bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and Characterization of VHF Band Small Antenna Using CRLH Transmission Line and Non-Foster Matching Circuit
Authors: Lee Soyeong , Lee Jonghyup , Choi Seongro , Lee Yong-Hyeok , Chung Jae-Young , Hwang Keum Cheol , Park Yong Bae
Published: September 2020

In this paper, we propose an electrically small antenna consisting of a composite right/left-handed (CRLH) transmission line (TL) and a non-Foster matching circuit. An interdigital capacitor (IDC) and spiral inductor are used to fabricate the very high frequency (VHF) band antenna based on CRLH TL. The size of the proposed antenna is as small as 0.025 × 0.014 × 0.0008 λ at 145.5 MHz using the zeroth-order resonant generated by the CRLH TL. The antenna operation bandwidth is extended by the non-Foster circuit (NFC) consisting of a pair of transistors in a cross-coupled manner. An antenna prototype is fabricated and the input impedance, the received power, and gain of the proposed antenna are measured. The results show that the broadband characteristic is maintained while the form factor is extremely small compared to the wavelength. The average received power enhancement and increased bandwidth of antenna are 17.3 dB and 335.5 MHz (from 249.2–268.2 to 145.5–500 MHz), respectively. The calculated gain of the proposed antenna with the non-Foster is about −45 dBi at 155 MHz. The proposed antenna can be considered as a potential candidate of a low-profile antenna for military ground communications at the VHF band.
Evaluation of Phenolic Compounds and Carotenoids Content and Mycotoxins Occurrence in Grains of Seventeen Barley and Eight Oat Cultivars Grown under Organic Management
Authors: Kazimierczak Renata , Średnicka-Tober Dominika , Leszczyńska Danuta , Nowacka Anna , Hallmann Ewelina , Barański Marcin , Kopczyńska Klaudia , Gnusowski Bogusław
Published: September 2020

In recent decades, organic farming based on natural means and methods of production is gaining more and more popularity. It is due to the growing awareness of the society regarding the harmfulness of chemicals used in intensive agriculture, which influences the growing interest of both producers and consumers in organic food. Searching for plant cultivars performing best under organic management in terms of crop quality is one of the important research topics of the recent years. The aim of the present study was therefore to compare 8 oat and 17 barley cultivars grown in identical organic production conditions in terms of polyphenols and carotenoids contents and the mycotoxins contamination in grains. The analyses of bioactive compounds were performed using HPLC and the mycotoxins occurrence using LC-MS/MS methods. Among the barley cultivars studied, the grains of SU Lolek, Rubaszek and Podarek accumulated the highest content of polyphenols. Grain of Soldo cultivar was richest in carotenoids, but at the same time most of the mycotoxins identified within the study were found in the grains of this cultivar. In the case of oat, the highest content of polyphenols was found in the grain of Harnaś, Nawigator and Arden cultivars, while Pascal and Amant grain was richest in carotenoids. Among all the oat cultivars tested, only Amant grain was free from the studied mycotoxins. These findings are important for producers as well as consumers, who search for quality organic foods.
Electromagnetic Induction Imaging with Atomic Magnetometers: Progress and Perspectives
Authors: Marmugi Luca , Renzoni Ferruccio
Published: September 2020

Electromagnetic induction imaging (EMI) allows mapping of the conductivity of target objects and, when combined with appropriate algorithms, the generation of full 3D tomographic images. Despite its tremendous potential, and the wealth of possible applications, the use of EMI has essentially been limited to eddy current testing for monitoring of corrosion and welding in metallic structures. The present work reviews the factors hindering the progress of electromagnetic induction imaging and highlights how the use of atomic magnetometers overcame some of them, opening the path to real world applications of EMI. Perspectives for further developments are discussed.
State of Charge Estimation for Lithium-Ion Power Battery Based on H-Infinity Filter Algorithm
Authors: Li Lan , Hu Minghui , Xu Yidan , Fu Chunyun , Jin Guoqing , Li Zonghua
Published: September 2020

To accurately estimate the state of charge (SOC) of lithium-ion power batteries in the event of errors in the battery model or unknown external noise, an SOC estimation method based on the H-infinity filter (HIF) algorithm is proposed in this paper. Firstly, a fractional-order battery model based on a dual polarization equivalent circuit model is established. Then, the parameters of the fractional-order battery model are identified by the hybrid particle swarm optimization (HPSO) algorithm, based on a genetic crossover factor. Finally, the accuracy of the SOC estimation results of the lithium-ion batteries, using the HIF algorithm and extended Kalman filter (EKF) algorithm, are verified and compared under three conditions: uncertain measurement accuracy, uncertain SOC initial value, and uncertain application conditions. The simulation results show that the SOC estimation method based on HIF can ensure that the SOC estimation error value fluctuates within ±0.02 in any case, and is slightly affected by environmental and other factors. It provides a way to improve the accuracy of SOC estimation in a battery management system.
Deterministic and Explicit: A Quantitative Characterization of the Matrix and Collagen Influence on the Stiffening of Peripheral Nerves Under Stretch
Authors: Sergi Pier Nicola
Published: September 2020

