44 research outputs found
Shoulder arthroplasty in alkaptonuric arthropathy: A clinical case report and literature review
No full textAlkaptonuria is a rare hereditary metabolic disease of autosomal recessive inheritance, resulting from deficiency of the enzyme homogentisic acid oxidase. The term ''alkaptonuria'' was first used in 1859 by Boedeker to describe a patient's urinary reducing compound, and in 1866, Virchow coined the term ''ochronosis'' due to typical yellow pigmentation. Deposition of this pigment in articular cartilage leads to ochronotic arthropathy, the most incapacitating complication of alkaptonuria. We report a rare case of shoulder ochronotic arthritis, treated with total shoulder arthroplasty, achieving a successful long-term clinical and radiological outcomes. © 2012 Springer-Verlag
Ossifying tendinitis of the rotator cuff after arthroscopic excision of calcium deposits: report of two cases and literature review
No full textOssifying tendinitis (OT) is a type of heterotopic ossification, characterized by deposition of hydroxyapatite crystals in a histologic pattern of mature lamellar bone. It is usually associated with surgical intervention or trauma and is more commonly seen in Achilles or distal biceps tendons, and also in the gluteus maximus tendon. To our knowledge, there is no description of OT as a complication of calcifying tendinitis of the rotator cuff. In this report, we describe two cases in which the patients developed an OT of the supraspinatus after arthroscopic removal of calcium deposits. The related literature is reviewed
DDoS detection and mitigation using machine learning
No full textDistributed Denial of Service (DDoS) attacks are very common nowadays. It is evident that the current industry solutions, such as completely relying on the In- ternet Service Provider (ISP) or setting up a DDoS defense infrastructure, are not sufficient in detecting and mitigating DDoS attacks, hence consistent research is needed. In this thesis we first tried to understand how DDoS attacks happen, then we discussed a way to detect DDoS attacks using machine learning tools at the routers, instead of setting up a centralized analysis system. We have proposed a standard communication architecture which can be used across all the networking devices for mitigating DDoS attacks. We have also created a simulation program to demonstrate our detection technique.M.S.Includes bibliographical referencesby Arpit Ramesh Gawand
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Screening, Defects, and Dangling Bonds Induced Optical Damage Threshold in Monolayer MoS2
No full textAn optoelectronic device based on the TMDs should be versatile in its applications and be able to endure high optical intensities. In this thesis, I have shown the experimentally-measured damage threshold intensity range of 75 to 100 kW/cm2 of a monolayer MoS2 at room temperature. The corresponding photo-excited carrier density, for the CW photo-excitation, is ~1.6 x 10^10 cm^(-2). While the goal has been to find the damage threshold intensity, certain patterns that have emerged from the optical response of the monolayer MoS2 in the vicinity of the optical damage threshold needed to be thoroughly examined. I have quantified the experimental results and have attempted to qualitatively understand the underlying physics. The many-body effects play a crucial role in all these processes such that there is a complicated correlation. While explaining the physics through experimental results, I have attempted to disentangle the screening-related effects and damage and/or defect states related effects from the experimental dependencies, viz., optical power, laser irradiance time, and beam position.
The measurements have been done by collecting the photoluminescence (PL) signals. The parameters such as excitonic peak amplitude, area, FWHM, and the central wavelength have been extracted from the curve fitting of the PL spectrums. In the optical power dependence measurement, I have compared the optical responses of the material by employing two different methods of measurement, viz., the Direct and Indirect PL measurement methods. In both these methods of measurement, I increase the excitation intensity step-wise but the method of collecting the PL signal differs. We will see that this slight difference in methodology provides us with a strikingly different optical response. In the laser irradiance time dependence measurement, I have exposed the sample continuously for 62 minutes in total. With this, the charge accumulation and resultant changes in the optical response of the material have been demonstrated. We will see that my experiments concretely debunk the claim of laser-induced atomic healing of defects. In the beam position dependent measurement, I deliberately create damage and optically scan the sample through pristine, within the damage, and at the damaged edge by collecting the PL signal from these locations. The characteristic enhancement in the PL signal is evidently found to be a real feature.
From these measurements, salient features have been consistently observed such that these can be marked as the signatures of the damage incurrence. Signatures such as 2x to 4x times the increment in the peak amplitude, a similar increment in the area, changes in PL efficiency, 30% to 50% shrinkage in the FWHM, and 4 nm to 15 nm of a spectral blue shift in the A exciton peak in the PL spectrum. In this thesis, I will further demonstrate that all these reversible and irreversible changes are from the contributions of the screening effects such as Bandgap Renormalization (BGR) and Coulomb screening, defects and dangling bonds induced damage threshold in the monolayer MoS2
Statistical field estimation and scale estimation for complex coastal regions and archipelagos
No full textThesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 153-158).A fundamental requirement in realistic computational geophysical fluid dynamics is the optimal estimation of gridded fields and of spatial-temporal scales directly from the spatially irregular and multivariate data sets that are collected by varied instruments and sampling schemes. In this work, we derive and utilize new schemes for the mapping and dynamical inference of ocean fields in complex multiply-connected domains, study the computational properties of our new mapping schemes, and derive and investigate new schemes for adaptive estimation of spatial and temporal scales. Objective Analysis (OA) is the statistical estimation of fields using the Bayesian-based Gauss-Markov theorem, i.e. the update step of the Kalman Filter. The existing multi-scale OA approach of the Multidisciplinary Simulation, Estimation and Assimilation System consists of the successive utilization of Kalman update steps, one for each scale and for each correlation across scales. In the present work, the approach is extended to field mapping in complex, multiply-connected, coastal regions and archipelagos. A reasonably accurate correlation function often requires an estimate of the distance between data and model points, without going across complex land-forms. New methods for OA based on estimating the length of optimal shortest sea paths using the Level Set Method (LSM) and Fast Marching Method (FMM) are derived, implemented and utilized in general idealized and realistic ocean cases.(cont.) Our new methodologies could improve widely-used gridded databases such as the climatological gridded fields of the World Ocean Atlas (WOA) since these oceanic maps were computed without accounting for coastline constraints. A new FMM-based methodology for the estimation of absolute velocity under geostrophic balance in complicated domains is also outlined. Our new schemes are compared with other approaches, including the use of stochastically forced differential equations (SDE). We find that our FMM-based scheme for complex, multiply-connected, coastal regions is more efficient and accurate than the SDE approach. We also show that the field maps obtained using our FMM-based scheme do not require postprocessing (smoothing) of fields. The computational properties of the new mapping schemes are studied in detail. We find that higher-order schemes improve the accuracy of distance estimates. We also show that the covariance matrices we estimate are not necessarily positive definite because the Weiner Khinchin and Bochner relationships for positive deniteness are only valid for convex simply-connected domains. Several approaches to overcome this issue are discussed and qualitatively evaluated. The solutions we propose include introducing a small process noise or reducing the covariance matrix based on the dominant singular value decomposition.(cont.) We have also developed and utilized novel methodologies for the adaptive estimation of spatial-temporal scales from irregularly spaced ocean data. The three novel methodologies are based on the use of structure functions, short term Fourier transform and second generation wavelets. To our knowledge, this is the first time that adaptive methodologies for the spatial-temporal scale estimation are proposed. The ultimate goal of all these methods would be to create maps of spatial and temporal scales that evolve as new ocean data are fed to the scheme. This would potentially be a significant advance to the ocean community for better understanding and sampling of ocean processes.by Arpit Agarwal.S.M
Improving a Reinforcement Learning Negotiating Agent’s Performance by Extracting Information from the Opponent’s Sequence of Offers
No full textWith the prospects of decentralized multi-agent systems becoming more prevalent in daily life, automated negotiation agents have made their place in these collaborative settings. They are an approach to promote communication between the agents in reaching solutions that are better for all involved.Recent literature has shown great potential in using machine learning, particularly model-free deep reinforcement learning like Proximal Policy Optimization (PPO), to develop more performant automated negotiation strategies. This work focuses on using information from the opponent's sequence of offers in a bilateral negotiation to further improve a baseline PPO agent. This involves extracting and representing information from the opponent's sequence of offers into a state vector with a fixed dimension to modify the input to the agent's policy, and then comparing the utilities this modified agent achieves to the baseline PPO agent. Since there is a large variety of numerical measures to represent a sequence of offers, an ablation study is conducted to investigate the effectiveness of each.The modified agents consistently reached solutions that had higher social welfare, although the agent's own utility did not improve or diminish significantly in comparison to the base PPO agent.https://github.com/brenting/negotiation_PPO The repository containing all the code this paper used. The code for this specific paper was done in the 'sequence-of-offers-single-thread' branch.CSE3000 Research ProjectComputer Science and Engineerin
Stock prediction, trading simulation and options volatility prediction using FASCOM++ (fuzzy associative cortical maps architecture)
No full textFuzzy Associative Cortical Maps Architecture (FASCOM) is inspired from the cortical maps found in many biological and artificial neural systems. The cortical maps organise and represent information obtained from sensory inputs and play important roles in learning and memory processes. FASCOM uses features inspired by the structure and functions of cortical maps and is integrated a linguistic fuzzy model to perform associative learning of input-output pairs. The project undertakes to improve the architecture of FASCOM to incorporate a learning mechanism, so that the network is capable of modifying its properties on the basis of the incoming data leading to better prediction and higher accuracy.
