Demonstrative Suffering: The Gestural (Re)embodiment of Symptoms

Despite the long-standing interest in emotion and bodily conduct, there remains relatively little research concerned with how gestures are used with talk and within interaction to reveal emotional and personal experience. In this article, the author considers the medical consultation and, in particular, the ways in which patients attempt to reveal their experience of illness to the doctor. The paper examines how gesture and other forms of bodily conduct are used to transform symptoms into suffering; to display, enact, and (re)embody medical problems and difficulties. The analysis is based on videorecordings of primary health care consultations and focuses on the social and interactional organization of demonstrative suffering.     

Effect of release rate and ratio of (Z)-11-hexadecen-1-ol from synthetic pheromone blends on trap capture ofHeliothis subflexa (Lepidoptera: Noctuidae)

Response of maleHeliothis subflexa to pheromone-baited traps containing blends of tetradecanal, (Z)-9-tetradecanal, hexadecanal, (Z)-7-hexadecenal, (Z)-9-hexadecenal, (Z)-11-hexadecenal, hexadecan-1-ol acetate, (Z)-7-hexadecen-1-ol acetate, (Z)-9-hexadecen-1-ol acetate, (Z)-11-hexadecen-1-ol acetate, (Z)-9-hexadecen-1-ol, and (Z)-11-hexadecen-1-ol was evaluated. Analysis of trap capture data indicated that (Z)-11-hexadecen-1-ol was a critical component of the pheromone blend. It was determined from emission rate data and measurements of the ratio of pheromone components emitted from rubber septa tested that a significant increase in trap capture of maleH. subflexa occurred when the blends investigated released the alcohol in a narrow range relative to the total amount of pheromone emitted. The optimum range of release ratio of the alcohol for the capture of males in sticky traps was determined to be 0.9–3.5% of the pheromone blend. This release ratio range was reduced to 0.9–1.6% when bucket traps were used.     

Channel Adaptive Quantization for Limited Feedback MIMO Beamforming Systems

Multiple-input multiple-output (MIMO) wireless systems can achieve significant diversity and array gain by using transmit beamforming and receive combining techniques. In the absence of full channel knowledge at the transmitter, the transmit beamforming vector can be quantized at the receiver and sent to the transmitter using a low-rate feedback channel. In the literature, quantization algorithms for the beamforming vector are designed and optimized for a particular channel distribution, commonly the uncorrelated Rayleigh distribution. When the channel is not uncorrelated Rayleigh, however, these quantization strategies result in a degradation of the receive signal-to-noise ratio (SNR). In this paper, switched codebook quantization is proposed where the codebook is dynamically chosen based on the channel distribution. The codebook adaptation enables the quantization to exploit the spatial and temporal correlation inherent in the channel. The convergence properties of the codebook selection algorithm are studied assuming a block-stationary model for the channel. In the case of a nonstationary channel, it is shown using simulations that the selected codebook tracks the distribution of the channel resulting in improvements in SNR. Simulation results show that in the case of correlated channels, the SNR performance of the link can be significantly improved by adaptation, compared with nonadaptive quantization strategies designed for uncorrelated Rayleigh-fading channels     

Unequal Power Allocation for JPEG Transmission Over MIMO Systems

With the introduction of multiple transmit and receive antennas in next generation wireless systems, real-time image and video communication are expected to become quite common, since very high data rates will become available along with improved data reliability. New joint transmission and coding schemes that explore advantages of multiple antenna systems matched with source statistics are expected to be developed. Based on this idea, we present an unequal power allocation scheme for transmission of JPEG compressed images over multiple-input multiple-output systems employing spatial multiplexing. The JPEG-compressed image is divided into different quality layers, and different layers are transmitted simultaneously from different transmit antennas using unequal transmit power, with a constraint on the total transmit power during any symbol period. Results show that our unequal power allocation scheme provides significant image quality improvement as compared to different equal power allocations schemes, with the peak-signal-to-noise-ratio gain as high as 14 dB at low signal-to-noise-ratios.      

Capsosomes with Multilayered Subcompartments: Assembly and Loading with Hydrophobic Cargo

Therapeutic artificial cells or organelles are nanoengineered vehicles that are expected to substitute for missing or lost cellular function. The creation of capsosomes, polymer carrier capsules containing liposomal subcompartments, is a promising approach towards constructing such therapeutic devices using the layer‐by‐layer assembly method. Herein, the assembly of intact, nonaggregated capsosomes containing multiple liposome layers is reported. It is also further demonstrated that thiocoraline, a hydrophobic model peptide with antitumor activity, can be efficiently loaded into the membrane of the liposomal subcompartments of the capsosomes. Cell viability assays verify the activity of the trapped antitumor cargo. It is also shown that pristine capsosomes do not display inherent cytotoxic effects. The ability to tune the number of liposome layers and hence the drug loading in capsosomes as well as their noncytotoxicity provide new opportunities for the creation of therapeutic artificial cells and organelles.     

