bluuebunny/crossref_metadata_2025 huggingface dataset:
MPEG and DA-AD Resilient DCT-Based Video Watermarking Using Adaptive Frame Selection
Authors: Hou Jong-Uk
Published: October 2021

We present a robust video watermarking scheme and report the detailed robustness of the video watermarking assessed based on standard criteria obtained from Information Hiding and its Criteria (IHC) Committee. Using discrete cosine transform domain spread-spectrum watermarking, our system achieves robustness under various non-hostile video processing techniques, including MPEG compression and digital/analog–analog/digital (DA-AD) conversion. The proposed system ensures that a 16-bit embedded sequence can be extracted through adaptive frame selection in any 15-s interval, even with a long video clip. To evaluate the performance of the proposed watermarking scheme, we conducted robustness tests under a DA-AD conversion environment, based on the MPEG-4 part 10 (H.264) codec. The experiment results obtained indicate that, in addition to being robust against non-hostile video processes, the proposed method achieves invisibility. The assessment of the developed watermarking scheme also satisfies the third edition of the IHC video watermarking evaluation criteria.
A New Tool for Building Energy Optimization: First Round of Successful Dynamic Model Simulations
Authors: Chiesa Giacomo , Fasano Francesca , Grasso Paolo
Published: October 2021

Several tools and pieces of software support building energy modelling for optimization, certification and comparisons of different scenarios and usages. Nevertheless, the consistent rise in accessible computational power and the expansion of ICT are pushing the development of new software functionalities and tools able to support cross-disciplinary work on smart building optimization. This paper introduces a new platform (under development) that combines the EnergyPlus dynamic simulation tool with extra-functionalities and pre-defined usage scenarios based on automatic actions to manage massive simulations and correlation analyses. The tool’s utility was tested in three experiments, with goals that we consider to be fundamental requirements: comparing simple retrofit actions to reduce net energy needs; analyzing the free-running potential of a demo building and the impacts of different low-energy technologies in terms of increasing thermal comfort (shading and ventilative cooling); and comparing measured sensor data indicators with simulated ones under real weather conditions for model verification. The results demonstrate the ability of the tool to automatically generate hundreds of EnergyPlus input building models by acting on building geometry; we focused on the most common uses for parametric dynamic simulations. Additionally, the way in which the tool combines the automatic modification of the building’s design and the parallel launching of multiple simulations allows the labor to be reduced. The user can execute complex tasks without spending any time working with model editing software and aggregating the results from multiple simulations.
A Novel Ultra-Short-Term PV Power Forecasting Method Based on DBN-Based Takagi-Sugeno Fuzzy Model
Authors: Liu Ling , Liu Fang , Zheng Yuling
Published: October 2021

Forecasting uncertainties limit the development of photovoltaic (PV) power generation. New forecasting technologies are urgently needed to improve the accuracy of power generation forecasting. In this paper, a novel ultra-short-term PV power forecasting method is proposed based on a deep belief network (DBN)-based Takagi-Sugeno (T-S) fuzzy model. Firstly, the correlation analysis is used to filter redundant information. Furthermore, a T-S fuzzy model, which integrates fuzzy c-means (FCM) for the fuzzy division of input variables and DBN for fuzzy subsets forecasting, is developed. Finally, the proposed method is compared to a benchmark DBN method and the T-S fuzzy model in case studies. The numerical results show the feasibility and flexibility of the proposed ultra-short-term PV power forecasting approach.
Design and Implementation of Frequency Controller for Wind Energy-Based Hybrid Power System Using Quasi-Oppositional Harmonic Search Algorithm
Authors: Mahto Tarkeshwar , Kumar Rakesh , Malik Hasmat , Khan Irfan Ahmad , Al Otaibi Sattam , Albogamy Fahad R.
Published: October 2021

An innovative union of fuzzy controller and proportional-integral-derivative (PID) controller under the environment of fractional order (FO) calculus is described in the present study for an isolated hybrid power system (IHPS) in the context of load frequency control. The proposed controller is designated as FO-fuzzy PID (FO-F-PID) controller. The undertaken model of IHPS presented here involves different independent power-producing units, a wind energy-based generator, a diesel engine-based generator and a device for energy storage (such as a superconducting magnetic energy storage system). The selection of the system and controller gains was achieved through a unique quasi-oppositional harmony search (QOHS) algorithm. The QOHS algorithm is based on the basic harmony search (HS) algorithm, in which the combined concept of quasi-opposition initialization and HS algorithm fastens the profile of convergence for the algorithm. The competency and potency of the intended FO-F-PID controller were verified by comparing its performance with three different controllers (integer-order (IO)-fuzzy-PID (IO-F-PID) controller, FO-PID and IO-PID controller) in terms of deviation in frequency and power under distinct perturbations in load demand conditions. The obtained simulation results validate the cutting-edge functioning of the projected FO-F-PID controller over the IO-F-PID, FO-PID and IO-PID controllers under non-linear and linear functioning conditions. In addition, the intended FO-F-PID controller, considered a hybrid model, proved to be more robust against the mismatches in loading and the non-linearity in the form of rate constraint under the deviation in frequency and power front.
Evaluating the Environmental Impact of Using Cargo Bikes in Cities: A Comprehensive Review of Existing Approaches
Authors: Vasiutina Hanna , Szarata Andrzej , Rybicki Stanisław
Published: October 2021

