Automated Seed-Based Region Growing Using The Moving K-Means Clustering For The Detection Of Mammographic Microcalcifications.

Mammography is by far the proven method of early detection of breast cancer. However, mammography is not without its problems. It is amongst the most difficult of radiological images to interpret as the images are of low contrast and features indicative of abnormalities are very subtle and minute. In this study, a new method of automated edge detection technique is proposed to detect the abnormalities in a region of interest in a mammogram

Segmentation Of Stretched Pap Smear Cytology Images Using Clustering Algorithm.

Papanicolaou test or better known as Pap test is the most popular and effective screening test for cervical cancer. At time, however, the detection of abnormal or cancerous cervical cells can be missed due to technical and human errors

Preliminary results of electrical characterization of GO towards MCF7 and MCF10a at different concentrations

GO is the 2D carbon sheet with additional functional groups, is more stable in various solvents, easy to be produced and manipulated especially in biological system. At the moment, GO is only utilized as the drug delivery agent during treatment. In this study, the resistivity of GO towards breast cancer cell (MCF7) and normal breast cell (MCF10a) using interdigitated electrodes (IDE) were investigated. The interaction of different concentrations of GO as the sensing material on the tested cells which act as analyte can change electrical response. The tested cell were treated with six different concentrations of GO and was dropped to the IDE with different period of time in order to examine electrical behavior. For MCF10a, at high concentration the resistances of MCF10 remain in the same order of magnitude with increasing time of detection while for MCF7 at high concentration, the resistances were greatly influenced by the time of detection where the value significantly changed after 5 minutes and 10 minutes. The number of viable cell does not give effect to the resistance

Fabricated germanium-doped optical fibres for computed tomography dosimetry: Glow curve characteristics

Fabricated germanium (Ge)-doped optical fibre glow curve characteristics are investigated with respect to computed tomography (CT) dosimetry. 2.3 mol% and 6 mol% Ge-dopant concentration preforms have been used to produce flat and cylindrical fibres (FF and CF) of various size and diameter. The fibres are irradiated to doses of 20, 30 and 40 mGy for each of the beam qualities RQT 8 (100 kV), RQT 9 (120 kV) and RQT 10 (150 kV). The thermoluminescence (TL) kinematic parameters studied are maximum temperature (Tmax), activation energy (Ea) and peak integral (PI). The glow curve formations are reconstructed from the Windows®–based radiation evaluation and management system (WinREMS), deconvoluted using glow curve deconvolution (CGCD) analysis software. The structures of the glow curves are broad single or double-peaked, occurring at relatively high glow peak temperatures, TL response increases with radiation dose and peak height decreases with increasing energy, showing clear photoelectric dependence. The deconvoluted glow curves for all fibres are seen to consist of five individual glow peaks, P1 to P5, P1 being dominant in all cases other than for 6 mol% Ge-FF for which P3 is dominant due to the formation of a double-peaked glow curve. Tmax increases from P1 to P5 for all fibres, throughout the energy range used. P1 and P3 (6 mol% Ge-FF) have the lowest Ea, while P4 shows the greatest Ea for all fibres. The results indicate that electrons in P1 and P3 (6 mol% Ge-FF) are occupied at low energy traps while for P4, the electrons are trapped at a deeper energy level. The lowest PI value, indicative of the least number of electrons, is shown to be that of the deeper trap P4 for all energies investigated. This study provides support for the use of 6 mol% and 2.3 mol% preform fibres for CT dosimetry, each with similar kinetic parameters

The Glaciozyma antarctica genome reveals an array of systems that provide sustained responses towards temperature variations in a persistently cold habitat

Extremely low temperatures present various challenges to life that include ice formation and effects on metabolic capacity. Psyhcrophilic microorganisms typically have an array of mechanisms to enable survival in cold temperatures. In this study, we sequenced and analysed the genome of a psychrophilic yeast isolated in the Antarctic region, Glaciozyma antarctica. The genome annotation identified 7857 protein coding sequences. From the genome sequence analysis we were able to identify genes that encoded for proteins known to be associated with cold survival, in addition to annotating genes that are unique to G. antarctica. For genes that are known to be involved in cold adaptation such as anti-freeze proteins (AFPs), our gene expression analysis revealed that they were differentially transcribed over time and in response to different temperatures. This indicated the presence of an array of adaptation systems that can respond to a changing but persistent cold environment. We were also able to validate the activity of all the AFPs annotated where the recombinant AFPs demonstrated anti-freeze capacity. This work is an important foundation for further collective exploration into psychrophilic microbiology where among other potential, the genes unique to this species may represent a pool of novel mechanisms for cold survival

The flow behaviour study of splitting device for horizontal pipeline

The study of the flow behaviour of splitting device for horizontal pipeline was conducted by using the numerical simulation. The splitting device is functionally to force the roping flow to become homogenous. The study scrutinised the air flow in the pipeline, and also the air flow with particle which is anthracite injected into air in the pipeline. A piping system with 5 different type of splitting device is simulated to find the best splitting device that can make the roping flow become homogenous and improved the roping problem. The simulation was conducted by using the Ansys Fluent. From this study, it can be concluded that the splitting device, does help successfully in reducing the roping problem in the horizontal pipeline

The numerical modelling of falling film thickness flow on horizontal tubes

This paper presents a computational modelling of water falling film flowing over horizontal tubes. The objective of this study is to use numerical predictions for comparing the film thickness along circumferential direction of tube on 2-D CFD models. The results are then validated with a theoretical result in previous literatures. A comprehensive design of 2-D models have been developed according to the real application and actual configuration of the falling film evaporator as well as previous experimental parameters. A computational modelling of the water falling film is presented with the aid of Ansys Fluent software. The Volume of Fluid (VOF) technique is adapted in this analysis since its capabilities of determining the film thickness on tubes surface is highly reliable. The numerical analysis is carried out under influence of ambient pressures at temperature of 27ºC. Three types of CFD numerical models were analyzed in this simulation with inter tube spacing of 30 mm, 20 mm and 10 mm respectively. The use of a numerical simulation tool on water falling film has resulted in a detailed investigation of film thickness. Based on the numerical simulated results, it is found that the average values of water film thickness for each model are 0.53 mm, 0.58 mm, and 0.63 mm

Effect of gravity modulation on mixed convection flow of second grade fluid with different shapes of nanoparticles

The problem of unsteady mixed convection flow of second grade fluid over an inclined stretching plate under the influence of different shapes of nanoparticles is studied in this paper. The influence of gravity modulation is also considered. Carboxymethyl cellulose solution (CMC) is chosen as the non-Newtonian base fluid. Based on Tiwari-Das nanofluid model, the governing partial differential equations are transformed into a system of ordinary differential equations and solved numerically using an implicit finite difference scheme. The effect of different shapes and volume fraction of solid nanoparticles on the enhancement of convective heat transfer of second grade nanofluid associated with the effect amplitude of modulation, frequency of oscillation, and material parameter is discussed in details. The results indicated that, the needle-shaped nanoparticles give the highest enhancement on the heat transfer of second grade nanofluid compared to sphere and disk-shaped nanoparticles