bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanisms of Insulin Action and Insulin Resistance
Authors: Petersen Max C. , Shulman Gerald I.
Published: August 2018

The 1921 discovery of insulin was a Big Bang from which a vast and expanding universe of research into insulin action and resistance has issued. In the intervening century, some discoveries have matured, coalescing into solid and fertile ground for clinical application; others remain incompletely investigated and scientifically controversial. Here, we attempt to synthesize this work to guide further mechanistic investigation and to inform the development of novel therapies for type 2 diabetes (T2D). The rational development of such therapies necessitates detailed knowledge of one of the key pathophysiological processes involved in T2D: insulin resistance. Understanding insulin resistance, in turn, requires knowledge of normal insulin action. In this review, both the physiology of insulin action and the pathophysiology of insulin resistance are described, focusing on three key insulin target tissues: skeletal muscle, liver, and white adipose tissue. We aim to develop an integrated physiological perspective, placing the intricate signaling effectors that carry out the cell-autonomous response to insulin in the context of the tissue-specific functions that generate the coordinated organismal response. First, in section II, the effectors and effects of direct, cell-autonomous insulin action in muscle, liver, and white adipose tissue are reviewed, beginning at the insulin receptor and working downstream. Section III considers the critical and underappreciated role of tissue crosstalk in whole body insulin action, especially the essential interaction between adipose lipolysis and hepatic gluconeogenesis. The pathophysiology of insulin resistance is then described in section IV. Special attention is given to which signaling pathways and functions become insulin resistant in the setting of chronic overnutrition, and an alternative explanation for the phenomenon of ‟selective hepatic insulin resistanceˮ is presented. Sections V, VI, and VII critically examine the evidence for and against several putative mediators of insulin resistance. Section V reviews work linking the bioactive lipids diacylglycerol, ceramide, and acylcarnitine to insulin resistance; section VI considers the impact of nutrient stresses in the endoplasmic reticulum and mitochondria on insulin resistance; and section VII discusses non-cell autonomous factors proposed to induce insulin resistance, including inflammatory mediators, branched-chain amino acids, adipokines, and hepatokines. Finally, in section VIII, we propose an integrated model of insulin resistance that links these mediators to final common pathways of metabolite-driven gluconeogenesis and ectopic lipid accumulation.
An Open IoT Platform to Promote Eco‐Sustainable Innovation in Western Africa: Real Urban and Rural Testbeds
Authors: Dupont Corentin , Vecchio Massimo , Pham Congduc , Diop Babacar , Dupont Charlotte , Koffi Sename
Published: August 2018

The digital revolution led by the Internet of Things (IoT) is already reshaping several traditional business sectors. Moreover, because of its very nature, the promise of the IoT is also to reduce energy consumption and pollutant emissions in several environmental scenarios. At the same time, it is desirable to keep the development of IoT as sustainable as possible, hence truly realizing the vision of the green IoT. In this paper, we show how a full‐stack IoT framework can alleviate some real environmental problems afflicting countries in Western Africa. We present three real IoT‐based deployments currently hosted in two rural areas of Senegal and Ghana and one metropolitan area of Togo. These testbeds are connected to a Cloud‐based software platform, purposely designed and engineered to address some very specific environmental, economic, and social requirements of the region.
Ensemble Prediction Algorithm of Anomaly Monitoring Based on Big Data Analysis Platform of Open‐Pit Mine Slope
Authors: Jiang Song , Lian Minjie , Lu Caiwu , Gu Qinghua , Ruan Shunling , Xie Xuecai
Published: August 2018

With the diversification of pit mine slope monitoring and the development of new technologies such as multisource data flow monitoring, normal alert log processing system cannot fulfil the log analysis expectation at the scale of big data. In order to make up this disadvantage, this research will provide an ensemble prediction algorithm of anomalous system data based on time series and an evaluation system for the algorithm. This algorithm integrates multiple classifier prediction algorithms and proceeds classified forecast for data collected, which can optimize the accuracy in predicting the anomaly data in the system. The algorithm and evaluation system is tested by using the microseismic monitoring data of an open‐pit mine slope over 6 months. Testing results illustrate prediction algorithm provided by this research can successfully integrate the advantage of multiple algorithms to increase the accuracy of prediction. In addition, the evaluation system greatly supports the algorithm, which enhances the stability of log analysis platform.
Fuzzy Sliding Mode Based Series Hybrid Active Power Filter for Power Quality Enhancement
Authors: Das Soumya Ranjan , Ray Prakash K. , Mohanty Asit
Published: August 2018

This paper contributes an innovative gating signal generation technique based on fuzzy sliding mode pulse width modulation (FSMPWM) with a Series Hybrid Active Power Filter (SEHAPF) for reducing the total harmonic distortion (THD). Hybrid filters are used for compensating reactive power on the load side and mitigate harmonics for the growth of power quality under variable source and load conditions in the utility system. The objective of the paper is to eradicate the various power quality (PQ) problems with development in power factor and reducing distortion in transmission and distribution line due to harmonics. With the implementation of FSMPWM of the proposed filter, the gating pulses are generated by implementing a Mamdani fuzzy rule with sliding surfaces. For producing a fixed pulse the presented method reduces the chattering reaction by controlling the narrow boundary coating on the sliding surface. The results of the projected technique are analyzed and compared with the traditional hysteresis band current controller (HCC). The overall proficiency and results are examined with the help of MATLAB/SIMULINK environment.
A High-Density L-Shaped Backscattering Chipless Tag for RFID Bistatic Systems
Authors: Issa Khaled , Alshoudokhi Yazeed A. , Ashraf Muhammad A. , AlShareef Mohammed R. , Behairy Hatim M. , Alshebeili S. , Fathallah H.
Published: August 2018

Chipless radiofrequency identification (RFID) technology is very promising for sensing, identification, and tracking for future Internet of Things (IoT) systems and applications. In this paper, we propose and demonstrate a compact 18-bit, dual polarized chipless RFID tag. The proposed tag is based on L-shaped resonators designed so as to maximize the spectral and spatial encoding capacities. The proposed RFID tag operates an over 4 GHz frequency band (i.e., 6.5 GHz to 10.5 GHz). The tag is simulated, fabricated, and tested in a nonanechoic milieu. The measured data have shown good agreement with the simulation results, with respect to resonators’ frequency positions, null depth, and null bandwidth over the operating spectrum. The proposed design achieves spectral and spatial encoding capacities of 4.5 bits/GHz and 18.8 bits/cm2, respectively. This, in turn, gives an encoding density of 4.7 bits/GHz/cm2. For code identification, we exploit the frequency content of the backscattered signals and identify similarity/correlation features with reference codes.
Radial Symmetry and Monotonicity of Solutions to a System Involving Fractional p-Laplacian in a Ball
Authors: Cao Linfen , Wang Xiaoshan , Dai Zhaohui
Published: August 2018

In this paper, we study a nonlinear system involving the fractional p-Laplacian in a unit ball and establish the radial symmetry and monotonicity of its positive solutions. By using the direct method of moving planes, we prove the following result. For 0<s,t<1,p>0, if u and v satisfy the following nonlinear system -Δpsux=fvx;  -Δptvx=gux,  x∈B10;  ux,vx=0,  x∉B10. and f,g are nonnegative continuous functions satisfying the following: (i) f(r) and g(r) are increasing for r>0; (ii) f′(r)/rp-2, g′(r)/rp-2 are bounded near r=0. Then the positive solutions (u,v) must be radially symmetric and monotone decreasing about the origin.
Providing Nutrition Care to Patients with Chronic Disease: An Irish Teaching Hospital Healthcare Professional Study
Authors: Keaver Laura , O’Meara Ciara , Mukhtar Mohsin , McHugh Catherine
Published: August 2018

An increasing prevalence of noncommunicable diseases (NCDs) and chronic illness is putting an ever increasing burden on healthcare services and delivery worldwide. Diet contributes significantly to the development of NCDs. Nutrition should therefore be viewed as an important aspect of patient care and be addressed by all healthcare professionals (HCPs). Previous work has highlighted a lack of competency around providing nutrition advice in HCPs; however, positive attitudes towards the importance of nutrition care are well documented in this group. The aim of this study is to document and compare Irish HCPs self-perceived competency towards incorporating nutrition care into practice. The NUTCOMP questionnaire was completed by 206 HCPs in Sligo University Hospital. The findings showed positive attitudes towards the incorporation of nutrition care into HCP practice; however, confidence in knowledge and skills was low, thus missing vital opportunities to prevent and/or treat chronic diseases and improve outcomes in acute illness. Previous nutrition education was associated with greater self-perceived knowledge about and skills in providing nutrition care to patients and positively associated with attitudes towards incorporating nutrition care into practice. HCPs expressed a desire and unmet need for additional and ongoing educational intervention in the area of nutritional intervention.
Transcoding Based Video Caching Systems: Model and Algorithm
Authors: Zhao Hongna , Li Chunxi , Zhao Yongxiang , Zhang Baoxian , Li Cheng
Published: August 2018

The explosive demand of online video watching brings huge bandwidth pressure to cellular networks. Efficient video caching is critical for providing high‐quality streaming Video‐on‐Demand (VoD) services to satisfy the rapid increasing demands of online video watching from mobile users. Traditional caching algorithms typically treat individual video files separately and they tend to keep the most popular video files in cache. However, in reality, one video typically corresponds to multiple different files (versions) with different sizes and also different video resolutions. Thus, caching of such files for one video leads to a lot of redundancy since one version of a video can be utilized to produce other versions of the video by using certain video coding techniques. Recently, fog computing pushes computing power to edge of network to reduce distance between service provider and users. In this paper, we take advantage of fog computing and deploy cache system at network edge. Specifically, we study transcoding based video caching in cellular networks where cache servers are deployed at the edge of cellular network for providing improved quality of online VoD services to mobile users. By using transcoding, a cached video can be used to convert to different low‐quality versions of the video as needed by different users in real time. We first formulate the transcoding based caching problem as integer linear programming problem. Then we propose a Transcoding based Caching Algorithm (TCA), which iteratively finds the placement leading to the maximal delay gain among all possible choices. We deduce the computational complexity of TCA. Simulation results demonstrate that TCA significantly outperforms traditional greedy caching algorithm with a decrease of up to 40% in terms of average delivery delay.
A Novel Differential Game Model-Based Intrusion Response Strategy in Fog Computing
Authors: An Xingshuo , Lin Fuhong , Xu Shenggang , Miao Li , Gong Chao
Published: August 2018

