencing (NGS) technologies has revolutionized the practice of Medical Genetics, and despite initial reticence in its application to prenatal genetics (PG), it is becoming gradually routine, subject to availability. Guidance for the clinical implementation of NGS in PG, in particular whole exome sequencing (ES), has been provided by several professional societies with multiple clinical studies quoting a wide range of testing yields. ES was introduced in our tertiary care center in 2017; however, its use in relation to prenatally assessed cases has been limited to the postnatal period. In this study, we review our approach to prenatal testing including the use of microarray (CMA), and NGS technology (gene panels, ES) over a period of three years. The overall diagnostic yield was 30.4%, with 43.2% of those diagnoses being obtained through CMA, and the majority by using NGS technology (42% through gene panels and 16.6% by ES testing, respectively). Of these, 43.4% of the diagnoses were obtained during ongoing pregnancies. Seventy percent of the abnormal pregnancies tested went undiagnosed. We are providing a contemporary, one tertiary care center retrospective view of a real-life PG practice in the context of an evolving use of NGS within a Canadian public health care system that may apply to many similar jurisdictions around the world.
Compound and Conditioned Likelihood Ratio Behavior within a Probabilistic Genotyping Context
Authors: Duke Kyle , Cuenca Daniela , Myers Steven , Wallin Jeanette
Published: November 2022

In cases where multiple questioned individuals are separately supported as contributors to a mixed DNA profile, guidance documents recommend performing a comparison to see if there is support for their joint contribution. Anecdotal observations suggest the summed log of the individual likelihood ratios (LR), termed the simple LR product, should be roughly equivalent to or less than the log(LR) for the joint likelihood ratio, termed the compound LR. To assist casework analysts in evaluating statistical weights applied to a case at hand, this study assessed how consistently compound LRs conform to an additive behavior when compared to the simple LR product counterparts. Two-, three-, and four-person DNA mixture data, of various mixture proportions and DNA inputs, were interpreted by STRmix® version 2.8 Probabilistic Genotyping Software. Relative magnitudes of LR increases were found to be dependent on both template level and mixture composition. The distribution of log(LR) differences between all compound/simple LR comparisons was ~−2.7 to ~28.3. This level of information gain was similar to that for compound LR comparisons, with and without interpretation conditioning (~−3.2 to ~27.7). In both scenarios, the probability density peaked at approximately 0.5, indicating the information gain from constrained genotype combinations has a comparable impact on the outcome of LR calculations whether the restriction is applied before or after interpretation.
Auditory Cueing of Pre-Learned Skills and Role of Subcortical Information Processing to Maximize Rehabilitative Outcomes Bridging Science and Music-Based Interventions
Authors: Tomaino Concetta M.
Published: November 2022

Auditory entrainment of motor function is a fundamental tool in neurologic music therapy with many studies demonstrating improved clinical outcomes in people with movement disorders such as Parkinson’s Disease, acquired brain injuries, and stroke. However, the specific mechanisms of action within neural networks and cortical regions that are aroused and influenced by auditory entrainment still need to be identified. This paper draws from some contemporary neuroscience studies that indicate the role of the cerebellum and other subcortical systems in modulating pre-learned motor schema and proposes a possible rationale for the success of auditory entrainment within neurologic music therapy.
Digital Quality Resources Resulting from Standardized Program for Rubric Training in Medical Residents
Authors: Jiménez Báez María Valeria , Gutiérrez De la Cruz María Erika , Chávez Hernández María Margarita , Martínez Castro Luis Roberto , Nuñez Francisco Javier Alcocer
Published: November 2022

