Computational modeling (CM) is a versatile scientific methodology used to examine the properties and behavior of complex systems, such as polymeric materials for biomedical bioengineering. CM has emerged as a primary tool for predicting, setting up, and interpreting experimental results. Integrating in silico and in vitro experiments accelerates scientific advancements, yielding quicker results at a reduced cost. While CM is a mature discipline, its recent prominence in Bio-medical Engineering for biopolymer materials has recently gained prominence. In biopolymer biomedical engineering, CM focuses on three key research areas: A) Computer-aided design (CAD/CAM), B) Finite Element Analysis, and C) Molecular Dynamic Simulations. This review centers on Molecular Dynamics (MD) simulations in biopolymers, analyzing structural, functional, and evolutionary aspects of biomolecular systems over time. MD simulations solve Newton's equations of motion for all-atom systems, generating spatial trajectories for each atom, providing insights into properties like water absorption on biopolymer surfaces and interactions with solid surfaces, crucial for biomaterial assessment. This review offers readers a comprehensive overview of the diverse applications of Molecular Dynamics (MD) simulations on biopolymers. Furthermore, it emphasizes the flexibility, robustness, and synergistic relationship between in silico and experimental techniques.

1D spin crossover (SCO) solids which convert between the low-spin (LS) and the high-spin (HS) states are widely studied in the literature due to their diverse thermal and optical characters which allows obtaining many original behaviors, such as large thermal hysteresis, incomplete spin tran-sitions, as multi-step spin transitions with self-organized states. In the present work, we investigate the thermal behaviors of a system of two-elastically coupled 1D mononuclear chains, using the electro-elastic model, by including an elastic frustration in the nearest neighbors (nn) bond length distances of each chain. The chains are made of SCO sites that are coupled elastically through springs with their nn and next-nearest neighbors. The elastic inter-chain coupling includes diagonal springs, while the nn inter-chains distance is fixed to that of the high-spin state. The model is solved using MC simulations, performed on the spin states and the lattice distortions. When we only frustrate the first chain, we found a strong effect on the thermal-dependence of the HS fraction of the second chain, whose, by lowering its transition temperature which is also accompanied with the appearance of a significant residual HS fraction at low temperature. In the second step, we frustrate both chains by imposing different frustration rates and found that, for high frustration values, the thermal dependence of the total HS fraction exhibits three step and even four step spin transitions. The careful examination of the spin state structures in the plateau regions revealed the existence of special antiferro-elastic structure of type LSLS-HSHS-LSLS-HSHS along the first chain, and HSHS-LSLS-HSHS-LSLS along the second, also showing that the two chains seem to be antifer-ro-elastically coupled. This type of organization is interesting, because it anticipates the possible existence of periodic structures made of alternate 1D antiferro-like HS-LS strings coupled in the ferro-like fashion along the interchain direction in the 2D case.

Pentagalloyl glucose (PGG) is currently being investigated as a non-surgical treatment for abdominal aortic aneurysms (AAA); however molecular mechanisms of action of PGG on the AAA matrix components and the intra-luminal thrombus (ILT) still need to be better understood. To assess these interactions, we utilized peptide fingerprinting and molecular docking simulations to predict the binding of PGG to vascular proteins in normal and aneurysmal aorta, including matrix metalloproteinases (MMPs), cytokines and fibrin. We performed PGG diffusion studies in pure fibrin gels and human ILT samples. PGG was predicted to bind with high affinity to most vascular proteins, the active sites of MMPs, and several cytokines known to be present in AAA. Finally, despite potential binding to fibrin, PGG was shown to diffuse readily through thrombus at physiologic pressures. In conclusion, PGG can bind to all the normal and aneurysmal aorta protein components with high affinity, potentially protecting the tissue from degradation and exerting anti-inflammatory activities. Diffusion studies showed that thrombus presence in AAA is not a barrier to endovascular treatment. Together, these results provide a deeper understanding of the clinical potential of PGG as a non-surgical treatment of AAA.

The β-amyloid cleaving enzyme 1 (BACE1) is regarded as an important target of drug design toward treatment of Alzheimer's disease (AD). In this study, three separate molecular dynamics (MD) simulations and calculations of binding free energies were carried out to comparatively probe identification mechanism of BACE1 on three inhibitors 60W, 954 and 60X. The analyses on MD trajectories indicate that the presence of three inhibitors influences structural stability, flexibility and internal dynamics of BACE1. Binding free energies calculated by using solvated interaction energy (SIE) and molecular mechanics generalized Born surface area (MM-GBSA) methods reveal that the hydrophobic interactions provide decisive forces for inhibitor-BACE1 binding. The calculations of residue-based free energy decomposition suggest that the sidechains of residues L91, D93, S96, V130, Q134, W137, F169 and I179 play key roles in inhibitor-BACE1 binding, which provides a direction for future drug design toward treatment of AD.

This study delves into the realm of potential therapeutics for breast cancer by conducting a comprehensive docking simulation and virtual screening analysis using Autodock Vina Algorithm. The focus based on the human epidermal growth factor receptor 2 (HER2), a key protein associated with various cancers, particularly in the context of breast cancer.The results reveal compelling insights into the binding interactions of several natural compounds and drugs with HER2. Notably, Acebilustat, Bemcentinib, and Amentoflavone exhibit outstanding binding energies, averaging around -10 kcal/mol, suggesting strong and favorable interactions with the HER2 target.These encouraging findings not only emphasize the potential biological significance of these compounds but also hint at their potential usefulness in fighting breast cancer.Their promising binding affinities with HER2 position them as potential candidates for further investigation and development as therapeutic agents against breast cancer.

Australia is a unique continent surrounded by the ocean and the majority of catchments flow to the coast. Some of these catchments are gauged and others are ungauged. There are 405 gauged catchments covering 2,549,000 km2 across the coastal regions of 12 drainage divisions in Australia. Whereas there are 771 catchments conceptualised as ungauged covering additional 835,000 km2. The mean annual rainfall and PET and its spatial and temporal distribution vary significantly from one drainage division to another. We developed a continuous daily streamflow time series of all gauged and ungauged catchments from 1993 onwards. We applied the GR4J lumped conceptual model to these catchments. The performance of gauged catchments was analysed through (i) visual inspection of daily hydrographs, flow duration curves and daily scatter plots, and (ii) performance metrics including NSE and PBias. Based on the NSE and PBias, performance ratings of 80% and 96% of the models respectively were found 'good'. There was no relationship found between the catchment area and model performance. The ungauged catchments were divided into four categories based on distance from potential donor catchments where observed data are available for GR4J model calibration, and Köppen climate zone. The total ungauged catchments represent 24.7% of the total drainage division areas. The streamflow from ungauged catchments was estimated using GR4J model based on the parameters of their donor catchments. Overall, runoff ratios from ungauged catchments were found to be higher compared to their donor gauged catchments, likely driven by their higher rainfall and less PET. This tendency was particularly evident in two drainage divisions – the Carpentaria Coast (CC) and Tanami-Timor Sea Coast (TTS) where ungauged areas comprised 51% and 43% respectively. The mean gauged annual streamflow varied significantly across drainage divisions – 230 GL from South Australian Gulf (SAG) to 146,150 GL in TTS. The streamflow from all ungauged catchments was estimated at 232,200 GL per year. Overall, the average streamflow from all drainage divisions, including gauged and ungauged areas, across the coastal regions of Australia was estimated at 419,950 GL per year. This nationwide estimate of streamflow dataset could potentially enhance our understanding of coastal processes and improvements of marine modelling systems and tools.