Shifting the MIMO Paradigm

Multi-user MIMO (MU-MIMO) networks reveal the unique opportunities arising from a joint optimization of antenna combining techniques with resource allocation protocols. Furthermore, it brings robustness with respect to multipath richness, allowing for compact antenna spacing at the BS and, crucially, yielding the diversity and multiplexing gains without the need for multiple antenna user terminals. To realize these gains, however, the BS should be informed with the user's channel coefficients, which may limit practical application to TDD or low-mobility settings. To circumvent this problem and reduce feedback load, combining MU-MIMO with opportunistic scheduling seems a promising direction. The success for this type of scheduler is strongly traffic and QoS-dependent, however.     

Opportunistic Space-Division Multiple Access With Beam Selection

In this paper, a novel transmission technique for the multiple-input multiple-output (MIMO) broadcast channel is proposed that allows simultaneous transmission to multiple users with limited feedback from each user. During a training phase, the base station modulates a training sequence on multiple sets of randomly chosen orthogonal beamforming vectors. Each user sends the index of the best beamforming vector and the corresponding signal-to-interference-plus-noise ratio for that set of orthogonal vectors back to the base station. The base station opportunistically determines the users and corresponding orthogonal vectors that maximize the sum capacity. Based on the capacity expressions, the optimal amount of training to maximize the sum capacity is derived as a function of the system parameters. The main advantage of the proposed system is that it provides throughput gains for the MIMO broadcast channel with a small feedback overhead, and provides these gains even with a small number of active users. Numerical simulations show that a 20% gain in sum capacity is achieved (for a small number of users) over conventional opportunistic space division multiple access, and a 100% gain (for a large number of users) over conventional opportunistic beamforming when the number of transmit antennas is four.     

Adaptive modulation and MIMO coding for broadband wireless datanetworks

Link adaptation techniques, where the modulation, coding rate, and/or other signal transmission parameters are dynamically adapted to the changing channel conditions, have emerged as powerful tools for increasing the data rate and spectral efficiency of wireless data-centric networks. While there has been significant progress on understanding the theoretical aspects of time adaptation in LA protocols, new challenges surface when dynamic transmission techniques are employed in broadband wireless networks with multiple signaling dimensions. Those additional dimensions are mainly frequency, especially in multicarrier systems, and space in multiple-antenna systems, particularly multiarray multiple-input multiple-output communication systems. We give an overview of the challenges and promises of link adaptation in future broadband wireless networks. We suggest guidelines to help in the design of robust, complexity/cost-effective algorithms for these future wireless networks     

Design of linear equalizers optimized for the structural similarity index.

We propose an algorithm for designing linear equalizers that maximize the structural similarity (SSIM) index between the reference and restored signals. The SSIM index has enjoyed considerable application in the evaluation of image processing algorithms. Algorithms, however, have not been designed yet to explicitly optimize for this measure. The design of such an algorithm is nontrivial due to the nonconvex nature of the distortion measure. In this paper, we reformulate the nonconvex problem as a quasi-convex optimization problem, which admits a tractable solution. We compute the optimal solution in near closed form, with complexity of the resulting algorithm comparable to complexity of the linear minimum mean squared error (MMSE) solution, independent of the number of filter taps. To demonstrate the usefulness of the proposed algorithm, it is applied to restore images that have been blurred and corrupted with additive white gaussian noise. As a special case, we consider blur-free image denoising. In each case, its performance is compared to a locally adaptive linear MSE-optimal filter. We show that the images denoised and restored using the SSIM-optimal filter have higher SSIM index, and superior perceptual quality than those restored using the MSE-optimal adaptive linear filter. Through these results, we demonstrate that a) designing image processing algorithms, and, in particular, denoising and restoration-type algorithms, can yield significant gains over existing (in particular, linear MMSE-based) algorithms by optimizing them for perceptual distortion measures, and b) these gains may be obtained without significant increase in the computational complexity of the algorithm.     

Mode switching and software download for software defined radio:the SDR Forum approach

The proliferation of air interfaces has created the need for a standard way of switching services supported by a wireless system and downloading new code to systems in the field. Both conventional and software defined systems need this capability. This article describes the work of the SDR Forum in developing such a switcher/downloader standard