Results 121 to 130 of about 61,394 (313)

Differential expression of cancer‐related genes supports prediction of poor response to first‐line treatments in T‐ALL pediatric patients with high minimal residual disease

Molecular Oncology, EarlyView.
In the present work, we have identified a transcriptional signature based on the differential expression of six genes (BCL2&MAST4, HSH2D&LAT2, METRN&PITPNM2) that would facilitate the early detection of T‐cell acute lymphoblastic leukemia (T‐ALL) patients prone to a poor treatment response and could be implemented at diagnosis, along with other risk ...
Antonio Lahera, Laura Vela‐Martín, Pablo Fernández‐Navarro, José Luis López‐Lorenzo, Javier Cornago, Pilar Llamas, Eduardo Pérez‐Gómez, José Luis Marín‐Rubio, Manuel Fresno, Javier Santos, José Fernández‐Piqueras, María Villa‐Morales   +11 more
wiley   +1 more source

A solution approach for dynamic vehicle and crew scheduling

In this paper, we discuss the dynamic vehicle and crew schedulingproblem and we propose a solution approach consisting of solving asequence of optimization problems.
Wagelmans, A.P.M., Huisman, D.
core  

Learning based dynamic approach to job-shop scheduling

, 2001
Dynamic selection of scheduling rules during real operations has been recognized as a promising approach to the scheduling of the production. This paper studies the dynamic job-shop scheduling and presents a fuzzy logic based learning approach ...
Yu HB(于海斌), Liang W(梁炜)
core  

CCDC80 suppresses high‐grade serous ovarian cancer migration via negative regulation of B7‐H3

Molecular Oncology, EarlyView.
PAX8 is a lineage‐specific master regulator of transcription in high‐grade serous ovarian cancer (HGSC) progression. We show for the first time that PAX8 facilitates proliferation and metastasis by repressing the cell autonomous tumor suppressor CCDC80 and inducing B7‐H3 expression.
Aya Saleh, Nitzan Medina‐Itzhaki, Milena Chekov, Eden Gal‐Swisa, Roba Gabesh‐Wahabi, Inbar Savyon, Inna Naroditsky, Hilary A. Kenny, Basem Fares, Lina Korsensky, Einav Girsh, Liron Berger, Ruth Perets   +12 more
wiley   +1 more source

Control of parallelized bioreactors I: dynamic scheduling software for efficient bioprocess management in high-throughput systems. [PDF]

Bioprocess Biosyst Eng, 2022
Bromig L, von den Eichen N, Weuster-Botz D.   +2 more
europepmc   +1 more source

A study in grid simulation and scheduling [PDF]

, 2006
Grid computing is emerging as an essential tool for large scale analysis and problem solving in scientific and business domains. Whilst the idea of stealing unused processor cycles is as old as the Internet, we are still far from reaching a position ...
Rhodes, Mark N.C.
core  

Heterozygous loss‐of‐function alleles associate the conserved 3′‐5′ exoribonuclease EXOSC10 with hypersensitivity to the anticancer drug 5‐fluorouracil

Molecular Oncology, EarlyView.
EXOSC10, an essential nuclear RNA exosome‐associated 3′‐5′ exoribonuclease, is inhibited by the anticancer drug 5‐fluorouracil (5‐FU), and EXOSC10 depletion increases 5‐FU sensitivity. The colon‐cancer variant EXOSC10S402T, located in a proteolysis motif, is stable and nuclear but nonfunctional in vivo.
Radhika Sain, Yann Le Page, Frédéric Percevault, Emmanuelle Becker, Luc Negroni, Almudena Fernandez, Marta Cantero, Diego Muñoz‐Santos, Lluís Montoliu, Cyrille Garnier, Michael Primig   +10 more
wiley   +1 more source

Analysis of Multi-Path Scheduling Network Model for Intelligent Transportation

Dianxin kexue, 2014
In the field of intelligent transportation, vehicle scheduling is a complex issue with multi-path, multi-types of vehicles and multi-destination. In this process, some time-varying attributes and dynamic indicators have a direct impact on the scheduling ...
Weiyang Qin
doaj   +2 more sources

An optimized two‐phase demand‐responsive transit scheduling model considering dynamic demand

IET Intelligent Transport Systems
Demand‐responsive transit has gradually attracted attention in recent years for its flexibility, efficiency, and ability to meet the diverse travel demands of passengers.
Cui‐Ying Song, He‐Ling Wang, Lu Chen, Xue‐Qin Niu   +3 more
doaj   +1 more source

A Dynamic Scheduling Method Combining Iterative Optimization and Deep Reinforcement Learning to Solve Sudden Disturbance Events in a Flexible Manufacturing Process

Mathematics
Unpredictable sudden disturbances such as machine failure, processing time lag, and order changes increase the deviation between actual production and the planned schedule, seriously affecting production efficiency. This phenomenon is particularly severe
Jun Yan, Tianzuo Zhao, Tao Zhang, Hongyan Chu, Congbin Yang, Yueze Zhang   +5 more
doaj   +1 more source