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With the rise of machine learning (ML), the modeling of chemical systems has reached a new era and has the potential to revolutionize how we understand and predict chemical reactions. Here, we probe the historic dependence on utilizing enantiomeric excess (ee) as a target variable and discuss the benefits of using relative Gibbs free activation energies (ΔΔG≠), grounded firmly in transition‐state theory, emphasizing practical benefits for chemists. This perspective is intended to discuss best practices that enhance modeling efforts especially for chemists with an experimental background in asymmetric catalysis that wish to explore modelling of their data. We outline the enhanced modeling performance using ΔΔG≠, escaping physical limitations, addressing temperature effects, managing non‐linear error propagation, adjusting for data distributions and how to deal with unphysical predictions,in order to streamline modeling for the practical chemist and provide simple guidelines to strong statistical tools. For this endeavor, we gathered ten datasets from the literature covering very different reaction types. We evaluated the datasets using fingerprint‐, descriptor‐, and graph neural network‐based models. Our results highlight the distinction in performance among varying model complexities with respect to the target representation, emphasizing practical benefits for chemists. [ABSTRACT FROM AUTHOR]

Summary Policymakers require health economic modeling to guide their decision‐making over the choice of interventions for obesity. This scoping review was undertaken to report on the health economic models in use for estimating the value of behavioral interventions (individual or population level) for obesity reduction. Electronic databases (MEDLINE, Embase, PsycINFO, EconLit, and Web of Science) were searched for publications meeting inclusion criteria from January 2015 to May 2023. Seventy‐three studies were included, using 44 health economic models between them. When considered against the expert recommendations for modeling of this type, only four models (9%) met all five key elements. The element most commonly unfulfilled was the use of a microsimulation modeling approach (41%, n = 18), followed by model validation (46%, n = 20). A majority of models met each of the other elements: use of a lifetime horizon (59%, n = 26), inclusion of key health events (66%, n = 29), and a risk equation approach to event simulation (71%, n = 31). In addition, under half of the studies considered health inequalities in their reporting. Continued proliferation of models with inadequate time horizons, breadth of obesity‐related health conditions, and perspectives on costs and outcomes risks underestimation of the benefits of longer term interventions and impacts on health inequalities. [ABSTRACT FROM AUTHOR]

In this study, nanocomposites of g‐C3N4/MN4 (where M is Mn, Fe and Co) have been designed using advanced density functional theory (DFT) calculations. A comprehensive analysis was conducted on the geometry, electronic, optical properties, work function, charge transfer interaction and adhesion energy of the g‐C3N4/MN4 heterostructures and concluded that g‐C3N4/FeN4 and g‐C3N4/CoN4 heterojunctions exhibit higher photocatalytic performance than individual units. The better photocatalytic activity can be attributed mainly by two facts; (i) the visible light absorption of both g‐C3N4/FeN4 and g‐C3N4/CoN4 interfaces are higher compared to its isolated analogs and (ii) a significant enhancement of band gap energy in g‐C3N4/FeN4 and g‐C3N4/CoN4 heterostructures limited the electron–hole recombination significantly. The potential of the g‐C3N4/MN4 heterojunctions as a photocatalyst for the water splitting reaction was assessed by examining its band alignment for water splitting reaction. Importantly, while the electronic and magnetic properties of MN4 systems were studied, this is the first example of inclusion of MN4 on graphene‐based material (g‐C3N4) for studying the photocatalytic activity. The state of the art DFT calculations emphasis that g‐C3N4/FeN4 and g‐C3N4/CoN4 heterojunctions are half metallic photocatalysts, which is limited till date. [ABSTRACT FROM AUTHOR]

Through alteration of the polarity of DC plasma during the growth of carbon nanotubes in a PECVD reactor, significantly different morphologies of such species have been achieved. By using this approach, for the first time, both Half‐aligned and Entangled structures were synthesized, along with Full‐aligned carbon nanotubes, introducing three binder‐free electrodes with various levels of tortuosity. The crucial parameter and influential effect of tortuosity in these three‐dimensional nanostructure scaffolds for application in lithium‐ion batteries were investigated. Previous research findings suggested that increasing the tortuosity of the conductive scaffolds leads to preferential accumulation of lithium at the top surface and causes the loss of capacity in subsequent charge‐discharge cycles. Our finding reveals that there exists a trade‐off between lithium‐demand, capacity, and preferential accumulation of lithium at the top surface. Among the presented scaffolds, the Half‐aligned MWCNTs was able to maintain a high capacity of 876.9 mAh/g over more than 300 cycles, and demonstrate capacity improvement during this period and excellent rate capability, even at a rate of 5 C. This capacity is almost three times that can be achieved with graphite, showcasing promising and outstanding results for carbon nanotubes. [ABSTRACT FROM AUTHOR]

The buffer leakage phenomena have a large effect on high‐power and fast‐switching GaN high electron mobility transistor devices. Herein, the buffer leakage mechanism in a GaN‐on‐Si substrate with AlGaN buffer layers is investigated by using samples with various carbon concentrations. Comparing the leakage current with crystallinity and impurity concentration, it is found that the vertical leakage current is dominated by both threading dislocations and bulk impurities. Increasing the carbon concentration of buffer layers suppresses leakage current in the bulk conducting regime in high electric fields but increases it in the dislocation conducting regime in low electric fields. These results indicate that the optimal carbon concentration of buffer layers depends on the target electric field. [ABSTRACT FROM AUTHOR]

Handling geotechnical peculiarities in specialized ground models – an experience report Dr. Spang GmbH has developed numerous specialized ground models in recent years and has gained corresponding experience in ground modeling. Within the company, a standard procedure for creating these specialized models has been established. From a software perspective, automatic meshing (triangulated 3D surface mesh of the layer boundaries) already delivers useful results for many standard cases. However, in geotechnics, there are not only standard cases and features to assess. Geotechnical peculiarities (e. g. inhomogeneous layering) result in an increased manual modeling effort. This article aims to shed light on how to handle these peculiarities in modeling, present the additional modeling steps involved, and highlight the software limitations that arise in automatic meshing (interpolation or triangulation) in such special cases. [ABSTRACT FROM AUTHOR]

Aim of the study was to analyze the metabolic profile of badminton matches and training drills. Therefore, 11 male (23.2 ± 3.8 years, 182 ± 7 cm, 74.4 ± 8.4 kg) and five female (19.3 ± 1.5 years, 170 ± 6 cm, 62.6 ± 9.2 kg) elite badminton players participated in either a training match (TM; n = 7) and/or three protocols of multifeeding drills (T10, T30,T50;n = 13), that varied in interval and rest durations (10 s/10 s, 30 s/30 s, 50 s/50 s). Absolute and relative energetic costs (Wtot and Etot) and contribution to oxidative (WOxid), phosphagen (WPCr), and anaerobic glycolytic (WLa) metabolism were calculated by the three‐component PCr‐La‐O2‐method based on an indirect calorimetric approach from oxygen consumption during exercise, post exercise, and net blood lactate concentration. A novel intermittent approach was used to consider replenishment of phosphocreatine during each resting phase. Results show that during TM, Etot was 676 ± 98J·kg−1 min−1, while metabolic pathways contributed by 56.9 ± 8.6% (WOxid), 42.7 ± 8.7% (WPCr), and 0.4 ± 0.6% (WLa). In the multifeeding drills Etot was comparable between T10 (1020 ± 160J·kg−1 min−1) and T30 (985 ± 173 J·kg−1 min−1) but higher in T50 (1266 ± 194J·kg−1 min−1) (p < 0.001). Relative contribution of WOxid was lower in T10 (47.3 ± 7.7%) but similar in T30 (56.5 ± 6.2%) and T50 (57.3 ± 6.0%) (p < 0.001). WPCr was highest in T10 (51.1 ± 8.3%) followed by T30 (42.2 ± 6.9%) and lowest in T50 (31.2 ± 7.7%) (p < 0.001). WLa was similar between T10 (1.6 ± 1.0%) and T30 (2.1 ± 1.0%) but higher in T50 (11.6 ± 4.8%) (p < 0.001). Concludingly, metabolic costs in badminton are predominantly covered by oxidative and phosphagen energetic pathways. Metabolic profiles of the multifeeding drills differ depending on rally/interval duration, with increasing contribution of anaerobic glycolysis and decreasing phosphagen contribution in case of longer intervals. Plain Language Summary: Badminton stands out as a high‐paced and exceptionally demanding sport, necessitating a very complex interaction between the aerobic and anaerobic metabolic systems. Using an innovative approach of indirect caloric measurement, the main aim of the investigation was to determine the metabolic profiles of elite badminton match play and badminton‐specific training drills. Therefore, 16 elite players conducted either a training match and/or three different protocols of a multifeeding drill (with varying interval/rest durations). The study underscores a pivotal role of anaerobic alactic energy supply in badminton, highlighting the critical need for rapid phosphocreatine (PCr) replenishment to prevent performance decline attributed to increasing acidosis. While aerobic capacity remains vital for PCr replenishment, occasional reliance on lactic metabolism may be important in certain probable match deciding situations. The multifeeding drills exhibit variations in the metabolic profile depending on rally and rest durations. As the interval length increases, the dominance of aerobic and lactic metabolism rises, while the proportion of anaerobic alactic contribution decreases. Emphasizing that in on‐court drills different interval durations address different metabolic pathways, training content should be chosen wisely to accurately address individual training goals and to align with a long‐term training periodization perspective. Highlights: This is the first study using an intermittent approach of the three‐component PCr‐La‐O2‐method, to determine the metabolic profile of elite badminton match play and the impact of drill prescription on metabolic stress in badminton‐specific training drills.The present findings reveal that energy in badminton generally is predominantly derived from oxidative and phosphagen energetic pathways, with the anaerobic glycolytic system contributing only minimally.Multifeeding drills essentially mirror the metabolic demands of matches but exhibit variations depending on rally and rest periods. These findings underscore the need to select training protocols thoughtfully, tailor training according to individualized goals and to structure those goals within a long‐term training periodization. [ABSTRACT FROM AUTHOR]

