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

2 and 3-dimensional Hamiltonians with Shape Invariance Symmetry

Via a special dimensional reduction, that is, Fourier transforming over one of the coordinates of Casimir operator of su(2) Lie algebra and 4-oscillator Hamiltonian, we have obtained 2 and 3 dimensional Hamiltonian with shape invariance symmetry. Using this symmetry we have obtained their eigenspectrum. In the mean time we show equivalence of shape invariance symmetry and Lie algebraic symmetry of these Hamiltonians.Comment: 24 Page

Creating, moving and merging Dirac points with a Fermi gas in a tunable honeycomb lattice

Dirac points lie at the heart of many fascinating phenomena in condensed matter physics, from massless electrons in graphene to the emergence of conducting edge states in topological insulators [1, 2]. At a Dirac point, two energy bands intersect linearly and the particles behave as relativistic Dirac fermions. In solids, the rigid structure of the material sets the mass and velocity of the particles, as well as their interactions. A different, highly flexible approach is to create model systems using fermionic atoms trapped in the periodic potential of interfering laser beams, a method which so far has only been applied to explore simple lattice structures [3, 4]. Here we report on the creation of Dirac points with adjustable properties in a tunable honeycomb optical lattice. Using momentum-resolved interband transitions, we observe a minimum band gap inside the Brillouin zone at the position of the Dirac points. We exploit the unique tunability of our lattice potential to adjust the effective mass of the Dirac fermions by breaking inversion symmetry. Moreover, changing the lattice anisotropy allows us to move the position of the Dirac points inside the Brillouin zone. When increasing the anisotropy beyond a critical limit, the two Dirac points merge and annihilate each other - a situation which has recently attracted considerable theoretical interest [5-9], but seems extremely challenging to observe in solids [10]. We map out this topological transition in lattice parameter space and find excellent agreement with ab initio calculations. Our results not only pave the way to model materials where the topology of the band structure plays a crucial role, but also provide an avenue to explore many-body phases resulting from the interplay of complex lattice geometries with interactions [11, 12]

Topological orbital ladders

We unveil a topological phase of interacting fermions on a two-leg ladder of unequal parity orbitals, derived from the experimentally realized double-well lattices by dimension reduction. $Z_2$ topological invariant originates simply from the staggered phases of $sp$-orbital quantum tunneling, requiring none of the previously known mechanisms such as spin-orbit coupling or artificial gauge field. Another unique feature is that upon crossing over to two dimensions with coupled ladders, the edge modes from each ladder form a parity-protected flat band at zero energy, opening the route to strongly correlated states controlled by interactions. Experimental signatures are found in density correlations and phase transitions to trivial band and Mott insulators.Comment: 12 pages, 5 figures, Revised title, abstract, and the discussion on Majorana numbe

Land subsidence susceptibility mapping in South Korea using machine learning algorithms

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. In this study, land subsidence susceptibility was assessed for a study area in South Korea by using four machine learning models including Bayesian Logistic Regression (BLR), Support Vector Machine (SVM), Logistic Model Tree (LMT) and Alternate Decision Tree (ADTree). Eight conditioning factors were distinguished as the most important affecting factors on land subsidence of Jeong-am area, including slope angle, distance to drift, drift density, geology, distance to lineament, lineament density, land use and rock-mass rating (RMR) were applied to modelling. About 24 previously occurred land subsidence were surveyed and used as training dataset (70% of data) and validation dataset (30% of data) in the modelling process. Each studied model generated a land subsidence susceptibility map (LSSM). The maps were verified using several appropriate tools including statistical indices, the area under the receiver operating characteristic (AUROC) and success rate (SR) and prediction rate (PR) curves. The results of this study indicated that the BLR model produced LSSM with higher acceptable accuracy and reliability compared to the other applied models, even though the other models also had reasonable results

Novel hybrid evolutionary algorithms for spatial prediction of floods

Adaptive neuro-fuzzy inference system (ANFIS) includes two novel GIS-based ensemble artificial intelligence approaches called imperialistic competitive algorithm (ICA) and firefly algorithm (FA). This combination could result in ANFIS-ICA and ANFIS-FA models, which were applied to flood spatial modelling and its mapping in the Haraz watershed in Northern Province of Mazandaran, Iran. Ten influential factors including slope angle, elevation, stream power index (SPI), curvature, topographic wetness index (TWI), lithology, rainfall, land use, stream density, and the distance to river were selected for flood modelling. The validity of the models was assessed using statistical error-indices (RMSE and MSE), statistical tests (Friedman and Wilcoxon signed-rank tests), and the area under the curve (AUC) of success. The prediction accuracy of the models was compared to some new state-of-the-art sophisticated machine learning techniques that had previously been successfully tested in the study area. The results confirmed the goodness of fit and appropriate prediction accuracy of the two ensemble models. However, the ANFIS-ICA model (AUC = 0.947) had a better performance in comparison to the Bagging-LMT (AUC = 0.940), BLR (AUC = 0.936), LMT (AUC = 0.934), ANFIS-FA (AUC = 0.917), LR (AUC = 0.885) and RF (AUC = 0.806) models. Therefore, the ANFIS-ICA model can be introduced as a promising method for the sustainable management of flood-prone areas

Oscillations and interactions of dark and dark-bright solitons in Bose-Einstein condensates

