Hierarchical sampling for metastable conformers determines biomolecular recognition: the case of malectin and diglucosylated N-glycan interactions

Structural information over the entire course of binding interactions based on the analyses of energy landscapes is described, which provides a framework to understand the events involved during biomolecular recognition. Conformational dynamics of malectin's exquisite selectivity for diglucosylated N-glycan (Dig-N-glycan), a highly flexible oligosaccharide comprising of numerous dihedral torsion angles, are described as an example. For this purpose, a novel approach based on hierarchical sampling for acquiring metastable molecular conformations constituting low-energy minima for understanding the structural features involved in a biologic recognition is proposed. For this purpose, four variants of principal component analysis were employed recursively in both Cartesian space and dihedral angles space that are characterized by free energy landscapes to select the most stable conformational substates. Subsequently, k-means clustering algorithm was implemented for geometric separation of the major native state to acquire a final ensemble of metastable conformers. A comparison of malectin complexes was then performed to characterize their conformational properties. Analyses of stereochemical metrics and other concerted binding events revealed surface complementarity, cooperative and bidentate hydrogen bonds, water-mediated hydrogen bonds, carbohydrate-aromatic interactions including CH-pi and stacking interactions involved in this recognition. Additionally, a striking structural transition from loop to beta-strands in malectin CRD upon specific binding to Dig-N-glycan is observed. The interplay of the above-mentioned binding events in malectin and Dig-N-glycan supports an extended conformational selection model as the underlying binding mechanism.

Adaptive Pulse Width Control and Sampling for Low Power Pulse Oximetry

Remote sensing of physiological parameters could be a cost effective approach to improving health care, and low-power sensors are essential for remote sensing because these sensors are often energy constrained. This paper presents a power optimized photoplethysmographic sensor interface to sense arterial oxygen saturation, a technique to dynamically trade off SNR for power during sensor operation, and a simple algorithm to choose when to acquire samples in photoplethysmography. A prototype of the proposed pulse oximeter built using commercial-off-the-shelf (COTS) components is tested on 10 adults. The dynamic adaptation techniques described reduce power consumption considerably compared to our reference implementation, and our approach is competitive to state-of-the-art implementations. The techniques presented in this paper may be applied to low-power sensor interface designs where acquiring samples is expensive in terms of power as epitomized by pulse oximetry.

Event-triggered sampling using signal extrema for instantaneous amplitude and instantaneous frequency estimation

Event-triggered sampling (ETS) is a new approach towards efficient signal analysis. The goal of ETS need not be only signal reconstruction, but also direct estimation of desired information in the signal by skillful design of event. We show a promise of ETS approach towards better analysis of oscillatory non-stationary signals modeled by a time-varying sinusoid, when compared to existing uniform Nyquist-rate sampling based signal processing. We examine samples drawn using ETS, with events as zero-crossing (ZC), level-crossing (LC), and extrema, for additive in-band noise and jitter in detection instant. We find that extrema samples are robust, and also facilitate instantaneous amplitude (IA), and instantaneous frequency (IF) estimation in a time-varying sinusoid. The estimation is proposed solely using extrema samples, and a local polynomial regression based least-squares fitting approach. The proposed approach shows improvement, for noisy signals, over widely used analytic signal, energy separation, and ZC based approaches (which are based on uniform Nyquist-rate sampling based data-acquisition and processing). Further, extrema based ETS in general gives a sub-sampled representation (relative to Nyquistrate) of a time-varying sinusoid. For the same data-set size captured with extrema based ETS, and uniform sampling, the former gives much better IA and IF estimation. (C) 2015 Elsevier B.V. All rights reserved.

Sampling Period Selection of Control Application Connected to FlexRay Bus

Flexray is a high speed communication protocol designed for distributive control in automotive control applications. Control performance not only depends on the control algorithm but also on the scheduling constraints in communication. A balance between the control performance and communication constraints must required for the choice of the sampling rates of the control loops in a node. In this paper, an optimum sampling period of control loops to minimize the cost function, satisfying the scheduling constraints is obtained. An algorithm to obtain the delay in service of each task in a node of the control loop in the hyper period has been also developed. (C) 2015 The Authors. Published by Elsevier B.V.

