bluuebunny/crossref_metadata_2025 huggingface dataset:
Pyloric Incompetence Associated with Helicobactor pylori Infection and Correlated to the Severity of Atrophic Gastritis
Authors: Sakaguchi Takuki , Sugihara Takaaki , Ohnita Ken , Fukuda Daisuke , Honda Tetsuro , Ogihara Ryohei , Kurumi Hiroki , Yashima Kazuo , Isomoto Hajime
Published: February 2022

Duodenogastric reflux (DGR) causes bile reflux gastritis (BRG) and may develop into gastric cancer. DGR is classified as primary in non-operated stomachs or secondary to surgical intervention. Primary DGR and Helicobacter pylori (H. pylori) infection are reportedly related. However, the mechanism is not fully understood. This study aimed to elucidate the relationship between H. pylori infection and pyloric incompetence in a non-operated stomach. A total of 502 non-operated participants who underwent an upper intestinal endoscopy were prospectively enrolled. Endoscopic findings (EAC, endoscopic atrophy classification; nodular gastritis; xanthoma; fundic gland polyp; and incompetence of pylorus), sex, age, gastrin, pepsinogen (PG) I and PG II levels were evaluated. PG I/PG II ratio, anti-H. pylori-Ab positivity, and atrophic gastritis status were significantly different between the normal and incompetent pylori (p = 0.043, <0.001, and 0.001, respectively). Open-type atrophic gastritis was significantly higher in the incompetent pylori. Incompetence of the pylorus and EAC were moderately correlated (Cramer’s V = 0.25). Multivariate analysis revealed that the presence of anti-H. pylori-Ab was the only independent factor associated with the incompetence of the pylorus, with an adjusted odds ratio of 2.70 (95% CI: 1.47–4.94, p = 0.001). In conclusion, pyloric incompetence was associated with H. pylori infection and moderately correlated to the severity of atrophic gastritis in non-operated stomachs.
Success Rates and Complications Associated with Single Immediate Implants: A Systematic Review
Authors: Thanissorn Charn , Guo Jason , Jing Ying Chan Dianna , Koyi Bryar , Kujan Omar , Khzam Nabil , Miranda Leticia Algarves
Published: February 2022

This study examined the success rates of single immediate implants and their associated biological, hardware and aesthetic complications. Using a developed search strategy, randomized controlled trials (RCTs) on single-unit immediate implants with at least six human participants, a minimum follow-up time of 12 months and published between January 1999 and January 2021 were identified. Data was extracted independently using pre-designed data extraction forms. Information on success rates and associated biological, hardware and aesthetic complications were obtained and assessed. Out of 191 potentially eligible studies, 26 RCTs assessing 1270 patients with a total of 1326 single implants were included and further evaluated. In this review, success rate was reported to be 96.7–100% over a total of 9 studies. However, there was a lack of consensus on a universal success criterion between authors emphasizing the need for agreement. The average follow up was 29 months and most reported complications were aesthetic (63 cases, 4.7%), whilst there were relatively fewer biological, (20 cases, 1.5%), and hardware complications (24 cases, 1.8%). Success rate is an uncommon clinical outcome with 9 out of 26 of the selected RCTs reporting it. In these studies, single immediate implants showed a high success rate with low numbers of biological and hardware complications, and high patient satisfaction with aesthetics were reported in the short-term follow-up of one year.
Equilibration and “Thermalization” in the Adapted Caldeira–Leggett Model
Authors: Albrecht Andreas
Published: February 2022

I explore the processes of equilibration exhibited by the Adapted Caldeira–Leggett (ACL) model, a small unitary “toy model” developed for numerical studies of quantum decoherence between an SHO and an environment. I demonstrate how dephasing allows equilibration to occur in a wide variety of situations. While the finite model size and other “unphysical” aspects prevent the notions of temperature and thermalization from being generally applicable, certain primitive aspects of thermalization can be realized for particular parameter values. I link the observed behaviors to intrinsic properties of the global energy eigenstates, and argue that the phenomena I observe contain elements which might be key ingredients that lead to ergodic behavior in larger more realistic systems. The motivations for this work range from curiosity about phenomena observed in earlier calculations with the ACL model to much larger questions related to the nature of equilibrium, thermalization, and the emergence of physical laws.
Self-Adaptive Image Thresholding within Nonextensive Entropy and the Variance of the Gray-Level Distribution
Authors: Deng Qingyu , Shi Zeyi , Ou Congjie
Published: February 2022

In order to automatically recognize different kinds of objects from their backgrounds, a self-adaptive segmentation algorithm that can effectively extract the targets from various surroundings is of great importance. Image thresholding is widely adopted in this field because of its simplicity and high efficiency. The entropy-based and variance-based algorithms are two main kinds of image thresholding methods, and have been independently developed for different kinds of images over the years. In this paper, their advantages are combined and a new algorithm is proposed to deal with a more general scope of images, including the long-range correlations among the pixels that can be determined by a nonextensive parameter. In comparison with the other famous entropy-based and variance-based image thresholding algorithms, the new algorithm performs better in terms of correctness and robustness, as quantitatively demonstrated by four quality indices, ME, RAE, MHD, and PSNR. Furthermore, the whole process of the new algorithm has potential application in self-adaptive object recognition.
The Effect of Working Mother Status on Children’s Education Attainment: Evidence from Longitudinal Data
Authors: Azizah Siti Nur , Saleh Samsubar , Sulistyaningrum Eny
Published: February 2022

