bluuebunny/crossref_metadata_2025 huggingface dataset:
Bacterial Endotoxins and Their Role in Periparturient Diseases of Dairy Cows: Mucosal Vaccine Perspectives
Authors: Eckel Emily F. , Ametaj Burim N.
Published: May 2020

During the periparturient period there is a significant increase in the incidence of multiple metabolic and infectious diseases in dairy cows. Dairy cows are fed high-grain diets immediately after calving to support production of large amounts of milk. Mounting evidence indicates these types of diets are associated with the release of high amounts of endotoxins in the rumen fluid. If infected, the udder and uterus additionally become important sources of endotoxins during the postpartum period. There is increasing evidence that endotoxins translocate from rumen, uterus, or udder into the systemic circulation and trigger chronic low-grade inflammatory conditions associated with multiple diseases including fatty liver, mastitis, retained placenta, metritis, laminitis, displaced abomasum, milk fever, and downer cow syndrome. Interestingly, endotoxin-related diseases are triggered by a bacterial component and not by a specific bacterium. This makes prevention of these type of diseases different from classical infectious diseases. Prevention of translocation of endotoxins into the host systemic circulation needs to take priority and this could be achieved with a new approach: mucosal vaccination. In this review article, we discuss all the aforementioned issues in detail and also report some of our trials with regards to mucosal vaccination of periparturient dairy cows.
Antibody Tests in Detecting SARS-CoV-2 Infection: A Meta-Analysis
Authors: Kontou Panagiota I. , Braliou Georgia G. , Dimou Niki L. , Nikolopoulos Georgios , Bagos Pantelis G.
Published: May 2020

The emergence of Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 made imperative the need for diagnostic tests that can identify the infection. Although Nucleic Acid Test (NAT) is considered to be the gold standard, serological tests based on antibodies could be very helpful. However, individual studies are usually inconclusive, thus, a comparison of different tests is needed. We performed a systematic review and meta-analysis in PubMed, medRxiv and bioRxiv. We used the bivariate method for meta-analysis of diagnostic tests pooling sensitivities and specificities. We evaluated IgM and IgG tests based on Enzyme-linked immunosorbent assay (ELISA), Chemiluminescence Enzyme Immunoassays (CLIA), Fluorescence Immunoassays (FIA), and the Lateral Flow Immunoassays (LFIA). We identified 38 studies containing data from 7848 individuals. Tests using the S antigen are more sensitive than N antigen-based tests. IgG tests perform better compared to IgM ones and show better sensitivity when the samples were taken longer after the onset of symptoms. Moreover, a combined IgG/IgM test seems to be a better choice in terms of sensitivity than measuring either antibody alone. All methods yield high specificity with some of them (ELISA and LFIA) reaching levels around 99%. ELISA- and CLIA-based methods perform better in terms of sensitivity (90%–94%) followed by LFIA and FIA with sensitivities ranging from 80% to 89%. ELISA tests could be a safer choice at this stage of the pandemic. LFIA tests are more attractive for large seroprevalence studies but show lower sensitivity, and this should be taken into account when designing and performing seroprevalence studies.
Diagnostic Value of Imaging Methods in the Histological Four Grading of Hepatocellular Carcinoma
Authors: Wang Feiqian , Numata Kazushi , Nakano Masayuki , Tanabe Mikiko , Chuma Makoto , Nihonmatsu Hiromi , Nozaki Akito , Ogushi Katsuaki , Luo Wen , Ruan Litao , Okada Masahiro , Otani Masako , Inayama Yoshiaki , Maeda Shin
Published: May 2020

We attempted to establish an ultrasound (US) imaging-diagnostic system for histopathological grades of differentiation of hepatocellular carcinoma (HCC). We conducted a retrospective study of histopathologically confirmed 200 HCCs, classified as early (45 lesions), well- (31 lesions), moderately (68 lesions) or poorly differentiated (diff.) (56 lesions) HCCs. We performed grayscale US to estimate the presence/absence of halo and mosaic signs, Sonazoid contrast-enhanced US (CEUS) to determine vascularity (hypo/iso/hyper) of lesion in arterial and portal phase (PP), and echogenicity of lesion in post-vascular phase (PVP). All findings were of significance for the diagnosis of some (but not all) histological grades (p < 0.001–0.05). Combined findings with a relatively high diagnostic efficacy for early, poorly and moderately diff. HCC were a combination of absence of halo sign and isoechogenicity in PVP of CEUS (accuracy: 93.0%, AUC: 0.908), hypovascularity in PP (accuracy: 78.0%, area under the curve (AUC): 0.750), and a combination of isovascularity in PP and hypoechogenicity in PVP (accuracy: 75.0%, AUC: 0.739), respectively. On the other hand, neither any individual finding nor any combination of findings yielded an AUC of over 0.657 for the diagnosis of well-diff. HCC. Our study provides encouraging data on Sonazoid CEUS in the histological differential diagnosis of HCC, especially in early HCC, and the effectiveness of this imaging method should be further proved by prospective, large sample, multicenter studies.
Sonographic Pearls for Imaging the Brachial Plexus and Its Pathologies
Authors: Hsu Po-Cheng , Chang Ke-Vin , Mezian Kamal , Naňka Ondřej , Wu Wei-Ting , Yang Yi-Chiang , Meng Stefan , Ricci Vincenzo , Özçakar Levent
Published: May 2020

