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This correspondence presents a novel method for the construction of translation-invariant discrete wavelet packet (TIDWP) transforms for any decomposition level k, starting from any phase of a critically sampled discrete wavelet-packet representation of level k. The process is performed by phase shifting, i.e., the direct recovering of the wavelet coefficients omitted by the downsampling operations of each decomposition level without reconstructing the input signal. The proposed method enables tradeoffs between memory utilization and computational efficiency for the construction of translation-invariant representations. Hence, it is useful in resource-constrained TIDWP-based applications of digital signal compression, image segmentation and detection of transients

A plethora of coding and streaming mechanisms have been proposed for real-time multimedia transmission over the Internet. However, most proposed mechanisms rely only on global (e.g. based on end-to-end measurements), delayed (at least by the round-trip-time), or statistical (often based on simplistic network models) information available about the network state. Based on recently-proposed state-of-the-art open-loop video coding schemes, we propose a new integrated streaming and routing framework for robust and efficient video transmission over networks exhibiting path failures. Our approach explicitly takes into account the network dynamics, path diversity, and the modeled video distortion at the receiver side to optimize the packet redundancy and scheduling. In the derived framework, multimedia streams can be adapted dynamically at the video server based on instantaneous routing-layer information or failure-modeling statistics. The performance of our integrated application and network-layer method is simulated against equivalent approaches that are not optimized based on routing-layer feedback and distortion modeling, and the obtained gains in video quality are quantified

The proliferation of wireless multihop communication infrastructures in office or residential environments depends on their ability to support a variety of emerging applications requiring real-time video transmission between stations located across the network. We propose an integrated cross-layer optimization algorithm aimed at maximizing the decoded video quality of delay-constrained streaming in a multihop wireless mesh network that supports quality-of-service. The key principle of our algorithm lays in the synergistic optimization of different control parameters at each node of the multihop network, across the protocol layers-application, network, medium access control, and physical layers, as well as end-to-end, across the various nodes. To drive this optimization, we assume an overlay network infrastructure, which is able to convey information on the conditions of each link. Various scenarios that perform the integrated optimization using different levels ("horizons") of information about the network status are examined. The differences between several optimization scenarios in terms of decoded video quality and required streaming complexity are quantified. Our results demonstrate the merits and the need for cross-layer optimization in order to provide an efficient solution for real-time video transmission using existing protocols and infrastructures. In addition, they provide important insights for future protocol and system design targeted at enhanced video streaming support across wireless mesh networks

Joint optimization strategies across various layers of the protocol stack have recently been proposed for improving the performance of real-time video transmission over wireless networks. In this paper, we propose a new, low complexity system for determining the optimal cross-layer strategies for wireless multimedia transmission based on classification and machine learning techniques. We first determine offline the optimal cross-layer strategy for various video sequences and channel conditions (training data). Subsequently, we extract relevant and easy to compute content features, encoder-specific parameters, and channel resources from the training data, and train a statistical classifier based on these optimal results. At run-time, we predict using the classifier the optimal cross-layer compression and transmission strategy using these simple, on-the-fly computed features. Hence, we consider the complex problem of finding the optimal cross-layer strategy during the training phase only, and rely at transmission-time on low-complexity classification techniques. We illustrate the proposed classification-based system by performing MAC-application layer optimizations for video transmission over 802.11a wireless LANs. Specifically, we predict the optimal MAC retry limits for the various video packets and compare our results against both optimal and conventionally used ad-hoc cross-layer solutions. Our results indicate that considerable improvements can be obtained through the proposed cross-layer techniques relying on classification as opposed to optimized ad-hoc solutions. The improvements are especially important at high packet-loss rates (5% and higher), where deploying a judicious mixture of strategies at the various layers becomes essential. Furthermore, our proposed classification-based system can be easily modified to include other layers from the OSI stack during the cross-layer optimization

Recent breakthroughs in motion-compensated temporal wavelet filtering have finally enabled implementation of highly efficient scalable and error-resilient video codecs. These new wavelet codecs provide numerous advantages over nonscalable conventional solutions techniques based on motion-compensated prediction, such as no recursive predictive loop, separation of noise and sampling artifacts from the content through use of longer temporal filters, removal of long range as well as short range temporal redundancies, etc. Moreover, these wavelet video coding schemes can provide flexible spatial, temporal, signal-to-noise ratio and complexity scalability with fine granularity over a large range of bit rates, while maintaining a very high coding efficiency. However, most motion-compensated wavelet video schemes are based on classical two-band decompositions that offer only dyadic factors of temporal scalability. In this paper, we propose a three-band temporal structure that extends the concept of motion-compensated temporal filtering (MCTF) that was introduced in the classical lifting framework. These newly introduced structures provide higher temporal scalability flexibility, as well as improved compression performance compared with dyadic Haar MCTF.

Based on our statistical investigation of a typical three-dimensional (3-D) wavelet codec, we present a unified mathematical model to describe its operational rate-distortion (RD) behavior. The quantization distortion of the reconstructed video frames is assessed by tracking the quantization noise along the 3-D wavelet decomposition trees. The coding bit-rate is estimated for a class of embedded video coders. Experimental results show that the model captures sequence characteristics accurately and reveals the relationship between wavelet decomposition levels and the overall RD performance. After being trained with offline RD data, the model enables accurate prediction of real RD performance of video codecs and therefore can enable optimal RD adaptation of the encoding parameters according to various network conditions

The objective of joint source channel coding (JSCC) is to optimally allocate the available channel bandwidth between source coding and channel coding in order to minimize the average distortion in the presence of packet losses. Unlike previous research, which focuses on determining distortion-optimized methods for JSCC using either assumptions about the rate-distortion (R-D) curve properties of source data (e.g., convexity) or experimental R-D data, we explicitly employ the analytical operational R-D model of a three-dimensional wavelet video coder to solve the JSCC problem. Using this model, we formulated the JSCC optimization as a nonlinear programming (NP) problem. By expressing the NP problem in terms of a dynamic programming equation, we derived the necessary conditions that facilitate the search for global optimal solutions. In this letter, we focus on finding the optimal JSCC problem for subband video coding and not on deriving computationally efficient methods for JSCC.

