bluuebunny/crossref_metadata_2025 huggingface dataset:
Thermal Defect Detection for Substation Equipment Based on Infrared Image Using Convolutional Neural Network
Authors: Wang Kaixuan , Zhang Jiaqiao , Ni Hongjun , Ren Fuji
Published: August 2021

Thermal defects of substation equipment have a great impact on the stability of power systems. Temperature is crucial for thermal defect detection in infrared images. The traditional detection methods, which have low efficiency and poor accuracy, record the temperature of infrared images manually. In this study, a thermal defect detection method based on infrared images using a convolutional neural network (CNN) is proposed. Firstly, the improved pre-processing method is applied to reduce background information, and the region of interest is located according to the contour and position information, hence improving the quality of images. Then, the temperature values are segmented to establish the dataset (T-IR11), which contains 11 labels. Finally, the CNN model is constructed to extract features, and the support vector machine is trained for classification. To verify the effectiveness of the proposed method, precision, recall, and F1 score are adopted and 10-fold cross-validation is employed on the T-IR11 dataset. The results demonstrate that the accuracy of the proposed method is 99.50%, and the performance is superior to that of previous methods in terms of infrared images. The proposed method can realize automatic temperature recognition and equipment with thermal defects can be recorded systematically, which has significant practical value for defect detection in substation equipment.
Intellectual Property Theft Protection in IoT Based Precision Agriculture Using SDN
Authors: Hossain Md. Selim , Rahman Md. Habibur , Rahman Md. Sazzadur , Hosen A. S. M. Sanwar , Seo Changho , Cho Gi Hwan
Published: August 2021

In this work, we examine the privacy and safety issues of Internet of Things (IoT)-based Precision Agriculture (PA), which could lead to the problem that industry is currently experiencing as a result of Intellectual Property Theft (IPT). Increasing IoT-based information flow in PA will make a system less secure if a proper security mechanism is not ensured. Shortly, IoT will transform everyday lives with its applications. Intellectual Property (IP) is another important concept of an intelligent farming system. If the IP of a wise farming system leaks, it damages all intellectual ideas like cultivation patterns, plant variety rights, and IoT generated information of IoT-based PA. Thus, we proposed an IoT enabled SDN gateway regulatory system that ensures control of a foreign device without having access to sensitive farm information. Most of the farm uses its devices without the use of its integrated management and memory unit. An SDN-based structure to solve IP theft in precision farming has been proposed. In our proposed concept, a control system integrates with the cloud server, which is called the control hub. This hub will carry out the overall PA monitoring system. By hiring the farm devices in the agricultural system, these devices must be tailored according to our systems. Therefore, our proposed PA is a management system for all controllable inputs. The overall goal is to increase the probability of profit and reduce the likelihood of IPT. It does not only give more information but also improves information securely by enhancing the overall performance of PA. Our proposed PA architecture has been measured based on the throughput, round trip time, jitter, packet error rate, and the cumulative distribution function. Our achieved results reduced around (1.66–6.46)% compared to the previous research. In the future, blockchain will be integrated with this proposed architecture for further implementation.
A Low-Cost High Radix Floating-Point Square-Root Circuit
Authors: Yang Yuheng , Yuan Qing , Liu Jian
Published: August 2021

In this paper, we propose an efficient architecture of floating-point square-root circuit with low area cost, which is in accordance with the IEEE-754 standard. We extend the principle of the standard SRT algorithm so that the latency and area cost of the proposed circuit are linear with the radix. In addition, no extra computation cycles are required. With 65 nm technology, the area cost of the single-precision floating-point square-root circuit based on proposed architecture is only 6450.84 μm2, and the dynamic power consumption is only 0.764 mW at 300 MHz. The implementation results show that the proposed square-root circuit can reduce the area cost by 60%~90% compared with other designs in the literature.
Trajectory Tracking and Stabilization of Nonholonomic Wheeled Mobile Robot Using Recursive Integral Backstepping Control
Authors: Rabbani Muhammad Junaid , Memon Attaullah Y.
Published: August 2021

In this paper, a generalized nontriangular normal form is presented to facilitate designing a recursive integral backstepping control for the class of underactuated nonholonomic systems, i.e., wheeled mobile robots (WMRs) that perform posture stabilization and trajectory tracking in environments without obstacles. Based on the differential geometry theory, we develop a multiple input multiple output (MINO) generalization of normal form using the input-output feedback linearization technique. Then, the change of variables (diffeomorphism) transform the state-space model of WMR, incorporating both kinematic and dynamic models into nontriangular normal form. As a result, the system dynamics can be represented as internal and external dynamics. The nonlinear internal dynamics of WMR pose serious challenges to design a suitable controller due to its internal dynamics being not minimum phase and non-strict feedback form structure. The proposed backstepping controller is designed in two steps. First, a standard integral backstepping controller is designed to stabilize the robot’s orientation angle. Then, a recursive integral backstepping control technique is applied to achieve asymptotic convergence of position error to zero. Hence, both asymptotic posture stabilization and trajectory tracking are achieved in semi-global regions, except the nonzero initial condition of the orientation angle. The asymptotic stability of the entire closed-loop system is shown using the Lyapunov criteria.
A Deep Learning Model with Self-Supervised Learning and Attention Mechanism for COVID-19 Diagnosis Using Chest X-ray Images
Authors: Park Junghoon , Kwak Il-Youp , Lim Changwon
Published: August 2021

