Subsequent Simulations Research Articles

Green building interior design based on digital image processing and thermal environment simulation

With the increasingly severe global climate change and energy crisis, this study aims to explore effective strategies for green building interior design, especially in terms of thermal environment control, through digital image processing and thermal environment simulation. The study simulates indoor scenes based on image processing technology, using methods such as image acquisition, localization, and object detection to improve the accuracy of scene reconstruction, and conducts in-depth analysis of detection effects, laying the foundation for subsequent thermal environment simulations. In the design of the thermal energy environment control system, the calculation of indoor cooling load was studied and compared with existing thermal environment models to determine the impact of user activities on the indoor thermal environment. By establishing a thermal energy environment control model and implementing precise environmental regulation for different usage scenarios, indoor comfort and energy efficiency have been significantly improved. The experimental results show that the use of digital image processing simulation technology can effectively improve the accuracy and flexibility of indoor thermal environment control in green buildings, optimize energy efficiency, emphasize the importance of thermal factors in interior design, and provide theoretical basis and practical guidance for future building design practices.

Crystal structure predictions for molecules with soft degrees of freedom using intermonomer force fields derived from first principles.

A molecular crystal structure prediction (CSP) protocol used in the seventh blind test is presented. The seventh blind test was divided into two stages and included seven targets, with crystals containing from one to three molecules in asymmetric units, monomers built of up to 100 atoms, and all targets containing monomers with flexible degrees of freedom. Some targets were cocrystals and one target was a salt. These diverse targets were treated using a CSP protocol starting from finding the global and local minima conformations of the target molecule. Subsequently, an ab initio two-body rigid-monomer six-dimensional force field (aiFF) was developed for the global-minimum conformer. These aiFFs were then used in CSPs consisting of packing and lattice-energy minimization stages. Flexible-monomer CSPs were used for some targets. To describe the intramonomer FF, either generic empirical FFs or reparametrized FFs of this type were used, with some parameters fitted to ab initio energies of monomers in the latter case. A novel packing procedure was applied for two targets in stage 1. The success rate in the structure generation stage was 15% in submission phase and 54% in post-submission phase, while the corresponding values in the structure rating stage were 33% and 89%. We conclude that the inexpensive conformer-based approach with rigid-monomer CSPs can be recommended for investigations of crystals with flexible monomers. An advantage of this protocol is that it is fully based on first-principles quantum mechanics and generates tailor-made FFs suitable for use in subsequent molecular dynamics simulations investigating temperature-dependent effects. However, empirical intramonomer FFs reparametrized using ab initio data are not yet adequate for CSPs.

On the importance of discharge observation uncertainty when interpreting hydrological model performance

Abstract. For users of hydrological models, the suitability of models can depend on how well their simulated outputs align with observed discharge. This study emphasizes the crucial role of factoring in discharge observation uncertainty when assessing the performance of hydrological models. We introduce an ad hoc approach, implemented through the eWaterCycle platform, to evaluate the significance of differences in model performance while considering the uncertainty associated with discharge observations. The analysis of the results encompasses 299 catchments from the Catchment Attributes and MEteorology for Large-sample Studies Great Britain (CAMELS-GB) large-sample catchment dataset, addressing three practical use cases for model users. These use cases involve assessing the impact of additional calibration on model performance using discharge observations, conducting conventional model comparisons, and examining how the variations in discharge simulations resulting from model structural differences compare with the uncertainties inherent in discharge observations. Based on the 5th to 95th percentile range of observed flow, our results highlight the substantial influence of discharge observation uncertainty on interpreting model performance differences. Specifically, when comparing model performance before and after additional calibration, we find that, in 98 out of 299 instances, the simulation differences fall within the bounds of discharge observation uncertainty. This underscores the inadequacy of neglecting discharge observation uncertainty during calibration and subsequent evaluation processes. Furthermore, in the model comparison use case, we identify numerous instances where observation uncertainty masks discernible differences in model performance, underscoring the necessity of accounting for this uncertainty in model selection procedures. While our assessment of model structural uncertainty generally indicates that structural differences often exceed observation uncertainty estimates, a few exceptions exist. The comparison of individual conceptual hydrological models suggests no clear trends between model complexity and subsequent model simulations falling within the uncertainty bounds of discharge observations. Based on these findings, we advocate integrating discharge observation uncertainty into the calibration process and the reporting of hydrological model performance, as has been done in this study. This integration ensures more accurate, robust, and insightful assessments of model performance, thereby improving the reliability and applicability of hydrological modelling outcomes for model users.

