Cepstrum based unsupervised spike classification

In this research, we study the effect of feature selection in the spike detection and sorting accuracy.We introduce a new feature representation for neural spikes from multichannel recordings. The features selection plays a significant role in analyzing the response of brain neurons. The more precise selection of features leads to a more accurate spike sorting, which can group spikes more precisely into clusters based on the similarity of spikes. Proper spike sorting will enable the association between spikes and neurons. Different with other threshold-based methods, the cepstrum of spike signals is employed in our method to select the candidates of spike features. To choose the best features among different candidates, the Kolmogorov-Smirnov (KS) test is utilized. Then, we rely on the superparamagnetic method to cluster the neural spikes based on KS features. Simulation results demonstrate that the proposed method not only achieve more accurate clustering results but also reduce computational burden, which implies that it can be applied into real-time spike analysis.

Transitions in reflective practice: exploring student development and preferred methods of engagement

Aim: Health-care professional students are required to demonstrate their reflective practice skills during their degree training programme. Online and digital technologies are increasingly being used to support this skill development. Our study aimed to explore whether different technology-based methods supported student growth and skill development in reflective practice at separate developmental time points (novice and competent). Methods: Third- (n = 23) and fourth-year undergraduate dietetic students (n = 22) from a single university were cross-sectionally surveyed via an online anonymous questionnaire at the end of the academic year. The mixed methods survey of 37 questions investigated the student experience of different reflective practice activities, their effect on a student's ability to self-reflect and whether using them aided a student's perceived transition towards becoming a competent dietitian. The data analysis included brief thematic enquiry, descriptive and independent t-test statistical examination. Results: Differences emerged in the way students engaged in reflection over time. Fourth-year students preferred to use more independent methods such as e-journaling (fourth- vs third-year students, P = 0.003) and engaged in reflection for reasons outside assessment (fourth- vs third-years, P = 0.027). Fourth-year students also identified fewer negative barriers to participating in reflection and reported being comfortable engaging in reflective practice. Conclusions: Overall, offering students a range of ways to engage in reflective practice over time supported their understanding and increased confidence in their reflective practice skills, thus potentially enabling a smoother transition into their profession where reflective practice is an essential and autonomous skill. © 2014 Dietitians Association of Australia.

An interval type-2 fuzzy logic system-based method for prediction interval construction

This paper introduces a new non-parametric method for uncertainty quantification through construction of prediction intervals (PIs). The method takes the left and right end points of the type-reduced set of an interval type-2 fuzzy logic system (IT2FLS) model as the lower and upper bounds of a PI. No assumption is made in regard to the data distribution, behaviour, and patterns when developing intervals. A training method is proposed to link the confidence level (CL) concept of PIs to the intervals generated by IT2FLS models. The new PI-based training algorithm not only ensures that PIs constructed using IT2FLS models satisfy the CL requirements, but also reduces widths of PIs and generates practically informative PIs. Proper adjustment of parameters of IT2FLSs is performed through the minimization of a PI-based objective function. A metaheuristic method is applied for minimization of the non-linear non-differentiable cost function. Performance of the proposed method is examined for seven synthetic and real world benchmark case studies with homogenous and heterogeneous noise. The demonstrated results indicate that the proposed method is capable of generating high quality PIs. Comparative studies also show that the performance of the proposed method is equal to or better than traditional neural network-based methods for construction of PIs in more than 90% of cases. The superiority is more evident for the case of data with a heterogeneous noise. © 2014 Elsevier B.V.

Tree-based iterated local search for Markov random fields with applications in image analysis

The maximum a posteriori assignment for general structure Markov random fields is computationally intractable. In this paper, we exploit tree-based methods to efficiently address this problem. Our novel method, named Tree-based Iterated Local Search (T-ILS), takes advantage of the tractability of tree-structures embedded within MRFs to derive strong local search in an ILS framework. The method efficiently explores exponentially large neighborhoods using a limited memory without any requirement on the cost functions. We evaluate the T-ILS on a simulated Ising model and two real-world vision problems: stereo matching and image denoising. Experimental results demonstrate that our methods are competitive against state-of-the-art rivals with significant computational gain.