Accurate treatment planning in radiotherapy essentially decreases secondary damage to healthy tissue surrounding the tumor. Due to plans to use a direct, highly collimated, narrow beam with high intensity to treat small area tumors, researchers have studied microbeam radiation therapy extensively. Using a synchrotron beam as the radiation source may help to limit secondary damage, but treatment planning using computerized simulations and dosimetry is still necessary to achieve optimal results. For this purpose, PDA-gel dosimeters were developed and their sensitivity around a 150 keV induced synchrotron X-ray radiation beam was examined via Monte Carlo simulations using the EGS5 code system. The microbeam development is now at the animal study stage. In this study, we simulate the irradiation of a rat's brain. The simulation results obtained spectra for two types of PDA-gel dosimeters that were compared with the spectrum obtained in a modelized brain tumor of a rat. Additionally, percentage depth dose curves were calculated for the brain tissue and the two gels. Correction equations for the dosimeters were obtained from the dose-difference plots. For further references, these equations can be used to calculate the actual dose in a brain tumor in a rat. The Monte Carlo simulations demonstrate that PDA-gel dosimeters can be used as a reference technique in planning treatment using synchrotron irradiations and in other medical treatment planning methods.

3D facial surface imaging is a useful tool in dentistry and in terms of diagnostics and treatment planning. Between-groups PCA (bgPCA) is a method that has been used to analyse shapes in biological morphometrics, although various “pathologies” of bgPCA have recently been proposed. Monte Carlo (MC) simulated datasets were created here in order to explore “pathologies” of multilevel PCA (mPCA), where mPCA with two levels is equivalent to bgPCA. The first set of MC experiments involved 300 uncorrelated normally distributed variables, whereas the second set of MC experiments used correlated multivariate MC data describing 3D facial shape. We confirmed previous results of other researchers that indicated that bgPCA (and so also mPCA) can give a false impression of strong differences in component scores between groups when there is none in reality. These spurious differences in component scores via mPCA reduced strongly as the sample sizes per group were increased. Eigenvalues via mPCA were also found to be strongly effected by imbalances in sample sizes per group, although this problem was removed by using weighted forms of covariance matrices suggested by the maximum likelihood solution of the two-level model. However, this did not solve problems of spurious differences between groups in these simulations, which was driven by very small sample sizes in one group here. As a “rule of thumb” only, all of our experiments indicate that reasonable results are obtained when sample sizes per group in all groups are at least equal to the number of variables. Interestingly, the sum of all eigenvalues over both levels via mPCA scaled approximately linearly with the inverse of the sample size per group in all experiments. Finally, between-group variation was added explicitly to the MC data generation model in two experiments considered here. Results for the sum of all eigenvalues via mPCA predicted the asymptotic amount for the total amount of variance correctly in this case, whereas standard “single-level” PCA underestimated this quantity.

Integrating photovoltaic (PV) systems plays a pivotal role in the global shift toward renewable energy, offering significant environmental benefits. In many instances, utility companies pay for both energy and peak demand. PV systems can effectively reduce energy consumption during their operational periods, while, their contribution during peak hours, particularly in the early morning and late evening, is often limited. To address this issue, battery storage systems are utilized for storing energy during off-peak hours and releasing it during peak times. However, finding the optimal size of PV-battery systems remains a challenge. This study proposes a novel statistical model to optimize PV-battery system sizing for enhanced peak demand reduction. The model aims to flatten 95% of peak demand days up to a certain demand threshold, ensuring consistent energy supply and financial benefit for utility companies. A straightforward and effective search methodology is employed to determine the optimal system sizes. Additionally, the model effectiveness is rigorously tested through a modified Monte Carlo simulation coupled with time series clustering to generate various scenarios to assess performance under different conditions. The results indicate that the optimal PV-battery system successfully flattens 95% of daily peak demand up to 2000 kW, yielding a financial benefit of $812,648 over 20 years.

Sustainable development of our society demands recycling of metallic wastes which may contain a variety of metallic impurities. Thus, it is desirable to develop a ‘universal’ structure, such as an amorphous alloy tolerating high concentrations of metallic pollutants. We performed ab initio molecular dynamics simulations to manufacture a novel multicomponent amorphous alloy of twenty elements (20e-HEAA). Analysis reveals both topological and chemical compositional short-range ordering in the obtained 20e-HEAA and formation of B-B clusters. Electronic structure calculations reveal the metallic nature of the amorphous alloy with its Fermi level falling in a valley in the density of states. Moreover, the Zn 3d and Cd 4d electrons exhibit a localized nature and thus, should be excluded from the valence electron concentration (VEC) analysis in the study of high-entropy alloys. The information obtained here is helpful to get insight into multicomponent high entropy materials, especially multicomponent high-entropy amorphous alloys as potential circular metals.

In its prefusion state, the SARS-CoV-2 Spike protein (similarly to other class I viral fusion proteins) is metastable, which is considered to be an important feature for optimizing or regulating their functions. After the binding process of its S1 subunit (S1) with the ACE2, the Spike protein (S) suffers a dramatic conformational change where S1 splits from the S2 subunit, which then penetrates the membrane of the host cell, promoting the fusion of the viral and cell membranes. This results in the infection of the host cell. In a previous work, we showed -using large scale molecular dynamics simulations- that the application of external electric fields (EF) induces drastic changes and damage in the receptor-binding domain (RBD) of the wild type Spike protein, as well of the Alpha, Beta and Gamma variants, leaving a structure which cannot be recognized any more by ACE2. In this work, we first extend the study to the Delta and Omicron variants and confirm the high sensitivity and extreme vulnerability of S to moderate EF (as weak as 104 V m-1), but, more importantly, we also show that, in contrast, the postfusion state of the spike protein does not suffer structural damage even if electric field intensities four orders of magnitude higher are applied. These results provide a solid scientific basis to confirm the prefusion state metastability roots of the SARS-CoV-2 Spike protein susceptibility to be damaged by EF. After the virus docks to the ACE2 receptor, the stable and robust postfusion conformation develops, which exhibits a similar resistance to EF (damage threshold higher than 108 V m-1) like most globular proteins.

This study investigates the possible mechanisms related to the wide range of relative humidity in cirrus clouds (RHi). Under the closed adiabatic assumption, the impacts of vertical motion and ice crystal deposition/sublimation on RHi are investigated through in situ observations and parcel model simulations. Vertical motion is an active external force that changes the RHi, and ice crystal deposition/sublimation plays a role in mitigating the change in RHi. They are the two most important mechanisms involved in controlling the RHi fluctuation during cirrus evolution and could well explain the wide range of RHi in wave-related cirrus clouds. Furthermore, a comparison of cloud statistical characteristics from both observations and simulations shows that a very low value (e.g., 0.001) for the water vapor ice deposition coefficient is highly unlikely.

