background: no data is available on morphology and genetic characteristics of echinococcus granulosus derived from donkeys of iran, despite of its existence in donkeys.in the present study morphometric variations of the rostellar hooks of protoscoleces and genotype characteristics of hydatid cyst of donkey from iran were determined. methods: protoscoleces prepared from hydatid cyst of donkey of...

Actin cytoskeleton networks generate local topological signatures due to the natural variations in number, size, and shape of holes networks. Persistent homology is a method that explores these properties data summarizes them as persistence diagrams. In this work, we analyze classify simulated actin filament by transforming into diagrams whose variability quantified via Bayesian framework on sp...

We demonstrate how to use persistent homology for cosmological parameter inference in a tomographic cosmic shear survey. obtain the first constraints from by applying our method first-year data of Dark Energy Survey. To these constraints, we analyse topological structure matter distribution extracting persistence diagrams signal-to-noise maps aperture masses. This presents natural extension wid...

we investigate the relative cohomology and relative homology theories of $f$-gorenstein modules, consider the relations between classical and $f$-gorenstein (co)homology theories.

Topological data analysis, such as persistent homology has shown beneficial properties for machine learning in many tasks. Topological representations, such as the persistence diagram (PD), however, have a complex structure (multiset of intervals) which makes it difficult to combine with typical machine learning workflows. We present novel compact fixed-size vectorial representations of PDs bas...

Time-series data are amongst the most widely-used in biomedical sciences, including domains such as functional Magnetic Resonance Imaging (fMRI). Structure within time series can be captured by tools of topological analysis (TDA). Persistent homology is mostly commonly used data-analytic tool TDA, and effectively summarize complex high-dimensional into an interpretable 2-dimensional representat...

Collections of measures on compact metric spaces form a model category (“data complexes”), whose morphisms are marginalization integrals. The fibrant objects in this represent collections which there is measure product space that marginalizes to any pairs its factors. homotopy and homology for allow measurement obstructions finding larger spaces. obstruction theory compatible with filtration bu...

Introduction Clinical studies have demonstrated that adoptive transfer of allogeneic Natural Killer (NK) cells can play a therapeutic role in hematological malignancies and potentially solid tumors. We established and characterized ex vivo methods to obtain murine NK1.1 cells from mouse fetal liver. These cells represent an orthologous cell type for expanded cells from human cord or placenta. P...

using quarterly data from 2002:1 to 2013:2 we study the persistence in the inflation rates in iran based on the total cpi and the cpi in 12 subgroups. the persistence is investigated using two different tools: (i) the adf unit root test and (ii) bootstrap confidence intervals. we calculate a 90% confidence interval for the sum of the autoregressive coefficients, as a measure of persistence, usi...

Recent years have witnessed an increased interest in the application of persistent homology, a topological tool for data analysis, to machine learning problems. Persistent homology is known for its ability to numerically characterize the shapes of spaces induced by features or functions. On the other hand, deep neural networks have been shown effective in various tasks. To our best knowledge, h...