Comparison between frequency domain and time domain riser analysis

In the optimization or parametric analyses of risers, several configurations must be analyzed. It is laborious to perform time domain solutions for the dynamic analysis, since they are time-consuming tasks. So, frequency domain solutions appear to be a possible alternative, mainly in the early stages of a riser design. However, frequency domain analysis is linear and requires that nonlinear effects are treated. The aim of this paper is to present a possible way to treat some of these nonlinearities, using an iterative process together with an analytical correction, and compare the results of a frequency domain analysis with the those of a full nonlinear analysis. [DOI: 10.1115/1.4006149]

Wavelet analysis of heart rate variability related to nocturnal frontal lobe epilepsy seizures

Introduction: Nocturnal frontal lobe epilepsy (NFLE) is a distinct syndrome of partial epilepsy whose clinical features comprise a spectrum of paroxysmal motor manifestations of variable duration and complexity, arising from sleep. Cardiovascular changes during NFLE seizures have previously been observed, however the extent of these modifications and their relationship with seizure onset has not been analyzed in detail. Objective: Aim of present study is to evaluate NFLE seizure related changes in heart rate (HR) and in sympathetic/parasympathetic balance through wavelet analysis of HR variability (HRV). Methods: We evaluated the whole night digitally recorded video-polysomnography (VPSG) of 9 patients diagnosed with NFLE with no history of cardiac disorders and normal cardiac examinations. Events with features of NFLE seizures were selected independently by three examiners and included in the study only if a consensus was reached. Heart rate was evaluated by measuring the interval between two consecutive R-waves of QRS complexes (RRi). RRi series were digitally calculated for a period of 20 minutes, including the seizures and resampled at 10 Hz using cubic spline interpolation. A multiresolution analysis was performed (Daubechies-16 form), and the squared level specific amplitude coefficients were summed across appropriate decomposition levels in order to compute total band powers in bands of interest (LF: 0.039062 - 0.156248, HF: 0.156248 - 0.624992). A general linear model was then applied to estimate changes in RRi, LF and HF powers during three different period (Basal) (30 sec, at least 30 sec before seizure onset, during which no movements occurred and autonomic conditions resulted stationary); pre-seizure period (preSP) (10 sec preceding seizure onset) and seizure period (SP) corresponding to the clinical manifestations. For one of the patients (patient 9) three seizures associated with ictal asystole were recorded, hence he was treated separately. Results: Group analysis performed on 8 patients (41 seizures) showed that RRi remained unchanged during the preSP, while a significant tachycardia was observed in the SP. A significant increase in the LF component was instead observed during both the preSP and the SP (p<0.001) while HF component decreased only in the SP (p<0.001). For patient 9 during the preSP and in the first part of SP a significant tachycardia was observed associated with an increased sympathetic activity (increased LF absolute values and LF%). In the second part of the SP a progressive decrease in HR that gradually exceeded basal values occurred before IA. Bradycardia was associated with an increase in parasympathetic activity (increased HF absolute values and HF%) contrasted by a further increase in LF until the occurrence of IA. Conclusions: These data suggest that changes in autonomic balance toward a sympathetic prevalence always preceded clinical seizure onset in NFLE, even when HR changes were not yet evident, confirming that wavelet analysis is a sensitive technique to detect sudden variations of autonomic balance occurring during transient phenomena. Finally we demonstrated that epileptic asystole is associated with a parasympathetic hypertonus counteracted by a marked sympathetic activation.

Blood component ratios in massively transfused, blunt trauma patients--a time-dependent covariate analysis

This study evaluated critical thresholds for fresh frozen plasma (FFP) and platelet (PLT) to packed red blood cell (PRBC) ratios and determined the impact of high FFP:PRBC and PLT:PRBC ratios on outcomes in patients requiring massive transfusion (MT).

Relationship between onset-to-door time and door-to-thrombolysis time: a pooled analysis of 10 dedicated stroke centers

