Approximating the Solution of Surface Wave Propagation Using Deep Neural Networks

Partial differential equations formalise the understanding of the behaviour of the physical world that humans acquire through experience and observation. Through their numerical solution, such equations are used to model and predict the evolution of dynamical systems. However, such techniques require extensive computational resources and assume the physics are prescribed \textit{a priori}. Here, we propose a neural network capable of predicting the evolution of a specific physical phenomenon: propagation of surface waves enclosed in a tank, which, mathematically, can be described by the Saint-Venant equations. The existence of reflections and interference makes this problem non-trivial. Forecasting of future states (i.e. spatial patterns of rendered wave amplitude) is achieved from a relatively small set of initial observations. Using a network to make approximate but rapid predictions would enable the active, real-time control of physical systems, often required for engineering design. We used a deep neural network comprising of three main blocks: an encoder, a propagator with three parallel Long Short-Term Memory layers, and a decoder. Results on a novel, custom dataset of simulated sequences produced by a numerical solver show reasonable predictions for as long as 80 time steps into the future on a hold-out dataset. Furthermore, we show that the network is capable of generalising to two other initial conditions that are qualitatively different from those seen at training time

Towards fast simulation of environmental fluid mechanics with multi-scale graph neural networks

Numerical simulators are essential tools in the study of natural fluid-systems, but their performance often limits application in practice. Recent machine-learning approaches have demonstrated their ability to accelerate spatio-temporal predictions, although, with only moderate accuracy in comparison. Here we introduce MultiScaleGNN, a novel multi-scale graph neural network model for learning to infer unsteady continuum mechanics in problems encompassing a range of length scales and complex boundary geometries. We demonstrate this method on advection problems and incompressible fluid dynamics, both fundamental phenomena in oceanic and atmospheric processes. Our results show good extrapolation to new domain geometries and parameters for long-term temporal simulations. Simulations obtained with MultiScaleGNN are between two and four orders of magnitude faster than those on which it was trained

Functional outcome of mild and moderate residual varus in posterior stabilized total knee arthroplasty in primary osteoarthritis knee: a prospective study

Background: Total knee arthroplasty (TKA) is one of the most commonly done orthopaedic surgical procedures for treating severe arthritis of the knee joint caused by osteoarthritis or inflammatory arthritis. The current clinical investigation, done at the Sanjay Gandhi Institute of Trauma and Orthopaedics in Bengaluru, provided the short-term functional result of mild and moderate residual varus in posterior stabilized TKA. The aim was to evaluate the efficacy of mild and moderate residual varus in total knee replacement for primary OA knee in terms of pain relief, range of motion and stability of the joint. Methods: 30 total knee replacements were performed. All patients were examined pre- and post-operatively using the knee society clinical and functional score. The average pre-op KSS knee score was 38.7, with a functional score of 23.3. The most common reason for TKR was osteoarthritis. The follow-up time ranged from 6 to 12 months.Results: By the knee society clinical, functional score method, 96.6% of our patients received an outstanding assessment after scoring 80 points or higher. The mean post-operative KSS knee score is 86.57, and the knee society functional score is 92. 92% of patients had little/no pain after surgery, and walking ability increased and was unlimited in 80% of patients.Conclusions: After a short term follow up of 1 year in a research population of 30 with pre-operative osteo arthritis of the knee, with post-operative mild to moderate varus alignment showed better clinical results

Non-parametric regression for robot learning on manifolds

Many of the tools available for robot learning were designed for Euclidean data. However, many applications in robotics involve manifold-valued data. A common example is orientation; this can be represented as a 3-by-3 rotation matrix or a quaternion, the spaces of which are non-Euclidean manifolds. In robot learning, manifold-valued data are often handled by relating the manifold to a suitable Euclidean space, either by embedding the manifold or by projecting the data onto one or several tangent spaces. These approaches can result in poor predictive accuracy, and convoluted algorithms. In this paper, we propose an "intrinsic" approach to regression that works directly within the manifold. It involves taking a suitable probability distribution on the manifold, letting its parameter be a function of a predictor variable, such as time, then estimating that function non-parametrically via a "local likelihood" method that incorporates a kernel. We name the method kernelised likelihood estimation. The approach is conceptually simple, and generally applicable to different manifolds. We implement it with three different types of manifold-valued data that commonly appear in robotics applications. The results of these experiments show better predictive accuracy than projection-based algorithms.Comment: 17 pages, 15 figure

A prospective comparative study of functional outcome of distal extra articular tibia fracture fixed with intramedullary nail versus locking compression plate

Background: Distal tibia fractures are one of the most common long bone fractures and their management presents with a series of problems due to the soft tissue surroundings and even more at risk due to their proximity to ankle joint. In our paper we showed functional outcome of distal extra articular tibia fracture while comparing its management between intramedullary nailing and locking compression plate.Methods: There were 40 patients from November 2019 to November 2020 with distal extra articular tibia fracture. Patients were divided into 2 groups, first group included 20 patients managed with intramedullary nail and the second group included 20 patients managed with locking compression plate. Patients were followed preoperatively, intraoperatively and postoperatively for functional outcome and assessed clinically using AOFAS score and radiologically using X-ray.Results: Out of the 40 cases treated in this manner, all cases were available for the follow up for a period of 1 year. Overall results by 1 year follow up showed excellent in 7 cases (35%) good in 13 cases (65%) in nailing group and in plating group showed excellent in 4 cases (20%), good in 12 cases (60%), fair in 3 cases (15%) and poor in 1 case (5%).Conclusions: All fractures united well. Complications were encountered in 4 patients, 2 patients had superficial wound infections,1 patient had deep infection and another had persistent ankle pain in plating group and 2 patients had superficial wound infection in nailing group. No cases showed malunion or nonunion in both plating as well as nailing group

