Worker piping triggers hissing for coordinated colony defence in the dwarf honeybee Apis florea

Defending a large social insect colony containing several thousands of workers requires the simultaneous action of many individuals. Ideally this action involves communication between the workers, enabling coordinated action and a fast response. The Asian dwarf honeybee, Apis florea, is a small honeybee with an open nesting habit and a comparatively small colony size, features that leave them particularly exposed to predators. We describe here a novel defence response of these bees in which the emission of an initial warning signal from one individual (“piping”) is followed 0.3 to 0.7 seconds later by a general response from a large number of bees (“hissing”). Piping is audible to the human ear, with a fundamental frequency of 384 ± 31Hz and lasting for 0.82 ± 0.35 seconds. Hissing is a broad band, noisy signal, clearly audible to the human observer and produced by slight but visible movements of the bees' wings. Hissing begins in individuals close to the piping bee, spreads rapidly to neighbours and results in an impressive coordinated crescendo occasionally involving the entire colony. Piping and hissing are accompanied by a marked decrease, or even cessation, of worker activities such as forager dancing and departures from the colony. We show that whereas hissing of the colony can be elicited without piping, the sequential and correlated piping and hissing response is specific to the presence of potential predators close to the colony. We suggest that the combined audio-visual effect of the hissing might deter small predators, while the cessation of flight activity could decrease the risk of predation by birds and insects which prey selectively on flying bees.

Resolution and sensitivity of the eyes of the Asian honeybees Apis florea, Apis cerana and Apis dorsata

Bees of the genus Apis are important foragers of nectar and pollen resources. Although the European honeybee, Apis mellifera, has been well studied with respect to its sensory abilities, learning behaviour and role as pollinators, much less is known about the other Apis species. We studied the anatomical spatial resolution and absolute sensitivity of the eyes of three sympatric species of Asian honeybees, Apis cerana, Apis florea and Apis dorsata and compared them with the eyes of A. mellifera. Of these four species, the giant honeybee A. dorsata (which forages during moonlit nights) has the lowest spatial resolution and the most sensitive eyes, followed by A. mellifera, A. cerana and the dwarf honeybee, A. florea (which has the smallest acceptance angles and the least sensitive eyes). Moreover, unlike the strictly diurnal A. cerana and A. florea, A. dorsata possess large ocelli, a feature that it shares with all dim-light bees. However, the eyes of the facultatively nocturnal A. dorsata are much less sensitive than those of known obligately nocturnal bees such as Megalopta genalis in Panama and Xylocopa tranquebarica in India. The differences in sensitivity between the eyes of A. dorsata and other strictly diurnal Apis species cannot alone explain why the former is able to fly, orient and forage at half-moon light levels. We assume that additional neuronal adaptations, as has been proposed for A. mellifera, M. genalis and X. tranquebarica, might exist in A. dorsata.

Resistance Minimum in Dilute Magnetic Alloys in the Absence of Impurity Moments

A possible mechanism for the resistance minimum in dilute alloys in which the localized impurity states are non-magnetic is suggested. The fact is considered that what is essential to the Kondo-like behaviour is the interaction of the conduction electron spin s with the internal dynamical degrees of freedom of the impurity centre. The necessary internal dynamical degrees of freedom are provided by the dynamical Jahn-Teller effect associated with the degenerate 3d-orbitals of the transition-metal impurities interacting with the surrounding (octahedral) complex of the nearest-neighbour atoms. The fictitious spin I characterizing certain low-lying vibronic states of the system is shown to couple with the conduction electron spin s via s-d mixing and spin-orbit coupling, giving rise to a singular temperature-dependent exchange-like interaction. The resistivity so calculated is in fair agreement with the experimental results of Cape and Hake for Ti containing 0.2 at% of Fe.

