FFT-Based Fast Computation of Multivariate Kernel Estimators with Unconstrained Bandwidth Matrices

The problem of fast computation of multivariate kernel density estimation (KDE) is still an open research problem. In our view, the existing solutions do not resolve this matter in a satisfactory way. One of the most elegant and efficient approach utilizes the fast Fourier transform. Unfortunately, the existing FFT-based solution suffers from a serious limitation, as it can accurately operate only with the constrained (i.e., diagonal) multivariate bandwidth matrices. In this paper we describe the problem and give a satisfactory solution. The proposed solution may be successfully used also in other research problems, for example for the fast computation of the optimal bandwidth for KDE.Comment: 10 pages, 1 figure, R source code

FPGA-Based Bandwidth Selection for Kernel Density Estimation Using High Level Synthesis Approach

FPGA technology can offer significantly hi\-gher performance at much lower power consumption than is available from CPUs and GPUs in many computational problems. Unfortunately, programming for FPGA (using ha\-rdware description languages, HDL) is a difficult and not-trivial task and is not intuitive for C/C++/Java programmers. To bring the gap between programming effectiveness and difficulty the High Level Synthesis (HLS) approach is promoting by main FPGA vendors. Nowadays, time-intensive calculations are mainly performed on GPU/CPU architectures, but can also be successfully performed using HLS approach. In the paper we implement a bandwidth selection algorithm for kernel density estimation (KDE) using HLS and show techniques which were used to optimize the final FPGA implementation. We are also going to show that FPGA speedups, comparing to highly optimized CPU and GPU implementations, are quite substantial. Moreover, power consumption for FPGA devices is usually much less than typical power consumption of the present CPUs and GPUs.Comment: 23 pages, 6 figures, extended version of initial pape

Breast cancer nuclei segmentation and classification based on a deep learning approach

One of the most popular methods in the diagnosis of breast cancer is fine-needle biopsy without aspiration. Cell nuclei are the most important elements of cancer diagnostics based on cytological images. Therefore, the first step of successful classification of cytological images is effective automatic segmentation of cell nuclei. The aims of our study include (a) development of segmentation methods of cell nuclei based on deep learning techniques, (b) extraction of some morphometric, colorimetric and textural features of individual segmented nuclei, (c) based on the extracted features, construction of effective classifiers for detecting malignant or benign cases. The segmentation methods used in this paper are based on (a) fully convolutional neural networks and (b) the marker-controlled watershed algorithm. For the classification task, seven various classification methods are used. Cell nuclei segmentation achieves 90% accuracy for benign and 86% for malignant nuclei according to the F-score. The maximum accuracy of the classification reached 80.2% to 92.4%, depending on the type (malignant or benign) of cell nuclei. The classification of tumors based on cytological images is an extremely challenging task. However, the obtained results are promising, and it is possible to state that automatic diagnostic methods are competitive to manual ones

Pre-Existing Hypertension Is Related with Disproportions in T-Lymphocytes in Older Age

Age-related immune deficiencies increase the risk of comorbidities and mortality. This study evaluated immunosenescence patterns by flow cytometry of naïve and memory T cell subpopulations and the immune risk profile (IRP), expressed as the CD4/CD8 ratio and IgG CMV related to comorbidities. The disproportions in naïve and memory T cells, as well as in the CD4/CD8 ratio, were analysed in 99 elderly individuals (71.9 ± 5.8 years) diagnosed with hypertension (n = 51) or without hypertension (n = 48), using an eight-parameter flow cytometer. The percentage of CD4+ T lymphocytes was significantly higher in hypertensive than other individuals independently from CMV infections, with approximately 34% having CD4/CD8 > 2.5, and only 4% of the elderly with hypertension having CD4/CD8 75 years. The decline in CD4+ naïve T lymphocytes was more prominent in IgG CMV+ men when compared to IgG CMV+ women. The changes in naïve and memory T lymphocyte population, CD4/CD8, and CMV seropositivity included in IRP are important markers of health status in the elderly that are dependent on hypertension

Intermittent Hypoxic Exposure with High Dose of Arginine Impact on Circulating Mediators of Tissue Regeneration

Intermittent exposure to hypoxia (IHE) increases production of reactive oxygen and nitrogen species which, as signalling molecules, participate in tissue injury–repair–regeneration cascade. The process is also stimulated by arginine whose bioavailability is a limiting factor for NO synthesis. The effects of IHE in combination with arginine (Arg) intake on myogenesis and angiogenesis mediators were examined in a randomized and placebo-controlled trial. Blood samples were collected from 38 elite athletes on the 1st, 7th and 14th days during the training camp. The oral doses of arginine (2 × 6 g/day) and/or IHE using hypoxicator GO2Altitude (IHE and Arg/IHE) were applied. Serum NO and H2O2 concentrations increased significantly and were related to muscle damage (CK activity >900 IU/mL) in IHE and Arg/IHE compared to placebo. The changes in NO and H2O2 elevated the levels of circulating growth factors such as HGF, IHG-1, PDGFBB, BDNF, VEGF and EPO. Modification of the lipid profile, especially reduced non-HDL, was an additional beneficial effect of hypoxic exposure with arginine intake. Intermittent hypoxic exposure combined with high-dose arginine intake was demonstrated to affect circulating mediators of injury–repair–regeneration. Therefore, a combination of IHE and arginine seems to be a potential therapeutic and non-pharmacological method to modulate the myogenesis and angiogenesis in elite athletes