bluuebunny/crossref_metadata_2025 huggingface dataset:
Visualization of the Redox Status of Cytosolic Glutathione Using the Organelle- and Cytoskeleton-Targeted Redox Sensors
Authors: Hatori Yuta , Kubo Takanori , Sato Yuichiro , Inouye Sachiye , Akagi Reiko , Seyama Toshio
Published: February 2020

Glutathione is a small thiol-containing peptide that plays a central role in maintaining cellular redox homeostasis. Glutathione serves as a physiologic redox buffer by providing thiol electrons for catabolizing harmful oxidants and reversing oxidative effects on biomolecules. Recent evidence suggests that the balance of reduced and oxidized glutathione (GSH/GSSG) defines the redox states of Cys residues in proteins and fine-tunes their stabilities and functions. To elucidate the redox balance of cellular glutathione at subcellular resolution, a number of redox-sensitive green fluorescent protein (roGFP) variants have been developed. In this study, we constructed and functionally validated organelle- and cytoskeleton-targeted roGFP and elucidated the redox status of the cytosolic glutathione at a subcellular resolution. These new redox sensors firmly established a highly reduced redox equilibrium of cytosolic glutathione, wherein significant deviation was observed among cells. By targeting the sensor to the cytosolic and lumen sides of the Golgi membrane, we identified a prominent redox gradient across the biological membrane at the Golgi body. The results demonstrated that organelle- and cytoskeleton-targeted sensors enable the assessment of glutathione oxidation near the cytosolic surfaces of different organelle membranes.
Vascularized Lower Respiratory-Physiology-On-A-Chip
Authors: Nam Hyoryung , Choi Yoo-mi , Jang Jinah
Published: February 2020

Recently, respiratory systems are increasingly threatened by high levels of environmental pollution. Organ-on-a-chip technology has the advantage of enabling more accurate preclinical experiments by reproducing in vivo organ physiology. To investigate disease mechanisms and treatment options, respiratory-physiology-on-a-chip systems have been studied for the last decade. Here, we delineate the strategic approaches to develop respiratory-physiology-on-a-chip that can recapitulate respiratory system in vitro. The state-of-the-art biofabrication methods and biomaterials are considered as key contributions to constructing the chips. We also explore the vascularization strategies to investigate complicated pathophysiological phenomena including inflammation and immune responses, which are the critical aggravating factors causing the complications in the respiratory diseases. In addition, challenges and future research directions are delineated to improve the mimicry of respiratory systems in terms of both structural and biological behaviors.
Behaviour Analysis of Reinforced Soil Retaining Wall According to Laboratory Scale Test
Authors: Kim Young Je , Jung Hyuk Sang , Lee Yong Joo , Oh Dong Wook , Son Min , Yoon Hwan Hee
Published: February 2020

Reinforced soil retaining wall are ground structures that can be readily seen all around us. The development of reinforcements to these walls and their demand have increased rapidly. These walls are advantageous because they can be used not only in simple construction compared with reinforced concrete retaining walls but also when the height of the wall needs to be higher. However, unlike reinforced concrete retaining walls, in which the walls are integrated and resist the earth pressure on the back, the block-type reinforced earth retaining wall method secures its structural stability by frictional force between the buried land and reinforcements. A phenomenon in which a block is cracked or dropped owing to deformation has been frequently reported. In particular, this phenomenon is concentrated at the curved parts of a reinforced soil retaining wall and is mainly known as a stress concentration. However, to date, the design of reinforced soil retaining walls has been limited by the two-dimensional plane strain condition and has not considered the characteristics of the curved part. There is a lack of research on curved part. Therefore, this research determines the behavioural characteristics of curved-part reinforced soil retaining walls with regard to the shape (convex or concave) and angle (60°, 90°, 120°, and 150°). The displacement generated in the straight part and the curved part was analysed through an Laboratory Scale Test. The results showed that the horizontal displacement of the curved part increases as a convex angle becomes smaller, and the horizontal displacement of the curved part decreases as a concave angle becomes smaller. At the center (D and H have the same length, but H represents the height and D represents the separation distance from the center of the curved part) of the convex curve, the horizontal displacement of the 0.5 D section decreased to 13.8%; it decreased to 41.0% in the 1.0 D section. For concave angles, it was revealed that the horizontal displacement from the center 0.0 D to the 0.5 D section of the curved part increased by 25%, and from the 1.0 D section, by 75%. It was confirmed that the displacement difference was largely based on the value of 0.5 D. It was judged that this can be used as basic data for the design and construction guidelines for reinforced soil retaining wall of reinforced soil retaining walls.
Temperature Dependence of the Fracture Toughness JC of Random Fibrous Material
Authors: Li Datao , Li Yan , Yu Wenshan
Published: February 2020

