bluuebunny/crossref_metadata_2025 huggingface dataset:
In Silico Modeling as a Perspective in Developing Potential Vaccine Candidates and Therapeutics for COVID-19
Authors: Barghash Reham F. , Fawzy Iten M. , Chandrasekar Vaisali , Singh Ajay Vikram , Katha Uma , Mandour Asmaa A.
Published: October 2021

The potential of computational models to identify new therapeutics and repurpose existing drugs has gained significance in recent times. The current ‘COVID-19’ pandemic caused by the new SARS CoV2 virus has affected over 200 million people and caused over 4 million deaths. The enormity and the consequences of this viral infection have fueled the research community to identify drugs or vaccines through a relatively expeditious process. The availability of high-throughput datasets has cultivated new strategies for drug development and can provide the foundation towards effective therapy options. Molecular modeling methods using structure-based or computer-aided virtual screening can potentially be employed as research guides to identify novel antiviral agents. This review focuses on in-silico modeling of the potential therapeutic candidates against SARS CoVs, in addition to strategies for vaccine design. Here, we particularly focus on the recently published SARS CoV main protease (Mpro) active site, the RNA-dependent RNA polymerase (RdRp) of SARS CoV2, and the spike S-protein as potential targets for vaccine development. This review can offer future perspectives for further research and the development of COVID-19 therapies via the design of new drug candidates and multi-epitopic vaccines and through the repurposing of either approved drugs or drugs under clinical trial.
Analysis of the Coloring and Antibacterial Effects of Natural Dye: Pomegranate Peel
Authors: Bouaziz Aicha , Dridi Dorra , Gargoubi Sondes , Chelbi Souad , Boudokhane Chedly , Kenani Abderraouf , Aroui Sonia
Published: October 2021

This work aims to conduct an eco-friendly textile finishing process by applying agricultural by-products as a dye for the finishing of polyamide fabrics. A natural dye was obtained from pomegranate peel extract. Polyamide fabrics were dyed at different conditions, and four mordanting agents were tested. The finished fabrics were analyzed in terms of CIE L, a, b and color yield (K/S) values, as well as washing fastness, rubbing fastness, light fastness and antibacterial activity. Results show that pomegranate peel extract could dye polyamide fabrics. The rubbing and washing fastness of the finished samples was good. The light fastness was fair, and its antibacterial efficiency against the tested bacteria was good.
Plasma Sputtered Tungsten Oxide Thin Film on Poly(lactic acid) for Food Packaging Applications
Authors: Pedroni Matteo , Vassallo Espedito , Aloisio Marco , Brasca Milena , Chen Hao , Firpo Giuseppe , Ghezzi Francesco , Morandi Stefano , Pietralunga Silvia Maria , Silvetti Tiziana , Virgili Tersilla
Published: October 2021

Biodegradable and bio-derived plastics such as poly(lactic acid) (PLA) are a promising solution to solve the huge environmental and economic issues caused by the enormous consumption of conventional oil-derived polymers, especially in food packaging applications. However, their poor gas barrier properties and high transparency to UV radiation limit their currently commercialization. Therefore, this study is focused on the deposition of tungsten oxide (WOx) thin films on commercial PLA in order to enhance its overall performance. Coatings with different thickness (25, 50 and 100 nm) were deposited by means of radiofrequency (RF) plasma magnetron reactive sputtering. Morphological characterization was carried out with atomic force microscopy (AFM) and scanning electron microscopy (SEM). In order to evaluate surface chemical changes due to plasma treatments, Fourier-transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS) analysis were performed. The PLA/WOx samples demonstrated remarkable improvements both in UV protection and oxygen barrier properties. In particular, light transmittance was reduced by approximately 95% in the UV-B region, 70% in the UV-A region and 50% in the visible region compared to pristine PLA. Regarding oxygen permeation, a reduction of at least 99.9% was achieved. In addition, the PLA/WOx antibacterial properties against Escherichia coli were also investigated, showing a reduction greater than 5 log10 CFU cm−2 after 24 h for the 50 and 100 nm samples. These results demonstrate the potential of WOx thin coating for sustainable food packaging applications.
Effect of Storage and Heat Treatment of Milk Destined for Cheese Production on Its Oxidative Characteristics
Authors: Tripaldi Carmela , Rinaldi Simona , Palocci Giuliano , Di Giovanni Sabrina , Claps Salvatore , Buttazzoni Luca
Published: October 2021

