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Photophysics of a newly synthesized dyad and its nanocomposite forms in a chloroplast setting
No full textSpectroscopic studies by using steady state as well as time resolved techniques were conducted to examine how photophysical properties of the nanocomposite forms of a pristine short-chain-dyad, (E)-(((9H-fluorene-2-yl) imino) methyl)-N,Ndimethylaniline (NNDMBF) when combined with Carbon quantum dots (CQDs), Graphene quantum dots (GQDs), reduced graphene oxide (RGO) and graphene oxide (GO) change dramatically in the environment of Chloroplast (clp). These studies were made to examine whether nanocomposite systems could retain their properties to serve as artificial light energy converters and charge storage systems within clp. The present experimental results suggest that the long-term stability in the trans conformation of nanocomposite dyad decreases noticeably in clp environment, particularly for CQD where surface trap effects are the primary causes.However, in the presence of clp a nanocomposite, formed with either GQD, CQD, GO (or with RGO) predominates in its folded cis-form. This causes reduction its retention capability due to lesser amount of elongated trans-conformer in the excited state. Time resolved studies also reveal that clp environment favors the energy wasting charge recombination reactions considerably. The photoswitchable nature of nanocomposite systems is improved in clp environments which makes them suitable for application in building molecular photoswitches and hence be used in building logic gates, optical data storage, drug delivery, photolithography and sensors. Further the proposed theoretical model indicates in favor of the interactions involving the oxygen groups of chlorophyll present within clp and the nitrogen atoms located in the spacer region of the dyad.This could be the primary cause of the observed response in clp
Regional variation in body size and estimated secular change among adult Indian males born in the 1890s–1950s
No full textRegional variation in the body size of Indian men 18–84 years of age (birth years 1891–1957) was considered. Heights, weights, and BMIs of Indian males from four regions of the country – North, East-Northeast, Central, and West were compared. Heights of men 35+ years of age were adjusted for estimated height loss with age; the estimate was added to observed height to provide an estimate of maximum height. Linear regressions of measured height and estimated maximum height on year of birth were used to evaluate secular change by region. Differences in measured and estimated maximum heights and weight among regions were significant in all age groups, while differences in the BMI were significant in all age groups except 55+ years. Men from the North region were tallest and those from the East-Northeast region were shortest, while body weight and the BMI varied among regions. Regression analyses of year of birth on measured and estimated maximum heights indicated small differences in estimates of secular change among regions but suggested a decline in estimated maximum heights with age among men in the four regions born in 1891 through the 1930s, and small but variable estimates of secular change in heights among men born in the 1930s through 1957. The variation likely reflected socio-economic disparities and ecological differences among regions, and by inference nutritional status though data are limited
REGULARITY AND NUMERICAL APPROXIMATION OF FRACTIONAL ELLIPTIC DIFFERENTIAL EQUATIONS ON COMPACT METRIC GRAPHS
No full textThe fractional differential equation Lβu = f posed on a compact metric graph is considered, where β \u3e 0 and L = κ2 − ∇(a∇) is a second-order elliptic operator equipped with certain vertex conditions and sufficiently smooth and positive coefficients κ, a. We demonstrate the existence of a unique solution for a general class of vertex conditions and derive the regularity of the solution in the specific case of Kirchhoff vertex conditions. These results are extended to the stochastic setting when f is replaced by Gaussian white noise. For the deterministic and stochastic settings under generalized Kirchhoff vertex conditions, we propose a numerical solution based on a finite element approximation combined with a rational approximation of the fractional power L−β. For the resulting approximation, the strong error is analyzed in the deterministic case, and the strong mean squared error as well as the L2(Γ×Γ)error of the covariance function of the solution are analyzed in the stochastic setting. Explicit rates of convergences are derived for all cases. Numerical experiments for L = κ2 − Δ, κ \u3e 0 are performed to illustrate the results
Restricted Mean Value Property on Riemannian manifolds
No full textA well studied classical problem is the harmonicity of functions satisfying the restricted mean-value property (RMVP). While this has so far been studied mainly for domains in Rn, we consider this problem in the general setting of domains in Riemannian manifolds, and obtain results generalizing classical results of Fenton. We also obtain a result for complete, simply connected Riemannian manifolds of pinched negative curvature where there is no restriction on the radius function in the RMVP
Robust and efficient estimation in ordinal response models using the density power divergence
No full textIn real life, we frequently encounter ordinal variables depending upon independent covariates. The latent linear regression model is useful for modelling such data. One can find the model\u27s parameters\u27 maximum likelihood estimate (MLE). Though noted for its optimum properties, a small proportion of outliers may destabilize the MLE. This paper uses the minimum density power divergence estimate (MDPDE) as a robust alternative. The roles of different link functions are analysed in this context. We discuss their asymptotic properties in this setup. Unlike the MLE, the MDPDEs are robust for– lower values of the gross error sensitivity, and very high breakdown point. Also, the slope’s MDPDEs never implode. In simulation studies for pure data, MDPDEs perform almost as good as the MLE. However, the MDPDEs outperform the MLE in data contamination. Moreover, MDPDEs are very competitive with the other robust alternatives. Finally, this article is wrapped up with a real-data example.
Shallow Convolutional Neural Network for COVID-19 Outbreak Screening Using Chest X-rays
No full textAmong radiological imaging data, Chest X-rays (CXRs) are of great use in observing COVID-19 manifestations. For mass screening, using CXRs, a computationally efficient AI-driven tool is the must to detect COVID-19-positive cases from non-COVID ones. For this purpose, we proposed a light-weight Convolutional Neural Network (CNN)-tailored shallow architecture that can automatically detect COVID-19-positive cases using CXRs, with no false negatives. The shallow CNN-tailored architecture was designed with fewer parameters as compared to other deep learning models. The shallow CNN-tailored architecture was validated using 321 COVID-19-positive CXRs. In addition to COVID-19-positive cases, another set of non-COVID-19 5856 cases (publicly available, source: Kaggle) was taken into account, consisting of normal, viral, and bacterial pneumonia cases. In our experimental tests, to avoid possible bias, 5-fold cross-validation was followed, and both balanced and imbalanced datasets were used. The proposed model achieved the highest possible accuracy of 99.69%, sensitivity of 1.0, where AUC was 0.9995. Furthermore, the reported false positive rate was only 0.0015 for 5856 COVID-19-negative cases. Our results stated that the proposed CNN could possibly be used for mass screening. Using the exact same set of CXR collection, the current results were better than other deep learning models and major state-of-the-art works
Single-cell RNA sequencing of peripheral blood links cell-type-specific regulation of splicing to autoimmune and inflammatory diseases
No full textAlternative splicing contributes to complex traits, but whether this differs in trait-relevant cell types across diverse genetic ancestries is unclear. Here we describe cell-type-specific, sex-biased and ancestry-biased alternative splicing in ~1 M peripheral blood mononuclear cells from 474 healthy donors from the Asian Immune Diversity Atlas. We identify widespread sex-biased and ancestry-biased differential splicing, most of which is cell-type-specific. We identify 11,577 independent cis-splicing quantitative trait loci (sQTLs), 607 trans-sGenes and 107 dynamic sQTLs. Colocalization between cis-eQTLs and trans-sQTLs revealed a cell-type-specific regulatory relationship between HNRNPLL and PTPRC. We observed an enrichment of cis-sQTL effects in autoimmune and inflammatory disease heritability. Specifically, we functionally validated an Asian-specific sQTL disrupting the 5′ splice site of TCHP exon 4 that putatively modulates the risk of Graves’ disease in East Asian populations. Our work highlights the impact of ancestral diversity on splicing and provides a roadmap to dissect its role in complex diseases at single-cell resolution
Singularities of Feynman integrals
No full textIn this paper, we study the singularities of Feynman integrals by compactifying the integration domain as well as the ambient space of these integrals, by embedding them in higher-dimensional space. In this compactified space, the singularities occur due to the meeting of compactified propagators at non-general position. The present analysis, which had been previously used only for the singularities of second type, is used to study other kinds of singularities viz threshold, pseudo-threshold and anomalous threshold singularities. We study various one-loop and two-loop examples and obtain their singularities. We also present observations based on results obtained, that allow us to determine whether the singularities lie on the physical sheet or not for some simple cases. Thus, this work at the frontier of our knowledge of Feynman integral calculus sheds insight into the analytic structure