Results 141 to 150 of about 775,681 (328)
Molecular Oncology, EarlyView.We quantified and cultured circulating tumor cells (CTCs) of 62 patients with various cancer types and generated CTC‐derived tumoroid models from two salivary gland cancer patients. Cellular liquid biopsy‐derived information enabled molecular genetic assessment of systemic disease heterogeneity and functional testing for therapy selection in both ...
Nataša Stojanović Gužvić +31 more
wiley +1 more source
S-Graph-Based Reactive Scheduling with Unexpected Arrivals of New Orders
MachinesManufacturing processes are often disrupted by unexpected events, such as machine breakdowns, raw material shortages, and the arrival of new orders. Effectively managing these uncertainties is crucial for maintaining the feasibility and optimality of the
Krisztián Attila Bakon +1 more
doaj +1 more source
Scalable Multi-agent Reinforcement Learning for Factory-wide Dynamic Scheduling [PDF]
arXivReal-time dynamic scheduling is a crucial but notoriously challenging task in modern manufacturing processes due to its high decision complexity. Recently, reinforcement learning (RL) has been gaining attention as an impactful technique to handle this challenge. However, classical RL methods typically rely on human-made dispatching rules, which are not
arxiv
Comparative study of different approaches to solve batch process scheduling and optimisation problems [PDF]
, 2012 Effective approaches are important to batch process scheduling problems, especially those with complex constraints. However, most research focus on improving optimisation techniques, and those concentrate on comparing their difference are inadequate ...
Huang, Wei +3 more
core
Genomic landscape and preclinical models of angiosarcoma
Molecular Oncology, Volume 19, Issue 4, Page 965-983, April 2025.Angiosarcomas are a rare and aggressive cancer with a poor prognosis for patients. The genomic landscape of angiosarcoma can be highly complex and heterogenous; however, recent studies have identified some common features especially within anatomic and molecular subgroups.
Annaleigh Benton +3 more
wiley +1 more source
Is the GPU Half-Empty or Half-Full? Practical Scheduling Techniques for LLMs [PDF]
arXivServing systems for Large Language Models (LLMs) improve throughput by processing several requests concurrently. However, multiplexing hardware resources between concurrent requests involves non-trivial scheduling decisions. Practical serving systems typically implement these decisions at two levels: First, a load balancer routes requests to different ...
arxiv
Molecular Oncology, EarlyView.The authors analyzed the spatial distributions of gene and metabolite profiles in cervical cancer through spatial transcriptomic and spatially resolved metabolomic techniques. Pivotal genes and metabolites within these cases were then identified and validated.
Lixiu Xu +3 more
wiley +1 more source
Optimizing Job Shop Scheduling in the Furniture Industry: A Reinforcement Learning Approach Considering Machine Setup, Batch Variability, and Intralogistics [PDF]
arXivThis paper explores the potential application of Deep Reinforcement Learning in the furniture industry. To offer a broad product portfolio, most furniture manufacturers are organized as a job shop, which ultimately results in the Job Shop Scheduling Problem (JSSP).
arxiv
Molecular Oncology, Volume 19, Issue 4, Page 1229-1243, April 2025.We assessed the associations between the gut microbiota and outcome in metastatic triple‐negative breast cancer patients treated with chemotherapy alone or chemotherapy in combination with immunotherapy. Our data indicate that high gut microbiota alpha diversity was associated with improved clinical outcome and with benefit from immunotherapy.
Andreas Ullern +8 more
wiley +1 more source
The concept of algorithm supporting the process of scheduling production tasks [PDF]
, 2018 Adrian Knapczyk, S. Francik, Z. Ślipek
openalex +1 more source