This study builds on the debate on whether mothers‘ employment in the early life of children bring positive or negative impact to children in later life. This is based on the fact that employment often result in reduced family time in which mother may not be able to take care of their children fully. This study estimated the effects of mothers’ employment status on children’s education in the short-term and in the long-term in 24 provinces in Indonesia. This study used data on children from three waves of the Indonesia Family Life Survey (IFLS): IFLS-3 (in 2000) aged 0–7 years, IFLS-4 (in 2007) aged 7–14 years, and IFLS-5 (in 2014) aged 14–21 years. The outcome variable was the children’s education and the variable of interest was the mother’s employment status. To overcome endogeneity, the analysis of the relationship between outcome and interest variables in this study was done by using the ordinary least square estimation (OLS) method and instrumental variables (IV). This study also used a cross-sectional design which estimated IFLS-4 (in 2007) and IFLS-5 (in 2014), separately. The main finding suggests that the mother’s employment status positively influenced children’s education both in the short- and long-term, as evidenced by the ordinary least square estimation (OLS) results. The instrumental variable (IV) estimate showed that decision-making was a strong instrument; and, it further revealed that mothers’ decision-making within the family affected their opportunity to work. This research could contribute to strengthening working mothers’ self-border and the concept of work-family facilitation in a family. It could also become a reference for stakeholders involved in the policy making to regulate policies which facilitate and support working mother to create ideal working environment. This condition is expected to supports children’s development as well as creating equity for working mothers in Indonesia.
A Deep Learning-Based Smart Framework for Cyber-Physical and Satellite System Security Threats Detection
Authors: Ashraf Imran , Narra Manideep , Umer Muhammad , Majeed Rizwan , Sadiq Saima , Javaid Fawad , Rasool Nouman
Published: February 2022

An intrusion detection system serves as the backbone for providing high-level network security. Different forms of network attacks have been discovered and they continue to become gradually more sophisticated and complicated. With the wide use of internet-based applications, cyber security has become an important research area. Despite the availability of many existing intrusion detection systems, intuitive cybersecurity systems are needed due to alarmingly increasing intrusion attacks. Furthermore, with new intrusion attacks, the efficacy of existing systems depletes unless they evolve. The lack of real datasets adds further difficulties to properly investigating this problem. This study proposes an intrusion detection approach for the modern network environment by considering the data from satellite and terrestrial networks. Incorporating machine learning models, the study proposes an ensemble model RFMLP that integrates random forest (RF) and multilayer perceptron (MLP) for increasing intrusion detection performance. For analyzing the efficiency of the proposed framework, three different datasets are used for experiments and validation, namely KDD-CUP 99, NSL-KDD, and STIN. In addition, performance comparison with state-of-the-art models is performed which suggests that the RFMLP can detect intrusion attacks with high accuracy than the existing approaches.
Android-SEM: Generative Adversarial Network for Android Malware Semantic Enhancement Model Based on Transfer Learning
Authors: Huang Yizhao , Li Xingwei , Qiao Meng , Tang Ke , Zhang Chunyan , Gui Hairen , Wang Panjie , Liu Fudong
Published: February 2022

Currently, among the millions of Android applications, there exist numerous malicious programs that pose significant threats to people’s security and privacy. Therefore, it is imperative to develop approaches for detecting Android malware. Recently developed malware detection methods usually rely on various features, such as application programming interface (API) sequences, images, and permissions, thereby ignoring the importance of source code and the associated comments, which are not usually included in malware. Therefore, we propose Android-SEM, which is an Android source code semantic enhancement model based on transfer learning. Our proposed model is built upon the Transformer architecture to achieve a pretraining framework for generating code comments from malware source code. The performance of the pretraining framework is optimized using a generative adversarial network. Our proposed model relies on a novel regression model-based filter to retain high-quality comments and source code for feature fusion pertinent to semantic enhancement. Creatively, and contrary to conventional methods, we incorporated a quantum support vector machine (QSVM) for classifying malicious Android code by combining quantum machine learning and classical deep learning models. The results proved that Android-SEM achieves accuracy levels of 99.55% and 99.01% for malware detection and malware categorization, respectively.
Broadband Millimeter-Wave 5G Power Amplifier Design in 22 nm CMOS FD-SOI and 40 nm GaN HEMT
Authors: Mayeda Jill , Lie Donald Y. C. , Lopez Jerry
Published: February 2022

