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The dynamic carbon footprint profile of methanol production from steel mill gases is affected by fluctuations of steel mill gas flow rates and compositions, as well as the composition of electricity mix. The cross‐industrial network of steel mill, gas conditioning, hydrogen production, chemical synthesis, and power generation was simulated under dynamic conditions. Dynamic life cycle assessment (LCA) was carried out for computing the dynamic carbon footprint profile in 15‐min resolution for the integrated system of steel and methanol production. The dynamic LCA indicated that the CO2 emissions in a power plant, electrolytic hydrogen demand, and variations in electricity mix were the major drivers of the fluctuations in the total carbon footprint. Dynamic LCA is useful for quantifying temporal uncertainty in environmental impacts. This insight can be used to analyze uncertainty in impacts for downstream products, processes, and use cases. [ABSTRACT FROM AUTHOR]

To overcome the deficiencies of large particle radius, strict vibration conditions, and low kinetic energy exchange rate of traditional particle dampers, it is proposed to organically combine the rack and pinion inerter device with a stacked single particle damper (SSPD) to form a novel stacked single particle‐inerter damping system (SSPIS). Based on a detailed analysis of the force state of particles at various stages, the vibration damping mechanism of SSPIS is analyzed, and a mechanical model of a single‐degree‐of‐freedom (SDOF) structure equipped with an SSPIS is established. The numerical simulation and analysis process of SSPIS is provided, and a parametric design method of inerter device based on the structural performance requirements is proposed. The accuracy of the theoretical mechanical model and numerical simulation analysis process of SSPIS is verified through shaking table tests of a single‐story steel frame, and the actual damping control effect of SSPIS on the controlled structure is investigated. Both test and theoretical results show that the numerical simulation analysis process of SSPIS is clear and accurate, and the mechanical model of the SSPIS‐SDOF structural system is highly accurate. The inerter device in SSPIS can significantly improve the momentum exchange efficiency between particles and structures, and SSPIS could adaptively adjust the particle radius size on demand compared with the traditional particle dampers, with a high damping frequency band, and can realize good damping control effect under the earthquake with various types of sites, which has expansive engineering application scenarios. [ABSTRACT FROM AUTHOR]

Due to their proteinaceous structure, monoclonal antibodies (mAbs) are susceptible to irreversible aggregation, with harmful consequences on drug efficacy and patient safety. To mitigate this risk in modern biopharmaceutical processes, it is critical to comply with current good manufacturing practices (cGMP) and pursue operating strategies minimizing irreversible aggregation whilst also maximizing mAb throughput. These conflicting objectives are targeted in this study by formulating and analyzing an integrated dynamic model accounting for both cultivation and aggregation of mAbs from a Chinese Hamster Ovary (CHO) cell line. Two manipulated dynamic variables are considered here in simulation studies: firstly temperature manipulation within a batch reactor, and secondly feed flow manipulation within a series of isothermal fed‐batch reactors. Following this, dynamic optimization investigations have been conducted, firstly with the single objective of maximizing mAb throughput and secondly with multiple (two) objectives of maximizing mAb throughput while also minimizing irreversible aggregate content, simultaneously. The study provides key insight into tradeoffs of how simultaneous temperature and feed flowrate manipulation affects mAb throughput and aggregation inside bioreactors. [ABSTRACT FROM AUTHOR]

This paper presents an advanced control strategy for a continuous biodiesel production plant based on a steady‐state optimizer and model predictive control (MPC). The proposed control system aims to optimize the production process and maintain product quality within required specifications. First, two steady‐state optimizers were developed with the aim of minimizing the steady‐state deviations of the manipulated and controlled variables and minimizing the biodiesel production cost. An MPC was then formulated to track the set points imposed by the steady‐state optimizers in real time and manipulate the control inputs accordingly. The scope of this work is limited to measured disturbances only. The effectiveness of the proposed control strategy is demonstrated through dynamic simulation studies performed using HYSYS and MATLAB. The results obtained using the proposed control methodology show significant improvements in performance compared to conventional control strategies. Furthermore, it avoids the quality problem reflected in the amount of water in the final product that the original plant presented due to an inadequate design of the control strategy. Overall, the results of this research indicate that the proposed advanced control strategy has the potential to improve the efficiency and profitability of continuous biodiesel production plants. [ABSTRACT FROM AUTHOR]

Enhancing the understanding of hydroxide transport mechanisms in anion exchange membranes (AEMs) is beneficial for the rational design of high‐performance AEMs in the renewable energy system. However, the high complexity and lack of adequate analytic tools make it challenging to clarify different mechanisms unambiguously. Herein, we developed an in‐house toolkit, the Reactive Diffusion Analyzer (RDAnalyzer), to conduct an effective analysis of hydroxide diffusion mechanisms from ReaxFF molecular dynamic simulations. Using the experimentally well‐synthesized T20NC6NC5N as a model system, we successfully decoupled the hydroxide diffusion mechanisms into free Vehicular and free Grotthuss, as well as associated Vehicular and associated Grotthuss, which was not yet achieved previously. Meanwhile, RDAnalyzer managed to specifically identify the drift length of hydroxide species for each mechanism under the electric field, which worked as a useful variable for calculating the conductivity of AEMs. Our theoretically predicted conductivity for T20NC6NC5N agrees reasonably with experimental results, indicating the reliability of RDAnalyzer. This work not only provides a rational understanding of the complex hydroxide diffusion mechanisms in AEMs but also holds the potential to guide the rational design of high‐performance AEMs with computations. [ABSTRACT FROM AUTHOR]

Point clouds captured using laser scanners mounted on mobile platforms contain errors at the centimetre to decimetre level due to motion distortion. In applications such as lidar odometry or SLAM, this motion distortion is often ignored. However, in applications such as HD mapping or precise vehicle localisation, it is necessary to correct the effect of motion distortion or ‘deskew’ the point clouds before using them. Existing methods for deskewing point clouds mostly rely on high frequency IMU, which may not always be available. In this paper, we propose a straightforward approach that uses the registration of consecutive point clouds to estimate the motion of the scanner and deskew the point clouds. We introduce a novel surface‐based evaluation method to evaluate the performance of the proposed deskewing method. Furthermore, we develop a lidar simulator using the reverse of the proposed deskewing method which can produce synthetic point clouds with realistic motion distortion. [ABSTRACT FROM AUTHOR]

The practical application of traditional data‐driven techniques for process monitoring encounters significant challenges due to the inherent nonlinear and dynamic nature of most industrial processes. Aiming at the problem of nonlinear dynamic process monitoring, a novel fault detection method based on dynamic kernel principal component analysis combined with weighted structural difference (DKPCA‐WSD) is proposed in this paper. Initially, the proposed method leverages a sophisticated nonlinear transformation to project the augmented matrix of the original input data into a high‐dimensional feature space, thereby facilitating the establishment of a DKPCA model. Subsequently, the WSD statistic is computed, utilizing a widely known sliding window technique, to quantify the mean and standard deviation differences across data structures. Ultimately, the WSD statistic is utilized for fault detection, completing the process monitoring task. By integrating the capability of DKPCA to capture nonlinear dynamic characteristics with the effectiveness of the WSD statistic in mitigating the impact of non‐Gaussian data distributions, DKPCA‐WSD significantly enhances the monitoring performance of traditional DKPCA in nonlinear dynamic processes. The proposed method is evaluated through a numerical case exhibiting nonlinear dynamic behaviors and a simulation model of a continuous stirred tank reactor. A comparative analysis with conventional methods, including principal component analysis (PCA), dynamic principal component analysis, KPCA, PCA similarity factor (SPCA), DKPCA, and moving window KPCA (MWKPCA), demonstrates that DKPCA‐WSD outperforms traditional fault detection techniques in nonlinear dynamic processes, offering a substantial improvement in monitoring performance. [ABSTRACT FROM AUTHOR]