The Dynamic Characteristics of a non-linear main landing gear system of an aircraft during landing

The landing gear plays a very important role during landing by absorbing the high impact energy of the aircraft. The main landing gear absorbs the bulk of the load to reduce the load experienced by both the aircraft fuselage and the nose landing gear. In this paper, a mathematical approach is used to extract the dynamic characteristics of the system. A two-degree of freedom mathematical model of the main landing gear is developed. This model is used to derive the dynamic equations of the landing gear system and to study the behaviour of main landing gear during main gear and nose gear touchdown conditions. The non-linear stiffness and damping co-efficient in an Oleo-Pneumatic shock absorber are integrated into the system to achieve a more accurate response of the system. The response of this system is established by adopting a complex modal analysis approach to account for the non-classical damping exhibited by the system. The obtained spring force, damping force and responses are reported. This work provides an alternative approach using complex modal analysis to obtain results for complex systems exhibiting non-linear characteristics

An Absorbing Improvement for Space Infection Decompression: A Novel Drainage Device

Introduction Infection of the facial spaces and the associated exudate can often necessitate surgical intervention. Whilst traditional decompression methodologies have reduced the mortality rate from complications such as Ludwig&rsquo;s Angina, there has been relatively little innovation in the procedure to minimize treatment times and patient distress. Negative pressure wound therapy, which can yield improvements to treatment time, wound healing and patient experience, has gained traction in abscess treatments in other parts of the body but seen limited adoption in maxillofacial surgeries. Methods A focused literature review explores the existing treatment methodologies for infected facial space decompression and identifies obstacles to implementing negative pressure wound therapy in maxillofacial surgeries. A novel drainage tool, which features a sleeved sponge over a perforated drainage tube, is proposed. Virtual prototyping and structural analyses of the novel drainage device including a parametric design study are presented. Results The parametric study validates the proposed tool&rsquo;s biocompatibility in terms of overall flexural and axial stiffness between the tool and complex structures in the head and neck. Ultimately, this work presents a necessary first step in the development of specialized drainage tools to promote the adoption of negative pressure wound therapy for infections of facial spaces. </div

ANTIBACTERIAL ACTIVITY OF FRESH WATER CRAB AND SNAIL AND ISOLATION OF ANTIBACTERIAL PEPTIDES FROM HAEMOLYMPH BY SDS – PAGE

Objective: The present study was undertaken to characterize antimicrobial molecules from the fresh water snail and crab.Methods: Collection of haemolymph, preparation of extracts, antimicrobial activity, TLC analysis, SDS PAGE analysis.Results: The result of the present investigation reported that the fresh water snail (Pomacea insularium) and crab (Callinectes sapidus) having remarkable antimicrobial activity in methanol, di-ethyl ether and water extracts. Antimicrobial activity was high in di-ethyl ether extracts of the snail against Streptococcus sp. (37.16±0.76 mm) and methanol extract of crab against E. coli (32.16±0.28 mm). The MIC of extracts ranges between 5 µl to 30 µl methanol extract of both snail and crab inhibited the growth of organisms at very low concentration. Biomolecules from the extract was separated by TLC. The molecular mass of the peptide was determined by SDS PAGE. Peptides from snail and crab haemolymph were ranges in 9 to 110 and 40 to 100 kDa respectively.Conclusion: The present findings suggest that fresh water crab and snail having good antimicrobial activity against pathogenic microbes. Therefore they can be used to treat many pathogenic infections.Â

Assessment on awareness of rational prescribing practices among medical interns in a tertiary care hospital: a questionnaire based study

Background: Awareness about rational use of Medicines is required to improve the quality of health care system. Attitude towards rational drug use is also an utmost importance as they constitute the future generation doctors.Methods: A set of 13 questionnaire is given to the interns through an online link to their e-mail which contains informed consent and questionnaires. Respondents has to select the best suitable option and after which the data will be compiled and statistically analyzed.Results: Age of the study participants range from 22-26yrs. Half of them have finished major postings. Almost 96.1 % of them were aware of the term essential drugs. Only 25% of them said that they have NLEMI at work place, 75% of them were aware of the term Rational use of Medicines. Only 32% of them were aware of the term P drugs. 44% of them were aware of STEP criteria for selection of drug and 47% of them were aware of the updated prescribing format. 8% knew the difference between old and new prescription format, 25% of them always prescribe. Almost 82% of them narrate regarding the disease and drug therapy, 31% of them prescribe only generic name.Conclusions: Educational intervention like CME and practical hands on training in Rational use of Medicines would help them in better understanding of the subject and its clinical implications thereby decreasing the prescribing errors