Constructive approximation in de Branges-Rovnyak spaces

In most classical holomorphic function spaces on the unit disk, a function $f$ can be approximated in the norm of the space by its dilates f\_r(z):=f(rz)~(r \textless{} 1). We show that this is \emph{not} the case for the de Branges--Rovnyak spaces \cH(b). More precisely, we give an example of a non-extreme point $b$ of the unit ball of $H^\infty$ and a function f\in\cH(b) such that \lim\_{r\to1^-}\|f\_r\|\_{\cH(b)}=\infty. It is known that, if $b$ is a non-extreme point of the unit ball of $H^\infty$, then polynomials are dense in \cH(b). We give the first constructive proof of this fact

On zero sets in the Dirichlet space

We study the zeros sets of functions in the Dirichlet space. Using Carleson formula for Dirichlet integral, we obtain some new families of zero sets. We also show that any closed subset of E \subset \TT with logarithmic capacity zero is the accumulation points of the zeros of a function in the Dirichlet space. The zeros satisfy a growth restriction which depends on $E$.Comment: Journal of Geometric Analysis (2011

Introducing a simple and economical method to purify Giardia lamblia cysts

Direct microscopic examination of stool to diagnosis giardiasis (wet mount) has low diagnostic value, but immunologic methods (like IFA and especially ELISA) that are based on the determination of parasite antigens in fecal samples (antigen detection) have relatively high sensitivity and specialty. To prepare anti-Giardia lamblia antibodies needed to design diagnostic kits as well as parasite culture and other molecular studies, we require purification of the parasite cysts. In this study, we designed a rapid, simple and inexpensive method to purify parasite cysts from fecal samples of the patients suffering from giardiasis. Initially, fecal samples that the presence of G. lamblia in them was affirmed by direct microscopic observation of cysts were subjected to various purification methods like one- and twophase sucrose gradient isolation, percoll-sucrose gradient isolation, and a modified two-phase method run by 0.85 and 1.5 M sucrose. The first procedure contained some contents of bacteria and small particles of feces. In the second and third procedure, bacteria were almost removed and the cysts were intact but the suspension contained some extras and cellulose particles. The recovery rate for modified two-phase method was 1.5 × 104 cysts for each two grams of fecal sample. In this study, by using and comparing with the results of some other studies, we introduce and run a modified method that in fact is a mélange of them with some changes. So this method could be recommended as a fast, advantageous and simple method in purification of G. lamblia cysts.Key words: Giardia lamblia, cyst, purification

Molecular diversity of Symbiodinium spp. within six coral species in Larak Island, the Persian Gulf

Reef-building coral harbor communities of photosynthetic taxa of the genus Symbiodinium (zooxanthellae). The genus Symbiodinium is currently classified into nine genetic clades (A–I). Various corals harbor different Symbiodinium clades; some show specificity to a single strain. Coral and their zooxanthellae are sensitive to environmental stresses. In the Persian Gulf, coral reefs are subject to harsh environmental conditions including extreme temperatures and high salinity. This is the first study to use clade specific primers to clarify the diversity of Symbiodinium in each coral species of Larak Island. For this purpose six coral species were collected at two different locations in Larak Island. After DNA extraction, PCR amplification was performed using clade specific primers. The results showed that multiple Symbiodinium clades are hosted by most coral species. In addition, among thirteen obtained Symbiodinium sequences, the frequency of either tree [sic] clades, A, C and D was almost the same. Corals species may contain different clades of Symbiodinium depending on the region and on the tolerance characteristics of each clade. Thus, knowledge of zooxanthellae diversity associated with scleractinian can contribute to a better understanding of the sensitivity of corals to environmental conditions

Designing of enzyme linked immunosorbent assay (ELISA) kit for diagnosis copro-antigens of Giardia lamblia

The sensitivity of microscopic examination of fecal samples to recognize Giardia parasites is low. In the methods based on antigen scanning of parasites such as enzyme linked immunosorbent assay (ELISA), copro-antigens of parasite will be traced and diagnosed even if the live parasite is absent in the fecal samples. To design this method, a pure antibody against parasite as well as an antibody conjugated to a proper enzyme is needed. In this study, an anti-Giardia IgG extracted from serum of contaminated rabbit was purified by ion-exchange chromatography and conjugated to the enzyme horse radish peroxidase (HRP). This antibody was used to design direct and indirect ELISA kits to measure conjugation titer. In both direct and indirect ELISA methods, optical densities (ODs) were 1 by using dilution of 1/4000 of conjugation. According to the results of both tests and the success in produced conjugate, it could be proceeded to prepare ELISA kits to diagnose giardiasis infections in various samples.Key words: Enzyme linked immunosorbent assay (ELISA), antibody, copro-antigen, Giardia lamblia

