Adaptive classification of interfering signals in a shared radio frequency environment

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1992.Includes bibliographical references (leaves 107-114).by Ganesh Nachiappa Ramaswamy.M.S

Hypolipidemic activity of Sesbania grandiflora in triton wr-1339 induced hyperlipidemic rats

Hyperlipidemia is the greatest risk factor of coronary heart disease. Currently available hypolipidemic drugs have been associated with number of side effects. Herbal treatment for hyperlipidemia has no side effects and is relatively cheap and locally available. A literature claims that flavonoids can able to reduce the hyperlipidemia. Based on high flavonoid content in herbal, Sesbania grandiflora (SG) was selected and the present study focus on the anti-hyperlipidemic activity of aqueous extract of leaves of SG against triton induced hyperlipidemia in rats. SG administered a dose of 200μg/kg (p.o) to the triton induced hyperlipidemic rats. SG shows a significant decrease in the levels of serum cholesterol, phospholipid, triglyceride, LDL, VLDL and significant increase in the level of serum HDL at the dose of 200μg/kg (p.o) against Triton induced hyperlipidemic in rats. Aqueous extract of leaves of SG was investigated hypolipidemic activity on Triton induced hyperlipidemic profile. Aqueous extract fraction decreased serum level of total cholesterol by 69.72. On the other hand, aqueous extract of SG increased the serum HDL cholesterol level by 24.11. The reduction of LDL cholesterol level by aqueous extract was 30.31.Keywords: Sesbania grandiflora- Hyperlipidemia- LDL- VLDL- HD

Optimal Control of Class of Non-Linear Plants using Artificial Immune Systems: Application of the Clonal Selection Algorithm

The function of natural immune system is to protect the living organisms against invaders/pathogens. Artificial Immune System (AIS) is a computational intelligence paradigm inspired by the natural immune system. Diverse engineering problems have been solved in the recent past using AIS. Clonal selection is one of the few algorithms that belong to the family of AIS techniques. Clonal selection algorithm is the computational implementation of the clonal selection principle. The process of affinity maturation of the immune system is explicitly incorporated in this algorithm. This paper presents the application of AIS for the optimal control of a class of non-linear plants which are affine in control. The clonal selection algorithm is adapted for optimal control. A new mutation operator that operates on real values and one that aids in fast convergence is developed in this paper. AIS is used to obtain constant coefficient Kalman gain matrices. The validation and evaluation of the results thus obtained are carried out by comparing with standard and the widely used State Dependent Algebraic Riccati Equation (SDARE) method for the non-linear plants. In case of non-linear systems with hard state constraints, the SDARE formulation requires the use of mathematically involved expressions to incorporate these state constraints. However, the modified clonal selection algorithm developed in this paper has been used with hardly any changes to incorporate the hard state constraints and obtain the Kalman gain matrix

Mural Cells: Potential Therapeutic Targets to Bridge Cardiovascular Disease and Neurodegeneration

Mural cells collectively refer to the smooth muscle cells and pericytes of the vasculature. This heterogenous population of cells play a crucial role in the regulation of blood pressure, distribution, and the structural integrity of the vascular wall. As such, dysfunction of mural cells can lead to the pathogenesis and progression of a number of diseases pertaining to the vascular system. Cardiovascular diseases, particularly atherosclerosis, are perhaps the most well-described mural cell-centric case. For instance, atherosclerotic plaques are most often described as being composed of a proliferative smooth muscle cap accompanied by a necrotic core. More recently, the role of dysfunctional mural cells in neurodegenerative diseases, such as Alzheimer's and Parkinson's disease, is being recognized. In this review, we begin with an exploration of the mechanisms underlying atherosclerosis and neurodegenerative diseases, such as mural cell plasticity. Next, we highlight a selection of signaling pathways (PDGF, Notch and inflammatory signaling) that are conserved across both diseases. We propose that conserved mural cell signaling mechanisms can be exploited for the identification or development of dual-pronged therapeutics that impart both cardio- and neuroprotective qualities

Evaluation of Tropaeolin 000-1 as a Colorimetric Reagent for Assay of Duloxetine and Escitalopram in Solid Dosage Form

Purpose: To explore the application of tropaeolin 000-1 reagent for the rapid, precise and accurate determination of duloxetine hydrochloride (DX) and escitalopram maleate (ECT).Methods: Determination of DX and ECT was based on the formation of complexes between the dye, DX and ECT in 0.1 M HCl. The resulting chromogen showed a maximum wavelength of absorption at 502 and 503 nm for DX and ECT, respectively. This method was validated for analytical parameters such as linearity, precision, accuracy, robustness, and ruggedness according to the guidelines of International Conference on Harmonization (ICH) and United States Pharmacopoeia (USP).Results: The absorbance of the each chromogen formed with DX and ECT was linear over the range of 4 - 30 and 2.5 - 27.5 μg mL-1 for DX and ECT, with 0.9968 and 0.9979 as the regression coefficient, respectively. The limits of detection (LOD) were 0.0045 and 0.0015 μg mL-1 for DX and ECT, respectively, with the limits of quantification (LOQ) at 0.5 and 0.08 μg mL-1. The recovery (accuracy) of the methods resulted in low RSD values of 0.856 – 0.983 % for DX and 0.765 – 0.987 % for ECT.Conclusion: The developed method shows a high degree of accuracy and precision for the determination of DX and ECT. Thus, tropaeolin 000-1 reagent is versatile for determining the contents of DX and ECT in their formulations.Keywords: Duloxetine, Escitalopram, Tropaeolin 000-1, Extractive spectrophotometry, Validatio

