Optimal Step Size Technique for Frequency Domain and Partition Block Adaptive Filters for PEM based Acoustic Feedback Cancellation

The adaptive filtering approach has been commonly used to perform acoustic feedback cancellation (AFC) in digital hearing-aids due to its reliable performance and feasibility. Because the loudspeaker and microphone are close together in hearing aids, the corresponding signals are highly correlated, resulting in biased estimation if adaptive filters are used. This problem can be addressed with the help of the decorrelation prefilter by incorporating the Prediction Error Method (PEM) technique into AFC. Frequency-Domain Adaptive Filters (FDAF) are preferable over the time-domain implementation to achieve better performance in terms of convergence and computational complexity. In addition, Partition-Block Frequency-Domain Adaptive Filters (PBFDAF) offers low processing delay. However, because of their fixed step-size, there is a trade-off between initial convergence and steady-state misalignment in the widely used frequency-domain algorithms. While Variable Step-Size (VSS) algorithms can help with this issue, VSS techniques for frequency-domain algorithms have not been extensively studied in the context of PEM-AFC. Hence, in this paper, we presented an Optimal Step-Size (OSS) technique for both the FDAF-PEM_AFC and PBFDAF-PEM_AFC algorithms to simultaneously accomplish fast convergence and minimal steady-state error. A Feedback Path Change Detector (FPCD) was also incorporated into the proposed algorithms to address the problem of convergence in non-stationary feedback paths. The results of simulations show that the proposed algorithms are clearly superior, and they are encouraging

The use of kurtosis de-noising for EEG analysis of patients suffering from Alzheimer's disease.

The use of electroencephalograms (EEGs) to diagnose and analyses Alzheimer’s disease (AD) has received much attention in recent years. The sample entropy (SE) has been widely applied to the diagnosis of AD. In our study, nine EEGs from 21 scalp electrodes in 3 AD patients and 9 EEGs from 3 age-matched controls are recorded. The calculations show that the kurtoses of the AD patients’ EEG are positive and much higher than that of the controls. This finding encourages us to introduce a kurtosis-based de-noising method. The 21-electrode EEG is first decomposed using independent component analysis (ICA), and second sort them using their kurtoses in ascending order. Finally, the subspace of EEG signal using back projection of only the last five components is reconstructed. SE will be calculated after the above de-noising preprocess. The classifications show that this method can significantly improve the accuracy of SE-based diagnosis. The kurtosis analysis of EEG may contribute to increasing the understanding of brain dysfunction in AD in a statistical way

A Focus on the Reminiscence Bump to Personalize Music Playlists for Dementia

PURPOSE: Music and memory are inextricably linked, and the recollection of music varies according to age. In order to create personalized music playlists tailored for people living with dementia, this study aimed to determine the age at which healthy individuals could best recall music that was popular at the time. METHODS: A survey was designed asking participants to identify the number of songs they recalled from a random selection of 10 from the 100 most popular songs from each year, presented in random order of years, from 1945 to 2015. Of the 311 individuals born between 1929 and 2002, who responded to the survey, 157 met the inclusion criteria. RESULTS: The median peak of recollection was between the ages of 13 and 19 across all age-cohorts, with participants recalling a maximum median number of 6– 8 songs in all of the age-cohorts. There was no evidence of a difference in the peak age of recollection between those who recognized seven or more songs in at least 1 year and those who recognized fewer than seven songs in all years. CONCLUSION: The peak of recollection of popular music occurs in the teenage years, regardless of era of birth. Music from this “reminiscence bump” provides a rich source of retained music that should be tapped when creating playlists of meaningful music for people living with dementia

Validation study of the Chinese Early Development Instrument (CEDI)

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Impact of nutritional supplements on cognitive development of children in developing countries: A meta-analysis

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Botanical Description of Pigeonpea [Cajanus Cajan (L.) Millsp.]

