Comparison between the Torquato-Rintoul theory of the interface effect in composite media and elementary results

We show that the interface effect on the properties of composite media recently proposed by Torquato and Rintoul (TR) [Phys. Rev. Lett. 75, 4067 (1995)] is in fact elementary, and follows directly from taking the limit in the dipolar polarizability of a coated sphere: the TR ``critical values'' are simply those that make the dipolar polarizability vanish. Furthermore, the new bounds developed by TR either coincide with the Clausius-Mossotti (CM) relation or provide poor estimates. Finally, we show that the new bounds of TR do not agree particularly well with the original experimental data that they quote.Comment: 13 pages, Revtex, 8 Postscript figure

Estimating ecosystem maximum light use efficiency based on the water use efficiency principle

Light use efficiency (LUE) defines the vegetation efficiency of converting radiative energy into biochemical energy through photosynthesis. Estimating the maximum LUE (ϵ max) is critical yet challenging for quantifying gross primary production (GPP) using LUE-based models. This study describes an analytical method for estimating ϵ max based on water use efficiency (WUE) as determined by plant water use and carbon gain. Unlike other complex parameterization schemes, this WUE-based method is simple and requires four variables relatively easy to acquire. The WUE-based ϵ max estimates compare favorably well with values based on traditional curve fitting method and that reported in the literature, and clearly distinguished ϵ max between C3 (1.48 0.33 {g C M}}{J}}{ - 1}) and C4 (2.63 0.21 {g C M}}{J}}{-1}}) dominated ecosystems. The range in ϵ max estimates was narrow across different years and sites within a biome. The WUE-based ϵ max estimate is theoretically constrained by vegetation water use and can be directly incorporated into LUE models for GPP estimation across ecosystems

A robust Gauss-Newton algorithm for the optimization of hydrological models: benchmarking against industry-standard algorithms

Optimization of model parameters is a ubiquitous task in hydrological and environmental modeling. Currently, the environmental modeling community tends to favor evolutionary techniques over classical Newton‐type methods, in the light of the geometrically problematic features of objective functions, such as multiple optima and general nonsmoothness. The companion paper (Qin et al., 2018, https://doi.org/10.1029/2017WR022488) introduced the robust Gauss‐Newton (RGN) algorithm, an enhanced version of the standard Gauss‐Newton algorithm that employs several heuristics to enhance its explorative abilities and perform robustly even for problematic objective functions. This paper focuses on benchmarking the RGN algorithm against three optimization algorithms generally accepted as “best practice” in the hydrological community, namely, the Levenberg‐Marquardt algorithm, the shuffled complex evolution (SCE) search (with 2 and 10 complexes), and the dynamically dimensioned search (DDS). The empirical case studies include four conceptual hydrological models and three catchments. Empirical results indicate that, on average, RGN is 2–3 times more efficient than SCE (2 complexes) by achieving comparable robustness at a lower cost, 7–9 times more efficient than SCE (10 complexes) by trading off some speed to more than compensate for a somewhat lower robustness, 5–7 times more efficient than Levenberg‐Marquardt by achieving higher robustness at a moderate additional cost, and 12–26 times more efficient than DDS in terms of robustness‐per‐fixed‐cost. A detailed analysis of performance in terms of reliability and cost is provided. Overall, the RGN algorithm is an attractive option for the calibration of hydrological models, and we recommend further investigation of its benefits for broader types of optimization problems.Youwei Qin, Dmitri Kavetski, George Kuczer

Test of the Kolmogorov-Johnson-Mehl-Avrami picture of metastable decay in a model with microscopic dynamics

The Kolmogorov-Johnson-Mehl-Avrami (KJMA) theory for the time evolution of the order parameter in systems undergoing first-order phase transformations has been extended by Sekimoto to the level of two-point correlation functions. Here, this extended KJMA theory is applied to a kinetic Ising lattice-gas model, in which the elementary kinetic processes act on microscopic length and time scales. The theoretical framework is used to analyze data from extensive Monte Carlo simulations. The theory is inherently a mesoscopic continuum picture, and in principle it requires a large separation between the microscopic scales and the mesoscopic scales characteristic of the evolving two-phase structure. Nevertheless, we find excellent quantitative agreement with the simulations in a large parameter regime, extending remarkably far towards strong fields (large supersaturations) and correspondingly small nucleation barriers. The original KJMA theory permits direct measurement of the order parameter in the metastable phase, and using the extension to correlation functions one can also perform separate measurements of the nucleation rate and the average velocity of the convoluted interface between the metastable and stable phase regions. The values obtained for all three quantities are verified by other theoretical and computational methods. As these quantities are often difficult to measure directly during a process of phase transformation, data analysis using the extended KJMA theory may provide a useful experimental alternative.Comment: RevTex, 21 pages including 14 ps figures. Submitted to Phys. Rev. B. One misprint corrected in Eq.(C1

