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Images gathered from different satellites are vastly available these days due to the fast development of remote sensing (RS) technology. These images significantly enhance the data sources of change detection (CD). CD is a technique of recognizing the dissimilarities in the images acquired at distinct intervals and are used for numerous applications, such as urban area development, disaster management, land cover object identification, etc. In recent years, deep learning (DL) techniques have been used tremendously in change detection processes, where it has achieved great success because of their practical applications. Some researchers have even claimed that DL approaches outperform traditional approaches and enhance change detection accuracy. Therefore, this review focuses on deep learning techniques, such as supervised, unsupervised, and semi-supervised for different change detection datasets, such as SAR, multispectral, hyperspectral, VHR, and heterogeneous images, and their advantages and disadvantages will be highlighted. In the end, some significant challenges are discussed to understand the context of improvements in change detection datasets and deep learning models. Overall, this review will be beneficial for the future development of CD methods.

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aWe demonstrate the ability of multidimensional Laplace NMR (LNMR), comprising relaxation and diffusion experiments, to reveal essential information about microscopic phase structures and dynamics of ionic liquids that is not observable using conventional NMR spectroscopy or other techniques.Ionic liquids (ILs) are salts that consist of ions and have, by definition, melting points below 100 1C. They have unique physical and chemical properties such as high ionic conductivity, negligible vapour pressure, nonflammability, broad liquid phase temperature ranges, and high thermal stability, which all make ILs attractive in many scientific and technological applications. The applications include organic synthesis and catalysis, gas separation, extraction of metals, lubrication, electrochemistry, crystallization media for pharmaceutically active compounds and functional materials, etc. 1 NMR relaxation and diffusion experiments provide versatile information about the dynamics and structure of substances such as proteins, polymers, liquid crystals and porous media.2 They may also improve chemical resolution by distinguishing different components in complex systems without spectral resolution. 3 The relaxation and diffusion data consist of exponentially decaying components and the processing requires a Laplace inversion in order to determine diffusion coefficient and relaxation time distributions. 2 Therefore, these methods are referred to as Laplace NMR (LNMR). Like in traditional NMR spectroscopy, a multidimensional approach significantly enhances the resolution and information content of LNMR. 4 The approach makes it possible to correlate diffusion coefficients and relaxation times, and enables the investigation of chemical exchange even in the case when the exchanging sites are not resolved in the spectrum. The method requires a reliable and robust multidimensional Laplace inversion algorithm for extracting the diffusion coefficient and relaxation time distributions from the experimental data. 5NMR relaxation and diffusion experiments have been widely used to investigate physicochemical properties, hydrogen bonding, aggregation, solvation dynamics and atomic level interactions of ILs.6 However, to the best of our knowledge, the ability of Laplace inversion algorithms to provide distributions of relaxation times and diffusion coefficients has not yet exploited in studies of ILs. Furthermore, the potential of multidimensional LNMR to provide unique information about correlations and exchange is yet unexplored in the IL context. In this work, we demonstrate that a combination of several one-dimensional (1D) and two-dimensional (2D) LNMR experiments can provide important microscopic information about the phase structures of ILs, which is not possible using conventional NMR spectroscopy or other methods. We concentrate on the investigation of a halogen-free orthoborate based ionic liquid (hf-BIL).7 The affinity to absorb water, high polarity and toxicity make halogen containing ILs undesirable in many applications, and h...

Mathematical modeling, coding or labeling with the help of numeric numbers based on the parameter of distance plays a vital role in the studies of the structural properties of the networks such as accessibility, centrality, clustering, complexity, connectivity, modularity, robustness and vulnerability. In particular, various distance based dimensions of the networks are used to rectify the problems in different strata of computer science and chemistry such as navigation, image processing, pattern recognition, integer programming problem, drug discovery and formation of different chemical compounds. In this note, we consider a family of rotationally symmetric and planar networks called by circular ladders consisting of different faced triangles, quadrangles and pentagons. We compute local fractional metric dimensions of the aforesaid networks and study their boundedness. Moreover, our findings at the closure of this note have been summarized in the form of tables and 3-D plots. INDEX TERMS Fractional metric dimension, symmetric networks, resolving neighbourhoods.

