bluuebunny/crossref_metadata_2025 huggingface dataset:
MARKOWITZ PORTFOLIO AND THE BLUR OF HISTORY
Authors: NG CHI TIM , SHI YUE , CHAN NGAI HANG
Published: May 2020

It is shown in this paper that when the true mean return vector is replaced by the inferred mean vector obtained indirectly from factor model and arbitrage pricing theory, its impact on the resulting optimal portfolio is insignificant. To achieve this goal, several assumptions are imposed: (i) the asset returns are generated from a factor model, (ii) the number of assets goes to infinity, and (iii) there is no asymptotic arbitrage opportunities. Issues related to the efficiency of the estimated optimal portfolio for high-frequency data are discussed. The portfolio constructed using the sample mean vector and using the inferred mean vector from arbitrage pricing theory are compared.
Schur indices for reality-based algebras with two nonreal basis elements
Authors: Herman Allen
Published: May 2020

This article discusses the representation theory of noncommutative algebras reality-based algebras with positive degree map over their field of definition. When the standard basis contains exactly two nonreal elements, the main result expresses the noncommutative simple component as a generalized quaternion algebra over its field of definition. The field of real numbers will always be a splitting field for this algebra, but there are noncommutative table algebras of dimension [Formula: see text] with rational field of definition for which it is a division algebra. The approach has other applications, one of which shows noncommutative association scheme of rank [Formula: see text] must have at least three symmetric relations.
On the configurations of codimension two linear subspaces of ℙN with the Waldschmidt constant less than 2
Authors: Haghighi Hassan , Mosakhani Mohammad
Published: May 2020

The purpose of this note is to generalize a result of [M. Dumnicki, T. Szemberg and H. Tutaj-Gasińska, Symbolic powers of planar point configurations II, J. Pure Appl. Alg. 220 (2016) 2001–2016] to higher-dimensional projective spaces and classify all configurations of [Formula: see text]-planes [Formula: see text] in [Formula: see text] with the Waldschmidt constants less than two. We also determine some numerical and algebraic invariants of the defining ideals [Formula: see text] of these classes of configurations, i.e. the resurgence, the minimal free resolution and the regularity of [Formula: see text], as well as the Hilbert function of [Formula: see text].
Hybrid Gaussian Process Inference Model for Construction Management Decision Making
Authors: Cheng Min-Yuan , Wu Yu-Wei , Huang Chin-Chi
Published: May 2020

Construction decision-making often involves several indefinite factors, and wrong decisions usually lead to many losses and may even cause the construction to fail. Correct policy making is very important. Construction decision making used to depend on managerial staff’ experience and subjective recognition, but this approach is likely to bring about wrong decisions because of an excessive number of factors involved or biased subjective recognition. To prevent such a situation, this study establishes a Hybrid Gaussian Process Inference Model (HGPIM), which uses a Gaussian process (GP) to sort out the mapping relationship between data input and output. It also uses Bayesian inference together with particle swarm optimization (PSO) to optimize the hyper-parameters of the covariance function in GP to obtain the best inference predictive ability. By predicting with the model and giving the events that need to be decided an expected value and a variance, we can establish the data’s confidence interval as a reference for making decisions. This study collects data from three construction projects to conduct the experiment and uses HGPIM to train, predict and retest these cases to prove HGPIMs predictive ability. It also shows that the model can be applied to various cases and data and thus can be applied to construction engineering.
Quaternion quantum neurocomputing
Authors: Bayro-Corrochano Eduardo , Solis-Gamboa Samuel
Published: May 2020

Since the introduction of quaternion by Hamilton in 1843, quaternions have been used in a lot of applications. One of the most interesting qualities is that we can use quaternions to carry out rotations and operate on other quaternions; this characteristic of the quaternions inspired us to investigate how the quantum states and quantum operator work in the field of quaternions and how we can use it to construct a quantum neural network. This new type of quantum neural network (QNN) is developed in the quaternion algebra framework that is isomorphic to the rotor algebra [Formula: see text] of the geometric algebra and is based on the so-called qubit neuron model. The quaternion quantum neural network (QQNN) is tested and shows robust performance.
Global dynamical time for binary point-like particle systems
Authors: Moreschi Osvaldo M.
Published: May 2020

A geometrical construction for a global dynamical time for binary point-like particle systems, modeled by relativistic equations of motions, is presented. Thus, we provide a convenient tool for the calculation of the dynamics of recent models for the dynamics of black holes that use individual proper times. The construction is naturally based on the local Lorentzian geometry of the spacetime considered. Although in this presentation we are dealing with the Minkowskian spacetime, the construction is useful for gravitational models that have as a seed Minkowski spacetime. We present the discussion for a binary system, but the construction is obviously generalizable to multiple particle systems. The calculations are organized in terms of the order of the corresponding relativistic forces. In particular, we improve on the Darwin and Landau–Lifshitz approaches, for the case of electromagnetic systems. We discuss the possibility of a Lagrangian treatment of the retarded effects, depending on the nature of the relativistic forces. The higher-order contractions are based on a Runge–Kutta type procedure, which is used to calculate the quantities at the required retarded time, by increasing evaluations of the forces at intermediate times. We emphasize the difference between approximation orders in field equations and approximation orders in retarded effects in the equations of motion. We show this difference by applying our construction to the binary electromagnetic case.
Cyclic Behavior and Simplified Design Method of Hybrid Rocking Columns with External Energy-Dissipators
Authors: Li Yongxing , Li Jianzhong , Shen Yu , Xu Wenjing
Published: May 2020