The brachial plexus (BP) is a complicated neural network, which may be affected by trauma, irradiation, neoplasm, infection, and autoimmune inflammatory diseases. Magnetic Resonance Imaging is the preferred diagnostic modality; however, it has the limitations of high cost and lack of portability. High-resolution ultrasound has recently emerged as an unparalleled diagnostic tool for diagnosing postganglionic lesions of the BP. Existing literature describes the technical skills needed for prompt ultrasound imaging and guided injections for the BP. However, it remains particularly challenging for beginners to navigate easily while scanning its different parts. To address this, we share several “clinical pearls” for the sonographic examination of the BP as well as its common pathologies.
Deep Learning-Based Morphological Classification of Human Sperm Heads
Authors: Iqbal Imran , Mustafa Ghulam , Ma Jinwen
Published: May 2020

Human infertility is considered as a serious disease of the reproductive system that affects more than 10% of couples across the globe and over 30% of the reported cases are related to men. The crucial step in the assessment of male infertility and subfertility is semen analysis that strongly depends on the sperm head morphology, i.e., the shape and size of the head of a spermatozoon. However, in medical diagnosis, the morphology of the sperm head is determined manually, and heavily depends on the expertise of the clinician. Moreover, this assessment as well as the morphological classification of human sperm heads are laborious and non-repeatable, and there is also a high degree of inter and intra-laboratory variability in the results. In order to overcome these problems, we propose a specialized convolutional neural network (CNN) architecture to accurately classify human sperm heads based on sperm images. It is carefully designed with several layers, and multiple filter sizes, but fewer filters and parameters to improve efficiency and effectiveness. It is demonstrated that our proposed architecture outperforms state-of-the-art methods, exhibiting 88% recall on the SCIAN dataset in the total agreement setting and 95% recall on the HuSHeM dataset for the classification of human sperm heads. Our proposed method shows the potential of deep learning to surpass embryologists in terms of reliability, throughput, and accuracy.
Role of Body-Fluid Biomarkers in Alzheimer’s Disease Diagnosis
Authors: Nguyen Thuy Trang , Ta Qui Thanh Hoai , Nguyen Thi Kim Oanh , Nguyen Thi Thuy Dung , Vo Van Giau
Published: May 2020

Alzheimer’s disease (AD) is a complex neurodegenerative disease that requires extremely specific biomarkers for its diagnosis. For current diagnostics capable of identifying AD, the development and validation of early stage biomarkers is a top research priority. Body-fluid biomarkers might closely reflect synaptic dysfunction in the brain and, thereby, could contribute to improving diagnostic accuracy and monitoring disease progression, and serve as markers for assessing the response to disease-modifying therapies at early onset. Here, we highlight current advances in the research on the capabilities of body-fluid biomarkers and their role in AD pathology. Then, we describe and discuss current applications of the potential biomarkers in clinical diagnostics in AD.
Improving Access to Diagnostics for Schistosomiasis Case Management in Oyo State, Nigeria: Barriers and Opportunities
Authors: Van G-Young , Onasanya Adeola , van Engelen Jo , Oladepo Oladimeji , Diehl Jan Carel
Published: May 2020

Schistosomiasis is one of the Neglected Tropical Diseases that affects over 200 million people worldwide, of which 29 million people in Nigeria. The principal strategy for schistosomiasis in Nigeria is a control and elimination program which comprises a school-based Mass Drug Administration (MDA) with limitations of high re-infection rates and the exclusion of high-risk populations. The World Health Organization (WHO) recommends guided case management of schistosomiasis (diagnostic tests or symptom-based detection plus treatment) at the Primary Health Care (PHC) level to ensure more comprehensive morbidity control. However, these require experienced personnel with sufficient knowledge of symptoms and functioning laboratory equipment. Little is known about where, by whom and how diagnosis is performed at health facilities within the case management of schistosomiasis in Nigeria. Furthermore, there is a paucity of information on patients’ health-seeking behaviour from the onset of disease symptoms until a cure is obtained. In this study, we describe both perspectives in Oyo state, Nigeria and address the barriers using adapted health-seeking stages and access framework. The opportunities for improving case management were identified, such as a prevalence study of high-risk groups, community education and screening, enhancing diagnostic capacity at the PHC through point-of-care diagnostics and strengthening the capability of health workers.
Deep Learning Based Automatic Malaria Parasite Detection from Blood Smear and Its Smartphone Based Application
Authors: Fuhad K. M. Faizullah , Tuba Jannat Ferdousey , Sarker Md. Rabiul Ali , Momen Sifat , Mohammed Nabeel , Rahman Tanzilur
Published: May 2020

