AWARE: Platform for Autonomous self-deploying and operation of Wireless sensor-actuator networks cooperating with unmanned AeRial vehiclEs

This paper presents the AWARE platform that seeks to enable the cooperation of autonomous aerial vehicles with ground wireless sensor-actuator networks comprising both static and mobile nodes carried by vehicles or people. Particularly, the paper presents the middleware, the wireless sensor network, the node deployment by means of an autonomous helicopter, and the surveillance and tracking functionalities of the platform. Furthermore, the paper presents the first general experiments of the AWARE project that took place in March 2007 with the assistance of the Seville fire brigades

Quantification of aircraft trajectory prediction uncertainty using polynomial chaos expansions

A novel approach to quantify the uncertainty associated with any aircraft trajectory prediction based on the application of the Polynomial Chaos (PC) theory is presented. The proposed method relies on univariate polynomial descriptions of the uncertainty sources affecting the trajectory prediction process. Those descriptions are used to build the multivariate polynomial expansions that represent the variability of the aircraft state variables along the predicted trajectory. A case study compares the results obtained by a classical Monte Carlo approach with those generated by applying the so-called arbitrary Polynomial Chaos Expansions (aPCE). The results provided herein lead to conclude that this new methodology can be used to accurately quantify trajectory prediction uncertainty with a very low computational effort, enabling the capability of computing the uncertainty of the individual trajectories of a traffic sample of thousands flights within very short time intervals

Comparison between a new thyroglobulin assay with the well-established Beckman Access immunoassay: A preliminary report

Objectives: Measurement of serum thyroglobulin (Tg) plays a key role in the post-thyroidectomy management of differentiated thyroid carcinoma (DTC). In this context, the performance of new-generation thyroglobulin assay has clinical implications in the follow-up of DTC patients. Aim of this study was to compare the new highly sensitive Liaison Tg II (Tg-L) with the well-established Tg Access assay (Tg-A). Materials and methods: A total of 91 residual serum samples (23 positive and 68 negatives for Tg auto-antibodies) were tested by the Beckman Access and Diasorin Liaison assays. Study samples were from 21 patients with pathologically proven DTC and control samples from 70 (16 patients with benign thyroid disease and 54 apparently healthy subjects). Results: Our results showed that Tg-L was highly correlated with Tg-A for both values ranging between 0.2 and 50 ng/mL (Pearson's r = 0.933 [95%CI 0.894-0.958], P <.001) and higher than 50 ng/mL (Pearson's r = 0.849 [95%CI 0.609-0.946], P <.001). For Tg values lower than 0.2 ng/mL, the overall concordance rate was 92%. Moreover, we tested 7 fine-needle aspiration washout fluids (FNA), showing an overall concordance rate in discriminating negative and positive of 100%. Finally, we found no interference by Tg auto-antibodies (TgAbs) for both Tg-L and Tg-A. Conversely, rheumatoid factor (RF) interferes with Tg-A, but not with Tg-L in one patient with no relapsing thyroid carcinoma. Conclusions: Liaison Tg II demonstrated a good correlation with Access Tg assay both for sera and FNAs. Further studies on larger population are needed to evaluate Tg-L clinical impact on DTC patient's follow-up

Modelling and Analysis of Vibrations in a UAV Helicopter with a Vision System

The analysis of the nature and damping of unwanted vibrations on Unmanned Aerial Vehicle (UAV) helicopters are important tasks when images from on‐board vision systems are to be obtained. In this article, the authors model a UAV system, generate a range of vibrations originating in the main rotor and design a control methodology in order to damp these vibrations. The UAV is modelled using VehicleSim, the vibrations that appear on the fuselage are analysed to study their effects on the on‐board vision system by using Simmechanics software. Following this, the authors present a control method based on an Adaptive Neuro‐Fuzzy Inference System (ANFIS) to achieve satisfactory damping results over the vision system on board

A Simple Transient Poiseuille-Based Approach to Mimic the Womersley Function and to Model Pulsatile Blood Flow

As it is known, the Womersley function models velocity as a function of radius and time. It has been widely used to simulate the pulsatile blood flow through circular ducts. In this context, the present study is focused on the introduction of a simple function as an approximation of theWomersley function in order to evaluate its accuracy. This approximation consists of a simple quadratic function, suitable to be implemented in most commercial and non-commercial computational fluid dynamics codes, without the aid of external mathematical libraries. The Womersley function and the new function have been implemented here as boundary conditions in OpenFOAM ESI software (v.1906). The discrepancy between the obtained results proved to be within 0.7%, which fully validates the calculation approach implemented here. This approach is valid when a simplified analysis of the system is pointed out, in which flow reversals are not contemplated

Hepatitis C virus infection and arthritis. A clinico-serological investigation of arthritis in patients with or without cryoglobulinemic syndrome.

OBJECTIVE: To compare the clinico-serological features of arthritis from two HCV+ patient groups characterized by mixed cryoglobulinemia (MC) or chronic hepatitis (CH).METHODS: We retrospectively studied 157 MC patients (119 females, mean age 64.8 yrs, range 36-88) and 155 CH patients (103 females, mean age 58.8 yrs, range 30-81). Patients with HBV and/or HIV co-infections and a follow-up shorter than 1 year were excluded. MC was classified according to standard criteria, while CH classification was based on Desmet's criteria.RESULTS: No differences in epidemiology were demonstrated between the two series of patients. Although significantly prevalent in MC patients, extra-hepatic manifestations including nephropathy, neuropathy, pneumopathy, mixed cryoglobulins, RF positivity and hypocomplementemia were detected in both patient groups. Arthritis was present in 23 CH (15%) and 12 MC (8%) patients. A symmetrical polyarthritis was observed in 87% of 23 CH patients, while cryoglobulinemic arthritis was invariably asymmetrical and pauciarticular. Unlike MC patients, who had a constantly non-erosive arthritis, in 7/23 CH patients arthritis was erosive. Steroids and/or hydroxycloroquine or D-penicillamine were safe and useful in controlling the arthritis over the short-medium time, although clinical response was more evident in MC patients. Instead, in 5/23 CH and 3/12 MC patients, interferon-alpha treatment was able to trigger or exacerbate the arthritis despite a good control of liver function.CONCLUSIONS: HCV infection seems to be, possibly in genetically predisposed patients, responsible for arthritis at times similar to rheumatoid arthritis. In these patients a careful assessment of the interferon-alpha treatment is mandatory owing to the potential "arthritogenic effect" due to its immunoregulatory properties

Optimized Identification of High-Grade Prostate Cancer by Combining Different PSA Molecular Forms and PSA Density in a Deep Learning Model

After skin cancer, prostate cancer (PC) is the most common cancer among men. The gold standard for PC diagnosis is based on the PSA (prostate-specific antigen) test. Based on this preliminary screening, the physician decides whether to proceed with further tests, typically prostate biopsy, to confirm cancer and evaluate its aggressiveness. Nevertheless, the specificity of the PSA test is suboptimal and, as a result, about 75% of men who undergo a prostate biopsy do not have cancer even if they have elevated PSA levels. Overdiagnosis leads to unnecessary overtreatment of prostate cancer with undesirable side effects, such as incontinence, erectile dysfunction, infections, and pain. Here, we used artificial neuronal networks to develop models that can diagnose PC efficiently. The model receives as an input a panel of 4 clinical variables (total PSA, free PSA, p2PSA, and PSA density) plus age. The output of the model is an estimate of the Gleason score of the patient. After training on a dataset of 190 samples and optimization of the variables, the model achieved values of sensitivity as high as 86% and 89% specificity. The efficiency of the method can be improved even further by training the model on larger datasets

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