Lacroixguldbrandsen1526

Collective decision making is important for maximizing total benefits while preserving equality among individuals in the competitive multi-armed bandit (CMAB) problem, wherein multiple players try to gain higher rewards from multiple slot machines. The CMAB problem represents an essential aspect of applications such as resource management in social infrastructure. In a previous study, we theoretically and experimentally demonstrated that entangled photons can physically resolve the difficulty of the CMAB problem. This decision-making strategy completely avoids decision conflicts while ensuring equality. However, decision conflicts can sometimes be beneficial if they yield greater rewards than non-conflicting decisions, indicating that greedy actions may provide positive effects depending on the given environment. In this study, we demonstrate a mixed strategy of entangled- and correlated-photon-based decision-making so that total rewards can be enhanced when compared to the entangled-photon-only decision strategy. Eprenetapopt We show that an optimal mixture of entangled- and correlated-photon-based strategies exists depending on the dynamics of the reward environment as well as the difficulty of the given problem. This study paves the way for utilizing both quantum and classical aspects of photons in a mixed manner for decision making and provides yet another example of the supremacy of mixed strategies known in game theory, especially in evolutionary game theory.A library of new spiro[diindeno[1,2-b2',1'-e]pyridine-11,3'-indoline]-2',10,12-trione derivatives has been prepared in an efficient, one-pot pseudo four-component method mediated by a reusable heterogeneous nano-ordered mesoporous SO3H functionalized-silica (MCM-41-SO3H) catalyst. Excellent yields, short reaction times, as well as convenient non-chromatographic purification of the products and environmental benefits such as green and metal-free conditions constitute the main advantages of the developed synthetic methodology. The obtained fused indole-indenone dyes would be of interest to pharmaceutical and medicinal chemistry. Furthermore, due to their sensitivity to pH changes, they could be used as novel pH indicators.Impaired left atrial (LA) function in heart failure with preserved ejection fraction (HFpEF) is associated with adverse outcomes. A subgroup of HFpEF may have LA myopathy out of proportion to left ventricular (LV) dysfunction; therefore, we sought to characterize HFpEF patients with disproportionate LA myopathy. In the prospective, multicenter, Prevalence of Microvascular Dysfunction in HFpEF study, we defined disproportionate LA myopathy based on degree of LA reservoir strain abnormality in relation to LV myopathy (LV global longitudinal strain [GLS]) by calculating the residuals from a linear regression of LA reservoir strain and LV GLS. We evaluated associations of disproportionate LA myopathy with hemodynamics and performed a plasma proteomic analysis to identify proteins associated with disproportionate LA myopathy; proteins were validated in an independent sample. Disproportionate LA myopathy correlated with better LV diastolic function but was associated with lower stroke volume reserve after passive leg raise independent of atrial fibrillation (AF). Additionally, disproportionate LA myopathy was associated with higher pulmonary artery systolic pressure, higher pulmonary vascular resistance, and lower coronary flow reserve. Of 248 proteins, we identified and validated 5 proteins (involved in cardiomyocyte stretch, extracellular matrix remodeling, and inflammation) that were associated with disproportionate LA myopathy independent of AF. In HFpEF, LA myopathy may exist out of proportion to LV myopathy. Disproportionate LA myopathy is a distinct HFpEF subtype associated with worse hemodynamics and a distinct proteomic signature, independent of AF.Corticosteroids, anti-CD20 agents, immunotherapies, and cytotoxic chemotherapy are commonly used in the treatment of patients with cancer. It is unclear how these agents affect patients with cancer who are infected with SARS-CoV-2. We retrospectively investigated associations between SARS-CoV-2-associated respiratory failure or death with receipt of the aforementioned medications and with pre-COVID-19 neutropenia. The study included all cancer patients diagnosed with SARS-CoV-2 at Memorial Sloan Kettering Cancer Center until June 2, 2020 (N = 820). We controlled for cancer-related characteristics known to predispose to worse COVID-19 as well as level of respiratory support during corticosteroid administration. Corticosteroid administration was associated with worse outcomes prior to use of supplemental oxygen; no statistically significant difference was observed in sicker cohorts. In patients with metastatic thoracic cancer, 9 of 25 (36%) and 10 of 31 (32%) had respiratory failure or death among those who did and did not receive immunotherapy, respectively. Seven of 23 (30%) and 52 of 187 (28%) patients with hematologic cancer had respiratory failure or death among those who did and did not receive anti-CD20 therapy, respectively. Chemotherapy itself was not associated with worse outcomes, but pre-COVID-19 neutropenia was associated with worse COVID-19 course. Relative prevalence of chemotherapy-associated neutropenia in previous studies may account for different conclusions regarding the risks of chemotherapy in patients with COVID-19. In the absence of prospective studies and evidence-based guidelines, our data may aid providers looking to assess the risks and benefits of these agents in caring for cancer patients in the COVID-19 era.Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and the traditional variables extracted from computed tomography (CT) images may not be sufficient to describe all the topological features of lung tissues in COPD patients. We employed an unsupervised three-dimensional (3D) convolutional autoencoder (CAE)-feature constructor (FC) deep learning network to learn from CT data and derive tissue pattern-clusters jointly. We then applied exploratory factor analysis (EFA) to discover the unobserved latent traits (factors) among pattern-clusters. CT images at total lung capacity (TLC) and residual volume (RV) of 541 former smokers and 59 healthy non-smokers from the cohort of the SubPopulations and Intermediate Outcome Measures in the COPD Study (SPIROMICS) were analyzed. TLC and RV images were registered to calculate the Jacobian (determinant) values for all the voxels in TLC images. 3D Regions of interest (ROIs) with two data channels of CT intensity and Jacobian value were randomly extracted from training images and were fed to the 3D CAE-FC model.