The author aims to validate the modified architecture of FASCOM by conducting benchmarking experiments and observing the improvement in the performance of the system over other systems. For this purpose, various classical datasets for classification and regression problems were used.
The author worked on many real-life application to observe FASCOM++’s performance on real-life data. One of the applications is stock data prediction where the author used Hong Kong stock data and predicted prices using FASCOM++ and compared the results with the actual prices. The analysis of FASCOM++’s performance helps in gauging its practical use in real-life applications such as stock trading. The author simulated a simple stock trading algorithm to compare and evaluate FASCOM++’s performance against other architectures.
The author explored other areas of applications and worked on options volatility prediction which is one of the core areas of research in the financial industry. By exploiting on the online learning capabilities FASCOM++ was able to perform better than the other architectures and demonstrated its capability to be a potential architecture for real-life purpose.Bachelor of Engineering (Computer Science
Using Pairwise Occurrence Information to Improve Knowledge Graph Completion on Large-Scale Datasets
No full textBilinear models such as DistMult and
ComplEx are effective methods for knowledge graph (KG) completion. However, they
require large batch sizes, which becomes a
performance bottleneck when training on
large scale datasets due to memory constraints. In this paper we use occurrences of
entity-relation pairs in the dataset to construct
a joint learning model and to increase the
quality of sampled negatives during training.
We show on three standard datasets that when
these two techniques are combined, they give
a significant improvement in performance,
especially when the batch size and the number
of generated negative examples are low
relative to the size of the dataset. We then
apply our techniques to a dataset containing
2 million entities and demonstrate that our
model outperforms the baseline by 2.8%
absolute on hits@1
Human Papillomavirus Vaccine Uptake Among U.S. Medical Residents in High-Exposure-Risk Specialties – A National Study
No full textBackground. HPV vaccination is not required for the United States (U.S.) medical residents, despite their potentially high risk of iatrogenic exposure to the virus. We aim to evaluate vaccination status, patterns of HPV vaccine uptake, and perceived risk of iatrogenic infection among residents in high-exposure-risk specialties.
Methods. In spring 2023, an anonymous online survey was distributed via program directors and coordinators of all Accreditation Council for Graduate Medical Education (ACGME)-accredited Obstetrics & Gynecology, Family Medicine, Otolaryngology, and Dermatology training programs to assess residents’ vaccination status, HPV exposure, and HPV vaccine knowledge.
Results. Responses from 537 residents at programs located in 42/52 U.S. states/territories showed that 91% of females and 62% of males were at least partially vaccinated (p \u3c 0.01), and 77% who were unvaccinated would consider vaccination in the future. Overall, 47% of residents estimated treating ≥ 26 cases/year of HPV-related disease, and 85% perceived a mild to high risk of iatrogenic exposure. Finally, 90% were familiar with the CDC’s HPV vaccination schedule, 92% felt comfortable counseling patients about the vaccine, and 99% agreed the vaccine provides protection to male and female patients.
Conclusion. This study found a 16% rate of non-vaccination, with men much less likely to be vaccinated, despite most residents feeling at risk of iatrogenic exposure. Additionally, despite nearly unanimous agreement that the HPV vaccine provides protection to patients, only 60% of residents routinely recommended vaccination to all eligible patients. These findings demonstrate potential opportunities to increase HPV vaccine uptake among residents who treat HPV-related diseases and to improve vaccination counseling for their patients
Multi-Derivative Runge-Kutta Flux Reconstruction for hyperbolic conservation laws
No full textWe extend the fourth order, two stage Multi-Derivative Runge Kutta (MDRK) scheme to the Flux Reconstruction (FR) framework by writing both stages in terms of a time averaged flux and then using the approximate Lax-Wendroff procedure to compute the time averaged flux. Numerical flux is carefully constructed to enhance Fourier CFL stability and accuracy. A subcell based blending limiter is developed for the MDRK scheme which ensures that the limited scheme is provably admissibility preserving. Along with being admissibility preserving, the blending scheme is constructed to minimize dissipation errors by using Gauss-Legendre solution points and performing MUSCL-Hancock reconstruction on subcells. The accuracy enhancement of the blending scheme is numerically verified on compressible Euler\u27s equations, with test cases involving shocks and small-scale structures.arXiv admin note: text overlap with arXiv:2305.10781, arXiv:2207.02954; text overlap with arXiv:1609.04491 by other author