The impact of the use of cargo bicycles for delivery processes on the environment is undeniably positive: it leads to the reduction of pollutants, noise, and vibrations caused by traditional vehicles; decreases traffic jams; causes more effective use of public space; and others. But how should such an effect be measured? What tools should be used to justify the necessity for change to more sustainable means of transport? How can we improve the state of the environment considering the interests of logistics service providers? There is a large amount of scientific literature dedicated to this problem: by using different modeling approaches, authors attempt to address the issue of sustainable transport. This paper conducts a literature review in the field of green cargo deliveries, investigates the benefits and drawbacks of integrating cargo bikes in urban logistics schemes, and examines methodologies and techniques for evaluating the impact of using cargo bicycles on the environment. By providing an opportunity to get acquainted with the situation in the sphere of green deliveries, the authors aim to encourage a breakthrough in the field of sustainable transport that may be achieved by using cargo bikes in modern cities. We review the existing approaches and tools for modeling transport emissions and state the significant positive environmental consequences.
A Review of Total Harmonic Distortion Factors for the Measurement of Harmonic and Interharmonic Pollution in Modern Power Systems
Authors: Arranz-Gimon Angel , Zorita-Lamadrid Angel , Morinigo-Sotelo Daniel , Duque-Perez Oscar
Published: October 2021

Harmonic distortion is one of the disturbances that most affects the quality of the electrical system. The widespread use of power electronic systems, especially power converters, has increased harmonic and interharmonic emission in a wide range of frequencies. Therefore, there are new needs in the measurement of harmonic distortion in modern electrical systems, such as measurement in the supra-harmonic range (>2 kHz) and the measurement of interharmonics. The International Electrotechnical Commission (IEC) standards define new total harmonic distortion (THD) rates based on the concept of frequency groupings. However, the rates defined in the IEC standards have shortcomings when measuring signals such as those present in the outputs of power systems with abundant interharmonic content and presence of components in the supra-harmonic range. Therefore, in this work, a comparison is made between the different THD factors currently defined, both in the literature and in the standards, to show which of them are the most suitable for assessing harmonic and interharmonic contamination in power system signals such as those present at the output of inverters.
The Microstructure of γ-Alumina
Authors: Stuart Natalie M. , Sohlberg Karl
Published: October 2021

Though γ-Al2O3 has played a central role in heterogeneous catalysis for more than two centuries, its microstructure continues to be debated. Specifically, the positions of Al3+ cations within the crystal lattice have been discussed extensively in the literature. Many authors uphold that the cations primarily occupy spinel sites, while others endorse the occupation of non-spinel sites. The other main point of dispute is whether the structure contains interstitial hydrogen, with some authors supporting a partially hydrated model and others claiming that the structure must be completely dehydrated. The use of different structural models directly affects the predicted geometry of γ-Al2O3 at the surface, which in turn has significant implications for its catalytic utility. A comparison of theoretical data to experimental infrared (IR), X-ray diffraction (XRD), and selected area electron diffraction (SAED) evidence suggests that γ-Al2O3 features cations primarily in spinel positions, while IR and nuclear magnetic resonance (NMR) data indicate that interstitial hydrogen is present within the bulk structure.
Methodology for Discontinuity Factors Generation for Simplified P3 Solver Based on Nodal Expansion Formulation
Authors: Xu Yuchao , Hou Jason , Ivanov Kostadin
Published: October 2021

The Simplified Spherical Harmonic (SPN) approximation was first introduced as a three-dimensional (3D) extension of the plane-geometry Spherical Harmonic (PN) equations. A third order SPN (SP3) solver, recently implemented in the Nodal Expansion Method (NEM), has shown promising performance in the reactor core neutronics simulations. This work is focused on the development and implementation of the transport-corrected interface and boundary conditions in an NEM SP3 solver, following recent published work on the rigorous SPN theory for piecewise homogeneous regions. A streamlined procedure has been developed to generate the flux zero and second order/moment discontinuity factors (DFs) of the generalized equivalence theory to minimize the error introduced by pin-wise homogenization. Moreover, several colorset models with varying sizes and configurations are later explored for their capability of generating DFs that can produce results equivalent to that using the whole-core homogenization model for more practical implementations. The new developments are tested and demonstrated on the C5G7 benchmark. The results show that the transport-corrected SP3 solver shows general improvements to power distribution prediction compared to the basic SP3 solver with no DFs or with only the zeroth moment DF. The complete equivalent calculations using the DFs can almost reproduce transport solutions with high accuracy. The use of equivalent parameters from larger size colorset models show a slightly reduced prediction error than that using smaller colorset models in the whole-core calculations.
Smart Power Management in OIC Countries: A Critical Overview Using SWOT-AHP and Hybrid MCDM Analysis
Authors: Kabir K. Habibul , Aurko Shafquat Yasar , Rahman Md. Saifur
Published: October 2021