The quality-of-service (QoS) guarantees enabled by the new IEEE 802.11 a/e Wireless LAN (WLAN) standard are specifically targeting the real-time transmission of multimedia content over the wireless medium. Since video data consume the largest part of the available bitrate compared to other media, optimization of video streaming for this new standard is a significant factor for the successful deployment of practical systems. Delay-constrained streaming of fully-scalable video over IEEE 802.11 a/e WLANs is of great interest for many multimedia applications. The new medium access control (MAC) protocol of IEEE 802.11e is called the Hybrid Coordination Function (HCF) and, in this paper, we will specifically consider the problem of video transmission over HCF Controlled Channel Access (HCCA). A cross-layer optimization across the MAC and application layers of the OSI stack is used in order to exploit the features provided by the combination of the new HCCA standard with new versatile scalable video coding algorithms. Specifically, we propose an optimized and scalable HCCA-based admission control for delay-constrained video streaming applications that leads to a larger number of stations being simultaneously admitted (without quality reduction to any video flow). Subsequently, given the allocated transmission opportunity, each station deploys an optimized Application-MAC-PHY adaptation, scheduling, and protection strategy that is facilitated by the fine-grain layering provided by the scalable bitstream. Given that each video flow needs to always comply with the predetermined (a priori negotiated) traffic specification parameters, this cross-layer strategy enables graceful quality degradation whenever the channel conditions or the video sequence characteristics change. For instance, it is demonstrated that the proposed cross-layer protection and bitstream adaptation strategies facilitate QoS token rate adaptation under link adaptation mechanisms that utilize different physical layer transmission rates. The expected gains offered by the optimized solutions proposed in this paper are established theoretically, as well as through simulations.

Scalable video coding offers a flexible representation for video adaptation in multiple dimensions comprising spatial detail and temporal resolution, thus providing great benefits for universal media access (UMA) applications. However, currently most of the approaches address the multidimensional adaptation (MDA) problem in an ad hoc manner. One challenging issue affecting the systematic MDA solution is the difficulty in constructing analytical models in theoretical optimization that capture the relations between video utility and MDA operations. In this paper, we propose a general classification-based prediction framework for selecting the preferred MDA operations based on subjective quality evaluation. For this purpose, we first apply domain-specific knowledge or general unsupervised clustering to construct distinct categories within which the videos share similar preferred MDA operations. Thereafter, a machine learning based method is applied where the low level content features extracted from the compressed video streams are employed to train a framework for the problem of joint signal-to-noise ratio (SNR)-temporal adaptation selection based on the motion compensated three-dimensional subband coding (MC-3DSBC) system. We conduct extensive subjective tests involving 31 subjects, 128 video clips, and formal subjective quality metrics. Statistical analysis of the experimental results confirms the excellent accuracy in using domain knowledge and content features to predict the MDA operation.

We present a framework for the systematic analysis of video encoding complexity, measured in terms of the number of motion estimation (ME) computations, that we illustrate on motion compensated wavelet video coding schemes. We demonstrate the graceful complexity scalability of these schemes through the modification of the spatiotemporal decomposition structure and the ME parameters, and the use of spatiotemporal prediction. We generate a wide range of rate-distortion-complexity (R-D-C) operating points for different sequences, by modifying these options. Using our analytical framework we derive closed form expressions for the number of ME computations for these different coding modes and show that they accurately capture the computational complexity independent of the underlying content characteristics. Our framework for complexity analysis can be combined with rate-distortion modeling to determine the encoding structure and parameters for optimal R-D-C tradeoffs.

Wireless networks are poised to enable a variety of existing and emerging multimedia streaming applications. As the use of wireless local area networks spreads beyond simple data transfer to bandwidth-intense, delay-sensitive, and loss-tolerant multimedia applications, addressing quality of service issues become extremely important. Currently, a multitude of protection and adaptation strategies exists in the different layers of the open systems interconnection (OSI) stack. Hence, an in-depth understanding and comparative evaluation of these strategies are necessary to effectively assess and enable the possible trade-offs in multimedia quality, power consumption, implementation complexity, and spectrum utilization that are provided by the various OSI layers. This further opens the question of cross-layer optimization and its effectiveness in providing an improved solution with respect to the above trade-offs. In this article we formalize the cross-layer problem, discuss its challenges, and present several possible solutions. Moreover, we also discuss the impact the cross-layer optimization strategy deployed at one station has on the multimedia performance of other stations. We introduce a new fairness concept for wireless multimedia systems that employs different cross-layer strategies, and show its advantages when compared to existing resource allocation mechanisms used in wireline communications. Finally, we propose a new paradigm for wireless communications based on competition, which allows wireless stations to harvest additional resources or free up resources as well as optimally and dynamically adapt their cross-layer transmission strategies to improve multimedia quality and/or power consumption.

Existing research on Universal Multimedia Access has mainly focused on adapting multimedia to the network characteristics while overlooking the receiver capabilities. Alternatively, part 7 of the MPEG-21 standard entitled Digital Item Adaptation (DIA) defines description tools to guide the multimedia adaptation process based on both the network conditions and the available receiver resources. In this paper, we propose a new and generic rate-distortion-complexity model that can generate such DIA descriptions for image and video decoding algorithms running on various hardware architectures. The novelty of our approach is in virtualizing complexity, i.e., we explicitly model the complexity involved in decoding a bitstream by a generic receiver. This generic complexity is translated dynamically into "real" complexity, which is architecture-specific. The receivers can then negotiate with the media server/proxy the transmission of a bitstream having a desired complexity level based on their resource constraints. Hence, unlike in previous streaming systems, multimedia transmission can be optimized in an integrated rate-distortion-complexity setting by minimizing the incurred distortion under joint rate-complexity constraints.

Motion-compensated temporal filtering (MCTF) is an essential ingredient of the recently developed wavelet-based scalable video coding schemes. Lifting implementation of these decompositions represents a versatile tool for spatiotemporal optimizations, and several improvements have already been proposed in this framework. In this paper, we propose new spatiotemporal update operators based either on weighted averages of multiple connected pixels or on nonlinear filtering of these pixels. We demonstrate the improved performance of the proposed operators, both theoretically and experimentally.

