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The authors study small disturbances to the periodic, plane Couette flow in the 3D incompressible Navier-Stokes equations at high Reynolds number Re. They prove that for sufficiently regular initial data of size $\\epsilon \\leq c_0\\mathbf {Re}^-1$ for some universal $c_0 > 0$, the solution is global, remains within $O(c_0)$ of the Couette flow in $L^2$, and returns to the Couette flow as $t \\rightarrow \\infty $. For times $t \\gtrsim \\mathbf {Re}^1/3$, the streamwise dependence is damped by a mixing-enhanced dissipation effect and the solution is rapidly attracted to the class of \"2.5 dimensional\" streamwise-independent solutions referred to as streaks.

Unmanned aerial vehicle laser scanning (UAVLS) systems present a relatively new means of remote sensing and are increasingly applied in the field of forest ecology and management. However, one of the most essential parameters in forest inventory, tree diameter at breast height (DBH), cannot be directly extracted from aerial point cloud data due to the limitations of scanning angle and canopy obstruction. Therefore, in this study DBH-UAVLS point cloud estimation models were established using a generalized nonlinear mixed-effects (NLME) model. The experiments were conducted using Larix olgensis as the subject species, and a total of 8364 correctly delineated trees from UAVLS data within 118 plots across 11 sites were used for DBH modeling. Both tree- and plot-level metrics were obtained using light detection and ranging (LiDAR) and were used as the models’ independent predictors. The results indicated that the addition of site-level random effects significantly improved the model fitting. Compared with nonparametric modeling approaches (random forest and k-nearest neighbors) and uni- or multivariable weighted nonlinear least square regression through leave-one-site-out cross-validation, the NLME model with local calibration achieved the lowest root mean square error (RMSE) values (1.94 cm) and the most stable prediction across different sites. Using the site in a random-effects model improved the transferability of LiDAR-based DBH estimation. The best linear unbiased predictor (BLUP), used to conduct local model calibration, led to an improvement in the models’ performance as the number of field measurements increased. The research provides a baseline for unmanned aerial vehicle (UAV) small-scale forest inventories and might be a reasonable alternative for operational forestry.

Study objectivesTLD-1 is a novel pegylated liposomal doxorubicin (PLD) formulation aiming to optimise the PLD efficacy-toxicity ratio. We aimed to characterise TLD-1’s population pharmacokinetics using non-compartmental analysis and nonlinear mixed-effects modelling.MethodsThe PK of TLD-1 was analysed by performing a non-compartmental analysis of longitudinal doxorubicin plasma concentration measurements obtained from a clinical trial in 30 patients with advanced solid tumours across a 4.5-fold dose range. Furthermore, a joint parent-metabolite PK model of doxorubicinentrapped, doxorubicinfree, and metabolite doxorubicinol was developed. Interindividual and interoccasion variability around the typical PK parameters and potential covariates to explain parts of this variability were explored.ResultsMedians ± standard deviations of dose-normalised doxorubicinentrapped+free Cmax and AUC0−∞ were 0.342 ± 0.134 mg/L and 40.1 ± 18.9 mg·h/L, respectively. The median half-life (95 h) was 23.5 h longer than the half-life of currently marketed PLD. The novel joint parent-metabolite model comprised a one-compartment model with linear release (doxorubicinentrapped), a two-compartment model with linear elimination (doxorubicinfree), and a one-compartment model with linear elimination for doxorubicinol. Body surface area on the volumes of distribution for free doxorubicin was the only significant covariate.ConclusionThe population PK of TLD-1, including its release and main metabolite, were successfully characterised using non-compartmental and compartmental analyses. Based on its long half-life, TLD-1 presents a promising candidate for further clinical development. The PK characteristics form the basis to investigate TLD-1 exposure-response (i.e., clinical efficacy) and exposure-toxicity relationships in the future. Once such relationships have been established, the developed population PK model can be further used in model-informed precision dosing strategies.Clinical trial registrationClinicalTrials.gov–NCT03387917–January 2, 2018

In this paper, an advanced electrothermal simulation strategy is applied to a 3.3 kV silicon carbide MOSFET power module. The approach is based on a full circuital representation of the module, where use is made of the thermal equivalent of the Ohm’s law. The individual transistors are described with subcircuits, while the dynamic power-temperature feedback is accounted for through an equivalent thermal network enriched with controlled sources enabling nonlinear thermal effects. A synchronous step-up DC-DC converter and a single-phase inverter, both incorporating the aforementioned power module, are simulated. Good accuracy was ensured by considering electromagnetic effects due to parasitics, which were experimentally extracted in a preliminary stage. Low CPU times are needed, and no convergence issues are encountered in spite of the high switching frequencies. The impact of some key parameters is effortlessly quantified. The analysis witnesses the efficiency and versatility of the approach, and suggests its adoption for design, analysis, and synthesis of high-frequency power converters in wide-band-gap semiconductor technology.

Lithium niobate on insulator (LNOI) combines a variety of optoelectronic properties and can meet practical performance requirements that are uncommon in optoelectronic materials. This review introduces the fundamentals and the photonic device concepts that arise from the LNOI materials platform. Firstly, the nonlinear optical response of LNOI is presented, including birefringent phase matching (BPM), modal phase matching (MPM), and quasi-phase matching (QPM). The tunable properties are also introduced, including electro-optical (EO), thermo-optical (TO), and acousto-optical (AO) effects. The structures of nonlinear optical devices, such as ridge waveguides (including periodically polarized inversion waveguides), Mach–Zehnder interferometer (MZI) modulators and micro-resonators (such as disks and rings) are demonstrated. Finally, the future of LNOI devices is discussed. In the already mature and developed optoelectronic material systems, it is rare to find one particular material system supporting so many basic optical components, photonic devices and optoelectronic devices as LNOI does in the field of integrated photonic chips.

Tree age (AGE) and stocking degree (P) strongly influence tree shape, but their effects have been neglected in most tree profile equations. In addition, data used to build traditional tree profile equations usually do not meet the statistical requirements of independence and identical distribution of observations. Therefore, our main objectives were to present a method to improve taper equations with measurements easily collected in tree inventories (age, stocking degree) and also improve the statistical accuracy of those equations by selecting parameters with a more rigorous way than what is traditionally being done. We evaluated the effects of incorporating age and stocking degree as regressors in tree profile equations selected among 30 candidate foundation equations and parameterized with data from 1858 Larix gmelinii (Rupr.) trees growing in the northern China. We used nonlinear mixed-effects models to minimize statistical problems present when building traditional tree profile equations: lack of independence and identical distribution of observations, random effects related to individual trees. Equations incorporating age and stocking degree significantly improved their accuracy. When the equation parameters were estimated with mixed-effects models containing exponential variance functions and accounting for non-independence of observations from the same tree, diameters at any height along the tree bole were more accurately estimated. We demonstrate a new methodology to build more accurate tree profile equations that could support better economic valorization of timber and improve calculations of carbon flows in forests, not only for natural L. gmelinii forest but for other species growing in dense natural stands around the globe.

This is the second in a pair of works which study small disturbances to the plane, periodic 3D Couette flow in the incompressible Navier-Stokes equations at high Reynolds number

Ecoregion-based height-diameter models were developed in the present study for Scots pine ( Pinus sylvestris L.) stands in Turkiye and included several ecological factors derived from a pre-existing ecoregional classification system. The data were obtained from 2831 sample trees in 292 sample plots. Ten generalized height–diameter models were developed, and the best model (HD10) was selected according to statistical criteria. Then, nonlinear mixed-effects modeling was applied to the best model. The R 2 for the generalized height‒diameter model (Richards function) modified by Sharma and Parton is 0.951, and the final model included number of trees, dominant height, and diameter at breast height, with a random parameter associated with each ecoregion attached to the inverse of the mean basal area. The full model predictions using the nonlinear mixed-effects model and the reduced model (HD10) predictions were compared using the nonlinear sum of extra squares test, which revealed significant differences between ecoregions; ecoregion-based height–diameter models were thus found to be suitable to use. In addition, using these models in appropriate ecoregions was very important for achieving reliable predictions with low prediction errors.