Structure-property correlations in model composite materials

We investigate the effective properties (conductivity, diffusivity and elastic moduli) of model random composite media derived from Gaussian random fields and overlapping hollow spheres. The morphologies generated in the models exhibit low percolation thresholds and give a realistic representation of the complex microstructure observed in many classes of composites. The statistical correlation functions of the models are derived and used to evaluate rigorous bounds on each property. Simulation of the effective conductivity is used to demonstrate the applicability of the bounds. The key morphological features which effect composite properties are discussed

Transient and sustained incentive effects on electrophysiological indices of cognitive control in younger and older adults

Preparing for upcoming events, separating task-relevant from task-irrelevant information and efficiently responding to stimuli all require cognitive control. The adaptive recruitment of cognitive control depends on activity in the dopaminergic reward system as well as the frontoparietal control network. In healthy aging, dopaminergic neuromodulation is reduced, resulting in altered incentive-based recruitment of control mechanisms. In the present study, younger adults (18–28 years) and healthy older adults (66–89 years) completed an incentivized flanker task that included gain, loss, and neutral trials. Event-related potentials (ERPs) were recorded at the time of incentive cue and target presentation. We examined the contingent negative variation (CNV), implicated in stimulus anticipation and response preparation, as well as the P3, which is involved in the evaluation of visual stimuli. Both younger and older adults showed transient incentive-based modulation of CNV. Critically, cue-locked and target-locked P3s were influenced by transient and sustained effects of incentives in younger adults, while such modulation was limited to a sustained effect of gain incentives on cue-P3 in older adults. Overall, these findings are in line with an age-related reduction in the flexible recruitment of preparatory and target-related cognitive control processes in the presence of motivational incentives

Sintering and mechanical properties of β‐SiC powder obtained from waste tires

Plasma synthesized SiC powder obtained from quartz and carbonaceous residue of waste tires was successfully sintered at 1925 ℃ by pressureless liquid-phase method using yttria and alumina as sintering aids (T-SiC). Comparison with sintered SiC obtained from commercial powder (C-SiC) put in evidence of similar sintered density (98%T.D.), but much finer microstructure of T-SiC than that of C-SiC. T-SiC also showed higher flexural strength than C-SiC both at room temperature (508 vs. 458 MPa) and at 1500 ℃ (280 vs. 171 MPa). Difference in liquid phase was responsible for the differences in hardness and fracture toughness. The high value of the Young's modulus of T-SiC (427 MPa) confirmed the high degree of sinterability of this powder and that it can be a promising candidate for structural applications with high added value. © 2016, The Author(s)

Digenic inheritance involving a muscle-specific protein kinase and the giant titin protein causes a skeletal muscle myopathy

\ua9 The Author(s) 2024.In digenic inheritance, pathogenic variants in two genes must be inherited together to cause disease. Only very few examples of digenic inheritance have been described in the neuromuscular disease field. Here we show that predicted deleterious variants in SRPK3, encoding the X-linked serine/argenine protein kinase 3, lead to a progressive early onset skeletal muscle myopathy only when in combination with heterozygous variants in the TTN gene. The co-occurrence of predicted deleterious SRPK3/TTN variants was not seen among 76,702 healthy male individuals, and statistical modeling strongly supported digenic inheritance as the best-fitting model. Furthermore, double-mutant zebrafish (srpk3−/−; ttn.1+/−) replicated the myopathic phenotype and showed myofibrillar disorganization. Transcriptome data suggest that the interaction of srpk3 and ttn.1 in zebrafish occurs at a post-transcriptional level. We propose that digenic inheritance of deleterious changes impacting both the protein kinase SRPK3 and the giant muscle protein titin causes a skeletal myopathy and might serve as a model for other genetic diseases