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41,807 results on '"A Sahni"'

1. Beyond Training: Social Dynamics of AI Adoption in Industry

Author

Sahni, Riya and Chilton, Lydia B.

Subjects
Computer Science - Human-Computer Interaction
Abstract

While organizations continue to invest in AI tools like M365 Copilot, little is known about how individual employees engage with these technologies once deployed. This study examines M365 Copilot adoption behaviors among a group of 10 experienced users across many industries in the United States. Findings reveal a strong preference for informal learning methods over structured training. Even though 9 out of 10 participants acknowledged that formal training for Copilot tools would be useful, 7 out of 10 stated that they ignored the Copilot onboarding videos provided to them, citing reasons such as time constraints, preference for self-guided learning, or reliance on external resources like ChatGPT. No participants used formal training as their primary learning method. Instead, experiential learning (trial and error, 8 participants) and social learning (peer discussions, 6 participants) emerged as dominant learning strategies. We discuss opportunities for promoting social learning of AI tools in the workplace.

Published
2025

2. Analyzing Communicability and Connectivity in the Indian Stock Market During Crises

Author

Pawanesh, Pawanesh, Sharma, Charu, and Sahni, Niteesh

Subjects
Quantitative Finance - Statistical Finance
Abstract

In financial networks, information does not always follow the shortest path between two nodes but may also take alternate routes. Communicability, a network measure, resolves this complexity and, in diffusion-like processes, provides a reliable measure of the ease with which information flows between nodes. As a result, communicability appears to be an important measure for detecting disturbances in connectivity within financial systems, similar to instability caused by periods of high volatility. This study investigates the evolution of communicability measures in the stock networks during periods of crises, showing how systemic shocks strengthen the pairwise interdependence between stocks in the financial market. In this study, the permutation test reveals that approximately 83.5 per cent of stock pairs were found to be statistically significant at the significance level of 0.001 and have an increase in the shortest communicability path length during the crisis than the normal days, indicating enhanced interdependence and heightened information flow in the market. Furthermore, we show that when employed as features in the classification model, the network shortest path-based measures, along with communicability measures, are able to accurately classify between the times periods of market stability and volatility. Additionally, our results show that the geometric measures perform better in terms of classification accuracy than topological measures. These findings provide important insights into market behaviour during times of increased volatility and advance our understanding of the financial market crisis., Comment: 20 pages, 6 figures

Published
2025

3. Weathering the Pain: Ambient Temperatures Role in Chronic Pain Syndromes.

Author

Jevotovsky, David, Oehlermarx, Whitman, Chen, Tommy, Ortiz, Christopher, Liu, Annie, Sahni, Sidharth, Kessler, Jason, Poli, Joseph, and Lau, Richard

Subjects
Ambient temperature, Chronic pain, Complex regional pain syndrome, Fibromyalgia, Multiple sclerosis, Osteoartritis, Humans, Chronic Pain, Fibromyalgia, Complex Regional Pain Syndromes, Osteoarthritis, Temperature, Multiple Sclerosis, Pain Management
Abstract

PURPOSE OF REVIEW: Chronic pain is highly prevalent and involves a complex interaction of sensory, emotional, and cognitive processes, significantly influenced by ambient temperature. Despite advances in pain management, many patients continue to experience inadequate pain relief. This review aims to consolidate and critically evaluate the current evidence on the impact of ambient temperature on chronic pain conditions such as fibromyalgia (FM), multiple sclerosis (MS), complex regional pain syndrome (CRPS), and osteoarthritis (OA). RECENT FINDINGS: Patients with FM often report pain exacerbations due to temperature changes, with studies showing lower thresholds for heat and cold-induced pain compared to healthy controls. In MS, the Uhthoff phenomenon, characterized by temperature-induced neurological deterioration, underscores the significance of ambient temperature in pain management. CRPS patients exhibit heightened pain sensitivity to temperature changes, with both warm and cold stimuli potentially aggravating symptoms. OA patients frequently report increased pain and rigidity associated with lower temperatures and higher humidity. Understanding the mechanisms through which temperature influences pain can enhance pain management strategies. This review highlights the need for further research to elucidate these mechanisms and develop targeted interventions, ultimately improving the quality of life for individuals with chronic pain conditions.

Published
2025

4. Serratus Anterior Plane Block for Procedural Anesthesia for Pigtail Tube Thoracostomy: A Case Series

Author

Lopez, Edward, Sahni, Raghav, Cooper, Maxwell, and Shalaby, Michael

Subjects
chest tube, Tube Thoracostomy, serratus anterior plane block, ultrasound, regional anesthesia
Abstract

Introduction: Pneumothoraces are frequently treated by emergency physicians. Tube thoracostomy, the definitive treatment for a spontaneous pneumothorax, is associated with significant pain. Analgesia prior to tube thoracostomy often involves the administration of opioids and local infiltration of anesthetics. Thus far, regional anesthesia prior to pigtail tube thoracostomy in the emergency department (ED) has not been well described; it offers promise in alleviating pain associated with this procedure. Due to its ability to anesthetize all or most of the structures associated with tube thoracostomy—skin, serratus anterior muscles, intercostal muscles, and the parietal pleura—the serratus anterior plane block (SAPB) is a potentially promising fascial plane block prior to pigtail tube thoracostomy.Case Series: We present three cases of patients in the ED who received a SAPB and had nearly complete or complete anesthesia during pigtail tube thoracostomy.Conclusion: Pigtail tube thoracostomies are commonly performed in the ED and can be associated with significant pain despite a multimodal approach to pain management. The SAPB offers a safe and effective approach to anesthesia for patients in the ED undergoing a pigtail tube thoracostomy.

Published
2025

5. Lla-VAP: LSTM Ensemble of Llama and VAP for Turn-Taking Prediction

Author

Jeon, Hyunbae, Guintu, Frederic, and Sahni, Rayvant

Subjects
Computer Science - Sound, Computer Science - Computation and Language, Computer Science - Human-Computer Interaction, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Turn-taking prediction is the task of anticipating when the speaker in a conversation will yield their turn to another speaker to begin speaking. This project expands on existing strategies for turn-taking prediction by employing a multi-modal ensemble approach that integrates large language models (LLMs) and voice activity projection (VAP) models. By combining the linguistic capabilities of LLMs with the temporal precision of VAP models, we aim to improve the accuracy and efficiency of identifying TRPs in both scripted and unscripted conversational scenarios. Our methods are evaluated on the In-Conversation Corpus (ICC) and Coached Conversational Preference Elicitation (CCPE) datasets, highlighting the strengths and limitations of current models while proposing a potentially more robust framework for enhanced prediction.

Published
2024

6. An Experimental Study Of Netflix Use and the Effects of Autoplay on Watching Behaviors

Author

Schaffner, Brennan, Ulloa, Yaretzi, Sahni, Riya, Li, Jiatong, Cohen, Ava Kim, Messier, Natasha, Gao, Lan, and Chetty, Marshini

Subjects
Computer Science - Human-Computer Interaction
Abstract

Prior work on dark patterns, or manipulative online interfaces, suggests they have potentially detrimental effects on user autonomy. Dark pattern features, like those designed for attention capture, can potentially extend platform sessions beyond that users would have otherwise intended. Existing research, however, has not formally measured the quantitative effects of these features on user engagement in subscription video-on-demand platforms (SVODs). In this work, we conducted an experimental study with 76 Netflix users in the US to analyze the impact of a specific attention capture feature, autoplay, on key viewing metrics. We found that disabling autoplay on Netflix significantly reduced key content consumption aggregates, including average daily watching and average session length, partly filling the evidentiary gap regarding the empirical effects of dark pattern interfaces. We paired the experimental analysis with users' perceptions of autoplay and their viewing behaviors, finding that participants were split on whether the effects of autoplay outweigh its benefits, albeit without knowledge of the study findings. Our findings strengthen the broader argument that manipulative interface designs can and do affect users in potentially damaging ways, highlighting the continued need for considering user well-being and varied preferences in interface design., Comment: CSCW 2025 Preprint

Published
2024

7. SnapGen: Taming High-Resolution Text-to-Image Models for Mobile Devices with Efficient Architectures and Training

Author

Hu, Dongting, Chen, Jierun, Huang, Xijie, Coskun, Huseyin, Sahni, Arpit, Gupta, Aarush, Goyal, Anujraaj, Lahiri, Dishani, Singh, Rajesh, Idelbayev, Yerlan, Cao, Junli, Li, Yanyu, Cheng, Kwang-Ting, Chan, S. -H. Gary, Gong, Mingming, Tulyakov, Sergey, Kag, Anil, Xu, Yanwu, and Ren, Jian

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Existing text-to-image (T2I) diffusion models face several limitations, including large model sizes, slow runtime, and low-quality generation on mobile devices. This paper aims to address all of these challenges by developing an extremely small and fast T2I model that generates high-resolution and high-quality images on mobile platforms. We propose several techniques to achieve this goal. First, we systematically examine the design choices of the network architecture to reduce model parameters and latency, while ensuring high-quality generation. Second, to further improve generation quality, we employ cross-architecture knowledge distillation from a much larger model, using a multi-level approach to guide the training of our model from scratch. Third, we enable a few-step generation by integrating adversarial guidance with knowledge distillation. For the first time, our model SnapGen, demonstrates the generation of 1024x1024 px images on a mobile device around 1.4 seconds. On ImageNet-1K, our model, with only 372M parameters, achieves an FID of 2.06 for 256x256 px generation. On T2I benchmarks (i.e., GenEval and DPG-Bench), our model with merely 379M parameters, surpasses large-scale models with billions of parameters at a significantly smaller size (e.g., 7x smaller than SDXL, 14x smaller than IF-XL).