Key messageIncluding individual-tree competition indices as predictor variables could significantly improve the performance of crown width and length models for Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.). Moreover, distance-dependent competition indices are superior to distance-independent ones when modeling crown width and length. Compared with crown width and length basic models with optimum competition indices, the performance of the two-level nonlinear mixed-effects models improved.ContextCrown width (CW) and crown length (CL) are two important variables widely included as the predictors in growth and yield models that contribute to forest management strategies.AimsIndividual-tree crown width and length models were developed with data from 1498 Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) trees in 16 sample plots located at Jiangle County, Fujian Province, southeastern China. Two hypotheses were proposed: (1) including individual-tree competition indices as predictor variables could significantly improve performance of both the CW—DBH and CL—DBH models; and (2) the distance-dependent competition indices would perform better than distance-independent ones.MethodsThe models were fitted using generalized linear least squares or generalized nonlinear least squares methods. In addition, to prevent correlations between observations from the same sampling unit, we introduced age classes and sample plots as random effects to develop the two-level nonlinear mixed-effects models.ResultsWe found introduction of competition indices could significantly improve the performance of the CW—DBH and CL—DBH models. The distance-dependent competition index (i.e., competitor to subject tree distance) performed best in modeling the crown width and length models. Compared with crown width and length basic models with optimum competition indices, the performance of the two-level nonlinear mixed-effects models was significantly better.ConclusionThe two hypotheses were accepted. We hope these models will contribute to scientific management of Chinese fir plantations.

Key messageHere, we present a workflow for determining the optimal tree height model and calibration design for forests affected to varying degrees by anthropogenic disturbance. For mixed Araucaria-Nothofagus forests, tree height predictions in newly surveyed stands are most accurate and effective when the height of up to five random trees is measured to recalibrate predefined nonlinear mixed-effects models.ContextAraucaria-Nothofagus forests in Chile are affected by anthropogenic disturbances such as intentional forest fires, grazing, and seed harvesting, causing forest structure to become more heterogeneous. This also challenges tree height predictions, which are required for yield estimations, carbon accounting, and forest management, since height measurements of standing trees are often considered too costly, difficult, and imprecise.AimsHow does the structure of these forests vary by different levels of anthropogenic disturbance? Which models for estimating tree height of Araucaria araucana and Nothofagus pumilio are most reliable and generally usable? And considering their application in stands they have not been fitted to, which calibration design is optimal for these models?MethodsTwelve stands were surveyed and classified into four different intensities of anthropogenic disturbance. In 25 to 36 plots per stand, horizontal point sampling measurements of stem diameter as well as of height of selected trees were carried out. Different quantitative stand-level properties were calculated to determine forest structure, which was compared among stands by cluster analysis. To identify the optimal height-diameter (H–D) model, simple models including diameter only as well as generalized models including stand variables were tested, each additionally extended by a nonlinear mixed-effects (NLME) modeling framework accounting for nested and random effects. To further determine tree height in new stands, the optimal model calibration design was identified involving the empirical best unbiased predictor technique.ResultsForest structure greatly varied among stands affected by different levels of anthropogenic disturbance, which challenged the development of tree height prediction models. Of all the simple H–D models considered, the Gompertz model was the best for A. araucana and the Näslund model for N. pumilio. The models progressively improved by adding stand variables and using NLME techniques. However, our final model comparisons indicate that a calibrated simple NLME model without stand variables should be preferred. It was further found that the optimal calibration design is to use five randomly selected trees.ConclusionAlthough anthropogenic disturbances can have a complex effect on height-diameter relationships, the same H–D model can be used for stands representing different anthropogenic disturbance levels and recalibrated by cost-effective measurements.