Projectile Penetration into Calcareous Sand Subgrade Airport Runway Pavement with Genetic Algorithm Optimization

As an important civil and military infrastructure, airport runway pavement is faced with threats from cluster munitions, since it is vulnerable to projectile impacts with internal explosions. Aiming at the damage assessment of an island airport runway pavement under impact, this work dealt with discrete modeling of rigid projectile penetration into concrete pavement and the calcareous sand subgrade multi-layer structure. First, the Discrete Element Method (DEM) is introduced to model concrete and calcareous sand granular material features, like cohesive fracture and strain hardening due to compression, with mesoscale constitutive laws governing the normal and shear interactions between adjacent particles. Second, the subsequent DEM simulations of uniaxial and triaxial compression were performed to calibrate the DEM parameters for pavement concrete, as well as subgrade calcareous sand. Prior to the multi-layer structure investigations, penetration into sole concrete or calcareous sand is validated in terms of projectile deceleration and depth of penetration (DOP) with relative error ≤ 5.6% providing a reliable numerical tool for deep penetration damage assessments. Third, projectile penetration into the airport runway structure with concrete pavement and calcareous sand subgrade was evaluated with validated DEM model. Penetration numerical simulations with various projectile weight, pavement concrete thickness as well as striking velocity, were performed to achieve the DOP. Moreover, the back-propagation (BP) neural network proxy model was constructed to predict the airport runway penetration data with good agreement realizing rapid and robust DOP forecasting. Finally, the genetic algorithm was coupled with the proxy model to realize intelligent optimization of pavement penetration, whereby the critical velocity projectile just perforates concrete pavement indicating the severest subsequent munition explosion damage.

Developing a multi-epitope vaccine against MR766 strain of Zika virus: A bioinformatics approach

The Zika Virus has emerged as a significant global health concern, particularly due to its association with severe neurological complications such as microcephaly and Guillain-Barré syndrome. Given the urgent need for effective intervention strategies, this study aims to develop a targeted vaccine leveraging bioinformatics methodologies to identify B- and T-cell epitopes within the Zika virus Strain MR766 structural proteins. Through comprehensive epitope prediction algorithms, novel epitopes were identified and selected based on criteria including toxicity, immunogenicity, and antigenicity. These epitopes were then integrated into a multiple epitope vaccine constructs, incorporating various linker sequences (EAAAK, AAY, GPGPG) to optimize immunogenicity. Subsequent molecular docking simulations facilitated the design of a vaccine structure capable of effectively interacting with its target receptors. The vaccine construct was cloned into a pET-28a (+) vector for expression in Escherichia coli using SnapGene software. Evaluation of the expressed vaccine demonstrated a robust immune response in preclinical studies. Computational tools were employed to analyze the vaccine's efficacy against diverse Zika virus strains. The resulting Multi-Epitope Vaccine (MEV) emerges as a promising candidate for combating Zika virus infections, offering potential benefits in global public health efforts against this pathogen.

Numerical Simulation Study on Ice–Water–Ship Interaction Based on FEM-SPH Adaptive Coupling Algorithm

To address the impact of layered ice and seawater on polar vessels navigating in icy waters, this study employs a coupled finite element method (FEM) and smoothed particle hydrodynamics (SPH) algorithm to simulate the collision dynamics between the bow and stern of a designated icebreaker and the ice layers. The foundational principles and deployment strategies of the coupling algorithm have been meticulously delineated, with a subsequent simulation conducted to model the trajectory of icebreakers navigating through stratified ice conditions. The ice load on the hull, the movement of broken ice bodies, and the temporal variation of ice resistance during collision were analyzed. The method’s applicability and precision were substantiated through a comparative analysis between the simulated ice resistance outcomes and the ice load estimations derived from the Lindqvist formula. Finally, the differences between the bow and stern icebreaking methods were compared. The research findings indicate that the coupling algorithm demonstrates high precision in simulating the navigation of icebreakers under layered ice conditions, aligning with actual scenarios. This provides a solid foundation for further exploration of the ice load on polar vessels. Furthermore, at equivalent speeds and ice thicknesses, stern icebreaking was observed to induce greater oscillations in ice load and yield a higher mean resistance compared to bow icebreaking.