A conventional electrical grid mostly depends on the electrical power generated from fossil fuels. However, the pollutants from fossil fuels are the key factors for adverse climate change. Most of the developed countries of the world have already recognized the fact that the energy mix requires to be diversified by incorporating renewable energy. This is especially relevant for a good number of the member countries of the Organization of Islamic Cooperation (OIC), as much of their electric power is still generated from fossil fuels due to the relative abundance of fossil fuels in those countries. In order to integrate renewable energy sources into the hybrid energy mix, an existing conventional grid needs to undergo drastic changes. Alongside this, the population boom in the OIC member countries has caused higher demand for a steady supply of electricity that the conventional grids have long been struggling to cope with. With a view to solving this multifaceted problem, incorporation of the smart power management schemes is indispensable using a smart electrical grid, where information and communications technology is integrated into its major building blocks. This allows advanced applications of a grid, such as the formation of micro-grids, demand-side management, energy storage, high-tech power electronic converters, etc. As the smart grids are being adopted by many developed countries, it is high time for the OIC member countries to pay due attention to this development, if they have not already done so. This paper explains, with special focus on the OIC member countries, the various smart power management technologies, their operations and applications, and the benefits and challenges. Then, it goes on to carry out the Strength–Weakness–Opportunity–Threat with Analytical-Heuristic-Procedure (SWOT-AHP) analysis to evaluate its feasibility of incorporation and the underlying strategies appropriate for its implementation. Furthermore, a Hybrid Multi-Criteria-Decision-Making (MCDM) analysis is performed to evaluate the sequence of the emphasis that should be given on each of the technologies from those available for the smart power management initiative. Finally, the study reinforces the stance by drawing parallels from the UN Sustainable Development Goals (SDG) and highlights the importance of the smart grid in line with the global vision of SDG. This paper aims at assisting the decision-makers in implementing smart power management schemes in the OIC member countries, in particular, and other countries of the world, in general.
A Concept of Risk Prioritization in FMEA Analysis for Fluid Power Systems
Authors: Fabis-Domagala Joanna , Domagala Mariusz , Momeni Hassan
Published: October 2021

FMEA analysis is a tool of quality improvement that has been widely used for decades. Its classical version prioritizes risk of failure by risk priority number (RPN). The RPN is a product of severity (S), occurrence (O), and detection (D), where all of the factors have equal levels of significance. This assumption is one of the most commonly criticized drawbacks, as it has given unreasonable results for real-world applications. The RPN can produce equal values for combinations of risk factors with different risk implications. Another issue is that of the uncertainties and subjectivities of information employed in FMEA analysis that may arise from lack of knowledge, experience, and employed linguistic terms. Many alternatives of risk assessment methods have been proposed to overcome the weaknesses of classical FMEA risk management in which we can distinguish methods of modification of RPN numbers of employing new tools. In this study, we propose a modification of the traditional RPN number. The main difference is that severity and occurrence are valued based on subfactors. The detection number remained unchanged. Additionally, the proposed method prioritizes risk in terms of implied risk to the systems by implementing functional failures (effects of potential failures). A typical fluid power system was used to illustrate the application of this method. The method showed the correct failure classification, which meets the industrial experience and other research results of failures of fluid power systems.
Modification of Energy Parameters in Wood Pellets with the Use of Waste Cooking Oil
Authors: Saletnik Aneta , Saletnik Bogdan , Puchalski Czesław
Published: October 2021

Biomass is one of the most important sources of renewable energy. It is expected that in the coming decades, biomass will play a major role in replacing fossil fuels. The most commonly used biofuels include wood pellet, which is a cost-effective, uniform and easy-to-use material. In view of the growing interest in this type of resource, novel methods are being investigated to improve the quality of pellet. This article presents the results of a laboratory study focusing on wood pellets refined with waste sunflower cooking oil applied by spraying. In this work, authors attempted to modify the energy parameters of wood pellets with the use of waste cooking oil. Addition of waste cooking oil, applied at the rates of 2%, 4%, 6%, 8%, 10% and 12% relative to the weight of pellets, increased the calorific value of the pellets without decreasing their durability. The highest dose of the modifier (12%) on average led to a 12–16% increase in calorific value. In each case, the addition of sunflower oil resulted in decreased contents of ash in the pellets; on average a decrease of 16–38% was observed in the samples treated with the highest dose of the modifier. The treatment led to a higher content of elements affecting the heating value, i.e., carbon and hydrogen, which on average increased by 7.5–12%, and 7.0–10.0%, respectively. The presented method seems to be a promising way of increasing the calorific value of pellets. Further research on refining the method and the possibility of using it in industry is necessary.
Beyond the Energy Poor/Non Energy Poor Divide: Energy Vulnerability and Mindsets on Energy Generation Modes in Hungary
Authors: Csizmady Adrienne , Ferencz Zoltán , Kőszeghy Lea , Tóth Gergely
Published: October 2021

