Parameter space of experimental chaotic circuits with high-precision control parameters

ACKNOWLEDGMENTS The authors thank Professor Iberê Luiz Caldas for the suggestions and encouragement. The authors F.F.G.d.S., R.M.R., J.C.S., and H.A.A. acknowledge the Brazilian agency CNPq and state agencies FAPEMIG, FAPESP, and FAPESC, and M.S.B. also acknowledges the EPSRC Grant Ref. No. EP/I032606/1.Peer reviewedPublisher PD

Dynamical estimates of chaotic systems from Poincar\'e recurrences

We show that the probability distribution function that best fits the distribution of return times between two consecutive visits of a chaotic trajectory to finite size regions in phase space deviates from the exponential statistics by a small power-law term, a term that represents the deterministic manifestation of the dynamics, which can be easily experimentally detected and theoretically estimated. We also provide simpler and faster ways to calculate the positive Lyapunov exponents and the short-term correlation function by either realizing observations of higher probable returns or by calculating the eigenvalues of only one very especial unstable periodic orbit of low-period. Finally, we discuss how our approaches can be used to treat data coming from complex systems.Comment: subm. for publication. Accepted fpr publication in Chao

Long Range Anticorrelations and Non-Gaussian Behavior of a Leaky Faucet

We find that intervals between successive drops from a leaky faucet display scale-invariant, long-range anticorrelations characterized by the same exponents of heart beat-to-beat intervals of healthy subjects. This behavior is also confirmed by numerical simulations on lattice and it is faucet-width- and flow-rate-independent. The histogram for the drop intervals is also well described by a L\'evy distribution with the same index for both histograms of healthy and diseased subjects. This additional result corroborates the evidence for similarities between leaky faucets and healthy hearts underlying dynamics.Comment: Self-extracting uuencoded postscript file. Phys.Rev.E (Rap.Comm.). Related papers can be found at http://www.if.uff.br/~tjpp/tjppe.htm