Fog computing is an emerging network paradigm. Due to its characteristics (e.g., geo-location and constrained resource), fog computing is subject to a broad range of security threats. Intrusion detection system (IDS) is an essential security technology to deal with the security threats in fog computing. We have introduced a fog computing IDS (FC-IDS) framework in our previous work. In this paper, we study the optimal intrusion response strategy in fog computing based on the FC-IDS scheme proposed in our previous work. We postulate the intrusion process in fog computing and describe it with a mathematical model based on differential game theory. According to this model, the optimal response strategy is obtained corresponding to the optimal intrusion strategy. Theoretical analysis and simulation results demonstrate that our security model can effectively stabilize the intrusion frequency of the invaders in fog computing.
Evaluation of Separate and Simultaneous Kinetic Parameters for Levulinic Acid and Furfural Production from Pretreated Palm Oil Empty Fruit Bunches
Authors: Gozan Misri , Panjaitan Jabosar Ronggur Hamonangan , Tristantini Dewi , Alamsyah Rizal , Yoo Young Je
Published: August 2018

Palm oil empty fruit bunches (POEFBs) can be converted into levulinic acid (LA) and furfural, which are among the top building-block chemicals. The purpose of this study was to investigate separate and simultaneous kinetic model parameters for LA and furfural production from POEFBs, which were pretreated by soaking in aqueous ammonia (SAA). The highest LA yield, which was obtained at a reaction temperature of 170°C after 90 min in an acidic solution with a concentration of 1 M, was 52.1 mol%. The highest furfural yield was 27.94 mol%, which was obtained at a reaction temperature of 170°C after 20 min in an acidic solution with a concentration of 0.5 M. SAA pretreatment affected activation energy in glucose degradation reactions and favoured direct conversion of hemicellulose to furfural. The activation energy of LA production (EakHMF) increases with higher acid catalyst concentration, and the activation energy of furfural production (EakXYN) decreases with higher acid concentration. These trends in the activation energy occurred in both separate and simultaneous kinetic models. Simultaneous kinetic model is better to calculate kinetic parameters of LA and furfural production than separate kinetic models because the simultaneous kinetic model had a lower sum of square error (SSE) when estimating kinetic parameters.
Similarity‐Based Summarization of Music Files for Support Vector Machines
Authors: Jakubik Jan , Kwaśnicka Halina
Published: August 2018

Automatic retrieval of music information is an active area of research in which problems such as automatically assigning genres or descriptors of emotional content to music emerge. Recent advancements in the area rely on the use of deep learning, which allows researchers to operate on a low‐level description of the music. Deep neural network architectures can learn to build feature representations that summarize music files from data itself, rather than expert knowledge. In this paper, a novel approach to applying feature learning in combination with support vector machines to musical data is presented. A spectrogram of the music file, which is too complex to be processed by SVM, is first reduced to a compact representation by a recurrent neural network. An adjustment to loss function of the network is proposed so that the network learns to build a representation space that replicates a certain notion of similarity between annotations, rather than to explicitly make predictions. We evaluate the approach on five datasets, focusing on emotion recognition and complementing it with genre classification. In experiments, the proposed loss function adjustment is shown to improve results in classification and regression tasks, but only when the learned similarity notion corresponds to a kernel function employed within the SVM. These results suggest that adjusting deep learning methods to build data representations that target a specific classifier or regressor can open up new perspectives for the use of standard machine learning methods in music domain.
Association of Elevated Serum GM-CSF, IFN-γ, IL-4, and TNF-αConcentration with Tobacco Smoke Induced Chronic Obstructive Pulmonary Disease in a South Indian Population
Authors: Mitra Ankita , Vishweswaraiah Sangeetha , Thimraj Tania Ahalya , Maheswarappa Mahendra , Krishnarao Chaya Sindaghatta , Sundararaja Lokesh Komarla , Biligere Siddaiah Jayaraj , Ganguly Koustav , Anand Mahesh Padukudru
Published: August 2018

Background. Chronic obstructive pulmonary disease (COPD) is a devastating condition with limited pharmacotherapeutic options and exceptionally high public-health burden globally as well as in India. Tobacco smoking is the primary cause for COPD among men in India. Systemic inflammation involving altered regulation of cytokines controlling the host defense mechanism is a hallmark of COPD pathogenesis. However, biomarker discovery studies are limited among Indian COPD patients.Methods. We assessed the serum concentrations [median (25th-75th percentile) pg/ml] of interleukin (IL)-2,4,6,8,10, granulocyte macrophage colony stimulating factor (GM-CSF), interferon gamma (IFN-γ), and tumor necrosis factor alpha (TNF-α) using a multiplexed immunoassay. Our study cohort consisted of 30 tobacco smokers with COPD (TS COPD) and 20 tobacco smokers without COPD (TS CONTROL) from South India. The study population was matched for age, sex (male), and tobacco consumption (pack-years). COPD was diagnosed according to the global initiative for chronic obstructive lung disease (GOLD) criteria of persistent airflow obstruction determined by the ratio of postbronchodilator forced expiratory volume in 1 second/forced vital capacity (FEV1/FVC) of <0.7. A validated structured questionnaire-based survey [Burden of Obstructive Lung Disease (BOLD) study] and spirometry were performed during house to house visit of the field study. Statistical analysis included nonparametric (two-tailed) Mann–Whitney U and Spearman rank test, as appropriate (significance: p<0.05).Results. Serum GM-CSF [69.64 (46.67, 97.48); 36.78 (30.07, 53.88), p=0.014], IFN-γ[51.06 (17.00, 84.86); 11.70 (3.18, 32.81), p=0.017], IL-4 [9.09 (1.8, 19.9); 1.8 (1.8, 4.46); p=0.024], and TNF-α[20.68 (5.5, 29.26); 3.5 (3.5, 4.5); p<0.001] concentrations (pg/ml) were increased in TS COPD subjects compared to TS CONTROL. A weak correlation between lung function parameters and cytokine concentrations was detected.Conclusion. Our pilot study reveals GM-CSF, IFN-γ, IL-4, and TNF-αas plausible COPD susceptibility biomarkers within the investigated South Indian population that needs to be validated in a larger cohort.
A Task Scheduling Algorithm Based on Classification Mining in Fog Computing Environment
Authors: Liu Lindong , Qi Deyu , Zhou Naqin , Wu Yilin
Published: August 2018

Fog computing (FC) is an emerging paradigm that extends computation, communication, and storage facilities towards the edge of a network. In this heterogeneous and distributed environment, resource allocation is very important. Hence, scheduling will be a challenge to increase productivity and allocate resources appropriately to the tasks. We schedule tasks in fog computing devices based on classification data mining technique. A key contribution is that a novel classification mining algorithm I‐Apriori is proposed based on the Apriori algorithm. Another contribution is that we propose a novel task scheduling model and a TSFC (Task Scheduling in Fog Computing) algorithm based on the I‐Apriori algorithm. Association rules generated by the I‐Apriori algorithm are combined with the minimum completion time of every task in the task set. Furthermore, the task with the minimum completion time is selected to be executed at the fog node with the minimum completion time. We finally evaluate the performance of I‐Apriori and TSFC algorithm through experimental simulations. The experimental results show that TSFC algorithm has better performance on reducing the total execution time of tasks and average waiting time.
Biomimetic Approach to CO2 Reduction
Authors: Gamba Ilaria
Published: August 2018

The development of artificial photosynthetic technologies able to produce solar-fuels from CO2 reduction is a fundamental task that requires the employment of specific catalysts being accomplished. Besides, effective catalysts are also demanded to capture atmospheric CO2, mitigating the effects of its constantly increasing emission. Biomimetic transition metal complexes are considered ideal platforms to develop efficient and selective catalysts to be implemented in electrocatalytic and photocatalytic devices. These catalysts, designed according to the inspiration provided by nature, are simple synthetic molecular systems capable of mimic features of the enzymatic activity. The present review aims to focus the attention on the mechanistic and structural aspects highlighted to be necessary to promote a proper catalytic activity. The determination of these characteristics is of interest both for clarifying aspects of the catalytic cycle of natural enzymes that are still unknown and for developing synthetic molecular catalysts that can readily be applied to artificial photosynthetic devices.
Prediction of Dynamic Stability Using Mapped Chebyshev Pseudospectral Method
Authors: Choi Jae-Young , Im Dong Kyun , Park Jangho , Choi Seongim
Published: August 2018

A mapped Chebyshev pseudospectral method is extended to solve three-dimensional unsteady flow problems. As the classical Chebyshev spectral approach can lead to numerical instabilities due to ill conditioning of the spectral matrix, the Chebyshev points are evenly redistributed over the domain by an inverse sine mapping function. The mapped Chebyshev pseudospectral method can be used as an alternative time-spectral approach that uses a Chebyshev collocation operator to approximate the time derivative terms in the unsteady flow governing equations, and the method can make general applications to both nonperiodic and periodic problems. In this study, the mapped Chebyshev pseudospectral method is employed to solve three-dimensional periodic problem to verify the spectral accuracy and computational efficiency with those of the Fourier pseudospectral method and the time-accurate method. The results show a good agreement with both of the Fourier pseudospectral method and the time-accurate method. The flow solutions also demonstrate a good agreement with the experimental data. Similar to the Fourier pseudospectral method, the mapped Chebyshev pseudospectral method approximates the unsteady flow solutions with a precise accuracy at a considerably effective computational cost compared to the conventional time-accurate method.
Numerical Simulation of Dispersed Particle-Blood Flow in the Stenosed Coronary Arteries
Authors: Kaewbumrung Mongkol , Orankitjaroen Somsak , Boonkrong Pichit , Nuntadilok Buraskorn , Wiwatanapataphee Benchawan
Published: August 2018

A mathematical model of dispersed bioparticle-blood flow through the stenosed coronary artery under the pulsatile boundary conditions is proposed. Blood is assumed to be an incompressible non-Newtonian fluid and its flow is considered as turbulence described by the Reynolds-averaged Navier-Stokes equations. Bioparticles are assumed to be spherical shape with the same density as blood, and their translation and rotational motions are governed by Newtonian equations. Impact of particle movement on the blood velocity, the pressure distribution, and the wall shear stress distribution in three different severity degrees of stenosis including 25%, 50%, and 75% are investigated through the numerical simulation using ANSYS 18.2. Increasing degree of stenosis severity results in higher values of the pressure drop and wall shear stresses. The higher level of bioparticle motion directly varies with the pressure drop and wall shear stress. The area of coronary artery with higher density of bioparticles also presents the higher wall shear stress.
Joint Range‐Doppler‐Angle Estimation for OFDM‐Based RadCom System via Tensor Decomposition
Authors: Kong Bo , Wang Yuhao , Deng Xiaohua , Qin Dong
Published: August 2018

