bluuebunny/crossref_metadata_2025 huggingface dataset:
Additivity of Ileal Amino Acid Digestibility in Diets Containing Corn, Soybean Meal, and Corn Distillers Dried Grains with Solubles for Male Broilers
Authors: An Su Hyun , Sung Jung Yeol , Kang Hwan-Ku , Kong Changsu
Published: May 2020

The aim was to test additivity of apparent ileal digestibility (AID) and standardized ileal digestibility (SID) of amino acids (AAs) in mixed diets for Ross 308 broiler chickens. Two hundred and eighty-eight, 20-d-old male broiler chickens were assigned to one of six diets, with six birds per cage using a randomized complete block design. The diets consisted of a nitrogen-free diet, three diets containing corn, soybean meal (SBM), and corn distillers dried grains with solubles (CDDGS) as the sole source of nitrogen, respectively, and two mixed diets containing corn, SBM or CDDGS. Chromic oxide was added to the diets as an indigestible index. On day 24, birds were euthanized for ileal digesta collection. Relative proportion of the basal endogenous loss of AAs to total ileal outflow of AAs in corn was greater (p < 0.05) than that of SBM and CDDGS. For the corn-SBM and corn-SBM-CDDGS mixed diets, the AID of AAs differed (p < 0.05) from the predicted values. No difference was observed between the measured and predicted SID of AA. In conclusion, the SID of AAs is more additive in mixed diets containing corn, SBM, or CDDGS compared to AID values.
Insight of Polyphenol Oxidase Enzyme Inhibition and Total Polyphenol Recovery from Cocoa Beans
Authors: Toro-Uribe Said , Godoy-Chivatá Jhair , Villamizar-Jaimes Arley René , Perea-Flores María de Jesús , López-Giraldo Luis J.
Published: May 2020

A full factorial design (ascorbic acid/l-cysteine inhibitors, temperature, and time as factors) study was conducted to enhance inhibition of polyphenol oxidase (PPO) activity without decreasing cocoa polyphenol concentrations. The data obtained were modelled through a new equation, represented by Γ, which correlates both high polyphenol content with reduced specific PPO activity. At optimized values (70 mM inhibitory solution at 96 °C for 6.4 min, Γ = 11.6), 93.3% PPO inhibition and total polyphenol of 94.9 mg GAE/g were obtained. In addition, microscopy images confirmed the cell morphological changes measured as the fractal dimension and explained the possible cell lysis and denaturation as a result of heat treatment and chemical inhibitors. Results also showed that PPO enzyme was most suitable (higher vmax/Km ratio) for catechol, with a reduction in its affinity of 13.7-fold after the inhibition heat treatment. Overall, this work proposed a suitable and food-safe procedure for obtaining enriched polyphenol extract with low enzyme activity.
Caffeine and NAD+ Improve Motor Neural Integrity of Dissociated Wobbler Cells In Vitro
Authors: Zwilling Mareike , Theiss Carsten , Matschke Veronika
Published: May 2020

Amyotrophic lateral sclerosis (ALS) is a common degenerative disease of the central nervous system concerning a progressive loss of upper and lower motor neurons. While 5%–10% of patients are diagnosed with the inherited form of the disease, the vast majority of patients suffer from the less characterized sporadic form of ALS (sALS). As the wobbler mouse and the ALS show striking similarities in view of phenotypical attributes, the mouse is rated as an animal model for the disease. Recent investigations show the importance of nicotinamide adenine dinucleotide (NAD+) and its producing enzyme nicotinic acid mononucleotide transferase 2 (Nmnat2) for neurodegeneration as well as for the preservation of health of the neuronal cells. Furthermore, it is newly determined that these molecules show significant downregulations in the spinal cord of wobbler mice in the stable phase of disease development. Here, we were able to prove a positive benefit on affected motor neurons from an additional NAD+ supply as well as an increase in the Nmnat2 level through caffeine treatment in cells in vitro. In addition, first assumptions about the importance of endogenous and exogenous factors that have an influence on the wellbeing of motor nerve cells in the model of ALS can be considered.
Grapevine Phenology in Four Portuguese Wine Regions: Modeling and Predictions
Authors: Reis Samuel , Fraga Helder , Carlos Cristina , Silvestre José , Eiras-Dias José , Rodrigues Pedro , Santos João A.
Published: May 2020

Phenological models applied to grapevines are valuable tools to assist in the decision of cultural practices related to winegrowers and winemakers. The two-parameter sigmoid phenological model was used to estimate the three main phenological stages of the grapevine development, i.e., budburst, flowering, and veraison. This model was calibrated and validated with phenology data for 51 grapevine varieties distributed in four wine regions in Portugal (Lisboa, Douro, Dão, and Vinhos Verdes). Meteorological data for the selected sites were also used. Hence, 153 model calibrations (51 varieties × 3 phenological stages) and corresponding parameter estimations were carried out based on an unprecedented comprehensive and systematized dataset of phenology in Portugal. For each phenological stage, the centroid of the estimated parameters was subsequently used, and three generalized sigmoid models (GSM) were constructed (budburst: d = −0.6, e = 8.6; flowering: d = −0.6, e = 13.7; veraison: d = −0.5, e = 13.2). Centroid parameters show high performance for approximately 90% of the varieties and can thereby be used instead of variety-specific parameters. Overall, the RMSE (root-mean-squared-error) is < 7 days, while the EF (efficiency coefficient) is > 0.5. Additionally, according to other studies, the predictive capacity of the models for budburst remains lower than for flowering or veraison. Furthermore, the F-forcing parameter (thermal accumulation) was evaluated for the Lisboa wine region, where the sample size is larger, and for the varieties with model efficiency equal to or greater than 0.5. A ranking and categorization of the varieties in early, intermediate, and late varieties was subsequently undertaken on the basis of F values. These results can be used to more accurately monitor and predict grapevine phenology during a given season, thus supporting decision making in the Portuguese wine sector.
Highly Efficient Implementation of Block Ciphers on Graphic Processing Units for Massively Large Data
Authors: An SangWoo , Seo Seog Chung
Published: May 2020

