Feynman-Enderlein Path Integral for Single-Molecule Nanofluidics

I present a photon statistics method for quasi-one dimensional sub-diffraction limited nanofluidic motions of single molecules using Feynman-Enderlein path integral approach. The theory is validated in Monte Carlo simulation platform to provide fundamental understandings of Knudsen type flow and diffusion of single molecule fluorescence in liquid. Distribution of single molecule burst size can be precise enough to detect molecular interaction. Realisation of this theoretical study considers several fundamental aspects of single-molecule nanofluidics, such as electrodynamics, photophysics, and multi-molecular events/molecular shot noise. I study two different sizes of molecules, one with 2 nm and another with 20 nm hydrodynamic radii driven by a wide range of flow velocities. The study reports distinctly different velocity dependent nanofluidic regimes, which have not been theoretically as well as experimentally reported earlier. Experimental single-molecule fluorescence bursts inside all-silica nanofluidic channels are used to validate the robustness of the method. It is not restricted to single molecule environment of uniform electrodynamic interactions and can be used to investigate complex refractive index mismatch related non-uniform single-molecule electrodynamic interactions as well. This fundamental investigation of single-molecule nanofluidics has a potential to accelerate the progress of dynamic and complex single-molecule experiments, such as dynamic heterogeneity, biomolecular interactions of misfolded proteins, and nanometric cavity electrodynamics.Comment: 8 page

Constraints on CP-violating gauge-Higgs operators

We consider the most general set of $SU(2) \times U(1)$ invariant CP-violating operators of dimension six, which contribute to $VVh$ interactions ($V = W, Z, \gamma$). Our aim is to constrain any CP-violating new physics above the electroweak scale via the effective couplings that arise when such physics is integrated out. For this purpose, we use, in turn, electroweak precision data, global fits of Higgs data at the Large Hadron Collider and the electric dipole moments of the neutron and the electron. We thus impose constraints mainly on two-parameter and three-parameter spaces. We find that the constraints from the electroweak precision data are the weakest. Among the existing Higgs search channels, considerable constraints come from the diphoton signal strength. We note that potential contribution to $h \rightarrow \gamma Z$ may in principle be a useful constraining factor, but it can be utilized only in the high energy run. The contributions to electric dipole moments mostly lead to the strongest constraints, though somewhat fine-tuned combinations of more than one parameter with large magnitudes are allowed. We also discuss constraints on gauge boson trilinear couplings which depend on the parameters of the CP-violating operators .Comment: Published in Physical Review

Single-photon-multi-layer-interference lithography for high-aspect-ratio and three-dimensional SU-8 micro-/nanostructures.

We report microstructures of SU-8 photo-sensitive polymer with high-aspect-ratio, which is defined as the ratio of height to in-plane feature size. The highest aspect ratio achieved in this work exceeds 250. A multi-layer and single-photon lithography approach is used in this work to expose SU-8 photoresist of thickness up to 100 μm. Here, multi-layer and time-lapsed writing is the key concept that enables nanometer localised controlled photo-induced polymerisation. We use a converging monochromatic laser beam of 405 nm wavelength with a controllable aperture. The reflection of the converging optics from the silicon substrate underneath is responsible for a trapezoidal edge profile of SU-8 microstructure. The reflection induced interfered point-spread-function and multi-layer-single-photon exposure helps to achieve sub-wavelength feature sizes. We obtained a 75 nm tip diameter on a pyramid shaped microstructure. The converging beam profile determines the number of multiple optical focal planes along the depth of field. These focal planes are scanned and exposed non-concurrently with varying energy dosage. It is notable that an un-automated height axis control is sufficient for this method. All of these contribute to realising super-high-aspect-ratio and 3D micro-/nanostructures using SU-8. Finally, we also address the critical problems of photoresist-based micro-/nanofabrication and their solutions

Associated Z′Z^\prime production in the flavorful U(1)U(1) scenario for RK(∗)R_{K^{(*)}}

The flavorful $Z^\prime$ model with its couplings restricted to the left-handed second generation leptons and third generation quarks can potentially resolve the observed anomalies in $R_K$ and $R_{K^*}$. After examining the current limits on this model from various low-energy processes, we probe this scenario at 14 TeV high-luminosity run of the LHC using two complementary channels: one governed by the coupling of $Z'$ to $b$-quarks and the other to muons. We also discuss the implications of the latest LHC high mass resonance searches in the dimuon channel on the model parameter space of our interest.Comment: 23 pages, 13 figures, 3 tables, Figures 5, 6, 7 and 8 have been modified, references have been updated, footnote added on page 12, version accepted for publication in The European Physical Journal

