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We study the modification of the electronic structure in the strong spin-orbit coupled Sr2IrO4 by epitaxial strain using density-functional methods. Structural optimization shows that strain changes the internal structural parameters such as the Ir-O-Ir bond angle, which has an important effect on the band structure. An interesting prediction is the Γ−X crossover of the valence band maximum with strain, while the conduction minimum at M remains unchanged. This in turn suggests strong strain dependence of the transport properties for the hole-doped system, but not when the system is electron doped. Taking the measured value of the Γ−X separation for the unstrained case, we predict the Γ−X crossover of the valence band maximum to occur for the tensile epitaxial strain exx 3%. A minimal tight-binding model within the Jeff = 1/2 subspace is developed to describe the main features of the band structure. The optical absorption spectra under epitaxial strain are computed using density-functional theory, which explains the observed anisotropy in the optical spectra with the polarization of the incident light. We show that the optical transitions between the Ir (d) states, which are dipole forbidden, can be explained in terms of the admixture of Ir (p) orbitals with the Ir (d) bands.

Automatic brain tumor segmentation using several image processing techniques supports early diagnosis and provides useful information for treatment planning. However, due to the heterogeneous nature of brain tumor makes the segmentation process very challenging and exhaustive. Glioma is one type of the fast-growing brain tumors. Its shape, size, and location vary across the patients. Manual extraction of exact glioma from brain MRI (Magnetic Resonance Imaging) is very tricky and time-consuming task for the radiologists. U-Net model is one of the most popular deep learning models for biomedical image segmentation utilized by the researchers and scientists around the world. The up-sampling and down-sampling architecture of U-Net model deliver a remarkable result with small amount of data in various medical image analysis applications. This paper presents the effect of different learning parameters on the performance of the deep U-Net model for brain tumor segmentation. Here, we have compared the performance by tuning the different learning parameters such as the activation function, pooling strategies, kernel or filter size, dropout and batch normalization and measured the accuracy in terms of AUC (area under the curve) and F1score. The experiment was performed on two well-known freely data sets available, BraTs 2017 and BraTs 2018. The whole tumor along with its core and enhancing parts were segmented from FLAIR (Fluid Attenuated Inversion Recovery) MR scans and it is observed that the AUC is improved by 2% in whole tumor segmentation from base model with fine-tuned parameters.

Climate change affects both the mean state and its variability. Hence, the decomposition of climate variability into a forced response and internal variability is essential to understand climate change. Especially how the hydrological cycle will change is still uncertain. Here, we use ensemble simulations to elucidate the forced response and internal variability changes in a hot world beyond 2100 in the Community Earth System Model version 2. We extract the dominant modes of the forced response and of internal variability. The dominant mode of the forced response of the hydrological cycle changes sign in the early 22nd century, even though greenhouse gas emissions are decreasing. We find that pronounced atmospheric circulation changes are largely responsible for the hydrological cycle shift. The dominant modes of internal variability exhibit significant reduced amplitude of the variability after the forced response mode changes its sign, suggesting that the forced response has significant impact on internal variability. These results have implications for anthropogenic climate change beyond 2100.

Background Spilosoma (=  Spilarctia ) obliqua (Walker) (Lepidoptera: Arctiidae), once considered as a sporadic pest, is now considered as a major and polyphagous pest widely distributed throughout India. Recent outbreaks of this pest were manifested in both jute and sunnhemp. During a survey in and around adjoining villages of I.C.A.R-C.R.I.J.A.F, Barrackpore, an epizootic was observed in the field population of S. obliqua caused by a nucleopolyhedrosis virus. Hence, an attempt was made to isolate, characterize using electron microscopy and assess the efficacy of S. obliqua nucleopolyhedrosis virus under laboratory and field conditions. Results Electron microscopic studies revealed typical baculovirus occlusion bodies of type nucleopolyhedrosis virus with tetrahedral and triangular in shape with the size ranging from 2.55 to 2.90 µm, with an average size of about 2.72 µm. Bioassay studies showed the larval mortality at low concentration of Spob NPV, i.e., 2.42 × 10 4  POBs/ml. The virus-infected S. obliqua was identified through the amplification of polyhedrin, polh gene sequences with the available sequences in public database, GenBank, NCBI. The sequence data generated for the polyhedrin gene were deposited in GenBank, and accession number was obtained, MN648213. Field experiment revealed 50.52, 63.25 and 82.91% larval reductions, respectively, at 2, 4 and 7 days after spray of S. obliqua nucleopolyhedrosis virus. Conclusion The present study revealed that foliar application of S. obliqua nucleopolyhedrosis virus was very effective in causing mortality against S. obliqua larvae and thus can be used as an effective microbial bioagent in the integrated pest management of the caterpillar, S. obliqua.