Published
2024

8. Identifying Core-Periphery Structures in Networks via Artificial Ants

Author

Ansari, Imran, Azhad, Qazi J, and Sahni, Niteesh

Subjects
Physics - Physics and Society, Computer Science - Social and Information Networks
Abstract

Core periphery structure represents a meso-scale structure in networks, characterized by a dense interconnection of core nodes and sparse connections among peripheral nodes. In this paper, we introduce an innovative approach for detecting core periphery structure, leveraging Artificial Ants. Core-periphery structures play a crucial role in elucidating network organization across various domains. The proposed approach, inspired by the foraging behavior of ants, employs artificial pheromone trails to iteratively construct and refine solutions, thereby eliminating the need for arbitrary partitions that often constrain traditional methods. Our method is applied to a diverse selection of real world networks including historical, literary, linguistic, sports, and animal social networks highlighting its adaptability and robustness. We systematically compare the performance of our approach against established core-periphery detection techniques, emphasizing differences in node classification between the core and periphery. Experimental results show that our method achieves superior flexibility and precision, offering marked improvements in the accuracy of core periphery structure detection.

Published
2024

9. Liger Kernel: Efficient Triton Kernels for LLM Training

Author

Hsu, Pin-Lun, Dai, Yun, Kothapalli, Vignesh, Song, Qingquan, Tang, Shao, Zhu, Siyu, Shimizu, Steven, Sahni, Shivam, Ning, Haowen, and Chen, Yanning

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Training Large Language Models (LLMs) efficiently at scale presents a formidable challenge, driven by their ever-increasing computational demands and the need for enhanced performance. In this work, we introduce Liger-Kernel, an open-sourced set of Triton kernels developed specifically for LLM training. With kernel optimization techniques like kernel operation fusing and input chunking, our kernels achieve on average a 20% increase in training throughput and a 60% reduction in GPU memory usage for popular LLMs compared to HuggingFace implementations. In addition, Liger-Kernel is designed with modularity, accessibility, and adaptability in mind, catering to both casual and expert users. Comprehensive benchmarks and integration tests are built in to ensure compatibility, performance, correctness, and convergence across diverse computing environments and model architectures. The source code is available under a permissive license at: github.com/linkedin/Liger-Kernel., Comment: 17 pages, 12 figures

Published
2024

10. Exploring the core-periphery and community structure in the financial networks through random matrix theory

Author

Pawanesh, Ansari, Imran, and Sahni, Niteesh

Subjects
Computer Science - Social and Information Networks, Physics - Physics and Society
Abstract

In finance, Random Matrix Theory (RMT) is an important tool for filtering out noise from large datasets, revealing true correlations among stocks, enhancing risk management and portfolio optimization. In this study, we use RMT to filter out noise from the full cross-correlation matrix of stock price returns for the NIFTY 200 and NIFTY 500 indices on the National Stock Exchange of India. In addition, we applied network theory tools to analyze market and sector modes as filtered correlation structures to study local interactions within financial networks. This allows us to study the very fundamental properties of networks, such as the core-periphery and the community structure of constructed networks over these filtered modes, and compare the results with the network constructed over the full cross-correlation matrix. The results suggest that the core-periphery structure is contained in the market mode, while the community structure is in the sector mode. Thus, both modes outperform the full cross-correlation in terms of capturing the essential respective structure of the network. Furthermore, we used these insights to build portfolios based on communities of the networks corresponding to the sector mode and the network corresponding to the full cross-correlation matrix. The results suggest that the portfolio constructed on the complete cross-correlation-based matrix performs better than the sector mode. These insights provide a greater understanding of RMT application in the financial market.

Published
2024

11. DynEx: Dynamic Code Synthesis with Structured Design Exploration for Accelerated Exploratory Programming

Author

Ma, Jenny, Sreedhar, Karthik, Liu, Vivian, Perez, Pedro Alejandro, Wang, Sitong, Sahni, Riya, and Chilton, Lydia B.

Subjects
Computer Science - Human-Computer Interaction
Abstract

Recent advancements in large language models have significantly expedited the process of generating front-end code. This allows users to rapidly prototype user interfaces and ideate through code, a process known as exploratory programming. However, existing LLM code generation tools focus more on technical implementation details rather than finding the right design given a particular problem. We present DynEx, an LLM-based method for design exploration in accelerated exploratory programming. DynEx introduces a technique to explore the design space through a structured Design Matrix before creating the prototype with a modular, stepwise approach to LLM code generation. Code is generated sequentially, and users can test and approve each step before moving onto the next. A user study of 10 experts found that DynEx increased design exploration and enabled the creation of more complex and varied prototypes compared to a Claude Artifact baseline. We conclude with a discussion of the implications of design exploration for exploratory programming., Comment: 27 pages, 9 figures

Published
2024

14. Introduction

Author

Sahni, Vaibhav, Bennett, Gabriel, Series Editor, Goodall, Emma, Series Editor, and Sahni, Vaibhav

Published
2025
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18. Outcomes after perioperative SARS-CoV-2 infection in patients with proximal femoral fractures: an international cohort study