Radar and communication (RadCom) systems have received increasing attention due to their high energy efficiency and spectral efficiency. They have been identified as green communications. This paper is concerned with a joint estimation of range‐Doppler‐angle parameters for an orthogonal frequency division multiplexing (OFDM) based RadCom system. The key idea of the proposed method is to derive different factor matrices by the tensor decomposition method and then extract parameters of the targets from these factor matrices. Different from the classical tensor decomposition method via alternating least squares or higher‐order singular value decomposition, we adopt a greedy based method with each step constituted by a rank‐1 approximation subproblem. To avoid local extremum, the rank‐1 approximation is solved by using a multiple random initialized tensor power method with a comparison procedure followed. A parameterized rectification method is also proposed to incorporate the inherent structures of the factor matrices. The proposed algorithm can estimate all the parameters simultaneously without parameter pairing requirement. The numerical experiments demonstrate superior performance of the proposed algorithm compared with the existing methods.
Topological Gravity on (D,N)-Shift Superspace Formulation
Authors: Lourenço J. A. , Neto J. A. Helayël , Spalenza W.
Published: August 2018

We reassess the subject of topological gravity by following the shift supersymmetry formalism. The gauge-fixing of the theory goes under the Batalin-Vilkovisky (BV) prescription based on a diagram that contains both ghost and antighost superfields, associated with the supervielbein and the super-Lorentz connection. We extend the formulation of the topological gravity action to an arbitrary number of dimensions of the shift superspace by adopting a formulation based on the gauge-fixing for BF-type models.
Hom-Yang-Baxter Equations and Frobenius Monoidal Hom-Algebras
Authors: Chen Yuanyuan , Zhang Liangyun
Published: August 2018

It is shown that quasi-Frobenius Hom-Lie algebras are connected with a class of solutions of the classical Hom-Yang-Baxter equations. Moreover, a similar relation is discussed on Frobenius (symmetric) monoidal Hom-algebras and solutions of quantum Hom-Yang-Baxter equations. Monoidal Hom-Hopf algebras with Frobenius structures are studied at last.
Complexity Simulation on Application of Asymmetric Bionic Cross‐Section Rod in Pantographs of High‐Speed Trains
Authors: Cao Yan , Bai Yu , Wang Qiangfeng
Published: August 2018

Ground transportation means and aircrafts with high‐speed running are composed of many rod components. Aerodynamic noise generated therefrom is very outstanding. Reduction of the aerodynamic noise of rods becomes a hot topic in recent years. Most reported studies are tentative researches on aerodynamic noise of a pantograph or involve noise reduction of the pantograph with using porous materials or reshaping rod surfaces. Through using porous materials and reshaping rod surface, the aerodynamic noise of pantograph can be reduced to a certain extent, but the aerodynamic resistance will be increased and it is not convenient for practical application in engineering. Regarding this situation, the paper explores noise reduction performance of a feather on the back of a carrier pigeon and conducts the bionic design on rod surface. Through numerical simulation, the paper researches noise reduction performance of the bionic structure on the rod surface, reveals the mechanism of bionic noise reduction, and explores noise reduction effects of bionic structural rods on pantographs of the high‐speed trains.
Oviposition Deterrent Efficacy and Characteristics of a Botanical Natural Product,Ocimum gratissimum(L.) Oil-Alginate Beads, againstAedes aegypti(L.)
Authors: Harikarnpakdee Saraporn , Chuchote Chomnapas
Published: August 2018

This study was aimed at investigating the oviposition deterrent activity ofOcimum gratissimum(L.) essential oil (O. gratissimumoil) and its product,Ocimum gratissimum(L.)- alginate beads (beads), againstAedes aegypti(Ae. aegypti) mosquitoes. Chemical analysis ofO. gratissimumoil obtained by hydrodistillation, using gas chromatography-mass spectroscopy techniques, presented eugenol (67.38%) and Z-β-ocimene (14.95 %) as major constituents. Good characteristics of beads were obtained by the orifice-ionic gelation method with calcium chloride as hardening agent and Tween®20 as emulsifier. The beads exhibited a good spherical shape and good hardness and flexibility with an average size of 1.49 ± 1.36 mm. The oil content, the yield percentage, and the entrapping efficiency were also examined. The beads (formulation code, F2) could prolong the essential oil release until the10thd. This beads provided a remarkably longer oviposition deterrence activity against gravidAe. aegyptiwith high percentage for 27 d, whereas freeO. gratissimumoil showed a short period of time (8 d) in this activity. The stability study showed the stability of oil content and its compositions in storage condition. These results are very affordable approaches to control the dengue fever.
The Convergence of Riemann Solutions to the Modified Chaplygin Gas Equations with a Coulomb-Like Friction Term as the Pressure Vanishes
Authors: Fan Yongqiang , Guo Lihui , Yin Gan
Published: August 2018