With the advent of IoT and Cloud computing service technology, the size of user data to be managed and file data to be transmitted has been significantly increased. To protect users’ personal information, it is necessary to encrypt it in secure and efficient way. Since servers handling a number of clients or IoT devices have to encrypt a large amount of data without compromising service capabilities in real-time, Graphic Processing Units (GPUs) have been considered as a proper candidate for a crypto accelerator for processing a huge amount of data in this situation. In this paper, we present highly efficient implementations of block ciphers on NVIDIA GPUs (especially, Maxwell, Pascal, and Turing architectures) for environments using massively large data in IoT and Cloud computing applications. As block cipher algorithms, we choose AES, a representative standard block cipher algorithm; LEA, which was recently added in ISO/IEC 29192-2:2019 standard; and CHAM, a recently developed lightweight block cipher algorithm. To maximize the parallelism in the encryption process, we utilize Counter (CTR) mode of operation and customize it by using GPU’s characteristics. We applied several optimization techniques with respect to the characteristics of GPU architecture such as kernel parallelism, memory optimization, and CUDA stream. Furthermore, we optimized each target cipher by considering the algorithmic characteristics of each cipher by implementing the core part of each cipher with handcrafted inline PTX (Parallel Thread eXecution) codes, which are virtual assembly codes in CUDA platforms. With the application of our optimization techniques, in our implementation on RTX 2070 GPU, AES and LEA show up to 310 Gbps and 2.47 Tbps of throughput, respectively, which are 10.7% and 67% improved compared with the 279.86 Gbps and 1.47 Tbps of the previous best result. In the case of CHAM, this is the first optimized implementation on GPUs and it achieves 3.03 Tbps of throughput on RTX 2070 GPU.
On the Performance of the Multiple Active Antenna Spatial Modulation with 3-Dimensional Constellation
Authors: Murtala Sheriff , Holoubi Tasnim , Muchena Nishal , Mohaisen Manar , Choi Kang-Sun
Published: May 2020

In spatial modulation (SM), a single signal symbol is transmitted from a given physical antenna, where both the signal symbol and the antenna index carry information. SM with multiple active antennas (MA-SM) transmits several signal symbols from a combination of antennas at each channel use, thereby increasing the spectral efficiency. MA-SM is proposed in combination with a new 3-dimensional constellation, where signal symbols transmitted from a given antenna combination are rotated before transmission. In this paper, we derived an upper-bound on the error probability of the MA-SM as a function of the rotation angles. The search for the optimal rotation angles is modeled as a multi-objective optimization problem. We concluded based on both analytical and simulation results that the 3-dimensional constellation with the optimal angles achieved negligible improvement. Therefore, we do not recommend using the 3-dimensional constellation with the MA-SM system.
Comparative Analysis of Energy Consumption, Indoor Thermal–Hygrometric Conditions, and Air Quality for HVAC, LDAC, and RDAC Systems Used in Operating Rooms
Authors: Chien Tsung-Yi , Liang Ching-Chieh , Wu Feng-Jen , Chen Chi-Tsung , Pan Ting-Hsin , Wan Gwo-Hwa
Published: May 2020

As controlling temperature and humidity is crucial for maintaining comfort and preventing microbial growth, operating rooms (ORs) are the most energy-intensive areas in hospitals. We aimed to evaluate the energy consumption of three dehumidification air conditioning systems used in ORs and their corresponding air quality for ORs at rest. This study selected three ORs using a conventional heating, ventilation, and air conditioning (HVAC) system; a liquid desiccant air conditioning (LDAC) system; and a rotary desiccant air conditioning (RDAC) system, respectively. The indoor thermal–hygrometric conditions, air quality, and energy consumption of the ORs were monitored in this study. The median levels of relative humidity (RH) were 66.7% in the OR using the conventional HVAC system, 60.8% in the OR using the LDAC system, and 60.5% in the OR using the RDAC system. The median daily total energy consumption of the RDAC system (10.1 kWh/m2) and LDAC system (11.8 kWh/m2) were 28.12% and 16.54% lower, respectively, than that of the conventional HVAC system (14.1 kWh/m2). The PM≥0.5 levels and airborne bacterial concentrations in the ORs met the ISO 14644-1 Class 7 standard and China’s GB50333-2013 standard, respectively. The RDAC system was clearly superior to the LDAC and conventional HVAC systems in terms of energy consumption.
FTIR-ATR Spectroscopy Combined with Multivariate Regression Modeling as a Preliminary Approach for Carotenoids Determination in Cucurbita spp.
Authors: Quijano-Ortega Natalia , Fuenmayor Carlos Alberto , Zuluaga-Dominguez Carlos , Diaz-Moreno Consuelo , Ortiz-Grisales Sanín , García-Mahecha Maribel , Grassi Silvia
Published: May 2020