Author

T Richards, S Shaikh, S Rehman, A Khan, J Shah, C Smith, A Brown, S Singh, A P Arnaud, A Young, D Bowen, P Patel, S Williams, J Dunn, J John, M Loubani, A Hainsworth, A Kolias, PJ Hutchinson, R Singh, S Sinha, S Shaw, J Edwards, S Mukherjee, AAB Jamjoom, A Singh, S Saeed, J Martin, S Smith, S Ross, M Mohan, P Hutchinson, G James, RDC Moon, P Brennan, A Williams, S Brown, A Ward, M Lee, K Thompson, S Ali, J Williams, S Reid, U Khan, J Lambert, A Smith, B Singh, M Hassan, N Sharma, J Reynolds, N Wright, T Williams, H Smith, M Ng, M Rahman, A Taylor, P Shah, D Saxena, J Evans, I Omar, M Ali, A Hanson, Z Li, R Andrade, P Cardoso, H Jeong, P Sharma, M Arrieta, J Clark, L Pearce, J McVeigh, V Sharma, B Kim, J Singh, S Newman, J Byrne, A Hassan, A Persad, A Gardner, H Liu, K Shah, I Hughes, S Davison, A Balakrishnan, K Patel, J Hall, S Mistry, J Parry, R Baumber, N McGrath, E Ross, R Mannion, S Murphy, FL Wright, A Rogers, B Rai, M Thomas, R Ribeiro, E Hamilton, J Teixeira, B Davidson, L Carvalho, R Garrido, A Puppo, A Guimarães, E Santos, M Kamal, M Denning, M Elhadi, J E Fitzgerald, D Miller, M Gowda, C Morris, A Phillips, H Yang, Y Zhang, N Machairas, A Fisher, A Kaufmann, A Aggarwal, L Hansen, M Otify, H Soleymani Majd, A Jones, M Rodrigues, S Sundar, C Jones, R Edmondson, A Sharkey, L Smith, G Williams, J Dunning, E Belcher, D Stavroulias, V Zamvar, M Patel, M Baker, R Evans, M Sherif, J Hopkins, R Mohammed, A Hill, H Jackson, G Jones, K George, J Dixon, A Tong, S Jallad, Deborah S Keller, A Pereira, L Elliott, D Ford, A Sermon, M Almond, Andrew Metcalfe, C Peluso, T White, S Shah, A Witek, Chetan Khatri, A Tiwari, T Lo, K Agarwal, C Sweeney, C Hart, T Holme, S Green, I Ahmed, A Sobti, C Anderson, N Modi, R Campbell, C Magee, M Mirza, D Jones, N Stylianides, X Luo, C Kang, J Ribeiro, L Kumar, J Diaz, A Bhalla, R Young, C Perkins, A James, A Walters, J Reid, R Pereira, C McDonald, A Aujayeb, K Jackson, M Allen, D Ghosh, M Chan, C Price, K Khan, R Moore, M Ibrahim, A Marchbank, M Silva, M Baig, J De Coster, J Castellanos, S Saxena, M Duque, E Li, E Martin, A Isik, J González, RJ Davies, B Smith, R Owen, K Lakhoo, M Rogers, MA Akhtar, K Mellor, S Agrawal, L Foster, G Harris, J McIntyre, M Garner, R West, R Cuthbert, D Johnson, H Gomes, C Roy, N Spencer, D Mehta, J Freedman, J Blair, K Rajput, K Williams, J Wall, A Soliman, F Chen, A Mokhtari, I Mohamed, J Pascoe, M Khalifa, R Das, A Lara, M Costa, A Mahmoud, K Roberts, J Lane, S Robertson, J P Evans, E Krishnan, I Haq, S Rogers, J Knowles, M Chowdhury, A Ghanbari, L Macdonald, S Powell, J Hunt, J Cornish, J Engel, S Page, I Blake, A Rolls, H Ross, D Simpson, J Hammond, A Goyal, K Parkins, A Desai, A Gaunt, A Salim, Y Yousef, A Schache, H Mohan, SR Brown, R Nair, M Flatman, J Lord, RJ Egan, R Harries, N Judkins, K Sugand, T Hine, J Luck, C Johnson, G Salerno, AW Phillips, R Houston, A Volpe, C Walker, C Steele, M Rela, C Barry, R Alves, L Ramsay, A Turnbull, A Daniele, C S Jones, P Gallagher, G Gradinariu, A Oliveira, C Hardie, H Ferguson, S Bhattacharya, E Davies, P Joshi, C Mellor, E Griffiths, A Bhangu, R Mahoney, F Kashora, G Ruiz, K Wong, G Hill, V Testa, S Ford, C Park, P Gomez, C Lopes, A Lázaro, A Shabana, A Agarwal, C Chung, C Politis, G Martin, E Chung, M Ismail, C Cunha, S Correia, I Santos, A Tang, A Robson, T Collier, G Baltazar, M Quintana, C English, M Ip, K Newton, J Kahn, C Tan, D Cheng, R Woods, M Ho, A ABBAS, A Henry, F Rivas, M Mohammed, N Parsons, T Board, S Madan, A Osorio, M Jarvis, M Hashem, A Egglestone, E Halliday, A Ridgway, G Gallo, J Gilliland, W Marx, R Shaw, A Mahmood, K Gohil, B Gallagher, D Alderson, A Karim, G D Stewart, G Peck, L Majkowski, J Carter, H Ishii, L HUMPHREYS, J Khan, S Abbott, C Newton, F Borghi, A Sud, K Bhatia, H Cao, V Vijay, L Sanderson, E Holler, N Hanna, D Ferguson, P Miranda, L Pickering, T Singhal, T Newman, K Ghosh, C Camacho, D Manning, C Lipede, R Clifford, S Higgs, C Menakaya, S Shankar, K Booth, M Abdalla, T Nelson, T Farrell, H Naseem, J Johnstone, A Wilkins, A Brunt, A Nogués, A Patience, D Jeevan, M Vatish, G Stables, S Adegbola, I Hunt, K Dickson, W Matthews, N Dunne, M Maher, G Faulkner, E Hernandez, R Sofat, K Sahnan, A Brunelli, M Raza, K Chui, C Brennan, P Vaughan, H Chu, R Hagger, ASD Liyanage, R Perkins, S Duff, C Gill, H Dean, S Bandyopadhyay, K Ragupathy, Y Cunningham, A Bateman, V Brown, B Ho, E Britton, H Ikram, R Hasan, A Colquhoun, S Handa, A Maqsood, M Caputo, J Torkington, G Fusai, N Hossain, DJ Lin, S Stefan, IR Daniels, D Pournaras, A Askari, P Nisar, S Moug, J Sagar, N Yassin, G Minto, Z Hamady, JR O'Neill, S Chowdhury, R Cresner, D Vimalachandran, FD Mcdermott, RP Jones, P Zerbib, L Sreedharan, S Wahed, SS Gisbertz, MI van Berge Henegouwen, R Preece, I Liew, S McCluney, D Watts, D Nehra, B Dean, D Chaudhry, L Ross, F Solari, S Chatterji, B Barmayehvar, S Lourenco, L Onos, F Mansour, A Radhakrishnan, M Varcada, M Richmond, I Hernández, A Spinelli, H Pham, J Shalhoub, F Wells, K Bevan, A Peckham-Cooper, N Campain, J Steinke, R Wilkin, K McEvoy, S Mastoridis, N Fine, J Bayer, Y Joshi, A Yener, S C McKay, NS Kalson, S Horvath, H Fu, A Parente, SE Lewis, Y Ahmad, G Seidel, M Dunstan, U von Oppell, J Vatish, H Hirsch, K Breen, C Dott, D Mathieu, J Hardie, K Aldridge, A Doorgakant, P Petrone, R Tansey, M El Amrani, C Branco, Y Viswanath, A Meagher, B Keeler, N Tewari, A Gabr, J Kinross, M Longhi, E M Harrison, P Daliya, P Asaad, F Langlands, N Misra, S Kristinsson, S Di Saverio, C Conso, H Roy, E Massie, L Masterson, D Baskaran, A Hannah, O Ismail, S URBAN, J Domenech, S Ranjit, L Massey, S Mannan, D Rutherford, F Colombo, R Kulkarni, D Kearney, Neil J Smart, G Bourke, D Shrestha, P Nankivell, O Breik, R Exley, D Zakai, AK Abou-Foul, P Naredla, R Vidya, G Mundy, H Marin, A E Ward, A Sudarsanam, W Singleton, M Ganau, F Moura, J Blanco, R Myatt, S Sousa, H Zahid, S Garrido, A Fell, E Caruana, D Nepogodiev, F Dhaif, B Bankhad-Kendall, H Kaafarani, C Bretherton, L Marais, K Siaw-Acheampong, B E Dawson, J C Glasbey, R R Gujjuri, E Heritage, S K Kamarajah, J M Keatley, S Lawday, G Pellino, J F F Simoes, I M Trout, M L Venn, R J W Wilkin, A O Ademuyiwa, E Al Ameer, O Alser, K M Augestad, B Bankhead-Kendall, R A Benson, S Chakrabortee, R Blanco-Colino, A Brar, A Minaya Bravo, K A Breen, I Lima Buarque, M F Cunha, G H Davidson, S Farik, M Fiore, G M A Gomes, C Halkias, I Lawani, H Lederhuber, S Leventoglu, M W Loffler, H Mashbari, D Mazingi, D Moszkowicz, J S Ng-Kamstra, S Metallidis, M Niquen, F Ntirenganya, O Outani, F Pata, T D Pinkney, P Pockney, D Radenkovic, A Ramos-De la Medina, A Schnitzbauer, S Shu, K Soreide, S Tabiri, P Townend, G Tsoulfas, G van Ramshorst, Mak JKC, F Tirotta, A Kisiel, LD Cato, AM Pathanki, A Chebaro, K Lecolle, S Truant, FR Pruvot, E Surmei, L Mattei, J Dudek, S El-Hasani, J Cuschieri, GH Davidson, RG Wade, H Elkadi, C Pompili, JR Burke, E Bagouri, Z Abual-Rub, S Munot, M Kowal, SC Winter, F Di Chiara, K Wallwork, A Qureishi, M Lami, S Sravanam, S Chidambaram, R Smillie, AV Shaw, C Cernei, D Jeyaretna, RJ Piper, E Duck, C Jelley, SC Tucker, G Bond-Smith, XL Griffin, GD Tebala, N Neal, TM Noton, H Ghattaura, OBF Risk, H Kharkar, C Verberne, A Senent-Boza, A Sánchez-Arteaga, I Benítez-Linero, F Manresa-Manresa, L Tallón-Aguilar, L Melero-Cortés, MR Fernández-Marín, VM Durán-Muñoz-Cruzado, I Ramallo-Solís, P Beltrán-Miranda, F Pareja-Ciuró, BT Antón-Eguía, AC Dawson, A Drane, F Oliva Mompean, J Gomez-Rosado, J Reguera-Rosal, J Valdes-Hernandez, L Capitan-Morales, del Toro Lopez, A Alanbuki, O Usman, AJ Beamish, D Bosanquet, D Magowan, H Nassa, G Mccabe, D Holroyd, NB Jamieson, NM Mariani, V Nicastro, D Motter, C Jenvey, T Minto, DR Sarma, C Godbole, W Carlos, A Khajuria, H Connolly, G Di Taranto, S Shanbhag, J Skillman, M Sait, H Al-omishy, B Heer, R Lunevicius, ARG Sheel, M Sundhu, AJA Santini, Fathelbab MSAT, KMA Hussein, QM Nunes, K Shahzad, Baig MMAS, JL Hughes, A Kattakayam, SB Shah, AL Clynch, N Georgopoulou, HM Sharples, AA Apampa, IC Nzenwa, D Podolsky, NL Coleman, MP Callahan, P Beak, I Gerogiannis, A Ebrahim, A Alwadiya, C Demetriou, E Grimley, E Theophilidou, E Ogden, FL Malcolm, G Davies-Jones, Ng JCK, N Elmaleh, Z Chia, J A'Court, A Konarski, R Talwar, P S Jambulingam, A Maity, C Hatzantonis, S Kudchadkar, N Cirocchi, CH Chan, H Eberbach, B Erdle, R Sandkamp, G Velmahos, LR Maurer, M El Moheb, A Gaitanidis, L Naar, MA Christensen, C Kapoen, K Langeveld, M El Hechi, B Main, T Maccabe, NS Blencowe, DP Fudulu, D Bhojwani, M Baquedano, F Rapetto, O Flannery, D Tadross, C Blundell, S Forlani, S Guha, CJ Kelty, G Chetty, G Lye, SP Balasubramanian, N Sureshkumar Shah, A Al-mukhtar, E Whitehall, A Giblin, A Adamec, J Konsten, M Van Heinsbergen, A Sou, J Jimeno Fraile, D Morales-Garcia, M Carrillo-Rivas, E Toledo Martínez, Pascual À, A Landaluce-olavarria, M Gonzalez De miguel, Fernández Gómez Cruzado L, E Begoña, D Lecumberri, A Calvo Rey, GM Prada hervella, L Dos Santos Carregal, MI Rodriguez Fernandez, M Freijeiro, S El Drubi Vega, J Van den Eynde, W Oosterlinck, R Van den Eynde, A Boeckxstaens, A Cordonnier, J Jaekers, M Miserez, M Galipienso Eri, JD Garcia Montesino, J Dellonder Frigolé, D Noriego Muñoz, V Lizzi, F Vovola, A Arminio, A