22 research outputs found
Coadjoint orbits and K\"ahler structure: examples from coherent states
No full textDo co-adjoint orbits of Lie groups support a K\"{a}hler structure? We study
this question from a point of view derived from coherent states. We examine
three examples of Lie groups: the Weyl-Heisenberg group, and
. In cases, where the orbits admit a K\"{a}hler structure, we
show that coherent states give us a K\"{a}hler embedding of the orbit into
projective Hilbert space. In contrast, squeezed states, (which like coherent
states, also saturate the uncertainty bound) only give us a symplectic
embedding. We also study geometric quantisation of the co-adjoint orbits of the
group of real, special, upper triangular matrices
in two dimensions. We glean some general insights from these examples. Our
presentation is semi-expository and accessible to physicists.Comment: To appear in Reports in Mathematical Physic
Halo orbit design around Lagrangian points using gradient and non gradient based optimization techniques
No full textImage denoising using optimally weighted bilateral filters: A sure and fast approach
No full textThe bilateral filter is known to be quite effective in denoising images corrupted with small dosages of additive Gaussian noise. The denoising performance of the filter, however, is known to degrade quickly with the increase in noise level. Several adaptations of the filter have been proposed in the literature to address this shortcoming, but often at a substantial computational overhead. In this paper, we report a simple pre-processing step that can substantially improve the denoising performance of the bilateral filter, at almost no additional cost. The modified filter is designed to be robust at large noise levels, and often tends to perform poorly below a certain noise threshold. To get the best of the original and the modified filter, we propose to combine them in a weighted fashion, where the weights are chosen to minimize (a surrogate of) the oracle mean-squared-error (MSE). The optimally-weighted filter is thus guaranteed to perform better than either of the component filters in terms of the MSE, at all noise levels. We also provide a fast algorithm for the weighted filtering. Visual and quantitative denoising results on standard test images are reported which demonstrate that the improvement over the original filter is significant both visually and in terms of PSNR. Moreover, the denoising performance of the optimally-weighted bilateral filter is competitive with the computation-intensive non-local means filter
Biased signalling in platelet G-protein‐coupled receptors.
No full textPlatelets are small megakaryocyte-derived, anucleate, disk-like structures that play an outsized role in human health and disease. Both a decrease in the number of platelets and a variety of platelet function disorders result in petechiae or bleeding that can be life threatening. Conversely, the inappropriate activation of platelets, within diseased blood vessels, remains the leading cause of death and morbidity by affecting heart attacks and stroke. The fine balance of the platelet state in healthy individuals is controlled by a number of receptor-mediated signaling pathways that allow the platelet to rapidly respond and maintain haemostasis. G-protein coupled receptors (GPCRs) are particularly important regulators of platelet function. Here we focus on the major platelet-expressed GPCRs and discuss the roles of downstream signaling pathways (e.g., different G-protein subtypes or β-arrestin) in regulating the different phases of the platelet activation. Further, we consider the potential for selectively targeting signaling pathways that may contribute to platelet responses in disease through development of biased agonists. Such selective targeting of GPCR-mediated signaling pathways by drugs, often referred to as biased signaling, holds promise in delivering therapeutic interventions that do not present significant side effects, especially in finely balanced physiological systems such as platelet activation in haemostasis.The presentation of the authors' names and (or) special characters in the title of the pdf file of the accepted manuscript may differ slightly from what is displayed on the item page. The information in the pdf file of the accepted manuscript reflects the original submission by the author
Limiting Autoimmune Neuroinflammation using Novel T Cell Suppressants & Investigating Overlapping Lysosomal Reductase Function in Macrophages and Osteoclasts