Quantitative analysis of carotenoids has been extensively reported using UV-Vis spectrophotometry and chromatography, instrumental techniques that require complex extraction protocols with organic solvents. Fourier transform infrared spectroscopy (FTIR) is a potential alternative for simplifying the analysis of food constituents. In this work, the application of FTIR with attenuated total reflectance (ATR) was evaluated for the determination of total carotenoid content (TCC) in Cucurbita spp. samples. Sixty-three samples, belonging to different cultivars of butternut squash (C. moschata) and pumpkin (C. maxima), were selected and analyzed with FTIR- ATR (attenuated total reflectance). Three different preparation protocols for samples were followed: homogenization (A), freeze-drying (B), and solvent extraction (C). The recorded spectra were used to develop regression models by Partial Least Squares (PLS), using data from TCC, determined by UV-Vis spectrophotometry. The PLS regression model obtained with the FTIR data from the freeze-dried samples, using the spectral range 920–3000 cm−1, had the best figures of merit (R2CAL of 0.95, R2PRED of 0.93 and RPD of 3.78), being reliable for future application in agriculture. This approach for carotenoid determination in pumpkin and squash avoids the use of organic solvents. Moreover, these results are a rationale for further exploring this technique for the assessment of specific carotenoids in food matrices.
Voice Pathology Detection and Classification Using Convolutional Neural Network Model
Authors: Mohammed Mazin Abed , Abdulkareem Karrar Hameed , Mostafa Salama A. , Khanapi Abd Ghani Mohd , Maashi Mashael S. , Garcia-Zapirain Begonya , Oleagordia Ibon , Alhakami Hosam , AL-Dhief Fahad Taha
Published: May 2020

Voice pathology disorders can be effectively detected using computer-aided voice pathology classification tools. These tools can diagnose voice pathologies at an early stage and offering appropriate treatment. This study aims to develop a powerful feature extraction voice pathology detection tool based on Deep Learning. In this paper, a pre-trained Convolutional Neural Network (CNN) was applied to a dataset of voice pathology to maximize the classification accuracy. This study also proposes a distinguished training method combined with various training strategies in order to generalize the application of the proposed system on a wide range of problems related to voice disorders. The proposed system has tested using a voice database, namely the Saarbrücken voice database (SVD). The experimental results show the proposed CNN method for speech pathology detection achieves accuracy up to 95.41%. It also obtains 94.22% and 96.13% for F1-Score and Recall. The proposed system shows a high capability of the real-clinical application that offering a fast-automatic diagnosis and treatment solutions within 3 s to achieve the classification accuracy.
Self-Similar Markovian Sources
Authors: Domański Adam , Domańska Joanna , Filus Katarzyna , Szyguła Jakub , Czachórski Tadeusz
Published: May 2020

Markov queueing models are a powerful tool to evaluate the performance of computer networks and have been used in telecommunication studies for over 100 years. To apply them to the evaluation of the modern Internet, we should not only adapt them to the contemporary network structures but also include a description of the complex stochastic patterns (self-similarity and long-range dependance) of transmitted flows. We examine the features of two Markov models of an almost self-similar process, keeping in mind the modeling of Internet traffic. We have found that the obtained results are comparable with those achieved using a well-known generator of self-similar traffic.
Empirical Thermal Performance Investigation of a Compact Lithium Ion Battery Module under Forced Convection Cooling
Authors: Hakeem Akinlabi A. A. , Solyali Davut
Published: May 2020

Lithium ion batteries (LiBs) are considered one of the most suitable power options for electric vehicle (EV) drivetrains, known for having low self-discharging properties which hence provide a long life-cycle operation. To obtain maximum power output from LiBs, it is necessary to critically monitor operating conditions which affect their performance and life span. This paper investigates the thermal performance of a battery thermal management system (BTMS) for a battery pack housing 100 NCR18650 lithium ion cells. Maximum cell temperature (Tmax) and maximum temperature difference (ΔTmax) between cells were the performance criteria for the battery pack. The battery pack is investigated for three levels of air flow rate combined with two current rate using a full factorial Design of Experiment (DoE) method. A worst case scenario of cell Tmax averaged at 36.1 °C was recorded during a 0.75 C charge experiment and 37.5 °C during a 0.75 C discharge under a 1.4 m/s flow rate. While a 54.28% reduction in ΔTmax between the cells was achieved by increasing the air flow rate in the 0.75 C charge experiment from 1.4 m/s to 3.4 m/s. Conclusively, increasing BTMS performance with increasing air flow rate was a common trend observed in the experimental data after analyzing various experiment results.
Fault Diagnosis of Rotating Machinery Based on Multi-Sensor Signals and Median Filter Second-Order Blind Identification (MF-SOBI)
Authors: Miao Feng , Zhao Rongzhen , Jia Leilei , Wang Xianli
Published: May 2020