Cells store triacylglycerol (TAG) within lipid droplets (LDs). A dynamic model describing complete LD formation at the endoplasmic reticulum (ER) membrane does not yet exist. A biochemical‐biophysical model of LD synthesis is proposed. It describes the time‐dependent accumulation of TAG in the ER membrane as the formation of a potential LD (pLD) bounded by spherical caps of the inner and outer monolayers of the membrane. The expansion rate of the pLD depends on the TAG supply, the elastic properties of the ER membrane, and the recruitment of phospholipids (PLs) to the cap‐covering monolayers. Model simulations provided the following insights: (a) Marginal differences in the surface tension of the cap monolayers are sufficient to fully drive the expansion of the pLD towards the cytosol or lumen. (b) Selective reduction of PL supply to the luminal monolayer ensures stable formation of cytosolic LDs, irrespective of variations in the elasto‐mechanical properties of the ER membrane. (c) The rate of TAG supply to the cytosolic monolayer has a major effect on the size and maturation time of LDs but has no significant effect on the TAG export per individual LD. The recruitment of additional PLs to the cap monolayers of pLDs critically controls the budding direction, size, and maturation time of LDs. The ability of cells to acquire additional LD initiation sites appears to be key to coping with acutely high levels of potentially toxic free fatty acids. [ABSTRACT FROM AUTHOR]

A methodology is presented for downscaling the Euro‐CORDEX climatic projections in order to derive spatially and temporally correlated weather fields that can be used for risk and resilience assessment of large‐scale asset portfolios or interconnected infrastructure. The temporal resolution of the Euro‐CORDEX data is downscaled to a 10 min basis by employing a modified analogue‐type approach that utilizes the k‐NN algorithm along with measurements from weather stations. The aim is to generate composite "Frankenstein" days comprising 144 jigsaw pieces of observed 10 min timeseries that are scaled and/or shifted, and matched together to form a continuous daily record. These point‐estimates, valid only at the locations of the weather stations, are expanded spatially by employing high‐fidelity weather intensity measure fields that provide variable yet synchronous patterns of weather parameters at all locations of interest. As a case study, the Euro‐CORDEX projections for wind, temperature, and precipitation are downscaled for the Metsovo‐Panagia segment of Egnatia Odos highway in Greece, by employing high‐fidelity Computational Fluid Dynamic simulations that account for the topography of the site to simulate turbulent wind flows. These are combined with measurements of two local weather stations to generate the Frankenstein timeseries and corresponding weather fields that can be used for estimating operability, recovery and direct/indirect loss statistics on an event‐by‐event basis for an ensemble of interconnected highway assets. [ABSTRACT FROM AUTHOR]

This research paper presents a comprehensive investigation aimed at enhancing the 2G bioethanol production process through the implementation of a dynamic process simulator. The simulator, developed using the Julia programming language, enables the prediction of acid hydrolysis behaviour by manipulating critical variables, including liquid–solid ratio (LSR), acid concentration (CA), and processing time (t). Through meticulous simulations and subsequent experimental validation, optimal operating conditions were revealed, with an H2SO4 concentration of 2% v/v, a LSR of 4% v/w, and 60‐min processing time at 121.1°C. This configuration led to remarkable outcomes, including a xylose concentration of 47.45 g L−1 and an 87.4% hemicellulose removal percentage. Moreover, the simulator unveiled the adverse influence of low LSR values on xylose production and the generation of degradation products. The recalibration of kinetic parameters, guided by experimental data, further fine‐tuned the simulator's predictive accuracy. Overall, this study underscores the potential of the simulator in optimizing various raw materials and presents a promising avenue for advancing 2G bioethanol industry practices. [ABSTRACT FROM AUTHOR]

BACKGROUND RESULTS CONCLUSION Mycotoxin contamination of food has been gaining increasing attention. Hidden mycotoxins that interact with biological macromolecules in food could make the detection of mycotoxins less accurate, potentially leading to the underestimation of the total exposure risk. Interactions of the mycotoxins alternariol (AOH) and alternariol monomethyl ether (AME) with high‐molecular glutenin were explored in this study.The recovery rates of AOH and AME (1, 2, and 10 μg kg−1) in three types of grains (rice, corn, and wheat) were relatively low. Molecular dynamics (MD) simulations indicated that AOH and AME bound to glutenin spontaneously. Hydrogen bonds and π‐π stacking were the primary interaction forces at the binding sites. Alternariol with one additional hydroxyl group exhibited stronger binding affinity to glutenin than AME when analyzing average local ionization energy. The average interaction energy between AOH and glutenin was −80.68 KJ mol−1, whereas that of AME was −67.11 KJ mol−1.This study revealed the mechanisms of the interactions between AOH (or AME) and high‐molecular glutenin using MD and molecular docking. This could be useful in the development of effective methods to detect pollution levels. These results could also play an important role in the evaluation of the toxicological properties of bound altertoxins. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

One colorimetric and one fluorescent‐indicator displacement assay (IDA) were studied to assess their interaction with methyl viologen (MV), an herbicide commercially known as paraquat. The host–guest complexes formed by cucurbit[7]uril (CB[7]) and the 4‐nitroaniline (NA) or Berberine (Be) dyes function as colorimetric‐ and fluorescent‐IDA for MV, respectively. The CB[7]@NA and CB[7]@Be complexes were characterized by UV–vis, fluorescence spectroscopy, and dynamic simulations. Isothermal titration calorimetry (ITC) experiments and dynamic simulations were employed to obtain thermodynamic data for the formation of the 1:1 inclusion complexes. Finally, NA is proposed as a reference colorimetric dye for determining CB[7]‐binding affinities using competitive host–guest titrations, and the fluorescent‐IDA as the best assay proposed, as it exhibits a high binding constant, a good detection limit of 2.7 × 10−6 mol L‐1, good linearity in the range from 4 × 10−6 mol L‐1 to 3.5 × 10−5 mol L‐1, in aqueous solution. [ABSTRACT FROM AUTHOR]

We provide improved uniform error estimates for the time‐splitting Fourier pseudo‐spectral (TSFP) methods applied to the Klein–Gordon–Dirac system (KGDS) with the small parameter ε∈(0,1]$$ \varepsilon \in \left(0,1\right] $$. We first reformulate the KGDS into a coupled Schrödinger–Dirac system (CSDS) and then apply the second‐order Strang splitting method to CSDS with the spatial discretization provided by Fourier pseudo‐spectral method. Based on rigorous analysis, we establish improved uniform error bounds for the second‐order Strang splitting method at O(hm−1+ετ2)$$ O\left({h}^{m-1}+\varepsilon {\tau}^2\right) $$ up to the long time at O(1/ε)$$ O\left(1/\varepsilon \right) $$. In addition to the conventional analysis methods, we mainly apply the regularity compensation oscillation technique for the analysis of long time dynamic simulation. The numerical results show that our method and conclusion are not only suitable for one‐dimensional problem, but also can be directly extended to higher dimensional problem and highly oscillatory problem. As far as we know there has not been any relevant long time analysis and any improved uniform error bounds for the TSFP method solving the KGDS. Our methods are novel and provides a reference for analyzing the improved error bounds of other coupled systems similar to the KGDS. [ABSTRACT FROM AUTHOR]

The maximum utilization of hydrocracking tail oil becomes increasingly important for petrochemical industry. The aim of this work is to develop optimized distillation processes to achieve various high‐valued qualified oil products from hydrocracking tail oil. Six different oil products is produced and the steady‐state distillation process, which aims to fractionate six qualified narrow distillates is established. The algorithm method incorporating divided‐wall column (DWC) configuration was introduced into the steady‐state design. Compared with traditional separation sequences, the DWC configuration leads to an energy‐saving potential up to 11.17%. Furthermore, effective dynamic control strategies were proposed, demonstrating precise and efficient control performance. In the presence of a 15% feed disturbance, the dynamic control structure is capable of maintaining the product distillation range near the set value. This comprehensive study provides a thorough investigation into the efficient utilization of hydrocracking tail oil, establishing a robust theoretical foundation for its industrial application. [ABSTRACT FROM AUTHOR]