Role of matrix metalloproteinases in multi-system inflammatory syndrome and acute COVID-19 in children

INTRODUCTION: Multisystem Inflammatory Syndrome in children (MIS-C) is a serious inflammatory sequela of SARS-CoV2 infection. The pathogenesis of MIS-C is vague and matrix metalloproteinases (MMPs) may have an important role. Matrix metalloproteinases (MMPs) are known drivers of lung pathology in many diseases. METHODS: To elucidate the role of MMPs in pathogenesis of pediatric COVID-19, we examined their plasma levels in MIS-C and acute COVID-19 children and compared them to convalescent COVID-19 and children with other common tropical diseases (with overlapping clinical manifestations). RESULTS: Children with MIS-C had elevated levels of MMPs (P < 0.005 statistically significant) in comparison to acute COVID-19, other tropical diseases (Dengue fever, typhoid fever, and scrub typhus fever) and convalescent COVID-19 children. PCA and ROC analysis (sensitivity 84–100% and specificity 80–100%) showed that MMP-8, 12, 13 could help distinguish MIS-C from acute COVID-19 and other tropical diseases with high sensitivity and specificity. Among MIS-C children, elevated levels of MMPs were seen in children requiring intensive care unit admission as compared to children not needing intensive care. Similar findings were noted when children with severe/moderate COVID-19 were compared to children with mild COVID-19. Finally, MMP levels exhibited significant correlation with laboratory parameters, including lymphocyte counts, CRP, D-dimer, Ferritin and Sodium levels. DISCUSSION: Our findings suggest that MMPs play a pivotal role in the pathogenesis of MIS-C and COVID-19 in children and may help distinguish MIS-C from other conditions with overlapping clinical presentation

Unique cellular immune signatures of multisystem inflammatory syndrome in children

The clinical presentation of MIS-C overlaps with other infectious/non-infectious diseases such as acute COVID-19, Kawasaki disease, acute dengue, enteric fever, and systemic lupus erythematosus. We examined the ex-vivo cellular parameters with the aim of distinguishing MIS-C from other syndromes with overlapping clinical presentations. MIS-C children differed from children with non-MIS-C conditions by having increased numbers of naïve CD8(+) T cells, naïve, immature and atypical memory B cells and diminished numbers of transitional memory, stem cell memory, central and effector memory CD4(+) and CD8(+) T cells, classical, activated memory B and plasma cells and monocyte (intermediate and non-classical) and dendritic cell (plasmacytoid and myeloid) subsets. All of the above alterations were significantly reversed at 6–9 months post-recovery in MIS-C. Thus, MIS-C is characterized by a distinct cellular signature that distinguishes it from other syndromes with overlapping clinical presentations. Trial Registration: ClinicalTrials.gov clinicaltrial.gov. No: NCT04844242

Modal structures and model reduction, with application to power system equivalencing

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (p. 131-145).by Ganesh Nachiappa Ramaswamy.Ph.D

IMPROVED SPEAKER MODEL MIGRATION VIA STOCHASTIC SYNTHESIS

Model migration in speaker recognition is a task of converting parametrically-obsolete models to new structures and configurations without the requirement to store the original speech waveforms or feature vector sequences along with the models. The need for model migration arises in large-scale deployments of speaker recognition technology in which the potential for legacy problems increases as the evolving technology may require configuration changes thus invalidating already existing user voice accounts. A migration may represent the only alternative to otherwise costly user re-enrollment or waveform storage and, as a new research problem, presents the challenge of developing algorithms to minimize the loss in accuracy in the migrated accounts. This paper reports on further enhancements of a statistical migration technique based on Gaussian Mixture Models, introduced previously. The present approach is based on a stochastic synthesis of feature sequences from obsolete models that are subsequently used to create the new models. Here, in addition to Gaussian means and priors, as utilized in the previous contribution, also the covariances are included resulting in significant performance gains in the migrated models, compared to the mean-only method. Overall, measured on the NIST 2003 cellular task, the described algorithm achieves a model migration incurring a loss in performance of 8-20 % relative to a full re-enrollment from waveforms, dependent on the type of mismatch between the obsolete and the new configuration. The inclusion of the covariance information is shown to reduce the loss of performance by a factor of 3-4 as compared to the baseline mean-only migration technique. 1

The Awe and Mystery of T-norm

A popular score normalization technique termed T-norm is the central focus of this paper. Based on widely confirmed experimental observation regarding T-norm tilting the DET curves of speaker detection systems, we set out to identify the components taking role in this phenomenon. We claim that under certain local assumptions the T-norm performs a gaussianization of the individual true and impostor score populations and further derive conditions for clockwise and counter-clockwise DET rotations caused by this transform. 1