Cotoia, AL Sarni, M Bekheit, BS Kamera, M Elhusseini, A Ahmeidat, W Cymes, G Mignot, J Agilinko, A Sgrò, MM Rashid, K Milne, KE Stewart, MSJ Wilson, K McGivern, BC Brown, B Wadham, IA Aneke, J Collis, H Warburton, DM Fountain, R Laurente, KV Sigamoney, M Dasa, Z Naqui, M Galhoum, MT Hasan, R Kalenderov, O Pathmanaban, R Chelva, K Subba, M Khalefa, F Hossain, T Moores, J Anthoney, O Emmerson, R Makin-Taylor, CS Ong, R Callan, O Bloom, G Chauhan, J Kaur, A Burahee, S Bleibleh, N Pigadas, D Snee, S Bhasin, A Crichton, A Habeebullah, AS Bodla, M Mondragon, V Dewan, MC Giuffrida, A Marano, S Palagi, S Di Maria Grimaldi, A Simonato, M D'Agruma, R Chiarpenello, L Pellegrino, F Maione, D Cianflocca, Pruiti Ciarello, G Giraudo, E Gelarda, E Dalmasso, A Abrate, V Ciriello, F Rosato, A Garnero, L Leotta, M Chiozza, G Anania, A Urbani, M Koleva Radica, P Carcoforo, M Portinari, M Sibilla, JE Archer, A Odeh, N Siddaiah, H Carmichael, CG Velopulos, RC McIntyre, TJ Schroeppel, EA Hennessy, L Zier, C Parmar, JM Muñoz Vives, CJ Gómez Díaz, CA Guariglia, C Soto Montesinos, L Sanchon, M Xicola Martínez, N Guàrdia, P Collera, R Diaz Del Gobbo, R Sanchez Jimenez, R Farre Font, R Flores Clotet, CEM Brathwaite, H Hakmi, AH Sohail, R Heckburn, D Townshend, N McLarty, A Shenfine, K Madhvani, M Hampton, AP Hormis, V Miu, K Sheridan, C Luney, MA Williams, A Alqallaf, A Ben-Sassi, R Crichton, J Sonksen, GR Layton, B Karki, S Pankhania, S Asher, A Folorunso, J Winyard, J Mangwani, BHB Babu, C Weerasinghe, M Ballabio, P Bisagni, T Armao, M Madonini, A Gagliano, P Pizzini, A Älgå, M Nordberg, G Sandblom, J El Kafsi, K Logishetty, A Saadya, R Midha, H Subbiah Ponniah, T Stockdale, T Bacarese-Hamilton, N Anjarwalla, D Marujo Henriques, R Hettige, C Baban, A Tenovici, F Anazor, SD King, S Kazzaz, S HKruijff, De Vries JPPM, PJ Steinkamp, PKC Jonker, WY Van der Plas, W Bierman, Y Janssen, ABJ Borgstein, D Enjuto, M Perez Gonzalez, P Díaz Peña, M Marqueta De Salas, P Martinez Pascual, L Rodríguez Gómez, R Garcés García, A Ramos Bonilla, N Herrera-Merino, P Fernández Bernabé, EP Cagigal Ortega, García de Castro Rubio E, I Cervera, MH Siddique, C Barmpagianni, A Basgaran, A Basha, V Okechukwu, A Bartsch, CA Leo, HK Ubhi, N Zafar, H Abdul-Jabar, F Mongelli, M Bernasconi, M Di Giuseppe, D Christoforidis, D La Regina, M Arigoni, A Al-Sukaini, S Mediratta, O Brown, M Boal, S Stanger, H Abdalaziz, J Constable, G Dovell, R Gopi reddy, A Dehal, HB Shah, GWV Cross, P Seyed-Safi, YW Smart, A Kuc, M Al-Yaseen, B Jayasankar, D Balasubramaniam, K Abdelsaid, N Mundkur, RE Soulsby, O Ryska, T Raymond, P Hawkin, G Kinnaman, I Sharma, K Freystaetter, JN Hadfield, A Hilley, S Arkani, M Youssef, I Shaikh, K Seebah, V Kouritas, D Chrastek, G Maryan, DF Gill, F Khatun, J Parakh, V Sarodaya, A Daadipour, KD Bosch, V Bashkirova, LS Dvorkin, VK Kalidindi, A Choudhry, M Espino Segura-Illa, G Sánchez Aniceto, AM Castaño-Leon, L Jimenez-Roldan, J Delgado Fernandez, A Pérez Núñez, A Lagares, D Garcia Perez, M Santas, I Paredes, O Esteban Sinovas, L Moreno-Gomez, E Rubio, V Vega, A Vivas Lopez, M Labalde Martinez, O García Villar, PM Pelaéz Torres, J Garcia Borda, E Ferrero Herrero, C Eiriz Fernandez, C Ojeda-Thies, JM Pardo Garcia, H Wynn Jones, H Divecha, C Whelton, E Powell-Smith, M Alotaibi, A Maashi, A Zowgar, M Alsakkaf, O Izquierdo, D Ventura, D Escobar, U Garcia de cortazar, Villamor Garcia, A Cioci, K Rakoczy, W Pavlis, R Saberi, A Khaleel, A Unnithan, K Memon, RR Pala Bhaskar, F Maqboul, F Kamel, A Al-Samaraee, R Madani, H Llaquet Bayo, N Duchateau, C De Gheldere, A Fayad, ML Wood, G Groot, I Hakami, C Boeker, J Mall, AF Haugstvedt, ML Jönsson, P Caja Vivancos, Villalabeitia Ateca, M Prieto Calvo, P Martin Playa, A Gainza, EJ Aragon Achig, A Rodriguez Fraga, Melchor Corcóstegui, G Mallabiabarrena Ormaechea, JJ Garcia Gutierrez, L Barbier, MA Pesántez Peralta, M Jiménez Jiménez, JA Municio Martín, J Gómez Suárez, G García Operé, LA Pascua Gómez, M Oñate Aguirre, A Fernandez-Colorado, M De la Rosa-Estadella, A Gasulla-Rodriguez, M Serrano-Martin, A Peig-Font, S Junca-Marti, M Juarez-Pomes, S Garrido-Ondono, L Blasco-Torres, M Molina-Corbacho, Y Maldonado-Sotoca, A Gasset-Teixidor, J Blasco-Moreu, V Turrado-Rodriguez, AM Lacy, FB de Lacy, X Morales, A Carreras-Castañer, P Torner, M Jornet-Gibert, M Balaguer-Castro, M Renau-Cerrillo, P Camacho-Carrasco, M Vives-Barquiel, B Campuzano-Bitterling, I Gracia, R Pujol-Muncunill, M Estaire Gómez, D Padilla-Valverde, S Sánchez-García, D Sanchez-Pelaez, E Jimenez Higuera, R Picón Rodríguez, Fernández Camuñas À, C Martínez-Pinedo, EP Garcia Santos, V Muñoz-Atienza, A Moreno Pérez, CA Cano, D Crego-Vita, M Huecas-Martinez, A Roselló Añón, MJ Sangüesa, JC Bernal-Sprekelsen, JC Catalá Bauset, P Renovell Ferrer, C Martínez Pérez, O Gil-Albarova, J Gilabert Estellés, K Aghababyan, R Rivas, J Escartin, JL Blas Laina, B Cros, Talal El-Abur, J Garcia Egea, C Yanez, JH Kauppila, E Sarjanoja, S Tzedakis, PA Bouche, S Gaujoux, D Gossot, A Seguin-Givelet, D Fuks, M Grigoroiu, R Sanchez Salas, X Cathelineau, P Macek, Y Barbé, F Rozet, E Barret, A Mombet, N Cathala, E Brian, F Zadegan, AJ Baldwin, E Gammeri, A Catton, S Marinos Kouris, J Pereca, M Kaushal, A Kler, V Reghuram, S Tezas, V Oktseloglou, F Mosley, MFI De La Cruz Monroy, P Bobak, S Ahad, E Lostis, GK Ambler, J Manara, M Doe, T Jichi, GD Stewart, J Ramzi, AA Singh, J Ashcroft, OJ Baker, P Coughlin, Durst AZED, A Abood, A Habeeb, VE Hudson, B Lamb, L Luke, S Mitrasinovic, Ngu AWT, S Waseem, F Georgiades, XS Tan, J Pushpa-rajah, I Abu-Nayla, S Rooney, E Irune, MHV Byrne, A Durrani, A Sethuraman Venkatesan, T Combellack, G Tahhan, M Kornaszewska, V Valtzoglou, I Deglurkar, M Koutentakis, Syed Nong Chek SAH, M Shinkwin, F Ayeni, H Tustin, M Bordenave, N Manu, N Eardley, OL Serevina, S Roy Mahapatra, K Mohankumar, I Khawaja, A Palepa, T Doulias, Y Premakumar, Y Jauhari, Z Koshnow, A Uberai, F Hirri, BM Stubbs, J Manickavasagam, S Dalgleish, R Kanitkar, CJ Payne, Ng CE, DE Henshall, T Drake, EM Harrison, A Tambyraja, RJE Skipworth, G Linder, R McGregor, J Mayes, R Pasricha, A Razik, S Thrumurthy, D Howden, Z Baxter, L Osagie, M Bence, GE Fowler, N Rajaretnam, A Goubran, JS McGrath, JRA Phillips, DA Raptis, JM Pollok, F Soggiu, S Xyda, C Hidalgo Salinas, H Tzerbinis, T Pissanou, R Mirnezami, N Angamuthu, T Shakir, H Capitelli-McMahon, L Hitchman, A Andronic, A Aboelkassem Ibrahim, J Totty, S Tayeh, T Chase, J Ayorinde, T Cuming, A Trompeter, C Hing, P Tsinaslanidis, MW Benjamin, A Leyte, J Smelt, G Santhirakumaran, A Labib, O Lyons, S Onida, KM Sarraf, S Erridge, S Yalamanchili, A Abuown, D Davenport, S Wheatstone, SM Andreani, MF Bath, A Sahni, L Rigueros Springford, C Sohrabi, J Bacarese-Hamilton, FG Taylor, P Patki, C Tanabalan, ME Alexander, CJ Smart, L Abdeh, M Zeiton, R Advani, S Nikolaou, T Oni, N Ilahi, K Ballantyne, Z Woodward, R Merh, B Robertson-Smith, P Ameerally, JG Finch, C Gnanachandran, I Pop, D Dass, G Thiruchandran, Toh SKC, A Allana, C Bellis, O Babawale, YC Phan, U Lokman, T Koc, L Duggleby, S Shamoon, H Clancy, A Mansuri, A Thakrar, L Wickramarachchi, S Sivayoganathan, E Karam, HV Colvin, A Badran, A Cadersa, A Cumpstey, R Aftab, F Wensley, V Morrison-Jones, GK Sekhon, H Shields, Z Shakoor, T Talbot, A Alzetani, J Rooney, M Rudic, A Aladeojebi, M Kitchen, R Lefroy, P Nanjaiah, AD Rajgor, RJ Scurrah, LJ Watson, T Royle, B Steel, Luk ACO, VG Thiruvasagam, W Marlow, C Konstantinou, D Yershov, A Denning, E Mangos, T Nambirajan, I Flindall, V Mahendran, J De Marchi, NF Davis, A Picciariello, V Papagni, DF Altomare, S Granieri, C Cotsoglou, A Cabeleira, P Serralheiro, T Teles, C Canhoto, J Simões, AC Almeida, O Nogueira, R Athayde Nemésio, MJ Amaral, A Valente da Costa, R Martins, P Guerreiro, A Ruivo, D Breda, JM Oliveira, AL De Oliveira Lopez, M Colino, J De Barros, AP Soares, H Morais, T Revez, MI Manso, JC Domingues, P Henriques, Cardoso N Ribeiro VI, G Martins dos Santos, M Peralta Ferreira, J Ascensão, B Costeira, L Rio Rodrigues, M Sousa Fernandes, P Azevedo, I Lourenço, G Mendinhos, A Nobre Pinto, H Taflin, H Abdou, L O'Meara, Z Cooper, SA Hirji, BU Okafor, V Roxo, CP Raut, JS Jolissaint, DA Mahvi, C Reinke, S Merola, A Ssentongo, P Ssentongo, Oh JS, J Hazelton, J Maines, N Gusani, RCG Martin, N Bhutiani, R Choron, F Soliman, MD E Dauer, E Renza-Stingone, E Gokcen, E Kropf, H Sufrin, J Sewards, J Poggio, K Sanserino, L Rae, M Philp, M Metro, P McNelis, R Petrov, T Pazionis, DB Lumenta, SP Nischwitz, E Richtig, M Pau, P Srekl-Filzmaier, N Eibinger, B Michelitsch, M Fediuk, A Papinutti, TU Cohnert, E Kantor, J Kahiu, S Hosny, A Sultana, M Taggarsi, L Vitone, OP Vaz, I Sarantitis, S Timbrell, A Shugaba, GP Jones, SS Tripathi, MS Greenhalgh, H Emerson, K Vejsbjerg, W McCormick, K Singisetti, Y Aawsaj, R Vanker, M Ghobrial, S Kanthasamy, H Fawi, M Awadallah, J Cheung, S Tingle, F Abbadessa, A Sachdeva, CD Chan, I McPherson, F Mahmoud Ali, S Pandanaboyana, T Grainger, S Nandhra, N Dawe, C McCaffer, J Riches, J Moir, H Elamin Ahmed, C Saleh, RM Koshy, LJ Rogers, PL Labib, N Hope, K Emslie, P Panahi, E Clough, I Enemosah, J Natale, N Raza, JI Webb, M Antar, J Noel, R Nunn, F Eriberto, R Tanna, S Lodhia, C Osório, J Antunes, P Balau, and M Godinho

