Commuting tillage operations of HRP under hydraulic cylinder movements on plough-breast performance

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Vibration of fast trains, palindromic eigenvalue problems and structure-preserving doubling algorithms

AbstractThe vibration of fast trains is governed by a quadratic palindromic eigenvalue problem (λ2A1T+λA0+A1)x=0, where A0,A1∈Cn×n and A0T=A0. Accurate and efficient solution can only be obtained using algorithms which preserve the structure of the eigenvalue problem. This paper reports on the successful application of the structure-preserving doubling algorithms

A novel mutation in the WFS1 gene identified in a Taiwanese family with low-frequency hearing impairment

<p>Abstract</p> <p>Background</p> <p>Wolfram syndrome gene 1 (<it>WFS1</it>) accounts for most of the familial nonsyndromic low-frequency sensorineural hearing loss (LFSNHL) which is characterized by sensorineural hearing losses equal to and below 2000 Hz. The current study aimed to contribute to our understanding of the molecular basis of LFSNHL in an affected Taiwanese family.</p> <p>Methods</p> <p>The Taiwanese family with LFSNHL was phenotypically characterized using audiologic examination and pedigree analysis. Genetic characterization was performed by direct sequencing of <it>WFS1 </it>and mutation analysis.</p> <p>Results</p> <p>Pure tone audiometry confirmed that the family members affected with LFSNHL had a bilateral sensorineural hearing loss equal to or below 2000 Hz. The hearing loss threshold of the affected members showed no progression, a characteristic that was consistent with a mutation in the <it>WFS1 </it>gene located in the DFNA6/14/38 locus. Pedigree analysis showed a hereditarily autosomal dominant pattern characterized by a full penetrance. Among several polymorphisms, a missense mutation Y669H (2005T>C) in exon 8 of <it>WFS1 </it>was identified in members of a Taiwanese family diagnosed with LFSNHL but not in any of the control subjects.</p> <p>Conclusion</p> <p>We discovered a novel heterozygous missense mutation in exon 8 of <it>WFS1 </it>(i.e., Y669H) which is likely responsible for the LFSNHL phenotype in this particular Taiwanese family.</p

Tillage condition effects on soil/plow-breast flow interaction of a horizontally reversible plow

Abstract : The horizontally reversible plow (HRP) is commonly utilized because of higher performances than the regular mold-board plow. Soil/plow surface flow interaction during HRP tillage trends to incur so severe pressure on the plow-breast as to reduce the plow life. This paper numerically characterized the soil/plow-breast flow interaction and subsequently assessed tillage-condition effects on the plow-breast surface. These tillage conditions herein involved tool speed and operation-al depth. The simulations showed that for either tool speed or operational depth the maximum pressure appeared at the plow-shank of the plow-breast and that the soil pressures were increased with them. The computational fluid dynamics (CFD) based predictions qualitatively agreed with the preliminary experimental results at the identified settings with scanning electronic microscopy. Once again, CFD analysis is demonstrated to be feasible and effective enough to provide insight into improve the horizontally reversible plow by predicting real soil behaviors

A K -means Interval Type-2 Fuzzy Neural Network for Medical Diagnosis

Abstract(#br)This paper proposes a new medical diagnosis algorithm that uses a K -means interval type-2 fuzzy neural network (KIT2FNN). This KIT2FNN classifier uses a K -means clustering algorithm as the pre-classifier and an interval type-2 fuzzy neural network as the main classifier. Initially, the training data are classified into k groups using the K -means clustering algorithm and these data groups are then used sequentially to train the structure of the k classifiers for the interval type-2 fuzzy neural network (IT2FNN). The test data are also initially used to determine to which classifier they are best suited and then they are inputted into the corresponding main classifier for classification. The parameters for the proposed IT2FNN are updated using the steepest descent gradient..