In the Hungarian as well as the international literature, debates regarding the methodology used for measuring energy poverty are ongoing. Our contribution sought to develop a methodology that would be relatively easy to measure via survey and have the potential to identify households’ energy vulnerability status beyond the energy poor/non energy poor divide. Based on a representative survey that was carried out in Hungary in 2018, we identified three groups of households: energy poor, non energy poor households, and a so-called transitional group, potentially at risk of energy poverty. In addition to socioeconomic differences, we analysed differences in the mindsets of respondents belonging to these three household groups concerning different aspects of heating energy generation (macrolevel aspects, such as environmental sustainability and energy supply system issues, and microlevel aspects, such as economic and technical issues). By this, the article aims to provide input for further research on factors, beyond the social and economic background, related to energy vulnerability.
An Optimal Control Scheme for Load Bus Voltage Regulation and Reactive Power-Sharing in an Islanded Microgrid
Authors: Khan Muhammad Zahid , Mu Chaoxu , Habib Salman , Hashmi Khurram , Ahmed Emad M. , Alhosaini Waleed
Published: October 2021

This paper presents an optimal control scheme for an islanded microgrid (MG), which performs reactive power-sharing and voltage regulation. Two-fold objectives are achieved, i.e., the load estimation strategy, firstly, approximates the MG’s impedance and transmits this information through a communication link. Based on approximated impedance information, an optimal regulator is then constructed to send optimal control commands to respective local power controllers of each distributed generation unit. An optimal regulator is a constraints optimized problem, mainly responsible to restore the buses’ voltage magnitudes and realize power-sharing proportionally. The important aspect of this control approach is that the voltage magnitude information is only required to be transferred to each inverter’s controller. In parallel, a secondary control layer for frequency restoration is implemented to minimize the system frequency deviations. The MATLAB/Simulink and experimental results obtained under load disturbances show the effectiveness for optimizing the voltage and power. Modeling and analysis are also verified through stability analysis using system-wide mathematical small-signal models.
A Hybrid GA–PSO–CNN Model for Ultra-Short-Term Wind Power Forecasting
Authors: Liu Jie , Shi Quan , Han Ruilian , Yang Juan
Published: October 2021

Accurate and timely wind power forecasting is essential for achieving large-scale wind power grid integration and ensuring the safe and stable operation of the power system. For overcoming the inaccuracy of wind power forecasting caused by randomness and volatility, this study proposes a hybrid convolutional neural network (CNN) model (GA–PSO–CNN) integrating genetic algorithm (GA) and a particle swarm optimization (PSO). The model can establish feature maps between factors affecting wind power such as wind speed, wind direction, and temperature. Moreover, a mix-encoding GA–PSO algorithm is introduced to optimize the network hyperparameters and weights collaboratively, which solves the problem of subjective determination of the optimal network in the CNN and effectively prevents local optimization in the training process. The prediction effectiveness of the proposed model is verified using data from a wind farm in Ningxia, China. The results show that the MAE, MSE, and MAPE of the proposed GA–PSO–CNN model decreased by 1.13–9.55%, 0.46–7.98%, and 3.28–19.29%, respectively, in different seasons, compared with Single–CNN, PSO–CNN, ISSO–CNN, and CHACNN models. The convolution kernel size and number in each convolution layer were reduced by 5–18.4% in the GA–PSO–CNN model.
Exploring the Sustainable Effects of Urban-Port Road System Reconstruction
Authors: Bernacki Dariusz , Lis Christian
Published: October 2021

The aim of the research is to identify and quantify the direct sustainable effects resulting from the improved road infrastructure in the local urban-port transport system. This case study considers the city port of Szczecin (Poland). The effects are identified for the local road transport system by comparing freight road transport performance in two options: with the investment and without the investment. The sustainable effects are quantified in terms of money and physical units. Sustainable economic, social, and environmental effects concern generalized freight road transport cost, i.e., truck operating costs and costs of truck drivers’ working time, as well as freight transit time, energy consumption, greenhouse gas emissions, and environmental savings. To capture effects, the forecast of truck traffic demand, as well as unit vehicle operating costs, values of time, and air pollution and climate change, values are elaborated and revealed in freight road transport. The investigations show that the primary effect of investment is the reduced traffic congestion, which enhance the velocity of trucks in the transport system. The increased trucks′ speed affect freight road traffic performance, time of delivery, and environmental externalities.
Volatile Oil Profile of Prickly Ash (Zanthoxylum) Pericarps from Different Locations in China
Authors: Ma Yao , Tian Jieyun , Chen Yabing , Chen Ming , Liu Yulin , Wei Anzhi
Published: October 2021

Volatile oils of prickly ash (Zanthoxylum) pericarps have various potential biological functions with considerable relevance to food, pharmacological, and industrial applications. The volatile profile of oils extracted from prickly ash pericarps obtained from 72 plantations in China was determined by gas chromatography and mass spectrometry. Several chemometric analyses were used to better understand the volatile oil profile differences among different pericarps and to determine the key factors that affected geographical variations in the main volatile constituents of oils. A total of 47 constituents were detected with D-limonene, alfa-myrcene, and linalool as the most abundant. The volatile profile of pericarp oils was significantly affected by prickly ash species and some environmental factors, and the key factors that affected volatile profile variations for different prickly ash species were diverse. Chemometric analyses based on the volatile oil profile could properly distinguish Z. armatum pericarps from other pericarps. This study provides comprehensive information on the volatile oil profile of pericarps from different prickly ash species and different plantations, and it can be beneficial to a system for evaluating of pericarp quality. Moreover, this study speculates on the key environmental factors that cause volatile oil variations for each species, and can help to obtain better prickly ash pericarp volatile oils by improving the cultivated environments.
Wildfires Effect on Debris Flow Occurrence in Italian Western Alps: Preliminary Considerations to Refine Debris Flow Early Warnings System Criteria
Authors: Tiranti Davide , Cremonini Roberto , Sanmartino Daniele
Published: October 2021