Experimental and theoretical investigation of cationic-based fluorescent-tagged polyacrylate copolymers for improving oil recovery

The growing need for energy and the depletion of oil wells necessitate advanced Enhanced Oil Recovery (EOR) techniques, particularly water and polymer flooding, which play a crucial role in augmenting hydrocarbon recovery rates. However, water flooding in high-permeability layers often leads to water breakthroughs, reduced sweep efficiency, and the formation of preferential channels, posing significant challenges to oil recovery and reservoir management. Conformance control treatments, including the use of polymer microspheres, offer a promising solution by sealing high-permeability zones and enhancing sweep efficiency. This study focuses on the application of fluorescent polymer microspheres based on polyacrylamide, which is extensively employed in the oil sector as an oil displacement agent. Fluorescent polymers called Poly 400, Poly 200, and Poly 600, incorporating cationic methacrylamide monomers, were synthesized through copolymerization to create amphiphilic polymers with enhanced stability and functionality. These fluorescent polymers were evaluated through flooding tests using a quarter-five-spot model of transparent quartz glass under UV light, allowing for instantaneous measurement and observation of fluorescence intensity. At reservoir conditions, the oil displacement experiments confirm that the incremental oil after water flooding by Poly 400, Poly 200, and Poly 600, is 13.1%, 9.1%, and 6.1% of OOIP respectively. The findings showed that fluorescent polymer microspheres could efficiently target high-permeability layers, adapt to varying pore throat sizes, and improve the plugging rate of high-permeability channels, thereby optimizing oil recovery. A subsequent simulation study using the CMG simulator provided further insights into the efficacy of these fluorescent polymers as EOR agents, revealing their potential to enhance sweep efficiency and enhance oil recovery. Simulation results showed that oil saturation decreased from 68% (initial) to 13.5%, 16.1%, and 18.3% after Poly 400, Poly 200, and Poly 600 flooding respectively. This work highlights the potential of fluorescent polymer microspheres as a valuable tool for EOR applications, offering significant advancements in reservoir management and oil recovery optimization.

Conformational and Solvent Effects on the Photoinduced Electron Transfer Dynamics of a Zinc Phthalocyanine-Benzoperylenetriimide Conjugate: A Nonadiabatic Dynamics Simulation.

Herein, we employed a combination of static electronic structure calculations and nonadiabatic dynamics simulations at linear-response time dependent density functional theory (LR-TDDFT) level with the optimally tuned range-separated hybrid (OT-RSH) functional to explore the ultrafast photoinduced dynamics of a zinc phthalocyanine-benzoperylenetriimide (ZnPc-BPTI) conjugate. Due to the flexibility of the linker, we identified two major conformations: the stacked conformation (ZnPc-BPTI-1) and the extended conformation (ZnPc-BPTI-2). Since the charge transfer states are much lower than the lowest local excitation in ZnPc-BPTI-1, which is contrary to ZnPc-BPTI-2, the ultrafast electron transfer (~3.6 ps) is only observed in the nonadiabatic simulations of ZnPc-BPTI-1 upon local excitation around the absorption maximum of ZnPc. However, when considering the solvent effects in benzonitrile: the lowest S1 states are both charge transfer states from ZnPc to BPTI for different conformers. Subsequent nonadiabatic dynamics simulations indicate that both conformers experience ultrafast electron transfer in benzonitrile with two time constants of 90 [100] fs and 1.40 [1.43] ps. Our present work not only agrees well with previous experimental study, but also points out the important role of conformational changes and solvent effects in regulating the photodynamics of organic donor-acceptor conjugates.

