bluuebunny/crossref_metadata_2025 huggingface dataset:
Site-Specific Response Spectra: Guidelines for Engineering Practice
Authors: Hu Yiwei , Lam Nelson , Khatiwada Prashidha , Menegon Scott Joseph , Looi Daniel T. W.
Published: September 2021

Code response spectrum models, which are used widely in the earthquake-resistant design of buildings, are simple to apply but they do not necessarily represent the real behavior of an earthquake. A code response spectrum model typically incorporates ground motion behavior in a diversity of earthquake scenarios affecting the site and does not represent any specific earthquake scenario. The soil amplification phenomenon is also poorly represented, as the current site classification scheme contains little information over the potential dynamic response behavior of the soil sediments. Site-specific response spectra have the merit of much more accurately representing real behavior. The improvement in accuracy can be translated into significant potential cost savings. Despite all the potential merits of adopting site-specific response spectra, few design engineers make use of these code provisions that have been around for a long time. This lack of uptake of the procedure by structural designers is related to the absence of a coherent set of detailed guidelines to facilitate practical applications. To fill in this knowledge gap, this paper aims at explaining the procedure in detail for generating site-specific response spectra for the seismic design or assessment of buildings. Surface ground motion accelerograms generated from the procedure can also be employed for nonlinear time-history analyses where necessary. A case study is presented to illustrate the procedure in a step-by-step manner.
An Adaptive Hybrid Model for Determining Subjective Causal Relationships in Fuzzy System Dynamics Models for Analyzing Construction Risks
Authors: Fateminia Seyed Hamed , Nguyen Phuong Hoang Dat , Fayek Aminah Robinson
Published: September 2021

Modeling risk management systems in construction projects is a complex process because of various internal and external factors and their interrelationships. Fuzzy system dynamics (FSD) have been commonly employed to model and analyze construction risk management systems. To run FSD simulation models, all hard (objective) and soft (subjective) causal relationships between variables must be quantified. However, a research gap exists regarding structured methods for constructing soft causal relationships in FSD models. This paper proposes an adaptive hybrid model consisting of fuzzy analytical hierarchy process, weighted principle of justifiable granularity, and fuzzy aggregation operators to determine crisp values of causality degree for soft (subjective) causal relationships in FSD modeling of construction risk analysis. The proposed model is implemented in analyzing construction risks of a windfarm project to illustrate its applicability. The proposed model generates two results: (1) optimized membership functions for linguistic terms representing the causality degree of soft relationships and (2) the crisp value for the causality degree of soft relationships. The contribution of study is to propose a structured model to improve efficiency and effectiveness of developing FSD quantitative modeling by addressing soft causal relationships between different variables in FSD models and considering multiple risk expertise of heterogeneous experts in construction risk assessment.
Students in Dormitories Were Not Major Drivers of the Pandemic during Winter Term 2020/2021: A Cohort Study with RT-PCR and Antibody Surveillance in a German University City
Authors: Torres Reyes Christian Rafael , Steinmann Eike , Timmesfeld Nina , Trampisch Hans-Joachim , Stein Julien , Schütte Christian , Skrygan Marina , Meyer Thomas , Sakinc-Güler Türkan , Schlottmann Renate , Brüggemann Yannick , Todt Daniel , Walker Andreas , Lübke Nadine , Quast Daniel Robert , Schmidt Wolfgang Ekkehard
Published: September 2021

The role of educational facilities, including schools and universities, in the SARS-CoV-2 pandemic is heavily debated. Specifically, the risk of infection in student dormitories has not been studied. This cohort study monitored students living in dormitories in Bochum, Germany, throughout the winter term of 2020/2021. Over the course of four months, participants were tested repeatedly for SARS-CoV-2 infections using RT-PCR from gargle samples and serological testing. An online questionnaire identified individual risk factors. A total of 810 (46.5% female) students participated. Of these, 590 (72.8%) students participated in the final visit. The cross-sectional antibody prevalence was n = 23 (2.8%) in November 2020 and n = 29 (4.9%) in February 2021. Of 2513 gargle samples analyzed, 19 (0.8%) tested positive for SARS-CoV-2, corresponding to 14 (2.4%) infections detected within the study period. Gargle samples available of cases with confirmed present infection were always positive. The person-time incidence rate was 112.7 (95% CI: 54.11–207.2) per 100,000 person weeks. The standardized incidence ratio was 0.9 (95% CI 0.51–1.46, p = 0.69). In conclusion, students living in student dormitories do not appear to be major drivers of SARS-CoV-2 infections. RT-PCR from gargle samples is a patient-friendly and scalable surveillance tool for detection of SARS-CoV-2 infections.
Self-Compatibility and Reproductive Success of Oenothera drummondii subsp. drummondii: Is It Similar between Native and Non-Native Populations?
Authors: Gallego-Fernández Juan B. , García-Franco José G.
Published: September 2021

