bluuebunny/crossref_metadata_2025 huggingface dataset:
Simulation of separating pedestrian flow in T-shaped passage based on guide sign considering unbalanced flow
Authors: Li Yongxing , Wang David Z.W. , Wang Yan , Chen Yanyan , Meng Meng , Jia Hongfei
Published: January 2019

This paper analyses the characteristics of separating pedestrian flow in T-shaped passage. Pedestrians would wave and the crowed phenomenon may happen in the connection area of the main passage and branch passage. In order to reduce the pedestrian conflicts, guide sign is set to guide the pedestrians and subconscious strength is introduced to show the effect of guide sign. On this basis, simulation model of separating pedestrian flow in T-shaped passage based on guide sign considering unbalanced flow is established. On the platform of MATLAB software, separating pedestrian flow simulation with the effect of guide sign is realized. Simulations indicate that efficiency of pedestrians passing the passage is improved with the effect of guide sign, suitable position of guide sign is obtained, and compared with the separating pedestrian flow based on guide sign without considering unbalanced flow, the model considering unbalanced flow is better in describing pedestrian distribution.
Development of Knudsen thermal force for mass analysis of CH4/He gas mixture
Authors: Gerdroodbary Mostafa Barzegar , Ganji D. D. , Taeibi-Rahni Mohammad , Pruiti B. , Moradi Rasoul
Published: January 2019

Natural gas is known as the main source of energy and also contains significant and noble gases. Numerous researches have been performed to present novel methods for the detection and analysis of natural gas. In this study, Direct Simulation Monte Carlo (DSMC) method is used to evaluate the performance of a new micro gas sensor (MIKRA) for detection of helium in CH4/He gas mixture. In this sensor, the temperature difference of two arms inside a rectangular domain at low-pressure condition induces a Knudsen force which is proportional to physical properties of the gas. In order to define flow feature of a low-pressure gas inside the micro gas actuator, high order equation of Boltzmann is used to attain high precision results. To solve these equations, DSMC approach is used as a robust method for the non-equilibrium flow field. The effects of main factors such as length and gap of arms are comprehensively investigated in different ambient pressures. Furthermore, the effect of various concentrations of the CH4/He gas mixture on force generation is comprehensively studied. Our findings show that value of generated Knudsen force significantly different when the fraction of He in CH4/He gas mixture is varied. This indicates that this micro gas sensor could precisely detect the concentration of Helium gas inside a low-pressure CH4/He gas mixture.
Transition matrix cluster algorithms
Authors: Yevick David , Lee Yong Hwan
Published: January 2019

We demonstrate that a series of procedures for increasing the efficiency of transition matrix calculations can be realized by integrating the standard single-spin flip transition matrix method with global cluster flipping techniques. Our calculations employ a simple and accurate method based on detailed balance for computing the density of states from the Ising model transition matrix.
Joint effect of individual’s memory and attractiveness in temporal network on spreading dynamics
Authors: Yang Mei , Wang Bing , Han Yuexing
Published: January 2019

Most real networks have been found to evolve dynamically. In addition, heterogeneity of interaction strengths and individual’s memory have been proved to be important to affect network evolution in the area of complex networks. Based on a recent extension of the activity-driven modeling framework, i.e. activity-driven model with attractiveness, where individuals are characterized by their activities and attractiveness, we propose a new temporal network model by considering individuals’ memory. Similar to the previous network model, we also investigate heterogeneous distributions and different correlations between the two variables (activity and attractiveness). By numerical simulations, we illustrate the impact of memory on epidemic spreading processes unfolding on the proposed model. We find that, when individuals’ attractiveness is fixed, memory does not cause dramatic change on the epidemic threshold in the SIR process, but it inhibits the epidemic spreading by reducing the infected ratio. While for the SIS process, in the case of uncorrelated and positive correlations between the two variables, memory facilitates the epidemic outbreaks by shrinking the epidemic threshold. When the two variables are negatively correlated, memory does not take obvious impact on the epidemic threshold. Besides, for the two processes unfolding on the network with and without memory, the propagation threshold decreases with the enhancement of the positive correlation, however, it almost does not get much influence from the negative correlation strength. It indicates that for the individuals with same activity, more attractive individuals will promote the disease spread. The findings deepen our understanding of the role of individuals’ memory and their attractiveness in the epidemic spreading process.
M-fractional solitons and periodic wave solutions to the Hirota–Maccari system
Authors: Sulaiman Tukur Abdulkadir , Yel Gulnur , Bulut Hasan
Published: January 2019

In this study, we construct several wave solutions to the nonlinear fractional Hirota–Maccari equation with a truncated M-fractional derivative via the extended sinh-Gordon equation expansion method. The constraint conditions that guarantee the existence of valid solutions are stated. We use suitable values of parameters in plotting the 2- and 3-dimensional graphs of the reported solutions.
Ernest Henley and hadron structure
Authors: Alberg Mary
Published: January 2019

Recollections of work with Ernest Henley on the structure of hadrons.
FIBONACCI OPTICAL LATTICE: A FRACTAL BIOMODULATION DEVICE
Authors: JOHANSSON BENNY , LUKACS AGNES
Published: January 2019