The structural organization of peripheral nerves enables them to adapt to different body postures and movements by varying their stiffness. Indeed, they could become either compliant or stiff in response to the amount of external solicitation. In this work, the global response of nerves to axial stretch was deterministically derived from the interplay between the main structural constituents of the nerve connective tissue. In particular, a theoretical framework was provided to explicitly decouple the action of the ground matrix and the contribution of the collagen fibrils on the macroscopic stiffening of stretched nerves. To test the overall suitability of this approach, as a matter of principle, the change of the shape of relevant curves was investigated for changes of numerical parameters, while a further sensitivity study was performed to better understand the dependence on them. In addition, dimensionless stress and curvature were used to quantitatively account for both the matrix and the fibril actions. Finally, the proposed framework was used to investigate the stiffening phenomenon in different nerve specimens. More specifically, the proposed approach was able to explicitly and deterministically model the nerve stiffening of porcine peroneal and canine vagus nerves, closely reproducing (R2>0.997) the experimental data.
Hydrometallurgical Extraction of Li and Co from LiCoO2 Particles–Experimental and Modeling
Authors: Cerrillo-Gonzalez Maria del Mar , Villen-Guzman Maria , Acedo-Bueno Luis Fernando , Rodriguez-Maroto Jose Miguel , Paz-Garcia Juan Manuel
Published: September 2020

The use of lithium-ion batteries as energy storage in portable electronics and electric vehicles is increasing rapidly, which involves the consequent increase of battery waste. Hence, the development of reusing and recycling techniques is important to minimize the environmental impact of these residues and favor the circular economy goal. This paper presents experimental and modeling results for the hydrometallurgical treatment for recycling LiCoO2 cathodes from lithium-ion batteries. Previous experimental results for hydrometallurgical extraction showed that acidic leaching of LiCoO2 particles produced a non-stoichiometric extraction of lithium and cobalt. Furthermore, the maximum lithium extraction obtained experimentally seemed to be limited, reaching values of approximately 65–70%. In this paper, a physicochemical model is presented aiming to increase the understanding of the leaching process and the aforementioned limitations. The model describes the heterogeneous solid–liquid extraction mechanism and kinetics of LiCoO2 particles under a weakly reducing environment. The model presented here sets the basis for a more general theoretical framework that would describe the process under different acidic and reducing conditions. The model is validated with two sets of experiments at different conditions of acid concentration (0.1 and 2.5 M HCl) and solid to liquid ratio (5 and 50 g L−1). The COMSOL Multiphysics program was used to adjust the parameters in the kinetic model with the experimental results.
Planetary Gearbox Fault Diagnosis Based on ICEEMD-Time-Frequency Information Entropy and VPMCD
Authors: Wang Yihan , Fan Zhonghui , Liu Hongmei , Gao Xin
Published: September 2020

Planetary gearboxes are more and more widely used in large and complex construction machinery such as those used in aviation, aerospace fields, and so on. However, the movement of the gear is a typical complex motion and is often under variable conditions in real environments, which may make vibration signals of planetary gearboxes nonlinear and nonstationary. It is more difficult and complex to achieve fault diagnosis than to fix the axis gearboxes effectively. A fault diagnosis method for planetary gearboxes based on improved complementary ensemble empirical mode decomposition (ICEEMD)-time-frequency information entropy and variable predictive model-based class discriminate (VPMCD) is proposed in this paper. First, the vibration signal of planetary gearboxes is decomposed into several intrinsic mode functions (IMFs) by using the ICEEMD algorithm, which is used to determine the noise component by using the magnitude of the entropy and to remove the noise components. Then, the time-frequency information entropy of intrinsic modal function under the new decomposition is calculated and regarded as the characteristic matrix. Finally, the fault mode is classified by the VPMCD method. The experimental results demonstrate that the method proposed in this paper can not only solve the fault diagnosis of planetary gearboxes under different operation conditions, but can also be used for fault diagnosis under variable operation conditions. Simultaneously, the proposed method is superior to the wavelet entropy method and variational mode decomposition (VMD)-time-frequency information entropy.
Influence of Nonthermal Atmospheric Plasma-Activated Water on the Structural, Optical, and Biological Properties of Aspergillus brasiliensis Spores
Authors: Ki Se Hoon , Noh Hyeongjin , Ahn Geum Ran , Kim Seong Hwan , Kaushik Nagendra K. , Choi Eun Ha , Lee Geon Joon
Published: September 2020