This work presents an image‐based hybrid model incorporating the initial spatial distribution for mesenchymal stem cell (MSC) cultivation process design. First, three levels of seeding bias in static MSC cultivation were experimentally investigated, and the resulting initial distribution was quantified using phase contrast microscopy image analysis. Second, the observed spatial heterogeneity was defined as a new parameter by calculating the standard deviation of the seeded cell number fraction among numerical 8 × 8 tiles on two‐dimensional plates. Third, the parameter was incorporated into kinetic models to consider spatial growth limitation. The model was then applied to simulate MSC cultivation processes with experimental data. Using dynamic and stochastic simulation outputs, feasible ranges of cell‐harvesting time could be determined to satisfy a given requirement for the minimum cell number and acceptable confluency level. The developed hybrid model could serve as a basis for quantitative decision‐making in the design of MSC cultivation processes. [ABSTRACT FROM AUTHOR]

Varying the chemical consistency of acoustically levitated droplets opens up an in situ study of chemical and biochemical reactions in small volumes. However, the optimization of the mixing time and the minimization of the positional instability induced by solution dispensing are necessary for practical applications such as the study of the transient state of macromolecules crystallography during the ligand binding processes. For this purpose, we study the inertial mixing in a configuration compatible with the room‐temperature crystallography using the acoustic levitation diffractometer, therein solution drops ejected at high velocity collide and coalesce with droplets dispensed on acoustically levitated and rotating polymer thin‐film sample holders. With the proposed method, we are able to achieve the mixing time of ∼0.1 s for sub‐micro and a few microliter droplets. The observed short mixing time is ascribed to the rapid penetration of the solution into the droplets and confirmed by a computational fluid dynamic simulation. The demonstrated accelerated solution mixing is tested in a pilot time‐lapse protein crystallography experiment using the acoustic levitation diffractometer. The results indicate the detection of transient ligand binding state within 2 s after the solution dispensing, suggesting the feasibility of the proposed method for studying slow biochemical processes. [ABSTRACT FROM AUTHOR]

Purpose: To employ optimal control for the numerical design of Chemical Exchange Saturation Transfer (CEST) saturation pulses to maximize contrast and stability against B0$$ {\mathrm{B}}_0 $$ inhomogeneities. Theory and Methods: We applied an optimal control framework for the design pulse shapes for CEST saturation pulse trains. The cost functional minimized both the pulse energy and the discrepancy between the corresponding CEST spectrum and the target spectrum based on a continuous radiofrequency (RF) pulse. The optimization is subject to hardware limitations. In measurements on a 7 T preclinical scanner, the optimal control pulses were compared to continuous‐wave and Gaussian saturation methods. We conducted a comparison of the optimal control pulses with Gaussian, block pulse trains, and adiabatic spin‐lock pulses. Results: The optimal control pulse train demonstrated saturation levels comparable to continuous‐wave saturation and surpassed Gaussian saturation by up to 50 % in phantom measurements. In phantom measurements at 3 T the optimized pulses not only showcased the highest CEST contrast, but also the highest stability against field inhomogeneities. In contrast, block pulse saturation resulted in severe artifacts. Dynamic Bloch‐McConnell simulations were employed to identify the source of these artifacts, and underscore the B0$$ {\mathrm{B}}_0 $$ robustness of the optimized pulses. Conclusion: In this work, it was shown that a substantial improvement in pulsed saturation CEST imaging can be achieved by using Optimal Control design principles. It is possible to overcome the sensitivity of saturation to B0 inhomogeneities while achieving CEST contrast close to continuous wave saturation. [ABSTRACT FROM AUTHOR]

In this study, the enantioselectivity of β‐cyclodextrin and its derivatives towards propranolol enantiomers are investigated by molecular dynamic (MD) simulations. β‐cyclodextrin (β‐CD) have previously been shown to be able to recognize propranolol (PRP) enantiomers. To improve upon the enantioselectivity of β‐cyclodextrin, we propose the use of an ionic‐liquid‐modified‐β‐cyclodextrin (β‐CD‐IL). β‐CD‐IL was found to be able to complex R and S propranolol enantiomers with differing binding energies. The molecular docking study reveals that the ionic liquid chain attached to the β‐CD molecule has significant interaction with propranolol. The formation of the most stable complex occurred between (S)‐β‐CD‐IL and (S)‐propranolol with an energy of −5.80 kcal/mol. This is attributed to the formation of a hydrogen bond between the oxygen of the propranolol and the hydrogen on the primary rim of the (S)‐β‐CD‐IL cavity. This interaction is not detected in other complexes. The root mean‐squared fluctuation (RMSF) value indicates that the NH group is the most flexible molecular fragment, followed by the aromatic group. Also of note, the formation of a complex between pristine β‐CD and (S)‐propranolol is the least favorable. [ABSTRACT FROM AUTHOR]

Assessment of energetic renovations for residential buildings by optimization The energetic renovation of existing buildings plays a crucial role in the decarbonization of the building sector. For the best allocation of available resources, a holistic quantification and optimization of renovation decisions is necessary. In this context optimization methods offer potential that has so far hardly been used, especially in German‐speaking countries. A new methodology is presented that allows the optimization of variable target functions. The methodology uses a mathematical replacement model based on selective results from dynamic building simulations. The strength of the proposed method lies in the analysis of a very large number of renovation combinations with minimal computational effort. The applicability to real objects is verified using two different exemplary residential building types. The resulting renovation strategies from the analysis are presented for 3 different target cost functions which include investment and operating costs as well as CO2 emissions under different restrictions. The method can currently be used to assess and optimize the heating demands of residential buildings. For the future different extensions of the methodology are planned. [ABSTRACT FROM AUTHOR]

Background and Objectives: When a haematopoietic stem cell registry size is constrained by limits on recruiting, as in Canada, identifying the right person to recruit is a critical determinant of effectiveness. The aim of this study was to evaluate the impact of changes to donor recruitment effort, within ethnic groups, on the matching effectiveness of the Canadian registry as it evolves over time. Materials and Methods: Simulation methods are applied to create a cohort of donor recruits and patients over a 10‐year time horizon. New recruits are added to the registry each year, while some existing donors 'age‐out' upon reaching their 36th birthday. In a similar fashion, simulated patient lists are created. At the end of each simulated year, simulated patients are matched against the simulated registry. Results: There are increased matches in non‐White populations when diverse registrants are preferentially recruited, but there are larger decreases in the number of matches for Caucasian patients. Additionally, ethnic communities that have limited registrants in the Canadian registry in 2021 do not benefit from increased recruiting efforts as much as communities with a larger initial number of registrants. Conclusion: Preferentially recruiting from non‐Caucasian populations reduces the number of matches from Canadian sources because increases in non‐Caucasian populations will not fully counterbalance decreases to Caucasian patient matches. Nevertheless, more than 80% of all matches are for Caucasian patients, regardless of the donor recruiting effort within ethnic groups. [ABSTRACT FROM AUTHOR]