Malaria is a life-threatening disease that is spread by the Plasmodium parasites. It is detected by trained microscopists who analyze microscopic blood smear images. Modern deep learning techniques may be used to do this analysis automatically. The need for the trained personnel can be greatly reduced with the development of an automatic accurate and efficient model. In this article, we propose an entirely automated Convolutional Neural Network (CNN) based model for the diagnosis of malaria from the microscopic blood smear images. A variety of techniques including knowledge distillation, data augmentation, Autoencoder, feature extraction by a CNN model and classified by Support Vector Machine (SVM) or K-Nearest Neighbors (KNN) are performed under three training procedures named general training, distillation training and autoencoder training to optimize and improve the model accuracy and inference performance. Our deep learning-based model can detect malarial parasites from microscopic images with an accuracy of 99.23% while requiring just over 4600 floating point operations. For practical validation of model efficiency, we have deployed the miniaturized model in different mobile phones and a server-backed web application. Data gathered from these environments show that the model can be used to perform inference under 1 s per sample in both offline (mobile only) and online (web application) mode, thus engendering confidence that such models may be deployed for efficient practical inferential systems.
Plasmodium falciparum Histidine-Rich Protein 2 and 3 Gene Deletions and Their Implications in Malaria Control
Authors: Nyataya Josphat , Waitumbi John , Mobegi Victor A. , Noreddin Ayman , El Zowalaty Mohamed E.
Published: May 2020

Malaria remains the biggest threat to public health, especially among pregnant women and young children in sub-Saharan Africa. Prompt and accurate diagnosis is critical for effective case management and detection of drug resistance. Conventionally, microscopy and rapid diagnostic tests (RDTs) are the tools of choice for malaria diagnosis. RDTs are simple to use and have been extensively used in the diagnosis of malaria among travelers to malaria-endemic regions, routine case management, and surveillance studies. Most RDTs target the histidine-rich protein (PfHRP) which is exclusively found in Plasmodium falciparum and a metabolic enzyme Plasmodium lactate dehydrogenase (pLDH) which is common among all Plasmodium species. Other RDTs incorporate the enzyme aldolase that is produced by all Plasmodium species. Recently, studies have reported false-negative RDTs primarily due to the deletion of the histidine-rich protein (pfhrp2 and pfhrp3) genes in field isolates of P. falciparum. Herein, we review published literature to establish pfhrp2/pfhrp3 deletions, the extent of these deletions in different geographical regions, and the implication in malaria control. We searched for publications on pfhrp2/pfhrp3 deletions and retrieved all publications that reported on this subject. Overall, 20 publications reported on pfhrp2/pfhrp3 deletions, and most of these studies were done in Central and South America, with very few in Asia and Africa. The few studies in Africa that reported on the occurrence of pfhrp2/pfhrp3 deletions rarely evaluated deletions on the flanking genes. More studies are required to evaluate the existence and extent of these gene deletions, whose presence may lead to delayed or missed treatment. This information will guide appropriate diagnostic approaches in the respective areas.
Comparison of Intraoral and Extraoral Digital Scanners: Evaluation of Surface Topography and Precision
Authors: Lee Sang J. , Kim Soo-Woo , Lee Joshua J. , Cheong Chan W.
Published: May 2020

The aim of this study was to evaluate the surface topography and the precision measurements of different intraoral and extraoral digital scanners. A reference model of a maxillary arch with four implant analogs was prepared and scanned by three intraoral and two extraoral scanners. The reference model was scanned fifteen times with each digital scanning system, investigating the surface topography and precision measurements for the same-arch and cross-arch measurements. The data was exported to 3D inspection and mesh-processing software (GOM Inspect, Braunschweig, Germany). Statistical analysis was performed using a one-way Analysis of Variance (ANOVA) with the Tukey method for pairwise comparisons. The effect of parameters on generating the surface topography was analyzed by Univariate Linear Regression Analysis. Of the scanner systems evaluated, iTero (IT) exhibited the most number of triangulation points, followed by Trios 3 Shape (TR) and Straumann Cares (SC). There were no significant differences observed in the surface topography when comparing flat and contoured surfaces, the anterior and posterior position, and interproximal areas. For the precision measurement in the same quadrant, no statistical difference was noted between intra- and extraoral scanners. However, the extraoral scanners showed substantially higher precision measurements for the cross-arch measurement. Surface topography did not correlate to precision. Rather, precision correlated with the scanning mechanism. For a quadrant scanning, both intraoral and extraoral scanners are recommended, but extraoral scanners are recommended for a full-arch scanning.
Optimization for Software Implementation of Fractional Calculus Numerical Methods in an Embedded System
Authors: Matusiak Mariusz
Published: May 2020

In this article, some practical software optimization methods for implementations of fractional order backward difference, sum, and differintegral operator based on Grünwald–Letnikov definition are presented. These numerical algorithms are of great interest in the context of the evaluation of fractional-order differential equations in embedded systems, due to their more convenient form compared to Caputo and Riemann–Liouville definitions or Laplace transforms, based on the discrete convolution operation. A well-known difficulty relates to the non-locality of the operator, implying continually increasing numbers of processed samples, which may reach the limits of available memory or lead to exceeding the desired computation time. In the study presented here, several promising software optimization techniques were analyzed and tested in the evaluation of the variable fractional-order backward difference and derivative on two different Arm® Cortex®-M architectures. Reductions in computation times of up to 75% and 87% were achieved compared to the initial implementation, depending on the type of Arm® core.
Systems with Size and Energy Polydispersity: From Glasses to Mosaic Crystals
Authors: Azizi Itay , Rabin Yitzhak
Published: May 2020

