Does acoustic adaptation drive vertical stratification? A test in a tropical cricket assemblage

In species-rich assemblages, differential utilization of vertical space can be driven by resource availability. For animals that communicate acoustically over long distances under habitat-induced constraints, access to an effective transmission channel is a valuable resource. The acoustic adaptation hypothesis suggests that habitat acoustics imposes a selective pressure that drives the evolution of both signal structure and choice of calling sites by signalers. This predicts that species-specific signals transmit best in native habitats. In this study, we have tested the hypothesis that vertical stratification of calling heights of acoustically communicating species is driven by acoustic adaptation. This was tested in an assemblage of 12 coexisting species of crickets and katydids in a tropical wet evergreen forest. We carried out transmission experiments using natural calls at different heights from the forest floor to the canopy. We measured signal degradation using 3 different measures: total attenuation, signal-to-noise ratio (SNR), and envelope distortion. Different sets of species supported the hypothesis depending on which attribute of signal degradation was examined. The hypothesis was upheld by 5 species for attenuation and by 3 species each for SNR and envelope distortion. Only 1 species of 12 provided support for the hypothesis by all 3 measures of signal degradation. The results thus provided no overall support for acoustic adaptation as a driver of vertical stratification of coexisting cricket and katydid species.

Stabilization of stochastic approximation by step size adaptation

A scheme for stabilizing stochastic approximation iterates by adaptively scaling the step sizes is proposed and analyzed. This scheme leads to the same limiting differential equation as the original scheme and therefore has the same limiting behavior, while avoiding the difficulties associated with projection schemes. The proof technique requires only that the limiting o.d.e. descend a certain Lyapunov function outside an arbitrarily large bounded set. (C) 2012 Elsevier B.V. All rights reserved.

Adaptation of small capacity natural gas engine for producer gas operation

This article addresses the adaptation of a low-power natural gas engine for using producer gas as a fuel. The 5.9 L natural gas engine with a compression ratio of 10.5:1, rated at 55 kW shaft power, delivered 30 kW using producer gas as fuel in the naturally aspirated mode. Optimal ignition timing for peak power was found to be 20 degrees before top dead centre. Air-to-fuel ratio (A/F) was found to be 1.2 +/- 0.1 over a range of loads. Critical evaluation of the energy flows in the engine resulted in identifying losses and optimizing the engine cooling. The specific fuel consumption was found to be 1.2 +/- 0.1 kg of biomass per kilowatt hour. A reduction of 40 per cent in brake mean effective pressure was observed compared with natural gas operation. Governor response to load variations has been studied with respect to frequency recovery time. The study also attempts to adopt a turbocharger for higher power output. Preliminary results suggest a possibility of about 30 per cent increase in the output.

Low complexity adaptation for SISO channel shortening equalizers

Since the days of Digital Subscriber Links (DSL), time domain equalizers (TEQ's) have been used to combat time dispersive channels in Multicarrier Systems. In this paper, we propose computationally inexpensive techniques to recompute TEQ weights in the presence of changes in the channel, especially over fast fading channels. The techniques use no extra information except the perturbation to the channel itself, and provide excellent approximations to the new TEQ weights. Adaptation methods for two existing Channel shortening algorithms are proposed and their performance over randomly varying, randomly perturbed channels is studied. The proposed adaptation techniques are shown to perform admirably well for small changes in channels for OFDM systems. (C) 2012 Elsevier GmbH. All rights reserved.

Catalytic activity of Peptidase N is required for adaptation of Escherichia coli to nutritional downshift and high temperature stress

Peptidase N (PepN), the sole M1 family member in Escherichia coli, displays broad substrate specificity and modulates stress responses: it lowers resistance to sodium salicylate (NaSal)-induced stress but is required during nutritional downshift and high temperature (NDHT) stress. The expression of PepN does not significantly change during different growth phases in LB or NaSal-induced stress; however, PepN amounts are lower during NDHT stress. To gain mechanistic insights on the roles of catalytic activity of PepN in modulating these two stress responses, alanine mutants of PepN replacing E264 (GAMEN motif) and E298 (HEXXH motif) were generated. There are no major structural changes between purified wild type (WT) and mutant proteins, which are catalytically inactive. Importantly, growth profiles of Delta pepN upon expression of WT or mutant proteins demonstrated the importance of catalytic activity during NDHT but not NaSal-induced stress. Further fluorescamine reactivity studies demonstrated that the catalytic activity of PepN is required to generate higher intracellular amounts of free N-terminal amino acids; consequently, the lower growth of Delta pepN during NDHT stress increases with high amounts of casamino acids. Together, this study sheds insights on the expression and functional roles of the catalytic activity of PepN during adaptation to NDHT stress. (C) 2012 Elsevier GmbH. All rights reserved.

Low complexity adaptation for channel shortening equalizers

Since the days of Digital Subscriber Links(DSL), Time Domain Equalizers(TEQ's) have been used to combat time dispersive channels in Multicarrier Systems. In this paper, we propose computationally inexpensive techniques to recompute TEQ weights in the presence of changes in the channel, especially over fast fading channels. The techniques use no extra information except the perturbation itself, and provide excellent approximations to the new TEQ weights. The proposed adaptation techniques are shown to perform admirably well for small changes in channels for OFDM systems.

