Effect of cold stress on boro rice seedlings

Cold stress at seedling stage is a major constraint in boro rice production. Nine boro rice lines were crossed in diallel fashion excluding reciprocals to obtain 36 crosses. All the 36 crosses along with parents were grown in nursery in three seasons (boro-2014, kharif-2015 and boro-2015). Performance of seedlings for survival per cent, chlorophyll content, relative water content, membrane stability index was recorded just before transplanting in all the three seasons. Scoring for cold tolerance was done in both boro seasons. Gautam showed highest survival rate over three seasons. Among crosses, IR 64 x Krishna Hamsa showed highest survival (84%) in boro-2014, MTU 1010 x Jaya (86.33%) in boro-2015 and MTU 1010 x Krishna Hamsa (95.67%) in kharif-2015. Jaya x Krishna Hamsa was most cold tolerant cross over both boro seasons. Significant positive correlation was observed among survival per cent, chlorophyll content, relative water content and membrane stability index over seasons

Induction of male flowers on female plants of Cannabis sativa by gibberellins and its inhibition by abscisic acid

Gibberellins (GA3, GA4+7, GA7 and GA9) induce male flowers on female plants of Cannabis sativa. This is, depending on concentration, partially or fully inhibited by abscisic acid (ABA). The ABA effect can in turn be partially overcome by increasing the concentration of GA3

Modeling Barkhausen Noise in Magnetic Glasses with Dipole-Dipole Interactions

Long-ranged dipole-dipole interactions in magnetic glasses give rise to magnetic domains having labyrinthine patterns. Barkhausen Noise is then expected to result from the movement of domain boundaries which is supposed to be modeled by the motion of elastic membranes with random pinning. We propose an atomistic model of such magnetic glasses in which we measure the Barkhausen Noise which indeed results from the movement of domain boundaries. Nevertheless the statistics of the Barkhausen Noise is found in striking disagreement with the expectations in the literature. In fact we find exponential statistics without any power law, stressing the fact that Barkhausen Noise can belong to very different universality classes. In this glassy system the essence of the phenomenon is the ability of spin-carrying particles to move and minimize the energy without any spin flip. A theory is offered in excellent agreement with the measured data without any free parameter.Comment: 5 Pages, 5 Figures, Submitted to EP

Flux jumps, Second Magnetization Peak anomaly and the Peak Effect phenomenon in single crystals of YNi2B2CYNi_2B_2C and LuNi2B2CLuNi_2B_2C

We present magnetization measurements in single crystals of the tetragonal $YNi_2B_2C$ compound, which exhibit the phenomenon of peak effect as well as the second magnetization peak anomaly for H $>$ 0.5T (H $||$ c). At the lower field (50mT $<$ H $<$ 200mT), we have observed the presence of flux jumps, which seem to relate to a structural change in the local symmetry of the flux line lattice (a first order re-orientation transition across a local field in some parts of the sample, in the range of 100mT to 150mT). These flux jumps are also observed in a single crystal of $LuNi_2B_2C$ for H $||$ c in the field region from 2 mT to 25 mT, which are compatible with the occurrence of a re-orientation transition at a lower field in a cleaner crystal of this compound, as compared to those of $YNi_2B_2C$. Vortex phase diagrams drawn for H $||$ c in $LuNi_2B_2C$ and $YNi_2B_2C$ show that the ordered elastic glass phase spans a larger part of (H, T) space in the former as compared to latter, thereby, reaffirming the difference in the relative purity of the two samples.Comment: 11 pages, 14 figure

Combining ability and heterosis for yield, its component traits and some grain quality parameters in rice (Oryza sativa L.)

The experiment was conducted to estimate combining ability and heterosis for yield, yield attributing traits and few grain quality parameters in rice. The crosses were made among three CMS lines i.e., IR58025A, Pusa6A and IR68897A and seven pollen parents viz., Sarjoo-52, Jaya, Sasyashree, Swetha, HUR 5-2, PR-106 and BPT 5204. Twenty one hybrids were generated in line x tester design. The superior hybrids were identified on the basis of combining ability effect and heterosis. Cross combination IR68897A/Jaya and IR68897A/BPT 5204 exhibited good x good parental GCA effects suggesting that there is additive x additive type of gene action. The cross IR68897A/Jaya showed highest positive SCA effect. The higher magnitude of heterosis for all the yield and quality traits were not expressed in a single hybrid combination. It varied from cross to cross due to diverse genetic background of their parents. The two crosses IR68897A/Jaya and IR68897A/BPT 5204 were found to be heterotic for yield and yield traits as well as the grain quality characteristcs

Physics-Driven Turbulence Image Restoration with Stochastic Refinement

Image distortion by atmospheric turbulence is a stochastic degradation, which is a critical problem in long-range optical imaging systems. A number of research has been conducted during the past decades, including model-based and emerging deep-learning solutions with the help of synthetic data. Although fast and physics-grounded simulation tools have been introduced to help the deep-learning models adapt to real-world turbulence conditions recently, the training of such models only relies on the synthetic data and ground truth pairs. This paper proposes the Physics-integrated Restoration Network (PiRN) to bring the physics-based simulator directly into the training process to help the network to disentangle the stochasticity from the degradation and the underlying image. Furthermore, to overcome the ``average effect" introduced by deterministic models and the domain gap between the synthetic and real-world degradation, we further introduce PiRN with Stochastic Refinement (PiRN-SR) to boost its perceptual quality. Overall, our PiRN and PiRN-SR improve the generalization to real-world unknown turbulence conditions and provide a state-of-the-art restoration in both pixel-wise accuracy and perceptual quality. Our codes are available at \url{https://github.com/VITA-Group/PiRN}.Comment: Accepted by ICCV 202

Single Frame Atmospheric Turbulence Mitigation: A Benchmark Study and A New Physics-Inspired Transformer Model

Image restoration algorithms for atmospheric turbulence are known to be much more challenging to design than traditional ones such as blur or noise because the distortion caused by the turbulence is an entanglement of spatially varying blur, geometric distortion, and sensor noise. Existing CNN-based restoration methods built upon convolutional kernels with static weights are insufficient to handle the spatially dynamical atmospheric turbulence effect. To address this problem, in this paper, we propose a physics-inspired transformer model for imaging through atmospheric turbulence. The proposed network utilizes the power of transformer blocks to jointly extract a dynamical turbulence distortion map and restore a turbulence-free image. In addition, recognizing the lack of a comprehensive dataset, we collect and present two new real-world turbulence datasets that allow for evaluation with both classical objective metrics (e.g., PSNR and SSIM) and a new task-driven metric using text recognition accuracy. Both real testing sets and all related code will be made publicly available.Comment: This paper is accepted as a poster at ECCV 202