Spontaneous Symmetry Breakdown and Critical Perspectives of Higgs Mechanism

The foundations of the mass generation mechanism of particles are reviewed. The Spontaneous Symmetry Breaking (SSB) process within the standard model (SM) and the minimal supersymmetric standard model (MSSM) is used to explore the present status of the Higgs Mechanism along with the constraints in detecting the Higgs particles in experiments. The possible explanations and generalizations for the case that the Higgs particles should not appear or to couple the Higgs Mechanism (because of their gravitational nature of interaction) are also iscussed in detail in view of the Higgs field gravity.Comment: 13 pages, no figures. Final version based on original to appear in the Indian Journal of Physic

Formation of caustics in Dirac-Born-Infeld type scalar field systems

We investigate the formation of caustics in Dirac-Born-Infeld type scalar field systems for generic classes of potentials, viz., massive rolling scalar with potential, $V(\phi)=V_0e^{\pm \frac{1}{2} M^2 \phi^2}$ and inverse power-law potentials with $V(\phi)=V_0/\phi^n,~0<n<2$. We find that in the case of\texttt{} exponentially decreasing rolling massive scalar field potential, there are multi-valued regions and regions of likely to be caustics in the field configuration. However there are no caustics in the case of exponentially increasing potential. We show that the formation of caustics is inevitable for the inverse power-law potentials under consideration in Minkowski space time whereas caustics do not form in this case in the FRW universe.Comment: 16 pages, 14 figures, major revision, conclusions strengthen, to appear in PR

Black Hole Solutions and Pressure Terms in Induced Gravity with Higgs Potential

We study the quintessential properties of the Black Hole solutions in a scalar--tensor theory of gravity with Higgs potential in view of the static and spherically symmetric line element. In view of our earlier results, Reissner--Nordstr\"om-like and Schwarzschild Black Hole solutions are derived with the introduction of a series-expansion method to solve the field equations without and with Higgs field mass. The physical consequences of the Black Hole solutions and the solutions obtained in the weak field limit are discussed in detail by the virtue of the equation-of-state parameter, the scalar-field excitations and the geodesic motion. The appearance of naked singularities is also discussed together with the dependence of Black Hole horizons on the field excitations, which are themselves dependent on pressure terms which effectively screen the mass terms. A possible connection to flat rotation curves following the interaction with the scalar field is also presented in the weak field limit of gravity, together with a discussion of dynamical effects of scalar fields and pressure terms on mass.Comment: 28 pages, 4 figures, contents and figures modified, major revision, results are unchanged, published in Classical and Quantum Gravit

The structures of secretory and dimeric immunoglobulin A

Secretory (S) Immunoglobulin (Ig) A is the predominant mucosal antibody, which binds pathogens and commensal microbes. SIgA is a polymeric antibody, typically containing two copies of IgA that assemble with one joining-chain (JC) to form dimeric (d) IgA that is bound by the polymeric Ig-receptor ectodomain, called secretory component (SC). Here, we report the cryo-electron microscopy structures of murine SIgA and dIgA. Structures reveal two IgAs conjoined through four heavy-chain tailpieces and the JC that together form a β-sandwich-like fold. The two IgAs are bent and tilted with respect to each other, forming distinct concave and convex surfaces. In SIgA, SC is bound to one face, asymmetrically contacting both IgAs and JC. The bent and tilted arrangement of complex components limits the possible positions of both sets of antigen-binding fragments (Fabs) and preserves steric accessibility to receptor-binding sites, likely influencing antigen binding and effector functions

From a Census of 680,000 Street Trees to Smart Stormwater Management: A Study of Efficacy and Economics of Street Tree Guards in New York City

Green Infrastructure (GI) is a strategy of incorporating a distributed network of eco-technical systems that retain and detain stormwater to improve the hydrology of developed landscapes. GI is particularly needed in urban environments where roads, buildings, parking areas, and paved public spaces create a hardscape that results in rainfall rapidly running off and subsequently polluting natural waterways. However, the same dense, built-up environment that necessitates GI also creates a barrier to installing the amount of GI needed to meaningfully alter urban hydrologic behavior. Although a wide array of systems have been developed to fit in different urban niches, as exemplified by sedum green roofs, bioswales, rain gardens, rainwater harvesting, and permeable paving, many can be costly and difficult to integrate at scale. Thus, measuring and optimizing the performance of existing urban vegetation represents an important area of focus for stormwater management and offers potential for more economical use of resources allocated for GI. This paper focuses on examining the role of urban street trees in stormwater management

Advanced Ensemble Modeling Method For Space Object State Prediction Accounting For Uncertainty In Atmospheric Density

For objects in the low Earth orbit region, uncertainty in atmospheric density estimation is an important source of orbit prediction error, which is critical for space traffic management activities such as the satellite conjunction analysis. This paper investigates the evolution of orbit error distribution in the presence of atmospheric density uncertainties, which are modeled using probabilistic machine learning techniques. The recently proposed HASDM-ML, CHAMP-ML, and MSIS-UQ machine learning models for density estimation (Licata and Mehta, 2022b; Licata et al., 2022b) are used in this work. The investigation is convoluted because of the spatial and temporal correlation of the atmospheric density values. We develop several Monte Carlo methods, each capturing a different spatiotemporal density correlation, to study the effects of density uncertainty on orbit uncertainty propagation. However, Monte Carlo analysis is computationally expensive, so a faster method based on the Kalman filtering technique for orbit uncertainty propagation is also explored. It is difficult to translate the uncertainty in atmospheric density to the uncertainty in orbital states under a standard extended Kalman filter or unscented Kalman filter framework. This work uses the so-called consider covariance sigma point (CCSP) filter that can account for the density uncertainties during orbit propagation. As a testbed for validation purposes, a comparison between CCSP and Monte Carlo methods of orbit uncertainty propagation is carried out. Finally, using the HASDM-ML, CHAMP-ML, and MSIS-UQ density models, we propose an ensemble approach for orbit uncertainty quantification for four different space weather conditions

Genetic evaluation for understanding combining ability effects and Heterotic grouping in Maize (Zea mays L.)

Combining ability of the genotypes/lines is a major factor in planning the breeding programme and for development of Heterotic hybrids. In the present study, twenty maize inbred lines were crossed to three diverse testers CM-111, GPM-549 and GPM-581 and the resultant F1 hybrids were evaluated in an alpha lattice design. General combining ability of lines which is representation of additive gene action was found to be significant for all the quantitative traits. Specific combining ability which is indication of non-additive gene action was found to be significant for the traits number of kernel rows per cob, number of kernels per row, cob girth, cob length, test weight and grain yield. Lines VL-058725, VL-1018527 and VL-108723 produced heterotic hybrids in cross combination with any of the tester due to their high GCA effects. Whereas, the lines VL-0536, SNL-1574 and VL-109086 interacted positively with their testers thus producing heterotic hybrids with high positive SCA. GGE biplot analysis was helpful in visualizing the combining ability effects and identify heterotic pattern among theinbred lines. Heterotic grouping based on SCA and mean grain yield was able to classify thirteen of the twenty inbred lines into two distinct heterotic groups i.e., Heterotic group A and B consisting of six and seven lines respectively. Heterotic group A consisted of lines with high GCA whereas, heterotic group B with low GCA lines. SCA effect showed significant positive correlation with all the quantitative traits and played a prominent role in determining the performance of hybrids, thus indicating the importance of non-additive gene action in developingheterotic hybrids