Three millimeter-wave (mm-Wave) power amplifiers (PAs) that cover the key 5G FR2 band of 24.25 to 43.5 GHz are designed in two different state-of-the-art device technologies and are presented in this work. First, a single-ended broadband PA that employs a third-order input matching network is designed in a 40 nm GaN/SiC HEMT (High Electron Mobility Transistor) technology. Good agreement between the measurement and post-layout parasitic extracted (PEX) electromagnetic (EM) simulation data is observed, and it achieves a measured 3-dB BW (bandwidth) of 18.0–40.3 GHz and >20% maximum PAE (power-added-efficiency) across the entire 20–44 GHz band. Expanding upon this measured design, a differential broadband GaN PA that utilizes neutralization capacitors is designed, laid out, and EM simulated. Simulation results indicate that this PA achieves 3-dB BW 20.1–44.3 GHz and maximum PAE > 23% across this range. Finally, a broadband mm-Wave differential CMOS PA using a cascode topology with RC feedback and neutralization capacitors is designed in a 22 nm FD-SOI (fully depleted silicon-on-insulator) CMOS technology. This PA achieves an outstanding measured 3-dB BW of 19.1–46.5 GHz and >12.5% maximum PAE across the entire frequency band. This CMOS PA as well as the single-ended GaN PA are tested with 256-QAM-modulated 5G NR signals with an instantaneous signal BW of 50/100/400/9 × 100 MHz at a PAPR (peak-to-average-power ratio) of 8 dB. The data exhibit impressive linearity vs. POUT trade-off and useful insights on CMOS vs. GaN PA linearity degradation against an increasing BW for potential mm-Wave 5G applications.
Study on Fiber Clogging Mechanism in Sewage Pump Based on CFD–DEM Simulation
Authors: Zheng Shuihua , Yang Chaojie , Yan Chaoshou , Chai Min , Sun Zenan
Published: February 2022

A large number of solid particles and fibrous impurities are always entrained in the fluid transported by a sewage pump, which can easily lead to the blockage of the sewage pump. In view of this, CFD–DEM simulations were conducted in this paper to reveal the fiber clogging mechanism in the sewage pump. A CFD–DEM coupling method with a fiber model was established and verified by an experimental benchmark, i.e., the rectangular flow channel. The method was then applied to a model sewage pump to, after mesh independence tests, analyze the effects of flow rate and fiber length on fiber motion and clogging. The results showed that the position of fiber retention coincides with the position of the vortex, mainly located at the inlet of the impeller, the head of the blade, the middle of the blade, and the tongue in the pump. In the case of a low flow rate, the fiber was more likely to cause blockage in the head of the blade, and in the case of a large flow rate, the fiber would wind around the tongue in the pump. At the same flow rate, long fiber was more likely to stay on the blade’s suction surface.
Evaluation of Indoor Thermal Environmental Conditions of Residential Buildings in Saudi Arabia
Authors: Alaboud Mosaab , Gadi Mohamed
Published: February 2022

The Saudi Arabian climate, generally speaking, is known to be hot and arid. Even with its extensive energy resources, Saudi Arabia is not immune to the demands of climate change. Over 50% of the country’s electricity is consumed by residential buildings. For economic, fiscal, and environmental reasons, government policy is to stem the profligate use of finite energy resources. It is incumbent on the Saudi building industry to adapt to changing conditions by re-assessing the choice of materials and the design and lay-out of new buildings to help quell demands for air-conditioning during the hotter parts of the year. Throughout the country, electricity consumption doubles in the summer months. Given this situation, this study explores the indoor thermal environment typical of residential buildings. The study selected one house located in a hot dry climatic region as a case study. The features of the house were assessed to determine the permeable features that require improvement. Two main methods used to evaluate indoor thermal conditions are physical measurements and computer modelling. Instruments were used to monitor the house during both summer and winter months. Thermal analysis software was used to model the thermal properties of the house for two purposes, first, to assess the thermal performance of the case-study building, and second, to identify areas in which improvements could be made using proposed alternative materials. Different parts of the building were simulated using different material combinations to achieve the optimal cooling reduction. The findings suggest that the cooling load can be reduced of up to 56.4%. Consequently, the intensity of the proposed annual cooling for the chosen house was predicted to be 79.7 kWh/m2/y.
Hybrid Nanofluid in a Direct Absorption Solar Collector: Magnetite vs. Carbon Nanotubes Compete for Thermal Performance
Authors: Struchalin Pavel G. , Kuzmenkov Dmitrii M. , Yunin Vladimir S. , Wang Xinzhi , He Yurong , Balakin Boris V.
Published: February 2022

The paper presents the experimental measurements of thermal efficiency of a tubular direct absorption solar collector (DASC) with a hybrid nanofluid based on magnetite (Fe3O4) and multi-walled carbon nanotubes (MWCNT). The volumetric concentration of Fe3O4 and MWCNT was 0.0053% and 0.0045%, respectively. The experiments were carried out for the flow rates of 2–10 L/min and a temperature difference up to 20 ∘C between the environment and the DASC. The performance of the DASC with a hybrid nanofluid was in the range of 52.3–69.4%, which was just beyond the performance of the collector with surface absorption. It was also found that using a MWCNT-based nanofluid with an equivalent total volumetric concentration of particles (0.0091%), the efficiency was 8.3–31.5% higher than for the cases with the hybrid nanofluid.
Using a Genetic Algorithm to Achieve Optimal Matching between PMEP and Diameter of Intake and Exhaust Throat of a High-Boost-Ratio Engine
Authors: Song Yindong , Xu Yiyu , Cheng Xiuwei , Wang Ziyu , Zhu Weiqing , Fan Xinyu
Published: February 2022