The SARS-CoV-2 virus has spread worldwide, and the World Health Organization has declared COVID-19 pandemic, proclaiming that the entire world must overcome it together. The chest X-ray and computed tomography datasets of individuals with COVID-19 remain limited, which can cause lower performance of deep learning model. In this study, we developed a model for the diagnosis of COVID-19 by solving the classification problem using a self-supervised learning technique with a convolution attention module. Self-supervised learning using a U-shaped convolutional neural network model combined with a convolution block attention module (CBAM) using over 100,000 chest X-Ray images with structure similarity (SSIM) index captures image representations extremely well. The system we proposed consists of fine-tuning the weights of the encoder after a self-supervised learning pretext task, interpreting the chest X-ray representation in the encoder using convolutional layers, and diagnosing the chest X-ray image as the classification model. Additionally, considering the CBAM further improves the averaged accuracy of 98.6%, thereby outperforming the baseline model (97.8%) by 0.8%. The proposed model classifies the three classes of normal, pneumonia, and COVID-19 extremely accurately, along with other metrics such as specificity and sensitivity that are similar to accuracy. The average area under the curve (AUC) is 0.994 in the COVID-19 class, indicating that our proposed model exhibits outstanding classification performance.
Privacy Assessment in Android Apps: A Systematic Mapping Study
Authors: Del Alamo Jose M. , Guaman Danny , Balmori Belen , Diez Ana
Published: August 2021

Android apps are daily installed by billions of users worldwide, who grant access to an extensive set of sensitive personal data. Different techniques have been developed over the years to understand how apps protect or harm their users’ privacy. However, these results have been produced in different research domains and addressing privacy from different perspectives, resulting in a growing but scattered body of knowledge. To bridge this gap, we have carried out a systematic mapping study to provide practitioners and researchers with an overview of the state-of-the-art technique, published between 2016 and 2020, to assess privacy in Android apps. In this paper, we highlight the most relevant findings, identify and analyse the most pressing gaps, and discuss the promising research directions.
Stochastic Modelling to Analyze the Impact of Electric Vehicle Penetration in Thailand
Authors: Uthathip Narongkorn , Bhasaputra Pornrapeepat , Pattaraprakorn Woraratana
Published: August 2021

Electric Vehicle (EV) technology is one of the most promising solutions to reduce dependence on fossil fuels and greenhouse gas (GHG) emissions in the transportation sector. However, a large increase of EVs raises concerns about negative impacts on electricity generation, transmission, and distribution systems. This study analyzes the benefits and trade-offs for EV penetration in Thai road transport based on EV penetration scenarios from 2019 to 2036. Two charging strategies are considered to assess the impact of EV charging: free charging and off-peak charging. Uncertainty variables are considered by a stochastic approach based on Monte-Carlo simulation (MCS). The simulation results shown that the adoption of EVs can reduce both energy consumption and GHG emissions. The results also indicate that the increased load due to EV charging demand in all scenarios is still within the buffer level, compared to the installed generation capacity in the Power Development Plan 2018 revision 1 (PDP2018r1), and the off-peak charging strategy is more beneficial than the free-charging strategy. However, the increased load demand caused by all EV charging strategies has a direct impact on the power generating schedule, and also decreases the system reliability level.
Standard and Modified SST Models with the Consideration of the Streamline Curvature for Separated Flow Calculation in a Narrow Channel with a Conical Dimple on the Heated Wall
Authors: Isaev Sergey , Nikushchenko Dmitry , Sudakov Alexandr , Tryaskin Nikita , Egorova Ann , Iunakov Leonid , Usachov Alexandr , Kharchenko Valery
Published: August 2021

The testing of the standard and modified SST models of the transfer of shear stresses was carried out on an example of calculating the heat transfer with an intense detached flow around a conical dimple with a slope angle of 45° on the heated wall of a narrow channel. It was shown that the standard turbulence model by Menter SST (MSST) of 2003, widely used in the packages Fluent, CFX, StarCCM+, etc., significantly underestimated the intensity of the return flow. A correction of this model was presented that took into account the influence of the curvature of streamlines within the framework of the Rodi-Leshziner-Isaev (RLI) approach for spatial separated flows. It was found that the predictions for the RLI MSST 2003 were close to the predictions for the original standard MSST 1993, in which the eddy viscosity was calculated using the vorticity modulus. At the same time, the predictions based on the modified one, following Smirnov-Menter (SM) MSST 2003, included in the ANSYS model catalog did not differ too much from the standard MSST 2003. The preference of the MSST modified within the RLI 2003 for calculating the heat transfer in intense separated flows was substantiated.
Problems of Remote Temperature Measurement of Small Objects of Electricity Power Systems—On the Example of Lashing Clamps of Bridge Connections on High Voltage Poles
Authors: Minkina Waldemar
Published: August 2021