The temperature dependence of the fracture toughness JC of a three-dimensional (3D) random fibrous (RF) material, with a porosity of 87% along the through-the-thickness (TTT) direction, was investigated using experiments and the finite element method (FEM) in this study. The temperature considered ranges from 299 to 1273 K. The experimental observations revealed the fracture toughness JC with crack length-to-width ratios of 0.4 and 0.5, which increased from 47.32 to 328.28 J/m2 and from 44.92 to 280.09 J/m2, respectively, as the temperature increased. Then, a 3D FE model, considering the meso-morphology characteristics of the 3D RF material, was developed to simulate a size-scaled compact tension (CT) specimen with a single edge crack. Using the elastic modulus and the fracture strength of the silica fibers at room temperature, we verified the effectiveness of the FE model, then predicted the fracture strength of the silica fibers and the bonding between the fibers at elevated temperatures. In addition, our developed FE model proved to successfully simulate the fracture toughness JC from 299 to 1273 K and reveal the deformation mechanism of the 3D RF material at different temperatures.
The Impact of Single- and Multicomponent Liquid Drops on a Heated Wall: Child Droplets
Authors: Demidovich Anastasia , Kropotova Svetlana , Piskunov Maxim , Shlegel Nikita , Vysokomornaya Olga
Published: February 2020

This paper presents the experimental research into the impingement of single- and multicomponent liquid drops on a solid wall. We focus on studying the conditions and characteristics of two impact scenarios: rebound and breakup. We performed a comprehensive analysis of the effect of a group of factors on the drop transformation and fragmentation characteristics. These factors include the drop velocity and size, Weber number, impinging angle, wall temperature, thermophysical properties of the wall material, surface roughness, hydrophilic and hydrophobic behavior of the surface, homogeneity and inhomogeneity of the drop composition, as well as viscosity and surface tension of the liquid. We compared the outcomes of one, two, and three drops with the same total volume on a wall. Histograms were plotted of the number and size distribution of the emerging secondary droplets. The results include the critical conditions for the intense breakup of drops. Such factors as wall heating, its roughness, impinging angle, drop size and velocity affected the breakup conditions most notably. The variation of a group of these factors could provide a 2–25-fold increase in the liquid surface area as a result of the impact.
Effect of Arbuscular Mycorrhizal Fungi (AMF) and Plant Growth-Promoting Bacteria (PGPR) Inoculations on Elaeagnus angustifolia L. in Saline Soil
Authors: Pan Jing , Huang Cuihua , Peng Fei , Zhang Wenjuan , Luo Jun , Ma Shaoxiu , Xue Xian
Published: February 2020

Arbuscular mycorrhizal fungi (AMF) and plant growth-promoting rhizobacteria (PGPR) are considered highly-efficient agents for conferring salt tolerance in host plants and improving soil fertility in rhizosphere. However, information about the inoculation of beneficial microbes on halophytes in arid and semi-arid regions remains inadequate. The objective of this study was to evaluate the influence of AMF (Glomus mosseae) inoculation, alone or in combination with PGPR (Bacillus amyloliquefaciens), on biomass accumulation, morphological characteristics, photosynthetic capacity, and rhizospheric soil enzyme activities of Elaeagnus angustifolia L., a typical halophyte in the northwest of China. The results indicate that, for one-year-old seedlings of Elaeagnus angustifolia L., AMF significantly promoted biomass accumulation in aboveground organs, increased the numbers of leaves and branches, and improved the leaf areas, stem diameters and plant height. AMF-mediated morphological characteristics of aboveground organs favored light interception and absorption and maximized the capacities for photosynthesis, transpiration, carbon dioxide assimilation and gas exchange of Elaeagnus angustifolia L. seedlings in saline soil. AMF also promoted root growth, modified root architecture, and enhanced soil enzyme activities. Elaeagnus angustifolia L. was more responsive to specific inoculation by AMF than by a combination of AMF and PGPR or by solely PGPR in saline soils. Therefore, we suggest that G. mosseae can be used in saline soil to enhance Elaeagnus angustifolia L. seedlings growth and improve soil nutrient uptake. This represents a biological technique to aid in restoration of saline-degraded areas.
Removal of Pb(II) Ions from Wastewater by Using Polyethyleneimine-Functionalized Fe3O4 Magnetic Nanoparticles
Authors: Tao Yu , Zhang Chuan , Lü Ting , Zhao Hongting
Published: February 2020

A class of polyethyleneimine (PEI)-functionalized Fe3O4 magnetic nanoparticles (MNPs) has been facilely produced through a solvothermal process. The synthetic MNPs have been characterized by multiple technologies and then used for Pb(II) ion sorption from the aqueous media in different conditions. It was found the Pb(II) adsorption behaviors could be well fitted by the pseudo second-order kinetic and Langmuir isotherm models. The maximum Pb(II) adsorption capacity at 25 °C and pH 5.0 was calculated to be 60.98 mg/g. Moreover, effects of temperature, pH, and electrolyte of aqueous phase on the Pb(II) adsorption capacity of MNPs have been carefully examined. The Pb(II) adsorbing capacity was enhanced with temperature or pH rising, but reduced with the addition of various electrolytes. Additionally, the recyclability of synthetic MNPs has been also assessed. The prepared PEI-functionalized MNPs could still maintain good adsorption performance after five cycles of Pb(II) removal. These results indicated that the PEI-functionalized Fe3O4 MNPs could be readily synthesized and served as a desirable and economic adsorbent in Pb(II)-contaminated wastewater treatment.
Integrated System Technology of POME Treatment for Biohydrogen and Biomethane Production in Malaysia
Authors: Zainal Bidattul Syirat , Ahmad Mohd Azwan , Danaee Mahmoud , Jamadon Nashrah , Mohd Nuruol Syuhadaa , Ibrahim Shaliza
Published: February 2020