Feature extraction plays a crucial role in the diagnosis of rotating machinery faults. However, the vibration signals measured are inherently complex and non-stationary and the features of faulty signals are often submerged by noise. The principle and method of blind source separation are introduced, and we point out that the blind source separation algorithm is invalid in an environment of strong impulse noise. In order to solve the problem of fast separation of multi-sensor signals in an environment of strong impulse noise, first, the window width of the median filter (MF) is calculated according to the sampling frequency, so that the impulse noise and part of the white noise can be effectively filtered out. Next, the filtered signals are separated by the improved second-order blind identification (SOBI) algorithm. At the same time, the method is tested on the strong pulse background noise and rub impact dataset. The results show that this method has higher efficiency and accuracy than the direct separation method. It is possible to apply the method to real-time signal analysis due to its speed and efficiency.
Mixed Reality Simulation of High-Endurance Unmanned Aerial Vehicle with Dual-Head Electromagnetic Propulsion Devices for Earth and Other Planetary Explorations
Authors: Kumar Ashish , Yoon Sugjoon , Kumar V.R.Sanal
Published: May 2020

One of the major limitations of existing unmanned aerial vehicles is limited flight endurance. In this study, we designed an innovative uninterrupted electromagnetic propulsion device for high-endurance missions of a quadcopter drone for the lucrative exploration of earth and other planets with atmospheres. As an airborne platform, this device could achieve scientific objectives better than state-of-the-art revolving spacecraft and walking robots, without any terrain limitation. We developed a mixed reality simulation based on a quadcopter drone and an X-Plane flight simulator. A computer with the X-Plane flight simulator represented the virtual part, and a real quadcopter operating within an airfield represented the real part. In the first phase of our study, we developed a connection interface between the X-Plane flight simulator and the quadcopter ground control station in MATLAB. The experimental results generated from the Earth’s atmosphere show that the flight data from the real and the virtual quadcopters are precise and very close to the prescribed target. The proof-of-concept of the mixed reality simulation of the quadcopter at the Earth atmosphere was verified and validated through several experimental flights of the F450 spider quadcopter with a Pixhawk flight controller with the restricted endurance at the airfield location of Hangang Drone Park in Seoul, South Korea. We concluded that the new generation drones integrated with lightweight electromagnetic propulsion devices are a viable option for achieving unrestricted flight endurance with improved payload capability for Earth and other planetary explorations with the aid of mixed reality simulation to meet the mission flight path demands. This study provides insight into mixed reality simulation aiming for Mars explorations and high-endurance missions in the Earth’s atmosphere with credibility using quadcopter drones regulated by dual-head electromagnetic propulsion devices.
Structure and Properties of Tantalum Coatings Obtained by Electron Beam Technology on Aluminum Substrates
Authors: Ananiashvili Khatia , Okrosashvili Mikheil , Loladze Tamar , Valko Natalia , Koltunowicz Tomasz N.
Published: May 2020

The paper deals with the study of the structure and properties of tantalum coatings formed by electron beam evaporation and deposition of tantalum powder on 300–450 °C aluminum substrate. The research results of surface morphology, phase and elemental composition show that high activity of an aluminum substrate and specific conditions for vapor-phase technology promote formation of tantalum coatings characterized by a high degree of crystalline grains, with high adhesion and hardness despite the surface cracks. It was observed that the optimum deposition temperature of tantalum on aluminum substrates varies from 300 °C to 350 °C. These coatings demonstrate excellent physical and mechanical properties due to formation of intermetallic phases in the reactive zone.
Trialing Innovative Technologies in Crisis Management—“Airborne and Terrestrial Situational Awareness” as Support Tool in Flood Response
Authors: Schröter Elisa , Kiefl Ralph , Neidhardt Eric , Gurczik Gaby , Dalaff Carsten , Lechner Konstanze
Published: May 2020

Flooding represents the most-occurring and deadliest threats worldwide among natural disasters. Consequently, new technologies are constantly developed to improve response capacities in crisis management. The remaining challenge for practitioner organizations is not only to identify the best solution to their individual demands, but also to test and evaluate its benefit in a realistic environment before the disaster strikes. To bridge the gap between theoretic potential and actual integration into practice, the EU-funded project DRIVER+ has designed a methodical and technical environment to assess innovation in a realistic but non-operational setup through trials. The German Aerospace Center (DLR) interdisciplinary merged mature technical developments into the “Airborne and terrestrial situational awareness” system and applied it in a DRIVER+ Trial to promote a sustainable and demand-oriented R&D. Experienced practitioners assessed the added value of its modules “KeepOperational” and “ZKI” in the context of large-scale flooding in urban areas. The solution aimed at providing contextual route planning in police operations and extending situational awareness based on information derived through aerial image processing. The user feedback and systematically collected data through the DRIVER + Test-bed approved that DLR’s system could improve transport planning and situational awareness across organizations. However, the results show a special need to consider, for example, cross-domain data-fusion techniques to provide essential 3D geo-information to effectively support specific response tasks during flooding.
Effective Suppression of Residual Magnetic Interference in a Conductive Shielded Room for Ultra-Low Field Nuclear Magnetic Resonance
Authors: Tan Yiqiu , Zhou Danfeng , Song Mengxiao , Li Jie
Published: May 2020