We introduce an efficient and flexible framework for temporal filtering in wavelet-based scalable video codecs called unconstrained motion compensated temporal filtering (UMCTF). UMCTF allows for the use of different filters and temporal decomposition structures through a set of controlling parameters that may be easily modified during the coding process, at different granularities and levels. The proposed framework enables the adaptation of the coding process to the video content, network and end-device characteristics, allows for enhanced scalability, content-adaptivity and reduced delay, while improving the coding efficiency as compared to state-of-the-art motion-compensated wavelet video coders. Additionally, a mechanism for the control of the distortion variation in video coding based on UMCTF employing only the predict step is proposed. The control mechanism is formulated by expressing the distortion in an arbitrary decoded frame, at any temporal level in the pyramid, as a function of the distortions in the reference frames at the same temporal level. All the different scenarios proposed in the paper are experimentally validated through a coding scheme that incorporates advanced features (such as rate-distortion optimized variable block-size multihypothesis prediction and overlapped block motion compensation). Experiments are carried out to determine the relative efficiency of different UMCTF instantiations, as well as to compare against the current state-of-the-art in video coding.

Robust streaming of video over 802.11 wireless LANs (WLANs) poses many challenges, including coping with packets losses caused by network buffer overflow or link erasures. In this paper, we propose a novel error protection method that can provide adaptive quality-of-service (QoS) to layered coded video by utilizing priority queueing at the network layer and retry-limit adaptation at the link layer. The design of our method is motivated by the observation that the retry limit settings of the MAC layer can be optimized in such a way that the overall packet losses that are caused by either link erasure or buffer overflow are minimized. We developed a real-time retry limit adaptation algorithm to trace the optimal retry limit for both the single-queue (or single-layer) and multiqueue (or multilayer) cases. The video layers are unequally protected over the wireless link by the MAC with different retry limits. In our proposed transmission framework, these retry limits are dynamically adapted depending on the wireless channel conditions and traffic characteristics. Furthermore, the proposed priority queueing discipline is enhanced with packet filtering and purging functionalities that can significantly save bandwidth by discarding obsolete or un-decodable packets from the buffer. Simulations show that the proposed cross-layer protection mechanism can significantly improve the received video quality.

Robust streaming of video over 802.11 wireless local area networks poses many challenges, including coping with bandwidth variations, data losses, and heterogeneity of the receivers. Currently, each network layer (including physical layer, media access control (MAC), transport, and application layers) provides a separate solution to these challenges by providing its own optimized adaptation and protection mechanisms. However, this layered strategy does not always result in an optimal overall performance for the transmission of video. Moreover, certain protection strategies can be implemented simultaneously in several layers and, hence, the optimal choices from the application and complexity perspective need to be identified. In this paper, we evaluate different error control and adaptation mechanisms available in the different layers for robust transmission of video, namely MAC retransmission strategy, application-layer forward error correction, bandwidth-adaptive compression using scalable coding, and adaptive packetization strategies. Subsequently, we propose a novel adaptive cross-layer protection strategy for enhancing the robustness and efficiency of scalable video transmission by performing tradeoffs between throughput, reliability, and delay depending on the channel conditions and application requirements. The results obtained using the proposed adaptive cross-layer protection strategies show a significantly improved visual performance for the transmitted video over a variety of channel conditions.

There is a rising concern about the environmental status of the seas of our planet. Such concern regards several kinds of anthropogenic activities and their impact on the marine ecosystems. Part of the adverse effects are recognised to be due to various forms of acoustic emissions generated by human activities related to the exploitation of sea resources and to shipping. The main regulatory bodies at international level, in the last decade, have started to look into the problem with the aim of monitoring the environmental status of marine waters, in particular the acoustical aspects) identify the situations where the anthropogenic impact is most intrusive and study and promote future actions for its control and reduction. The present work reports about the development and validation of a simulation tool able to predict the noise field generated by a set of ships sailing in a specific area. The simulation is based on real traffic data derived from the Automatic Identification System (AIS) normally used to monitor shipping traffic and on specific data characterising the environment of the zone of interest. The tool is meant to provide the Regulator with a means to study the present situation (with on-line AIS data) and/or study the effectiveness of possible measures devoted to reduce the acoustical impact of shipping by design and/or operative requirements. Motivation, bases and characteristics of the developed procedure are described in the paper, where a first validation of the tool is presented on the basis of data regarding a sea area off Barcelona (Spain). Data include AIS records, environmental parameters and underwater sound levels surveyed by an hydrophone placed in the area. The work has been developed in the framework of the collaborative project AQUO (Achieve QUieter Oceans by shipping noise footprint reduction), funded by the European Commission within a call of the 7th Framework Programme dedicated to the assessment and mitigation of noise impacts of the maritime transport on the marine environment, coordinated topic “The Ocean of Tomorrow”.

Transmission of video over wireless and mobile networks requires a scalable solution that is capable of adapting to the varying channel conditions in real-time (bit-rate scalability). Furthermore, video content needs to be coded in a scalable fashion to match the capabilities of a variety of devices (complexity scalability). These two scalability properties provide the flexibility that is necessary to satisfy the "anywhere, anytime and anyone" network paradigm of wireless systems. MPEG-4 fine-granular-scalability (FGS) is a flexible low-complexity solution for video streaming over heterogeneous networks (e.g., the Internet and wireless networks) and is highly resilient to packet losses. However, the flexibility and packet-loss resilience come at the expense of decreased coding efficiency compared with nonscalable coding. A novel scalable video-coding framework and corresponding compression methods for wireless video streaming is introduced. Building on the FGS approach, the proposed framework, which we refer to as adaptive motion-compensation FGS (AMC-FGS), provides improved video quality of up to 2 dB. Furthermore, the new scalability structures provide the FGS framework with the flexibility to provide tradeoffs between resilience, higher coding efficiency and terminal complexity for more efficient wireless transmission.

PI4KIIIβ recruitment to Golgi membranes relies on GBF1/Arf and ACBD3. Enteroviruses such as poliovirus and coxsackievirus recruit PI4KIIIβ to their replication sites via their 3A proteins. Here, we show that human rhinovirus (HRV) 3A also recruited PI4KIIIβ to replication sites. Unlike other enterovirus 3A proteins, HRV 3A failed to bind GBF1. Although HRV 3A was previously shown to interact with ACBD3, our data suggest that PI4KIIIβ recruitment occurred independently of both GBF1 and ACBD3.