BACKGROUND AND PURPOSE Inverse relationship between onset-to-door time (ODT) and door-to-needle time (DNT) in stroke thrombolysis was reported from various registries. We analyzed this relationship and other determinants of DNT in dedicated stroke centers. METHODS Prospectively collected data of consecutive ischemic stroke patients from 10 centers who received IV thrombolysis within 4.5 hours from symptom onset were merged (n=7106). DNT was analyzed as a function of demographic and prehospital variables using regression analyses, and change over time was considered. RESULTS In 6348 eligible patients with known treatment delays, median DNT was 42 minutes and kept decreasing steeply every year (P<0.001). Median DNT of 55 minutes was observed in patients with ODT ≤30 minutes, whereas it declined for patients presenting within the last 30 minutes of the 3-hour time window (median, 33 minutes) and of the 4.5-hour time window (20 minutes). For ODT within the first 30 minutes of the extended time window (181-210 minutes), DNT increased to 42 minutes. DNT was stable for ODT for 30 to 150 minutes (40-45 minutes). We found a weak inverse overall correlation between ODT and DNT (R(2)=-0.12; P<0.001), but it was strong in patients treated between 3 and 4.5 hours (R(2)=-0.75; P<0.001). ODT was independently inversely associated with DNT (P<0.001) in regression analysis. Octogenarians and women tended to have longer DNT. CONCLUSIONS DNT was decreasing steeply over the last years in dedicated stroke centers; however, significant oscillations of in-hospital treatment delays occurred at both ends of the time window. This suggests that further improvements can be achieved, particularly in the elderly.

Time-Series Panel Analysis (TSPA): Multivariate Modeling of Temporal Associations in Psychotherapy Process.

Objective: Processes occurring in the course of psychotherapy are characterized by the simple fact that they unfold in time and that the multiple factors engaged in change processes vary highly between individuals (idiographic phenomena). Previous research, however, has neglected the temporal perspective by its traditional focus on static phenomena, which were mainly assessed at the group level (nomothetic phenomena). To support a temporal approach, the authors introduce time-series panel analysis (TSPA), a statistical methodology explicitly focusing on the quantification of temporal, session-to-session aspects of change in psychotherapy. TSPA-models are initially built at the level of individuals and are subsequently aggregated at the group level, thus allowing the exploration of prototypical models. Method: TSPA is based on vector auto-regression (VAR), an extension of univariate auto-regression models to multivariate time-series data. The application of TSPA is demonstrated in a sample of 87 outpatient psychotherapy patients who were monitored by postsession questionnaires. Prototypical mechanisms of change were derived from the aggregation of individual multivariate models of psychotherapy process. In a 2nd step, the associations between mechanisms of change (TSPA) and pre- to postsymptom change were explored. Results: TSPA allowed a prototypical process pattern to be identified, where patient's alliance and self-efficacy were linked by a temporal feedback-loop. Furthermore, therapist's stability over time in both mastery and clarification interventions was positively associated with better outcomes. Conclusions: TSPA is a statistical tool that sheds new light on temporal mechanisms of change. Through this approach, clinicians may gain insight into prototypical patterns of change in psychotherapy.

Flavor tagged time-dependent angular analysis of the B0s → J/ψΦ decay and extraction of Δ Γs and the weak phase Φs in ATLAS

A measurement of the B 0 s →J/ψϕ decay parameters, updated to include flavor tagging is reported using 4.9  fb −1 of integrated luminosity collected by the ATLAS detector from s √ =7  TeV pp collisions recorded in 2011 at the LHC. The values measured for the physical parameters are ϕ s 0.12±0.25(stat)±0.05(syst)  rad ΔΓ s 0.053±0.021(stat)±0.010(syst)  ps −1 Γ s 0.677±0.007(stat)±0.004(syst)  ps −1 |A ∥ (0)| 2 0.220±0.008(stat)±0.009(syst) |A 0 (0)| 2 0.529±0.006(stat)±0.012(syst) δ ⊥ =3.89±0.47(stat)±0.11(syst)  rad where the parameter ΔΓ s is constrained to be positive. The S -wave contribution was measured and found to be compatible with zero. Results for ϕ s and ΔΓ s are also presented as 68% and 95% likelihood contours, which show agreement with the Standard Model expectations.

Time-varying signal analysis to detect high-altitude periodic breathing in climbers ascending to extreme altitude.

This work investigates the performance of cardiorespiratory analysis detecting periodic breathing (PB) in chest wall recordings in mountaineers climbing to extreme altitude. The breathing patterns of 34 mountaineers were monitored unobtrusively by inductance plethysmography, ECG and pulse oximetry using a portable recorder during climbs at altitudes between 4497 and 7546 m on Mt. Muztagh Ata. The minute ventilation (VE) and heart rate (HR) signals were studied, to identify visually scored PB, applying time-varying spectral, coherence and entropy analysis. In 411 climbing periods, 30-120 min in duration, high values of mean power (MP(VE)) and slope (MSlope(VE)) of the modulation frequency band of VE, accurately identified PB, with an area under the ROC curve of 88 and 89%, respectively. Prolonged stay at altitude was associated with an increase in PB. During PB episodes, higher peak power of ventilatory (MP(VE)) and cardiac (MP(LF)(HR) ) oscillations and cardiorespiratory coherence (MP(LF)(Coher)), but reduced ventilation entropy (SampEn(VE)), was observed. Therefore, the characterization of cardiorespiratory dynamics by the analysis of VE and HR signals accurately identifies PB and effects of altitude acclimatization, providing promising tools for investigating physiologic effects of environmental exposures and diseases.