We use Langevin dynamics simulations to study dense 2d systems of particles with both size and energy polydispersity. We compare two types of bidisperse systems which differ in the correlation between particle size and interaction parameters: in one system big particles have high interaction parameters and small particles have low interaction parameters, while in the other system the situation is reversed. We study the different phases of the two systems and compare them to those of a system with size but not energy bidispersity. We show that, depending on the strength of interaction between big and small particles, cooling to low temperatures yields either homogeneous glasses or mosaic crystals. We find that systems with low mixing interaction, undergo partial freezing of one of the components at intermediate temperatures, and that while this phenomenon is energy-driven in both size and energy bidisperse systems, it is controlled by entropic effects in systems with size bidispersity only.
Improving Underwater Continuous-Variable Measurement-Device-Independent Quantum Key Distribution via Zero-Photon Catalysis
Authors: Wang Yuang , Zou Shanhua , Mao Yun , Guo Ying
Published: May 2020

Underwater quantumkey distribution (QKD) is tough but important formodern underwater communications in an insecure environment. It can guarantee secure underwater communication between submarines and enhance safety for critical network nodes. To enhance the performance of continuous-variable quantumkey distribution (CVQKD) underwater in terms ofmaximal transmission distance and secret key rate as well, we adopt measurement-device-independent (MDI) quantum key distribution with the zero-photon catalysis (ZPC) performed at the emitter of one side, which is the ZPC-based MDI-CVQKD. Numerical simulation shows that the ZPC-involved scheme, which is a Gaussian operation in essence, works better than the single photon subtraction (SPS)-involved scheme in the extreme asymmetric case. We find that the transmission of the ZPC-involved scheme is longer than that of the SPS-involved scheme. In addition, we consider the effects of temperature, salinity and solar elevation angle on the system performance in pure seawater. The maximal transmission distance decreases with the increase of temperature and the decrease of sunlight elevation angle, while it changes little over a broad range of salinity
Triple the Gamma—A Unifying Shrinkage Prior for Variance and Variable Selection in Sparse State Space and TVP Models
Authors: Cadonna Annalisa , Frühwirth-Schnatter Sylvia , Knaus Peter
Published: May 2020

Time-varying parameter (TVP) models are very flexible in capturing gradual changes in the effect of explanatory variables on the outcome variable. However, in particular when the number of explanatory variables is large, there is a known risk of overfitting and poor predictive performance, since the effect of some explanatory variables is constant over time. We propose a new prior for variance shrinkage in TVP models, called triple gamma. The triple gamma prior encompasses a number of priors that have been suggested previously, such as the Bayesian Lasso, the double gamma prior and the Horseshoe prior. We present the desirable properties of such a prior and its relationship to Bayesian Model Averaging for variance selection. The features of the triple gamma prior are then illustrated in the context of time varying parameter vector autoregressive models, both for simulated dataset and for a series of macroeconomics variables in the Euro Area.
Molybdenum-Suboxide Thin Films as Anode Layers in Planar Lithium Microbatteries
Authors: Lakshmi-Narayana Ambadi , Hussain Obili M. , Ramana Chintalapalle V. , Camacho-Lopez Marco , Abdel-Ghany Ashraf , Hashem Ahmed , Mauger Alain , Julien Christian M.
Published: May 2020

In this paper, we investigate the effects of operational conditions on structural, electronic and electrochemical properties on molybdenum suboxides (MoO3-δ) thin films. The films are prepared using pulsed-laser deposition by varying the deposition temperature (Ts), laser fluence (Φ), the partial oxygen pressure (PO2) and annealing temperature (Ta). We find that three classes of samples are obtained with different degrees of stoichiometric deviation without post-treatment: (i) amorphous MoO3-δ (δ < 0.05) (ii) nearly-stoichiometric samples (δ ≈ 0) and (iii) suboxides MoO3-δ (δ > 0.05). The suboxide films 0.05 ≤ δ ≤ 0.25 deposited on Au/Ti/SiO2/flexible-Si substrates with appropriate processing conditions show high electrochemical performance as an anode layer for lithium planar microbatteries. In the realm of simple synthesis, the MoO3-δ film deposited at 450 °C under oxygen pressure of 13 Pa is a mixture of α-MoO3 and Mo8O23 phases (15:85). The electrochemical test of the 0.15MoO3-0.85Mo8O23 film shows a specific capacity of 484 µAh cm−2 µm−1 after 100 cycles of charge-discharge at a constant current of 0.5 A cm−2 in the potential range 3.0-0.05 V.
Experimental Transmission of Digital Data Coded on Electrical Carriers at 2.1 GHz and 4.2 GHz by Using a Microwave Photonic Filter
Authors: Correa-Mena Ana Gabriela , Vera-Marquina Alicia , García-Juárez Alejandro , Rodríguez-Asomoza Jorge , Zaldívar-Huerta Ignacio Enrique
Published: May 2020

