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This study aimed to design and fabricate planar constricted–expanded structures that are integrated into paper-based channels in order to enhance their chaotic advection and improve their mixing performance. Chromatography papers were used to print paper-based microfluidics using a solid-wax printer. Three different constricted–expanded structures—i.e., zigzag, crossed, and curved channels—were designed in order to evaluate their mixing performance in comparison with that of straight channels. A numerical simulation was performed in order to investigate the mixing mechanism, and to examine the ways in which the planar constricted–expanded structures affected the flow patterns. The experimental and numerical results indicated that the proposed structures can successfully mix confluents. The experimental results revealed that the mixing indices (σ) rose from the initial 20.1% (unmixed) to 34.5%, 84.3%, 87.3%, and 92.4% for the straight, zigzag, curved, and cross-shaped channels, respectively. In addition, the numerical calculations showed a reasonable agreement with the experimental results, with a variation in the range of 1.0–11.0%. In future, we hope that the proposed passive paper-based mixers will be a crucial component in the application of paper-based microfluidic devices.

The heterocharge accumulated in the oil‐paper insulation system of the converter transformer will enhance the local electric field and cause insulation deterioration. Numerical simulation is an effective method to analyze heterocharge. Currently, the numerical simulation of heterocharge is mainly based on the bipolar charge transport (BCT) model and the impurity ion transport (IIT) model. However, the effects of temperature, conductivity, and thickness of oil‐impregnated paper on charge transport have not been considered in these models. In view of this, a modified charge transport (MCT) model by introducing the Maxwell–Wagner model and heat conduction equation is proposed in this paper based on the BCT model and IIT model. Then, the influence of multi‐factors (temperature gradient, moisture content, and oil‐impregnated paper thickness) on heterocharge accumulation is investigated by using the MCT model. The simulation results obtained by the MCT model are more consistent with the experimental results than the BCT model, which proves the accuracy and superiority of the MCT model. Moreover, the increase in temperature gradient, moisture content, and oil‐impregnated paper thickness will enlarge the ion dissociation rate, conductivity, and trap density, and thus promote the generation of heterocharge. In that respect, the MCT model is expected to optimize the insulation design and provide a reference for space charge dynamic simulation.

The specific energy absorption of a thin-walled tube can be improved by filler. This study examined the potential use of a cheaper biomass filler, paper scraps, to enhance the energy absorption characteristics of the structure while reducing its cost, compared to that with a traditional filler such as foam material. Quasi-static crushing tests and finite element simulations were performed by using the explicit non-linear finite element software LS-DYNA to determine the improvements to the mean crushing force and specific energy absorption of the steel tube when filled with different densities of paper scraps. The mean crushing force and specific energy absorption of the empty tube, the paper scraps, and thin-walled tube filled with paper scraps were determined, and corresponding numerical simulations were performed. The simulation and test results showed that the impact performance of tube filled with paper scraps was greatly improved when paper scraps density was 0.35 g/cm3. By optimizing paper scraps filling structure, a new structure that could further enhance the specific energy absorption was obtained. The optimal scheme could increase the specific energy absorption of Q345 steel tube by 11.35%.

Cognitive modeling involves the creation of computer simulations that emulate the internal processes of the mind. This set of papers are the five best representatives of the papers presented at the 17th International Conference on Cognitive Modeling, ICCM 2019. While they represent a diversity of techniques and tasks, they all also share a striking similarity: They make strong statements about the importance of accounting for individual differences.

The governing international standard for the development of prosthetic heart valves is International Organization for Standardization (ISO) 5840. This standard requires the assessment of the thrombus potential of transcatheter heart valve substitutes using an integrated thrombus evaluation. Besides experimental flow field assessment and ex vivo flow testing, computational fluid dynamics is a critical component of this integrated approach. This position paper is intended to provide and discuss best practices for the setup of a computational model, numerical solving, post-processing, data evaluation and reporting, as it relates to transcatheter heart valve substitutes. This paper is not intended to be a review of current computational technology; instead, it represents the position of the ISO working group consisting of experts from academia and industry with regards to considerations for computational fluid dynamic assessment of transcatheter heart valve substitutes.

SciPy is an open source scientific computing library for the Python programming language. SciPy 1.0 was released in late 2017, about 16 years after the original version 0.1 release. SciPy has become a de facto standard for leveraging scientific algorithms in the Python programming language, with more than 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories, and millions of downloads per year. This includes usage of SciPy in almost half of all machine learning projects on GitHub, and usage by high profile projects including LIGO gravitational wave analysis and creation of the first-ever image of a black hole (M87). The library includes functionality spanning clustering, Fourier transforms, integration, interpolation, file I/O, linear algebra, image processing, orthogonal distance regression, minimization algorithms, signal processing, sparse matrix handling, computational geometry, and statistics. In this work, we provide an overview of the capabilities and development practices of the SciPy library and highlight some recent technical developments., Comment: Article source data is available here: https://github.com/scipy/scipy-articles

Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2020, Director: Anna Puig Puig, [en] This project aims to create a multi-platform application that allows the user to emulate the folding of a paper into an origami figure in a virtual environment. This application would start to solve the very time-consuming task in the origami world of diagramming, creating instructions for a specific model. In this proposal, a list of possible simple folds has been selected and each has been mathematically described with its constraints and requirements. A data structure that adapts to the complex origami folding process has been designed and a Unity application has been coded to allow the user to visualize and intuitively interact with it in a simple and clean graphic interface.

Papirnica Količevo Karton d.o.o. želi povečati svojo zmogljivost delovanja papirniških strojev. Stroji in strojni deli bodo zato posledično veliko bolj obremenjeni pod novimi pogoji delovanja. V diplomskem delu smo prikazali nosilnost valjev papirniškega stroja pod novimi obremenitvami in opisali tehnologije izdelave papirja, ki jih uporabljajo v papirnici Količevo. S pomočjo računalniškega programa Solidworks smo naredili geometrijske modele po načrtih, ki jih je posredovalo podjetje. Simulacije valjev smo izdelali pod novimi obremenitvami, ki jih je posredoval naročnik. Simulacije valjev so narejene s pomočjo programske opreme Abaqus in so izdelane po metodi končnih elementov (MKE). Naredili smo tudi analitični preračun valja. Na koncu je prikazana še primerjava rezultatov, podani pa so tudi faktorji varnosti za posamezen valj papirniškega stroja. Paper Mill Količevo Karton d.o.o. would like to increase the production capacity of their paper machines. The machines and their components will be experiencing more load with these new conditions. In this diploma we showed the paper machine rollers' capacity with new load and described the technologies which are used for paper making in the paper mill Količevo. With help of the application Solidworks we made geometric models in accordance with the plans we acquired at the company. The simulation of rollers was done with new load. The roller simulation were carried out with the finite element method, with help of the Abaqus application. We also did an analytical conversion of the roller. At the end we presented the comparison of results. We also presented safety factors for individual paper machine rollers.

Over the last years, more stringent safety requirements for an increasing number of chemicals across many regulatory fields (e.g. industrial chemicals, pharmaceuticals, food, cosmetics,...) have triggered the need for an efficient screening strategy to prioritize the substances of highest Concern. In this context, alternative methods such as in silica (i.e. computational) techniques gain more and more importance. In the current study, a new prioritization strategy for identifying potentially mutagenic substances was developed based on the combination of multiple (quantitative) structure-activity relationship ((Q)SAR) tools. Non-evaluated substances used in printed paper and board food contact materials (FCM) were selected for a case study. By applying our strategy, 106 out of the 1723 substances were assigned 'high priority' as they were predicted mutagenic by 4 different (Q)SAR models. Information provided within the models allowed to identify 53 substances for which Ames mutagenicity prediction already has in vitro Ames test results. For further prioritization, additional support could be obtained by applying local i.e. specific models, as demonstrated here for aromatic azo compounds, typically found in printed paper and board FCM. The strategy developed here can easily be applied to other groups of chemicals facing the same need for priority ranking. (C) 2017 Elsevier Ltd. All rights reserved.

International audience; Scenario analysis constitutes a useful approach to synthesize knowledge and derive hypotheses in the case of complex systems that are documented with mainly qualitative or very diverse information. In this article, a framework for scenario analysis is designed and then, applied to global wheat health within a timeframe from today to 2050. Scenario analysis entails the choice of settings, the definition of scenarios of change, and the analysis of outcomes of these scenarios in the chosen settings. Three idealized agrosystems, representing a large fraction of the global diversity of wheat-based agrosystems, are considered, which represent the settings of the analysis. Several components of global changes are considered in their consequences on global wheat health: climate change and climate variability, nitrogen fertilizer use, tillage, crop rotation, pesticide use, and the deployment of host plant resistances. Each idealized agrosystem is associated with a scenario of change that considers first, a production situation and its dynamics, and second, the impacts of the evolving production situation on the evolution of crop health. Crop health is represented by six functional groups of wheat pathogens: the pathogens associated with Fusarium head blight; biotrophic fungi, Septoria-like fungi, necrotrophic fungi, soilborne pathogens, and insect-transmitted viruses. The analysis of scenario outcomes is conducted along a risk-analytical pattern, which involves risk probabilities represented by categorized probability levels of disease epidemics, and risk magnitudes represented by categorized levels of crop losses resulting from these levels of epidemics within each production situation. The results from this scenario analysis suggest an overall increase of risk probabilities and magnitudes in the three idealized agrosystems. Changes in risk probability or magnitude however vary with the agrosystem and the functional groups of pathogens. We discuss the effects of global changes on the six functional groups, in terms of their epidemiology and of the crop losses they cause. Scenario analysis enables qualitative analysis of complex systems, such as plant pathosystems that are evolving in response to global changes, including climate change and technology shifts. It also provides a useful framework for quantitative simulation modeling analysis for plant disease epidemiology.

The present comment refers to some doubtful results included in the above mentioned paper.

This paper proposed a simulation method for the charge transport in single-layer oil-paper insulation. The method of transient upstream finite-element method (FEM) is derived in order to calculate the time variation of charge densities in medium. The numerical simulation of charge transport in the single-layer oil-paper insulation is realized by applying the transient upstream FEM to the transport equations of bipolar charges. With reasonable microparameter, the charge transport in an experimental object is simulated. The simulation results are consistent with the experimental data. A bent model of oil-paper insulation is analyzed to study the charge distribution under the actual condition. This paper provides an exploratory research to the simulation of charge phenomenon in oil-paper, and has guiding significance to the design of oil-paper insulation.

For offshore wind turbines (OWTs) located in relatively shallow water, the design is influenced by the occurrence of breaking waves. The strongly nonlinear properties associated with the wave breaking process result in challenges in modelling their impact loads on the structures. The total impact loads are normally calculated as the sum of a slowly varying quasi-static load and an impulsive slamming load. The quasi-static load is normally calculated using Morison's equation and the slamming load is approximated by the Goda model or the Wienke-Oumeraci model. Given the dynamic properties of OWTs, structural resonances might be excited by the impulsive slamming load. Therefore, there is a clear need to evaluate the response effect excited by the slamming load. In this paper, the response of a vertical pile subjected to a severe breaking wave case is investigated by a combination of data from a large-scale experiment and numerical simulations. The slowly varying quasi-static load obtained in a non-breaking wave packet is modelled using Morison's equation with the wave kinematics obtained from a fully nonlinear potential flow solver OceanWave3D. The governing parameters used in a slamming load model are estimated using the Monte Carlo method and verified by comparing the experimental data with the numerical simulation results. It is found that the slamming coefficient and the curling factor are close to the values found by the Wienke-Oumeraci model, however the impact duration is significantly larger than the values found by the Goda model and the Wienke-Oumeraci model, which is important for the assessment of the dynamic responses of OWTs.

Cooperation is a fundamental behaviour observed in all forms of life. The evolution of cooperation has been widely studied, but almost all theories focused on the cooperating individual and its genes. We suggest a different approach, taking into account the microbes carried by the interacting individuals. Accumulating evidence reveals that microbes can affect their host's well-being and behaviour, yet hosts can evolve mechanisms to resist the manipulations of their microbes. We thus propose that coevolution of microbes with their hosts may favour microbes that induce their host to cooperate. Using computational modelling, we show that microbe-induced cooperation can evolve and be maintained in a wide range of conditions, including when facing hosts' resistance to the microbial effect. We find that host–microbe coevolution leads the population to a rock–paper–scissors dynamics that enables maintenance of cooperation in a polymorphic state. Our results suggest a mechanism for the evolution and maintenance of cooperation that may be relevant to a wide variety of organisms, including cases that are difficult to explain by current theories. This study provides a new perspective on the coevolution of hosts and their microbiome, emphasizing the potential role of microbes in shaping their host's behaviour.

An increasing number of publications include modeling. Often, such studies help us to gain a deeper insight into the phenomena studied and break down barriers between experimental and theoretical communities. However, combining experimental and theoretical work is challenging for authors, reviewers, and readers. To help maximize the usefulness and impact of combined theoretical and experimental research, this Primer describes the purpose, usefulness, and different types of models and addresses the practical aspect of integrated publications by outlining characteristics of good modeling, presentation, and fruitful collaborations.

Charge transport in oil impregnated paper impacts the insulation performance of a transformer. This paper proposes a simulation method for the charge transport in oil impregnated paper insulation. The transient upstream finite element method (FEM) is applied to the transport equations of bipolar charges for establishing a numerical simulation model of charge transport in oil impregnated paper insulation. The method is validated by experimental results. The charge transport and electric field distribution in single-layer oil impregnated paper insulation under different temperature gradients is simulated. The trends of the simulation results are seen to agree with the corresponding experimental results. This paper conducts exploratory research into the simulation of charge transportation phenomenon in oil impregnated paper, and is of importance to the design of oil impregnated paper insulation.

The value of in silico methods in drug development and evaluation has been demonstrated repeatedly and convincingly. While their benefits are now unanimously recognized, international standards for their evaluation, accepted by all stakeholders involved, are still to be established. In this white paper, we propose a risk-informed evaluation framework for mechanistic model credibility evaluation. To properly frame the proposed verification and validation activities, concepts such as context of use, regulatory impact and risk-based analysis are discussed. To ensure common understanding between all stakeholders, an overview is provided of relevant in silico terminology used throughout this paper. To illustrate the feasibility of the proposed approach, we have applied it to three real case examples in the context of drug development, using a credibility matrix currently being tested as a quick-start tool by regulators. Altogether, this white paper provides a practical approach to model evaluation, applicable in both scientific and regulatory evaluation contexts. ispartof: CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY vol:10 issue:8 pages:804-825 ispartof: location:United States status: published

This study employs simulated electronic paper to investigate critical issues and focuses on improving legibility of display and reducing users' visual fatigue. Three critical factors--choice of surface treatment, ambient illumination, and bending curvature--are evaluated through the method of a letter-search task. The results show that subjects performed better on legibility and felt less visual fatigue with an anti-glare treatment. Choosing the better anti-glare treatment instead of the anti-reflection series can save significant cost for manufacturers. In addition, ambient lighting of 1500 lux is more appropriate for reading on electronic paper than an environment with extreme illumination (e.g., 8000 lux). The present study also found that curvature had no impact on legibility or visual fatigue. These evaluations of simulated electronic paper may provide manufacturers useful information in fulfilling ergonomic requirements for product design.

Purpose. Mathematical and simulation models are increasingly used to plan for and evaluate health sector responses to disasters, yet no clear consensus exists regarding best practices for the design, conduct, and reporting of such models. The authors examined a large selection of published health sector disaster response models to generate a set of best practice guidelines for such models. Methods . The authors reviewed a spectrum of published disaster response models addressing public health or health care delivery, focusing in particular on the type of disaster and response decisions considered, decision makers targeted, choice of outcomes evaluated, modeling methodology, and reporting format. They developed initial recommendations for best practices for creating and reporting such models and refined these guidelines after soliciting feedback from response modeling experts and from members of the Society for Medical Decision Making. Results . The authors propose 6 recommendations for model construction and reporting, inspired by the most exemplary models: health sector disaster response models should address real-world problems, be designed for maximum usability by response planners, strike the appropriate balance between simplicity and complexity, include appropriate outcomes that extend beyond those considered in traditional cost-effectiveness analyses, and be designed to evaluate the many uncertainties inherent in disaster response. Finally, good model reporting is particularly critical for disaster response models. Conclusions . Quantitative models are critical tools for planning effective health sector responses to disasters. The proposed recommendations can increase the applicability and interpretability of future models, thereby improving strategic, tactical, and operational aspects of preparedness planning and response.

Motivation Microbial communities have been shown to be associated with many complex diseases, such as cancers and cardiovascular diseases. The identification of differentially abundant taxa is clinically important. It can help understand the pathology of complex diseases, and potentially provide preventive and therapeutic strategies. Appropriate differential analyses for microbiome data are challenging due to its unique data characteristics including compositional constraint, excessive zeros and high dimensionality. Most existing approaches either ignore these data characteristics or only account for the compositional constraint by using log-ratio transformations with zero observations replaced by a pseudocount. However, there is no consensus on how to choose a pseudocount. More importantly, ignoring the characteristic of excessive zeros may result in poorly powered analyses and therefore yield misleading findings. Results We develop a novel microbiome-based direction-assisted test for the detection of overall difference in microbial relative abundances between two health conditions, which simultaneously incorporates the characteristics of relative abundance data. The proposed test (i) divides the taxa into two clusters by the directions of mean differences of relative abundances and then combines them at cluster level, in light of the compositional characteristic; and (ii) contains a burden type test, which collapses multiple taxa into a single one to account for excessive zeros. Moreover, the proposed test is an adaptive procedure, which can accommodate high-dimensional settings and yield high power against various alternative hypotheses. We perform extensive simulation studies across a wide range of scenarios to evaluate the proposed test and show its substantial power gain over some existing tests. The superiority of the proposed approach is further demonstrated with real datasets from two microbiome studies. Availability and implementation An R package for MiDAT is available at https://github.com/zhangwei0125/MiDAT. Supplementary information Supplementary data are available at Bioinformatics online.