Introduction: In the health care area, tuition is an essential part to provide the instrument that proves the graduates have acquired the necessary skills in their specialties. Objective: Evaluation of the improvement in quality of resources for residents after standardized digital training program with rubrics. Methods: Prospective observational study of first year medical residents in seven medical specialties in four different training centers. Five dimensions were considered to scale the quality of medical resident research: Validation of rubric in investigation methodology topics for each block in b-learning mode; initial and ending evaluation; colloquium investigation rubric; results of final investigation; satisfaction survey of 360 degrees. The instruments were validated using the delphi method with a minimum agreement of 0.8. We considered global values greater than 80 points as good quality. Results: 85 medical residents participated and obtained a final average of 80.62 (±9.59), and the satisfaction of the course was qualified as excellent/good in 82.5%. A positive relation was observed between the scope of the evaluation and the level of satisfaction. Mean quality score for the course was good. There is no relationship between the research experience of the students and the final average r = 0.123 (p = 0.291). Conclusions: The implementation of research seminars in b-learning mode results in improving the education program for health residents after a training program with a rubric system and their acquiring research skills, and, as a consequence, the final product also showed better quality, even when the student did not have any experience in a scientific publication.
Registered Nurses’ Experiences of End-of-Life Care in Nursing Homes of South Korea: A Qualitative Study
Authors: Chang Soo-Jung
Published: November 2022

This study aimed to qualitatively describe how registered nurses (RNs) experienced and perceived end-of-life (EOL) care for older residents in South Korean nursing homes. The participants included 11 nurses with experience of providing EOL care for older residents in six nursing homes. Data were collected through one-on-one in-depth interviews using semi-structured questions from 27 December 2019 to 22 October 2020. Around 1–2 interviews were conducted for each participant, and each interview lasted between 40 min and two hours. The interview data were analyzed using qualitative content analysis. Eight sub-themes were identified and abstracted under three themes: (a) “feeling fulfilled for doing my best until the last day,” (b) “defensive coping due to legal and institutional limitations,” and (c) “requirements for effective EOL care.” This study suggests that there are many challenges and issues regarding EOL care at nursing homes. In order to provide effective EOL care to older residents, the foundation of the EOL care system, as well as skills training, should be strengthened. Furthermore, securing qualified nursing manpower and achieving institutional improvement by reducing obstacles are warranted.
Impact of COVID-19 Pandemic on Health-Related Quality of Life and Physical Activity of Patients in Hemodialysis
Authors: Segura-Ortí Eva , Martínez-Olmos Francisco J. , Ródenas-Pascual Álvaro , Guillem-Giménez Edgar , Vercher-Narbona Verónica , Piñón-Ruiz Martha Jocelyne , Garcia-Testal Alicia
Published: November 2022

Chronic dialysis patients have an increased risk of severe COVID-19 infection-related complications. The aim of this study was to quantify the impact of the COVID-19 pandemic on health-related quality of life (HRQoL) and physical activity levels of patients undertaking hemodialysis (HD). This was an observational study that compared data from two periods of time, before the COVID-19 pandemic vs pandemic. We used the Medical Outcomes Survey Short Form (SF-36) to measure the HRQoL and the Human Activity Profile (HAP) questionnaire was used to measure the physical activity. Data were analyzed with a mixed ordinal linear regression. A total of 27 eligible participants were interviewed during COVID-19 pandemic (median age 78 years). The linear regression model showed that the pandemic, after controlling for the covariates age, comorbidity, albumin, and hemoglobin, had a significant impact on the HRQoL. Physical function (−15.7) and social functioning subscales (−28.0) worsened (p = 0.001), and the physical component scale also showed a significant decrease (−3.6; p = 0.05). Time had a significant impact on the Human Activity Profile, with an average activity score diminished with the pandemic (−13.9; p = 0.003). The COVID-19 pandemic had a very negative impact on HRQoL and physical activity level of subjects undertaking hemodialysis. Interventions to improve HRQoL and activity levels of patients undertaking HD are recommended.
Patient Safety Culture in Latin American Hospitals: A Systematic Review with Meta-Analysis
Authors: Camacho-Rodríguez Doriam E. , Carrasquilla-Baza Deibys A. , Dominguez-Cancino Karen A. , Palmieri Patrick A.
Published: November 2022

Introduction: Adverse events in hospitals are prevented through risk reduction and reliable processes. Highly reliable hospitals are grounded by a robust patient safety culture with effective communication, leadership, teamwork, error reporting, continuous improvement, and organizational learning. Although hospitals regularly measure their patient safety culture for strengths and weaknesses, there have been no systematic reviews with meta-analyses reported from Latin America. Purpose: Our systematic review aims to produce evidence about the status of patient safety culture in Latin American hospitals from studies using the Hospital Survey on Patient Safety Culture (HSOPSC). Methods: This systematic review was guided by the JBI guidelines for evidence synthesis. Four databases were systematically searched for studies from 2011 to 2021 originating in Latin America. Studies identified for inclusion were assessed for methodological quality and risk of bias. Descriptive and inferential statistics, including meta-analysis for professional subgroups and meta-regression for subgroup effect, were calculated. Results: In total, 30 studies from five countries—Argentina (1), Brazil (22), Colombia (3), Mexico (3), and Peru (1)—were included in the review, with 10,915 participants, consisting primarily of nursing staff (93%). The HSOPSC dimensions most positive for patient safety culture were “organizational learning: continuous improvement” and “teamwork within units”, while the least positive were “nonpunitive response to error” and “staffing”. Overall, there was a low positive perception (48%) of patient safety culture as a global measure (95% CI, 44.53–51.60), and a significant difference was observed for physicians who had a higher positive perception than nurses (59.84; 95% CI, 56.02–63.66). Conclusions: Patient safety culture is a relatively unknown or unmeasured concept in most Latin American countries. Health professional programs need to build patient safety content into curriculums with an emphasis on developing skills in communication, leadership, and teamwork. Despite international accreditation penetration in the region, there were surprisingly few studies from countries with accredited hospitals. Patient safety culture needs to be a priority for hospitals in Latin America through health policies requiring annual assessments to identify weaknesses for quality improvement initiatives.
Surveillance and Molecular Characterization of SARS-CoV-2 Infection in Non-Human Hosts in Gujarat, India
Authors: Kumar Dinesh , Antiya Sejalben P. , Patel Sandipkumar S. , Pandit Ramesh , Joshi Madhvi , Mishra Abhinava K. , Joshi Chaitanya G. , Patel Arunkumar C.
Published: November 2022

Since December 2019, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) has been spreading worldwide, triggering one of the most challenging pandemics in the human population. In light of the reporting of this virus in domestic and wild animals from several parts of the world, a systematic surveillance study was conceptualized to detect SARS-CoV-2 among species of veterinary importance. Nasal and/or rectal samples of 413 animals (dogs n= 195, cattle n = 64, horses n = 42, goats n = 41, buffaloes n = 39, sheep n = 19, cats n = 6, camels n = 6, and a monkey n = 1) were collected from different places in the Gujarat state of India. RNA was extracted from the samples and subjected to RT-qPCR-based quantification of the target sequences in viral nucleoprotein (N), spike (S), and ORF1ab genes. A total of 95 (23.79%) animals were found positive, comprised of n = 67 (34.35%) dogs, n= 15 (23.43%) cattle, and n = 13 (33.33%) buffaloes. Whole SARS-CoV-2 genome sequencing was done from one sample (ID-A4N, from a dog), where 32 mutations, including 29 single-nucleotide variations (SNV) and 2 deletions, were detected. Among them, nine mutations were located in the receptor binding domain of the spike (S) protein. The consequent changes in the amino acid sequence revealed T19R, G142D, E156-, F157-, A222V, L452R, T478K, D614G, and P681R mutations in the S protein and D63G, R203M, and D377Y in the N protein. The lineage assigned to this SARS-CoV-2 sequence is B.1.617.2. Thus, the present study highlights the transmission of SARS-CoV-2 infection from human to animals and suggests being watchful for zoonosis.
Short and Long-Term Wellbeing of Children following SARS-CoV-2 Infection: A Systematic Review
Authors: Franco Juan Victor Ariel , Garegnani Luis Ignacio , Oltra Gisela Viviana , Metzendorf Maria-Inti , Trivisonno Leonel Fabrizio , Sgarbossa Nadia , Ducks Denise , Heldt Katharina , Mumm Rebekka , Barnes Benjamin , Scheidt-Nave Christa
Published: November 2022