This study characterizes the variability in different parameters using high-frequency ground-based instruments, i.e., ceilometer and Micro Rain Radar (MRR), on a diurnal scale installed at the Indian Institute of Technology Bhubaneswar, Odisha, India. The study evaluates cloud base height (CBH) and boundary layer height (BLH) to understand their role in influencing convection from liquid water content (LWC), rain rate, radar reflectivity, and fall velocity over a tropical location for different seasons on a diurnal scale. The data retrieved from these surface-based instruments are segregated into four different seasons, i.e., pre-monsoon, monsoon, post-monsoon, and winter, for 2019 and 2020. It is noted that the atmospheric processes influencing convection and associated rainfall over the study location differ for different seasons. The frequency distribution of different types of clouds depending on their vertical levels, i.e., low-level clouds (LLC), mid-level clouds (MLC), and high-level clouds (HLC), during different seasons revealed a high occurrence of low- to mid-level clouds in pre-monsoon and post-monsoon seasons, mid-level clouds in the monsoon season, and low-level clouds in the winter season. The results also illustrate that the rainfall during different seasons largely depends on the types of clouds, i.e., LLC, MLC, and HLC, as detected from the CBH layers, which contribute to convection and rainfall over the study location. It is also revealed that the boundary layer processes in convection and rainfall influence the evolution of BLH during different seasons. Further, the study compares model skills in verifying boundary layer height and rainfall against surface-based observations. Besides characterizing the diurnal variability in these parameters on a daily scale, the study also elucidates the relationship between the cloud types and BLH. The results indicate that LLC occurrences were positively related to BLH during the pre-monsoon and monsoon seasons in 2019 and 2020. In contrast, a negative correlation is observed for cloud types MLC and HLC with BLH for the rest of the seasons of 2019 and 2020. Also, during post-monsoon and monsoon, distinct signatures of deep convection are noted over the study region, suggesting the influence of the boundary layer on MLC and HLC. The results from radar reflectivity and fall velocity during the monsoon and post-monsoon season support the influence of MLC and HLC on deep convection over the region. The diurnal variation in the observed parameters on a seasonal scale will help in understanding the role of various atmospheric parameters and processes in convection and associated rainfall over a tropical location and can provide necessary verification skills for weather and climate regional models against observations.

Rare earth (RE) and Mg ions co-doped ZnO samples were synthesized by wet-chemical method. XRD characterization of samples indicated that all samples crystalize in wurtzite structure of ZnO without the formation any additional phase. Morphological characterization revealed that all the samples display nanorod features. UV–Visible characterization showed that the Mg and RE co-doping leads to band gap narrowing in ZnO. The signature of green emission band in all the samples ascribed to the presence of defects like zinc vacancies, oxygen vacancies, donor–acceptor pairs, etc. Magnetic characterization indicated that all the samples exhibit weak ferromagnetism. The present study suggested that the samples could be beneficial for blue LED as well as photocatalytic application.