The article presents problems occurring during remote temperature measurement of lashing clamps of bridge connections on high voltage poles using thermal imaging cameras. The basic metrological parameters of thermal imaging cameras are described. On this basis, typical errors made during the inspection of high voltage lines supplying power substations are presented using infrared cameras. Researching the possible solutions for the problems of remote temperature measurement of small objects of electricity power systems—on the example of lashing clamps of bridge connections on high voltage poles in the proposed paper and showing the basic metrological aspects and parameters of thermal imaging cameras are important because, in this way, it is observed to eliminate costly interruptions in the supply of electricity associated with the breaking of power lines. Small objects are quite difficult to be controlled and monitored on large grids and on large powerline poles; thus, it is very challenging to interpret the data offered by thermograms. The problem of remote temperature measurement of small objects in electrical power engineering is very important from the point of view of the quality and reliability of electricity supply. Obtaining early warning information about the occurrence of overheating, e.g., on lashing clamps of bridge connections, is very important, as it eliminates costly interruptions in the supply of electricity associated with the breaking of power lines supplying high voltage switchgears or substations.
The Permitting, Licensing and Environmental Compliance Process: Lessons and Experiences within U.S. Marine Renewable Energy
Authors: Barr Zachary , Roberts Jesse , Peplinski William , West Anna , Kramer Sharon , Jones Craig
Published: August 2021

The marine renewable energy (MRE; renewable energy captured from waves, tides, ocean currents, the natural flow of water in rivers, and marine thermal gradients, without building new dams or diversions) industry has a vital role in the U.S. clean energy strategy as we progress to meet U.S. electricity and blue economy needs with renewable, domestic energy sources. However, a thorough assessment of the U.S. marine energy permitting process from the viewpoints of both developers that propose projects and regulators that permit them has not been performed. Sharing practical experiences in this new industry is vital to increase the efficiency and effectiveness of the permitting process, identify data and information gaps, develop lessons learned, and advance the industry. This paper is a case study of qualitative findings, lessons learned, and recommendations from guided discussions, workshops, and webinars with both marine renewable energy developers and state and federal regulators that have experience in the permitting process in the U.S.
Phase-Shifting Transformer Efficiency Analysis Based on Low-Voltage Laboratory Units
Authors: Albrechtowicz Paweł
Published: August 2021

Phase-shifting transformers are effective elements used to control power flows in many power systems. Their positive influence on power flows has been proved in the literature. However, the efficiency of phase-shifting transformers has not been analyzed, especially not with regard for their various types. This study is therefore focused on the efficiency question with respect to electrical energy parameters. Research was performed on a laboratory phase-shifter unit with longitudinal and quadrature voltage regulation, and then these results were correlated to the simulation model equivalent. Laboratory transformer parameter data were used to prepare asymmetrical and symmetrical phase-shifting transformer simulation models. Simulation results were then used to compare the electrical properties and efficiency of all the types of phase-shifting transformer considered. All phase-shifting transformer types had a significant impact on the transmitted active power, but each type had different features. The symmetrical unit had the lowest power losses and a stable output voltage level compared to the asymmetrical one, which increased the output voltage, while the quadrature voltage also grew. These features must be considered, taking into account power system conditions such as the voltage variability profile and active power transfer demand. In this study, we propose the construction of an asymmetrical controllable phase-shifting transformer in order to achieve flexible control.
Study on the Influence and Optimization of the Venturi Effect on the Natural Ventilation of Buildings in the Xichang Area
Authors: Zhang Lili , Tian Lei , Shen Qiong , Liu Fei , Li Haolin , Dong Zhuojun , Cheng Jingyue , Liu Haoru , Wan Jiangjun
Published: August 2021

Natural ventilation is a way to reduce the energy consumption of building operations and improve the indoor living environment comfort. The venturi cap is designed with a roof, grille and wind deflector to intensify the natural ventilation of buildings. The structural parameters of the venturi cap were designed using an orthogonal design. Fluid analysis software was used for numerical simulation, and variance analysis was used to study the importance of seven influence factors: the width of the roof opening, the roof slope, the height of the wind deflector, the horizontal width of the wind deflector, the angle of the wind deflector, the angle of the grille, and the spacing of the grille slices. The results show that the most significant influencing factor is the width of the roof opening, while significant influence factors include the angle of the grille and the horizontal width of the wind deflector. Additionally, the optimum parameter combination for ventilation performance at the research level was put forward, with the proposed combination achieving a volume flow rate of 5.507 m3/s. The average temperature of the horizontal plane at a height of 1.2 m above the ground was 3.002 K lower than that without a venturi cap, which provides a reference for the optimization of indoor ventilation design in buildings in the Xichang area.
Comparison of Hydrocarbon Fiscal Regimes of Some European Oil and Gas Producers and Perspectives for Improvement in the Republic of Croatia
Authors: Kolovrat Marko , Jukić Lucija , Sedlar Daria Karasalihović
Published: August 2021