Novel peptides of therapeutic promise from Indian Conidae

Highly structured small peptides are the major toxic constituents of the venom of cone snails, a family of widely distributed predatory marine molluscs. These animals use the venom for rapid prey immobilization. The peptide components in the venom target a wide variety of membrane-bound ion channels and receptors. Many have been found to be highly selective for a diverse range of mammalian ion channels and receptors associated with pain-signaling pathways. Their small size, structural stability, and target specificity make them attractive pharmacologic agents. A select number of laboratories mainly from the United States, Europe, Australia, Israel, and China have been engaged in intense drug discovery programs based on peptides from a few snail species. Coastal India has an estimated 20-30% of the known cone species; however, few serious studies have been reported so far. We have begun a comprehensive program for the identification and characterization of peptides from cone snails found in Indian Coastal waters. This presentation reviews our progress over the last 2 years. As expected from the evolutionary history of these venom components, our search has yielded novel peptides of therapeutic promise from the new species that we have studied.

Sensitivity of the simulated precipitation to changes in convective relaxation time scale

The paper describes the sensitivity of the simulated precipitation to changes in convective relaxation time scale (TAU) of Zhang and McFarlane (ZM) cumulus parameterization, in NCAR-Community Atmosphere Model version 3 (CAM3). In the default configuration of the model, the prescribed value of TAU, a characteristic time scale with which convective available potential energy (CAPE) is removed at an exponential rate by convection, is assumed to be 1 h. However, some recent observational findings suggest that, it is larger by around one order of magnitude. In order to explore the sensitivity of the model simulation to TAU, two model frameworks have been used, namely, aqua-planet and actual-planet configurations. Numerical integrations have been carried out by using different values of TAU, and its effect on simulated precipitation has been analyzed. The aqua-planet simulations reveal that when TAU increases, rate of deep convective precipitation (DCP) decreases and this leads to an accumulation of convective instability in the atmosphere. Consequently, the moisture content in the lower-and mid-troposphere increases. On the other hand, the shallow convective precipitation (SCP) and large-scale precipitation (LSP) intensify, predominantly the SCP, and thus capping the accumulation of convective instability in the atmosphere. The total precipitation (TP) remains approximately constant, but the proportion of the three components changes significantly, which in turn alters the vertical distribution of total precipitation production. The vertical structure of moist heating changes from a vertically extended profile to a bottom heavy profile, with the increase of TAU. Altitude of the maximum vertical velocity shifts from upper troposphere to lower troposphere. Similar response was seen in the actual-planet simulations. With an increase in TAU from 1 h to 8 h, there was a significant improvement in the simulation of the seasonal mean precipitation. The fraction of deep convective precipitation was in much better agreement with satellite observations.

GNSS Signal Detection Under Noise Uncertainty

High sensitivity detection techniques are required for indoor navigation using Global Navigation Satellite System (GNSS) receivers, and typically, a combination of coherent and non- coherent integration is used as the test statistic for detection. The coherent integration exploits the deterministic part of the signal and is limited due to the residual frequency error, navigation data bits and user dynamics, which are not known apriori. So, non- coherent integration, which involves squaring of the coherent integration output, is used to improve the detection sensitivity. Due to this squaring, it is robust against the artifacts introduced due to data bits and/or frequency error. However, it is susceptible to uncertainty in the noise variance, and this can lead to fundamental sensitivity limits in detecting weak signals. In this work, the performance of the conventional non-coherent integration-based GNSS signal detection is studied in the presence of noise uncertainty. It is shown that the performance of the current state of the art GNSS receivers is close to the theoretical SNR limit for reliable detection at moderate levels of noise uncertainty. Alternate robust post-coherent detectors are also analyzed, and are shown to alleviate the noise uncertainty problem. Monte-Carlo simulations are used to confirm the theoretical predictions.