Wheel‐rail contact is a link between the vehicle system and the rail system, and the contact processing approach affects accuracy of vehicle dynamic simulation. Contact detection is usually the start of wheel‐rail contact calculation, and detecting precision of contact patch center affect accuracy of contact force calculating results, therefore it is significant to improve detecting precision of contact patch center. An alternate search method (ASM) and an extended trace line method are proposed to improve precision and efficiency of contact patch centers detection. The proposed alternate search method applies Golden Ratio Search Method and variable intervals between grids to detect contact patch centers. To make the detected contact patch centers match rail tangential directions better, an extended trace line method is constructed based on geometrical constraints between contact points and rail tangential directions. Dynamic simulations of a bogie vehicle formed by two wheelsets and a bogie frame negotiating a rail curve are conducted to evaluate effects of the proposed methods. Calculating times of the proposed methods for finishing the simulations are compared to explain computational efficiencies of the different methods. The proposed approaches are real‐time capable and can be used for vehicle dynamics simulations. [ABSTRACT FROM AUTHOR]

A hydrocracking unit operates at high temperature, high pressure, and near hydrogen, which can be susceptible to fire and explosions accidents due to equipment failure. Therefore, it is essential to identify and analyze the risk factors. The dynamic simulation‐based quantitative hazard and operability (HAZOP) study can effectively and purposefully quantify deviations and consequences as well as reduce the redundancy of safety analysis results. Furthermore, the time parameter is introduced through dynamic simulation, which reflects more realistically the dynamic characteristics of the system in the event of a fault. In this paper, we take the process flow of the absorbing‐stabilizing system of an actual hydrocracking unit in a refining company as an example and carry out steady‐state and dynamic simulations for the deviations of pressure, temperature, and liquid level with the help of Aspen Plus V11 and Aspen Plus Dynamics V11 software to complete the dynamic simulation‐based quantitative HAZOP analysis. [ABSTRACT FROM AUTHOR]

In the display industry, in line with the high performance and miniaturization of products, the fine patterning and the increase in integration in the backplane process are becoming very important. It is the Electrostatic Discharge (ESD) issue that is increased importance in such a display panel development environment. Careful ESD management is very important because various types of electrostatic issues arising from the panel production process are directly connected to the decline in product quality and productivity. In this paper, we introduce the case of ESD defects in the ESD diode protection circuit of display panels being developed. The ESD failure caused by plasma ions and external surges during fabrication process was identified, and the charge and current path were verified through static and transient simulation to determine how it affects the actual display OLED panel. In addition, the design of ESD diode protection circuits optimized for ESD to robust layout was proposed. As a result, it was possible to reduce electric‐field, an insulating breakdown factor, by more than 80%. [ABSTRACT FROM AUTHOR]

Understanding the convection flows driven by the uneven temperature distribution in heated aqueous solutions is fascinating and meaningful both in fundamental and industrial aspects. Therefore, it is desirable to develop a simple and convenient method for real‐time tracking of surface temperature distribution and the solvent flow state. Herein, we designed and screened a water‐soluble spiropyran derivative (BS‐SP1) that contains benzothiazole and sulfonic acid groups. The BS‐SP1 molecule was found to exceptionally maintain the reversible photochromic characteristics in water, and then served as a photo‐responsive indicator for visualizing the temperature distribution and flow behavior on water surface with high resolution. This study provides feasible guidance on the dynamic self‐assembly and thermodynamics occurring in the water evaporation system and offers a practical tool for investigating these behaviors. [ABSTRACT FROM AUTHOR]

This study focuses on the structural integrity analyses of a submersible cage with dimensions of 20 m in diameter and 10 m depth under extreme oceanographic conditions, including current speed of 0.5 and 1 m/s, combined with waves ranging from 2 to 5 m in height and a period of 7 s. Employing a dynamic simulation model based on finite elements, The study examines the stresses in the cage's pipes, as well as the tension in the bridle lines and mooring lines. Results indicate that submerging the cage leads to a reduction in peak tensions, with mooring lines experiencing a decrease of up to 32% and bridle lines experiencing a decrease of up to 59%. Furthermore, the stresses in the pipes exhibit a significant decline of up to 71.4%. These findings demonstrate that the submersible cage, when submerged, significantly reduces peak stresses, thereby decreasing the risk of structural loss or damage when the system is submerged. [ABSTRACT FROM AUTHOR]

The scaffolds of two known CDK inhibitors (CAN508 and dinaciclib) were the starting point for synthesizing two series of pyarazolo[1,5‐a]pyrimidines to obtain potent inhibitors with proper selectivity. The study presented four promising compounds; 10d, 10e, 16a, and 16c based on cytotoxic studies. Compound 16a revealed superior activity in the preliminary anticancer screening with GI % = 79.02–99.13 against 15 cancer cell lines at 10 μM from NCI full panel 60 cancer cell lines and was then selected for further investigation. Furthermore, the four compounds revealed good safety profile toward the normal cell lines WI‐38. These four compounds were subjected to CDK inhibitory activity against four different isoforms. All of them showed potent inhibition against CDK5/P25 and CDK9/CYCLINT. Compound 10d revealed the best activity against CDK5/P25 (IC50 = 0.063 µM) with proper selectivity index against CDK1 and CDK2. Compound 16c exhibited the highest inhibitory activity against CDK9/CYCLINT (IC50 = 0.074 µM) with good selectivity index against other isoforms. Finally, docking simulations were performed for compounds 10e and 16c accompanied by molecular dynamic simulations to understand their behavior in the active site of the two CDKs with respect to both CAN508 and dinaciclib. [ABSTRACT FROM AUTHOR]

Population heterogeneity is due to intrinsic and extrinsic noises; cell to cell variability is related to cell partitioning at division and external forcing by the environment. In this article, a Monte‐Carlo calculation of integral source terms is coupled to a compartment approach. The biological phase is represented by an ensemble of discrete particles which are equipped with a coarse‐grained model that describes the intracellular response to extracellular conditions. The redistribution of cell properties at division generates unbalanced cells and introduces additional time scales into the population dynamics. Using this fully two‐way coupled approach, the consequences of repeated exposure to feast and famine events on both the reactor and the population heterogenities are investigated in a CSTR+PFR scale‐down bioreactor. It is shown that the integration of intrinsic noise due to cell division continuously produces cells that are not at equilibrium with their environment and this contributes to population heterogeneity, even in homogeneous environments. [ABSTRACT FROM AUTHOR]

All instrumented basaltic caldera collapses have generated Mw > 5 very long period earthquakes. However, previous studies of source dynamics have been limited to lumped models treating the caldera block as rigid, leaving open questions related to how ruptures initiate and propagate around the ring fault, and the seismic expressions of those dynamics. We present the first 3D numerical model capturing the nucleation and propagation of ring fault rupture, the mechanical coupling to the underlying viscoelastic magma, and the associated seismic wavefield. We demonstrate that seismic radiation, neglected in previous models, acts as a damping mechanism reducing coseismic slip by up to half, with effects most pronounced for large magma chamber volume/ring fault radius or highly compliant crust/compressible magma. Viscosity of basaltic magma has negligible effect on collapse dynamics. In contrast, viscosity of silicic magma significantly reduces ring fault slip. We use the model to simulate the 2018 Kı̄lauea caldera collapse. Three stages of collapse, characterized by ring fault rupture initiation and propagation, deceleration of the downward‐moving caldera block and magma column, and post‐collapse resonant oscillations, in addition to chamber pressurization, are identified in simulated and observed (unfiltered) near‐field seismograms. A detailed comparison of simulated and observed displacement waveforms corresponding to collapse earthquakes with hypocenters at various azimuths of the ring fault reveals a complex nucleation phase for earthquakes initiated on the northwest. Our numerical simulation framework will enhance future efforts to reconcile seismic and geodetic observations of caldera collapse with conceptual models of ring fault and magma chamber dynamics. Plain Language Summary: Caldera collapse manifests as the rapid subsidence of a kilometer‐scale block of crust circumscribed by a near‐circular fault on top of a volcano. The subsidence of the caldera block is caused by the eruption‐induced withdrawal of magma and reduction in pressure in the underlying magma chamber. All scientifically instrumented caldera collapses at volcanoes with low‐viscosity magma are accompanied by earthquakes of magnitude 5 and above. How do magma viscosity and the seismic wave radiation influence the amount of slip per earthquake on the fault? What can we learn about the dynamics of these earthquakes from seismic records? We address these questions by performing computer simulations of caldera collapse earthquakes and compare the results to the seismic records from the Kı̄lauea caldera collapse of 2018. Key Points: Seismic wave radiation through ring fault and magma, as well as high magma viscosity, reduce fault slip by up to half during collapseRupture propagation, downward momentum transfer via magma pressure waves, and chamber pressurization are identified in unfiltered seismogramsComparison between simulated and observed near‐field seismograms from Kı̄lauea 2018 reveals complex nucleation phase on the ring fault [ABSTRACT FROM AUTHOR]

