Bond Breaking and Bond Formation: How Electron Correlation is Captured in Many-Body Perturbation Theory and Density-Functional Theory

For the paradigmatic case of H2-dissociation we compare state-of-the-art many-body perturbation theory (MBPT) in the GW approximation and density-functional theory (DFT) in the exact-exchange plus random-phase approximation for the correlation energy (EX+cRPA). For an unbiased comparison and to prevent spurious starting point effects both approaches are iterated to full self-consistency (i.e. sc-RPA and sc-GW). The exchange-correlation diagrams in both approaches are topologically identical, but in sc-RPA they are evaluated with non-interacting and in sc-GW with interacting Green functions. This has a profound consequence for the dissociation region, where sc-RPA is superior to sc-GW. We argue that for a given diagrammatic expansion, the DFT framework outperforms the many-body framework when it comes to bond-breaking. We attribute this to the difference in the correlation energy rather than the treatment of the kinetic energy.Comment: 6 pages, 4 figure

Controlling A Gas Plant Using State Space Approach

Monitoring and controlling of a plant’s process variables can be carried out using the computer via software in the instrumentation and control industry. Control systems oil and gas industries are designed using the conventional approach, as opposed to the modern control approach commonly used in\ud aerospace industries, thus controller qualities such as robustness, optimality and adaptivity could have been overlooked. This project aims to theoretically apply the concepts of modern control engineering in plant process control systems. The entire project involves understanding process control and state space, grasping the concept of system identification and mastering the functions of MATLAB and Simulink for controller and observer design and simulation. Extensive utilization of MATLAB and Simulink were involved in the several experiments and simulations that were carried out and run. Results from this project indicate the practicality of modern control in plant process control systems. This project successfully achieved the theoretical implementation of modern control engineering in plant process control systems, paving way for a possible design of a new controller and observer strategy that are robust, optimal and adaptive via modern control approach

Increased risk for T cell autoreactivity to ß-cell antigens in the mice expressing the Avy obesity-associated gene.

There has been considerable debate as to whether obesity can act as an accelerator of type 1 diabetes (T1D). We assessed this possibility using transgenic mice (MIP-TF mice) whose ß-cells express enhanced green fluorescent protein (EGFP). Infecting these mice with EGFP-expressing murine herpes virus-68 (MHV68-EGFP) caused occasional transient elevation in their blood glucose, peri-insulitis, and Th1 responses to EGFP which did not spread to other ß-cell antigens. We hypothesized that obesity-related systemic inflammation and ß-cell stress could exacerbate the MHV68-EGFP-induced ß-cell autoreactivity. We crossed MIP-TF mice with Avy mice which develop obesity and provide models of metabolic disease alongside early stage T2D. Unlike their MIP-TF littermates, MHV68-EGFP-infected Avy/MIP-TF mice developed moderate intra-insulitis and transient hyperglycemia. MHV68-EGFP infection induced a more pronounced intra-insulitis in older, more obese, Avy/MIP-TF mice. Moreover, in MHV68-EGFP-infected Avy/MIP-TF mice, Th1 reactivity spread from EGFP to other ß-cell antigens. Thus, the spreading of autoreactivity among ß-cell antigens corresponded with the transition from peri-insulitis to intra-insulitis and occurred in obese Avy/MIP-TF mice but not lean MIP-TF mice. These observations are consistent with the notion that obesity-associated systemic inflammation and ß-cell stress lowers the threshold necessary for T cell autoreactivity to spread from EGFP to other ß-cell autoantigens

Effects of Parkinson’s disease on optic flow perception for heading direction during navigation

Visuoperceptual disorders have been identified in individuals with Parkinson’s disease (PD) and may affect the perception of optic flow for heading direction during navigation. Studies in healthy subjects have confirmed that heading direction can be determined by equalizing the optic flow speed (OS) between visual fields. The present study investigated the effects of PD on the use of optic flow for heading direction, walking parameters, and interlimb coordination during navigation, examining the contributions of OS and spatial frequency (dot density). Twelve individuals with PD without dementia, 18 age-matched normal control adults (NC), and 23 young control adults (YC) walked through a virtual hallway at about 0.8 m/s. The hallway was created by random dots on side walls. Three levels of OS (0.8, 1.2, and 1.8 m/s) and dot density (1, 2, and 3 dots/m2) were presented on one wall while on the other wall, OS and dot density were fixed at 0.8 m/s and 3 dots/m2, respectively. Three-dimensional kinematic data were collected, and lateral drift, walking speed, stride frequency and length, and frequency, and phase relations between arms and legs were calculated. A significant linear effect was observed on lateral drift to the wall with lower OS for YC and NC, but not for PD. Compared to YC and NC, PD veered more to the left under OS and dot density conditions. The results suggest that healthy adults perceive optic flow for heading direction. Heading direction in PD may be more affected by the asymmetry of dopamine levels between the hemispheres and by motor lateralization as indexed by handedness.Published versio