Hydrocarbon exploration and production activities are basic to the functioning of the oil and gas industry, while concession contracts and fees are central concepts in the aforementioned activities. The authors consider several questions regarding these concepts, such as: what is the legislative, institutional, and fiscal framework in certain European countries regarding hydrocarbon exploration and production? What are the major differences between them? Finally, is there room for improvement of the framework in the Republic of Croatia? To answer these questions, the authors contacted some of the relevant institutions and accessed official government gazettes, institution websites, legal aggregators, journal articles, books, and different legal publications regarding the oil and gas industry for several European countries, namely the Kingdom of Norway, the Russian Federation, the Republic of Austria, and the Republic of Croatia. As a result, this paper presents an overview of legislation, institutions, concession contracts, taxes, and fees for each of the aforementioned countries. The authors conclude that the Republic of Croatia could benefit from applying some foreign solutions in its own legislative and fiscal framework, i.e., using a sliding scale for royalty calculation and simplifying some administrative procedures.
Hydrogen-Based Energy Conversion: Polymer Electrolyte Fuel Cells and Electrolysis
Authors: Park Jin-Soo
Published: August 2021

This book [...]
Transition to Periodic Behaviour of Flow Past a Circular Cylinder under the Action of Fluidic Actuation in the Transitional Regime
Authors: Sarwar Wasim , Mellibovsky Fernando , Alam Md. Mahbub , Zafar Farhan
Published: August 2021

This study focuses on the numerical investigation of the underlying mechanism of transition from chaotic to periodic dynamics of circular cylinder wake under the action of time-dependent fluidic actuation at the Reynolds number = 2000. The forcing is realized by blowing and suction from the slits located at ±90∘ on the top and bottom surfaces of the cylinder. The inverse period-doubling cascade is the underlying physical mechanism underpinning the wake transition from mild chaos to perfectly periodic dynamics in the spanwise-independent, time-dependent forcing at twice the natural vortex-shedding frequency.
Profiles of Food Insecurity: Similarities and Differences across Selected CEE Countries
Authors: Dudek Hanna , Myszkowska-Ryciak Joanna , Wojewódzka-Wiewiórska Agnieszka
Published: August 2021

Food security (FS) is influenced by primarily financial but also sociodemographic factors. Identification of correlates of food insecurity (FI) is a crucial issue in the context of achieving sustainable development goals. The aims of the study were: (1) to recognize FI in the selected Central and Eastern European (CEE) countries, (2) to examine common socioeconomic and demographic characteristics for FI. The analysis used the set of eight-item FI indicators adopted by the Food and Agriculture Organization, applying the Gallup World Poll survey data from 2017 to 2019. Multinomial logistic regressions were used to examine FI at mild and moderate or severe levels compared with FS. Differences in the profiles of FI were observed in analyzed countries: Poland, Lithuania and Slovakia. Lithuanians experienced the lowest FS, and Slovaks the highest. The FI status was associated with education, gender, age, household composition and income. It was found that the impact of these factors was not the same in the examined countries. Differences in profiles of FI in CEE countries indicate the need to analyze the problem individually for each country. Identifying groups particularly vulnerable to FI may allow appropriate targeting of instruments counteracting FI and adapt them to people with different characteristics.
Low-RPM Torque Converter (LRTC)
Authors: Savin Andrej , Salar Dana , Hultman Erik
Published: August 2021

The concept concerned in this paper is based on energy conversion of the ocean waves via rotational generators. The objective of this research is to develop a new type of slow-motion converter. The LRTC device consists of a drum that is connected via wire to a floating buoy. The drum is connected to rotary generators. The generators are heavily braked when the direction of movement changes (up/down); this is because the generators have been charged the maximum load in order to obtain maximum output power. For upcoming improvement, the generators should have some power storage as flywheel. In the future experiments, the torque converter can even be tuned to rotate in resonance with the incoming waves, strongly increasing power absorption. Constant force springs are applied for this purpose. The focus of this project is, therefore, a new generation of wave power device for utility-scale energy conversion offering a cost of energy that can compete with established energy resources.
Output Temperature Predictions of the Geothermal Heat Pump System Using an Improved Grey Prediction Model
Authors: Salhein Khaled , Ashraf Javed , Zohdy Mohamed
Published: August 2021

This paper presents the Improved Grey Prediction Model, also called IGM (1,1) model, to increase the prediction accuracy of the Grey Prediction Model (GM) model that performs the GHPS output temperature prediction. This was based on correcting the current predicted value by subtracting the error between the previous predicted value and the previous immediate mean of the measured value. Subsequently, the IGM (1,1) model was applied to predict the output temperature of the GHPSs at Oklahoma University, the University Politècnica de València, and Oakland University, respectively. For each GHPS, the model uses a small dataset of 24 data points (i.e., 24 h) for training to predict the output temperature eight hours in advance. The proposed model was verified using three different output temperature datasets; these datasets were also used to validate the power efficiency of the proposed model. In addition, the empirical results show that the proposed IGM (1,1) model significantly improves the simulation (in-sample) and the prediction (out-of-sample) of the output temperature of the GHPS through error reduction, thereby enhancing the GM (1,1) model’s overall accuracy. As a result, the prediction accuracies were compared, and the improved model was found to be more accurate than the GM (1,1) model in both simulation and prediction results for all datasets used.
Technical and Economic Evaluation of CO2 Capture and Reinjection Process in the CO2 EOR and Storage Project of Xinjiang Oilfield
Authors: Zhang Liang , Geng Songhe , Yang Linchao , Hao Yongmao , Yang Hongbin , Dong Zhengmiao , Shi Xian
Published: August 2021