The hydrophobic molecules of the metabolome – also named the lipidome – constitute a major part of the entire metabolome. Novel technologies show the existence of a staggering number of individual lipid species, the biological functions of which are, with the exception of only a few lipid species, unknown. Much can be learned from pathogens that have evolved to take advantage of the complexity of the lipidome to escape the immune system of the host organism and to allow their survival and replication. Different types of pathogens target different lipids as shown in interaction maps, allowing visualization of differences between different types of pathogens. Bacterial and viral pathogens target predominantly structural and signaling lipids to alter the cellular phenotype of the host cell. Fungal and parasitic pathogens have complex lipidomes themselves and target predominantly the release of polyunsaturated fatty acids from the host cell lipidome, resulting in the generation of eicosanoids by either the host cell or the pathogen. Thus, whereas viruses and bacteria induce predominantly alterations in lipid metabolites at the host cell level, eukaryotic pathogens focus on interference with lipid metabolites affecting systemic inflammatory reactions that are part of the immune system. A better understanding of the interplay between host–pathogen interactions will not only help elucidate the fundamental role of lipid species in cellular physiology, but will also aid in the generation of novel therapeutic drugs., The lipidome constitutes a major part of the entire cellular metabolome with functions in cell structure, membrane dynamics and organization, energy supply and storage, and cellular signaling. Pathogens have adapted in different ways to take advantage of the complexity of the host cell lipidome in order to escape the immune system and to allow their survival and replication. Here we review the lipid targeting by various types of pathogens and provide interaction maps, allowing visualization of differences between viruses, bacteria, fungi and parasites.

Real-time streaming of audiovisual content over the Internet is emerging as an important technology area in multimedia communications. Due to the wide variation of available bandwidth over Internet sessions, there is a need for scalable video coding methods and (corresponding) flexible streaming approaches that are capable of adapting to changing network conditions in real time. In this paper, we describe a new scalable video-coding framework that has been adopted recently by the MPEG-4 video standard. This new MPEG-4 video approach, which is known as Fine-Granular-Scalability (FGS), consists of a rich set of video coding tools that support quality (i.e., SNR), temporal, and hybrid temporal-SNR scalabilities. Moreover, one of the desired features of the MPEG-J FGS method is its simplicity and flexibility in supporting unicast and multicast streaming applications over IF.

Transmission of video over bandwidth varying networks like the Internet requires a highly scalable solution capable of adapting to the network condition in real-time. To address this requirement, scalable video-coding schemes with multiple enhancement layers have been proposed. However, under this multiple-layer paradigm, the transmission bit-rate of each layer has to be predetermined at encoding time. Consequently, the range of bit-rates that can be covered with these compression schemes is limited and often lower than, or different from, the desired range required at transmission time. In this paper, a novel scalable video-coding framework and a corresponding compression method for Internet video streaming are introduced. Building upon the MPEG-4 SNR fine-granular-scalability (FGS) approach, the proposed framework provides a new level of abstraction between the encoding and transmission process by supporting both SNR and temporal scalability through a single enhancement layer. Therefore, our proposed approach enables streaming systems to support full SNR, full temporal, and hybrid temporal-SNR scalability in real-time depending on the available bandwidth, packet-loss patterns, user preferences, and/or receiver complexity. Moreover, our experiments revealed that the presented FGS temporal-SNR scalability has similar or better PSNR performance than the multilayer scalability schemes. Subsequently, an Internet video streaming system employing the proposed hybrid FGS-temporal scalability structure is introduced, together with a very simple, yet effective, rate-control that performs the tradeoffs between individual image quality (SNR) and motion-smoothness in real-time. The hybrid temporal-SNR scalability presented in this paper has been adopted in the MPEG-4 standard to support video-streaming applications.

Several embedded video coding schemes have been recently developed for multimedia streaming over IP. In particular, fine-granular-scalability (FGS) video coding has been recently adopted by the MPEG-4 standard as the core video-compression method for streaming applications. From its inception, the FGS scalability structure was designed to be packet-loss resilient especially under unequal packet-loss protection (UPP). However, since the introduction of FGS, there has not been a comprehensive study evaluating its packet-loss resilience under unrecoverable packet losses that are common in Internet streaming applications. In this paper, we evaluate two important aspects of FGS packet-loss resilience. First, we study the impact of applying UPP between the base- and enhancement-layers on FGS-based streams, and we compare equal packet-loss protection (EPP) with UPP scenarios. Second, we introduce the notion of fine-grained loss protection (FGLP), which is suitable for the FGS enhancement-layer, and we develop an analytical framework for evaluating FGLP bounds. Based on these bounds, we show the impact of applying fine-grained protection to the FGS enhancement-layer for different types of video sequences and over a wide range of bit-rates and packet-loss ratios. As illustrated by our extensive simulation results, applying 1) UPP between the base- and enhancement-layers and 2) FGLP for the FGS enhancement-layer can provide significant resilience under moderate-to-high packet-loss ratios (e.g., 5-10%). Furthermore, the merits of this new packet-loss protection technique go beyond the FGS coding scheme, because FGLP can be successfully applied to improve the resilience to packet-losses of other embedded video coding techniques.

In this letter, we tackle the problem of competitive single antenna transmitters accessing a multiple antenna access point using a random access protocol. We show that the access point can help the system to reach a unique Stackelberg equilibrium and prevent network collapse due to the selfish nature of the transmitters.

