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

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

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

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

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

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

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

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

A quantum search for zeros of polynomials

A quantum mechanical search procedure to determine the real zeros of a polynomial is introduced. It is based on the construction of a spin observable whose eigenvalues coincide with the zeros of the polynomial. Subsequent quantum mechanical measurements of the observable output directly the numerical values of the zeros. Performing the measurements is the only computational resource involved

Nature Of Transition Circumstellar Disks. I. The Ophiuchus Molecular Cloud

We have obtained millimeter-wavelength photometry, high-resolution optical spectroscopy, and adaptive optics near-infrared imaging for a sample of 26 Spitzer-selected transition circumstellar disks. All of our targets are located in the Ophiuchus molecular cloud (d similar to 125 pc) and have spectral energy distributions (SEDs) suggesting the presence of inner opacity holes. We use these ground-based data to estimate the disk mass, multiplicity, and accretion rate for each object in our sample in order to investigate the mechanisms potentially responsible for their inner holes. We find that transition disks are a heterogeneous group of objects, with disk masses ranging from <0.6 to 40 M(JUP) and accretion rates ranging from <10(-11) to 10(-7) M(circle dot) yr(-1), but most tend to have much lower masses and accretion rates than "full disks" (i.e., disks without opacity holes). Eight of our targets have stellar companions: six of them are binaries and the other two are triple systems. In four cases, the stellar companions are close enough to suspect they are responsible for the inferred inner holes. We find that nine of our 26 targets have low disk mass (<2.5 M(JUP)) and negligible accretion (<10(-11) M(circle dot) yr(-1)), and are thus consistent with photoevaporating (or photoevaporated) disks. Four of these nine non-accreting objects have fractional disk luminosities <10(-3) and could already be in a debris disk stage. Seventeen of our transition disks are accreting. Thirteen of these accreting objects are consistent with grain growth. The remaining four accreting objects have SEDs suggesting the presence of sharp inner holes, and thus are excellent candidates for harboring giant planets.NASA 1224608, 1230782, 1230779, 1407FONDECYT 1061199Basal CATA PFB 06/09ALMA FUND 31070021ALMA-Conicyt FUND 31060010National Science Foundation AST0-808144Spitzer Space Telescope Legacy Science ProgramAstronom