Results 81 to 90 of about 6,626 (272)
Discrete Approximation and Quantification in Distributionally Robust Optimization [PDF]
Summary: Discrete approximation of probability distributions is an important topic in stochastic programming. In this paper, we extend the research on this topic to distributionally robust optimization (DRO), where discretization is driven by either limited availability of empirical data (samples) or a computational need for improving numerical ...
Yongchao Liu, Alois Pichler, Huifu Xu
openaire +2 more sources
Pancreatic sensory neurons innervating healthy and PDAC tissue were retrogradely labeled and profiled by single‐cell RNA sequencing. Tumor‐associated innervation showed a dominant neurofilament‐positive subtype, altered mitochondrial gene signatures, and reduced non‐peptidergic neurons.
Elena Genova +14 more
wiley +1 more source
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 +11 more
wiley +1 more source
KDM7A and KDM1A inhibition suppresses tumour promoting pathways in prostate cancer
Treatment resistance is a major challenge for patients with advanced prostate cancer. This study examined an alternative approach to target the major prostate cancer‐promoting pathway by targeting epigenetic factors, whose levels are higher in tumours.
Jennie N Jeyapalan +16 more
wiley +1 more source
Intratumour heterogeneity complicates precision management of advanced endometrial cancer. Circulating tumor DNA (ctDNA) offers a minimally invasive strategy to capture tumor evolution and therapeutic resistance. Here, we compare tumor‐agnostic NGS with tumor‐informed ddPCR, outlining their relative sensitivity, concordance, and clinical implications ...
Carlos Casas‐Arozamena +15 more
wiley +1 more source
Microgrid formation provides a viable solution for enhancing the resilience of distribution systems under extreme conditions. In general, the on-outage areas of the distribution system are partitioned into multiple islands to restore the critical loads ...
Weixu Tian +5 more
doaj +1 more source
A framework of distributionally robust possibilistic optimization
In this paper, an optimization problem with uncertain constraint coefficients is considered. Possibility theory is used to model the uncertainty. Namely, a joint possibility distribution in constraint coefficient realizations, called scenarios, is specified.
Romain Guillaume +2 more
openaire +3 more sources
Distributionally Robust Bootstrap Optimization
Control architectures and autonomy stacks for complex engineering systems are often divided into layers to decompose a complex problem and solution into distinct, manageable sub-problems. To simplify designs, uncertainties are often ignored across layers, an approach with deep roots in classical notions of separation and certainty equivalence.
Summers, Tyler, Kamgarpour, Maryam
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A urine‐based digital PCR assay targeting two hotspot TERT promoter variants detected bladder cancer with high sensitivity and no false positives in this case–control cohort. The streamlined AbsoluteQ workflow outperformed Sanger sequencing and supports non‐invasive molecular testing for bladder cancer detection.
Anna Nykel +12 more
wiley +1 more source
Distributionally Robust Return-Risk Optimization Models and Their Applications
Based on the risk control of conditional value-at-risk, distributionally robust return-risk optimization models with box constraints of random vector are proposed.
Li Yang +3 more
doaj +1 more source