In recent years, hybrid rocking columns incorporating post-tensioned (PT) tendons and energy dissipation devices become prevalent on account of the superior self-centering capacity. In this paper, the simplified analysis method based on interface section analysis is employed to conduct parametric analyses on the hybrid rocking columns with external buckling-restrained devices, which are adopted as the external energy-dissipators. The effects of four parameters including the aspect ratio, the initial PT force, the area of PT tendons and the area of energy-dissipators are investigated. Furthermore, a simplified design method for hybrid rocking columns with external energy-dissipators is proposed using the parametric analysis results. In the design procedure, the performance index [Formula: see text] is employed considering the requirement of residual drift. The efficiency of the design method is verified by a numerical design example to show the application. The results show that the design objectives of lateral force and residual drift can be achieved through a small number of iterations.
On parametrizations of loxodromes on time-like rotational surfaces in Minkowski space-time
Authors: Babaarslan Murat , Gümüş Murat
Published: May 2020

We investigate the parametrizations of loxodromes on the time-like rotational surfaces by using suitable Lorentzian angles in Minkowski space-time. Also, some examples and corresponding graphs are given by using Mathematica.
Boundedness of integral operators associated with the Kontorovich–Lebedev transform in the Lebesgue spaces type
Authors: Kroumi Anis
Published: May 2020

In this paper, we prove the boundedness for the maximal and fractional maximal operators and Riesz potential-type operator associated with the Kontorovich–Lebedev transform (KL transform)in the [Formula: see text] spaces.
COVID-19 and Rheumatic Diseases: Practical Issues
Authors: So Ho , Mok Chi Chiu
Published: May 2020

On March 12, 2020, the World Health Organization (WHO) declared coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) a pandemic. The rapidly increasing number of cases and deaths have overwhelmed the health care system worldwide. We aimed to provide a narrative review on some practical issues of COVID-19 and rheumatic diseases with the limited data to the date of April 26, 2020.
Structural controls on the location, geometry and longevity of an intraplate volcanic system: the Tuatara Volcanic Field, Great South Basin, New Zealand
Authors: Phillips Thomas B. , Magee Craig
Published: June 2020

Intraplate volcanism is widely distributed across the continents, but the controls on the 3D geometry and longevity of individual volcanic systems remain poorly understood. Geophysical data provide insights into magma plumbing systems, but, as a result of the relatively low resolution of these techniques, it is difficult to evaluate how magma transits highly heterogeneous continental interiors. We use borehole-constrained 2D seismic reflection data to characterize the 3D geometry of the Tuatara Volcanic Field located offshore New Zealand's South Island and investigate its relationship with the pre-existing structure. This
c
. 270 km
2
field is dominated by a dome-shaped lava edifice, surrounded and overlain by
c
. 69 volcanoes and >70 sills emplaced over 40 myr from the Late Cretaceous to Early Eocene (
c
. 85–45 Ma). The Tuatara Volcanic Field is located above a basement terrane boundary represented by the Livingstone Fault; the recently active Auckland Volcanic Field is similarly located along-strike on North Island. We suggest that the Livingstone Fault controlled the location of the Tuatara Volcanic Field by producing relief at the base of the lithosphere, thereby focussing lithospheric detachment over
c
. 40 myr, and provided a pathway that facilitated the ascent of magma. We highlight how observations from ancient intraplate volcanic systems may inform our understanding of active intraplate volcanic systems, including the Auckland Volcanic Field.

Supplementary material: Interpreted seismic section showing well control on stratigraphic interpretation is available at
https://doi.org/10.6084/m9.figshare.c.5004464
Comparing and Combining Interaction Data and Eye-tracking Data for the Real-time Prediction of User Cognitive Abilities in Visualization Tasks
Authors: Conati Cristina , Lallé Sébastien , Rahman Md Abed , Toker Dereck
Published: May 2020

