Logarithmic Scale Research Articles

Pola Radiasi Antena Patch dalam Skala Linier

An antenna radiation pattern experiment has been carried out with the aim of determining the patch antenna radiation pattern on a logarithmic and linear scale, understanding the properties and principles of the antenna, and understanding the types of antenna radiation patterns. In the experiment, the angle, frequency, and radian intensity data were obtained, and the value of the linear intensity was calculated. With the principle of converting electrical signals into electromagnetic signals. a graph between angle and intensity is obtained. the graph between radian intensity and angle forms a circular pattern, in which the value of intensity and frequency at each point with a difference of 5 degrees has almost the same value. In conclusion, the antenna is a structure that can receive and release electromagnetic waves in the air. The patch antenna used has a unidirectional radiation pattern. Converts electromagnetic signals into electrical signals and vice versa, has a certain radiation pattern, and is easily disturbed by metallic materials.

Development of long-range phase coherence on the Kondo lattice

Despite of many efforts, we still lack a clear picture on how heavy electrons emerge and develop on the Kondo lattice. Here we introduce a key concept named the hybridization bond phase and propose a scenario based on phase correlation to address this issue. The bond phase is a gauge-invariant quantity combining two onsite hybridization fields mediated by inter-site magnetic correlations. Its probabilistic distribution decays exponentially with site distance, from which a characteristic length scale can be extracted to describe the spatial correlation of Kondo hybridizations. Our calculations show that this correlation length grows logarithmically with lowering temperature at large Kondo coupling, and reveal a precursor pseudogap state with short-range phase correlation before long-range phase coherence is developed to form the Kondo insulating (or heavy electron) state at low temperatures. This provides a potential microscopic explanation of the two-stage hybridization proposed by recent pump-probe experiment and the logarithmic scaling in the phenomenological two-fluid model. Our work offers a novel theoretical framework to describe the phase-related physics in Kondo lattice systems.

Acoustic surface wave dispersion with strain gradient elasticity and micro-inertia effect in lossy polymer-coated piezoelectric structure

This research paper utilizes second-order gradient electroelasticity theory to develop a theoretical model of Love-type surface wave transference considering strain and inertia gradient effects in a Kelvin–Voigt type viscoelastic lossy polymer-coated piezoelectric substrate. Non-classical constitutive equations derived from variational principles are used to obtain electromechanically coupled field equations. Using proper analytical techniques and non-classical boundary conditions, dispersion relations for electrically open and short cases are derived. Numerical example has been provided and graphs have been plotted to visualize the dependency of velocity and attenuation traits of Love-type waves on considered strain gradient, inertia gradient, and other relevant parameters like viscosity and layer width. It has been observed that the phase velocity of the fundamental mode of surface wave is highly affected by strain gradient elasticity and micro-inertia and high gradient elasticity helps to achieve high phase velocity. The investigation can provide proper guidelines to optimize biological or chemical surface acoustic wave (SAW) sensors with nanocoating. Highlights Nanoscale strain gradient elasticity and micro-inertia effect are considered in the shear wave propagation model. Non-conductive Kelvin–Voigt model-based viscoelasticity is assumed for coating polymer. Attenuation is also characterized along with phase velocity on a logarithmic scale. Dispersion characteristics are investigated for electrically open and short boundary types.

Comparing bupivacaine alone to liposomal bupivacaine plus bupivacaine in interscalene blocks for total shoulder arthroplasty: a randomized, non-inferiority trial

IntroductionInterscalene brachial plexus blocks are a commonly performed procedure to reduce pain following total shoulder arthroplasty. Liposomal bupivacaine has been purported to prolong the duration of brachial plexus blocks for...

Internally generated time in the rodent hippocampus is logarithmically compressed.

The Weber-Fechner law proposes that our perceived sensory input increases with physical input on a logarithmic scale. Hippocampal 'time cells' carry a record of recent experience by firing sequentially during a circumscribed period of time after a triggering stimulus. Different cells have 'time fields' at different delays up to at least tens of seconds. Past studies suggest that time cells represent a compressed timeline by demonstrating that fewer time cells fire late in the delay and their time fields are wider. This paper asks whether the compression of time cells obeys the Weber-Fechner Law. Time cells were studied with a hierarchical Bayesian model that simultaneously accounts for the firing pattern at the trial level, cell level, and population level. This procedure allows separate estimates of the within-trial receptive field width and the across-trial variability. After isolating across-trial variability, time field width increased linearly with delay. Further, the time cell population was distributed evenly along a logarithmic time axis. These findings provide strong quantitative evidence that the neural temporal representation in rodent hippocampus is logarithmically compressed and obeys a neural Weber-Fechner Law.

Modeling Urban Atmospheric Lead Dispersion from a Mining Tailings Basin in Bahia, Brazil

After the exhaustion of the lead mine in Boquira, Bahia in the 1990s, mining support structures and the tailings basin were abandoned, resulting in one of the largest environmental liabilities from mining in the state. Detailed studies on environmental damages are inexistent and this article aimed to analyze lead contamination in the urban area of the municipality, based on atmospheric dispersion modeling. For this purpose, a model was elaborated and implemented in Matlab R2014a considering houses, streets and air as three coexisting spatial domains. The model uses wind speed and direction as input data and results were calibrated (RMSE = 0.64 on decadal logarithmic scale) against existing measurements taken in 2014 of lead concentrations in street sediments and house dust within the urban area. Results suggested that particulate resuspension from streets and accumulation in houses may explain observed concentration patterns, and that the amount of suspended lead in the air is small compared to that in streets and houses. Additional simulations carried out for a hypothetical future remediation scenario showed that after 200 days the concentrations in the air and in the streets decreased considerably, while they stopped accumulating in houses. Hence, the model may be a potentially useful tool to assist in the evaluation and management of this and other urban areas affected by contamination through atmospheric dispersion of particulates. Consistent with our model formulation, we recommend mass per area for lead concentrations in streets and houses as more meaningful units for exposure risk/intensity than ppm (mass per mass) of street sediment or house dust.

Phases of Small Worlds: A Mean Field Formulation

A network is said to have the properties of a small world if a suitably defined average distance between any two nodes is proportional to the logarithm of the number of nodes, N. In this paper, we present a novel derivation of the small-world property for Gilbert–Erdös–Renyi random networks. We employ a mean field approximation that permits the analytic derivation of the distribution of shortest paths that exhibits logarithmic scaling away from the phase transition, inferable via a suitably interpreted order parameter. We begin by framing the problem in generality with a formal generating functional for undirected weighted random graphs with arbitrary disorder, recovering the result that the free energy associated with an ensemble of Gilbert graphs corresponds to a system of non-interacting fermions identified with the edge states. We then present a mean field solution for this model and extend it to more general realizations of network randomness. For a two family class of stochastic block models that we refer to as dimorphic networks, which allow for links within the different families to be drawn from two independent discrete probability distributions, we find the mean field approximation maps onto a spin chain combinatorial problem and again yields useful approximate analytic expressions for mean path lengths. Dimorophic networks exhibit a richer phase structure, where distinct small world regimes separate in analogy to the spinodal decomposition of a fluid. We find that is it possible to induce small world behavior in sub-networks that by themselves would not be in the small-world regime.