FRI0191 CRANIAL-LIMITED AND LARGE-VESSEL GIANT CELL ARTERITIS: PRESENTING FEATURES AND OUTCOME

Background:Giant cell arteritis (GCA) comprises two main phenotypes: cranial (C) and large-vessel (LV) disease1. A full baseline steroid-free vascular imaging evaluation is required to properly diagnose LV involvement2Objectives:To compare presenting and prognostic features of LV-GCA and C-GCA patients after an adequate vascular imaging evaluation at baselineMethods:Data from GCA patients followed-up at our Institution were retrospectively collected. Only patients who underwent large-vessel imaging (PET, CTA, MRA) at disease onset or within 1 week after steroid introduction were included. Patients with evidence of LV involvement were classified as LV-GCA. Differences between LV-GCA and C-GCA patients regarding presenting features, treatment, prognosis were evaluated. Non-parametric tests were usedResults:In our cohort, we identified 161/280 patients who underwent LV-imaging study at baseline. Of these, 100 (62.1%) had signs of LV inflammation. Table 1 compares demographic features, diagnostic delay, pre-existing comorbidities and complementary treatment between the 2 groups. Table 2 compares disease features at diagnosis. Mean follow-up was similar between LV- and C-GCA patients (31.8±31.8 vs 27.8±29.1 months; 70% vs 73.8% followed-up ≥12 months). Corrected cumulative prednisone dose (CCPD, grams/months) was equivalent (LV, 0.67±0.57; C, 0.87±1.37; p=0.871). A DMARD was added in 73% of LV- and in 55.7% of C-GCA patients (p=0.027), but, notably, it was introduced at baseline in 52% of LV- vs 23.5% of C-GCA patients (p=0.006). CCPD was equivalent even considering only patients who did not receive DMARDs (LV, 0.92±0.81; C, 0.94±1.18; p=0.522). Frequency of relapses was not significantly different (LV, 51%; C, 57.3%, p=0.515), even when considering only DMARD-receiving patients (LV, 36.1%; C, 38.2%, p=0.833). Aortic aneurysms incidence at 5 years was similar (LV, 17.3%; C, 15.7%; p=0.826). Rate of metabolic and infective complications was similar, in terms of arterial hypertension (LV, 3%; C, 0%, p=0.286), diabetes (2% vs 0%, p=0.524), osteoporotic fractures (7% vs 5%, p=0.742), severe infections (3% vs 3.3%, p=1)Table 1.Demographic features, diagnostic delay, pre-existing comorbidities, and complementary treatment at baseline in LV and C-GCA patientsLV imaging +n=100 (%)LV imaging-n=61 (%)p-valueAge (years)73.2 ± 8.976 ± 8.80.018Sex (female)65 (65)40 (65)1Diagnostic delay (months)3.5 ± 4.62.3 ± 4.90.001Pre-existing comorbidities- CAD3 (3)7 (11.5)0.043- Diabetes4 (4)6 (9.8)0.181- Dyslipidemia17 (17)17 (27.9)0.114- Hypertension42 (42)34 (55.7)0.105- Stroke3 (3)3 (5)0.674- Cancer20 (20)6 (9.8)0.122Ongoing complementary treatment- Antiplatelet18 (18)15 (25)0.322- Anticoagulant1 (1)6 (9.8)0.012- Statin14 (14)14 (23)0.198Table 2.Diseases features at onset in LV and C-GCA patientsLV imaging +n=100 (%)LV imaging-n=61 (%)p-valueTemporal biopsy positive17/31 (55)9(43)0.573Symptoms- Headache65 (65)52 (85)0.006- Jaw claudication22 (22)20 (32.8)0.142- Scalp tenderness31 (31)26 (42.6)0.174- Ocular symptoms14 (14)20 (32.8)0.006- Ischemic optic neuropathy7 (7)17 (27.9)<0.001- Stroke3 (3)0 (0)0.290- Polymyalgia rheumatica42 (42)31 (50.8)0.328- Fever44 (44)12 (19.7)0.002- Fatigue72 (72)21 (34.4)<0.001- Weight loss37 (37)7 (11.5)<0.001- Cough10 (10)1 (1.6)0.053Laboratory findings, mean- C-reactive protein, mg/L80.8 ± 60.865.7 ± 58.20.057- Erythrocyte sedimentation rate76.8 ± 3071.5 ± 270.360- Hemoglobin, g/dL11.4 ± 1.512 ± 1.60.007- Platelet count389.4 ± 116.6366.8 ± 125.20.758Conclusion:LV-GCA patients are younger and suffer of a greater diagnostic delay. Although a greater systemic inflammation seems to be a feature of LV-GCA patients, the vascular prognosis is similar to C-GCA patients, who, conversely, have a greater incidence of ocular complicationsReferences:[1]Dejaco C, et al. Nat Rev Rheumatol (2017)[2]Kermani T, et al. Rheumatology (2019)Disclosure of Interests:Alessandro Tomelleri: None declared, Corrado Campochiaro Speakers bureau: Novartis, Pfizer, Roche, GSK, SOBI, Silvia Sartorelli: None declared, Nicola Farina: None declared, Elena Baldissera Speakers bureau: Novartis, Pfizer, Roche, Alpha Sigma, Sanofi, Lorenzo Dagna Grant/research support from: Abbvie, BMS, Celgene, Janssen, MSD, Mundipharma Pharmaceuticals, Novartis, Pfizer, Roche, SG, SOBI, Consultant of: Abbvie, Amgen, Biogen, BMS, Celltrion, Novartis, Pfizer, Roche, SG, and SOB

Monte Carlo Simulations of Some Dynamical Aspects of Drop Formation

In this work we present some results from computer simulations of dynamical aspects of drop formation in a leaky faucet. Our results, which agree very well with the experiments, suggest that only a few elements, at the microscopic level, would be necessary to describe the most important features of the system. We were able to set all parameters of the model in terms of real ones. This is an additional advantage with respect to previous theoretical works.Comment: 7 pages (Latex), 6 figures (PS) Accepted to publication in Int. J. Mod. Phys. C Source Codes at http://www.if.uff.br/~arlim