Previous work has shown that some user cognitive abilities relevant for processing information visualizations can be predicted from eye-tracking data. Performing this type of
user modeling
is important for devising visualizations that can detect a user's abilities and adapt accordingly during the interaction. In this article, we extend previous user modeling work by investigating for the first time
interaction data
as an alternative source to predict cognitive abilities during visualization processing when it is not feasible to collect eye-tracking data. We present an extensive comparison of user models based solely on eye-tracking data, on interaction data, as well as on a combination of the two. Although we found that eye-tracking data generate the most accurate predictions, results show that interaction data can still outperform a majority-class baseline, meaning that adaptation for interactive visualizations could be enabled even when it is not feasible to perform eye tracking, using solely interaction data. Furthermore, we found that interaction data can predict several cognitive abilities with better accuracy at the very beginning of the task than eye-tracking data, which are valuable for delivering adaptation early in the task. We also extend previous work by examining the value of multimodal classifiers combining interaction data and eye-tracking data, with promising results for some of our target user cognitive abilities. Next, we contribute to previous work by extending the type of visualizations considered and the set of cognitive abilities that can be predicted from either eye-tracking data and interaction data. Finally, we evaluate how noise in gaze data impacts prediction accuracy and find that retaining rather noisy gaze datapoints can yield equal or even better predictions than discarding them, a novel and important contribution for devising adaptive visualizations in real settings where eye-tracking data are typically noisier than in laboratory settings.
Technology-Enhanced Interaction with Cultural Heritage
Authors: Pretto Niccoló , Micheloni Edoardo , Gasparotto Silvia , Fantozzi Carlo , Poli Giovanni De , Canazza Sergio
Published: May 2020

Digital technology in museum practice provides new means of interaction with artifacts and collections. In particular, we need interactive installations in order to encourage and stimulate visitors to learn and understand archaeological musical instruments through engagement and active participation: these instruments (i.e., interactive artifacts
per se
) are
de facto
unplayable and inaccessible to visitors, as a consequence of their preservation issues. However, presenting artifacts to the general public is a complex task for their multifaceted nature, and digital technology must not sacrifice accuracy or depth of information for the sake of entertainment. Moreover, deploying digital technology is a multidisciplinary effort that requires an interplay among different fields, from history and archaeology to information engineering and craftsmanship. In this article, we present a methodology to relate such disciplines in order to design a digital multimedia installation that promotes archaeological musical instruments in a museum. In defining the problem, we identify four different aspects to consider: the museum collection, the museum environment, the manufacturing opportunities for the installation, and the user experience. Such aspects are integrated in a design approach that is centered on
Design Thinking
. The proposed methodology is exemplified in the designing and manufacturing of an installation for a Pan flute from Egypt dated back to 700 A.D., a case in which multisensory interaction is particularly important to convey the lost sound of the instrument. We describe in detail an installation (exhibited at the Museum of Archaeological Science and Art at the University of Padova), which virtually recreates the Pan flute and communicates information related to its history, iconography, acoustics, and musicology. Just after the deployment of the installation, we also carried out an assessment with a group of experts in the fields of information engineering, music, musicology, and archaeology. The good results obtained demonstrate that the installation is a convenient way of interaction, simple to use and aesthetically integrated in the museum context.
Maximizing Boosted Influence Spread with Edge Addition in Online Social Networks
Authors: Yu Lei , Li Guohui , Yuan Ling
Published: May 2020

Influence maximization with application to viral marketing is a well-studied problem of finding a small number of influential users in a social network to maximize the spread of influence under certain influence cascade models. However, almost all previous studies have focused on node-level mining, where they consider identifying nodes as the initial seeders to achieve the desired outcomes. In this article, instead of targeting nodes, we investigate a new boosted influence maximization problem from the edge-level perspective, which asks for finding an edge set that is added to the network to maximize the increased influence spread of a given seed set. We show that the problem is NP-hard and the influence spread function no longer exhibits the property of submodularity, which impose more challenging on the problem. Therefore, we devise a restricted form that is submodular and propose a greedy algorithm with approximate guarantee to solve the problem. However, because of its poor computational efficiency, we further propose an improved greedy algorithm that integrates several effective optimization strategies to significantly speed up the edge selection without sacrificing its accuracy. Extensive experiments over real-world available social networks of different sizes demonstrate the effectiveness and efficiency of the proposed methods.
Designing an AI Health Coach and Studying Its Utility in Promoting Regular Aerobic Exercise
Authors: Mohan Shiwali , Venkatakrishnan Anusha , Hartzler Andrea L.
Published: May 2020

Our research aims to develop interactive, social agents that can coach people to learn new tasks, skills, and habits. In this article, we focus on coaching sedentary, overweight individuals (i.e., “trainees”) to exercise regularly. We employ adaptive goal setting in which the intelligent health coach generates, tracks, and revises personalized exercise goals for a trainee. The goals become incrementally more difficult as the trainee progresses through the training program. Our approach is model-based—the coach maintains a parameterized model of the trainee’s aerobic capability that drives its expectation of the trainee’s performance. The model is continually revised based on trainee-coach interactions. The coach is embodied in a smartphone application, N
utri
W
alking
, which serves as a medium for coach-trainee interaction. We adopt a task-centric evaluation approach for studying the utility of the proposed algorithm in promoting regular aerobic exercise. We show that our approach can adapt the trainee program not only to several trainees with different capabilities but also to how a trainee’s capability improves as they begin to exercise more. Experts rate the goals selected by the coach better than other plausible goals, demonstrating that our approach is consistent with clinical recommendations. Further, in a 6-week observational study with sedentary participants, we show that the proposed approach helps increase exercise volume performed each week.
Thresholds
Authors: Tennent Paul , Martindale Sarah , Benford Steve , Darzentas Dimitrios , Brundell Pat , Collishaw Mat
Published: May 2020

