Ultracold quantum gases in triangular optical lattices

Over the last years the exciting developments in the field of ultracold atoms confined in optical lattices have led to numerous theoretical proposals devoted to the quantum simulation of problems e.g. known from condensed matter physics. Many of those ideas demand for experimental environments with non-cubic lattice geometries. In this paper we report on the implementation of a versatile three-beam lattice allowing for the generation of triangular as well as hexagonal optical lattices. As an important step the superfluid-Mott insulator (SF-MI) quantum phase transition has been observed and investigated in detail in this lattice geometry for the first time. In addition to this we study the physics of spinor Bose-Einstein condensates (BEC) in the presence of the triangular optical lattice potential, especially spin changing dynamics across the SF-MI transition. Our results suggest that below the SF-MI phase transition, a well-established mean-field model describes the observed data when renormalizing the spin-dependent interaction. Interestingly this opens new perspectives for a lattice driven tuning of a spin dynamics resonance occurring through the interplay of quadratic Zeeman effect and spin-dependent interaction. We finally discuss further lattice configurations which can be realized with our setup.Comment: 19 pages, 7 figure

Complications and carcinogenic effects of mustard gas - A systematic review and meta-analysis in Iran

Background: Catastrophic effects of mustard gas as a chemical warfare agent have always been a major problem for those exposed to this agent. In this meta-analysis it was tried to evaluate carcinogenesis, ocular, cutaneous and respiratory complications of mustard gas exposure among Iranians who had been exposed to this agent during the Iran-Iraq war. Materials and Methods: In this meta-analysis, the required data were collected using keywords "mustard gas", "sulfur mustard", "cancer", "neoplasm", "respiratory complications", "ocular complications", "lung disease", "chronic complication", "eye", "skin", "cutaneous complication", "carcinogenesis" and their combination with keywords "Iran", "Iranian", "prevalence", "mortality" and their Farsi equivalent terms from the databases of SID, Iranmedex, Magiran, Pubmed, Science Direct, Google Search engine, Gray Literature and Reference of References. To determine the prevalence of each complication and perform meta-analysis, CMA: 2 (Comprehensive Meta-Analysis) software with a randomized model was used. Results: Of the 542 articles found, 7 national articles, consistent with the aims of this study were selected. Metaanalysis of seven papers revealed that cancer risk, especially cancer of the respiratory system was elevated, so that the relative risk (RR) of cancer role of mustard gas was inconsistent from 2/1 to 4 in this survey. Also prevalence of delayed skin disorders due to sulfur mustard was 94.6, pulmonary complications 94.5 and ocular complications 89.9. The incidence of various cancers in victims exposed to mustard gas was 1.7 worldwide where the rate was 2.2 in Iranian victims of the Iraq-Iran war. Conclusions: Based on present study the prevalence of delayed mustard gas related cutaneous, pulmonary and ocular complications is above 90 and risk of carcinogenesis is higher in comparison to worldwide statistics. This may suggest need for long-term and persistent follow-up and rehabilitation procedures es for populations exposed to this agent

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

Autonomous assessment of spontaneous retinal venous pulsations in fundus videos using a deep learning framework

The presence or absence of spontaneous retinal venous pulsations (SVP) provides clinically significant insight into the hemodynamic status of the optic nerve head. Reduced SVP amplitudes have been linked to increased intracranial pressure and glaucoma progression. Currently, monitoring for the presence or absence of SVPs is performed subjectively and is highly dependent on trained clinicians. In this study, we developed a novel end-to-end deep model, called U3D-Net, to objectively classify SVPs as present or absent based on retinal fundus videos. The U3D-Net architecture consists of two distinct modules: an optic disc localizer and a classifier. First, a fast attention recurrent residual U-Net model is applied as the optic disc localizer. Then, the localized optic discs are passed on to a deep convolutional network for SVP classification. We trained and tested various time-series classifiers including 3D Inception, 3D Dense-ResNet, 3D ResNet, Long-term Recurrent Convolutional Network, and ConvLSTM. The optic disc localizer achieved a dice score of 95% for locating the optic disc in 30 milliseconds. Amongst the different tested models, the 3D Inception model achieved an accuracy, sensitivity, and F1-Score of 84 ± 5%, 90 ± 8%, and 81 ± 6% respectively, outperforming the other tested models in classifying SVPs. To the best of our knowledge, this research is the first study that utilizes a deep neural network for an autonomous and objective classification of SVPs using retinal fundus videos