We develop a novel design framework for dynamic distributed spectrum sharing among secondary users (SUs) who adjust their power levels to compete for spectrum opportunities while satisfying the interference temperature (IT) constraints imposed by primary users. The considered interaction among the SUs is characterized by the following three features. First, since the SUs are decentralized, they are selfish and aim to maximize their own long-term payoffs from utilizing the network rather than obeying the prescribed allocation of a centralized controller. Second, the SUs interact with each other repeatedly and they can coexist in the system for a long time. Third, the SUs have limited and imperfect monitoring ability: they only observe whether the IT constraints are violated, and their observation is imperfect due to the erroneous measurements. To capture these features, we model the interaction of the SUs as a repeated game with imperfect monitoring. We first characterize the set of Pareto optimal payoffs that can be achieved by deviation-proof spectrum sharing policies, which are policies that the selfish users find it in their interest to comply with. Next, for any given payoff in this set, we show how to construct a deviation-proof policy to achieve it. The constructed deviation-proof policy is amenable to distributed implementation, and allows users to transmit in a time-division multiple-access (TDMA) fashion. In the presence of strong multi-user interference, our policy outperforms existing spectrum sharing policies that dictate users to transmit at constant power levels simultaneously. Moreover, our policy can achieve Pareto optimality even when the SUs have limited and imperfect monitoring ability, as opposed to existing solutions based on repeated games, which require perfect monitoring abilities., 37 pages, 8 figures, 4 tables; IEEE Journal on Selected Areas in Communications (JSAC) 2012

Information exchange systems differ in many ways, but all share a common vulnerability to selfish behavior and free-riding. In this paper, we build incentives schemes based on social norms. Social norms prescribe a social strategy for the users in the system to follow and deploy reputation schemes to reward or penalize users depending on their behaviors. Because users in these systems often have only limited capability to observe the global system information, e.g. the reputation distribution of the users participating in the system, their beliefs about the reputation distribution are heterogeneous and biased. Such belief heterogeneity causes a positive fraction of users to not follow the social strategy. In such practical scenarios, the standard equilibrium analysis deployed in the economics literature is no longer directly applicable and hence, the system design needs to consider these differences. To investigate how the system designs need to change when the participating users have only limited observations, we focus on a simple social norm with binary reputation labels but allow adjusting the punishment severity through randomization. First, we model the belief heterogeneity using a suitable Bayesian belief function. Next, we formalize the users' optimal decision problems and derive in which scenarios they follow the prescribed social strategy. With this result, we then study the system dynamics and formally define equilibrium in the sense that the system is stable when users strategically optimize their decisions. By rigorously studying two specific cases where users' belief distribution is constant or is linearly influenced by the true reputation distribution, we prove that the optimal reputation update rule is to choose the mildest possible punishment. This result is further confirmed for higher order beliefs in simulations., 24 pages, 9 figures

Item does not contain fulltext RNA viruses can rapidly mutate and acquire resistance to drugs that directly target viral enzymes, which poses serious problems in a clinical context. Therefore, there is a growing interest in the development of antiviral drugs that target host factors critical for viral replication, since they are unlikely to mutate in response to therapy. We recently demonstrated that phosphatidylinositol-4-kinase IIIbeta (PI4KIIIbeta) and its product phosphatidylinositol-4-phosphate (PI4P) are essential for replication of enteroviruses, a group of medically important RNA viruses including poliovirus (PV), coxsackievirus, rhinovirus, and enterovirus 71. Here, we show that enviroxime and GW5074 decreased PI4P levels at the Golgi complex by directly inhibiting PI4KIIIbeta. Coxsackievirus mutants resistant to these inhibitors harbor single point mutations in the non-structural protein 3A. These 3A mutations did not confer compound-resistance by restoring the activity of PI4KIIIbeta in the presence of the compounds. Instead, replication of the mutant viruses no longer depended on PI4KIIIbeta, since their replication was insensitive to siRNA-mediated depletion of PI4KIIIbeta. The mutant viruses also did not rely on other isoforms of PI4K. Consistently, no high level of PI4P could be detected at the replication sites induced by the mutant viruses in the presence of the compounds. Collectively, these findings indicate that through specific single point mutations in 3A, CVB3 can bypass an essential host factor and lipid for its propagation, which is a new example of RNA viruses acquiring resistance against antiviral compounds, even when they directly target host factors.

Underwater gliders are autonomous vehicles that use small changes in their buoyancy in conjunction with wings to convert vertical motion to horizontal, and thereby propel themselves forward, with very low power consumption, through the ocean for a long period of time. Gliders typically make measurements such as temperature, conductivity (to calculate salinity), currents, chlorophyll fluorescence, optical backscatter and bottom depth. However, such a platform could be a good candidate if properly equipped with an acoustic payload to persistently monitor the underwater acoustic environment. For that reason, NURC and the Technical University of Catalonia (UPC) decided in 2010 to jointly develop a glider acoustic payload that would provide the recording of two hydrophones but also, which is quite unique, provide in addition a real-time detection / classification (DC) capability. The DC capability will allow, while the glider being at-sea, to provide real-time feedback on the acoustic environment the glider is passing by, instead of only providing recording capability for postprocessing work as previously done in the past. The purpose of the paper is to describe the characteristics of the system that has been developed and additionally reports at-sea results from a deep-water WEBB glider operating in the Mediterranean Sea. Those results demonstrate the capability of the developed acoustic payload to detect and classify marine mammals in real-time within the glider. Examples of the noise generated by the glider are also presented

This paper develops a game-theoretic framework for the design and analysis of a new class of incentive schemes called intervention schemes. We formulate intervention games, propose a solution concept of intervention equilibrium, and prove its existence in a finite intervention game. We apply our framework to resource sharing scenarios in wireless communications, whose non-cooperative outcomes without intervention yield suboptimal performance. We derive analytical results and analyze illustrative examples in the cases of imperfect and perfect monitoring. In the case of imperfect monitoring, intervention schemes can improve the suboptimal performance of non-cooperative equilibrium when the intervention device has a sufficiently accurate monitoring technology, although it may not be possible to achieve the best feasible performance. In the case of perfect monitoring, the best feasible performance can be obtained with an intervention scheme when the intervention device has a sufficiently strong intervention capability., 29 pages, 1 table, 6 figures

The development and broad use of passive acoustic monitoring techniques have the potential to help assessing the large-scale influence of artificial noise on marine organisms and ecosystems. Deep-sea observatories have the potential to play a key role in understanding these recent acoustic changes. LIDO(Listening to the Deep Ocean Environment) is an international project that is allowing the real-time longterm monitoring of marine ambient noise as well as marine mammal sounds at cabled and standalone observatories. Here, we present the overall development of the project and the use of passive acoustic monitoring (PAM) techniques to provide the scientific community with real-time data at large spatial and temporal scales. Special attention is given to the extraction and identification of high frequency cetacean echolocation signals given the relevance of detecting target species, e.g. beaked whales, in mitigation processes, e.g. during military exercises.

