bluuebunny/crossref_metadata_2025 huggingface dataset:
Chemoprevention of Experimental Periodontitis in Diabetic Rats with Silk Fibroin Nanoparticles Loaded with Resveratrol
Authors: Giménez-Siurana Ana , Gómez García Francisco , Pagan Bernabeu Ana , Lozano-Pérez Antonio Abel , Aznar-Cervantes Salvador D. , Cenis José Luis , López-Jornet Pía
Published: January 2020

Objective: the objective of the present work is to study the effectiveness of treatment with silk fibroin nanoparticles loaded with resveratrol in experimental periodontitis in a diabetic rat model. Introduction: Periodontitis is an inflammatory pathology highly related to other diseases, such as type II diabetes. Both diseases have a specific inflammatory condition, with Interleukin (IL)-6, IL-1β and Transforming Grow Factor (TGF)-1β being the most relevant proinflammatory factors. Silk fibroin (SF) nanoparticles loaded with resveratrol (Res-SFN) are a new alternative as a treatment. Methods: 40 diabetic Sprague Dawley male rats were used and periodontitis was induced by ligation. The animals were divided into 5 treatment groups, and 1 mL of treatment was administered once a day for 4 weeks. The groups were: I: Carboxymethyl cellulose (CMC) 0.8%, II: CMC 0.8% + SF 1%, III: CMC 0.8% + RES-SFN 3 mg/mL, IV: CMC 0.8% + SF 1% + RES-SFN 3 mg/mL, V: Water. A peripheral blood sample was taken every week to quantify the inflammatory profile by ELISA (IL-6, IL-1β and TGF-1β). After 4 weeks the sacrifice was carried out and biopsies of the gum were taken. Results: Treatment with SF and RES-SFN reduced the amount of chemical inflammation mediators (with the exception of IL-1β in comparisons I-IV and II-IV (p > 0.05)), as well as the anatomopathological variables linked to it, in a significant way (p < 0.05). Conclusion: treatment with RES-SFN has reduced local inflammation in this experimental periodontitis model.
A New Life Prediction Scheme for Mechanical System with Considering the Mission Profile Switching
Authors: Yin Jiancheng , Zheng Huailiang , Yang Yuantao , Xu Minqiang
Published: January 2020

The life prediction is crucial to guarantee the reliability and safety of the mechanical system. The current prediction methods predict the life only based on the historical usage pattern of the mechanical system, and do not consider the mission profile of the future working process. To realize the life prediction with considering the switching of mission profile, which is composed of different operating conditions, this paper proposes a new prediction scheme on the base of the similarity trajectory method (STM). Two main improvements are employed. First, the reference degradation models are constructed according to the predicted trend of each constant operating condition obtained by the relevance vector machine (RVM). Secondly, the life under specific mission profile is calculated through weighted aggregating the life of each constant operating condition. The proposed method is validated by a turbofan engine simulation data. The results show that the proposed method achieves an excellent predicted result, in which the predicted result is close to the actual result. In addition, the proposed method can deal with the problem of mission profile switching.
Which Influencing Factors Could Reduce Ecological Consumption? Evidence from 90 Countries for the Time Period 1996–2015
Authors: Zhang Shuai , Zhu Dajian , Zhang Jiaping , Li Lilian
Published: January 2020

In the “full world” and Anthropocene, global ecological consumption is beyond natural capital’s regenerative and absorptive abilities, and ecological consumption of humanity has to be reduced to have an ecologically sustainable future. To achieve the goal of ecological sustainability, influencing factors that could reduce ecological consumption need to be explored. Based on three panel datasets for the time period 1996–2015, this paper estimates the impacts of urbanization, renewable energy consumption, service industries, and internet usage on ecological consumption for all 90 sample countries, the 42 developed countries, and the 48 developing countries. Education and income are taken as control variables in the panel regressions. As a consumption-side indicator, the ecological footprint is selected to measure ecological consumption. The estimations find that (1) urbanization has negative impacts for all sample countries and the developed countries, and it is insignificant for the developing countries, (2) renewable energy consumption and service industries have negative impacts for all of the three samples, and (3) internet usage has lagged negative impacts for all sample countries, and it is an independent and significant force of reducing ecological consumption in the developing countries rather than the developed countries. It is found that there is a positive linear relationship, an inversed U-shaped relationship, and a U-shaped relationship between ecological consumption and income in all sample countries, the developed countries, and the developing countries, respectively. The estimated results provide guidance for evidence-based policymaking on reducing ecological consumption.
Design and Manufacturing of an Innovative Triple-Layer Thermo-Insulated Fabric
Authors: Furferi Rocco , Mantellassi Franco , Volpe Yary
Published: January 2020