Natural scenes or structures share fractal-like geometries with scale-invariant statistical patterns that exhibit useful functional physiological properties in humans. This paper explores the self-assembling of alumina microelements on a nanostructured silica-embedded PET substrate and the application of Fibonacci fractal geometry as a photonic wave-guiding device. Two concentric Fibonacci circles impinged on the top of embedded silica clusters were investigated using fractal analysis. Calculating the fractal dimension of spatial scaling properties demonstrated the potential of a fractal photonic element. Simulating the propagation of spectral visible or low NIR incident light through the fractal trajectory shows that the fractal scaling properties generate novel nonlinear and double-twisted electromagnetic waves with biophilic interconnecting potential.
FRACTAL-BASED ANALYSIS OF THE INFLUENCE OF COLOR TONALITY ON HUMAN EYE MOVEMENTS
Authors: ALIPOUR HEDIEH , NAMAZI HAMIDREZA , AZARNOUSH HAMED , JAFARI SAJAD
Published: January 2019

An important category of studies in vision science is related to the analysis of the influence of environmental changes on human eye movement. In this way, scientists analyze human eye movement in different conditions using different methods. An important category of works is devoted to the decoding of eye reaction to color tonality. In this research for the first time, we examined the application of fractal theory for decoding of eye reaction to variations in color intensity of visual stimuli. Three green visual stimuli with different color intensities have been applied to subjects and accordingly the fractal dimension of their eye movements has been analyzed. We also tested the eye movement in non-stimulation condition (rest). Based on the obtained results, increasing the color intensity of visual stimuli caused a lower complexity in subject’s eye movement. We also observed that eye movement is less complex in case of non-stimulation compared to different stimulation conditions. The application of fractal theory in analysis of eye movement can be extended to analyze the effect of other stimulation conditions on eye movement to investigate about the decoding behavior of human eye, which is very important in vision science.
JARNÍK’S THEOREM WITHOUT THE MONOTONICITY ON THE APPROXIMATING FUNCTION
Authors: MA CHAO , ZHANG SHAOHUA
Published: January 2019

Let [Formula: see text] be a non-negative function such that [Formula: see text] as [Formula: see text]. The well-known Jarník–Besicovtich theorem concerns the Hausdorff dimension of the set of [Formula: see text]- approximable numbers. In this paper, we give an alternative but short proof of the Jarník–Besicovitch theorem for approximating functions with no monotonicity. The main tool is the appropriate usage of the mass transference principle of Beresnevich–Velani [A mass transference principle and the Duffin–Schaeffer conjecture for Hausdorff measures, Ann. of Math. (2) 164(3) (2006) 971–992].
EVALUATION OF SURFACE ROUGHNESS PRODUCED BY NANOCUTTING COPPER STRUCTURE USING A LEAST SQUARE MEAN METHOD
Authors: JI CHUNHUI , SUN SHUANGQIU , LIN BIN , SUI TIANYI
Published: January 2019

This work performed molecular dynamic simulations to study the 2D profile and 3D surface topography in the nanometric cutting process. The least square mean method was used to model the evaluation criteria for the surface roughness at the nanometric scale. The result showed that the cutting speed was the most important factor influencing the spacing between the peaks, the sharpness of the peaks, and the randomness of the profile. The plastic deformation degree of the machined surface at the nanometric scale was significantly influenced by the cutting speed and depth of cut. The 2D and 3D surface roughness parameters exhibited a similar variation tendency, and the parameters Ra and Rq tended to increase gradually with an increase in the cutting speed and a decrease in the depth of cut. Finally, it is concluded that at the nanometric scale, the 3D surface roughness parameters could more accurately reflect the real surface characteristics than the 2D parameters.
Optimizing the electro-optic detection of terahertz waves by ZnTe at 780 and 1560-nm probe-beam wavelengths
Authors: Hatem O.
Published: January 2019

Investigations were made for optimizing ZnTe as a THz detector at 1560-nm probe beam wavelength, and was compared with its performance at 780[Formula: see text]nm. High-sensitive THz detection was achieved when phase matching was maintained for long coherence lengths between the probe beam and the incident THz waves. A 1-mm thick ZnTe crystal enabled detection bandwidths of THz radiation up to 2 and 3 THz with probe wavelengths at 1560 and 780[Formula: see text]nm, respectively. Theoretical calculations showed coherence length of less than 50[Formula: see text][Formula: see text]m in ZnTe between the THz wave components above 4 THz and the optical waves at 780 and 1560[Formula: see text]nm.
Internal Resonance Responses of Rectangular Cross-Ply Composite Plates with Graphene Skins
Authors: Guo Xiangying , Jiang Pan , Yan Wenhan , Lai Siu-Kai , Zhang Wei
Published: January 2019

This paper presents an investigation on the nonlinear dynamic behavior of three-phase rectangular composite plates made of cross-ply macro fiber composites (MFC) in the polymer with graphene (GP) skins, which are uniformly dispersed at the top and bottom surfaces of the plates. According to the mixture rules for multi-components of composite materials, the constitutive laws for MFC-GP composite materials can be obtained. A simply-supported rectangular plate model subjected to a transversal excitation in thermal environments is considered. The governing equations are formulated by using the first-order shear deformation theory, von Kármán geometrical kinematics and Hamilton’s principle. The Galerkin approach is used to discretize the governing equations for analysis. The vibration frequencies of MFC-GP composite plates with different modes are presented and the case of 1:2 internal resonance is selected to be investigated here. Three different coupled forms (i.e. uncoupled, weakly coupled and strongly coupled cases) of two vibration modes are presented. In addition, the influences of various parameters, including volume fraction of graphene, applied voltage, temperature effect and external excitation, on the nonlinear dynamic characteristics of MFC-GP composite plates are also examined.
Numerical algorithm for morphogen synthesis region identification with indirect image-type measurement data
Authors: Penenko Alexey , Zubairova Ulyana , Mukatova Zhadyra , Nikolaev Sergey
Published: January 2019

Diffusion–reaction models are used to describe development processes in the framework of morphogen theory. The images of the concentration fields for the subset of the interacting morphogens are available. In order to interpret this data in terms of the model parameters, the inverse source problem is stated. The sensitivity operator, composed of the independent adjoint problem solutions ensemble, allows transforming the inverse problem to the family of nonlinear ill-posed operator equations. The equations are solved with the Newton–Kantorovich-type algorithm. The approach is applied to the morphogen synthesis region identification problem for the model of regulation of the renewing zone size in biological tissue.
Noise model estimation with application to gene expression
Authors: Zhornikova Polina , Golyandina Nina , Spirov Alexander
Published: January 2019

Algorithms for the estimation of noise level and the detection of noise model are proposed. They are applied to gene expression data for Drosophila embryos. The 2D data on gene expression and the extracted 1D profiles are considered. Since the 1D data contain processing errors, an algorithm for separation of these processing errors is constructed to estimate the biological noise level. An approach to discrimination between the additive and multiplicative models is suggested for the 1D and 2D cases. Singular spectrum analysis and its 2D extension are exploited for the pattern extraction. The algorithms are tested on artificial data similar to the real data. Comparison of the results, which are obtained by the 1D and 2D methods, is performed for Krüppel and giant genes.
Predicting drug synergy for precision medicine using network biology and machine learning
Authors: Cuvitoglu Ali , Zhou Joseph X. , Huang Sui , Isik Zerrin
Published: January 2019

Identification of effective drug combinations for patients is an expensive and time-consuming procedure, especially for in vitro experiments. To accelerate the synergistic drug discovery process, we present a new classification model to identify more effective anti-cancer drug pairs using in silico network biology approach. Based on the hypotheses that the drug synergy comes from the collective effects on the biological network, therefore, we developed six network biology features, including overlap and distance of drug perturbation network, that were derived by using individual drug-perturbed transcriptome profiles and the relevant biological network analysis. Using publicly available drug synergy databases and three machine-learning (ML) methods, the model was trained to discriminate the positive (synergistic) and negative (nonsynergistic) drug combinations. The proposed models were evaluated on the test cases to predict the most promising network biology feature, which is the network degree activity, i.e. the synergistic effect between drug pairs is mainly accounted by the complementary signaling pathways or molecular networks from two drugs.
General Winkler Model for Kinematic Responses of Shafts in Linear Soil
Authors: Zhang B. , Chen Z. Y.
Published: January 2019

A simplified model for calculating the seismic responses of the shaft is proposed in this paper. Based on the theory of Winkler elastic foundation beam, the urban shaft is simplified as a vertical beam. The horizontal soil reaction and vertical shear tractions between the shaft circumference and the surrounding soils are considered through horizontal springs and rotating springs on the sidewall of the shaft. The translation and rocking motion of the shaft are considered through horizontal springs and rotating springs at the bottom of the shaft. Then, the dynamic analysis model of the shafts under seismic motion is established, and the control equation of the dynamic response of the shaft in frequency domain is deduced. The analytical solution of the steady state response of the shaft is obtained. Considering the randomness of the earthquake motion, this method can get the shaft kinematic responses under different ground motions efficiently in conceptual design process.
A Comparison Study of HO-CFD and DSC-RSK with Small Computational Bandwidths for Solving Some Classes of Boundary-Value and Eigenvalue Problems
Authors: Li Wei , Song Zhiwei , He Xiaoqiao , Xie De
Published: January 2019

This paper conducts a comparison analysis of high order central finite difference (HO-CFD) method and discrete singular convolution-regularized Shannon kernel (DSC-RSK) scheme with small computational bandwidths for solving some classes of boundary-value and eigenvalue problems. Second-, fourth- and sixth-order partial differential equations are taken into account. New strategies to generate parameters [Formula: see text] in DSC-RSK are proposed to ensure minimum errors for each case, and the influence of parameters [Formula: see text] with more decimal places is analyzed. Apart from the existing matched interface and boundary (MIB) scheme, a new double-parameter MIB scheme is also proposed. The influence of small computational bandwidths is discussed in detail. Numerical results by using HO-CFD and DSC-RSK are presented and compared to illustrate the performance of both methods in small bandwidth limit. Some remarkable conclusions have been drawn at the end of this study.
Higgs fields induced by Yang–Mills type Lagrangians on gauge-natural prolongations of principal bundles
Authors: Palese Marcella , Winterroth Ekkehart
Published: January 2019