Profile-Based Load Scheduling in Wireless Energy Harvesting Sensors for Data Rate Maximization

In this paper, power management algorithms for energy harvesting sensors (EHS) that operate purely based on energy harvested from the environment are proposed. To maintain energy neutrality, EHS nodes schedule their utilization of the harvested power so as to save/draw energy into/from an inefficient battery during peak/low energy harvesting periods, respectively. Under this constraint, one of the key system design goals is to transmit as much data as possible given the energy harvesting profile. For implementational simplicity, it is assumed that the EHS transmits at a constant data rate with power control, when the channel is sufficiently good. By converting the data rate maximization problem into a convex optimization problem, the optimal load scheduling (power management) algorithm that maximizes the average data rate subject to energy neutrality is derived. Also, the energy storage requirements on the battery for implementing the proposed algorithm are calculated. Further, robust schemes that account for the insufficiency of battery storage capacity, or errors in the prediction of the harvested power are proposed. The superior performance of the proposed algorithms over conventional scheduling schemes are demonstrated through computations using numerical data from solar energy harvesting databases.

Throughput Maximization of Delay-Constrained Traffic in Wireless Energy Harvesting Sensors

A wireless Energy Harvesting Sensor (EHS) needs to send data packets arriving in its queue over a fading channel at maximum possible throughput while ensuring acceptable packet delays. At the same time, it needs to ensure that energy neutrality is satisfied, i.e., the average energy drawn from a battery should equal the amount of energy deposited in it minus the energy lost due to the inefficiency of the battery. In this work, a framework is developed under which a system designer can optimize the performance of the EHS node using power control based on the current channel state information, when the EHS node employs a single modulation and coding scheme and the channel is Rayleigh fading. Optimal system parameters for throughput optimal, delay optimal and delay-constrained throughput optimal policies that ensure energy neutrality are derived. It is seen that a throughput optimal (maximal) policy is packet delay-unbounded and an average delay optimal (minimal) policy achieves negligibly small throughput. Finally, the influence of the harvested energy profile on the performance of the EHS is illustrated through the example of solar energy harvesting.

Cyclic Prefix Based Cooperative Sequential Spectrum Sensing Algorithms for OFDM

This paper considers the problem of spectrum sensing in cognitive radio networks when the primary user is using Orthogonal Frequency Division Multiplexing (OFDM). For this we develop cooperative sequential detection algorithms that use the autocorrelation property of cyclic prefix (CP) used in OFDM systems. We study the effect of timing and frequency offset, IQ-imbalance and uncertainty in noise and transmit power. We also modify the detector to mitigate the effects of these impairments. The performance of the proposed algorithms is studied via simulations. We show that sequential detection can significantly improve the performance over a fixed sample size detector.

Relay Load Balancing in Queued Cooperative Wireless Networks with Rateless Codes

Relay selection combined with buffering of packets of relays can substantially increase the throughput of a cooperative network that uses rateless codes. However, buffering also increases the end-to-end delays due to the additional queuing delays at the relay nodes. In this paper we propose a novel method that exploits a unique property of rateless codes that enables a receiver to decode a packet from non-contiguous and unordered portions of the received signal. In it, each relay, depending on its queue length, ignores its received coded bits with a given probability. We show that this substantially reduces the end-to-end delays while retaining almost all of the throughput gain achieved by buffering. In effect, the method increases the odds that the packet is first decoded by a relay with a smaller queue. Thus, the queuing load is balanced across the relays and traded off with transmission times. We derive explicit necessary and sufficient conditions for the stability of this system when the various channels undergo fading. Despite encountering analytically intractable G/GI/1 queues in our system, we also gain insights about the method by analyzing a similar system with a simpler model for the relay-to-destination transmission times.

A Complete Characterization of an Optimal Timer Based Selection Scheme

Timer-based mechanisms are often used in several wireless systems to help a given (sink) node select the best helper node among many available nodes. Specifically, a node transmits a packet when its timer expires, and the timer value is a function of its local suitability metric. In practice, the best node gets selected successfully only if no other node's timer expires within a `vulnerability' window after its timer expiry. In this paper, we provide a complete closed-form characterization of the optimal metric-to-timer mapping that maximizes the probability of success for any probability distribution function of the metric. The optimal scheme is scalable, distributed, and much better than the popular inverse metric timer mapping. We also develop an asymptotic characterization of the optimal scheme that is elegant and insightful, and accurate even for a small number of nodes.