In recent years, production of biohydrogen and biomethane (or a mixture of these; biohythane) from organic wastes using two-stage bioreactor have been implemented by developing countries such as Germany, USA and the United Kingdom using the anaerobic digestion (AD) process. In Thailand, biohythane production in a two-stage process has been widely studied. However, in Malaysia, treating organic and agricultural wastes using an integrated system of dark fermentation (DF) coupled with anaerobic digestion (AD) is scarce. For instance, in most oil palm mills, palm oil mill effluent (POME) is treated using a conventional open-ponding system or closed-digester tank for biogas capture. This paper reviewed relevant literature studies on treating POME and other organic wastes using integrated bioreactor implementing DF and/or AD process for biohydrogen and/or biomethane production. Although the number of papers that have been published in this area is increasing, a further review is needed to reveal current technology used and its benefits, especially in Malaysia, since Malaysia is the second-largest oil palm producer in the world.
Current Harmonic Suppression Algorithm for Asymmetric Dual Three-Phase PMSM
Authors: Wu Zhihong , Gu Weisong , Lu Ke , Zhu Yuan , Guan Jianbin
Published: February 2020

Based on the vector space decomposition (VSD) transformation, the currents of an asymmetric dual three-phase permanent magnet synchronous motor (ADT-PMSM) with isolated neutral points are decoupled into the torque, producing α-ß components in the fundamental subspace and the loss-producing x-y components in the harmonic subspace. In order to suppress the current harmonics, a feedforward voltage compensation that is calculated according to the dead time, turn on/off time, and the voltage drop is added to the reference voltage of the control algorithm. Due to the limitations of the feedforward voltage compensation method, a feedback current control loop is set up in the x-y subspace, where an improved resonant controller is adopted to generate the compensation voltage. The improved resonant controller can achieve a high gain at a specific frequency. The experimental results verify the effectiveness of the proposed method.
Dependence Representation Learning with Convolutional Neural Networks and 2D Histograms
Authors: Kim Taejun , Kim Han-joon
Published: February 2020

Researchers frequently use visualizations such as scatter plots when trying to understand how random variables are related to each other, because a single image represents numerous pieces of information. Dependency measures have been widely used to automatically detect dependencies, but these measures only take into account a few types of data, such as the strength and direction of the dependency. Based on advances in the applications of deep learning to vision, we believe that convolutional neural networks (CNNs) can come to understand dependencies by analyzing visualizations, as humans do. In this paper, we propose a method that uses CNNs to extract dependency representations from 2D histograms. We carried out three sorts of experiments and found that CNNs can learn from visual representations. In the first experiment, we used a synthetic dataset to show that CNNs can perfectly classify eight types of dependency. Then, we showed that CNNs can predict correlations based on 2D histograms of real datasets and visualize the learned dependency representation space. Finally, we applied our method and demonstrated that it performs better than the AutoLearn feature generation algorithm in terms of average classification accuracy, while generating half as many features.
Targeted Sentiment Classification Based on Attentional Encoding and Graph Convolutional Networks
Authors: Xiao Luwei , Hu Xiaohui , Chen Yinong , Xue Yun , Gu Donghong , Chen Bingliang , Zhang Tao
Published: February 2020

Targeted sentiment classification aims to predict the emotional trend of a specific goal. Currently, most methods (e.g., recurrent neural networks and convolutional neural networks combined with an attention mechanism) are not able to fully capture the semantic information of the context and they also lack a mechanism to explain the relevant syntactical constraints and long-range word dependencies. Therefore, syntactically irrelevant context words may mistakenly be recognized as clues to predict the target sentiment. To tackle these problems, this paper considers that the semantic information, syntactic information, and their interaction information are very crucial to targeted sentiment analysis, and propose an attentional-encoding-based graph convolutional network (AEGCN) model. Our proposed model is mainly composed of multi-head attention and an improved graph convolutional network built over the dependency tree of a sentence. Pre-trained BERT is applied to this task, and new state-of-art performance is achieved. Experiments on five datasets show the effectiveness of the model proposed in this paper compared with a series of the latest models.
Influence of Cryoconcentration on Quality Attributes of Apple Juice (Malus Domestica cv. Red Fuji)
Authors: Orellana-Palma Patricio , Lazo-Mercado Virgilio , Gianelli María Pía , Hernández Eduard , Zúñiga Rommy N. , Petzold Guillermo
Published: February 2020