Adavosertib (AZD1775) is a potent small‐molecule inhibitor of Wee1 kinase. This analysis utilized pharmacokinetic data from 8 Phase I/II studies of adavosertib to characterize the population pharmacokinetics of adavosertib in patients (n = 538) with solid tumors and evaluate the impact of covariates on exposure. A nonlinear mixed‐effects modeling approach was employed to estimate population and individual parameters from the clinical trial data. The model for time dependency of apparent clearance (CL) was developed in a stepwise manner and the final model validated by visual predictive checks (VPCs). Using an adavosertib dose of 300 mg once daily on a 5 days on/2 days off dosing schedule given 2 weeks out of a 3‐week cycle, simulation analyses evaluated the impact of covariates on the following exposure metrics at steady state: maximum concentration during a 21‐day cycle, area under the curve (AUC) during a 21‐day cycle, AUC during the second week of a treatment cycle, and AUC on day 12 of a treatment cycle. The final model was a linear 2‐compartment model with lag time into the dosing compartment and first‐order absorption into the central compartment, time‐varying CL, and random effects on all model parameters. VPCs and steady‐state observations confirmed that the final model satisfied all the requirements for reliable simulation of randomly sampled Phase I and II populations with different covariate characteristics. Simulation‐based analyses revealed that body weight, renal impairment status, and race were key factors determining the variability of drug‐exposure metrics. [ABSTRACT FROM AUTHOR]

High‐aluminum advanced high‐strength steels have received increasing interest due to their excellent combination of strength and ductility. The control of nonmetallic inclusions in steel is among the most important issue for the production of high‐aluminum steel. This study proposes a model for the evolution of size distributions of AlN inclusions during solidification of steel based on the Kampmann–Wagner numerical model and microsegregation calculation. Both homogeneous (pure AlN) and heterogeneous precipitations (AlN+oxide or MnS) are described using homogeneous nucleation and free growth models of Greer et al. respectively. The model is applied to calculate the size distributions of AlN in high‐Al (up to 5%) Fe–Cr–Al steels and high‐ and medium‐manganese steels and validated by the experimental data in the literature. The model correctly describes the influence of cooling rates on the precipitation of AlN in Fe–Cr–Al steels and high‐manganese steels, and the sizes of AlN are reduced and the number densities of AlN inclusions are increased by increasing the cooling rate. The effects of nitrogen and aluminum concentration in medium‐manganese steel on inclusion precipitation are investigated by the model calculation. The increases in nitrogen and aluminum concentration facilitate the homogeneous precipitation of AlN inclusions. [ABSTRACT FROM AUTHOR]

A longstanding project of the chemical kinetics community is to predict reaction rates and the behavior of reacting systems, even for systems where there are no experimental data. Many important reacting systems (atmosphere, combustion, pyrolysis, partial oxidations) involve a large number of reactions occurring simultaneously, and reaction intermediates that have never been observed, making this goal even more challenging. Improvements in our ability to compute rate coefficients and other important parameters accurately from first principles, and improvements in automated kinetic modeling software, have partially overcome many challenges. Indeed, in some cases quite complicated kinetic models have been constructed which accurately predicted the results of independent experiments. However, the process of constructing the models, and deciding which reactions to measure or compute ab initio, relies on accurate estimates (and indeed most of the numerical rate parameters in most large kinetic models are estimates.) Machine‐learned models trained on large datasets can improve the accuracy of these estimates, and allow a better integration of quantum chemistry and experimental data. The need for continued development of shared (perhaps open‐source) software and databases, and some directions for improvement, are highlighted. As we model more complicated systems, many of the weaknesses of the traditional ways of doing chemical kinetic modeling, and of testing kinetic models, have been exposed, identifying several challenges for future research by the community. [ABSTRACT FROM AUTHOR]

With recent improvements in computer performance, computer‐aided studies have become increasingly important. Computer‐aided methods have been applied in fat crystallization studies for modeling, simulation, optimization, data analysis and visualization. In this paper, various methods, such as molecular dynamic simulation, Monte Carlo, cellular automata modeling, finite element analysis, machine learning and computer vision, are introduced. Applications and advances in mechanism explanation, behavior prediction, process optimization, and so forth, are reviewed for fat crystallization. As a powerful and essential tool, computer‐aided study should play an important role in the field of lipid research in the future. [ABSTRACT FROM AUTHOR]

The repeated rapid heating and nonlinear cooling associated with electropulsing treatment (EPT) hinder the accurate modeling of temperature variations based on a constitutive approach using physical models. This objective is not attainable through conventional machine learning (ML) approaches as well, such as artificial neural network (ANN) and long short‐term memory (LSTM). The present study investigates the intricate nonlinear thermal history of Mg alloys induced by EPT to improve a predictive model under multipulse conditions. Furthermore, it enhances the predictivity and generalizability of a given problem using an ML model called i‐LSTM by specifically tailoring a dataset. The i‐LSTM model performance surpasses that of the constitutive approaches and conventional ML models when predicting the complicated thermal history of EPT specimens in a wide variety of processing parameters. The mechanisms underlying this improvement are discussed based on several experimental datasets. This study not only addresses challenges in existing models but also offers a promising avenue for understanding and predicting the thermal dynamics of Mg alloys subjected to the multipulse EPT process. [ABSTRACT FROM AUTHOR]

Age/size selective fishery, which targets large individuals and retains immature individuals, is practiced worldwide. Yet, selective fishing can result in bycatch of undersized target species, posing a serious problem in stock management. In addition, there is a growing concern that intensive selective removal alters the composition of a population. Therefore, a comprehensive understanding of the effects of selective fishery on stock dynamics is essential for sustainable fishery management. In this study, an age‐structured model based on the Schaefer model assumptions was used to investigate the effects of selective fisheries and their bycatch on stock dynamics. Local stability analyses suggest that selective fishery can cause undesirable oscillatory stock dynamics in fishery management. Numerical simulations revealed that maximum sustainable yield‐based management with a large age at maturity is more likely to lead to stock oscillations. Notably, bycatch, which is detrimental to the sustainability of the fishery, was found to reduce the oscillatory dynamics. Overall, selective fisheries tend to cause oscillatory stock dynamics in various situations. Selective fishing also tends to reduce the critical fishing effort that causes stock extinction; therefore, a precautionary approach is necessary to mitigate such issues. Recommendations for Resource ManagersAge/size selective fishing that retains immature individuals is practiced worldwide and often cause unwanted bycatch, thus requiring a solid understanding for successful management.Selective fishing can cause fluctuations in stock dynamics that are undesirable for sustainable fisheries. This situation may be more likely to occur when the minimum age for fishing is large. It may also occur in fisheries based on maximum sustainable yield.Precautionary management, such as the establishment of marine protected areas, is therefore required. [ABSTRACT FROM AUTHOR]

On 2 April 2024, an MW 7.4 earthquake struck the northern Longitudinal Valley in eastern Taiwan, about 18 km SSW of Hualien, causing damage and casualties. In this study, we investigated a comprehensive geodetic data set, employing Global Navigation Satellite Systems (GNSS) and Interferometric Synthetic Aperture Radar (InSAR) measurements to assess the rupture geometry associated with earthquake sequence. Although geodetic data can be satisfactorily reproduced by simple single‐fault models (i.e., a high‐angle E‐dipping plane related to the Longitudinal Valley Fault (LVF), or a gentle W‐dipping surface associated with the Central Range Fault, CRF), a composite model involving the rupture of different fault segments (a major CRF‐related W‐dipping fault, a deep segment of the E‐dipping LVF, and the Milun Fault) is able to explain the observations, the distribution of seismicity, and the complex structural arrangement of the northernmost sector of the Longitudinal Valley. Plain Language Summary: On 2 April 2024, a powerful magnitude 7.4 earthquake hit the northern Longitudinal Valley in eastern Taiwan, near Hualien, causing significant damage and loss of life. This study examined a detailed set of geodetic data, including measurements from Global Navigation Satellite Systems (GNSS) and Interferometric Synthetic Aperture Radar (InSAR), to understand the geometry of the earthquake's rupture. While simple models focused on single faults (like the Longitudinal Valley Fault (LVF) or the Central Range Fault) can replicate the geodetic data to some extent, a more complex model involving the rupture of different fault segments (including a major Central Range Fault segment, a deep segment of the LVF, and the Milun Fault) better explains the data, seismic activity distribution, and the intricate structural layout of the northern part of the Longitudinal Valley. Key Points: We developed a composite rupture geometry of the MW 7.4 2024 Hualien (eastern Taiwan) earthquake sequenceThe earthquake primarily ruptured a major W‐dipping fault, while secondary affecting both deep and shallow segments of an E‐dipping faultOur results support the clear partitioning of the seismic release on different structures [ABSTRACT FROM AUTHOR]

ABSTRACT The current study involved production, comprehensive structural analysis, and physicochemical characterizing of two distinctive complexes namely, Cu(TBH) and Zn(TBH); TBH donor ligand: N′‐(1‐(3,6‐dihydro‐4‐hydroxy‐2,6‐dioxo‐2H‐1,3‐thiazin‐5‐yl)ethylidene)‐2‐hydroxybenzohydrazide) using a wide range of analytical methods, including elemental analysis, UV–Vis, FT‐IR, and 1HNMR spectrometry, molar conductivity and magnetic susceptibility measurements, and thermal analysis. According to the findings, chelation can occur through O, N, and O donor atoms of monoanionic chelator for generating mono‐nuclear chelates with tetrahedral geometry for Cu (II) and octahedral geometry for Zn (II). The anticarcinogenic ability of TBH chelator and its coordinated compounds against human liver cancer (HepG‐2) was investigated. The Cu(TBH) complex was found to have selective and promising anticancer activity against a liver cancer cell line, with lower IC50 (liver carcinoma cell line) and higher IC50 (normal human cell line) values than other produced compounds and standard drugs. Utilizing DFT computations, the molecular structures of the TBH and its complexes were verified, offering a detailed understanding of their quantum chemical characteristics. A quantitative structure–activity relationship (QSAR) model, which illustrates the association between DFT‐computed descriptors and biological activities pIC50, was also created using multiple linear regression (MLR) on the synthesized compounds as anticancer medicines. Additionally, there are no issues with the produced compounds' oral bioavailability according to (ROF) Lipinski's rule of five. Furthermore, docking studies of the synthesized TBH chelator and its chelates with CDK2 kinase have been performed to validate the biological findings. According to our findings, the novel Cu(TBH) nanodrug exhibits considerable cytotoxic activity, prompting further study into its pharmacological profile and exploring its potential in drug development. [ABSTRACT FROM AUTHOR]

ABSTRACT The investigation encompassed an examination of the drying durations, modeling, and quality attributes (color, rehydration capacity, microstructural features, total soluble solid [TSS], and pH values) of strawberry slices subjected to diverse drying methodologies, namely electrohydrodynamic (EHD), EHD‐hot air, and hot air processes. Furthermore, 10 distinct thin‐layer drying models were applied, and their goodness‐of‐fit was assessed to identify the most suitable model for the drying process. This analysis encompassed applying two distinct temperatures (50°C and 55°C), and voltage levels (20 and 30 kV). The EHD method yielded the lengthiest drying durations for the strawberry samples, with hot air and EHD‐hot air drying techniques subsequent in descending order of drying time. The outcomes of the modeling analyses demonstrated that the thin‐layer drying behaviors of used drying methods were best described by the Midilli et al. and Wang and Singh models in terms of their goodness‐of‐fit. A decline in the L* values was noted with the elevation of temperature in the hot air drying method and with the escalation of voltage in the EHD drying. The minimum a* value was detected in the hot air drying method conducted at 55°C. The rehydration capacity of strawberry samples subjected to the EHD and EHD‐hot air combination drying methods (except 20 kV‐55°C) did not exhibit any statistically significant variation in response to different voltage settings. Although the structure of strawberry samples dried with 20 kV application was observed as smoother, cracks occurred on the product surface in other drying applications. In hot air and EHD methods, varying temperature and volt applications did not show a significant effect on TSS and pH values. As a result, it has been seen that EHD technology, which is a promising drying method used in this study, is a suitable method in terms of processing efficiency and consumer acceptability of dried strawberry products. [ABSTRACT FROM AUTHOR]

The insertion of finer Z‐pins is an effective method to reduce the microstructure damage and maintain the in‐plane performance of composite laminates. In this paper, an ultrasound guided insertion process is proposed to achieve the insertion of fine Z‐pins and the influence of Z‐pin material on the mechanical properties of Ø0.11 mm Z‐pin reinforced composite laminates is revealed based on experiments and simulations. For in‐plane mechanical properties, stainless steel Z‐pins help to reduce the loss of compression modulus and compression strength. For the interlaminar mechanical properties, stainless steel Z‐pins and carbon fiber Z‐pins exhibit bilinear and trilinear bridging laws respectively, resulting in the mode‐I maximum load and fracture toughness of carbon fiber Z‐pin reinforced composites being greater than that of stainless steel Z‐pin reinforced composites. By adjusting the insertion spacing, it is found that for unidirectional composite laminates reinforced by Ø0.11 mm carbon fiber Z‐pins with an insertion spacing of 2 mm, the compression strength reduction is only 3.39% while the mode‐I fracture toughness can be improved by 14.4 times in comparison with the unpinned specimens, achieving a better balance between in‐plane performance loss and interlaminar reinforcement effect. Highlights: The effect of Z‐pin material on fine Z‐pin reinforced composites is studied.The compression properties are simulated by the RVE model.The mode‐I fracture properties are simulated by the DCB unit strip model. [ABSTRACT FROM AUTHOR]

Summary Characteristic of all conifer needles, the transfusion tissue mediates the radial transport of water and sugar between the endodermis and axial vasculature. Physical constraints imposed by the needle's linear geometry introduce two potential extravascular bottlenecks where the opposition of sugar and water flows may frustrate sugar export: one at the vascular access point and the other at the endodermis. We developed a network model of the transfusion tissue to explore how its structure and composition affect the delivery of sugars to the axial phloem. To describe extravascular transport with cellular resolution, we construct networks from images of Pinus pinea needles obtained through tomographic microscopy, as well as fluorescence and electron microscopy. The transfusion tissue provides physically distinct pathways for sugar and water, reducing resistance between the vasculature and endodermis and mitigating flow constriction at the vascular flank. Dissipation of flow velocities through the transfusion tissue's branched structure allows for bidirectional transport of an inbound diffusive sugar flux against an outbound advective water flux across the endodermis. Our results clarify the structure–function relationships of the transfusion tissue under conditions free of physiological stress. The presented model framework is also applicable to different transfusion tissue morphologies in other gymnosperms. [ABSTRACT FROM AUTHOR]

The Asian Summer Monsoon (ASM) convection transports aerosols and their precursors from the boundary layer to the upper troposphere and lower stratosphere (UTLS). This process forms an annually recurring aerosol layer near the tropopause. Recent observations have revealed a distinct property of the aerosol layer over the ASM region, it is nitrate‐rich. We present a newly implemented aerosol formation algorithm that enhances the representation of nitrate aerosol in the Community Aerosol and Radiation Model for Atmospheres (CARMA) coupled with the Community Earth System Model (CESM). The simulated aerosol chemical composition, as well as vertical distributions of aerosol size and mass, are evaluated using in situ and remote sensing observations. The simulated concentrations (ammonium, nitrate, and sulfate) and size distributions are generally within the error bars of data. We find nitrate, organics, and sulfate contribute significantly to the UTLS aerosol concentration between 15°–45°N and 0°–160°E. The two key formation mechanisms of nitrate‐containing aerosols in the ATAL are ammonium neutralization to form ammonium nitrate in regions where convection is active, and condensation of nitric acid in regions of cold temperature. Furthermore, including nitrate formation in the model doubles the surface area density in the tropical tropopause region between 15°–45°N and 0°–160°E, which alters the chlorine partitioning and subsequently impacts the rate of ozone depletion. Plain Language Summary: The Asian Summer Monsoon can efficiently transport pollutants into the upper troposphere and form a layer of aerosols called the Asian Tropopause Aerosol Layer (ATAL). This research investigates the two key formation mechanisms for nitrate aerosol in the ATAL: one is due to cold temperature, and one is due to ammonium neutralization. The simulations are validated against in situ measurements. It also found that O3 chemistry inside ATAL is influenced by nitrate aerosol. Key Points: A new nitrate aerosol formation algorithm is implemented for the community model CARMA to represent the Asian Tropopause Aerosol LayerThe simulated aerosol size distributions and compositions are within error bars of observationsIncluding the new nitrate formation scheme doubles the simulated surface area, changing the chlorine partitioning and ozone depletion [ABSTRACT FROM AUTHOR]