An extensive review of literature simulations of polymer melts is given, considering results that test aspects of the Rouse model in the melt. We focus on the mean-square amplitudes < (X_p(0))^{2} > and time correlation functions < X_p(0) X_p(t) > of the Rouse modes $X_p(t)$. Contrary to the Rouse model: (i) Mean-square Rouse mode amplitudes < (X_p(0))^2> do not scale as sin^{-2}(p \pi/2N), N being the number of beads in the polymer. For small p (say, p <= 3) < (X_p(0))^2> scales with p as p^{-2}$; for larger p it scales as p^{-3}. (ii) Rouse mode time correlation functions < X_p(t) X_p(0) > do not decay with time as exponentials; they instead decay as stretched exponentials exp(-a t^b)$. b depends on p, typically with a minimum near N/2 or N/4. (iii) Polymer bead displacements are not described by independent Gaussian random processes. (iv) For p not equal to q, < X_p(t) X_{q}(0) > is sometimes non-zero. (v) The response of a polymer coil to a shear flow is a rotation, not the affine deformation predicted by Rouse. Simulations thus conclusively demonstrate that the Rouse model is invalid in polymer melts. We also briefly consider the Kirkwood-Riseman polymer model.

Oleanolic acid (OA) being the ubiquitous compound in the plant kingdom is studied for both the neuroprotective and neurotoxic properties. The mechanism of acetylcholinesterase (AChE) inhibitory potential of OA is investigated using the molecular dynamic simulations (MD) and docking as well as membrane-like and in vitro tests. There are also applied SH-SY5Y human neuroblastoma cells as well as in vivo on the zebrafish tests. The inhibitory potential towards the AChE enzyme is examined using the TLC-bioautography assay (the IC50 value is 9.22 μM). The CH- interactions between the central fragment of the ligand molecule and the aromatic cluster created by the His440, Phe288, Phe290, Phe330, Phe331, Tyr121, Tyr334, Trp84 and Trp279 side chains are observed. The in vitro tests carried out on the SH-SY5Y cells indicates that the viability rate is reduced to 71.5%, 61%, and 43% at the concentrations of 100 µg/mL, 300 µg/mL, and 1000 µg/mL, respectively after 48 hours of incubation whereas cytotoxicity against the tested cell line with the IC50 value is 714.32 ± 32.40 µg/mL. The in vivo tests on the zebrafish prove that there is no difference between the control and experimental groups as regards the mortality rate and morphology (P>0.05).

This work exclusively focuses on the assessment of the thermal performance of a multifunctional facade panel incorporating PCM in foam layers, recurring to a hot box heat flux meter method to determine the thermal transmittance (U-value). The experimental setup is based on the steady-state approach using climatic chambers, assuring a stable thermal environment. Even small fractions of PCM achieved a small reduction in thermal amplitude. Numerical simulations using Ansys Fluent were developed to evaluate the performance of PCM use over a wide range of temperature boundary conditions and operating modes. These numerical models were calibrated and validated using the results of experimental tests, achieving a correlation factor of 0.9674, thus accurately representing a real-world scenario. The decrement factor (f) was used to analyse the data. It was identified that the efficiency of the panel and size of the optimum region increased with the PCM fraction growth. The simulated behaviour was optimum when the input mean temperature is of 20 °C for a room temperature of between 18-20 °C. The results show the significant potential of the multi-layered panel and the thermal regulator effect of the PCM incorporated on indoor space temperature to reach good thermal comfort levels.

A new approach was presented in this study to simulate a stable atom along with subatomic particles in it. Subatomic particles in an atom are treated as conventional particles, exhibiting attraction and repulsion between them, giving a stable atom simulation. This new approach leads to developing new potentials for subatomic particles to simulate a stable atom. Subatomic particle dynamics (SPD) simulations were developed for within-atom simulations that give a stable atom structure for infinite time and provide many insights into electron trajectories and atom properties like energies and radius of the atom. The effect of protons and neutrons movement in the nucleus on electron trajectories was captured in SPD. Hydrogen and Carbon atom SPD were reported in this study. The Pilot-wave theory was implemented in this study to simulate the wave nature of subatomic particles in an atom. Electrons motion was guided by the interference pattern produced by the electron’s aether medium waves in SPD. SPD was implemented on molecules, resulting in a stable molecular structure giving insights into electron trajectories shared by multiple atoms.

Cholinesterase (ChE) and secretase (BACE) inhibitors, and fibril- and β-amyloid-suppressing medicines are used to treat Alzheimer's disease (AD) symptomatically. The prevalence and complex nature of AD have increased the urgent need for multi-targeted directed ligands (MTDLs). This is because MTDLs can prevent potential drug-drug interactions during poly-therapy and have a better therapeutic profile than single targeted agents. Using piperazine linker or spacer and two primary scaffolds, benzofuran and 8-hydroxyquinoline, a unique class of multi-targeted medicines was recently reported by our group. These compounds showed re-markable effectiveness in inhibiting Aβ1-42 aggregation and acting as iron chelators.The results prompted us to synthesize an additional series of compounds as multimodal anti-AD agents and investigate its inhibitor activities to ChE (AChE/BChE) and BACE1 enzymes. The resulting in-hibitory effects suggested that the compounds under study might be used to improve cognitive function. The docking analysis' findings revealed that the compounds bind to AChE and BChE by forming H-bond interactions with amino acid residues at binding sites and µ-stacking inter-actions with aromatic residues, whereas the binding to BACE1 only revealed H-bond interac-tions with amino acid residues at binding sites.

The paper deals with an electrothermal model of a thermoelectric converter dedicated to performing simulations of coupled thermal and electrical phenomena taking place in harvesting processes. The proposed model is used to estimate the electrical energy gain from waste heat that would be sufficient to supply electronic circuits, in particular autonomous battery-less nodes of wireless sensor networks (WSN) and Internet of Things (IoT) devices. The developed model is not limited to low power electronic solutions such as WSN or IoT; it can also be scaled up and applied to simulations of considerably higher thermal power conversion. In the paper, a few practical case studies are presented that show the feasibility and suitability of the proposed model for complex simultaneous simulation processes, in both electrical and thermal domains. The first example deals with a combined simulation of the electrothermal model of a thermoelectric generator (TEG) and an electronic harvester circuit based on Analog Devices’ power management integrated circuit LTC3108. The second example relates to the thermalization effect in heat sink-less harvesting applications that could be mitigated by a pulse mode operation.

The hot rolling in the process chain of the aluminium rolled products present the critical element of material quality and influence on productivity. The desire to increase the letter demand modifications of hot rolling, consequential changes of microstructure, crystallographic texture, mechanical and formability properties must be knowledge and consistently considered in planning the rolling process and rolled product. Achieving lower thicknesses of the hot-rolled band would enable fewer passes with cold rolling; consequently, hot rolling with the same number of passes will complete with lower temperatures. Microstructural and texture characterization with the optical microscope and scanning electron microscope for the hot-rolled band 3.25 mm the smaller grains appeared in the center of the cross-section, unlike for the hot-rolled band 6 mm, the smaller grains were detected on the upper and bottom position of the cross-section. Furthermore, the comparison shows also that the hot-rolled band 6 mm has 64 % of random texture components and 83 % of recrystallized grains, and the proportional adjustment for the hot-rolled band 3.25 mm has the 42 % of random texture components and 55 % of recrystallized grains. For the mechanical testing results, the elongation values in rolling and transverse directions significantly differ just in the case of a hot rolled band of 3.25 mm. Consequently, the earing results are more than 1.5 % higher for the hot-rolled band, 3.25 mm, than the hot-rolled band, 6 mm.