The mating system of plants widely distributed can change in native range but also in non-native habitats. Oenothera drummondii, native to the coastal dunes of the Gulf of Mexico, has been introduced to Europe, Africa, Asia and Oceania. Hand self- and cross-pollination were performed to determine compatibility and to compare fruit set, fruit weight, seed set and germination characteristics from natives and non-natives populations and a comprehensive integral reproductive success index (IRSI) was built. Oenothera drummondii exhibited high self-compatibility and mixed reproductive systems in all populations. Characteristics of fruits and seeds from self- and cross-pollination varied within and between native and non-native populations and some had a positive clinal variation in the native range. The IRSI was sensitive to changes of fruit set, seed set and final germination of both self- and cross-pollination, showing differences between native populations. Differences in characteristics of fruits and seeds in the native and non-native ranges suggest the occurrence of distinct selection factors. The mixed reproductive system of O. drummondii suggests it can take advantage of local visitors in the native range, but also can provide advantages for the establishment at non-native sites giving the opportunity to interact with local flower visitors.
Development of a Dynamic Hands-Free Door Opener to Prevent COVID-19 Pandemic Spreading
Authors: Maranha Vítor , Maia Pedro , Margalho Luís , Lourenço Nicolle , Oliveira Diogo , Maurício Diogo , Caseiro João F. , Roseiro Luis
Published: September 2021

The situation caused by COVID-19 has shown several vulnerabilities in the attitudes and habits of modern society, inducing the need to adopt new behaviors that will directly impact daily activities. The quickly spreading virus contaminates the surfaces of handles and objects, and subsequent contact with the eyes, nose, or mouth is one of the main contagion factors. There is an urgent need to rethink how we interact with the most-touched surfaces, such as door handles in public places with a high flux of people. A revision was performed of the most-used door handles to develop a proposal that could be applied to already existing models, thus avoiding the need for their total replacement. Through interaction between engineering, design, and ergonomics, an auxiliary hands-free door opener device was developed, following iteration improvement from an initial static geometry and culminating in a dynamic system aiming to provide greater ergonomic comfort in its use. The development followed a methodology using 3D modelling supported by 3D printing of the various components to accurately understand their functioning. In addition, the finite element method supported the prediction of the structural behavior of the developed systems. The final models were produced through CNC machining and submitted to functional validation tests with volunteers. The developed HFDO demonstrated relevant differentiation from the existing models on the market: for its geometry and material, but mainly for its strong emphasis on the interaction between the object and the user, resulting from the dynamic component in its use/manipulation.
Novel Insights into the Role of Probiotics in Respiratory Infections, Allergies, Cancer, and Neurological Abnormalities
Authors: Balta Igori , Butucel Eugenia , Mohylyuk Valentyn , Criste Adriana , Dezmirean Daniel Severus , Stef Lavinia , Pet Ioan , Corcionivoschi Nicolae
Published: September 2021

In recent years, probiotics have attracted public attention and transformed the social perception of microorganisms, convening a beneficial role/state on human health. With aging, the immune system, body physiology, and intestinal microbiota tend to change unfavorably, resulting in many chronic conditions. The immune-mediated disorders can be linked to intestinal dysbiosis, consequently leading to immune dysfunctions and a cluster of conditions such as asthma, autoimmune diseases, eczema, and various allergies. Probiotic bacteria such as Lactobacillus and Bifidobacterium species are considered probiotic species that have a great immunomodulatory and anti-allergic effect. Moreover, recent scientific and clinical data illustrate that probiotics can regulate the immune system, exert anti-viral and anti-tumoral activity, and shields the host against oxidative stress. Additionally, microbiota programming by probiotic bacteria can reduce and prevent the symptoms of respiratory infections and ameliorate the neurological status in humans. This review describes the most recent clinical findings, including safe probiotic therapies aiming to medicate respiratory infections, allergies, cancer, and neurological disorders due to their physiological interconnection. Subsequently, we will describe the major biological mechanism by which probiotic bacteriotherapy expresses its anti-viral, anti-allergic, anticancer, and neuro-stimulatory effects.
Role of Active Morphing in the Aerodynamic Performance of Flapping Wings in Formation Flight
Authors: Billingsley Ethan , Ghommem Mehdi , Vasconcellos Rui , Abdelkefi Abdessattar
Published: September 2021