CO2 capture and reinjection process (CCRP) can reduce the used CO2 amount and improve the CO2 storage efficiency in CO2 EOR projects. To select the best CCRP is an important aspect. Based on the involved equipment units of the CCRP, a novel techno-economic model of CCRP for produced gas in CO2 EOR and storage project was established. Five kinds of CO2 capture processes are covered, including the chemical absorption using amine solution (MDEA), pressure swing adsorption (PSA), low-temperature fractionation (LTF), membrane separation (MS), and direct reinjection mixed with purchased CO2 (DRM). The evaluation indicators of CCRP such as the cost, energy consumption, and CO2 capture efficiency and purity can be calculated. Taking the pilot project of CO2 EOR and storage in XinJiang oilfield China as an example, a sensitivity evaluation of CCRP was conducted based on the assumed gas production scale and the predicted yearly gas production. Finally, the DRM process was selected as the main CCRP associated with the PSA process as an assistant option. The established model of CCRP can be a useful tool to optimize the CO2 recycling process and assess the CO2 emission reduction performance of the CCUS project.
The Current State of the Art in Research on Predictive Maintenance in Smart Grid Distribution Network: Fault’s Types, Causes, and Prediction Methods—A Systematic Review
Authors: Mahmoud Moamin A. , Md Nasir Naziffa Raha , Gurunathan Mathuri , Raj Preveena , Mostafa Salama A.
Published: August 2021

With the exponential growth of science, Internet of Things (IoT) innovation, and expanding significance in renewable energy, Smart Grid has become an advanced innovative thought universally as a solution for the power demand increase around the world. The smart grid is the most practical trend of effective transmission of present-day power assets. The paper aims to survey the present literature concerning predictive maintenance and different types of faults that could be detected within the smart grid. Four databases (Scopus, ScienceDirect, IEEE Xplore, and Web of Science) were searched between 2012 and 2020. Sixty-five (n = 65) were chosen based on specified exclusion and inclusion criteria. Fifty-seven percent (n = 37/65) of the studies analyzed the issues from predictive maintenance perspectives, while about 18% (n = 12/65) focused on factors-related review studies on the smart grid and about 15% (n = 10/65) focused on factors related to the experimental study. The remaining 9% (n = 6/65) concentrated on fields related to the challenges and benefits of the study. The significance of predictive maintenance has been developing over time in connection with Industry 4.0 revolution. The paper’s fundamental commitment is the outline and overview of faults in the smart grid such as fault location and detection. Therefore, advanced methods of applying Artificial Intelligence (AI) techniques can enhance and improve the reliability and resilience of smart grid systems. For future direction, we aim to supply a deep understanding of Smart meters to detect or monitor faults in the smart grid as it is the primary IoT sensor in an AMI.
1,2—Propanediol Production from Glycerol Derived from Biodiesel’s Production: Technical and Economic Study
Authors: Restrepo Juan B. , Paternina-Arboleda Carlos D. , Bula Antonio J.
Published: August 2021

For every nine tons of produced biodiesel, there is another ton of glycerol as a byproduct. Therefore, glycerol prices dropped significantly worldwide in recent years; the more significant biodiesel production is, the more glycerol exists as a byproduct. glycerol prices also impact the biodiesel manufacturing business, as it could be sold according to its refinement grade. The primary objective of this work was to evaluate the economic potential of the production of 1,2-propanediol derived from the biodiesel produced in Colombia. A plant to produce 1,2-propanediol via catalytic hydrogenation of glycerol in a trickle-bed reactor was designed. The plant comprised a reaction scheme where non-converted excess hydrogen was recycled, and the heat generated in the reactor was recovered. The reactor effluent was sent to a separation train where 98% m/m purity 1,2-propanediol was attained. Capital and operational costs were estimated from the process simulation. The net present value (NPV) and the modified internal return rate (MIRR) of the plant were used to assess the viability of the process. Their sensitivity to key input variables was evaluated to find the viability limits of the project. The economic potential of the 1,2-propanediol was calculated in USD 1.2/kg; for the base case, the NPV and the MIRR were USD 54.805 million and 22.56%, respectively, showing that, for moderate variations in products and raw material prices, the process is economically viable.
Design Consideration Regarding a Residential Renewable-Based Microgrid with EV Charging Station Capabilities
Authors: Marinescu Corneliu
Published: August 2021

Electric Vehicles (EVs) will be a key component of sustainable e-transportation systems. It is important to provide a charging infrastructure for EVs. EVs are “zero” polluting and highly efficient, but these qualities are valid only if the EV is supplied from renewable energy sources (RES). In urban areas, there is a lot of unused space such as roofs of residential and enterprise buildings, roofs of parking lots, building facades, etc. In cities, the PV and small wind turbines RES should be able to supply EVs with clean energy. Such a solution has many advantages. In an EU-financed research project, the team developed a solution for a Residential Charging Station (RCS), the design solution being implemented with the equipment available on the market. In this paper, the design considerations and some challenges raised by it are presented. Improvements of the existing equipment to better suit future needs are further discussed. The proposed solution solves the matter optimally and the implementing it will offer future Smart Cities an RCS with public access with several useful properties.
Classification of Void Space Types in Fractured-Vuggy Carbonate Reservoir Using Geophysical Logging: A Case Study on the Sinian Dengying Formation of the Sichuan Basin, Southwest China
Authors: Wang Kunyu , Teng Juan , Deng Hucheng , Fu Meiyan , Lu Hongjiang
Published: August 2021