Blister-actuated laser-induced forward transfer (BA-LIFT): Understanding blister dynamics for enhanced process control

Blister-Actuated Laser-Induced Forward Transfer (BA-LIFT) stands as an innovative laser-based printing method designed to circumvent conventional nozzle-based systems and eliminate direct interactions between the laser pulse and the material to be transferred. This technique involves the interposition of a polyimide layer, strategically placed between the laser and the material. This work is aimed at understanding the critical role played by blister dynamics in the transference process, which is induced by the laser.Building upon a prior investigation where variations in laser pulse energy were explored, the current research involves the capture of high-speed imagery portraying the evolution and expansion of the blister, executed at distinct focal positions. The primary objective is to assess the blister’s influence on the overall process.During the blister’s expansion, our observations unveiled the presence of rapid oscillations, a consistent phenomenon observed regardless of the focal position. Consequently, we propose two polynomial fits, aimed at accurately replicating the blister’s dynamic behavior. These polynomial fits serve as valuable inputs for subsequent numerical simulations in the context of BA-LIFT, allowing for enhanced process control and performance optimization.

Phytosterols as inhibitors of New Delhi metallo-β-lactamase (NDM-1): an in silico study.

The global emergence of New Delhi metallo-β-lactamase-1 (NDM-1) poses a formidable challenge to antibiotic therapy, as it confers resistance to a wide range of β-lactam antibiotics. This study aims to identify potential inhibitors of NDM-1 and thereby restore the effectiveness of the current antibiotics. Employing a comprehensive computational approach integrating molecular docking and molecular dynamics (MD) simulations, a library of phytosterols was screened to identify promising candidates for inhibiting NDM-1 activity. Using the binding energy of meropenem, a frontline carbapenem antibiotic, as a reference, avenasterol, brassicasterol, and stigmasterol emerged as top phytosterol candidates for further investigation. Subsequent MD simulations confirmed the stability of NDM-1 complexes with avenasterol and stigmasterol over the simulation period, indicating their potential efficacy. These findings suggest that avenasterol and stigmasterol may effectively inhibit NDM-1 activity, warranting validation through in vitro and in vivo studies. Furthermore, these phytosterols hold promise as lead compounds for developing novel NDM-1 inhibitors. Their natural origin and potential inhibitory activity against NDM-1 offer compelling avenues for developing alternative antibacterial therapies to combat multidrug-resistant infections. This study underscores the utility of computational methods in drug discovery and highlights the potential of phytosterols as valuable candidates for addressing antibiotic resistance.

Use of multi-modelling methods to inform conservation and reintroductions of pine marten Martes martes in Britain

The successful onset of recovery of the European pine marten (Martes martes) in some parts of Britain through range expansion and, more recently translocation for reintroductions, has resulted in a strong interest in reintroduction projects throughout the country. However, the geographic scope and conservation goals of these initiatives are often local and lack consideration of how they fit within the wider context of national-scale pine marten conservation. Here, we aim to maximize conservation benefit strategically at a national level by developing a simple, transparent, and transferable framework based on landscape modelling methods and spatially explicit population viability analyses. Our new methodology has been developed specifically to inform decisions involving the spatial targeting of pine marten conservation measures. We began by applying habitat suitability and connectivity modelling at a national scale. Then, we performed spatially explicit life history simulations to assess the natural recovery of the species. This information was used to identify regions of interest for future reintroductions, and we performed subsequent simulations to assess the viability of a reintroduced population within each region. From all the regions assessed, we identified two that should be prioritized for further consideration based on our analyses of habitat suitability, connectivity and the viability of reintroduced populations. While our framework can be used to identify and prioritize regions of conservation value generally, our focus here is on the biological considerations associated with identifying suitable landscapes for pine marten reintroduction.

Precision Dosing of Intravenous Tocilizumab: Development of Pharmacokinetic Model-Derived Tapering Strategies for Patients With Rheumatoid Arthritis.

