9 research outputs found
SCOURING AT BRIDGES PIERS UNDER UNSTEADY FLOW CONDITION AND ARMORED BEDS USING ANFIS AND OPTIMIZATION ALGORITHMS
No full textSeveral studies have been performed to study the scouring depth at bridge
piers. Due to the complication of the problem and variety of the hydraulic and
geometric parameters affecting the scouring phenomena, a generalized
relationship has not been presented yet. Therefore, adaptive neuro-fuzzy
inference system (ANFIS) is an alternative to overcome these problems. This
approach is an effective tool to provide the hydraulic engineers, precise estimation of the scouring depth around the bridge piers. Although a large number of former studies have just focused on scouring at bridge piers under steady flow condition and uniform-graded bed materials even by applying ANFIS model, a lack of studies exists on scouring under unsteady flood flow condition as well as for non-uniform bed materials. Generally, river beds are composed mainly of non-uniform materials. Motion of the finer sediment particles initiates results in the protective effect of greater particles, namely armoring effect on the bed surface, thereby eliminating further erosion of the bed. Furthermore, in most of the rivers the flow regime is commonly unsteady. During a flood, the maximum scouring depth regarding to the peak of the flood hydrograph would be smaller than the equilibrium scouring depth which is commonly estimated using a constant flow discharge. When the flow unsteadiness is pronounced, the difference between the maximum scouring depth and the equilibrium scouring depth is quite substantial and thus should be addressed.In the present study, armoring effect on local scouring under unsteady flow condition was investigated based on a comprehensive dataset collected by different former investigators using ANFIS model. For this purpose, two different models were constructed. The first model was based on 372 dataset collected in a practical study on different bridges in USA. Measurements were conducted under steady flow condition. The second model was developed for estimating the maximum scouring depth in the beds of uniform and armored materials under unsteady flow condition. To present a more accurate model, some strategies including; reduction of dimension and detection of outlier were used to improve the performance of calculations. Genetic algorithm and particle swarm optimization methods were applied to develop a novel hybrid learning algorithm for ANFIS model. The new hybrid learning algorithm train the
antecedent part of the fuzzy rules. Then the least square method was applied
for training the conclusion part of the rules. It was shown that ANFIS model
gives more accurate results compared to the empirical equations. Results
highlighted the effectiveness of the data on the estimations of ANFIS model.
Furthermore, according to the results, this approach is potentially able to train the ANFIS model in both steady and unsteady flow conditions
Relationship Between Voice and Motor Disabilities of Parkinson's Disease
No full textTo evaluate voice of Iranian patients with Parkinson's disease (PD) and find any relationship between motor disabilities and acoustic voice parameters as speech motor components. We evaluated 27 Farsi-speaking PD patients and 21 age- and sex-matched healthy persons as control. Motor performance was assessed by the Unified Parkinson's Disease Rating Scale part III and Hoehn and Yahr rating scale in the �on� state. Acoustic voice evaluation, including fundamental frequency (f0), standard deviation of f0, minimum of f0, maximum of f0, shimmer, jitter, and harmonic to noise ratio, was done using the Praat software via /a/ prolongation. No difference was seen between the voice of the patients and the voice of the controls. f0 and its variation had a significant correlation with the duration of the disease, but did not have any relationships with the Unified Parkinson's Disease Rating Scale part III. Only limited relationship was observed between voice and motor disabilities. Tremor is an important main feature of PD that affects motor and phonation systems. Females had an older age at onset, more prolonged disease, and more severe motor disabilities (not statistically significant), but phonation disorders were more frequent in males and showed more relationship with severity of motor disabilities. Voice is affected by PD earlier than many other motor components and is more sensitive to disease progression. Tremor is the most effective part of PD that impacts voice. PD has more effect on voice of male versus female patients. © 2016 The Voice Foundatio
Genetic screening in two Iranian families with early-onset Alzheimer's disease identified a novel PSEN1 mutation
No full textA subset of early-onset Alzheimer's disease is inherited as an autosomal-dominant trait and is associated with mutations in the genes encoding β-amyloid precursor protein, presenilin 1, or presenilin 2. In this study, we identified 2 PSEN1 mutations (1 novel and 1 known) in 2 unrelated Iranian families with autosomal-dominant Alzheimer's disease. The disease progressed rapidly with a mean age at onset of 33 and 42 years and an age at death ranging from 43 to 48 years. © 2017 Elsevier Inc
The ACMSD gene, involved in tryptophan metabolism, is mutated in a family with cortical myoclonus, epilepsy, and parkinsonism
No full textMutations in the Drosophila homolog of human PLA2G6 give rise to age-dependent loss of psychomotor activity and neurodegeneration
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