Mechanistic Model For Prediction Research Articles

Real-time bone sawing interaction in orthopedic surgical simulation based on the volumetric object

Bone sawing is widely used for mandibular angle reduction. In this paper, we develop a surgical simulator for mandibular angle reduction with real-time collision detection, bone reconstruction and force haptic. A volume-based model was organized following the CT or MRI image sequence arrangement. The surgical instrument was simplified into two triangles in geometric model. Then, a new volume-based collision detection method was used to meet the real-time requirements of the simulator. Currently, most of the bone sawing operations regarded the swept surface as the real cut surface of bone. Due to the high-speed reciprocating of the bone saw operation, we innovatively used Marching Cubes Method for the real-time reconstruction of the bone internal sawing part and provided the users with a fine cutting surface. In addition, to obtain a well virtual effect, a simplified bone removal and reconstruction method is carried out to implement the real-time topological changing of the mandibular surface. This paper presents a mechanistic model for prediction of the force during bone sawing, and the simulated force is similar to the measured force in real surgery. Eventually, we realized the high quality visual rendering and tactile rendering, the refresh rate of the force reaches 1000 Hz, and visual refresh frequency up to 30 Hz. To validate the effectiveness of the system, some experiments of simulator evaluation based on the patient-specific data was constructed. Results shown that the virtual orthopedic surgical simulation system can provide inexperienced interns and students with a low-cost, repeatable surgical training platform.

A review of internal corrosion mechanism and experimental study for pipelines based on multiphase flow

AbstractThe internal corrosion of pipelines in the petroleum industry is highly risky, and induced pipeline cracking may give rise to potential injury to personnel and environmental issues. The oil-water two-phase flow and the oil-gas-water three-phase flow are often observed in gathering and transportation pipelines. It is generally accepted that corrosion is induced by the presence of water, although it is a complex hydrodynamic process in which the material is removed from the pipeline due to physicochemical reactions. Hence, it is necessary to determine the key parameters that dominate the corrosion phenomena and how they can be modeled. As the water phase that wets the steel surface determines the initiation of corrosion, several aspects are widely discussed here, such as corrosive medium, phase inversion, water-wetting behavior, the entrainment of water, and the wettability of steel, to explain the corrosion mechanism of multiphase flow and correlation with the corrosion behavior. Of course, empirical and mechanistic models for corrosion prediction in pipelines are discussed. Also, the mostly applied techniques of identifying flow patterns and attaining related parameters in experiments for the evaluation of the corrosiveness of oil-brine mixtures are introduced. Further studies must be undertaken to expand the knowledge of corrosion and find applicable models for corrosion damage prediction and prevention.

Incorporation of lysosomal sequestration in the mechanistic model for prediction of tissue distribution of basic drugs

The prediction of tissue-to-plasma water partition coefficients (Kpu) from in vitro and in silico data using the tissue-composition based model (Rodgers & Rowland, J Pharm Sci. 2005, 94(6):1237–48.) is well established. However, distribution of basic drugs, in particular into lysosome-rich lung tissue, tends to be under-predicted by this approach. The aim of this study was to develop an extended mechanistic model for the prediction of Kpu which accounts for lysosomal sequestration and the contribution of different cell types in the tissue of interest. The extended model is based on compound-specific physicochemical properties and tissue composition data to describe drug ionization, distribution into tissue water and drug binding to neutral lipids, neutral phospholipids and acidic phospholipids in tissues, including lysosomes. Physiological data on the types of cells contributing to lung, kidney and liver, their lysosomal content and lysosomal pH were collated from the literature. The predictive power of the extended mechanistic model was evaluated using a dataset of 28 basic drugs (pKa≥7.8, 17 β-blockers, 11 structurally diverse drugs) for which experimentally determined Kpu data in rat tissue have been reported. Accounting for the lysosomal sequestration in the extended mechanistic model improved the accuracy of Kpu predictions in lung compared to the original Rodgers model (56% drugs within 2-fold or 88% within 3-fold of observed values). Reduction in the extent of Kpu under-prediction was also evident in liver and kidney. However, consideration of lysosomal sequestration increased the occurrence of over-predictions, yielding overall comparable model performances for kidney and liver, with 68% and 54% of Kpu values within 2-fold error, respectively. High lysosomal concentration ratios relative to cytosol (>1000-fold) were predicted for the drugs investigated; the extent differed depending on the lysosomal pH and concentration of acidic phospholipids among cell types. Despite this extensive lysosomal sequestration in the individual cells types, the maximal change in the overall predicted tissue Kpu was <3-fold for lysosome-rich tissues investigated here. Accounting for the variability in cellular physiological model input parameters, in particular lysosomal pH and fraction of the cellular volume occupied by the lysosomes, only partially explained discrepancies between observed and predicted Kpu data in the lung. Improved understanding of the system properties, e.g., cell/organelle composition is required to support further development of mechanistic equations for the prediction of drug tissue distribution. Application of this revised mechanistic model is recommended for prediction of Kpu in lysosome-rich tissue to facilitate the advancement of physiologically-based prediction of volume of distribution and drug exposure in the tissues.

A mechanistic model for prediction of three-phase flow in petroleum reservoirs

Multiphase flow in the porous media is of great interest for many engineering fields such as underground oil and gas reservoirs, environmental process (e.g. carbon dioxide (CO2) geological storage) and underground water resources remediation. Modelling of these process requires relative permeability (kr) of each fluid as a function of the fluid saturation. The experimental measurement of the three-phase relative permeability is much more complex and time consuming process than the two-phase relative permeability. Hence, many correlations have been proposed in the oil industry for the calculation of the three-phase relative permeability using two-phase kr data. However, most of the existing three-phase models ignore the physical mechanism underlying the multiphase flow in the porous media.In this study, a novel mechanistic model is proposed to predict the three-phase relative permeability of the oil, water and gas in the petroleum reservoir (i.e. porous rock). The new idea is that the interaction between various fluids (i.e. oil, water and gas) and also the fluid saturation distribution are somehow considered in the estimation of the relative permeability. For this purpose, a new parameter named characteristic coefficient is introduced in the model. This parameter reflects the contribution of each fluid in controlling the flow of the other fluids. In other words, this factor is net impact of the various rock and fluid parameters (e.g. surface tension between fluids, wettability and saturation distribution) that all influence the flow in the porous media. This idea is taken from the glass-micro-model experiment that visualises the mechanism underlying the flow at the pore scale. Another feature of this method is that, at least one set of experimental three-phase kr data is required to tune the characteristic coefficients. The estimated characteristic factors can then be employed to predict the three-phase relative permeability for the other saturation path.The model is successfully validated against the experimentally measured three-phase relative permeability data.

Assessment of inhibitory effects on major human cytochrome P450 enzymes by spasmolytics used in the treatment of overactive bladder syndrome.

The objective of this study was to examine the inhibitory potential of darifenacin, fesoterodine, oxybutynin, propiverine, solifenacin, tolterodine and trospium chloride on the seven major human cytochrome P450 enzymes (CYP) by using a standardized and validated seven-in-one cytochrome P450 cocktail inhibition assay. An in vitro cocktail of seven highly selective probe substrates was incubated with human liver microsomes and varying concentrations of the seven test compounds. The major metabolites of the probe substrates were simultaneously analysed using a validated liquid chromatography tandem mass spectrometry (LC-MS/MS) method. Enzyme kinetics were estimated by determining IC50 and Ki values via nonlinear regression. Obtained Ki values were used for predictions of potential clinical impact of the inhibition using a static mechanistic prediction model. In this study, 49 IC50 experiments were conducted. In six cases, IC50 values lower than the calculated threshold for drug-drug interactions (DDIs) in the gut wall were observed. In these cases, no increase in inhibition was determined after a 30 min preincubation. Considering a typical dosing regimen and applying the obtained Ki values of 0.72 µM (darifenacin, 15 mg daily) and 7.2 µM [propiverine, 30 mg daily, immediate release (IR)] for the inhibition of CYP2D6 yielded a predicted 1.9-fold and 1.4-fold increase in the area under the curve (AUC) of debrisoquine (CYP2D6 substrate), respectively. Due to the inhibition of the particular intestinal CYP3A4, the obtained Ki values of 14 µM of propiverine (30 mg daily, IR) resulted in a predicted doubling of the AUC for midazolam (CYP3A4 substrate). In vitro/in vivo extrapolation based on pharmacokinetic data and the conducted screening experiments yielded similar effects of darifenacin on CYP2D6 and propiverine on CYP3A4 as obtained in separately conducted in vivo DDI studies. As a novel finding, propiverine was identified to potentially inhibit CYP2D6 at clinically occurring concentrations.

The linkage between nutrient supply, intracellular enzyme abundances and bacterial growth: New evidences from the central carbon metabolism of Corynebacterium glutamicum

Corynebacterium glutamicum serves as important production host for small molecular compounds that are derived from precursor molecules of the central carbon metabolism. It is therefore a well-studied model organism of industrial biotechnology. However, a deeper understanding of the regulatory principles underlying the synthesis of central metabolic enzymes under different environmental conditions as well as its impact on cell growth is still missing. We studied enzyme abundances in C. glutamicum in response to growth on: (i) one limiting carbon source by sampling chemostat and fed-batch cultivations and (ii) changing carbon sources provided in excess by sampling batch cultivations. The targeted quantification of 20 central metabolic enzymes by isotope dilution mass spectrometry revealed that cells maintain stable enzyme concentrations when grown on d-glucose as single carbon and energy source and, most importantly, independent of its availability. By contrast, switching from d-glucose to d-fructose, d-mannose, d-arabitol, acetate, l-lactate or l-glutamate results in highly specific enzyme regulation patterns that can partly be explained by the activity of known transcriptional regulators. Based on these experimental results we propose a simple framework for modeling cell population growth as a nested function of nutrient supply and intracellular enzyme abundances. In summary, our study extends the basis for the formulation of predictive mechanistic models of bacterial growth, applicable in industrial bioprocess development.

A Mechanistic Model for Prediction of Cutting Parameters in Micro-Scale Milling

While down-scaling of micro milling process is similar to the conventional process, there are specific issues that differ from macro machining due to higher ratios of feed per tooth to tool radius and tool run-out to tool diameter, size-effect, minimum chip thickness, elastic-plastic deformation, microstructure effects, etc. One of the challenges in micro machining is attaining accurate and reliable machining parameters, which can reduce tool wear and breakage to achieve higher productivity and quality at a lower cost. Therefore, this paper presents a new mechanistic model for predicting the precise process parameters considering material properties and principles of micro-milling under various cutting conditions. The proposed model also takes into account the nonlinearity and dynamics of minimum chip-thickness, micro-milling cutting forces considering cutting, as well as edge and damping coefficients into. The predicted stability lobes and the stability limits from experiments are in sufficient agreement. The research of micro-scale milling parameters is significant to improve the precision of machined parts, reduce the wear and tear of the micro-milling blade and extend the life of micro-tools.

Development of a mechanistic model for prediction of CO2 capture from gas mixtures by amine solutions in porous membranes.

A mechanistic model was developed in order to predict capture and removal of CO2 from air using membrane technology. The considered membrane was a hollow-fiber contactor module in which gas mixture containing CO2 was assumed as feed while 2-amino-2-metyl-1-propanol (AMP) was used as an absorbent. The mechanistic model was developed according to transport phenomena taking into account mass transfer and chemical reaction between CO2 and amine in the contactor module. The main aim of modeling was to track the composition and flux of CO2 and AMP in the membrane module for process optimization. For modeling of the process, the governing equations were computed using finite element approach in which the whole model domain was discretized into small cells. To confirm the simulation findings, model outcomes were compared with experimental data and good consistency was revealed. The results showed that increasing temperature of AMP solution increases CO2 removal in the hollow-fiber membrane contactor.

A mechanistic model for embryo size prediction at boiling incipience: ‘Work of formation’ based approach

The initial size of the embryo, which is formed at the inception of boiling, plays a vital role in the accurate prediction of component scale wall boiling phenomenon. Embryo size predictions are typically calculated using the classical theory of nucleation. However, in recent times, the predictive capability of this theory was found to have limitations. Hence, there is need for a more fundamental and mechanistic model to overcome some of the drawbacks. In this paper, we propose a ‘work of formation’ based model for the embryo formation. This model is mechanistic and includes a Van der Waals based real gas treatment for the vapour. It also incorporates Lewins surface tension model that is a function of the boiling-nucleus size. The present model also accounts for the boiling occurrence in the presence of undissolved nanobubbles on the surface. The embryo formation model has been extensively tested for both low and high pressures, horizontal and vertical test section orientation, and for different surfaces and fluids. The energy required for the embryo formation was found to be higher, when the initial gas bubble is intact compared to when the gas bubble diffuses into the embryo. Some of the contradictory claims on the suitability of classical theory of nucleation to nanosurfaces have been tested. From the present embryo formation model, the physics of nucleation such as, the effect of pressure fluctuations and energy dissipation mechanisms involved in the formation is explained.