Materials used for creating fabrics featuring insulation and thermoregulation are typically made of multi-layer materials consisting of two outer layers and inner padding, traditionally made from goose or duck feathers or even with synthetic materials. In this context, the development of a fabric in which the insulation is carried out directly thanks to the structure of its weave, i.e., where the thermoregulation function is entrusted to one of the yarns (suitably volumized to reduce its density and trap the air) may be an important improvement compared to the state of the art. Accordingly, the present work describes the development of a new kind of triple-layer thermo-insulated innovative fabric (named T4Innovation), in which the thermal insulation is not obtained by means of a padding but rather through the use of appropriate volumized yarns, able to ensure thermal insulation in a reduced thickness. This fabric is manufactured in a single weaving phase, greatly facilitating the subsequent operations of the garment maker. The designed and manufactured fabric was extensively tested to assess its performance. The test demonstrated the effectiveness of such a new class of textile product in terms of thermal performance, which is comparable to the ones of a padded material. Since T4Innovation demonstrates aesthetic properties very close to that of traditional unpadded fabrics, its future commercialization could open new horizons in terms of design, fashion, and style, which are cornerstones of the fashion textile industry.
Improved Empirical Wavelet Transform for Compound Weak Bearing Fault Diagnosis with Acoustic Signals
Authors: Qin Chaoren , Wang Dongdong , Xu Zhi , Tang Gang
Published: January 2020

Most of the current research on the diagnosis of rolling bearing faults is based on vibration signals. However, the location and number of sensors are often limited in some special cases. Thus, a small number of non-contact microphone sensors are a suboptimal choice, but it will result in some problems, e.g., underdetermined compound fault detection from a low signal-to-noise ratio (SNR) acoustic signal. Empirical wavelet transform (EWT) is a signal processing algorithm that has a dimension-increasing characteristic, and is beneficial for solving the underdetermined problem with few microphone sensors. However, there remain some critical problems to be solved for EWT, especially the determination of signal mode numbers, high-frequency modulation and boundary detection. To solve these problems, this paper proposes an improved empirical wavelet transform strategy for compound weak bearing fault diagnosis with acoustic signals. First, a novel envelope demodulation-based EWT (DEWT) is developed to overcome the high frequency modulation, based on which a source number estimation method with singular value decomposition (SVD) is then presented for the extraction of the correct boundary from a low SNR acoustic signal. Finally, the new fault diagnosis scheme that utilizes DEWT and SVD is compared with traditional methods, and the advantages of the proposed method in weak bearing compound fault diagnosis with a single-channel, low SNR, variable speed acoustic signal, are verified.
Impact Damage Resistance and Post-Impact Tolerance of Optimum Banana-Pseudo-Stem-Fiber-Reinforced Epoxy Sandwich Structures
Authors: Hassan Mohamad Zaki , Sapuan S. M. , A. Rasid Zainudin , Nor Ariff Farhan Mohd , Dolah Rozzeta , Md Daud Mohd Yusof
Published: January 2020

Banana fiber has a high potential for use in fiber composite structures due to its promise as a polymer reinforcement. However, it has poor bonding characteristics with the matrixes due to hydrophobic–hydrophilic incompatibility, inconsistency in blending weight ratio, and fiber length instability. In this study, the optimal conditions for a banana/epoxy composite as determined previously were used to fabricate a sandwich structure where carbon/Kevlar twill plies acted as the skins. The structure was evaluated based on two experimental tests: low-velocity impact and compression after impact (CAI) tests. Here, the synthetic fiber including Kevlar, carbon, and glass sandwich structures were also tested for comparison purposes. In general, the results showed a low peak load and larger damage area in the optimal banana/epoxy structures. The impact damage area, as characterized by the dye penetration, increased with increasing impact energy. The optimal banana composite and synthetic fiber systems were proven to offer a similar residual strength and normalized strength when higher impact energies were applied. Delamination and fracture behavior were dominant in the optimal banana structures subjected to CAI testing. Finally, optimization of the compounding parameters of the optimal banana fibers improved the impact and CAI properties of the structure, making them comparable to those of synthetic sandwich composites.
Secondary Atomization of a Biodiesel Micro-Emulsion Fuel Droplet Colliding with a Heated Wall
Authors: Ashikhmin Alexander E. , Khomutov Nikita A. , Piskunov Maxim V. , Yanovsky Vyacheslav A.
Published: January 2020

Using high-speed video recording, we establish the following regimes of hydrodynamic interaction of a biodiesel micro-emulsion fuel droplet with a heated wall: deposition (including drop spreading and receding), drop hydrodynamic breakup, and rebound. Collision regime maps are plotted using a set of dimensionless criteria: Weber number We = 470–1260, Ohnesorge number Oh = 0.146–0.192, and Reynolds number Re = 25–198. The scenarios of droplet hydrodynamic disintegration are studied for transient and film boiling. We also estimate the disintegration characteristics of a biodiesel micro-emulsion droplet (mean diameter of child droplets, their number, and evaporation surface area increase due to breakup). The study establishes the effect of water proportion on the micro-emulsion composition (8–16 vol.%), heating temperature (300–500 °C), droplet size (1.8–2.8 mm), droplet velocity (3–4 m/s), rheological properties of the examined compositions, and emulsifier concentration (10.45 vol.% and 20 vol.%) on the recorded characteristics. The results show that the initial liquid surface area can be increased 2–19 times. The paper analyzes ways to control the process. The hydrodynamic disintegration characteristics of a biodiesel micro-emulsion fuel droplet are compared using 2D and 3D recording.
In-Line Target Production for Laser IFE
Authors: Aleksandrova Irina , Koshelev Eugeniy , Koresheva Elena
Published: January 2020

