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23. A study of chronic tendon Achilles rupture and the different modalities of its repair.

Author

Bisen, Swarup, Kumar, Naresh, Chaturvedi, Aditya, Sharma, Shashank, and Gupta, Rupesh

Subjects
LEG injuries, TENDON rupture, ACHILLES tendon, CALF muscles, DELAYED diagnosis, ACHILLES tendon rupture
Abstract

Background: Achilles tendon rupture is a common and primary cause of lower limb tendon injuries suffered during sports-related activities. The causes of Achilles tendon rupture include calf muscle and tendon overuse, steroid local injection in tendon, poor tendon quality, and various medical conditions. Historically, acute Achilles tendon rupture was treated conservatively. However, historical techniques are now associated with an increased risk of rerupture. Aim and Objective: To study of the reconstruction of chronic tendoachilles ruptures with the flexor hallucis longus and peroneus brevis. Material and Method: 30 patients aged between 30 and 60 years underwent reconstruction of chronically ruptured tendon Achilles either with flexor hallucis longus or peroneus brevis. Ruptures are due to stumbling in fields, falling from stairs, and some being uneventful. All these patients attended the department of Orthopaedics OPD and tertiary care of SSIMS, Bhilai. The patients were admitted and surgically treated after appropriate counseling and consent. The results were compared with the Quigley scale and Leppilahti scores. Results: Rupture of the Achilles tendon is more common in middle-aged males. Delay in diagnosis is due to a lack of adequate knowledge by the treating physician and a lack of immediate disability for the patient. The Thompson test has high sensitivity and specificity in diagnosis. Complications such as superficial skin infections and wound dehiscence are more common in patients treated with peroneus Peroneus and Sensory disturbance on foot is post operative complication. Conclusion: Flexor hallucis longus is superior to Peroneus brevis because of its anatomical and technical advantages, less incidence of superficial infections, wound dehiscence, and sensory disturbance, and better weight-bearing times and functional recovery. [ABSTRACT FROM AUTHOR]

Published
2024

33. Additively Manufactured Alnico Permanent Magnet Materials—A Review.

Author

Dussa, Saikumar, Joshi, Sameehan S., Sharma, Shashank, Krishna, Karri Venkata Mani, Radhakrishnan, Madhavan, and Dahotre, Narendra B.

Subjects
THREE-dimensional printing, PERMANENT magnets, MICROSTRUCTURE, POROSITY, SOLIDIFICATION
Abstract

Additive manufacturing offers manufacturing flexibility for intricate components and also allows for precise control over the microstructure. This review paper explores the current state of the art in additive manufacturing techniques for Alnico permanent magnets, emphasizing the notable advantages and challenges associated with this innovative approach. Both the LPBF and L-DED processes have demonstrated promising results in fabricating Alnico with magnetic properties comparable with conventionally processed samples. The optimization of process parameters successfully reduced porosity and cracking in the LPBF processing of Alnico. The review further explored the significance of additive manufacturing process parameter optimization in managing the temperature gradient and solidification rate for a desired microstructure and enhanced magnetic properties. Other potential additive manufacturing methods suitable for the fabrication of Alnico were discussed, along with the challenges associated with the process. The insights provided also highlight how additive manufacturing holds the potential to replace post-processing techniques like solutionization, magnetic annealing, and tempering often necessary in Alnico production. [ABSTRACT FROM AUTHOR]

Published
2024
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45. Performance Comparison of Machine Learning Platforms

Author

Roy, Asim, Qureshi, Shiban, Pande, Kartikeya, Nair, Divitha, Gairola, Kartik, Jain, Pooja, Singh, Suraj, Sharma, Kirti, Jagadale, Akshay, Lin, Yi-Yang, Sharma, Shashank, Gotety, Ramya, Zhang, Yuexin, Tang, Ji, Mehta, Tejas, Sindhanuru, Hemanth, Okafor, Nonso, Das, Santak, Gopal, Chidambara N., Rudraraju, Srinivasa B., and Kakarlapudi, Avinash V.

Subjects
Microsoft Corp., Automation -- Comparative analysis, Computer software industry -- Comparative analysis, Mechanization -- Comparative analysis, Machine learning -- Comparative analysis, Data mining -- Comparative analysis, Algorithms -- Comparative analysis, Data warehousing/data mining, Algorithm, Computers, Science and technology
Abstract

Abstract. In this paper, we present a method for comparing and evaluating different collections of machine learning algorithms on the basis of a given performance measure (e.g., accuracy, area under [...]

Published
2019
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50. Multiphysics multi-scale computational framework for linking process–structure–property relationships in metal additive manufacturing: a critical review.

Author

Sharma, Shashank, Joshi, Sameehan S., Pantawane, Mangesh V., Radhakrishnan, Madhavan, Mazumder, Sangram, and Dahotre, Narendra B.

Subjects
*DIGITAL twins, *ELECTRON beam furnaces, *RESIDUAL stresses, *THERMOCYCLING, *MACHINE learning, *PHENOMENOLOGICAL theory (Physics)
Abstract

This review article provides a critical assessment of the progress made in computational modelling of metal-based additive manufacturing (AM) with emphasis on its ability to predict physical phenomena, concepts of microstructural evolution, residual stresses, role of multiple thermal cycles, and formation of multi-dimensional defects along with the achieved degree of experimental validation. The uniqueness of this article stems from the inclusion of comprehensive information on computational progress in the field of fusion-based, sintering-based, and mechanical deformation-based AM. A computational model's role in determining the process framework for the desired outcome of the set properties of the AM components is recognised while presenting the process-microstructure maps, thereby appraising computational ability towards the qualification of products. The inclusion of a detailed discussion on the bi-directional coupling of machine learning and physics-based computational models provides a futuristic roadmap for the digital twin of metal-based AM. [ABSTRACT FROM AUTHOR]

Published
2023
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