The fractured-vuggy carbonate reservoirs display strong heterogeneity and need to be classified into different types for specific characterization. In this study, a total of 134 cores from six drilled wells and six outcrops of the Deng #2 and Deng #4 members of the Dengying Formation (Sichuan Basin, Southwest China) were selected to investigate the petrographic characteristics of void spaces in the fractured-vuggy carbonate reservoirs. Four void space types (VSTs) were observed, namely the solution-filling type (SFT), cement-reducing type (CRT), solution-filling breccia type (SFBT) and solution-enlarging fractures and vugs type (SEFVT). The CRT void spaces presented the largest porosity and permeability, followed by the SEFVT, SFBT and SFT. The VSTs presented various logging responses and values, and based on these, an identification method of VSTs using Bayes discriminant analysis (BDA) was proposed. Two test wells were employed for the validation of the identification method, and the results show that there is good agreement between the identification results and core description. The vertical distribution of VSTs indicates that the SFT and SEFVT are well distributed in both the Deng #2 and Deng #4 members. The CRT is mainly found in the Deng #2 member, and the SFBT occurs in the top and middle of the Deng #4 member.
Effect of Pyrolysis Reactions on Coal and Biomass Gasification Process
Authors: Chmielniak Tomasz , Stepien Leszek , Sciazko Marek , Nowak Wojciech
Published: August 2021

Thermodynamic analysis of a gasification process was conducted assuming that it is composed of two successive stages, namely: pyrolysis reaction followed by a stage of gasification reaction. This approach allows formulation the models of selected gasification processes dominating in industrial applications namely: Shell (coal), SES (coal), and DFB (dual fluid bed, biomass) gasification. It was shown that the enthalpy of fuel formation is essential for the correctness of computed results. The specific computational formula for a wide range of fuels enthalpy of formation was developed. The following categories were evaluated in terms of energy balance: total reaction enthalpy of gasification process, enthalpy of pyrolysis reaction, enthalpy of gasification reaction, heat demand for pyrolysis reaction, and heat demand for gasification reactions. The discussion of heat demand for particular stages of gasification related to the various processes was performed concluding the importance of the pyrolysis stage.
Metabolically Active Prokaryotic Complex in Grassland and Forests’ Sod-Podzol under Polycyclic Aromatic Hydrocarbon Influence
Authors: Manucharova Natalia A. , Pozdnyakov Lev A. , Vlasova Anastasiya P. , Yanovich Anastasiya S. , Ksenofontova Natalia A. , Kovalenko Maria A. , Stepanov Pavel Y. , Gennadiev Alexander N. , Golovchenko Alla V. , Stepanov Alexey L.
Published: August 2021

Molecular genetic techniques (FISH, RT-PCR, and metagenomic analysis) were used to investigate the comparative functional biodiversity in the prokaryotic complex in grassland and forests’ sod-podzol under polycyclic aromatic hydrocarbon influence. The polluted samples showed a decrease in the biomass of the prokaryotic community representatives and a change in the metabolically active dominants–representatives of the Bacteria and Archaea domains compared to the control samples. The suppression of the metabolic activity of prokaryote cells under the influence of PAHs in sod-podzolic soil under meadow vegetation was more pronounced compared to soils under forest vegetation. The representatives of prokaryotes that are sensitive and resistant to the studied PAHs were identified. The representatives of the phylogenetic groups from the bacterial complex resistant to PAH pollution were Proteobacteria (Alphaproteobacteria), Bacteroidetes, Firmicutes, Chloroflexi, and Thaumarhaeota in the archaeal complex. Representatives of the phylum Acidobacteria and Actinobacteria (Streptosporangiales) are noted among those sensitive to PAH contamination. The presence and expression of the functional alkane monooxygenase (alkB) gene were established in all the experimental variants studied. In the plant variants, the number of copies of alkB genes increased by an order of magnitude and the biomass of metabolically active prokaryotic representatives with the functional alkB gene doubled compared to the unpolluted territories. The copy number index of the alkB gene can be used as one of the parameters when characterizing an ecosystem for the presence of PAH pollutants.
Profiling of 2-Acetyl-1-Pyrroline and Other Volatile Compounds in Raw and Cooked Rice of Traditional and Improved Varieties of India
Authors: Kasote Deepak , Singh Vivek Kumar , Bollinedi Haritha , Singh Ashok Kumar , Sreenivasulu Nese , Regina Ahmed
Published: August 2021

