Search results for: Krish Makkar

Authors: Anvikshaa Bisen, Krish Makkar

Abstract:

Professionals misdiagnose autism by ticking off symptoms on a checklist without questioning the causes of said symptoms, and without understanding the innate neurophysiology of the autistic brain. A dysfunctional cingulate gyrus (CG) hyperfocuses attention in the left frontal lobe (logical/analytical) with no ability to access the right frontal lobe (emotional/creative), which plays a central role in spontaneity, social behavior, and nonverbal abilities. Autistic people live in a specialized inner space that is entirely intellectual, free from emotional and social distractions. They have no innate biological way of emotionally connecting with other people. Autistic people process their emotions intellectually, a process that can take 24 hours, by which time it is too late to have felt anything. An inactive amygdala makes it impossible for autistic people to experience fear. Because they do not feel emotion, they have no emotional memories. All memories are of events that happened about which they felt no emotion at the time and feel no emotion when talking about it afterward.

Keywords: autism, Asperger, Asd, neuropsychology, neuroscience

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Authors: Preeti Makkar, R. C. Agarwala, Vijaya Agarwala

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The present study focuses on the preparation of Al2O3 nanoparticles by top down approach i.e. mechanical milling using high energy planetary ball mill at 250 rpm for 40h. The milled Al2O3 nanoparticles are then used as the second phase to develop electroless (EL) Ni-P- Al2O3 nanocomposite coatings on mild steel substrate. An alkaline bath was used with a suspension of Al2O3 particles (4 g/L) for the synthesis of Ni-P-Al2O3 nanocomposite coating. The surface morphology, size range and phase analysis of as-prepared Al2O3 particles and the coatings were characterized using X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM). The coatings were heat treated at 400°C for 1h in argon atmosphere and the hardness of the nanocomposite coatings was investigated with respect to Ni-P before and after heat treatment. The results showed that as milled Al2O3 nanoparticles exhibit irregular shaped and size ranges around 40-45 nm. The Al2O3 particles are uniformly distributed in Ni-P matrix. The microhardness of the coatings is found to be significantly improved after heat treatment (1126 VHN).

Keywords: Electroless (EL), Ni-P-Al2O3, nanocomposite, mechanical milling, microhardness

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Authors: Femy M. Makkar, S. Chandrakaran, N. Sankar

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The concept of reinforced earth has been used in the field of geotechnical engineering since 1960s, for many applications such as, construction of road and rail embankments, pavements, retaining walls, shallow foundations, soft ground improvement and so on. Conventionally, planar geosynthetic materials such as geotextiles and geogrids were used as the reinforcing elements. Recently, the use of three dimensional reinforcements becomes one of the emerging trends in this field. So, in the present investigation, three dimensional geogrid is proposed as a reinforcing material. Laboratory scaled plate load tests are conducted on a model square footing resting on 3D geogrid reinforced sand bed. The performance of 3D geogrids in triangular and square pattern was compared with conventional geogrids and the improvement in bearing capacity and reduction in settlement and heave are evaluated. When single layer of reinforcement was placed at an optimum depth of 0.25B from the bottom of the footing, the bearing capacity of conventional geogrid reinforced soil improved by 1.85 times compared to unreinforced soil, where as 3D geogrid reinforced soil with triangular pattern and square pattern shows 2.69 and 3.05 times improvement respectively compared to unreinforced soil. Also, 3D geogrids performs better than conventional geogrids in reducing the settlement and heave of sand bed around the model footing.

Keywords: 3D reinforcing elements, bearing capacity, heavy, settlement

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Authors: Krish Batra

Abstract:

