Currently there are ∼3,000 known species of Sarcophagidae (Diptera), which are classified into 173 genera in three subfamilies. Almost 25% of sarcophagids belong to the genus Sarcophaga (sensu lato) however little is known about the validity of, and relationships between the ∼150 (or more) subgenera of Sarcophaga s.l. In this ...

BACKGROUND: It is challenging to assist people to attend to risk factors for coronary artery disease (CAD). There is potential for cultural elements associated with place of residence (i.e., urban- or rural-living) to have an effect on peoples' decision-making about managing CAD risk. AIM: To better understand patient's decision-making processes ...

Cardiovascular diseases are very common and are one of the main reasons of death. Being among the major types of these diseases, correct and in-time diagnosis of coronary artery disease (CAD) is very important. Angiography is the most accurate CAD diagnosis method; however, it has many side effects and is ...

Recent advances in high-throughput technologies for biological data acquisition have spurred a broad interest in the construction of mathematical models for biological phenomena.The development of such mathematical models relies on the estimation of unknown parameters of the system using the time-course profiles of different metabolites in the system. One of ...

BACKGROUND: No anatomical study has been conducted over Asian population to design humeral head prosthesis for the population concerned. This study was done to evaluate the accuracy of commercially available humeral head prosthetic designs, in replicating the humeral head anatomy. METHODS: CT scan data of 48 patients were taken and ...

Aim: Transparent hollow models are needed to visualize and quantify flow in various applications. To obtain the final transparent model, an intermediate molding of the fluid space with an easily removable material is required. Currently used materials to produce this intermediate molding have limitations: toxicity, cost, and a tendency to ...

Objectives. To build a 3D parametric model to detect shape and volume of dental roots, from a panoramic radiograph (PAN) of the patient. Materials and Methods. A PAN and a cone beam computed tomography (CBCT) of a patient were acquired. For each tooth, various parameters were considered (coronal and root ...

Background: The study describes the development and implementation of a digital nose database in order to provide patients with nasal prostheses following rhinectomy. Mirrored data for computer-aided design (CAD) cannot be used due to the unpaired structure of the nose. Materials and Methods: The faces of 202 people were digitized ...

Background -  The third iteration of the Canine Atopic Dermatitis Extent and Severity Index (CADESI-03) is the only tool rigorously validated for canine atopic dermatitis (CAD) lesion scoring. The CADESI-03 requires 248 evaluations, limiting its widespread use. Hypothesis/Objectives -  The goal of the study was to develop and validate a ...

Alhough thermal sterilisation is a widely employed industrial process, little work is reported in the available literature including patents on the mathematical analysis and simulation of these processes. In the present work,  software packages have been developed for computer aided optimum design of thermal sterilisation processes. Systems involving steam sparging, ...

OBJECTIVES: Aim of the research is to compare the orthodontic appliances fabricated by using rapid prototyping (RP) systems, in particular 3D printers, with those manufactured by using computer numerical control (CNC) milling machines. 3D printing is today a well-accepted technology to fabricate orthodontic aligners by using the thermoforming process, instead ...

Abstract The aim of the study was to evaluate the short and medium term use of personalised insoles, produced by combining additive manufacturing (AM) with three-dimensional (3-D) foot scanning and computer aided design (CAD) systems. For that, 38 runners (19 pairings) were recruited. The experimental conditions were: personalised and control. ...

BACKGROUND: A numerical based brace design platform, including biomechanical simulation, Computer Aided Design and Computer Aided Manufacturing (CAD/CAM) was developed to rationalize braces for the treatment of adolescent idiopathic scoliosis. The objective of this study was to test the feasibility of the approach and assess the effectiveness of braces issued ...

A case report of a nasal spur detected on pre-operative 3-D Cad-Cam models illustrating the use of these models in predicting and preventing anaesthetic difficulties.

Often CAD models already exist for parts of a geometry being simulated using GEANT4. Direct import of these CAD models into GEANT4 however, may not be possible and complex components may be difficult to define via other means. Solutions that allow for users to work around the limited support in ...

Evaluation of protein models against the native structure is essential for the development and benchmarking of protein structure prediction methods. Although a number of evaluation scores have been proposed to date, many aspects of model assessment still lack desired robustness. In this study we present CAD-score, a new evaluation function ...

The human hand plays an important role in daily life. It is the interface between the human and the exterior world by positioning, orienting, touching and grasping objects. The human hand has multiple degrees of freedom (DOFs) to enable mobility and dexterity. A virtual human hand model can be inserted ...

