26 papers · ranked by Valyu relevance
Sombuddha Bhattacharyya, Mondal, Tuhin, Suman Kumar Sahoo
In this article we study Momentum Light Ray Transform (MLRT) on symmetric tensor fields. MLRT is an integral transform in time-space domain ((t, x) ∈ R 1+n ), which integrates a scalar function or a tensor field along the light rays with a polynomial type weight. We explore necessary and sufficient conditions for…
Xikang Jiang, Lin Zhang, Lei Li, Manuel José Cabral dos Santos Reis + 1 more
'Nishu Gupta'] Radar-based personal identification and fall detection have received considerable attention in smart healthcare scenarios. Deep learning algorithms have been introduced to improve the performance of non-contact radar sensing applications. However, the original Transformer network is not suitable for…
Zhuo Zeng, Chengyu Zhou, Wenhui Yin, Tao Chen + 3 more
Introduction This study investigated whether stepwise load reduction training (SLRT) yields comparable or superior effects to medium load resistance training (MLRT) on one-repetition maximum (1RM) barbell back squat, thigh circumference (TC), muscle endurance (ME), counter movement jump (CMJ) performance, and acute…
Alexander Lavin, Ciarán M. Gilligan-Lee, Alessya Visnjic, Siddha Ganju + 11 more
'Siddha Ganju' 'Dava Newman' 'Sujoy Ganguly' 'Danny Lange' 'Atílím Güneş Baydin' 'Amit Sharma' 'Adam Gibson' 'Stephan Zheng' 'Eric P. Xing' 'Chris Mattmann' 'James Parr' 'Yarin Gal'] The development and deployment of machine learning systems can be executed easily with modern tools, but the process is typically rushed…
Yuan Xie, Tianshui Chen, Zheng Ge, Lionel M. Ni
Long-form video understanding, characterized by long-range temporal dependencies and multiple events, remains a challenge. Existing methods often rely on static reasoning or external visual-language models (VLMs), which face issues like complexity and sub-optimal performance due to the lack of end-to-end training. In…
Sylwia Mańka, Piotr Smolewski, Barbara Cebula-Obrzut, Agata Majchrzak + 3 more
'Agata Majchrzak' 'Klaudia Szmejda' 'Magdalena Witkowska' 'Kenneth P.H. Pritzker'] Melatonin (MLT), a pineal gland hormone, not only regulates circadian and seasonal rhythms, but also plays an important role in many aspects of human physiology and pathophysiology. MLT is of great interest as a natural substance with…
Amanda C. Winters, Kathrin M. Bernt
The mixed-lineage leukemia 1 (MLL1) gene (now renamed Lysine [K]-specific MethylTransferase 2A or KMT2A) on chromosome 11q23 is disrupted in a unique group of acute leukemias. More than 80 different partner genes in these fusions have been described, although the majority of leukemias result from MLL1 fusions with one…
Zhengyang Li, Campos, Sawyer, Nana Wang
— This paper introduces LLM-MARL, a unified framework that incorporates large language models (LLMs) into multi-agent reinforcement learning (MARL) to enhance coordination, communication, and generalization in simulated game environments. The framework features three modular components of Coordinator, Communicator, and…
叶青 王
对于伴混合系白血病基因重排（Mixed Lineage leukemia rearrangement, MLL-r）的AML，MLL相关的融合基因可以作为有效的微小残留病（MRD）标志，对造血干细胞移植后的复发进行有效预测。伴不同MLL-r的AML初诊时融合基因定量水平不同，随着肿瘤负荷变化的动力学也不尽相同，因此，可能并非所有类型的MLL-r都是最佳的分子MRD监测指标。此外，少数患者会出现克隆演变，流式细胞术（FCM）检测AML…
Authors not listed
Chemical reactions in solution are central to biological function, synthetic chemistry, and materials design. Accurate modeling of these systems is essential for obtaining mechanistic insights, but remains computationally demanding. Hybrid machine-learned/molecular mechanics (ML/MM) simulations offer a promising…
William F. Richter, Rohan N. Shah, Alexander J. Ruthenburg
MLL-rearranged leukemia depends on H3K79 methylation. Depletion of this transcriptionally-activating mark by DOT1L deletion or high concentrations of the inhibitor pinometostat downregulates HOXA9 and MEIS1, and consequently reduces leukemia survival. Yet some MLL-rearranged leukemias are inexplicably susceptible to…
Mohammad B. Aljazi, Yuen Gao, Yan Wu, George I Mias + 1 more
ASH1L and MLL1 are two histone methyltransferases that facilitate transcriptional activation during normal development. However, the roles of ASH1L and its enzymatic activity in the development of MLL-rearranged leukemias are not fully elucidated in the Ash1L gene knockout animal models. In this study, we used an Ash1L…
Authors not listed
Our study focused on the implementation and testing of machine learning interatomic potentials (MLIPs) into the AMBER software suite. This implementation enables us to perform a novel type of molecular dynamics simulation utilizing the hybrid machine learning/molecular mechanics (ML/MM) potentials. To underpin the…