This paper studies the convergence of Riemann solutions to the inhomogeneous modified Chaplygin gas equations as the pressure vanishes. The delta shock waves and vacuum states occur as the pressure vanishes. The Riemann solutions of inhomogeneous modified Chaplygin gas equations are no longer self-similar. It is obviously different from the Riemann solutions of homogeneous modified Chaplygin gas equations. When the pressure vanishes, the Riemann solutions of the modified Chaplygin gas equations with a coulomb-like friction term converge to the Riemann solutions of the pressureless Euler system with a source term.
The Use of Dried Blood Spots for the Quantification of Antihypertensive Drugs
Authors: Chernonosov Alexander
Published: August 2018

Hypertension or high blood pressure is a harbinger of cardiovascular diseases. There are several classes of drugs used to treat hypertension. This review discusses the use of dried blood spots (DBSs) for the quantification by mass spectrometry (MS), tandem mass spectrometry (MS/MS), or, in some cases, by fluorescence detection methods the following antihypertensive medications: angiotensin-converting enzyme inhibitors (ramipril, ramiprilat, captopril, and lisinopril); angiotensin II receptor antagonists (valsartan, irbesartan, losartan, and losartan carboxylic acid); calcium channel blockers (verapamil, amlodipine, nifedipine, pregabalin, and diltiazem);αblockers (guanfacine, doxazosin, and prazosin);βblockers (propranolol, bisoprolol, atenolol, and metoprolol); endothelin receptor antagonists (bosentan and ambrisentan); and statins (simvastatin, atorvastatin, and rosuvastatin).
A New Default Probability Calculation Formula and Its Application under Uncertain Environments
Authors: Wu Liang , Mei Xian-bin , Sun Jian-guo
Published: August 2018

In the real world, corporate defaults will be affected by both external market shocks and counterparty risks. With this in mind, we propose a new default intensity model with counterparty risks based on both external shocks and the internal contagion effect. The effects of the external shocks and internal contagion on a company cannot, however, be observed, as uncertainty in the real world contains both randomness and fuzziness. This prevents us from determining the size of the shocks accurately. In this study, fuzzy set theory is utilized to study a looping default credit default swap (CDS) pricing model under uncertain environments. Following this, we develop a new fuzzy form pricing formula for CDS, the simulation analysis of which shows that all kinds of fuzziness in the market have a significant impact on credit spreads, and that the credit spreads, relative to the degree of external shock fuzziness, are much more sensitive. Nevertheless, for a certain degree of fuzziness in the market, credit spreads, relative to changes in counterparty risk, are much more sensitive. Using random analysis and fuzzy numbers, one can think of even more uncertain sources at play than the processes of looping default and investor subjective judgment on the financial markets, and this broadens the scope of possible credit spreads. Compared to the existing related literature, our new fuzzy form CDS pricing model with counterparty risk can consider more factors that influence default and is closer to the reality of the complexity of the dynamics of default. It can also employ the membership function to describe the fuzzy phenomenon, enable the fuzzy phenomenon to be estimated in two kinds of state, and can simultaneously reflect both the fuzziness and randomness in financial markets.
Suppressing the OFDM CFO‐Caused Constellation Symbol Phase Deviation by PAPR Reduction
Authors: Lipovac Adriana , Lipovac Vlatko , Njemčević Pamela
Published: August 2018

The well‐known major drawbacks of the Orthogonal Frequency‐Division Multiplexing (OFDM), namely, the transmitter versus receiver Carrier Frequency Offset (CFO), and the Peak‐to‐Average Power Ratio (PAPR) of the transmitted OFDM signal, may degrade the error performance, by causing Intercarrier Interference (ICI), as well as in‐band distortion and adjacent channel interference, respectively. Moreover, in spite of the utmost care given to CFO estimation and compensation in OFDM wireless systems, such as wireless local networks or the mobile radio systems of the fourth generation, e.g., the Long‐Term Evolution (LTE), still some residual CFO remains. With this regard, though so far the CFO and the PAPR have been treated independently, in this paper, we develop an Error Vector Magnitude (EVM) based analytical model for the CFO‐induced constellation symbol phase distortion, which essentially reveals that the maximal CFO‐caused squared phase deviation is linear with the instantaneous (per‐OFDM‐symbol) PAPR. This implies that any PAPR reduction technique, such as simple clipping or coding, indirectly suppresses the CFO‐induced phase deviation, too. The analytically achieved results and conclusions are tested and successfully verified by conducted Monte Carlo simulations.
Application of the Bionic Concept in Reducing the Complexity Noise and Drag of the Mega High‐Speed Train Based on Computer Simulation Technologies
Authors: Hu He-xuan , Tang Bo , Zhang Ye
Published: August 2018