Tocilizumab targets the interleukin-6 receptor, and dosing is complex owing to its nonlinear clearance related to target binding. Therefore, tapering tocilizumab requires a different approach than that of tumor necrosis factor inhibitors (TNFi). This study aimed to identify these differences and enable personalized treatment of rheumatoid arthritis (RA) beyond TNFi therapy. A population pharmacokinetic model of intravenous tocilizumab was developed using data from a randomized controlled trial of dose tapering in patients with RA. Subsequent population-level Monte Carlo and individual Bayesian simulations were performed to create tapering strategies involving dose reduction and interval extension. The target trough concentration of tocilizumab was 5 mg/L. Finally, the drug savings were compared between the 2 methods. The pharmacokinetic of tocilizumab was described with a 2-compartment model with parallel linear (CL 0.20 L/d) and nonlinear (VM 5.2 mg/d, KM 0.19 mg/L) elimination. The linear clearance rate and central volume of distribution increased with lean body mass, and men exhibited higher clearance rates than women. The simulated concentration-time profiles demonstrated that, owing to nonlinear clearance, drug concentrations decreased more than dose-proportionally with lower doses. Tapering based on an individual Bayesian approach emerged as the most promising strategy, yielding a 39% reduction in drug use across virtual populations. Tapering strategies were developed for intravenous tocilizumab, offering potential application in patients with RA who have reached low disease activity or remission, pending clinical validation. The developed strategies demonstrate that the tapering of tocilizumab should be approached more carefully and in smaller steps than that of TNFi.

Modeling the influence of bainite transformation on the flow behavior of steel using a macroscale finite element analysis

This study comprehensively investigates the kinetics of bainitic ferrite transformation in steel alloys by integrating experimental results, finite element analysis, and thermodynamic modeling. Using a dilatometer and Gleeble tests, empirical data were acquired to calibrate the Bhadeshia and Hensel-Spittel models, forming the basis for subsequent finite element simulations. Owing to the high importance of temperature in bainite transformation, the accuracy of the predicted temperature fields was validated precisely against experimental measurements, confirming the reliability of the methodology. A modified Bhadeshia model was proposed incorporating the influence of the applied shear stress on the activation energy, thereby emphasizing the temperature-dependent Cstress coefficient. The electron backscatter diffraction results validate the finite element model, and further exploration reveals the implications for fracture patterns and density changes due to bainitic transformation. This study contributes to a nuanced understanding of bainitic ferrite kinetics, offering valuable insights for alloy design and optimization under various thermomechanical conditions, and paving the way for advanced research on phase transformation kinetics and material behavior.

Robustness of prefabricated construction supply chain network against underload cascading failure

A prefabricated construction supply chain(PCSC) is a complex network with high interdependency between entities. After disturbance, it is prone to cascading failure, leading to project delays or budget overruns. Therefore, it is necessary to model a robust network against cascading failure to achieve a sustainable prefabricated construction system. This study explores the functional robustness of a prefabricated construction supply chain network (PCSCN) against underload cascading failure. First, the PCSCN is constructed as a three-echelon supply chain network based on complex network theory, which can characterize the general characteristics of PCSC and provide the network foundation for the subsequent numerical simulation research. Then, a more realistic underload cascading failure model that adds the new element of substitute nodes is established to describe load loss propagation in the PCSCN. Finally, the Order Fulfillment Rate(OFR) is used as the robustness index to quantify network robustness from a functional perspective. The numerical simulation results indicate that in the PCSCN, the larger the initial load is, the more important the node, and component manufacturers are more important than building material suppliers. In addition, the node capacity upper bound parameter α has a positive relationship with robustness, the failure coefficient β has a negative relationship, and the edge weight adjustment coefficient θ has no significant impact on robustness. This research can provide guidance for developing cascade control and defense strategies in PCSCN risk management.