We consider the constitutive law of paper and its relation to a spatially inhomogeneous, random paper structure, the so-called formation. Under biaxial tensile loading, paper may be taken as an elastic-plastic hardening material, modelled here by a hyperbolic tangent law. The fact that paper is a quasi-two-dimensional solid offers a chance to inspect its formation via a basis-weight distribution (mass per unit area), and then carry out cross-correlations of two planar fields: the formation versus the strain (or stress) field resulting from a fine-mesh finite-element simulation of a sheet of paper subjected to a specified in-plane loading. The simulation requires an assumption of constitutive coefficients as a function of formation, and the higher the resultant cross-correlation, the better the assumed constitutive law. With this methodology we conclude that the higher the basis-weight, the higher the local stiffness and strength of the paper (on millimetre scales) in two very different cases: a Crayola sketch-paper and a paperboard. We next set up a Boolean model of paper formation, where each grain plays the role of a floc of cellulose fibres. First, we employ a computational-mechanics fibre-network model to demonstrate the effects of formation on non-uniform strain fields in the elastic regime. Moving on to the inelastic regime, we treat flocs as continuum ellipses, and, employing the resulting relation between formation and constitutive coefficients, we study scale-dependent homogenization of paper and establish that the representative volume element in the sense of Hill (1963 J. Mech. Phys. Solids 11, 357-372) is approximately reached on scales about 10 times larger than the floc size.

Background: Globally, colorectal cancer (CRC) is one of the most lethal malignant diseases. However, the currently approved therapeutic options for CRC failed to acquire satisfactory treatment efficacy. Tailoring therapeutic strategies for CRC individuals can provide new insights into personalized prediction approaches and thus maximize clinical benefits. Methods: In this study, a multi-step process was used to construct an immune-related genes (IRGs) based signature leveraging the expression profiles and clinical characteristics of CRC from the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database. An integrated immunogenomic analysis was performed to determine the association between IRGs with prognostic significance and cancer genotypes in the tumor immune microenvironment (TIME). Moreover, we performed a comprehensive in silico therapeutics screening to identify agents with subclass-specific efficacy. Results: The established signature was shown to be a promising biomarker for evaluating clinical outcomes in CRC. The immune risk score as calculated by this classifier was significantly correlated with over-riding malignant phenotypes and immunophenotypes. Further analyses demonstrated that CRCs with low immune risk scores achieved better therapeutic benefits from immunotherapy, while AZD4547, Cytochalasin B and S-crizotinib might have potential therapeutic implications in the immune risk score-high CRCs. Conclusions: Overall, this IRGs-based signature not only afforded a useful tool for determining the prognosis and evaluating the TIME features of CRCs, but also shed new light on tailoring CRCs with precise treatment.

To evaluate the long-term performance of bioretention cell (BRC), a study was undertaken to assess the flow distribution and conductivity. Despite initial conductivity of the original medium being the common predictor of hydraulic performance, most of the BRCs are affected by conductivity variations during actual operation. This happen due to the fact that microbial behavior plays an important role in the conductivity variations. This linkage may occur when bacteria as inert colloids transports between particles and biodegrades dissolved pollutants, either promoting or retarding flow distribution and conductivity in BRC. Flow distribution was determined by numerical simulation and tracer test, and the correlation between conductivity and flow distribution was revealed by conductivity experiment coupled with flow distribution analysis. Results revealed a non-uniform flow distribution in BRC, and seepage flow in submerged zone was virtually impossible push flow. Conductivity had an inversely proportional relationship with hydraulic efficiency where hydraulic efficiency reached the highest value (0.297) under a low hydraulic conductivity (0.000107 m/s, approximately K/Kini = 0.79). Primary cause of hydraulic capacity reduction was the initial permeability decrease due to medium structure changes. Results revealed a sharp upward trend followed by a slight decrease, and then, stabilized to a stable infiltration stage. Permeation process of sewage influent was similar to the one of potable water where the permeability reduced to 0.000102 m/s after 450 h and declined continuously. Thus, it is clear that flow distribution and conductivity in bioretention must be estimated more accurately on a microscopic scale.

Graphical abstract This paper aims at studying open channel geometries in a layer-bed-type immobilized enzyme reactor with computer-aided simulations. The main properties of these reactors are their simple channel pattern, simple immobilization procedure, regenerability, and disposability; all these features make these devices one of the simplest yet efficient enzymatic microreactors. The high surface-to-volume ratio of the reactor was achieved using narrow (25–75 μm wide) channels. The simulation demonstrated that curves support the mixing of solutions in the channel even in strong laminar flow conditions; thus, it is worth including several curves in the channel system. In the three different designs of microreactor proposed, the lengths of the channels were identical, but in two reactors, the liquid flow was split to 8 or 32 parallel streams at the inlet of the reactor. Despite their overall higher volumetric flow rate, the split-flow structures are advantageous due to the increased contact time. Saliva samples were used to test the efficiencies of the digestions in the microreactors. Supplementary Information The online version contains supplementary material available at 10.1007/s00216-021-03588-x.

This paper is concerned with the mathematical modeling and simulation of the steady-state operation of an industrial moving bed heterogeneous reactor for the kraft pulping of Eucalyptus globulus. The cooking takes place in a single-vessel hydraulic digester adapted for isothermal cooking (ITC), a further development of the modified continuous cooking (MCC) process. A heterogeneous model is used to take into account the different phases, each with distinct profiles of temperature and concentration of organic (lignin, cellulose and hemicellulose) and inorganic (effective alkali and sulfide) compounds. The numerical solution of the model is based on a non-uniform discretization strategy to cope with special geometric and operational features of the digester. The decrease in bulk porosity caused by the compaction of the bed and the progressive increase in the voidage of chips as a result of chemical reactions are incorporated into the model as well as the resulting implications in the entrapped and free liquor flows. The model presented here can be used in optimization studies and has been validated with data from an industrial mill. http://www.sciencedirect.com/science/article/B6TFK-40GJ2MB-D/1/fd03feb4f6373ea0a583b9ddc3b427ed

In view of the facts in the infection and propagation of COVID-19, a stochastic reaction–diffusion epidemic model is presented to analyse and control this infectious diseases. Stationary distribution and Turing instability of this model are discussed for deriving the sufficient criteria for the persistence and extinction of disease. Furthermore, the amplitude equations are derived by using Taylor series expansion and weakly nonlinear analysis, and selection of Turing patterns for this model can be determined. In addition, the optimal quarantine control problem for reducing control cost is studied, and the differences between the two models are compared. By applying the optimal control theory, the existence and uniqueness of the optimal control and the optimal solution are obtained. Finally, these results are verified and illustrated by numerical simulation.