The oxidative stability of milk and dairy products is a very interesting topic for the dairy industry due to the growing demand for foods containing bioactive compounds with positive health effects. The aim was to evaluate the oxidative stability of milk intended for cheese production. The effect of storage time, heat pre-treatment, and milk pasteurization temperature on the characteristics of milk and cheese was investigated. The cheese samples were produced with pasteurized milk at both 72 and 77 °C for a time of 15 s using three types of milk: raw fresh milk processed within 48 h of milking, raw stored milk processed within 96 h, and thermized milk that was heat-treated upon arrival at the dairy and processed within 96 h of milking. In total, three repetitions were carried out for each type of milk and pasteurization. Samples of milk before and after pasteurization and cheese at 14 days of storage were analyzed. Antioxidant activity decreased from starting milk to milk after pasteurization to final cheese. The longer storage time of the milk had significant effects on the antioxidant stability of the cheese (64.95 vs. 59.05% of antioxidant activity). Thermization of the milk further reduced the stability of the cheese (54.05% of antioxidant activity). The greater antioxidant stability of fresh milk and cheeses produced with fresh milk is the first result that encourages the production of cheese from a milk that best preserves its original characteristics.
Model-Based Prediction of an Effective Adhesion Parameter Guiding Multi-Type Cell Segregation
Authors: Rossbach Philipp , Böhme Hans-Joachim , Lange Steffen , Voss-Böhme Anja
Published: October 2021

The process of cell-sorting is essential for development and maintenance of tissues. Mathematical modeling can provide the means to analyze the consequences of different hypotheses about the underlying mechanisms. With the Differential Adhesion Hypothesis, Steinberg proposed that cell-sorting is determined by quantitative differences in cell-type-specific intercellular adhesion strengths. An implementation of the Differential Adhesion Hypothesis is the Differential Migration Model by Voss-Böhme and Deutsch. There, an effective adhesion parameter was derived analytically for systems with two cell types, which predicts the asymptotic sorting pattern. However, the existence and form of such a parameter for more than two cell types is unclear. Here, we generalize analytically the concept of an effective adhesion parameter to three and more cell types and demonstrate its existence numerically for three cell types based on in silico time-series data that is produced by a cellular-automaton implementation of the Differential Migration Model. Additionally, we classify the segregation behavior using statistical learning methods and show that the estimated effective adhesion parameter for three cell types matches our analytical prediction. Finally, we demonstrate that the effective adhesion parameter can resolve a recent dispute about the impact of interfacial adhesion, cortical tension and heterotypic repulsion on cell segregation.
Engineering Classical Capacity of Generalized Pauli Channels with Admissible Memory Kernels
Authors: Siudzińska Katarzyna , Das Arpan , Bera Anindita
Published: October 2021

In this paper, we analyze the classical capacity of the generalized Pauli channels generated via memory kernel master equations. For suitable engineering of the kernel parameters, evolution with non-local noise effects can produce dynamical maps with a higher capacity than a purely Markovian evolution. We provide instructive examples for qubit and qutrit evolution. Interestingly, similar behavior is not observed when analyzing time-local master equations.
Imaging Techniques Used for Wound Healing Assessment: A Systematic Review Part 1 Chronic Wounds
Authors: Tan Poh , Lim Joanne , Moiemen Naiem
Published: October 2021

Background: chronic wounds are complex to manage and require an objective assessment for diagnosis and prognosis purposes. Therefore, this article aims to provide an overview of available noninvasive imaging techniques for chronic wound healing described in the literature. Methods: a systematic literature review using electronic databases was performed with appropriate “Mesh” terms. The primary outcome was the validity and reliability of the instrument, whilst the secondary outcome was its feasibility, such as speed of assessment, ease of use and cost of the tool. All studies underwent quality assessment of diagnostic accuracy studies (QUADAS) to ensure the quality of the data. Results: 44 articles were identified evaluating six wound assessment modalities. Most studies (n = 9) reported on a two-dimensional device with a mean error ranging from 1.9–5.1% and an inter/intra rater correlation over 0.9 with a high ICC (>95%). The average QUADAS score was 13, with the lowest being 9 and the highest being 14. Conclusion: this review collectively evaluates objective, reliable, quantitative, and innovative tools to assess wound healing objectively. The most superior wound measuring device was two dimensional. However, hyperspectral imaging had strong potential but required further development in its technology and future clinic validation studies.
Formation of a Study Program in the Context of Conformity with the ESG (on the Material of the Analysis of Study Programs in Ukraine)
Authors: Butenko Andrii , Denyskina Ganna , Yeremenko Olena
Published: October 2021

The article discusses the issues of forming a study program in the context of the process’ compliance with the recommendations provided by Standards and Guidelines for Quality Assurance in the European Higher Education Area (ESG), which are relevant for Ukrainian higher education. The study achieved its goal: the main prerequisites for the formation of the study program (SP) were analyzed, its structural and semantic parameters were determined, and a step-by-step model of concluding a quality study program in accordance with the ESG guidelines was suggested. The search for the materials on which the study was based was conducted using the following databases: scientometric (Scopus, Web of Science), the information system (online platform) of the National Agency for Quality Assurance in Higher Education (NAQA), and the “Legislation of Ukraine” database. Quantitative methods included an online questionnaire, qualitative methods included system analysis, and other comparative method were used. Due to the contradictions between the interpretations of the concepts at the level of legislation and internal regulations, a definition of the “formation of the study program” concept is suggested. The components of the SP formation process, the resources required for the formation of the quality SP, and an analysis of positive and negative practices from the NAQA accreditation procedure experience, based on which the optimal model of the SP as a dynamic system based on ESG guidelines was developed, which has a functional character and is based on theoretical generalization of the latest approaches and real cases of Ukrainian HEIs, were discussed.
On the Relationship between Intrinsic Saliency and Implicit Learning of Apologetic Strategies: The Case of Taiwanese EFL Learners
Authors: Liu Chin-Ting , Chen Yuan-shan
Published: October 2021

