Geometric distortions in FMCW SAR images due to inaccurate knowledge of electronic radar parameters: analysis and correction by means of corner reflectors

Abstract In the last years the Frequency Modulated Continuous Wave (FMCW) technology has been playing an ever greater role in the realization of compact, light and cheap Synthetic Aperture Radar (SAR) systems to be mounted onboard small, low altitude platforms such as airplanes, helicopters and drones. To correctly focus FMCW SAR images, it is necessary to accurately know some system parameters, including the frequency sweep rate of the signal transmitted by the radar. It may happen, however, that this frequency sweep rate is not very accurately measured by the radar provider, and thus an incorrect value of this parameter is used during the SAR data focusing procedure. This may produce serious geometric distortion effects in the focused FMCW SAR images. To circumvent these problems, in this work we present a procedure that estimates the frequency sweep rate actually employed by the FMCW radar, thus providing a key information that can be then profitably used to achieve the correct focusing of the SAR data acquired by the radar system at hand. More specifically, we propose an algorithm that exploits on one side the focused SAR images corrupted by the geometric distortion effects induced by the inaccurate knowledge of this radar parameter, and on the other side the very precise in-situ measurements of the positions of a limited number of Corner Reflectors (CRs) properly deployed over the observed scene. The effectiveness of the proposed algorithm has been tested on real data acquired by an airborne X-band FMCW SAR system

Le dimensioni psicologiche nel monitoraggio del paziente diabetico in terapia con microinfusore: stato attuale e prospettive.

SUMMARY Psychological aspects in the evaluation of the diabetic patient treated with infusion pump-therapy: current state and perspectives This article aim is to offer a close examination of up-to-date theoretical contributions referring to the following subject: psychological aspects in CSII therapy. This close examination was made considering two different researches: the first by regarding the evaluation of the post implant period, and the second concerning the study of drop out causes. It was possible to find out problems and psychosocial changes caused by the implant, but also to specify critical points, useful to build necessary protocols, to support diabetological valuations and to suggest psychoeducational interventions

L’adattamento psicologico alla diagnosi di diabete di tipo 2.

SUMMARY Psychological adjustment to type 2 diabetes Objective. Based upon the literature of the past ten years, this study analyzes the initial phase of psychological adjustment after a diagnosis of type 2 diabetes, with the goal of providing useful guidelines to diabetologists in supporting their patients from the very first moment of clinical work. The study identifies five functional areas that characterize this adjustment: anxiety, depression, locus of control, self-esteem and self-efficacy. Method. Using a battery of psychometric tests, we assessed the psychological condition in a sample of 42 subjects with type 2 diabetes, comparing with a control sample of 420 subjects, without diabetes. Results. The initial psychological adjustment after six months from diagnosis, seems characterized by decreased tone of mood and self-efficacy, without anxious symptoms. The subjects seem to develop a fatalistic attitude or a strong external entrustment, showing inclination to underestimate the disease’s reality and to seek external dependence that could affect the path towards an adequate and effective self-management. Conclusions. The authors discuss the findings emerged and possible directions for a smoother working relationship between diabetologists and their patients

Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification

Quality indicators for patients with traumatic brain injury in European intensive care units

Background: The aim of this study is to validate a previously published consensus-based quality indicator set for the management of patients with traumatic brain injury (TBI) at intensive care units (ICUs) in Europe and to study its potential for quality measur

Changing care pathways and between-center practice variations in intensive care for traumatic brain injury across Europe

Purpose: To describe ICU stay, selected management aspects, and outcome of Intensive Care Unit (ICU) patients with traumatic brain injury (TBI) in Europe, and to quantify variation across centers. Methods: This is a prospective observational multicenter study conducted across 18 countries in Europe and Israel. Admission characteristics, clinical data, and outcome were described at patient- and center levels. Between-center variation in the total ICU population was quantified with the median odds ratio (MOR), with correction for case-mix and random variation between centers. Results: A total of 2138 patients were admitted to the ICU, with median age of 49 years; 36% of which were mild TBI (Glasgow Coma Scale; GCS 13–15). Within, 72 h 636 (30%) were discharged and 128 (6%) died. Early deaths and long-stay patients (> 72 h) had more severe injuries based on the GCS and neuroimaging characteristics, compared with short-stay patients. Long-stay patients received more monitoring and were treated at higher intensity, and experienced worse 6-month outcome compared to short-stay patients. Between-center variations were prominent in the proportion of short-stay patients (MOR = 2.3, p < 0.001), use of intracranial pressure (ICP) monitoring (MOR = 2.5, p < 0.001) and aggressive treatme

Adherence issues related to sublingual immunotherapy as perceived by allergists

Objectives: Sublingual immunotherapy (SLIT) is a viable alternative to subcutaneous immunotherapy to treat allergic rhinitis and asthma, and is widely used in clinical practice in many European countries. The clinical efficacy of SLIT has been established in a number of clinical trials and meta-analyses. However, because SLIT is self-administered by patients without medical supervision, the degree of patient adherence with treatment is still a concern. The objective of this study was to evaluate the perception by allergists of issues related to SLIT adherence. Methods: We performed a questionnaire-based survey of 296 Italian allergists, based on the adherence issues known from previous studies. The perception of importance of each item was assessed by a VAS scale ranging from 0 to 10. Results: Patient perception of clinical efficacy was considered the most important factor (ranked 1 by 54% of allergists), followed by the possibility of reimbursement (ranked 1 by 34%), and by the absence of side effects (ranked 1 by 21%). Patient education, regular follow-up, and ease of use of SLIT were ranked first by less than 20% of allergists. Conclusion: These findings indicate that clinical efficacy, cost, and side effects are perceived as the major issues influencing patient adherence to SLIT, and that further improvement of adherence is likely to be achieved by improving the patient information provided by prescribers. © 2010 Scurati et al, publisher and licensee Dove Medical Press Ltd

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations