Position-dependent power spectra of the 21-cm signal from the epoch of reionization

The 21-cm signal from the epoch of reionization is non-Gaussian. Current radio telescopes are focused on detecting the 21-cm power spectrum, but in the future the Square Kilometre Array is anticipated to provide a first measurement of the bispectrum. Previous studies have shown that the position-dependent power spectrum is a simple and efficient way to probe the squeezed-limit bispectrum. In this approach, the survey is divided into subvolumes and the correlation between the local power spectrum and the corresponding mean density of the subvolume is computed. This correlation is equivalent to an integral of the bispectrum in the squeezed limit, but is much simpler to implement than the usual bispectrum estimators. It also has a clear physical interpretation: it describes how the small-scale power spectrum of tracers such as galaxies and the 21-cm signal respond to a large-scale environment. Reionization naturally couples large and small scales as ionizing radiation produced by galactic sources can travel up to tens of Megaparsecs through the intergalactic medium during this process. Here we apply the position-dependent power spectrum approach to fluctuations in the 21-cm background from reionization. We show that this statistic has a distinctive evolution in time that can be understood with a simple analytic model. We also show that the statistic can easily distinguish between simple "inside-out" and "outside-in" models of reionization. The position-dependent power spectrum is thus a promising method to validate the reionization signal and to extract higher-order information on this process.Comment: 24 pages, 10 figures, accepted in JCA

A Study on Changes in GDP due to its Relative Dependence on Tourism Receipts

Tourism is a social phenomenon, driven by the natural urge of human beings to experience new places, cuisines, and destinations. The tourism industry being an established industry is considered as a vehicle for economic development. It is amongst the top ten sectors in India as it attracts a high level of foreign direct investment (FDI).The tourism industry has contributed a lot to the economy by attracting a large number of both foreign and domestic tourists travelling for professional as well as holiday purposes. This results in increased foreign exchange income and greater employment opportunities that stimulate the growth of tourism industry as well the overall economic growth.This research is mainly directed towards finding out the contribution of tourism sector towards the GDP of the country and giving suggestions on ways to improve it further. The possibilities of improvement and increase of foreign cash inflow is a crucial part of tourism sector towards contributions to the economy. The researcher has used correlation and regression to establish the relationship as well as the influence of the tourism sector towards GDP and has found a positive impact, and this has been evident in all the countries. But if we compare the GDP contribution of the tourism sector from a world perspective, Indian tourism sector has not contributed enough to GDP. World average contribution from tourism sector towards GDP is 9.8%,but India’s contribution towards GDP is 6.7%. This shows that there is huge opportunity in Indian tourism sector, and this huge opportunity has to be capitalized through government policies and reforms

The potential for liquid biopsies in the precision medical treatment of breast cancer.

Currently the clinical management of breast cancer relies on relatively few prognostic/predictive clinical markers (estrogen receptor, progesterone receptor, HER2), based on primary tumor biology. Circulating biomarkers, such as circulating tumor DNA (ctDNA) or circulating tumor cells (CTCs) may enhance our treatment options by focusing on the very cells that are the direct precursors of distant metastatic disease, and probably inherently different than the primary tumor's biology. To shift the current clinical paradigm, assessing tumor biology in real time by molecularly profiling CTCs or ctDNA may serve to discover therapeutic targets, detect minimal residual disease and predict response to treatment. This review serves to elucidate the detection, characterization, and clinical application of CTCs and ctDNA with the goal of precision treatment of breast cancer

Synthesis and Supramolecular Structure of a (5-(3-(1H-tetrazol-5-yl)phenyl)-1H-tetrazole) Cobalt Complex

The reaction of CoCl2·6H2O with m-BDTH2 (1,3-benzeneditetrazol-5-yl) leads to [Co(C8H6N8)2(H2O)2(CH3CN)2]Cl2 (1). Both tetrazolic groups remain protonated existing in a 1H tautomeric form. A trifurcated chlorine atom and stacking interactions assemble compound 1 into a three-dimensional network

The Influence of Halide Substituents on the Structural and Magnetic Properties of Fe6_{6}Dy3_{3} Rings

We report the synthesis and magnetic properties of three new nine-membered Fe(III)-Dy(III) cyclic coordination clusters (CCCs), with a core motif of [Fe$_{6}$Dy$_{3}$(μ-OMe)$_{9}$(vanox)$_{6}$(X-benz)$_{6}$] where the benzoate ligands are substituted in the para-position with X = F (1), Cl (2), Br (3). Single crystal X-ray diffraction structure analyses show that for the smaller fluorine or chlorine substituents the resulting structures exhibit an isostructural Fe$_{6}$Dy$_{3}$ core, whilst the 4-bromobenzoate ligand leads to structural distortions which affect the dynamic magnetic behavior. The magnetic susceptibility and magnetization of 1-3 were investigated and show similar behavior in the dc (direct current) magnetic data. Additional ac (alternating current) magnetic measurements show that all compounds exhibit frequency-dependent and temperature-dependent signals in the in-phase and out-of-phase component of the susceptibility and can therefore be described as field-induced SMMs. The fluoro-substituted benzoate cluster 1 shows a magnetic behavior closely similar to that of the corresponding unsubstituted Fe$_{6}$Dy$_{3}$ cluster, with U$_{eff}$ = 21.3 K within the Orbach process. By increasing the size of the substituent toward 4-chlorobenzoate within 2, an increase of the energy barrier to U$_{eff}$ = 36.1 K was observed. While the energy barrier becomes higher from 1 to 2, highlighting that the introduction of different substituents on the benzoate ligand in the para-position has an impact on the magnetic properties, cluster 3 shows a significantly different SMM behavior where U$_{eff}$ is reduced in the Orbach regime to only 4.9 K

A nickel(II) complex with an unsymmetrical tetradentate chelating ligand derived from pyridine-2,6-dicarbaldehyde and 2-aminothiophenol

[(2-{[6-(1,3-Benzo­thia­zol-2-yl)pyridin-2-yl]carbonyl­aza­nid­yl}phen­yl)sulf­anido]nickel(II), [Ni(C$_{19}$H$_{11}$N$_3$OS$_2$)], crystallizes in the centrosymmetric monoclinic space group $P2_1/n$ with one mol­ecule in the asymmetric unit. The expected ligand, a bis-Schiff base derived from pyridine-2,6-dicarbaldehyde and 2-amino­thio­phenol, had modified in situ in a both unexpected and unsymmetrical fashion. One arm had cyclized to form a benzo[$d$]thia­zol-2-yl functionality, while the imine linkage of the second arm had oxidized to an amide group. The geometry about the central Ni$^{II}$ atom is distorted square-planar N$_3$S. The mol­ecules form supra­molecular face-to-face dimers via rather strong π–π stacking inter­actions, with these dimers then linked into chains via pairwise C—H$\cdot\cdot\cdot$O inter­actions

An undecanuclear ferrimagnetic Cu9Dy2 SMM achieved through ligand fine-tuning

We describe the concept of increasing the nuclearity of a previously reported high-spin Cu5Gd2 core using a “fine tuning” ligand approach. Thus two Cu9Ln2 coordination clusters, with Ln = Dy (1), Gd(2) were synthesized with the Gd compound having a ground spin state of 17/2 and the Dy analogue showing SMM behavior in zero field

Semi-Siamese Network for Robust Change Detection Across Different Domains with Applications to 3D Printing

Automatic defect detection for 3D printing processes, which shares many characteristics with change detection problems, is a vital step for quality control of 3D printed products. However, there are some critical challenges in the current state of practice. First, existing methods for computer vision-based process monitoring typically work well only under specific camera viewpoints and lighting situations, requiring expensive pre-processing, alignment, and camera setups. Second, many defect detection techniques are specific to pre-defined defect patterns and/or print schematics. In this work, we approach the defect detection problem using a novel Semi-Siamese deep learning model that directly compares a reference schematic of the desired print and a camera image of the achieved print. The model then solves an image segmentation problem, precisely identifying the locations of defects of different types with respect to the reference schematic. Our model is designed to enable comparison of heterogeneous images from different domains while being robust against perturbations in the imaging setup such as different camera angles and illumination. Crucially, we show that our simple architecture, which is easy to pre-train for enhanced performance on new datasets, outperforms more complex state-of-the-art approaches based on generative adversarial networks and transformers. Using our model, defect localization predictions can be made in less than half a second per layer using a standard MacBook Pro while achieving an F1-score of more than 0.9, demonstrating the efficacy of using our method for in-situ defect detection in 3D printing