With the increasingly stringent CO2 emission regulations, the degree of strengthening of the engines is increasing. Under high-pressure conditions, the airway throat parts of the intake and exhaust systems have a great influence on the flow loss of the diesel engine. The reasonable distribution of the throat area of the intake and exhaust ports in the limited cylinder headspace is key to improving the performance of supercharged engines. This study took a large-bore, high-pressure ratio diesel engine as the research object. Firstly, the three-dimensional (3D) flow simulation method was used to reveal the influence law of different throat areas on the engine intake and exhaust flow under steady-state conditions, and a steady-flow test bench was built to verify the accuracy of the simulation model and law. Secondly, based on the 3D steady-state calculation and test results, a more accurate one-dimensional simulation model was constructed, and a joint optimization simulation platform was established based on the dynamic data link library. On this basis, the mathematical description of the multi-objective optimization of airway throat size was established using machine learning methods, such as a genetic algorithm, the design domain and boundary conditions of variable parameters were clarified, and the collaborative optimization objective of integrated flow coefficient and flow loss is proposed to achieve the fast and accurate optimization of intake and exhaust throat diameters.
Displacement Estimation of Six-Pole Hybrid Magnetic Bearing Using Modified Particle Swarm Optimization Support Vector Machine
Authors: Liu Gai , Zhu Huangqiu
Published: February 2022

In order to solve the problems of the large volume and high cost of a six-pole hybrid magnetic bearing (SHMB) with displacement sensors, a displacement estimation method using a modified particle swarm optimization (MPSO) least-squares support vector machine (LS-SVM) is proposed. Firstly, the inertial weight of the MPSO is changed to achieve faster iterations, and the prediction model of an LS-SVM-based MPSO is built. Secondly, the prediction model is simulated and verified according to the parameters optimized by the MPSO, and the predicted values of MPSO and PSO are compared. Finally, static and dynamic suspension experiments and a disturbance experiment are carried out, which verify the robustness and stability of the displacement estimation method.
Development of Data Cleaning and Integration Algorithm for Asset Management of Power System
Authors: Hwang Jae-Sang , Mun Sung-Duk , Kim Tae-Joon , Oh Geun-Won , Sim Yeon-Sub , Chang Seung Jin
Published: February 2022

Asset management technology is rapidly growing in the electric power industry because utilities are paying attention to which of their aged assets should be replaced first. The global trend of asset management follows risk management that comprehensively considers the probability and consequences of failures. In the asset management system, the risk assessment algorithm operates by interfacing digital datasets from various legacy systems. In this study, among the various electric power assets, we consider transmission cable systems as a representative linear asset consisting of different segments. First, the configurations and characteristics of linear asset datasets are analyzed. Second, six types of data cleaning functions are proposed for extracting dirty data from the entire dataset. Third, three types of data integration functions are developed to simulate the risk assessment algorithm. This technique supports the integration of distributed asset data in various legacy systems into one dataset. Finally, an automatic data cleaning and integration system is developed and the algorithm could repeat the cleaning and integration process until data quality is satisfied. To evaluate the performance of the proposed system, an automatic cleaning process is demonstrated using actual legacy datasets.
A Mathematical Model of Electrical Arc Furnaces for Analysis of Electrical Mode Parameters and Synthesis of Controlling Influences
Authors: Lozynskyy Andriy , Kozyra Jacek , Łukasik Zbigniew , Kuśmińska-Fijałkowska Aldona , Kutsyk Andriy , Paranchuk Yaroslav , Kasha Lidiia
Published: February 2022

The synthesis of a real-time model of the electric mode of an arc steelmaking furnace is shown. This model is based on the method of medium-voltage and can be used to analyze the impact of the arc steelmaking furnace on the supply network at different stages of the melting process at different control systems of the electromechanical electrode movement system, and to create model-predictive control systems of electrode movement, when control using hardware in the loop technology. To implement the chosen method, the dynamic arc resistance was used. The last was obtained on the basis of the averaged experimentally taken volt-ampere characteristics of the arc. In paper was proposed its approximation as a current function and arc length. The simulation results obtained using the created model for different operation modes of the arc steelmaking chipboard for a system with a traditional regulator of the electrode movement system are demonstrated.
Radio-Oxidation of Electric Cabled Models: Ageing Evaluation at the Atomic Scale
Authors: Ferry Muriel , Miserque Frederic
Published: February 2022

