Photoinduced absorption in disubstituted polyacetylenes: Comparison of theory with experiments

In a recently performed experiment Korovyanko et al [Phys. Rev. B 67, 035114 (2003)] have measured the photo-induced absorption (PA) spectrum of phenyl-disubstituted polyacetylenes (PDPA) from 1$B_{u}$ and 2$A_{g}$ excited states. In 1$B_{u}$ PA spectrum they identified two main features namely PA1 and PA2. While in the 2$A_{g}$ spectrum they identified only one feature called PA$_{g}$. In this paper we present a theoretical study of 1$B_{u}$ and 2$A_{g}$ PA spectra of oligo-PDPA's using correlated-electron Pariser-Parr-Pople (P-P-P) model and various configuration interaction (CI) methodologies. We compare the calculated spectra with the experiments, as well as with the calculated spectra of polyenes of the same conjugation lengths. Calculated spectra are in good agreement with the experiments. Based upon our calculations, we identify PA1 as the m$A_{g}$ state and PA$_{g}$ as the $nB_{u}$ state of the polymer. Regarding the PA2 feature, we present our speculations. Additionally, it is argued that the nature of excited states contributing to the $2A_{g}$-PA spectra of oligo-PDPA's is qualitatively different from those contributing to the spectra of polyenes.Comment: Revtex4, 14 pages, 8 figures (To appear in Phys. Rev. B, March 15 (2005) issue

Ab initio Wannier-function-based many-body approach to Born charge of crystalline insulators

In this paper we present an approach aimed at performing many-body calculations of Born-effective charges of crystalline insulators, by including the electron-correlation effects. The scheme is implemented entirely in the real space, using Wannier-functions as single-particle orbitals. Correlation effects are computed by including virtual excitations from the Hartree-Fock mean field, and the excitations are organized as per a Bethe-Goldstone-like many-body hierarchy. The results of our calculations suggest that the approach presented here is promising.Comment: 5 pages, to appear in Phys. Rev. B. (Rapid Comm., Dec 15, 2004

A Review on Vitamin D Deficiency

Vitamin D is a fat-soluble vitamin that plays an important role in bone metabolism and seems to have some anti-inflammatory and immune-modulating properties. In addition, recent epidemiologic studies have observed relationships between low vitamin D levels and multiple disease states. Low vitamin D levels are associated with increased overall and cardiovascular mortality, cancer incidence and mortality, and autoimmune diseases such as multiple sclerosis. Although it is well known that the combination of vitamin D and calcium is necessary to maintain bone density as people age, vitamin D may also be an independent risk factor for falls among the elderly. Vitamin D had been linked to skeletal disease including calcium, phosphorus, and bone metabolism, osteoporosis, fractures, muscle strength, and falls. In the 2000s, growing scientific attention turned to non-skeletal chronic diseases as vitamin D deficiency was linked to cancer, cardiovascular diseases, metabolic disorders, infectious diseases, and autoimmune diseases, as well as mortality

Ab initio Wannier-function-based correlated calculations of Born effective charges of crystalline Li2_{2}O and LiCl

In this paper we have used our recently developed ab initio Wannier-function-based methodology to perform extensive Hartree-Fock and correlated calculations on Li$_{2}$O and LiCl to compute their Born effective charges. Results thus obtained are in very good agreement with the experiments. In particular, for the case of Li$_{2}$O, we resolve a controversy originating in the experiment of Osaka and Shindo {[}Solid State Commun. 51 (1984) 421] who had predicted the effective charge of Li ions to be in the range 0.58--0.61, a value much smaller compared to its nominal value of unity, thereby, suggesting that the bonding in the material could be partially covalent. We demonstrate that effective charge computed by Osaka and Shindo is the Szigeti charge, and once the Born charge is computed, it is in excellent agreement with our computed value. Mulliken population analysis of Li$_{2}$O also confirms ionic nature of the bonding in the substance.Comment: 11 pages, 1 figure. To appear in Phys. Rev. B (Feb 2008