Migratory birds have the ability to save energy during flight by arranging themselves in a V-formation. This arrangement enables an increase in the overall efficiency of the group because the wake vortices shed by each of the birds provide additional lift and thrust to every member. Therefore, the aerodynamic advantages of such a flight arrangement can be exploited in the design process of micro air vehicles. One significant difference when comparing the anatomy of birds to the design of most micro air vehicles is that bird wings are not completely rigid. Birds have the ability to actively morph their wings during the flapping cycle. Given these aspects of avian flight, the objective of this work is to incorporate active bending and torsion into multiple pairs of flapping wings arranged in a V-formation and to investigate their aerodynamic behavior using the unsteady vortex lattice method. To do so, the first two bending and torsional mode shapes of a cantilever beam are considered and the aerodynamic characteristics of morphed wings for a range of V-formation angles, while changing the group size in order to determine the optimal configuration that results in maximum propulsive efficiency, are examined. The aerodynamic simulator incorporating the prescribed morphing is qualitatively verified using experimental data taken from trained kestrel flights. The simulation results demonstrate that coupled bending and twisting of the first mode shape yields the highest propulsive efficiency over a range of formation angles. Furthermore, the optimal configuration in terms of propulsive efficiency is found to be a five-body V-formation incorporating coupled bending and twisting of the first mode at a formation angle of 140 degrees. These results indicate the potential improvement in the aerodynamic performance of the formation flight when introducing active morphing and bioinspiration.
Use of Satellite Data for Air Pollution Modeling in Bulgaria
Authors: Georgieva Emilia , Syrakov Dimiter , Atanassov Dimiter , Spassova Tatiana , Dimitrova Maria , Prodanova Maria , Veleva Blagorodka , Kirova Hristina , Neykova Nadya , Neykova Rozeta , Hristova Elena , Petrov Anton
Published: September 2021

Air pollution continues to be of concern for Bulgarian cities, mainly due to particulate matter of aerodynamic diameter smaller than 10 μm (PM10). There is public and expert interest in the improvement of two operational air quality modeling systems: the Bulgarian Chemical Weather Forecast System (BgCWFS) and the Local Air Quality Management System (LAQMS) for the city of Plovdiv. The aim of the study is to investigate the effects of satellite data assimilation in BgCWFS on surface concentrations over Bulgaria (resolution 9 km), to downscale BgCWFS output to LAQMS (resolution 250 m), and to examine effects on PM10 in Plovdiv. Data from the Global Ozone Monitoring Experiment-2 (GOME-2) (MetOP satellites) for aerosols, nitrogen dioxide (NO2), and sulfur dioxide (SO2) were assimilated in BgCWFS using objective analysis. Simulation experiments with and without satellite data were conducted for a summer and a winter month. The comparison to surface observations in the country showed improvement of results when using satellite data, especially in the summer due to mineral dust events captured by satellites. The decrease in the normalized mean bias (NMB) over the two months was 43% (PM10) and 73% (SO2). The LAQMS estimated background contributions to PM10 in the city as 32%. The absolute NMB by LAQMS decreased by 38%.
Learning to Classify the Consumer Confidence Indicator (in Portugal)
Authors: Caleiro António Bento
Published: September 2021

The literature paid some attention, some time ago, to the relationship that, supposedly, should exist between the level of consumer confidence and the unemployment rate. This relationship is interesting, both from a scientific point of view, given the inherently subjective character of that level of confidence, but also from the point of view of economic policy, given the importance of the unemployment rate. In this article, that relationship is revisited, using learning models, namely regression and classification trees. Using, for example, the case of Portugal, the unemployment rate presents itself as an adequate classifier of the consumer confidence level. The use of classification trees shows that the separation between low and high values of the consumer confidence indicator is made from an adequate threshold value of the unemployment rate. The use of regression trees shows that the levels of consumer confidence are inversely related to the levels of the unemployment rate. In terms of policy lessons, this confirms that, in the face of economic crises, such as the one we are experiencing, in which confidence levels tend to fall and the unemployment rate increases, the relationship between these two variables cannot be ignored.
The Influence of Gender and Educational Attainment Differences on International Migrants’ Occupational Status in OECD Countries
Authors: Al-Dalahmeh Main , Sarihasan Imran , Dajnoki Krisztina
Published: September 2021

The purpose of the study is to show two essential elements of the occupational status of international migrants in OECD countries. The study extends the current research by focusing on how the educational attainment of international migrants and the gender dimension affect migrants’ occupational status. To achieve the aim of the study, a quantitative research approach was followed. Ordinary least square regression analysis was used to emphasize the relationship between educational attainment and gender differences, and occupational status. The databases were taken from the OECD DIOC 2015/2016. It has been found that high-level educational attainment matches with representative vacancies, and female migrants tend to have those occupations more than male migrants in OECD countries. On the other hand, the study’s limitations included a lack of data on testing the exact occupational status of migrants in OECD countries, as well as educational attainment levels that were not specifically divided into each level of education in the databases.
The Effects of Information and Communication Technology (ICT) Use on Human Development—A Macroeconomic Approach
Authors: Karaman Aksentijević Nada , Ježić Zoran , Zaninović Petra Adelajda
Published: September 2021