Residual magnetic interference induced by applied magnetic field pulses inside a conductive shielded room (SR) has been a common issue in ultra-low-field (ULF) nuclear magnetic resonance (NMR). The rapid cutoff of the applied pre-polarizing field (Bp) induces eddy currents in the walls of the SR, which produces a decaying residual magnetic interference that may cause severe image distortions and signal loss. In this study, a pair of cancellation coils (CC) and control electronics were designed for the suppression of the residual magnetic interference in a SR. Simulations show that this method was effective in suppressing the residual magnetic field (Br) after removal of the pre-polarizing magnetic field. Then, a small-scale SR was designed and the effectiveness of this cancellation scheme was experimentally verified. The test results showed a good agreement with the simulation, which indicated that the cancellation scheme was capable of reducing Br field to a much lower level. The scheme proposed in this study provides a solution for suppressing the residual magnetic field in the ULF NMR system. After decoupling the eddy–current field, the effect of the suppression may be further improved by optimization of the cancellation coil in further work.
Influence of Tunnel Boring Machine (TBM) Advance on Adjacent Tunnel during Ultra-Rapid Underground Pass (URUP) Tunneling: A Case Study and Numerical Investigation
Authors: Liu Chao , Peng Zhuohua , Pan Liufeng , Liu Hai , Yang Yubing , Chen Weiyun , Jiang Huaqin
Published: May 2020

This study investigates the influence of subsequent tunnel boring machine (TBM)-driven processes on the responses of the first tunnel in twin-tunnel construction using the ultra-rapid underground pass (URUP) method. A comprehensive finite element analysis (FEA) is performed to simulate the URUP TBM tunneling, considering the non-uniform convergence caused by the TBM geometry, the tunnel face supporting pressure, and the tail-grouting pressure. The FEA model is validated by the monitoring results of the bending element of the first tunnel lining. The FEA results reveal that the grouting pressure of the second tunnel has significant influence on lining deformation of the first tunnel, while the face supporting pressure shows little effect. The relationship between the grouting pressure and the maximum bending moment of adjacent first tunnel can be fitted by linear function. A grouting pressure equals to the lateral earth pressure is able the reduce the variation of the bending element of the first tunnel during the TBM-driven process of the second tunnel. The bending element of the first tunnel shows a typical lognormal relationship with the face supporting pressure during the TBM advance of the second tunnel. A critical cover-to-depth ratio, under which the horizontal and vertical soil arching effect vanishes, can be deduced to be within the range of 0.55–0.60.
Design, Fabrication, and Evaluation of Polyglycolic Acid Modules with Canals as Tissue Elements in Cellular-Assembly Technology
Authors: Ji Jingyuan , Pang Yuan , Sutoko Stephanie , Horimoto Yohei , Sun Wei , Niino Toshiki , Sakai Yasuyuki
Published: May 2020

The aim of the present study was to design and fabricate polyglycolic acid (PGA) modules on the basis of the Raschig ring as a tissue element for bottom–top tissue engineering to increase the feasibility of cellular-assembly technology. Three types of modules, namely, cylindrical, Raschig ring, and transverse-pore modules, with different numbers and orientations of canals, were designed and fabricated by modified selective-laser-sintering (SLS) technology. These modules maintained their structure in a flowing culture environment, and degradation did not create an acidic environment, hence promoting their ability to scale up to highly functional tissue. The modules were seeded with human hepatoma Hep G2 cells and cultured for 10 days. The transverse-pore modules were found to have the highest glucose consumption, albumin production, and cell viability among the three tested modules. Our study showed that the proposed module design provided better mass transfer and possessed the required mechanical strength to enable use in the construction of large tissue.
Ion Current Rectification in Extra-Long Nanofunnels
Authors: Repetto Diego , Angeli Elena , Pezzuoli Denise , Guida Patrizia , Firpo Giuseppe , Repetto Luca
Published: May 2020

Nanofluidic systems offer new functionalities for the development of high sensitivity biosensors, but many of the interesting electrokinetic phenomena taking place inside or in the proximity of nanostructures are still not fully characterized. Here, to better understand the accumulation phenomena observed in fluidic systems with asymmetric nanostructures, we study the distribution of the ion concentration inside a long (more than 90 µm) micrometric funnel terminating with a nanochannel. We show numerical simulations, based on the finite element method, and analyze how the ion distribution changes depending on the average concentration of the working solutions. We also report on the effect of surface charge on the ion distribution inside a long funnel and analyze how the phenomena of ion current rectification depend on the applied voltage and on the working solution concentration. Our results can be used in the design and implementation of high-performance concentrators, which, if combined with high sensitivity detectors, could drive the development of a new class of miniaturized biosensors characterized by an improved sensitivity.
A Method for Separating Multisource Partial Discharges in a Substation Based on Selected Bispectra of UHF Signals
Authors: He Zhimin , Hou Huijuan , Zang Yiming , Sheng Gehao , Jiang Xiuchen
Published: May 2020

A method for separating multisource partial discharges (PDs) in a substation is proposed based on selected bispectra of ultrahigh frequency (UHF) electromagnetic waves. Bispectra are sensitive to Gaussian noises and processes of symmetrical distribution. The phase information contained in bispectra can be useful and important for further signal processing. Bifrequencies where Fisher-like class separability measures between signals’ bispectra achieve their maximums are selected as characteristic parameters of the signals. Then, the selected bispectra are utilized for training the radial basis neural network to separate PD UHF signals in a substation. The method is used to analyze simulated UHF signals mixed with Gaussian white noise and frequency-fixed interference, and to separate PD UHF signals that are collected in a 500 kV substation. In order to prove the validity of the proposed separation method, the localization results are compared with the results calculated by time delay sequence, and the proposed separating algorithm is verified in the interference circumstances of a substation. However, the exact location of PD sources cannot be calculated according to the time delay sequence when the PD sources in a substation are close to each other or there are fewer than four antennas for receiving signals.
Data Augmentation Method by Applying Color Perturbation of Inverse PSNR and Geometric Transformations for Object Recognition Based on Deep Learning
Authors: Kim Eun Kyeong , Lee Hansoo , Kim Jin Yong , Kim Sungshin
Published: May 2020