Plasma-activated water (PAW) has emerged as a platform for sterilizing fungal pathogens. In this study, we investigated the influence of PAW on black melanized spores of Aspergillus brasiliensis to explore the mechanism of fungal spore inactivation. PAW was prepared by activating deionized water with a nonthermal atmospheric pressure air plasma jet (soft plasma jet). The concentrations of H2O2 and NOx in the PAW treated by the soft plasma jet for 3 min were 50 μM and 1.8 mM, respectively, and the pH of the PAW was 3.10. The reactive oxygen and nitrogen species (RONS) in the PAW increased with longer plasma activation time. After being treated for 30 min in the PAW with a plasma activation time of 3 min, the spore viability dramatically dropped to 15%. The viabilities of 0.3% H2O2- and 0.3% HNO3-treated spores were 22% and 42%, respectively. The breakage of the spore cell wall by the PAW was revealed in scanning electron microscope images and flow cytometry measurements. Disruption of cell wall integrity provides a path for intracellular components to escape and RONS of the PAW can attack intracellular components directly. Degradation of high molecular genomic DNA was also observed by agarose gel electrophoresis. These results suggest that long-lived reactive species generated in the PAW play an important role in the inactivation of melanized fungal spores. Consequently, PAW produced by a soft plasma jet can be applied to sterilize bioprotective walled fungal spores in a relatively large volume.
Multiobjective Optimization for the Aero-Structural Design of Adaptive Compliant Wing Devices
Authors: De Gaspari Alessandro
Published: September 2020

The design of morphing structures must combine conflicting structural requirements and multiple load conditions that are related to the aerodynamic shapes aimed at optimizing aircraft performance. This article proposes a multilevel approach for the design of adaptive compliant wing devices. A set of aerodynamic shapes, and associated their loads, is defined by a shape optimization, coupled with a three-dimensional parametric technique, that can identify only feasible shape changes due to the morphing. A topology and sizing multiobjective optimization drives the Pareto-optimal structural design of the compliant structure, which is able to deform itself to match, once actuated, all of the previously defined aerodynamic shapes. Next two design levels produce a more detailed solution which is extended until the definition of the complete device. A 90 pax, twin prop green regional aircraft is used as an innovative aircraft demonstration platform for the design of the morphing droop nose to be installed on the wing. The results show the structural capabilities of this device in terms of the external shape quality and the strain requirements. This work enables the validation of the design method and prove the functionality of compliant structures when accounting for the aeroelastic effects due to the interaction with the wing-box.
Tonal Contour Generation for Isarn Speech Synthesis Using Deep Learning and Sampling-Based F0 Representation
Authors: Janyoi Pongsathon , Seresangtakul Pusadee
Published: September 2020

The modeling of fundamental frequency (F0) in speech synthesis is a critical factor affecting the intelligibility and naturalness of synthesized speech. In this paper, we focus on improving the modeling of F0 for Isarn speech synthesis. We propose the F0 model for this based on a recurrent neural network (RNN). Sampled values of F0 are used at the syllable level of continuous Isarn speech combined with their dynamic features to represent supra-segmental properties of the F0 contour. Different architectures of the deep RNNs and different combinations of linguistic features are analyzed to obtain conditions for the best performance. To assess the proposed method, we compared it with several RNN-based baselines. The results of objective and subjective tests indicate that the proposed model significantly outperformed the baseline RNN model that predicts values of F0 at the frame level, and the baseline RNN model that represents the F0 contours of syllables by using discrete cosine transform.
Single-Shot Object Detection with Split and Combine Blocks
Authors: Wang Hongwei , Li Dahua , Song Yu , Gao Qiang , Wang Zhaoyang , Liu Chunping
Published: September 2020

Feature fusion is widely used in various neural network-based visual recognition tasks, such as object detection, to enhance the quality of feature representation. It is common practice for both the one-stage object detectors and the two-stage object detectors to implement feature fusion in feature pyramid networks (FPN) to enhance the capacity to detect objects of different scales. In this work, we propose a novel and efficient feature fusion unit, which is referred to as the Split and Combine (SC) Block, that splits the input feature maps into several parts, then processes these sub-feature maps with different emphasis, and finally gradually concatenates the outputs one-by-one. The SC block implicitly encourages the network to focus on features that are more important to the task, thus improving network efficiency and reducing inference computations. In order to prove our analysis and conclusions, a backbone network and an FPN employing this technique are assembled into a one-stage detector and evaluated on the MS COCO dataset. With the newly introduced SC block and other novel training tricks, our detector achieves a good speed-accuracy trade-off on COCO test-dev set, with 37.1% AP (average precision) at 51 FPS and 38.9% AP at 40 FPS.
Fatigue-Life Prediction of Mechanical Element by Using the Weibull Distribution
Authors: Barraza-Contreras Jesús M. , Piña-Monarrez Manuel R. , Molina Alejandro
Published: September 2020

