Transmission Model for Plasmodium Vivax Malaria: Conditions for Bifurcation

Plasmodium vivax malaria differs from P. falciparum malaria in that a person suffering from P. vivax infection can suffer relapses of the disease. This is due the parasite being able to remain dormant in the liver of the patients where it is able to re-infect the patient after a passage of time. During this stage, the patient is classified as being in the dormant class. The model to describe the transmission of P. vivax malaria consists of a human population divided into four classes, the susceptible, the infected, the dormant and the recovered. The effect of a time delay on the transmission of this disease is studied. The time delay is the period in which the P. vivax parasite develops inside the mosquito (vector) before the vector becomes infectious (i.e., pass on the infection). We analyze our model by using standard dynamic modeling method. Two stable equilibrium states, a disease free state E0 and an endemic state E1, are found to be possible. It is found that the E0 state is stable when a newly defined basic reproduction number G is less than one. If G is greater than one the endemic state E1 is stable. The conditions for the endemic equilibrium state E1 to be a stable spiral node are established. For realistic values of the parameters in the model, it is found that solutions in phase space are trajectories spiraling into the endemic state. It is shown that the limit cycle and chaotic behaviors can only be achieved with unrealistic parameter values.

A Novel Nucleus-Based Classifier for Discrimination of Osteoclasts and Mesenchymal Precursor Cells in Mouse Bone Marrow Cultures

Bone remodeling occurs by the balanced action of bone resorbing osteoclasts (OC) and bone-building osteoblasts. Increased bone resorption by excessive OC activity contributes to malignant and non-malignant diseases including osteoporosis. To study OC differentiation and function, OC formed in in vitro cultures are currently counted manually, a tedious procedure which is prone to inter-observer differences. Aiming for an automated OC-quantification system, classification of OC and precursor cells was done on fluorescence microscope images based on the distinct appearance of fluorescent nuclei. Following ellipse fitting to nuclei, a combination of eight features enabled clustering of OC and precursor cell nuclei. After evaluating different machine-learning techniques, LOGREG achieved 74% correctly classified OC and precursor cell nuclei, outperforming human experts (best expert: 55%). In combination with the automated detection of total cell areas, this system allows to measure various cell parameters and most importantly to quantify proteins involved in osteoclastogenesis.

Effect of Calcium Chloride on Rheological Properties and Structure of Inulin - Whey Protein Gels

The rheological properties, structure and potential synergistic interactions of whey proteins (1-6%) and inulin (20%) in mixed gels in the presence of CaCl2 was the aim of this study. Whey proteins have a strong influence on inulin gel formation. At low concentrations (2%) whey proteins did not impair in inulin gel formation. At higher concentration (4%) whey proteins impaired inulin gelation and inulin impaired the formation of a Ca2+-induced whey protein network. The presence of whey proteins at a level allowing for protein gel network formation (6%) significantly increased the rheological parameters values of the gels. SEM micrographs showed that whey protein structure was coated by inulin moieties which could make the mixed gels firmer. The protein surface hydrophobicity measurements did not exclude synergistic interactions between inulin and whey proteins, however. The use of an electrophoretic technique did not show any stable inulin-whey protein complexes.

Artificial Neural Networks for Classifying Magnetic Measurements in Tokamak Reactors

This paper is mainly concerned with the application of a novel technique of data interpretation to the characterization and classification of measurements of plasma columns in Tokamak reactors for nuclear fusion applications. The proposed method exploits several concepts derived from soft computing theory. In particular, Artifical Neural Networks have been exploited to classify magnetic variables useful to determine shape and position of the plasma with a reduced computational complexity. The proposed technique is used to analyze simulated databases of plasma equilibria based on ITER geometry configuration. As well as demonstrating the successful recovery of scalar equilibrium parameters, we show that the technique can yield practical advantages compares with earlier methods.

In Search of an SVD and QRcp Based Optimization Technique of ANN for Automatic Classification of Abnormal Heart Sounds

Artificial Neural Network (ANN) has been extensively used for classification of heart sounds for its discriminative training ability and easy implementation. However, it suffers from overparameterization if the number of nodes is not chosen properly. In such cases, when the dataset has redundancy within it, ANN is trained along with this redundant information that results in poor validation. Also a larger network means more computational expense resulting more hardware and time related cost. Therefore, an optimum design of neural network is needed towards real-time detection of pathological patterns, if any from heart sound signal. The aims of this work are to (i) select a set of input features that are effective for identification of heart sound signals and (ii) make certain optimum selection of nodes in the hidden layer for a more effective ANN structure. Here, we present an optimization technique that involves Singular Value Decomposition (SVD) and QR factorization with column pivoting (QRcp) methodology to optimize empirically chosen over-parameterized ANN structure. Input nodes present in ANN structure is optimized by SVD followed by QRcp while only SVD is required to prune undesirable hidden nodes. The result is presented for classifying 12 common pathological cases and normal heart sound.