We address some new issues concerning spontaneous symmetry breaking. We define classical Higgs fields for gauge-natural invariant Yang–Mills type Lagrangian field theories through the requirement of the existence of canonical covariant gauge-natural conserved quantities. As an illustrative example, we consider the ‘gluon Lagrangian’, i.e. a Yang–Mills Lagrangian on the [Formula: see text]-order gauge-natural bundle of [Formula: see text]-principal connections, and canonically define a ‘gluon’ classical Higgs field through the split reductive structure induced by the kernel of the associated gauge-natural Jacobi morphism.
Complete linear Weingarten spacelike submanifolds with higher codimension in the de Sitter space
Authors: Araújo Jogli Gidel da Silva , de Lima Henrique Fernandes , dos Santos Fábio Reis , Velásquez Marco Antonio Lázaro
Published: January 2019

We study complete linear Weingarten spacelike submanifolds with arbitrary high codimension [Formula: see text] in the de Sitter space [Formula: see text] of index [Formula: see text] and whose normalized mean curvature vector is parallel. Under suitable restrictions on the values of the mean curvature function and on the norm of the traceless part of the second fundamental form, we prove that such a spacelike submanifold must be either totally umbilical or isometric to a certain hyperbolic cylinder of [Formula: see text]. Our approach is based on the use of a Simons type formula related to an appropriate Cheng–Yau modified operator jointly with an extension of Hopf’s maximum principle for complete Riemannian manifolds.
One-Step Construction of Ni/Co-Doped C–N Nanotube Composites as Excellent Cathode Catalysts for Neutral Zinc–Air Battery
Authors: Yu Liang , Yi Qingfeng , Yang Xiaokun , Zhou Xiulin
Published: January 2019

Development of a neutral Zn–air battery is of much significance due to the high stability of zinc in a neutral electrolyte. Here, Ni/Co-doped C–N nanotube composites (C–N, Ni/C–N, Co/C–N, and Ni–Co/C–N) as efficient oxygen reduction reaction (ORR) electrocatalysts in a neutral medium have been prepared by direct pyrolysis of Ni/Co salt, dicyandiamide (DCD) and glucose. Among the synthesized catalysts, Ni–Co/C–N presents a high ORR current density of 8.5[Formula: see text]mA[Formula: see text][Formula: see text][Formula: see text]cm[Formula: see text] in a 0.5[Formula: see text]mol[Formula: see text][Formula: see text][Formula: see text]L[Formula: see text] KNO3solution. The ORR electron transfer number of the catalyst Ni–Co/C–N is 3.8, indicating that O2is almost completely reduced to H2O. A neutral zinc–air battery utilizing a 0.5[Formula: see text]mol[Formula: see text][Formula: see text][Formula: see text]L[Formula: see text] KNO3solution has been assembled by using the prepared composite catalyst coated on carbon paper as an air cathode, and Zn plate as an anode. The battery with the cathode catalyst Ni–Co/C–N delivers the open-circuit voltage of 1.13[Formula: see text]V and the maximum power density of 65[Formula: see text]mW[Formula: see text][Formula: see text][Formula: see text]cm[Formula: see text]. The constant discharge current density of 50[Formula: see text]mA[Formula: see text][Formula: see text][Formula: see text]cm[Formula: see text], 100[Formula: see text]mA[Formula: see text][Formula: see text][Formula: see text]cm[Formula: see text] and 150[Formula: see text]mA[Formula: see text][Formula: see text][Formula: see text]cm[Formula: see text] can last 202[Formula: see text]h, 93[Formula: see text]h and 11[Formula: see text]h, respectively. A stable voltage plateau appears at various discharge current densities. The neutral zinc–air battery can be repeatedly discharged after replacing the zinc anode. Results indicate that the synthesized Ni–Co/C–N catalyst is an excellent cathode material applied to a neutral zinc–air battery, showing broad application prospects as a mobile power source.
The effect of drying modes on aqueous dispersion of graphene oxide solids
Authors: Shen Liang , Wang Dian , Jin Ziheng , Che Liming , Cai Ning , Wang Yuanpeng , Lu Yinghua
Published: January 2019

The graphene oxide solids are derived from four representative drying methods, denoted as AGO (air drying), HGO (heat-vacuum drying), VGO (vacuum drying) and FGO (freezing drying), studied in view of aqueous dispersion. Their dispersion stability was found in order of FGO [Formula: see text] VGO [Formula: see text] AGO [Formula: see text] HGO, corresponding to the increasing C/O ratio of 1.771, 1.778, 2.337 and 2.483 indicated by XPS, respectively. The variation in structure and composition of GO solids caused by different drying processes was further characterized through Raman, XRD, SEM and HR-TEM. By such, the mechanism interpreting the rationale between dispersion and drying for GO was proposed.
Developing North Korea’s Economy amid Uncertain Geopolitical Situation
Authors: CHIANG Min-Hua
Published: January 2019

With negative growth of 3.5% in 2017, North Korea’s economy suffered its worst setback in a decade due to the effects of international economic sanctions. The Trump—Kim meeting on 12 June 2018 in Singapore raised hopes of lifting sanctions on North Korea and of bolstering North Korea’s economy. However, North Korea’s disagreement with the United States over its denuclearisation process and China—US competition in geopolitical interests in the Korean peninsula may overshadow its economic outlook.
TRENDS AND VARIABILITIES IN ANNUAL PRECIPITATION AND TEMPERATURE DURING 2006–2100 IN THE WEYB RIVER BASIN, ETHIOPIA
Authors: SERUR ABDULKERIM BEDEWI
Published: January 2019