By experimental characterization and numerical modeling, the dependence of thermophysical properties on time and temperature as well as its influence on the thermomechanical behavior of alumina–magnesia castables has been studied in this work. The thermal conductivity, thermal expansion coefficient, and Young's modulus are the most important parameters, which evolve with temperature and piecewise change with the thermal processes of drying, preheating, and service. It is mainly related to the sintering degree and amount of formed calcium aluminate and spinel phases. The sensitivity analysis of parallel simulations for multilayer steel ladle with different numbers of temperature‐dependent thermophysical parameters demonstrates that the thermal conductivity is the most influential parameter, as it dominates the temperature distribution and affects the succeeding thermal expansion as well as deformation. The increase of thermal expansion coefficient and decrease of Young's modulus with temperature counterbalance the deformation of linings under thermal process. Meanwhile, compared with the simulation using temperature‐independent parameters, the model with temperature‐dependent thermophysical parameters exhibits more severe damage in outer surface of both the working lining and the permanent lining. This gives new insight into the adoption of temperature‐dependent parameters for actual thermomechanical behavior evaluation of refractories. [ABSTRACT FROM AUTHOR]

While blast furnaces remain the dominant ironmaking technology, there is growing interest in using hydrogen to partially replace coke and pulverized coal to reduce CO2 emissions in this hard‐to‐decarbonize process. However, significant discrepancies in modeling the tuyere injection of hydrogen are noted in the literature, which can challenge the scale‐up from modeling predictions and pilot trials to actual blast furnace operations. To address this, the impact of uncertainties in the assumptions of the temperature in the thermal reserve zone and the ratio of H2 and CO utilization on the results of blast furnace process modeling are evaluated using a 1D steady‐state zonal model. The study indicates that variations in the assumed value of thermal reserve zone temperature significantly impact the estimation of optimal hydrogen injection rate, coke replacement ratio, and direct CO2 emissions reductions. In contrast, the same parameters are much less affected by the variations in the assumed value of the proportion between H2 and CO utilization ratios, which, however, affect the top gas composition. A need for further research to determine the range of the difference in temperatures of gas and solid in the thermal reserve zone tolerable for smooth blast furnace operation is highlighted. [ABSTRACT FROM AUTHOR]

In this study, a mathematical model was formulated to characterize the functioning of third‐generation enzyme‐based amperometric biosensors. This study utilized a horseradish peroxidase (HRP)‐based, screen‐printed biosensor. The model parameters were determined using the Environment for Modeling Simulation and Optimization (EMSO), validated with experimental data, and exhibited high determination coefficients, indicating the accuracy of the models in capturing biosensor behavior. Simulations based on this model emphasize diffusion as a limiting factor. Further sensitivity analysis was conducted using simulated response surfaces and biosensor performance optimization, which confirmed that higher concentrations of HRP in the thinnest polymeric film resulted in enhanced biosensor sensitivity. [ABSTRACT FROM AUTHOR]

Leaf respiratory carbon loss decreases independent of temperature as the night progresses. Detailed nighttime measurements needed to quantify cumulative respiratory carbon loss at night are challenging under both lab and field conditions. We provide a simple yet accurate approach to represent variation in nighttime temperature‐independent leaf respiratory CO2 efflux in environments with both stable and fluctuating temperatures, which requires no detailed measurements throughout the night. We demonstrate that the inter‐ and intraspecific variation in the cumulative leaf respiratory CO2 efflux at constant temperature, at any length of night, scales linearly with the inter‐ and intraspecific variation in initial measurement of leaf respiratory CO2 efflux at the same temperature at the beginning of the night. This approach informs large‐scale predictions of cumulative leaf respiratory CO2 efflux, which is needed to understand plant carbon economy in global change studies as well as in global modeling and eddy covariance monitoring of the land–atmosphere exchange of CO2. [ABSTRACT FROM AUTHOR]

Glacial isostatic adjustment (GIA) describes the response of the solid Earth, oceans, and gravitational field to the spatio‐temporal evolution of ice sheets during a glacial cycle. Present‐day vertical displacements and sea‐level changes vary throughout eastern North America in response to the melting of the Laurentide Ice Sheet following the Last Glacial Maximum. We use the open‐source software SELEN4.0 (a SealEveL EquatioN solver) to investigate the influence of GIA on vertical land motions and sea‐level changes in eastern North America. Further, we evaluate the uncertainties associated with the lithospheric thickness and viscosity structure using an ensemble modeling approach (129,956 total simulations). We identify the best‐fitting rheological profiles by comparing modeled vertical displacements to vertical velocity rates derived from Global Positioning System (GPS). We find a general pattern of subsidence (causing accelerated relative sea‐level rise) in the eastern United States region and uplift (causing relative sea‐level fall) in the eastern Canada region consistent with previous studies for two tested ice sheet models (ICE‐6G(VM5a) and ICE‐7G(VM7)). Overall, we find lower rates of modeled vertical displacement using ICE‐6G(VM5a) compared with ICE‐7G(VM7), which produces lower residuals when compared with the GPS‐derived vertical velocity rates. Our ensemble analysis identifies adjustments to the nominal VM5a and VM7 viscosity models that improve fits to the GPS‐imaged vertical velocity rates throughout eastern North America and on the North American Atlantic Coast. The differences in our best‐fitting models for inland versus coastal regions highlight the importance of exploring lateral viscosity variations for GIA modeling throughout North America and elsewhere. Plain Language Summary: Approximately 19,000–26,000 years ago a massive ice sheet covered Canada and a portion of the northern United States. We investigate the Earth's surface movements following the melting of the ice sheet throughout eastern North America. Through computational modeling, we predict rates of vertical land motion and relative sea‐level change throughout eastern North America. We see a general pattern of downward movements (causing relative sea‐level rise) in the eastern United States region and upward movements (causing relative sea‐level fall) in the eastern Canada region. However, modeled rates vary depending on the assumptions about Earth's internal structure. We test different models of Earth structure, based upon variations of the Earth structure profiles paired with two published models of ice sheet history. Our different models vary the lithospheric thickness and radial viscosity structure (viscosity varies by depth only). By comparing the rates of Earth's surface movements generated by these different models to published data of observed vertical land motions, we determine which Earth structure models produce the best fits to the published observations. Differences in the best‐fitting Earth structure for different regions of eastern North America indicate the importance of exploring Earth structures that vary both radially and laterally. Key Points: Modeled present‐day vertical displacement and sea‐level change rates fit observed data better using ICE‐6G(VM5a) compared with ICE‐7G(VM7)Ensemble analysis suggests adjustments to VM5a and VM7 viscosity models improve fits to geodetic data throughout eastern North AmericaRegional differences in best‐fitting Earth structure support the adoption of lateral viscosity in glacial isostatic adjustment modeling [ABSTRACT FROM AUTHOR]

Shear stress levels on reverse faults are anticipated to be several times higher than on normal faults with the same pore pressure ratio. In addition, ruptures on normal faults release gravitational potential energy, whereas earthquakes on reverse faults expend work in uplifting rocks. In this study, I investigate the significance of these differences for earthquake cycles and I question whether the source of energy driving earthquakes is the same on reverse and normal faults. Based on the assumption that normal and reverse faults have the same background frictional properties and pore pressure states, I use numerical simulations with a two‐dimensional dynamic elastic‐plastic model to show that due to stress differences, earthquakes on reverse faults tend to occur less frequently, produce more coseismic slip and stress drop and involve higher slip rates than ruptures on normal faults with equivalent dimensions. The analysis also shows differences in the energy changes associated with earthquake cycles on reverse and normal faults. However, the earthquakes on both fault types result from abrupt release of elastic strain energy, which proceed and essentially drive variations in gravitational potential energy. Thus, ruptures on both normal and reverse faults are consistent with elastic rebound theory. Plain Language Summary: Normal faults found in regions experiencing extension are normally thought to have lower stress levels than reverse faults in zones of convergence. In addition, whereas the action of normal faulting causes mostly subsidence and is therefore assisted by gravity, reverse faulting tends to uplift topography, which requires that work be done against gravity. This study uses numerical modeling to address whether there are significant differences in the earthquakes on reverse and normal faults, assuming that they have identical pore pressures and frictional properties. The results show that ruptures on reverse faults are larger, more energetic and less frequent than earthquakes on normal faults. These differences are due to the higher stress levels on reverse faults than normal faults with the same dimension. The results also show than although earthquakes on normal faults are assisted by gravity, they result from an abrupt drop in elastic energy in the same way as ruptures on reverse faults. Thus, the results do not support claims that earthquakes on normal faults have a different energy source and require an explanation other than elastic rebound. Key Points: Model earthquakes on reverse faults involve higher slip rates, more slip, and larger stress drop and occur less frequently than on normal faultsModel earthquakes on both fault types involve abrupt release of elastic strain energy, much of which is dissipated plasticallyDespite differences in energetics, model earthquakes on both fault types are consistent with elastic rebound theory [ABSTRACT FROM AUTHOR]