Apple juice was subjected to centrifugal block cryoconcentration (CBCC) for three cycles and their effect on the physicochemical properties, bioactive compounds, antioxidant activity, volatile profile, and sensory analysis was investigated. In the final cycle, the solutes were approximately four-fold of the initial condition (≈14 °Brix) and the color (ΔE* ≈ 25.0) was darker than the fresh juice, with bioactive compound concentration values close to 819 mg GAE/100 g d.m., 248 and 345 mg CEQ/100 g d.m. for total polyphenol, flavonoid, and flavanol content, respectively, equivalent to a retention of over 60%. DPPH and FRAP assays presented high antioxidant activities, with values of approximately 1803 μmol TE/100 g d.m. and 2936 μmol TE/100 g d.m, respectively. The cryoconcentrate showed a similar aromatic profile to the fresh juice, with 29 and 28 volatile compounds identified, respectively. The centrifugal force allowed to obtain excellent process parameters, with 73%, 0.87 (kg/kg), and 85% for efficiency, solute yield, and percentage of concentrate, respectively. Sensory evaluation shows that the odor, aroma, and flavor of fresh sample were remained in the reconstituted cryoconcentrate sample, with good qualifications (four points in a five-score hedonic scale) by trained panelists. Therefore, CBCC can preserve important quality attributes from apple juice.
Serious Game Platform with Haptic Feedback and EMG Monitoring for Upper Limb Rehabilitation and Smoothness Quantification on Spinal Cord Injury Patients
Authors: Gutiérrez Álvaro , Sepúlveda-Muñoz Delia , Gil-Agudo Ángel , de los Reyes Guzmán Ana
Published: February 2020

Cervical Spinal Cord injury (SCI) is a neurological disease that produces, as a consequence, impairments of the upper limb function. This paper illustrates a virtual reality platform based on three serious games for upper limb rehabilitation with electromyography monitoring, providing force feedback to the patient. In the rehabilitation process proposed, haptic feedback was provided to the patients to strength the arm muscles by means of the Novint Falcon device. This end-effector device was used to manipulate the serious games. During the therapy performance, the system recorded electromyography signals from the patient’s arm muscles, which may be used to monitor muscle contraction. The work presented a virtual reality system developed for spinal cord-injured patients. Each virtual reality environment could be modified in strength and duration according to the patients’ needs and was implemented for recording quantitative data about the motor performance. The platform was validated as a proof of concept in cervical spinal cord-injured patients. Results showed that this rehabilitation platform could be used for obtaining objective information in relation to motor control characteristics.
Selected Papers from IEEE ICASI 2018
Authors: Meen Teen-Hang , Chang Shoou-Jinn , Prior Stephen D.
Published: February 2020

This Special Issue on “Selected Papers from IEEE ICASI 2018” includes excellent papers presented at the IEEE ICASI 2018 regarding the “applied system innovation” topic. Mechanical engineering and design innovations are both academic and practical engineering fields, which involve systematic technological materialization through scientific principles and engineering designs. Technological innovations in mechanical engineering include IT-based intelligent mechanical systems, mechanics and design innovations, and applied materials in nanosciences and nanotechnology. The aim is to encourage the attendees at the IEEE ICASI 2018 to publish their experimental and theoretical research relating to applied system innovation.
Assessment of the Lateral Vibration Serviceability Limit State of Slender Footbridges Including the Postlock-in Behaviour
Authors: Cuevas Rocío G. , Jiménez-Alonso Javier F. , Martínez Francisco , Díaz Iván M.
Published: February 2020

The lateral vibration serviceability of slender footbridges has been the subject of many studies over the last few decades. However, in spite of the large amount of research, a common criterion has not been set yet. Although the human–structure interaction phenomenon is widely accepted as the main cause of the sudden onset of high amplitudes of vibration, the current design recommendations do not include an expression for the auto-induced component of the pedestrian action and, as a consequence, it is not possible to evaluate the footbridge comfort once the lock-in effect has developed. Hence, the purpose of this paper is to propose a general formulation, which allows the analysis of the different load scenarios that the footbridge will experience during its overall life cycle. An important advantage over most current design guidelines is that the procedure permits the evaluation of the comfort level of the footbridge, even with crowd densities above the “critical number”, and thus takes informed decisions about the possible use of external devices to control the vibration response, depending on the probability of occurrence of the problem. The performance of the proposed method is successfully evaluated through numerical response simulations of two real footbridges, showing a good agreement with the experimental data.
Tunable Effect of the Calcination of the Silanol Groups of KIT-6 and SBA-15 Mesoporous Materials
Authors: Basso Adriano M. , Nicola Bruna P. , Bernardo-Gusmão Katia , Pergher Sibele B. C.
Published: February 2020

The calcination process is a crucial step during SBA-15 and KIT-6 synthesis. It is used to completely remove the organic template and condense silanol groups, and it allows the determination of the textural and physical properties of these materials, depending on the adopted conditions. Moreover, calcination influences the number of silanols available on the surface of the material. The concentration of silanols is important if these materials were synthesized for use in adsorption or functionalization. To understand and optimize the silanol groups of SBA-15 and KIT-6, in this study, the temperature and time calcination parameters were varied. The experiments were performed at 300, 400, and 500 °C for 300, 400, and 500 min. The results show that the ideal temperature to preserve the silanol groups is 300 °C, but to optimize the textural properties, it is better to calcine these molecular sieves at 400 °C. A calcination for 10 h did not give better results than a calcination for 5 h, demonstrating that the former duration is excessive for use.
Two-Stage Optimal Scheduling of Large-Scale Renewable Energy System Considering the Uncertainty of Generation and Load
Authors: Kong Xiangyu , Quan Shuping , Sun Fangyuan , Chen Zhengguang , Wang Xingguo , Zhou Zexin
Published: February 2020