Rarely, a close correlation between wildfires and the occurrence of channelized debris flows has been observed in the Western Italian Alps. Only two cases in history have been reported, after brief and localized rainfall events of moderate intensity in Italy’s Piemonte region (NW Italy) caused debris flows, on 18 July 2005, in Verbania province (Pallanzeno municipality), and on June 2018 in Turin province (Bussoleno municipality). These phenomena occurred after a large portion of the catchments were affected by wide wildfires in the preceding months. Debris flow deposits showed an unusually large number of fine-grained particles, forming dark-brown mud-rich deposits associated with burnt wood deposits. Rainfall analysis related to the period between the wildfires’ occurrence and the debris flow events, using both raingauge and weather radar data, pointed out that the debris flows triggered in July 2005 and June 2018 were characterized by greater magnitude but associated with less precipitation intensity rates as compared with previous mud flows occurring just after wildfires. These behaviors can be explained by the presence of burned organic material and fine-grained sediment, generated from the soil’s thermal reworking, which formed a thick layer, centimeters deep, covering a large percentage of catchments and slopes. Most of this layer, generated by wildfires’ action were winnowed by rainfall events that had occurred in the months before the debris flow events, of significant magnitude, exhuming a discontinuous hydrophobic soil surface that changed the slopes’ permeability characteristics. In such conditions, runoff increased, corrivation time shortened, and, consequently, discharge along the two catchments’ channels-network increased as well. Consequently, the rainfall effects associated with rainfall events in July 2005 and June 2019 were more effective in mobilizing coarse sediments in channel beds than was typical for those catchments.
Factors Associated with Healthcare Workers’ (HCWs) Acceptance of COVID-19 Vaccinations and Indications of a Role Model towards Population Vaccinations from a Cross-Sectional Survey in Greece, May 2021
Authors: Fotiadis Konstantinos , Dadouli Katerina , Avakian Ioanna , Bogogiannidou Zacharoula , Mouchtouri Varvara A. , Gogosis Konstantinos , Speletas Matthaios , Koureas Michalis , Lagoudaki Eleni , Kokkini Sofia , Bolikas Emmanouil , Diamantopoulos Vasilios , Tzimitreas Athanasios , Papadopoulos Christos , Farmaki Evangelia , Sofos Antonis , Chini Maria , Tsolia Maria , Papaevangelou Vassiliki , Ntzani Evangelia E. , Gikas Achilleas , Prezerakos Panagiotis , Hadjichristodoulou Christos
Published: October 2021

A Knowledge, Attitudes and Practices (KAP) study was conducted at the end of May 2021 engaging 1456 healthcare workers (HCWs) from 20 hospitals throughout Greece. Acceptance of vaccination against coronavirus disease 2019 (COVID-19) was estimated at 77.7%, with lower vaccine acceptance identified in nurses compared to physicians. Fears related to vaccine safety, lack of information and general knowledge about vaccinations, influenza vaccine acceptance, education level and years of practice were among the factors independently associated with vaccine acceptance. A strong association was identified between vaccination of HCWs in each health region and the population coverage, indicating that HCWs may be role models for the general population. Information campaigns should continue despite decisions taken regarding mandatory vaccinations.
The Impact of Mobility Restriction Strategies in the Control of the COVID-19 Pandemic: Modelling the Relation between COVID-19 Health and Community Mobility Data
Authors: Al Wahaibi Adil , Al Maani Amal , Alyaquobi Fatma , Al Manji Abdullah , Al Harthy Khalid , Al Rawahi Bader , Alqayoudhi Abdullah , Al Khalili Sulien , Al-Jardani Amina , Al-Abri Seif
Published: October 2021

Background: Non-pharmaceutical interventions (NPIs), particularly mobility restrictions, are mainstay measures for the COVID-19 pandemic worldwide. We evaluated the effects of Oman’s mobility restriction strategies to highlight their efficacy in controlling the pandemic. Methods: Accessible national data of daily admissions and deaths were collected from 1 April 2020 to 22 May 2021. Google Community Mobility Report (CMR) data were downloaded for the same period. Among six CMR categories, three were used and reduced to one index—the community mobility index (CMI). We used a generalised linear model with a negative binomial distribution combined with a non-linear distributed lag model to investigate the short-term effects of CMI on the number of admitted PCR-confirmed COVID-19 cases and deaths, controlling for public holidays, day of the week, and Eid/Ramadan days. Results: We demonstrated the feasibility of using CMRs in the evaluation and monitoring of different NPIs, particularly those related to movement restriction. The best movement restriction strategy was a curfew from 7 p.m. to 5 a.m. (level 3 of CMI = 8), which had a total reduction of 35% (95% confidence interval (CI); 25–44%) in new COVID-19 admissions in the following two weeks, and a fatality reduction in the following four weeks by 52% (95% CI; 11–75%). Conclusion: Evening lockdown significantly affected the course of the pandemic in Oman which lines up with similar studies throughout the world.
Analysis of Policies to Protect the Health of Urban Refugees and Asylum Seekers in Thailand: A Qualitative Study and Delphi Survey
Authors: Julchoo Sataporn , Phaiyarom Mathudara , Sinam Pigunkaew , Kunpeuk Watinee , Pudpong Nareerut , Suphanchaimat Rapeepong
Published: October 2021