We examine the experience of
Thresholds
, a virtual reality (VR) recreation of the world's first photographic exhibition, which has toured to multiple museums. Following the method of performance-led research in the wild, we provide an account of the artist's design rationale and the experiences of visitors as the work toured. We reveal how the overlaying and juxtaposing of virtual and physical spaces established a VR architecture that underpinned the extended user experience. Overlaying was used to layer a virtual model onto a corresponding physical set to deliver physical sensations of touch and movement alongside visual and audio stimuli. Juxtaposition was used to embed the VR installation within the surrounding gallery space at each host museum, dealing with the challenges of entering, exiting, spectating, and invigilating the experience. We propose that museum designers can use these techniques to deliver VR installations that are compelling but also scalable and tourable.
Damage Assessment of Earthen Sites of the Ming Great Wall in Qinghai Province
Authors: Du Yumin , Chen Wenwu , Cui Kai , Zhang Jingke , Chen Zhuo , Zhang Qiyong
Published: May 2020

Being a world-renowned heritage site, the Ming Great Wall, located in Qinghai Province, China, mainly has existed as the form of earthen sites with high historical, artistic, and scientific values. However, exposed under environmental impacts for about 500 years, these sites have been seriously threatened. The study on their damage assessment using reasonable methods is the key premise for further protection work. As there are few studies focused on the damage assessment of earthen sites, especially by using machine learning methods, this study explored to apply the current effective machine learning approaches, namely Support Vector Machine (SVM) and back-propagation (BP) Neural Network, into solving this problem. The authors used two such algorithms by training and testing the existing data of damage assessment results of 18 earthen sites located in Qinghai Province. By comparing experimental results, the prediction effects of SVM are much better than those of BP Neural Network. To test its practicability, Liutun Great Wall was chosen as an engineering case, showing better prediction and reasonable performance of SVM. This research has proved that SVM can be selected as a suitable model to assess the damage levels of earthen sites located in Qinghai Province for their future conservation works.
Transactuations
Authors: Leesatapornwongsa Tanakorn , Sengupta Aritra , Ardekani Masoud Saeida , Petri Gustavo , Stuardo Cesar A.
Published: May 2020

A large class of IoT applications read sensors, execute application logic, and actuate actuators. However, the lack of high-level programming abstractions compromises correctness, especially in the presence of failures and unwanted interleaving between applications. A key problem arises when operations on IoT devices or the application itself fails, which leads to inconsistencies between the physical state and application state, breaking application semantics and causing undesired consequences. Transactions are a well-established abstraction for correctness, but assume properties that are absent in an IoT context. In this article, we study one such environment, smart home, and establish inconsistencies manifesting out of failures. We propose an abstraction called
transactuation
that empowers developers to build reliable applications. Our runtime,
Relacs
, implements the abstraction atop a real smart-home platform. We evaluate programmability, performance, and effectiveness of
transactuations
to demonstrate its potential as a powerful abstraction and execution model.
Planar Graph Perfect Matching Is in NC
Authors: Anari Nima , Vazirani Vijay V.
Published: May 2020

Is perfect matching in NC? That is, is there a deterministic fast parallel algorithm for it? This has been an outstanding open question in theoretical computer science for over three decades, ever since the discovery of RNC perfect matching algorithms. Within this question, the case of planar graphs has remained an enigma: On the one hand, counting the number of perfect matchings is far harder than finding one (the former is #P-complete and the latter is in P), and on the other, for planar graphs, counting has long been known to be in NC whereas finding one has resisted a solution.

In this article, we give an NC algorithm for finding a perfect matching in a planar graph. Our algorithm uses the above-stated fact about counting perfect matchings in a crucial way. Our main new idea is an NC algorithm for finding a face of the perfect matching polytope at which a set (which could be polynomially large) of conditions, involving constraints of the polytope, are simultaneously satisfied. Several other ideas are also needed, such as finding, in NC, a point in the interior of the minimum-weight face of this polytope and finding a balanced tight odd set.
GIS-Based Irrigation Dams Potential Assessment of Floating Solar PV System
Authors: Nebey Abraham Hizkiel , Taye Biniyam Zemene , Workineh Tewodros Gera
Published: May 2020

The majority of the Ethiopian population lives in rural areas and uses wood for domestic energy consumption. Using wood and fuel for domestic uses accounts for deforestation and health problems, which is also dangerous for the environment. The Ethiopian government has been planning to generate power from available renewable resources around the community. Therefore, determining the water surface potential of energy harvesting with floating solar photovoltaic system by using geographic information system is used to support decision-makers to use high potential areas. To identify useable areas for floating solar photovoltaic, factors that affect the usability were identified and weighted by using Analytical Hierarchy Processes. Thus, weighted values and reclassified values were multiplied to do the final usability map of floating solar photovoltaic with ArcGIS software. Due to the improper location of floating solar photovoltaic, efficiency is dropped. Therefore, the objective of this study was to identify the most usable surface of water bodies in Amhara regional, state irrigation dams for generating electrical power. The usability of the water surface for floating solar photovoltaic power plant was 63.83%, 61.09%, and 57.20% of Angereb, Rib, and Koga irrigation dams, respectively. The majority of the usable areas were found in the middle of the water surface. Nature water surface is a key factor in generating solar energy; it affects the floating solar photovoltaic and irradiance coming to the solar photovoltaic panel surface.
Fixed Point Theorems for Generalized Kannan-Type Mappings in a New Type of Fuzzy Metric Space
Authors: Zhou Mi , Liu Xiao-lan , Secelean Nicolae Adrian
Published: May 2020