The current study explored the relationship between the intrinsic saliency of apologetic strategies and the effects of implicit learning. Seventeen Taiwanese English as a Foreign Language (EFL) learners with intermediate proficiency participated in the experiment with a pretest on apology in the first week, a noticing session in the second week and a posttest in the third week. The results from the noticing session indicated that providing reasons (e.g., taking on responsibility/explanation or account) and offer of repair were more salient in input to those learners. Additionally, the use of the apologetic strategies taking on responsibility and offer of repair increased in the posttest. Taken together, the results indicated that higher degrees of saliency in input led to better implicit learning outcomes. The interplay between input saliency and explicit/implicit learning as well as the pedagogical implications were discussed.
Modeling and Control of a Phase-Shifted Full-Bridge Converter for a LiFePO4 Battery Charger
Authors: Mendoza-Varela Ivan A. , Alvarez-Diazcomas Alfredo , Rodriguez-Resendiz Juvenal , Martinez-Prado Miguel Angel
Published: October 2021

A proper charge in an electric vehicle (EV) battery allows it to have a longer useful life and lower maintenance costs. For this purpose, the voltage and current supplied to the battery must be precisely regulated. In this article, the model of a phase-shifted full-bridge (PSFB) converter is obtained. Moreover, a dual control loop was designed to regulate the state of charge of a lithium ferrofosfate (LiFePO4) battery. The autoregressive exogenous (ARX) model is used to model the system. Once the plant model is obtained, it is controlled using a classical controller. A couple of cases are evaluated where the control parameters are modified, and the best approach is selected. From the obtained model, the controller is designed for the proposed cases. The theoretical controller response is compared with the experimental response. The results show a 94% accuracy of the model. In the same way, the result obtained from the controller is accurate in a 96% by comparing it with a simulation. Both the modeling and the control obtained experimentally resemble the results obtained theoretically. The controller manages to respond as expected in all proposed cases.
Optimization of Self-Heating Driven Leakage Current Properties of Gate-All-Around Field-Effect Transistors Using Neural Network Modeling and Genetic Algorithm
Authors: Park Chuntaek , Yun Ilgu
Published: October 2021

As the technology nodes of semiconductor devices have become finer and more complex, progressive scaling down has been implemented to achieve higher densities for electronic devices. Thus, three-dimensional (3D) channel field-effect transistors (FETs), such as fin-shaped FETs (FinFETs) and gate-all-around FETs (GAAFETs), have become popular as they have increased effective surface areas for the channels (Weff), owing to the scaling down strategy. These 3D channel FETs, which have completely covered channel structures with gate oxide and metal, are prone to the self-heating effect (SHE). The SHE is generally known to degrade the on-state drain current; however, when AC pulsed inputs are applied to these devices, the SHE also degrades the off-state leakage current during the off-phase of the pulse. In this study, an optimization methodology to minimize leakage current generation by the SHE is examined.
Wearable Textile Antenna with a Graphene Sheet or Conductive Fabric Patch for the 2.45 GHz Band
Authors: Kapetanakis Theodoros N. , Nikolopoulos Christos D. , Petridis Konstantinos , Vardiambasis Ioannis O.
Published: October 2021

Textile patch antennas of simple rectangular, triangular, and circular shape, for operation in the 2.4–2.5 GHz free industrial, scientific, and medical (ISM) band, are designed in this paper. Thirty-six patch antenna prototypes have been fabricated by engaging different patch geometries, patch materials, and substrate materials. Each patch antenna is designed after optimization by a genetic algorithm, which evolves the initial dimensions and feeding position of the prototype’s microstrip counterpart to the final optimal geometrical characteristics of the wearable prototype (with the originally selected shape and materials). The impact of the design and fabrication details on antenna performance were thoroughly investigated. Graphene sheet patches were tested against conductive fabric and copper sheet ones, while denim and felt textile substrates were competing. The comparative study between a large number of different graphene, all, and copper textile prototypes, which revealed the excellent suitability of graphene for wearable applications, is the main contribution of this paper. Additional novelty elements are the compact, flexible, and easy-to-fabricate structure of the proposed antennas, as well as the use of state-of-the-art conductive materials and commercially available fabrics and the extensive investigation of many prototypes in various bending conditions. Simulations and measurements of the proposed antennas are in very good agreement. All fabricated prototypes are characterized by flexibility, light weight, mechanical stability, resistance to shock, bending and vibrations, unhindered integration to clothes, low-cost implementation, simple, time-saving, and industry-compatible fabrication process, and low specific absorption rate (SAR) values (computed using rectangular and voxel models); the graphene prototypes are additionally resistant to corrosion, and the circular ones have very good performance under bending conditions. Many antenna prototypes demonstrate interesting characteristics, such as relatively wide bandwidth, adequate gain, firm radiation patterns, coverage of the ISM band even under bending, and very low SAR values. For example, the circular graphene patch (with 55.3 mm diameter attached upon a 165.9 × 165.9 mm) felt substrate CGsF1 prototype accomplishes 109 MHz measured bandwidth, 5.45 dBi gain, 56% efficiency, full coverage of the ISM band under bending, and SAR less than 0.003 W/Kg.
Exploring the Effect of Robot-Based Video Interventions for Children with Autism Spectrum Disorder as an Alternative to Remote Education
Authors: Urdanivia Alarcon Diego Antonio , Cano Sandra , Paucar Fabian Hugo Rucano , Quispe Ruben Fernando Palomino , Talavera-Mendoza Fabiola , Zegarra María Elena Rojas
Published: October 2021