A Software for Calculation of Optimum Conditions for Cotton Bobbin Drying in a Hot-Air Bobbin Dryer

In this study, a software has been developed to predict the optimum conditions for drying of cotton based yarn bobbins in a hot air dryer. For this purpose, firstly, a suitable drying model has been specified using experimental drying behavior for different values of drying parameters. Drying parameters in the experiments were drying temperature, drying pressure, and volumetric flow rate of drying air. After obtaining a suitable drying model, additional curve fittings have been performed to obtain equations for drying time and energy consumption taking into account the effects of drying parameters. Then, a software has been developed using Visual Basic programming language to predict the optimum drying conditions for drying time and energy consumption.

Study on the Evaluation of the Chaotic Cipher System Using the Improved Volterra Filters and the RBFN Mapping

In this paper, we propose a chaotic cipher system consisting of Improved Volterra Filters and the mapping that is created from the actual voice by using Radial Basis Function Network. In order to achieve a practical system, the system supposes to use the digital communication line, such as the Internet, to maintain the parameter matching between the transmitter and receiver sides. Therefore, in order to withstand the attack from outside, it is necessary that complicate the internal state and improve the sensitivity coefficient. In this paper, we validate the robustness of proposed method from three perspectives of "Chaotic properties", "Randomness", "Coefficient sensitivity".

Algebraic Approach for the Reconstruction of Linear and Convolutional Error Correcting Codes

In this paper we present a generic approach for the problem of the blind estimation of the parameters of linear and convolutional error correcting codes. In a non-cooperative context, an adversary has only access to the noised transmission he has intercepted. The intercepter has no knowledge about the parameters used by the legal users. So, before having acess to the information he has first to blindly estimate the parameters of the error correcting code of the communication. The presented approach has the main advantage that the problem of reconstruction of such codes can be expressed in a very simple way. This allows us to evaluate theorical bounds on the complexity of the reconstruction process but also bounds on the estimation rate. We show that some classical reconstruction techniques are optimal and also explain why some of them have theorical complexities greater than these experimentally observed.

Experimental Design and Performance Analysis in Plasma Arc Surface Hardening

In this paper, the experimental design of using the Taguchi method is employed to optimize the processing parameters in the plasma arc surface hardening process. The processing parameters evaluated are arc current, scanning velocity and carbon content of steel. In addition, other significant effects such as the relation between processing parameters are also investigated. An orthogonal array, signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are employed to investigate the effects of these processing parameters. Through this study, not only the hardened depth increased and surface roughness improved, but also the parameters that significantly affect the hardening performance are identified. Experimental results are provided to verify the effectiveness of this approach.

CFD Simulation of the Hydrodynamic Vibrator for Stuck - Pipe Liquidation

Stuck-pipe in drilling operations is one of the most pressing and expensive problems in the oil industry. This paper describes a computational simulation and an experimental study of the hydrodynamic vibrator, which may be used for liquidation of stuck-pipe problems during well drilling. The work principle of the vibrator is based upon the known phenomena of Vortex Street of Karman and the resulting generation of vibrations. We will discuss the computational simulation and experimental investigations of vibrations in this device. The frequency of the vibration parameters has been measured as a function of the wide range Reynolds Number. The validity of the computational simulation and of the assumptions on which it is based has been proved experimentally. The computational simulation of the vibrator work and its effectiveness was carried out using FLUENT software. The research showed high degree of congruence with the results of the laboratory tests and allowed to determine the effect of the granular material features upon the pipe vibration in the well. This study demonstrates the potential of using the hydrodynamic vibrator in a well drilling system.

Quantitative Genetics Researches on Milk Protein Systems of Romanian Grey Steppe Breed

The paper makes part from a complex research project on Romanian Grey Steppe, a unique breed in terms of biological and cultural-historical importance, on the verge of extinction and which has been included in a preservation programme of genetic resources from Romania. The study of genetic polymorphism of protean fractions, especially kappa-casein, and the genotype relations of these lactoproteins with some quantitative and qualitative features of milk yield represents a current theme and a novelty for this breed. In the estimation of the genetic parameters we used R.E.M.L. (Restricted Maximum Likelihood) method. The main lactoprotein from milk, kappa - casein (K-cz), characterized in the specialized literature as a feature having a high degree of hereditary transmission, behaves as such in the nucleus under study, a value also confirmed by the heritability coefficient (h2 = 0.57 %). We must mention the medium values for milk and fat quantity (h2=0.26, 0.29 %) and the fat and protein percentage from milk having a high hereditary influence h2 = 0.71 - 0.63 %. Correlations between kappa-casein and the milk quantity are negative and strong. Between kappa-casein and other qualitative features of milk (fat content 0.58-0.67 % and protein content 0.77- 0.87%), there are positive and very strong correlations. At the same time, between kappa-casein and β casein (β-cz), β lactoglobulin (β- lg) respectively, correlations are positive having high values (0.37 – 0.45 %), indicating the same causes and determining factors for the two groups of features.