The functionality of electric cables, being the safety components of plants, has to be ensured. In nuclear power plants, when they are in the reactor building, these cables can suffer γ irradiation even in normal operating conditions. Their ageing behaviour needs to be well understood to be able to determine a precise end-of-life criterion. As polymers are the most radiosensitive material of the cables, this paper focuses on the ageing of this kind of material and, more specifically, on the ageing of silane-crosslinked polyethylenes (XLPEs). XLPEs are now one of the most employed polymers to manufacture cables. We performed irradiation under oxidative conditions of several model silane-crosslinked polyethylenes with different additives and filler: at three different doses (0, 67, 220 and 374 kGy) for one dose rate (78 Gy·h−1) and at one dose (67 kGy) for three dose rates (8.5, 78 and 400 Gy·h−1). Modifications in the organic materials were followed by X-ray photoelectron spectroscopy. This analytical technique allows following the evolution of the different chemical products formed under irradiation. A better understanding at the atomic scale of the effect of additives on the degradation of polymers is proposed as a function of the ageing conditions.
RBF Neural Network-Based Sliding Mode Control for Modular Multilevel Converter with Uncertainty Mathematical Model
Authors: Yang Xuhong , Fang Haoxu
Published: February 2022

For medium and high-powered applications, modular multilevel converters have become the most promising converter application. In this paper, a sliding mode controller based on an RBF neural network is proposed for a modular multilevel converter. The RBF neural network is designed to approximate the uncertainty mathematical model of a modular multilevel converter. The main innovation of the proposed method is that it does not require any model parameters and control parameters during the whole control process. This means that parameter changes caused by the external environment will not influence the controller performances. Finally, by comparing with a conventional PI controller, the simulation proves the feasibility and effectiveness of the proposed control method. In addition, the experimental results show that the grid-side current can become stable immediately while the active power is stabilized after 20 ms when the set value is changed.
Comment on Rogalev et al. Structural and Parametric Optimization of S-CO2 Thermal Power Plants with a Pulverized Coal-Fired Boiler Operating in Russia. Energies 2021, 14, 7136
Authors: Variny Miroslav
Published: February 2022

The reconstruction of ageing thermal power plants with the possibility of their increased efficiency, prolonged service and decreased environmental impact is an intensely debated and researched topic nowadays. Among various concepts, the replacement of the steam cycle by a supercritical CO2 cycle is proposed with the prospect of reaching higher efficiencies at the same working fluid inlet parameters as the ultra-supercritical steam cycles. A paper published previously by Rogalev et al. (2021) analyzed the variants of supercritical coal power plant reconstruction to a supercritical CO2 cycle and ranked them according to the cycle efficiency. This contribution comments on the scope and applied method in that paper aiming to provide additional input relevant to the decision-making process on thermal power plant reconstruction to such a cycle.
Management the Operation Process of Photovoltaic Modules in Terms of Quality and Performance Evaluation—A Case Study
Authors: Idzikowski Adam , Cierlicki Tomasz , Al-Zubiedy Ali , Zawada Marcin
Published: February 2022

This article’s focuses of photovoltaic installations, which are becoming more and more popular in Poland and around the world. A short theoretical introduction to photovoltaic cells is presented, and the aim of the research is distinguished. Then, the formulas for the parameters characterizing solar cells are derived. The parameters that determine the highest efficiency of solar cells are specified in the next section. In the experimental part, tests of a selected photovoltaic installation were carried out. Based on the research, we conclude that temperature and sunlight have a significant impact on the efficiency of solar cells.
Design Evaluation of a Next-Generation High-Temperature Particle Receiver for Concentrating Solar Thermal Applications
Authors: Mills Brantley H. , Ho Clifford K. , Schroeder Nathaniel R. , Shaeffer Reid , Laubscher Hendrik F. , Albrecht Kevin J.
Published: February 2022

High-temperature particle receivers are being developed to achieve temperatures in excess of 700 °C for advanced power cycles and solar thermochemical processes. This paper describes designs and features of a falling particle receiver system that has been evaluated and tested at the National Solar Thermal Test Facility at Sandia National Laboratories. These advanced designs are intended to reduce heat losses and increase the thermal efficiency. Novel features include aperture covers, active air flow, particle flow obstructions, and optimized receiver shapes that minimize advective heat losses, increase particle curtain opacity and uniformity, and reduce cavity wall temperatures. Control systems are implemented in recent on-sun tests to maintain a desired particle outlet temperature using an automated closed-loop proportional–integral–derivative controller. These tests demonstrate the ability to achieve and maintain particle outlet temperatures approaching 800 °C with efficiencies between 60 and 90%, depending on incident power, mass flow, and environmental conditions. Lessons learned regarding the testing of design features and overall receiver operation are also presented.
Cost Optimal Renewable Electricity-Based HVAC System: Application of Air to Water or Water to Water Heat Pump
Authors: Delač Boris , Pavković Branimir , Grozdek Marino , Bezić Luka
Published: February 2022

This paper aims to determine cost optimality between heating, ventilation and air conditioning (HVAC) systems operating with air to water heat pumps (AWHP) and water to water heat pumps (WWHP). The analysis is performed for a certain number of heat pump units with fixed and variable capacity made by four manufacturers available on European market. Simulations are performed in Trnsys software. The results show that heat pump partial load efficiency should not be neglected in analysis of application while the difference in energy consumption and costs can be up to 17%. The requirement for performing analysis on a wider range of units is indicated, especially when heat pump systems with different sources are considered. HVAC system with AWHP units with capacity control is a cost optimal solution for case study nursery building operating on the Croatian coast. The application of the photovoltaic (PV) array sized to cover nonrenewable part of electricity consumed in HVAC system has a return period of 12 years. It is determined that seasonal efficiency indicators from relevant European database do not support unit operation.
Dynamic Programming Based Rapid Energy Management of Hybrid Electric Vehicles with Constraints on Smooth Driving, Battery State-of-Charge and Battery State-of-Health
Authors: Anselma Pier Giuseppe
Published: February 2022