Subjects
Medicine
Abstract

Objectives Studies have demonstrated high rates of mortality in people with proximal femoral fracture and SARS-CoV-2, but there is limited published data on the factors that influence mortality for clinicians to make informed treatment decisions. This study aims to report the 30-day mortality associated with perioperative infection of patients undergoing surgery for proximal femoral fractures and to examine the factors that influence mortality in a multivariate analysis.Setting Prospective, international, multicentre, observational cohort study.Participants Patients undergoing any operation for a proximal femoral fracture from 1 February to 30 April 2020 and with perioperative SARS-CoV-2 infection (either 7 days prior or 30-day postoperative).Primary outcome 30-day mortality. Multivariate modelling was performed to identify factors associated with 30-day mortality.Results This study reports included 1063 patients from 174 hospitals in 19 countries. Overall 30-day mortality was 29.4% (313/1063). In an adjusted model, 30-day mortality was associated with male gender (OR 2.29, 95% CI 1.68 to 3.13, p80 years (OR 1.60, 95% CI 1.1 to 2.31, p=0.013), preoperative diagnosis of dementia (OR 1.57, 95% CI 1.15 to 2.16, p=0.005), kidney disease (OR 1.73, 95% CI 1.18 to 2.55, p=0.005) and congestive heart failure (OR 1.62, 95% CI 1.06 to 2.48, p=0.025). Mortality at 30 days was lower in patients with a preoperative diagnosis of SARS-CoV-2 (OR 0.6, 95% CI 0.6 (0.42 to 0.85), p=0.004). There was no difference in mortality in patients with an increase to delay in surgery (p=0.220) or type of anaesthetic given (p=0.787).Conclusions Patients undergoing surgery for a proximal femoral fracture with a perioperative infection of SARS-CoV-2 have a high rate of mortality. This study would support the need for providing these patients with individualised medical and anaesthetic care, including medical optimisation before theatre. Careful preoperative counselling is needed for those with a proximal femoral fracture and SARS-CoV-2, especially those in the highest risk groups.Trial registration number NCT04323644