Ply-ply friction behavior between unidirectional thermoplastic prepreg plies during thermoforming: Characterization and modeling

The ply-ply friction behavior of unidirectional carbon fiber reinforced polyphenylene sulfide (UD CF/PPS) prepreg in thermoforming was investigated through an improved pull-through testing system. The effects of temperature, normal force and slipping velocity were considered in testing. The results indicated the existence of three key mechanisms underlying slipping: namely the resin shear, fiber–fiber contact and fiber-resin interaction. A three-stage division of the experimental curve was proposed, and several factors were defined to establish a quantitative definition of the ply-ply friction behavior. The results showed that the influence of slipping velocity is particularly evident. Its post-yield stress (12.8 kPa), steady-state CoF (0.118) and residual stress (0.705 kPa) were the highest, exhibiting the largest changes of 957.9 %, 736.9 % and 47.2 %, respectively. This indicated the strong contribution of resin in ply-ply friction. In addition, the Stribeck analysis also suggested the dominance of hydrodynamic lubrication condition in slipping. Based on the experimental results, a simple phenomenological model was proposed based on experimental curves to accurately describe the effects of processing parameters. This work presents a comprehensive characterization of the ply-ply friction behavior of UD CF/PPS prepreg in thermoforming, providing a substantial experimental foundation for the subsequent simulation research.

Simulation inversion analysis of simultaneous commutation failure of Zhaoyi and Yindong DC

Abstract Aim at the three times simultaneous commutation failure of two Multi-outfeed and Multi-infeed DC Systems in a Similar Path of Ningxia, the Ningxia power grid model is built in Power System Analysis Software Package (PSASP) with actual parameters, and the accident inversion simulation is carried out based on the operation state of the power grid before the fault. Based on the inversion simulation, the simulation results were compared with the measured PMU data. The results showed that the trend of simulation and the measured curve is consistent, and the simulation was slightly more serious than the actual fault, but the overall error was less than 10%, which verified the accuracy of the simulation model and method, and provided a basis for the subsequent simulation analysis of the power grid operation mode.

A Study on the Mid-frequency Tire-Sourced Cabin Noise in Electric Vehicles

ABSTRACT This study investigates and provides a framework for addressing a reported tire- sourced cabin noise in the mid-frequency range of 300–500 Hz for an electric vehicle (EV). Noise, vibration, and harshness (NVH) of EVs present new challenges compared with internal combustion engine vehicles because of significant design changes between the two vehicle types. In turn, the tire–road interaction noise becomes a more significant source of cabin noise in EVs. In this regard, some prominent EV manufacturers recently reported relatively high measured cabin noise, particularly in the mid-frequency range of 300–500 Hz. Identifying the root cause(s) of noise in that range is a challenging task, as both tire structure–borne and airborne sources are contributors in that frequency range of elevated noise. The current work presents the results of an experimental modal analysis to provide insight into some potential sources of the reported noise for an all-season tire/wheel assembly designed for an EV. The subsequent parametric simulations, conducted via the tire–vehicle finite element model, evaluate some of the mitigation solutions for the reported noise.

Binding of a Drug (Colchicine) to L-Asparaginase Enzyme Using Multispectroscopic, Thermodynamics, and Simulation Studies: Possible Implication in Acute Lymphoblastic Leukemia Treatment.

The research aims to elucidate how drug interactions affect the activity of L-asparaginase (L-ASNase), an essential enzyme in cancer treatment, especially for acute lymphoblastic leukemia (ALL). Understanding these interactions is crucial for optimizing treatment effectiveness and reducing adverse effects. This study explores the intricate molecular interactions and structural dynamics of L-ASNase upon binding with colchicine. Fluorescence quenching experiments were conducted at various temperatures (298, 303, and 310 K), revealing notable interactions between L-ASNase and colchicine. These interactions were characterized by a reduction in fluorescence intensity and a blue shift in emission maxima. Additional analyses, including the determination of Stern-Volmer quenching constants (KSV), bimolecular quenching rate constants (kq), and thermodynamic parameters, indicated a static quenching mechanism with moderate binding affinities (Ka: 1.40-2.71 × 104 M-1) across different temperatures. Thermodynamic study suggested positive enthalpy and entropy changes (ΔH° = -10.26 kcal mol-1; ΔS° = -14.19 cal mol-1 K-1), suggesting a spontaneous reaction with negative ΔG° values (-5.86 to -6.03 kcal mol-1). FRET measurements supported optimal distances (r and Ro) for FRET occurrence, reinforcing the static quenching mechanism. Molecular docking further supported these findings, revealing a 1:1 stoichiometric binding ratio for L-ASNase:colchicine and elucidating specific binding orientations and interactions critical for complex stability. Subsequent molecular dynamics simulations spanning 100 ns underscored the stability of the L-ASNase-colchicine complex, with minimal deviations observed in key structural parameters such as RMSD, RMSF, Rg, and SASA. Additionally, spectroscopic analyses, including circular dichroism (CD), synchronous fluorescence, and 3D fluorescence provided insights into the conformational changes and alterations in the microenvironment of aromatic amino acid residues in L-ASNase upon colchicine binding. Moreover, L-ASNase activity was slightly reduced by 25% in the presence of colchicine. This comprehensive investigation sheds light on the molecular intricacies of the L-ASNase-colchicine complex, advancing our understanding of drug-target interactions and offering potential avenues for therapeutic applications.