Applying Goodman, Gerber, Soderberg and Elliptical failure theories does not make it possible to determine the span of failure times (cycles to failure-Ni) of a mechanical element, and so in this paper a fatigue-life/Weibull method to predict the span of the Ni values is formulated. The input’s method are: (1) the equivalent stress (σeq) value given by the used failure theory; (2) the expected Neq value determined by the Basquin equation; and (3) the Weibull shape β and scale η parameters that are fitted directly from the applied principal stress σ1 and σ2 values. The efficiency of the proposed method is based on the following facts: (1) the β and η parameters completely reproduce the applied σ1 and σ2 values. (2) The method allows us to determine the reliability index R(t), that corresponds to any applied σ1i value or observed Ni value. (3) The method can be applied to any mechanical element’s analysis where the corresponding σ1 and σ2, σeq and Neq values are known. In the performed application, the σ1 and σ2 values were determined by finite element analysis (FEA) and from the static stress analysis. Results of both approaches are compared. The steps to determine the expected Ni values by using the Weibull distribution are given.
Editorial Introduction to the Special Issue “Biomaterials and Biofabrication”
Authors: Kim Jangho , Kim Kyunghoon , Kim Hong Nam
Published: September 2020

This Special Issue “Biomaterials and Biofabrication” of applied sciences comprises 10 papers that are the latest advances in basic and application research in the field of biomaterials and biofabrication [...]
Analysis of Association between Intake of Red Wine Polyphenols and Oxidative Stress Parameters in the Liver of Growing Male Rats
Authors: Kołota Aleksandra , Głąbska Dominika , Oczkowski Michał , Gromadzka-Ostrowska Joanna
Published: September 2020

Red wine is a complex alcoholic beverage containing various substances, including those of a potential health-promoting properties, such as polyphenols, responsible for the sensory features of wine. Their potential positive influence is associated with possibility of antioxidative, anti-inflammatory, anticancer, immunomodulating, and antiallergenic effects, but at the same time, there is a possibility of their pro-oxidative effect. In spite of the fact that in adolescence alcohol may be highly damaging, as it may disturb the development, it is abused frequently. The aim of the study was to verify the association between red wine consumption as well as dietary polyphenol intake with wine and the oxidative stress parameters in the liver of growing male rats. The growing male Wistar rats were studied, while divided into three groups of six animals, receiving red wine in a solution characterized by 10% of ethanol content since 30th day of life, for two, four, and six weeks. The alcohol intake was controlled and the content of total phenolic compounds, selected phenolic acids (hydroxybenzoic acid, caffeic acid, p-coumaric acid, ferulic acid, and sinapic acid), total anthocyanidins and selected anthocyanins (cyanidin, cyanidin 3-glucoside, cyanidin 3-rutinoside, delphinidin, and pelargonidin) were assessed. At the same time, for the liver homogenates, the levels of Thiobarbituric Acid Reactive Substances (TBARS) and protein carbonyl groups were verified. The analysis revealed statistically significant influence of red wine intake, as well as of supply of phenolic acids (hydroxybenzoic acid, caffeic acid, p-coumaric acid, ferulic acid, and sinapic acid), and anthocyanins (cyanidin, cyanidin 3-glucoside, cyanidin 3-rutinoside, delphinidin, and pelargonidin) on TBARS and protein carbonyl groups level (R > 0.80; p < 0.05), but the influence was stated only for the period of two weeks. The obtained results may suggest pro-oxidative effect of both ethanol and polyphenols for the liver of the growing male rats. At the same time, for the periods of four and six weeks, no influence on TBARS and protein carbonyl groups level was observed (p > 0.05), which may allow to suppose an adaptive mechanism of the growing organism while the ethanol and polyphenols exposition is prolonged. Further studies are required to confirm the mechanism of the pro-oxidative effect of polyphenols contained in red wine for the liver of growing organism.
Toward Scalable Video Analytics Using Compressed-Domain Features at the Edge
Authors: Nguyen Dien Van , Choi Jaehyuk
Published: September 2020

Intelligent video analytics systems have come to play an essential role in many fields, including public safety, transportation safety, and many other industrial areas, such as automated tools for data extraction, and analyzing huge datasets, such as multiple live video streams transmitted from a large number of cameras. A key characteristic of such systems is that it is critical to perform real-time analytics so as to provide timely actionable alerts on various tasks, activities, and conditions. Due to the computation-intensive and bandwidth-intensive nature of these operations, however, video analytics servers may not fulfill the requirements when serving a large number of cameras simultaneously. To handle these challenges, we present an edge computing-based system that minimizes the transfer of video data from the surveillance camera feeds on a cloud video analytics server. Based on a novel approach of utilizing the information from the encoded bitstream, the edge can achieve low processing complexity of object tracking in surveillance videos and filter non-motion frames from the list of data that will be forwarded to the cloud server. To demonstrate the effectiveness of our approach, we implemented a video surveillance prototype consisting of edge devices with low computational capacity and a GPU-enabled server. The evaluation results show that our method can efficiently catch the characteristics of the frame and is compatible with the edge-to-cloud platform in terms of accuracy and delay sensitivity. The average processing time of this method is approximately 39 ms/frame with high definition resolution video, which outperforms most of the state-of-the-art methods. In addition to the scenario implementation of the proposed system, the method helps the cloud server reduce 49% of the load of the GPU, 49% that of the CPU, and 55% of the network traffic while maintaining the accuracy of video analytics event detection.
Robust Chromatic Adaptation Based Color Correction Technology for Underwater Images
Authors: Yang Xieliu , Yin Chenyu , Zhang Ziyu , Li Yupeng , Liang Wenfeng , Wang Dan , Tang Yandong , Fan Huijie
Published: September 2020

