OMA analysis of a launcher under operational conditions with time-varying properties

The objective of the paper is the investigation of the capability of Operational Modal Analysis approaches to deal with time-varying system in the low-frequency domain. Specifically, the problem of the identification of the dynamic properties of a launch-vehicle, working under actual operative conditions, is studied. Two OMA methods are considered: the Frequency Domain Decomposition and the Hilbert Transform Method. It is demonstrated that both OMA approaches allow the time-tracking of modal parameters, namely, natural frequencies, damping ratios and mode shapes, from the response accelerations only recorded during actual flight tests of a launcher characterized by a large mass variation due to fuel burning typical of the first phase of the flight

Learning Interpretable Microscopic Features of Tumor by Multi-task Adversarial CNNs Improves Generalization

Adopting Convolutional Neural Networks (CNNs) in the daily routine of primary diagnosis requires not only near-perfect precision, but also a sufficient degree of generalization to data acquisition shifts and transparency. Existing CNN models act as black boxes, not ensuring to the physicians that important diagnostic features are used by the model. Building on top of successfully existing techniques such as multi-task learning, domain adversarial training and concept-based interpretability, this paper addresses the challenge of introducing diagnostic factors in the training objectives. Here we show that our architecture, by learning end-to-end an uncertainty-based weighting combination of multi-task and adversarial losses, is encouraged to focus on pathology features such as density and pleomorphism of nuclei, e.g. variations in size and appearance, while discarding misleading features such as staining differences. Our results on breast lymph node tissue show significantly improved generalization in the detection of tumorous tissue, with best average AUC 0.89 (0.01) against the baseline AUC 0.86 (0.005). By applying the interpretability technique of linearly probing intermediate representations, we also demonstrate that interpretable pathology features such as nuclei density are learned by the proposed CNN architecture, confirming the increased transparency of this model. This result is a starting point towards building interpretable multi-task architectures that are robust to data heterogeneity. Our code is available at https://bit.ly/356yQ2u.Comment: 21 pages, 4 figure

CCN family member 1 (CCN1) is an early marker of infarct size and left ventricular dysfunction in STEMI patients.

BACKGROUND AND AIMS CCN family member 1 (CCN1) has recently been proposed as a novel biomarker of myocardial injury, improving prediction of 30-day and one-year mortality following acute coronary syndromes. Among ST-elevation myocardial infarction (STEMI) patients, we evaluated the utility of CCN1 measured immediately before primary percutaneous coronary intervention (PPCI) as a predictor of two earlier endpoints: final myocardial infarct size and post-infarction left ventricular ejection fraction (LVEF). Furthermore, we evaluated the impact of CCN1 on the discriminatory power of the CADILLAC score. METHODS STEMI patients were obtained from the SPUM-ACS cohort. Serum CCN1 was measured prior to PPCI. Linear regression assessed the association between CCN1, peak creatinine kinase (CK), and post-infarction LVEF. Cox models assessed an association between CCN1 and 30-day all-cause mortality. RESULTS CCN1 was measured in 989 patients with a median value of 706.2 ng/l (IQR 434.3-1319.6). A significant correlation between CCN1, myocardial infarct size (peak CK) and LVEF was observed in univariate and multivariate analysis (both p < 0.001). Even among patients with normal classical cardiac biomarker levels at the time of PPCI, CCN1 correlated significantly with final infarct size. CCN1 significantly improved prediction of 30-day all-cause mortality by the CADILLAC score (C-index 0.864, likelihood-ratio chi-square test statistic 6.331, p = 0.012; IDI 0.026, p= 0.050). CONCLUSIONS Compared with classical cardiac biomarkers, CCN1 is potentially the earliest predictor of final myocardial infarct size and post-infarction LVEF. CCN1 improved the discriminatory capacity of the CADILLAC score suggesting a potential role in the very-early risk stratification of STEMI patients

Head-to-head comparison of two angiography-derived fractional flow reserve techniques in patients with high-risk acute coronary syndrome: A multicenter prospective study