Dynamic programming (DP) is currently the reference optimal energy management approach for hybrid electric vehicles (HEVs). However, several research concerns arise regarding the effective application of DP for optimal HEV control problems which involve a significant number of control variables, state variables and optimization constraints. This paper deals with an optimal control problem for a full parallel P2 HEV with constraints on battery state-of-charge (SOC), battery lifetime in terms of state-of-health (SOH), and smooth driving in terms of the frequencies of internal combustion engine (ICE) activations and gear shifts over time. The DP formulation for the considered HEV control problem is outlined, yet its practical application is demonstrated as unfeasible due to a lack of computational power and memory in current desktop computers. To overcome this drawback, a computationally efficient version of DP is proposed which is named Slope-weighted Rapid Dynamic Programming (SRDP). Computational advantage is achieved by SRDP in considering only the most efficient HEV powertrain operating points rather than the full set of control variable values at each time instant of the drive cycle. A benchmark study simulating various drive cycles demonstrates that the introduced SRDP can achieve compliance with imposed control constraints on battery SOC, battery SOH and smooth driving. At the same time, SRDP can achieve up to 78% computational time saving compared with a baseline DP approach considering the Worldwide Harmonized Light Vehicle Test Procedure (WLTP). On the other hand, the increase in the fuel consumption estimated by SRDP is limited within 3.3% compared with the baseline DP approach if the US06 Supplemental Federal Test Procedure is considered. SRDP could thus be exploited to efficiently explore the large design space associated to HEV powertrains.
LambertW Function to Extract Physical Parameters of a Schottky Barrier Diode from Its I–V Characteristics
Authors: Aazou Safae , White Matthew Schuette , Kaltenbrunner Martin , Sekkat Zouheir , Egbe Daniel Ayuk Mbi , Assaid El Mahdi
Published: February 2022

In the current work, the exact analytical expression of the current–voltage characteristics, which are given in terms of the LambertW function, is used to extract the physical parameters of organic and inorganic Schottky barrier diodes (SBDs). The extraction is achieved by a variety of methods using the experimental I–V characteristics. The organic SBD is based on a Poly (3-hexylthiophene-2,5-diyle) conjugated polymer (P3HT) with Al contact, measured at 300 K. Regarding the inorganic SBDs, one is based on Iridium–Silicon Carbide (Ir–SiC), measured at 300 K, and the second diode is based on Gold–Gallium Arsenide (Au–GaAs), measured at 200 K. The numerical characteristics based on the physical parameters extracted by the presented methods are in good agreement with the experimental data. The determination coefficient of the modeling methods for the three SBDs is higher than 99.99%.
Multi-Energy Concern as an Example of the Implementation of Agenda 2030: Poland as a Case Study
Authors: Toborek-Mazur Joanna , Wójcik-Jurkiewicz Magdalena
Published: February 2022

The motive for the functioning of enterprises in the market economy is the maximization of benefits by achieving positive financial results with the minimum possible involvement of capital. The positive results achieved are perceived very positively by the stakeholders. To achieve this, it is necessary to carry out reorganization processes (mergers and acquisitions) within capital groups, which are perceived as necessary (positive) measures. These phenomena have been observed in the energy sector for many years, and the years 2010–2021 were adopted as the research period. The aim of this article is to attempt to answer the question of whether the multi-energy concern is the result of activities carried out in light of the 2030 Agenda. The effect of merging the entities is capital concentration. This fact has been verified by reviewing changes in the structures of capital groups in the energy sector against the background of the largest mergers and acquisitions in Poland in terms of value. The theoretical part presents the differences in the terminology of mergers and acquisitions and the motives for their creation and operation, with an emphasis on energy groups. Therefore, the authors undertook research aimed at identifying and assessing the main premises and effects of capital concentration through mergers and acquisitions in the energy sector in Poland.
Variable Structure Disturbance Observer Based Dynamic Surface Control of Electrohydraulic Systems with Parametric Uncertainty
Authors: Li Shuai , Zhu Ke , Chen Liang , Yan Yao , Guo Qing
Published: February 2022

This paper focuses on the position tracking control issue of electrohydraulic systems (EHS). The dynamical model of EHS is introduced in the first place, based on which a type of Variable Structure Disturbance Observer (VSDO) is constructed for EHS to estimate the parametric uncertainty the EHS possesses. Then, a backstepping controller is designed under VSDO to realize the high precision position tracking purpose. To avoid the phenomenon of differential explosion, a dynamic surface control method is adopted in this paper, which improved the position tracking control performance of EHS. The proposed theoretical results are verified by numerical simulation and experiment to illustrate the feasibility.
Adversarial Fusion Network for Forest Fire Smoke Detection
Authors: Li Tingting , Zhang Changchun , Zhu Haowei , Zhang Junguo
Published: February 2022