This paper proposes and demonstrates the use of filtered microwave band-pass windows situated at 2.1 GHz and 4.2 GHz as electrical carriers to transmit digital signals. The use of an appropriate microwave photonic filter (MPF) allows for the generation of the microwave band-pass windows. The key parameters of the filtering effect are the intermodal separation of a multimode laser diode (MLD), the chromatic dispersion parameter of the optical link, and its own length. Experimentally, it is demonstrated that the filtered band-pass windows can be used as electrical carriers to transmit digital signals at frequencies of 50 MHz, 100 MHz, and 150 MHz over 25.31 km of single-mode-standard-fiber (SM-SF). The quality Q-factor, jitter, and bit-error-rate are the parameters that allow for the evaluation of the quality of the digital signal transmission. The obtained results allow for the proposition of this photonic architecture in a passive optical network (PON) to distribute services like Internet Protocol (IP) telephony, internet, streaming video, and high definition television.
Assessment of Head Impacts and Muscle Activity in Soccer Using a T3 Inertial Sensor and a Portable Electromyography (EMG) System: A Preliminary Study
Authors: Worsey Matthew , Jones Bethany , Cervantes Andres , Chauvet Sabrina , Thiel David , Espinosa Hugo
Published: May 2020

Heading the ball is an important skill in soccer. Head impacts are of concern because of the potential adverse health effects. Many elite players now wear GPS (that include inertial monitoring units) on the upper spine for location tracking and workload measurement. By measuring the maximum acceleration of the head and the upper spine, we calculated the acceleration ratio as an attenuation index for participants (n = 8) of different skill levels during a front heading activity. This would allow for in-field estimates of head impacts to be made and concussive events detected. For novice participants, the ratio was as high as 8.3 (mean value 5.0 ± 1.8), whereas, for experienced players, the mean ratio was 3.2 ± 1.5. Elite players stiffen the neck muscles to increase the ball velocity and so the torso acts as a support structure. Electromyography (EMG) signals that were recorded from the neck and shoulder before and after a training intervention showed a major increase in mean average muscle activity (146%, p = 3.39 × 10−6). This was accompanied by a major decrease in acceleration ratio (34.41%, p = 0.008). The average head-ball impact velocity was 1.95 ± 0.53 m/s determined while using optical motion capture. For this low velocity, the impact force was 102 ± 19 N, 13% of the published concussive force. The voluntary action of neck muscles decreases isolated head movements during heading. Coaches and trainers may use this evidence in their development of junior players.
A Mobile Augmented Reality System for the Real-Time Visualization of Pipes in Point Cloud Data with a Depth Sensor
Authors: Jin Young-Hoon , Hwang In-Tae , Lee Won-Hyung
Published: May 2020

Augmented reality (AR) is a useful visualization technology that displays information by adding virtual images to the real world. In AR systems that require three-dimensional information, point cloud data is easy to use after real-time acquisition, however, it is difficult to measure and visualize real-time objects due to the large amount of data and a matching process. In this paper we explored a method of estimating pipes from point cloud data and visualizing them in real-time through augmented reality devices. In general, pipe estimation in a point cloud uses a Hough transform and is performed through a preprocessing process, such as noise filtering, normal estimation, or segmentation. However, there is a disadvantage in that the execution time is slow due to a large amount of computation. Therefore, for the real-time visualization in augmented reality devices, the fast cylinder matching method using random sample consensus (RANSAC) is required. In this paper, we proposed parallel processing, multiple frames, adjustable scale, and error correction for real-time visualization. The real-time visualization method through the augmented reality device obtained a depth image from the sensor and configured a uniform point cloud using a voxel grid algorithm. The constructed data was analyzed according to the fast cylinder matching method using RANSAC. The real-time visualization method through augmented reality devices is expected to be used to identify problems, such as the sagging of pipes, through real-time measurements at plant sites due to the spread of various AR devices.
Analysis of an Operating State of the Innovative Capacitive Power Transmission System with Sliding Receiver Supplied by the Class-E Inverter
Authors: Ludowicz Wojciech , Pietrowski Wojciech , Wojciechowski Rafal M.
Published: May 2020

In recent years, there has been a significant increase in interest in applications of wireless power transmission (WPT). The development of electromobility and consumer electronics creates a need for newer and more effective systems for wireless charging. In spite of the unceasing progress in the research area of wireless energy transmission systems, the significant problem of the motion of the receiver has still not been solved. In this work, an innovative capacitive power transmission (CPT) system with a sliding receiver has been proposed, which enables efficient energy transmission regardless of the location of the receiver system relative to the transmitter system. The analysis of the operating states of the considered system has been conducted with the use of an in-house algorithm, in which the parameters of the equivalent circuit of the CPT system have been implemented. The parameters have been determined by the finite element method (FEM) using the electric scalar potential V. The system of capacitive power transmission was supplied from an E-class inverter. Selected results of calculations of the considered system have been presented and discussed.
Generation of Multi-Scroll Chaotic Attractors from a Jerk Circuit with a Special Form of a Sine Function
Authors: Ding Pengfei , Feng Xiaoyi
Published: May 2020