With the development of smart grid and low-carbon electricity, a high proportion of renewable energy is connected to the grid. In addition, the peak-valley difference of system load increases, which makes the traditional grid scheduling method no longer suitable. Therefore, this paper proposes a two-stage low-carbon economic scheduling model considering the characteristics of wind, light, thermal power units, and demand response at different time scales. This model not only concerns the deep peak state of thermal power units under the condition of large-scale renewable energy, but also sets the uncertain models of PDR (Price-based Demand Response) virtual units and IDR (Incentive Demand Response) virtual units. Taking the system operation cost and carbon treatment cost as the target, the improved bat algorithm and 2PM (Two-point Estimation Method) are used to solve the problem. The introduction of climbing costs and low load operating costs can more truly reflect the increased cost of thermal power units. Meanwhile, the source-load interaction can weigh renewable energy limited costs and the increased costs of balancing volatility. The proposed method can be applied to optimal dispatch and safe operation analysis of the power grid with a high proportion of renewable energy. Compared with traditional methods, the total scheduling cost of the system can be reduced, and the rights and obligations of contributors to system operation can be guaranteed to the greatest extent.
Boosting Minority Class Prediction on Imbalanced Point Cloud Data
Authors: Lin Hsien-I , Nguyen Mihn Cong
Published: February 2020

Data imbalance during the training of deep networks can cause the network to skip directly to learning minority classes. This paper presents a novel framework by which to train segmentation networks using imbalanced point cloud data. PointNet, an early deep network used for the segmentation of point cloud data, proved effective in the point-wise classification of balanced data; however, performance degraded when imbalanced data was used. The proposed approach involves removing between-class data point imbalances and guiding the network to pay more attention to majority classes. Data imbalance is alleviated using a hybrid-sampling method involving oversampling, as well as undersampling, respectively, to decrease the amount of data in majority classes and increase the amount of data in minority classes. A balanced focus loss function is also used to emphasize the minority classes through the automated assignment of costs to the various classes based on their density in the point cloud. Experiments demonstrate the effectiveness of the proposed training framework when provided a point cloud dataset pertaining to six objects. The mean intersection over union (mIoU) test accuracy results obtained using PointNet training were as follows: XYZRGB data (91%) and XYZ data (86%). The mIoU test accuracy results obtained using the proposed scheme were as follows: XYZRGB data (98%) and XYZ data (93%).
Development of a Low Cost and Path-free Autonomous Patrol System Based on Stereo Vision System and Checking Flags
Authors: Lan Chien-Wu , Chang Chi-Yao
Published: February 2020

Nowadays, security guard patrol services are becoming roboticized. However, high construction prices and complex systems make patrol robots difficult to be popularized. In this research, a simplified autonomous patrolling robot is proposed, which is fabricated by upgrading a wheeling household robot with stereo vision system (SVS), radio frequency identification (RFID) module, and laptop. The robot has four functions: independent patrolling without path planning, checking, intruder detection, and wireless backup. At first, depth information of the environment is analyzed through SVS to find a passable path for independent patrolling. Moreover, the checkpoints made with RFID tag and color pattern are placed in appropriate positions within a guard area. While a color pattern is detected by the SVS, the patrolling robot is guided to approach the pattern and check its RFID tag. For more, the human identification function of SVS is used to detect an intruder. While a skeleton information of the human is analyzed by SVS, the intruder detection function is triggered, then the robot follows the intruder and record the images of the intruder. The recorded images are transmitted to a server through Wi-Fi to realize the remote backup, and users can query the recorded images from the network. Finally, an experiment is made to test the functions of the autonomous patrolling robot successfully.
Study of Solid Particle Erosion on Helicopter Rotor Blades Surfaces
Authors: Bai Xupeng , Yao Yongming , Han Zhiwu , Zhang Junqiu , Zhang Shuaijun
Published: February 2020

In this study, titanium alloy (Ti-4Al-1.5Mn), magnesium alloy (Mg-Li9-A3-Zn3), or aluminum alloy (Al7075-T6) were used to construct the shell model of helicopter rotor blade to study the solid particle erosion of helicopter rotor blades. The erosion resistance of the three materials at different angles of attack (6°, 3°, or 0°) and particle collision speeds (70, 150, or 220 m/s) was examined using the finite volume method, the discrete phase method, and erosion models. In addition, the leading edge of the helicopter blades was coated with two types of bionic anti-erosion coating layers (V- and VC-type), in an attempt to improve erosion resistance at the angles of attack and particle collision speeds given above. The results showed that Ti-4Al-1.5Mn had the best erosion resistance at high speed, followed by Al7075-T6 and Mg-Li9-A3-Zn3. The angle of attack appeared to affect only the surface area of the blade erosion, while the erosion rate was not affected. Finally, the results of this article showed that the V-type bionic coating had better erosion resistance than the VC-type coating at the same impact speeds. The angle of attack did not have a significant effect on the erosion rate of the bionic coating.
Investigation of Airborne Molecular Contamination in Cleanroom Air Environment through Portable Soft X-Ray Radiolysis Detector
Authors: Kim Changhyuk , Cho Kyungil , Pui David Y. H.
Published: February 2020