BACKGROUND FFRangio and QFR are angiography-based technologies that have been validated in patients with stable coronary artery disease. No head-to-head comparison to invasive fractional flow reserve (FFR) has been reported to date in patients with acute coronary syndromes (ACS). METHODS This study is a subset of a larger prospective multicenter, single-arm study that involved patients diagnosed with high-risk ACS in whom 30-70% stenosis was evaluated by FFR. FFRangio and QFR - both calculated offline by 2 different and blinded operators - were calculated and compared to FFR. The two co-primary endpoints were the comparison of the Pearson correlation coefficient between FFRangio and QFR with FFR and the comparison of their inter-observer variability. RESULTS Among 134 high-risk ACS screened patients, 59 patients with 84 vessels underwent FFR measurements and were included in this study. The mean FFR value was 0.82 ± 0.40 with 32 (38%) being ≤0.80. The mean FFRangio was 0.82 ± 0.20 and the mean QFR was 0.82 ± 0.30, with 27 (32%) and 25 (29%) being ≤0.80, respectively. The Pearson correlation coefficient was significantly better for FFRangio compared to QFR, with R values of 0.76 and 0.61, respectively (p = 0.01). The inter-observer agreement was also significantly better for FFRangio compared to QFR (0.86 vs 0.79, p < 0.05). FFRangio had 91% sensitivity, 100% specificity, and 96.8% accuracy, while QFR exhibited 86.4% sensitivity, 98.4% specificity, and 93.7% accuracy. CONCLUSION In patients with high-risk ACS, FFRangio and QFR demonstrated excellent diagnostic performance. FFRangio seems to have better correlation to invasive FFR compared to QFR but further larger validation studies are required

CCN family member 1 (CCN1) is an early marker of infarct size and left ventricular dysfunction in STEMI patients

BACKGROUND AND AIMS CCN family member 1 (CCN1) has recently been proposed as a novel biomarker of myocardial injury, improving prediction of 30-day and one-year mortality following acute coronary syndromes. Among ST-elevation myocardial infarction (STEMI) patients, we evaluated the utility of CCN1 measured immediately before primary percutaneous coronary intervention (PPCI) as a predictor of two earlier endpoints: final myocardial infarct size and post-infarction left ventricular ejection fraction (LVEF). Furthermore, we evaluated the impact of CCN1 on the discriminatory power of the CADILLAC score. METHODS STEMI patients were obtained from the SPUM-ACS cohort. Serum CCN1 was measured prior to PPCI. Linear regression assessed the association between CCN1, peak creatinine kinase (CK), and post-infarction LVEF. Cox models assessed an association between CCN1 and 30-day all-cause mortality. RESULTS CCN1 was measured in 989 patients with a median value of 706.2 ng/l (IQR 434.3-1319.6). A significant correlation between CCN1, myocardial infarct size (peak CK) and LVEF was observed in univariate and multivariate analysis (both p < 0.001). Even among patients with normal classical cardiac biomarker levels at the time of PPCI, CCN1 correlated significantly with final infarct size. CCN1 significantly improved prediction of 30-day all-cause mortality by the CADILLAC score (C-index 0.864, likelihood-ratio chi-square test statistic 6.331, p = 0.012; IDI 0.026, p= 0.050). CONCLUSIONS Compared with classical cardiac biomarkers, CCN1 is potentially the earliest predictor of final myocardial infarct size and post-infarction LVEF. CCN1 improved the discriminatory capacity of the CADILLAC score suggesting a potential role in the very-early risk stratification of STEMI patients

Enhancing LTE with Cloud-RAN and Load-Controlled Parasitic Antenna Arrays

Cloud radio access network systems, consisting of remote radio heads densely distributed in a coverage area and connected by optical fibers to a cloud infrastructure with large computational capabilities, have the potential to meet the ambitious objectives of next generation mobile networks. Actual implementations of C-RANs tackle fundamental technical and economic challenges. In this article, we present an end-to-end solution for practically implementable C-RANs by providing innovative solutions to key issues such as the design of cost-effective hardware and power-effective signals for RRHs, efficient design and distribution of data and control traffic for coordinated communications, and conception of a flexible and elastic architecture supporting dynamic allocation of both the densely distributed RRHs and the centralized processing resources in the cloud to create virtual base stations. More specifically, we propose a novel antenna array architecture called load-controlled parasitic antenna array (LCPAA) where multiple antennas are fed by a single RF chain. Energy- and spectral-efficient modulation as well as signaling schemes that are easy to implement are also provided. Additionally, the design presented for the fronthaul enables flexibility and elasticity in resource allocation to support BS virtualization. A layered design of information control for the proposed end-to-end solution is presented. The feasibility and effectiveness of such an LCPAA-enabled C-RAN system setup has been validated through an over-the-air demonstration