Background Inaccurate documentation of sampling and infusion times is a potential source of error in personalizing busulfan doses using therapeutic drug monitoring (TDM). Planned times rather than the actual times for sampling and infusion time are often documented. Therefore, this study aimed to evaluate the robustness of a limited sampling TDM of busulfan with regard to inaccurate documentation. Methods A pharmacometric analysis was conducted in NONMEM® 7.4.3 and “R” by performing stochastic simulation and estimation with four, two and one sample(s) per patient on the basis of a one-compartment- (1CMT) and two-compartment (2CMT) population pharmacokinetic model. The dosing regimens consisted of i.v. busulfan (0.8 mg/kg) every 6 h (Q6H) or 3.2 mg/kg every 24 h (Q24H) with a 2 h- and 3 h infusion time, respectively. The relative prediction error (rPE) and relative root-mean-square error (rRmse) were calculated in order to determine the accuracy and precision of the individual AUC estimation. Results A noticeable impact on the estimated AUC based on a 1CMT-model was only observed if uncertain documentation reached ± 30 min (1.60% for Q24H and 2.19% for Q6H). Calculated rPEs and rRmse for Q6H indicate a slightly lower level of accuracy and precision when compared to Q24H. Spread of rPE’s and rRmse for the 2CMT-model were wider and higher compared to estimations based on a 1CMT-model. Conclusions The estimated AUC was not affected substantially by inaccurate documentation of sampling and infusion time. The calculated rPEs and rRmses of estimated AUC indicate robustness and reliability for TDM of busulfan, even in presence of erroneous records.

Purpose Peptide-conjugated phosphorodiamidate morpholino oligomers (PPMOs) have shown promise in treating Duchenne muscular dystrophy (DMD). We evaluated a semi-mechanistic pharmacokinetic (PK) and pharmacodynamic (PD) model to capture the relationship between plasma and muscle tissue exposure/response in mdx mice treated by mouse surrogate PPMO. Methods A single or repeated (every 4 weeks for 20 weeks) intravenous PPMO dose was administered to mdx mice (n = 6/timepoint). A PK/PD model was built to characterize data via sequential modeling. A 2-compartment model was used to describe plasma PK. A simultaneous tissue PK/PD model was subsequently developed: 2-compartment model to describe muscle PK; linked to an indirect response model describing stimulation of synthesis of skipped transcript, which was in turn linked to stimulation of synthesis of dystrophin protein expression. Results Model performance assessment via goodness-of-fit plots, visual predictive checks, and accurate parameter estimation indicated robust fits of plasma PK and muscle PK/PD data. The model estimated a PPMO tissue half-life of 5 days—a useful parameter in determining the longevity of PPMOs in tissue and their limited accumulation after multiple doses. Additionally, the model successfully described dystrophin expression after single dosing and associated protein accumulation after multiple dosing (increasing ~ twofold accumulation from the first to last dose). Conclusions This first PK/PD model of a PPMO in a DMD disease model will help characterize and predict the time course of PK/PD biomarkers in mdx mice. Furthermore, the model framework can be used to develop clinical PK/PD models and can be extended to other exon-skipping therapies and species.

The treatment outcome of a given fractionated radiotherapy scheme is affected by oxygen tension and cell cycle kinetics of the tumor population. Numerous experimental studies have supported the variability of radiosensitivity with cell cycle phase. Oxygen modulates the radiosensitivity through hypoxia-inducible factor (HIF) stabilization and oxygen fixation hypothesis (OFH) mechanism. In this study, an existing mathematical model describing cell cycle kinetics was modified to include the oxygen-dependent G1/S transition rate and radiation inactivation rate. The radiation inactivation rate used was derived from the linear-quadratic (LQ) model with dependence on oxygen enhancement ratio (OER), while the oxygen-dependent correction for the G1/S phase transition was obtained from numerically solving the ODE system of cyclin D-HIF dynamics at different oxygen tensions. The corresponding cell cycle phase fractions of aerated MCF-7 tumor population, and the resulting growth curve obtained from numerically solving the developed mathematical model were found to be comparable to experimental data. Two breast radiotherapy fractionation schemes were investigated using the mathematical model. Results show that hypoxia causes the tumor to be more predominated by the tumor subpopulation in the G1 phase and decrease the fractional contribution of the more radioresistant tumor cells in the S phase. However, the advantage provided by hypoxia in terms of cell cycle phase distribution is largely offset by the radioresistance developed through OFH. The delayed proliferation caused by severe hypoxia slightly improves the radiotherapy efficacy compared to that with mild hypoxia for a high overall treatment duration as demonstrated in the 40-Gy fractionation scheme.

While novel statistical methods quantifying the shared heritability of traits and diseases between ancestral distinct populations have been recently proposed, a thorough evaluation of these approaches under differing circumstances remain elusive. Brown et al.2016 proposed the method Popcorn to estimate the shared heritability, i.e. genetic correlation, using only summary statistics. Here, we evaluate Popcorn under several parameters and circumstances: sample size, number of SNPs, sample size of external reference panel, various population pairs, inappropriate external reference panel, and admixed population involved. Our results determined the minimum sample size of the external reference panel, summary statistics, and number of SNPs required to accurately estimate both the genetic correlation and heritability. Moreover, the number of individuals and SNPs required to produce accurate and stable estimates was directly proportional with heritability in Popcorn. Misrepresentation of the reference panel overestimated the genetic correlation by 20% and heritability by 60%. Lastly, applying Popcorn to homogeneous (EUR) and admixed (ASW) populations underestimated the genetic correlation by 15%. Although statistical approaches estimating the shared heritability between ancestral populations will provide novel etiologic insight, caution is required ensuring results are based on the appropriate sample size, number of SNPs, and the generalizability of the reference panel to the discovery populations.