Education systems are currently in a state of uncertainty in the face of the changes and complexities that have accompanied SARS-CoV2, leading to new directions in educational models and curricular reforms. Video-based Intervention (VBIs) is a form of observational learning based on social learning theory. Thus, this study aims to make use of a humanoid robot called NAO, which has been used in educational interventions for children with autism spectrum disorder. Integrating it in video-based interventions. This study aims to characterize, in an everyday context, the mediating role of the NAO robot presented in group videoconferences to stimulate video-based on observational learning for children with cognitive and social communication deficits. The children in the study demonstrated a minimal ability to understand simple instructions. This qualitative study was applied to three children with autism spectrum disorder (ASD), level III special education students at Center for Special Basic Education (CEBE) in the city of Arequipa, Perú. Likewise, an instrument was designed for assessment of the VBIs by a group of psychologists. The results showed that the presence of the NAO robot in the VBIs successfully stimulated their interaction capabilities.
A Novel Three-Vector-Based Model Predictive Direct Power Control for Three-Phase PWM Rectifier
Authors: Tai Liuchen , Lin Mingyao , Li Hui , Li Yongsheng
Published: October 2021

A novel strategy of three-vector-based model predictive direct power control (MPDPC) is proposed for three-phase Pulse-width Modulation (PWM) rectifier. Under ideal grid conditions, three-vector MPDPC is studied, and a good control effect has been achieved. However, under the unbalanced power grid condition, the traditional control strategy has some problems, such as a high harmonic content of current and large instantaneous power pulsation. A new three-vector model predictive control is proposed based on the new instantaneous power theory, and the objective function is established by instantaneous power error. The duty cycle of the selected vector is calculated by solving the optimal objective function. Under an unbalanced power grid, this paper takes a three-phase PWM rectifier as a research object, and carries out simulation and experimental tests on the traditional and new control strategies. The experimental results show that the new control strategy has lower current harmonics, and eliminates the twice grid-frequency oscillation of the grid in instantaneous power.
Modeling and Analysis of a Coated Tube Adsorber for Adsorption Heat Pumps
Authors: Dias João M. S. , Costa Vítor A. F.
Published: October 2021

This work investigates the effects of several parameters on the coefficient of performance (COP) and the specific heating power (SHP) of a coated-tube adsorber for adsorption heat pumps (AHP) suitable for water heating (space and/or domestic water heating). The COP and SHP are obtained based on physical models that have already been proven to adequately describe this type of adsorber. Several parameters are tested, namely, the regeneration, condenser and evaporator temperatures, the heat transfer fluid velocity, the tube diameter, the adsorbent coating thickness, the metal–adsorbent heat transfer coefficient, and the cycle time. Two different scenarios were tested, corresponding to distinct working conditions. The working conditions for Scenario A are suitable for pre-heating water in mild climates. Scenario B’s working conditions are based on the European standard EN16147. The maximum COP is obtained for regeneration temperatures of 75 °C and 95 °C for Scenarios A and B, respectively. The COP increases for longer cycle times (more complete adsorption and desorption processes) whilst the SHP decreases (less complete cycles by unit time). Hence, the right balance between the COP and the SHP must be found for each particular scenario to have the best whole performance of the AHP. A metal–adsorbent heat transfer coefficient lower than 200 W·m−2·K−1 leads to reduced SHP. Lower adsorbent coating thicknesses lead to higher SHP and can still provide reasonably high COP. However, low coating thicknesses would require a too-high number of tubes to achieve the desired adsorbent mass to deliver the required useful heating power, resulting in too-large systems. Due to this, the best relationship between the SHP and the size of the system must be selected for each specific application.
Numerical Simulation of Combustion of Natural Gas Mixed with Hydrogen in Gas Boilers
Authors: Xin Yue , Wang Ke , Zhang Yindi , Zeng Fanjin , He Xiang , Takyi Shadrack Adjei , Tontiwachwuthikul Paitoon
Published: October 2021