Our laboratory has shown that calpain‐2 activation in the brain following acute injury is directly related to neuronal damage and the long‐term functional consequences of the injury, while calpain‐1 activation is generally neuroprotective and calpain‐1 deletion exacerbates neuronal injury. We have also shown that a relatively selective calpain‐2 inhibitor, referred to as C2I, enhanced long‐term potentiation and learning and memory, and provided neuroprotection in the controlled cortical impact (CCI) model of traumatic brain injury (TBI) in mice. Using molecular dynamic simulation and Site Identification by Ligand Competitive Saturation (SILCS) software, we generated about 130 analogs of C2I and tested them in a number of in vitro and in vivo assays. These led to the identification of two interesting compounds, NA‐112 and NA‐184. Further analyses indicated that NA‐184, (S)‐2‐(3‐benzylureido)‐N‐((R,S)‐1‐((3‐chloro‐2‐methoxybenzyl)amino)‐1,2‐dioxopentan‐3‐yl)‐4‐methylpentanamide, selectively and dose‐dependent inhibited calpain‐2 activity without evident inhibition of calpain‐1 at the tested concentrations in mouse brain tissues and human cell lines. Like NA‐112, NA‐184 inhibited TBI‐induced calpain‐2 activation and cell death in mice and rats, both male and females. Pharmacokinetic and pharmacodynamic analyses indicated that NA‐184 exhibited properties, including stability in plasma and liver and blood–brain barrier permeability, that make it a good clinical candidate for the treatment of TBI. [ABSTRACT FROM AUTHOR]

As the development of well types for low permeability reservoirs shifts from vertical to highly inclined/horizontal wells, targeted studies of oil and gas reservoir damage must be conducted for such well types to improve the science and effectiveness of acidification conversion. Taking into account the formation of mud cake and the dynamic damage factors caused by drilling fluid on the reservoir during horizontal well drilling, a refined dynamic description model for nonuniform damage in horizontal wells was established. The coupled simulation accounts for the dynamical destruction of the skin factor of the reservoir and the dynamical generation of the slurry. The coupled model consists of a radial mud cake dynamic formation model, a reservoir damage radius model, a permeability distribution model, and a horizontal well inhomogeneous skin factor model. It captures the dynamic evolution of reservoir damage due to drilling fluid contamination during horizontal well drilling and provides a real‐time representation of changes in the reservoir skin factor of horizontal wells, measuring the depth and extent of radial reservoir damage. Clarifying the extent of reservoir damage and its impact in horizontal well sections can help select appropriate acidification methods, improve acid distribution processes, and ultimately improve the effectiveness of mitigating reservoir damage and increasing oil and gas well productivity. [ABSTRACT FROM AUTHOR]

Defect engineering and metal decoration onto 2-D materials have gained major attention as a means of creating viable hydrogen storage materials. This Density Functional Theory (DFT) based study presents lithium decorated single vacancy (SV) and Stone-Wales (SW) defective silicene as a viable media for storing hydrogen via physisorption. Introducing defects increases the Li adatom's binding energy from −2.36 eV in pristine silicene to −3.44 and −2.73 eV in SV and SW silicene, respectively, preventing Li adatom clustering. The presence of defects and Li adatom further aid hydrogen adsorption onto the substrates with binding energies present between the US-DOE set range of −0.2 to −0.7 eV/H2 with the highest binding energy measured to be −0.389 eV/H2. The enhanced H2 binding energies are a result of a combined contribution of the Li(p) and Li(s) orbitals with the H(s) orbital with an indirect electronic transfer from the silicene substrate to the Li adatom. Upon double side Li decoration, both the Li-decorated defective systems were able to effectively store multiple H2 molecules up to 28 H2 with the highest gravimetric density being 5.97 wt%. Ab Initio molecular dynamic simulations conducted at 300 K and 310 K confirm the stability of the Li adatom as well as the adsorbed H2 molecules at room temperature and establish the viability of these systems as effective, high gravimetric density, physisorption-based hydrogen storage media. [ABSTRACT FROM AUTHOR]

Personalized dosing approaches play important roles in clinical practices to improve benefit: risk profiles. Whereas this is also important for drug development, especially in the context of drugs with narrow therapeutic windows, such approaches have not been fully evaluated during clinical development. Fazpilodemab (BFKB8488A) is an agonistic bispecific antibody which was being developed for the treatment of nonalcoholic steatohepatitis. The objective of this study was to characterize the exposure‐response relationships of fazpilodemab with the purpose of guiding dose selection for a phase II study, as well as to evaluate various personalized dosing strategies to optimize the treatment benefit. Fazpilodemab exhibited clear exposure‐response relationships for a pharmacodynamic (PD) biomarker and gastrointestinal adverse events (GIAEs), such as nausea and vomiting. Static exposure‐response analysis, as well as longitudinal adverse event (AE) analysis using discrete‐time Markov model, were performed to characterize the observations. Clinical trial simulations were performed based on the developed exposure‐response models to evaluate probability of achieving target PD response and the frequency of GIAEs to inform phase II dose selection. Dynamic simulation of personalized dosing strategies demonstrated that the AE‐based personalized dosing is the most effective approach for optimizing the benefit–risk profiles. The approach presented here can be a useful framework for quantifying the benefit of personalized dosing for drugs with narrow therapeutic windows. [ABSTRACT FROM AUTHOR]

Recombinant keratins possess strong hemostatic and wound healing properties but suffer from poor water solubility that restricts their bioactivities in biomedical applications. Herein, we report the rational design and synthesis of water‐soluble keratins using a simple methodology named the QTY code. In vitro biophysical analyses and molecular dynamic simulation demonstrated a 200‐fold increase in the water solubility of QTY variant keratins without apparent structural changes compared to native proteins. Homotypic self‐assembly was observed for the first time in recombinant keratins in an aqueous environment, without urea and after QTY modification. Cell and animal experiments showed the in situ gel‐forming capability of QTY variant keratins with superior hemostatic and wound healing activities at the wound sites compared to native recombinant keratins. Our work not only presented a simple and feasible pathway to produce large amounts of water‐soluble keratins using QTY modification but also validated the enhanced self‐assembly, hemostasis, and wound healing properties of these novel keratin species that may open up new venues for biomedical applications. [ABSTRACT FROM AUTHOR]