Recovering correct or at least realistic colors of underwater scenes is a challenging issue for image processing due to the unknown imaging conditions including the optical water type, scene location, illumination, and camera settings. With the assumption that the illumination of the scene is uniform, a chromatic adaptation-based color correction technology is proposed in this paper to remove the color cast using a single underwater image without any other information. First, the underwater RGB image is first linearized to make its pixel values proportional to the light intensities arrived at the pixels. Second, the illumination is estimated in a uniform chromatic space based on the white-patch hypothesis. Third, the chromatic adaptation transform is implemented in the device-independent XYZ color space. Qualitative and quantitative evaluations both show that the proposed method outperforms the other test methods in terms of color restoration, especially for the images with severe color cast. The proposed method is simple yet effective and robust, which is helpful in obtaining the in-air images of underwater scenes.
Concatenated Coding for GNSS Signals in Urban Environments
Authors: Ke Jing , Lu Xiaochun , Wang Xue , Chen Xiaofei , Tang Sheng
Published: September 2020

This work investigated concatenated coding schemes for Global Navigation Satellite System (GNSS) signals in order to increase their error correction capability in urban environments. In particular, a serial concatenated code that combines an outer Reed–Solomon (RS) code with an inner low-density parity-check (LDPC) code was designed, and the performance was investigated over the land mobile satellite (LMS) channel for characterizing multipath and shadow fading in urban environments. The performance of the proposed concatenated coding scheme was compared to that of a B-CNAV1 message, in which two interleaved 64-ary LDPC codes were employed. The simulation results demonstrate that the proposed concatenated code can obtain a similar error correction performance to the two interleaved 64-ary LDPC codes in both the additive white Gaussian noise (AWGN) and LMS channels at a lower complexity level.
A SWOT Analysis for Offshore Wind Energy Assessment Using Remote-Sensing Potential
Authors: Majidi Nezhad Meysam , Shaik Riyaaz Uddien , Heydari Azim , Razmjoo Armin , Arslan Niyazi , Astiaso Garcia Davide
Published: September 2020

The elaboration of a methodology for accurately assessing the potentialities of blue renewable energy sources is a key challenge among the current energy sustainability strategies all over the world. Consequentially, many researchers are currently working to improve the accuracy of marine renewable assessment methods. Nowadays, remote sensing (RSs) satellites are used to observe the environment in many fields and applications. These could also be used to identify regions of interest for future energy converter installations and to accurately identify areas with interesting potentials. Therefore, researchers can dramatically reduce the possibility of significant error. In this paper, a comprehensive SWOT (strengths, weaknesses, opportunities and threats) analysis is elaborated to assess RS satellite potentialities for offshore wind (OW) estimation. Sicily and Sardinia—the two biggest Italian islands with the highest potential for offshore wind energy generation—were selected as pilot areas. Since there is a lack of measuring instruments, such as cup anemometers and buoys in these areas (mainly due to their high economic costs), an accurate analysis was carried out to assess the marine energy potential from offshore wind. Since there are only limited options for further expanding the measurement over large areas, the use of satellites makes it easier to overcome this limitation. Undoubtedly, with the advent of new technologies for measuring renewable energy sources (RESs), there could be a significant energy transition in this area that requires a proper orientation of plans to examine the factors influencing these new technologies that can negatively affect most of the available potential. Satellite technology for identifying suitable areas of wind power plants could be a powerful tool that is constantly increasing in its applications but requires good planning to apply it in various projects. Proper planning is only possible with a better understanding of satellite capabilities and different methods for measuring available wind resources. To this end, a better understanding in interdisciplinary fields with the exchange of updated information between different sectors of development, such as universities and companies, will be most effective. In this context, by reviewing the available satellite technologies, the ability of this tool to measure the marine renewable energies (MREs) sector in large and small areas is considered. Secondly, an attempt is made to identify the strengths and weaknesses of using these types of tools and techniques that can help in various projects. Lastly, specific scenarios related to the application of such systems in existing and new developments are reviewed and discussed.
Reduced Supply in the Organ Donor Market and How 3D Printing Can Address This Shortage: A Critical Inquiry into the Collateral Effects of Driverless Cars
Authors: Mills Patrick A. S. , Mills David K.
Published: September 2020