Three structure functions have been determined in the reaction [sup 16]O([ital e],[ital e][prime][ital p])[sup 15]N at [ital Q][sup 2]=0.20 (GeV/[ital c])[sup 2] for 1[ital p][sub 1/2] and 1[ital p][sub 3/2] knockout and for the excitation of the (5/2[sup +],1/2[sup +]) doublet at [ital E][sub [ital x]]=5.3 MeV in [sup 15]N. The longitudinal-transverse interference structure function [ital W][sub [ital L][ital T]] is enhanced by a factor 2.05[plus minus]0.06[plus minus]0.12 for 1[ital p][sub 3/2] knockout and by a factor 1.50[plus minus]0.10[plus minus]0.08 for 1[ital p][sub 1/2] knockout with respect to a calculation that gives a proper account of data taken in parallel kinematics. The longitudinal structure function [ital W][sub [ital L]] is also enhanced, albeit less with respect to these calculations.

In a search for nuclear deformation effects in the (e, e'p) reaction, proton knockout from the spherical nucleus 142Nd and the transitional isotope 146Nd has been investigated. Momentum distributions for the transitions to the discrete states below 1.3 MeV excitation energy in 141Pr and below 0.6 MeV in 145Pr have been measured and compared to results of calculations with the Nilsson + BCS model, assuming 146Nd to be deformed and including Coriolis coupling. For the transitions to the 72+ states (1g72 knockout) the spectroscopic strength changes in going from 142Nd to 146Nd but the shape of the momentum distribution remains fairly unchanged. The same is true for the 52+ states. For the transition to the 32+ state at 0.348 MeV in 145Pr, the measured momentum distribution is influenced by a mixture of ∼ 25% s-wave in agreement with the prediction of a close-lying 12+ state in the deformed shell model. The theory is well able to account for the increased level density in 145Pr and for the other experimental features observed, but the calculated spectroscopic factors are systematically larger than the experimental ones.

In this paper, we consider a wireless amplify-and- forward relay network with one relay node and multiple source-destination pairs/users and propose a compensation framework such that the relay has incentives to forward the users' signals. Specifically, depending on the quality of the received signals, the relay sets the prices to maximize its revenue and correspondingly charges the users utilizing the relay for their transmissions. Given the specified price, the users competitively employ the relay node to forward their signals. We model each user as a strategic player, which aims at maximizing its own net utility through power allocation, and apply non-cooperative game theory to analyze the competition among the users. It is shown that, in the game played by the users, there always exists a unique Nash equilibrium point that can be achieved through distributed iterations. Then, subject to the availability of complete information about the users at the relay, we propose a low- complexity uniform pricing algorithm and an optimal differentiated pricing algorithm, in which the relay charges the users at a sub-optimal uniform price and at different prices, respectively.

In this paper, we consider the problem of real-time transmission scheduling over time-varying channels. We first formulate the transmission scheduling problem as a Markov decision process (MDP) and systematically unravel the structural properties (e.g. concavity in the state-value function and monotonicity in the optimal scheduling policy) exhibited by the optimal solutions. We then propose an online learning algorithm which preserves these structural properties and achieves -optimal solutions for an arbitrarily small . The advantages of the proposed online method are that: (i) it does not require a priori knowledge of the traffic arrival and channel statistics and (ii) it adaptively approximates the state-value functions using piece-wise linear functions and has low storage and computation complexity. We also extend the proposed low-complexity online learning solution to the prioritized data transmission. The simulation results demonstrate that the proposed method achieves significantly better utility (or delay)-energy trade-offs when comparing to existing state-of-art online optimization methods., 41pages

In the frame of the European Sea-floor Observatory Network (ESONET) and in preparation of the Demonstration Mission Listening to the Deep-Ocean Environment (LIDO) algorithms for the automated real-time detection, classification and localisation of cetaceans have been developed. Such Passive Acoustic Monitoring techniques have the potential to play a key role in cetaceans’ conservation for they allow a non-invasive study of their behaviour, a better knowledge of their population dynamics, and a better understanding of their dynamic relationship with their environment. This paper investigates the development of efficient and accurate techniques to be used as the basis of a localisation module for an automated real-time Passive Acoustic Monitoring system. An opportunity to assess the capabilities of the developed localisation modules was given by recordings collected with a bottom-mounted (around 2080 m depth) tetrahedral compact hydrophone array located offshore the port of Catania (Sicily) during the NEMO-ONDE campaign in the years 2005–2006 by INFN and CIBRA [2]. A well-known class of methods for acoustic source localisation is based on time differences of arrival (TDOA). Its capabilities have shown to be useful even in adverse situations (i.e., few sensors, high noise levels and/or poor calibration). A second class of methods, the space–time methods, originated in underwater applications such as sonar but reached its most significant achievements over the last 20 years in digital communications with recent progress in the treatment of broadband signals. These developments are here revisited under the scope of the localisation and tracking of cetacean vocalisations. Various broadband space–time methods were implemented and allowed to map the sound radiated during the detected clicks and to consequently localise both sperm whales and vessels. Hybrid methods were also developed which improved the robustness of space–time methods to noise and reverberation and reduced processing time. In most cases, the small variance obtained for these estimates lessened the necessity of additional statistical clustering. Even though not independently confirmed by sightings, the tracks derived in the proposed frame can be considered to be consistent with the known movements of sperm whales and vessels.

Contains fulltext : 87489.pdf (Publisher’s version ) (Closed access) Many RNA viruses remodel intracellular membranes to generate specialized sites for RNA replication. How membranes are remodeled and what properties make them conducive for replication are unknown. Here we show how RNA viruses can manipulate multiple components of the cellular secretory pathway to generate organelles specialized for replication that are distinct in protein and lipid composition from the host cell. Specific viral proteins modulate effector recruitment by Arf1 GTPase and its guanine nucleotide exchange factor GBF1, promoting preferential recruitment of phosphatidylinositol-4-kinase IIIbeta (PI4KIIIbeta) to membranes over coat proteins, yielding uncoated phosphatidylinositol-4-phosphate (PI4P) lipid-enriched organelles. The PI4P-rich lipid microenvironment is essential for both enteroviral and flaviviral RNA replication; PI4KIIIbeta inhibition interferes with this process; and enteroviral RNA polymerases specifically bind PI4P. These findings reveal how RNA viruses can selectively exploit specific elements of the host to form specialized organelles where cellular phosphoinositide lipids are key to regulating viral RNA replication.

