Distributed Rate Allocation in Inter-Session Network Coding

In this work, we propose a distributed rate allocation algorithm that minimizes the average decoding delay for multimedia clients in inter-session network coding systems. We consider a scenario where the users are organized in a mesh network and each user requests the content of one of the available sources. We propose a novel distributed algorithm where network users determine the coding operations and the packet rates to be requested from the parent nodes, such that the decoding delay is minimized for all clients. A rate allocation problem is solved by every user, which seeks the rates that minimize the average decoding delay for its children and for itself. Since this optimization problem is a priori non-convex, we introduce the concept of equivalent packet flows, which permits to estimate the expected number of packets that every user needs to collect for decoding. We then decompose our original rate allocation problem into a set of convex subproblems, which are eventually combined to obtain an effective approximate solution to the delay minimization problem. The results demonstrate that the proposed scheme eliminates the bottlenecks and reduces the decoding delay experienced by users with limited bandwidth resources. We validate the performance of our distributed rate allocation algorithm in different video streaming scenarios using the NS-3 network simulator. We show that our system is able to take benefit of inter-session network coding for simultaneous delivery of video sessions in networks with path diversity.

Cardiopulmonary performance testing using a robotics-assisted tilt table: Feasibility assessment in able-bodied subjects

BACKGROUND: Robotics-assisted tilt table technology was introduced for early rehabilitation of neurological patients. It provides cyclical stepping movement and physiological loading of the legs. The aim of the present study was to assess the feasibility of this type of device for peak cardiopulmonary performance testing using able-bodied subjects. METHODS: A robotics-assisted tilt table was augmented with force sensors in the thigh cuffs and a work rate estimation algorithm. A custom visual feedback system was employed to guide the subjects' work rate and to provide real time feedback of actual work rate. Feasibility assessment focused on: (i) implementation (technical feasibility), and (ii) responsiveness (was there a measurable, high-level cardiopulmonary reaction?). For responsiveness testing, each subject carried out an incremental exercise test to the limit of functional capacity with a work rate increment of 5 W/min in female subjects and 8 W/min in males. RESULTS: 11 able-bodied subjects were included (9 male, 2 female; age 29.6 ± 7.1 years: mean ± SD). Resting oxygen uptake (O_{2}) was 4.6 ± 0.7 mL/min/kg and O_{2}peak was 32.4 ± 5.1 mL/min/kg; this mean O_{2}peak was 81.1% of the predicted peak value for cycle ergometry. Peak heart rate (HRpeak) was 177.5 ± 9.7 beats/min; all subjects reached at least 85% of their predicted HRpeak value. Respiratory exchange ratio (RER) at O_{2}peak was 1.02 ± 0.07. Peak work rate) was 61.3 ± 15.1 W. All subjects reported a Borg CR10 value for exertion and leg fatigue of 7 or more. CONCLUSIONS: The robotics-assisted tilt table is deemed feasible for peak cardiopulmonary performance testing: the approach was found to be technically implementable and substantial cardiopulmonary responses were observed. Further testing in neurologically-impaired subjects is warranted.

Feasibility of cardiopulmonary exercise testing and training using a robotics-assisted tilt table in dependent-ambulatory stroke patients