Structure analysis, morphological observations and electrical behavior of Co0·4Fe2·6O4 synthesized by surfactant-free solvothermal route

Cobalt nano-ferrite of formula Co0·4Fe2·6O4 was successfully prepared by a surfactant-free solvothermal reaction. Powder X-ray Diffraction (PXRD) revealed a cubic spinel structure. Transmission Electron Microscopy (TEM) observations confirmed the presence of agglomerated nanoparticles of two different sizes and shapes. 57Fe Mössbauer Spectrometry (MS) studies suggested a cationic redistribution between tetrahedral and octahedral sites in the spinel lattice. The low-frequency dependence of the dielectric properties is significantly affected by the presence of all polarization phenomena, in particular the interface polarization, on the basis of the phenomenological theory of the Koop model and the Maxwell-Wagner approach. At low frequencies, a linear negative correlation between the imaginary part of the permittivity and the frequency in the logarithm scale is observed. This is attributed to a dc-conductivity process. Furthermore, the electrical modulus analysis shows both Debye and non-Debye dielectric relaxations. The complex impedance plots were analyzed using the equivalent circuit model; grain and grain boundaries effects coexist. In the conductivity spectra, three regions were detected. A single power law and a double power law were separately applied to resolve the grains and grain boundaries effects. This unusual conductivity behavior can be explained by the modification in microstructure as well as the variation in charge carrier mobility. All results were interpreted in terms of microstructure properties and correlated with the cationic distribution within the spinel structure. The close values of activation energies obtained from the impedance, modulus and ac-conductivity in different temperature regions confirmed that the transport is probably due to a hopping mechanism dominated by smaller amount of oxygen vacancies.

Compact Modeling of Forward Operation Band-to-Band andTrap-Assisted Tunneling Currents in SiGe HBTs

Band-to-band tunneling (BTBT) [1] and trap-assisted tunneling (TAT) [2] have been observed in the forward operation base current of SiGe HBTs [3], due to increasing emitter-base junction doping and decreasing bandgap from high Ge mole fraction. At present, a compact model for the BTBT base current in forward operation does not exist. The reverse bias BTBT current is modeled in Mextram for both emitter-base and collector-base junctions. A compact model of the forward TAT base current was developed by our group for wide temperature range operation [4]. In this work, we present a new compact model of BTBT and further develop the TAT compact model of [4] for commercial temperature range application, and demonstrate their effectiveness on SiGe HBTs with around 250 GHz peak fT and fmax.Fig. 1 shows measured IB-VBE characteristics at several temperatures, together with simulation using the latest version of Mextram, 505.3. VCB=0V. At moderate VBE, the IB-VBE slope starts to decrease, similar to high injection effect in diodes, when we know high injection has not occurred as IC-VBE slope remains its low injection value (not shown). Such behavior cannot be modeled with standard base current models. A newly developed neutral-base-recombination (NBR) model introduced in 505.3 is used to fit such high-injection like IB-VBE behavior [5]. In this work we focus on the low VBE regions. At VBE<0.2V, IB first increases, then decreases, exhibiting a negative differential resistance, which is due to BTBT [3]. This BTBT region shows very weak temperature dependence. IB then slowly increases, with a large non-ideality factor of 3.78, which we believe is due to TAT [2] [3] [4]. Note that this should not be confused with the depletion-region recombination current, called IB2 in Mextram [5], with an ideality factor close to 2. The corresponding saturation current in this “TAT” region shows a temperature dependence much weaker than what one expects from the depletion region recombination current as well.Our BTBT model is based on the approach of Esaki [1] and Karlovsky [6], and has a simple functional form: IB,BTBT = kBTBTVBE,btbt(VBE,btbt – VBTBT)2, KBTBT and VBTBT are model parameters that can be extracted from the IB peak position and slope of IB-VBE followed by optimization. VBTBT has a physical meaning of VBTBT =[(Efn-Ec)|n-side+(Ev-Efp)|p-side]/q, with all symbols having their usual meanings in PN junctions. VBE,btbt is a smoothly limited version of VBE for modeling BTBT. When VBE<0, VBE is smoothly limited to 0, i.e. VBE,btbt->0, so that it does not interfere with the existing reverse bias BTBT model. When 0<VBE< VBTBT, VBE,btbt is essentially equal to VBE by design except at the boundaries. When VBE>VBTBT, VBE is smoothly limited to VBTBT, so that the BTBT current decays to zero, as there will be no aligned available states for BTBT. We observe that the BTBT current is insensitive to temperature, consistent with [3], and find that no temperature scaling is necessary for modeling the BTBT current.The TAT current is modeled as ITAT = ISTAT(exp(VBE,tat/VTUN)-1), with VTUN and ISTAT as model parameters [4]. VBE,tat is approximately VBE when VBE>0, and smoothly becomes zero when VBE<0. ISTAT scales with temperature T according to ISTAT,T=ISTAT(T/Tref)1/2exp(kTAT(T-Tref)), where Tref is the reference temperature, and kTAT is a temperature scaling model parameter. VTUN is temperature independent.Fig. 2 shows the 25°C IB-VBE modeling result at low VBE using a linear current scale, to better illustrate the behavior of all IB components at low VBE. Fig. 3 shows a full range view on a logarithmic scale. Fig. 4 shows the modeling results at all four temperatures, with the insert showing the low bias details.Overall the proposed BTBT and TAT models do a good job fitting the forward operation IB-VBE characteristics, with an easy to use formulation, and a small number of model parameters, 2 for BTBT and 3 for TAT.

Experimental insights toward carrier localization in in-rich InGaAs/InP as candidate for SWIR detection: Microstructural analysis combined with optical investigation

Hyperspectral imaging has been flourished thanks to the huge investigation of the infrared spectrum from NIR to LWIR bands. The ternary InGaAs has been investigated herein in the context of studying the structural dependences of localization phenomenon by X-ray diffraction (XRD), scanning electron microscopy-energy dispersive X-ray (SEM-EDX), Raman, ultraviolet–visible (UV–vis), and photoluminescence (PL) techniques. Using metal-organic vapor phase epitaxy (MOVPE), we succeed to grow the InGaAs directly on InP substrate at 560 °C as an active layer with indium concentration exceeding the “golden” value (53%) to enlarge its cutoff absorption wavelength. X-ray diffraction proved a good crystallinity of the heterostructure with a sharp peak related to the thick substrate and another peak attributed to the thin layer of InGaAs. Moreover, an interfacial layer appeared at the logarithmic scale of XRD patterns and was confirmed by Raman analysis. The SEM-EDX revealed an average indium concentration (62%), almost the growth concentration. However, a cross-section compositional profile over the heterostructure showed an inhomogeneous distribution of the indium. This is predictable from the composition fluctuation in the indium-containing alloys and the volatility (surface segregation) of As (In). On the other side, the optical investigation of InGaAs demonstrated an anomalous behavior of luminescence versus temperature, manifested by the S-shape feature. This trend stems from the potential fluctuation induced by the non-uniform distribution of indium. A numerical simulation was developed based on the localized state ensemble (LSE) model to well-reproduce this anomaly by giving the best fitting parameters and comparing them with those calculated using the semi-empirical models (Viña and Pässler). The results reported here will help in optimizing the epitaxy design of future InGaAs/InP and further studying its surface morphology and device performance.

Probabilistic stress and strain-life fatigue crack initiation models with mean stress effects and life-dependent scatter considering runouts

A powerful probabilistic framework is proposed to account for life-dependent data scatter in fatigue crack initiation (FCI) predictions considering mean stress effects. It is applicable to any stress, strain, or energy-based fatigue damage parameter (DP), as long as the logarithm of DP for a given FCI life Nf can be assumed to follow a three-parameter Weibull (W3P) distribution. The proposed approach, named P-DP-N, does not require the assumption of any particular statistical distribution for Nf, thus it can fit the shape of virtually any equation correlating DP and Nf. Hence, it can deal simultaneously with LCF, HCF and VHCF FCI data, considering mean stress effects and runout statistics. The approach deals with heteroscedasticity through a user-defined life-dependent scedastic function of Nf, allowing the consideration of variable data scatter in log–log scales. The P-DP-N performance is evaluated using the Walker Equivalent Strain (WES) equation proposed by the authors, which is generalized to explicitly consider fatigue limits. Procedures are proposed to calibrate both stress and strain-based versions of the deterministic WES-life FCI model, as well as to optimize the W3P parameters from the resulting P-WES-N probabilistic model, considering runout data when available. A compact computational implementation of the calibration routines is presented as well. The W3P-based P-WES-N probabilistic model is evaluated for 31 metallic alloy data sets from the literature that include non-zero mean stresses and at least twenty specimens each, totaling 1,498 uniaxial fatigue specimens, including 141 runouts. This comprehensive evaluation shows that the proposed probabilistic model is able to account for tensile and compressive mean stress effects, as well as to calibrate the usually observed increase in experimental scatter for longer FCI lives.

Causal, Bayesian, & non-parametric modeling of the SARS-CoV-2 viral load distribution vs. patient's age.

The viral load of patients infected with SARS-CoV-2 varies on logarithmic scales and possibly with age. Controversial claims have been made in the literature regarding whether the viral load distribution actually depends on the age of the patients. Such a dependence would have implications for the COVID-19 spreading mechanism, the age-dependent immune system reaction, and thus for policymaking. We hereby develop a method to analyze viral-load distribution data as a function of the patients’ age within a flexible, non-parametric, hierarchical, Bayesian, and causal model. The causal nature of the developed reconstruction additionally allows to test for bias in the data. This could be due to, e.g., bias in patient-testing and data collection or systematic errors in the measurement of the viral load. We perform these tests by calculating the Bayesian evidence for each implied possible causal direction. The possibility of testing for bias in data collection and identifying causal directions can be very useful in other contexts as well. For this reason we make our model freely available. When applied to publicly available age and SARS-CoV-2 viral load data, we find a statistically significant increase in the viral load with age, but only for one of the two analyzed datasets. If we consider this dataset, and based on the current understanding of viral load’s impact on patients’ infectivity, we expect a non-negligible difference in the infectivity of different age groups. This difference is nonetheless too small to justify considering any age group as noninfectious.

Evaluating the neutrophil-to-lymphocyte ratio as an indicator for early referral of patients with COVID-19 pneumonia to a high-care facility.

Early identification of patients at high risk of severe disease requiring referral and treatment at a high-care facility is imperative in the management of COVID-19 pneumonia in a limited-resource setting, as transfer of unstable patients can be detrimental. To examine the value of the neutrophil-to-lymphocyte ratio (NLR) calculated on admission to a healthcare facility as a predictor of the need for early referral to a high-care facility for further treatment. We designed a cohort analytical study of 198 patients with COVID-19 pneumonia admitted to the COVID-19 unit at Universitas Academic Hospital in Bloemfontein, South Africa, between 20 May and 30 September 2021. Of the 198 patients enrolled in the study, 134 (67.7%) were admitted to high care and 93 (46.9%) died. The median (interquartile range (IQR)) NLR measured on admission to the hospital was 8.09 (4.90 - 14.86), and the NLR ranged from 0.26 to 136.7. The admission NLR was statistically significantly higher in the high-care group v. the general ward group (p<0.001). After converting the NLR to log scale, to bring it closer to conditional normality, logistic regression analysis identified log NLR (odds ratio (OR) 4.089; 95% confidence interval (CI) 2.464 - 6.787; p<0.001) and age (OR 1.029; 95% CI 1.004 - 1.056; p=0.024) as significant in determining who will require high care. The area under the receiver operating characteristic curve for the combined model of NLR and age was 0.829 (95% CI 0.767 - 0.891). An NLR cut-off value of 7.5 (sensitivity 0.7462, specificity 0.7968) has been calculated as the optimal cut-off value to determine who will need high care. Admission log NLR and age were significant in determining who died (OR 2.067; 95% CI 1.404 - 3.045; p<0.001, and OR 1.043; 95% CI 1.018 - 1.068; p=0.001, respectively). The NLR measured on admission and age can be used to predict whether a patient with COVID-19 pneumonia will require high care.