The rotational disruption of porous dust aggregates from ab initio kinematic calculations

The size of dust grains in the interstellar medium follows a distribution where most of the dust mass is made up of smaller grains. However, the redistribution from larger grains towards smaller sizes, especially by means of rotational disruption, is still poorly understood. We aim to study the dynamics of porous grain aggregates undergoing an accelerated rotation, namely, a spin-up process that rapidly increases the angular velocity of the aggregate. In particular, we aim to determine the deformation of the grains and the maximal angular velocity up to the rotational disruption event by caused by centrifugal forces. We precalculated the porous grain aggregate by means of ballistic aggregation analogous to the interstellar dust as input for subsequent numerical simulations. We performed three-dimensional (3D) N-body simulations, mimicking the radiative torque spin-up process up to the point where the grain aggregates become rotationally disrupted. Our simulations results are in agreement with theoretical models predicting a characteristic angular velocity, $ disr $, on the order of $ rad\ $, where grains become rotationally disrupted. In contrast to theoretical predictions, we show that for large porous grain aggregates ($ nm $), the $ disr $ values do not strictly decline. Instead, they reach a lower asymptotic value. Hence, such grains can withstand an accelerated rotation more efficiently up to a factor of 10 because the displacement of mass by centrifugal forces and the subsequent mechanical deformation supports the buildup of new connections within the aggregate. Furthermore, we report that the rapid rotation of grains deforms an ensemble with initially 50:50 prolate and oblate shapes, respectively, preferentially into oblate shapes. Finally, we present a best-fit formula to predict the average rotational disruption of an ensemble of porous dust aggregates dependent on the internal grain structure, total number of monomers, and applied material properties.

A Novel A105Y Mutant of CYP17A1 Exhibits Almost Perfect Regioselectivity in the Production of 17α-Hydroxyprogesterone.

17α-Hydroxyprogesterone (17α-OHP) is a steroid hormone with significant biological activity that can be obtained by catalyzing progesterone (PROG), the main product of sitosterol, through CYP17A1. However, increasing the catalytic specificity of HCYP17A1 for C17 hydroxylation of progesterone (PROG) poses a formidable challenge due to the close proximity of the C16 and C17 positions. In this study, a rational design was utilized to alter the spatial configuration of the substrate channel, leading to the complete abolition of its 16-hydroxylation activity. Subsequent molecular dynamics simulations revealed that the A105Y mutation heightened the rigidity of the G95-I112 region of CYP17A1, consequently regulating the direction of the entry of PROG into the catalytic pocket. Moreover, the establishment of hydrogen bonding between Y105 and R239, coupled with Pi-stacking of A105Y with F114, effectively immobilizes the substrate PROG in a fixed position, explaining the practically perfect regioselectivity observed in A105Y. Finally, a multifaceted enzymatic cascade system, incorporating A105Y, cytochrome P450 reductase (CPR), and glucose-6-phosphate dehydrogenase (ZWF) for NADPH cofactor regeneration, was constructed in Pichia pastoris GS115. The resulting biocatalyst produced 106 ± 3.2 mg L-1 17α-OHP, a 4.6-fold increase compared with A105Y alone. Thus, this study provides valuable insights for improving the regioselectivity and activity of P450 enzymes.