A novel chaotic system for generating multi-scroll attractors based on a Jerk circuit using a special form of a sine function (SFSF) is proposed in this paper, and the SFSF is the product of a sine function and a sign function. Although there are infinite equilibrium points in this system, the scroll number of the generated chaotic attractors is certain under appropriate system parameters. The dynamical properties of the proposed chaotic system are studied through Lyapunov exponents, phase portraits, and bifurcation diagrams. It is found that the scroll number of the chaotic system in the left and right part of the x-y plane can be determined arbitrarily by adjusting the values of the parameters in the SFSF, and the size of attractors is dominated by the frequency of the SFSF. Finally, an electronic circuit of the proposed chaotic system is implemented on Pspice, and the simulation results of electronic circuit are in agreement with the numerical ones.
K-ONE Playground: Reconfigurable Clusters for a Cloud-Native Testbed
Authors: Shin Jun-Sik , Kim JongWon
Published: May 2020

Cloud-native computing with edge clouds is dominating the current computing paradigm. To prepare a flexible testbed for this paradigm, the build-out of K-ONE Playground started in 2015 based on the concept of SmartXPlayground. K-ONE Playground targets a multi-site edge cloud testbed based on the concept of composable playground that can flexibly compose physical, virtual, container resources from a resource pool to user-defined infrastructure. SmartX Playground should properly handle demanding requirements for a composable playground. In this paper, we propose a unique design of reconfigurable clusters, which can provide physical and virtual resources ready for cloud-native DevOps services. We also describe a detailed implementation of the reconfigurable cluster for the real-world infrastructure of K-ONE Playground. Finally, we verify its feasibility with operations and practical examples of cloud-native service development.
Sinusoidal Oscillators Operating at Frequencies Exceeding Unity-Gain Bandwidth of Operational Amplifiers
Authors: Ulansky Vladimir , Raza Ahmed
Published: May 2020

This paper proposes a novel operational amplifier (OPA) voltage-controlled oscillator (VCO) circuits on the basis of impedance converters. The VCO can operate over a frequency range exceeding unity-gain bandwidth due to the location of the tank circuit, not at the output of the OPA, but at the noninverting input. The paper presents the mathematical modeling of oscillated amplitude and start-up conditions. The simulation results confirm the theoretical achievements. The designed and simulated VCO uses an ultra-low noise wideband OPA LMH6629MF, covers a frequency band between 0.830 GHz and 1.429 GHz, and exhibits a maximum in-band total harmonic distortion (THD) of 1.7%. It has a maximum in-band phase noise of −139.3 dBc/Hz at 100 kHz offset frequency and has an outstanding value of a standard figure of merit (FoM) of −198.6 dBc/Hz. The zero-peak amplitude of output voltage is from 3.2 V to 4 V for all generated frequencies at a supply voltage of ±5 V. The fabricated prototype-oscillator based on OPA LMH6624 operates at a frequency of 583.1 MHz with a power level of 0 dBm.
A Robust Structured Tracker Using Local Deep Features
Authors: Javanmardi Mohammadreza , Farzaneh Amir Hossein , Qi Xiaojun
Published: May 2020

Deep features extracted from convolutional neural networks have been recently utilized in visual tracking to obtain a generic and semantic representation of target candidates. In this paper, we propose a robust structured tracker using local deep features (STLDF). This tracker exploits the deep features of local patches inside target candidates and sparsely represents them by a set of templates in the particle filter framework. The proposed STLDF utilizes a new optimization model, which employs a group-sparsity regularization term to adopt local and spatial information of the target candidates and attain the spatial layout structure among them. To solve the optimization model, we propose an efficient and fast numerical algorithm that consists of two subproblems with the close-form solutions. Different evaluations in terms of success and precision on the benchmarks of challenging image sequences (e.g., OTB50 and OTB100) demonstrate the superior performance of the STLDF against several state-of-the-art trackers.
Nonlinear Voltage Control for Three-Phase DC-AC Converters in Hybrid Systems: An Application of the PI-PBC Method
Authors: Serra Federico M. , Fernández Lucas M. , Montoya Oscar D. , Gil-González Walter , Hernández Jesus C.
Published: May 2020

In this paper, a proportional-integral passivity-based controller (PI-PBC) is proposed to regulate the amplitude and frequency of the three-phase output voltage in a direct-current alternating-current (DC-AC) converter with an LC filter. This converter is used to supply energy to AC loads in hybrid renewable based systems. The proposed strategy uses the well-known proportional-integral (PI) actions and guarantees the stability of the system by means of the Lyapunov theory. The proposed controller continues to maintain the simplicity and robustness of the PI controls using the Hamiltonian representation of the system, thereby ensuring stability and producing improvements in the performance. The performance of the proposed controller was validated based on simulation and experimental results after considering parametric variations and comparing them with classical approaches.
Combustion Instability Monitoring through Deep-Learning-Based Classification of Sequential High-Speed Flame Images
Authors: Choi Ouk , Choi Jongwun , Kim Namkeun , Lee Min Chul
Published: May 2020