The paper presents the results of mathematical and experimental modeling of in-line production of inertial fusion energy (IFE) targets of a reactor-scaled design. The technical approach is the free-standing target (FST) layering method in line-moving spherical shells. This includes each step of the fabrication and injection processes in the FST transmission line (FST-TL) considered as a potential solution of the problem of mass target manufacturing. Finely, we discuss the development strategy of the FST-TL creation seeking to develop commercial power production based on laser IFE.
Control Points Selection Based on Maximum External Reliability for Designing Geodetic Networks
Authors: Matsuoka Marcelo Tomio , Rofatto Vinicius Francisco , Klein Ivandro , Roberto Veronez Maurício , da Silveira Luiz Gonzaga , Neto João Batista Silva , Alves Ana Cristina Ramos
Published: January 2020

A set of stable and identifiable points—known as control points—are interconnected by direction, distance or height differences measurements form a geodetic network. Geodetic networks are used in various branches of modern science, such as monitoring the man-made structures, analysing the crustal deformation of the Earth, establishing and maintaining a geospatial reference frame, mapping, civil engineering projects and others. One of the most crucial components for ensuring the network quality is Geodetic Network Design. The design of a geodetic network depends on its purpose. In this paper, an automatic procedure for selection of control points is proposed. The goal is to find the optimum control points location so that the maximum influence of an anomaly measurement (outlier) on the coordinates of the network is minimum. Here, the concept of Minimal Detectable Bias defines the size of the outlier and its propagation on the network coordinates is used to describe the external reliability. The proposed procedure was applied to design a levelling network. Two scenarios were investigated: design of a network with one control point (minimally constrained levelling network) and another with two control points (over-constrained levelling network). The centre of the network was the optimum position to set the control point. Results for that network reveal that the centre of the network was the optimum position to set the control point for the minimal constraint case, whereas the over-constraint case were those with less line connections. We highlight that the procedure is a generally applicable method.
Shuffled Frog Leaping Algorithm and Wind-Driven Optimization Technique Modified with Multilayer Perceptron
Authors: Moayedi Hossein , Bui Dieu Tien , Thi Ngo Phuong Thao
Published: January 2020

The prediction aptitude of an artificial neural network (ANN) is improved by incorporating two novel metaheuristic techniques, namely, the shuffled frog leaping algorithm (SFLA) and wind-driven optimization (WDO), for the purpose of soil shear strength (simply called shear strength) simulation. Soil information of the Trung Luong national expressway project (Vietnam) including depth of the sample (m), percentage of sand, percentage of silt, percentage of clay, percentage of moisture content, wet density (kg/m3), liquid limit (%), plastic limit (%), plastic index (%), liquidity index, and the shear strength (kPa) was collocated through a field survey. After constructing the hybrid ensembles of SFLA–ANN and WDO–ANN, both models were optimized in terms of complexity using a population-based trial-and error-scheme. The learning quality of the ANN was compared with both improved versions to examine the effect of the used metaheuristic techniques. In this phase, the training error dropped by 14.25% and 28.25% by applying the SFLA and WDO, respectively. This reflects a significant improvement in pattern recognition ability of the ANN. The results of the testing data revealed 25.57% and 39.25% decreases in generalization (i.e., testing) error. Moreover, the correlation between the measured and predicted shear strengths (i.e., the coefficient of determination) rose from 0.82 to 0.89 and 0.92, which indicates the efficiency of both SFLA and WDO metaheuristic techniques in optimizing the ANN.
Immediate Effect of Whole-Body Vibration on Skin Temperature and Lower-Limb Blood Flow in Older Adults with Type 2 Diabetes: Pilot Study
Authors: Alves Kennedy Freitas Pereira , Ferreira Ana Paula de Lima , Parente Luana Caroline de Oliveira , Rodrigues François Talles Medeiros , Marques Thais Vitorino , Antonino Gabriel Barreto , Melo Luiz Carlos de , Villela Débora Wanderley , Guerino Marcelo Renato , Leite Wagner Souza , Campos Shirley Lima , Lucena Larissa Coutinho de , Taiar Redha , Araújo Maria das Graças Rodrigues de
Published: January 2020