This study investigates on variabilities in annual precipitation, maximum temperature, and minimum temperature within the Weyb River basin during 2006–2100 under representative concentration pathway (RCP) 2.6/4.5/8.5 scenarios based on predictions of three Earth System Models (GFDL-ESM2M, CanESM2, and GFDL-ESM2G). Our results showed that precipitation, maximum temperature, and minimum temperature would rise in the near term (2011–2040), the medium term (2041–2070), and the long term (2071–2100) as compared to the baseline scenario (1981–2005). The larger increments are predicted by GFDL-ESM2M than those by GFDL-ESM2G and CanESM2 in all three time periods. The variabilities of precipitation, maximum temperature, and minimum temperature are predicted to be higher under RCP8.5 scenario than those under RCP4.5 or RCP2.6 scenario in simulations of all three ESMs. Results also revealed that there would be significant spatiotemporal variations in precipitation, maximum temperature, and minimum temperature within the Weyb River basin, which implies that the basin would possibly experience droughts or floods more frequently during the 21st century.
Exogenous ubiquitin reduces inflammatory response and preserves myocardial function 3 days post-ischemia-reperfusion injury
Authors: Scofield Stephanie L. C. , Dalal Suman , Lim Kristina A. , Thrasher Patsy R. , Daniels Christopher R. , Peterson Jonathan M. , Singh Mahipal , Singh Krishna
Published: January 2019

β-Adrenergic receptor (β-AR) stimulation increases extracellular levels of ubiquitin (UB) in myocytes, and exogenous UB decreases β-AR-stimulated myocyte apoptosis and myocardial fibrosis. Here, we hypothesized that exogenous UB modulates the inflammatory response, thereby playing a protective role in cardiac remodeling after ischemia-reperfusion (I/R) injury. C57BL/6 mice infused with vehicle or UB (1 μg·g−1·h−1) were subjected to myocardial I/R injury. Functional and biochemical parameters of the heart were examined 3 days post-I/R. Heart weight-to-body weight ratios were similarly increased in I/R and UB + I/R groups. The area at risk and infarct size were significantly lower in UB + I/R versus I/R groups. Measurement of heart function using echocardiography revealed that I/R decreases percent fractional shortening and percent ejection fraction. However, the decrease in fractional shortening and ejection fraction was significantly lower in the UB + I/R group. The UB + I/R group displayed a significant decrease in inflammatory infiltrates, neutrophils, and macrophages versus the I/R group. Neutrophil activity was significantly lower in the UB + I/R group. Analysis of the concentration of a panel of 23 cytokines/chemokines in the serum using a Bio-Plex assay revealed a significantly lower concentration of IL-12 subunit p40 in the UB + I/R versus I/R group. The concentration of monocyte chemotactic protein-1 was lower, whereas the concentration of macrophage inflammatory protein-1α was significantly higher, in the UB+I/R group versus the sham group. Expression of matrix metalloproteinase (MMP)-2 and activity of MMP-9 were higher in the UB + I/R group versus the I/R group. Levels of ubiquitinated proteins and tissue inhibitor of metalloproteinase 2 expression were increased to a similar extent in both I/R groups. Thus, exogenous UB plays a protective role in myocardial remodeling post-I/R with effects on cardiac function, area at risk/infarct size, the inflammatory response, levels of serum cytokines/chemokines, and MMP expression and activity.

NEW & NOTEWORTHY Stimulation of β-adrenergic receptors increases extracellular levels of ubiquitin (UB) in myocytes, and exogenous UB decreases β-adrenergic receptor-stimulated myocyte apoptosis and myocardial fibrosis. Here, we provide evidence that exogenous UB decreases the inflammatory response and preserves heart function 3 days after myocardial ischemia-reperfusion injury. Further identification of the molecular events involved in the anti-inflammatory role of exogenous UB may provide therapeutic targets for patients with ischemic heart disease.
PAK4 Phosphorylates Fumarase and Blocks TGFβ-Induced Cell Growth Arrest in Lung Cancer Cells
Authors: Chen Tao , Wang Ting , Liang Wenhua , Zhao Qin , Yu Qiujing , Ma Chun-Min , Zhuo Lingang , Guo Dong , Zheng Ke , Zhou Chengzhi , Wei Shupei , Huang Wenhua , Jiang Juhong , Liu Jing , Li Shiyue , He Jianxing , Jiang Yuhui , Zhong Nanshan
Published: January 2019

The metabolic activity of fumarase (FH) participates in gene transcription linking to tumor cell growth. However, whether this effect is implicated in lung cancer remains unclear. Here, we show TGFβ induces p38-mediated FH phosphorylation at Thr 90, which leads to a FH/CSL (also known as RBP-Jκ)/p53 complex formation and FH accumulation at p21 promoter under concomitant activation of Notch signaling; in turn, FH inhibits histone H3 Lys 36 demethylation and thereby promotes p21 transcription and cell growth arrest. In addition, FH is massively phosphorylated at the Ser 46 by PAK4 in non–small cell lung cancer (NSCLC) cells, and PAK4-phosphorylated FH binds to 14-3-3, resulting in cytosolic detention of FH and prohibition of FH/CSL/p53 complex formation. Physiologically, FH Ser 46 phosphorylation promotes tumorigenesis through its suppressive effect on FH Thr 90 phosphorylation–mediated cell growth arrest in NSCLC cells and correlates with poor prognosis in patients with lung cancer. Our findings uncover an uncharacterized mechanism underlying the local effect of FH on TGFβ-induced gene transcription, on which the inhibitory effect from PAK4 promotes tumorigenesis in lung cancer.