Understanding the interaction between Mars and the solar wind is crucial for comprehending the atmospheric evolution and climate change on Mars. To gain a comprehensive understanding of the Martian plasma environment, global numerical simulations are essential in addition to spacecraft observations. However, there are still discrepancies among different simulation models. This study investigates how these discrepancies stem from the considered physical processes and numerical implementations. We compare two global multispecies MHD models: the "Sun model" based on the BATS‐R‐US code and the "Sakata model" based on a newly developed multifluid model MAESTRO. By employing the same typical upstream conditions and the same neutral atmosphere for current Mars, along with similar numerical implementations such as inner boundary conditions, we obtain simulation results that exhibit unprecedented agreement between the two models. The dayside results are nearly identical, especially along the subsolar line, indicating the robustness of MHD models to predict dayside interaction under given upstream conditions and ionosphere assumptions. The escape rates of planetary ions are also in good agreement. However, discrepancies remain in the terminator and nightside regions. Detailed numerical implementations, including inner boundary conditions, magnetic field divergence control methods, and radial resolutions, are shown to influence certain aspects of the results greatly, such as magnetotail configuration and ion diffusion. Key Points: The same physical assumptions are employed for two different global multispecies MHD modelsThe results for the dayside interaction and planetary ion escape are in unprecedented good agreementDetails of the numerical implementations influence the results, especially on the nightside [ABSTRACT FROM AUTHOR]

Research into network dynamics of spreading processes typically employs both discrete and continuous time methodologies. Although each approach offers distinct insights, integrating them can be challenging, particularly when maintaining coherence across different time scales. This review focuses on the Microscopic Markov Chain Approach (MMCA), a probabilistic f ramework originally designed for epidemic modeling. MMCA uses discrete dynamics to compute the probabilities of individuals transitioning between epidemiological states. By treating each time step—usually a day—as a discrete event, the approach captures multiple concurrent changes within this time frame. The approach allows to estimate the likelihood of individuals or populations being in specific states, which correspond to distinct epidemiological compartments. This review synthesizes key findings from the application of this approach, providing a comprehensive overview of its utility in understanding epidemic spread. [ABSTRACT FROM AUTHOR]

Bouillon is a widely consumed condiment in many West African countries, including Nigeria. Although Nigeria has mandatory fortification standards for multiple food vehicles, bouillon fortification could help address remaining gaps in micronutrient intake. Using household food consumption data, we used the nutrient density method to model the additional contribution of bouillon fortified with vitamin A (40–250 µg/g bouillon), folic acid (20–120 µg/g), vitamin B12 (0.2–2 µg/g), iron (0.6–5 mg/g), and zinc (0.6–5 mg/g) for meeting micronutrient requirements of women of reproductive age (WRA) and children aged 6–59 months. Accounting for existing fortification programs, our results showed that, except for iron, the prevalence of inadequacy was substantially higher among WRA and children living in poorer and rural households. Given the ubiquity of bouillon consumption, bouillon fortification has the potential to virtually eliminate vitamin A, folate, and vitamin B12 inadequacy, reduce the prevalence of zinc inadequacy by over 20 percentage points, and improve equity in the micronutrient adequacy of diets across socioeconomic strata and urban and rural residence. Our results also suggested that designing a bouillon fortification program would require careful planning to balance reductions in inadequacy with the risk of high intakes. This evidence provides important input into decisions around bouillon fortification in Nigeria. [ABSTRACT FROM AUTHOR]

Highlights In this study, we present a model for predicting the Young's modulus of polymer/nanodiamond (ND) composites, taking into account the interphase properties. The Christensen‐Lo model is adapted and refined to predict the modulus of ND‐based nanocomposites by considering the properties of spherical NDs and their surrounding interphase. The outcomes of the developed model are benchmarked against experimental data, exploring the impact of various parameters, such as ND radius, ND concentration, and interphase properties (thickness and modulus) on the nanocomposite modulus. Findings suggest an inverse correlation between the size of the nanoparticles and the modulus of nanocomposite. Specifically, it is observed that nanoparticles with a minimum radius of 1 nm and a maximum concentration of 5 vol% can increase the nanocomposite modulus by 180%. Additionally, maximum thickness and modulus of the interphase can significantly improve the nanocomposite modulus. The highest interphase thickness of 10 nm and maximum interphase modulus of 100 GPa can grow the modulus of samples by 300%. The predicted influences of all parameters on the nanocomposite modulus validate the accuracy of the developed model. A model for the Young's modulus of polymer nanodiamond (ND) composites is presented. ND radius, ND concentration, and interphase thickness and modulus are considered. The outcomes of the developed model are compared to the experimental data. 5 vol% of the smallest ND (R = 1 nm) increases the nanocomposite modulus by 180%. The thickest and the toughest interphase enhance the nanocomposite modulus by 300%. [ABSTRACT FROM AUTHOR]

Belzutifan (Welireg, Merck & Co., Inc., Rahway, NJ, USA) is an oral, potent hypoxia‐inducible factor‐2α inhibitor, recently approved in the United States for the treatment of von Hippel–Lindau (VHL) disease‐associated renal cell carcinoma (RCC) and other VHL disease‐associated neoplasms. Safety and efficacy were investigated in two clinical studies: a Phase 1 dose escalation/expansion study in solid tumors and RCC and a Phase 2 study in VHL‐RCC. A population pharmacokinetic model was used to estimate belzutifan exposures to facilitate exposure–response (E‐R) analyses for efficacy and safety endpoints. Relationships between exposure and efficacy (overall response rate, disease control rate, progression‐free survival, best overall tumor size response, and other endpoints), safety outcomes (Grade ≥3 anemia, Grade ≥3 hypoxia, and time to first dose reduction/dose interruption), and pharmacodynamic biomarkers (erythropoietin [EPO] and hemoglobin [Hgb]) were evaluated using various regression techniques and time‐to‐event analyses. Efficacy E‐R was generally flat with non‐significant positive trends with exposure. The safety E‐R analyses demonstrated a lack of relationship for Grade ≥3 hypoxia and a positive relationship for Grade ≥3 anemia, with incidences also significantly dependent on baseline Hgb. Exposure‐dependent reductions in EPO and Hgb were observed. Based on the cumulative benefit–risk assessment in VHL disease‐associated neoplasms using E‐R, no a priori dose adjustment is recommended for any subpopulation. These analyses supported the benefit–risk profile of belzutifan 120 mg once daily dosing in patients with VHL‐RCC for labeling and the overall development program. [ABSTRACT FROM AUTHOR]

Most studies regarding heat transfer on low‐finned tubes address the condensation of refrigerants and water on copper tubes. Existing models are mainly validated for this use case since studies regarding different substances or tube materials are scarce in the literature. This paper presents measurement data on the condensation of n‐propanol, isopropanol, isobutanol, and acetone on low‐finned stainless‐steel tubes. Together with experimental data from the literature, the measurements are used to test the performance of models from the literature. As the investigated models fail to describe all measurement data, a new model based on a set of dimensionless numbers is derived and fitted to the experimental data. [ABSTRACT FROM AUTHOR]

Adaptively managing marine protected areas (MPAs) requires accurately assessing whether established MPAs are achieving their goals of protecting and conserving biomass, especially for harvested populations. Ecological MPA assessments commonly compare inside of the MPA to a reference point outside of and/or before implementation (i.e., calculating "response ratios"). Yet, MPAs are not simple ecological experiments; by design, protected populations interact with those outside, and population dynamic responses can be nonlinear. This complicates assessment interpretations. Here, we used a two‐patch population model to explore how MPA response ratios (outside–inside, before–after, and before–after‐control‐impact [BACI]) for fished populations behave under different conditions, like whether the population is receiving a sustainable larval supply or if it is declining despite protection from harvest. We then conducted a Bayesian evaluation of MPA effects on fish and invertebrate populations based on data collected from 82 published studies on 264 no‐take MPAs worldwide, using the results of an earlier global meta‐analysis as priors. We considered the effects of calculating different summary metrics on these results, drawing on the theoretical insights from our population model as a comparative framework. We demonstrate that not all response ratio comparison types provide the same information: For example, outside–inside and BACI comparisons can fail to detect population decline within MPAs, whereas before–after comparisons likely detect that pattern. Considering these limitations, we nonetheless found that MPAs globally are producing positive outcomes, with on average greater biomass, density, and organism size within their boundaries than reference sites. However, only a small portion of studies (18 of 82) provided the temporal data necessary to determine that protection, on average, has led to increased abundance of populations within MPAs over time. These findings demonstrate the importance of considering the underlying system dynamics when assessing MPA effects. Assuming that large outside–inside or BACI response ratios always reflect large and net positive conservation effects may lead to misleading conclusions, we recommend that: (1) when assessing specific MPA effects, empirical findings be considered alongside theoretical knowledge relevant to that MPA system, and (2) management should respond to the local conditions and outcomes, rather than a blanket expectation for positive MPA effects. [ABSTRACT FROM AUTHOR]