The health of urban refugees and asylum seekers (URAS) in Bangkok has been neglected and health policies for USAR have not materialized. This study aimed to explore the views of stakeholders on policies to protect URAS well-being in Thailand. This study conducted a mixed-methods approach comprising both in-depth interviews and Delphi survey. The interview findings revealed six main themes: (1) the government position on URAS; (2) opinions on Thailand becoming a party of the 1951 Refugee Convention; (3) NGOs on health promotion for URAS; (4) options on health insurance management for URAS; (5) working potential of URAS; and (6) uncertainty of future life plans for URAS. The Delphi survey showed that URAS should have the right to acquire a work permit and be enrolled in the public insurance scheme managed by the Ministry of Public Health. Moreover, the ideology of national security was more influential than the concept of human rights. The ambiguity of the central authorities’ policy direction to take care of URAS creates haphazard legal interpretations. The Delphi survey findings suggested the need for a more inclusive policy for URAS, however actual policy implementation requires further research on policy feasibility and acceptance by the wider public.
Analysis of the Research Methodology in Spanish Doctoral Theses on Handball. A Systematic Review
Authors: Antúnez Antonio , Ibáñez Sergio J. , Feu Sebastian
Published: October 2021

The objective of this investigation was to analyze scientific production assessed by indexed doctoral theses in the Ordered Spanish Theses (TESEO) database, on the topic of the sport of handball in Spain. Productivity was analyzed on the basis of variables grouped by contextual information, methodologies and procedures. Seventy-two indexed theses from between 1976 and 2021 were analyzed. A progressive increase was identified in scientific production based on these theses during this period. The scientific disciplines that presented the highest number of theses were Sport Sciences (n = 33) and Sport Pedagogy (n = 19). The main results show that quantitative approaches are the most common (n = 49), doctoral theses using descriptive studies based on systematic observation represent the majority (73%), the predominant type of data collection was the use of cross-sectional studies (70.8%) versus longitudinal studies (26.4%), and the most used sampling method was that of convenience (n = 65). The results make it possible to ascertain the reality of this research topic, the methodological positioning and research tendencies, and to draw the basic lines for development.
Effects of Anger and Moral Identity on the Relationship between Supervisors’ Incivility and Deviant Behavior: A Study of Public Service Officers in Republic of Korea
Authors: Kim Yong Hyun , Son Seung Yeon , Kang Seung-Wan
Published: October 2021

This study investigated the effects of supervisors’ incivility regarding employees’ deviant behavior, the mediating effect of anger, and the moderating role of moral identity in the relationship between incivility and deviant behavior. To test our hypotheses, we collected data from supervisor–employee dyads in South Korean military units, applying a time-lagged design, hierarchical regression, and SPSS macro. The results elicited three relevant findings. First, supervisors’ incivility was found to positively influence employees’ deviant behavior. Second, employees’ anger was confirmed to have a mediating effect between supervisors’ incivility and employees’ deviant behavior. Third, the analysis demonstrated that moral identity moderates the relationship between anger and deviant behavior, and incivility through anger has an indirect effect on deviant behavior. These findings imply that supervisors’ incivility, which is readily observed within the organization, is a harmful behavior that increases anger and deviant behavior. These findings suggest that negative leadership should be minimized and employees with high moral identity should be selected to reduce deviant behavior that harms the organization.
Effect of Rest Period Duration between Sets of Repeated Sprint Skating Ability Test on the Skating Ability of Ice Hockey Players
Authors: Baron Jakub , Gupta Subir , Bieniec Anna , Klich Grzegorz , Gabrys Tomasz , Swinarew Andrzej Szymon , Svatora Karel , Stanula Arkadiusz
Published: October 2021