In this paper, first, we introduce a new type of S∗−fuzzy metric space which is a generalization of fuzzy metric spaces. Second, we study the topological properties of S∗−fuzzy metric spaces. Finally, we extend Kannan-type mappings to generalized Kannan-type mappings under ϕ−gauge functions introduced by Fang in S∗−fuzzy metric spaces and prove the existence and uniqueness of fixed point for this kind of mappings. Furthermore, we also obtain the common fixed point theorems for weak compatibility along with E.A. property or CLRg property. Our results extend and improve very recent theorems in the related literature.
Comparative Analysis of Soil‐Water Characteristic Curve in Fractal and Empirical Models
Authors: Tao Gaoliang , Chen Yangyang , Xiao Henglin , Chen Yin , Peng Wan
Published: June 2020

The fitting analysis of soil‐water characteristic curve (SWCC) is the foundation of engineering properties of unsaturated soils. The purpose of this paper is to explore the differences of fitting effects between different fractal and empirical models as well as the effect of residual water content θr on the model fitting. The experimental SWCCs of Hunan clay at different initial dry densities are measured by pressure plate instrument, and then they are fitted by fractal and empirical models. The effect of the limit of θr on the fitting results is analyzed by comparing the results of indoor evaporation test. The results show that within the measured data point range, fractal model II‐2 and van Genuchten model (VG model) have the best fitting effect, fractal models I and II‐1 take the second place, and the fitting effect of Gardner model is the worst. When the matrix suction is more than the measured data, the fitting accuracy of the model is poor. For the model with θr, reasonable limit range of θr can only improve the fitting accuracy of the model to a certain extent. For the fractal model, the fitting accuracy of the model can be improved effectively when θr is considered. Furthermore, the difference of fractal dimension and air‐entry value in various fractal models are also discussed in this paper.
Combination of Spectral Representation and Wavelet Packets for Generating Long‐Period Ground Motions
Authors: Dai Minghui , Li Yingmin
Published: May 2020

Far‐field long‐period ground motions (hereafter long‐period ground motions) featuring low‐frequency components are responsible for the resonant responses of high‐rise buildings. In this context, it is beneficial to assess the dynamic performance of these buildings under long‐period ground motions with the aid of time history analysis. This paper proposes a method for generating long‐period motions by combining long‐period components synthesized by spectral representation with high‐frequency components simulated by wavelet packets. Later‐arriving long‐period surface waves (LALP surface waves), which are determined on the grounds of phase dispersion, represent the main long‐period properties in sense of velocity spectrum at longer periods of interest. An analytical expression for power spectrum density is employed to capture the narrowband properties of LALP velocity surface waves. Meanwhile, modification of the Gaussian random process is performed in time and frequency domains to attain a modulated initial seed motion, which shows the variability of the targeted ground motion. A simulation of high‐frequency components is accomplished by means of iteration, in which wavelet coefficients of the modulated seed motion are adjusted to match the targeted response spectrum and cumulative energy plot. Furthermore, comparisons between an ensemble of realizations and target motions demonstrate the feasibility of the proposed method to generate long‐period simulations sharing similar properties to target motions.
In Vitro Evaluation of Curcumin‐Encapsulated Chitosan Nanoparticles against Feline Infectious Peritonitis Virus and Pharmacokinetics Study in Cats
Authors: Ng Shing Wei , Selvarajah Gayathri Thevi , Hussein Mohd Zobir , Yeap Swee Keong , Omar Abdul Rahman
Published: May 2020

