Analysis of the convergence of the 1/t and Wang-Landau algorithms in the calculation of multidimensional integrals

In this communication, the convergence of the 1/t and Wang - Landau algorithms in the calculation of multidimensional numerical integrals is analyzed. Both simulation methods are applied to a wide variety of integrals without restrictions in one, two and higher dimensions. The errors between the exact and the calculated values of the integral are obtained and the efficiency and accuracy of the methods are determined by their dynamical behavior. The comparison between both methods and the simple sampling Monte Carlo method is also reported. It is observed that the time dependence of the errors calculated with 1/t algorithm goes as N^{-1/2} (with N the MC trials) in quantitative agreement with the simple sampling Monte Carlo method. It is also showed that the error for the Wang - Landau algorithm saturates in time evidencing the non-convergence of the methods. The sources for the error are also determined.Comment: 8 pages, 5 figure

Inversion of electrical conductivity data with Tikhonov regularization approach: some considerations

Electromagnetic induction measurements, which are generally used to determine lateral variations of apparent electrical conductivity, can provide quantitative estimates of the subsurface conductivity at different depths. Quantitative inference about the Earth’s interior from experimental data is, however, an ill-posed problem. Using the generalised McNeill’s theory for the EM38 ground conductivity meter, we generated synthetic apparent conductivity curves (input data vector) simulating measurements at different heights above the soil surface. The electrical conductivity profile (the Earth model) was then estimated solving a least squares problem with Tikhonov regularization optimised with a projected conjugate gradient algorithm. Although the Tikhonov approach improves the conditioning of the resulting linear system, profile reconstruction can be surprisingly far from the desired true one. On the contrary, the projected conjugate gradient provided the best solution without any explicit regularization (a = 0) of the objective function of the least squares problem. Also, if the initial guess belongs to the image of the system matrix, Im(A), we found that it provides a unique solution in the same subspace Im(A)

The circle of Gánovce. Natural history of an endocast

The natural endocranial cast of Gánovce was found in Slovakia in 1926, and then stored in the National Museum (Národní Muzeum) of Prague. The endocast was extensively studied by Emanuel Vlček (1925-2006), mostly during the 50s and 60s of the past century (e.g., Vlček, 1949, 1953, 1955, 1969), with a large set of analytical tools including radiographic and biochemical sur- veys, and outline shape analysis. He recognized the Neanderthal morphology of the cast, which was dated to 105 ka and which has an estimated volume of 1320cc. In particular, Vlček noticed a similarity with specimens such as Krapina 3, Gibraltar 1 and Saccopastore 1. In fact, these three specimens all display a similar overall cra- nial anatomy, being possibly representatives of an “early and small-brained” Neanderthal morpho- type (Bruner & Manzi, 2006, 2008)

Inversion of electrical conductivity data with Tikhonov regularization approach: some considerations

Electromagnetic induction measurements, which are generally used to determine lateral variations of apparent electrical conductivity, can provide quantitative estimates of the subsurface conductivity at different depths. Quantitative inference about the Earth's interior from experimental data is, however, an ill-posed problem. Using the generalised McNeill's theory for the EM38 ground conductivity meter, we generated synthetic apparent conductivity curves (input data vector) simulating measurements at different heights above the soil surface. The electrical conductivity profile (the Earth model) was then estimated solving a least squares problem with Tikhonov regularization optimised with a projected conjugate gradient algorithm. Although the Tikhonov approach improves the conditioning of the resulting linear system, profile reconstruction can be surprisingly far from the desired true one. On the contrary, the projected conjugate gradient provided the best solution without any explicit regularization ( a= 0) of the objective function of the least squares problem. Also, if the initial guess belongs to the image of the system matrix, Im(A), we found that it provides a unique solution in the same subspace Im(A)

Large K-exciton dynamics in GaN epilayers: the non-thermal and thermal regime

We present a detailed investigation concerning the exciton dynamics in GaN epilayers grown on c-plane sapphire substrates, focussing on the exciton formation and the transition from the nonthermal to the thermal regime. The time-resolved kinetics of LO-phonon replicas is used to address the energy relaxation in the excitonic band. From ps time-resolved spectra we bring evidence for a long lasting non-thermal excitonic distribution which accounts for the rst 50 ps. Such a behavior is con rmed in di erent experimental conditions, both when non-resonant and resonant excitation are used. At low excitation power density the exciton formation and their subsequent thermalization is dominated by impurity scattering rather than by acoustic phonon scattering. The estimate of the average energy of the excitons as a function of delay after the excitation pulse provides information on the relaxation time, which describes the evolution of the exciton population to the thermal regime.Comment: 9 pages,8 figure

Daytime turbulent exchange between the Amazon forest and the atmosphere

Detailed observations of turbulence just above and below the crown of the Amazon rain forest during the wet season are presented. The forest canopy is shown to remove high frequency turbulent fluctuations while passing lower frequencies. Filter characteristics of turbulent transfer into the Amazon rain forest canopy are quantified. Simple empirical relations that relate observed turbulent heat fluxes to horizontal wind variance are presented. Changes in the amount of turbulent coupling between the forest and the boundary layer associated with deep convective clouds are presented both as statistical averages and as a series of case studies. These convective processes during the rainy season are shown to alter the diurnal course of turbulent fluxes. In wake of giant coastal systems, no significant heat or moisture fluxes occur for up to a day after the event. Radar data is used to demonstrate that even small raining clouds are capable of evacuating the canopy of substances normally trapped by persistent static stability near the forest floor. Recovery from these events can take more than an hour, even during mid-day. In spite of the ubiquitous presence of clouds and frequent rain during this season, the average horizontal wind speed spectrum is well described by dry CBL similarity hypotheses originally found to apply in flat terrain

