Acoustic Feedback Noise Cancellation in Hearing Aids Using Adaptive Filter

To enhance speech intelligibility for people with hearing loss, hearing aids will amplify speech using gains derived from evidence-based prescriptive methods, in addition to other advanced signal processing mechanisms. While the evidence supports the use of hearing aid signal processing for speech intelligibility, these signal processing adjustments can also be detrimental to hearing aid sound quality, with poor hearing aid sound quality cited as a barrier to device adoption. In general, an uncontrolled environment may contain degradation components like background noise, speech from other speakers etc. along with required speech components. In this paper, we implement adaptive filtering design for acoustic feedback noise cancellation in hearing aids. The adaptive filter architecture has been designed using normalized least mean square algorithm. By using adaptive filters both filter input coefficients are changeable during run-time and reduce noise in hearing aids. The proposed design is implemented in matlab and the simulations shows that the proposed architecture produces good quality of speech, accuracy, maintain stable steady state. The proposed design is validated with parameters like Noise Distortion, Perceptual Evaluation of Speech Quality, Signal to Noise Ratio, and Speech Distortion. The feedback canceller is implemented in MATLAB 9.4 simulink version release name of R2018a is used for validation with Echo Return Loss Enhancement (ERLE). The ERLE of the NMLS is reduced when the filter order is increases. Around 10% of the power spectrum density (PSD) is less when compared with existing designs

Acoustic Feedback Noise Cancellation in Hearing Aids Using Adaptive Filter

To enhance speech intelligibility for people with hearing loss, hearing aids will amplify speech using gains derived from evidence-based prescriptive methods, in addition to other advanced signal processing mechanisms. While the evidence supports the use of hearing aid signal processing for speech intelligibility, these signal processing adjustments can also be detrimental to hearing aid sound quality, with poor hearing aid sound quality cited as a barrier to device adoption. In general, an uncontrolled environment may contain degradation components like background noise, speech from other speakers etc. along with required speech components. In this paper, we implement adaptive filtering design for acoustic feedback noise cancellation in hearing aids. The adaptive filter architecture has been designed using normalized least mean square algorithm. By using adaptive filters both filter input coefficients are changeable during run-time and reduce noise in hearing aids. The proposed design is implemented in matlab and the simulations shows that the proposed architecture produces good quality of speech, accuracy, maintain stable steady state. The proposed design is validated with parameters like Noise Distortion, Perceptual Evaluation of Speech Quality, Signal to Noise Ratio, and Speech Distortion. The feedback canceller is implemented in MATLAB 9.4 simulink version release name of R2018a is used for validation with Echo Return Loss Enhancement (ERLE). The ERLE of the NMLS is reduced when the filter order is increases. Around 10% of the power spectrum density (PSD) is less when compared with existing designs

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject

Formulation and Optimization of Zolmitriptan Orodispersible Tablets

Zolmitriptan is a selective 5-hydroxytryptamine receptor agonist reported for the acute migraine treatment, having poor water solubility leads to poor bioavailability. In the present study, attempt to improve the bioavailability of zolmitriptan with the help of PVP K-30 using the microwave irradiation method.  The zolmitriptan and PVP K- 30 in 1:1 ratio was subjected to microwave irradiation for different times such as 60,80,100,120 seconds at 650 watts. Characterization of solid dispersion was done by drug content, XRD, FTIR, DSC. FTIR analysis demonstrated there are no compatibility issues. XRD studies prove that the solid dispersion was in amorphous form. DSC studies prove that solid dispersion was amorphous based on the intensity of peaks. The prepared dispersion was made into orodispersible tablets by direct compression. The optimization of these formulations was carried out by using 32 factorial designs on Design Expert 10.0 software. In order to examine the effect of independent variables Crospovidone (X1), croscarmellose sodium (X2), and combined effect of independent variables 32 factorial design was selected. In this design, two responses such as disintegration time and % drug release were evaluated, and experimental trials are performed for all 9 formulations. For all formulations, the precompression and post-compression parameters were studied. Based upon the model optimized formulation (C1 and C2) was obtained having the disintegration time (34.4±0.84 and 39.8±0.91) and %drug release (98.7±0.42 and 93.2±0.46) respectively. Keywords: Zolmitriptan, Solid dispersion, Microwave irradiation, Crospovidone, Croscarmellose sodium

Anaesthesia for awake craniotomy: A retrospective study of 54 cases

Background and Aims: The anaesthetic challenge of awake craniotomy is to maintain adequate sedation, analgesia, respiratory and haemodynamic stability in an awake patient who should be able to co-operate during intraoperative neurological assessment. The current literature, sharing the experience on awake craniotomy, in Indian context, is minimal. Hence, we carried out a retrospective study with the aim to review and analyse the anaesthetic management and perioperative complications in patients undergoing awake craniotomy, at our centre. Methods: Medical records of 54 patients who underwent awake craniotomy for intracranial lesions over a period of 10 years were reviewed, retrospectively. Data regarding anaesthetic management, intraoperative complications and post-operative course were recorded. Results: Propofol (81.5%) and dexmedetomidine (18.5%) were the main agents used for providing conscious sedation to facilitate awake craniotomy. Hypertension (16.7%) was the most commonly encountered complication during intraoperative period, followed by seizures (9.3%), desaturation (7.4%), tight brain (7.4%), and shivering (5.6%). The procedure had to be converted to general anaesthesia in one of patients owing to refractory brain bulge. The incidence of respiratory and haemodynamic complications were comparable in the both groups (P > 0.05). There was less incidence of intraoperative seizures in patients who received propofol (P = 0.03). In post-operative period, 20% of patients developed new motor deficit. Mean intensive care unit stay was 2.8 ± 1.9 day (1-14 days) and mean hospital stay was 7.0 ± 5.0 day (3-30 days). Conclusions: ′Conscious sedation′ was the technique of choice for awake craniotomy, at our institute. Fentanyl, propofol, and dexmedetomidine were the main agents used for this purpose. Patients receiving propofol had less incidence of intraoperative seizure. Appropriate selection of patients, understanding the procedure of surgery, and judicious use of sedatives or anaesthetic agents are key to the success for awake craniotomy as a procedure

Mapping the human genetic architecture of COVID-19

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3–7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease

Mapping the human genetic architecture of COVID-19

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3,4,5,6,7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease