CORRELATION OF TWO PYRAZOLINE MOIETY IN A SINGLE MOLECULE VIA N-LINKAGE CONTAINING FLUORINE ATOM AS A SUBSTITUENT AND THEIR BIOLOGICAL SIGNIFICANCE

Objective: The aim of the present invention is to synthesize and find out the biological importance of the series of the designed pyrazoline compounds. Methods: A series of 3-[3'-(2â€,4â€-dichloro-5â€-fluorophenyl)-5'-(2â€-furyl)-4', 5'-dihydro-1H-pyrazol-1'-yl]-5-substituted phenyl-2-pyrazolines (2a-j) and 1-Nitroso-3-[3'-(2â€,4â€-dichloro-5â€-fluorophenyl)-5'-(2â€-furyl)-4', 5'-dihydro-1H-pyrazol-1'-yl]-5-substituted phenyl-2-pyrazolines (3a-j) were prepared in moderate yields. The structures of both pyrazoline and N-nitroso pyrazoline derivatives have been characterized on the basis of physical properties of the molecule and satisfactory spectral (IR, 1H NMR) data. The antimicrobial activity of the compounds against some Gram (+) and Gram (–) bacteria is reported. Results: The Moderate yield of the proposed compounds was obtained. Spectral analysis showed the structural confirmation of the synthesized compounds. Some of the compounds showed lower to moderate level of drug-like properties. Conclusion: From the results of spectral data and microbial activity it has been concluded that the compounds were found to exhibit some functional lead properties; hence these compounds are worth to be considered as potential lead molecules for further study

Euler characteristic and quadrilaterals of normal surfaces

Let $M$ be a compact 3-manifold with a triangulation $\tau$. We give an inequality relating the Euler characteristic of a surface $F$ normally embedded in $M$ with the number of normal quadrilaterals in $F$. This gives a relation between a topological invariant of the surface and a quantity derived from its combinatorial description. Secondly, we obtain an inequality relating the number of normal triangles and normal quadrilaterals of $F$, that depends on the maximum number of tetrahedrons that share a vertex in $\tau$.Comment: 7 pages, 1 figur

Takayasu arteritis in pregnancy: a case report, and clinical lessons learnt

A case report of known case of Takayasu arteritis (known to the woman in case report) in a primigravida, but unrevealed to the obstetrician till advanced stage of pregnancy is reported. The authors share the lessons learnt by them from this case which would improve diagnosis, evaluation and management of pregnancy hypertension. A brief account on clinical manifestations and diagnosis of Takayasu arteritis is also included

The Early Evolution of Magnetar Rotation I: Slowly Rotating "Normal" Magnetars

In the seconds following their formation in core-collapse supernovae, "proto"-magnetars drive neutrino-heated magneto-centrifugal winds. Using a suite of two-dimensional axisymmetric MHD simulations, we show that relatively slowly rotating magnetars with initial spin periods of $P_{\star0}=50-500$ ms spin down rapidly during the neutrino Kelvin-Helmholtz cooling epoch. These initial spin periods are representative of those inferred for normal Galactic pulsars, and much slower than those invoked for gamma-ray bursts and super-luminous supernovae. Since the flow is non-relativistic at early times, and because the Alfv\'en radius is much larger than the proto-magnetar radius, spindown is millions of times more efficient than the typically-used dipole formula. Quasi-periodic plasmoid ejections from the closed zone enhance spindown. For polar magnetic field strengths $B_0\gtrsim5\times10^{14}$ G, the spindown timescale can be shorter than than the Kelvin-Helmholtz timescale. For $B_0\gtrsim10^{15}$ G, it is of order seconds in early phases. We compute the spin evolution for cooling proto-magnetars as a function of $B_0$, $P_{\star0}$, and mass ($M$). Proto-magnetars born with $B_0$ greater than $\simeq1.3\times10^{15}\,{\rm\,G}\,(P_{\star0}/{400\,\rm\,ms})^{-1.4}(M/1.4\,{\rm M}_\odot)^{2.2}$ spin down to periods $> 1$ s in just the first few seconds of evolution, well before the end of the cooling epoch and the onset of classic dipole spindown. Spindown is more efficient for lower $M$ and for larger $P_{\star0}$. We discuss the implications for observed magnetars, including the discrepancy between their characteristic ages and supernova remnant ages. Finally, we speculate on the origin of 1E 161348-5055 in the remnant RCW 103, and the potential for other ultra-slowly rotating magnetars.Comment: 16 pages, 10 figure

Improving Diversity with Adversarially Learned Transformations for Domain Generalization