The management of developed barrier islands is often piece‐meal and reactionary despite the complex, dynamic nature of these systems, and sustainable practices will become increasingly difficult due to heightened pressures of climate change. Adaptation actions, including nature‐based solutions, need to be thoroughly evaluated prior to implementation to understand system‐wide impacts and avoid maladaptation. Anarde et al. (2024a), (https://doi.org/10.1029/2023ef003672), Anarde et al. (2024b), (https://doi.org/10.1029/2023ef004200) is the latest important contribution in a growing body of transdisciplinary research that more robustly evaluates the complex physical process‐and‐response relationship of barrier systems via sophisticated numerical modeling approaches that also interface with socioeconomic models to inform coastal management actions in response to mitigating coastal risk. This new research indicates the importance of coordinated system‐scale barrier island management, as strategies to reduce coastal hazard risk in one location will directly affect adjacent communities. Further, this work demonstrates that reducing barrier management interventions may actually promote barrier recovery and sustainability in the face of sea level rise. In addition, recent advances in the analysis and application of remotely sensed data from satellites and oblique aerial photography provide scientists an unprecedented opportunity to track coastal evolution over a wide range of spatial and temporal scales at minimal cost. As sea level rise and changing storm patterns challenge the sustainable management of barrier island systems, integrating these advanced, transdisciplinary tools will enable scientists and coastal practitioners to more thoroughly evaluate coastal adaptation options, efficiently invest limited resources to mitigate coastal hazard risk for communities, support healthy ecosystems, and reduce system‐wide impacts. Plain Language Summary: Barrier island communities and ecosystems are on the front lines of climate change, as accelerating sea level rise and changing storm conditions increase the probability of flooding and erosion for these narrow strips of sand. New research by Anarde et al. (2024a), (https://doi.org/10.1029/2023ef003672), Anarde et al. (2024b), (https://doi.org/10.1029/2023ef004200) shows how typical, often reactive management actions to protect coastal communities on barrier islands (e.g., building tall dunes) are short‐sighted, and may actually threaten the long‐term sustainability of these communities. Further, local actions such as beach nourishment and construction of hard structures can affect adjacent communities, and therefore coastal management strategies must consider the entire barrier island system. Using numerical modeling, satellite observations, and social and economic drivers will allow for better informed decisions that promote the sustainability of these threatened coastal communities. Key Points: Barrier island communities and ecosystems are on the front lines of climate changeCoastal management strategies must consider the entire barrier island systemTransdisciplinary research will allow for better informed decisions that promote the sustainability of barrier island communities [ABSTRACT FROM AUTHOR]

Coastal change and evolution are the product of physical drivers (e.g., waves) tightly coupled with human behavior. As climate change impacts intensify, demand is increasing for information on where, when, and how coastal areas may change in the future. Although considerable research investments have been made in understanding the physical drivers and processes that modify and shape coastal environments, many do not account for human behavior, compromising the accuracy of comprehensive future change predictions. We outline four social science approaches—historic case studies, simulations, longitudinal studies, and longitudinal studies supported by experimental data—that can be coupled with physical change information to support transdisciplinary understanding of future change. A fundamental need for each approach is more and better empirical data to better gauge human behavior. In addition, foundational investments in transdisciplinary collaboration help research teams support the integration of these approaches. Plain Language Summary: Coastal areas are constantly being reshaped by waves, tides, storms, and sea‐level rise. Humans also change the coast, often to protect themselves and places of value from ongoing natural changes. Therefore, understanding how the coast may change in the future requires science teams that can incorporate both the natural changes that may occur with human actions that may modify the coast in response to or in anticipation of these changes. We outline the need for evidence‐based information on human behavior and four ways science teams might integrate this information with our understanding of how the coast may change naturally to improve predictions of future coastal change. Key Points: There are limited empirical data documenting how humans respond, and do not respond, to physical changes along the coastLongitudinal studies can leverage co‐production to yield insights on future human‐coastal dynamicsBuilding trust and a shared language in transdisciplinary science teams provides a foundation to support integrative coastal work [ABSTRACT FROM AUTHOR]

We introduced DrYFiT (drying data fitting tool), a Microsoft Excel freeware tool to be used for modeling thin‐layer drying of foods, which is available at https://drive.google.com/drive/folders/1ouompmNkmdmw1KMTJUnY0t8dJqSJ9iKv?usp=drive%5flink. There are 12 models in the tool and it can be used without any modeling and programming skills. Time and moisture ratio data can be entered and one of models available (one at a time) can be selected to describe the drying data. Parameter values, standard error of the parameters, p value and a statement that indicates whether the parameter is statistically significant or not (α = 0.05) are reported. Moreover, R2, adjusted R2 and root mean square error values are calculated for each model. Users can instantaneously observe the experimental data and the model fit on the same graph. Residual plot is given next to this graph. It is possible for the users to have the results of all models applied to drying data within a couple of minutes. The results of DrYFiT were compared with some popular software programs used for nonlinear regression and identical values (parameters, standard errors, p values, goodness‐of‐fit statistics) were obtained for 40 datasets. [ABSTRACT FROM AUTHOR]

The lithosphere of Mars accommodates horizontal shortening through folding and faulting, producing landforms described as wrinkle ridges or lobate scarps. Despite this nomenclature, we lack a deep understanding of the drivers of morphological differences observed between landform types. This study aims to develop a quantitative model for shortening landform classification based on surface morphology, subsurface architecture, and strain accommodation, facilitating interpretations of where and how lithospheric stresses are recorded. We developed this model by mapping 100 shortening landforms in a Geographic Information System, recording 12 unique geomorphic parameters such as length and asymmetry, and estimating the strain of each landform. We conducted a Discriminant Function Analysis (DFA) using surface morphometrics. This DFA produced a predictive linear function for categorizing wrinkle ridges and lobate scarps and for quantifying which landforms were exemplars within those categories. The three most influential variables on the surface morphometry DFA were the maximum width, forelimb slope, and back limb length. We then modeled the subsurface structural geology of 50 landforms using MOVE Structural Geology Modeling Software and conducted a second DFA based on subsurface metrics. DFA was most influenced by the dip and depth of the lower ramp base. When both surface morphology and subsurface geometry are input into single DFA, wrinkle ridges and lobate scarps can be distinguished quantitatively 96% of the time. Our results also show that lobate scarps accommodate more strain and imply that studies should consider landform type when interpreting local, regional, and global geological stress histories. Plain Language Summary: The tectonic structures of a planet record its geologic history. Some of these structures, such as those classified as lobate scarps and wrinkle ridges, account for the horizontal shortening of the planet's surface. These two groups of shortening structures are observed on the surface of almost every rocky planet. Planetary geologists have historically assumed that wrinkle ridges and lobate scarps represent different types or amounts of shortening based on differences in their visual morphologies. In this work, we mapped 100 of these landforms on Mars and quantified their surface characteristics. We then further analyzed 50 landforms using a structural geology modeling software to assess their subsurface fault and fold geometries. Using the parameters we measured, we applied a statistical analysis called a Discriminant Function Analysis to quantify and learn about the differences between these landform types. We find that lobate scarps are rooted by faults that extend deeper into the subsurface than faults that underly wrinkle ridges, and that because of the greater variability in landform characteristics, lobate scarps may represent a range of stages in the formation of these landforms while wrinkle ridges developed entirely during one phase of the geologic history of Mars. Key Points: Shortening landforms on Mars were analyzed at the surface and subsurface to quantify their morphometrics and structural geometriesTraditional definitions of lobate scarps and wrinkle ridges are end member descriptions of landforms that exist across a morphological spectrumLobate scarps are fault‐dominated structures while wrinkle ridges are fold‐dominated structures [ABSTRACT FROM AUTHOR]

Many methods have been proposed to model the spatial distribution of a species. While some methods have been specifically designed for this purpose, others are well‐known statistical tools that can be used in many scientific fields. In this paper, I propose a new ecological niche model, called the Environmental String Model (ESM), that is based on the concept of environmental string, which is defined as being a combination of environmental variables, with as many nodes as environmental variables. There are two types of environmental strings: (1) the abundance‐known string and (2) the abundance‐unknown string (or target string) for which an estimation of abundance is searched. The novelty of the model is that it assesses the abundance associated with a target string from nearby abundance‐known strings, which preserve the local multidimensional relationships with the target string. The model does not provide an abundance estimate in the absence of data from a similar environment and it can therefore deal with truncated spatial distributions or niches. It is tested in the North Atlantic Ocean on two key copepod species, Calanus finmarchicus and Calanus helgolandicus, which have been monitored by the Continuous Plankton Recorder (CPR) survey for decades. I investigate the influence of variables on model performance. I show that the model reconstructs the mean spatial distribution and seasonal fluctuations in both Calanus well. When compared with generalized linear models (GLMs), generalized additive models (GAMs) and generalized regression neural network (GRNN), the ESM gives the best performance. I propose a number of indicators to evaluate the robustness of estimated abundance in space and time and show how the model may be extended to presence/absence or presence‐only data. I think that the ESM could be used to fill gaps in any sampling program such as the CPR survey and many satellite databases (e.g., ocean color and photosynthetically active radiation). [ABSTRACT FROM AUTHOR]

