The detection and classification of blast cell in Leukaemia Acute Promyelocytic Leukaemia (AML M3) blood using simulated annealing and neural networks

This paper was delivered at AIME 2011: 13th Conference on Artifical Intelligence in Medicine.This paper presents a method for the detection and classification of blast cells in M3 with others sub-types using simulated annealing and neural networks. In this paper, we increased our test result from 10 images to 20 images. We performed Hill Climbing, Simulated Annealing and Genetic Algorithms for detecting the blast cells. As a result, simulated annealing is the “best” heuristic search for detecting the leukaemia cells. From the detection, we performed features extraction on the blast cells and we classifying based on M3 and other sub-types using neural networks. We received convincing result which has targeting around 97% in classifying of M3 with other sub-types. Our results are based on real world image data from a Haematology Department.Universiti Sains Islam Malaysia and the Ministry of Higher Education, Malaysi

Soft computing for intelligent data analysis

Intelligent data analysis (IDA) is an interdisciplinary study concerned with the effective analysis of data. The paper briefly looks at some of the key issues in intelligent data analysis, discusses the opportunities for soft computing in this context, and presents several IDA case studies in which soft computing has played key roles. These studies are all concerned with complex real-world problem solving, including consistency checking between mass spectral data with proposed chemical structures, screening for glaucoma and other eye diseases, forecasting of visual field deterioration, and diagnosis in an oil refinery involving multivariate time series. Bayesian networks, evolutionary computation, neural networks, and machine learning in general are some of those soft computing techniques effectively used in these studies

The SUMMIT trial: a field comparison of buprenorphine versus methadone maintenance treatment.

This prospective patient-preference study examined the effectiveness in practice of methadone versus buprenorphine maintenance treatment and the beliefs of subjects regarding these drugs. A total of 361 opiate-dependent individuals (89% of those eligible, presenting for treatment over 2 years at a drug service in England) received rapid titration then flexible dosing with methadone or buprenorphine; 227 patients chose methadone (63%) and 134 buprenorphine (37%). Participants choosing methadone had more severe substance abuse and psychiatric and physical problems but were more likely to remain in treatment. Survival analysis indicated those prescribed methadone were over twice as likely to be retained (hazard ratio for retention was 2.08 and 95% confidence interval [CI] = 1.49-2.94 for methadone vs. buprenorphine), However, those retained on buprenorphine were more likely to suppress illicit opiate use (odds ratio = 2.136, 95% CI = 1.509-3.027, p < .001) and achieve detoxification. Buprenorphine may also recruit more individuals to treatment because 28% of those choosing buprenorphine (10% of the total sample) stated they would not have accessed treatment with methadone

Scaling of the Random-Field Ising Model at Zero Temperature

The exact determination of ground states of small systems is used in a scaling study of the random-field Ising model. While three variants of the model are found to be in the same universality class in 3 dimensions, the Gaussian and bimodal models behave distinctly in 4 dimensions with the latter apparently having a discontinuous jump in the magnetization. A finite-size scaling analysis is presented for this transition.Comment: 14 pages Latex, 4 figure

Sds22 regulates aurora B activity and microtubule-kinetochore interactions at mitosis

Sds22 defines protein phosphatase 1 location and function at kinetochores and subsequent activity of aurora B in mitosis

Renormalization Group Method and Reductive Perturbation Method

It is shown that the renormalization group method does not necessarily eliminate all secular terms in perturbation series to partial differential equations and a functional subspace of renormalizable secular solutions corresponds to a choice of scales of independent variables in the reductive perturbation method.Comment: 5 pages, late

Shock and Release Temperatures in Molybdenum

Shock and release temperatures in Mo were calculated, taking account of heating from plastic flow predicted using the Steinberg-Guinan model. Plastic flow was calculated self-consistently with the shock jump conditions: this is necessary for a rigorous estimate of the locus of shock states accessible. The temperatures obtained were significantly higher than predicted assuming ideal hydrodynamic loading. The temperatures were compared with surface emission spectrometry measurements for Mo shocked to around 60GPa and then released into vacuum or into a LiF window. Shock loading was induced by the impact of a planar projectile, accelerated by high explosive or in a gas gun. Surface velocimetry showed an elastic wave at the start of release from the shocked state; the amplitude of the elastic wave matched the prediction to around 10%, indicating that the predicted flow stress in the shocked state was reasonable. The measured temperatures were consistent with the simulations, indicating that the fraction of plastic work converted to heat was in the range 70-100% for these loading conditions

Lattice Boltzmann simulations of lamellar and droplet phases

Lattice Boltzmann simulations are used to investigate spinodal decomposition in a two-dimensional binary fluid with equilibrium lamellar and droplet phases. We emphasise the importance of hydrodynamic flow to the phase separation kinetics. For mixtures slightly asymmetric in composition the fluid phase separates into bulk and lamellar phases with the lamellae forming distinctive spiral structures to minimise their elastic energy.Comment: 19 pages, 5 figure

Derivation of Amplitude Equations by Renormalization Group Method

A proper formulation in the perturbative renormalization group method is presented to deduce amplitude equations. The formulation makes it possible not only avoiding a serious difficulty in the previous reduction to amplitude equations by eliminating all of the secular terms but also consistent derivation of higher-order correction to amplitude equations.Comment: 6 page, revte

Explanation for Anomalous Shock Temperatures Measured by Neutron Resonance Spectroscopy

Neutron resonance spectrometry (NRS) has been used to measure the temperature inside Mo samples during shock loading. The temperatures obtained were significantly higher than predicted assuming ideal hydrodynamic loading. The effect of plastic flow and non-ideal projectile behavior were assessed. Plastic flow was calculated self-consistently with the shock jump conditions: this is necessary for a rigorous estimate of the locus of shock states accessible. Plastic flow was estimated to contribute a temperature rise of 53K compared with hydrodynamic flow. Simulations were performed of the operation of the explosively-driven projectile system used to induce the shock in the Mo sample. The simulations predicted that the projectile was significantly curved on impact, and still accelerating. The resulting spatial variations in load, including radial components of velocity, were predicted to increase the apparent temperature that would be deduced from the width of the neutron resonance by 160K. These corrections are sufficient to reconcile the apparent temperatures deduced using NRS with the accepted properties of Mo, in particular its equation of state.Comment: near-final version, waiting for final consent from an autho