Osteocytes are vital for regulating bone remodeling by sensing the flow-induced mechanical stimuli applied to their cell processes. In this mechanosensing mechanism, tethering elements (TEs) connecting the osteocyte process with the canalicular wall potentially amplify the strain on the osteocyte processes. The ultrastructure of the osteocyte processes and canaliculi can be visualized at a nanometer scale using high-resolution imaging via ultra-high voltage electron microscopy (UHVEM). Moreover, the irregular shapes of the osteocyte processes and the canaliculi, including the TEs in the canalicular space, should considerably influence the mechanical stimuli applied to the osteocytes. This study aims to characterize the roles of the ultrastructure of osteocyte processes and canaliculi in the mechanism of osteocyte mechanosensing. Thus, we constructed a high-resolution image-based model of an osteocyte process and a canaliculus using UHVEM tomography and investigated the distribution and magnitude of flow-induced local strain on the osteocyte process by performing fluid–structure interaction simulation. The analysis results reveal that local strain concentration in the osteocyte process was induced by a small number of TEs with high tension, which were inclined depending on the irregular shapes of osteocyte processes and canaliculi. Therefore, this study could provide meaningful insights into the effect of ultrastructure of osteocyte processes and canaliculi on the osteocyte mechanosensing mechanism.

The rock-paper-scissors game is a paradigmatic model for biodiversity, with applications ranging from microbial populations to human societies. Research has shown, however, that mobility jeopardizes biodiversity by promoting the formation of spiral waves, especially if there is no conservation law in place for the total number of competing players. Firstly, we show that even if such a conservation law applies, mobility still jeopardizes biodiversity in the spatial rock-paper-scissors game if only a small fraction of links of the square lattice is randomly rewired. Secondly, we show that zealots are very effective in taming the amplitude of oscillations that emerge due to mobility and/or interaction randomness, and this regardless of whether the later is quenched or annealed. While even a tiny fraction of zealots brings significant benefits, at 5\% occupancy zealots practically destroy all oscillations regardless of the intensity of mobility, and regardless of the type and strength of randomness in the interaction structure. Interestingly, by annealed randomness the impact of zealots is qualitatively the same as by mobility, which highlights that fast diffusion does not necessarily destroy the coexistence of species, and that zealotry thus helps to recover the stable mean-field solution. Our results strengthen the important role of zealots in models of cyclic dominance, and they reveal fascinating evolutionary outcomes in structured populations that are a unique consequence of such uncompromising behavior., Comment: 6 two-column pages, 4 figures; accepted for publication in Physical Review E

Computational drug design is increasingly becoming important with new and unforeseen diseases like COVID‐19. In this study, we present a new computational de novo drug design and repurposing method and applied it to find plausible drug candidates for the receptor binding domain (RBD) of SARS‐CoV‐2 (COVID‐19). Our study comprises three steps: atom‐by‐atom generation of new molecules around a receptor, structural similarity mapping to existing approved and investigational drugs, and validation of their binding strengths to the viral spike proteins based on rigorous all‐atom, explicit‐water well‐tempered metadynamics free energy calculations. By choosing the receptor binding domain of the viral spike protein, we showed that some of our new molecules and some of the repurposable drugs have stronger binding to RBD than hACE2. To validate our approach, we also calculated the free energy of hACE2 and RBD, and found it to be in an excellent agreement with experiments. These pool of drugs will allow strategic repurposing against COVID‐19 for a particular prevailing conditions., Schematic diagram of atom‐by‐atom molecule generation, followed by repurposed molecule selection and validation using fre‐energy calculations.

The ecological theory of species interactions rests largely on the competition, interference, and predator–prey models. In this paper, we propose and investigate a three-species predator–prey model to inspect the mutual interference between predators. We analyze boundedness and Kolmogorov conditions for the non-spatial model. The dynamical behavior of the system is analyzed by stability and Hopf bifurcation analysis. The Turing instability criteria for the Spatio-temporal system is estimated. In the numerical simulation, phase portrait with time evolution diagrams shows periodic and chaotic oscillations. Bifurcation diagrams show the very rich and complex dynamical behavior of the non-spatial model. We calculate the Lyapunov exponent to justify the dynamics of the non-spatial model. A variety of patterns like interference, spot, and stripe are observed with special emphasis on Beddington–DeAngelis function response. These complex patterns explore the beauty of the spatio-temporal model and it can be easily related to real-world biological systems.

We construct confidence regions in high dimensions by inverting the globaltest statistics, and use them to choose the tuning parameter for penalized regression. The selected model corresponds to the point in the confidence region of the parameters that minimizes the penalty, making it the least complex model that still has acceptable fit according to the test that defines the confidence region. As the globaltest is particularly powerful in the presence of many weak predictors, it connects well to ridge regression, and we thus focus on ridge penalties in this paper. The confidence region method is quick to calculate, intuitive, and gives decent predictive potential. As a tuning parameter selection method it may even outperform classical methods such as cross‐validation in terms of mean squared error of prediction, especially when the signal is weak. We illustrate the method for linear models in simulation study and for Cox models in real gene expression data of breast cancer samples.

We propose a mathematical model based on probability theory to optimize COVID‐19 testing by a multistep batch testing approach with variable batch sizes. This model and simulation tool dramatically increase the efficiency and efficacy of the tests in a large population at a low cost, particularly when the infection rate is low. The proposed method combines statistical modeling with numerical methods to solve nonlinear equations and obtain optimal batch sizes at each step of tests, with the flexibility to incorporate geographic and demographic information. In theory, this method substantially improves the false positive rate and positive predictive value as well. We also conducted a Monte Carlo simulation to verify this theory. Our simulation results show that our method significantly reduces the false negative rate. More accurate assessment can be made if the dilution effect or other practical factors are taken into consideration. The proposed method will be particularly useful for the early detection of infectious diseases and prevention of future pandemics. The proposed work will have broader impacts on medical testing for contagious diseases in general.