Hydrogen mixed natural gas for combustion can improve combustion characteristics and reduce carbon emission, which has important engineering application value. A casing swirl burner model is adopted to numerically simulate and research the natural gas hydrogen mixing technology for combustion in gas boilers in this paper. Under the condition of conventional air atmosphere and constant air excess coefficient, the six working conditions for hydrogen mixing proportion into natural gas are designed to explore the combustion characteristics and the laws of pollution emissions. The temperature distributions, composition, and emission of combustion flue gas under various working conditions are analyzed and compared. Further investigation is also conducted for the variation laws of NOx and soot generation. The results show that when the boiler heating power is constant, hydrogen mixing will increase the combustion temperature, accelerate the combustion rate, reduce flue gas and CO2 emission, increase the generation of water vapor, and inhibit the generation of NOx and soot. Under the premise of meeting the fuel interchangeability, it is concluded that the optimal hydrogen mixing volume fraction of gas boilers is 24.7%.
Effect of Localized Temperature Difference on Hydrogen Fermentation
Authors: Im Seongwon , Lee Mo-Kwon , Mostafa Alsayed , Prakash Om , Lim Kyeong-Ho , Kim Dong-Hoon
Published: October 2021

In a lab-scale bioreactor system, (20 L of effective volume in our study) controlling a constant temperature inside bioreactor with a total volume 25 L is a simple process, whereas it is a complicated process in the actual full-scale system. There might exist a localized temperature difference inside the reactor, affecting bioenergy yield. In the present work, the temperature at the middle layer of bioreactor was controlled at 35 °C, while the temperature at top and bottom of bioreactor was controlled at 35 ± 0.1, ±1.5, ±3.0, and ±5.0 °C. The H2 yield of 1.50 mol H2/mol hexoseadded was achieved at ±0.1 and ±1.5 °C, while it dropped to 1.27 and 0.98 mol H2/mol hexoseadded at ±3.0 and ±5.0 °C, respectively, with an increased lactate production. Then, the reactor with automatic agitation speed control was operated. The agitation speed was 10 rpm (for 22 h) under small temperature difference (<±1.5 °C), while it increased to 100 rpm (for 2 h) when the temperature difference between top and bottom of reactor became larger than ±1.5 °C. Such an operation strategy helped to save 28% of energy requirement for agitation while producing a similar amount of H2. This work contributes to facilitating the upscaling of the dark fermentation process, where appropriate agitation speed can be controlled based on the temperature difference inside the reactor.
Exploring Intention toward Using an Electric Scooter: Integrating the Technology Readiness and Acceptance into Norm Activation Model (TRA-NAM)
Authors: Ho Chien-Wei , Wu Chi-Chuan
Published: October 2021

The issues of renewable energy, energy crisis, and carbon reduction have caught people’s attention all over the world, and governments have put forth greater effort to proactively solve these problems. Electric transportation not only benefits the environment, but can also utilize renewable energy to prevent an energy crisis. Based on previous theoretical strands of the literature, this research integrates the technology readiness and acceptance model (TRAM) into the norm activation model (NAM) and proposes an integrated model denoted as TRA-NAM. It takes TRA-NAM as our theoretical foundation and aims to explore the effect of technology readiness and awareness of consequence on the intention toward using an electric scooter (ES). The results display that technology readiness positively influences perceived usefulness and perceived ease of use and further improves consumers’ intention toward adopting ES. In addition, personal norm mediates the relationship between awareness of consequence and intention to adopt ES. This study offers the integrated TRAM-NAM model in order to understand the crucial factors affecting consumers’ intention to adopt electric vehicles (EVs). Overall, this research fills the gap in the field of government policies and transportation and proposes ponderable suggestions, in particular that if they want to encourage or attract consumers to drive an ES, they should not overlook the effect of technology readiness and awareness of consequence.
Biogas, Solar and Geothermal Energy—The Way to a Net-Zero Energy Wastewater Treatment Plant—A Case Study
Authors: Myszograj Sylwia , Bocheński Dariusz , Mąkowski Mirosław , Płuciennik-Koropczuk Ewelina
Published: October 2021

Wastewater treatment plants designed to meet the requirements of discharging wastewater to a receiving water body are often not energy optimised. Energy requirements for conventional activated sludge wastewater treatment plants are estimated to range from 0.30 to 1.2 kWh/m3, with the highest values achieved using the nitrification process. This article describes the energy optimisation process of the wastewater treatment plant in Gubin (Poland) designed for 90,000 PE (population equivalent) using renewable energy sources: solar, biogas, and geothermal. At the analysed wastewater treatment plant electricity consumption for treating 1 m3 of wastewater was 0.679 kWh in 2020. The combined production of electricity and heat from biogas, the production of electricity in a photovoltaic system, and heat recovery in a geothermal process make it possible to obtain a surplus of heat in relation to its demand in the wastewater treatment plant, and to cover the demand for electricity, with the possibility of also selling it to the power grid.
Fault Diagnosis and Reconstruction of Wind Turbine Anemometer Based on RWSSA-AANN
Authors: Zhou Ling , Zhao Qiancheng , Wang Xian , Zhu Anfeng
Published: October 2021