No full textAberrant activation of adaptive immune cells can culminate in autoimmune diseases such as multiple sclerosis (MS). Recently, potent anti-inflammatory properties for the cooling compound, icilin, and its receptor target, Transient Receptor Potential Melastatin-8 (TRPM8), were characterized in the context of inflammatory colitis—the first half of this dissertation describes an attempt to repurpose the anti-inflammatory qualities of icilin and TRPM8 for the treatment of lymphocyte-mediated neuroinflammation. We found icilin treatment strongly attenuated experimental autoimmune encephalomyelitis (EAE), a murine model of MS, via an unexpected TRPM8-independent mechanism. Icilin inhibited the proliferation, polarization and downstream effector function of CD4+ T cells, suggesting a promising drug for limiting neuroinflammation. Citing the advantageous pharmacodynamics of icilin, we additionally screened a library of icilin-related analogues for anti-proliferative character. We identified several lead compounds with improved anti-proliferative properties compared to icilin in vitro and preliminary efficacy in vivo limiting EAE severity. Collectively, this work characterizes a new class of T cell suppressants while emphasizing clear off-target effects for the cooling drug icilin beyond TRP channel activation. Antigen presenting cells such as macrophages process phagocytosed cargo within the highly degradative phagolysosome, facilitating antigenic stimulation of T cells and adaptive immunity. The redox microenvironment of the phagolysosomal lumen regulates several phagolysosomal biochemistries, including proteolysis and disulfide reduction. The lysosomal enzyme γ-interferon-inducible lysosomal thiol reductase (GILT) directly catalyzes disulfide reduction and enhances proteolysis by thiol-dependent cysteine cathepsins within the phagolysosome—while clearly implicated in antigen processing, secondary roles for GILT remain largely undefined. The second half of this dissertation establishes a role for GILT in osteoclasts, bone resorbing cells derived from macrophages. GILT expression was highly upregulated in osteoclasts in response to osteoclastogenic and inflammatory cytokines, and GILT-deficient mice were discovered to be osteopetrotic. In vitro, GILT-deficient osteoclasts demonstrated a reduced capacity to resorb bone. GILT not only directly reduced disulfides within bone matrix structural proteins, but also enhanced the activity of cathepsin K, the prototypical osteoclast collagenase. Thus, this work reveals a novel, non-immunological role for GILT in osteoclast function and bone turnover
Time Series Prediction for Traffic Flow Forecasting Using CNN
No full textTraffic problems are very common nowadays throughout the world. In India also heavy traffic also occurred in many populated cities. For this reason, the public loses their time and life, and this pollution impacts human health. So, traffic research is necessary for this situation. We concentrate on the traffic network to find a better solution or model to predict future traffic. Our proposed model uses a time series for traffic forecasting. It deals with time series analysis for traffic congestion, traffic control, and traffic prediction. This paper focuses on appropriate datasets with different vehicles in various time series. A novel time series forecasting model was used for this research, and it also predicted a 99% accuracy rate. A comparative study is also presented in this research
Perfusion index as a predictor of hypotension following induction of general anaesthesia with propofol-An observational study
No full textBackground: Perfusion index (PI) is a somewhat novel parameter evaluating the pulsatility of blood in the extremities, calculated using the infrared spectrum as a component of plethysmography waveform processing.
Aims and Objectives: To obtain a cutoff value of pre-anesthesia PI, which may be helpful for the prediction of hypotension following anesthetic induction with propofol.
Materials and Methods: This descriptive observational research was carried out at the Sree Gokulam medical college and research foundation, Venjaramoodu, Trivandrum, Kerala, from June 2020 to June 2021. A total of 174 patients of age group 17–60 years, with ASA 1 or 2 scheduled for surgery under general anesthesia, were included. The parameters (systolic blood pressure [SBP], diastolic blood pressure, mean arterial pressure, PI, and SPO2) were recorded until 5 min of induction. Intravenous (IV) fentanyl 2 μg/kg was administered, propofol injected was given slowly at a rate of 10 mg per every 5 s, titrated to loss of verbal communication responseuronium 0.1 mg/kg IV was administered. The calculation for hypertension was done 5 min after anesthesia. The predictive validity of PI was calculated, keeping SBP as the standard gold test. For statistical analysis coGuide software.
Results: The cutoff value for PI at 5 min was low (≤2.45) for 27 (90%) participants and high (>2.45) for 3 (10%) participants. With a sensitivity of 90% in predicting hypotension and specificity of 87.50%, false-positive rate was 12.50%, false-negative rate was 10, positive predictive value was 60% (95 CI 44.43–74.30%), the negative predictive value (NPV) was 97.67%, and the total diagnostic accuracy was 87.93%.