Driverless cars, such as those currently operated by Uber and others as well as those being researched and developed by major and niche automobile manufacturers, are expected to dramatically reduce the number of highway fatalities in the coming years. While no one will fault any technology that safely and effectively protects and saves lives, many individuals with an array of medical conditions rely on organ donors to provide the liver, kidney, or other organs required to facilitate a life-saving organ transplant. Consequently, one collateral effect of the introduction of driverless car technology will be a reduction in the market supply of healthy organs for transplantation. In this paper, a venture capital lawyer, a medical researcher, and a bioengineer will establish the expected size of this reduction in supply, the associated harm resulting from this reduction, and discuss two promising technological solutions—bioprosthetics and 3D bioprinting of tissues and organs. In the case of both technologies, the authors will discuss the challenges and opportunities presented for institutional investors (private equity, venture capital, angel funds) and medical researchers in tackling the potential reduction in organ donations.
Hydrodynamic Forces of a Semi-Submerged Cylinder in an Oscillatory Flow
Authors: Ren Haojie , Fu Shixiao , Liu Chang , Zhang Mengmeng , Xu Yuwang , Deng Shi
Published: September 2020

This work experimentally investigated the performance of hydrodynamic forces on a semi-submerged cylinder under an oscillatory flow. To generate the equivalent oscillatory flow, the semi-submerged cylinder is forced to oscillate in several combinations of different periods and amplitudes. The mean downward lift force was observed to be significant and the fluctuating lift forces show dominant frequency is twice that of oscillatory flow and amplitude that is the same as the mean lift force. Based on this main hydrodynamic feature, a novel empirical prediction formula for the lift forces on semi-submerged cylinder under oscillatory flow is proposed where the lift forces expression is proportional to the square of oscillatory flow velocity. This novel empirical formula directly assigns the fluctuating lift force with frequency twice of oscillatory flow and the amplitude that is the same as the mean lift force. This assignment of empirical lift force formula reduces parameters required to determine a dynamic lift force but is demonstrated to well predict the fluctuating lift force. The lift coefficient can reach 1.5, which is larger than the typical value 1.2 of the drag coefficient for a fully submerged cylinder with infinite depth. Moreover, relationships among hydrodynamic coefficients, Keulegan-Carpenter (KC) number, Stokes number and Froude number are studied. With the increase of KC number, the Froude number has a more significant influence on the distribution of hydrodynamic coefficients. As Froude number is increasing, the drag coefficient shows a nonlinear decay (KC < 20) but a linear increase (KC > 20), while the added mass coefficients show a nonlinear (KC < 20) and a linear (KC > 20) increase trend. The present work can provide useful references for design of the relevant marine structures and serve as the useful guideline for future research.
Choice between Surgery and Conservative Treatment for Patients with Lumbar Spinal Stenosis: Predicting Results through Data Mining Technology
Authors: Tseng Li-Ping , Pei Yu-Cheng , Chen Yen-Sheng , Hou Tung-Hsu , Ou Yang-Kun
Published: September 2020

Currently, patients with lumbar spinal stenosis (LSS) have two treatment options: nonoperative conservative treatment and surgical treatment. Because surgery is invasive, patients often prefer conservative treatment as their first choice to avoid risks from surgery. However, the effectiveness of nonoperative conservative treatment for patients with LSS may be lower than expected because of individual differences. Rules to determine whether patients with LSS should undergo surgical treatment merits exploration. In addition, without a decision-making system to assist patients undergoing conservative treatment to decide whether to undergo surgical treatment, medical professionals may encounter difficulty in providing the best treatment advice. This study collected medical record data and magnetic resonance imaging diagnostic data from patients with LSS, analyzed and consolidated the data through data mining techniques, identified crucial factors and rules affecting the final outcome the patients with LSS who opted for conservative treatment and ultimately underwent surgical treatment, and, finally, established an effective prediction model. This study applied logistic regression (LGR) and decision tree algorithms to extract the crucial features and combined them with back propagation neural networks (BPNN) and support vector machines (SVM) to establish the prediction model. The crucial features obtained are as follows: reduction of the intervertebral disc height, age, blood pressure difference, leg pain, gender, etc. Among the models predicting whether patients with LSS ultimately underwent surgical treatment, the model combining LGR and the decision tree for feature selection with a BPNN has a testing accuracy rate of 94.87%, sensitivity of 0.9, specificity of 1, and area under the receiver operating characteristic curve of 0.952. Adopting these data mining techniques to predict whether patients with LSS who opted for conservative treatment ultimately underwent surgical treatment may assist medical professionals in reaching a treatment decision and provide clearer treatment. This may effectively mitigate disease progression, aid the goals of precision medicine, and ultimately enhance the quality of health care.
Grover on Korean Block Ciphers
Authors: Jang Kyoungbae , Choi Seungju , Kwon Hyeokdong , Kim Hyunji , Park Jaehoon , Seo Hwajeong
Published: September 2020