Vision-Based Intelligent Robot Grasping Using Sparse Neural Network

In the modern era of Deep Learning, network parameters play a vital role in models efficiency but it has its own limitations like extensive computations and memory requirements, which may not be suitable for real time intelligent robot grasping tasks. Current research focuses on how the model efficiency can be maintained by introducing sparsity but without compromising accuracy of the model in the robot grasping domain. More specifically, in this research two light-weighted neural networks have been introduced, namely Sparse-GRConvNet and Sparse-GINNet, which leverage sparsity in the robotic grasping domain for grasp pose generation by integrating the Edge-PopUp algorithm. This algorithm facilitates the identification of the top K% of edges by considering their respective score values. Both the Sparse-GRConvNet and Sparse-GINNet models are designed to generate high-quality grasp poses in real-time at every pixel location, enabling robots to effectively manipulate unfamiliar objects. We extensively trained our models using two benchmark datasets: Cornell Grasping Dataset (CGD) and Jacquard Grasping Dataset (JGD). Both Sparse-GRConvNet and Sparse-GINNet models outperform the current state-of-the-art methods in terms of performance, achieving an impressive accuracy of 97.75% with only 10% of the weight of GR-ConvNet and 50% of the weight of GI-NNet, respectively, on CGD. Additionally, Sparse-GRConvNet achieve an accuracy of 85.77% with 30% of the weight of GR-ConvNet and Sparse-GINNet achieve an accuracy of 81.11% with 10% of the weight of GI-NNet on JGD. To validate the performance of our proposed models, we conducted extensive experiments using the Anukul (Baxter) hardware cobot

Energetics and electronic structure of phenyl-disubstituted polyacetylene: A first-principles study

Phenyl-disubstituted polyacetylene (PDPA) is an organic semiconductor which has been studied during the last years for its efficient photo-luminescence. In contrast, the molecular geometry, providing the basis for the electronic and optical properties, has been hardly investigated. In this paper, we apply a density-functional-theory based molecular-dynamics approach to reveal the molecular structure of PDPA in detail. We find that oligomers of this material are limited in length, being stable only up to eight repeat units, while the polymer is energetically unfavorable. These facts, which are in excellent agreement with experimental findings, are explained through a detailed analysis of the bond lengths. A consequence of the latter is the appearance of pronounced torsion angles of the phenyl rings with respect to the plane of the polyene backbone, ranging from $55^{\circ}$ up to $95^{\circ}$. We point out that such large torsion angles do not destroy the conjugation of the $\pi$ electrons from the backbone to the side phenyl rings, as is evident from the electronic charge density.Comment: 9 pages, 7 figures, accepted for publication in Phys. Rev.

Context-aware 6D Pose Estimation of Known Objects using RGB-D data

6D object pose estimation has been a research topic in the field of computer vision and robotics. Many modern world applications like robot grasping, manipulation, autonomous navigation etc, require the correct pose of objects present in a scene to perform their specific task. It becomes even harder when the objects are placed in a cluttered scene and the level of occlusion is high. Prior works have tried to overcome this problem but could not achieve accuracy that can be considered reliable in real-world applications. In this paper, we present an architecture that, unlike prior work, is context-aware. It utilizes the context information available to us about the objects. Our proposed architecture treats the objects separately according to their types i.e; symmetric and non-symmetric. A deeper estimator and refiner network pair is used for non-symmetric objects as compared to symmetric due to their intrinsic differences. Our experiments show an enhancement in the accuracy of about 3.2% over the LineMOD dataset, which is considered a benchmark for pose estimation in the occluded and cluttered scenes, against the prior state-of-the-art DenseFusion. Our results also show that the inference time we got is sufficient for real-time usage

Sharing Science Through Shared Values, Goals, and Stories: An Evidence-Based Approach to Making Science Matter

Scientists in and beyond academia face considerable challenges to effectively sharing science, including lack of time and training, systemic disincentives, and the complexity of the modern media/attention landscape. Considering these constraints, 3 achievable shifts in mindset and practice can substantively enhance science communication efforts. Here, we provide evidence-based and experientially informed advice on how to center shared values, articulate science communication goals, and leverage the power of stories to advance our communication goals in connection with the values we share with our stakeholders. In addition to a discussion of relevant, foundational principles in science communication, we provide actionable recommendations and tools scientists can immediately use to articulate their values, identify shared values between stakeholders, set science communication goals, and use storytelling as a means of building and reinforcing relationships around shared values, thereby working productively to achieve those goals