The purpose of this study was to evaluate the response of a single whole-body vibration (WBV) training session to peripheral skin temperature and peripheral blood flow of older adults with type 2 diabetes. A double-blind, controlled clinical trial was conducted following the Consolidated Standards of Reporting Trials (CONSORT) guidelines. A single session of WBV (24 Hz; amplitude 4 mm; vibration time 45 s, with a series of eight repetitions with recovery between repetitions of 30 s; total time of 10 min) or sham vibration on the Kikos P204 Vibrating Platform was employed. To assess skin temperature, the FLIR E40bxs thermographic camera and the ultrasonic vascular Doppler for flow velocity were used. Evaluation occurred before and after a WBV or sham intervention. The sample consisted of three men and 17 women. In the WBV group, there was a decrease in the temperature from 29.7 °C (±1.83) to 26.6 °C (±2.27), with p = 0.01. Temperature following sham decreased from 28.6 °C (±1.84) to 26.3 °C (±2.49), with p = 0.01. Regarding blood flow, there was a decrease in the analyzed arteries, especially the left posterior tibial artery, where there was a statistically significant flow reduction from 27.1 m/s (±25.36) to 20.5 m/s (±19.66), post WBV (p = 0.01). In the sham group, an increased flow velocity was observed for all the arteries analyzed, except for the left dorsal artery. Immediately following a full-body vibration session, peripheral skin temperature and lower-limb blood flow tend to decrease in diabetic patients. However, from the design of study developed, we cannot infer the maintenance of this effect in the medium and long term.
From Modeling to Failure Prognosis of Permanent Magnet Synchronous Machine
Authors: Ginzarly Riham , Hoblos Ghaleb , Moubayed Nazih
Published: January 2020

Due to the accelerating pace of environmental concerns and fear of the depletion of conventional sources of energy, researchers are working on finding renewable energy sources of power for different axes of life. The transportation sector has intervened in this field and introduced hybrid electric vehicles. Many complaints have been mentioned concerning fault detection and identification in the vehicle to ensure its safety, reliability and availability. Diagnosis has not been able to overcome all these concerns, and research has shifted toward prognosis, where the manufacturing sector is urged to integrate fault prognosis in the vehicle’s electrical powertrain. In this article, prognosis of the vehicle’s electrical machine is treated using a hidden Markov model after modeling the electrical machine using the finite element method. Permanent magnet machines are preferable in this application. The modeling of the machine is a combination of the electromagnetic, thermal and vibration finite element models. The considered faults are demagnetization, turn-to-turn short circuit and eccentricity. A strategy for the calculation of the remaining useful life (RUL) is suggested when a turn-to-turn short circuit fault occurs.
High-Speed Light Signal Transmitters for Optical Communication Based on Ultraviolet Radiation
Authors: Li Xin , Wu Yue , Yuan Jialei , Ni Shuyu , Qin Chuan , Jiang Yan , Li Jie , Wang Yongjin
Published: January 2020

A light signal transmitter based on ultraviolet radiation is realized on GaN-on-silicon platform. The light signal transmitter with ultra-small active area is fabricated by a double-etching process. The absolute value of negative junction capacitance of transmitter is as low as the pF (picofarads) scale in positive bias voltage. Small capacitance is beneficial to improve the communication performance of a transmitter. The dominant EL (electroluminescence) peak of transmitter is located at about 380 nm in the ultraviolet range. With the increase of the current, the dominant peak of transmitter remains stable and the light output power is lineally modulated. A free-space data transmission test in the ultraviolet range with 250 Mbps was conducted to indicate a promising high-speed optical communication capability of a light signal transmitter in the ultraviolet range.
Failure Trends of High-Voltage Porcelain Insulators Depending on the Constituents of the Porcelain
Authors: Sanyal Simpy , Kim Taeyong , Yi Junsin , Koo Ja-Bin , Son Ju-Am , Choi In-Hyuk
Published: January 2020

The aging of porcelain insulators is responsible for the failure of power utilities. Porcelain insulators from different places in South Korea, possessing various aging times and years of installation, have been investigated to carry out lifetime statistics. These samples have a mass of 36,000 lbs and are operated at 154 kV. X-ray fluorescence (XRF) and scanning electron microscopy (SEM) were performed on the porcelain bodies of the samples collected. XRF and SEM revealed trends in the weight percentage of SiO2, Al2O3, and Fe2O3 in the porcelain bodies of the collected samples. The SiO2 and Fe2O3 weight percentage reduced to 8.93% and 73.17%, respectively, in sample C compared to A. However, the Al2O3 weight percentage increased to 16.23% in sample C compared to sample A. This change in weight percentage of SiO2, Fe2O3, and Al2O3 contributed toward enhancing the mechanical and electrical properties of the insulators. Mechanical load tests with electrical voltage (M&E), thermal and mechanical load tests (T&M), and hardness tests (HRB) were performed to evaluate these characteristics. Experiments revealed an increase of 90.9% in the inequality factor (K) in sample C compared to A. The impact of constituents of porcelain on the lifetime expectancy of a porcelain insulator was reported by implementing statistical strategies, such as the Weibull distribution.
A Division Algorithm in a Redundant Residue Number System Using Fractions
Authors: Chervyakov Nikolay , Lyakhov Pavel , Babenko Mikhail , Lavrinenko Irina , Deryabin Maxim , Lavrinenko Anton , Nazarov Anton , Valueva Maria , Voznesensky Alexander , Kaplun Dmitry
Published: January 2020