Published
2021
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23. Linking the Path to Zero Hunger: Analysing Sustainable Development Goals Within the Context of Global Sustainability

Author

Sharma, Smita, Sahni, Jolly, Joy, Rosewine, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Lu, Xinzheng, Series Editor, Mansour, Yasser, editor, Subramaniam, Umashankar, editor, Mustaffa, Zahiraniza, editor, Abdelhadi, Abdelhakim, editor, Al-Atroush, Mohamed, editor, and Abowardah, Eman, editor

Published
2025
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24. Uncovering the hidden core-periphery structure in hyperbolic networks

Author

Ansari, Imran, Yadav, Pawanesh, and Sahni, Niteesh

Subjects
Physics - Physics and Society, Computer Science - Artificial Intelligence
Abstract

The hyperbolic network models exhibit very fundamental and essential features, like small-worldness, scale-freeness, high-clustering coefficient, and community structure. In this paper, we comprehensively explore the presence of an important feature, the core-periphery structure, in the hyperbolic network models, which is often exhibited by real-world networks. We focused on well-known hyperbolic models such as popularity-similarity optimization model (PSO) and S1/H2 models and studied core-periphery structures using a well-established method that is based on standard random walk Markov chain model. The observed core-periphery centralization values indicate that the core-periphery structure can be very pronounced under certain conditions. We also validate our findings by statistically testing for the significance of the observed core-periphery structure in the network geometry. This study extends network science and reveals core-periphery insights applicable to various domains, enhancing network performance and resiliency in transportation and information systems.

Published
2024

25. Multi-Source Coflow Scheduling in Collaborative Edge Computing with Multihop Network

Author

Sahni, Yuvraj, Cao, Jiannong, Yang, Lei, and Wang, Shengwei

Subjects
Computer Science - Networking and Internet Architecture, Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Collaborative edge computing has become a popular paradigm where edge devices collaborate by sharing resources. Data dissemination is a fundamental problem in CEC to decide what data is transmitted from which device and how. Existing works on data dissemination have not focused on coflow scheduling in CEC, which involves deciding the order of flows within and across coflows at network links. Coflow implies a set of parallel flows with a shared objective. The existing works on coflow scheduling in data centers usually assume a non-blocking switch and do not consider congestion at different links in the multi-hop path in CEC, leading to increased coflow completion time (CCT). Furthermore, existing works do not consider multiple flow sources that cannot be ignored, as data can have duplicate copies at different edge devices. This work formulates the multi-source coflow scheduling problem in CEC, which includes jointly deciding the source and flow ordering for multiple coflows to minimize the sum of CCT. This problem is shown to be NP-hard and challenging as each flow can have multiple dependent conflicts at multiple links. We propose a source and coflow-aware search and adjust (SCASA) heuristic that first provides an initial solution considering the coflow characteristics. SCASA further improves the initial solution using the source search and adjust heuristic by leveraging the knowledge of both coflows and network congestion at links. Evaluation done using simulation experiments shows that SCASA leads to up to 83% reduction in the sum of CCT compared to benchmarks without a joint solution.

Published
2024

26. SAM3D: Zero-Shot Semi-Automatic Segmentation in 3D Medical Images with the Segment Anything Model

Author

Chan, Trevor J., Sahni, Aarush, Fang, Yijin, Li, Jie, Luthra, Alisha, Pouch, Alison, and Rajapakse, Chamith S.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

We introduce SAM3D, a new approach to semi-automatic zero-shot segmentation of 3D images building on the existing Segment Anything Model. We achieve fast and accurate segmentations in 3D images with a four-step strategy involving: user prompting with 3D polylines, volume slicing along multiple axes, slice-wide inference with a pretrained model, and recomposition and refinement in 3D. We evaluated SAM3D performance qualitatively on an array of imaging modalities and anatomical structures and quantify performance for specific structures in abdominal pelvic CT and brain MRI. Notably, our method achieves good performance with zero model training or finetuning, making it particularly useful for tasks with a scarcity of preexisting labeled data. By enabling users to create 3D segmentations of unseen data quickly and with dramatically reduced manual input, these methods have the potential to aid surgical planning and education, diagnostic imaging, and scientific research.

Published
2024

27. A novel portfolio construction strategy based on the core-periphery profile of stocks

Author

Ansari, Imran, Sharma, Charu, Agrawal, Akshay, and Sahni, Niteesh

Subjects
Quantitative Finance - Statistical Finance
Abstract

This paper highlights the significance of mesoscale structures, particularly the core-periphery structure, in financial networks for portfolio optimization. We build portfolios of stocks belonging to the periphery part of the Planar maximally filtered subgraphs of the underlying network of stocks created from Pearson correlations between pairs of stocks and compare its performance with some well-known strategies of Pozzi et. al. hinging around the local indices of centrality in terms of the Sharpe ratio, returns and standard deviation. Our findings reveal that these portfolios consistently outperform traditional strategies and further the core-periphery profile obtained is statistically significant across time periods. These empirical findings substantiate the efficacy of using the core-periphery profile of the stock market network for both inter-day and intraday trading and provide valuable insights for investors seeking better returns.

Published
2024

28. Exploiting the geometry of heterogeneous networks: A case study of the Indian stock market

Author

Pawanesh, Pawanesh, Sharma, Charu, and Sahni, Niteesh

Subjects
Physics - Physics and Society, Computer Science - Machine Learning, Quantitative Finance - Statistical Finance
Abstract

In this study, we model the Indian stock market as heterogenous scale free network, which is then embedded in a two dimensional hyperbolic space through a machine learning based technique called as coalescent embedding. This allows us to apply the hyperbolic kmeans algorithm on the Poincare disc and the clusters so obtained resemble the original network communities more closely than the clusters obtained via Euclidean kmeans on the basis of well-known measures normalised mutual information and adjusted mutual information. Through this, we are able to clearly distinguish between periods of market stability and volatility by applying non-parametric statistical tests with a significance level of 0.05 to geometric measures namely hyperbolic distance and hyperbolic shortest path distance. After that, we are able to spot significant market change early by leveraging the Bollinger Band analysis on the time series of modularity in the embedded networks of each window. Finally, the radial distance and the Equidistance Angular coordinates help in visualizing the embedded network in the Poincare disc and it is seen that specific market sectors cluster together., Comment: 39 pages, 11 figures

Published
2024

29. Deciphering the impact of genomic variation on function

Author

Engreitz, Jesse M, Lawson, Heather A, Singh, Harinder, Starita, Lea M, Hon, Gary C, Carter, Hannah, Sahni, Nidhi, Reddy, Timothy E, Lin, Xihong, Li, Yun, Munshi, Nikhil V, Chahrour, Maria H, Boyle, Alan P, Hitz, Benjamin C, Mortazavi, Ali, Craven, Mark, Mohlke, Karen L, Pinello, Luca, Wang, Ting, Bly, Zo, Calluori, Stephanie, Gilchrist, Daniel A, Hutter, Carolyn M, Morris, Stephanie A, and Samer, Ella K

Subjects
Biochemistry and Cell Biology, Bioinformatics and Computational Biology, Genetics, Biological Sciences, Human Genome, Biotechnology, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Generic health relevance, Humans, Cells, Computer Simulation, Gene Expression Regulation, Gene Regulatory Networks, Genetic Association Studies, Genetic Predisposition to Disease, Genetic Variation, Genome, Human, Genomics, Models, Genetic, Phenotype, Protein Interaction Maps, Single-Cell Analysis, IGVF Consortium, General Science & Technology
Abstract

Our genomes influence nearly every aspect of human biology-from molecular and cellular functions to phenotypes in health and disease. Studying the differences in DNA sequence between individuals (genomic variation) could reveal previously unknown mechanisms of human biology, uncover the basis of genetic predispositions to diseases, and guide the development of new diagnostic tools and therapeutic agents. Yet, understanding how genomic variation alters genome function to influence phenotype has proved challenging. To unlock these insights, we need a systematic and comprehensive catalogue of genome function and the molecular and cellular effects of genomic variants. Towards this goal, the Impact of Genomic Variation on Function (IGVF) Consortium will combine approaches in single-cell mapping, genomic perturbations and predictive modelling to investigate the relationships among genomic variation, genome function and phenotypes. IGVF will create maps across hundreds of cell types and states describing how coding variants alter protein activity, how noncoding variants change the regulation of gene expression, and how such effects connect through gene-regulatory and protein-interaction networks. These experimental data, computational predictions and accompanying standards and pipelines will be integrated into an open resource that will catalyse community efforts to explore how our genomes influence biology and disease across populations.