The Grover search algorithm reduces the security level of symmetric key cryptography with n-bit security level to O(2n/2). In order to evaluate the Grover search algorithm, the target block cipher should be efficiently implemented in quantum circuits. Recently, many research works evaluated required quantum resources of AES block ciphers by optimizing the expensive substitute layer. However, few works were devoted to the lightweight block ciphers, even though it is an active research area, nowadays. In this paper, we present optimized implementations of every Korean made lightweight block ciphers for quantum computers, which include HIGHT, CHAM, and LEA, and NSA made lightweight block ciphers, namely SPECK. Primitive operations for block ciphers, including addition, rotation, and exclusive-or, are finely optimized to achieve the optimal quantum circuit, in terms of qubits, Toffoli gate, CNOT gate, and X gate. To the best of our knowledge, this is the first implementation of ARX-based Korean lightweight block ciphers in quantum circuits.
Precipitation Microphysical Characteristics of Typhoon Mangkhut in Southern China Using 2D Video Disdrometers
Authors: Feng Lu , Hu Sheng , Liu Xiantong , Xiao Hui , Pan Xiao , Xia Feng , Ou Guanhua , Zhang Chu
Published: September 2020

The microphysical characteristics of tropical cyclones vary in different rain regions, which affects not only the dynamic and thermodynamic mechanisms of the typhoon system but also the development of tropical cyclones. This study analyzed the raindrop size distribution (DSD) and the gamma DSD parameters associated with Typhoon Mangkhut using three two-dimensional (2D) video disdrometers from the Longmen Field Experiment Base for Cloud Physics, China Meteorological Administration in Guangdong, China during 16–17 September 2018. According to the observed track and radar reflectivity, this process can be divided into three distinct segments: the outer rainband before landfall (S1), the inner core (S2), and the outer rainband after landfall (S3). The outer rainband mainly produces stratiform rains, while the inner core mainly produces convective rains. The temporal and spatial variations in the rain rate, radar reflectivity, and DSD parameters of the different segments were analyzed and compared at three sites. Although the DSD characteristics are distinctly different in the three segments, the DSD characteristics of the same segment were similar at different sites. In the inner core (S2), the precipitation contains smaller drops (around 0.5 mm) and the concentrations are higher within each size bin compared with those of the other segments, resulting in the maximum rain rate (11.66 mm h−1), radar reflectivity (34.53 dBZ), liquid water content (0.65 g m−3), and number concentration (4.12 mm−1 m−3 on a logarithmic scale) occurring in this segment. The Nw–Dm scatter pairs have maritime-like convection, which increases outward from the inner core (S2). The relationship between the shape (μ) and slope (Λ) was also investigated. The microphysical characteristics determined in this study provide useful information for understanding microphysical precipitation processes and for improving the precision of numerical weather prediction models.
Long-Term Analysis of Atmospheric Energetics Components over the Mediterranean, Middle East and North Africa
Authors: Michaelides Silas
Published: September 2020

In this research, one aspect of the climate that is not commonly referred to, namely, the long-term changes in the components of the atmospheric energy, is investigated. In this respect, the changes in four energy forms are considered, namely, Kinetic Energy (KE), Thermal Energy (TE), Internal Energy (IE), Potential Energy (PE) and Latent Energy (LE); the Energy Conversion (EC) between Kinetic Energy and Potential plus Internal Energy (PIE) is also considered. The area considered in this long-term energetics analysis covers the entire Mediterranean basin, the Middle East and a large part of North Africa. This broad geographical area has been identified by many researchers as a hot spot of climate change. Analyses of climatic data have indeed shown that this region has been experiencing marked changes regarding several climatic variables. The present energetics analysis makes use of the ERA-Interim database for the period from 1979 to 2018. In this 40-year period, the long-term changes in the above energetics components are studied. The monthly means of daily means for all the above energy forms and Energy Conversion comprise the basis for the present research. The results are presented in the form of monthly means, annual means and spatial distributions of the energetics components. They show the dominant role of the subtropical jet-stream in the KE regime. During the study period, the tendency is for KE to decrease with time, with this decrease found to be more coherent in the last decade. The tendency for TE is to increase with time, with this increase being more pronounced in the most recent years, with the maximum in the annual mean in KE noted in 2015. The sum of Potential and Internal energies (PIE) and the sum of Potential, Internal and Latent energies (PILE) follow closely the patterns established for TE. In particular, the strong seasonal influence on the monthly means is evident with minima of PIE and PILE noted in winters, whereas, maxima are registered during summers. In addition, both PIE and PILE exhibit a tendency to increase with time in the 40-year period, with this increase being more firmly noted in the more recent years. Although local conversion from KE into PIE is notable, the area averaging of EC shows that the overall conversion is in the direction of increasing the PIE content of the area at the expense of the KE content. EC behaves rather erratically during the study period, with values ranging from 0.5 to 3.7 × 102 W m−2. Averaged over the study area, the Energy Conversion term operates in the direction of converting KE into PIE; it also lacks a seasonal behavior.
Temperature Response from the Change of Surface Heat Flux and Vertical Diffusivity by Urbanization
Authors: Ren Shuzhan , Stroud Craig A.
Published: September 2020