We introduce a new version of the perceptual retouch model. This model was used for explaining properties of temporal interaction of successive objects in reaching conscious representation. The new model incorporates two interactive binding operations - binding features for objects and binding the bound feature-objects with a large scale oscillatory ...

Modern microelectrode arrays acquire neural signals from hundreds of neurons in parallel that are subsequently processed for spike sorting. It is important to identify, extract and transmit appropriate features that allow accurate spike sorting while using minimum computational resources. This paper describes a new set of spike sorting features, explicitly ...

Coronary artery calcification (CAC) score is an important predictor of coronary artery disease (CAD), which is the primary cause of death in advanced countries. Early prediction of high-risk of CAC based on progression rate enables people to prevent CAD from developing into severe symptoms and diseases. In this study, we ...

Physicians have difficulty to subjectively estimate the cardiovascular risk of their patients. Using an estimate of global cardiovascular risk could be more relevant to guide decisions than using binary representation (presence or absence) of risk factors data. The main aim of the paper is to compare different models of predicting ...

Recently, the N-way partial least squares (NPLS) approach was reported as an effective tool for neuronal signal decoding and brain-computer interface (BCI) system calibration. This method simultaneously analyzes data in several domains. It combines the projection of a data tensor to a low dimensional space with linear regression. In this ...

Since the Kalman filter and Monte Carlo techniques, much theoretical work has been put into the development of signal deconvolution tools. Among recent developments taking place in neuroscience are Dynamic Expectation Maximization, Generalized Filtering and the Cubature Kalman Filter. While there are exciting prospects to use these tools for Dynamic ...

In this paper we detail a phase lagging model of brain response to external stimuli. The model is derived using the basic laws of physics like conservation of energy law. This model eliminates the paradox of instantaneous propagation of the action potential in the brain. The solution of this model ...

Over the last two decades, significant strides has been made toward acquiring a better knowledge of both the etiology and pathogenesis of Parkinson's disease (PD). Experimental models are of paramount importance to obtain greater insights into the pathogenesis of the disease. Thus far, neurotoxin-based animal models have been the most ...

Epileptic seizures, epileptic spikes and high-frequency oscillations (HFOs) are recognized as three electrophysiological markers of epileptogenic neuronal systems. It can be reasonably hypothesized that distinct (hyper)excitability mechanisms underlie these electrophysiological signatures. The question is 'What are these mechanisms?'. Solving this difficult question would considerably help our understanding of epileptogenic processes ...

Direction selectivity is a fundamental physiological property that arises from primary visual cortex (V1) circuitry, yet basic questions of how direction-selective (DS) receptive fields are constructed remain unanswered. We built a set of simple, plausible neuronal circuits that produce DS cells via different mechanisms and tested these circuits to determine ...

Abstract Objectives: The increasing popularities of traditional Chinese medicine (TCM) and telehealth indicate a need for digitalizing major clinical assessment methods used during TCM consultations. In this study, an electronic TCM pulse diagnostic system was developed, and its validity was explored. Materials and Methods: The system was developed with an ...

A specific type of neural networks, the Restricted Boltzmann Machines (RBM), are implemented for classification and feature detection in machine learning. They are characterized by separate layers of visible and hidden units, which are able to learn efficiently a generative model of the observed data. We study a "hybrid" version ...

The spatial component of input signals often carries information crucial to a neuron's function, but models mapping synaptic inputs to the transmembrane potential can be computationally expensive. Existing reduced models of the neuron either merge compartments, thereby sacrificing the spatial specificity of inputs, or apply model reduction techniques that sacrifice ...

Olfactory transduction exhibits two distinct types of adaptation, which we denote multipulse and step adaptation. In terms of measured transduction current, multipulse adaptation appears as a decrease in the amplitude of the second of two consecutive responses when the olfactory neuron is stimulated with two brief pulses. Step adaptation occurs ...

The wide diversity of dendritic trees is one of the most striking features of neural circuits. Here we develop a general quantitative theory relating the total length of dendritic wiring to the number of branch points and synapses. We show that optimal wiring predicts a 2/3 power law between these ...

The goal of this study was to create a realistic and quantitative simulation of vasopressin (AVP) secretion under iso-osmotic and short-term challenged plasma osmolality. The relationship between AVP concentration ([AVP]) and plasma osmolality was computed using a sophisticated and integrated model that chronologically simulates (1) the overall firing rate of ...