Deep learning is applied in various manufacturing domains. To train a deep learning network, we must collect a sufficient amount of training data. However, it is difficult to collect image datasets required to train the networks to perform object recognition, especially because target items that are to be classified are generally excluded from existing databases, and the manual collection of images poses certain limitations. Therefore, to overcome the data deficiency that is present in many domains including manufacturing, we propose a method of generating new training images via image pre-processing steps, background elimination, target extraction while maintaining the ratio of the object size in the original image, color perturbation considering the predefined similarity between the original and generated images, geometric transformations, and transfer learning. Specifically, to demonstrate color perturbation and geometric transformations, we compare and analyze the experiments of each color space and each geometric transformation. The experimental results show that the proposed method can effectively augment the original data, correctly classify similar items, and improve the image classification accuracy. In addition, it also demonstrates that the effective data augmentation method is crucial when the amount of training data is small.
Non-Invasive Method for In-Service Induction Motor Efficiency Estimation Based on Sound Acquisition
Authors: César da Silva Júlio , Leite de Vasconcelos Lima Thyago , de Lucena Júnior José Anselmo , Jordão Lyra Gabriela , Vidal Souto Filipe , de Souza Pimentel Hugo , Antônio Belo Francisco , Cavalcante Lima Filho Abel
Published: May 2020

Induction motors (IMs) are present in practically all production processes and account for two-thirds of the energy consumption in industrial settings. Therefore, monitoring them is essential to prevent accidents, optimize production, and increase energy efficiency. Monitoring methods found in the literature require a certain level of invasiveness, causing some applications to be unfeasible. In the present study, a new completely non-invasive method implemented in an embedded system performs the embedded processing of the sound signal emitted by an in-service IM to estimate speed, torque, and efficiency. Motor speed is estimated from the analysis in the frequency domain using the Fourier Transform. Torque and efficiency are estimated from the speed and motor nameplate information. To perform the tests and validate the proposed method/system, a workbench with a controllable torque was used. The workbench was also equipped to allow the results to be compared with the airgap torque method. The results indicate a high accuracy for the nominal load (error of approximately 1%) in the measurement of the efficiency and torque, and a mean relative error of 0.2% for the speed.
Evolution of Microbial Composition and Enzymatic Activities during the Composting of Textile Waste
Authors: Biyada Saloua , Merzouki Mohammed , Dėmčėnko Taisija , Vasiliauskienė Dovilė , Urbonavičius Jaunius , Marčiulaitienė Eglė , Vasarevičius Saulius , Benlemlih Mohamed
Published: May 2020

The production of stable and mature compost often depends on the performance of microbes and their enzymatic activity. Environmental and nutritional conditions influence the characteristics of microbial communities and, therefore, the dynamics of major metabolic activities. Using three waste mixtures (textile waste mixed with either green, paper, or cardboard waste), the maturity of the compost produced was assessed by following the physico-chemical parameters and enzymatic activities provided by the microorganisms that were identified using next-generation sequencing (NGS). Among the three mixtures used, it was found that the two best mixtures showed C/N ratios of 16.30 and 16.96, total nitrogen of 1.37 and 1.39%, cellulase activities of 50.62 and 52.67 Ug−1, acid phosphatase activities of 38.81 and 68.77 Ug−1, and alkaline phosphatase activities of 51.12 and 56.86 Ug−1. In addition, several lignocellulosic species, together with those that are able to solubilize phosphate, were identified. Among those known for cellulase and acid/alkaline phosphatase activities, bacteria belonging to the Proteobacteria, Bacteroidetes, Actinobacteria, and Firmicutes phyla were shown. The presence of species belonging to the Ascomycota and Basidiomycota phyla of Fungi, which are known for their ability to produce cellulase and acid/alkaline phosphatases, was demonstrated. These findings provide a basis for the production of stable and mature compost based on textile waste.
Latitude and Topographical Dependence of Lightning Return Stroke Peak Current in Natural and Tower-Initiated Negative Ground Flashes
Authors: Cooray Vernon , Rubinstein Marcos , Rachidi Farhad
Published: May 2020

Experimental data show that the peak currents of first and subsequent lightning return strokes in negative ground flashes increase with decreasing latitude. In this paper, the reason for this dependence of peak return stroke current on latitude is explained using the fact that the height of the charge centers increases with decreasing latitude. Results show that in tropical regions where the height to the negative charge center is about 8 km, the median values of the first and the subsequent return stroke peak currents are about 42 kA and 15 kA, respectively. If the height to the charge center is larger than 8 km, the peak currents will also become larger. For example, if the location of the charge center is increased to about 9 km, the median values of the first and subsequent return stroke peak currents will increase to about 45 kA and 16 kA respectively. The same reasoning shows that, even in the same geographical region, the peak return stroke current may decrease as the elevation of the ground where the lightning strikes take place increases. The results also indicate that the peak subsequent return stroke current in tower-initiated negative lightning flashes decreases as the height of the tower increases. These theoretical predictions are in general agreement with the available experimental data.
Photoionization of KCs Molecule: Origin of the Structured Continuum?
Authors: Pichler Goran , Beuc Robert , Kokaj Jahja , Sarkisyan David , Jose Nimmy , Mathew Joseph
Published: May 2020