Feline infectious peritonitis (FIP) is an important feline viral disease, causing an overridden inflammatory response that results in a high mortality rate, primarily in young cats. Curcumin is notable for its biological activities against various viral diseases; however, its poor bioavailability has hindered its potential in therapeutic application. In this study, curcumin was encapsulated in chitosan nanoparticles to improve its bioavailability. Curcumin‐encapsulated chitosan (Cur‐CS) nanoparticles were synthesised based on the ionic gelation technique and were spherical and cuboidal in shape, with an average particle size of 330 nm and +42 mV in zeta potential. The nanoparticles exerted lower toxicity in Crandell‐Rees feline kidney (CrFK) cells and enhanced antiviral activities with a selective index (SI) value three times higher than that of curcumin. Feline‐specific bead‐based multiplex immunoassay and qPCR were used to examine their modulatory effects on proinflammatory cytokines, including tumour necrosis factor (TNF)α, interleukin‐ (IL‐) 6, and IL‐1β. There were significant decrements in IL‐1β, IL‐6, and TNFα expression in both curcumin and Cur‐CS nanoparticles. Based on the multiplex immunoassay, curcumin and the Cur‐CS nanoparticles could lower the immune‐related proteins in FIP virus (FIPV) infection. The single‐ and multiple‐dose pharmacokinetics profiles of curcumin and the Cur‐CS nanoparticles were determined by high‐performance liquid chromatography (HPLC). Oral delivery of the Cur‐CS nanoparticles to cats showed enhanced bioavailability with a maximum plasma concentration (Cmax) value of 621.5 ng/mL. Incorporating chitosan nanoparticles to deliver curcumin improved the oral bioavailability and antiviral effects of curcumin against FIPV infection. This study provides evidence for the potential of Cur‐CS nanoparticles as a supplementary treatment of FIP.
Poly(vinyl alcohol boric acid)-Diclofenac Sodium Salt Drug Delivery Systems: Experimental and Theoretical Studies
Authors: Ailincai Daniela , Dorobanțu Alexandra Maria , Dima Bogdan , Irimiciuc Ștefan Andrei , Lupașcu Cristian , Agop Maricel , Olguta Orzan
Published: May 2020

The main aim of the paper was to simulate the drug release by a multifractal theoretical model, as a valuable method to assess the drug release mechanism. To do this, drug delivery films were prepared by mixing poly(vinyl alcohol boric acid) (PVAB) and diclofenac (DCF) sodium salt drug in different mass ratios from 90/10 to 70/30, in order to obtain drug delivery systems with different releasing rates. The different drug content of the three systems was confirmed by energy-dispersive spectroscopy (EDAX) analysis, and the encapsulation particularities were investigated by scanning electron microscopy (SEM), atomic force microscopy (AFM), and polarized optical microscopy (POM) techniques. The ability of the PVAB matrix to anchor the DCF was assessed by Fourier transform infrared (FTIR) spectroscopy. The in vitro release of the diclofenac sodium salt from the formulations was investigated in biomimetic conditions (pH=7.4 and 37°C) by UV-Vis spectroscopy, measuring the absorbance of the drug at 275 nm and fitting the results on a previously drawn calibration curve. An estimation of the drug release kinetics was performed by fitting three traditional mathematical models on experimental release data. Further, the drug delivery was simulated by the fractal theory of motion, in which the release dynamics of the polymer-drug complex system is described through various Riccati-type “regimes.” To explain such dynamics involved multifractal self-modulation in the form of period doubling, quasiperiodicity, intermittency, etc., as well as multifractal self-modulation of network type. Standard release dynamics were explained by multifractal behaviors of temporary kink type. The good correlation between the traditional mathematical models and the new proposed theoretical model demonstrated the validity of the multifractal model for the investigation of the drug release.
An Intelligent Fuzzy Rule-Based Personalized News Recommendation Using Social Media Mining
Authors: Manoharan Saravanapriya , Senthilkumar Radha
Published: May 2020

Recommendation of a relevant and suitable news article is an essential but a challenging task due to changes in the user interest categories over time. Moreover, the Internet technology provides abundant news articles from a huge amount of resources. Meanwhile, nowadays, many people are confronted with viral news articles through social media cost-free without considering the news sites. Therefore, mining of social media for addressing such viral news articles has become another key challenge. To overcome the above challenges, this paper proposes fuzzy logic approach for predicting users’ diversified interest and its categories by analysing their implicit user profile. Depending on users’ interest categories, the viral news articles and their categories were determined and analysed through mining social media feeds-Facebook and Twitter. Furthermore, fresh news articles are retrieved from news feeds incorporated with retrieved viral news articles provided as recommendation with respect to users’ diversified interest. The performance of the proposed approach for predicting overall users’ interest for all categories attained 84.238%, and recommendation accuracy from News feed, Facebook, and Twitter attained 100%, 90%, and 100% with respect to users’ interest categories.
A Feasible Approach to Detect Pesticides in Food Samples Using THz-FDS and Chemometrics
Authors: Chen Qian , Jia Shengyao , Qin Jianyuan , Du Yong , Zhao Zongshan
Published: May 2020

The use of pesticides will have an impact on food, organisms, and environment. Specifically, pesticide residues in food will damage human health. Because of its high permeability, low energy, high spectral resolution, and fingerprint characteristics, terahertz frequency-domain spectroscopy has been introduced into the determination of pesticides (imidacloprid, acetamiprid, and triadimefon) residues in food samples (glutinous rice flour, wheat flour, and corn flour) in our present study. These three pesticides exhibit their own absorption peaks in the region of 0.4–1.7 THz. For understanding the origins of these peaks, the experimental data are interpreted by using density functional theory calculations at the level of B3LYP/6-31G (d). It is found that these absorption peaks come from the intramolecular and intermolecular interactions. The absorption peaks of pesticides are still detectable in a mixture of pesticides and food samples when they reach a certain concentration. The results from chemometrics analysis show that quantitative detection of pesticides in food samples is feasible. The partial least squares regression models have high correlation coefficient (>0.99), low root-mean-square error of calibration (<1.5%), low root-mean-square error of cross-validation (<2.4%), and low root-mean-square error of prediction (<2.3%), indicating good quality of prediction for pesticides concentration. Our results prove that the terahertz frequency-domain spectrum combined with chemometrics can be used for the detection of pesticides in food samples.
Experimental and Numerical Study on Characterization and Evaluation of Surface Cracks with Wireless Ultrasonic Sensor
Authors: Chen Shuo , Li Jing , Huang Donghui , Chen Yuzhi , Zhao Haitao
Published: May 2020

