Iterative actions of normal operators

Let $A$ be a normal operator in a Hilbert space $\mathcal{H}$, and let $\mathcal{G} \subset \mathcal{H}$ be a countable set of vectors. We investigate the relations between $A$, $\mathcal{G}$ , and $L$ that makes the system of iterations $\{A^ng: g\in \mathcal{G},\;0\leq n< L(g)\}$ complete, Bessel, a basis, or a frame for $\mathcal{H}$. The problem is motivated by the dynamical sampling problem and is connected to several topics in functional analysis, including, frame theory and spectral theory. It also has relations to topics in applied harmonic analysis including, wavelet theory and time-frequency analysis.Comment: 14 pages, 0 figure

A Compact Representation of Histopathology Images using Digital Stain Separation & Frequency-Based Encoded Local Projections

In recent years, histopathology images have been increasingly used as a diagnostic tool in the medical field. The process of accurately diagnosing a biopsy sample requires significant expertise in the field, and as such can be time-consuming and is prone to uncertainty and error. With the advent of digital pathology, using image recognition systems to highlight problem areas or locate similar images can aid pathologists in making quick and accurate diagnoses. In this paper, we specifically consider the encoded local projections (ELP) algorithm, which has previously shown some success as a tool for classification and recognition of histopathology images. We build on the success of the ELP algorithm as a means for image classification and recognition by proposing a modified algorithm which captures the local frequency information of the image. The proposed algorithm estimates local frequencies by quantifying the changes in multiple projections in local windows of greyscale images. By doing so we remove the need to store the full projections, thus significantly reducing the histogram size, and decreasing computation time for image retrieval and classification tasks. Furthermore, we investigate the effectiveness of applying our method to histopathology images which have been digitally separated into their hematoxylin and eosin stain components. The proposed algorithm is tested on the publicly available invasive ductal carcinoma (IDC) data set. The histograms are used to train an SVM to classify the data. The experiments showed that the proposed method outperforms the original ELP algorithm in image retrieval tasks. On classification tasks, the results are found to be comparable to state-of-the-art deep learning methods and better than many handcrafted features from the literature.Comment: Accepted for publication in the International Conference on Image Analysis and Recognition (ICIAR 2019

Unitized regenerative fuel cell systems

Energy storage systems with extremely high specific energy (>400 Wh/kg) have been designed that use lightweight pressure vessels to contain the gases generated by reversible (unitized) regenerative fuel cells (URFCs).[1] URFC systems are being designed and developed for a variety of applications, including high altitude long endurance (HALE) solar rechargeable aircraft (SRA), zero emission vehicles (ZEVs), hybrid energy storage/propulsion systems for spacecraft, energy storage for remote (off-grid) power sources, and peak shaving for on-grid applications.[1-10] Energy storage for HALE SRA was the original application for this set of innovations, and a prototype solar powered aircraft (Pathfinder-Plus) recently set another altitude record for all propeller-driven aircraft on August 6, 1998, when it flew to 80,285 feet (24.47 km).[11

Prescribing patterns in dementia: a multicentre observational study in a German network of CAM physicians

<p>Abstract</p> <p>Background</p> <p>Dementia is a major and increasing health problem worldwide. This study aims to investigate dementia treatment strategies among physicians specialised in complementary and alternative medicine (CAM) by analysing prescribing patterns and comparing them to current treatment guidelines in Germany.</p> <p>Methods</p> <p>Twenty-two primary care physicians in Germany participated in this prospective, multicentre observational study. Prescriptions and diagnoses were reported for each consecutive patient. Data were included if patients had at least one diagnosis of dementia according to the 10th revision of the International Classification of Diseases during the study period. Multiple logistic regression was used to determine factors associated with a prescription of any anti-dementia drug including <it>Ginkgo biloba</it>.</p> <p>Results</p> <p>During the 5-year study period (2004-2008), 577 patients with dementia were included (median age: 81 years (IQR: 74-87); 69% female). Dementia was classified as unspecified dementia (57.2%), vascular dementia (25.1%), dementia in Alzheimer's disease (10.4%), and dementia in Parkinson's disease (7.3%). The prevalence of anti-dementia drugs was 25.6%. The phytopharmaceutical <it>Ginkgo biloba </it>was the most frequently prescribed anti-dementia drug overall (67.6% of all) followed by cholinesterase inhibitors (17.6%). The adjusted odds ratio (AOR) for receiving any anti-dementia drug was greater than 1 for neurologists (AOR = 2.34; CI: 1.59-3.47), the diagnosis of Alzheimer's disease (AOR = 3.28; CI: 1.96-5.50), neuroleptic therapy (AOR = 1.87; CI: 1.22-2.88), co-morbidities hypertension (AOR = 2.03; CI: 1.41-2.90), and heart failure (AOR = 4.85; CI: 3.42-6.88). The chance for a prescription of any anti-dementia drug decreased with the diagnosis of vascular dementia (AOR = 0.64; CI: 0.43-0.95) and diabetes mellitus (AOR = 0.55; CI: 0.36-0.86). The prescription of <it>Ginkgo biloba </it>was associated with sex (female: AOR = 0.41; CI: 0.19-0.89), patient age (AOR = 1.06; CI: 1.02-1.10), treatment by a neurologist (AOR = 0.09; CI: 0.03-0.23), and the diagnosis of Alzheimer's disease (AOR = 0.07; CI: 0.04-0.16).</p> <p>Conclusions</p> <p>This study provides a comprehensive analysis of everyday practice for treatment of dementia in primary care in physicians with a focus on CAM. The prescribing frequency for anti-dementia drugs is equivalent to those found in other German studies, while the administration of <it>Ginkgo biloba </it>is significantly higher.</p