Pigeonpea [Cajanus cajan (L.) Millspaugh] is an important legume crop of the papilionaceae family. It is an often cross-pollinated crop, and breeding principles of both self and cross-pollinated crops are highly effective in its genetic enhancement. Pigeonpea is a hard woody shrub, extensively adaptable to a range of soil types, temperature, and rainfall. It has a deep taproot system extending up to two meters and can grow to a height of four meters. Pigeonpea roots form a symbiotic association with Brady rhizobium spp. and perform biological nitrogen fixation. The branching pattern of stem may vary from bush type to compact upright type and is of determinate, semi-determinate, and non-determinate type based on the flowering pattern. The primary leaves are simple, opposite, and caduceus, while the latter ones are pinnately trifoliate with lanceolate to elliptical leaflets. Pigeonpea flowers are zygomorphic, borne on terminal or auxiliary racemes and are normally yellow in color with some variations. It has ten stamens in diadelphous condition with light or dark yellow anthers. The ovary is superior with a long style attached to a thickened, incurved, and swollen stigma. Pigeonpea is an often cross-pollinated crop with an average of 20% cross-pollination. The fruit of pigeonpea is called pod, which is of various colors, with and without deep constrictions. Seeds (with 20–22% proteins and amino acids) can be round or lens shaped, in shades of white and brown color with yellow color cotyledon. Pigeonpea is a widely consumed multi-utility pulse crop, thus the knowledge about the crop botany is vital for modifying it according to future challenges and goals

Bianchi Type-II String Cosmological Models in Normal Gauge for Lyra's Manifold with Constant Deceleration Parameter

The present study deals with a spatially homogeneous and anisotropic Bianchi-II cosmological models representing massive strings in normal gauge for Lyra's manifold by applying the variation law for generalized Hubble's parameter that yields a constant value of deceleration parameter. The variation law for Hubble's parameter generates two types of solutions for the average scale factor, one is of power-law type and other is of the exponential form. Using these two forms, Einstein's modified field equations are solved separately that correspond to expanding singular and non-singular models of the universe respectively. The energy-momentum tensor for such string as formulated by Letelier (1983) is used to construct massive string cosmological models for which we assume that the expansion ($\theta$) in the model is proportional to the component $\sigma^{1}_{~1}$ of the shear tensor $\sigma^{j}_{i}$. This condition leads to $A = (BC)^{m}$, where A, B and C are the metric coefficients and m is proportionality constant. Our models are in accelerating phase which is consistent to the recent observations. It has been found that the displacement vector $\beta$ behaves like cosmological term $\Lambda$ in the normal gauge treatment and the solutions are consistent with recent observations of SNe Ia. It has been found that massive strings dominate in the decelerating universe whereas strings dominate in the accelerating universe. Some physical and geometric behaviour of these models are also discussed.Comment: 24 pages, 10 figure

The Surgical Infection Society revised guidelines on the management of intra-abdominal infection

Background: Previous evidence-based guidelines on the management of intra-abdominal infection (IAI) were published by the Surgical Infection Society (SIS) in 1992, 2002, and 2010. At the time the most recent guideline was released, the plan was to update the guideline every five years to ensure the timeliness and appropriateness of the recommendations. Methods: Based on the previous guidelines, the task force outlined a number of topics related to the treatment of patients with IAI and then developed key questions on these various topics. All questions were approached using general and specific literature searches, focusing on articles and other information published since 2008. These publications and additional materials published before 2008 were reviewed by the task force as a whole or by individual subgroups as to relevance to individual questions. Recommendations were developed by a process of iterative consensus, with all task force members voting to accept or reject each recommendation. Grading was based on the GRADE (Grades of Recommendation Assessment, Development, and Evaluation) system; the quality of the evidence was graded as high, moderate, or weak, and the strength of the recommendation was graded as strong or weak. Review of the document was performed by members of the SIS who were not on the task force. After responses were made to all critiques, the document was approved as an official guideline of the SIS by the Executive Council. Results: This guideline summarizes the current recommendations developed by the task force on the treatment of patients who have IAI. Evidence-based recommendations have been made regarding risk assessment in individual patients; source control; the timing, selection, and duration of antimicrobial therapy; and suggested approaches to patients who fail initial therapy. Additional recommendations related to the treatment of pediatric patients with IAI have been included. Summary: The current recommendations of the SIS regarding the treatment of patients with IAI are provided in this guideline