BACKGROUND: We evaluated the feasibility of an augmented robotics-assisted tilt table (RATT) for incremental cardiopulmonary exercise testing (CPET) and exercise training in dependent-ambulatory stroke patients. METHODS: Stroke patients (Functional Ambulation Category ≤ 3) underwent familiarization, an incremental exercise test (IET) and a constant load test (CLT) on separate days. A RATT equipped with force sensors in the thigh cuffs, a work rate estimation algorithm and real-time visual feedback to guide the exercise work rate was used. Feasibility assessment considered technical feasibility, patient tolerability, and cardiopulmonary responsiveness. RESULTS: Eight patients (4 female) aged 58.3 ± 9.2 years (mean ± SD) were recruited and all completed the study. For IETs, peak oxygen uptake (V'O2peak), peak heart rate (HRpeak) and peak work rate (WRpeak) were 11.9 ± 4.0 ml/kg/min (45 % of predicted V'O2max), 117 ± 32 beats/min (72 % of predicted HRmax) and 22.5 ± 13.0 W, respectively. Peak ratings of perceived exertion (RPE) were on the range "hard" to "very hard". All 8 patients reached their limit of functional capacity in terms of either their cardiopulmonary or neuromuscular performance. A ventilatory threshold (VT) was identified in 7 patients and a respiratory compensation point (RCP) in 6 patients: mean V'O2 at VT and RCP was 8.9 and 10.7 ml/kg/min, respectively, which represent 75 % (VT) and 85 % (RCP) of mean V'O2peak. Incremental CPET provided sufficient information to satisfy the responsiveness criteria and identification of key outcomes in all 8 patients. For CLTs, mean steady-state V'O2 was 6.9 ml/kg/min (49 % of V'O2 reserve), mean HR was 90 beats/min (56 % of HRmax), RPEs were > 2, and all patients maintained the active work rate for 10 min: these values meet recommended intensity levels for bouts of training. CONCLUSIONS: The augmented RATT is deemed feasible for incremental cardiopulmonary exercise testing and exercise training in dependent-ambulatory stroke patients: the approach was found to be technically implementable, acceptable to the patients, and it showed substantial cardiopulmonary responsiveness. This work has clinical implications for patients with severe disability who otherwise are not able to be tested.

Content-Aware Delivery of Scalable Video in Network Coding Enabled Named Data Networks

In this work, we propose a novel network coding enabled NDN architecture for the delivery of scalable video. Our scheme utilizes network coding in order to address the problem that arises in the original NDN protocol, where optimal use of the bandwidth and caching resources necessitates the coordination of the forwarding decisions. To optimize the performance of the proposed network coding based NDN protocol and render it appropriate for transmission of scalable video, we devise a novel rate allocation algorithm that decides on the optimal rates of Interest messages sent by clients and intermediate nodes. This algorithm guarantees that the achieved flow of Data objects will maximize the average quality of the video delivered to the client population. To support the handling of Interest messages and Data objects when intermediate nodes perform network coding, we modify the standard NDN protocol and introduce the use of Bloom filters, which store efficiently additional information about the Interest messages and Data objects. The proposed architecture is evaluated for transmission of scalable video over PlanetLab topologies. The evaluation shows that the proposed scheme performs very close to the optimal performance

Investigation of robotics-assisted tilt table technology for cardiopulmonary exercise testing in stroke patients

Due to the lack of exercise testing devices that can be employed in stroke patients with severe disability, the aim of this PhD research was to investigate the clinical feasibility of using a robotics-assisted tilt table (RATT) as a method for cardiopulmonary exercise testing (CPET) and exercise training in stroke patients. For this purpose, the RATT was augmented with force sensors, a visual feedback system and a work rate calculation algorithm. As the RATT had not been used previously for CPET, the first phase of this project focused on a feasibility study in 11 healthy able-bodied subjects. The results demonstrated substantial cardiopulmonary responses, no complications were found, and the method was deemed feasible. The second phase was to analyse validity and test-retest reliability of the primary CPET parameters obtained from the RATT in 18 healthy able-bodied subjects and to compare the outcomes to those obtained from standard exercise testing devices (a cycle ergometer and a treadmill). The results demonstrated that peak oxygen uptake (V'O2peak) and oxygen uptake at the submaximal exercise thresholds on the RATT were ̴20% lower than for the cycle ergometer and ̴30% lower than on the treadmill. A very high correlation was found between the RATT vs the cycle ergometer V'O2peak and the RATT vs the treadmill V'O2peak. Test-retest reliability of CPET parameters obtained from the RATT were similarly high to those for standard exercise testing devices. These findings suggested that the RATT is a valid and reliable device for CPET and that it has potential to be used in severely impaired patients. Thus, the third phase was to investigate using the RATT for CPET and exercise training in 8 severely disabled stroke patients. The method was technically implementable, well tolerated by the patients, and substantial cardiopulmonary responses were observed. Additionally, all patients could exercise at the recommended training intensity for 10 min bouts. Finally, an investigation of test-retest reliability and four-week changes in cardiopulmonary fitness was carried out in 17 stroke patients with various degrees of disability. Good to excellent test-retest reliability and repeatability were found for the main CPET variables. There was no significant difference in most CPET parameters over four weeks. In conclusion, based on the demonstrated validity, reliability and repeatability, the RATT was found to be a feasible and appropriate alternative exercise testing and training device for patients who have limitations for use of standard devices.