Conclusion: With the current study’s findings, we conclude that PI cutoff value 2.45 can be used to predict hypotension following anesthetic induction with propofol. It has a high NPV with fair diagnostic accuracy
High accuracy decoding of motor imagery directions from EEG-based brain computer interface using filter bank spatially regularised common spatial pattern method
No full textOne of the important requirements of a practical Brain Computer Interface (BCI) system is the ability to establish multiple control commands corresponding to different kinematics of motor imagery. Most of the previous BCI-based motor imagery studies in literature focus on classifying left vs. right hand motor imagery from electroencephalogram (EEG) signals. Very few studies have reported decoding imagined hand movement kinematics from EEG-based BCI. The present study decodes the left vs. right directional information from the Motor Imagery (MI) of dominant hand movement using EEG-based BCI. The proposed method employs common spatial pattern (CSP) and its variants as features to decode imagined (motor imagery) bidirectional hand movements. The direction discriminability of these features are enhanced using the regularisation technique. Spatial regularisation based on electrode positions is also incorporated for comparison. The regularisation methods are applied on overlapped frequency bands and the results are compared. The classifications of extracted features are done using 5-fold cross-validation and Linear Discriminant Analysis (LDA). The study on 15 healthy subjects shows that filter bank-based spatially regularized CSP method (FBSRCSP) offers the highest average classification accuracy of 90% for decoding bidirectional motor imagery of hand movement. This is a substantial improvement in classification accuracy by 26.3% compared to the best method reported in literature on the same dataset.</p
Comorbidities Associated with Mortality in COVID-19 Patients: A Retrospective Study at a Tertiary Health Care Hospital
No full textIntroduction: Due to unprecedented outbreak of COVID-19 worldwide since December 2019, the knowledge about which health conditions may impact the likelihood of a person getting infected and dying with COVID-19 is limited. It is observed that the mortality rate varies from one region to another region across globally. It remains unclear how the pre-existing health conditions affect the risk of infection and severity of COVID-19. The present study was undertaken to describe the presence of associated comorbidities in the adult patients who died of COVID-19 at a tertiary care hospital in this part of India.Methods: The present study is a hospital based retrospective study, done at Yenepoya Medical College and Hospital which is a tertiary health care hospital. Data was collected from the medical records of patients above 16 years of age who died due to COVID-19 illness and details of the age, gender distribution, associated co morbidities, and laboratory investigation reports of the patients at the time of admission were obtained. Data was analyzed and compared as mean and percentage of distribution among different groups.Results: Out of 110 deaths due to COVID-19, 76 (69.09%) were males and 34 (30.9%) were females. The average age of the patients died due to COVID-19 is 57.4413.01years. The overall COVID-19 mortality above the age of 60 years is 49.09% (54). The mortality was lowest in the age group of 16-30 years (4, 3.63%). The most prevalent comorbidity associated with COVID-19 mortality observed in the study is diabetes mellitus (73, 66.3%) followed by systemic hypertension (57, 51.81%). The other comorbidities observed in the present study are: cardiovascular diseases (21, 19.09%), chronic kidney diseases (10, 9.09%), malignancies (11, 10%), chronic respiratory diseases (9, 8.1%), cerebrovascular diseases (8, 7.2%) and chronic liver diseases (7, 6.3%). Overall, 8 (7.27%) patients among 110 patients had no prior comorbidities.Conclusions: In this study we found a significant effect of age, gender and other comorbidities on risk of mortality among patients with COVID-19. In our study mortality in COVID-19 patients with age ≥60 years were at a significantly high compared to those aged <60 years. Male patients with COVID-19 were associated with significantly increased risk of mortality compared to females. Mortality was significantly higher in those patients with diabetes, hypertension, cardiovascular disease, cerebrovascular disease, respiratory disease, chronic kidney disease, chronic liver disease and malignancy. Adequate protection and interventions in COVID-19 patients, particularly in male patients with age ≥60 years may significantly reduce the risk of mortality