Adopting both wireless ultrasonic sensing and numerical simulation techniques, this research investigates the interaction between Rayleigh wave and artificial surface cracks of varying depths. When analyzing experimental ultrasonic data collected by a wireless sensing node, the signals are enhanced through a two-step procedure including signal reconstruction and envelope extraction. The waveforms are interpreted in detail by analyzing wave components through time-of-flight technique. A finite element (FE) model is devised to properly simulate the experimental testing. The simulated waveforms are consistent with experimental results and corroborate the analysis and explanations of experimental waveforms. Based on both experimental and numerical waveform analysis, a relationship between ultrasonic characteristic parameter and crack size is established for the quantitative estimation purpose. The proposed model shows a good agreement with data from both test and literatures.
Uncertainties Analysis on the Prediction of Flow and Heat Transfer of Liquid Sodium with CFD Technology
Authors: Liu Zhanwei , Li Xinyu , Cong Tenglong , Zhang Rui , Zheng Lingyun , Deng Hang , Cui Yuning
Published: May 2020

The prediction of flow and heat transfer characteristics of liquid sodium with CFD technology is of significant importance for the design and safety analysis of sodium-cooled fast reactor. The accuracies and uncertainties of the CFD models should be evaluated to improve the confidence of the numerical results. In this work, the uncertainties from the turbulent model, boundary conditions, and physical properties for the flow and heat transfer of liquid sodium were evaluated against the experimental data. The results of uncertainty quantization show that the maximum uncertainties of the Nusselt number and friction coefficient occurred in the transition zone from the inlet to the fully developed region in the circular tube, while they occurred near the reattachment point in the backward-facing step. Furthermore, in backward-facing step flow, the maximum uncertainty of temperature migrated from the heating wall to the geometric center of the channel, while the maximum uncertainty of velocity occurred near the vortex zone. The results of sensitivity analysis illustrate that the Nusselt number was negatively correlated with the thermal conductivity and turbulent Prandtl number, while the friction coefficient was positively correlated with the density and Von Karman constant. This work can be a reference to evaluate the accuracy of the standard k-ε model in predicting the flow and heat transfer characteristics of liquid sodium.
Three-Dimensional Path Planning of Constant Thrust Unmanned Aerial Vehicle Based on Artificial Fluid Method
Authors: Qi Yongqiang , Li Shuai , Ke Yi
Published: May 2020

In this paper, a three-dimensional path planning problem of an unmanned aerial vehicle under constant thrust is studied based on the artificial fluid method. The effect of obstacles on the original fluid field is quantified by the perturbation matrix, the streamlines can be regarded as the planned path for the unmanned aerial vehicle, and the tangential vector and the disturbance matrix of the artificial fluid method are improved. In particular, this paper addresses a novel algorithm of constant thrust fitting which is proposed through the impulse compensation, and then the constant thrust switching control scheme based on the isochronous interpolation method is given. It is proved that the planned path can avoid all obstacles smoothly and swiftly and reach the destination eventually. Simulation results demonstrate the effectiveness of this method.
V-Proximal Trustworthy Banach Spaces
Authors: Bounkhel Messaoud , Bachar Mostafa
Published: June 2020

In a recent work (2016), the first author proved the fuzzy sum rule for the V-proximal subdifferential under some natural assumptions on an equivalent norm of the Banach spaces. In the present paper, we are going to prove that the class of Banach spaces satisfying the fuzzy sum rule is very large and contains all Lp spaces 1<p<∞ as well as the sequence spaces lp1<p<∞, the Sobolev spaces Wp,n1<p<∞, and the Schatten trace ideals Cp1<p<∞.
Chinese Tone Recognition Based on 3D Dynamic Muscle Information
Authors: Wang JianRong , Wan Li , Zhang Ju , Fang Qiang , Yang Fan , Hu Jing
Published: May 2020

To advance the study of lip-reading recognition in accordance with Chinese pronunciation norms, we carefully investigated Mandarin tone recognition based on visual information, in contrast to that of the previous character-based Chinese lip reading technique. In this paper, we mainly studied the vowel tonal transformation in Chinese pronunciation and designed a lightweight skipping convolution network framework (SCNet). And, the experimental results showed that the SCNet was sensitive to the more detailed description of the pitch change than that of the traditional model and achieved a better tone recognition effect and outstanding antiinterference performance. In addition, we conducted a more detailed study on the assistance of the deep texture information in lip-reading recognition. We found that the deep texture information has a significant effect on tone recognition, and the possibility of multimodal lip reading in Chinese tone recognition was confirmed. Similarly, we verified the role of the SCNet syllable tone recognition and found that the vowel and syllable tone recognition accuracy of our model was as high as 97.3%, which also showed the robustness of our proposed method for Chinese tone recognition and it can be widely used for tone recognition.
Evaluating Encryption Algorithms for Sensitive Data Using Different Storage Devices
Authors: Sassani (Sarrafpour) Bahman A. , Alkorbi Mohammed , Jamil Noreen , Naeem M. Asif , Mirza Farhaan
Published: May 2020