Published
2024

30. Predatory journals: what can we do to protect their prey?

Author

Laine, Christine, Babski, Dianne, Bachelet, Vivienne C., Barnighausen, Till W., Baethge, Christopher, Bibbins-Domingo, Kirsten, Frizelle, Frank, Gollogly, Laragh, Kleinert, Sabine, Loder, Elizabeth, Monteiro, Joao, Rubin, Eric J., Sahni, Peush, Wee, Christina C., Yoo, Jin-Hong, and Zakhama, Lilia

Subjects
Publishing industry, Financial misrepresentation, Financial misrepresentations
Abstract

Predatory or pseudo journals can endanger the public by facilitating the dissemination of unvetted and fraudulent health information. Their deceptive practices also harm authors, academic institutions, and legitimate journals and [...]

Published
2025
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40. Resource-efficient Parallel Split Learning in Heterogeneous Edge Computing

Author

Zhang, Mingjin, Cao, Jiannong, Sahni, Yuvraj, Chen, Xiangchun, and Jiang, Shan

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Edge AI has been recently proposed to facilitate the training and deployment of Deep Neural Network (DNN) models in proximity to the sources of data. To enable the training of large models on resource-constraint edge devices and protect data privacy, parallel split learning is becoming a practical and popular approach. However, current parallel split learning neglects the resource heterogeneity of edge devices, which may lead to the straggler issue. In this paper, we propose EdgeSplit, a novel parallel split learning framework to better accelerate distributed model training on heterogeneous and resource-constraint edge devices. EdgeSplit enhances the efficiency of model training on less powerful edge devices by adaptively segmenting the model into varying depths. Our approach focuses on reducing total training time by formulating and solving a task scheduling problem, which determines the most efficient model partition points and bandwidth allocation for each device. We employ a straightforward yet effective alternating algorithm for this purpose. Comprehensive tests conducted with a range of DNN models and datasets demonstrate that EdgeSplit not only facilitates the training of large models on resource-restricted edge devices but also surpasses existing baselines in performance., Comment: Accepted by International Conference on Computing, Networking and Communications (ICNC 2024)

Published
2024

41. Digital Twin-assisted Reinforcement Learning for Resource-aware Microservice Offloading in Edge Computing

Author

Chen, Xiangchun, Cao, Jiannong, Liang, Zhixuan, Sahni, Yuvraj, and Zhang, Mingjin

Subjects
Computer Science - Networking and Internet Architecture, Computer Science - Machine Learning
Abstract

Collaborative edge computing (CEC) has emerged as a promising paradigm, enabling edge nodes to collaborate and execute microservices from end devices. Microservice offloading, a fundamentally important problem, decides when and where microservices are executed upon the arrival of services. However, the dynamic nature of the real-world CEC environment often leads to inefficient microservice offloading strategies, resulting in underutilized resources and network congestion. To address this challenge, we formulate an online joint microservice offloading and bandwidth allocation problem, JMOBA, to minimize the average completion time of services. In this paper, we introduce a novel microservice offloading algorithm, DTDRLMO, which leverages deep reinforcement learning (DRL) and digital twin technology. Specifically, we employ digital twin techniques to predict and adapt to changing edge node loads and network conditions of CEC in real-time. Furthermore, this approach enables the generation of an efficient offloading plan, selecting the most suitable edge node for each microservice. Simulation results on real-world and synthetic datasets demonstrate that DTDRLMO outperforms heuristic and learning-based methods in average service completion time., Comment: 9 pages, 5 figures

Published
2024
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42. New models of Quintessential Inflation featuring plateau and hilltop potentials

Author

Mishra, Swagat S. and Sahni, Varun

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology, High Energy Physics - Phenomenology, High Energy Physics - Theory
Abstract

We introduce a new class of hilltop and plateau potentials which can successfully unify inflation and dark energy resulting in Quintessential Inflation (QI). Interestingly these new potentials are related through an inverse transformation. Namely, if $V(\phi) = V_0 \, v(\phi)$ is a plateau potential then the inverse potential $V(\phi) = V_0 \, \left[v(\phi)\right]^{-1}$ describes hilltop QI. A simple example is provided by the KKLT-inspired potential $v(\phi) = \left\lbrack \frac{M^{2n} + \phi^{2n}}{N^{2n} + \phi^{2n}}\right\rbrack \,$. When $M/N \ll 1$ this potential describes plateau QI, while its inverse, $\left[v(\phi)\right]^{-1}$ describes hilltop QI. Other simple models of QI arise for the class of potentials $V(\phi) \sim \exp\left\lbrack\mp f(\phi)\right\rbrack$, where the $-$ ($+$) sign is associated with a plateau (hilltop). A key feature of this new class of QI models is the near absence of small parameters which are usually associated with the presence of dark energy. A forecast for the gravitational wave background generated in these models is provided., Comment: 43 pages, 14 figures

Published
2024

43. Cu$_2$ZnSiTe$_4$: A potential thermoelectric material with promising electronic transport

Author

Sharma, Himanshu, Sahni, Bhawna, Saha-Dasgupta, Tanusri, and Alam, Aftab

Subjects
Condensed Matter - Materials Science
Abstract

Transition metal-based quaternary chalcogenides have gathered immense attention for various renewable energy applications including thermoelectrics (TE). While low-symmetry and complex structure help to achieve low thermal conductivity, the TE power factor and hence the figure of merit (ZT) remains low which hinders to promote these class of materials for future TE applications. Here, we investigated the TE properties of a new system, Cu$_2$ZnSiTe$_4$, with improved electronic transport using first-principles calculation. The presence of heavy chalcogen like Te, helps to achieve a relatively low bandgap (0.58 eV). This, together with unique electronic band topology, leads to a promising value of power-factor of 3.95(n-type) and 3.06(p-type) mWm$^{-1}$K$^{-2}$ at 900 K. Te atoms also play a crucial role in mixing the optical and acoustic phonon branches which, in turn, are responsible for reduced lattice thermal conductivity ($\sim$0.7 Wm$^{-1}$K$^{-1}$ at high temperature). Though the thermal conductivity is not appreciably low, the electronic transport properties (power factor) are quite favorable to yield promising TE figure of merit (ZT $\sim$2.67 (n-type) and $\sim$2.11 (p-type) at 900 K). We propose Cu$_2$ZnSiTe$_4$ to be a potential candidate for TE applications, and believe to attract future experimental/theoretical studies.

Published
2024

45. Durability of Original Monovalent mRNA Vaccine Effectiveness Against COVID-19 Omicron-Associated Hospitalization in Children and Adolescents - United States, 2021-2023.

Author

Zambrano, Laura, Newhams, Margaret, Simeone, Regina, Payne, Amanda, Wu, Michael, Orzel-Lockwood, Amber, Halasa, Natasha, Calixte, Jemima, Pannaraj, Pia, Mongkolrattanothai, Kanokporn, Boom, Julie, Sahni, Leila, Kamidani, Satoshi, Chiotos, Kathleen, Cameron, Melissa, Maddux, Aline, Irby, Katherine, Schuster, Jennifer, Mack, Elizabeth, Biggs, Austin, Coates, Bria, Michelson, Kelly, Bline, Katherine, Nofziger, Ryan, Crandall, Hillary, Hobbs, Charlotte, Gertz, Shira, Heidemann, Sabrina, Bradford, Tamara, Walker, Tracie, Schwartz, Stephanie, Staat, Mary, Bhumbra, Samina, Hume, Janet, Kong, Michele, Stockwell, Melissa, Connors, Thomas, Cullimore, Melissa, Flori, Heidi, Levy, Emily, Cvijanovich, Natalie, Zinter, Matt, Maamari, Mia, Bowens, Cindy, Zerr, Danielle, Guzman-Cottrill, Judith, Gonzalez, Ivan, Campbell, Angela, and Randolph, Adrienne

Subjects
Humans, Adolescent, Child, United States, COVID-19 Vaccines, COVID-19, mRNA Vaccines, Vaccine Efficacy, SARS-CoV-2, Hospitalization, RNA, Messenger
Abstract

Pediatric COVID-19 vaccination is effective in preventing COVID-19-related hospitalization, but duration of protection of the original monovalent vaccine during SARS-CoV-2 Omicron predominance merits evaluation, particularly given low coverage with updated COVID-19 vaccines. During December 19, 2021-October 29, 2023, the Overcoming COVID-19 Network evaluated vaccine effectiveness (VE) of ≥2 original monovalent COVID-19 mRNA vaccine doses against COVID-19-related hospitalization and critical illness among U.S. children and adolescents aged 5-18 years, using a case-control design. Too few children and adolescents received bivalent or updated monovalent vaccines to separately evaluate their effectiveness. Most case-patients (persons with a positive SARS-CoV-2 test result) were unvaccinated, despite the high frequency of reported underlying conditions associated with severe COVID-19. VE of the original monovalent vaccine against COVID-19-related hospitalizations was 52% (95% CI = 33%-66%) when the most recent dose was administered

