Experimental synchrony of semiconductor lasers in coupled networks.

The emission and synchronization of mutually-coupled semiconductor lasers with short cavities has been already recorded, with transversely unstable solutions existing within the chaotic synchronization manifold. Noise and laser-mismatch induced instabilities cause short de-synchronization events within the overall generalized synchronization, influencing the pragmatism of using these signals in secure data exchange applications. However, such operation can be functional for user authentication and sensing applications by assessing a time-averaged performance of synchrony. Until now, this has not been examined either in large-scale laser network configurations or in large transmission coupling paths, as real network implementations oblige. Here we present the first implementation of a fully-coupled fiber network with up to 16 semiconductor lasers, independently controlled and coupled through long interacting cavities. High level of consistent global or cluster synchrony via chaotic signals is demonstrated among all devices of the same origin and under appropriate operation. Devices that are not identical fail to synchronize at any condition, when coupled to the network. Under multiplexed operation, groups of lasers that emit at spectral distances as low as 50pm are shown to preserve intra-cluster synchronization when transmitted in the same fiber-optic channel, despite their large bandwidth of emitted signals.

Experimental evaluation of subcarrier modulation in chaotic optical communication systems.

Data streams with bit rates of up to 1 Gbit/s have been applied though the subcarrier modulation technique in an experimentally deployed optical communication system based on chaos data encryption and have been recovered efficiently. By shifting the spectral components of the encrypted data in regions where the chaotic carrier is powerful, a more efficient encryption and final message recovery is recorded with respect to the baseband modulation technique, improving the up-to-date performance of analogous systems.

Blood pressure variability within a single visit and all-cause mortality.

BACKGROUND: Within-visit variability of repeated sequential readings of blood pressure (BP) is an important phenomenon that may affect precision of BP measurement and thus decision making concerning BP-related risk and hypertension management. However, limited data exist concerning predictive ability of within-visit BP variability for clinical outcomes. Therefore, we aimed to investigate the association between the variability of three repeated office BP measurements and the risk of all-cause mortality, independent of BP levels. METHODS: Data collected through the National Health and Nutrition Examination Survey (NHANES) were analysed. NHANES is a program of studies designed to assess health and nutritional status of adults and children in the United States. A complete set of three sequential BP measurements, together with survival status, were available for 24969 individuals (age 46.8±;19.3 years, 49% males). Multivariable logistic regression models were used to determine the prognostic ability of the examined demographic, clinical, and haemodynamic indices. RESULTS: Among various examined indices of variability of systolic (SBP) and diastolic (DBP) blood pressure measurements, the standard deviation of DBP (DBPSD) was the stronger independent predictor of mortality (odds ratio 1.064, 95% Confidence Interval: 1.011-1.12) after adjustment for age, sex, body mass index, smoking, SBP, heart rate, history of hypertension, diabetes mellitus, hypercholesterolaemia, and cardiovascular events. CONCLUSION: Within-visit variability of three sequential office DBP readings may allow for the identification of high-risk patients better than mean SBP and DBP levels. The predictive value of within-visit BP variability and methods to improve its clinical application are worthy of further research.

Association of left ventricular structural and functional abnormalities with aortic and brachial blood pressure variability in hypertensive patients: the SAFAR study.

Both brachial blood pressure (BP) level and its variability (BPV) significantly associate with left ventricular (LV) structure and function. Recent studies indicate that aortic BP is superior to brachial BP in the association with LV abnormalities. However, it remains unknown whether aortic BPV better associate with LV structural and functional abnormalities. We therefore aimed to investigate and compare aortic versus brachial BPV, in terms of the identification of LV abnormalities. Two hundred and three participants who underwent echocardiography were included in this study. Twenty-four-hour aortic and brachial ambulatory BP was measured simultaneously by a validated BP monitor (Mobil-O-Graph, Stolberg, Germany) and BPV was calculated with validated formulae. LV mass and LV diastolic dysfunction (LVDD) were evaluated by echocardiography. The prevalence of LV hypertrophy (LVH) and LVDD increased significantly with BPV indices (P⩽0.04) in trend tests. After adjustment to potential confounders, only aortic average real variability (ARV), but not brachial ARV or weighted s.d. (wSD, neither aortic nor brachial) significantly associated with LV mass index (P=0.02). Similar results were observed in logistic regression. After adjustment, only aortic ARV significantly associated with LVH (odds ratio (OR) and 95% confidence interval (CI): 2.28 (1.08, 4.82)). As for LVDD, neither the brachial nor the aortic 24-hour wSD, but the aortic and brachial ARV, associated with LVDD significantly, with OR=2.28 (95% CI: (1.03, 5.02)) and OR=2.36 (95% CI: (1.10, 5.05)), respectively. In summary, aortic BPV, especially aortic ARV, seems to be superior to brachial BPV in the association of LV structural and functional abnormalities.

Association of left ventricular diastolic dysfunction with 24-h aortic ambulatory blood pressure: the SAFAR study.

Aortic blood pressure (BP) and 24-h ambulatory BP are both better associated with target organ damage than office brachial BP. However, it remains unclear whether a combination of these two techniques would be the optimal methodology to evaluate patients' BP in terms of left ventricular diastolic dysfunction (LVDD) prevention. In 230 participants, office brachial and aortic BPs were measured by a validated BP monitor and a tonometry-based device, respectively. 24-h ambulatory brachial and aortic BPs were measured by a validated ambulatory BP monitor (Mobil-O-Graph, Germany). Systematic assessment of patients' LVDD was performed. After adjustment for age, gender, hypertension and antihypertensive treatment, septum and lateral E/Ea were significantly associated with office aortic systolic BP (SBP) and pulse pressure (PP) and 24-h brachial and aortic SBP and PP (P ⩽ 0.04), but not with office brachial BP (P ⩾ 0.09). Similarly, 1 standard deviation in SBP was significantly associated with 97.8 ± 20.9, 86.4 ± 22.9, 74.1 ± 23.3 and 51.3 ± 22.6 in septum E/Ea and 68.6 ± 2 0.1, 54.2 ± 21.9, 37.9 ± 22.4 and 23.1 ± 21.4 in lateral E/Ea, for office and 24-h aortic and brachial SBP, respectively. In qualitative analysis, except for office brachial BP, office aortic and 24-h brachial and aortic BPs were all significantly associated with LVDD (P ⩽ 0.03), with the highest odds ratio in 24-h aortic SBP. Furthermore, aortic BP, no matter in the office or 24-h ambulatory setting, showed the largest area under receiver operating characteristic curves (P ⩽ 0.02). In conclusion, 24-h aortic BP is superior to other BPs in the association with LVDD.

Photonic integrated device for chaos applications in communications.

A novel photonic monolithic integrated device consisting of a distributed feedback laser, a passive resonator, and active elements that control the optical feedback properties has been designed, fabricated, and evaluated as a compact potential chaotic emitter in optical communications. Under diverse operating parameters, the device behaves in different modes providing stable solutions, periodic states, and broadband chaotic dynamics. Chaos data analysis is performed in order to quantify the complexity and chaoticity of the experimental reconstructed attractors by applying nonlinear noise filtering.