Utilização de suplementos nutricionais por fisiculturistas em fase de competição - estudo transversal

Among athletes, the consumption of nutritional supplements (NS) is commonly seen as a resource to improve adaptations and performance in sport. In bodybuilding, this practice can be associated with improved aesthetics, especially during competition periods. The objective of this work was to analyze the use of SN by bodybuilders and associate it with the other variables during the competition phase. This is a cross-sectional study carried out in 2016 with 25 male bodybuilding athletes in the competition phase. These were questioned about the consumption of NS, whether they were under nutritional monitoring and, also, skinfolds were measured to estimate body fat. Fisher's exact test was used to associate the variables. The athletes' mean age was 28.56±9.71 years, 88% reported using whey protein; 76% Branched Chain Amino Acids (BCAA); 40% creatine and glutamine. Nutritional monitoring was associated with the consumption of vitamin C (88.9%) and glutamine (44.4%). While the mens sport model category was associated with the use of creatine (77.8%). Thus, it is concluded that many athletes used NS and that some were associated with nutritional monitoring and competition category.Entre atletas o consumo de suplementos nutricionais (SN) é comumente visto como recurso para melhorar as adaptações e desempenho no esporte. No fisiculturismo essa prática pode ser associada a melhora da estética, principalmente em períodos de competição. O objetivo deste trabalho foi analisar a utilização de SN por fisiculturistas e associar às demais variáveis durante a fase de competição. Trata-se de estudo transversal realizado em 2016 com 25 atletas masculinos do fisiculturismo em fase de competição. Esses foram questionados quanto ao consumo de SN, se estavam em acompanhamento nutricional e, ainda, foram aferidas dobras cutâneas para estimativa de gordura corporal. Para associação das variáveis foi utilizado o teste exato de Fisher. A média de idade dos atletas foi 28,56±9,71 anos, 88% relataram fazer uso de whey protein; 76% de Branched Chain Amino&nbsp;&nbsp; Acids (BCAA); 40%&nbsp;&nbsp; de&nbsp;&nbsp; creatina&nbsp;&nbsp; e glutamina. O acompanhamento nutricional esteve associado com o consumo de vitamina C (88,9%) e glutamina (44,4%). Enquanto a categoria mens sport model foi associada à utilização de creatina (77,8%). Dessa forma, conclui-se que muitos atletas faziam uso de SN e que alguns estavam associados ao acompanhamento nutricional e categoria de competição

Utilização de suplementos nutricionais por fisiculturistas em fase de competição - estudo transversal

Entre atletas o consumo de suplementos nutricionais (SN) é comumente visto como recurso para melhorar as adaptações e desempenho no esporte. No fisiculturismo essa prática pode ser associada a melhora da estética, principalmente em períodos de competição. O objetivo deste trabalho foi analisar a utilização de SN por fisiculturistas e associar às demais variáveis durante a fase de competição. Trata-se de estudo transversal realizado em 2016 com 25 atletas masculinos do fisiculturismo em fase de competição. Esses foram questionados quanto ao consumo de SN, se estavam em acompanhamento nutricional e, ainda, foram aferidas dobras cutâneas para estimativa de gordura corporal. Para associação das variáveis foi utilizado o teste exato de Fisher. A média de idade dos atletas foi 28,56±9,71 anos, 88% relataram fazer uso de whey protein; 76% de Branched Chain Amino   Acids (BCAA); 40%   de   creatina   e glutamina. O acompanhamento nutricional esteve associado com o consumo de vitamina C (88,9%) e glutamina (44,4%). Enquanto a categoria mens sport model foi associada à utilização de creatina (77,8%). Dessa forma, conclui-se que muitos atletas faziam uso de SN e que alguns estavam associados ao acompanhamento nutricional e categoria de competição