Regarding the continuous development of high‐speed trains and the increase of running speeds, the aerodynamic design of high‐speed trains has become significantly important, while reduction of drag and noise comprises a significant challenge in order to optimize aerodynamic design of high‐speed trains. The design form factor of a high‐speed train is highly influenced by aerodynamic aspects including aerodynamic drag, lift force, and noise. With the high‐speed train as the object, the paper aims to take bionic concept as the entry point, selecting the hummingbird as the bionic prototype and extracting bionic elements to establish a bionic train model. Then, the finite volume method was used for numerical simulation and analysis of the aerodynamic performance and aerodynamic noise of the bionic high‐speed train. Computational results prove that drag and noise of the bionic head type were lower than those of the original train; drag of the head train of the bionic model was reduced by 2.21% in comparison with the original model, while the whole‐train drag was reduced by 3.53%, indicating that drag reduction effects are available and implying that the bionic head type could reduce drag and noise. Noise sources of the bionic train are mainly located at positions with easy airflow separation and violent turbulence motion. Large turbulence energy is in bogie areas and mainly exists at the leeward side of the bogie area. Obviously, the bogie area is the major noise source of the train. Aerodynamic noise of the bionic train in far‐field comprises a wide‐frequency range. Noises were concentrated within 613 Hz~3150 Hz. When the bionic high‐speed train ran at 350 km/h, through comparative analysis of total noise levels at observed points of the high‐speed train, it is found that this position with the maximum noise level was 25 m away from the head train nose tip, with the maximum value of 88.4 dB (A). When the bionic train ran at 600 km/h, the maximum sound pressure level at the longitudinal point was 99.7 dB (A) and the average noise level was 96.6 dB (A). When the running speed increased from 350 km/h to 600 km/h, the maximum noise level increased by 11.3 dB (A) and the average noise level increased by 11.6 dB (A). Computation results of aerodynamic noise at the point which is 7.5 m away from the rail center show that the maximum aerodynamic noise level existed at the first‐end bogie of the head train, while the noise level was larger at the position closer to the ground.
Solution of Some Types for Composition Fractional Order Differential Equations Corresponding to Optimal Control Problems
Authors: Qasim Hasan Sameer , Abbas Holel Moataz
Published: August 2018

The approximate solution for solving a class of composition fractional order optimal control problems (FOCPs) is suggested and studied in detail. However, the properties of Caputo and Riemann-Liouville derivatives are also given with complete details on Chebyshev approximation function to approximate the solution of fractional differential equation with different approach. Also, the relation between Caputo and Riemann-Liouville of fractional derivative took a big role for simplifying the fractional differential equation that represents the constraints of optimal control problems. The approximate solutions are defined on interval [0,1] and are compared with the exact solution of order one which is an important condition to support the working method. Finally, illustrative examples are included to confirm the efficiency and accuracy of the proposed method.
Forecasting Crude Oil Consumption in China Using a Grey Prediction Model with an Optimal Fractional‐Order Accumulating Operator
Authors: Duan Huiming , Lei Guang Rong , Shao Kailiang
Published: August 2018

Crude oil, which is an important part of energy consumption, can drive or hinder economic development based on its production and consumption. Reasonable predictions of crude oil consumption in China are meaningful. In this paper, we study the grey‐extended SIGM model, which is directly estimated with differential equations. This model has high simulation and prediction accuracies and is one of the important models in grey theory. However, to achieve the desired modeling effect, the raw data must conform to a class ratio check. Unfortunately, the characteristics of the Chinese crude oil consumption data are not suitable for SIGM modeling. Therefore, in this paper, we use a least squares estimation to study the parametric operation properties of the SIGM model, and the gamma function is used to extend the integer order accumulation sequence to the fractional‐order accumulation generation sequence. The first‐order SIGM model is extended to the fractional‐order FSIGM model. According to the particle swarm optimization (PSO) mechanism and the properties of the gamma function of the fractional‐order cumulative generation operator, the optimal fractional‐order particle swarm optimization algorithm of the FSIGM model is obtained. Finally, the data concerning China’s crude oil consumption from 2002 to 2014 are used as experimental data. The results are better than those of the classical grey GM, DGM, and NDGM models as well as those of the grey‐extended SIGM model. At the same time, according to the FSIGM model, this paper predicts China’s crude oil consumption for 2015–2020.
The Novel Nutraceutical KJS018A Prevents Hepatocarcinogenesis Promoted by Inflammation
Authors: Huynh Do Luong , Chandimali Nisansala , Zhang Jiao Jiao , Kim Nameun , Park Yang Ho , Kwon Taeho , Jeong Dong Kee
Published: August 2018

Inflammation is tightly associated with carcinogenesis at both the initiation and development of tumor. Many reports indicated that Cox‐2 substantially contributes to inflammation and tumorigenesis. The novel nutraceutical KJS018A (BRM270 Function Enhanced Products) is the extract mixture from 8 herbal plants, which have been used to inhibit cancers and inflammation. The aim of the present study is to examine the inhibitory effects of KJS018A mixture to hepatocarcinogenesis and inflammation. The results showed that KJS018A significantly inhibited the proliferation of hepatic malignant cells and downregulated levels of IL‐6 and Cox‐2. Furthermore, KJS018A diminished the effect of PMA, an inflammatory inducer via IL‐6/STAT3/Cox‐2 pathway. Furthermore, KJS018A suppressed metastatic traits of hepatic malignant cells via downregulating Twist, N‐cadherin, and MMP‐9 while restoring E‐cadherin expression. KJS018A also restrained tumor growth and levels of IL‐6 and Cox‐2 in immunohistochemistry staining. Taken together, these data suggest potential application of KJS018A in prevention of hepatocarcinogenesis promoted by inflammation.
Deep Convolutional Neural Networks for Chest Diseases Detection
Authors: Abiyev Rahib H. , Ma’aitah Mohammad Khaleel Sallam
Published: August 2018