The advent of open banking has revolutionized the financial services industry by fostering innovation, enhancing customer experience, and promoting competition. However, this paradigm shift towards more open and interconnected banking ecosystems has introduced complex cybersecurity challenges. This research paper delves into the multifaceted cybersecurity landscape of open banking, highlighting the vulnerabilities and threats inherent in sharing financial data across a network of banks and third-party providers. Through a detailed analysis of recent data breaches, phishing attacks, and other cyber incidents, the paper assesses the current state of cybersecurity within the open banking framework. It examines the effectiveness of existing security measures, such as encryption, API security protocols, and authentication mechanisms, in protecting sensitive financial information. Furthermore, the paper explores the regulatory response to these challenges, including the implementation of standards such as PSD2 in Europe and similar initiatives globally. By identifying gaps in current cybersecurity practices, the research aims to propose a set of robust, forward-looking strategies that can enhance the security and resilience of open banking systems. This includes recommendations for banks, third-party providers, regulators, and consumers on how to mitigate risks and ensure a secure open banking environment. The ultimate goal is to provide stakeholders with a comprehensive understanding of the cybersecurity implications of open banking and to outline actionable steps for safeguarding the financial ecosystem in an increasingly interconnected world.

Keywords: open banking, financial services industry, cybersecurity challenges, data breaches, phishing attacks, encryption, API security protocols, authentication mechanisms, regulatory response, PSD2, cybersecurity practices

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Authors: Krish Jhurani

Abstract:

The research paper presents an in-depth analysis of symmetry properties in linear algebraic systems under the operation of non-canonical scalar multiplication structures, specifically semirings, and near-rings. The objective is to unveil the profound alterations that occur in traditional linear algebraic structures when we replace conventional field multiplication with these non-canonical operations. In the methodology, we first establish the theoretical foundations of non-canonical scalar multiplication, followed by a meticulous investigation into the resulting symmetry properties, focusing on eigenvectors, eigenspaces, and invariant subspaces. The methodology involves a combination of rigorous mathematical proofs and derivations, supplemented by illustrative examples that exhibit these discovered symmetry properties in tangible mathematical scenarios. The core findings uncover unique symmetry attributes. For linear algebraic systems with semiring scalar multiplication, we reveal eigenvectors and eigenvalues. Systems operating under near-ring scalar multiplication disclose unique invariant subspaces. These discoveries drastically broaden the traditional landscape of symmetry properties in linear algebraic systems. With the application of these findings, potential practical implications span across various fields such as physics, coding theory, and cryptography. They could enhance error detection and correction codes, devise more secure cryptographic algorithms, and even influence theoretical physics. This expansion of applicability accentuates the significance of the presented research. The research paper thus contributes to the mathematical community by bringing forth perspectives on linear algebraic systems and their symmetry properties through the lens of non-canonical scalar multiplication, coupled with an exploration of practical applications.

Keywords: eigenspaces, eigenvectors, invariant subspaces, near-rings, non-canonical scalar multiplication, semirings, symmetry properties

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Authors: Talal Asif, Maya Kosinska, Lucas Georger, Krish Sardesai, Muhammad Shah Miran

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This article presents a case review and literature review focused on the challenges of managing subaortic membranes (SAM) in young adult patients with mild aortic regurgitation (AR) or aortic stenosis (AS). The study aims to discuss the diagnosis of SAM, imaging studies used for assessment, management strategies in young patients, the risk of valvular damage, and the controversy surrounding prophylactic resection in mild AR. The management of SAM in adults poses challenges due to limited treatment options and potential complications, necessitating further investigation into the progression of AS and AR in asymptomatic SAM patients. The case presentation describes a 40-year-old male with muscular dystrophy who presented with symptoms and was diagnosed with SAM. Various imaging techniques, including CT chest, transthoracic echocardiogram (TTE), and transesophageal echocardiogram (TEE), were used to confirm the presence and severity of SAM. Based on the patient's clinical profile and the absence of surgical indications, medical therapy was initiated, and regular outpatient follow-up was recommended to monitor disease progression. The discussion highlights the challenges in diagnosing SAM, the importance of imaging studies, and the potential complications associated with SAM in young patients. The article also explores the management options for SAM, emphasizing surgical resection as the definitive treatment while acknowledging the limited success rates of alternative approaches. Close monitoring and prompt intervention for complications are crucial in the management of SAM. The concluding statement emphasizes the need for further research to explore alternative treatments for SAM in young patients.