Cells infected with dengue virus release a high proportion of immature prM-containing virions. In accordance, substantial levels of prM antibodies are found in sera of infected humans. Furthermore, it has been recently described that the rates of prM antibody responses are significantly higher in patients with secondary infection compared to those with primary infection. This suggests that immature dengue virus may play a role in disease pathogenesis. Interestingly, however, numerous functional studies have revealed that immature particles lack the ability to infect cells. In this report, we show that fully immature dengue particles become highly infectious upon interaction with prM antibodies. We demonstrate that prM antibodies facilitate efficient binding and cell entry of immature particles into Fc-receptor-expressing cells. In addition, enzymatic activity of furin is critical to render the internalized immature virus infectious. Together, these data suggest that during a secondary infection or primary infection of infants born to dengue-immune mothers, immature particles have the potential to be highly infectious and hence may contribute to the development of severe disease., Author Summary Dengue virus represents a major emerging arboviral pathogen circulating in the (sub)tropical regions of the world, putting 2.5 billion people at risk of infection. Each of the four circulating serotypes can cause disease ranging from febrile illness to devastating manifestations including dengue hemorrhagic fever and dengue shock syndrome. Severe illness is observed in individuals experiencing a re-infection with a heterologous dengue virus serotype and in infants born to dengue-immune mothers, presumably due to antibody-dependent enhancement of infection. Interestingly, it has been recently reported that patients experiencing a secondary infection have elevated levels of antibodies directed against the prM protein of immature dengue virus particles. Although it is known that cells infected with dengue virus release substantial amounts of prM-containing virions, numerous functional studies have demonstrated that immature particles lack the ability to infect cells. Herein, we show that essentially non-infectious fully immature dengue virions become virtually as infectious as wild type virus particles in the presence of prM antibodies. Anti-prM antibodies facilitate efficient binding and entry of immature dengue virus into cells carrying Fc-receptors. Furthermore, furin activity in target cells is critical for triggering infectivity of immature virus. These data indicate that immature dengue virus has the potential to be highly infectious and hence may contribute to disease pathogenesis.

The interference structure function {ital f}{sub 01}, the transverse structure function {ital f}{sub 11}, and the longitudinal structure function {ital f}{sub 00} have been determined in a {sup 2}H({ital e},{ital e}{prime}{ital p}) experiment at a four-momentum transfer {ital Q}{sup 2}=0.21 (GeV/{ital c}){sup 2}. The {ital f}{sub 00} and {ital f}{sub 11} data are in agreement both with a nonrelativistic calculation that includes the effects of final-state interaction (FSI), meson-exchange currents, and isobar configurations, and with a relativistic calculation that only includes FSI effects. The {ital f}{sub 01} data demonstrate the relevance of a relativistic approach even at this low value of the momentum transfer.

The main challenges of cognitive radio include spectrum sensing at the physical (PHY) layer to detect the activity of primary users and spectrum sharing at the medium access control (MAC) layer to coordinate access among coexisting secondary users. In this paper, we consider a cognitive radio network in which a primary user shares a channel with secondary users that cannot distinguish the signals of the primary user from those of a secondary user. We propose a class of distributed cognitive MAC protocols to achieve efficient spectrum sharing among the secondary users while protecting the primary user from potential interference by the secondary users. By using a MAC protocol with one-slot memory, we can obtain high channel utilization by the secondary users while limiting interference to the primary user at a low level. The results of this paper suggest the possibility of utilizing MAC design in cognitive radio networks to overcome limitations in spectrum sensing at the PHY layer as well as to achieve spectrum sharing at the MAC layer., 24 pages, 7 figures

Large-scale multimedia semantic concept detection requires realtime identification of a set of concepts in streaming video or large image datasets. The potentially high data volumes of multimedia content, and high complexity associated with individual concept detectors, have hindered the practical deployment of many current solutions. In this paper, we present a summary of our work in building systems and applications for resource adaptive semantic concept detection in multimedia using large-scale distributed stream mining systems. We construct such concept detection applications as a hierarchical topology of individual concept detectors, and deploy them on distributed processing infrastructure. We then focus on dynamically configuring individual concept detectors to meet system imposed resource constraints while minimizing a penalty defined in terms of the misclassification cost. We present multiple centralized and distributed algorithms for this configuration, and describe the implemented application and system. We also verify through simulations that significant improvement in terms of accuracy of classification can be achieved through our approach.

Contains fulltext : 80659.pdf (Publisher’s version ) (Open Access) The replication of enteroviruses is sensitive to brefeldin A (BFA), an inhibitor of endoplasmic reticulum-to-Golgi network transport that blocks activation of guanine exchange factors (GEFs) of the Arf GTPases. Mammalian cells contain three BFA-sensitive Arf GEFs: GBF1, BIG1, and BIG2. Here, we show that coxsackievirus B3 (CVB3) RNA replication is insensitive to BFA in MDCK cells, which contain a BFA-resistant GBF1 due to mutation M832L. Further evidence for a critical role of GBF1 stems from the observations that viral RNA replication is inhibited upon knockdown of GBF1 by RNA interference and that replication in the presence of BFA is rescued upon overexpression of active, but not inactive, GBF1. Overexpression of Arf proteins or Rab1B, a GTPase that induces GBF1 recruitment to membranes, failed to rescue RNA replication in the presence of BFA. Additionally, the importance of the interaction between enterovirus protein 3A and GBF1 for viral RNA replication was investigated. For this, the rescue from BFA inhibition of wild-type (wt) replicons and that of mutant replicons of both CVB3 and poliovirus (PV) carrying a 3A protein that is impaired in binding GBF1 were compared. The BFA-resistant GBF1-M832L protein efficiently rescued RNA replication of both wt and mutant CVB3 and PV replicons in the presence of BFA. However, another BFA-resistant GBF1 protein, GBF1-A795E, also efficiently rescued RNA replication of the wt replicons, but not that of mutant replicons, in the presence of BFA. In conclusion, this study identifies a critical role for GBF1 in CVB3 RNA replication, but the importance of the 3A-GBF1 interaction requires further study.