When the state of the wind turbine sensors, especially the anemometer, appears abnormal it will cause unnecessary wind loss and affect the correctness of other parameters of the whole system. It is very important to build a simple and accurate fault diagnosis model. In this paper, the model has been established based on the Random Walk Improved Sparrow Search Algorithm to optimize auto-associative neural network (RWSSA-AANN), and is used for fault diagnosis of wind turbine group anemometers. Using the cluster analysis, six wind turbines are determined to be used as a wind turbine group. The 20,000 sets of normal historical data have been used for training and simulating of the model, and the single and multiple fault states of the anemometer are simulated. Using this model to analyze the wind speed supervisory control and data acquisition system (SCADA) data of six wind turbines in a wind farm from 2013 to 2017, can effectively diagnose the fault state and reconstruct the fault data. A comparison of the results obtained using the model developed in this work has also been made with the corresponding results generated using AANN without optimization and AANN optimized by genetic algorithm. The comparison results indicate that the model has a higher accuracy and detection rate than AANN, genetic algorithm auto-associative neural network (GA-AANN), and principal component analysis (PCA).
Hybrid Controller Based on LQR Applied to Interleaved Boost Converter and Microgrids under Power Quality Events
Authors: Valencia-Rivera Gerardo Humberto , Amaya Ivan , Cruz-Duarte Jorge M. , Ortíz-Bayliss José Carlos , Avina-Cervantes Juan Gabriel
Published: October 2021

Renewable energy sources are an environmentally attractive idea, but they require a proper control scheme to guarantee optimal operation. In this work, we tune different controllers for an Interleaved Boost Converter (IBC) powered by a photovoltaic array using three metaheuristics: Genetic Algorithm, Particle Swarm Optimization, and Gray Wolf Optimization. We also develop several controllers for a second simulated scenario where the IBC is plugged into an existing microgrid (MG) as this can provide relevant data for real-life applications. In both cases, we consider hybrid controllers based on a Linear Quadratic Regulator (LQR). However, we hybridize it with an Integral action (I-LQR) in the first scenario to compare our data against previously published controllers. In the second one, we add a Proportional-Integral technique (PI-LQR) as we do not have previous data to compare against to provide a more robust controller than I-LQR. To validate our approach, we run extensive simulations with each metaheuristic and compare the resulting data. We focus on two fronts: the performance of the controllers and the computing cost of the solvers when facing practical issues. Our results demonstrate that the approach proposed for tuning controllers is a feasible strategy. The controllers tuned with the metaheuristics outperformed previously proposed strategies, yielding solutions thrice faster with virtually no overshoot and a voltage ripple seven times smaller. Not only this, but our controllers could correct some issues liaised to the IBC when it is plugged into an MG. We are confident that these insights can help migrate this approach to a more diverse set of MGs with different renewable sources and escalate it to real-life experiments.
Electric Cooking Diary in Bangladesh: Energy Requirement, Cost of Cooking Fuel, Prospects, and Challenges
Authors: Saha Avijit , Razzak Md. Abdur , Khan M. Rezwan
Published: October 2021

Detrimental effects exerted by biomass-based traditional cookstoves on health, environment, hygiene, and the soaring price of gas makes it imperative to investigate the feasibility of electric cooking as a promising clean cooking fuel in the context of Bangladesh. However, the adoption of electric cooking is unlikely to be welcomed if the monthly cost of electricity consumed by the electric cooking appliances is not comparable to traditional cooking fuels. So far, no study has been reported in this respect. Therefore, this paper is aimed to assess the energy consumption of available electric cooking appliances for cooking typical Bangladeshi dishes. Estimated monthly electricity cost of electric cooking is also reported and then compared to that of traditional cooking fuels. For the study purpose, three respondent families were provided with a rice cooker, hot plate, induction cooker and electric pressure cooker for cooking their daily meals. After four months of use, data related to dish cooked, amount of food, cooking time, and energy consumption were collected which shows that hot plate and rice cooker were the least preferred appliances due to their poor workmanship and limited use respectively. On the contrary, despite the fact that electric pressure cookers cannot perform all types of frying, it was the most preferred appliance owing to its ability to significantly reduce the cooking time and its less energy consumption. Induction cooker was less preferred for the additional requirement of compatible cook pots. The study also reveals that monthly energy requirements for electric cooking varied from 72–87 kWh corresponding to a cooking electricity bill ranging from BDT 504–609 per month (USD 6–7.5) which is less expensive as compared with biomass and LPG based cooking. This paper also highlights the prospects and challenges associated with the adoption of electricity as the primary cooking fuel in Bangladesh.
An Experimental Study of the Influence of the Preflush Salinity on Enhanced Oil Recovery Using Silica-Based Nanofluids
Authors: Sreu Tola , Sasaki Kyuro , Sugai Yuichi , Nguele Ronald
Published: October 2021