Keywords: subaortic membrane, management, case report, literature review, aortic regurgitation, aortic stenosis, left ventricular outflow obstruction, guidelines, heart failure

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Authors: Pranav Gunhal., Krish Jhurani

Abstract:

This study tackles the significant computational challenge of predicting excited state dynamics in organic photovoltaic (OPV) materials—a pivotal factor in the performance of solar energy solutions. Time-dependent density functional theory (TDDFT), though effective, is computationally prohibitive for larger and more complex molecules. As a solution, the research explores the application of transformer neural networks, a type of artificial intelligence (AI) model known for its superior performance in natural language processing, to predict excited state dynamics in OPV materials. The methodology involves a two-fold process. First, the transformer model is trained on an extensive dataset comprising over 10,000 TDDFT calculations of excited state dynamics from a diverse set of OPV materials. Each training example includes a molecular structure and the corresponding TDDFT-calculated excited state lifetimes and key electronic transitions. Second, the trained model is tested on a separate set of molecules, and its predictions are rigorously compared to independent TDDFT calculations. The results indicate a remarkable degree of predictive accuracy. Specifically, for a test set of 1,000 OPV materials, the transformer model predicted excited state lifetimes with a mean absolute error of 0.15 picoseconds, a negligible deviation from TDDFT-calculated values. The model also correctly identified key electronic transitions contributing to the excited state dynamics in 92% of the test cases, signifying a substantial concordance with the results obtained via conventional quantum chemistry calculations. The practical integration of the transformer model with existing quantum chemistry software was also realized, demonstrating its potential as a powerful tool in the arsenal of materials scientists and chemists. The implementation of this AI model is estimated to reduce the computational cost of predicting excited state dynamics by two orders of magnitude compared to conventional TDDFT calculations. The successful utilization of transformer neural networks to accurately predict excited state dynamics provides an efficient computational pathway for the accelerated discovery and design of new OPV materials, potentially catalyzing advancements in the realm of sustainable energy solutions.

Keywords: transformer neural networks, organic photovoltaic materials, excited state dynamics, time-dependent density functional theory, predictive modeling

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Authors: Suraj Makkar, Asis Isor, Jeetendra Gupta, Simran Bareja, Maushumi K. Talukdar

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During the exploratory testing phase of an offshore oil and gas well, when the tubing string was pulled out after production testing, it was observed that there was visible corrosion/pitting in a few of the 3-1/2” API 5 CT L-80 Grade tubing. The area of corrosion was at the same location in all the tubing, i.e., just above the pin end. Since the corrosion was observed in the tubing within two months of their installation, it was a matter of concern, as it could lead to premature failures resulting in leakages and production loss and thus affecting the integrity of the asset. Therefore, the tubing was analysed to ascertain the mechanism of the corrosion occurring on its surface. During the visual inspection, it was observed that the corrosion was totally external, which was near the pin end, and no significant internal corrosion was observed. The chemical compositional analysis and mechanical properties (tensile and impact) show that the pipeline material was conforming to API 5 CT L-80 specifications. The metallographic analysis of the tubing revealed tempered martensitic microstructure. The grain size was observed to be different at the pin end as compared to the microstructure at base metal. The microstructures of the corroded area near threads reveal an oriented microstructure. The clearly oriented microstructure of the cold-worked zone near threads and the difference in microstructure represents inappropriate heat treatment after cold work. This was substantiated by hardness test results as well, which show higher hardness at the pin end in comparison to hardness at base metal. Scanning Electron Microscope (SEM) analysis revealed the presence of round and deep pits and cracks on the corroded surface of the tubing. The cracks were stress corrosion cracks in a corrosive environment arising out of the residual stress, which was not relieved after cold working, as mentioned above. Energy Dispersive Spectroscopy (EDS) analysis indicates the presence of mainly Fe₂O₃, Chlorides, Sulphides, and Silica in the corroded part indicating the interaction of the tubing with the well completion fluid and well bore environment. Thus it was concluded that residual stress after the cold working of male pins during threading and the corrosive environment acted in synergy to cause this pitting corrosion attack on the highly stressed zone along the circumference of the tubing just below the threaded area. Accordingly, the following suitable recommendations were given to avoid the recurrence of such corrosion problems in the wells. (i) After any kind of hot work/cold work, tubing should be normalized at full length to achieve uniform microstructure throughout its length. (ii) Heat treatment requirements (as per API 5 CT) should be part of technical specifications while at the procurement stage.

Keywords: pin end, microstructure, grain size, stress corrosion cracks

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