The residue number system (RNS) is widely used for data processing. However, division in the RNS is a rather complicated arithmetic operation, since it requires expensive and complex operators at each iteration, which requires a lot of hardware and time. In this paper, we propose a new modular division algorithm based on the Chinese remainder theorem (CRT) with fractional numbers, which allows using only one shift operation by one digit and subtraction in each iteration of the RNS division. The proposed approach makes it possible to replace such expensive operations as reverse conversion based on CRT, mixed radix conversion, and base extension by subtraction. Besides, we optimized the operation of determining the most significant bit of divider with a single shift operation of the modular divider. The proposed enhancements make the algorithm simpler and faster in comparison with currently known algorithms. The experimental simulation using Kintex-7 showed that the proposed method is up to 7.6 times faster than the CRT-based approach and is up to 10.1 times faster than the mixed radix conversion approach.
A Method for Detecting Coffee Leaf Rust through Wireless Sensor Networks, Remote Sensing, and Deep Learning: Case Study of the Caturra Variety in Colombia
Authors: Velásquez David , Sánchez  Alejandro , Sarmiento  Sebastian , Toro  Mauricio , Maiza Mikel , Sierra  Basilio
Published: January 2020

Agricultural activity has always been threatened by the presence of pests and diseases that prevent the proper development of crops and negatively affect the economy of farmers. One of these pests is Coffee Leaf Rust (CLR), which is a fungal epidemic disease that affects coffee trees and causes massive defoliation. As an example, this disease has been affecting coffee trees in Colombia (the third largest producer of coffee worldwide) since the 1980s, leading to devastating losses between 70% and 80% of the harvest. Failure to detect pathogens at an early stage can result in infestations that cause massive destruction of plantations and significantly damage the commercial value of the products. The most common way to detect this disease is by walking through the crop and performing a human visual inspection. As a result of this problem, different research studies have proven that technological methods can help to identify these pathogens. Our contribution is an experiment that includes a CLR development stage diagnostic model in the Coffea arabica, Caturra variety, scale crop through the technological integration of remote sensing (through drone capable multispectral cameras), wireless sensor networks (multisensor approach), and Deep Learning (DL) techniques. Our diagnostic model achieved an F1-score of 0.775. The analysis of the results revealed a p-value of 0.231, which indicated that the difference between the disease diagnosis made employing a visual inspection and through the proposed technological integration was not statistically significant. The above shows that both methods were significantly similar to diagnose the disease.
Structural Optimization of Slotting Nozzle Used to Improve Coal-Seam Permeability
Authors: Ge Zhaolong , Zhong Jianyu , Zhang Jianguo , Wang Yingwei , Lvu Youchang , Zhang Sai
Published: January 2020

Slotting directional hydraulic fracturing is a new method for improving permeability of a coal seam in underground coal mines that can solve problems related to non-uniform permeability enhancement in the seam. A slotting nozzle is the key to this technology: its performance determines the length and stability of the slotted hole. In this study, computational fluid dynamics was used to study the effects of stable segment length L, convergent angle θ, and straight segment length l on the performance of slotting nozzles. The results showed that the order of parameters affecting nozzle performance is: θ > L > l. When the total length of the slotting nozzle was fixed, the dynamic pressure gradually decreased with an increase of L and the rate of decrease slowed down. With an increase of θ, dynamic pressure increased quadratically and the rate of change gradually decreased. With an increase of l, the dynamic pressure decreased quadratically and the rate of change gradually increased. A slotting nozzle (L = 0 mm, θ = 30°, l = 9 mm) was manufactured and measurements of flow coefficient, water jet morphology, and a slotting experiment were carried out. The experimental results showed that the flow coefficient, water jet convergence, and slotting depth of the optimized slotting nozzle were obviously higher than those of the original design, which proved the validity of using this numerical method to optimize the slotting nozzle structure.
Global MPPT Based on Machine-Learning for PV Arrays Operating under Partial Shading Conditions
Authors: Kalogerakis Christos , Koutroulis Eftichis , Lagoudakis Michail G.
Published: January 2020

A global maximum power point tracking (GMPPT) process must be applied for detecting the position of the GMPP operating point in the minimum possible search time in order to maximize the energy production of a photovoltaic (PV) system when its PV array operates under partial shading conditions. This paper presents a novel GMPPT method which is based on the application of a machine-learning algorithm. Compared to the existing GMPPT techniques, the proposed method has the advantage that it does not require knowledge of the operational characteristics of the PV modules comprising the PV system, or the PV array structure. Additionally, due to its inherent learning capability, it is capable of detecting the GMPP in significantly fewer search steps and, therefore, it is suitable for employment in PV applications, where the shading pattern may change quickly (e.g., wearable PV systems, building-integrated PV systems etc.). The numerical results presented in the paper demonstrate that the time required for detecting the global MPP, when unknown partial shading patterns are applied, is reduced by 80.5%–98.3% by executing the proposed Q-learning-based GMPPT algorithm, compared to the convergence time required by a GMPPT process based on the particle swarm optimization (PSO) algorithm.
Coupling Control Strategy and Experiments for Motion Mode Switching of a Novel Electric Chassis
Authors: Qu Jiwei , Guo Kangquan , Zhang Zhenya , Song Shujie , Li Yining
Published: January 2020