The aim of this study was to determine the effects of two different rest periods, 2 min and 3 min, between consecutive sets of a repeated sprint skating ability (RSSA) test, on the skating ability of ice hockey players. Two RSSA tests, RSSA-2 and RSSA-3, were assessed on 24 ice hockey players. In RSSA-2, six sets of 3 × 80 m sprint skating, with 2 min passive recovery between two consecutive sets was allowed. In RSSA-3, the recovery period between the sets was 3 min. Average speed, average heart rate (HRaver), peak heart rate (HRpeak), blood lactate concentration ([BLa]), and rate of perceived exertion (RPE) were measured in both RSSA-2 and RSSA-3 tests. In all the sets, except set 1, the average speed of the subjects was significantly (p < 0.05) higher in RSSA-3 than the respective set in RSSA-2. Average HR and RPE were higher in RSSA-2 than RSSA-3 in most of the sets. For any given set, no difference in HRpeak was noted between RSSA-2 and RSSA-3. Post-sprint (Set 6) [BLa] was significantly (p < 0.05) higher in RSSA-3 than RSSA-2. This study concludes that the 3 min rest period is more beneficial than the 2 min rest period, for (1) increasing skating speed and (2) reducing overall cardiac workload and perceived fatigue.
Effects of Fine Particulate Matter and Its Components on Emergency Room Visits for Pediatric Pneumonia: A Time-Stratified Case-Crossover Study
Authors: Tsai Ming-Ta , Ho Yu-Ni , Chiang Charng-Yen , Chuang Po-Chun , Pan Hsiu-Yung , Chiu I-Min , Tsai Chih-Min , Cheng Fu-Jen
Published: October 2021

Pneumonia, one of the important causes of death in children, may be induced or aggravated by particulate matter (PM). Limited research has examined the association between PM and its constituents and pediatric pneumonia-related emergency department (ED) visits. Measurements of PM2.5, PM10, and four PM2.5 constituents, including elemental carbon (EC), organic carbon (OC), nitrate, and sulfate, were extracted from 2007 to 2010 from one core station and two satellite stations in Kaohsiung City, Taiwan. Furthermore, the medical records of patients under 17 years old who had visited the ED in a medical center and had a diagnosis of pneumonia were collected. We used a time-stratified, case-crossover study design to estimate the effect of PM. The single-pollutant model demonstrated interquartile range increase in PM2.5, PM10, nitrate, OC, and EC on lag 3, which increased the risk of pediatric pneumonia by 18.2% (95% confidence interval (Cl), 8.8–28.4%), 13.1% (95% CI, 5.1–21.7%), 29.7% (95% CI, 16.4–44.5%), 16.8% (95% CI, 4.6–30.4%), and 14.4% (95% Cl, 6.5–22.9%), respectively. After PM2.5, PM10, and OC were adjusted for, nitrate and EC remained significant in two-pollutant models. Subgroup analyses revealed that nitrate had a greater effect on children during the warm season (April to September, interaction p = 0.035). In conclusion, pediatric pneumonia ED visit was related to PM2.5 and its constituents. Moreover, PM2.5 constituents, nitrate and EC, were more closely associated with ED visits for pediatric pneumonia, and children seemed to be more susceptible to nitrate during the warm season.
Machine Learning to Identify Interaction of Single-Nucleotide Polymorphisms as a Risk Factor for Chronic Drug-Induced Liver Injury
Authors: Moore Roland , Ashby Kristin , Liao Tsung-Jen , Chen Minjun
Published: October 2021

Drug-induced liver injury (DILI) is a major cause of drug development failure and drug withdrawal from the market after approval. The identification of human risk factors associated with susceptibility to DILI is of paramount importance. Increasing evidence suggests that genetic variants may lead to inter-individual differences in drug response; however, individual single-nucleotide polymorphisms (SNPs) usually have limited power to predict human phenotypes such as DILI. In this study, we aim to identify appropriate statistical methods to investigate gene–gene and/or gene–environment interactions that impact DILI susceptibility. Three machine learning approaches, including Multivariate Adaptive Regression Splines (MARS), Multifactor Dimensionality Reduction (MDR), and logistic regression, were used. The simulation study suggested that all three methods were robust and could identify the known SNP–SNP interaction when up to 4% of genotypes were randomly permutated. When applied to a real-life DILI chronicity dataset, both MARS and MDR, but not logistic regression, identified combined genetic variants having better associations with DILI chronicity in comparison to the use of individual SNPs. Furthermore, a simple decision tree model using the SNPs identified by MARS and MDR was developed to predict DILI chronicity, with fair performance. Our study suggests that machine learning approaches may help identify gene–gene interactions as potential risk factors for better assessing complicated diseases such as DILI chronicity.
Urinary Proteomics of Simulated Firefighting Tasks and Its Relation to Fitness Parameters
Authors: Zhu Ting , Hu Yuxiang , Hwang Jooyeon , Zhao Dan , Huang Libin , Qiao Liang , Wei Ankui , Xu Xin
Published: October 2021

Firefighting rescues are high-hazard activities accompanied by uncertainty, urgency, and complexity. Knowledge of the metabolic characteristics during firefighting rescues is of great value. The purpose of this study was to explore the firefighting-induced physiological responses in greater depth. The urine samples of ten firefighters were collected before and after the simulated firefighting, and the proteins in urine samples were identified by the liquid chromatography–mass spectroscopy. Blood lactate and heart rate were measured. There were 360 proteins up-regulated and 265 proteins downregulated after this simulated firefighting. Changes in protein expression were significantly related to acute inflammatory responses, immune responses, complement activation, and oxidative stress. Beta-2-microglobulin (r = 0.76, p < 0.05) and von Willebrand factors (r = 0.81, p < 0.01) were positively correlated with heart rate during simulated firefighting, and carbonic anhydrase 1 (r = 0.67, p < 0.05) were positively correlated with blood lactate after simulated firefighting. These results illustrated that Beta-2-microglobulin, von Willebrand, and carbonic anhydrase 1 could be regarded as important indicators to evaluate exercise intensity for firefighters.
The Țigani Community Adaptability to Changes in Rural Romania and the COVID-19 Impact
Authors: Voda Mihai , Murgu Andrei , Sarpe Constantin Adrian , Graves Steven M. , Avram Calin
Published: October 2021