Post-COVID conditions in children and adolescents were mostly investigated as the incidence of individual or clusters of symptoms. We aimed to describe the findings of studies assessing key outcomes related to global wellbeing and recovery in children and adolescents from a public health perspective. We searched the Cochrane COVID-19 Study Register and WHO COVID-19 Global literature on coronavirus disease database on 5 November 2021 and tracked ongoing studies published after this date. We included observational studies on children and adolescents with a follow-up greater than 12 weeks and focused on the outcomes of quality of life, recovery/duration of symptoms, school attendance and resource use/rehabilitation. We assessed their methodological quality, and we prepared a narrative synthesis of the results. We included 21 longitudinal and 4 cross-sectional studies (6 with a control group) with over 68 thousand unvaccinated children and adolescents with mostly asymptomatic or mild disease. Study limitations included convenience sampling, a poor description of their study population and heterogeneous definitions of outcomes. Quality of life was not largely affected in adolescents following COVID-19, but there might be greater impairment in young children and in those with more severe forms of the disease (4 studies). There might also be an impairment in daily activities and increased school absenteeism following COVID-19, but the findings were heterogeneous (5 studies). A total of 22 studies provided highly variable estimates based on heterogeneous definitions of overall persistence of symptoms (recovery), ranging from 0 to 67% at 8–12 weeks and 8 to 51% at 6–12 months. We found limited data on resource use and the need for rehabilitation. One controlled study indicated that the quality of life of infected children and adolescents might not substantially differ from controls. All controlled studies found a higher burden of persistent symptoms in COVID-19 cases compared with test-negative controls or cases of influenza. There is limited evidence on the short and long-term well-being of children following SARS-CoV-2 infection. High-quality longitudinal studies with control groups are needed to describe the outcomes in this population, especially in vaccinated children and those affected by new variants of the virus.
Dual-Attitude Decision-Making Processes of Construction Worker Safety Behaviors: A Simulation-Based Approach
Authors: Zhou Man , Chen Xiancong , He Lei , Ouedraogo Franck Aristide Kiswendsida
Published: November 2022

Workplace accidents are of great concern in the construction industry. Most of those accidents are caused by unsafe behavior in the workplace. Many previous studies have analyzed the causes of workers’ unsafe behaviors, but few have investigated workers’ feelings of insecurity from the perspective of systematic psychological theory. This study developed an attitude–behavior–intervention feedback loop mechanism of construction workers and used the dual-attitude theory to explain the occurrence mechanisms of unsafe behavior. Using this mechanism, an active-intervention system-dynamics model and a passive-intervention system-dynamics model were designed and simulated. The coefficient of the system dynamics equation in the simulation model involved meta-analysis to combine the correlation coefficients of existing studies, which increased the sample size and improved the statistical test efficiency. The results show that an implicit safety attitude has a more significant impact on safety behavior, and the effect of an active intervention is stronger than that of a passive intervention. Based on these results, this paper presents some feasible suggestions to reduce the probability of unsafe worker behaviors occurring.
Moderating Effects of Religious Tourism Activities on Environmental Risk, Leisure Satisfaction, Physical and Mental Health and Well-Being among the Elderly in the Context of COVID-19
Authors: Lin Hsiao-Hsien , Lin Tzu-Yun , Hsu Chun-Wei , Chen Che-Hsiu , Li Qi-Yuan , Wu Po-Hsuan
Published: November 2022