A flexible chassis (FC) is a type of electric vehicle driven by in-wheel motors that can be used in narrow conditions in agricultural facilities. The FC is composed primarily of four off-center steering mechanisms (OSMs) that can be controlled independently. Various FC operation modes can be achieved including cross motion (CM), in-place rotation (IR), diagonal motion (DM), and steering motion (SM). However, it is difficult to achieve satisfactory motion mode switching (MMS) results under traditional distribution control methodologies due to a lack of linkage relationships between the four OSMs. The goal of this study was to provide a coupling control method that can cope with this problem. First, dynamic MMS models were derived. Then, an MMS coupling error (CE) model was derived based on coupling control and Lyapunov stability theory. Second, a fuzzy proportional integral derivative (PID) controller with self-tuning parameters was designed to reduce the CE during MMS. A fuzzy PI controller was also employed to improve response times and decrease OSM tracking motion steady-state error. Finally, MATLAB/Simulink simulations were performed and experimentally validated on hard pavement. The results showed that the proposed methodology could effectively reduce CE and guarantee MMS control stability while substantially shortening response times. The proposed methodology is effective and feasible for FC MMS.
Performance Degradation Analysis and Optimization of the Stepless Capacity Regulation System for Reciprocating Compressors
Authors: Liu Wenhua , Jiang Zhinong , Wang Yao , Zhou Chao , Sun Xu , Zhang Jinjie
Published: January 2020

The regulating performance degradation of the stepless capacity regulation system for reciprocating compressors occurs frequently in long-term operations. It affects the safe and stable operation of the compressor seriously. The degradation mechanisms in a stepless capacity regulation system are mainly caused by valve leakage, degeneration of the reset spring of the unloader, and (or) deviation of the solenoid valve’s characteristic parameters. In this study, to research the system performance degradation mechanisms and the influence of control parameters on system behavior, a multi-subsystem mathematics model which integrates compressor, gas pipeline, buffer tank, and actuator was built. In order to calculate the rate of degradation, a load prediction model based on a modified back-propagation neural network was established. The rate of degradation can be calculated using the predicted results. In order to optimize system regulation performance, a degradation-based optimization framework was developed which determines optimum control parameter compensation to achieve a minimum degradation rate. In addition, in order to avoid over-compensation, an adaptive control parameter compensation optimization method was adopted. According to the deviation between the given load and the prediction load, the control parameter compensations are obtained adaptively. Finally, two optimization experiments are carried out to show the effectiveness of the developed framework. The optimization results illustrate the degradation rate of the system gradually returning to normal during 60s without any over-compensation.
Evaluation of Condition of Concrete Structures Using Ultrasonic Pulse Velocity Method
Authors: Hong Seonguk , Yoon Sangki , Kim Jonghyun , Lee Changjong , Kim Seunghun , Lee Yongtaeg
Published: January 2020

The purpose of this study is to estimate the compressive strength according to the age of the concrete structure using ultrasonic pulse velocity method. If the correlation between the ultrasonic pulse velocity and the compressive strength according to the age is derived, the compressive strength of the early age of the concrete structure can be estimated at the new construction site and the compressive strength of the existing structure can be estimated at the remodeling construction site. Concrete structural specimens were constructed with 123 specimens by setting 9 parameters based on the design compressive strength of 24, 30, 40 MPa at 16, 20, 24, 48, 72, 120, 168, 360, 672 h. For the calculation of the average ultrasonic velocity according to the age of concrete, it is carried out according to KS F 2731, ASTM C597 and ACI 228-2R, and the concrete compressive strength is carried out according to KS F 2405. From correlation between ultrasonic pulse velocity and compressive strength, this experiment suggests compressive strength estimation equation. The proposed estimation equation confirmed that it is possible to estimate the compressive strength of concrete according to its age using nondestructive test methods.
A Quantum-Like Model of Information Processing in the Brain
Authors: Khrennikov Andrei , Asano Masanari
Published: January 2020

We present the quantum-like model of information processing by the brain’s neural networks. The model does not refer to genuine quantum processes in the brain. In this model, uncertainty generated by the action potential of a neuron is represented as quantum-like superposition of the basic mental states corresponding to a neural code. Neuron’s state space is described as complex Hilbert space (quantum information representation). The brain’s psychological functions perform self-measurements by extracting concrete answers to questions (solutions of problems) from quantum information states. This extraction is modeled in the framework of open quantum systems theory. In this way, it is possible to proceed without appealing to the state’s collapse. Dynamics of the state of psychological function F is described by the quantum master equation. Its stationary states represent classical statistical mixtures of possible outputs of F (decisions). This model can be used for justification of quantum-like modeling cognition and decision-making. The latter is supported by plenty of statistical data collected in cognitive psychology.
Numerical Study for the Effects of Temperature Dependent Viscosity Flow of Non-Newtonian Fluid with Double Stratification
Authors: Wahab Hafiz Abdul , Zeb Hussan , Bhatti Saira , Gulistan Muhammad , Kadry Seifedine , Nam Yunyoung
Published: January 2020

