Design and Modeling a Tunable Non-Hermitian Acoustic Filter

In this thesis, we explore an application of a non-Hermitian acoustic system with tunable loss in filtering specific frequencies from an upcoming signal at will. Using the commercial computational software, we design our proposed tunable filter made of a phononic super-lattice. The super-lattice consists of two sublattices connected in series. The first sublattice is Hermitian, whereas the other can be Hermitian or Non-Hermitian depending on the amount of loss induced in it. By introducing the loss in the system, we observe the generation of absorbed resonances that can be seen in the reflection spectrum. The range of the filtered frequencies can be controlled by adjusting the degree of non-Hermiticity and designing the first sublattice\u27s resonances. The resonances in the first sub-lattice can be adjusted by increasing or decreasing the number of unit cells in the sub-lattice. Our tunable acoustic filter can be extended to higher frequency ranges, such as ultrasound and other areas, such as photonics. In addition, we explore the geometry-induced non-Hermitian mode couplings and study the different modes in a system of acoustic ring resonators with induced loss and study the field localization within the system

Diastolic And Systolic Right Ventricular Dysfunction Precedes Left Ventricular Dysfunction In Patients Paced From Right Ventricular Apex

Background: Cardiac dysfunction after right ventricular (RV) apical pacing is well known but its extent, time frame of appearance and individual effect on left ventricular (LV), RV systolic and diastolic parameters has not evaluated in a systematic fashion. Methods: Patients with symptomatic bradycardia and ACC-AHA Class I indication for permanent pacemaker implantation (PPI) were implanted a single chamber (VVI) pacemaker. They were followed prospectively by echocardiographic examination which was done at baseline, 1 week, 1 month and 6 months after implantation. Parameters observed were chamber dimensions (M-line), chamber volumes, cardiac output (modified Simpson's method), systolic functions (ejection fraction, pre-ejection period, ejection time and ratio) and diastolic functions( isovolumic relaxation time & deceleration time) of left and right heart. Results: Forty eight consecutive patients (mean age 65.6±11.8 yrs, 66.7% males, mean EF 61.82±10.36%) implanted a VVI pacemaker were enrolled in this study. The first significant change to appear in cardiac function after VVI pacing was in diastolic properties of RV as shown by increase in RV isovolumic relaxation time (IVRT) from 65.89±15.93 to 76.58±17.00 ms,(p<0.001) at 1week and RV deceleration time (DT) from 133.84±38.13 to 153.09±31.41 ms, (p=0.02) at 1 month. Increase in RV internal dimension (RVID) from 1.26±0.41 to 1.44±0.44, (p<0.05) was also noticed at 1 week. The LV diastolic parameters were significantly altered after 1 month with increase in LV-IVRT from 92.36±21.47 to 117.24±27.21ms, (p<0.001) and increase in LV DT from 147.56±31.84 to 189.27±28.49ms,(p<0.01). This was followed by LV systolic abnormality which appeared at 6 months with an increase in LVPEP from 100.33±14.43 to 118.41±21.34ms, (p<0.001) and increase in LVPEP/LVET ratio from 0.34±0.46 to 0.44±0.10, (p<0.001)]. The reduction in LV EF was manifested at 6 months falling from 61.82±10.36% to52.52±12.11%, (p<0.05) without any significant change in the resting cardiac output. Conclusion: The present study shows that dysfunction of right ventricle is the first abnormality that occurs in VVI paced patients, which manifests by 1 week followed by LV dysfunction which starts appearing by 1 month and the diastolic dysfunctions precede the systolic dysfunction in both ventricles

Bank Borrowers and Loan Sales: New Evidence on the Uniqueness of Bank Loans

This paper examines the information content of the announcement of the sale of a borrower’s loan by its bank. A large body of research has documented the positive impact on a firm’s stock price around the announcement of formation and renewal of bank lending relationships. In light of these findings it would seem natural that when a bank chooses to sell off its loans, the stock returns of the borrower would be adversely affected. Our paper is the first study to test this hypothesis. We find that the stock returns of these borrowers are significantly negatively impacted on average for the period surrounding the announcement of a loan sale. The post-loan sale period is also marked by a large incidence of bankruptcy filings by the borrowers whose loans are sold. Overall, the evidence supports the hypothesis that the news of a bank loan sale has a negative certification impact, which is validated by the subsequent performance of the firm whose loan is sold. We conduct similar event study tests for those banks that engage in loan sales and find that the stock returns of the selling banks are not significantly impacted on average. Cross-sectional tests reveal that loan sales were made by banks that emphasized trading income and had relatively large Commercial and Industrial loan portfolios. For our sample period, a bank’s capital adequacy position did not appear to have a material effect on a bank’s decision to sell its loans

Outerbridge classification as a predictor for the need of patellar resurfacement in total knee arthroplasty: a prospective study