The thermodynamic landscape of carbon redox biochemistry

Redox biochemistry plays a key role in the transduction of chemical energy in all living systems. Observed redox reactions in metabolic networks represent only a minuscule fraction of the space of all possible redox reactions. Here we ask what distinguishes observed, natural redox biochemistry from the space of all possible redox reactions between natural and non-natural compounds. We generate the set of all possible biochemical redox reactions involving linear chain molecules with a fixed numbers of carbon atoms. Using cheminformatics and quantum chemistry tools we analyze the physicochemical and thermodynamic properties of natural and non-natural compounds and reactions. We find that among all compounds, aldose sugars are the ones with the highest possible number of connections (reductions and oxidations) to other molecules. Natural metabolites are significantly enriched in carboxylic acid functional groups and depleted in carbonyls, and have significantly higher solubilities than non-natural compounds. Upon constructing a thermodynamic landscape for the full set of reactions as a function of pH and of steady-state redox cofactor potential, we find that, over this whole range of conditions, natural metabolites have significantly lower energies than the non-natural compounds. For the set of 4-carbon compounds, we generate a Pourbaix phase diagram to determine which metabolites are local energetic minima in the landscape as a function of pH and redox potential. Our results suggest that, across a set of conditions, succinate and butyrate are local minima and would thus tend to accumulate at equilibrium. Our work suggests that metabolic compounds could have been selected for thermodynamic stability, and yields insight into thermodynamic and design principles governing nature’s metabolic redox reactions.https://www.biorxiv.org/content/10.1101/245811v1Othe

A new framework for consensus for discrete-time directed networks of multi-agents with distributed delays

Copyright @ 2012 Taylor & FrancisIn this article, the distributed consensus problem is considered for discrete-time delayed networks of dynamic agents with fixed topologies, where the networks under investigation are directed and the time-delays involved are distributed time delays including a single or multiple time delay(s) as special cases. By using the invariance principle of delay difference systems, a new unified framework is established to deal with the consensus for the discrete-time delayed multi-agent system. It is shown that the addressed discrete-time network with arbitrary distributed time delays reaches consensus provided that it is strongly connected. A numerical example is presented to illustrate the proposed methods.This work was supported in part by City University of Hong Kong under Grant 7008114, the Royal Society of the UK, the National Natural Science Foundation of China under Grants 60774073 and 61074129, and the Natural Science Foundation of Jiangsu Province of China under Grant BK2010313

SQ Lower Bounds for Non-Gaussian Component Analysis with Weaker Assumptions

We study the complexity of Non-Gaussian Component Analysis (NGCA) in the Statistical Query (SQ) model. Prior work developed a general methodology to prove SQ lower bounds for this task that have been applicable to a wide range of contexts. In particular, it was known that for any univariate distribution $A$ satisfying certain conditions, distinguishing between a standard multivariate Gaussian and a distribution that behaves like $A$ in a random hidden direction and like a standard Gaussian in the orthogonal complement, is SQ-hard. The required conditions were that (1) $A$ matches many low-order moments with the standard univariate Gaussian, and (2) the chi-squared norm of $A$ with respect to the standard Gaussian is finite. While the moment-matching condition is necessary for hardness, the chi-squared condition was only required for technical reasons. In this work, we establish that the latter condition is indeed not necessary. In particular, we prove near-optimal SQ lower bounds for NGCA under the moment-matching condition only. Our result naturally generalizes to the setting of a hidden subspace. Leveraging our general SQ lower bound, we obtain near-optimal SQ lower bounds for a range of concrete estimation tasks where existing techniques provide sub-optimal or even vacuous guarantees.Comment: Conference version published in NeurIPS 202