Investigating the validity and usability of an interactive computer programme for assessing competence in telephone-based mental health triage

Telephone-based mental health triage services are frontline health-care providers that operate 24/7 to facilitate access to psychiatric assessment and intervention for people requiring assistance with a mental health problem. The mental health triage clinical role is complex, and the populations triage serves are typically high risk; yet to date, no evidence-based methods have been available to assess clinician competence to practice telephone-based mental health triage. The present study reports the findings of a study that investigated the validity and usability of the Mental Health Triage Competency Assessment Tool, an evidence-based, interactive computer programme designed to assist clinicians in developing and assessing competence to practice telephone-based mental health triage.

Prediction interval-based modelling and control of nonlinear processes

 Novel computational intelligence-based methods have been investigated to quantify uncertainties prevalent in the operation of chemical plants. A new family of predication interval-based controlling algorithms is proposed and successfully applied to chemical reactors in order to minimise energy consumption and operational cost.

An audio signal based model for condition monitoring of sheet metal stamping process

Tool condition monitoring is an important factor in ensuring manufacturing efficiency and product quality. Audio signal based methods are a promising technique for condition monitoring. However, the influence of interfering signals and background noise has hindered the use of this technique in production sites. Blind signal separation (BSS) has the potential to solve this problem by recovering the signal of interest out of the observed mixtures, given that the knowledge about the BSS model is available. In this paper, we discuss the development of the BSS model for sheet metal stamping with a mechanical press system, so that the BSS techniques based on this model can be developed in future. This involves conducting a set of specially designed machine operations and developing a novel signal extraction technique. Also, the link between stamping process conditions and the extracted audio signal associated with stamping was successfully demonstrated by conducting a series of trials with different lubrication conditions and levels of tool wear.

Testing unit root based on partially adaptive estimation

This paper proposes unit tests based on partially adaptive estimation. The proposed tests provide an intermediate class of inference procedures that are more efficient than the traditional OLS-based methods and simpler than unit root tests based on fully adptive estimation using nonparametric methods. The limiting distribution of the proposed test is a combination of standard normal and the traditional Dickey-Fuller (DF) distribution, including the traditional ADF test as a special case when using Gaussian density. Taking into a account the well documented characteristic of heavy-tail behavior in economic and financial data, we consider unit root tests coupled with a class of partially adaptive M-estimators based on the student-t distributions, wich includes te normal distribution as a limiting case. Monte Carlo Experiments indicate that, in the presence of heavy tail distributions or innovations that are contaminated by outliers, the proposed test is more powerful than the traditional ADF test. We apply the proposed test to several macroeconomic time series that have heavy-tailed distributions. The unit root hypothesis is rejected in U.S. real GNP, supporting the literature of transitory shocks in output. However, evidence against unit roots is not found in real exchange rate and nominal interest rate even haevy-tail is taken into a account.

Otimização topológica de estruturas termoelásticas tridimensionais

This work presents an optimization technique based on structural topology optimization methods, TOM, designed to solve problems of thermoelasticity 3D. The presented approach is based on the adjoint method of sensitivity analysis unified design and is intended to loosely coupled thermomechanical problems. The technique makes use of analytical expressions of sensitivities, enabling a reduction in the computational cost through the use of a coupled field adjoint equation, defined in terms the of temperature and displacement fields. The TOM used is based on the material aproach. Thus, to make the domain is composed of a continuous distribution of material, enabling the use of classical models in nonlinear programming optimization problem, the microstructure is considered as a porous medium and its constitutive equation is a function only of the homogenized relative density of the material. In this approach, the actual properties of materials with intermediate densities are penalized based on an artificial microstructure model based on the SIMP (Solid Isotropic Material with Penalty). To circumvent problems chessboard and reduce dependence on layout in relation to the final optimal initial mesh, caused by problems of numerical instability, restrictions on components of the gradient of relative densities were applied. The optimization problem is solved by applying the augmented Lagrangian method, the solution being obtained by applying the finite element method of Galerkin, the process of approximation using the finite element Tetra4. This element has the ability to interpolate both the relative density and the displacement components and temperature. As for the definition of the problem, the heat load is assumed in steady state, i.e., the effects of conduction and convection of heat does not vary with time. The mechanical load is assumed static and distributed

Methacycline: A Review of Analytical Methods

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Time-domain analysis of piezoelectric impedance-based structural health monitoring using multilevel wavelet decomposition

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Performance of fluorescence methods, radiographic examination and ICDAS II on occlusal surfaces in vitro

