Informative State-Based Video Communication

We study state-based video communication where a client simultaneously informs the server about the presence status of various packets in its buffer. In sender-driven transmission, the client periodically sends to the server a single acknowledgement packet that provides information about all packets that have arrived at the client by the time the acknowledgment is sent. In receiver-driven streaming, the client periodically sends to the server a single request packet that comprises a transmission schedule for sending missing data to the client over a horizon of time. We develop a comprehensive optimization framework that enables computing packet transmission decisions that maximize the end-to-end video quality for the given bandwidth resources, in both prospective scenarios. The core step of the optimization comprises computing the probability that a single packet will be communicated in error as a function of the expected transmission redundancy (or cost) used to communicate the packet. Through comprehensive simulation experiments, we carefully examine the performance advances that our framework enables relative to state-of-the-art scheduling systems that employ regular acknowledgement or request packets. Consistent gains in video quality of up to 2B are demonstrated across a variety of content types. We show that there is a direct analogy between the error-cost efficiency of streaming a single packet and the overall rate-distortion performance of streaming the whole content. In the case of sender-driven transmission, we develop an effective modeling approach that accurately characterizes the end-to-end performance as a function of the packet loss rate on the backward channel and the source encoding characteristics.

Invited Abstract: Issues with State-based Energy Consumption Modelling

Energy consumption modelling by state based approaches often assume constant energy consumption values in each state. However, it happens in certain situations that during state transitions or even during a state the energy consumption is not constant and does fluctuate. This paper discusses those issues by presenting some examples from wireless sensor and wireless local area networks for such cases and possible solutions.

Noxious stimulation response index: a novel anesthetic state index based on hypnotic-opioid interaction

The noxious stimulation response index (NSRI) is a novel anesthetic depth index ranging between 100 and 0, computed from hypnotic and opioid effect-site concentrations using a hierarchical interaction model. The authors validated the NSRI on previously published data.

Morphological and biochemical T2 evaluation of cartilage repair tissue based on a hybrid double echo at steady state (DESS-T2d) approach

To use a new approach which provides, based on the widely used three-dimensional double-echo steady-state (DESS) sequence, in addition to the morphological information, the generation of biochemical T2 maps in one hybrid sequence.

Time course based artifact identification for independent components of resting-state FMRI

In functional magnetic resonance imaging (fMRI) coherent oscillations of the blood oxygen level-dependent (BOLD) signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting-state networks (RSN). Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA) and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting-state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82, and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting-state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting-state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.

Implementation of Evidence-Based Practices for Treatment of Alcohol and Drug Disorders: The Role of the State Authority

The current climate of increasing performance expectations and diminishing resources, along with innovations in evidence-based practices (EBPs), creates new dilemmas for substance abuse treatment providers, policymakers, funders, and the service delivery system. This paper describes findings from baseline interviews with representatives from 49 state substance abuse authorities (SSAs). Interviews assessed efforts aimed at facilitating EBP adoption in each state and the District of Columbia. Results suggested that SSAs are concentrating more effort on EBP implementation strategies such as education, training, and infrastructure development, and less effort on financial mechanisms, regulations, and accreditation. The majority of SSAs use EBPs as a criterion in their contracts with providers, and just over half reported that EBP use is tied to state funding. To date, Oregon remains the only state with legislation that mandates treatment expenditures for EBPs; North Carolina follows suit with legislation that requires EBP promotion within current resources.

Rapid estimation of cartilage T2 based on double echo at steady state (DESS) with 3 Tesla

The double-echo-steady-state (DESS) sequence generates two signal echoes that are characterized by a different contrast behavior. Based on these two contrasts, the underlying T2 can be calculated. For a flip-angle of 90 degrees , the calculated T2 becomes independent of T1, but with very low signal-to-noise ratio. In the present study, the estimation of cartilage T2, based on DESS with a reduced flip-angle, was investigated, with the goal of optimizing SNR, and simultaneously minimizing the error in T2. This approach was validated in phantoms and on volunteers. T2 estimations based on DESS at different flip-angles were compared with standard multiecho, spin-echo T2. Furthermore, DESS-T2 estimations were used in a volunteer and in an initial study on patients after cartilage repair of the knee. A flip-angle of 33 degrees was the best compromise for the combination of DESS-T2 mapping and morphological imaging. For this flip angle, the Pearson correlation was 0.993 in the phantom study (approximately 20% relative difference between SE-T2 and DESS-T2); and varied between 0.429 and 0.514 in the volunteer study. Measurements in patients showed comparable results for both techniques with regard to zonal assessment. This DESS-T2 approach represents an opportunity to combine morphological and quantitative cartilage MRI in a rapid one-step examination.