Attentional control over prepotent responses has previously been shown by manipulating the probability with which stimuli appear. Here, we examined whether prepotent responses to self-associated stimuli can be modulated by their frequency of occurrence. Participants were instructed to associate geometric shapes with the self, their mother, or a stranger before having to judge whether the sequential shape-label pairs matched or mismatched the instruction. The probability of the different shape-label pairs was varied. There was a robust advantage to self-related stimuli in all cases. Reducing the proportion of matched self pairs did not weaken performance with self-related stimuli, whereas reducing the frequency of either matched mother or stranger pairs hurt performance, relative to when the different match trials were equiprobable. In addition, while mother and stranger pairs jointly benefitted when they both occurred frequently, there were benefits only to self pairs when the frequency of self trials increased along with either mother or stranger trials. The results suggest that biases favoring self-related stimuli occur automatically, even when self-related stimuli have a low probability of occurrence, and that expectations to frequent, self-related stimuli operate in a relatively exclusive manner, minimizing biases to high-probability stimuli related to other people. In contrast, biases to high-familiarity stimuli (mother pairs) can be reduced when the items occur infrequently and they do not dominate expectations over other high-frequency stimuli.

We introduce a novel approach for noise-robust feature extraction in speech recognition, based on non-negative matrix factorization (NMF). While NMF has previously been used for speech denoising and speaker separation, we directly extract time-varying features from the NMF output. To this end we extend basic unsupervised NMF to a hybrid supervised/unsupervised algorithm. We present a Dynamic Bayesian Network (DBN) architecture that can exploit these features in a Tandem manner together with the maximum likelihood phoneme estimate of a bidirectional long short-term memory (BLSTM) recurrent neural network. We show that addition of NMF features to spelling recognition systems can increase word accuracy by up to 7 % absolute in a noisy car environment.

No abstract

he Achilles tendon is the largest, thickest, and strongest tendon in the human body. Problems with the Achilles tendon are frequent in athletes and the general population because of the increased incidence of sports-related injuries, which cause foot and ankle pain. [1][2][3][4] The area 5 cm proximal to the calcaneus is especially predisposed to tendinopathy and subsequent tearing due to vascular and biomechanical factors. Sonography plays an important role in the evaluation of tendon disorders, owing to its low cost, relative availability, noninvasiveness, and dynamic character. However, its diagnostic accuracy remains controversial. 5,6 Magnetic resonance imaging is a useful modality for imaging the Achilles tendon, but it is expensive and time-consuming.Shuai Fu, MD, Ligang Cui, MD, Xiaoxi He, MD, Yang Sun, MD Received January 20, 2016, Methods-A total of 326 healthy volunteers older than 18 years were divided into different groups by sex and age. The thickness, shear wave velocity (SWV) in sagittal and axial sections, and anisotropic coefficient of the Achilles tendon in a state of relaxation were obtained by conventional sonography and Virtual Touch imaging quantification elastography. These parameters were compared in different age and sex groups, and their correlations with age were evaluated.Results-The thickness of the Achilles tendon in men and women increased gradually with age, and it was larger in men than in women in each age group (P < .05). The SWV of the tendon in the sagittal section decreased slightly with age, but the sagittal and axial SWVs and anisotropic coefficient had no significant differences among different age groups (P > .05), and they also had no significant differences between men and women within any group (P > .05). The SWVs in the sagittal and axial sections and anisotropic coefficient had no correlation with age. Intraclass correlation coefficients for sagittal and axial SWVs obtained by 2 independent observers were 0.923 and 0.870, respectively.Conclusions-The thickness of the Achilles tendon increased gradually with age. We confirmed that tendinous elastographic anisotropy and the stiffness of the tendon had no significant correlation with age.

No abstract

No abstract

Shear Wave Elastography (SWE) is an objective and non-invasive method widely used to quantify the tissue solidity. However, there are concerns about the accuracy of the skin SWE results due to the low signal-to-noise ratio (SNR) caused by subcutaneous fat, muscle and bone. This article analyzed the reproducibility of the result for skin SWE and therefore evaluated the availability of SME for skin elasticity involved diseases. Thirty volunteers (mean age: 37 ± 12 years) were selected. SWE were taken on the skin of abdomen and the middle tibia in order to assess the impact of fat, muscle and bone on SWE results. Skin in the area of anterior and lateral tibia marked with seven parallel lines, and each line indicated an identical thickness of the subcutaneous fat from 1–7 mm. Intra-class correlation coefficients (ICC) were used to evaluate the intra-observer and inter-observer reproducibility. The solidity of abdominal skin showed soft and small individual differences (12.4 ± 2.7 kPa), whereas high shear moduli (25–48 kPa) were observed in the skin above tibia and tibialis anterior muscle. When the subcutaneous fat was thicker than 3 mm (≥3), we obtained excellent intra-observer reproducibility (ICC range 0.78–0.98) and inter-observer reproducibility (ICC range 0.75–0.98). The thickness of subcutaneous fat could affect the reproducibility of skin SWE. The further study on skin SWE standardization should be taken.

No abstract