In this study, novel deep learning models based on high-speed flame images are proposed to diagnose the combustion instability of a gas turbine. Two different network layers that can be combined with any existing backbone network are established—(1) An early-fusion layer that can learn to extract the power spectral density of subsequent image frames, which is time-invariant under certain conditions. (2) A late-fusion layer which combines the outputs of a backbone network at different time steps to predict the current combustion state. The performance of the proposed models is validated by the dataset of high speed flame images, which have been obtained in a gas turbine combustor during the transient process from stable condition to unstable condition and vice versa. Excellent performance is achieved for all test cases with high accuracy of 95.1–98.6% and a short processing time of 5.2–12.2 ms. Interestingly, simply increasing the number of input images is as competitive as combining the proposed early-fusion layer to a backbone network. In addition, using handcrafted weights for the late-fusion layer is shown to be more effective than using learned weights. From the results, the best combination is selected as the ResNet-18 model combined with our proposed fusion layers over 16 time-steps. The proposed deep learning method is proven as a potential tool for combustion instability identification and expected to be a promising tool for combustion instability prediction as well.
Multi-Objective Optimal Scheduling of a Hybrid Ferry with Shore-to-Ship Power Supply Considering Energy Storage Degradation
Authors: Hein Kyaw , Yan Xu , Wilson Gary
Published: May 2020

To improve the operation efficiency and reduce the emission of a solar power integrated hybrid ferry with shore-to-ship (S2S) power supply, a two-stage multi-objective optimal operation scheduling method is proposed. It aims to optimize the two conflicting objectives, operation cost (fuel cost of diesel generators (DGs), carbon dioxide (CO2) emission tax and S2S power exchange) and energy storage (ES/ESS) degradation cost, based on the preference of the vessel operator and solar photovoltaic (PV) power output. For the day-ahead optimization, interval forecast data of the PV is used to map the solution space of the objectives with different sets of weight assignment. The solution space from the day-ahead optimization is used as a guide to determine the operating point of the hour-ahead optimization. As for the hour-ahead scheduling, more accurate short-lead time forecast data is used for the optimal operation scheduling. A detailed case study is carried out and the result indicates the operation flexibility improvement of the hybrid vessel. The case study also provides more in-depth information on the dispatching scheme and it is especially important if there are conflicting objectives in the optimization model.
Localized and Moderate Phosphorus Application Improves Plant Growth and Phosphorus Accumulation in Rosa multiflora Thunb. ex Murr. via Efficient Root System Development
Authors: Ma Qinghua , Chen Lin , Du Manyi , Zhang Yongan , Zhang Yaoxiang
Published: May 2020

Roots have high plasticity with the ability to adapt to heterogeneous nutrient distribution, but little is known about the effects of phosphorus (P) supply methods and levels on Rosa multiflora Thunb. ex Murr. root growth and nutrient accumulation. A pot study was conducted with two P supply methods (mixed and localized application) and three levels (P-deficient, P-moderate and P-adequate). The results showed that with localized application, P-deficient and P-moderate treatments significantly improved total root length, total surface area, total length of fine roots, shoot DW and total P accumulation in Rosa multiflora compared with their respective mixed application at 45 days after being transplanted (DAT) and 92 DAT; for P-adequate supply, the same trends were observed at 45 DAT, but not at 92 DAT. At 92 DAT, with localized application, when P levels increased from P-deficient to P-moderate, total P accumulation increased by 43.3%; but when P levels increased from P-moderate to P-adequate, no effect was observed. Furthermore, higher P accumulation in leaves was observed in localized P-moderate condition; decreased P uptake per root dry weight and greater root/shoot ratio were observed in localized P-adequate at 92 DAT. Total P accumulation was positively correlated with total root length and root surface area (R2: 0.68~0.94). There was a significant interaction effect among treatment days, P supply methods and levels (p ≤ 0.05) on shoot DW, root DW, root/shoot ratio and total P accumulation. These findings indicated that localized and moderate P supply appear efficient for improving R. multiflora growth and P accumulation via efficient root system development.
A Bibliometric Overview of Twitter-Related Studies Indexed in Web of Science
Authors: Yu Jingyuan , Muñoz-Justicia Juan
Published: May 2020

Twitter has been one of the most popular social network sites for academic research; the main objective of this study was to update the current knowledge boundary surrounding Twitter-related investigations and, further, identify the major research topics and analyze their evolution across time. A bibliometric analysis has been applied in this article: we retrieved 19,205 Twitter-related academic articles from Web of Science after several steps of data cleaning and preparation. The R package “Bibliometrix” was mainly used in analyzing this content. Our study has two sections, and performance analysis contains 5 categories (Annual Scientific Production, Most Relevant Sources, Most Productive Authors, Most Cited Publications, Most Relevant Keywords.). The science mapping included country collaboration analysis and thematic analysis. We highlight our thematic analysis by splitting the whole bibliographic dataset into three temporal periods, thus a thematic evolution across time has been presented. This study is one of the most comprehensive bibliometric overview in analyzing Twitter-related studies by far. We proceed to explain how the results will benefit the understanding of current academic research interests on the social media giant.
An Infant Milk Formula Supplemented with Heat-Treated Probiotic Bifidobacterium animalis subsp. lactis CECT 8145, Reduces Fat Deposition in C. elegans and Augments Acetate and Lactate in a Fermented Infant Slurry
Authors: Silva Ángela , Gonzalez Nuria , Terrén Ana , García Antonio , Martinez-Blanch Juan Francisco , Illescas Vanessa , Morales Javier , Maroto Marcos , Genovés Salvador , Ramón Daniel , Martorell Patricia , Chenoll Empar
Published: May 2020