[Acute lower gastrointestinal bleeding--an evidence-based algorithm for diagnosis and treatment]

Novel means to locate and treat lower gastrointestinal bleeding (lGB) allow to reduce the rate of required surgical interventions and help to limit the extend of resection. The risk stratification of patients with lGB is the primary step of our recommended treatment algorithm. Accordingly, risk stratifying instruments, which are only partly validated up to now, are gaining significance in lGB. Whereas, gastro-duodenoscopy and colonoscopy prior to angiography or scintigraphy are established diagnostic tools, capsule enteroscopy offers a novel approach to hemodynamic stable patients with lGB that are difficult to localize. With its every increasing sensitivity, Angio-Computer Tomography is likely to replace scintigraphy and diagnostic angiography in the very near future. In addition, recent advances in superselective microembolisation have been shown to have the potential rendering surgical interventions in a majority of patients with acute lGB unnecessary. The extend of required surgical resection is largely dependent on the success to localize the bleeding source of prior diagnostics. Only if the source is identified, a limited segmental resection should be performed. Should surgery be required, we suggest to maintain the effort to localize the bleeding, either by prior laparoscopy and/or by intraoperative entero-colonoscopy. Eventually, if the source of bleeding remains unclear total colectomy with ileorectal anastomosis represents the procedure of choice in patients with acute lGB.

Safety and Feasibility of a Diagnostic Algorithm Combining Clinical Probability, d-Dimer Testing, and Ultrasonography for Suspected Upper Extremity Deep Venous Thrombosis: A Prospective Management Study.

BACKGROUND Although well-established for suspected lower limb deep venous thrombosis, an algorithm combining a clinical decision score, d-dimer testing, and ultrasonography has not been evaluated for suspected upper extremity deep venous thrombosis (UEDVT). OBJECTIVE To assess the safety and feasibility of a new diagnostic algorithm in patients with clinically suspected UEDVT. DESIGN Diagnostic management study. (ClinicalTrials.gov: NCT01324037) SETTING: 16 hospitals in Europe and the United States. PATIENTS 406 inpatients and outpatients with suspected UEDVT. MEASUREMENTS The algorithm consisted of the sequential application of a clinical decision score, d-dimer testing, and ultrasonography. Patients were first categorized as likely or unlikely to have UEDVT; in those with an unlikely score and normal d-dimer levels, UEDVT was excluded. All other patients had (repeated) compression ultrasonography. The primary outcome was the 3-month incidence of symptomatic UEDVT and pulmonary embolism in patients with a normal diagnostic work-up. RESULTS The algorithm was feasible and completed in 390 of the 406 patients (96%). In 87 patients (21%), an unlikely score combined with normal d-dimer levels excluded UEDVT. Superficial venous thrombosis and UEDVT were diagnosed in 54 (13%) and 103 (25%) patients, respectively. All 249 patients with a normal diagnostic work-up, including those with protocol violations (n = 16), were followed for 3 months. One patient developed UEDVT during follow-up, for an overall failure rate of 0.4% (95% CI, 0.0% to 2.2%). LIMITATIONS This study was not powered to show the safety of the substrategies. d-Dimer testing was done locally. CONCLUSION The combination of a clinical decision score, d-dimer testing, and ultrasonography can safely and effectively exclude UEDVT. If confirmed by other studies, this algorithm has potential as a standard approach to suspected UEDVT. PRIMARY FUNDING SOURCE None.

Personalized Tuning of a Reinforcement Learning Control Algorithm for Glucose Regulation