The main aim of the current study is to determine the effects of the temperature dependent viscosity and thermal conductivity on magnetohydrodynamics (MHD) flow of a non-Newtonian fluid over a nonlinear stretching sheet. The viscosity of the fluid depends on stratifications. Moreover, Powell–Eyring fluid is electrically conducted subject to a non-uniform applied magnetic field. Assume a small magnetic reynolds number and boundary layer approximation are applied in the mathematical formulation. Zero nano-particles mass flux condition to the sheet is considered. The governing model is transformed into the system of nonlinear Ordinary Differential Equation (ODE) system by using suitable transformations so-called similarity transformation. In order to calculate the solution of the problem, we use the higher order convergence method, so-called shooting method followed by Runge-Kutta Fehlberg (RK45) method. The impacts of different physical parameters on velocity, temperature and concentration profiles are analyzed and discussed. The parameters of engineering interest, i.e., skin fraction, Nusselt and Sherwood numbers are studied numerically as well. We concluded that the velocity profile decreases by increasing the values of S t , H and M. Also, we have analyzed the variation of temperature and concentration profiles for different physical parameters.
Use of Smart Technology to Improve Management of Utility Tunnels
Authors: Shahrour Isam , Bian Hanbing , Xie Xiongyao , Zhang Zixin
Published: January 2020

This paper presents a smart solution for the utility tunnel, which allows hosting a wide range of water and energy utilities in an accessible underground space. It is well known that utility tunnels offer major advantages such as the possibility to inspect, maintain, and easily extend urban utilities without excavation, thereby eliminating disturbances related to urban excavation such as traffic jams, noise, pollution, and pavement degradation. However, despite these advantages, the effective development of this facility remains below expectations, because of serious challenges related to the security and governance of this “shared space”. The solution presented in this paper is based on discussions with experts and companies involved in the design, construction, and management of utility tunnels, as well as on the authors’ experiences in the design and implementation of smart solutions for urban utilities. The paper firstly presents the major challenges of utility tunnels and then discusses how theb smart technology could help in coping with these challenges. The paper presents the architecture of this solution, as well as the main layers of monitoring, information system data analysis, and system control. It also presents the methodology to be followed for the implementation of this smart solution. Finally, the paper discusses two major issues for utility tunnels: fire risk and risk assessment. The paper shows that the use of smart technology allows developing a comprehensive digital solution, which uses advanced monitoring system to collect real-time data about the tunnel environment and functioning. These data can be easily shared by authorized staffs. Analysis of these data allows improving the utility tunnel security and performances.
Variable Curvature Displays: Optical Designs and Applications for VR/AR/MR Headsets
Authors: Muslimov Eduard , Behaghel Thibault , Hugot Emmanuel , Joaquina Kelly , Guskov Ilya
Published: January 2020

In the present paper, we discuss the design of a projection system with curved display and its enhancement by variably adjusting the curvature. We demonstrate that the focal surface curvature varies significantly with a change of the object position and that it can easily be computed with the Seidel aberration theory. Using this analytically derived curvature value as the starting point, we optimise a refocusable projection system with 90 ° field of view and F / # = 6.2 . It is demonstrated that such a system can provide stable image quality and illumination when refocusing from infinity to 1.5 m. The gain in spatial resolution is as high as 1.54 times with respect to a flat focal surface. Furthermore, we prove that a silicon die can be curved to the required shape with a safety factor of 4.3 in terms of the mechanical stress. Finally, it is shown that the developed system can be used in a virtual reality headset providing high resolution, low distortion and a flexible focusing mode.
Fast and Robust Object Tracking Using Tracking Failure Detection in Kernelized Correlation Filter
Authors: Shin Jungsup , Kim Heegwang , Kim Dohun , Paik Joonki
Published: January 2020

Object tracking has long been an active research topic in image processing and computer vision fields with various application areas. For practical applications, the object tracking technique should be not only accurate but also fast in a real-time streaming condition. Recently, deep feature-based trackers have been proposed to achieve a higher accuracy, but those are not suitable for real-time tracking because of an extremely slow processing speed. The slow speed is a major factor to degrade tracking accuracy under a real-time streaming condition since the processing delay forces skipping frames. To increase the tracking accuracy with preserving the processing speed, this paper presents an improved kernelized correlation filter (KCF)-based tracking method that integrates three functional modules: (i) tracking failure detection, (ii) re-tracking using multiple search windows, and (iii) motion vector analysis to decide a preferred search window. Under a real-time streaming condition, the proposed method yields better results than the original KCF in the sense of tracking accuracy, and when a target has a very large movement, the proposed method outperforms a deep learning-based tracker, such as multi-domain convolutional neural network (MDNet).
Acknowledgement to Reviewers of Atmosphere in 2019
Authors:   Atmosphere Editorial Office
Published: January 2020

The editorial team greatly appreciates the reviewers who have dedicated their considerable time and expertise to the journal’s rigorous editorial process over the past 12 months, regardless of whether the papers are finally published or not [...]
Acknowledgement to Reviewers of Biomedicines in 2019
Authors:   Biomedicines Editorial Office
Published: January 2020

The editorial team greatly appreciates the reviewers who have dedicated their considerable time and expertise to the journal’s rigorous editorial process over the past 12 months, regardless of whether the papers are finally published or not [...]
Reliability and Validity of a Method for Assessment of Executive Functions in Drivers
Authors: Racheva Rositsa , Totkova Zornitsa
Published: January 2020