The objective was to prevent loss of some implicit structural and local contextual information of lung nodules by current one- (1D) or two-dimensional (2D) schemes. The testing data set used in this study consisted of computed tomographic scans from 196 different patients in Jilin Tumor Hospital, which consisted of 8428 ...

We show that the stochastic Morris-Lecar neuron, in a neighborhood of its stable point, can be approximated by a two-dimensional Ornstein-Uhlenbeck (OU) modulation of a constant circular motion. The associated radial OU process is an example of a leaky integrate-and-fire (LIF) model prior to firing. A new model constructed from ...

This paper describes the development of a new biorobotic platform inspired by the lamprey. Design, fabrication and implemented control are all based on biomechanical and neuroscientific findings on this eel-like fish. The lamprey model has been extensively studied and characterized in recent years because it possesses all basic functions and ...

The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit ...

Recurrent neural networks (RNNs) are widely used in computational neuroscience and machine learning applications. In an RNN, each neuron computes its output as a nonlinear function of its integrated input. While the importance of RNNs, especially as models of brain processing, is undisputed, it is also widely acknowledged that the ...

The etiology of Parkinson's disease (PD) is attributed to both environmental and genetic factors. The development of PD reportedly involves mitochondrial impairment, oxidative stress, α-synuclein aggregation, dysfunctional protein degradation, glutamate toxicity, calcium overloading, inflammation and loss of neurotrophic factors. Based on a link between mitochondrial dysfunction and pesticide exposure, many ...

As multi-electrode and imaging technology begin to provide us with simultaneous recordings of large neuronal populations, new methods for modeling such data must also be developed. We present a model of responses to repeated trials of a sensory stimulus based on thresholded Gaussian processes that allows for analysis and modeling ...

Dynamic Causal Modelling (DCM) was introduced to study the effective connectivity among brain regions using neuroimaging data. Until recently, DCM relied on deterministic models of distributed neuronal responses to external perturbation (e.g., sensory stimulation or task demands). However, accounting for stochastic fluctuations in neuronal activity and their interaction with task-specific ...

Traumatic brain injuries have recently been put under the spotlight as one of the most important causes of accidental brain dysfunctions. Significant experimental and modeling efforts are thus underway to study the associated biological, mechanical and physical mechanisms. In the field of cell mechanics, progress is also being made at ...

Measuring pairwise and higher-order spike correlations is crucial for studying their potential impact on neuronal information processing. In order to avoid misinterpretation of results, the tools used for data analysis need to be carefully calibrated with respect to their sensitivity and robustness. This, in turn, requires surrogate data with statistical ...

The ability to quantitatively evaluate the impact of a potential therapeutic intervention for Huntington disease (HD) in animal models for the disease is a critical step in the pathway to development of an effective therapy for this devastating neurodegenerative disorder. We report here an approach that combines a cell-based assay's ...

Networks of neurons perform complex calculations using distributed, parallel computation, including dynamic "real-time" calculations required for motion control. The brain must combine sensory signals to estimate the motion of body parts using imperfect information from noisy neurons. Models and experiments suggest that the brain sometimes optimally minimizes the influence of ...

Several authors have previously discussed the use of log-linear models, often called maximum entropy models, for analyzing spike train data to detect synchrony. The usual log-linear modeling techniques, however, do not allow time-varying firing rates that typically appear in stimulus-driven (or action-driven) neurons, nor do they incorporate non-Poisson history effects ...

We study the dynamics of a quadratic integrate-and-fire model of a single-compartment neuron with a slow recovery variable, as input current and parameters describing timescales, recovery variable, and postspike reset change. Analysis of a codimension 2 bifurcation reveals that the domain of attraction of a stable hyperpolarized rest state interacts ...

The construction of compartmental models of neurons involves tuning a set of parameters to make the model neuron behave as realistically as possible. While the parameter space of single-compartment models or other simple models can be exhaustively searched, the introduction of dendritic geometry causes the number of parameters to balloon. ...

Hodgkin-Huxley (HH) models of neuronal membrane dynamics consist of a set of nonlinear differential equations that describe the time-varying conductance of various ion channels. Using observations of voltage alone we show how to estimate the unknown parameters and unobserved state variables of an HH model in the expected circumstance that ...

Studies of spike-timing dependent plasticity (STDP) have revealed that long-term changes in the strength of a synapse may be substantially modulated by temporal relationships between multiple presynaptic and postsynaptic spikes. While long-term potentiation (LTP) and long-term depression (LTD) of synaptic strength have been modeled as distinct or separate functional mechanisms, ...