Relation between sex and mortality after myocardial infarction in high-income and middle-income European countries

Abstract Background The relationship between female sex and cardiovascular mortality in myocardial infarction (MI) is controversial. Most available data are from high-income countries (HIC) where baseline risk is lower and revascularization procedures are more likely, so the generalizability to other populations is unclear. Purpose The main goal of this study was to unravel the relation between patient-specific revascularization through percutaneous coronary intervention (PCI) and mortality among women and men. Methods Data were drawn from the ISACS-Archives (NCT04008173) which includes a large cohort of patients enrolled in 6 European HIC (Croatia, Italy, Lithuania, Hungary, Romania, and United Kingdom) and 7 middle-income countries (MIC; Bosnia &amp; Herzegovina, Kosovo, Macedonia, Moldova, Montenegro, and Serbia). Participants were stratified by MI subtypes: STEMI and NSTEMI. The primary outcome was 30-day mortality. To yield unbiased sex estimates of the effects of MI on mortality we modeled covariates and outcomes by propensity score-based analytic methods. We calculated the women to men risk ratios (RRs) using weighting with estimates compared by test of interaction on the log scale. Results The cohort consisted of 22,087 patients with MI (30.2% women). Patient outcomes varied according to the subtype of MI. Females was associated with a greater excess risk of 30-day mortality in STEMI (RR: 1.94; 95% CI: 1.71–2.21) compared with NSTEMI (RR: 1.12; 95% CI: 0.95–1.50; P interaction &amp;lt;0.001). Coronary revascularization reduced the incidence of death among women and men in the overall population. Despite this, the primary outcome of 30-day mortality remained higher in women than men with STEMI (RR: 2.38; 95% CI: 2.00–2.82) whereas it was comparable across sexes in patients with NSTEMI (RR: 1.21; 95% CI: 0.79–1.83; P interaction=0.002). Sex differences in mortality from STEMI were more significant in MIC compared with HIC (RRs: 2.30; 95% CI: 1.98–2.68 vs. 1.36; 95% CI: 1.05–1.75; P interaction &amp;lt;0.001). The sex gap in mortality was mitigated by the use of revascularization therapy (RRs: 2.05; 95% CI: 1.68–2.50 in MIC vs. 2.17; 95% CI: 1.48–3.18 in HIC; P interaction=0.40) Conclusion Women presenting with STEMI have worse early mortality rates than their male counterparts in both HIC and MIC even in patients undergoing revascularization. By contrast, sex differences are attenuated or no longer apparent in NSTEMI. With no information on the type of MI on admission, sex differences in early outcomes are difficult to be fully understood. Funding Acknowledgement Type of funding sources: None.

Social vulnerability and cancer-related mortality among U.S. counties, 2013 to 2019.