Significance:

Fumarase counteracts CSL via its metabolic activity to facilitate TGFβ-induced cell growth arrest, an effect largely blocked by PAK4-mediated phosphorylation of fumarase.
Growth Hormone Response to Oral Glucose Load: From Normal to Pathological Conditions
Authors: Hage Mirella , Kamenický Peter , Chanson Philippe
Published: January 2019

The exact physiological basis of acute growth hormone (GH) suppression by oral glucose is not fully understood. Glucose-mediated increase in hypothalamic somatostatin seems to be the most plausible explanation. Attempts to better understand its underlying mechanisms are compromised by species disparities in the response of GH to glucose load. While in humans, glucose inhibits GH release, the acute elevation of circulating glucose levels in rats has either no effect on GH secretion or may be stimulatory. Likewise, chronic hyperglycemia alters GH release in both humans and rats nonetheless in opposite directions. Several factors influence nadir GH concentrations including, age, gender, body mass index, pubertal age, and the type of assay used. Besides the classical suppressive effects of glucose on GH release, a paradoxical GH increase to oral glucose may be observed in around one third of patients with acromegaly as well as in various other disorders. Though its pathophysiology is poorly characterized, an altered interplay between somatostatin and GH-releasing hormone has been suggested and a link with pituitary ectopic expression of glucose-dependent insulinotropic polypeptide receptor has been recently demonstrated. A better understanding of the dynamics mediating GH response to glucose may allow a more optimal use of the OGTT as a diagnostic tool in various conditions, especially acromegaly.
A Novel Wideband Bandpass Filter using H-shaped DGS
Authors: Do Van-Phuong , Luong Duy-Manh , Ta Chi-Hieu , Doan Minh-Tan
Published: January 2019

This paper presents a novel compact wide-band bandpass filter (BPF) having good selectivity. It is designed using a dual-plane structure which consists of a parallel-coupled microstrip line on the upper surface and three H-shape defected ground structures (DGS) on the ground plane. By adding three H-shape DGS units on the ground plane, then properly adjusting their dimensions and position, the bandwidth and selectivity of the designed filter can be significantly improved. A compact prototype of wide-band microstrip bandpass filter has been designed, fabricated and measured for the wireless systems applications. The filter exhibits a center frequency at 4.8 GHz, passband from 2.8 GHz to 6.8 GHz with best insertion loss and return loss of 0.8 dB and 40 dB, respectively. The measured results agrees well with the theoretical expectations validating the proposed design.
A Neural Network Approach to Identify Hyperspectral Image Content
Authors: Rajegowda Puttaswamy Malali , P. Balamurugan
Published: January 2019

A Hyperspectral is the imaging technique that contains very large dimension data with the hundreds of channels. Meanwhile, the Hyperspectral Images (HISs) delivers the complete knowledge of imaging; therefore applying a classification algorithm is very important tool for practical uses. The HSIs are always having a large number of correlated and redundant feature, which causes the decrement in the classification accuracy; moreover, the features redundancy come up with some extra burden of computation that without adding any beneficial information to the classification accuracy. In this study, an unsupervised based Band Selection Algorithm (BSA) is considered with the Linear Projection (LP) that depends upon the metric-band similarities. Afterwards Monogenetic Binary Feature (MBF) has consider to perform the ‘texture analysis’ of the HSI, where three operational component represents the monogenetic signal such as; phase, amplitude and orientation. In post processing classification stage, feature-mapping function can provide important information, which help to adopt the Kernel based Neural Network (KNN) to optimize the generalization ability. However, an alternative method of multiclass application can be adopt through KNN, if we consider the multi-output nodes instead of taking single-output node.
Good Parameters for PSO in Optimizing Laying Hen Diet
Authors: Fanshuri Alfarisy Gusti Ahmad , Mahmudy Wayan Firdaus , Natsir Muhammad Halim
Published: January 2019

Manual formulation of poultry diet by taking into account the fulfillment of all nutrients requirement with least cost is a difficult task. Particle Swarm Optimization (PSO) shows promising technique to solve this problem. However, there is a lack of studying a good parameter for PSO to solve feed formulation problem since PSO is sensitive to control parameter which depends on the problem. Therefore, this study investigates good swarm size, total iterations, acceleration coefficients, and inertia weight to produce a better formula. PSO with proposed good parameters is compared with other parameters. The obtained result shows that PSO with good parameters choice produces the highest fitness. Furthermore, good parameters of PSO can be used as a reference for a software developer and for further research to optimize poultry diet using PSO.
Wind Generation Impact on Symmetrical Fault Level at Grid Buses
Authors: Hamzeh A. , Hamed Sadeq A. , Al-Omari Zakaria
Published: January 2019