Transport of aerosols and nanoparticles through respirators and masks

In several countries wearing multiple surgical masks or N95 respirators was mandatory in public during the COVID pandemic. In this study, we investigated the transportation and filtering mechanism of heterogeneous nanoparticles and viruses through surgical masks and N95 respirators. We conducted experiments in vitro using aerosol spray paints containing nanoparticles and validated the findings in vivo on a human volunteer. Scanning electron microscopy was employed to analyse the transportation and distribution of nanoparticles in different mask layers and on pristine silicon substrates placed on human skin. We provide analytical insights into the pressure distribution and fluid velocity profiles within the complex polymer network. Remarkably, our results showed that both single surgical masks and N95 respirators demonstrated similar efficiency in filtering colloidal and jet-stream nanoparticles in the air. These comprehensive findings have significant implications for policymakers in defining regulations for airborne pandemics and air pollution control

Role of Organochlorine Pesticides in Chronic Kidney Diseases of Unknown Etiology

Chronic kidney disease (CKD) contributes to a significant burden on the healthcare system and economy worldwide. In the last two decades, a new form of CKD: chronic kidney disease of unknown etiology (CKDu) in which the disease is not attributed to known causes has emerged as a major health issue in different geographical areas over the world mainly from farming community and has become a global concern today. Despite intense and numerous research works dedicated to CKDu, very little is known with certainty regarding its etiology and the pathophysiology behind its development. Recent evidences are emerging in favor of possible role of agrochemicals and pesticides in the pathogenesis of CKDu. Organochlorine pesticides (OCPs) due to their longer half-life and lipophilic nature persist long in the environment and are known to be biomagnified through food chain. Some study reports by the authors and a few others constitute the important body of evidences depicting the association between chronic exposures to OCPs and occurrence of CKDu through environmental contamination in farming as well as non-farming communities in different geographical areas around the globe

Effective field theory of stochastic diffusion from gravity

Planar black holes in AdS have long-lived quasinormal modes which capture the physics of charge and momentum diffusion in the dual field theory. How should we characterize the effective dynamics of a probe system coupled to the conserved currents of the dual field theory? Specifically, how would such a probe record the long-lived memory of the black hole and its Hawking fluctuations? We address this question by exhibiting a universal gauge invariant framework which captures the physics of stochastic diffusion in holography: a designer scalar with a gravitational coupling governed by a single parameter, the Markovianity index. We argue that the physics of gauge and gravitational perturbations of a planar Schwarzschild-AdS black hole can be efficiently captured by such designer scalars. We demonstrate that this framework allows one to decouple, at the quadratic order, the long-lived quasinormal and Hawking modes from the short-lived ones. It furthermore provides a template for analyzing fluctuating open quantum field theories with memory. In particular, we use this set-up to analyze the diffusive Hawking photons and gravitons about a planar Schwarzschild-AdS black hole and derive the quadratic effective action that governs fluctuating hydrodynamics of the dual CFT. Along the way we also derive results relevant for probes of hyperscaling violating backgrounds at finite temperature.Comment: 57 pages + appendices. v2: typos fixed. v3: minor changes, published versio

DGPose: Deep Generative Models for Human Body Analysis

Deep generative modelling for human body analysis is an emerging problem with many interesting applications. However, the latent space learned by such approaches is typically not interpretable, resulting in less flexibility. In this work, we present deep generative models for human body analysis in which the body pose and the visual appearance are disentangled. Such a disentanglement allows independent manipulation of pose and appearance, and hence enables applications such as pose-transfer without specific training for such a task. Our proposed models, the Conditional-DGPose and the Semi-DGPose, have different characteristics. In the first, body pose labels are taken as conditioners, from a fully-supervised training set. In the second, our structured semi-supervised approach allows for pose estimation to be performed by the model itself and relaxes the need for labelled data. Therefore, the Semi-DGPose aims for the joint understanding and generation of people in images. It is not only capable of mapping images to interpretable latent representations but also able to map these representations back to the image space. We compare our models with relevant baselines, the ClothNet-Body and the Pose Guided Person Generation networks, demonstrating their merits on the Human3.6M, ChictopiaPlus and DeepFashion benchmarks.Comment: IJCV 2020 special issue on 'Generating Realistic Visual Data of Human Behavior' preprint. Keywords: deep generative models, semi-supervised learning, human pose estimation, variational autoencoders, generative adversarial network