In the development of a digital twin (DT) for hydropower turbines, dynamic modeling of the system (e.g., penstock, turbine, speed control) is crucial, along with all the necessary data interface, virtualization, and dashboard designs. Since the DT must mimic the actual dynamics of the hydropower turbine accurately, adaptive learning is required to train these dynamic models online so that the models in the DT can effectively follow the representation of the actual hydropower turbine dynamics accurately and reliably. This study presents an adaptive learning method for obtaining the hydropower turbine models for DT development of hydropower systems using recursive least squares algorithm. To simplify the formulation, the hydropower turbine under consideration was assumed to operate near a fixed operating point, where the system dynamics can be well represented by a set of linear differential equations with constant parameters. In this context, the well-known six-coefficient model for the Francis turbine was formulated as the starting point to obtain input and output models for the turbine. Then, an adaptive learning mechanism was developed to learn model parameters using the real-time data from a hydropower turbine testing system. This led to a semi-physical modeling in which the first principles and data-driven modeling are integrated to produce dynamic models for the DT development. Applications to a pilot system at the Norwegian University of Science and Technology (NTNU) were made, and the models learned adaptively using the data collected from the university’s pilot system. Desired modeling and validation results were obtained.

RANS simulations have been broadly used to investigate turbulence in the oceans and atmosphere. Within these environments there are a multitude of tracers undergoing reactions (eg. phytoplankton growth, chemical reactions). The distribution of these reactive tracers is strongly influenced by turbulent mixing. With a 50 member ensemble of two dimensional Rayleigh-Taylor induced turbulent mixing, we show that the dynamics of a reactive tracer growing according to Fisher’s equation are poorly captured by the mean. A fluctuation-dependent sink introduced by Reynolds averaging Fisher’s equation transfers concentration from the mean to the fluctuations. We compare the dynamics of the reactive tracer with those of a passive tracer. The reaction causes the concentration of reactive tracer to increase thereby increasing Fickian diffusion and allowing the reactive tracer to diffuse into turbulent structures that the passive tracer cannot reach. A positive feedback between turbulent mixing and fluctuation growth is identified. We show that eddy viscosity and diffusivity parameterizations fail to capture the bulk trends of the system and identify a need for negative eddy diffusivities. One must therefore be cautious when interpreting RANS results for reactive tracers.

Chest X-ray (CXR) is the first tool globally employed to detect cardiopulmonary pathologies. These acquisitions are highly affected by scattered photons due to the large field-of-view required. Scatter in CXRs introduces background in the images, which reduces their contrast. We developed three deep learning-based models to estimate and correct the scatter contribution to CXRs. We used a Monte Carlo (MC) ray-tracing model to simulate CXRs from human models obtained from CT scans using different configurations (depending on the availability of dual-energy acquisitions). The simulated CXRs contained the separated contribution of direct and scattered X-rays in the detector. These simulated datasets were then used as the reference for the supervised training of several NN. Three NN models (single and dual energy) were trained with the MultiResUNet architecture. The performance of the NN models was evaluated on CXRs obtained with the MC code from chest CTs of patients affected by COVID-19. The results showed that the NN models were able to estimate and correct the scatter contribution to CXRs with an error &lt;5%, being robust to variations in the simulation setup and improving the contrast in soft tissue. The single-energy model was tested with real CXRs, providing robust estimations of the scatter-corrected CXRs.

The WORLD3 world model, which served as the basis for The Club of Rome report The Limits to Growth (1972), was criticized, among other things, for not being able to simulate social interactions. In order to remedy this shortcoming, a research group led by Karl Deutsch at the Berlin Science Center developed a far more comprehensive model between 1979 and 1988 entitled GLOBUS, which was supposed to be able to include political developments in the calculation. This article aims to explain the hopes that were attached to the creation of a further world model and the means by which attempts were made to assert its results. To this end, three genealogical lines of the model -I. as part of the world modeling community, II. as part of quantitative international relations research, III. as part of Karl Deutsch's cybernetic-political science research- will be presented. The data basis and the functioning of GLOBUS are then described. Finally, section VI is devoted to the research group's efforts to make the model "effective".

Redox-flow batteries are rechargeable batteries that store energy in two liquid electrolytes, separated by a membrane. During charging and discharging, the electrolytes flow through the membrane and undergo chemical reactions that generate or consume electrical energy. These batteries are known for their scalability and long cycle life and are versatile energy storage technologies developed to enhance efficiency and lower costs. Deep Eutectic Solvents (DES) are eco-friendly alternatives to traditional electrolytes, and their properties have been studied to improve the performance of redox-flow batteries. We investigated choline chloride/ethylene glycol (ChlCl/Eg) mixtures with LiPF6 salt at four concentrations through experimental and MD simulations. The thermophysical and transport properties of the mixture, including density, diffusion coefficient, viscosity, and ionic conductivity, were calculated across a temperature range of 298.15–398.5 K. Our findings indicate that an increase in salt concentration leads to a decrease in diffusion coefficients and ionic conductivity, while increasing the viscosity of the deep eutectic solvent. This research provides valuable insights into the behavior of DES mixtures and can aid in the design and optimization of DES-based processes for use in redox-flow batteries.

This paper is a further development of our “Proposal of a new double-nozzle technique for in-gas-jet laser resonance ionization spectroscopy” published in journal Atoms earlier in this year. Here, we propose to equip the proposed double-nozzle technique with the RF-only funnel and RF-buncher placed in the gas-jet chamber at 70 mm distance downstream the double-nozzle exit. It allows for highly effective extraction into vacuum heavy ion beams, produced in two-steps laser resonance ionization in the argon supersonic jet. We explored the operation of this new full version of the double-nozzle technique through detailed gas dynamic and then Monte Carlo trajectory simulations, which results are presented and discussed. In particularly, we have shown by calculations that more than 80% of all nobelium-254 neutral atoms, extracted by argon flow from the gas stopping cell through the double-nozzle into the supersonic jet can be extracted into vacuum in a form of pulsed ion beam having low transverse and longitudinal emittance.s dynamic and Monte Carlo simulations

This study addresses the central question that how can a precise measurement of the gluon Parton Distribution Function (PDF) be attained, thereby enhancing our understanding of the intricate quark-gluon composition within nucleons? Through a dual approach involving Quantum Chromodynamics (QCD) and high-energy particle collisions, the research combines computational tools and experimental techniques, focusing on protons and neutrons. Scattering experiments and advanced detectors are utilized to probe nucleon structure. Theoretical frameworks like QCD equations and the Momentum Sum Rule investigate Parton Distribution Functions at specific momentum fractions and energy scales. The primary goal is to achieve an accurate measurement of the gluon PDF, crucial for unraveling strong force complexities and internal nucleon dynamics. The study's theoretical plots and equations illustrate hypothetical behaviors of gluon distribution, quark distribution, and splitting functions, contributing to a deeper understanding of fundamental particles.

Despite being small and simple structured in comparison to their victims, virus particles have the potential to harm severly and even kill highly developed species such as humans. To face upcoming virus pandemics, detailed quantitative biophysical understanding of intracellular virus replication mechanisms is inevitable. Unveiling the relationship of form and function might allow to determine putative attack points relevant for the systematic development of direct antiviral agents (DAA) and potent vaccines. Biophysical investigations of spatio-temporal dynamics of intracellular virus replication so far are rare. We are developing a framework to allow for fully spatio-temporal resolved virus replication dynamics simulations based on partial differential equations models (PDE) and evaluated with advanced numerical mathematical methods on leading supercomputers. This study presents an advanced highly nonlinear model of the genome replication cycle of a specific RNA virus, the Hepatitis C virus (HCV). The diffusion-reaction model mimics the interplay of the major components of the viral RNA (vRNA) cycle, namely non structural viral proteins (NSP), vRNA and a generic host factor. Technically, we couple surface PDEs (sufPDEs) on the 3D embedded 2D Endoplasmatic Reticulum (ER) manifold with PDEs in the 3D membranous web (MW) and cytosol volume. (The MWs are the replication factories growing on the ER induced by NSPs.) The sufPDE/PDE model is evaluated at realistic reconstructed cell geometries which are based on experimental data. The simulations couple the effects of NSPs which are restricted to the ER surface with effects appearing in the volume. The volume effects include the host factor supply from the cytosol and the MW dynamics. Special emphasis is put to the exchange of components between ER surface, MWs and cytosol volume. As the vRNA spatial properties are not fully understood so far in experiment, the model allows for vRNA both restricted to the ER and moving in the cytosol. The visualization of the simulation resembles a look into some sort of fully 3D resolved “in silico microscopes” to mirror and complement in vitro / in vivo experiments for the intracellular vRNA cycle dynamics. The output data are quantitatively consistent with experimental data and provoke advanced experimental studies to validate the model.

