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The present paper represents an improved Multiverse Optimizer Algorithm (MVO) modified with Parallel Mirror based global learning opposition method to solve Unit Commitment problem in a Microgrid network including wind and solar sources. Unit Commitment (UC) is one of mathematical optimization problems that deal with the schedule of a given combination of generating units to achieve a minimum-cost production plan usually to satisfy the load demand. The mean objective of Unit Commitment problem is to achieve the optimal generation planning of the committed units while the overall generation cost is reduced, when subject to varying constraints at each time period. Hence, each (substantial) variation in the demand side must be matched by a corresponding amount of generation output. In fact, the minimum power generation scheduling is very difficult as UC problem encompasses a mix of variables as time varying unit constraints. The found results as the generation cost in the case without renewable sources (563977.0172$) show that the proposed method is capable to provide very competitive results and outperforms recent algorithms available in the literature which is above this result. The comparison shows clearly the effectiveness of the used technique. [ABSTRACT FROM AUTHOR]

Background & Purpose: FLASH or ultra-high dose rate (UHDR) radiation therapy (RT) has gained attention in recent years for its ability to spare normal tissues relative to conventional dose rate (CDR) RT in various preclinical trials. However, clinical implementation of this promising treatment option has been limited because of the lack of availability of accelerators capable of delivering UHDR RT. Commercial options are finally reaching the market that produce electron beams with average dose rates of up to 1000 Gy/s. We established a framework for the acceptance, commissioning, and periodic quality assurance (QA) of electron FLASH units and present an example of commissioning., Methods: A protocol for acceptance, commissioning, and QA of UHDR linear accelerators was established by combining and adapting standards and professional recommendations for standard linear accelerators based on the experience with UHDR at four clinical centers that use different UHDR devices. Non-standard dosimetric beam parameters considered included pulse width, pulse repetition frequency, dose per pulse, and instantaneous dose rate, together with recommendations on how to acquire these measurements., Results: The 6- and 9-MeV beams of an UHDR electron device were commissioned by using this developed protocol. Measurements were acquired with a combination of ion chambers, beam current transformers (BCTs), and dose-rate-independent passive dosimeters. The unit was calibrated according to the concept of redundant dosimetry using a reference setup., Conclusions: This study provides detailed recommendations for the acceptance testing, commissioning, and routine QA of low-energy electron UHDR linear accelerators. The proposed framework is not limited to any specific unit, making it applicable to all existing eFLASH units in the market. Through practical insights and theoretical discourse, this document establishes a benchmark for the commissioning of UHDR devices for clinical use.

Purpose: Although remarkably effective in some patients, precision medicine typically induces only transient responses despite initial absence of resistance-conferring mutations. Using BRAF -mutated myeloma as a model for resistance to precision medicine we investigated if BRAF- mutated cancer cells have the ability to ensure their survival by rapidly adapting to BRAF inhibitor treatment., Experimental Design: Full-length single-cell RNA (scRNA) sequencing (scRNA-seq) was conducted on 3 patients with BRAF -mutated myeloma and 1 healthy donor. We sequenced 1,495 cells before, after 1 week, and at clinical relapse to BRAF/MEK inhibitor treatment. We developed an in vitro model of dabrafenib resistance using genetically homogeneous single-cell clones from two cell lines with established BRAF mutations (U266, DP6). Transcriptional and epigenetic adaptation in resistant cells were defined by RNA-seq and H3K27ac chromatin immunoprecipitation sequencing (ChIP-seq). Mitochondrial metabolism was characterized by metabolic flux analysis., Results: Profiling by scRNA-seq revealed rapid cellular state changes in response to BRAF/MEK inhibition in patients with myeloma and cell lines. Transcriptional adaptation preceded detectable outgrowth of genetically discernible drug-resistant clones and was associated with widespread enhancer remodeling. As a dominant vulnerability, dependency on oxidative phosphorylation (OxPhos) was induced. In treated individuals, OxPhos was activated at the time of relapse and showed inverse correlation to MAPK activation. Metabolic flux analysis confirmed OxPhos as a preferential energetic resource of drug-persistent myeloma cells., Conclusions: This study demonstrates that cancer cells have the ability to rapidly adapt to precision treatments through transcriptional state changes, epigenetic adaptation, and metabolic rewiring, thus facilitating the development of refractory disease while simultaneously exposing novel vulnerabilities., (©2021 American Association for Cancer Research.)