While deep learning (DL) models exhibit superior simulation accuracy over traditional distributed hydrological models (DHMs), their main limitations lie in opacity and the absence of underlying physical mechanisms. The pursuit of synergies between DL and DHMs is an engaging research domain, yet a definitive roadmap remains elusive. In this study, a novel framework that seamlessly integrates a process‐based hydrological model encoded as a neural network (NN), an additional NN for mapping spatially distributed and physically meaningful parameters from watershed attributes, and NN‐based replacement models representing inadequately understood processes is developed. Multi‐source observations are used as training data, and the framework is fully differentiable, enabling fast parameter tuning by backpropagation. A hybrid DL model of the Amazon Basin (∼6 × 106 km2) was established based on the framework, and HydroPy, a global‐scale DHM, was encoded as its physical backbone. Trained simultaneously with streamflow observations and Gravity Recovery and Climate Experiment satellite data, the hybrid model yielded median Nash‐Sutcliffe efficiencies of 0.83 and 0.77 for dynamic and distributed simulations of streamflow and total water storage, respectively, 41% and 35% higher than those of the original HydroPy model. Replacing the original Penman‒Monteith formulation in HydroPy with a replacement NN produces more plausible potential evapotranspiration (PET) estimates, and unravels the spatial pattern of PET in this giant basin. The NN used for parameterization was interpreted to identify the factors controlling the spatial variability in key parameters. Overall, this study lays out a feasible technical roadmap for distributed hydrological modeling in the big data era. Key Points: A fully differentiable framework that seamlessly integrates physics and deep learning was developed for distributed hydrological modelingThe framework flexibly fuses multi‐source observations and improves the efficiency and accuracy of large‐scale hydrological modelingThe hybrid model for the Amazon Basin exhibits excellent fidelity and physical plausibility and provides insights into the ET process [ABSTRACT FROM AUTHOR]

Root hydraulic properties are key physiological traits that determine the capacity of root systems to take up water, at a specific evaporative demand. They can strongly vary among species, cultivars or even within the same genotype, but a systematic analysis of their variation across plant functional types (PFTs) is still missing. Here, we reviewed published empirical studies on root hydraulic properties at the segment‐, individual root‐, or root system scale and determined its variability and the main factors contributing to it. This corresponded to a total of 241 published studies, comprising 213 species, including woody and herbaceous vegetation. We observed an extremely large range of variation (of orders of magnitude) in root hydraulic properties, but this was not caused by systematic differences among PFTs. Rather, the (combined) effect of factors such as root system age, driving force used for measurement, or stress treatments shaped the results. We found a significant decrease in root hydraulic properties under stress conditions (drought and aquaporin inhibition, p <.001) and a significant effect of the driving force used for measurement (hydrostatic or osmotic gradients, p <.001). Furthermore, whole root system conductance increased significantly with root system age across several crop species (p <.01), causing very large variation in the data (>2 orders of magnitude). Interestingly, this relationship showed an asymptotic shape, with a steep increase during the first days of growth and a flattening out at later stages of development. We confirmed this dynamic through simulations using a state‐of‐the‐art computational model of water flow in the root system for a variety of crop species, suggesting common patterns across studies and species. These findings provide better understanding of the main causes of root hydraulic properties variations observed across empirical studies. They also open the door to better representation of hydraulic processes across multiple plant functional types and at large scales. All data collected in our analysis has been aggregated into an open access database (https://roothydraulic-properties.shinyapps.io/database/), fostering scientific exchange. [ABSTRACT FROM AUTHOR]

To improve the multiscale dynamic dispatching and distribution capacity of regional integrated energy, a multiscale dynamic time‐domain dispatching model of regional integrated energy with seasonal load difference is proposed. The master–slave game coordination planning model of regional comprehensive energy multiscale dispatching is constructed, and the difference fusion model of regional comprehensive energy multiscale dynamic dispatching is established by using the active and reactive power coordination control method according to the influence factors of voltage deviation and line overload absorption. Maximize the weight factors of the positive contribution of distributed photovoltaic (PV) power to the active distribution network. On the basis of the quantitative regulation analysis method of demand response power based on the equivalent slope of the load curve, establish an energy absorption capacity analysis model of seasonal load differentiation. On the basis of the dynamic interaction between different systems, a multiscale dynamic time‐domain analysis and dynamic simulation model of regional integrated energy is constructed by using the method of PV absorptive capacity assessment on both sides of demand uncertainty, to achieve multiscale dynamic time‐domain feature extraction of integrated energy and integrated scheduling of seasonal load differences. The simulation results show that the multiscale dynamic time‐domain allocation of regional comprehensive energy using this method improves the energy dispatching and balanced allocation capability, and the time‐domain dynamic allocation capability is good. Considering the terminal load demand and the electricity price demand formulated by the distribution network investment operators, the seasonal load response and comprehensive dispatching capability are improved. [ABSTRACT FROM AUTHOR]

Tuberculosis (TB) is the second leading cause of mortality after COVID‐19, with a global death toll of 1.6 million in 2021. The escalating situation of drug‐resistant forms of TB has threatened the current TB management strategies. New therapeutics with novel mechanisms of action are urgently required to address the current global TB crisis. The essential mycobacterial primase DnaG with no structural homology to homo sapiens presents itself as a good candidate for drug targeting. In the present study, Mitoxantrone and Vapreotide, two FDA‐approved drugs, were identified as potential anti‐mycobacterial agents. Both Mitoxantrone and Vapreotide exhibit a strong Minimum Inhibitory Concentration (MIC) of ≤25μg/ml against both the virulent (M.tb‐H37Rv) and avirulent (M.tb‐H37Ra) strains of M.tb. Extending the validations further revealed the inhibitory potential drugs in ex vivo conditions. Leveraging the computational high‐throughput multi‐level docking procedures from the pool of ~2700 FDA‐approved compounds, Mitoxantrone and Vapreotide were screened out as potential inhibitors of DnaG. Extensive 200 ns long all‐atoms molecular dynamic simulation of DnaGDrugs complexes revealed that both drugs bind strongly and stabilize the DnaG during simulations. Reduced solvent exposure and confined motions of the active centre of DnaG upon complexation with drugs indicated that both drugs led to the closure of the active site of DnaG. From this study's findings, we propose Mitoxantrone and Vapreotide as potential anti‐mycobacterial agents, with their novel mechanism of action against mycobacterial DnaG. [ABSTRACT FROM AUTHOR]

Molecular Dynamics (MD) simulations constitute a powerful tool that provides a 3D perspective of the dynamical behavior of chemical systems. Herein the first MD study of the dynamics of a catalytic organometallic system, in micellar media, is presented. The challenging methane catalytic functionalization into ethyl propionate through a silver‐catalyzed process has been targeted as the case study. The intimate nature of the micelles formed with the surfactants sodium dodecylsulfate (SDS) and potassium perfluorooctane sulfonate (PFOS) has been ascertained, as well as the relative distribution of the main actors in this transformation, namely methane, the diazo reagent and the silver catalyst, the latter in two different forms: the initial compound and a silver‐carbene intermediate. Catalyst deactivation occurs with halide containing surfactants dodecyltrimethylammonium chloride (DTAC) and Triton X‐100. Computed simulations allow explaining the experimental results, indicating that micelles behave differently regarding the degree of accumulation and the local distribution of the reactants and their effect in the molecular collisions leading to net reaction. [ABSTRACT FROM AUTHOR]

With the increasing environmental requirements for improving products and materials using renewable and sustainable resources, cellulose has been seen as one of the most attractive and promising alternatives to traditional inorganic fillers. We developed a new modification method to improve the interface compatibility between natural rubber and sisal cellulose, to improve the mechanical and thermal conductivity properties of rubber composite. Microcrystalline cellulose (MCC) was extracted from sisal cellulose and then the hydrophobic cellulose (SA‐MCC) was prepared by grafting stearic acid on the surface of MCC. MCC and SA‐MCC were added to the thermal conductivity composite material composed of natural rubber and boron nitride. The results showed that the thermal conductivity and tensile properties of the natural rubber composites increased by 17.3% and 20%, respectively, under the addition of 1.8 wt% SA‐MCC. Furthermore, the interfacial interaction between the components in the composite was studied by molecular dynamics simulation. The solubility parameters, free volume fraction, and molecular binding energy were calculated to verify the effectiveness of the modification. This work is expected to provide a theoretical basis for the design and preparation of high‐performance natural rubber composite materials. Highlights: Cellulose microcrystals were successfully extracted from sisal fiber and modified.Through the combination of boron nitride and the modified cellulose microcrystals, the thermal conductivity and tensile properties of thermal rubber were successfully improved synchronously.A reasonable molecular simulation model was established to analysis the strengthening mechanism from the microscopic point of view.The molecular simulation conclusions on interface enhancement are in good agreement with the experimental properties. [ABSTRACT FROM AUTHOR]