This study compared the performance of fluorescence-based methods, radiographic examination, and International Caries Detection and Assessment System (ICDAS) II on occlusal surfaces. One hundred and nineteen permanent human molars were assessed twice by 2 experienced dentists using the laser fluorescence (LF and LFpen) and fluorescence camera (FC) devices, ICDAS II and bitewing radiographs (BW). After measuring, the teeth were histologically prepared and assessed for caries extension. The sensitivities for dentine caries detection were 0.86 (FC), 0.78 (LFpen), 0.73 (ICDAS II), 0.51 (LF) and 0.34 (BW). The specificities were 0.97 (BW), 0.89 (LF), 0.65 (ICDAS II), 0.63 (FC) and 0.56 (LFpen). BW presented the highest values of likelihood ratio (LR)+ (12.47) and LR- (0.68). Rank correlations with histology were 0.53 (LF), 0.52 (LFpen), 0.41 (FC), 0.59 (ICDAS II) and 0.57 (BW). The area under the ROC curve varied from 0.72 to 0.83. Inter- and intraexaminer intraclass correlation values were respectively 0.90 and 0.85 (LF), 0.93 and 0.87 (LFpen) and 0.85 and 0.76 (FC). The ICDAS II kappa values were 0.51 (interexaminer) and 0.61 (intraexaminer). The BW kappa values were 0.50 (interexaminer) and 0.62 (intraexaminer). The Bland and Altman limits of agreement were 46.0 and 38.2 (LF), 55.6 and 40.0 (LFpen) and 1.12 and 0.80 (FC), for intra- and interexaminer reproducibilities. The posttest probability for dentine caries detection was high for BW and LF. In conclusion, LFpen, FC and ICDAS II presented better sensitivity and LF and BW better specificity. ICDAS II combined with BW showed the best performance and is the best combination for detecting caries on occlusal surfaces. Copyright (C) 2008 S. Karger AG, Basel.

Influence of Different Professional Prophylactic Methods on Fluorescence Measurements for Detection of Occlusal Caries

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Differentiation of Acidithiobacillus ferrooxidans and A-thiooxidans strains based on 16S-23S rDNA spacer polymorphism analysis

Restriction fragment length polymorphism (RFLP) and sequence analyses of the PCR-amplified 16S-23S rDNA intergenic spacer (ITS) were used for differentiating Acidithiobacillus thiooxidans strains from other related acidithiobacilli, including A. ferrooxidans and A. caldus. RFLP fingerprints obtained with AluI, DdeI, HaeIII, HinfI and MspI enabled the differentiation of all Acidithiobacillus reference strains into species groups. The A. thiooxidans strains investigated (metal mine isolates) yielded identical RFLP patterns to the A. thiooxidans type strain (ATCC 19377(T)), except for strain DAMS, which had a distinct pattern for all enzymes tested. Fourteen A. ferrooxidans mine strains were assigned to 3 RFLP groups, the majority of which were grouped with A. ferrooxidans ATCC 23270(T). The spacer region of one representative strain from each of the RFLP groups obtained was subjected to sequence analysis, in addition to eleven additional A. thiooxidans strains isolated from sediment and water samples, and A. caldus DSM 8584(T). The tRNA(IIe) and tRNA(Ala) genes, present in all strains analyzed, showed high sequence similarity. Phylogenetic analysis of the ITS sequences differentiated all three Acidithiobacillus species. Inter- and infraspecific genetic variations detected were mainly due to the size and sequence polymorphism of the ITS3 region. Mantel tests showed no significant correlation between ITS sequence similarity and the geographical origin of strains. The results showed that the 16S-23S rDNA spacer region is a useful target for the development of molecular-based methods aimed at the detection, rapid differentiation and identification of acidithiobacilli. (C) 2004 Elsevier SAS. All rights reserved.

A PZT-based technique for SHM using the coherence function

This paper presents a new approach for damage detection in structural health monitoring systems exploiting the coherence function between the signals from PZT (Lead Zirconate Titanate) transducers bonded to a host structure. The physical configuration of this new approach is similar to the configuration used in Lamb wave based methods, but the analysis and operation are different. A PZT excited by a signal with a wide frequency range acts as an actuator and others PZTs are used as sensors to receive the signal. The coherences between the signals from the PZT sensors are obtained and the standard deviation for each coherence function is computed. It is demonstrated through experimental results that the standard deviation of the coherence between the signals from the PZTs in healthy and damaged conditions is a very sensitive metric index to detect damage. Tests were carried out on an aluminum plate and the results show that the proposed methodology could be an excellent approach for structural health monitoring (SHM) applications.