Examinations of mechanical, and shielding properties of CeO2 reinforced B2O3-ZnF2-Er2O3-ZnO glasses for gamma-ray shield and neutron applications.

The glass system 75B2O3 - 4.5ZnF2 - 0.5 Er2O3- ( 20 - x ) ZnO- x CeO2, x = (0 ≤  x  ≤ 1 mol. %) was manufactured using a melt quenching process, with CeO2 substituted for ZnO in the glass matrix in concentrations ranging from 0 to 1 mol %. The Makishima-Mackenzie model and sound wave velocity measurements were used to evaluate the mechanical parameters and elastic characteristics of the examined glass system, respectively. The results showed that increasing CeO2 doping ratio from 0 to 1 mol% increased density, sound velocities, elastic properties, and microhardness from 5.80 to 9.01 GPa. Phy-X/PSD software was employed to assess the effect of replacing ZnO with CeO2 on shielding capacity. The obtained results revealed that replacing ZnO with CeO2 enhances shielding characteristics and the manufactured glass may be useful in shielding applications.

Development of a Rice Plant Disease Classification Model in Big Data Environment.

More than the half of the global population consume rice as their primary energy source. Therefore, this work focused on the development of a prediction model to minimize agricultural loss in the paddy field. Initially, rice plant diseases, along with their images, were captured. Then, a big data framework was used to encounter a large dataset. In this work, at first, feature extraction process is applied on the data and after that feature selection is also applied to obtain the reduced data with important features which is used as the input to the classification model. For the rice disease datasets, features based on color, shape, position, and texture are extracted from the infected rice plant images and a rough set theory-based feature selection method is used for the feature selection job. For the classification task, ensemble classification methods have been implemented in a map reduce framework for the development of the efficient disease prediction model. The results on the collected disease data show the efficiency of the proposed model.

New achievement of the global sheath-bulk model for the collisionless radio-frequency using in scale industries.

Plasma processing is extensively utilized in enormous industries products like semiconductor devices, textile fabrics, modifying polymers, and seed treatments. One of the most significant enhancements to this technology is the low pressure of capacitively coupled plasma (CCPs). Contrary to other plasma processes like atmospheric pressure plasma jet, low-pressure plasma under vacuum is the best choice for scale industrial applications, including etching, semiconductor IC fabrication, and seed processing for agricultural use. This is due to its full soft control and complete ionization chamber. It is quite difficult to analyze the dynamics of the plasma sheath theory. Despite being among the most relevant models, the step approximation model does not fully account for all nonlinear dynamics, particularly high harmonic effects, the particle density singularity between the sheath and bulk regions, and the absence of an ambipolar field in the bulk zone. We provide a significant solution to this issue in this study. The numerical fluid model for collisionless self-consistency is solved. As a result, the sheath charge distribution V(Q), which is considered as the main factor of control all nonlinear dynamics of the sheath, is estimated. Strong agreement between experimental data from the Ziegler et al. [7] study and our cubic fitting formula for the V(Q) distribution. Additionally, by compared the results of step approximation with the non step model, theoretical advancements like handling the particle density singularity and the merging of the sheath-bulk zone are further illustrated. Moreover, the most simple but effective solution at a minimal computing cost, the global model, is solved. By applying accurate sheath charge distribution, which controls all nonlinear dynamics, the global model's accuracy is established. As a result, more nonlinear dynamics are achieved, including distributions of currents, densities, charges, and power. Finally, excellent calculations of average power and sheath distance in case of collisionless region are calculated. Our study can find a more accurate physical and engineering approach which may help in industry applications.

De-novo Domestication for Improving Salt Tolerance in Crops.

Global agriculture production is under serious threat from rapidly increasing population and adverse climate changes. Food security is currently a huge challenge to feed 10 billion people by 2050. Crop domestication through conventional approaches is not good enough to meet the food demands and unable to fast-track the crop yields. Also, intensive breeding and rigorous selection of superior traits causes genetic erosion and eliminates stress-responsive genes, which makes crops more prone to abiotic stresses. Salt stress is one of the most prevailing abiotic stresses that poses severe damages to crop yield around the globe. Recent innovations in state-of-the-art genomics and transcriptomics technologies have paved the way to develop salinity tolerant crops. De novo domestication is one of the promising strategies to produce superior new crop genotypes through exploiting the genetic diversity of crop wild relatives (CWRs). Next-generation sequencing (NGS) technologies open new avenues to identifying the unique salt-tolerant genes from the CWRs. It has also led to the assembly of highly annotated crop pan-genomes to snapshot the full landscape of genetic diversity and recapture the huge gene repertoire of a species. The identification of novel genes alongside the emergence of cutting-edge genome editing tools for targeted manipulation renders de novo domestication a way forward for developing salt-tolerance crops. However, some risk associated with gene-edited crops causes hurdles for its adoption worldwide. Halophytes-led breeding for salinity tolerance provides an alternative strategy to identify extremely salt tolerant varieties that can be used to develop new crops to mitigate salinity stress.

Crosstalk of Multi-Omics Platforms with Plants of Therapeutic Importance.

From time immemorial, humans have exploited plants as a source of food and medicines. The World Health Organization (WHO) has recorded 21,000 plants with medicinal value out of 300,000 species available worldwide. The promising modern "multi-omics" platforms and tools have been proven as functional platforms able to endow us with comprehensive knowledge of the proteome, genome, transcriptome, and metabolome of medicinal plant systems so as to reveal the novel connected genetic (gene) pathways, proteins, regulator sequences and secondary metabolite (molecule) biosynthetic pathways of various drug and protein molecules from a variety of plants with therapeutic significance. This review paper endeavors to abridge the contemporary advancements in research areas of multi-omics and the information involved in decoding its prospective relevance to the utilization of plants with medicinal value in the present global scenario. The crosstalk of medicinal plants with genomics, transcriptomics, proteomics, and metabolomics approaches will be discussed.