Romanian rural villages are struggling to survive present times when youngsters leave for a better life in the city while elders work the land like a hundred years ago. Our paper integrates human environments research with public health preparedness, presenting the Țigani (Gypsy/Roma) ethnic group from rural Romania as an example to the world. The future security of mankind will require a new understanding of the human place in its environment. That will lead to a new society, not the most powerful or intelligent, but the one that is more adaptable to changes, with sensitive and interconnected community members. Therefore, the Țigani ethnic group that fought for its rights and flourished despite unfavorable odds, including the recent COVID-19 pandemic, represents the best example for a new world that prioritizes humans, promotes health and wellbeing, facilitating innovation and transformative networks environmental integration. This research attempts to quantify the Țigani′s unique attributes that helped their communities survive and made them more adaptive to change. Always marginalized, they identified the other ethnic groups’ weaknesses to penetrate the villages and learned to use the smartphone apps to communicate, for their trades, coppersmith, metal roof tiles and drainage systems. Our research was based on Geographical Information System, Microsoft Power Bi analytics data visualization tools and statistical analysis with SPSS V20 to demonstrate what enables their flourishing and what resistance they face locally. We argue that the Țigani′s intense social cooperation, strong sense of family, community and mutual assistance helped them to fight COVID-19, generating their significant adaptability to the societal changes and their power to keep intact their cultural identity. The results show how the constant growing Țigani population changed and may change Romania′s rural environments in the future.
Simultaneous Determination of Seven Antibiotics and Five of Their Metabolites in Municipal Wastewater and Evaluation of Their Stability under Laboratory Conditions
Authors: Han Sheng , Li Xinyue , Huang Hongmei , Wang Ting , Wang Zhenglu , Fu Xiaofang , Zhou Zilei , Du Peng , Li Xiqing
Published: October 2021

The selection and spread of antibiotic resistance poses risks to public health by reducing the therapeutic potential of antibiotics against human pathogens. Wastewater-based epidemiology (WBE) is potentially the most reliable approach to estimate antibiotics use. Previous WBE studies used parent antibiotics as biomarkers, which may lead to overestimation since parent antibiotics may be directly disposed of. Using metabolites as biomarkers can avoid this drawback. This study developed a simultaneous solid-phase extraction coupled with ultra-high-performance liquid chromatography tandem mass spectrometry method for analyzing 12 antibiotics and human metabolites in wastewater to help assess health risk. Optimum conditions were achieved using a PEP cartridge at pH 3.0. The extraction efficiencies were 73.3~95.4% in influent and 72.0~102.7% in effluent for most of the target analytes. Method detection limit ranged from 0.1 to 1.5 ng/L for influent wastewater and 0.03 to 0.7 ng/L for effluent wastewater. A stability experiment showed that sulfonamide parents and their metabolites were stable at 4 °C, −20 °C and −80 °C, while macrolides metabolites were more stable than their corresponding parents at 4 °C and −20 °C. Finally, the method was applied to measure these analytes in wastewater samples collected from three Beijing WWTPs and to derive apparent removal rates. All metabolites were detected in wastewater samples with concentrations ranging from 1.2 to 772.2 ng/L in influent, from <MDL to 235.6 ng/L in effluent. The apparent removal rates of five metabolites were above 72.6%. These results set a solid foundation for applying WBE to evaluate antibiotics use and its public health effects.
Vegetation Coverage Prediction for the Qinling Mountains Using the CA–Markov Model
Authors: Cui Lu , Zhao Yonghua , Liu Jianchao , Wang Huanyuan , Han Ling , Li Juan , Sun Zenghui
Published: October 2021

The Qinling Mountains represent the dividing line of the natural landscape of north-south in China. The prediction on vegetation coverage is important for protecting the ecological environment of the Qinling Mountains. In this paper, the data accuracy and reliability of three vegetation index data (GIMMS NDVI, SPOT NDVI, and MODIS NDVI) were compared at first. SPOT, NDVI, and MODIS NDVI were used for calculating the vegetation coverage in the Qinling Mountains. Based on the CA–Markov model, the vegetation coverage grades in 2008, 2010, and 2013 were used to simulate the vegetation coverage grade in 2025. The results show that the grades of vegetation coverage of the Qinling Mountains calculated by SPOT, NDVI, and MODIS NDVI are highly similar. According to the prediction results, the grade of vegetation coverage in the Qinling Mountains has a rising trend under the guidance of the policy, particularly in urban areas. Most of the vegetation coverage transit from low vegetation coverage to middle and low vegetation coverage. The grades of the vegetation coverage, which were predicted by the CA–Markov model using SPOT, NDVI, and MODI NDVI, are consistent in spatial distribution and temporal variation.