Ab Initio Molecular Dynamics Simulations of Amino Acids in Aqueous Solutions: Estimating pK(a) Values from Metadynamics Sampling

Changes in the protonation and deprotonation of amino acid residues in proteins play a key role in many biological processes and pathways. Here, we report calculations of the free-energy profile for the protonation deprotonation reaction of the 20 canonical alpha amino acids in aqueous solutions using ab initio Car-Parrinello molecular dynamics simulations coupled with metad-ynamics sampling. We show here that the calculated change in free energy of the dissociation reaction provides estimates of the multiple pK(a) values of the amino acids that are in good agreement with experiment. We use the bond-length-dependent number of the protons coordinated to the hydroxyl oxygen of the carboxylic and the amine groups as the collective variables to explore the free-energy profiles of the Bronsted acid-base chemistry of amino acids in aqueous solutions. We ensure that the amino acid undergoing dissociation is solvated by at least three hydrations shells with all water molecules included in the simulations. The method works equally well for amino acids with neutral, acidic and basic side chains and provides estimates of the multiple pK(a) values with a mean relative error, with respect to experimental results, of 0.2 pK(a) units.

Role of upward leaders in modifying the induced currents in solitary down-conductors during a nearby lightning strike to ground

Electromagnetic field produced by a lightning strike to ground causes significant induction to tall objects in the vicinity. The frequency of occurrence of such nearby ground strikes can be higher than the number of direct strikes. Therefore, a complete knowledge on these induced currents is of practical relevance. However, limited efforts towards the characterisation of such induced currents in tall down-conductors could be seen in the literature. Due to the intensification of the background field caused by the descending stepped leader, tall towers/down-conductors can launch upward leaders of significant length. The nonlinearity in the conductance of upward leader and the surrounding corona sheath can alter the characteristics of the induced currents. Preliminary aspects of this phenomenon have been studied by the author previously and the present work aims to perform a detailed investigation on the role of upward leaders in modifying the characteristics of the induced currents. A consistent model for the upward leader, which covers all the essential electrical aspects of the phenomena, is employed. A first order arc model for representing the conductance of upward leader and a field dependant quadratic conductivity model for the corona sheath is employed. The initial gradient in the upward leader and the field produced by the return stroke forms the excitation. The dynamic electromagnetic response is determined by solving the wave equation using thin-wire time-domain formulation. Simulations are carried out initially to ascertain the role of individual parameters, including the length of the upward leader. Based on the simulation results, it is shown that the upward leader enhances the induced current, and when significant in length, can alter the waveshape of induced current from bipolar oscillatory to unipolar. The duration of the induced current is governed by the length of upward leader, which in turn is dependant on the return stroke current and the effective length of the down-conductor. If the current during the upward leader developmental phase is considered along with that after the stroke termination to ground, it would present a bipolar current pulse. (C) 2015 Elsevier Ltd. All rights reserved.

Event-triggered Sampling and Reconstruction of Sparse Real-valued Trigonometric Polynomials

We propose data acquisition from continuous-time signals belonging to the class of real-valued trigonometric polynomials using an event-triggered sampling paradigm. The sampling schemes proposed are: level crossing (LC), close to extrema LC, and extrema sampling. Analysis of robustness of these schemes to jitter, and bandpass additive gaussian noise is presented. In general these sampling schemes will result in non-uniformly spaced sample instants. We address the issue of signal reconstruction from the acquired data-set by imposing structure of sparsity on the signal model to circumvent the problem of gap and density constraints. The recovery performance is contrasted amongst the various schemes and with random sampling scheme. In the proposed approach, both sampling and reconstruction are non-linear operations, and in contrast to random sampling methodologies proposed in compressive sensing these techniques may be implemented in practice with low-power circuitry.