Evaporation suppression from reservoirs using floating covers: Lab scale wind-tunnel observations and mechanistic model predictions

Evaporation suppression from reservoirs using floating covers: Lab scale wind-tunnel observations and mechanistic model predictions

State-of-the-art overview of pipeline steel corrosion in impure dense CO2 for CCS transportation: mechanisms and models

ABSTRACTThis work reviews the existing open literature concerned with pipeline steel corrosion in CO2-rich phase with impurities for carbon capture and storage purpose. The intent of this review was to provide information on the corrosion mechanisms, which is crucial for establishing the mechanistic prediction models. The primary focus was placed on key affecting parameters and their corresponding mechanisms, while the corrosion control strategies and research prospects are also discussed. This review covers the effects of: impurities, pressure, temperature, flow, exposure time, product layers, and steel chemistry. The influences of flow dynamics, amines, sulphur, and solids that had received little systematic attention need to be further addressed. Contradictory conclusions regarding the influence of H2O and O2 on the corrosion rates should be re-evaluated. The localised corrosion and cathodic reaction mechanisms also require further investigation, especially under synergistic conditions with multiple impurities.

Fortune favours the brave: Movement responses shape demographic dynamics in strongly competing populations

Animal movement is a key mechanism for shaping population dynamics. The effect of interactions between competing animals on a population's survival has been studied for many decades. However, interactions also affect an animal's subsequent movement decisions. Despite this, the indirect effect of these decisions on animal survival is much less well-understood. Here, we incorporate movement responses to foreign animals into a model of two competing populations, where inter-specific competition is greater than intra-specific competition. When movement is diffusive, the travelling wave moves from the stronger population to the weaker. However, by incorporating behaviourally induced directed movement towards the stronger population, the weaker one can slow the travelling wave down, even reversing its direction. Hence movement responses can switch the predictions of traditional mechanistic models. Furthermore, when environmental heterogeneity is combined with aggressive movement strategies, it is possible for spatially segregated co-existence to emerge. In this situation, the spatial patterns of the competing populations have the unusual feature that they are slightly out-of-phase with the environmental patterns. Finally, incorporating dynamic movement responses can also enable stable co-existence in a homogeneous environment, giving a new mechanism for spatially segregated co-existence.

Cu-Catalyzed aromatic C-H imidation with N-fluorobenzenesulfonimide: mechanistic details and predictive models.

The LCuBr-catalyzed C-H imidation of arenes by N-fluorobenzenesulfonimide (NFSI), previously reported by us, utilizes an inexpensive catalyst and is applicable to a broad scope of complex arenes. The computational and experimental study reported here shows that the mechanism of the reaction is comprised of two parts: (1) generation of the active dinuclear CuII-CuII catalyst; and (2) the catalytic cycle for the C-H bond imidation of arenes. Computations show that the LCuIBr complex used in experiments is not an active catalyst. Instead, upon reacting with NFSI it converts to an active dinuclear CuII-CuII catalyst that is detected using HRMS techniques. The catalytic cycle starting from the CuII-CuII dinuclear complex proceeds via (a) one-electron oxidation of the active catalyst by NFSI to generate an imidyl radical and dinuclear CuII-CuIII intermediate, (b) turnover-limiting single-electron-transfer (SET1) from the arene to the imidyl radical, (c) fast C-N bond formation with an imidyl anion and an aryl radical cation, (d) reduction of the CuII-CuIII dinuclear intermediate by the aryl radical to regenerate the active catalyst and produce an aryl-cation intermediate, and (e) deprotonation and rearomatization of the arene ring to form the imidated product. The calculated KIE for the turnover-limiting SET1 step reproduces its experimentally observed value. A simple predictive tool was developed and experimentally validated to determine the regiochemical outcome for a given substrate. We demonstrated that the pre-reaction LCuX complexes, where X = Cl, Br and I, show a similar reactivity pattern as these complexes convert to the same catalytically active dinuclear CuII-CuII species.