Airborne molecular contamination (AMC) represents a wide range of gaseous contaminants in the cleanroom air environment. It is difficult to monitor AMC in the cleanroom air using conventional methods in real-time due to its ultra-low concentrations, such as part-per-billion or -trillion (ppb or ppt). In this study, AMC in the real university cleanroom air environment was investigated to figure out hot spots through portable soft X-ray radiolysis detector, which converts gaseous AMC into nanoparticles (gas-to-particle conversion) under the soft X-ray irradiation. A soft X-ray was connected to a clean stainless steel chamber to convert the introduced AMC into nanoparticles, and the size distributions of nanoparticles were measured through a scanning mobility particle sizer, which consists of a differential mobility analyzer and a condensation particle counter. By converting the size distribution information into total particle volume concentrations, equivalent AMC concentrations can be calculated using an appropriate calibration curve between AMC and the total particle volume concentration. The volume concentration of nanoparticles were converted into an equivalent sulfur dioxide (SO2, a major acidic AMC in the cleanroom air) concentration by a calibration curve between SO2 and the particle volume concentrations. AMC levels at different locations in the cleanroom at the University of Minnesota were measured by the soft X-ray-assisted AMC detector, and revealed that several tenth-order of pptV (lower than 15 pptV) in terms of the equivalent SO2 concentration existed in the cleanroom air environment.
The Gyrotrons as Promising Radiation Sources for THz Sensing and Imaging
Authors: Idehara Toshitaka , Sabchevski Svilen Petrov , Glyavin Mikhail , Mitsudo Seitaro
Published: February 2020

The gyrotrons are powerful sources of coherent radiation that can operate in both pulsed and CW (continuous wave) regimes. Their recent advancement toward higher frequencies reached the terahertz (THz) region and opened the road to many new applications in the broad fields of high-power terahertz science and technologies. Among them are advanced spectroscopic techniques, most notably NMR-DNP (nuclear magnetic resonance with signal enhancement through dynamic nuclear polarization, ESR (electron spin resonance) spectroscopy, precise spectroscopy for measuring the HFS (hyperfine splitting) of positronium, etc. Other prominent applications include materials processing (e.g., thermal treatment as well as the sintering of advanced ceramics), remote detection of concealed radioactive materials, radars, and biological and medical research, just to name a few. Among prospective and emerging applications that utilize the gyrotrons as radiation sources are imaging and sensing for inspection and control in various technological processes (for example, food production, security, etc). In this paper, we overview the current status of the research in this field and show that the gyrotrons are promising radiation sources for THz sensing and imaging based on both the existent and anticipated novel techniques and methods.
Stress-Induced Magnetic Anisotropy Enabling Engineering of Magnetic Softness and GMI Effect of Amorphous Microwires
Authors: Corte-León Paula , Talaat Ahmed , Zhukova Valentina , Ipatov Mihail , Blanco Juan María , Gonzalez Julián , Zhukov Arcady
Published: February 2020

Stress-annealing enabled a considerable improvement in the GMI effect in both Fe- and Co-rich glass-coated microwires. Additionally, a remarkable magnetic softening can be achieved in stress-annealed Fe-rich microwires. Observed stress-annealing induced magnetic anisotropy is affected by annealing conditions (temperatures and stresses applied during annealing). The highest GMI ratio up to 310% was obtained in stress-annealed Co-rich microwires, although they presented rectangular hysteresis loops. A remarkable magnetic softness and improved GMI ratio over a wide frequency range were obtained in stress-annealed Fe-rich microwires. Irregular magnetic field dependence observed for some stress-annealing conditions is attributed to the contribution of both the inner axially magnetized core and outer shell, with transverse magnetic anisotropy.
Real-Time Detection for Cache Side Channel Attack using Performance Counter Monitor
Authors: Cho Jonghyeon , Kim Taehun , Kim Soojin , Im Miok , Kim Taehyun , Shin Youngjoo
Published: February 2020

Cache side channel attacks extract secret information by monitoring the cache behavior of a victim. Normally, this attack targets an L3 cache, which is shared between a spy and a victim. Hence, a spy can obtain secret information without alerting the victim. To resist this attack, many detection techniques have been proposed. However, these approaches have limitations as they do not operate in real time. This article proposes a real-time detection method against cache side channel attacks. The proposed technique performs the detection of cache side channel attacks immediately after observing a variation of the CPU counters. For this, Intel PCM (Performance Counter Monitor) and machine learning algorithms are used to measure the value of the CPU counters. Throughout the experiment, several PCM counters recorded changes during the attack. From these observations, a detecting program was implemented by using these counters. The experimental results show that the proposed detection technique displays good performance for real-time detection in various environments.
Groove Formation in Glass Substrate by a UV Nanosecond Laser
Authors: Shin Joonghan , Nam Kimoon
Published: February 2020