Herein, optimized headspace solid phase microextraction with gas chromatography–tandem mass spectrometry (HS-SPME-GC-MS/MS) was used to estimate the 2-acetyl-1-pyrroline (2-AP) in raw and cooked rice samples of ten different traditional and improved varieties. Furthermore, HS-SPME-GC-MS-based volatile profiling was subjected to untargeted analyses to identify major odorants in raw and cooked rice samples, and to understand chemical proximities among volatile profiles. Results showed that 2-AP content was remarkably increased in cooked rice compared to raw. Among the varieties studied, Pusa-1652 (Improved Kala Namak) and Kala Namak-2 were superior in the 2-AP content than Basmati varieties. Additionally, Govind Bhog, Kala Jeera and Jeera-32 had 2-AP content equivalent to or superior to Basmati rice varieties. Altogether, 18 and 22 volatiles were identified in the raw and cooked rice samples studied, respectively. Of these, ethyl butyrate, ethyl 3-methylbutanoate, 2-undecanone, ethyl benzoate, ethyl benzeneacetate, 2-methylnaphthalene, and 1-methylnaphthalene were characteristically detected in the cooked rice. The high amount of 2-ethyl-1-hexanol was uniquely found in raw rice samples, which can be a marker compound for freshly milled rice. Along with 2-AP, butanoic acid and benzoic acid derivatives, phenylethyl alcohol, ethyl 3-hydroxybutyrate, and indole may be responsible for the overall perceived characteristic Basmati-like aroma in cooked rice.
Orthonormal Ultraspherical Operational Matrix Algorithm for Fractal–Fractional Riccati Equation with Generalized Caputo Derivative
Authors: Youssri Youssri Hassan
Published: August 2021

Herein, we developed and analyzed a new fractal–fractional (FF) operational matrix for orthonormal normalized ultraspherical polynomials. We used this matrix to handle the FF Riccati differential equation with the new generalized Caputo FF derivative. Based on the developed operational matrix and the spectral Tau method, the nonlinear differential problem was reduced to a system of algebraic equations in the unknown expansion coefficients. Accordingly, the resulting system was solved by Newton’s solver with a small initial guess. The efficiency, accuracy, and applicability of the developed numerical method were checked by exhibiting various test problems. The obtained results were also compared with other recent methods, based on the available literature.
Hydrogen Jet Fire from a Thermally Activated Pressure Relief Device (TPRD) from Onboard Storage in a Naturally Ventilated Covered Car Park
Authors: Hussein Harem , Brennan Síle , Molkov Vladimir
Published: August 2021

Hydrogen jet fires from a thermally activated pressure relief device (TPRD) on onboard storage are considered for a vehicle in a naturally ventilated covered car park. Computational Fluid Dynamics was used to predict behaviour of ignited releases from a 70 MPa tank into a naturally ventilated covered car park. Releases through TPRD diameters 3.34, 2 and 0.5 mm were studied to understand effect on hazard distances from the vehicle. A vertical release, and downward releases at 0°, 30° and 45° for TPRD diameters 2 and 0.5 mm were considered, accounting for tank blowdown. direction of a downward release was found to significantly contribute to decrease of temperature in a hot cloud under the ceiling. Whilst the ceiling is reached by a jet exceeding 300 °C for a release through a TPRD of 2 mm for inclinations of either 0°, 30° or 45°, an ignited release through a TPRD of 0.5 mm and angle of 45° did not produce a cloud with a temperature above 300 °C at the ceiling during blowdown. The research findings, specifically regarding the extent of the cloud of hot gasses, have implications for the design of mechanical ventilation systems.
Evaluating a Psychoeducation Program to Foster Chinese Primary School Students’ Covitality
Authors: Fang Min , Zhang Li , Pan Dachen , Xie Jiashu
Published: August 2021

This investigation evaluated the Growth Psychoeducation Intervention (GPI) designed to increase primary school students’ covitality, a construct describing the beneficial combinatorial effects of positive psychological skills and mindsets. Students with higher covitality levels have stronger relationships with their teachers and classmates, and behave in more positive ways. This GPI intervention study employed a pretest-posttest-follow quasi-experimental design to evaluate a culturally adapted group counseling intervention designed to foster Chinese senior primary school students’ (n = 189, ages 9–12 years) covitality levels. The hypothesis was that covitality increases would positively correlate with school belonging and life satisfaction and less frequent bullying victimization. The Social Emotional Health Survey-Primary (SEHS-P) assessed the effectiveness of the GPI eight-week program to promote mental health and decrease bullying. GPI demonstrated effectiveness by improving students’ covitality and school belonging and reducing bullying victimization.
Predicting User Activity Intensity Using Geographic Interactions Based on Social Media Check-In Data
Authors: Li Jing , Guo Wenyue , Liu Haiyan , Chen Xin , Yu Anzhu , Li Jia
Published: August 2021