With more and more transportation tunnels have been and will be constructed in loess areas in Northwest China with high earthquake potential, the overall stability of portal section under earthquakes actions and the related aseismic countermeasures attracted the attentions from both the scholars and engineers, especially the tunnels in the upper slope connecting the high bridges crossing rivers or valleys. In order to study the dynamic response characteristics and damage evolution of steep loess slope with a tunnel under the earthquake actions, a large-scale shaking table tests were performed on steep loess slope with a tunnel. Wenchuan-tangyu (WT) wave and El Centro (El) wave records were applied on the model to investigate the displacement response and acceleration response of loess slope with a tunnel under the horizontal (X) and the combined action of horizontal and vertical (X-Z) seismic loads, respectively. In particular, three-dimensional non-contact optical measurement techniques were used to obtain the slope surface displacements. The results showed that the main deformation pattern of the slope was horizontal movement and settlement when the seismic wave input was in the X and X-Z directions, respectively. However, the X direction seismic wave had a greater impact on the deformation of the slope, and the tunnel portal slope was destroyed under the action of a large horizontal seismic acceleration finally. Slope failure ahead of a tunnel could be divided into four stages, i.e. elastic deformation stage, plastic deformation accumulation stage, local failure stage, and overall failure stage. The peak ground displacement of X direction (PGDX) and peak ground displacement of Z direction (PGDZ) of the slope surface increased with the increasing of the input peak ground acceleration (PGA) when the input wave was same waveform and same direction. The existence of the tunnel had a great influence on the PGA and the PGA amplification factor (PGAAF) of the soil mass surrounding it. This was because the seismic waves encounter a tunnel surface with clear differences in the physical properties of the medium during their propagation in the slope, thereby forming a strong reflection and refraction effect, and the amplitude changed significantly. Numerical simulation results were basically consistent with the experimental results.

This paper presents the results of laboratory tests of CFRP (carbon fibre-reinforced polymer) laminates, which allowed the development of numerical material models. The obtained data were used in a further stage to perform numerical simulations of four variants of medical tabletops differing, among other features, in the shape of the cross-section. Maximum deflections and effort in the composite material were analyzed. The final step was to perform a laboratory test for one of the tabletop versions, the results of which confirmed the correctness of the numerical calculations. This work is aimed at both researchers and designers involved in the practical application of fibre-reinforced polymer matrix composites.

The “circular bioeconomy” offers numerous opportunities for the health, cosmetic, and nutrition sectors through the potential reuse of Castanea sativa by-products. This abundant and sustainable resource provides valuable bioactive secondary metabolites with antioxidants and anti-inflammatory properties. The transformation of these by-products into high-value products for human health can contribute to sustainable economic growth and reduce the environmental impact of traditional waste disposal practices, thus creating added value from previously underutilized resources. In the present study, we investigated the antioxidant capacity, phytochemical composition and in vitro antioxidant and anti-inflammatory activity of C. sativa burrs (CSB) aqueous extract. The spectrophotometric study yielded optimal total phenolic content (TPC) values, along with significant antioxidant and anti-radical properties. The utilization of UPLC-MS-MS techniques for phytochemical investigation resulted in the identification of a total of 56 metabolites, providing confirmation of the presence of phenolic compounds in CSB. In addition, CSB significantly downregulated pro-inflammatory mediators in LPS-stimulated RAW 264.7 macrophage cells without significant cell toxicity.

Explosive boiling is a fast phase transition from an ultra-thin liquid film to vapor under an extremely high heat flux, which typically has been studied using molecular dynamics simulation (MDS) method. The present MDS study investigated the explosive boiling of a liquid argon nanofilm over different solid copper surfaces with different nanowall patterns including parallel and cross nanowalls. For each surface, atomic motion trajectories, number of liquid and vapor argon atoms, heat flux, and, mainly, onset time of explosive boiling were investigated. The simulation results indicated that explosive boiling occurs earlier on parallel and cross nanowall surfaces than on an ideally smooth surface, regardless of the topology and configuration of nanowalls. Moreover, the results revealed that by using the cross nanowall surfaces, the onset time of explosive boiling decreased by 0.7–4% compared to the parallel nanowall surfaces. In addition, it was found that the onset time of explosive boiling strongly depends on the potential energy barrier and the movement space between nanowalls for both parallel and cross nanowall surfaces. Furthermore, simulation findings showed that even though increasing the height of cross nanowalls increases heat flux and temperature of the fluid argon domain, it does not necessarily result in a shorter onset time of explosive boiling. These findings demonstrate the capability of cross nanowall surfaces for explosive boiling, thereby could be utilized in future surface design for thermal management applications.

This study explores how the properties of heater materials impact nucleate pool boiling using a comprehensive simulation model. The model integrates well-known heat transfer mechanisms, allowing us to assess the effects of two distinct heater materials. Findings indicate that materials with higher thermal conductivity, such as copper, notably improve refrigeration efficiency in nucle- ate boiling. The study provides insights into the relationship between bubble growth, microlayer recovery beneath a bubble, temperature fluctuations, and heater properties. Comparisons between copper and silicon oxide underscore variations in bubble frequency, attributed to differences in bubble growth time, microlayer recovery time, and material-dependent behavior. The influence of neighboring bubbling sites, especially pronounced in silicon oxide due to its low thermal conductivity and diffusivity, was observed. Temperature variations in such materials became highly visible due to their significant inertia in recovery. Simulation results align well with empirical correlations, confirming the model’s versatility in capturing the intricate phenomena of nucleate pool boiling.

Here we propose a simple way in which one can considerably improve performance of the gas stripper setup at the GSI UNILAC. To do so, it will be enough to replace inside the main GSI stripper chamber the present nozzle and the short windowless storage gas cell (for pulsed gas-jet operation mode) by a simple conical diverging nozzle combined with a gas catcher tube placed on the axis of gas-jet at some distance downstream the nozzle exit. As a result, the background pressure in the main and differentially pumped adjacent vacuum chambers of the gas stripper at the GSI UNILAC will dramatically reduce, and it will make possible to achieve the required optimal thickness of gas targets. The pulsed gas stripper operation is simply realized by implementing a commercially available fast gas valve connected to the nozzle entrance. Moreover, the ion beam pulses repetition rate can be increased and it will allow for the considerably higher average intensity of the ion beams extracted from the GSI UNILAC. Performance of the proposed GSI UNILAC gas stripper modification we explored by means of detailed computer experiments, which give a realistic description of supersonic gas jets flowing out the nozzle into vacuum. Results of these computer experiments have presented and discussed.