This study reports the laser grooving of glass. In this study, an ultraviolet (UV) nanosecond laser is used to produce grooves in soda lime glass by varying laser power, scan speed, pulse repetition rate, and number of scans. The threshold power density to generate damage on glass surface is found to be ~6.37 × 108 W/cm2. According to the result of a single laser scan, at a high laser power and low scan speed, material removal does not nearly occur, and only volume melting underneath the glass surface and large thermal crack are induced. With the decreasing laser power and increasing scan speed, a groove with a smooth surface is formed owing to the melting-dominant material removal process. The groove of rough surface morphology is produced with the further increase of the scan speed due to shattering induced by shock wave. Under this condition, it is found that either small cracks are produced or a crack-free groove is obtained. In this study, the fabrication of the microchannel for bio-chip application is also attempted by multiple laser scans. The near rectangular-shaped and crack-free groove (width × depth: ~220 μm × ~500 μm) with quite a smooth surface is fabricated by the multiple laser scans with a non-zero scan spacing.
Simultaneous Sensing of Touch and Pressure by Using Highly Elastic e-Fabrics
Authors: Vu Chi Cuong , Kim Jooyong
Published: February 2020

In recent years, electronic skins have been widely studied for human monitoring systems. This research field needs multi-sensing points for large deformation, strong recovery, and mass production methods. Toward these aims, the fabrication of e-fabric skins made from a capacitive touch sensing layer and a capacitive pressure sensing layer is presented in the paper. Due to the high elasticity of the dielectric layer of the spacer fabric, this structure exhibits a very fast recovery time (6 ms), low hysteresis (<5%), and high cycling stability (>20,000 times). Besides, the stacking structure of the electrode layers ( single-wall carbon nanotube/silver paste) is due to good durability even under large deformations (grasping, bending, stretching), and the skin is breathable for applications. As expected, the e-fabric skin is proven to be robust for detecting a spatial pressure distribution in real time. The extremely simple fabrication process is also an extra plus point in view of point mass production.
Durability Issues and Corrosion of Structural Materials and Systems in Farm Environment
Authors: Maraveas Chrysanthos
Published: February 2020

This review paper investigated the durability and corrosion of materials used in the construction of agricultural buildings. Even though concrete and metal were the materials of choice in the construction of farm structures, they are susceptible to corrosion and environmental degradation. Acid attacks result in the oxidation of metals and mass losses and reduced compressive strength of the metal structures. Concrete structures are degraded in high humidity environments, such as lagoons, agricultural effluents, and animal manure. Poultry, cow, and pig manure contain variable quantities of corrosion-inducing chemicals, such as sulfates, nitrates, chlorides, hydrogen sulfide, and ammonia. However, the degradation of concrete structures can be mitigated by the utilization of modified concrete containing sulfur, fly ash, silica fume, and nanoparticles such as silica. Concrete structures made of fiber-reinforced polymers are less prone to corrosion and are more durable. The design for durability has also emerged as a viable option for optimizing the service life of agricultural buildings by adhering to the exposure limits.
Tar Removal by Nanosecond Pulsed Dielectric Barrier Discharge
Authors: Dors Mirosław , Kurzyńska Daria
Published: February 2020

Plasma-catalytic reforming of simulated biomass tar composed of naphthalene, toluene, and benzene was carried out in a coaxial plasma reactor supplied with nanosecond high-voltage pulses. The effect of Rh-LaCoO3/Al2O3 and Ni/Al2O3 catalysts covering high-voltage electrode on the tar conversion efficiency was evaluated. Compared to the plasma reaction without a catalyst, the combination of plasma with the catalyst significantly enhanced the conversion of all three tar components, achieving complete conversion when an Rh-based catalyst was used. Apart from gaseous and liquid samples, char samples taken at five locations inside the reactor were also analyzed for their chemical composition. Char was not formed when the Rh-based catalyst was used. Different by-products were detected for the plasma reactor without a catalyst, with the Ni- and Rh-based catalysts. A possible reaction pathway in the plasma-catalytic process for naphthalene, as the most complex compound, was proposed through the combined analysis of liquid and solid products.
Study on Radiated Noise of a Panel under Fluctuating Surface Pressure Due to an Idealized Side Mirror
Authors: Shao Jianwang , Yang Jinmeng , Wu Xian , Wang Cheng , Deng Guoming
Published: February 2020