Information and communication technology (ICT) is considered a significant factor in economic growth and development. Over the past two decades, scholars have studied the impact of ICT on economic growth, but there has been little research that has addressed the impact of ICT on human development, which is considered one of the fundamental factors of economic development. This could be especially important from the perspective of developing countries, which can develop faster through the implementation of ICT. Thus, the aim of this paper is to investigate the effects of ICT use on human development, distinguishing effects among high, upper-middle, lower-middle and low-income countries following the World Bank classification 2020. Our sample includes 130 countries in the period from 2007 to 2019. The empirical analysis is based on dynamic panel data regression analysis. We use Generalized Method of Moments (GMM) as an estimator, i.e., two-step system GMM. The results primarily support the dynamic behaviour of human development. The results of the analysis also show that ICT has highly significant positive effects on human development in lower-middle-income and low-income countries, while the effects do not appear to be significant in high- and middle-income countries. This research serves as an argument for the need to invest in ICT and its implementation in low-income countries; however, it also suggests that the story is not one-sided and that there are possible negative effects of ICT use on human development. From the perspective of economic policy, the results can be a guideline for the implementation and use of ICT in developing countries, which could lead to economic growth and development and thus better quality of life. On the other hand, policymakers in developed countries cannot rely on ICT alone; they should also consider other technological innovations that could ensure a better quality of life.
Perceptions and Degree of Satisfaction with the Health Sciences University Educational Community Regarding the Measures Adopted for the Prevention of COVID-19 in the Academic Year 2020/2021
Authors: Rodríguez-Nogueira Óscar , Leirós-Rodríguez Raquel , Quiroga-Sánchez Enedina , Álvarez-Álvarez Mª José , Álvarez-Barrio Lorena
Published: September 2021

The COVID-19 pandemic caused the start of the academic year 2020/2021 to be conditioned by health and safety regulations. The present research was defined with the aim of analyzing the degree of satisfaction and perceptions on the establishment of bubble groups and pairs and on the use of audiovisual platforms for the development of theoretical and practical university teaching in three degrees of health sciences. A cross-sectional descriptive study was carried out on a representative sample of students and teachers of health sciences in Ponferrada (n = 285). Specific questionnaires designed for this study were completed virtually during April and May 2021. The results indicate that that satisfaction was moderate–high. The perception of the influence of bubble pairs on the quality of teaching can be interpreted as very low. These results increase with the age and academic and professional experience of students and faculty members, respectively. However, the participants belonging to physiotherapy considered that the quality of teaching had worsened much more compared to their counterparts in nursing and podiatry.
A Regularized Procedure to Generate a Deep Learning Model for Topology Optimization of Electromagnetic Devices
Authors: Tucci Mauro , Barmada Sami , Formisano Alessandro , Thomopulos Dimitri
Published: September 2021

The use of behavioral models based on deep learning (DL) to accelerate electromagnetic field computations has recently been proposed to solve complex electromagnetic problems. Such problems usually require time-consuming numerical analysis, while DL allows achieving the topologically optimized design of electromagnetic devices using desktop class computers and reasonable computation times. An unparametrized bitmap representation of the geometries to be optimized, which is a highly desirable feature needed to discover completely new solutions, is perfectly managed by DL models. On the other hand, optimization algorithms do not easily cope with high dimensional input data, particularly because it is difficult to enforce the searched solutions as feasible and make them belong to expected manifolds. In this work, we propose the use of a variational autoencoder as a data regularization/augmentation tool in the context of topology optimization. The optimization was carried out using a gradient descent algorithm, and the DL neural network was used as a surrogate model to accelerate the resolution of single trial cases in the due course of optimization. The variational autoencoder and the surrogate model were simultaneously trained in a multi-model custom training loop that minimizes total loss—which is the combination of the two models’ losses. In this paper, using the TEAM 25 problem (a benchmark problem for the assessment of electromagnetic numerical field analysis) as a test bench, we will provide a comparison between the computational times and design quality for a “classical” approach and the DL-based approach. Preliminary results show that the variational autoencoder manages regularizing the resolution process and transforms a constrained optimization into an unconstrained one, improving both the quality of the final solution and the performance of the resolution process.
PSO Based Optimized Ensemble Learning and Feature Selection Approach for Efficient Energy Forecast
Authors: Shafqat Wafa , Malik Sehrish , Lee Kyu-Tae , Kim Do-Hyeun
Published: September 2021

Swarm intelligence techniques with incredible success rates are broadly used for various irregular and interdisciplinary topics. However, their impact on ensemble models is considerably unexplored. This study proposes an optimized-ensemble model integrated for smart home energy consumption management based on ensemble learning and particle swarm optimization (PSO). The proposed model exploits PSO in two distinct ways; first, PSO-based feature selection is performed to select the essential features from the raw dataset. Secondly, with larger datasets and comprehensive range problems, it can become a cumbersome task to tune hyper-parameters in a trial-and-error manner manually. Therefore, PSO was used as an optimization technique to fine-tune hyper-parameters of the selected ensemble model. A hybrid ensemble model is built by using combinations of five different baseline models. Hyper-parameters of each combination model were optimized using PSO followed by training on different random samples. We compared our proposed model with our previously proposed ANN-PSO model and a few other state-of-the-art models. The results show that optimized-ensemble learning models outperform individual models and the ANN-PSO model by minimizing RMSE to 6.05 from 9.63 and increasing the prediction accuracy by 95.6%. Moreover, our results show that random sampling can help improve prediction results compared to the ANN-PSO model from 92.3% to around 96%.
Two-Stage Clock-Free Time-to-Digital Converter Based on Vernier and Tapped Delay Lines in FPGA Device
Authors: Szplet Ryszard , Czuba Arkadiusz
Published: September 2021

