Development and qualification of a room used to investigate component and system performance characteristics of heating, ventilating, and air-conditioning systems

An environmentally controlled room that can be used to investigate component and system performance characteristics of heating, ventilating, and air-conditioning (HVAC) systems was developed and qualified. The room has two air supply distribution systems, one is a conventional air distribution system where conditioned air is delivered from the ceiling diffusers, and the second is an underfloor air distribution system where conditioned air is delivered through diffusers located in the floor. The development required extensive construction work for the two air distribution systems and the surface temperature control, data acquisition, and recording systems. The room surfaces were divided into thirteen separate zones that can be independently maintained at specified temperatures. This was accomplished through the use of a Daikin central condenser unit and thirteen separate Daikin fan-coil units that supplied conditioned air to each of the thirteen zones. A computer-controlled instrumentation measurement system was implemented per the ASHRAE standards for testing. The under floor air distribution system was tested and shown to have a leakage rate that was within acceptable limits. Other tests, which included the measurement of airflow velocities around baseboard heaters and from ceiling and floor air distribution diffusers and the ability to control room surface temperatures over an extended period of time, were conducted to qualify the environmentally controlled room

Compressive speech enhancement using semi-soft thresholding and improved threshold estimation

Compressive speech enhancement is based on the compressive sensing (CS) sampling theory and utilizes the sparsity of the signal for its enhancement. To improve the performance of the discrete wavelet transform (DWT) basis-function based compressive speech enhancement algorithm, this study presents a semi-soft thresholding approach suggesting improved threshold estimation and threshold rescaling parameters. The semi-soft thresholding approach utilizes two thresholds, one threshold value is an improved universal threshold and the other is calculated based on the initial-silence-region of the signal. This study suggests that thresholding should be applied to both detail coefficients and approximation coefficients to remove noise effectively. The performances of the hard, soft, garrote and semi-soft thresholding approaches are compared based on objective quality and speech intelligibility measures. The normalized covariance measure is introduced as an effective intelligibility measure as it has a strong correlation with the intelligibility of the speech signal. A visual inspection of the output signal is used to verify the results. Experiments were conducted on the noisy speech corpus (NOIZEUS) speech database. The experimental results indicate that the proposed method of semi-soft thresholding using improved threshold estimation provides better enhancement compared to the other thresholding approaches

Improving the intelligibility of dysarthric speech using a time domain pitch synchronous-based approach

Dysarthria is a motor speech impairment that reduces the intelligibility of speech. Observations indicate that for different types of dysarthria, the fundamental frequency, intensity, and speech rate of speech are distinct from those of unimpaired speakers. Therefore, the proposed enhancement technique modifies these parameters so that they fall in the range for unimpaired speakers. The fundamental frequency and speech rate of dysarthric speech are modified using the time domain pitch synchronous overlap and add (TD-PSOLA) algorithm. Then its intensity is modified using the fast Fourier transform (FFT) and inverse fast Fourier transform (IFFT)-based approach. This technique is applied to impaired speech samples of ten dysarthric speakers. After enhancement, the intelligibility of impaired and enhanced dysarthric speech is evaluated. The change in the intelligibility of impaired and enhanced dysarthric speech is evaluated using the rating scale and word count methods. The improvement in intelligibility is significant for speakers whose original intelligibility was poor. In contrast, the improvement in intelligibility was minimal for speakers whose intelligibility was already high. According to the rating scale method, for diverse speakers, the change in intelligibility ranges from 9% to 53%. Whereas, according to the word count method, this change in intelligibility ranges from 0% to 53%

Binary classification of rainfall time-series using machine learning algorithms

Summer monsoon rainfall contributes more than 75% of the annual rainfall in India. For the state of Maharashtra, India, this is more than 80% for almost all regions of the state. The high variability of rainfall during this period necessitates the classification of rainy and non-rainy days. While there are various approaches to rainfall classification, this paper proposes rainfall classification based on weather variables. This paper explores the use of support vector machine (SVM) and artificial neural network (ANN) algorithms for the binary classification of summer monsoon rainfall using common weather variables such as relative humidity, temperature, pressure. The daily data, for the summer monsoon months, for nineteen years, was collected for the Shivajinagar station of Pune in the state of Maharashtra, India. Classification accuracy of 82.1 and 82.8%, respectively, was achieved with SVM and ANN algorithms, for an imbalanced dataset. While performance parameters such as misclassification rate, F1 score indicate that better results were achieved with ANN, model parameter selection for SVM was less involved than ANN. Domain adaptation technique was used for rainfall classification at the other two stations of Maharashtra with the network trained for the Shivajinagar station. Satisfactory results for these two stations were obtained only after changing the training method for SVM and ANN

Role of non-immune mechanisms of muscle damage in idiopathic inflammatory myopathies

Idiopathic inflammatory myopathies (IIMs) comprise a group of autoimmune diseases that are characterized by symmetrical skeletal muscle weakness and muscle inflammation with no known cause. Like other autoimmune diseases, IIMs are treated with either glucocorticoids or immunosuppressive drugs. However, many patients with an IIM are frequently resistant to immunosuppressive treatments, and there is compelling evidence to indicate that not only adaptive immune but also several non-immune mechanisms play a role in the pathogenesis of these disorders. Here, we focus on some of the evidence related to pathologic mechanisms, such as the innate immune response, endoplasmic reticulum stress, non-immune consequences of MHC class I overexpression, metabolic disturbances, and hypoxia. These mechanisms may explain how IIM-related pathologic processes can continue even in the face of immunosuppressive therapies. These data indicate that therapeutic strategies in IIMs should be directed at both immune and non-immune mechanisms of muscle damage

A novel frequency reconfigurable antenna for smart grid applications in TV white space band

This paper presents the design and analysis of a frequency reconfigurable, aperture coupled rectangular patch antenna for use in smart grid applications in TV white space bands. The proposed antenna model has been realized on multi-substrate layers of Polylactic acid (PLA) material (εr=2.65, tanδ=0.003) with a ground plane sandwiched in between them. An aperture has been made in the ground plane for coupling energy to the patch. The overall system dimensions are 270×270 mm. The feature of frequency reconfigurability has been achieved by incorporating a switch and varying the reactance of the feed line on the bottom substrate. A rectangular slot on the long feed line improves impedance matching. The ON and OFF states of the switch provide two operating frequency bands namely 630.13 to 636.7 MHz and 619.16 to 625.3 MHz respectively. The proposed aperture coupled reconfigurable system operates with a maximum gain of 6.4 dB and average efficiency of 78.5% in both bands. The measured results are satisfactory and the proposed antenna will be suitable for operation in the smart grid environment

Prospective, randomized, open label comparative study of efficacy of atorvastatin versus atorvastatin with vitamin D3 in patients with dyslipidemia attending tertiary care hospital

Background: Cardiovascular diseases are one of the most important group of diseases causing premature mortality and morbidity. Dyslipidemia is an independent risk factor for cardiovascular diseases and is a disorder of lipoprotein metabolism. Various research studies support role of vitamin D against dyslipidemia. Vitamin D concentration positively correlates with HDL cholesterol and negatively with serum LDL and triglyceride levels. Vitamin D supplementation to Atorvastatin appeared to have increased cholesterol lowering activity more than either substance did alone.Methods: The study was conducted in an outpatient department of general medicine for a duration of 12 weeks in a tertiary care hospital. Total of 100 patients with dyslipidemia were selected based on measurement of lipid profile. Out of 100 patients, 50 patients under group A were treated with atorvastatin 10mg and balance 50 patients under group B treated with atorvastatin and Vitamin D3 1000 IU/day orally. Patients were followed up monthly for 3 months and lipid profile was assessed at baseline and at the end of study. The baseline characteristics were similar in both study groups.Results: On comparing groups at the end of 12 weeks mean LDL, triglycerides and VLDL were significantly reduced in group B than group A with p<0.001. The mean HDL level too increased in group B than group A with p<0.001.Conclusions: Fasting plasma lipid profile improvement was higher in the atorvastatin with vitamin D3 group compared to atorvastatin group

Idiopathic inflammatory myopathies: Pathogenic mechanisms of muscle weakness

Idiopathic inflammatory myopathies (IIMs) are a heterogenous group of complex muscle diseases of unknown etiology. These diseases are characterized by progressive muscle weakness and damage, together with involvement of other organ systems. It is generally believed that the autoimmune response (autoreactive lymphocytes and autoantibodies) to skeletal muscle-derived antigens is responsible for the muscle fiber damage and muscle weakness in this group of disorders. Therefore, most of the current therapeutic strategies are directed at either suppressing or modifying immune cell activity. Recent studies have indicated that the underlying mechanisms that mediate muscle damage and dysfunction are multiple and complex. Emerging evidence indicates that not only autoimmune responses but also innate immune and non-immune metabolic pathways contribute to disease pathogenesis. However, the relative contributions of each of these mechanisms to disease pathogenesis are currently unknown. Here we discuss some of these complex pathways, their inter-relationships and their relation to muscle damage in myositis. Understanding the relative contributions of each of these pathways to disease pathogenesis would help us to identify suitable drug targets to alleviate muscle damage and also improve muscle weakness and quality of life for patients suffering from these debilitating muscle diseases