Genetic Resistance Determinants, In Vitro Time-Kill Curve Analysis and Pharmacodynamic Functions for the Novel Topoisomerase II Inhibitor ETX0914 (AZD0914) in Neisseria gonorrhoeae.

Resistance in Neisseria gonorrhoeae to all available therapeutic antimicrobials has emerged and new efficacious drugs for treatment of gonorrhea are essential. The topoisomerase II inhibitor ETX0914 (also known as AZD0914) is a new spiropyrimidinetrione antimicrobial that has different mechanisms of action from all previous and current gonorrhea treatment options. In this study, the N. gonorrhoeae resistance determinants for ETX0914 were further described and the effects of ETX0914 on the growth of N. gonorrhoeae (ETX0914 wild type, single step selected resistant mutants, and efflux pump mutants) were examined in a novel in vitro time-kill curve analysis to estimate pharmacodynamic parameters of the new antimicrobial. For comparison, ciprofloxacin, azithromycin, ceftriaxone, and tetracycline were also examined (separately and in combination with ETX0914). ETX0914 was rapidly bactericidal for all wild type strains and had similar pharmacodynamic properties to ciprofloxacin. All selected resistant mutants contained mutations in amino acid codons D429 or K450 of GyrB and inactivation of the MtrCDE efflux pump fully restored the susceptibility to ETX0914. ETX0914 alone and in combination with azithromycin and ceftriaxone was highly effective against N. gonorrhoeae and synergistic interaction with ciprofloxacin, particularly for ETX0914-resistant mutants, was found. ETX0914, monotherapy or in combination with azithromycin (to cover additional sexually transmitted infections), should be considered for phase III clinical trials and future gonorrhea treatment.

NONLINEAR TIME SERIES/SYSTEM ANALYSIS (STATE-SPACE, DYNAMICS, INTERVENTION, RESILIENCE, KALMAN)

A discussion of nonlinear dynamics, demonstrated by the familiar automobile, is followed by the development of a systematic method of analysis of a possibly nonlinear time series using difference equations in the general state-space format. This format allows recursive state-dependent parameter estimation after each observation thereby revealing the dynamics inherent in the system in combination with random external perturbations.^ The one-step ahead prediction errors at each time period, transformed to have constant variance, and the estimated parametric sequences provide the information to (1) formally test whether time series observations y(,t) are some linear function of random errors (ELEM)(,s), for some t and s, or whether the series would more appropriately be described by a nonlinear model such as bilinear, exponential, threshold, etc., (2) formally test whether a statistically significant change has occurred in structure/level either historically or as it occurs, (3) forecast nonlinear system with a new and innovative (but very old numerical) technique utilizing rational functions to extrapolate individual parameters as smooth functions of time which are then combined to obtain the forecast of y and (4) suggest a measure of resilience, i.e. how much perturbation a structure/level can tolerate, whether internal or external to the system, and remain statistically unchanged. Although similar to one-step control, this provides a less rigid way to think about changes affecting social systems.^ Applications consisting of the analysis of some familiar and some simulated series demonstrate the procedure. Empirical results suggest that this state-space or modified augmented Kalman filter may provide interesting ways to identify particular kinds of nonlinearities as they occur in structural change via the state trajectory.^ A computational flow-chart detailing computations and software input and output is provided in the body of the text. IBM Advanced BASIC program listings to accomplish most of the analysis are provided in the appendix. ^

SeismicWaveTool: Continuous and discrete wavelet analysis and filtering for multichannel seismic data

A MATLAB-based computer code has been developed for the simultaneous wavelet analysis and filtering of multichannel seismic data. The considered time–frequency transforms include the continuous wavelet transform, the discrete wavelet transform and the discrete wavelet packet transform. The developed approaches provide a fast and precise time–frequency examination of the seismograms at different frequency bands. Moreover, filtering methods for noise, transients or even baseline removal, are implemented. The primary motivation is to support seismologists with a user-friendly and fast program for the wavelet analysis, providing practical and understandable results.

On the identification of multi-output linear time-invariant and periodic dynamic systems /

Includes bibliographies (p. 27-29).