Sub-fertility is one of the most common problems observed in crossbred males, but the etiology remains unknown in most of the cases. Although proteomic differences in the spermatozoa and seminal plasma between breeds have been investigated, the possible differences at the sperm precursor cells and supporting/nourishing cells have not been studied. The present study reports the differential proteomic profile of spermatogenic and Sertoli cells in crossbred and purebred bulls. Testis was removed by unilateral castration of 12 peri-pubertal bulls (10 months age), four each from crossbred (Holstein Friesian × Tharparkar), exotic purebred [Holstein Friesian (HF)] and indigenous purebred [Tharparkar (TP)] bulls. Spermatogenic and Sertoli cells were isolated and subjected to proteomic analysis. Protein extracts from the Sertoli and spermatogenic cells of each breed were analyzed with 2-dimensional difference gel electrophoresis (2D-DIGE) and analyzed with Decyder™ software. Compared to HF, 26 protein spots were over expressed and 14 protein spots were under expressed in spermatogenic cells of crossbred bulls. Similarly, 7 protein spots were over expressed and 15 protein spots were under expressed in the spermatogenic cells of TP bulls compared to that of crossbred bulls. Out of 12 selected protein spots identified through mass spectrometry, Phosphatidyl ethanolamine binding protein was found to be over expressed in the spermatogenic cells of crossbred bulls compared to TP bulls. The protein, gamma actin was found to be over expressed in the Sertoli cells of HF bulls, whereas Speedy Protein-A was found to be over expressed in Sertoli cells of crossbred bulls. It may be concluded that certain proteomic level differences exist in sperm precursor cells and nourishing cells between breeds, which might be associated with differences in the fertility among these breeds.

Aim:The present study compared the testicular cytology and histology between crossbred (Holstein–Friesian [HF] × Tharparkar) and purebred (HF and Tharparkar) bulls to find out differences if any.Materials and Methods:Four peripubertal bulls from each breed were utilized for the study. Through percutaneous needle aspiration biopsy, Sertoli and spermatogenic cells were extracted, and morphometry was studied. For histological studies, testicular tissues obtained through unilateral castration were utilized. Sertoli cells specific GATA4 antibody was used to study the population of Sertoli cells in the seminiferous tubule through immunofluorescence.Results:The testicular weight, volume, and scrotal circumference differed significantly among the breeds. The diameter and area of the seminiferous tubule was high in HF, followed by Karan Fries (KF), and Tharparkar bulls. However, the degree of compactness, based on qualitative evaluation, was high in Tharparkar followed by KF and HF bulls. The intensity of Leydig cells was higher in Tharparkar bulls followed by KF and HF. The proportion of Sertoli cells was higher (p<0.05) in HF and Tharparkar bulls compared to KF bulls.Conclusion:It may be concluded that variations exist in testicular components of the breeds studied and the proportion of Sertoli cells in relation to spermatogenic cells was significantly lower in crossbred bulls compared to purebred bulls.

Present study analyzed the changes in peripheral blood testosterone concentrations and testicular cytogram in relation to age and semen quality in crossbred males. Three different age groups of crossbred males viz. bull calves (6 months, n = 5), young bulls (15 months, n = 5) and adult bulls (4 to 6 years, n = 8) were utilized for the study. Testicular fine needle aspiration cytology technique was used to quantify testicular cytology and their indices. Peripheral blood testosterone concentrations were measured using enzyme-linked immunosorbent assay method. Semen samples collected from adult bulls were microscopically evaluated for quality parameters. Mean peripheral blood testosterone concentrations in bull calves, young bulls and adult bulls were 2.28±0.09 ng/mL, 1.42±0.22 ng/mL and 5.66±1.08 ng/mL respectively, and that in adult bulls were significantly different (p<0.01) from young bulls and bull calves. There was no significant difference between the proportion of different testicular cells in bull calves and young bulls. Between young and adult bulls, significant differences (p<0.01) were observed in the proportion of spermatocytes, spermatozoa, and sperm: Sertoli cell ratio. The proportions of Sertoli cells showed a significant difference (p<0.01) between the three age groups. The number of primary spermatocytes had a positive correlation with peripheral blood testosterone concentrations in bull calves (r = 0.719, p<0.01). Number of Sertoli cells per 100 germ cells was negatively correlated with blood testosterone concentration in young bulls (r = −0.713, p<0.01). Among different semen parameters in adult bulls, ejaculate volume (r = 0.790, p<0.05) had positive relationship, and sperm motility had significant negative correlation (r = −0.711, p<0.05) with testosterone concentrations. The number of Sertoli cells and Sertoli cell index had a positive correlation with various semen quality parameters (p<0.001). Results of the present study conclude that number of Sertoli cells and Sertoli cell index are good indicators of semen quality, but peripheral blood testosterone concentrations may not have a direct relationship with various seminal attributes in crossbred bulls.