Both nitric oxide (NO) and nitrogen dioxide (NO2) gasses are toxic to humans but are commonly found in industrial settings such as semiconductor manufacturing sites. Due to the spontaneous oxidation of NO to NO2 under ambient conditions, individuals working with NO may in fact be exposed to both gasses in the case of an accidental release. Unfortunately, most safety materials provided to NO users do not address the potential for associated NO2 toxicity, and, until now, models developed to predict health consequences following a release of NO have not appropriately considered the oxidation kinetics nor the toxicity of both NO and NO2 in their assessments. This paper describes an improved multi‐module model that addresses these limitations and explores whether facilities using NO should consider adopting measures that can mitigate the simultaneous health effects of both gasses. The model predicts the morbidity (intoxication/injury), mortality (death), and treatment outcomes that may arise following an industrial NO release by first calculating the doses of both NO and NO2 received by exposed individuals and then applying newly defined toxicity parameters for NO and NO2 to assign dose‐dependent probabilities for the onset of intoxication and/or death and the ability of appropriate treatment(s) to save lives. Modeling results indicate low risk to worker health in the likeliest release scenarios while identifying less likely situations that carry substantially higher risk. Moreover, these results indicate that risks to worker health can be mitigated with simple measures like maintaining reliable alarms, adequate ventilation, and on‐site supplies of methylene blue, as well as encouraging quick responses by personnel. With appropriate parameterization, the improved modeling framework is generalizable to any chemical release, especially multi‐hazard releases resulting from the conversion of one toxic compound into another under likely environmental conditions. By directly addressing the toxicities of multiple compounds, the improved model presents a more realistic picture of the potential health consequences of a chemical release. This generalizable framework for modeling of multi‐hazard chemical releases can inform preparedness and risk mitigation strategies for NO release events. Given the spontaneous oxidation of NO to NO2 under ambient conditions, individuals working with NO in industrial contexts may be exposed to both NO and NO2. This paper describes an improved multi‐module model that considers facility ventilation, oxidation kinetics, and the toxicity of both NO and NO2 and applies the model to explore whether facilities using NO should consider adopting measures that can mitigate the potential for adverse health effects from both gasses during a NO release. [ABSTRACT FROM AUTHOR]

The controls on the development of submarine channel sinuosity are contested: slope gradient and Coriolis forcing have both been recognized as key governing factors: gradient via an inverse relationship (low sinuosity at high slope and vice versa), and Coriolis forcing through its effect on sedimentation patterns (reducing lateral bend migration, and hence sinuosity development, at high latitudes and/or in large channels). Using theoretical models to calculate the bulk properties of channelized turbidity currents, this study investigates the joint role of the Coriolis force and parameters including channel size, downchannel slope and turbidity current properties in the development of submarine channel sinuosity. Model validation is undertaken through the comparison of the calculated turbidity current tilting against the measured tilting of channel levees in the Northwest Atlantic Mid‐Ocean Channel; this approach is then used to evaluate the controls on channel sinuosity in nine other modern seafloor channels. The results indicate that the Coriolis force only becomes significant when the size of the channel, the slope gradient and flow conditions are within appropriate ranges instead of solely being dependent on latitude. Thus, thick and dense (≥1% bulk sediment concentration) flows traveling within steep‐gradient, small‐scale channels were shown to be relatively less susceptible to flow modification by Coriolis forcing even at high latitudes. On the other hand, thin and dilute (≪1% bulk sediment concentration) flows in shallow‐gradient, large‐scale channels showed susceptibility to Coriolis forcing at all latitudes. These results offer new insights into submarine channel evolution and intra‐channel sedimentation patterns. Plain Language Summary: Sediments are widely distributed in the oceans by underwater currents akin to powder snow avalanches. These "turbidity currents" may sculpt the sea floor to build submarine channels which, like rivers, may range in sinuosity from being virtually straight to highly sinuous. Several competing controls have been suggested to explain this variation. Some argue that slope is most important, with low sinuosity channels forming on high angle slopes and vice versa. Others claim that the Coriolis force, which affects flows moving across a rotating surface (such as the Earth), is the main control ‐ either via latitude alone (with high sinuosity channels restricted to lower latitudes) or only affecting channels that are large enough. To test these ideas we developed a new numerical modeling approach that looks at the combined effects of channel axis gradient, channel size and flow conditions. By modeling the tilt of turbidity currents flowing around bends we show that single factors cannot be used to explain channel sinuosity. The model is tested with real world data. Although sinuosity is generally greater at low latitudes there are exceptions; variations across a range of controlling factors can produce channels of any sinuosity at any latitude. Key Points: We present a novel methodology to assess the contested controlling factors on the development of sinuous channelsDeep and dense flows that pass through small channels in steep slopes, regardless of the latitude, promote sinuosityDilute and shallow flows that pass through large channels in low gradient systems hinder sinuosity development at any latitude [ABSTRACT FROM AUTHOR]

Inverse problems aim at determining model parameters that produce observed data to subsequently understand, predict or manage hydrological or other environmental systems. While statistical inversion is especially popular, its sampling‐based nature often inhibits its application to computationally costly models, which has compromised the use of the Generalized Likelihood Uncertainty Estimation (GLUE) methodology, for example, for spatially distributed (partial) differential equation based models. In this study we introduce multilevel GLUE (MLGLUE), which alleviates the computational burden of statistical inversion by utilizing a hierarchy of model resolutions. Inspired by multilevel Monte Carlo, most parameter samples are evaluated on lower levels with computationally cheap low‐resolution models and only samples associated with a likelihood above a certain threshold are subsequently passed to higher levels with costly high‐resolution models for evaluation. Inferences are made at the level of the highest‐resolution model but substantial computational savings are achieved by discarding samples with low likelihood already on levels with low resolution and low computational cost. Two example inverse problems, using a rainfall‐runoff model and groundwater flow model, demonstrate the substantially increased computational efficiency of MLGLUE compared to GLUE as well as the similarity of inversion results. Findings are furthermore compared to inversion results from Markov‐chain Monte Carlo (MCMC) and multilevel delayed acceptance MCMC, a corresponding multilevel variant, to compare the effects of the multilevel extension. All examples demonstrate the wide‐range suitability of the approach and include guidelines for practical applications. Key Points: We extend the Generalized Likelihood Uncertainty Estimation methodology to a strategy that considers multiple resolution levels (MLGLUE)We demonstrate the acceleration with MLGLUE for different spatial (groundwater flow model) and temporal (rainfall‐runoff model) resolutionsWe show that inversion results from multilevel and conventional methods align and discuss factors affecting computational efficiency [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the stress evolution of high‐density polyethylene (HDPE) at loading, relaxation, and recovery stages in a multi‐relaxation‐recovery (RR) test. The analysis is based on a three‐branch spring‐dashpot model that uses the Eyring's law to govern the viscous behavior. The spring‐dashpot model comprises two viscous branches to represent the short‐ and long‐term time‐dependent stress responses to deformation, and a quasi‐static branch to represent the time‐independent stress response. A fast numerical analysis framework based on genetic algorithms was developed to determine values for the model parameters so that the difference between the simulation and the experimental data could be less than 0.08 MPa. Using this approach, values of the model parameters were determined as functions of deformation and time so that the model can simulate the stress response at loading, relaxation, and recovery stages of the RR test. The simulation also generated 10 sets of model parameter values to examine their consistency. The study concludes that the three‐branch model can serve as a suitable tool for analyzing the mechanical properties of HDPE, and values for the model parameters can potentially be used to characterize the difference among PEs for their mechanical performance. Highlights: Developed computer programs to determine parameter values automatically.Explained the unusual stress drop during stress recovery after unloading.Evaluated the statistical range of the parameter values for the good fitting. [ABSTRACT FROM AUTHOR]

In this paper, test results for woven ceramic matrix composites (CMCs) based on an oxide matrix and oxide fiber are presented. Stress–strain curves under cyclic loading for different in‐plane fiber orientations as well as strength values for different fiber orientations under tension and compression and under pure shear are presented. Based on the experimental data, a nonlinear damage model is derived which allows to determine the progressive degradation of the elastic moduli and the nonelastic remanent strain in a satisfactory manner. It has been implemented into the finite element code ANSYS and shows excellent convergence behavior. To predict the failure of CMC components, the failure mode concept proposed by Cuntze is extended to include friction effects due to tension and compression on the in‐plane shear failure mode. The predicted failure onset matches the experimental data very well, whereas existing models like the max‐stress or the Tsai–Hill criteria show larger deviations. [ABSTRACT FROM AUTHOR]