Yield loss to damage functions were established to determine multiple-pest economic injury levels (EILs) on jute, Corchorus olitoris L. (var. JRO 204) at different crop growth stages through field experiments during 2015–2017. The yield loss to damage functions were derived for two-pest combinations viz ., yellow mite, Polyphagotarsonemus latus (Banks) (Acari: Tarsonemidae) and lepidopterans i.e. Bihar hairy caterpillar (BHC), Spilosoma obliqua Walker (Lepidoptera: Arctiidae) and jute semilooper (SL), Anomis sabulifera Guenee (Lepidoptera: Noctuidae). The grouping of insects was made into different injury guilds, based on the plants' physiological response to insect injury. In the present study, the damage mechanism for yellow mite as sap assimilator and Bihar hairy caterpillar and semilooper as tissue consumer were grouped. Based on yield loss functions, single-species as well as multi-species EILs were determined. Across the experiments, single-species EILs of yellow mite combined with BHC and SL, ranged from 32.73–37.20 mites/cm 2 on the second unfolded leaf and 8.84–9.90% plant damage, respectively. The iso-loss equations were depicted by the various two-pest incidence combinations which resulted in economic damage although each pest was below its respective EIL. The multi-pest EILs can be useful to monitor the simultaneous occurrence of two-pest species thereby helping to prevent yield losses in jute.

We study the modification of the electronic structure in the strong spin–orbit coupled Sr2IrO4 by epitaxial strain using density-functional methods. Structural optimization shows that strain changes the internal structural parameters such as the Ir–O–Ir bond angle, which has an important effect on the band structure. An interesting prediction is the Γ-X crossover of the valence band maximum with strain, while the conduction minimum at M remains unchanged. This in turn suggests strong strain dependence of the transport properties for the hole-doped system, but not when the system is electron doped. Taking the measured value of the Γ-X separation for the unstrained case, we predict the Γ-X crossover of the valence band maximum to occur for the tensile epitaxial strain e xx ≈ 3%. A minimal tight-binding model within the J eff = 1/2 subspace is developed to describe the main features of the band structure. The optical absorption spectra under epitaxial strain are computed using density-functional theory, which explains the observed anisotropy in the optical spectra with the polarization of the incident light. We show that the optical transitions between the Ir (d) states, which are dipole forbidden, can be explained in terms of the admixture of Ir (p) orbitals with the Ir (d) bands.

The composites of 0.5(BiLa y Fe 1−y O 3 )–0.5(PbZrO 3 ) [y = 0.05, 0.10, 0.15 and 0.20] were synthesized through solid-state reaction technique. The X-ray diffraction data confirms the rhombohedral structure of the above systems at room temperature. From the SEM, it is shown that the grains were inhomogeneously distributed over the surface of the composites. The dielectric constant and loss of the composites increased with rise in temperature. The low remanent polarization (0.005, 0.006, 0.008, and 0.004 μC/cm 2 ) for 0.5(BiLa y Fe 1−y O 3 )–0.5(PbZrO 3 ) [y = 0.05, 0.10, 0.15 and 0.20] respectively shows the weak ferroelectric nature. The Nyquist plot showed the contribution of bulk effect and slight indication of grain boundary effect. The presence of temperature dependent relaxation process occurs in the material. The activation energies calculated from the ac conductivity using least square fitting. The dc and ac conductivity increases with rise in temperature. The ac conductivity spectrum obeyed Johnscher universal power law. The low remanent magnetization was found to be 0.010, 0.009, 0.008 and 0.005 emu/gm for 0.5(BiLa y Fe 1−y O 3 )–0.5(PbZrO 3 ) [y = 0.05, 0.10, 0.15 and 0.20] respectively.

We study the transition to complete synchronized state of two diffusively coupled identical chaotic parametric excited pendula, when uncoupled pendulum is in its oscillating chaotic motion only. We find the transition is through anti-lag synchronization, anti-synchronization, and lag synchronization. The analysis is based on numerical calculations of phase portraits, largest two Lyapunov and transverse Lyapunov exponents, bifurcation diagram from Poincaré sections, and the similarity functions as a function of coupling constant. Whenever the largest transverse Lyapunov exponent is equal to the second largest Lyapunov exponent of the coupled systems, the systems achieve complete synchronization.