Solitons are among the most distinguishing fundamental excitations in a wide range of non-linear systems such as water in narrow channels, high speed optical communication, molecular biology and astrophysics. Stabilized by a balance between spreading and focusing, solitons are wavepackets, which share some exceptional generic features like form-stability and particle-like properties. Ultra-cold quantum gases represent very pure and well-controlled non-linear systems, therefore offering unique possibilities to study soliton dynamics. Here we report on the first observation of long-lived dark and dark-bright solitons with lifetimes of up to several seconds as well as their dynamics in highly stable optically trapped $^{87}$Rb Bose-Einstein condensates. In particular, our detailed studies of dark and dark-bright soliton oscillations reveal the particle-like nature of these collective excitations for the first time. In addition, we discuss the collision between these two types of solitary excitations in Bose-Einstein condensates.Comment: 9 pages, 4 figure

Age-related variations in corneal biomechanical properties

Purpose To determine age-related changes in corneal viscoelastic properties in healthy individuals. Methods This observational cross-sectional study was performed at the Department of Ophthalmology, Imam Khomeini Hospital, Ahvaz, Iran and included 302 healthy individuals in 6 age decades (range: 10�69 years). After complete ocular examination, corneal viscoelastic properties were measured by ocular response analyzer and central corneal thickness (CCT) by an ultrasonic pachymeter. Our main outcome measures were corneal viscoelastic properties in different age groups. Results Corneal hysteresis (CH) and corneal resistance factor (CRF) showed a significant negative correlation with age (P < 0.001 for both, r = �0.353 and r = �0.246, respectively). Female gender had significantly higher CH (P = 0.017) and CRF (P = 0.019). CH and CRF were significantly correlated (P < 0.001, r = 0.821). CCT showed a biphasic pattern with significantly higher thicknesses before 20 and after 50 years of age. CH and CRF were significantly correlated with CCT (P < 0.001 for both, r = 0.21 and r = 0.26, respectively) and intraocular pressure (IOP) (P < 0.001 for both, r = �0.474 and r = 0.598, respectively). Corneal-compensated IOP (IOPcc) was significantly higher after age 40 compared to age group <20 (p < 0.045). Goldmann-correlated IOP (IOPg) was significantly correlated with CCT (P = 0.001, r = 0.193), while IOPcc showed no correlation with CCT (P = 0.265, r = 0.062). CH was significantly higher in hyperopic eyes compared to emmetropic eyes (P = 0.009) and myopic eye (P < 0.001). Conclusions In this study, there was a decrease in CH and CRF with an increase in age. Hyperopia and female gender are associated with higher CH and CRF. CCT is higher toward the extremes of life and is significantly correlated with CH and CRF. © 2016 Iranian Society of Ophthalmolog

Age-related variations in corneal biomechanical properties

Purpose To determine age-related changes in corneal viscoelastic properties in healthy individuals. Methods This observational cross-sectional study was performed at the Department of Ophthalmology, Imam Khomeini Hospital, Ahvaz, Iran and included 302 healthy individuals in 6 age decades (range: 10�69 years). After complete ocular examination, corneal viscoelastic properties were measured by ocular response analyzer and central corneal thickness (CCT) by an ultrasonic pachymeter. Our main outcome measures were corneal viscoelastic properties in different age groups. Results Corneal hysteresis (CH) and corneal resistance factor (CRF) showed a significant negative correlation with age (P < 0.001 for both, r = �0.353 and r = �0.246, respectively). Female gender had significantly higher CH (P = 0.017) and CRF (P = 0.019). CH and CRF were significantly correlated (P < 0.001, r = 0.821). CCT showed a biphasic pattern with significantly higher thicknesses before 20 and after 50 years of age. CH and CRF were significantly correlated with CCT (P < 0.001 for both, r = 0.21 and r = 0.26, respectively) and intraocular pressure (IOP) (P < 0.001 for both, r = �0.474 and r = 0.598, respectively). Corneal-compensated IOP (IOPcc) was significantly higher after age 40 compared to age group <20 (p < 0.045). Goldmann-correlated IOP (IOPg) was significantly correlated with CCT (P = 0.001, r = 0.193), while IOPcc showed no correlation with CCT (P = 0.265, r = 0.062). CH was significantly higher in hyperopic eyes compared to emmetropic eyes (P = 0.009) and myopic eye (P < 0.001). Conclusions In this study, there was a decrease in CH and CRF with an increase in age. Hyperopia and female gender are associated with higher CH and CRF. CCT is higher toward the extremes of life and is significantly correlated with CH and CRF. © 2016 Iranian Society of Ophthalmolog

A novel ensemble artificial intelligence approach for gully erosion mapping in a semi-arid watershed (Iran)

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. In this study, we introduced a novel hybrid artificial intelligence approach of rotation forest (RF) as a Meta/ensemble classifier based on alternating decision tree (ADTree) as a base classifier called RF-ADTree in order to spatially predict gully erosion at Klocheh watershed of Kurdistan province, Iran. A total of 915 gully erosion locations along with 22 gully conditioning factors were used to construct a database. Some soft computing benchmark models (SCBM) including the ADTree, the Support Vector Machine by two kernel functions such as Polynomial and Radial Base Function (SVM-Polynomial and SVM-RBF), the Logistic Regression (LR), and the Naïve Bayes Multinomial Updatable (NBMU) models were used for comparison of the designed model. Results indicated that 19 conditioning factors were effective among which distance to river, geomorphology, land use, hydrological group, lithology and slope angle were the most remarkable factors for gully modeling process. Additionally, results of modeling concluded the RF-ADTree ensemble model could significantly improve (area under the curve (AUC) = 0.906) the prediction accuracy of the ADTree model (AUC = 0.882). The new proposed model had also the highest performance (AUC = 0.913) in comparison to the SVM-Polynomial model (AUC = 0.879), the SVM-RBF model (AUC = 0.867), the LR model (AUC = 0.75), the ADTree model (AUC = 0.861) and the NBMU model (AUC = 0.811)