Grid Cells, Place Cells, and Geodesic Generalization for Spatial Reinforcement Learning

Reinforcement learning (RL) provides an influential characterization of the brain's mechanisms for learning to make advantageous choices. An important problem, though, is how complex tasks can be represented in a way that enables efficient learning. We consider this problem through the lens of spatial navigation, examining how two of the brain's location representations—hippocampal place cells and entorhinal grid cells—are adapted to serve as basis functions for approximating value over space for RL. Although much previous work has focused on these systems' roles in combining upstream sensory cues to track location, revisiting these representations with a focus on how they support this downstream decision function offers complementary insights into their characteristics. Rather than localization, the key problem in learning is generalization between past and present situations, which may not match perfectly. Accordingly, although neural populations collectively offer a precise representation of position, our simulations of navigational tasks verify the suggestion that RL gains efficiency from the more diffuse tuning of individual neurons, which allows learning about rewards to generalize over longer distances given fewer training experiences. However, work on generalization in RL suggests the underlying representation should respect the environment's layout. In particular, although it is often assumed that neurons track location in Euclidean coordinates (that a place cell's activity declines “as the crow flies” away from its peak), the relevant metric for value is geodesic: the distance along a path, around any obstacles. We formalize this intuition and present simulations showing how Euclidean, but not geodesic, representations can interfere with RL by generalizing inappropriately across barriers. Our proposal that place and grid responses should be modulated by geodesic distances suggests novel predictions about how obstacles should affect spatial firing fields, which provides a new viewpoint on data concerning both spatial codes

Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease

Background: Experimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. Methods: We conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. RESULTS: At 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in the 300-mg group than in the placebo group. Canakinumab did not reduce lipid levels from baseline. At a median follow-up of 3.7 years, the incidence rate for the primary end point was 4.50 events per 100 person-years in the placebo group, 4.11 events per 100 person-years in the 50-mg group, 3.86 events per 100 person-years in the 150-mg group, and 3.90 events per 100 person-years in the 300-mg group. The hazard ratios as compared with placebo were as follows: in the 50-mg group, 0.93 (95% confidence interval [CI], 0.80 to 1.07; P = 0.30); in the 150-mg group, 0.85 (95% CI, 0.74 to 0.98; P = 0.021); and in the 300-mg group, 0.86 (95% CI, 0.75 to 0.99; P = 0.031). The 150-mg dose, but not the other doses, met the prespecified multiplicity-adjusted threshold for statistical significance for the primary end point and the secondary end point that additionally included hospitalization for unstable angina that led to urgent revascularization (hazard ratio vs. placebo, 0.83; 95% CI, 0.73 to 0.95; P = 0.005). Canakinumab was associated with a higher incidence of fatal infection than was placebo. There was no significant difference in all-cause mortality (hazard ratio for all canakinumab doses vs. placebo, 0.94; 95% CI, 0.83 to 1.06; P = 0.31). Conclusions: Antiinflammatory therapy targeting the interleukin-1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid-level lowering. (Funded by Novartis; CANTOS ClinicalTrials.gov number, NCT01327846.

[mu-1,3-Bis(diphenylphosphino)propane-kappa P-2:P `]bis[bromidogold(I)]

The title compound, [Au2Br2(C27H26P2)], features linearly coordinated Au-I atoms within P,Br-donor sets. The central portion of the molecule is practically planar as quantified by the Br-Au center dot center dot center dot Au-Br torsion angle of -169.9 (2)degrees. The P-Au-Br chromophores are twisted with respect to each other [dihedral angle = 52.3 (6)degrees]. The benzene rings on each P atom lie on either side of this plane. The Au atoms are positioned at the periphery of the molecule, which facilitates the formation of Au center dot center dot center dot Au interactions [3.2575 (11) angstrom] that result in the formation of supramolecular chains along the b-axis direction. The Au center dot center dot center dot Au interactions are responsible for the deviations from the ideal linear geometry for each Au atom