Published
2024

46. Gene expression analyses of the calmodulin binding protein 60 family under water stress conditions in rice

Author

Bishun Deo Prasad, Ramakant, Sangita Sahni, Diksha Kumari, Pankaj Kumar, Sanjay J. Jambhulkar, Saud Alamri, and Muhammad Faheem Adil

Subjects
Rice (Oryza sativa L.), Rice Calmodulin-binding protein 60 (OsCBP60), Calcium/calmodulin (Ca2+/CaM), Reproductive drought, Submergence stress, Medicine, Science
Abstract

Abstract Plants have developed elaborate mechanisms for perceiving extracellular stimuli and subsequently activating defense reactions through a multifaceted interaction of signaling cascades. Calcium ion (Ca²⁺), an essential and ubiquitous intracellular second messenger molecules, whose concentration ([Ca2+]cyt) has been observed to rise in response to numerous environmental stresses. The calcium/calmodulin (Ca²⁺/CaM) complex triggers apposite cellular responses through modifying the activities of a varied array of CaM-binding proteins (CBPs). Among CBPs, the CBP60 gene family has been identified as key regulators of stress responses in several crop species. Recently, we have demonstrated the expanded and diversified role of OsCBP60 in rice against devastating pathogens. Here, we analyzed the diversified roles of OsCBP60s in two major abiotic stresses, namely reproductive drought and submergence stress. OsCBP60bcd-2 and OsCBP60g-1/OsSARD1 were consistently upregulated during reproductive drought stress in rice. However, OsCBP60g-5 and OsCBP60g-6 were steadily up-regulated under submergence stress in rice. Interestingly, OsCBP60g-4 was consistently upregulated in both abiotic stresses, except on the third day of reproductive drought. The differential expression of OsCBP60s under water stress highlights the importance of further studying these genes as potential targets for enhancing stress resilience in rice.

Published
2025
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47. Flavored Tobacco Products (FTPs): A New-generation Gimmick in the Indian Market—A Narrative Review

Author

Heena Sahni, Hunny Sharma, Swati Verma, Abhilasha Tiwari, Aditi Sharma, and Harsha Malhotra

Subjects
adolescent health, flavoring agents, menthol, smoking, smoking cessation, tobacco, Medicine
Abstract

Flavored tobacco products (FTPs) have gained global popularity but are associated with significant health concerns. These products, which include flavored cigarettes, cigars, e-cigarettes, hookahs, and nicotine dissolvable, come in a range of different flavors. For example, cigarettes come in a variety of flavors, including menthol, alcohol, spices, and herbs, which are more appealing to young adults, and fruit or candy, which are more appealing to kids. Despite the perceived safety of these flavorings for consumption, their toxicity remains largely unknown. Additionally, the deliberate promotion of FTPs by the tobacco industry in emerging nations such as India has hindered tobacco control efforts. The current review seeks to offer a thorough examination of additives used in tobacco, the various flavors found in emerging tobacco products, patterns of consumption, strategies employed in marketing, and the necessity for regulating these emerging tobacco products. A systematic review methodology was employed for this narrative review using relevant medical subject headings (MeSH) terms. The literature search was conducted between March 2022 and March 2023, utilizing databases such as PubMed, Scopus, Google Scholar, guidelines, advisory, survey reports, factsheets, editorial, communication, and news related to topic of interest. Pertinent articles were selected based on specific inclusion and exclusion criteria. The synthesized results illuminate the prevalence and usage of tobacco products with flavors in the market, effectively fulfilling the research objectives. Moreover, in addition to fulfilling the research objectives, the synthesized results offer valuable perspectives on how FTPs influence patterns of tobacco use, particularly among the younger population. These findings underscore the need for effective regulations and guidelines to curb the appeal and consumption of FTPs, ultimately reducing the prevalence of smoking-related disorders and promoting public health.

Published
2025
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48. Serratus Anterior Plane Block for Procedural Anesthesia for Pigtail Tube Thoracostomy: A Case Series

Author

Edward Lopez, Raghav Sahni, Maxwell Cooper, and Michael Shalaby

Subjects
Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

Introduction: Pneumothoraces are frequently treated by emergency physicians. Tube thoracostomy, the definitive treatment for a spontaneous pneumothorax, is associated with significant pain. Analgesia prior to tube thoracostomy often involves the administration of opioids and local infiltration of anesthetics. Thus far, regional anesthesia prior to pigtail tube thoracostomy in the emergency department (ED) has not been well described; it offers promise in alleviating pain associated with this procedure. Due to its ability to anesthetize all or most of the structures associated with tube thoracostomy—skin, serratus anterior muscles, intercostal muscles, and the parietal pleura—the serratus anterior plane block (SAPB) is a potentially promising fascial plane block prior to pigtail tube thoracostomy. Case Series: We present three cases of patients in the ED who received a SAPB and had nearly complete or complete anesthesia during pigtail tube thoracostomy. Conclusion: Pigtail tube thoracostomies are commonly performed in the ED and can be associated with significant pain despite a multimodal approach to pain management. The SAPB offers a safe and effective approach to anesthesia for patients in the ED undergoing a pigtail tube thoracostomy.

Published
2025
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49. Silymarin: a promising modulator of apoptosis and survival signaling in cancer

Author

Ujjawal Sharma, Praveen Kumar Sahni, Bunty Sharma, Madhu Gupta, Damandeep Kaur, Darin Mansor Mathkor, Shafiul Haque, Sabiha Khatoon, Hardeep Singh Tuli, Astha Mishra, and Faraz Ahmad

Subjects
Anticancer, Apoptosis, Natural compounds, Silymarin, Therapeutics, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Cancer, one of the deadliest diseases, has remained the epicenter of biological research for more than seven decades. Yet all the efforts for a perfect therapeutic cure come with certain limitations. The use of medicinal plants and their phytochemicals as therapeutics has received much attention in recent years. Silymarin, a polyphenolic flavonoid with a variety of anti-cancerous properties, was isolated from the plant Silybum marianum. The present review centres on the function of silymarin in controlling important signalling pathways related to apoptosis and survival, such as the JAK/STAT pathway, PI3K/Akt/mTOR, Bcl-2/Bax, and Fas/FasL. It is emphasised that silymarin's capacity to target these pathways is a key mechanism behind its anticancer effects against a variety of malignancies. By upregulating pro-apoptotic and downregulating anti-apoptotic proteins, silymarin controls a series of events that result in tumor suppression and cell death in a variety of cancer types. The low bioavailability and limited therapeutic efficacy of silymarin are improved by the application of various nano-delivery systems. As efficient carriers, liposomes, polymeric micelles, lipid- and metal-based nanoparticles, increase the solubility and distribution of silymarin in target tissues. Lastly, a number of preclinical studies that provide a basis for upcoming therapeutic interventions are highlighted in the review, providing encouraging directions for additional research and advancement.

Published
2025
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50. Multifaceted approach to evacuating multi-level premacular hemorrhage in a case of suspected Valsalva retinopathy – a case report

Author

B. R. Smitha, Naman Sahni, Priyanka Gandhi, Rupal Kathare, Vishma Prabhu, Prathiba Hande, Jay Chhablani, and Ramesh Venkatesh

Subjects
Yag laser membranotomy, Outcome, sub-ILM hemorrhage, Valsalva retinopathy, Vitrectomy, Ophthalmology, RE1-994
Abstract

Abstract Background Accurate localization of premacular hemorrhages (PMHs) is crucial as treatment strategies vary significantly based on whether the hemorrhage resides within the vitreous gel, subhyaloid space, or beneath the internal limiting membrane (ILM). This report outlines the clinical features, diagnostic findings, and treatment outcomes in a patient diagnosed with a PMH secondary to suspected Valsalva retinopathy. Methods This is a retrospective interventional case report. Results A 43-year-old healthy male presented with sudden vision loss in his left eye, reporting a visual acuity of 6/120 since the previous evening. Fundus examination revealed a PMH characterized by a “double-ring sign” accompanied by diffuse retinal hemorrhages. Optical coherence tomography confirmed that the hemorrhage was located in the sub-ILM space. The patient underwent two sessions of YAG laser membranotomy, utilizing energies of 2.5 mJ and 5 mJ, which successfully facilitated drainage of fresh hemorrhage from the sub-ILM space to the subhyaloid space and vitreous cavity. However, the presence of residual coagulated blood over the fovea resulted in persistent visual impairment, necessitating a subsequent pars plana vitrectomy (PPV). The PPV, in conjunction with internal limiting membrane peeling, effectively removed the remaining blood in front of the fovea and restored the visual acuity. By postoperative day 3, the patient experienced a significant improvement in visual acuity, measuring 6/8. Conclusion This case underscores the importance of thorough clinical examination and precise diagnostic techniques in the individualized management of PMHs, which is essential for achieving optimal visual outcomes.

Published
2025
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