Recent advances suggest that deep learning has been widely used to detect smoke for early forest fire warnings. Despite its remarkable success, this approach has a number of problems in real life application. Deep neural networks only learn deep and abstract representations, while ignoring shallow and detailed representations. In addition, previous models have been trained on source domains but have generalized weakly on unseen domains. To cope with these problems, in this paper, we propose an adversarial fusion network (AFN), including a feature fusion network and an adversarial feature-adaptation network for forest fire smoke detection. Specifically, the feature fusion network is able to learn more discriminative representations by fusing abstract and detailed features. Meanwhile, the adversarial feature adaptation network is employed to improve the generalization ability and transfer gains of the AFN. Comprehensive experiments on two self-built forest fire smoke datasets, and three publicly available smoke datasets, validate that our method significantly improves the performance and generalization of smoke detection, particularly the accuracy of the detection of small amounts of smoke.
Geographic Cline and Genetic Introgression Effects on Seed Morphology Variation and Germination Fitness in Two Closely Related Pine Species in Southeast Asia
Authors: Zhang Zheng-Ren , Li Wei-Ying , Dong Yi-Yi , Liu Jing-Xin , Lan Qin-Ying , Yang Xue , Xin Pei-Yao , Gao Jie
Published: February 2022

There is still limited information on how genetic introgression impacts morphological variation and population fitness in long-lived conifer species. Two closely related pine species, Pinus kesiya Royle ex Gordon and Pinus yunnanensis Franch. are widely distributed over Southeast Asia and Yunnan province of China, with a large spatial scale of asymmetric genetic introgression and hybridization, and form a hybrid lineage, P. kesiya var. langbianensis, where their ranges overlap in southeast Yunnan. We compared seed trait variation and germination performance between hybrids and parental species and characterized environmental gradients to investigate the genetic and ecological evolutionary consequences of genetic introgression. We found that seed width (SW) differed significantly among the three pines, and all the seed traits were significantly negatively correlated with latitude and associated with the mean temperatures of the driest and wettest quarters. A higher germination fitness of hybrids was detected at a low temperature, indicating that they had better adaptability to temperature stress than their parental species during the germination process. Our results suggest that environmental factors shape seed phenotypic variation in the pine species and that genetic introgression significantly affects seed germination fitness. Therefore, assisting gene flow in natural forest populations might facilitate their adaptation to climate change.
Comparative Assessment of the Antibacterial Efficacies and Mechanisms of Different Tea Extracts
Authors: Liu Shuyuan , Zhang Qiqi , Li Hang , Qiu Zheyu , Yu Youben
Published: February 2022

Tea is a popular beverage known for its unique taste and vast health benefits. The main components in tea change greatly during different processing methods, which makes teas capable of having different biological activities. We compared the antibacterial activity of four varieties of tea, including green, oolong, black, and Fuzhuan tea. All tea extracts showed antibacterial activity and Gram-positive bacteria (Enterococcus faecalis and Staphylococcus aureus) were more susceptible to tea extracts than Gram-negative bacteria (Escherichia coli and Salmonella typhimurium). Green tea extracts inhibited bacterial pathogens much more effectively in all four varieties of tea with the minimum inhibitory concentration (MIC) values at 20 mg/mL, 10 mg/mL, 35 mg/mL, and 16 mg/mL for E. faecalis, S. aureus, E. coli, and S. typhimurium, respectively. Catechins should be considered as the main antibiotic components of the four tea extracts. Total catechins were extracted from green tea and evaluated their antibacterial activity. Additional studies showed that the catechins damaged the cell membrane and increased cell membrane permeability, leading to changes in the relative electrical conductivity and the release of certain components into the cytoplasm. Tea extracts, especially green tea extracts, should be considered as safe antibacterial food additives.
A Reliable Approach for Solving Delay Fractional Differential Equations
Authors: Hashim Ishak , Sharadga Mwaffag , Syam Muhammed I. , Al-Refai Mohammed
Published: February 2022

In this paper, we study a class of second-order delay fractional differential equations with a variable-order Caputo derivative. This type of equation is an extension to ordinary delay equations which are used in the modeling of several biological systems such as population dynamics, epidemiology, and immunology. Usually, fractional differential equations are difficult to solve analytically, and with fractional derivatives of variable-order, they become more challenging. Therefore, the need for reliable numerical techniques is worth investigating. To solve this type of equation, we derive a new approach based on the operational matrix. We use the shifted Chebyshev polynomials of the second kind as the basis for the approximate solutions. A convergence analysis is discussed and the uniform convergence of the approximate solutions is proven. Several examples are discussed to illustrate the efficiency of the presented approach. The computed errors, figures, and tables show that the approximate solutions converge to the exact ones by considering only a few terms in the expansion, and illustrate the novelty of the presented approach.
Maillard-Type Protein–Polysaccharide Conjugates and Electrostatic Protein–Polysaccharide Complexes as Delivery Vehicles for Food Bioactive Ingredients: Formation, Types, and Applications
Authors: Sun Xiaohong , Wang Hao , Li Shengnan , Song Chunli , Zhang Songyuan , Ren Jian , Udenigwe Chibuike C.
Published: February 2022