We report the experimental observation of photoionization bands of the KCs molecule in the deep ultraviolet spectral region between 200 and 420 nm. We discuss the origin of observed photoionization bands as stemming from the absorption from the ground state of the KCs molecule to the excited states of KCs+ molecule for which we used existing potential curves of the KCs+ molecule. An alternative explanation relies on the absorption from the ground state of the KCs molecule to the doubly excited states of the KCs** molecule, situated above the lowest molecular state of KCs+. The relevant potential curves of KCs** are not known yet, but all those KCs** potential curves are certainly autoionizing. However, these two photoionization pathways may interfere resulting in a special interference structured continuum, which is observed as complex bands.
The Use of Euterpe oleracea Mart. As a New Perspective for Disease Treatment and Prevention
Authors: de Almeida Magalhães Thalita Sévia Soares , de Oliveira Macedo Pollyana Cristina , Converti Attilio , Neves de Lima Ádley Antonini
Published: May 2020

Euterpe oleracea Mart. (EO), popularly known as açaí, belongs to the Arecaceae family and grows abundantly in Brazil. The fruit of this palm tree is widely used because of its anti-inflammatory and antioxidant properties. In this review, a search for literature and patent technological prospecting has been performed on the use of EO to treat and prevent diseases as well as to prepare pharmaceutical formulations. EO leaves, fruits, and oil stand out for their large number of pharmacological activities such as anti-inflammatory, antioxidant, antimicrobial, antinociceptive, anticancer, anti-atherogenic, and healing activities, protection against metabolic syndromes such as diabetes, hypertension, and hyperlipidemia, and protection of organs such as lung, kidney, liver, heart, and nervous system. While the phytochemical composition is intrinsically linked to identified biological activities, discoveries of the past decade concerning the use of this species have shown pharmacological alternatives mainly in the treatment and prevention of breast cancer and metabolic syndromes. Although studies and inventions on the use of EO though are believed to have been important in light of the pharmacological activities found, few clinical and toxicity tests have been performed. Nevertheless, with the increase of interest in EO, this species is believed to be only at the beginning of the breakthroughs in the development of promising products for the pharmaceutical industry.
Small Circular DNA Molecules as Triangular Scaffolds for the Growth of 3D Single Crystals
Authors: Wang Yu , Guo Xin , Kou Bo , Zhang Ling , Xiao Shou-Jun
Published: May 2020

DNA is a very useful molecule for the programmed self-assembly of 3D (three dimension) nanoscale structures. The organised 3D DNA assemblies and crystals enable scientists to conduct studies for many applications such as enzymatic catalysis, biological immune analysis and photoactivity. The first self-assembled 3D DNA single crystal was reported by Seeman and his colleagues, based on a rigid triangle tile with the tile side length of two turns. Till today, successful designs of 3D single crystals by means of programmed self-assembly are countable, and still remain as the most challenging task in DNA nanotechnology, due to the highly constrained conditions for rigid tiles and precise packing. We reported here the use of small circular DNA molecules instead of linear ones as the core triangle scaffold to grow 3D single crystals. Several crystallisation parameters were screened, DNA concentration, incubation time, water-vapour exchange speed, and pH of the sampling buffer. Several kinds of DNA single crystals with different morphologies were achieved in macroscale. The crystals can provide internal porosities for hosting guest molecules of Cy3 and Cy5 labelled triplex-forming oligonucleotides (TFOs). Success of small circular DNA molecules in self-assembling 3D single crystals encourages their use in DNA nanotechnology regarding the advantage of rigidity, stability, and flexibility of circular tiles.
Post-Treatment of Synthetic Polyphenolic 1,3,4 Oxadiazole Compound A3, Attenuated Ischemic Stroke-Induced Neuroinflammation and Neurodegeneration
Authors: Mohsin Alvi Arooj , Tariq Al Kury Lina , Umar Ijaz Muhammad , Ali Shah Fawad , Tariq Khan Muhammad , Sadiq Sheikh Ahmed , Nadeem Humaira , Khan Arif-ullah , Zeb Alam , Li Shupeng
Published: May 2020