An adaptation framework for head-pose classification in dynamic multi-view scenarios

Multi-view head-pose estimation in low-resolution, dynamic scenes is difficult due to blurred facial appearance and perspective changes as targets move around freely in the environment. Under these conditions, acquiring sufficient training examples to learn the dynamic relationship between position, face appearance and head-pose can be very expensive. Instead, a transfer learning approach is proposed in this work. Upon learning a weighted-distance function from many examples where the target position is fixed, we adapt these weights to the scenario where target positions are varying. The adaptation framework incorporates reliability of the different face regions for pose estimation under positional variation, by transforming the target appearance to a canonical appearance corresponding to a reference scene location. Experimental results confirm effectiveness of the proposed approach, which outperforms state-of-the-art by 9.5% under relevant conditions. To aid further research on this topic, we also make DPOSE- a dynamic, multi-view head-pose dataset with ground-truth publicly available with this paper.

Joint evaluation of channel feedback schemes, rate adaptation, and scheduling in OFDMA downlinks with feedback delays

Orthogonal frequency-division multiple access (OFDMA) systems divide the available bandwidth into orthogonal subchannels and exploit multiuser diversity and frequency selectivity to achieve high spectral efficiencies. However, they require a significant amount of channel state feedback for scheduling and rate adaptation and are sensitive to feedback delays. We develop a comprehensive analysis for OFDMA system throughput in the presence of feedback delays as a function of the feedback scheme, frequency-domain scheduler, and rate adaptation rule. Also derived are expressions for the outage probability, which captures the inability of a subchannel to successfully carry data due to the feedback scheme or feedback delays. Our model encompasses the popular best-n and threshold-based feedback schemes and the greedy, proportional fair, and round-robin schedulers that cover a wide range of throughput versus fairness tradeoff. It helps quantify the different robustness of the schedulers to feedback overhead and delays. Even at low vehicular speeds, it shows that small feedback delays markedly degrade the throughput and increase the outage probability. Further, given the feedback delay, the throughput degradation depends primarily on the feedback overhead and not on the feedback scheme itself. We also show how to optimize the rate adaptation thresholds as a function of feedback delay.

Interplay Between Optimal Selection Scheme, Selection Criterion, and Discrete Rate Adaptation in Opportunistic Wireless Systems

An opportunistic, rate-adaptive system exploits multi-user diversity by selecting the best node, which has the highest channel power gain, and adapting the data rate to selected node's channel gain. Since channel knowledge is local to a node, we propose using a distributed, low-feedback timer backoff scheme to select the best node. It uses a mapping that maps the channel gain, or, in general, a real-valued metric, to a timer value. The mapping is such that timers of nodes with higher metrics expire earlier. Our goal is to maximize the system throughput when rate adaptation is discrete, as is the case in practice. To improve throughput, we use a pragmatic selection policy, in which even a node other than the best node can be selected. We derive several novel, insightful results about the optimal mapping and develop an algorithm to compute it. These results bring out the inter-relationship between the discrete rate adaptation rule, optimal mapping, and selection policy. We also extensively benchmark the performance of the optimal mapping with several timer and opportunistic multiple access schemes considered in the literature, and demonstrate that the developed scheme is effective in many regimes of interest.

Joint Evaluation of Reduced Feedback Scheme, Scheduling, and Rate Adaptation in OFDMA Systems with Feedback Delays

Orthogonal frequency division multiple access (OFDMA) systems exploit multiuser diversity and frequency-selectivity to achieve high spectral efficiencies. However, they require considerable feedback for scheduling and rate adaptation, and are sensitive to feedback delays. We develop a comprehensive analysis of the OFDMA system throughput as a function of the feedback scheme, frequency-domain scheduler, and discrete rate adaptation rule in the presence of feedback delays. We analyze the popular best-n and threshold-based feedback schemes. We show that for both the greedy and round-robin schedulers, the throughput degradation, given a feedback delay, depends primarily on the fraction of feedback reduced by the feedback scheme and not the feedback scheme itself. Even small feedback delays at low vehicular speeds are shown to significantly degrade the throughput. We also show that optimizing the link adaptation thresholds as a function of the feedback delay can effectively counteract the detrimental effect of delays.

Optimal Joint Antenna Selection and Power Adaptation in Underlay Cognitive Radios

Transmit antenna selection (AS) is a popular, low hardware complexity technique that improves the performance of an underlay cognitive radio system, in which a secondary transmitter can transmit when the primary is on but under tight constraints on the interference it causes to the primary. The underlay interference constraint fundamentally changes the criterion used to select the antenna because the channel gains to the secondary and primary receivers must be both taken into account. We develop a novel and optimal joint AS and transmit power adaptation policy that minimizes a Chernoff upper bound on the symbol error probability (SEP) at the secondary receiver subject to an average transmit power constraint and an average primary interference constraint. Explicit expressions for the optimal antenna and power are provided in terms of the channel gains to the primary and secondary receivers. The SEP of the optimal policy is at least an order of magnitude lower than that achieved by several ad hoc selection rules proposed in the literature and even the optimal antenna selection rule for the case where the transmit power is either zero or a fixed value.

