Applications of inverse simulation to a nonlinear model of an underwater vehicle

Inverse simulation provides an important alternative to conventional simulation and to more formal mathematical techniques of model inversion. The application of inverse simulation methods to a nonlinear dynamic model of an unmanned underwater vehicle with actuator limits is found to give rise to a number of challenging problems. It is shown that this particular problem requires, in common with other applications that include hard nonlinearities in the model or discontinuities in the required trajectory, can best be approached using a search-based optimization algorithm for inverse simulation in place of the more conventional Newton- Raphson approach. Results show that meaningful inverse simulation results can be obtained but that multi-solution responses exist. Although the inverse solutions are not unique they are shown to generate the required trajectories when tested using conventional forward simulation methods

Methionine adenosyltransferases in liver cancer.

Methionine adenosyltransferases (MATs) are essential enzymes for life as they produce S-adenosylmethionine (SAMe), the biological methyl donor required for a plethora of reactions within the cell. Mammalian systems express two genes, MAT1A and MAT2A, which encode for MATα1 and MATα2, the catalytic subunits of the MAT isoenzymes, respectively. A third gene MAT2B, encodes a regulatory subunit known as MATβ which controls the activity of MATα2. MAT1A, which is mainly expressed in hepatocytes, maintains the differentiated state of these cells, whilst MAT2A and MAT2B are expressed in extrahepatic tissues as well as non-parenchymal cells of the liver (e.g., hepatic stellate and Kupffer cells). The biosynthesis of SAMe is impaired in patients with chronic liver disease and liver cancer due to decreased expression and inactivation of MATα1. A switch from MAT1A to MAT2A/MAT2B occurs in multiple liver diseases and during liver growth and dedifferentiation, but this change in the expression pattern of MATs results in reduced hepatic SAMe level. Decades of study have utilized the Mat1a-knockout (KO) mouse that spontaneously develops non-alcoholic steatohepatitis (NASH) and hepatocellular carcinoma (HCC) to elucidate a variety of mechanisms by which MAT proteins dysregulation contributes to liver carcinogenesis. An increasing volume of work indicates that MATs have SAMe-independent functions, distinct interactomes and multiple subcellular localizations. Here we aim to provide an overview of MAT biology including genes, isoenzymes and their regulation to provide the context for understanding consequences of their dysregulation. We will highlight recent breakthroughs in the field and underscore the importance of MAT's in liver tumorigenesis as well as their potential as targets for cancer therapy

Mapping the Outer Edge of the Young Stellar Cluster in the Galactic Center

We present new near-infrared spectroscopic observations of the outer edges of the young stellar cluster around the supermassive black hole at the Galactic center. The observations show a break in the surface-density profile of young stars at approximately 13 arcsec (0.52 pc). These observations spectroscopically confirm previous suggestions of a break based on photometry. Using Gemini North's Near-Infrared Integral Field Spectrometer (NIFS) we are able to detect and separate early- and late-type stars with a 75% completeness at Ks = 15.5. We sample a region with radii between 7" to 23" (0.28 pc to 0.92 pc) from Sgr A*, and present new spectral classifications of 144 stars brighter than Ks = 15.5, where 140 stars are late-type (> 1 Gyr) and only four stars are early-type (young, 4-6 Myr). A broken power-law fit of the early-type surface-density matches well with our data and previously published values. The projected surface-density of late-type stars is also measured and found to be consistent with previous results. We find that the observed early-type surface-density profile is inconsistent with the theory of the young stars originating from a tightly bound infalling cluster, as no significant trail of young stars is found at radii above 13". We also note that either a simple disk instability criterion or a cloud-cloud collision could explain the location of the outer edge, though we lack information to make conclusive remarks on either alternative. If this break in surface-density represents an edge to the young stellar cluster it would set an important scale for the most recent episode of star formation at the Galactic center.Comment: 17 pages, 11 figures, 3 tables, ApJ accepte

Single-Molecule Dynamics Reveals Cooperative Binding-Folding in Protein Recognition