Neonatal exposure to 17 beta-estradiol down-regulates the expression of synaptogenesis related genes in selected brain regions of adult female rats

Aims: Administration of estradiol or compounds with estrogenic activity to newborn female rats results in irreversible masculinization as well as defeminization in the brain and the animals exhibit altered reproductive behavior as adults. The cellular and molecular mechanism involved in inducing the irreversible changes is largely unknown. In the present study, we have monitored the changes in the expression of selected synaptogenesis related genes in the sexually dimorphic brain regions such as POA, hypothalamus and pituitary following 17 beta-estradiol administration to neonatal female rats. Main methods: Female Wistar rats which were administered 17 beta-estradiol on day 2 and 3 after birth were sacrificed 120 days later and the expression levels of genes implicated in synaptogenesis were monitored by semi-quantitative reverse transcription PCR. Since estradiol induced up-regulation of COX-2 in POA is a marker for estradiol induced masculinization as well as defeminization, in the present study only animals in which the increase in expression of COX-2 gene was observed in POA were included in the study. Key findings: Down-regulation of genes such as NMDA-2B, NETRIN-1, BDNF, MT-5 MMP and TNF-alpha was observed in the pre-optic area of neonatally E2 treated female rat brain but not in hypothalamus and pituitary compared to the vehicle- treated controls as assessed by RT-PCR and Western blot analysis. Significance: Our results suggest a possibility that down-regulation of genes associated with synaptogenesis in POA, may be resulting in disruption of the cyclical regulation of hormone secretion by pituitary the consequence of which could be infertility and altered reproductive behavior. (C) 2015 Elsevier Inc. All rights reserved.

Lack of Critical Slowing Down Suggests that Financial Meltdowns Are Not Critical Transitions, yet Rising Variability Could Signal Systemic Risk

Complex systems inspired analysis suggests a hypothesis that financial meltdowns are abrupt critical transitions that occur when the system reaches a tipping point. Theoretical and empirical studies on climatic and ecological dynamical systems have shown that approach to tipping points is preceded by a generic phenomenon called critical slowing down, i.e. an increasingly slow response of the system to perturbations. Therefore, it has been suggested that critical slowing down may be used as an early warning signal of imminent critical transitions. Whether financial markets exhibit critical slowing down prior to meltdowns remains unclear. Here, our analysis reveals that three major US (Dow Jones Index, S&P 500 and NASDAQ) and two European markets (DAX and FTSE) did not exhibit critical slowing down prior to major financial crashes over the last century. However, all markets showed strong trends of rising variability, quantified by time series variance and spectral function at low frequencies, prior to crashes. These results suggest that financial crashes are not critical transitions that occur in the vicinity of a tipping point. Using a simple model, we argue that financial crashes are likely to be stochastic transitions which can occur even when the system is far away from the tipping point. Specifically, we show that a gradually increasing strength of stochastic perturbations may have caused to abrupt transitions in the financial markets. Broadly, our results highlight the importance of stochastically driven abrupt transitions in real world scenarios. Our study offers rising variability as a precursor of financial meltdowns albeit with a limitation that they may signal false alarms.

Investigations into the structural and down-shifting and up-conversion luminescence properties of Ba2Na1-3xErxNb5O15 (0 <= x <= 0.06) nanocrystalline phosphor synthesized via sol-gel route

The present work deals with the structural and efficient down-shifting (DS) and up-conversion (UC) luminescence properties of erbium ion (Er3+) doped nanocrystalline barium sodium niobate (Ba2Na1-3xErxNb5O15, where x = 0, 0.02, 0.04 and 0.06) powders synthesized via novel citrate-based sol-gel route. The monophasic nature of the title compound was confirmed via x-ray powder diffraction followed by FT-IR studies. High-resolution transmission electron microscopy (HRTEM) facilitated the establishment of the nanocrystalline phase and the morphology of the crystallites. The Kubelka-Munk function, based on diffused reflectance studies and carried out on nano-sized crystallites, was employed to obtain the optical band-gap. The synthesized nanophosphor showed efficient DS/PL-photoluminescence and UC luminescence properties, which have not yet been reported so far in this material. The material emits intense DS green emission on excitation with 378 nm radiation. Interestingly, the material gives intense UC emission in the visible region dominated by green emission and relatively weak red emission on 976 nm excitation (NIR laser excitation). Such a dual-mode emitting nanophosphor could be very useful in display devices and for many other applications.