Road-embedded inductive power transfer (IPT) systems have the potential to accelerate the electrification of the transportation sector. For these systems to be economically viable however, they need to have a similar durability and lifespan compared to that of asphalt roads. One area that has lacked investigation is thermally induced stresses in a primary IPT pad, which is caused by the increase in temperature of the pad when it is energized and the differing thermal expansion of the materials within. This paper presents an experimental and a finite-element based methodology for investigating the thermal-mechanical behaviour of a ¼-scale double-D pad, which was energized while suspended in air, as well as energized when embedded in pavement. A focus was placed on the measurement and prediction of strains in the magnetic ferrite cores because of their brittleness. Ferrite strains were measured using a combination of resistive strain gauges and non-metallic Fibre Bragg Grating (FBG) sensors. Coupled electromagnetic-thermal-structural simulations were conducted to predict temperature and strains in the system, with temperature-dependent properties obtained through physical testing. At an ambient temperature of 50°C, the temperature in the middle of the copper litz wire coil was predicted to be 100°C in both the suspended and embedded case. There was excellent correlation to experimental results, with a difference of less than 10% for most temperature measurements. When energized, the pad was predicted to experience an upward bow due to its temperature rise, resulting bending strains in the ferrite cores. At an ambient temperature of 50°C, maximum tensile strain in the ferrites of the embedded pad was measured to be 62 microstrain (με), with a root-mean square error that was 18 με across three sensors. The experimental and validated numerical methodology can be applied to full-scale operational IPT pads to analyse and improve their thermal-mechanical performance.

NiO-based nanomaterials have attracted a great deal of interest in view of various applications, that have stimulated the implementation of various synthetic approaches to control their chemico-physical properties as a function of the desired end-use. In this regard, their bottom-up preparation starting from suitable precursors plays an important role, but a molecular level in-sight into their reactivity remains an open challenge. In this study, we focus on the fragmentation of Ni(II) diketonate-diamine adducts, of interest as precursors for Ni(II) oxide systems, by com-bined electrospray ionization mass spectrometry (ESI-MS) with multiple collisional experiments (ESI-MSn) and theoretical calculations. The joint analyses revealed common features in the frag-mentation pattern of the target compounds: i) in the first-fragmentation, all three complexes form analogous base-peak cations by losing a negatively charged diketonate; in these cations, Ni-O and Ni-N interactions are stronger and the Ni positive charge is lower than in the neutral complexes; ii) the tendency of ligand electronic charge to migrate towards Ni further increases in the subsequent fragmentation processes, leading to the formation – in all three cases – of a tetracoordinated Ni environment involving an interesting cation-π intramolecular interaction.

The intensive development of nanodevices acting as two-state systems has motivated the search for nanoscale molecular structures whose long-term conformational dynamics are similar to the dynamics of bistable mechanical systems such as Euler arches and Duffing oscillators. Collective synchrony in bistable dynamics of molecular-sized systems has attracted immense attention as a potential pathway to amplify the output signals of molecular nanodevices. Recently, pyridin-furan oligomers of helical shape that are a few nanometers in size and exhibit bistable dynamics similar to a Duffing oscillator have been identified through molecular dynamics simulations. In this article, we present the case of dynamical synchronization of these bistable systems. We show that two pyridine-furan springs connected by a rigid oligomeric bridge spontaneously synchronize vibrations and stochastic resonance enhances the synchronization effect.

It’s been reported that Mori Folium (MF) and Eucommiae Cortex (EC) exhibit pharmacological effects on the treatment of immunosuppression. However, the mechanism of MF and EC against immunosuppression remains unclear. This study aims to explore the mechanism of action of MF and EC for the treatment of immunosuppression through network pharmacology, molecular docking, molecular dynamics simulations and animal experiments. As a result, 11 critical components, 9 hub targets, and related-signaling pathways of treatment of immunosuppression were obtained based on network pharmacology. The molecular docking suggested that 11 critical components exhibited great binding affinity to 9 hub targets of immunosuppression. The molecular dynamics simulations results showed that (-)-Tabernemontanine-AR, beta-sitosterol-AR and Dehydrodieugenol-HSP90AA1 complexes are stably bound. Additionally, in the animal experiments, the treated group results compared to the control group suggest that MF and EC have a significant effect on the treatment of immunosuppression. Therefore, the MF and EC treatment for immunosuppression may take effects in a multi-component, multi-target, and multi-pathway manner. The results would provide novel insights into the treatment of immunosuppression in humans.

This is the second paper in a cycle investigating the exact solution of loop equations in decaying turbulence. We perform numerical simulations of the Euler ensemble, suggested in the previous work, as a solution to the loop equations. We designed novel algorithms for simulation, which take a small amount of computer RAM so that only the CPU time grows linearly with the size of the system and its statistics. This algorithm allows us to simulate systems with billions of discontinuity points on our fractal curve, dual to the decaying turbulence. For the vorticity correlation function, we obtain \textbf{quantum fractal laws} with regime changes between universal discrete values of indexes. The traditional description of turbulence with fractal or multifractal scaling laws does not apply here. The measured conditional probabilities of fluctuating variables are smooth functions of the logarithm of scale, with statistical errors being negligible at our large number of random samples $T = 167,772,160$ with $N = 200,000,000$ points on a fractal curve. The quantum jumps arise from the analytical distribution of scaling variable $X = \frac{\cot^2(\pi p/q)}{q^2}$ where $\frac{p}{q}$ is a random fraction. This distribution is related to the totient summatory function and is a discontinuous function of $X$. In particular, the energy spectrum is a devil's staircase with tilted uneven steps with slopes between $-1$ and $-2.03$. The logarithmic derivative of energy decay $n(t)$ as a function of time is jumping down the stairs of universal levels between $1.50$ and $1.53$. The quantitative verification of this quantization would require more precise experimental data.

Numerical simulations of standard situations in the transition region from gas kinetics to fluid dynamics at small Mach numbers indicate a clear dependence of the simulation results on the underlying kinetic model (here: nonlinear and linearized Boltzmann collision operator vs. BGK relaxation model). We develop an improved mathematical framework (trace theory) to explain these differences. In particular we reveal certain deficiencies for the classical BKG system as well as for the standard Navier Stokes approach.

Soccer is the leading cause of all sports-related ocular injuries in Europe and Israel and leads to blindness at a disproportionately high rate, especially among children (Thompson et al., 2019). With soccer being the most popular sport in the world, it is surprising the only solution to ocular injuries are sports glasses which can cause direct damage to the eye and impair peripheral vision by 15%, calling for an alternative (Smith & Jones, 2020). This work, based on an imported facial model, focuses on both the qualitative and quantitative aspects of building a personalized, low-cost (through optimizing material needed), superior apparatus to conventional sports glasses. The quantitative side examines a modified and model-validated (through a SRS of thirty unique extrapolated points) multivariate linear regression equation, based on horizontal and vertical rotation angles (n=60) trained with residual and computer simulation data, that can accurately extrapolate and quantify ocular impact from all horizontal and vertical rotation angles and a modified Hertzian Contact Stress Equation to determine the thickness of the apparatus using the elasticity modulus, impact force, and geometrical facial and soccer-ball features. The qualitative side examines where firstly, ocular impact is most prevalent, and secondly, where most impact is seen from rotating the ball horizontally and vertically through analysis of Pearson’s Correlation Coefficient at the supraorbital, medial canthus, infraorbital, and lateral canthus regions from both regression equations as well as a cost-benefit analysis for comparison with conventional sports glasses. The findings discovered in this work lay the groundwork for future research to build a customized low-cost ocular injury prevention device which can simultaneously ensure complete ocular safety while enhancing athletic performance for over 250,000,000 players (Johnson & Garcia, 2022).