162 Background: Substantial differences exist among US counties with regards to cancer-related mortality. Social determinants of health (SDOH) can predispose underserved communities to poor cancer outcomes. We investigated the impact of county-level social vulnerability on age-adjusted cancer mortality rates (AAMRs). Methods: We linked cancer-related deaths across US counties from 2013 to 2019 in the CDC WONDER database to county-level Social Vulnerability Index (SVI) data from the CDC/ATSDR. Scores for overall SVI and its 4 subcomponents (socioeconomic status; household composition and disability; minority status and language; housing type and transportation) were calculated using 15 SDOH attributes. These were presented as percentile rankings by county and classified into quartiles based on their distribution among US counties (1st [least vulnerable] = 0 - 0.25; 4th [most vulnerable = 0.75 - 1.00]). AAMRs per 100,000 individuals across US counties were compared between 1st and 4th SVI quartiles using robust linear regression models with a log scale. Results: There were 4,107,273 deaths with overall AAMR 173 per 100,000 individuals. Highest AAMRs were noted among older adults &gt; 65 years, men, non-Hispanic Black, and rural counties. AAMRs increased proportionally when moving from least to most vulnerable counties. Counties in 4th SVI quartile had 20% higher AAMRs compared to 1st SVI quartile (rate ratio; RR 1.08, 95% CI [1.08, 1.09], p &lt; 0.001). This was pronounced for ages 45-65 (42% increase; RR 1.21, 95% CI [1.12 – 1.24]), Hispanic race (26% increase; RR 1.11, 95% CI [1.06, 1.16]), and rural counties (21% increase; RR 1.17, 95% CI [1.15, 1.19]). Increase in AAMR between 1st and 4th SVI quartile from vulnerable socioeconomic status was most pronounced in rural counties (RR 1.17; 95% CI [1.15, 1.2]), women (RR 1.17; 95% CI [1.15, 1.2]) and ages 45-65 (RR 1.15; 95% CI [1.09, 1.14]). Vulnerable household composition/disability was most pronounced for rural residents (RR 1.12; 95% CI [1.09, 1.14]), and housing/transportation barriers for Hispanic individuals (RR 1.15; 95% CI [1.09, 1.21]). Conclusions: This study highlights the most socially vulnerable US counties have higher cancer mortality rates than the least vulnerable US counties. Furthermore, non-Hispanic blacks, older adults, and rural counties face highest risks of health inequities. Our findings inform ongoing congressional deliberations on transportation, telehealth, and rural infrastructure to achieve geographic parity.[Table: see text]

Metastability for expanding bubbles on a sticky substrate

We study the dynamical behavior of a one dimensional interface interacting with a sticky impenetrable substrate or wall. The interface is subject to two effects going in opposite directions. Contacts between the interface and the substrate are given an energetic bonus while an external force with constant intensity pulls the interface away from the wall. Our interface is modeled by the graph of a one-dimensional nearest-neighbor path on Z+, starting at 0 and ending at 0 after 2N steps, with the wall being the horizontal axis. At equilibrium each path ξ=(ξx)x=02N is given a probability proportional to λH(ξ)exp(σNA(ξ)), where H(ξ):=#{x:ξx=0} and A(ξ) is the area enclosed between the path ξ and the x-axis. We then consider the classical heat-bath dynamics which equilibrates the value of each ξx at a constant rate via corner-flip. Investigating the statics of the model, we derive the full phase diagram in λ and σ of this model, and identify the critical line which separates a localized phase where the pinning force sticks the interface to the wall and a delocalized one, for which the external force stabilizes ξ around a deterministic shape at a macroscopic distance of the wall. On the dynamical side, we identify a second critical line, which separates a rapidly mixing phase (for which the system mixes in polynomial time) to a slow phase where the mixing time grows exponentially. In this slowly mixing regime, we obtain a sharp estimate of the mixing time on the log scale, and provide evidences of a metastable behavior.

Prediction of flow regime boundary and pressure drop for hexagonal wire-wrapped rod bundles using artificial neural networks

This study used an artificial neural network (ANN) regression model in wire-wrapped fuel assemblies to estimate the transition-to-turbulence flow regime boundary (RebT) and friction factor. The ANN models were trained and validated using existing experimental datasets. The bundle dataset comprised several design parameters, such as the number of rods, rod diameter, wire diameter, lattice pitch, edge pitch, and wire helical pitch. The log–log scale Reynolds number and linearity characteristics of the friction coefficient were used to over-sample the friction factor in the laminar and turbulent regimes for resolving the data imbalance. Three-quarters of the entire dataset was used for training, while the remainder was used for validation. The Levenberg–Marquardt approach with the Gauss–Newton approximation for the Hessian of the training cost function was used for training the model. The number of hidden layers for RebT was selected based on the minimum validation error. The pin number effect was additionally considered for the friction factor while selecting the number of hidden layers. The ANN model predicted using the oversampled data set had a 50% reduction in the root mean square error (RMSE) than the model predicted using the original data set. Compared to previous correlations, the prediction of ANN models for the friction factor demonstrated significantly low errors (0.10% mean error and 7.36% RMSE of 142 bundle data).