The underlying effect of preflush salinity and silica nanofluid (Si-NF) on oil production is examined. The influence of salinity on the stability of Si-NFs is studied. A series of sand-pack floodings evaluating oil production was conducted at different concentrations of preflush salinity (0 to 4 wt.%), followed by the injection of a Si-NF (0.5 wt.%) at the trail of which postflush water was injected. The effluent water and solids were collected and analyzed using X-ray fluorescence (XRF). Interfacial tension (IFT) and contact angle measurements were conducted on the Si-NF in the presence of salinity to confirm the effect. The Si-NF became unstable and formed precipitate in the presence of salinity. The sand-pack flooding showed that when the preflush salinity was increased, the displacement efficiency (ED) using the Si-NF and postflush injection was increased (ED = 44%). The XRF of the precipitated effluent revealed that the preflush salinity and Si-NF caused mineral leaching, which triggered pore clogging. The IFT value reduced from 13.3 to 8.2 mN/m, and the wettability was altered to be more strongly water-wet when the salinity increased. The primary mechanisms of oil recovery using the Si-NF after preflush salinity is attributed mainly to the clogging mechanism. This clogging helps block the high-perm area, shift the fluid flow to the oil-trapped zone, and free the oil out. Other contribution mechanisms are IFT reduction and wettability alteration.
An Attempt to Use Machine Learning Algorithms to Estimate the Rockburst Hazard in Underground Excavations of Hard Coal Mine
Authors: Wojtecki Łukasz , Iwaszenko Sebastian , Apel Derek B. , Cichy Tomasz
Published: October 2021

Rockburst is a dynamic rock mass failure occurring during underground mining under unfavorable stress conditions. The rockburst phenomenon concerns openings in different rocks and is generally correlated with high stress in the rock mass. As a result of rockburst, underground excavations lose their functionality, the infrastructure is damaged, and the working conditions become unsafe. Assessing rockburst hazards in underground excavations becomes particularly important with the increasing mining depth and the mining-induced stresses. Nowadays, rockburst risk prediction is based mainly on various indicators. However, some attempts have been made to apply machine learning algorithms for this purpose. For this article, we employed an extensive range of machine learning algorithms, e.g., an artificial neural network, decision tree, random forest, and gradient boosting, to estimate the rockburst risk in galleries in one of the deep hard coal mines in the Upper Silesian Coal Basin, Poland. With the use of these algorithms, we proposed rockburst risk prediction models. Neural network and decision tree models were most effective in assessing whether a rockburst occurred in an analyzed case, taking into account the average value of the recall parameter. In three randomly selected datasets, the artificial neural network models were able to identify all of the rockbursts.
Injection Treatment for Tunneling Excavation in Sandy Soils with High Fines Content
Authors: González-García Johnatan , González-Nicieza Celestino , Álvarez-Fernández Martina-Inmaculada , Prendes-Gero María-Belén
Published: October 2021

Instability and high permeability are two of the problems facing tunnelling excavations in soils with high fines content. Among the different techniques used to improve these soils, the injection of cement grouts stands out. In this work, a grouting treatment is designed to ensure the stability of the ground during the construction of two tunnels linking two municipalities in the north of Spain in Biscay, and to reduce the inflow of water from the aquifer located in the vicinity of these tunnels. First of all, the rock mass is analysed and the material to be injected is selected on the basis of the authors’ experience as well as setting time and compressive strength. Subsequently, with a test device designed by the DinRock research group of the University of Oviedo, two types of laboratory tests are carried out in order to analyse the effect of fines migration and washing on the water flows and the effect of re-injections of grouts with different densities on the permeability value. The results show that, in sandy materials, obtaining high degrees of waterproofing together with large stable zones can only be achieved by a combination of treatments and stages with different materials and densities. In addition, maximum values for both injection pressure and flow rate must be established depending on the type of grout and the permeability of the soil. Once the problem has been analysed, the injection treatment is designed and executed. The treatment consists of one pre-injection in four stages with 30 boreholes drilled in the top heading, 19–20 boreholes drilled in the bench, and one post-injection with boreholes drilled around the perimeter of the tunnel in those areas where the pre-injection does not achieve the desired degree of waterproofing.
The Role of Advocacy Coalitions in Shaping the Technological Innovation Systems: The Case of the Russian Renewable Energy Policy
Authors: Nevzorova Tatiana , Kutcherov Vladimir
Published: October 2021

Many hydrocarbon-rich countries have recognized the global shift towards renewable energy sources, and Russia is not an exception. Drawing on two strands of literature—technological innovation systems and the advocacy coalition framework—we investigate the roles of actors and coalitions in shaping the Russian renewable energy policy and explore why particular renewable energy sources have progressed more than others, and what the main reasons are for their sudden development. The results show that the more successful renewable energy industries are those that were promoted by influential actors from traditional energy industries. Moreover, these actors also promoted the specific design of support schemes for renewable energy policy in Russia. We discuss the importance of policy process theories for understanding energy transition studies and provide specific policy recommendations for policy creation in the renewables industry.
Comparison of Techniques for the Estimation of Flow Parameters of Fan Inflow Turbulence from Noisy Hot-Wire Data
Authors: Caldas Luciano , Kissner Carolin , Behn Maximilian , Tapken Ulf , Meyer Robert
Published: October 2021