Chest diseases are very serious health problems in the life of people. These diseases include chronic obstructive pulmonary disease, pneumonia, asthma, tuberculosis, and lung diseases. The timely diagnosis of chest diseases is very important. Many methods have been developed for this purpose. In this paper, we demonstrate the feasibility of classifying the chest pathologies in chest X-rays using conventional and deep learning approaches. In the paper, convolutional neural networks (CNNs) are presented for the diagnosis of chest diseases. The architecture of CNN and its design principle are presented. For comparative purpose, backpropagation neural networks (BPNNs) with supervised learning, competitive neural networks (CpNNs) with unsupervised learning are also constructed for diagnosis chest diseases. All the considered networks CNN, BPNN, and CpNN are trained and tested on the same chest X-ray database, and the performance of each network is discussed. Comparative results in terms of accuracy, error rate, and training time between the networks are presented.
Study of Rare Mesonic Decays Involving Di-Neutrinos in Their Final State
Authors: Mir Azeem , Tahir Farida , Mahmood Shakeel , Dong Shi- Hai
Published: August 2018

We have studied phenomenological implication of R-parity violating (Rp) Minimal Supersymmetric Model (MSSM) via analyses of pure leptonic (M→νν¯) and semileptonic decays of pseudoscalar mesons (M→Xνν¯). These analyses involve comparison between theoretical predictions made by Rp MSSM and the Standard Model (SM) with the experimental results like branching fractions (Br) of the said process. We have found, in general, that Rp contribution dominates over the SM contribution, i.e., by a factor of 10 for the pure leptonic decays of KL,S and by 102 and 104 in case of Bs and Bd, respectively. Furthermore, the limits obtained on Rp Yukawa couplings (λαkβ′λαkγ′⁎) by using Br  (M→Xνν¯) are used to calculate Br  (M→νν¯). This demonstrates the role of Rp MSSM as a viable model for the study of new physics contribution in rare decays at places like Super B factories, KOTO (J-PARC) and NA62 at CERN.
Dynamic Output Feedback Control of Discrete Markov Jump Systems based on Event-Triggered Mechanism
Authors: Zhao Zhen , Gao Jinfeng , Zhang Tingting
Published: August 2018

This paper is devoted to the co-design strategy of event-triggered scheme and dynamic output feedback controller for a class of discrete-time networked control systems (NCSs) with random time delay. An event-triggered mechanism is given to ease the information transmission. Both the sensor and controller are set with mode-dependent quantizers in the system. A Markov process is used to model the time delay which is used to describe the quantization density. By employing the Lyapunov-Krasovskii functional and linear matrix inequality (LMI), sufficient conditions are obtained for the system. A specific example is given to demonstrate the proposed approach.
Challenges and Results of Laparoscopic Splenectomy for Hematological Diseases in a Developing Country
Authors: Shakya Vikal Chandra , Byanjankar Bikram , Pandit Rabin , Pangeni Anang , Shrestha Anir Ram Moh , Poudyal Bishesh
Published: August 2018

Introduction. Though, in developed countries, laparoscopy is now a gold standard for splenectomy, we are lacking in this aspect in the eastern world. Splenectomy has mostly been performed by open surgery in our region. This is our effort to introduce laparoscopic splenectomy in our country.Methods. This is a retrospective cohort study done in patients presenting to hematology and surgery department of our hospital who underwent laparoscopic splenectomy for hematological diseases from January 2013 to December 2016.Results. There were 50 patients (38 females, 12 males). The diagnoses were idiopathic thrombocytopenic purpura in 31, (steroid/azathioprine-resistant, steroid dependent), hereditary spherocytosis in 9, alpha-thalassemia in 3, beta-thalassemia in 2, autoimmune hemolytic anemia in 4, and isolated splenic tuberculosis in 1. Average platelet counts preoperatively were62000±11000/mm3 (range 52000-325000/mm3). The mean operative time was130±49minutes (range 108-224 min). The mean postoperative stay was4±2.11days (range 3-9 days). Laparoscopic splenectomy could be completed in 45 (90%) patients.Conclusion. Laparoscopic splenectomy could be successfully contemplated in patients with hematological diseases, especially if spleen is normal or only mildly enlarged, and is an advantageous alternative to open splenectomy. Absence of ideal resources has not limited our progress in minimal access approach.
The Metric Dimension of Some Generalized Petersen Graphs
Authors: Shao Zehui , Sheikholeslami S. M. , Wu Pu , Liu Jia-Biao
Published: August 2018

The distance d(u,v) between two distinct vertices u and v in a graph G is the length of a shortest (u,v)-path in G. For an ordered subset W={w1,w2,…,wk} of vertices and a vertex v in G, the code of v with respect to W is the ordered k-tuple cW(v)=(d(v,w1),d(v,w2),…,d(v,wk)). The set W is a resolving set for G if every two vertices of G have distinct codes. The metric dimension of G is the minimum cardinality of a resolving set of G. In this paper, we first extend the results of the metric dimension of P(n,3) and P(n,4) and study bounds on the metric dimension of the families of the generalized Petersen graphs P(2k,k) and P(3k,k). The obtained results mean that these families of graphs have constant metric dimension.