Pediatric obesity has a growing health and socio-economical impact due to cardiovascular and metabolic complications in adult life. Some recent studies suggest that live or heat-treated probiotics have beneficial effects in preventing fat deposition and obesity in preclinical and clinical sets. Here, we have explored the effects of heat-treated probiotic Bifidobacterium animalis subsp. lactis CECT 8145 (HT-BPL1), added as a supplement on an infant milk formula (HT-BPL1-IN), on Caenorhabditis elegans fat deposition and short-chain fatty acids (SCFAs) and lactate, using fermented baby fecal slurries. We have found that HT-BPL1-IN significantly reduced fat deposition in C. elegans, at the time it drastically augmented the generation of some SCFAs, particulary acetate and organic acid lactate. Data suggest that heat-treated BPL1 maintains its functional activities when added to an infant powder milk formula.
Effect of Packaging and Coating Technique on Postharvest Quality and Shelf Life of Raphanus sativus L. and Hibiscus sabdariffa L. Microgreens
Authors: Ghoora Manjula D. , Srividya Nagarajan
Published: May 2020

Microgreens are highly respiring produce characterized by a relatively short shelf-life. In this study, the efficacy of two types of macro-perforated packaging, PET clamshell (PET–CS) and LDPE self-seal bag (LDPE–SSB), was assessed on the postharvest quality and shelf life of radish (RaS) and roselle (HbS) microgreens stored at 5 °C. Pre-harvest spray treatment (AGSC) was compared with postharvest dip coating (AGDC) using Aloe vera gel (AG) for the first time in microgreens for postharvest quality improvement. PET–CS had a lower physiological loss in weight (PLW), respiration rate (RR), electrolyte leakage (EL), microbial counts (MCs), and higher overall acceptability (OA) than LDPE–SSB. AG-coated microgreens had significantly (p ≤ 0.05) lesser deteriorative postharvest changes and higher ascorbic acid content than uncoated control. AGSC maintained better OA and postharvest quality than AGDC, especially at the end of the study period in terms of reducing EL, retaining greenness (−a*), and chroma value in HbS microgreens. In RaS microgreens, AGSC helped to maintain lower PLW, MC, and higher ascorbic acid levels. AGSC could be suggested as an eco-friendly ergonomic pre-harvest treatment along with PET–CS for enhancement of postharvest quality and shelf life in RaS and HbS microgreens, with a tremendous potential to be extended to other microgreens.
Consumers’ Attitude to Consumption of Rabbit Meat in Eight Countries Depending on the Production Method and Its Purchase Form
Authors: Szendrő Katalin , Szabó-Szentgróti Eszter , Szigeti Orsolya
Published: May 2020

The study’s aim was to investigate the consumers’ attitude to their preference of rabbit meat in eight countries depending on the production method and its purchase form. In Spain and China almost all factors got low scores. High scores (above 4 out of 5) for origin were found in Italy, France, Poland, Hungary and Brazil. The importance of feeding was highlighted in Italy, Poland, Hungary and Mexico. High values were received for housing conditions in Italy, Poland, Hungary and Mexico. The level of processing was the most important in China and Brazil, while the slaughtering method was considered the most important in Brazil and Mexico. Breed received the lowest score in almost all countries. The preference of fresh meat was the highest (above 50%) in Spain, France and Mexico, and that of frozen in Brazil and Mexico (about 20%). The highest preference for a whole carcass (above 50%) was given by the respondents in France and Mexico. Thigh was mostly preferred in France whereas consumers preferred loin in Mexico. Roasted, smoked and semi-finished forms were mostly favored in Mexico. It can be concluded that the preference of respondents depended on the country. Preferences were different among the Mediterranean countries, and also Latin American countries.
Assessment of Direct Normal Irradiance Forecasts Based on IFS/ECMWF Data and Observations in the South of Portugal
Authors: Perdigão João , Canhoto Paulo , Salgado Rui , Costa Maria João
Published: May 2020

Direct Normal Irradiance (DNI) predictions obtained from the Integrated Forecasting System of the European Centre for Medium-Range Weather Forecast (IFS/ECMWF) were compared against ground-based observational data for one location at the south of Portugal (Évora). Hourly and daily DNI values were analyzed for different temporal forecast horizons (1 to 3 days ahead) and results show that the IFS/ECMWF slightly overestimates DNI for the period of analysis (1 August 2018 until 31 July 2019) with a fairly good agreement between model and observations. Hourly basis evaluation shows relatively high errors, independently of the forecast day. Root mean square error increases as the forecast time increases with a relative error of ~45% between the first and the last forecast. Similar patterns are observed in the daily analysis with comparable magnitude errors. The correlation coefficients between forecast and observed data are above 0.7 for both hourly and daily data. A methodology based on a new DNI attenuation Index (DAI) was developed to estimate cloud fraction from hourly values integrated over a day and, with that, to correlate the accuracy of the forecast with sky conditions. This correlation with DAI reveals that in IFS/ECMWF model, the atmosphere as being more transparent than reality since cloud cover is underestimated in the majority of the months of the year, taking the ground-based measurements as a reference. The use of the DAI estimator confirms that the errors in IFS/ECMWF are larger under cloudy skies than under clear sky. The development and application of a post-processing methodology improves the DNI predictions from the IFS/ECMWF outputs, with a decrease of error of the order of ~30%, when compared with raw data.