Predicting user activity intensity is crucial for various applications. However, existing studies have two main problems. First, as user activity intensity is nonstationary and nonlinear, traditional methods can hardly fit the nonlinear spatio-temporal relationships that characterize user mobility. Second, user movements between different areas are valuable, but have not been utilized for the construction of spatial relationships. Therefore, we propose a deep learning model, the geographical interactions-weighted graph convolutional network-gated recurrent unit (GGCN-GRU), which is good at fitting nonlinear spatio-temporal relationships and incorporates users’ geographic interactions to construct spatial relationships in the form of graphs as the input. The model consists of a graph convolutional network (GCN) and a gated recurrent unit (GRU). The GCN, which is efficient at processing graphs, extracts spatial features. These features are then input into the GRU, which extracts their temporal features. Finally, the GRU output is passed through a fully connected layer to obtain the predictions. We validated this model using a social media check-in dataset and found that the geographical interactions graph construction method performs better than the baselines. This indicates that our model is appropriate for fitting the complex nonlinear spatio-temporal relationships that characterize user mobility and helps improve prediction accuracy when considering geographic flows.
Heat Maps: Perfect Maps for Quick Reading? Comparing Usability of Heat Maps with Different Levels of Generalization
Authors: Słomska-Przech Katarzyna , Panecki Tomasz , Pokojski Wojciech
Published: August 2021

Recently, due to Web 2.0 and neocartography, heat maps have become a popular map type for quick reading. Heat maps are graphical representations of geographic data density in the form of raster maps, elaborated by applying kernel density estimation with a given radius on point- or linear-input data. The aim of this study was to compare the usability of heat maps with different levels of generalization (defined by radii of 10, 20, 30, and 40 pixels) for basic map user tasks. A user study with 412 participants (16–20 years old, high school students) was carried out in order to compare heat maps that showed the same input data. The study was conducted in schools during geography or IT lessons. Objective (the correctness of the answer, response times) and subjective (response time self-assessment, task difficulty, preferences) metrics were measured. The results show that the smaller radius resulted in the higher correctness of the answers. A larger radius did not result in faster response times. The participants perceived the more generalized maps as easier to use, although this result did not match the performance metrics. Overall, we believe that heat maps, in given circumstances and appropriate design settings, can be considered an efficient method for spatial data presentation.
Within-Host Adaptation of Staphylococcus aureus in a Bovine Mastitis Infection Is Associated with Increased Cytotoxicity
Authors: Mayer Katharina , Kucklick Martin , Marbach Helene , Ehling-Schulz Monika , Engelmann Susanne , Grunert Tom
Published: August 2021

Within-host adaptation is a typical feature of chronic, persistent Staphylococcus aureus infections. Research projects addressing adaptive changes due to bacterial in-host evolution increase our understanding of the pathogen’s strategies to survive and persist for a long time in various hosts such as human and bovine. In this study, we investigated the adaptive processes of S. aureus during chronic, persistent bovine mastitis using a previously isolated isogenic strain pair from a dairy cow with chronic, subclinical mastitis, in which the last variant (host-adapted, Sigma factor SigB-deficient) quickly replaced the initial, dominant variant. The strain pair was cultivated under specific in vitro infection-relevant growth-limiting conditions (iron-depleted RPMI under oxygen limitation). We used a combinatory approach of surfaceomics, molecular spectroscopic fingerprinting and in vitro phenotypic assays. Cellular cytotoxicity assays using red blood cells and bovine mammary epithelial cells (MAC-T) revealed changes towards a more cytotoxic phenotype in the host-adapted isolate with an increased alpha-hemolysin (α-toxin) secretion, suggesting an improved capacity to penetrate and disseminate the udder tissue. Our results foster the hypothesis that within-host evolved SigB-deficiency favours extracellular persistence in S. aureus infections. Here, we provide new insights into one possible adaptive strategy employed by S. aureus during chronic, bovine mastitis, and we emphasise the need to analyse genotype–phenotype associations under different infection-relevant growth conditions.
Inhibition of Cell Proliferation and Metastasis by Scutellarein Regulating PI3K/Akt/NF-κB Signaling through PTEN Activation in Hepatocellular Carcinoma
Authors: Ha Sang Eun , Kim Seong Min , Vetrivel Preethi , Kim Hun Hwan , Bhosale Pritam Bhagwan , Heo Jeong Doo , Lee Ho Jeong , Kim Gon Sup
Published: August 2021

Scutellarein (SCU) is a well-known flavone with a broad range of biological activities against several cancers. Human hepatocellular carcinoma (HCC) is major cancer type due to its poor prognosis even after treatment with chemotherapeutic drugs, which causes a variety of side effects in patients. Therefore, efforts have been made to develop effective biomarkers in the treatment of HCC in order to improve therapeutic outcomes using natural based agents. The current study used SCU as a treatment approach against HCC using the HepG2 cell line. Based on the cell viability assessment up to a 200 μM concentration of SCU, three low-toxic concentrations of (25, 50, and 100) μM were adopted for further investigation. SCU induced cell cycle arrest at the G2/M phase and inhibited cell migration and proliferation in HepG2 cells in a dose-dependent manner. Furthermore, increased PTEN expression by SCU led to the subsequent downregulation of PI3K/Akt/NF-κB signaling pathway related proteins. In addition, SCU regulated the metastasis with EMT and migration-related proteins in HepG2 cells. In summary, SCU inhibits cell proliferation and metastasis in HepG2 cells through PI3K/Akt/NF-κB signaling by upregulation of PTEN, suggesting that SCU might be used as a potential agent for HCC therapy.