This article presents an idea, design and test results of a new time-to-digital converter (TDC) implemented in an FPGA device. The high resolution of 13 ps and measurement range of 3.4 ns are achieved based on a two-stage time interpolation (TI). In the first and second stages of the TI we have used the Vernier delay line and a single tapped delay line, respectively. This solution provides respectable metrological parameters without the need to use a clock signal, and significantly saves the logical resources of an integrated circuit (IC). The proposed method, generally based on two different variants of the discrete delay line, is easy to design and implement in digital ICs. For experimental verification, the TDC was implemented in a single programmable device from family Virtex-7 (Xilinx).
Remote Laboratory for E-Learning of Systems on Chip and Their Applications to Nuclear and Scientific Instrumentation
Authors: Crespo Maria Liz , Foulon François , Cicuttin Andres , Bogovac Mladen , Onime Clement , Sisterna Cristian , Melo Rodrigo , Florian Samayoa Werner , García Ordóñez Luis Guillermo , Molina Romina , Valinoti Bruno
Published: September 2021

Configuring and setting up a remote access laboratory for an advanced online school on fully programmable System-on-Chip (SoC) proved to be an outstanding challenge. The school, jointly organized by the International Centre for Theoretical Physics (ICTP) and the International Atomic Energy Agency (IAEA), focused on SoC and its applications to nuclear and scientific instrumentation and was mainly addressed to physicists, computer scientists and engineers from developing countries. The use of e-learning tools, which some of them adopted and others developed, allowed the school participants to directly access both integrated development environment software and programmable SoC platforms. This facilitated the follow-up of all proposed exercises and the final project. During the four weeks of the training activity, we faced and overcame different technology and communication challenges, whose solutions we describe in detail together with dedicated tools and design methodology. We finally present a summary of the gained experience and an assessment of the results we achieved, addressed to those who foresee to organize similar initiatives using e-learning for advanced training with remote access to SoC platforms.
Sand Production of the Shale Gas Well in Different Production Periods: Structure and Component
Authors: Li Xiangchen , Yi Lin , Fan Zhang
Published: September 2021

Complex geology and fracturing operations have led to frequent sand production problem in the shale gas well. Sand production brings huge engineering risks and seriously affects the normal production of the shale gas well. In order to study the property and source of the yielded sand, sand samples in three production periods of flowback, production test and gas production are collected from Sichuan Basin of China. Combining the methods of particle size analysis, microscope observation, scanning electron microscope, CT scanning, infrared spectroscopy and energy dispersive spectrum analysis, the multi-scale structure and composition characteristics of the yielded sand from different production periods were investigated. Results show that the sand size is the largest in the production test period and the smallest in the gas production period. The large-size sand is blocky in the flowback period, while it is flaky in the period of production test and gas production. The roundness of sand becomes worse as the sand size decreasing. Sand composition has the characteristics of fracturing proppant and shale mineral. Cementing material between large-size sands has the network structure and the higher content of aluminum and iron. Organic chemicals are found to be adhered to the sand surface in all three periods. Both shale fracture and proppant failure can generate particles that provide the material source for sand production. This research provides the source of the yielded sand and a theoretical guidance for the sand production mechanism.
A Hybrid Maximum Power Point Tracking Method without Oscillations in Steady-State for Photovoltaic Energy Systems
Authors: Hua Chih-Chiang , Zhan Yu-Jun
Published: September 2021

This paper proposes a hybrid maximum power point tracking (MPPT) method with zero oscillation in steady-state by combining genetic algorithm (GA) and perturbation and observation (P&O) method. The proposed MPPT can track the global maximum power point (GMPP) fast for a photovoltaic (PV) system even under partial shaded conditions (PSC). The oscillations around the GMPP are eliminated and the power loss can be reduced significantly. In addition, the proposed MPPT can make the PV system operate at the highest efficiencies under various atmospheric conditions. During the MPP tracking, the system will oscillate around the MPPs, resulting in unnecessary power loss. To solve the problem, the artificial intelligence (AI) algorithms, such as PSO, Bee Colony optimization, GA, etc., were developed to deal with this issue. However, the problem with the AI algorithm is that the time for convergence may be too long if the range of the MPP search space is large. In addition, if the atmospheric conditions change fast, the PV system may operate at or close to the local maximum power points (LMPPs) for a long time. In this paper, a method combining the P&O’s fast tracking and GA’s GMPP tracking ability is proposed. The proposed system can stop the oscillations as soon as the GMPP is found, thus minimizing the power loss due to oscillations. The proposed MPPT can achieve superior performance while maintaining the simplicity of implementation. Finally, the simulation and experimental results are presented to demonstrate the feasibility of the proposed system.
Energy Conservation Behaviors and Awareness of Polish, Czech and Ukrainian Students: A Case Study
Authors: Gródek-Szostak Zofia , Malinowski Mateusz , Suder Marcin , Kwiecień Klaudia , Bodziacki Stanisław , Vaverková Magdalena D. , Maxianová Alżbeta , Krakowiak-Bal Anna , Ziemiańczyk Urszula , Uskij Hrihorii , Kotulewicz-Wisińska Karolina , Lisiakiewicz Rafał , Niemczyk Agata , Szeląg-Sikora Anna , Niemiec Marcin
Published: September 2021