Artificial pancreas is in the forefront of research towards the automatic insulin infusion for patients with type 1 diabetes. Due to the high inter- and intra-variability of the diabetic population, the need for personalized approaches has been raised. This study presents an adaptive, patient-specific control strategy for glucose regulation based on reinforcement learning and more specifically on the Actor-Critic (AC) learning approach. The control algorithm provides daily updates of the basal rate and insulin-to-carbohydrate (IC) ratio in order to optimize glucose regulation. A method for the automatic and personalized initialization of the control algorithm is designed based on the estimation of the transfer entropy (TE) between insulin and glucose signals. The algorithm has been evaluated in silico in adults, adolescents and children for 10 days. Three scenarios of initialization to i) zero values, ii) random values and iii) TE-based values have been comparatively assessed. The results have shown that when the TE-based initialization is used, the algorithm achieves faster learning with 98%, 90% and 73% in the A+B zones of the Control Variability Grid Analysis for adults, adolescents and children respectively after five days compared to 95%, 78%, 41% for random initialization and 93%, 88%, 41% for zero initial values. Furthermore, in the case of children, the daily Low Blood Glucose Index reduces much faster when the TE-based tuning is applied. The results imply that automatic and personalized tuning based on TE reduces the learning period and improves the overall performance of the AC algorithm.

Development and validation of a novel pedometer algorithm to quantify extended characteristics of the locomotor behavior of dairy cows

Behavior is one of the most important indicators for assessing cattle health and well-being. The objective of this study was to develop and validate a novel algorithm to monitor locomotor behavior of loose-housed dairy cows based on the output of the RumiWatch pedometer (ITIN+HOCH GmbH, Fütterungstechnik, Liestal, Switzerland). Data of locomotion were acquired by simultaneous pedometer measurements at a sampling rate of 10 Hz and video recordings for manual observation later. The study consisted of 3 independent experiments. Experiment 1 was carried out to develop and validate the algorithm for lying behavior, experiment 2 for walking and standing behavior, and experiment 3 for stride duration and stride length. The final version was validated, using the raw data, collected from cows not included in the development of the algorithm. Spearman correlation coefficients were calculated between accelerometer variables and respective data derived from the video recordings (gold standard). Dichotomous data were expressed as the proportion of correctly detected events, and the overall difference for continuous data was expressed as the relative measurement error. The proportions for correctly detected events or bouts were 1 for stand ups, lie downs, standing bouts, and lying bouts and 0.99 for walking bouts. The relative measurement error and Spearman correlation coefficient for lying time were 0.09% and 1; for standing time, 4.7% and 0.96; for walking time, 17.12% and 0.96; for number of strides, 6.23% and 0.98; for stride duration, 6.65% and 0.75; and for stride length, 11.92% and 0.81, respectively. The strong to very high correlations of the variables between visual observation and converted pedometer data indicate that the novel RumiWatch algorithm may markedly improve automated livestock management systems for efficient health monitoring of dairy cows.

CHEOPS Performance for Exomoons: The Detectability of Exomoons by Using Optimal Decision Algorithm

Many attempts have already been made to detect exomoons around transiting exoplanets, but the first confirmed discovery is still pending. The experiences that have been gathered so far allow us to better optimize future space telescopes for this challenge already during the development phase. In this paper we focus on the forthcoming CHaraterising ExOPlanet Satellite (CHEOPS), describing an optimized decision algorithm with step-by-step evaluation, and calculating the number of required transits for an exomoon detection for various planet moon configurations that can be observable by CHEOPS. We explore the most efficient way for such an observation to minimize the cost in observing time. Our study is based on PTV observations (photocentric transit timing variation) in simulated CHEOPS data, but the recipe does not depend on the actual detection method, and it can be substituted with, e.g., the photodynamical method for later applications. Using the current state-of-the-art level simulation of CHEOPS data we analyzed transit observation sets for different star planet moon configurations and performed a bootstrap analysis to determine their detection statistics. We have found that the detection limit is around an Earth-sized moon. In the case of favorable spatial configurations, systems with at least a large moon and a Neptune-sized planet, an 80% detection chance requires at least 5-6 transit observations on average. There is also a nonzero chance in the case of smaller moons, but the detection statistics deteriorate rapidly, while the necessary transit measurements increase quickly. After the CoRoT and Kepler spacecrafts, CHEOPS will be the next dedicated space telescope that will observe exoplanetary transits and characterize systems with known Doppler-planets. Although it has a smaller aperture than Kepler (the ratio of the mirror diameters is about 1/3) and is mounted with a CCD that is similar to Kepler's, it will observe brighter stars and operate with larger sampling rate; therefore, the detection limit for an exomoon can be the same as or better, which will make CHEOPS a competitive instruments in the quest for exomoons.