The study is focused on examining 2,5‐Substituted 4‐Pyrone based compounds through quantum chemical and topological analysis techniques, evaluating the properties of these compounds, including their geometrical structure, intermolecular interactions and assess their possible applications. Additionally, the molecular stability, charge delocalization and UV‐Visible data was investigated and compared with the calculated energy and oscillator strength using the TD‐DFT approach. The researchers observed that charge transfer occurred within the molecule, indicated by the HOMO and LUMO energies. It was also found that the compound exhibited planarity and higher chemical reactivity. The calculated Mulliken charges and molecular electrostatic potential were used to interpret the Fukui index data that help predict reactive sites and understand the reactivity patterns of specific atoms in a compound. The study is aimed to understand the role of NCI in the molecule under investigation using electron localization functions and localized orbit locator methods. Molecular docking and ADMET studies were conducting involving a detailed MD simulation of a protein‐ligand complex using the OPLS3e force field and the SPC water model. These findings could prove to be beneficial in developing new therapeutic agents with various pharmacological effects and potential toxicities. [ABSTRACT FROM AUTHOR]

Adipic acid (AA) is a crucial feedstock for nylon polymers, and is industrially produced by thermal oxidation of cyclohexanone/cyclohexanol mixture (KA oil). However, this process consumes large quantities of corrosive nitric acid as oxidants, while emits ozone‐depleting greenhouse gas N2O. Here, an electrocatalytic strategy for selective oxidation of KA oil to AA coupled with H2 evolution over a Co3O4/graphdiyne cooperative catalyst (Co3O4/GDY) is reported. The Co3O4/GDY displays high electrooxidation activity of KA oil to AA (100 mA cm−2 at ≈1.5 V vs RHE), outperforming all the reported findings. Detailed ex situ and in situ experimental studies, theoretical calculations, and molecular dynamic simulations reveal that GDY not only facilitates the enrichment of cyclohexanone on the catalyst surface in aqueous medium, but also upshifts the d‐band center of Co sites, strengthening the adsorption/activation of cyclohexanone. This study offers a green route for AA synthesis and proposes a GDY interface engineering strategy for efficient electrooxidation. [ABSTRACT FROM AUTHOR]

Background: Computational fluid dynamics (CFD) simulations are a powerful tool for studying cerebral aneurysms, capable of evaluating hemodynamics in a way that is infeasible with imaging alone. However, the difficulty of incorporating patient‐specific information and inherent obstacles of in vivo validation have limited the clinical usefulness of CFD of cerebral aneurysms. In this work we investigate the effect of using standardized blood viscosity values in CFD simulations of cerebral aneurysms when compared to simulations of the same aneurysms using patient‐specific viscosity values derived from hematocrit measurements. Purpose: The objective of this work is to determine the level of error, on average, that is, caused by using standardized values of viscosity in CFD simulations of cerebral aneurysms. By quantifying this error, we demonstrate the need for incorporating patient‐specific viscosity in future CFD investigations of cerebral aneurysms. Methods: CFD simulations of forty‐one cerebral aneurysms were conducted using patient‐specific boundary conditions. For each aneurysm two simulations were conducted, one utilizing patient‐specific blood viscosity derived from hematocrit measurements and another using a standardized value for blood viscosity. Hemodynamic parameters such as wall shear stress (WSS), wall shear stress gradient (WSSG), and the oscillatory shear index (OSI) were calculated for each of the simulations for each aneurysm. Paired t‐tests for differences in the time‐averaged maps of these hemodynamic parameters between standardized and patient‐specific viscosity simulations were conducted for each aneurysm. Bland–Altman analysis was used to examine the cohort‐wide changes in the hemodynamic parameters. Subjects were broken into two groups, those with higher than standard viscosity and those with lower than standard viscosity. An unpaired t‐test was used to compare the percent change in WSS, WSSG, and OSI between patient‐specific and standardized viscosity simulations for the two cohorts. The percent changes in hemodynamic parameters were correlated against the direction and magnitude of percent change in viscosity, aneurysm size, and aneurysm location. For all t‐tests, a Bonferroni‐corrected significance level of 0.0167 was used. Results: 63.2%, 41.5%, and 48.7% of aneurysms showed statistically significant differences between patient‐specific and standardized viscosity simulations for WSS, WSSG, and OSI respectively. No statistically significant difference was found in the percent changes in WSS, WSSG, and OSI between the group with higher than standard viscosity and those with lower than standard viscosity, indicating an increase in viscosity can cause either an increase or decrease in each of the hemodynamic parameters. On a study‐wide level no significant bias was found in either direction for WSS, WSSG, or OSI between the simulation groups due to the bidirectional effect of changing viscosity. No correlation was found between percent change of viscosity and percent change of WSS, WSSG, or OSI, meaning an after‐the‐fact correction for patient‐specific viscosity is not feasible. Conclusion: Standardizing viscosity values in CFD of cerebral aneurysms has a large and unpredictable impact on the calculated WSS, WSSG, and OSI when compared to CFD simulations of the same aneurysms using a patient‐specific viscosity. We recommend implementing hematocrit‐based patient‐specific blood viscosity values for all CFD simulations of cerebral aneurysms. [ABSTRACT FROM AUTHOR]

This study presents a specialized mixer design for gas burners aimed at improving the efficiency of phase mixing while minimizing system resistance and energy consumption. The proposed design utilizes a multi‐cavity mixer employing both radial and axial mixing techniques, eliminating the need for additional power supply. Full premixed combustion of small gas‐fired industrial boiler has the function of "inhibiting" NOx emission from the source, and good mixing of fuel and combustion supporting air in the early stage is the primary prerequisite for realizing full premixed combustion denitration. In this article, a radial multichamber static mixer is designed following the characteristics of full premixed mixing in gas‐fired industrial boilers. The results demonstrate that the maximum pressure drop of the static mixer is 806 Pa; for gas and air branch pipes, the resistance coefficient f decreases rapidly with the increase in Reynolds number; when Re ≥ 1.2 × 103, the resistance coefficient in the air branch pipe decreases slowly; when Re ≥ 4.5 × 103, the resistance coefficient of gas branch pipe decreases slowly. Additionally, the maximum calculation error of symmetrical gas branch pipe is 9.1%. The static mixer's inlet exhibits a converted velocity of 24 m/s, and the outlet demonstrates an airflow velocity of 23.2 m/s. As a result, a kinetic energy loss of 6.5% is observed. The static mixing chamber makes the airflow rotate and causes different gases to shear and mix. The mixing channel has the function of correcting the airflow deviation, especially for the sudden expansion section. Generally, the two gases can be mixed evenly at the outlet of the mixer. The standard k‐e model and realizable k‐e model are employed to simulate the sudden expansion channel, and indicate that the standard k‐e has a wider range of influence. Further investigation is recommended to better comprehend and optimize this particular area of influence. [ABSTRACT FROM AUTHOR]