Energy education of the younger generation, who are the future decision makers, investors, consumers, scientists, or skilled labor force in new energy technologies, is crucial for the future of Europe and the world. However, beyond the long-term goals of energy education policies, the short-term effects on energy conservation and the promotion of renewable energy sources are equally as important. The main purpose of the paper is to identify and analyze the behavior of students (who study the issues related to energy saving and RES), in terms of energy conservation. The conducted analysis focused on examining and comparing the scope of responses of the surveyed students in individual countries, especially in the Czech Republic, Poland, and Ukraine. The survey was carried out using the computer-assisted web interview (CAWI). Descriptive and graphical methods were used to present the results. Statistical analysis of the collected data included basic measures of descriptive statistics and the chi-square test. The main results of the study are as follows: Almost 60% of the surveyed students follow the principles of energy conservation; however increased educational activities on eco-energy behaviors is recommended. The share of RES in the heating systems of the studied residential buildings is 9%, on average, with the highest percentage of houses in Poland (14%) and the lowest in Ukraine (only 2.6%). When compared with literature reports, the collect data show that educational activities can be as effective as a tool in implementing RES and pro-environmental behaviors as the government’s environmental policy and household subsidies.
Frequency Control of Large-Scale Interconnected Power Systems via Battery Integration: A Comparison between the Hybrid Battery Model and WECC Model
Authors: Abdollahi Biroon Roghieh , Pisu Pierluigi , Schoenwald David
Published: September 2021

The increasing penetration of renewable energy sources in power grids highlights the role of battery energy storage systems (BESSs) in enhancing the stability and reliability of electricity. A key challenge with the renewables’, specially the BESSs, integration into the power system is the lack of proper dynamic models and their application in power system analyses. The control design strategy mainly depends on the system dynamics which underlines the importance of the system accurate dynamic modeling. Moreover, control design for the power system is a complicated issue due to its complexity and inter-connectivity, which makes the application of distributed control to improve the stability of a large-scale power system inevitable. This paper presents an optimal distributed control design for the interconnected systems to suppress the effects of small disturbances in the power system employing utility-scale batteries based on existing battery models. The control strategy is applied to two dynamic models of the battery: hybrid model and Western electricity coordinating council (WECC) model. The results show that (i) the smart scheduling of the batteries’ output reduces the inter-area oscillations and improves the stability of the power systems; (ii) the hybrid model of the battery is more user-friendly compared to the WECC model in power system analyses.
Heating Performances of a Large-Scale Factory Evaluated through Thermal Comfort and Building Energy Consumption
Authors: Kim Daehyun , Lim Hyunmuk , Moon Jongmin , Park Jinsoo , Rhee Gwanghoon
Published: September 2021

Workshops with a large area and a high ceiling height without compartments, such as large-scale assembly factories, have an uneven thermal comfort during heating, making it difficult to establish an effective heating strategy. In this study, we evaluate the heating performance of a large-scale factory based on thermal comfort and energy flow and discuss effective heating methods. In addition, an analysis of the heating performance of a large-scale factory is attempted for the first time. To analyze the heating performance, computational fluid dynamics (CFD) and building energy simulation (BES) were used to confirm thermal comfort distribution and energy flow in a large-scale factory. Temperature distribution and thermal comfort were evaluated through CFD, and the temperature of a large-scale assembly factory was compared with experimental data. Based on the CFD results, the current heating level of large factories was predicted to be 15.4 °C, and the ADPIrev was 70%. Moreover, the BES results show that the energy losses due to forced ventilation and the inflow of outside air contributed 35.5% and 27.8%, respectively. The heating strategy proposed in this study could improve thermal comfort by 79% compared to the same energy consumption. Therefore, to improve the heating performance compared to the heating energy consumption of large-scale factory, the imbalance in thermal comfort caused by the inflow of outside air must be resolved.
Urban-Scale Computational Fluid Dynamics Simulations with Boundary Conditions from Similarity Theory and a Mesoscale Model
Authors: Bouris Demetri , Triantafyllou Athanasios G. , Krestou Athina , Leivaditou Elena , Skordas John , Konstantinidis Efstathios , Kopanidis Anastasios , Wang Qing
Published: September 2021