The purpose of this study is to explore whether religious tourism activities can create a safe leisure environment and improve the well-being of the elderly during the COVID-19 pandemic, with the participants in the Baishatun Mazu pilgrimage in Taiwan as the subjects of this study. A mixed research method was used. First, statistical software and the Pearson product-moment correlation coefficient were used to analyze the data. Then the respondents’ opinions were collected. Finally, a multivariate analysis method was used to discuss the results of analysis. The findings showed that the elderly respondents thought that the epidemic prevention information and leisure space planning for the pilgrimage made them feel secure. The elderly believed the scenery, religious atmosphere, and commodities en route could reduce the perception of environmental risks to tourists, relieve pressure on the brain, and increase social opportunities. Therefore, the friendlier the leisure environment around the pilgrimage, the greater the leisure satisfaction among the elderly respondents. The happier the elderly felt, the less they considered the concentration of airborne contaminants, including viruses. The better their physical and mental health was, the less likely they were to want to ask for religious goods.
Prevalence of Musculoskeletal Disorders and Their Associated Risk Factors among Furniture Manufacturing Workers in Guangdong, China: A Cross-Sectional Study
Authors: Yang Yan , Zeng Jiancheng , Liu Yimin , Wang Zhongxu , Jia Ning , Wang Zhi
Published: November 2022

Objective: This study aims to investigate the one-year prevalence and the associated factors of work-related musculoskeletal disorders (WMSDs) among furniture manufacturing workers in Guangdong, China. Methods: A cross-sectional study of 4181 (2953 males and 1228 females) furniture manufacturing workers was conducted between September 2019 and December 2019. All information about WMSDs was collected by the electronic version of Chinese Musculoskeletal Questionnaires (CMQ). Descriptive statistics and a binary logistic regression model were used to interpret the data. Result: The overall prevalence of WMSDs was 31.57%. The WMSD symptoms most commonly occurred in the neck (16.77%), followed by the shoulders (14.90%), ankles/feet (14.64%), hands/wrists (13.30%), upper back (11.48%), and lower back (10.95%). Multiple logistic regression analysis revealed that several individual, labor organization, and ergonomics-related factors conferred significant risks to WMSDs at different body sites. Conclusions: WMSDs remain the major occupational health problem for furniture manufacturing workers. Hence, some effective and feasible protective measures for furniture manufacturing workers are required in order to alleviate the health burden caused by WMSDs.
Health Security, Quality of Life and Democracy during the COVID-19 Pandemic: Comparative Approach in the EU-27 Countries
Authors: Șoitu Conțiu Tiberiu , Grecu Silviu-Petru , Asiminei Romeo
Published: November 2022

The aim of this paper is to emphasize the role played by the social, economic and political variables in shaping models of sustainable healthcare systems and strategies able to support and improve the quality of life during and after the COVID-19 pandemic. The context of our research is represented by the medical and socioeconomic crises generated by the COVID-19 pandemic. The current pandemic negatively affects healthcare systems, quality of life and the global economy. In this respect, this paper aims to thoroughly scrutinize the effects of the COVID-19 pandemic on the social and healthcare systems of EU countries, to analyze the impact of human development in the field of the Global Health Security Index and to estimate the relation between resilience and quality of life during the COVID-19 pandemic. The research design is quantitative, resorting to the use of both descriptive and inferential statistics, against the background of a long-term comparative approach to the respective situations in the EU-27 countries. Empirical findings are relevant for emphasizing the fact that human development and social progress are predictors for the dynamics of health security measures. Moreover, the quality of the political regime, particularly in the case of full and flawed democracies, is strongly related to a high level of resilience and could influence the perception of quality of life. All of these empirical results could prove valuable for scholars interested in understanding the relationships between democracy, healthcare systems and quality of life, and for political decision makers involved in the effort of reducing the negative effects of COVID-19 in EU-27 countries.
Perceived Exertion: Revisiting the History and Updating the Neurophysiology and the Practical Applications
Authors: Lopes Thiago Ribeiro , Pereira Hugo Maxwell , Silva Bruno Moreira
Published: November 2022