The ability to simulate realistically the electronic structure of superconducting materials is important to understand and predict various properties emerging in both the superconducting topological and spintronics realms. We introduce a tight-binding implementation of the Bogoliubov-de Gennes method, parameterized from density functional theory, which we utilize to explore the bulk and thin films of Nb, known to host a significant superconducting gap. The latter is useful for various applications such as the exploration of trivial and topological in-gap states. Here, we focus on the simulations aspects of superconductivity and study the impact of temperature, Cooper-pair coupling and dimensionality on the size of the superconducting order parameter.

The target area of the present study is the entrance to the Sulina channel in the Black Sea, the zero-kilometer of the Danube River. This represents the southern gate of the seventh Pan-European transport corridor and is subjected to high navigation traffic. The coastal environment at the Danube’s mouth is very often subjected to strong environmental conditions inducing high risks for navigation hazards. From this perspective, the objective of the present work is to provide a more comprehensive picture concerning the past and future expected dynamics of the environmental matrix in this area, including especially wind and wave conditions. An analysis of some in situ measurements performed at the zero kilometer of the Danube is first carried out for the 15 years 2009-2023. A second analysis is based on data provided by regional climate wind models. Two 30-year periods are considered, the recent past (1976-2005), when also comparisons with ERA5 reanalysis data were performed, and the near future (2041-2070), when two different models and three climate scenarios were considered. Finally, using as a forcing factor each of the wind fields before analyzed, simulations with a spectral wave model were carried out and the nearshore wave conditions were evaluated. The results show that both extreme wind and wave conditions are expected to be slightly enhanced in the future. Strong wind fields are characteristic in this area, with wind gusts exceeding on average with more than 70% the maximum hourly averaged wind speed. As regards the waves, due to the complex nearshore phenomena, considerable enhancements in terms of significant wave heights are induced. Furthermore, there is also a high risk of rogue wave’s occurrence.

EV transmissions operate at high speeds, upto 30,000 rpm. High speed operation puts higher demands on bearings, seals, and gears. Bearings in EV transmissions are prone to electrically induced bearing damage and may exhibit signs of pitting and fluting. Surface-initiated rolling contact fatigue is another common problem gaining increased attention lately. Most EV transmissions require a coupling between an oil-lubricated gearbox to an electrical motor that runs with minimal lubrication at very high rpm. High mechanical and thermal stresses the seals are exposed to under starved lubrication conditions have a detrimental impact on their service life. Hence, proper lubrication is critical. In general, EV transmission fluids call for a somewhat different spectrum of properties compared to conventional ATF. Gear tribology simulations open new ways to the design and optimization of lubrication for EV transmissions. Additionally, such simulations can also provide valuable insights into the effects of different oil properties on cooling and lubrication efficiencies, thereby helping in matching the lubricant and hardware characteristics for optimal performance. In the present communication, we demonstrate the effects of different lubricants and surface finishing technologies on the tribology of high-speed gears using tribological tests and advanced thermal elastohydrodynamic (TEHD) simulations. Important roles of lubricity additives and surface finish optimization are highlighted in conjunction with a move towards ultralow viscosity EV transmission fluids.

The Active Distribution Networks (ADNs) are Multi-Input Multi-Output (MIMO) systems with coupled dynamics which cause interactions among the control loops of the Distributed Energy Resources (DERs). This undesired effect lead to performance degradation in the voltage control. To mitigate the effects of these unavoidable coupling, the present paper proposes a systematic design procedure based on the analysis of the interaction's sources. In details, each DER is equipped with a double loop PI to control the active and reactive powers output by the Voltage Source Converter (VSC) which connects the DER to the network's node. Furthermore, to guarantee Ancillary Services (ASs), the two loops are coupled by a simple mechanism of cooperation of the active power to voltage regulation realized by a filtered droop law. To achieve voltage regulation with reduced loop interactions, the PI parameters and the filter's pulse are designed according to a two sequential steps procedure based on the (Internal Model Control) IMC technique. Simulation studies are finally presented to demonstrate that the proposed design method achieves both reduction of the loop interaction and robust voltage control in presence of model parameter uncertainty in the MIMO model.

During the thinning process, in the semiconductor industry, residual stress from thin films can cause severe warpage in wafers, which can compromise their processability and packaging. This warpage can lead to bifurcation or buckling, making it important to understand this phenomenon for the manufacturing of large semiconductor wafers. We conducted a finite element analysis of the thinning process using ANSYS mechanical enterprise 2023/R2 to investigate the asymmetric curvatures resulting from bifurcation in a standard 300 mm Si (001) wafer. We induced an asymmetry in the system by applying a slight force on a point of the circumferential region perpendicularly to the substrate. We also simulated the compressive stress from the damaged layer formed during the thinning process and considered its influence on warpage and bifurcation in both linear and non-linear cases. We also included the influence of Earth's gravity induced deflection (GID) and investigated the influence of the compressive stress damaged layer on the grinding process of the whole wafer by adding a metal front layer to the ground back damaged wafer.

As a widely used plastic, the aging and degradation of polyethylene (PE) are inevitable problems, whether the goal is to prolong the life of PE products or address the issue of white pollution. Molecular simulation is a vital scientific tool in elucidating the mechanisms and processes of chemical reactions. To obtain the distribution and evolution process of PE's thermal oxidation products, this work employs the self-consistent charge density functional tight binding (SCC-DFTB) method to perform molecular simulations of the thermal oxidation of PE with different crystallinity and branched structures. We discovered that crystallinity does not affect the thermal oxidation mechanism of PE, but higher crystallinity makes PE more susceptible to cross-linking and carbon chain growth, reducing the degree of PE carbon chain breakage. The branched structure of PE results in differences in pore size between the carbon chains, with larger pores leading to a concentrated distribution of O2 and free radicals subsequently formed. The breakdown of PE is slowed down when free radicals are localized in low-density regions of the carbon chain. The specifics and mechanism of PE's thermal oxidation are clearly revealed in this paper, which is essential for understanding the process in-depth and for the development of anti-aging PE products.

Scaling up the production of power devices involves, in the semiconductor industry, the use of large semiconductor 8” and 12” wafers of Si or SiC. Their use implicates a successful an effective monitoring and control of wafer warpage, as the geometrical size of the substrate increases, as well as a command control on the degeneration of non-linear warpage into critical phenomena known as bifurcation or buckling.To mitigate the warpage, the use of taiko wafers, which consists of wafers having a thicker region on the rim region of the wafer, has been generally adopted in the production lines. In a previous work [1] we investigated the warpage of taiko wafers by introducing the concept of equivalent thickness, in the linear approximation, for the case of a front side metalized taiko wafer. However, as the thickness of the central semiconductor substrate region decreases the possibility that also the taiko wafer bifurcates emerges. For this reason, in this work we have investigated the occurrence of bifurcation or buckling in a taiko wafer. In particular, we implemented a finite element analysis method by using ANSYS Mechanical Enterprise 2023/R2 to investigate the phenomenon of bifurcation in a taiko wafer. The investigated system consisted of a 200 mm Si (001) front side metalized (FSM) taiko wafer, having a substrate thickness ranging from 100 µm to 400 µm, with a step height fixed to 450 µm. The FSM layer consisted of an Al layer of 4.5 µm thin. The system was subjected to a thermal load such that, getting cooled from a nominal temperature T to 25°C, the metal layer can develop a residual stress. To investigate the bifurcation, an asymmetry was induced in the system by applying a slight force on a point of the circumferential region perpendicularly to the substrate. The temperature investigated ranged from 30 °C to 170 °C. From this investigation, it results that also the bifurcation is mitigated by the taiko structure. Indeed, the bifurcation emerges at higher values of the stresses with respect to the case of flat wafers having the same size and thickness of the substrate. Moreover, the concept of equivalent thickness needs to be reformulated by taking into account of the bifurcation phenomenon. Indeed, from the warpage at the bifurcation point of the taiko wafer, we can determine an overall equivalent thickness of the taiko wafer.