As traditional automobiles develop towards new energy vehicles, the noise, vibration and harshness (NVH) performance of automobiles is facing new challenges. Without the cover of the traditional engine noise and inlet and exhaust noise, the high-speed wind noise becomes more prominent. Thus, research on the calculation method of vehicle interior noise in high-speed driving condition is needed. However, vehicle body structure is complex, and the external excitation components are complicated. In order to analyze the method of predicting the vehicle interior noise at high speed, an idealized side mirror model is taken as the research object in this paper and the radiated noise of a panel under the fluctuating surface pressure (FSP) due to the idealized side mirror is studied. The FSP of the panel is first studied by the numerical simulations of incompressible and compressible flow field. For the incompressible flow field, the Corcos turbulent boundary layer (TBL) model is established to simulate the convective component and the boundary element method (BEM) is used to extract the acoustic component. Subsequently, the Corcos model coupling BEM method, the random modal force coupling BEM method and the deterministic modal force coupling BEM method are used separately to calculate the noise of the panel under the FSP. For the compressible flow field, the convective and acoustic component in the fluctuating pressure are separated by the wavenumber-frequency spectrum (WFS) method. The radiated noise of the panel under the FSP is calculated again by using the WFS, the method of random modal force and the method of deterministic modal force, respectively. Then, the computational time of the six methods of incompressible and compressible calculation is compared. Finally, a fast and accurate method of calculating the panel radiated noise under FSP is obtained by comparing the computational accuracy with the experimental results and combining the computational time: the method of incompressible random modal force. This method can be used to quickly and accurately analyze the vehicle interior noise at high speed, and to optimize the exterior protrusions and the vehicle sound package for improving the vehicle NVH performance at high speed.
Ultrafast X-ray Photochemistry at European XFEL: Capabilities of the Femtosecond X-ray Experiments (FXE) Instrument
Authors: Khakhulin Dmitry , Otte Florian , Biednov Mykola , Bömer Christina , Choi Tae-Kyu , Diez Michael , Galler Andreas , Jiang Yifeng , Kubicek Katharina , Lima Frederico Alves , Rodriguez-Fernandez Angel , Zalden Peter , Gawelda Wojciech , Bressler Christian
Published: February 2020

Time-resolved X-ray methods are widely used for monitoring transient intermediates over the course of photochemical reactions. Ultrafast X-ray absorption and emission spectroscopies as well as elastic X-ray scattering deliver detailed electronic and structural information on chemical dynamics in the solution phase. In this work, we describe the opportunities at the Femtosecond X-ray Experiments (FXE) instrument of European XFEL. Guided by the idea of combining spectroscopic and scattering techniques in one experiment, the FXE instrument has completed the initial commissioning phase for most of its components and performed first successful experiments within the baseline capabilities. This is demonstrated by its currently 115 fs (FWHM) temporal resolution to acquire ultrafast X-ray emission spectra by simultaneously recording iron Kα and Kβ lines, next to wide angle X-ray scattering patterns on a photoexcited aqueous solution of [Fe(bpy)3]2+, a transition metal model compound.
Dense, Strong, and Precise Silicon Nitride-Based Ceramic Parts by Lithography-Based Ceramic Manufacturing
Authors: Altun Altan Alpay , Prochaska Thomas , Konegger Thomas , Schwentenwein Martin
Published: February 2020

Due to the high level of light absorption and light scattering of dark colored powders connected with the high refractive indices of ceramic particles, the majority of ceramics studied via stereolithography (SLA) have been light in color, including ceramics such as alumina, zirconia and tricalcium phosphate. This article focuses on a lithography-based ceramic manufacturing (LCM) method for β-SiAlON ceramics that are derived from silicon nitride and have excellent material properties for high temperature applications. This study demonstrates the general feasibility of manufacturing of silicon nitride-based ceramic parts by LCM for the first time and combines the advantages of SLA, such as the achievable complexity and low surface roughness (Ra = 0.50 µm), with the typical properties of conventionally manufactured silicon nitride-based ceramics, such as high relative density (99.8%), biaxial strength (σf = 764 MPa), and hardness (HV10 = 1500).
A Deep-Learning Approach for Diagnosis of Metastatic Breast Cancer in Bones from Whole-Body Scans
Authors: Papandrianos Nikolaos , Papageorgiou Elpiniki , Anagnostis Athanasios , Feleki Anna
Published: February 2020

(1) Background: Bone metastasis is one of the most frequent diseases in breast, lung and prostate cancer; bone scintigraphy is the primary imaging method of screening that offers the highest sensitivity (95%) regarding metastases. To address the considerable problem of bone metastasis diagnosis, focused on breast cancer patients, artificial intelligence methods devoted to deep-learning algorithms for medical image analysis are investigated in this research work; (2) Methods: Deep learning is a powerful algorithm for automatic classification and diagnosis of medical images whereas its implementation is achieved by the use of convolutional neural networks (CNNs). The purpose of this study is to build a robust CNN model that will be able to classify images of whole-body scans in patients suffering from breast cancer, depending on whether or not they are infected by metastasis of breast cancer; (3) Results: A robust CNN architecture is selected based on CNN exploration performance for bone metastasis diagnosis using whole-body scan images, achieving a high classification accuracy of 92.50%. The best-performing CNN method is compared with other popular and well-known CNN architectures for medical imaging like ResNet50, VGG16, MobileNet, and DenseNet, reported in the literature, providing superior classification accuracy; and (4) Conclusions: Prediction results show the efficacy of the proposed deep learning approach in bone metastasis diagnosis for breast cancer patients in nuclear medicine.