Authors not listed
The rapid advancement in machine-learned interatomic potentials (MLIPs) and the proliferation of uni- versal MLIPs (uMLIPs) have significantly broadened their application scope. Community benchmarks and leaderboard rankings are frequently updated, providing statistical insights into overall progress. However, the…
Julie A. Johannessen, Miriam Formica, Nora Rojahn Bråthen, Amani Al Outa + 4 more
MLL-rearranged leukemias are among the leukemic subtypes with poorest survival, and treatment options have barely improved over the last decades. Furthermore, despite increasing molecular understanding of the mechanisms behind these hematopoietic malignancies, this knowledge has had poor translation into the clinic.…
Sarah E. Glazer, Margie N. Sutton, Ping Yang, Federica Pisaneschi + 3 more
Radioligand therapy (RLT), a re-emerging oncologic strategy using molecularly-targeted therapeutic radioisotopes, clinically reduces tumor burden and enhances survival for select patients with otherwise unresponsive advanced prostate cancer and neuroendocrine tumors. Developing new approaches to next generation targets…
Laila Kobrossy, Weiyi Xu, Chunling Zhang, Christopher E. Turner + 1 more
Much of our understanding of the pathology of acute leukemias is based on studies of 11q23 chromosomal translocations of the gene encoding the mixed lineage leukemia-1 (MLL1) histone H3 lysine 4 (H3K4) methyltransferase. Translocations of the MLL1 gene result in MLL1-fusion (MLL1_F_) proteins that replace the catalytic…
Lilia Kaustov, Alexander Lemak, Hong Wu, Marco Faini + 10 more
Histone H3K4 methylation is an epigenetic mark associated with actively transcribed genes. This modification is catalyzed by the mixed lineage leukaemia (MLL) family of histone methyltransferases including MLL1, MLL2, MLL3, MLL4, SET1A and SET1B. Catalytic activity of MLL proteins is dependent on interactions with…
Authors not listed
Hybrid machine-learning/molecular-mechanics (ML/MM) methods extend the classical QM/MM paradigm by replacing the quantum desription with neural network interatomic potentials trained to reproduce accurately quantum-mechanical (QM) results. By describing only the chemically active region with ML and the surrounding…
Marisa J. L. Aitken, Farhad Ravandi, Keyur P. Patel, Nicholas J. Short
'Nicholas J. Short'] Quantification of measurable residual disease (MRD) provides critical prognostic information in acute myeloid leukemia (AML). A variety of platforms exist for MRD detection, varying in their sensitivity and applicability to individual patients. MRD detected by quantitative polymerase chain…
Junjie Zhou, Yan Shu, Bo Zhao, Boya Wu + 6 more
'Yongping Xiong' 'Bo Zhang' 'Tiejun Huang' 'Zheng Liu'] The evaluation of Long Video Understanding (LVU) performance poses an important but challenging research problem. Despite previous efforts, the existing video understanding benchmarks are severely constrained by several issues, especially the insufficient lengths…
Anubhav Jain
The number of studies that apply machine learning (ML) to materials science has been growing at a rate of approximately 1.67 times per year over the past decade. In this review, I examine this growth in various contexts. First, I present an analysis of the most commonly used tools (software, databases, materials…
Muhammad Hanzla, Abdul Rehman Shinwari
Machine Learning (ML) can be defined as a class of Artificial Intelligence for automated data analysis, which is capable of detecting patterns in data. The extracted patterns can be used to predict un-known data or to assist in decision-making processes under uncertainty. Recent advances in experimental and…
Authors not listed
The Microporous Layer (MPL) plays a crucial role in Proton Exchange Membrane Fuel Cells (PEMFCs), as its microstructure significantly influences the overall transport properties within these devices. This study introduces a novel Machine Learning (ML) approach to optimize the MPL microstructure and properties.…
Zachary Kileeg, Aparna Haldar, Hasna Khan, Arooj Qamar + 1 more
To maximize overall fitness, plants must accurately respond to a host of growth, developmental, and environmental signals throughout their life. Many of these internal and external signals are perceived by the leucine-rich repeat receptor-like kinases, which play roles in regulating growth, development, and immunity.…
Authors not listed
The integration of machine learning methods is transforming many areas of research by, for instance, accelerating molecular dynamics simulations and enabling improved prediction and optimization of chemical reactions. However, despite this progress, the adoption of data-driven approaches in atomic layer deposition…