Mesoscale numerical weather prediction models usually provide information regarding environmental parameters near urban areas at a spatial resolution of the order of thousands or hundreds of meters, at best. If detailed information is required at the building scale, an urban-scale model is necessary. Proper definition of the boundary conditions for the urban-scale simulation is very demanding in terms of its compatibility with environmental conditions and numerical modeling. Here, steady-state computational fluid dynamics (CFD) microscale simulations of the wind and thermal environment are performed over an urban area of Kozani, Greece, using both the k-ε and k-ω SST turbulence models. For the boundary conditions, instead of interpolating vertical profiles from the mesoscale solution, which is obtained with the atmospheric pollution model (TAPM), a novel approach is proposed, relying on previously developed analytic expressions, based on the Monin Obuhkov similarity theory, and one-way coupling with minimal information from mesoscale indices (Vy = 10 m, Ty = 100 m, L*). The extra computational cost is negligible compared to direct interpolation from mesoscale data, and the methodology provides design phase flexibility, allowing for the representation of discrete urban-scale atmospheric conditions, as defined by the mesoscale indices. The results compared favorably with the common interpolation practice and with the following measurements obtained for the current study: SODAR for vertical profiles of wind speed and a meteorological temperature profiler for temperature. The significance of including the effects of diverse atmospheric conditions is manifested in the microscale simulations, through significant variations (~30%) in the critical building-related design parameters, such as the surface pressure distributions and local wind patterns.
Wind Energy Analysis in the Coastal Region of Bangladesh
Authors: Islam Khandaker Dahirul , Theppaya Thanansak , Ali Fida , Waewsak Jompob , Suepa Tanita , Taweekun Juntakan , Titseesang Teerawet , Techato Kuaanan
Published: September 2021

Diversifying the energy mix of Bangladesh is becoming indispensable not only to improve its energy security, but also for a more sustainable economic development. This study focused on mapping the wind potential of southern coastal areas of Bangladesh to estimate the wind energy potential, along with the reduction in carbon emissions due to wind energy. Analysis of the carbon footprint was based on the annual energy production (AEP) from the selected low-wind turbine generators (WTGs). The time series-measured and -predicted wind data were incorporated with the high-resolution mesoscale and microscale wind re-source mapping technique at 60, 80, and 100 m above ground level (AGL). Coupling mesoscale and microscale modeling provided reliable mapping results for the commercially exploitable wind resource and was verified by ground-based wind measurement. The results revealed that, among the selected areas, two sites named Charfashion and Monpura have a promising annual mean wind speed of 7.3 m/s at 100 m AGL for energy generation. Different WTGs with ranges of 1–3.3 MW were used to estimate the wind energy generation capacity at different sites in the study area. A WTG with a 1 MW wind energy generation capacity installed at 60 m AGL in the selected site has the potential to produce 2.79 GWh/year of clean energy, reducing 1781.689 tons of CO2 per year, whereas a 3.3 MW WTG at 80 m AGL can produce 18.99 GWh/year of energy, reducing 12,098.54 tons of CO2 per year, and a 1.6 MW WTG at 100 m AGL produces 11.04 GWh/year of energy, cutting 7035.028 tons of CO2 per year. With its reliable scientific and time-tested wind energy estimation method, this research is very important for the development of wind energy in the southern coastal areas of Bangladesh to meet the increasing energy demands through initiating the development of renewable energy to improve the energy security and reduce the carbon emissions of the country.
The Stress Axis in Obesity and Diabetes Mellitus: An Update
Authors: Gianotti Laura , Belcastro Sara , D’Agnano Salvatore , Tassone Francesco
Published: September 2021

The hypothalamic–pituitary–adrenal axis is a tightly regulated system that represents one of the body’s mechanisms for responding to acute and chronic stress. Prolonged stress and/or inadequate regulation of the stress system can lead to a condition of chronic hypercortisolism or, in some cases, a blunted cortisol response to stress, contributing to insulin resistance, increased adiposity and type 2 diabetes mellitus. Moreover, acute and chronic stress can exacerbate or worsen metabolic conditions by supporting an inflammatory state and a tight relationship between stress, inflammation and adipose tissue has been reported and has been a growing subject of interest in recent years. We reviewed and summarized the evidence supporting hypothalamic–pituitary–adrenal axis dysregulation as an important biological link between stress, obesity, inflammation and type 2 diabetes mellitus. Furthermore, we emphasized the possible role of infectious-related stress such as SarsCov2 infection in adrenal axis dysregulation, insulin resistance and diabetes in a bidirectional link. Understanding and better defining the links between stress and obesity or diabetes could contribute to further definition of the pathogenesis and the management of stress-related complications, in which the HPA axis dysregulation has a primary role.
Optimization of the Nutrient Medium for Flammulina velutipes Submerged Biomass Production and Micromorphology of Its Mycelium
Authors: Krasnopolskaya Larissa , Shuktueva Maria , Golyshkin Aleksandr , Almyasheva Nailya , Yarina Maria
Published: September 2021

Based on the assessment of the trophic needs of basidiomycete Flammulina velutipes and the optimization of the composition of the nutrient medium using design of experimental approach, the yield of the submerged biomass of the fungus was increased to 41 g/L, the duration of the cultivation process was reduced to 5 days. For this purpose, the 24 full factorial design, the Box–Wilson steep ascent method and the construction of the response surface were used. Using the method of scanning electron microscopy, it was shown that the studied F. velutipes strain grew in the form of small spherical pellets with a diameter of 1–2 mm on an optimized medium. The surface of the pellets was loose; the inner part was filled with hyphae tightly adjacent to each other. The center of the pellets had no cavity. F. velutipes pellets were formed by septate hyphae with clamp connections. The micromorphological characteristics of the submerged F. velutipes mycelium ensured a high diffusion of nutrients and oxygen into the pellets and their maximum filling of the volume of the culture medium.
Advanced Composite Retrofit of RC Columns and Frames with Prior Damages—Pseudodynamic Finite Element Analyses and Design Approaches
Authors: Rousakis Theodoros , Anagnostou Evgenia , Fanaradelli Theodora
Published: September 2021