Network Error Correction for Unit-Delay, Memory-Free Networks Using Convolutional Codes

A single source network is said to be memory-free if all of the internal nodes (those except the source and the sinks) do not employ memory but merely send linear combinations of the symbols received at their incoming edges on their outgoing edges. In this work, we introduce network-error correction for single source, acyclic, unit-delay, memory-free networks with coherent network coding for multicast. A convolutional code is designed at the source based on the network code in order to correct network- errors that correspond to any of a given set of error patterns, as long as consecutive errors are separated by a certain interval which depends on the convolutional code selected. Bounds on this interval and the field size required for constructing the convolutional code with the required free distance are also obtained. We illustrate the performance of convolutional network error correcting codes (CNECCs) designed for the unit-delay networks using simulations of CNECCs on an example network under a probabilistic error model.

Single-Generation Network Coding for Networks with Delay

A single-source network is said to be memory-free if all of the internal nodes (those except the source and the sinks) do not employ memory but merely send linear combinations of the incoming symbols (received at their incoming edges) on their outgoing edges. Memory-free networks with delay using network coding are forced to do inter-generation network coding, as a result of which the problem of some or all sinks requiring a large amount of memory for decoding is faced. In this work, we address this problem by utilizing memory elements at the internal nodes of the network also, which results in the reduction of the number of memory elements used at the sinks. We give an algorithm which employs memory at all the nodes of the network to achieve single- generation network coding. For fixed latency, our algorithm reduces the total number of memory elements used in the network to achieve single- generation network coding. We also discuss the advantages of employing single-generation network coding together with convolutional network-error correction codes (CNECCs) for networks with unit- delay and illustrate the performance gain of CNECCs by using memory at the intermediate nodes using simulations on an example network under a probabilistic network error model.

Training-Embedded, Single-Symbol ML-Decodable, Distributed STBCs for Relay Networks

Recently, a special class of complex designs called Training-Embedded Complex Orthogonal Designs (TE-CODs) has been introduced to construct single-symbol Maximum Likelihood decodable (SSD) distributed space-time block codes (DSTBCs) for two-hop wireless relay networks using the amplify and forward protocol. However, to implement DSTBCs from square TE-CODs, the overhead due to the transmission of training symbols becomes prohibitively large as the number of relays increase. In this paper, we propose TE-Coordinate Interleaved Orthogonal Designs (TE-CIODs) to construct SSD DSTBCs. Exploiting the block diagonal structure of TE-CIODs, we show that the overhead due to the transmission of training symbols to implement DSTBCs from TE-CIODs is smaller than that for TE-CODs. We also show that DSTBCs from TE-CIODs offer higher rate than those from TE-CODs for identical number of relays while maintaining the SSD and full-diversity properties.

X-Codes: A Low Complexity Full-Rate High-Diversity Achieving Precoder for TDD MIMO Systems

We consider a time division duplex multiple-input multiple-output (nt × nr MIMO). Using channel state information (CSI) at the transmitter, singular value decomposition (SVD) of the channel matrix is performed. This transforms the MIMO channel into parallel subchannels, but has a low overall diversity order. Hence, we propose X-Codes which achieve a higher diversity order by pairing the subchannels, prior to SVD preceding. In particular, each pair of information symbols is encoded by a fixed 2 × 2 real rotation matrix. X-Codes can be decoded using nr very low complexity two-dimensional real sphere decoders. Error probability analysis for X-Codes enables us to choose the optimal pairing and the optimal rotation angle for each pair. Finally, we show that our new scheme outperforms other low complexity precoding schemes.