The study of associations between two biomolecules is the key to understanding molecular function and recognition. Molecular function is often thought to be determined by underlying structures. Here, combining a single-molecule study of protein binding with an energy-landscape–inspired microscopic model, we found strong evidence that biomolecular recognition is determined by flexibilities in addition to structures. Our model is based on coarse-grained molecular dynamics on the residue level with the energy function biased toward the native binding structure (the Go model). With our model, the underlying free-energy landscape of the binding can be explored. There are two distinct conformational states at the free-energy minimum, one with partial folding of CBD itself and significant interface binding of CBD to Cdc42, and the other with native folding of CBD itself and native interface binding of CBD to Cdc42. This shows that the binding process proceeds with a significant interface binding of CBD with Cdc42 first, without a complete folding of CBD itself, and that binding and folding are then coupled to reach the native binding state. The single-molecule experimental finding of dynamic fluctuations among the loosely and closely bound conformational states can be identified with the theoretical, calculated free-energy minimum and explained quantitatively in the model as a result of binding associated with large conformational changes. The theoretical predictions identified certain key residues for binding that were consistent with mutational experiments. The combined study identified fundamental mechanisms and provided insights about designing and further exploring biomolecular recognition with large conformational changes

Sensitivity-analysis method for inverse simulation application

An important criticism of traditional methods of inverse simulation that are based on the Newton–Raphson algorithm is that they suffer from numerical problems. In this paper these problems are discussed and a new method based on sensitivity-analysis theory is developed and evaluated. The Jacobian matrix may be calculated by solving a sensitivity equation and this has advantages over the approximation methods that are usually applied when the derivatives of output variables with respect to inputs cannot be found analytically. The methodology also overcomes problems of input-output redundancy that arise in the traditional approaches to inverse simulation. The sensitivity- analysis approach makes full use of information within the time interval over which key quantities are compared, such as the difference between calculated values and the given ideal maneuver after each integration step. Applications to nonlinear HS125 aircraft and Lynx helicopter models show that, for this sensitivity-analysis method, more stable and accurate results are obtained than from use of the traditional Newton–Raphson approach

Multiplicative LSTM for sequence modelling

We introduce multiplicative LSTM (mLSTM), a recurrent neural network architecture for sequence modelling that combines the long short-term memory (LSTM) and multiplicative recurrent neural network architectures. mLSTM is characterised by its ability to have different recurrent transition functions for each possible input, which we argue makes it more expressive for autoregressive density estimation. We demonstrate empirically that mLSTM outperforms standard LSTM and its deep variants for a range of character level language modelling tasks. In this version of the paper, we regularise mLSTM to achieve 1.27 bits/char on text8 and 1.24 bits/char on Hutter Prize. We also apply a purely byte-level mLSTM on the WikiText-2 dataset to achieve a character level entropy of 1.26 bits/char, corresponding to a word level perplexity of 88.8, which is comparable to word level LSTMs regularised in similar ways on the same task

Critical role of NF-κB in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, and in spite of intense efforts there are limited therapeutic options for patients with PDAC. PDACs harbor a high frequency of Kras mutations and other driver mutations that lead to altered signaling pathways and contribute to therapeutic resistance. Importantly, constitutive activation of nuclear factor κB (NF-κB) is frequently observed in PDAC. An increasing body of evidence suggests that both classical and non-classical NF-κB pathways play a crucial role in PDAC development and progression. In this review, we update the most recent advances regarding different aspects of NF-κB involvement in PDAC development and progression, emphasizing its potential as a therapeutic target and the need to discover pathway-specific cytosolic NF-κB regulators which could be used to design novel therapeutic strategies for PDAC

Feedback methods for inverse simulation of dynamic models for engineering systems applications

Inverse simulation is a form of inverse modelling in which computer simulation methods are used to find the time histories of input variables that, for a given model, match a set of required output responses. Conventional inverse simulation methods for dynamic models are computationally intensive and can present difficulties for high-speed applications. This paper includes a review of established methods of inverse simulation,giving some emphasis to iterative techniques that were first developed for aeronautical applications. It goes on to discuss the application of a different approach which is based on feedback principles. This feedback method is suitable for a wide range of linear and nonlinear dynamic models and involves two distinct stages. The first stage involves design of a feedback loop around the given simulation model and, in the second stage, that closed-loop system is used for inversion of the model. Issues of robustness within closed-loop systems used in inverse simulation are not significant as there are no plant uncertainties or external disturbances. Thus the process is simpler than that required for the development of a control system of equivalent complexity. Engineering applications of this feedback approach to inverse simulation are described through case studies that put particular emphasis on nonlinear and multi-input multi-output models