Turbulence parameters, in particular integral length scale (ILS) and turbulence intensity (Tu), are key input parameters for various applications in aerodynamics and aeroacoustics. The estimation of these parameters is typically performed using data obtained via hot-wire measurements. On the one hand, hot-wire measurements are affected by external disturbances resulting in increased measurement noise. On the other hand, commonly applied turbulence parameter estimators lack in robustness. If not addressed correctly, both issues may impede the accuracy of the turbulence parameter estimation. In this article, a procedure consisting of several signal processing steps is presented to filter non-turbulence related disturbances from the unsteady velocity data. The signal processing techniques comprise time- and frequency-domain approaches. For the turbulence parameter estimation, two different models of the turbulence spectra—the von Kármán model and the Bullen model—are fitted to match the spectrum of the measured data. The results of several parameter estimation techniques are compared. Computational Fluid Dynamics (CFD) data are used to validate the estimation techniques and also to assess the influence of the variation in window size on the estimated parameters. Additionally, hot-wire data from a high-speed fan rig are analyzed. ILS and Tu are assessed at several radial positions for two fan speeds. It is found that most techniques yield similar values for ILS and Tu. The comparison of the fitted spectra with the spectra of the measured data shows a good agreement in most cases provided that a sufficiently fine frequency resolution is applied. The ratio of ILS and Tu of the velocity components in longitudinal and transverse direction allows the assessment of flow-isotropy. Results indicate that the turbulence is anisotropic for the investigated flow fields.
Stability of a Buoyant Oldroyd-B Flow Saturating a Vertical Porous Layer with Open Boundaries
Authors: Lazzari Stefano , Celli Michele , Barletta Antonio
Published: October 2021

The performance of several engineering applications are strictly connected to the rheology of the working fluids and the Oldroyd-B model is widely employed to describe a linear viscoelastic behaviour. In the present paper, a buoyant Oldroyd-B flow in a vertical porous layer with permeable and isothermal boundaries is investigated. Seepage flow is modelled through an extended version of Darcy’s law which accounts for the Oldroyd-B rheology. The basic stationary flow is parallel to the vertical axis and describes a single-cell pattern where the cell has an infinite height. A linear stability analysis of such a basic flow is carried out to determine the onset conditions for a multicellular pattern. This analysis is performed numerically by employing the shooting method. The neutral stability curves and the values of the critical Rayleigh number are evaluated for different retardation time and relaxation time characteristics of the fluid. The study highlights the extent to which the viscoelasticity has a destabilising effect on the buoyant flow. For the limiting case of a Newtonian fluid, the known results available in the literature are recovered, namely a critical value of the Darcy–Rayleigh number equal to 197.081 and a corresponding critical wavenumber of 1.05950.
Changes during Food Freezing and Frozen Storage
Authors: Giannakourou Maria , Taoukis Petros
Published: October 2021

Multiple factors can directly influence frozen food quality, during processing and post-processing, in the cold chain [...]
Characteristics of the Gut Microbiota and Potential Effects of Probiotic Supplements in Individuals with Type 2 Diabetes mellitus
Authors: Ballan Rafael , Saad Susana Marta Isay
Published: October 2021

The increasing prevalence of type 2 diabetes mellitus (T2DM) worldwide has become a burden to healthcare systems. In 2019, around 463 million adults were living with diabetes mellitus, and T2DM accounted for 90 to 95% of cases. The relationship between the gut microbiota and T2DM has been explored with the advent of metagenomic techniques. Genome-wide association studies evaluating the microbiota of these individuals have pointed to taxonomic, functional, and microbial metabolite imbalances and represent a potential intervention in T2DM management. Several microbial metabolites and components, such as imidazole propionate, trimethylamine, and lipopolysaccharides, appear to impair insulin signaling, while short-chain fatty acids, secondary bile acids, and tryptophan metabolites may improve it. In addition, the use of probiotics with the aim of transiently restoring the microbial balance or reducing the effects of microbial metabolites that impair insulin sensitivity has been explored. Herein, we critically review the available literature on the changes in the gut microbiota in T2DM together with potential adjuvant therapies that may improve the health status of this population.
An Efficient Stochastic Numerical Computing Framework for the Nonlinear Higher Order Singular Models
Authors: Sabir Zulqurnain , Wahab Hafiz Abdul , Javeed Shumaila , Baskonus Haci Mehmet
Published: October 2021

The focus of the present study is to present a stochastic numerical computing framework based on Gudermannian neural networks (GNNs) together with the global and local search genetic algorithm (GA) and active-set approach (ASA), i.e., GNNs-GA-ASA. The designed computing framework GNNs-GA-ASA is tested for the higher order nonlinear singular differential model (HO-NSDM). Three different nonlinear singular variants based on the (HO-NSDM) have been solved by using the GNNs-GA-ASA and numerical solutions have been compared with the exact solutions to check the exactness of the designed scheme. The absolute errors have been performed to check the precision of the designed GNNs-GA-ASA scheme. Moreover, the aptitude of GNNs-GA-ASA is verified on precision, stability and convergence analysis, which are enhanced through efficiency, implication and dependability procedures with statistical data to solve the HO-NSDM.