This study develops three-dimensional (3D) finite element (FE) models of composite retrofits in deficient reinforced concrete (RC) columns and frames. The aim is to investigate critical cases of RC columns with inadequate lap splices of bars or corroded steel reinforcements and the beneficial effects of external FRP jacketing to avoid their premature failure and structural collapse. Similarly, the RC-frame FE models explore the effects of an innovative intervention that includes an orthoblock brick infill wall and an advanced seismic joint made of highly deformable polymer at the boundary interface with the RC frame. The experimental validation of the technique in RC frames is presented in earlier published papers by the authors (as well as for a four-column structure), revealing the potential to extend the contribution of the infills at high displacement ductility levels of the frames, while exhibiting limited infill damages. The analytical results of the advanced FE models of RC columns and frames compare well with the available experimental results. Therefore, this study’s research extends to critical cases of FE models of RC frames with inadequate lap splices or corroded steel reinforcements, without or with brick wall infills with seismic joints. The advanced pseudodynamic analyses reveal that for different reinforcement detailing of RC columns, the effects of inadequate lap-spliced bars may be more detrimental in isolated RC columns than in RC frames. It seems that in RC frames, additional critical regions without lap splices are engaged and redistribution of damage is observed. The detrimental effects of corroded steel bars are somewhat greater in bare RC frames than in isolated RC columns, as all reinforcements in the frame are considered corroded. Further, all critical cases of RC frames with prior damages at risk of collapse may receive the innovative composite retrofit and achieve higher base shear load than the original RC frame without corroded or lap-spliced bars, at comparable top displacement ductility. Finally, the FE analyses are utilized to propose modified design equations for the shear strength and chord rotation in cases of failure of columns with deficiencies or prior damages in RC structures.
Spatiotemporal Analysis of Active Fires in the Arctic Region during 2001–2019 and a Fire Risk Assessment Model
Authors: Zhang Zhen , Wang Leilei , Xue Naiting , Du Zhiheng
Published: September 2021

The increasing frequency of active fires worldwide has caused significant impacts on terrestrial, aquatic, and atmospheric systems. Polar regions have received little attention due to their sparse populations, but active fires in the Arctic cause carbon losses from peatlands, which affects the global climate system. Therefore, it is necessary to focus on the spatiotemporal variations in active fires in the Arctic and to assess the fire risk. We used MODIS C6 data from 2001 to 2019 and VIIRS V1 data from 2012 to 2019 to analyse the spatiotemporal characteristics of active fires and establish a fire risk assessment model based on logistic regression. The trends in active fire frequency based on MODIS C6 and VIIRS V1 data are consistent. Throughout the Arctic, the fire frequency appears to be fluctuating and overall increasing. Fire occurrence has obvious seasonality, being concentrated in summer (June–August) and highest in July, when lightning is most frequent. The frequency of active fires is related to multiple factors, such as vegetation type, NDVI, elevation, slope, air temperature, precipitation, wind speed, and distances from roads and settlements. A risk assessment model was constructed based on logistic regression and found to be accurate. The results are helpful in understanding the risk of fires in the Arctic under climate change and provide a scientific basis for fire prediction and control and for reducing fire-related carbon emissions.
Using Observed Residual Error Structure Yields the Best Estimates of Individual Growth Parameters
Authors: Curiel-Bernal Marcelo V. , Aragón-Noriega E. Alberto , Cisneros-Mata Miguel Á. , Sánchez-Velasco Laura , Jiménez-Rosenberg S. Patricia A. , Parés-Sierra Alejandro
Published: September 2021

Obtaining the best possible estimates of individual growth parameters is essential in studies of physiology, fisheries management, and conservation of natural resources since growth is a key component of population dynamics. In the present work, we use data of an endangered fish species to demonstrate the importance of selecting the right data error structure when fitting growth models in multimodel inference. The totoaba (Totoaba macdonaldi) is a fish species endemic to the Gulf of California increasingly studied in recent times due to a perceived threat of extinction. Previous works estimated individual growth using the von Bertalanffy model assuming a constant variance of length-at-age. Here, we reanalyze the same data under five different variance assumptions to fit the von Bertalanffy and Gompertz models. We found consistent significant differences between the constant and nonconstant error structure scenarios and provide an example of the consequences using the growth performance index ϕ′ to show how using the wrong error structure can produce growth parameter values that can lead to biased conclusions. Based on these results, for totoaba and other related species, we recommend using the observed error structure to obtain the individual growth parameters.