Abstract: Although experimental attempts to measure a single molecule/particle at room temperature or under physiological conditions without immobilization, for example on a surface, or without hydrodynamic flow have so far failed, this failure has given impetus to the underlying theory of Brownian motion towards its stochastic due to diffusion. Quantifying the thermodynamic jitter of molecules/particles inspires many and forms the theoretical basis of single-molecule/single-particle biophysics and biochemistry. For the first time, our simulation results for a live cell (cytoplasm) show that the tracks of individual single molecules are localized in Brownian motion, while there is fanning out in fractal diffusion (anomalous diffusion).

In numerical simulations, achieving high accuracy without significantly increasing computational costs is often challenging. To address this, this paper presents an improved finite volume weighted essentially non-oscillatory (WENO) scheme tailored for applicability in computational fluid dynamics (CFD) and implemented in the flow solver NUAA-Turbo for simulating turbomachinery flows using both RANS and RANS/LES coupling. Firstly, the new WENO scheme is validated against classic numerical test cases to assess its stability and reliability in handling discontinuities, the Double problem, and Raleigh-Taylor (RT) instability issues. Compared to the original format, this enhanced finite volume WENO scheme demonstrates superior stability near discontinuities and resolves flow features with the same grid resolution more effectively. Next, for engineering applications related to turbomachinery, such as compressor and turbine characteristics, computations are performed using RANS, and the results obtained using WENO-ZQ3 and WENO-JS3 are compared. Finally, the new fifth-order WENO scheme is applied to RANS/LES coupled simulations of turbine wakes and film cooling. The results show that the enhanced finite volume WENO scheme offers improved stability and accuracy in engineering applications, allowing for high-precision calculations with fewer grid points to capture more detailed flow physics, thereby reducing computational costs in aerodynamic applications.

This study presents a detailed computational investigation aimed at identifying and evaluating potential small organic molecular scaffolds as inhibitors targeting the Pks13 protein, a critical enzyme in tuberculosis (TB) drug discovery. Our approach integrates multiple computational techniques, including quantitative structure-activity relationship (QSAR) modelling, compound library generation, molecular docking, biological activity prediction, re-evaluation of screened compounds, molecular dynamics (MD) analysis, and binding free energy estimation using the MM-GBSA approach. We developed a robust QSAR model using multiple linear regression (MLR) techniques, specifically tailored to predict the minimum inhibitory concentration (MIC) values of potential anti-TB agents. This model demonstrated excellent predictive performance, validated through rigorous internal and external validation procedures. Through molecular docking simulations, we identified five promising inhibitors Ethyl (R,Z)-2-(2-((2-chlorobenzyl) oxy)benzylidene)-5-(4-chlorophenyl)-7-methyl-3-oxo-2,3-dihydro-5H-thiazolo [3,2-a] pyrimidine-6-carboxylate (PKD1), (7R,9aR)-7-(2-hydroxyphenyl)-4-(2-methoxyphenyl)-3-methyl-7,8,9,9a-tetrahydroisoxazolo[5,4-b]quinolin-5(6H)-one (PKD2), (7-(4-methoxy phenyl)-2-methyl-3-phenylpyrazolo[1,5-a]pyrimidin-5-yl)(4-(3-(trifluoromethyl)phenyl) piperazin-1-yl)methanone (PKD3), (8S,10S)-10-(((2R,4S,5S,6S)-4-amino-5-hydroxy-6-methyl tetrahydro-2H-pyran-2-yl)oxy)-6,8,11-trihydroxy-8-(2-hydroxyacetyl)-1-methoxy-7,8,9,10-tetra-hydrotetracene-5,12-dione (PKD4), 3-(3,4-dimethylphenyl)-5-((2-(4-fluorophenyl)-2-oxoethyl) thio)-6-phenyl-2-thioxo-2,3,5,7a-tetrahydrothiazolo[4,5-d]pyrimidin-7(6H)-one (PKD5)with high binding affinities, prioritizing them based on their binding energies. These selected compounds were further assessed for their biological activity predictions, guiding the selection of candidates for experimental validation. Subsequent re-evaluation using absolute binding free energy estimation and MD simulations provided insights into the stability and dynamics of the protein-ligand complexes over time. Our findings highlighted the potential of identified compounds as stable binders within the Pks13-TE domain binding pocket, underscoring their viability as drug candidates. Additionally, binding free energy analysis using MM-GBSA reaffirmed the strong affinity of the proposed compounds towards Pks13. Our integrated computational approach offers a systematic and detailed framework for the identification and characterization of potential Pks13 inhibitors with specific relevance to TB drug discovery.

Abstract: Development of the fast neutron radiography with higher penetration capability in Non-Destructive Testing (NDT) techniques is rapidly. The detection efficiency and the imaging spatial resolution are the main problem of the radiography detector for many fast neutron imaging systems. In this paper, a detector composed of pixelated EJ200 scintillator array，an 16 × 16 silicon-photomultipliers (SiPM) array, and a capacitive multiplexing network readout electronics is designed. Using Monte-Carlo simulations，the main parameters of the detector was optimization. Then the detector prototype was fabricated and tested at a 14 MeV D-T neutron source. The preliminary test results showed that the prototype has spatial resolution of 1.26 mm. Using pixelated scintillator structure，the conflict between spatial resolution and detect efficiency could improved. Moreover, SiPMs offer a flexibility for the expansion of application field of the imaging system due to their excellent photon detection performance, relatively low price and joint possibility for large area.

This study presents the complexity and sensitivity of chaotic system dynamics in the case of the double pendulum. It applied detailed numerical analyses of the double pendulum in multiple computing platforms in order to demonstrate the complexity in behavior of the system of double pendulums. The equations of motion were derived from the Euler-Lagrange formalism, in order to capture the system's dynamics, which is coupled nonlinearly. These were solved numerically using the efficient Runge-Kutta-Fehlberg method, implemented in Python, R, GNU Octave, and Julia, while runtimes and memory usage were extensively benchmarked across these environments. Time series analyses, including the calculation of Shannon entropy and the Kolmogorov-Smirnov test, quantified the system's unpredictability and sensitivity to infinitesimal perturbations of the initial conditions. Phase space diagrams illustrated the intricate trajectories and strange attractors, as further confirmation of the chaotic nature of the double pendulum. All the findings have a clear indication of the importance of accurate measurements of the initial condition in a chaotic system, contributing to an increased understanding of nonlinear dynamics. Future research directions are faster simulations using Numba and GPU computing, stochastic effects, chaotic synchronization, and applications in climate modeling. This work will be useful for understanding chaos theory and efficient computational approaches in complex systems of dynamical nature.