A Simple Hysteretic Energy Harvesting Method for Nonneutral AC Switches in Load Automation

This paper presents a simple hysteretic method to obtain the energy required to operate the gate-drive, sensors, and other circuits within nonneutral ac switches intended for use in load automated buildings. The proposed method features a switch-mode low part-count self-powered MOSFET ac switch that achieves efficiency and load current THD figures comparable to those of an externally gate-driven switch built using similar MOSFETS. The fundamental operation of the method is explained in detail, followed by the modifications required for practical implementation. Certain design rules that allow the method to accommodate a wide range of single-phase loads from 10 VA to 1 kVA are discussed, along with an efficiency enhancement feature based on inherent MOSFET characteristics. The limitations and side effects of the method are also mentioned according to their levels of severity. Finally, experimental results obtained using a prototype sensor switch are presented, along with a performance comparison of the prototype with an externally gate-driven MOSFET switch.

Ellipse Fitting Using the Finite Rate of Innovation Sampling Principle

Standard approaches for ellipse fitting are based on the minimization of algebraic or geometric distance between the given data and a template ellipse. When the data are noisy and come from a partial ellipse, the state-of-the-art methods tend to produce biased ellipses. We rely on the sampling structure of the underlying signal and show that the x- and y-coordinate functions of an ellipse are finite-rate-of-innovation (FRI) signals, and that their parameters are estimable from partial data. We consider both uniform and nonuniform sampling scenarios in the presence of noise and show that the data can be modeled as a sum of random amplitude-modulated complex exponentials. A low-pass filter is used to suppress noise and approximate the data as a sum of weighted complex exponentials. The annihilating filter used in FRI approaches is applied to estimate the sampling interval in the closed form. We perform experiments on simulated and real data, and assess both objective and subjective performances in comparison with the state-of-the-art ellipse fitting methods. The proposed method produces ellipses with lesser bias. Furthermore, the mean-squared error is lesser by about 2 to 10 dB. We show the applications of ellipse fitting in iris images starting from partial edge contours, and to free-hand ellipses drawn on a touch-screen tablet.

Empirical Analysis of Sampling Based Estimators for Evaluating RBMs

The Restricted Boltzmann Machines (RBM) can be used either as classifiers or as generative models. The quality of the generative RBM is measured through the average log-likelihood on test data. Due to the high computational complexity of evaluating the partition function, exact calculation of test log-likelihood is very difficult. In recent years some estimation methods are suggested for approximate computation of test log-likelihood. In this paper we present an empirical comparison of the main estimation methods, namely, the AIS algorithm for estimating the partition function, the CSL method for directly estimating the log-likelihood, and the RAISE algorithm that combines these two ideas.

Time-Instant Sampling Based Encoding of Time-Varying Acoustic Spectrum

The inner ear has been shown to characterize an acoustic stimuli by transducing fluid motion in the inner ear to mechanical bending of stereocilia on the inner hair cells (IHCs). The excitation motion/energy transferred to an IHC is dependent on the frequency spectrum of the acoustic stimuli, and the spatial location of the IHC along the length of the basilar membrane (BM). Subsequently, the afferent auditory nerve fiber (ANF) bundle samples the encoded waveform in the IHCs by synapsing with them. In this work we focus on sampling of information by afferent ANFs from the IHCs, and show computationally that sampling at specific time instants is sufficient for decoding of time-varying acoustic spectrum embedded in the acoustic stimuli. The approach is based on sampling the signal at its zero-crossings and higher-order derivative zero-crossings. We show results of the approach on time-varying acoustic spectrum estimation from cricket call signal recording. The framework gives a time-domain and non-spatial processing perspective to auditory signal processing. The approach works on the full band signal, and is devoid of modeling any bandpass filtering mimicking the BM action. Instead, we motivate the approach from the perspective of event-triggered sampling by afferent ANFs on the stimuli encoded in the IHCs. Though the approach gives acoustic spectrum estimation but it is shallow on its complete understanding for plausible bio-mechanical replication with current mammalian auditory mechanics insights.