This paper aims to investigate detailed mechanical interactions between the pulmonary haemodynamics and left heart function in pathophysiological situations (e.g. atrial fibrillation and acute mitral regurgitation). This is achieved by developing a complex computational framework for a coupled pulmonary circulation, left atrium and mitral valve model. The left atrium and mitral valve are modelled with physiologically realistic three-dimensional geometries, fibre-reinforced hyperelastic materials and fluid–structure interaction, and the pulmonary vessels are modelled as one-dimensional network ended with structured trees, with specified vessel geometries and wall material properties. This new coupled model reveals some interesting results which could be of diagnostic values. For example, the wave propagation through the pulmonary vasculature can lead to different arrival times for the second systolic flow wave (S2 wave) among the pulmonary veins, forming vortex rings inside the left atrium. In the case of acute mitral regurgitation, the left atrium experiences an increased energy dissipation and pressure elevation. The pulmonary veins can experience increased wave intensities, reversal flow during systole and increased early-diastolic flow wave (D wave), which in turn causes an additional flow wave across the mitral valve (L wave), as well as a reversal flow at the left atrial appendage orifice. In the case of atrial fibrillation, we show that the loss of active contraction is associated with a slower flow inside the left atrial appendage and disappearances of the late-diastole atrial reversal wave (AR wave) and the first systolic wave (S1 wave) in pulmonary veins. The haemodynamic changes along the pulmonary vessel trees on different scales from microscopic vessels to the main pulmonary artery can all be captured in this model. The work promises a potential in quantifying disease progression and medical treatments of various pulmonary diseases such as the pulmonary hypertension due to a left heart dysfunction.

This study examined whether pilots operating a flight simulator completed digital or paper flight checklists more accurately after receiving postflight graphic and verbal feedback. The dependent variable was the number of checklist items completed correctly per flight. Following treatment, checklist completion with paper and digital checklists increased from 38% and 39%, respectively, to nearly 100% and remained close to 100% after feedback and praise for improvement were withdrawn. Performance was maintained at or near 100% during follow-up probes.

Lateral flow immunoassays (LFIA) are ideal biosensors to detect proteins, but their lack of sensitivity hinders their extensive use. We report a strategy that yields up to an 8-fold improvement in the sensitivity of a gold nanoparticles-based LFIA by changing the sizes of the pads. Theoretical flow simulations of the developed LFIA architectures are in accordance with the experimental results. © The Royal Society of Chemistry 2013., We acknowledge MEC (Madrid) for the project MAT2011-25870, the EU’s support under FP7 contract number 246513 ‘‘NADINE’’ and the NATO Science for Peace and Security Programme’s support under the project SfP 983807.

In this paper, we discuss issues in verification, validation, and uncertainty prediction in computational fluid dynamics (CFD). Mesh adaptation is used to perform the systematic grid refinement studies required for code and simulation verification. We demonstrate the method of manufactured solutions (MMS) for code verification. Examples of successful and failed validation show that reliable prediction can only occur with an appropriate mathematical model of physics along with accurate numerical solution of the differential equations. The paper emphasizes good CFD practices to achieve systematic verification and put validation studies on solid grounds. Finally, the sensitivity equation method (SEM) is used to cascade input data uncertainty through the CFD code for estimating the uncertainty of the flow response.

Contains fulltext : 178217.pdf (Publisher’s version ) (Open Access) During the last 10 years the European Medicines Agency (EMA) organized a number of workshops on modeling and simulation, working towards greater integration of modeling and simulation (M&S) in the development and regulatory assessment of medicines. In the 2011 EMA - European Federation of Pharmaceutical Industries and Associations (EFPIA) Workshop on Modelling and Simulation, European regulators agreed to the necessity to build expertise to be able to review M&S data provided by companies in their dossier. This led to the establishment of the EMA Modelling and Simulation Working Group (MSWG). Also, there was agreement reached on the need for harmonization on good M&S practices and for continuing dialog across all parties. The MSWG acknowledges the initiative of the EFPIA Model-Informed Drug Discovery and Development (MID3) group in promoting greater consistency in practice, application, and documentation of M&S and considers the paper is an important contribution towards achieving this objective.

Thoracic endovascular aortic repair (TEVAR) has been accepted as the mainstream treatment for type B aortic dissection, but post-TEVAR biomechanical-related complications are still a major drawback. Unfortunately, the stent-graft (SG) configuration after implantation and biomechanical interactions between the SG and local aorta are usually unknown prior to a TEVAR procedure. The ability to obtain such information via personalised computational simulation would greatly assist clinicians in pre-surgical planning. In this study, a virtual SG deployment simulation framework was developed for the treatment for a complicated aortic dissection case. It incorporates patient-specific anatomical information based on pre-TEVAR CT angiographic images, details of the SG design and the mechanical properties of the stent wire, graft and dissected aorta. Hyperelastic material parameters for the aortic wall were determined based on uniaxial tensile testing performed on aortic tissue samples taken from type B aortic dissection patients. Pre-stress conditions of the aortic wall and the action of blood pressure were also accounted for. The simulated post-TEVAR configuration was compared with follow-up CT scans, demonstrating good agreement with mean deviations of 5.8% in local open area and 4.6 mm in stent strut position. Deployment of the SG increased the maximum principal stress by 24.30 kPa in the narrowed true lumen but reduced the stress by 31.38 kPa in the entry tear region where there was an aneurysmal expansion. Comparisons of simulation results with different levels of model complexity suggested that pre-stress of the aortic wall and blood pressure inside the SG should be included in order to accurately predict the deformation of the deployed SG.

There are several antibody therapeutics in preclinical and clinical development, industry-wide, for the treatment of central nervous system (CNS) disorders. Due to the limited permeability of antibodies across brain barriers, the quantitative understanding of antibody exposure in the CNS is important for the design of antibody drug characteristics and determining appropriate dosing regimens. We have developed a minimal physiologically-based pharmacokinetic (mPBPK) model of the brain for antibody therapeutics, which was reduced from an existing multi-species platform brain PBPK model. All non-brain compartments were combined into a single tissue compartment and cerebral spinal fluid (CSF) compartments were combined into a single CSF compartment. The mPBPK model contains 16 differential equations, compared to 100 in the original PBPK model, and improved simulation speed approximately 11-fold. Area under the curve ratios for minimal versus full PBPK models were close to 1 across species for both brain and plasma compartments, which indicates the reduced model simulations are similar to those of the original model. The minimal model retained detailed physiological processes of the brain while not significantly affecting model predictability, which supports the law of parsimony in the context of balancing model complexity with added predictive power. The minimal model has a variety of applications for supporting the preclinical development of antibody therapeutics and can be expanded to include target information for evaluating target engagement to inform clinical dose selection. Supplementary Information The online version contains supplementary material available at 10.1007/s10928-021-09776-7.

The search for new compounds with activity against Paracoccidioides, etiologic agents of Paracoccidioidomycosis (PCM), is extremely necessary due to the current scenario of the available therapeutic arsenal. Treatment is restricted to three classes of antifungals with side effects. Curcumin is a polyphenol with antifungal effects that is extracted from Curcuma longa. The present work aimed to evaluate the activity of curcumin in different species of Paracoccidioides and to evaluate the potential molecular targets of curcumin using computational strategies. In addition, interactions with classic antifungals used in the treatment of PCM were evaluated. Curcumin inhibits the growth of Paracoccidioides spp. exerting a fungicidal effect. The combination of curcumin with amphotericin B, co-trimoxazole, and itraconazole showed a synergistic or additive interaction. Molecular targets as superoxide dismutase, catalase, and isocitrate lyase were proposed based on in silico approaches. Curcumin affects the fungal plasma membrane and increases the production of reactive oxygen species. Therefore, curcumin is a good alternative for the treatment of PCM. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42770-021-00548-6.

Muscle architecture, which includes parameters like fascicle length, pennation angle, and physiological cross-sectional area, strongly influences skeletal muscles' mechanical properties. During maturation, the muscle architecture has to adapt to a growing organism. This study aimed to develop an architectural model capable of predicting the complete 3D fascicle architecture for primarily unipennate muscles of an arbitrary age, based on fascicle data for an initial age. For model development, we collected novel data on 3D muscle architecture of the rabbit (Oryctolagus cuniculus) M. plantaris of eight animals ranging in age from 29 to 106 days. Experimental results show that plantaris muscle belly length increases by 73%, whereas mean fascicle length and mean pennation angle increases by 39 and 14%, respectively. Those changes were incorporated into the model. In addition to the data collected for M. plantaris the predictions of the model were compared to existing literature data of rabbit M. soleus and M. gastrocnemius medialis. With an error of -1.0 ± 8.6% for relative differences in aponeurosis length, aponeurosis width, muscle height, and muscle mass, the model delivered good results matching interindividual differences. For future studies, the model could be utilized to generate realistic architectural data sets for simulation studies., Deutsche Forschungsgemeinschaft, Projekt DEAL

In this study, a novel reaction-diffusion model for the spread of the new coronavirus (COVID-19) is investigated. The model is a spatial extension of the recent COVID-19 SEIR model with nonlinear incidence rates by taking into account the effects of random movements of individuals from different compartments in their environments. The equilibrium points of the new system are found for both diffusive and non-diffusive models, where a detailed stability analysis is conducted for them. Moreover, the stability regions in the space of parameters are attained for each equilibrium point for both cases of the model and the effects of parameters are explored. A numerical verification for the proposed model using a finite difference-based method is illustrated along with their consistency, stability and proving the positivity of the acquired solutions. The obtained results reveal that the random motion of individuals has significant impact on the observed dynamics and steady-state stability of the spread of the virus which helps in presenting some strategies for the better control of it.

Coronavirus and its spread all over the world have been the most challenging crisis in 2020. Hospitals are categorized among the most vulnerable centers due to their presumably highest traffic of this virus. In this study, centrifugal isolation of coronavirus is successfully deployed for purifying hospitals’ air using air conditioners and ducts, suggesting an efficient setup. Numerical simulations have been used to testify the proposed setup due to the complexities of using experimental investigation such as high cost and clinical hazards of the airborne SARS-CoV-2 in the air. Results show that a 20-cm pipe with an inlet velocity of 4 m/s constitutes the best choice for the separation and purification of air from the virus. The proposed scalable method also efficiently separates larger particles, but it can separate smaller particles too. Numerical results also suggest installing the air purifying system on the floor of the hospitals’ room for maximum efficiency.

We study the effects of ambient air humidity on the dynamics of imbibition in a paper. We observed that a quick increase of ambient air humidity leads to depinning and non-Washburn motion of wetting fronts. Specifically, we found that after depinning the wetting front moves with decreasing velocity v∝ (hp /hD )γ, where hD is the front elevation with respect to its pinned position at lower humidity hp, while γ≅1/3. The spatiotemporal maps of depinned front activity are established. The front motion is controlled by the dynamics of local avalanches directed at 30 to the balk flow direction. Although the roughness of the pinned wetting front is self-affine and the avalanche size distribution displays a power-law asymptotic, the roughness of the moving front becomes multiaffine a few minutes after depinning. © 2013 American Physical Society., This work was supported by the PEMEX under the research grants SENER-CONACYT No. 143927 and No. 116458.

In this work, we developed a robust permutation test for the concordance correlation coefficient (ρ c) for testing the general hypothesis H 0 : ρ c = ρ c(0). The proposed test is based on an appropriately studentized statistic. Theoretically, the test is proven to be asymptotically valid in the general setting when two paired variables are uncorrelated but dependent. This desired property was demonstrated across a range of distributional assumptions and sample sizes in simulation studies, where the test exhibits robust type I error control in all settings tested, even when the sample size is small. We demonstrated the application of this test in two real world examples across cardiac output measurements and endocardiographic imaging.

Purpose To investigate how the simultaneous exposure to gradient and RF fields affects the temperature rise in patients with a metallic hip prosthesis during an MRI session. Methods In silico analysis was performed with an anatomically realistic human model with CoCrMo hip implant in 12 imaging positions. The analysis was performed at 1.5 T and 3 T, considering four clinical sequences: turbo spin-echo, EPI, gradient-echo, and true fast imaging sequence with steady precession. The exposure to gradient and RF fields was evaluated separately and superposed, by adopting an ad hoc computational algorithm. Temperature increase within the body, rather than specific absorption rate, was used as a safety metric. Results With the exception of gradient-echo, all investigated sequences produced temperature increases higher than 1 K after 360 seconds, at least for one body position. In general, RF-induced heating dominates the turbo spin-echo sequence, whereas gradient-induced heating prevails with EPI; the situation with fast imaging sequence with steady precession is more diversified. The RF effects are enhanced when the implant is within the RF coil, whereas the effects of gradient fields are maximized if the prosthesis is outside the imaging region. Cases for which temperature-increase thresholds were exceeded were identified, together with the corresponding amount of tissue mass involved and the exposure time needed to reach these limits. Conclusion The analysis confirms that risky situations may occur when a patient carrying a hip implant undergoes an MRI exam and that, in some cases, the gradient field heating may be significant. In general, exclusion criteria only based on whole-body specific absorption rate may not be sufficient to ensure patients' safety.