A 1-D diffusion model of temperature is employed to understand important features of temperature response to the changes of surface heat flux (SHF) and vertical diffusivity shown in 3-D model simulations. Analytical results show that the temperature response to the SHF change is the convolution of the SHF change and Green’s function (GF). Because the GF is inversely proportional to the square root of diffusion coefficient near the surface, weak/strong diffusivity in the early morning/noontime tends to generate a large/small temperature response by slowing/accelerating heat flow from surface to the atmosphere. The modulation effect of the GF and the convolution effect explain very different temperature responses to the SHF change during each period. Analytical results also show that the temperature response to the change of DF is equal to the convolution of the product of diffusion coefficient change, vertical gradients of reference temperature and the GF. Because the vertical gradient of the GF is negative below 80 m, enhanced/reduced diffusivity would enhance/weaken the urban temperature, if the vertical gradient of reference temperature is negative/positive. Numerical results with typical values of the changes of SHF and diffusivity suggest that the changes of SHF has the dominant contribution to the temperature response.
What Can We Learn from Comparing Glacio-Hydrological Models?
Authors: Stoll Elena , Hanzer Florian , Oesterle Felix , Nemec Johanna , Schöber Johannes , Huttenlau Matthias , Förster Kristian
Published: September 2020

Glacio-hydrological models combine both glacier and catchment hydrology modeling and are used to assess the hydrological response of high-mountain glacierized catchments to climate change. To capture the uncertainties from these model combinations, it is essential to compare the outcomes of several model entities forced with the same climate projections. For the first time, we compare the results of two completely independent glacio-hydrological models: (i) HQsim-GEM and (ii) AMUNDSEN. In contrast to prevailing studies, we use distinct glacier models and glacier initialization times. At first glance, the results achieved for future glacier states and hydrological characteristics in the Rofenache catchment in Ötztal Alps (Austria) appear to be similar and consistent, but a closer look reveals clear differences. What can be learned from this study is that low-complexity models can achieve higher accuracy in the calibration period. This is advantageous especially when data availability is weak, and priority is given to efficient computation time. Furthermore, the time and method of glacier initialization play an important role due to different data requirements. In essence, it is not possible to make conclusions about the model performance outside of the calibration period or more specifically in the future. Hence, similar to climate modeling, we suggest considering different modeling approaches when assessing future catchment discharge or glacier evolution. Especially when transferring the results to stakeholders, it is vital to transparently communicate the bandwidth of future states that come with all model results.
Phase Diagram of the Attractive Kane-Mele-Hubbard Model at Half Filling
Authors: Koinov Zlatko
Published: September 2020

Motivated by recent developments in the experimental study of ultracold atoms in graphene-like honeycomb optical lattices, we investigate superconductivity of the attractive Kane-Mele-Habbard (KMH) model with the next-nearest-neighbor (NNN) hoping at half filling. The mean-field approximation is used to study the phase diagram which interpolates the trivial and the non-trivial topological states. It is shown that: (a) when the NNN hoping is taken into account, one has to introduce two mean-field gap equations for the two sublattices, instead of a single gap when the NNN hopping is neglected, and (b) in the non-trivial topological region the phase diagram with the NNN hopping is significantly different compared to the phase diagram calculated previously, but without the NNN term. We also discuss the superconducting instability of the attractive KMH model that is driven by condensation of Cooperons.
Star-Shapedness of \({\mathcal N}\)-Structures in Euclidean Spaces
Authors: Lee Kyoung , Song Seok-Zun , Jun Young
Published: September 2020

The notions of (quasi, pseudo) star-shaped sets are introduced, and several related properties are investigated. Characterizations of (quasi) star-shaped sets are considered. The translation of (quasi, pseudo) star-shaped sets are discussed. Unions and intersections of quasi star-shaped sets are conceived. Conditions for a quasi (or, pseudo) star-shaped set to be a star-shaped set are provided.
Deductive Systems in Traditional and Modern Logic
Authors: Citkin Alex , Wybraniec-Skardowska Urszula
Published: September 2020

Since its inception, logic has studied the acceptable rules of reasoning, the rules that allow us to pass from certain statements, serving as premises or assumptions, to a statement taken as a conclusion [...]
Lithium Polysulfide Interaction with Group III Atoms-Doped Graphene: A Computational Insight
Authors: Sgroi Mauro Francesco , Pullini Daniele , Pruna Alina Iuliana
Published: September 2020

The development of long lifetime Li–S batteries requires new sulfur–carbon based composite materials that are able to suppress the shuttle effect—namely, the migration of soluble lithium polysulfides from the cathode to the anode of the cell. Graphene is one of the most promising carbon supports for sulfur, thanks to its excellent conductivity and to the possibility of tailoring its chemical–physical properties, introducing heteroatoms in its structure. By using first principle density functional theory simulations, this work aims at studying the effect of doping graphene with group III elements (B, Al, Ga) on its electronic properties and on its chemical affinity towards lithium polysulfides. Our results show that Al and Ga doping strongly modify the local structure of the lattice near heteroatom site and generate a charge transfer between the dopant and its nearest neighbor carbon atoms. This effect makes the substrate more polar and greatly enhances the adsorption energy of polysulfides. Our results suggest that Al- and Ga-doped graphene could be used to prepare cathodes for Li–S cells with improved performances and lifetime.