Permanent Deformation Characteristics of Coarse Grained Subgrade Soils under Train-Induced Repeated Load

This paper presents the results of a laboratory experiment that aimed to characterize the permanent deformation behavior of coarse grained soils. To evaluate the effects of the cyclic stress amplitude, initial mean stress, and initial stress ratio on the permanent axial deformation, six series of repeated load triaxial tests were performed. The results indicate that permanent deformation of coarse grained soils increased with increasing cyclic stress amplitude. In particular, for relative low cyclic stress levels, accumulation rate of permanent deformation decreased progressively with number of cycles and eventually reached an equilibrium state. The initial stress ratio was also found to obviously facilitate the buildup of axial deformation since it means higher deviatoric stress as the mean pressure kept constant. As the initial stress ratio was less than the slope of static failure line, the experimental results indicated that the increase of initial mean stress enhanced the capability of resisting deformation. A simplified mechanistic empirical prediction model was proposed, which predicted the permanent deformation as product of four independent functions about cyclic stress amplitude, initial mean stress, initial stress ratio, and number of load cycles. Satisfactory predictions of the permanent deformation behavior of coarse grained soils were obtained with the proposed model.

Population Heterogeneity in the Epithelial to Mesenchymal Transition Is Controlled by NFAT and Phosphorylated Sp1.

Epithelial to mesenchymal transition (EMT) is an essential differentiation program during tissue morphogenesis and remodeling. EMT is induced by soluble transforming growth factor β (TGF-β) family members, and restricted by vascular endothelial growth factor family members. While many downstream molecular regulators of EMT have been identified, these have been largely evaluated individually without considering potential crosstalk. In this study, we created an ensemble of dynamic mathematical models describing TGF-β induced EMT to better understand the operational hierarchy of this complex molecular program. We used ordinary differential equations (ODEs) to describe the transcriptional and post-translational regulatory events driving EMT. Model parameters were estimated from multiple data sets using multiobjective optimization, in combination with cross-validation. TGF-β exposure drove the model population toward a mesenchymal phenotype, while an epithelial phenotype was enhanced following vascular endothelial growth factor A (VEGF-A) exposure. Simulations predicted that the transcription factors phosphorylated SP1 and NFAT were master regulators promoting or inhibiting EMT, respectively. Surprisingly, simulations also predicted that a cellular population could exhibit phenotypic heterogeneity (characterized by a significant fraction of the population with both high epithelial and mesenchymal marker expression) if treated simultaneously with TGF-β and VEGF-A. We tested this prediction experimentally in both MCF10A and DLD1 cells and found that upwards of 45% of the cellular population acquired this hybrid state in the presence of both TGF-β and VEGF-A. We experimentally validated the predicted NFAT/Sp1 signaling axis for each phenotype response. Lastly, we found that cells in the hybrid state had significantly different functional behavior when compared to VEGF-A or TGF-β treatment alone. Together, these results establish a predictive mechanistic model of EMT susceptibility, and potentially reveal a novel signaling axis which regulates carcinoma progression through an EMT versus tubulogenesis response.

Uncertainty quantification and global sensitivity analysis of mechanistic one-dimensional models and flow pattern transition boundaries predictions for two-phase pipe flows

The prediction of uncertainties is a growing interest in flow assurance industrial applications, but only few works have been presented on this topic. In this work, an uncertainty quantification and a global sensitivity analysis are performed to quantify the level of confidence in predictions of one-dimensional mechanistic models considering different two-phase flow regimes. A method is proposed for this purpose accounting for the effect of several variables on pressure drop and hold-up predictions by the well-known one-dimensional two-fluid model, such as fluid flow rates, geometry (the inclination angle and the pipe diameter), and fluid properties (density and viscosity); the case of a non-Newtonian shear-thinning fluid behaviour is also considered. Flow pattern transition boundaries, including the stability of the stratified flow regime, are included in this analysis. Monte Carlo simulations were used for the uncertainty quantification while different approaches for the sensitivity analysis (scatter plot, linear regression, the Morris’s method, and the Sobol’s Method) were used and compared to identify the best tool for this family of models. The Sobol’s method appears to be the most convenient approach and a discussion is provided considering different practical cases for gas/liquid and liquid/liquid systems. The most critical input parameters in terms of uncertainty are rigorously identified case by case. A way to reduce the output uncertainty is indicated by the interpretation of the results of the global sensitivity analysis. The conclusions of this analysis gives new insights regarding the degree of uncertainties in predictions of one-dimensional mechanistic models.

Computational fluid dynamics and population balance modelling of nucleate boiling of cryogenic liquids: Theoretical developments

The main focus in the analysis of pool or flow boiling in saturated or subcooled conditions is the basic understanding of the phase change process through the heat transfer and wall heat flux partitioning at the heated wall and the two-phase bubble behaviours in the bulk liquid as they migrate away from the heated wall. This paper reviews the work in this rapid developing area with special reference to modelling nucleate boiling of cryogenic liquids in the context of computational fluid dynamics and associated theoretical developments. The partitioning of the wall heat flux at the heated wall into three components – single-phase convection, transient conduction and evaporation – remains the most popular mechanistic approach in predicting the heat transfer process during boiling. Nevertheless, the respective wall heat flux components generally require the determination of the active nucleation site density, bubble departure diameter and nucleation frequency, which are crucial to the proper prediction of the heat transfer process. Numerous empirical correlations presented in this paper have been developed to ascertain these three important parameters with some degree of success. Albeit the simplicity of empirical correlations, they remain applicable to only a narrow range of flow conditions. In order to extend the wall heat flux partitioning approach to a wider range of flow conditions, the fractal model proposed for the active nucleation site density, force balance model for bubble departing from the cavity and bubble lifting off from the heated wall and evaluation of nucleation frequency based on fundamental theory depict the many enhancements that can improve the mechanistic model predictions. The macroscopic consideration of the two-phase boiling in the bulk liquid via the two-fluid model represents the most effective continuum approach in predicting the volume fraction and velocity distributions of each phase. Nevertheless, the interfacial mass, momentum and energy exchange terms that appear in the transport equations generally require the determination of the Sauter mean diameter or interfacial area concentration, which strongly governs the fluid flow and heat transfer in the bulk liquid. In order to accommodate the dynamically changing bubble sizes that are prevalent in the bulk liquid, the mechanistic approach based on the population balance model allows the appropriate prediction of local distributions of Sauter mean diameter or interfacial area concentration, which in turn can improve the predictions of the interfacial mass, momentum and energy exchanges that occur across the interface between the phases. Need for further developments are discussed.

Mechanistic modeling and numerical simulation of in-situ gas void fraction inside ESP impeller

When gas is entrained with liquid into an electrical submersible pump (ESP), the in-situ gas void fraction (αG) inside the ESP impeller is closely related to its pressure boosting ability. Due to complex pump geometries, the direct measurement of αG is very difficult to carry out. In this study, a mechanistic model for predicting the in-situ αG inside an ESP impeller is developed and validated by three-dimensional (3D) computational fluid dynamics (CFD) simulations. The pressure increment of ESP obtained from single-phase numerical simulations matches experimental measurement well. With a new bubble size prediction model implemented into multiphase CFD simulations, the calculated ESP pressure increments under gassy flow conditions also agree with experimental pump performance curves. As the inlet gas volumetric fraction (GVF) increases, the ESP boosting pressure deteriorates. The simulated in-situ αG, which is used to verify mechanistic model predictions, increases with bubble size increase and gas density or rotational speed decrease. Based on the radial velocity slippage between gas and liquid phases, the in-situ αG can be determined with GVF, rotational speed, bubble size, and fluid properties etc. Compared with empirical correlations, the proposed mechanistic model can predict in-situ αG better by accounting for the gas-liquid phase interaction using the radial force balance between centrifugal buoyancy and drag forces exerted on a stable bubble.

Modelling mammalian energetics: the heterothermy problem

Global climate change is expected to have strong effects on the world’s flora and fauna. As a result, there has been a recent increase in the number of meta-analyses and mechanistic models that attempt to predict potential responses of mammals to changing climates. Many models that seek to explain the effects of environmental temperatures on mammalian energetics and survival assume a constant body temperature. However, despite generally being regarded as strict homeotherms, mammals demonstrate a large degree of daily variability in body temperature, as well as the ability to reduce metabolic costs either by entering torpor, or by increasing body temperatures at high ambient temperatures. Often, changes in body temperature variability are unpredictable, and happen in response to immediate changes in resource abundance or temperature. In this review we provide an overview of variability and unpredictability found in body temperatures of extant mammals, identify potential blind spots in the current literature, and discuss options for incorporating variability into predictive mechanistic models.

Continuous-Flow Synthesis and Derivatization of Aziridines through Palladium-Catalyzed C(sp(3) )-H Activation.

A continuous‐flow synthesis of aziridines by palladium‐catalyzed C(sp3)−H activation is described. The new flow reaction could be combined with an aziridine‐ring‐opening reaction to give highly functionalized aliphatic amines through a consecutive process. A predictive mechanistic model was developed and used to design the C−H activation flow process and illustrates an approach towards first‐principles design based on novel catalytic reactions.