Background: While the development of CT imaging technique has brought cognition of in vivo organs, the resolution of CT images and their static characteristics have gradually become barriers of microscopic tissue research. Purpose: Previous research used the finite element method to study the airflow and gas exchange in the alveolus and acinar to show the fate of inhaled aerosols and studied the diffusive, convective, and sedimentation mechanisms. Our study combines these techniques with CT scan simulation to study the mechanisms of respiratory movement and its imaging appearance. Methods: We use 3D fluid‐structure interaction simulation to study the movement of an ideal alveolus under regular and forced breathing situations and ill alveoli with different tissue elasticities. Additionally, we use the Monte Carlo algorithm within the OpenGATE platform to simulate the computational CT images of the dynamic process with different designated resolutions. The resolutions show the relationship between the kinematic model of the human alveolus and its imaging appearance. Results: The results show that the alveolus and the wall thickness can be seen with an image resolution smaller than 15.6 μm. With ordinary CT resolution, the alveolus is expressed with four voxels. Conclusions: This is a preliminary study concerning the imaging appearance of the dynamic alveolus model. This technique will be used to study the imaging appearance of the dynamic bronchial tree and the lung lobe models in the future. [ABSTRACT FROM AUTHOR]

Amphiphobic fluoroalkyl chains are exploited for creating robust and diverse self‐assembled biomimetic catalysts. Long terminal perfluoroalkyl chains (CnF2n+1 with n=6, 8, and 10) linked with a short perhydroalkyl chains (CmH2m with m=2 and 3) were used to synthesize several 1,4,7‐triazacyclononane (TACN) derivatives, CnF2n+1‐CmH2m‐TACN. In the presence of an equimolar amount of Zn2+ ions that coordinate the TACN moiety and drive the self‐assembly into micelle‐like aggregates, the critical aggregation concentration of polyfluorinated CnF2n+1‐CmH2m‐TACN⋅Zn2+ was lowered by ∼1 order of magnitude compared to the traditional perhyroalkyl counterpart with identical carbon number of alkyl chain. When 2'‐hydroxypropyl‐4‐nitrophenyl phosphate was used as the model phosphate substrate, polyfluorinated CnF2n+1‐CmH2m‐TACN⋅Zn2+ assemblies showed higher affinity and catalytic activity, compared to its perhyroalkyl chain‐based counterpart. Coarse‐grained molecular dynamic simulations have been introduced to explore the supramolecular assembly of polyfluoroalkyl chains in the presence of Zn2+ ions and to better understand their enhanced catalytic activity. [ABSTRACT FROM AUTHOR]

The following paper proposes a modern method of obtaining an extract from Viola tricolor L. with a high rutin content and enhanced antioxidant activity. Conventional isolation of active substances from plant raw material is high‐cost, elaborate and often harmful to the environment. The ultrasonic assistance micelle‐mediated extraction method (UAMME) and the cloud‐point extraction/separation technique are interesting alternatives. This work discusses the relationship between salt concentration and the cloud‐point extraction (CPE) yield. The molecular dynamic simulations investigated the impact of hydrocarbon chain length and the ratio of oxyethylene/oxypropylene units of model surfactants on the interactions between extraction system components. Micellar extract from the Viola tricolor was obtained using C9‐11 Pareth‐5 at 1 wt/vol% and subsequently concentrated by CPE with the addition of NaCl in concentrations from 5% to 30%. For comparison, water and ethanol extracts were also prepared. Antioxidant properties, polyphenols and flavonoid contents were measured for all samples. The HPLC method was used to determine the rutin concentration. The simulation part of the study confirmed the dependence of bioflavonoid solubilization efficiency on the surfactant structure. The determined descriptors allowed for finding the optimal structure of the model surfactants and gave a hint for their application to obtain extracts with high concentrations of antioxidants. [ABSTRACT FROM AUTHOR]

The integration of offshore wind energy into Power‐to‐X (PtX) process chains offers opportunities for the efficient use of renewable energy. This article analyzes different PtX process chain configurations and their adaptation to the offshore environment. However, direct coupling of PtX platforms with fluctuating electrical energy poses major challenges. Dynamic process simulation is presented for analysis of different plant configurations and operating strategies. The article emphasizes the need for interdisciplinary research to consider technological as well as economic and environmental aspects. [ABSTRACT FROM AUTHOR]

One of the central problems in ecology is how to scale from small‐scale observations and experiments to large‐scale patterns and processes. One approach to such upscaling is to use dynamic simulation models, but their application to large scales relevant for management is limited by computational costs, and their outputs are difficult to analyse without a systematic strategy. Our general objective is to propose such a strategy. The idea is to approximate the dynamics of detailed simulation models through a set of states, external drivers, and transition matrices, and then use Markov chain and network analysis of the resulting transition matrices to gain insights into the dynamics of the underlying detailed model. We used the individual‐based model COIRON, which simulates the dynamics of semiarid grass steppes in Patagonia (Argentina) under alternative grazing management, as example. Our specific objectives are to identify pathways of degradation and rehabilitation, as well as critical grazing thresholds and early‐warning vegetation states to guide sustainable grazing management in these steppes. Our results indicate nonlinear effects of stocking rate and grazing season on steppe dynamics. Markov chain analysis suggests benefits of seasonal over continuous grazing at intermediate stocking rates, and network analysis of recovery and degradation trajectories shows that intermediate stocking rates maximize differences between grazing seasons. Finally, our analysis identified specific vegetation states as early warning signals that indicate a high risk of irreversible vegetation changes. Patagonian grass steppes should ideally be managed with multi‐paddock grazing at moderate stocking rates around 0.5 sheep ha−1. The transition matrices summarize the relevant key features of the detailed model for larger scales, and applying Markov and network theory provides a systematic strategy to analyse its dynamics to respond to biological questions, both are often difficult to obtain by direct analysis of the detailed model. [ABSTRACT FROM AUTHOR]

The primary goal of the current study is to optimise crash box designs for automobiles. Machine learning (ML) techniques are used to build an intelligent and reliable ML framework. With the help of this framework, the crash box design can be optimised for crashworthiness analysis. The optimisation of the crash box design is resource‐intensive due to its intricate geometric design, use of a variety of materials, and extensive use of dynamic simulations to determine the ideal structural parameters through simulations. A reinforcement learning‐based (RL) optimization technique is developed for this reason. The crash box is built with nonlinear first‐order shear deformation shell elements to provide the necessary simulation data, and nonlinear elastoplastic material is used to model the dynamic impact process. The RL agents are tuned using finite element (FE) simulations and synthetic data generated by a generative adversarial network (GAN) to optimise and select the optimal model parameters for vehicle crashworthiness analysis. To estimate the correct model parameter required to fulfil specified crashworthiness metrics, the RL agent learns and optimises automatically. This method is effective in terms of resources and could be helpful in the early stages of vehicle development. [ABSTRACT FROM AUTHOR]

The ongoing commercialization and installation of full‐scale membrane aerated biofilm reactors (MABRs) stimulate the increasing need to monitor biofilm development. Biofilm thickness in MABRs can be assessed indirectly by plotting the exhaust oxygen purity versus bulk ammonia concentration, defined here as the MABR fingerprint soft sensor. Dynamic simulations with diurnal flow variations of an MABR unit model were implemented over a broad range of biofilm thicknesses and influent conditions consisting of variable C/N ratios and applied ammonia fluxes to assess the utility of the MABR fingerprint. Results show that the continuously decreasing trend of the MABR fingerprint plot slopes can be employed as a useful signal for biofilm thickness control in nitrogen removal processes. This technique is useful in a wide range of influent conditions and is helpful for MABR operators and designers to arrange biofilm thickness control events efficiently and determine where in an overall treatment process the technique can be applied to control biofilm thickness and optimize process performance. Practitioner points: The linear relationship between exhaust oxygen purity and bulk ammonia concentration is defined as the MABR fingerprint plot.MABR fingerprint plots are generated for a given biofilm thickness with diurnal flow or short‐term loading variations implemented.Continuously decreasing trends of the MABR fingerprint plot slopes are useful signals for biofilm control in nitrogen removal.The MABR fingerprint is useful over a wide range of influent conditions regarding C/N ratios and applied ammonia fluxes.MABR practitioners can use the fingerprint plots to determine when biofilm control measures should be taken. [ABSTRACT FROM AUTHOR]