Structural Changes and Ferroelectric Properties of BiFeO₃-PbTiO₃ Thin Films Grown via a Chemical Multilayer Deposition Method

Thin films of (1-x)BiFeO3-xPbTiO3 (BF-xPT) with x ~ 0.60 were fabricated on Pt/Si substrates by chemical solution deposition of precursor BF and PT layers alternately in three different multilayer configurations. These multilayer deposited precursor films upon annealing at 700{\deg}C in nitrogen show pure perovskite phase formation. In contrast to the equilibrium tetragonal structure for the overall molar composition of BF:PT::40:60, we find monoclinic structured BF-xPT phase of MA type. Piezo-force microscopy confirmed ferroelectric switching in the films and revealed different normal and lateral domain distributions in the samples. Room temperature electrical measurements show good quality ferroelectric hysteresis loops with remanent polarization, Pr, of up to 18 {\mu}C/cm2 and leakage currents as low as 10-7 A/cm2.Comment: 14 Pages and 6 figure

Non perturbative and thermal dynamics of confined fields in dual QCD

In order to study the detailed dynamics and associated non-perturbative features of QCD, a dual version of the color gauge theory based on the topologically viable homogeneous fiber bundle approach has been analysed taking into account its magnetic symmetry structure. In the dynamically broken phase of magnetic symmetry, the associated flux tube structure on a S 2 -sphere in the magnetically condensed state of the dual QCD vacuum has been analyzed for the profiles of the color electric field using flux quantization and stability conditions. The color electric field has its intimate association with the vector mode of the magnetically condensed QCD vacuum and such field configurations have been analyzed to show that the color electric flux gets localized towards the poles for a large sphere case while it gets uniformly distributed for the small sphere case in the infrared sector of QCD. The critical flux tube densities have been computed for various couplings and are shown to be in agreement with that for lead-ion central collisions in the near infrared sector of QCD. The possible annihilation/unification of flux tubes under some typical flux tube density and temperature conditions in the magnetic symmetry broken phase of QCD has also been analyzed and shown to play an important role in the process of QGP formation. The thermal variation of the profiles of the color electic field is further investigated which indicates the survival of flux tubes even in the thermal domain that leads the possibility of the formation of some exotic states like QGP in the intermedate regime during the quark-hadron phase transition

E-Recruiting : Anforderungen und Präferenzen von HR-Professionals

Karnal bunt disease in wheat is caused by hemibiotrophic fungus, Tilletia indica that has been placed as quarantine pest in more than 70 countries. Despite its economic importance, little knowledge about the molecular components of fungal pathogenesis is known. In this study, first time the genome sequence of T. indica has been deciphered for unraveling the effectors' functions of molecular pathogenesis of Karnal bunt disease. The T. indica genome was sequenced employing hybrid approach of PacBio Single Molecule Real Time (SMRT) and Illumina HiSEQ 2000 sequencing platforms. The genome was assembled into 10,957 contigs (N50 contig length 3 kb) with total size of 26.7 Mb and GC content of 53.99%. The number of predicted putative genes were 11,535, which were annotated with Gene Ontology databases. Functional annotation of Karnal bunt pathogen genome and classification of identified effectors into protein families revealed interesting functions related to pathogenesis. Search for effectors' genes using pathogen host interaction database identified 135 genes. The T. indica genome sequence and putative genes involved in molecular pathogenesis would further help in devising novel and effective disease management strategies including development of resistant wheat genotypes, novel biomarkers for pathogen detection and new targets for fungicide development

Simultaneous estimation of etodolac and thiocolchicoside in bulk and in tablet formulation by UV-spectrophotometry

Two simple, rapid and reproducible simultaneous equation and Q-Analysis UV-Spectrophotometric methods have been developed for simultaneous estimation of Etodolac (ETO) and Thiocolchicoside (THC) in combined tablet dosage form. The methods involved solving simultaneous equations and Q-value Analysis based on measurement of absorbance at wavelengths, 223 (λmax of ETO), 259.4 nm (λmax of THC) and 236 nm (Iso-absorptive point). Linearity was found in the concentration range of 1-6 μg/mL and 4 - 24 μg/mL for ETO & THC respectively with coefficient correlation 0.9998 & 0.9992. The amount of drugs estimated by proposed methods are in excellent agreement with label claimed. Further-more, the methods were applied for the determination of ETO and THC in spiked human urine. The degradation behavior of ETO and THC was investigated under acid hydrolysis, alkali hydrolysis, photo and oxidative degradation. The samples subsequently generated were used for degradation studies using the developed method. Thiocolchicoside was found to degrade extensively under alkali hydrolysis and unaffected by other stress conditions while ETO was found to be stable in all stress conditions. The methods were validated according to ICH guidelines. The method, suitable for routine quality control, has been successfully applied to the determination of both drugs in commercial brands of tablets

On vertex peripherians and Wiener index of graphs with fixed number of cut vertices

The distance of a vertex in a graph is the sum of distances from that vertex to all other vertices of the graph. The Wiener index of a graph is the sum of distances between all its unordered pairs of vertices. A graph has been obtained that contains a vertex achieving the maximum distance among all graphs on $n$ vertices with fixed number of cut vertices. Further the graphs having maximum Wiener index among all graphs on $n$ vertices with at most $3$ cut vertices have been characterised

Contrastive Learning-based Multi Modal Architecture for Emoticon Prediction by Employing Image-Text Pairs

The emoticons are symbolic representations that generally accompany the textual content to visually enhance or summarize the true intention of a written message. Although widely utilized in the realm of social media, the core semantics of these emoticons have not been extensively explored based on multiple modalities. Incorporating textual and visual information within a single message develops an advanced way of conveying information. Hence, this research aims to analyze the relationship among sentences, visuals, and emoticons. For an orderly exposition, this paper initially provides a detailed examination of the various techniques for extracting multimodal features, emphasizing the pros and cons of each method. Through conducting a comprehensive examination of several multimodal algorithms, with specific emphasis on the fusion approaches, we have proposed a novel contrastive learning based multimodal architecture. The proposed model employs the joint training of dual-branch encoder along with the contrastive learning to accurately map text and images into a common latent space. Our key finding is that by integrating the principle of contrastive learning with that of the other two branches yields superior results. The experimental results demonstrate that our suggested methodology surpasses existing multimodal approaches in terms of accuracy and robustness. The proposed model attained an accuracy of 91% and an MCC-score of 90% while assessing emoticons using the Multimodal-Twitter Emoticon dataset acquired from Twitter. We provide evidence that deep features acquired by contrastive learning are more efficient, suggesting that the proposed fusion technique also possesses strong generalisation capabilities for recognising emoticons across several modes