Ischemic stroke is categorized by either permanent or transient blood flow obstruction, impeding the distribution of oxygen and essential nutrients to the brain. In this study, we examined the neuroprotective effects of compound A3, a synthetic polyphenolic drug product, against ischemic brain injury by employing an animal model of permanent middle cerebral artery occlusion (p-MCAO). Ischemic stroke induced significant elevation in the levels of reactive oxygen species and, ultimately, provoked inflammatory cascade. Here, we demonstrated that A3 upregulated the endogenous antioxidant enzymes, such as glutathione s-transferase (GST), glutathione (GSH), and reversed the ischemic-stroke-induced nitric oxide (NO) and lipid peroxidation (LPO) elevation in the peri-infarct cortical and striatal tissue, through the activation of endogenous antioxidant nuclear factor E2-related factor or nuclear factor erythroid 2 (Nrf2). In addition, A3 attenuated neuroinflammatory markers such as ionized calcium-binding adapter molecule-1 (Iba-1), cyclooxygenase-2 (COX-2), tumor necrotic factor-α (TNF-α), toll-like receptors (TLR4), and nuclear factor-κB (NF-κB) by down-regulating p-JNK as evidenced by immunohistochemical results. Moreover, treatment with A3 reduced the infarction area and neurobehavioral deficits. We employed ATRA to antagonize Nrf2, which abrogated the neuroprotective effects of A3 to further assess the possible involvement of the Nrf2 pathway, as demonstrated by increased infarction and hyperexpression of inflammatory markers. Together, our findings suggested that A3 could activate Nrf2, which in turn regulates the downstream antioxidants, eventually mitigating MCAO-induced neuroinflammation and neurodegeneration.
Autocrine TGF-β1 Maintains the Stability of Foxp3+ Regulatory T Cells via IL-12Rβ2 Downregulation
Authors: Choi Garam , Na Hyeongjin , Kuen Da-Sol , Kim Byung-Seok , Chung Yeonseok
Published: May 2020

Transforming growth factor beta 1 (TGF-β1) is an immunosuppresive cytokine that plays an essential role in immune homeostasis. It is well known that regulatory T (Treg) cells express TGF-β1; however, the role of autocrine TGF-β1 in the development, function, and stability of Treg cells remains poorly understood. We found that Treg cell-derived TGF-β1 was not required for the development of thymic Treg cells in mice, but played a role in the expression of latency-associated peptide and optimal suppression of naïve T cell proliferation in vitro. Moreover, the frequency of Treg cells was significantly reduced in the mesenteric lymph nodes of the Treg cell-specific TGF-β1-deficient mice, which was associated with increased frequency of IFN-γ-producers among Treg cells. TGF-β1-deficient Treg cells were more prone to express IFN-γ than TGF-β1-sufficient Treg cells in a dendritic cell-mediated stimulation in vitro as well as in an adoptive transfer study in vivo. Mechanistically, TGF-β1-deficient Treg cells expressed higher levels of Il12rb2 and were more sensitive to IL-12-induced conversion into IFN-γ-producing Treg cells or IFN-γ-producing exTreg cells than TGF-β1-sufficient Treg cells. Our findings demonstrate that autocrine TGF-β1 plays a critical role in the optimal suppressive activity and stability of Treg cells by downregulating IL-12R on Treg cells.
An Isoform of the Oncogenic Splice Variant AIMP2-DX2 Detected by a Novel Monoclonal Antibody
Authors: Kim Dae Gyu , Nguyen Thi Thu Ha , Kwon Nam Hoon , Sung Junsik , Lim Semi , Kang Eun-Joo , Lee Jihye , Seo Woo Young , Kim Arum , Chang Yoon Soo , Shim Hyunbo , Kim Sunghoon
Published: May 2020

AIMP2-DX2, an exon 2-deleted splice variant of AIMP2 (aminoacyl-tRNA synthetase-interacting multifunctional protein 2), is highly expressed in lung cancer and involved in tumor progression in vivo. Oncogenic function of AIMP2-DX2 and its correlation with poor prognosis of cancer patients have been well established; however, the application of this potentially important biomarker to cancer research and diagnosis has been hampered by a lack of antibodies specific for the splice variant, possibly due to the poor immunogenicity and/or stability of AIMP2-DX2. In this study a monoclonal antibody, H5, that specifically recognizes AIMP2-DX2 and its isoforms was generated via rabbit immunization and phage display techniques, using a short peptide corresponding to the exon 1/3 junction sequence as an antigen. Furthermore, based on mutagenesis, limited cleavage, and mass spectrometry studies, it is also suggested that the endogenous isoform of AIMP2-DX2 recognized by H5 is produced by proteolytic cleavage of 33 amino acids from N-terminus and is capable of inducing cell proliferation similarly to the uncleaved protein. H5 monoclonal antibody is applicable to enzyme-linked immunosorbent assay, immunoblot, immunofluorescence, and immunohistochemistry, and expected to be a valuable tool for detecting AIMP2-DX2 with high sensitivity and specificity for research and diagnostic purposes.
Extracellular Vesicles: Current Analytical Techniques for Detection and Quantification
Authors: Serrano-Pertierra Esther , Oliveira-Rodríguez Myriam , Matos María , Gutiérrez Gemma , Moyano Amanda , Salvador María , Rivas Montserrat , Blanco-López María Carmen
Published: May 2020

Since their first observation, understanding the biology of extracellular vesicles (EV) has been an important and challenging field of study. They play a key role in the intercellular communication and are involved in important physiological and pathological functions. Therefore, EV are considered as potential biomarkers for diagnosis, prognosis, and monitoring the response to treatment in some diseases. In addition, due to their properties, EV may be used for therapeutic purposes. In the study of EV, three major points have to be addressed: 1. How to isolate EV from cell culture supernatant/biological fluids, 2. how to detect them, and 3. how to characterize and quantify. In this review, we focus on the last two questions and provide the main analytical techniques up-to-date for detection and profiling of EV. We critically analyze the advantages and disadvantages of each one, aimed to be of relevance for all researchers working on EV biology and their potential applications.