Manifold Contrastive Learning with Variational Lie Group Operators

Self-supervised learning of deep neural networks has become a prevalent paradigm for learning representations that transfer to a variety of downstream tasks. Similar to proposed models of the ventral stream of biological vision, it is observed that these networks lead to a separation of category manifolds in the representations of the penultimate layer. Although this observation matches the manifold hypothesis of representation learning, current self-supervised approaches are limited in their ability to explicitly model this manifold. Indeed, current approaches often only apply augmentations from a pre-specified set of "positive pairs" during learning. In this work, we propose a contrastive learning approach that directly models the latent manifold using Lie group operators parameterized by coefficients with a sparsity-promoting prior. A variational distribution over these coefficients provides a generative model of the manifold, with samples which provide feature augmentations applicable both during contrastive training and downstream tasks. Additionally, learned coefficient distributions provide a quantification of which transformations are most likely at each point on the manifold while preserving identity. We demonstrate benefits in self-supervised benchmarks for image datasets, as well as a downstream semi-supervised task. In the former case, we demonstrate that the proposed methods can effectively apply manifold feature augmentations and improve learning both with and without a projection head. In the latter case, we demonstrate that feature augmentations sampled from learned Lie group operators can improve classification performance when using few labels

Genome-wide analysis of alternative splicing events in Hordeum vulgare: highlighting retention of intron-based splicing and its possible function through network analysis

In this study, using homology mapping of assembled expressed sequence tags against the genomic data, we identified alternative splicing events in barley. Results demonstrated that intron retention is frequently associated with specific abiotic stresses. Network analysis resulted in discovery of some specific sub-networks between miRNAs and transcription factors in genes with high number of alternative splicing, such as cross talk between SPL2, SPL10 and SPL11 regulated by miR156 and miR157 families. To confirm the alternative splicing events, elongation factor protein (MLOC_3412) was selected followed by experimental verification of the predicted splice variants by Semi quantitative Reverse Transcription PCR (qRT-PCR). Our novel integrative approach opens a new avenue for functional annotation of alternative splicing through regulatory-based network discovery.Bahman Panahi, Seyed Abolghasem Mohammadi, Reyhaneh Ebrahimi Khaksefidi, Jalil Fallah Mehrabadi, Esmaeil Ebrahimi

High Performance Computing Applications in Remote Sensing Studies for Land Cover Dynamics

Global and regional land cover studies require the ability to apply complex models on selected subsets of large amounts of multi-sensor and multi-temporal data sets that have been derived from raw instrument measurements using widely accepted pre-processing algorithms. The computational and storage requirements of most such studies far exceed what is possible on a single workstation environment. We have been pursuing a new approach that couples scalable and open distributed heterogeneous hardware with the development of high performance software for processing, indexing, and organizing remotely sensed data. Hierarchical data management tools are used to ingest raw data, create metadata, and organize the archived data so as to automatically achieve computational load balancing among the available nodes and minimize I/O overheads. We illustrate our approach with four specific examples. The first is the development of the first fast operational scheme for the atmospheric correction of Landsat TM scenes, while the second example focuses on image segmentation using a novel hierarchical connected components algorithm. Retrieval of global BRDF (Bidirectional Reflectance Distribution Function) in the red and near infrared wavelengths using four years (1983 to 1986) of Pathfinder AVHRR Land (PAL) data set is the focus of our third example. The fourth example is the development of a hierarchical data organization scheme that allows on-demand processing and retrieval of regional and global AVHRR data sets. Our results show that substantial improvements in computational times can be achieved by using the high performance computing technology

Regional moisture change over India during the past Millennium: A comparison of multi-proxy reconstructions and climate model simulations

AbstractThe Indian Monsoon Variability during the past Millennium has been simulated with the ECHAM5 model in two different time slices: Medieval Climate Anomaly and the Little Ice Age. The simulations are compared with new centennial-resolving paleo-reconstructions inferred from various well-dated multi-proxies from two core regions, the Himalaya and Central India. A qualitative moisture index is derived from the proxies and compared with simulated moisture anomalies.The reconstructed paleo-hydrological changes between the Little Ice Age and the Medieval Climate Anomaly depict a dipole pattern between Himalaya and Central India, which is also captured by the model.In the Medieval Climate Anomaly the model exhibits stronger (weaker) dipole signals during summer (winter) compared to Little Ice Age. In summer (winter) months of “Medieval Climate Anomaly minus Little Ice Age” the model simulates wetter conditions over eastern (western and central) Himalaya. Over Central India, a simulated weakening of Indian Summer Monsoon during warmer climate is coincident with reconstructed drying signal in the Lonar Lake record.Based on the model simulations, we can differentiate three physical mechanisms which can lead to the moisture anomalies: (i) the western and central Himalaya are influenced by extra-tropical Westerlies during winter, (ii) the eastern Himalaya is affected by summer variations of temperature gradient between Bay of Bengal and Indian subcontinent and by a zonal band of intensified Indian–East Asian monsoon link north of 25°N, and (iii) Central India is dominated by summer sea surface temperature anomalies in the northern Arabian Sea which have an effect on the large-scale advection of moist air masses. The temperatures in the Arabian Sea are linked to the Indo Pacific Warm Pool, which modulates the Indian monsoon strength