Background: Residual anterior knee pain after total knee arthroplasty is one of the common causes of early revision surgery in form of patellar resurfacing and even resurfacing the patella in these circumstances may not relieve the symptoms. So, the decision to perform patellar resurfacing during total knee arthroplasty to prevent anterior knee pain remains controversial. The purpose of this study is to determine if the outerbridge classification can predict the need for Patellar resurfacing as part of total knee arthroplasty.Methods: 100 patients with advanced osteoarthritis of knee fulfilling the inclusion and exclusion criteria were randomized into two groups of 50 patients each. In group A-patellar resurfacing done and in group B-patella was not resurfaced while carrying out TKR. Each patient was assessed intraoperatively and his/her patella classified as per Outerbridge classification. Patients were followed-up at 03, 06 and 12 months postoperatively and assessed by modified hospital for special surgery (HSS) knee scores.Results: In case of Outerbridge class III group there is a statistically significant difference (p value -0.002) in HSS score at 03 months, which becomes highly significant at 06 months (p value -0.001) and 01 year (p value &lt;0.001). Similarly, there is statistically significant difference in HSS score (p value- 0.001) in Outerbridge class IV group at 03 months, 06 months and 01 year.Conclusions: Patellar resurfacing in patients undergoing total knee arthroplasty with patella in Outerbridge class III and IV can be safely carried out to further improve the functional outcome. There is no distinct advantage of resurfacing patella in Outerbridge class I and II in terms of functional gain. Thus, Outerbridge classification for patella can effectively guide us whether to resurface patella or not in patients undergoing total knee arthroplasty.

SubFoveal Choroidal Imaging in High Myopic Nepalese Cohort

Current image captioning models produce fluent captions, but they rely on a one-size-fits-all approach that does not take into account the preferences of individual end-users. We present a method to generate descriptions with an adjustable amount of content that can be set at inference-time, thus providing a step toward a more user centered approach to image captioning

TO EVALUATE CARDIAC AUTONOMIC NERVOUS SYSTEM FUNCTIONS IN PATIENTS WITH RHEUMATOID ARTHRITIS

AIM: To evaluate cardiac autonomic nervous system functions in patients with rheumatoid arthritis. MATERIAL AND METHODS: The present study was carried out on both males and females of mean age group 44+12 years to study autonomic functions in RA. All parameters were recorded and studied on 35 volunteers, out of which 25 were diagnosed with RA and 10 were healthy individuals which served as controls.The cardiac functions were evaluated by six non-invasive standardized tests consisting of 30:15 ratio, standing / lying ratio, expiration / inspiration ratio, valsalva ratio, blood pressure response to standing, blood pressure response to valsalva maneuver and hand grip test.The tests were carried out on patient (in and out door) in department of Medicine, at DMC &amp; H by using cardiofax Machine (Medicarid systems).Details of history and examination were recorded on special proforma. RESULTS: In the present study standing to lying ratio (p&lt;0.001),Expiration to inspiration ratio (p&lt;0.01) both indicative of parasympathetic function were significantly less in RA patients as compared to control indicating an impaired vagal function in study group.On the blood pressure response to standing, the decrease in diastolic blood pressure was significant (P&lt;0.01) in study group as compared to control which is indicative of hypofunctional sympathetic ANS. CONCLUSIONS: There is cardiac autonomic nervous system dysfunction (both sympathetic and parasympathetic) in the patients with Rheumatoid arthritis when compared to control.Autonomic function tests can help in predicting cardio vascular risk in Rheumatoid Arthritis patients

LEADNet: Detection of Alzheimer’s Disease using Spatiotemporal EEG Analysis and Low-Complexity CNN

© 2024 The Author(s). This is an open access article under the Creative Commons Attribution-Non Commercial-No Derivatives CC BY-NC-ND licence, https://creativecommons.org/licenses/by-nc-nd/4.0/Clinical methods for dementia detection are expensive and prone to human errors. Despite various computer-aided methods using electroencephalography (EEG) signals and artificial intelligence, a reliable detection of Alzheimer’s disease (AD) remains a challenge. The existing EEG-based machine learning models have limited performance or high computation complexity. Hence, there is a need for an optimal deep learning model for the detection of AD. This paper proposes a low-complexity EEG-based AD detection CNN called LEADNet to generate disease-specific features. LEADNet employs spatiotemporal EEG signals as input, two convolution layers for feature generation, a max-pooling layer for asymmetric spatiotemporal redundancy reduction, two fully-connected layers for nonlinear feature transformation and selection, and a softmax layer for disease probability prediction. Different quantitative measures are calculated using an open-source AD dataset to compare LEADNet and four pre-trained CNN models. The results show that the lightweight architecture of LEADNet has at least a 150-fold reduction in network parameters and the highest testing accuracy of 99.24% compared to pre-trained models. The investigation of individual layers of LEADNet showed successive improvements in feature transformation and selection for detecting AD subjects. A comparison with the state-of-the-art AD detection models showed that the highest accuracy, sensitivity, and specificity were achieved by the LEADNet model.Peer reviewe