ML/DL/HPC Ecosystem of the HybriLIT Heterogeneous Platform (MLIT JINR): New Opportunities for Applied Research

The work presents the possibilities for using the ML/DL/HPC ecosystem deployed on the HybriLIT Heterogeneous Platform (Meshcheryakov Laboratory of Information Technologies JINR) on top of JupyterHub, which provides opportunities for solving tasks not only in the field of machine learning and deep learning, but also for the convenient organization of calculations and scientific visualization. The ecosystem allows one to develop and implement program modules in Python, as well as to carry out methodical computations. The relevance of deploying such an environment is primarily associated with the great demand for software modules that are provided to a group of researchers or the scientific community, when all stages of the study can be reproduced; the code has been modified and used by the scientific community. Using the example of solving a specific problem to study the dynamics of magnetization in a Phi-0 Josephson Junction (Superconductor-Ferromagnet-Superconductor structure), a methodology for developing software modules is presented; it enables not only to carry out calculations, but also to visualize the results of the study and accompany them with the necessary formulas and explanations. The possibility of parallel implementation of the algorithm for performing computations for various values of parameters of the model based on the Joblib Python library is shown, and the results of computational experiments demonstrating the efficiency of parallel data processing are presented

Object Classificators Using the AdaBoost Algorithm and Neural Networks

The construction of image object detectors is still a relevant task, due to dynamic developments in the field of computer vision. In this work, we combined neural network technologies with existing data processing algorithms to obtain effective object classifiers. We demonstrate our approach on the example of face detection

Comparative Performance Analysis of Neural Network Real-Time Object Detections in Different Implementations

The performance of neural networks is one of the most important topics in the field of computer vision. In this work, we analyze the speed of object detection using the well-known YOLOv3 neural network architecture in different frameworks under different hardware requirements. We obtain results, which allow us to formulate preliminary qualitative conclusions about the feasibility of various hardware scenarios to solve tasks in real-time environments

Object Classificators Using the AdaBoost Algorithm and Neural Networks

The construction of image object detectors is still a relevant task, due to dynamic developments in the field of computer vision. In this work, we combined neural network technologies with existing data processing algorithms to obtain effective object classifiers. We demonstrate our approach on the example of face detection

Object Classificators Using the AdaBoost Algorithm and Neural Networks

The construction of image object detectors is still a relevant task, due to dynamic developments in the field of computer vision. In this work, we combined neural network technologies with existing data processing algorithms to obtain effective object classifiers. We demonstrate our approach on the example of face detection

Comparative Performance Analysis of Neural Network Real-Time Object Detections in Different Implementations

The performance of neural networks is one of the most important topics in the field of computer vision. In this work, we analyze the speed of object detection using the well-known YOLOv3 neural network architecture in different frameworks under different hardware requirements. We obtain results, which allow us to formulate preliminary qualitative conclusions about the feasibility of various hardware scenarios to solve tasks in real-time environments

Study of Structure–Activity Relationships of the Marine Alkaloid Fascaplysin and Its Derivatives as Potent Anticancer Agents

Marine alkaloid fascaplysin and its derivatives are known to exhibit promising anticancer properties in vitro and in vivo. However, toxicity of these molecules to non-cancer cells was identified as a main limitation for their clinical use. Here, for the very first time, we synthesized a library of fascaplysin derivatives covering all possible substituent introduction sites, i.e., cycles A, C and E of the 12H-pyrido[1-2-a:3,4-b’]diindole system. Their selectivity towards human prostate cancer versus non-cancer cells, as well as the effects on cellular metabolism, membrane integrity, cell cycle progression, apoptosis induction and their ability to intercalate into DNA were investigated. A pronounced selectivity for cancer cells was observed for the family of di- and trisubstituted halogen derivatives (modification of cycles A and E), while a modification of cycle C resulted in a stronger activity in therapy-resistant PC-3 cells. Among others, 3,10-dibromofascaplysin exhibited the highest selectivity, presumably due to the cytostatic effects executed via the targeting of cellular metabolism. Moreover, an introduction of radical substituents at C-9, C-10 or C-10 plus C-3 resulted in a notable reduction in DNA intercalating activity and improved selectivity. Taken together, our research contributes to understanding the structure–activity relationships of fascaplysin alkaloids and defines further directions of the structural optimization

HIV-associated Burkitt lymphoma: outcomes from a US-UK collaborative analysis

Abstract Data addressing prognostication in patients with HIV related Burkitt lymphoma (HIV-BL) currently treated remain scarce. We present an international analysis of 249 (United States: 140; United Kingdom: 109) patients with HIV-BL treated from 2008 to 2019 aiming to identify prognostic factors and outcomes. With a median follow up of 4.5 years, the 3-year progression-free survival (PFS) and overall survival (OS) were 61% (95% confidence interval [CI] 55% to 67%) and 66% (95%CI 59% to 71%), respectively, with similar results in both countries. Patients with baseline central nervous system (CNS) involvement had shorter 3-year PFS (36%) compared to patients without CNS involvement (69%; P 5 upper limit of normal (HR 2.09; P 1 extranodal sites (HR 1.58; P = .043). The same variables were significant in multivariate models for OS. Adjusting for these prognostic factors, treatment with cyclophosphamide, vincristine, doxorubicin, and high-dose methotrexate, ifosfamide, etoposide, and high-dose cytarabine (CODOX-M/IVAC) was associated with longer PFS (adjusted HR [aHR] 0.45; P = .005) and OS (aHR 0.44; P = .007). Remarkably, HIV features no longer influence prognosis in contemporaneously treated HIV-BL