EESM-Based Link Adaptation in Point-to-Point and Multi-Cell OFDM Systems: Modeling and Analysis

In contemporary wideband orthogonal frequency division multiplexing (OFDM) systems, such as Long Term Evolution (LTE) and WiMAX, different subcarriers over which a codeword is transmitted may experience different signal-to-noise-ratios (SNRs). Thus, adaptive modulation and coding (AMC) in these systems is driven by a vector of subcarrier SNRs experienced by the codeword, and is more involved. Exponential effective SNR mapping (EESM) simplifies the problem by mapping this vector into a single equivalent fiat-fading SNR. Analysis of AMC using EESM is challenging owing to its non-linear nature and its dependence on the modulation and coding scheme. We first propose a novel statistical model for the EESM, which is based on the Beta distribution. It is motivated by the central limit approximation for random variables with a finite support. It is simpler and as accurate as the more involved ad hoc models proposed earlier. Using it, we develop novel expressions for the throughput of a point-to-point OFDM link with multi-antenna diversity that uses EESM for AMC. We then analyze a general, multi-cell OFDM deployment with co-channel interference for various frequency-domain schedulers. Extensive results based on LTE and WiMAX are presented to verify the model and analysis, and gain new insights.

Antenna Selection with Power Adaptation in Interference-Constrained Cognitive Radios

The performance of an underlay cognitive radio (CR) system, which can transmit when the primary is on, is curtailed by tight constraints on the interference it can cause to the primary receiver. Transmit antenna selection (AS) improves the performance of underlay CR by exploiting spatial diversity but with less hardware. However, the selected antenna and its transmit power now both depend on the channel gains to the secondary and primary receivers. We develop a novel Chernoffbound based optimal AS and power adaptation (CBBOASPA) policy that minimizes an upper bound on the symbol error probability (SEP) at the secondary receiver, subject to constraints on the average transmit power and the average interference to the primary. The optimal antenna and its power are presented in an insightful closed form in terms of the channel gains. We then analyze the SEP of CBBOASPA. Extensive benchmarking shows that the SEP of CBBOASPA for both MPSK and MQAM is one to two orders of magnitude lower than several ad hoc AS policies and even optimal AS with on-off power control.

Bi-Domain Protein Tyrosine Phosphatases Reveal an Evolutionary Adaptation to Optimize Signal Transduction

Significance: The bi-domain protein tyrosine phosphatases (PTPs) exemplify functional evolution in signaling proteins for optimal spatiotemporal signal transduction. Bi-domain PTPs are products of gene duplication. The catalytic activity, however, is often localized to one PTP domain. The inactive PTP domain adopts multiple functional roles. These include modulation of catalytic activity, substrate specificity, and stability of the bi-domain enzyme. In some cases, the inactive PTP domain is a receptor for redox stimuli. Since multiple bi-domain PTPs are concurrently active in related cellular pathways, a stringent regulatory mechanism and selective cross-talk is essential to ensure fidelity in signal transduction. Recent Advances: The inactive PTP domain is an activator for the catalytic PTP domain in some cases, whereas it reduces catalytic activity in other bi-domain PTPs. The relative orientation of the two domains provides a conformational rationale for this regulatory mechanism. Recent structural and biochemical data reveal that these PTP domains participate in substrate recruitment. The inactive PTP domain has also been demonstrated to undergo substantial conformational rearrangement and oligomerization under oxidative stress. Critical Issues and Future Directions: The role of the inactive PTP domain in coupling environmental stimuli with catalytic activity needs to be further examined. Another aspect that merits attention is the role of this domain in substrate recruitment. These aspects have been poorly characterized in vivo. These lacunae currently restrict our understanding of neo-functionalization of the inactive PTP domain in the bi-domain enzyme. It appears likely that more data from these research themes could form the basis for understanding the fidelity in intracellular signal transduction.

Single network adaptive critic aided dynamic inversion for optimal regulation and command tracking with online adaptation for enhanced robustness

To combine the advantages of both stability and optimality-based designs, a single network adaptive critic (SNAC) aided nonlinear dynamic inversion approach is presented in this paper. Here, the gains of a dynamic inversion controller are selected in such a way that the resulting controller behaves very close to a pre-synthesized SNAC controller in the output regulation sense. Because SNAC is based on optimal control theory, it makes the dynamic inversion controller operate nearly optimal. More important, it retains the two major benefits of dynamic inversion, namely (i) a closed-form expression of the controller and (ii) easy scalability to command tracking applications without knowing the reference commands a priori. An extended architecture is also presented in this paper that adapts online to system modeling and inversion errors, as well as reduced control effectiveness, thereby leading to enhanced robustness. The strengths of this hybrid method of applying SNAC to optimize an nonlinear dynamic inversion controller is demonstrated by considering a benchmark problem in robotics, that is, a two-link robotic manipulator system. Copyright (C) 2013 John Wiley & Sons, Ltd.