This paper mainly aims at evaluating quantitatively the impact of wind turbine generators (WTGs) on fault level (FL) in case of a balanced fault occurring in the host grid (HG). This impact is not generic but it depends on the grid configuration, operation mode, and load profile; the impact may be positive for a network while it is negative for another one. Therefore, the impact will be estimated for a specific distribution network (DN). The grid faults and wind generations (WGs) are simulated by the simulation tool Power Factory DigSilent 14.0.506. The paper addresses the influence on FL of grid buses in general and particularly on FL of the point of common coupling (PCC). The effect of both penetration and dispersion levels of embedded WTGs on fault response is also investigated. Moreover, the influence of WG type on FL is assessed. It is concluded, among other points, that the FL at PCC could rise by about 150% and 17% due to embedded WG of type 1 and type 2 respectively, what it leads to the recommendation to avoid installing type 1 wind systems for new wind farms
Effect of Feature Selection on Gene Expression Datasets Classification Accurac
Authors: Omara Hicham , Lazaar Mohamed , Tabii Youness
Published: January 2019

Feature selection attracts researchers who deal with machine learning and data mining. It consists of selecting the variables that have the greatest impact on the dataset classification, and discarding the rest. This dimentionality reduction allows classifiers to be fast and more accurate. This paper traits the effect of feature selection on the accuracy of widely used classifiers in literature. These classifiers are compared with three real datasets which are pre-processed with feature selection methods. More than 9% amelioration in classification accuracy is observed, and k-means appears to be the most sensitive classifier to feature selection.
FIToplankton: Wireless Controlled Remotely-operated Underwater Vehicle (ROV) for Shallow Water Exploratio
Authors: Sani Muhammad Ikhsan , Siregar Simon , Kurniawan Aris Pujud , Irwan M. Abid
Published: January 2019

Remotely Operated Vehicle (ROV) for underwater exploration is typically controlled using umbilical cable connected to ground control station. Unfortunately, while it’s used for power distribution and data transmission, it also obstruct the movement of ROV especially for shallow water (<50 cm). This paper proposed an alternative method for controlling ROV using wireless remote control system. This work also aims to explore the possibility of using RF wireless technology between 420-450 MHz as underwater communication system. Furthermore, the control system was used to manage actuators i.e. DC motor and bilge pump for maneuvring and picking small size cargo. To help the ROV to hold on a desired, Inertial Measurement Unit (IMU) is installed on board ROV within maximum deviation 0.2 m/s2. The prototype of the system has been successfully implemented and evaluated to confirm the  functionality and the feasibility of the proposed approach.
Performance Evaluation of Adaptive Continuous Wavelet Transform based Rake Receiver for UWB Systems
Authors: Navitha Ch. , Sivani K. , Reddy K. Ashoka
Published: January 2019

This paper proposes an adaptive continuous wavelet transform (ACWT) based Rake receiver to mitigate interference for high speed ultra wideband (UWB) transmission. The major parts of the receiver are least mean square (LMS) adaptive equalizer and N-selective maximum ratio combiner (MRC). The main advantage of using continuous wavelet rake receiver is that it utilizes the maximum bandwidth (7.5GHz) of the UWB transmitted signal, as announced by the Federal Communication Commission (FCC). In the proposed ACWT Rake receiver, the weights and the finger positions are updated depending upon the convergence error over a period in which training data is transmitted. Line of sight (LOS) channel model (CM1 from 0 to 4 meters) and the Non line of sight (NLOS) channel models (CM, CM3 and CM4) are the indoor channel models selected for investigating in this research . The performance of the proposed adaptive system   is evaluated by comparing with conventional rake and continuous wavelet transform (CWT) based rake. It showed an improved performance in all the different UWB channels (CM1 to CM4) for rake fingers of 2, 4 and 8. Simulations showed that for 8 rake fingers, the proposed adaptive CWT rake receiver has shown an SNR improvement of 2dB, 3dB, 10dB and 2dB respectively over CWT rake receiver in different UWB channels CM1, CM2, CM3 and CM4.
DNA Pool Analysis-based Forgery-Detection of Dairy Products
Authors: Rossi Francesco , Modesto Paola , Biolatti Cristina , Benso Alfredo , Di Carlo Stefano , Politano Gianfranco , Acutis Pierluigi
Published: January 2019

Food integrity and food safety have received much attention in recent years due to the dramatic increasing number of food frauds. In this article we focus on the problem of dairy products traceability. In particular, we propose an automatic forgery detection system able to detect frauds in milk and cheese. We investigate the use of Short Tandem Repeats analysis data, processed by a Covariance Matrix Adaptation Evolution Strategy algorithm in order to evaluate a traceability score between the products and their producer, and to highlight possible adulterations and inconsistencies. To demonstrate the usability of the proposed heuristic algorithm in a real setup, we also present the results collected from two real Italian farms.
A Comparative Analysis on the Evaluation of Classification Algorithms in the Prediction of Diabetes
Authors: Patil Ratna , Tamane Sharavari
Published: January 2019