This paper discusses a special type of multi-user communication scenario, in which users' utilities are linearly impacted by their competitors' actions. First, we explicitly characterize the Nash equilibrium and Pareto boundary of the achievable utility region. Second, the price of anarchy incurred by the non-collaborative Nash strategy is quantified. Third, to improve the performance in the non-cooperative scenarios, we investigate the properties of an alternative solution concept named conjectural equilibrium, in which individual users compensate for their lack of information by forming internal beliefs about their competitors. The global convergence of the best response and Jacobi update dynamics that achieve various conjectural equilibria are analyzed. It is shown that the Pareto boundaries of the investigated linearly coupled games can be sustained as stable conjectural equilibria if the belief functions are properly initialized. The investigated models apply to a variety of realistic applications encountered in the multiple access design, including wireless random access and flow control., Comment: 20 pages, 1 figure

In the four-momentum-transfer range 0.05{le}{ital q}{sub {nu}}{sup 2}{le}0.27 (GeV/{ital c}){sup 2}, longitudinal and transverse response functions have been determined by performing a Rosenbluth separation of {sup 2}H({ital e},{ital e}{prime}{ital p}) coincidence cross sections measured in parallel kinematics. The results are compared to nonrelativistic calculations that include the effects of final-state interaction, meson-exchange currents, and isobar configurations, and to relativistic calculations that include the effects of final-state interaction. The ratios of the response functions agree with both calculations; the absolute values are (16{plus minus}3{plus minus}8)% larger than predicted.

The incidence and disease burden of arthropod-borne flavivirus infections have dramatically increased during the last decades due to major societal and economic changes, including massive urbanization, lack of vector control, travel, and international trade. Specifically, in the case of dengue virus (DENV), the geographical spread of all four serotypes throughout the subtropical regions of the world has led to larger and more severe outbreaks. Many studies have established that recovery from infection by one DENV serotype provides immunity against that serotype, whereas reinfection with another serotype may result in severe disease. Pre-existing antibodies thus play a critical role in controlling viral infection. Both neutralization and enhancement of DENV infection by antibodies are thought to be related to the natural route of viral entry into cells. In this review, we will describe the current knowlegde on the mechanisms involved in flavivirus cell entry and discuss how antibodies may influence the course of infection towards neutralization or enhancement of viral disease. (C) 2008 Elsevier GmbH. All rights reserved.

In this paper, we model the various wireless users in a cognitive radio network as a collection of selfish, autonomous agents that strategically interact in order to compete for the dynamically available spectrum opportunities. We propose a stochastic game framework to model how the competition among users for spectrum opportunities evolves over time. At each stage of the dynamic resource allocation, a spectrum moderator auctions the available resources and the users strategically bid for the required resources. Based on the observed resource allocation and corresponding rewards from previous allocations, we propose a best response learning algorithm that can be deployed by wireless users to improve their bidding policy at each stage. The simulation results show that by deploying the proposed best response learning algorithm, the wireless users can significantly improve their own performance in terms of both the packet loss rate and the incurred cost for the used resources.

This paper studies the value of learning for cognitive transceivers in dynamic wireless networks. We quantify the utility improvement that can be obtained by a wideband cognitive user which learns the stationary usage pattern of the spectrum occupied by narrowband users and, based on this information adapt its transmission. Specifically, we investigate the trade-off between the learning duration and the achievable performance in stationary environments. We apply optimization and large deviations theory to analytically derive an upper bound of the minimum required learning duration, given the user's tolerable performance loss and outage probability. Furthermore, noticing that learning techniques require the information feedback of the spectrum usage pattern between the transceivers, we investigate how the cognitive user can further improve its performance by taking account of its feedback delay. The impact of inaccurate delay estimation on the achievable performance is quantified.

Available spectrum for wireless communications is a limited resource which gains importance with the increasing demand for mobile communication services with high data rates. Measurements show that assigned frequency bands (FBs) are not used efficiently. One approach for increasing the efficiency in spectrum use is the concept of overlay systems, which can be seen as an enabling technology for cognitive radio and dynamic spectrum access by providing frequency agility. In this paper, we propose an approach for the detection of spectral resources based on reinforcement learning, allowing the cognitive radio to select the FBs with the most available resources.

Dynamic resource management by the various cognitive nodes fundamentally changes the passive way that wireless nodes are currently adapting their transmission strategies to match available wireless resources, by enabling them to consciously influence the wireless system dynamics based on the gathered information about other network nodes. In this paper, we discuss the main challenges of performing such dynamic resource management by emphasizing the distributed information in the dynamic multi-agent system. Specifically, the decisions on how to adapt the aforementioned resource management at sources and relays need to be performed in an informationally-decentralized manner, as the tolerable delay does not allow propagating information back and forth throughout the multi-hop infrastructure to a centralized decision maker. The term "cognitive" refers in our paper to both the capability of the network nodes to achieving large spectral efficiencies through exploitation and mitigation of channel and interference variability by dynamically using different frequency bands as well as their ability to learn the "environment" (channel conditions and source characteristic) and the actions of competing nodes through the designed information exchange. We propose our dynamic resource management algorithms performed at each network nodes integrated with multi-agent learning that explicitly consider the timeliness and the cost of such information exchange. The results show that our dynamic resource management approach improves the PSNR of multiple video streams by more than 3 dB as opposed to the state-of-the-art dynamic frequency channel/route selection approaches without learning capability, when the network resources are limited.

Existing cross-layer optimization solutions are often based on the assumption that each layer's parameters are fully accessible to other layers or a centralized optimizer, thereby violating the layered network architecture of the protocol stack. This paper presents a new systematic framework named layered Markov decision process (MDP) for cross-layer optimization, which allows each layer to make autonomous decisions individually and determine the optimal message to be exchanged among layers in order to cooperatively maximize the utility of the wireless station. Hence, this layered cross-layer framework does not change the current layered architecture and is suitable for the delay-sensitive applications over wireless networks.