Using Interval Constrained Petri Nets and Fuzzy Method for Regulation of Quality: The Case of Weight in Tobacco Factory

The existence of maximal durations drastically modifies the performance evaluation in Discrete Event Systems (DES). The same particularity may be found on systems where the associated constraints do not concern the time. For example weight measures, in chemical industry, are used in order to control the quantity of consumed raw materials. This parameter also takes a fundamental part in the product quality as the correct transformation process is based upon a given percentage of each essence. Weight regulation therefore increases the global productivity of the system by decreasing the quantity of rejected products. In this paper we present an approach based on mixing different characteristics theories, the fuzzy system and Petri net system to describe the behaviour. An industriel application on a tobacco manufacturing plant, where the critical parameter is the weight is presented as an illustration.

Consideration of Criteria of Vibration Comfort of People in Diagnosis and Design of Buildings

The increasing influence of traffic on building objects and people residing in them should be taken into account in diagnosis and design. Users of buildings expect that vibrations occurring in their environment, will not only lead to damage to the building or its accelerated wear, but neither would affect the required comfort in rooms designed to accommodate people. This article describes the methods and principles useful in designing and building diagnostics located near transportation routes, with particular emphasis on the impact of traffic vibration on people in buildings. It also describes the procedures used in obtaining information about the parameters of vibrations in different cases of diagnostics and design. A universal algorithm of procedure in diagnostics and design of buildings taking into account assurance of human vibration comfort of people residing in the these buildings was presented.

Analysis of Lower Extremity Muscle Flexibility among Indian Classical Bharathnatyam Dancers

Musculoskeletal problems are common in high performance dance population. This study attempts to identify lower extremity muscle flexibility parameters prevailing among bharatanatyam dancers and analyze if there is any significant difference exist between normal and injured dancers in flexibility parameters. Four hundred and one female dancers and 17 male dancers were participated in this study. Flexibility parameters (hamstring tightness, hip internal and external rotation and tendoachilles in supine and sitting posture) were measured using goniometer. Results of our study it is evident that injured female bharathnatyam dancers had significantly (p < 0.05) high hamstring tightness on left side lower extremity compared to normal female dancers. The range of motion for left tendoachilles was significantly (p < 0.05) high for the normal female group when compared to injured dancers during supine lying posture. Majority of the injured dancers had high hamstring tightness that could be a possible reason for pain and MSDs.

Induced Acyclic Path Decomposition in Graphs

A decomposition of a graph G is a collection ψ of graphs H1,H2, . . . , Hr of G such that every edge of G belongs to exactly one Hi. If each Hi is either an induced path in G, then ψ is called an induced acyclic path decomposition of G and if each Hi is a (induced) cycle in G then ψ is called a (induced) cycle decomposition of G. The minimum cardinality of an induced acyclic path decomposition of G is called the induced acyclic path decomposition number of G and is denoted by ¤Çia(G). Similarly the cyclic decomposition number ¤Çc(G) is defined. In this paper we begin an investigation of these parameters.

Closed form Delay Model for on-Chip VLSIRLCG Interconnects for Ramp Input for Different Damping Conditions

Fast delay estimation methods, as opposed to simulation techniques, are needed for incremental performance driven layout synthesis. On-chip inductive effects are becoming predominant in deep submicron interconnects due to increasing clock speed and circuit complexity. Inductance causes noise in signal waveforms, which can adversely affect the performance of the circuit and signal integrity. Several approaches have been put forward which consider the inductance for on-chip interconnect modelling. But for even much higher frequency, of the order of few GHz, the shunt dielectric lossy component has become comparable to that of other electrical parameters for high speed VLSI design. In order to cope up with this effect, on-chip interconnect has to be modelled as distributed RLCG line. Elmore delay based methods, although efficient, cannot accurately estimate the delay for RLCG interconnect line. In this paper, an accurate analytical delay model has been derived, based on first and second moments of RLCG interconnection lines. The proposed model considers both the effect of inductance and conductance matrices. We have performed the simulation in 0.18μm technology node and an error of as low as less as 5% has been achieved with the proposed model when compared to SPICE. The importance of the conductance matrices in interconnect modelling has also been discussed and it is shown that if G is neglected for interconnect line modelling, then it will result an delay error of as high as 6% when compared to SPICE.

Characterization of Microroughness Parameters in Cu and Cu2O Nanoparticles Embedded in Carbon Film

The morphological parameter of a thin film surface can be characterized by power spectral density (PSD) functions which provides a better description to the topography than the RMS roughness and imparts several useful information of the surface including fractal and superstructure contributions. Through the present study Nanoparticle copper/carbon composite films were prepared by co-deposition of RF-Sputtering and RF-PECVD method from acetylene gas and copper target. Surface morphology of thin films is characterized by using atomic force microscopy (AFM). The Carbon content of our films was obtained by Rutherford Back Scattering (RBS) and it varied from .4% to 78%. The power values of power spectral density (PSD) for the AFM data were determined by the fast Fourier transform (FFT) algorithms. We investigate the effect of carbon on the roughness of thin films surface. Using such information, roughness contributions of the surface have been successfully extracted.