Comparative Evaluation of Action Recognition Methods via Riemannian Manifolds, Fisher Vectors and GMMs: Ideal and Challenging Conditions

We present a comparative evaluation of various techniques for action recognition while keeping as many variables as possible controlled. We employ two categories of Riemannian manifolds: symmetric positive definite matrices and linear subspaces. For both categories we use their corresponding nearest neighbour classifiers, kernels, and recent kernelised sparse representations. We compare against traditional action recognition techniques based on Gaussian mixture models and Fisher vectors (FVs). We evaluate these action recognition techniques under ideal conditions, as well as their sensitivity in more challenging conditions (variations in scale and translation). Despite recent advancements for handling manifolds, manifold based techniques obtain the lowest performance and their kernel representations are more unstable in the presence of challenging conditions. The FV approach obtains the highest accuracy under ideal conditions. Moreover, FV best deals with moderate scale and translation changes

High resolution melting technique for molecular epidemiological studies of cystic echinococcosis: Differentiating G1, G3, and G6 genotypes of Echinococcus granulosus sensu lato

Reliable and rapid genotyping of large number of Echinococcus granulosus sensu lato isolates is crucial for understanding the epidemiology and transmission of cystic echinococcosis. We have developed a method for distinguishing and discriminating common genotypes of E. granulosus s.l. (G1, G3, and G6) in Iran. This method is based on polymerase chain reaction coupled with high resolution melting curve (HRM), ramping from 70 to 86 C with fluorescence data acquisition set at 0.1 C increments and continuous fluorescence monitoring. Consistency of this technique was assessed by inter- and intra-assays. Assessment of intra- and inter-assay variability showed low and acceptable coefficient of variations ranging from 0.09 to 0.17 %. Two hundred and eighty E. granulosus s.l. isolates from sheep, cattle, and camel were used to evaluate the applicability and accuracy of the method. The isolates were categorized as G1 (93, 94, and 25 %), G3 (7, 4, and 4 %), and G6 (0, 2, and 71 %) for sheep, cattle, and camel, respectively. HRM results were completely compatible with those obtained from sequencing and rostellar hook measurement. This method proved to be a valuable screening tool for large-scale molecular epidemiological studies. © 2013 Springer-Verlag Berlin Heidelberg

A Generalization of a Greguš Fixed Point Theorem in Metric Spaces

We first introduce a new class of contractive mappings in the setting of metric spaces and then we present certain Greguš type fixed point theorems for such mappings. As an application, we derive certain Greguš type common fixed theorems. Our results extend Greguš fixed point theorem in metric spaces and generalize and unify some related results in the literature. An example is also given to support our main result

A SVM-based method for face recognition using a wavelet PCA representation

ABSTRACT This paper proposes a new method of fac

Relationship between Social Determinants of Health and General Health Status of the Elderly in Alborz Province: Path Analysis

The purpose of this study was to examine the relationship between social determinants of health (SDH), quality of life, lifestyle, and general health of the aging people in Alborz province. A descriptive cross-sectional study conducted in 2000 aging people. A two-stage cluster sampling was applied to select participants. We used a four-section questionnaire. The statistical analysis was performed with AMOS 22. We used path analysis to examine whether SDH, QOL and lifestyle would directly or indirectly affect general health and whether the pathway model was acceptable. The general health status of the most of participants was low. The results of path analysis show that general health is affected by the SDH, lifestyle and quality of life. Our pathway model was an acceptable model. Variables such as marital status, educational level, job, income, number of family members, QOL, and lifestyle can be considered as predictors of general health status in the aging people. It can be concluded that it is necessary to provide appropriate strategies to promote general health of the elder person. © 2020, Springer Science+Business Media, LLC, part of Springer Nature

Classifying the unknown: discovering novel gravitational-wave detector glitches using similarity learning

The observation of gravitational waves from compact binary coalescences by LIGO and Virgo has begun a new era in astronomy. A critical challenge in making detections is determining whether loud transient features in the data are caused by gravitational waves or by instrumental or environmental sources. The citizen-science project \emph{Gravity Spy} has been demonstrated as an efficient infrastructure for classifying known types of noise transients (glitches) through a combination of data analysis performed by both citizen volunteers and machine learning. We present the next iteration of this project, using similarity indices to empower citizen scientists to create large data sets of unknown transients, which can then be used to facilitate supervised machine-learning characterization. This new evolution aims to alleviate a persistent challenge that plagues both citizen-science and instrumental detector work: the ability to build large samples of relatively rare events. Using two families of transient noise that appeared unexpectedly during LIGO's second observing run (O2), we demonstrate the impact that the similarity indices could have had on finding these new glitch types in the Gravity Spy program

Genome-wide association study identifies the SERPINB gene cluster as a susceptibility locus for food allergy

Genetic factors and mechanisms underlying food allergy are largely unknown. Due to heterogeneity of symptoms a reliable diagnosis is often difficult to make. Here, we report a genome-wide association study on food allergy diagnosed by oral food challenge in 497 cases and 2387 controls. We identify five loci at genome-wide significance, the clade B serpin (SERPINB) gene cluster at 18q21.3, the cytokine gene cluster at 5q31.1, the filaggrin gene, the C11orf30/LRRC32 locus, and the human leukocyte antigen (HLA) region. Stratifying the results for the causative food demonstrates that association of the HLA locus is peanut allergy-specific whereas the other four loci increase the risk for any food allergy. Variants in the SERPINB gene cluster are associated with SERPINB10 expression in leukocytes. Moreover, SERPINB genes are highly expressed in the esophagus. All identified loci are involved in immunological regulation or epithelial barrier function, emphasizing the role of both mechanisms in food allergy

Single-cell BCR and transcriptome analysis after influenza infection reveals spatiotemporal dynamics of antigen-specific B cells

B cell responses are critical for antiviral immunity. However, a comprehensive picture of antigen-specific B cell differentiation, clonal proliferation, and dynamics in different organs after infection is lacking. Here, by combining single-cell RNA and B cell receptor (BCR) sequencing of antigen-specific cells in lymph nodes, spleen, and lungs after influenza infection in mice, we identify several germinal center (GC) B cell subpopulations and organ-specific differences that persist over the course of the response. We discover transcriptional differences between memory cells in lungs and lymphoid organs and organ-restricted clonal expansion. Remarkably, we find significant clonal overlap between GC-derived memory and plasma cells. By combining BCR-mutational analyses with monoclonal antibody (mAb) expression and affinity measurements, we find that memory B cells are highly diverse and can be selected from both low- and high-affinity precursors. By linking antigen recognition with transcriptional programming, clonal proliferation, and differentiation, these finding provide important advances in our understanding of antiviral immunity