Echocardiography combined with cardiopulmonary exercise testing for the prediction of outcome in idiopathic pulmonary arterial hypertension

BACKGROUND: Right ventricular (RV) function is a major determinant of exercise intolerance and outcome in idiopathic pulmonary arterial hypertension (IPAH). The aim of the study was to evaluate the incremental prognostic value of echocardiography of the RV and cardiopulmonary exercise testing (CPET) on long-term prognosis in these patients. METHODS: One hundred-thirty treatment-naïve IPAH patients were enrolled and prospectively followed. Clinical worsening (CW) was defined by a reduction in 6-minute walk distance plus an increase in functional class, or non elective hospitalization for PAH, or death. Baseline evaluation included clinical, hemodynamic, echocardiographic and CPET variables. Cox regression modeling with c-statistic and bootstrapping validation methods were done. RESULTS: During a mean period of 528 ± 304 days, 54 patients experienced CW (53%). Among demographic, clinical and hemodynamic variables at catheterization, functional class and cardiac index were independent predictors of CW (Model-1). With addition of echocardiographic and CPET variables (Model-2), peak O2 pulse (peak VO2/heart rate) and RV fractional area change (RVFAC) independently improved the power of the prognostic model (AUC: 0.81 vs 0.66, respectively; p=0.005). Patients with low RVFAC and low O2 pulse (low RVFAC + low O2 pulse) and high RVFAC+low O2 pulse showed 99.8 and 29.4 increase in the hazard ratio, respectively (relative risk -RR- of 41.1 and 25.3, respectively), compared with high RVFAC+high O2 pulse (p=0.0001). CONCLUSIONS: Echocardiography combined with CPET provides relevant clinical and prognostic information. A combination of low RVFAC and low O2 pulse identifies patients at a particularly high risk of clinical deterioration

Sexual violence in post-conflict Liberia: survivors and their care.

Using routine data from three clinics offering care to survivors of sexual violence (SV) in Monrovia, Liberia, we describe the characteristics of SV survivors and the pattern of SV and discuss how the current approach could be better adapted to meet survivors' needs. There were 1500 survivors seeking SV care between January 2008 and December 2009. Most survivors were women (98%) and median age was 13 years (Interquartile range: 9-17 years). Sexual aggression occurred during day-to-day activities in 822 (55%) cases and in the survivor's home in 552 (37%) cases. The perpetrator was a known civilian in 1037 (69%) SV events. Only 619 (41%) survivors sought care within 72 h. The current approach could be improved by: effectively addressing the psychosocial needs of child survivors, reaching male survivors, targeting the perpetrators in awareness and advocacy campaigns and reducing delays in seeking care

Pattern Recognition and Clustering of Transient Pressure Signals for Burst Location

[EN] A large volume of the water produced for public supply is lost in the systems between sources and consumers. An important-in many cases the greatest-fraction of these losses are physical losses, mainly related to leaks and bursts in pipes and in consumer connections. Fast detection and location of bursts plays an important role in the design of operation strategies for water loss control, since this helps reduce the volume lost from the instant the event occurs until its effective repair (run time). The transient pressure signals caused by bursts contain important information about their location and magnitude, and stamp on any of these events a specific "hydraulic signature". The present work proposes and evaluates three methods to disaggregate transient signals, which are used afterwards to train artificial neural networks (ANNs) to identify burst locations and calculate the leaked flow. In addition, a clustering process is also used to group similar signals, and then train specific ANNs for each group, thus improving both the computational efficiency and the location accuracy. The proposed methods are applied to two real distribution networks, and the results show good accuracy in burst location and characterization.Manzi, D.; Brentan, BM.; Meirelles, G.; Izquierdo Sebastián, J.; Luvizotto Jr., E. (2019). Pattern Recognition and Clustering of Transient Pressure Signals for Burst Location. Water. 11(11):1-13. https://doi.org/10.3390/w11112279S1131111Creaco, E., & Walski, T. (2017). Economic Analysis of Pressure Control for Leakage and Pipe Burst Reduction. Journal of Water Resources Planning and Management, 143(12), 04017074. doi:10.1061/(asce)wr.1943-5452.0000846Campisano, A., Creaco, E., & Modica, C. (2010). RTC of Valves for Leakage Reduction in Water Supply Networks. 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Data Mining and Knowledge Discovery, 15(2), 107-144. doi:10.1007/s10618-007-0064-zNavarrete-López, C., Herrera, M., Brentan, B., Luvizotto, E., & Izquierdo, J. (2019). Enhanced Water Demand Analysis via Symbolic Approximation within an Epidemiology-Based Forecasting Framework. Water, 11(2), 246. doi:10.3390/w11020246Meirelles, G., Manzi, D., Brentan, B., Goulart, T., & Luvizotto, E. (2017). Calibration Model for Water Distribution Network Using Pressures Estimated by Artificial Neural Networks. Water Resources Management, 31(13), 4339-4351. doi:10.1007/s11269-017-1750-2Adamowski, J., & Chan, H. F. (2011). A wavelet neural network conjunction model for groundwater level forecasting. Journal of Hydrology, 407(1-4), 28-40. doi:10.1016/j.jhydrol.2011.06.013Brentan, B., Meirelles, G., Luvizotto, E., & Izquierdo, J. (2018). Hybrid SOM+ k -Means clustering to improve planning, operation and management in water distribution systems. 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