Due to their combination of featured properties, protein and polysaccharide-based carriers show promising potential in food bioactive ingredient encapsulation, protection, and delivery. The formation of protein–polysaccharide complexes and conjugates involves non-covalent interactions and covalent interaction, respectively. The common types of protein–polysaccharide complex/conjugate-based bioactive ingredient delivery systems include emulsion (conventional emulsion, nanoemulsion, multiple emulsion, multilayered emulsion, and Pickering emulsion), microcapsule, hydrogel, and nanoparticle-based delivery systems. This review highlights the applications of protein–polysaccharide-based delivery vehicles in common bioactive ingredients including polyphenols, food proteins, bioactive peptides, carotenoids, vitamins, and minerals. The loaded food bioactive ingredients exhibited enhanced physicochemical stability, bioaccessibility, and sustained release in simulated gastrointestinal digestion. However, limited research has been conducted in determining the in vivo oral bioavailability of encapsulated bioactive compounds. An in vitro simulated gastrointestinal digestion model incorporating gut microbiota and a mucus layer is suggested for future studies.
Formation of Hydrogels Based on a Copolymer of N-Vinyl-2-pyrrolidone and Glycidyl Methacrylate in the Presence of the Reaction Product of 1,3-Dimethylmidazolium Dimethylphosphate and Elemental Sulfur
Authors: Tarasova Natalia , Krivoborodov Efrem , Zanin Alexey , Pascal Ekaterina , Toropygin Ilya , Artyukhov Alexander , Muradyan Samson , Mezhuev Yaroslav
Published: February 2022

The aim of the study is to search for a reaction that provides the possibility of tandem “one-pot” formation of polymer networks during radical copolymerization of N-vinyl-2-pyrrolidone and glycidyl methacrylate. It was shown that the addition of recently synthesized 1,3-dimethylimidazolium (phosphonooxy-)oligosulfanide makes it possible to obtain a cross-linked copolymer in one stage as a result of radical copolymerization of N-vinyl-2-pyrrolidone and glycidyl methacrylate with a molar ratio of monomers less than 1.4. The structure of the copolymerization products of N-vinyl-2-pyrroldione and glycidyl methacrylate formed in the presence of 1,3-dimethylimidazolium (phosphonooxy-)oligosulfanide was characterized by 1H NMR, FTIR and MALDI spectroscopy. 1H NMR spectroscopy revealed an interaction under moderate heating between glycidyl methacrylate and 1,3-dimethylimidazolium (phosphonooxy-)oligosulfanide, accompanied by the formation of a mixture of unsaturated products of complex structure, presumably acting as crosslinking agents. It is shown that when the molar ratio of N-vinyl-2-pyrroldione/glycidyl methacrylate comonomers is 0.89, a densely crosslinked copolymer is formed, capable of limited swelling in water with a velocity constant of 5.06 × 10−2 min−1 and an equilibrium degree of swelling of about 227%.
Large-Scale Meta-Longitudinal Microbiome Data with a Known Batch Factor
Authors: Oh Vera-Khlara S. , Li Robert W.
Published: February 2022

Data contamination in meta-approaches where multiple biological samples are combined considerably affects the results of subsequent downstream analyses, such as differential abundance tests comparing multiple groups at a fixed time point. Little has been thoroughly investigated regarding the impact of the lurking variable of various batch sources, such as different days or different laboratories, in more complicated time series experimental designs, for instance, repeatedly measured longitudinal data and metadata. We highlight that the influence of batch factors is significant on subsequent downstream analyses, including longitudinal differential abundance tests, by performing a case study of microbiome time course data with two treatment groups and a simulation study of mimic microbiome longitudinal counts.
A Step towards a Sustainable Tourism in Apennine Mountain Areas: A Proposal of Geoitinerary across the Matese Mountains (Central-Southern Italy)
Authors: Filocamo Francesca , Rosskopf Carmen Maria , Amato Vincenzo , Cesarano Massimo
Published: February 2022

The Apennine mountain areas suffer progressive abandonment and marginality, although being characterized by an extraordinary richness in natural and cultural resources, and landscapes of great beauty. Therefore, their natural heritage, and especially their geoheritage, tranformed into geotourism initiatives, can represent an essential resource to support local economy andsustainable development. The present study illustrates the case of Matese Mountains (Southern Apennines), particularly rich in protected areas, including the Matese National Park currently taking off, which is characterized by a rich geoheritage, based on 59 geosites. Among these geosites, examining the specially built geosite GIS database, 16 geosites were selected to construct a geoitinerary crossing the Matese Mountains. The geoitinerary was delineated to optimally represent the major geomorphological and geological (especially geohistorical) features of the Matese area. The selected geosites were associated to a new procedure to assess their Scientific Value (SV) and Potential Tourism Use (PTU), and to confirm their suitability for the purpose. To illustrate the geoitinerary, a geoitinerary map, and illustration material such as descriptive cards were produced. As an overall result, the proposed geoitinerary represents a valuable contribution for the geotourism promotion of the Matese Mountains on which to base future studies and initiatives in this perspective.