Data mining techniques are applied in many applications as a standard procedure for analyzing the large volume of available data, extracting useful information and knowledge to support the major decision-making processes. Diabetes mellitus is a continuing, general, deadly syndrome occurring all around the world. It is characterized by hyperglycemia occurring due to abnormalities in insulin secretion which would in turn result in irregular rise of glucose level. In recent years, the impact of Diabetes mellitus has increased to a great extent especially in developing countries like India. This is mainly due to the irregularities in the food habits and life style. Thus, early diagnosis and classification of this deadly disease has become an active area of research in the last decade. Numerous clustering and classifications techniques are available in the literature to visualize temporal data to identify trends for controlling diabetes mellitus. This work presents an experimental study of several algorithms which classifies Diabetes Mellitus data effectively. The existing algorithms are analyzed thoroughly to identify their advantages and limitations. The performance assessment of the existing algorithms is carried out to determine the best approach.
Effective Router Assisted Congestion Control for SDN
Authors: Hertiana Sofia Naning , Kurniawan Adit , Hendrawan Hendrawan , Pasaribu Udjianna Sekteria
Published: January 2019

Router Assisted Congestion Control (RACC) was designed to improve endto- end congestion control performance by using prior knowledge on network condition. However, the traditional Internet does not provide such information, which makes this approach is not feasible to deliver. Our paper addresses this network information deficiency issue by proposing a new congestion control method that works on the Software Defined Network (SDN) framework. We call this proposed method as PACEC (Path Associativity Centralized Congestion Control). In SDN, global view of the network information contains the network topology including link properties (i.e., type, capacity, power consumption, etc.). PACEC uses this information to determine the feedback signal, in order for the source to start sending data at a high rate and to quickly reach fair-share rate. The simulation shows that the efficiency and fairness of PACEC are better than Transmission Control Protocol (TCP) and Rate Control Protocol (RCP).
A Novel Hybrid Classification Approach for Sentiment Analysis of Text Document
Authors: Amrani Yassine Al , Lazaar Mohamed , Kadiri Kamal Eddine El
Published: January 2019

Sentiment analysis is a more popular area of highly active research in Automatic Language Processing. She assigns a negative or positive polarity to one or more entities using different natural language processing tools and also predicted high and low performance of various sentiment classifiers. Our approach focuses on the analysis of feelings resulting from reviews of products using original text search techniques. These reviews can be classified as having a positive or negative feeling based on certain aspects in relation to a query based on terms. In this paper, we chose to use two automatic learning methods for classification: Support Vector Machines (SVM) and Random Forest, and we introduce a novel hybrid approach to identify product reviews offered by Amazon. This is useful for consumers who want to research the sentiment of products before purchase, or companies that want to monitor the public sentiment of their brands. The results summarize that the proposed method outperforms these individual classifiers in this amazon dataset.
A Comparison of Cloud Execution Mechanisms Fog, Edge, and Clone Cloud Computing
Authors: Francis T.
Published: January 2019

Cloud computing is a technology that was developed a decade ago to provide uninterrupted, scalable services to users and organizations. Cloud computing has also become an attractive feature for mobile users due to the limited features of mobile devices. The combination of cloud technologies with mobile technologies resulted in a new area of computing called mobile cloud computing. This combined technology is used to augment the resources existing in Smart devices. In recent times, Fog computing, Edge computing, and Clone Cloud computing techniques have become the latest trends after mobile cloud computing, which have all been developed to address the limitations in cloud computing. This paper reviews these recent technologies in detail and provides a comparative study of them. It also addresses the differences in these technologies and how each of them is effective for organizations and developers.
Design and Implementation of a Contactless Smart House Network System
Authors: Younis Mohammed Issam , Hussein Taif Fadhil
Published: January 2019

The Internet of Things (IoT) technology is every object around us and it is used to connect these objects to the Internet to verify Machine to Machine (M2M) communication. The smart house system is the most important application of IoT technology; it is increase the quality of life and decrease the efforts. There were many problems that faced the existing smart house networking systems, including the high cost of implementation and upgrading, high power consumption, and supported limited features. Therefore, this paper presents the design and implementation of smart house network system (SHNS) using Raspberry Pi and Arduino platforms as network infrastructure with ZigBee technology as wireless communication. SHNS consists of two main parts: the main station part and the wireless house nodes part. The local wireless communication between the house nodes and the main station is done through ZigBee technology with low power and low data rate. The mode of operation of these house nodes can be configured dynamically by the end user and determined multicast or broadcast operation according to the user requirements. The implementation and upgrading of SHNS are costless, flexible and required less power comparing with other reviewed systems.
Hybrid Genetic Algorithm for Optimization of Food Composition on Hypertensive Patient
Authors: Fauziyah Aprilia Nur , Mahmudy Wayan Firdaus
Published: January 2019

The healthy food with attention of salt degree is one of the efforts for healthy living of hypertensive patient. The effort is important for reducing the probability of hypertension change to be dangerous disease. In this study, the food composition is build with attention nutrition amount, salt degree, and minimum cost. The proposed method is hybrid method of Genetic Algorithm (GA) and Variable Neighborhood Search (VNS). The three scenarios of hybrid GA-VNS types had been developed in this study. Although hybrid GA and VNS take more time than pure GA or pure VNS but the proposed method give better quality of solution. VNS successfully help GA avoids premature convergence and improves better solution. The shortcomings on GA in local exploitation and premature convergence is solved by VNS, whereas the shortcoming on VNS that less capability in global exploration can be solved by use GA that has advantage in global exploration.