Petro-seismic properties of Brazilian pre-salt carbonate reservoir: measurements and modeling at rock, log and seismic scales

Petro-seismic properties of Brazilian pre-salt carbonate reservoir: measurements and modeling at rock, log and seismic scales

Stellar Populations in type Ia supernova host galaxies at intermediate-high redshift: Star formation and metallicity enrichment histories

ABSTRACT We present a summary of our project that studies galaxies hosting type Ia supernova (SN Ia) at different redshifts. We present Gran Telescopio de Canarias (GTC) optical spectroscopy of six SN Ia host galaxies at redshift z ∼ 0.4–0.5. They are joined to a set of SN Ia host galaxies at intermediate-high redshift, which include galaxies from surveys SDSS and COSMOS. The final sample, after a selection of galaxy spectra in terms of signal-to-noise and other characteristics, consists of 680 galaxies with redshift in the range 0.04 &amp;lt; z &amp;lt; 1. We perform an inverse stellar population synthesis with the code fado to estimate the star formation and enrichment histories of this set of galaxies, simultaneously obtaining their mean stellar age and metallicity and stellar mass. After analysing the correlations among these characteristics, we look for possible dependencies of the Hubble diagram residuals and supernova features (luminosity, colour and strength parameter) on these stellar parameters. We find that the Hubble residuals show a clear dependence on the stellar metallicity weighted by mass with a slope of −0.061 mag dex−1, when represented in logarithmic scale, log 〈ZM/Z⊙〉. This result supports our previous findings obtained from gas oxygen abundances for local and SDSS-survey galaxies. Comparing with other works from the literature that also use the stellar metallicity, we find a similar value, but with more precision and a better significance (2.08 versus ∼ 1.1), due to the higher number of objects and wider range of redshift of our sample.

Is cell segregation like oil and water: Asymptotic versus transitory regime.

Understanding the segregation of cells is crucial to answer questions about tissue formation in embryos or tumor progression. Steinberg proposed that separation of cells can be compared to the separation of two liquids. Such a separation is well described by the Cahn-Hilliard (CH) equations and the segregation indices exhibit an algebraic decay with exponent 1/3 with respect to time. Similar exponents are also observed in cell-based models. However, the scaling behavior in these numerical models is usually only examined in the asymptotic regime and these models have not been directly applied to actual cell segregation data. In contrast, experimental data also reveals other scaling exponents and even slow logarithmic scaling laws. These discrepancies are commonly attributed to the effects of collective motion or velocity-dependent interactions. By calibrating a 2D cellular automaton (CA) model which efficiently implements a dynamic variant of the differential adhesion hypothesis to 2D experimental data from Méhes et al., we reproduce the biological cell segregation experiments with just adhesive forces. The segregation in the cellular automaton model follows a logarithmic scaling initially, which is in contrast to the proposed algebraic scaling with exponent 1/3. However, within the less than two orders of magnitudes in time which are observable in the experiments, a logarithmic scaling may appear as a pseudo-algebraic scaling. In particular, we demonstrate that the cellular automaton model can exhibit a range of exponents ≤1/3 for such a pseudo-algebraic scaling. Moreover, the time span of the experiment falls into the transitory regime of the cellular automaton rather than the asymptotic one. We additionally develop a method for the calibration of the 2D Cahn-Hilliard model and find a match with experimental data within the transitory regime of the Cahn-Hilliard model with exponent 1/4. On the one hand this demonstrates that the transitory behavior is relevant for the experiment rather than the asymptotic one. On the other hand this corroborates the ambiguity of the scaling behavior, when segregation processes can be only observed on short time spans.