The δ‐conotoxins, a class of peptides produced in the venom of cone snails, are of interest due to their ability to inhibit the inactivation of voltage‐gated sodium channels causing paralysis and other neurological responses, but difficulties in their isolation and synthesis have made structural characterization challenging. Taking advantage of recent breakthroughs in computational algorithms for structure prediction that have made modeling especially useful when experimental data is sparse, this work uses both the deep‐learning‐based algorithm AlphaFold and comparative modeling method RosettaCM to model and analyze 18 previously uncharacterized δ‐conotoxins derived from piscivorous, vermivorous, and molluscivorous cone snails. The models provide useful insights into the structural aspects of these peptides and suggest features likely to be significant in influencing their binding and different pharmacological activities against their targets, with implications for drug development. Additionally, the described protocol provides a roadmap for the modeling of similar disulfide‐rich peptides by these complementary methods. [ABSTRACT FROM AUTHOR]

We explore the viability of modeling dynamic problems with a new formulation of an impulse‐based Level‐Set DEM (LS‐DEM). The new formulation is stable, fast, and energy conservative. However, it can be numerically stiff when the assembly has substantial mass differences between particles. We also demonstrate the feasibility of modeling deformable structures in a rigid body framework and propose several enhancements to improve the convergence of collision resolution, including a hybrid time integration scheme to separately handle at rest contacts and dynamic collisions. Finally, we extend the impulse‐based LS‐DEM to include arbitrarily shaped topographic surfaces and exploit its algorithmic advantages to demonstrate the feasibility of modeling realistic behavior of granular flows. The new formulation significantly improves the performance of dynamic simulations by allowing larger time steps, which is advantageous for observing the full development of physical phenomena such as rock avalanches, which we present as an illustrative example. [ABSTRACT FROM AUTHOR]

While deterministically predicting the time and location of earthquakes remains impossible, earthquake forecasting models can provide estimates of the probabilities of earthquakes occurring within some region over time. To enable informed decision‐making of civil protection, governmental agencies, or the public, Operational Earthquake Forecasting (OEF) systems aim to provide authoritative earthquake forecasts based on current earthquake activity in near‐real time. Establishing OEF systems involves several nontrivial choices. This review captures the current state of OEF worldwide and analyzes expert recommendations on the development, testing, and communication of earthquake forecasts. An introductory summary of OEF‐related research is followed by a description of OEF systems in Italy, New Zealand, and the United States. Combined, these two parts provide an informative and transparent snapshot of today's OEF landscape. In Section 4, we analyze the results of an expert elicitation that was conducted to seek guidance for the establishment of OEF systems. The elicitation identifies consensus and dissent on OEF issues among a non‐representative group of 20 international earthquake forecasting experts. While the experts agree that communication products should be developed in collaboration with the forecast user groups, they disagree on whether forecasting models and testing methods should be user‐dependent. No recommendations of strict model requirements could be elicited, but benchmark comparisons, prospective testing, reproducibility, and transparency are encouraged. Section 5 gives an outlook on the future of OEF. Besides covering recent research on earthquake forecasting model development and testing, upcoming OEF initiatives are described in the context of the expert elicitation findings. Plain Language Summary: The exact location, time, and magnitude of future earthquakes cannot be predicted. However, based on past earthquake sequences, it is possible to assess probabilities for future earthquakes. This is called earthquake forecasting. Operational Earthquake Forecasting (OEF) systems are designed to provide near‐real‐time authoritative earthquake forecasts, based on current earthquake activity, to aid the decision‐making of various societal stakeholders. Setting up these systems is complex, involving decisions about which model to use, how to best test the model, and how to turn earthquake probability estimates into practical information. This review captures the current state of OEF worldwide and analyzes expert recommendations on the development, testing, and communication of earthquake forecasts. Section 2 provides an overview of OEF‐related research and the background knowledge required to understand the other parts. Section 3 describes existing OEF systems of Italy, New Zealand, and the United States in detail. Section 4 discusses an elicitation of expert views on modeling, testing, and communicating earthquake forecasts (Mizrahi, Dallo, & Kuratle, 2023, https://doi.org/10.3929/ethz‐b‐000637239). Data from the elicitation allow to identify consensus and dissent on OEF issues and provide guidance for future earthquake forecasting efforts. Finally, Section 5 gives an outlook on future OEF‐related research and planned OEF efforts at various institutions. Key Points: We capture the state of earthquake forecasting systems in Italy, New Zealand, and the United States, and future plans in these and other countriesExperts encourage benchmark comparison, prospective testing, reproducibility and transparency, but avoid endorsing specific models or testsExperts stress the need to co‐design forecast communication products with end‐users to ensure their societal relevance and usefulness [ABSTRACT FROM AUTHOR]

The phase problem in the context of focusing synchrotron beams with X‐ray lenses is addressed. The feasibility of retrieving the surface error of a lens system by using only the intensity of the propagated beam at several distances is demonstrated. A neural network, trained with a few thousand simulations using random errors, can predict accurately the lens error profile that accounts for all aberrations. It demonstrates the feasibility of routinely measuring the aberrations induced by an X‐ray lens, or another optical system, using only a few intensity images. [ABSTRACT FROM AUTHOR]

The purpose of the PRODEC scenario‐based design method is the incremental cross‐fertilization and refinement of procedural scenarios and declarative configurations. It uses virtual prototypes of the developed systems (mainly life‐critical systems) to conduct human‐in‐the‐loop simulations (HITLSs). Based on human systems integration (HSI) principles and criteria, as well as expertise and experience in the domain at stake, this HSI approach grounded in virtual environments requires a clear definition of physical and cognitive tangibility metrics to assess the distance between virtual and tangible (grasp) dimensions of the system being developed when it is put to work. PRODEC considers human and machine systems described in terms of structures and functions incrementally designed using procedural scenarios (i.e., stories) in task and activity networks, which provide life to declarative configurations (i.e., system's functions and structures). This active modeling and simulation process enables the discovery of emergent structures and functions of the system being developed when it is virtually operated. PRODEC's use is illustrated in an example. We discuss the use of PRODEC and its results as to how they can be used with digital twins. [ABSTRACT FROM AUTHOR]

Hip dislocation is one of the leading causes of failure and revision surgery for total hip arthroplasty. To reduce dislocation rates, lipped liners have been designed with an elevated portion of the rim, to increase jump distance and maintain greater contact area. While it has been documented that lipped liners help reduce dislocation, the objective of this study is to investigate whether lipped liners also help reduce smaller instances of hip micromotion, separation, and edge loading. This study uses an advanced three‐dimensional preoperative planning tool to analyze 10 patients, each implanted with both a neutral and lipped liner. Patients within the simulation performed stance phase of gait, and each cup was implanted with the rotation center aligned with the preoperative acetabulum center as well as shifted medially by 2, 4, 6, 8, and 10 mm, yielding 120 total simulations. Specific postoperative outcomes‐of‐interest included specified component offset, resultant in vivo hip forces, hip separation, and contact area to evaluate edge loading. The planner predicted a reduction in hip separation and an increase in articulating contact area for when using a lipped liner compared to a neutral liner. Additionally, regardless of liner type, increases in hip separation corresponded to decreases in contact area, therefore resulting in edge loading of the liner. Together, this indicates that improper component alignment and offsets may lead to an increase in hip separation and edge loading, but the use of a lipped liner may provide improved stability and resistance to this micromotion. [ABSTRACT FROM AUTHOR]

This study aims to identify preoperative risk factors for iliopsoas tendonitis after total hip arthroplasty, a complication typically attributed to acetabular cup position and orientation, using a validated iliopsoas impingement detection simulation. Analyzing CT scans and X‐rays of 448 patients using a validated preoperative planning protocol, patients were simulated for iliopsoas impingement and categorized into at‐risk and not at‐risk groups based on a prior validation study, with a 23% at‐risk incidence. Implementing a propensity score matching algorithm to reduce covariate imbalance, we identified factors that may exacerbate risk of iliopsoas tendonitis. Parameters that were investigated included standing pelvic tilt, functional femoral rotation, and the difference between the planned acetabular cup diameter and native femoral head diameter (ΔC‐NFH). Comparing pelvic tilt, we found a significant difference between the groups (at‐risk: −6.0°, not at‐risk: −0.7°; p << 0.01). A similar trend was noted for ΔC‐NFH (at‐risk: +5.7 mm, not at‐risk: +5.1 mm; p = 0.01). Additional simulations of at‐risk patients indicated increased anteversion of the acetabular cup reduces impingement risk more effectively than medialisation. These findings suggest that spinopelvic parameters may exacerbate iliopsoas irritation risk, underscoring their importance in preoperative planning and patient expectation management. Similar findings of a greater than 6 mm difference between cup size and native femoral head diameter being a significant risk for iliopsoas tendonitis have been observed before, underscoring its potential veracity. These results may provide surgeons with a simple threshold that can be used in determining a cup size to reduce the risk of iliopsoas tendonitis. [ABSTRACT FROM AUTHOR]