The perceived exertion construct creation is a landmark in exercise physiology and sport science. Obtaining perceived exertion is relatively easy, but practitioners often neglect some critical methodological issues in its assessment. Furthermore, the perceived exertion definition, neurophysiological basis, and practical applications have evolved since the perceived exertion construct’s inception. Therefore, we revisit the careful work devoted by Gunnar Borg with psychophysical methods to develop the perceived exertion construct, which resulted in the creation of two scales: the rating of perceived exertion (RPE) and the category-ratio 10 (CR10). We discuss a contemporary definition that considers perceived exertion as a conscious perception of how hard, heavy, and strenuous the exercise is, according to the sense of effort to command the limbs and the feeling of heavy breathing (respiratory effort). Thus, other exercise-evoked sensations would not hinder the reported perceived exertion. We then describe the neurophysiological mechanisms involved in the perceived exertion genesis during exercise, including the influence of the peripheral feedback from the skeletal muscles and the cardiorespiratory system (i.e., afferent feedback) and the influence of efferent copies from the motor command and respiratory drive (i.e., corollary discharges), as well as the interaction between them. We highlight essential details practitioners should consider when using the RPE and CR10 scales, such as the perceived exertion definition, the original scales utilization, and the descriptors anchoring process. Finally, we present how practitioners can use perceived exertion to assess cardiorespiratory fitness, individualize exercise intensity prescription, predict endurance exercise performance, and monitor athletes’ responses to physical training.
Reliability and Validity of the Korean Version of the Social Justice Scale in Nursing Students
Authors: Jung Hogi , Yang Yaki
Published: November 2022

The purpose of this study was to translate and adapt a scale to evaluate social justice in nursing students and to examine the validity and reliability within a Korean context. With a survey design, a total of 267 nursing students were recruited, and data were collected using a self-administered study questionnaire to measure their levels of SJS. Using SPSS/WIN 28.0, construct validity, item convergent and discriminant validity, concurrent validity, and internal consistency reliability of the scale was evaluated. Exploratory factor analysis supported the construct validity with a four-factor solution; that explained 55.52% of the total variance. Criterion validity was demonstrated with the Social Issues Advocacy Scale (r = 0.78, p < 0.001). Cronbach’s α coefficient for the scale was 0.96. The findings show satisfactory construct and criterion validity and reliability of the Korean version of the SJS for measuring social justice in nursing students.
Trends in Prescription Opioid Use in Motor Vehicle Crash Injuries in the United States: 2014–2018
Authors: Jin Lan , Vermund Sten H. , Zhang Yawei
Published: November 2022

Motor vehicle crashes (MVC) cause over three million people to be nonfatally injured each year in the United States alone. We investigated trends and patterns in prescription opioid usage among nonfatal MVC injuries in 50 states in the US and the District of Columbia from 2014 to 2018. All emergency department visits for an MVC event (N = 142,204) were identified from the IBM® MarketScan® Databases. Using log-binomial regression models, we investigated whether the prevalence of prescription opioids in MVC injuries varied temporally, spatially, or by enrollees’ characteristics. Adjusting for age, relationship to the primary beneficiary, employment status, geographic region, and residence in metropolitan statistical area, the prevalence decreased by 5% (95% CI: 2–8%) in 2015, 18% (95% CI: 15–20%) in 2016, 31% (95% CI: 28–33%) in 2017, and 49% (95% CI: 46–51%) in 2018, compared to 2014. Moreover, the prevalence decreased by 28% (95% CI: 26–29%) after the publication of the CDC Guidelines for Prescribing Opioids for Chronic Pain. Spatial variations were observed in the prevalence and temporal trend of prevalence. The decreasing trend in the prevalence of prescription opioids in MVC is consistent with the decrease in the dispensing rate of opioids and the percentage of high-dosage opioids in the study population.