To be successful in single source domain generalization, maximizing diversity of synthesized domains has emerged as one of the most effective strategies. Many of the recent successes have come from methods that pre-specify the types of diversity that a model is exposed to during training, so that it can ultimately generalize well to new domains. However, na\"ive diversity based augmentations do not work effectively for domain generalization either because they cannot model large domain shift, or because the span of transforms that are pre-specified do not cover the types of shift commonly occurring in domain generalization. To address this issue, we present a novel framework that uses adversarially learned transformations (ALT) using a neural network to model plausible, yet hard image transformations that fool the classifier. This network is randomly initialized for each batch and trained for a fixed number of steps to maximize classification error. Further, we enforce consistency between the classifier's predictions on the clean and transformed images. With extensive empirical analysis, we find that this new form of adversarial transformations achieve both objectives of diversity and hardness simultaneously, outperforming all existing techniques on competitive benchmarks for single source domain generalization. We also show that ALT can naturally work with existing diversity modules to produce highly distinct, and large transformations of the source domain leading to state-of-the-art performance.Comment: WACV 2023. Code: https://github.com/tejas-gokhale/AL

Attribute-Guided Adversarial Training for Robustness to Natural Perturbations

While existing work in robust deep learning has focused on small pixel-level norm-based perturbations, this may not account for perturbations encountered in several real-world settings. In many such cases although test data might not be available, broad specifications about the types of perturbations (such as an unknown degree of rotation) may be known. We consider a setup where robustness is expected over an unseen test domain that is not i.i.d. but deviates from the training domain. While this deviation may not be exactly known, its broad characterization is specified a priori, in terms of attributes. We propose an adversarial training approach which learns to generate new samples so as to maximize exposure of the classifier to the attributes-space, without having access to the data from the test domain. Our adversarial training solves a min-max optimization problem, with the inner maximization generating adversarial perturbations, and the outer minimization finding model parameters by optimizing the loss on adversarial perturbations generated from the inner maximization. We demonstrate the applicability of our approach on three types of naturally occurring perturbations -- object-related shifts, geometric transformations, and common image corruptions. Our approach enables deep neural networks to be robust against a wide range of naturally occurring perturbations. We demonstrate the usefulness of the proposed approach by showing the robustness gains of deep neural networks trained using our adversarial training on MNIST, CIFAR-10, and a new variant of the CLEVR dataset.Comment: AAAI 2021. Camera Ready version + Appendi

The early evolution of magnetar rotation -- II. Rapidly rotating magnetars: Implications for Gamma-Ray Bursts and Super Luminous Supernovae

Rapidly rotating magnetars have been associated with gamma-ray bursts (GRBs) and super-luminous supernovae (SLSNe). Using a suite of 2D magnetohydrodynamic simulations at fixed neutrino luminosity and a couple of evolutionary models with evolving neutrino luminosity and magnetar spin period, we show that magnetars are viable central engines for powering GRBs and SLSNe. We also present analytic estimates of the energy outflow rate from the proto-neutron star (PNS) as a function of polar magnetic field strength $B_0$, PNS angular velocity $\Omega_{\star}$, PNS radius $R_{\star}$ and mass outflow rate $\dot{M}$. We show that rapidly rotating magnetars with spin periods $P_{\star}\lesssim 4$ ms and polar magnetic field strength $B_0\gtrsim 10^{15}$ G can release $10^{50}-5\times 10^{51}$ ergs of energy during the first $\sim2$ s of the cooling phase. Based on this result, it is plausible that sustained energy injection by magnetars through the relativistic wind phase can power GRBs. We also show that magnetars with moderate field strengths of $B_0\lesssim 5\times 10^{14}$ G do not release a large fraction of their rotational kinetic energy during the cooling phase and hence, are not likely to power GRBs. Although we cannot simulate to times greater than $\sim 3-5$ s after a supernova, we can hypothesize that moderate field strength magnetars can brighten the supernova light curves by releasing their rotational kinetic energy via magnetic dipole radiation on timescales of days to weeks, since these do not expend most of their rotational kinetic energy during the early cooling phase.Comment: 15 pages, 13 Figure

A case of pulmonary hemorrhage and renal failure

Background: Alveolar hemorrhage can be seen in many vasculitic disorders. However, granulomatosis polyangiitis (formerly Wegener’s granulomatosis) uncommonly presents with life threatening alveolar hemorrhage and has only been discussed in a few case reports [1]. Case Presentation: A 53 year old Caucasian male presented with hemoptysis and profound anemia. Two weeks prior, he had presented with abdominal pain with normal renal function and numerous pulmonary nodules. During the current admission, the patient was hypoxic with acute renal failure requiring hemodialysis. Urine sediment demonstrated dysmorphic red blood cells. A bronchoscopy revealed diffuse alveolar hemorrhage. The diagnosis of pulmonary-renal syndrome was made and therapeutic plasma exchange was initiated. Laboratory studies were significant for a c-ANCA titer positive at 1:640 FIU and anti-proteinase (PR)-3 antibody titer positive with 78.3 U/ml. Renal biopsy demonstrated necrotizing crescentic glomerulonephritis. A diagnosis of granulomatosis vasculitis was determined. Conclusion: Alveolar hemorrhage is rare to be the presenting symptom of granulomatosis vasculitis where the common presenting features are recurrent sinusitis, epistaxis, chronic otitis media or rhinitis. Physicians should consider granulomatosis vasculitis in the differential diagnosis of pulmonary-renal syndrome presenting with hemoptysis