Sensitive data need to be protected from being stolen and read by unauthorized persons regardless of whether the data are stored in hard drives, flash memory, laptops, desktops, and other storage devices. In an enterprise environment where sensitive data is stored on storage devices, such as financial or military data, encryption is used in the storage device to ensure data confidentiality. Nowadays, the SSD-based NAND storage devices are favored over HDD and SSHD to store data because they offer increased performance and reduced access latency to the client. In this paper, the performance of different symmetric encryption algorithms is evaluated on HDD, SSHD, and SSD-based NAND MLC flash memory using two different storage encryption software. Based on the experiments we carried out, Advanced Encryption Standard (AES) algorithm on HDD outperforms Serpent and Twofish algorithms in terms of random read speed and write speed (both sequentially and randomly), whereas Twofish algorithm is slightly faster than AES in sequential reading on SSHD and SSD-based NAND MLC flash memory. By conducting full range of evaluative tests across HDD, SSHD, and SSD, our experimental results can give better idea for the storage consumers to determine which kind of storage device and encryption algorithm is suitable for their purposes. This will give them an opportunity to continuously achieve the best performance of the storage device and secure their sensitive data.
A Joint Back-Translation and Transfer Learning Method for Low-Resource Neural Machine Translation
Authors: Luo Gong-Xu , Yang Ya-Ting , Dong Rui , Chen Yan-Hong , Zhang Wen-Bo
Published: May 2020

Neural machine translation (NMT) for low-resource languages has drawn great attention in recent years. In this paper, we propose a joint back-translation and transfer learning method for low-resource languages. It is widely recognized that data augmentation methods and transfer learning methods are both straight forward and effective ways for low-resource problems. However, existing methods, which utilize one of these methods alone, limit the capacity of NMT models for low-resource problems. In order to make full use of the advantages of existing methods and further improve the translation performance of low-resource languages, we propose a new method to perfectly integrate the back-translation method with mainstream transfer learning architectures, which can not only initialize the NMT model by transferring parameters of the pretrained models, but also generate synthetic parallel data by translating large-scale monolingual data of the target side to boost the fluency of translations. We conduct experiments to explore the effectiveness of the joint method by incorporating back-translation into the parent-child and the hierarchical transfer learning architecture. In addition, different preprocessing and training methods are explored to get better performance. Experimental results on Uygur-Chinese and Turkish-English translation demonstrate the superiority of the proposed method over the baselines that use single methods.
Multiobjective Optimized Dispatching for Integrated Energy System Based on Hierarchical Progressive Parallel NSGA-II Algorithm
Authors: Zeng Aidong , Hao Sipeng , Ning Jia , Xu Qingshan , Jiang Ling
Published: May 2020

Considering the importance of reducing system operating costs and controlling pollutant emissions by optimizing the operation of the integrated energy system, the energy supply structure of the integrated energy system and the joint multiobjective optimization dispatching structure is analyzed in this paper based on a day-ahead economic optimization dispatching model of the integrated energy system. Afterwards, the multiobjective optimization model of the integrated energy system is studied and multiobjective hierarchical progressive parallel algorithm based on improved NSGA-II is proposed according to the characteristics of the model. The algorithm improves the nondominated layer sorting algorithm, changes the convergence judgment condition while introducing the target reaching method to accelerate convergence, and introduces parallel computing technology according to the characteristics of the algorithm. The case shows that the proposed algorithm not only has advantages on the diversity in searching solutions but also can achieve better results in many aspects such as the iteration time and algorithm convergence which are required in practical engineering projects.
On Generalized Schur Numbers of the Equation x+ay=z
Authors: Khamseh Amir
Published: May 2020

Let a and r be positive integers. By definition, sar is the least positive integer such that, for any r-coloring of the interval 1,sar, there exists a monochromatic solution to x+ay=z. For a=1, the numbers sr=s1r are classical Schur numbers. In this paper, we study the numbers sar for a≥2.
Fixed-Time Flocking Problem of a Cucker–Smale Model
Authors: Nie Fen , Liu Yicheng
Published: May 2020

In this paper, we studied a Cucker–Smale model with continuous non-Lipschitz protocol. The methodology presented in the current work is based on the explicit construction of a Lyapunov functional. By using the fixed-time control technology, we show that the flocking can occur in fixed time if the communication rate function is locally Lipschitz continuous and has a lower bound, and we can obtain the estimation of the converging time which is independent of the initial states of agents. Theoretical results are supported by numerical simulations.