The quality of drivers’ performance is one of the crucial components related to road safety. One of the key cognitive characteristics related to the ability to drive safely are executive functions. The main goal of the presented research is to propose a new method (Trace-route task) for assessment of executive functions in drivers. The present article discusses the results of two consecutive studies. Study one aims to determine the validity and reliability of the method used and includes 134 participants, equally divided in two groups—people with disturbances in executive functions and people from the general population. Study two aims to assess the ability of the method to distinguish drivers with risky behavior. It includes 1440 participants divided in two groups—people with and without actual risky driving behavior. The results from the studies show that people with different neurological or psychiatric diseases and drivers with different road violations demonstrate worse planning ability, working memory, decision making, and cognitive flexibility. This data show that the trace-route task method is a valid and reliable instrument for assessing executive functions and has the ability to distinguish people with risky driving behavior from those who drive safely. This study reveals that the proposed method can be used for implementation in the area of traffic psychology.
Improvement of Ethylene Removal Performance by Adsorption/Oxidation in a Pin-Type Corona Discharge Coupled with Pd/ZSM-5 Catalyst
Authors: Saud Shirjana , Nguyen Duc Ba , Kim Seung-Geon , Lee Ho Won , Kim Seong Bong , Mok Young Sun
Published: January 2020

The adsorption and plasma-catalytic oxidation of dilute ethylene were performed in a pin-type corona discharge-coupled Pd/ZSM-5 catalyst. The catalyst has an adsorption capacity of 320.6 μ mol   g cat − 1 . The catalyst was found to have two different active sites activated at around 340 and 470 °C for ethylene oxidation. The removal of ethylene in the plasma catalyst was carried out by cyclic operation consisting of repetitive steps: (1) adsorption (60 min) followed by (2) plasma-catalytic oxidation (30 min). For the purpose of comparison, the removal of ethylene in the continuous plasma-catalytic oxidation mode was also examined. The ethylene adsorption performance of the catalyst was improved by the cyclic plasma-catalytic oxidation. With at least 80% of C2H4 in the feed being adsorbed, the cyclic plasma-catalytic oxidation was carried out for the total adsorption time of 8 h, whereas it occurred within 2 h of early adsorption in the case of catalyst alone. There was a slight decrease in catalyst adsorption capability with an increased number of adsorption cycles due to the incomplete release of CO2 during the plasma-catalytic oxidation step. However, the decreased rate of adsorption capacity was negligible, which is less than one percent per cycle. Since the activation temperature of all active sites of Pd/ZSM-5 for ethylene oxidation is 470 °C, the specific input energy requirement by heating the feed gas in order to activate the catalyst is estimated to be 544 J/L. This value is higher than that of the continuous plasma-catalytic oxidation (450 J/L) for at least 86% ethylene conversion. Interestingly, the cyclic adsorption and plasma-catalytic oxidation of ethylene is not only a low-temperature oxidation process but also reduces energy consumption. Specifically, the input energy requirement was 225 J/L, which is half that of the continuous plasma-catalytic oxidation; however, the adsorption efficiency and conversion rate were maintained. To summarize, cyclic plasma treatment is an effective ethylene removal technique in terms of low-temperature oxidation and energy consumption.
The Use of Tunable Optical Absorption Plasmonic Au and Ag Decorated TiO2 Structures as Efficient Visible Light Photocatalysts
Authors: Yang Xiaohong , Wang Yan , Zhang Lingtong , Fu Haitao , He Peng , Han Dezhi , Lawson Tom , An Xizhong
Published: January 2020

Exploring solar-excited heterogeneous photocatalysts by taking advantage of surface plasmon resonance (SPR) has drawn growing research attention. As it could help to pave the way for global sustainable development. The decoration of TiO2 particles with noble metals possessing SPR effects is regarded as one of the most effective solutions. The perfect match of the SPR absorption band with the spectrum of incident light is an essential factor for plasmonic enhancement. However, modifying with sole noble metal is often limited as it tunes wavelength of only several nanometers. To overcome this drawback, an alternative approach can be offered by decoration with more than one noble metal. For instance, Au-Ag co-decoration displays greatly adjustable, composition-dependent SPR agent over a broad range of the visible light spectrum (ca. from 415 to 525 nm). Hence Au-Ag complex is a remarkable candidate for tuning the photo adsorption of TiO2 from UV to visible light. This study presents a novel and tailored method for the fabrication of Au-Ag co-modified TiO2 particles, and how Au-Ag dependent SPR was applied as the visible light-responsive TiO2 based photocatalysts in a simple but reliable way. The fabricated Au-Ag co-decorated TiO2 (AuxAg(1−x)/TiO2) was characterized and proved to own excellent stability and large specific surface area. The optimization of these particles against the wavelength of maximal solar light intensity was confirmed by photo degradation of methylene blue under visible light radiation. This work may provide further insight into the design of TiO2-based composites with improved photocatalytic properties for environmental remediation and renewable energy utilization.