Previous Formulations Research Articles

Generalized and efficient wall boundary condition treatment in GPU-accelerated smoothed particle hydrodynamics

This paper presents a generalized and efficient wall boundary treatment in the smoothed particle hydrodynamics (SPH) method for 3-D complex and arbitrary geometries with single- and multi-phase flows to be executed on graphics processing units (GPUs). Using a force balance between the wall and fluid particles with a novel penalty method, a pressure boundary condition is applied on the wall dummy particles which effectively prevents non-physical particle penetration into the wall also in highly violent impacts and multi-phase flows with high density ratios. A new density reinitialization scheme is also presented to enhance the accuracy and robustness. The proposed method is simple in comparison with previous wall boundary formulations on GPUs and enforces no additional memory caching and thus is well suited for massively parallel architecture of GPUs. The method is validated in various test cases involving inviscid violent single- and multi-phase flows, demonstrating very good robustness, accuracy and performance. The new wall boundary treatment is able to improve the high accuracy of its previous version by Adami et al. [1] also in 3-D and multi-phase problems, while it is efficiently executable on GPUs. Therefore, the method can be a reliable solution for the long-lasting wall boundary condition challenge in SPH for a broad range of problems.

Anisotropic Diffusion in Consensus-Based Optimization on the Sphere

In this paper we are concerned with the global minimization of a possibly non-smooth and non-convex objective function constrained on the unit hypersphere by means of a multi-agent derivative-free method. The proposed algorithm falls into the class of the recently introduced Consensus-Based Optimization. In fact, agents move on the sphere driven by a drift towards an instantaneous consensus point, which is computed as a convex combination of agent locations, weighted by the cost function according to Laplaces principle, and it represents an approximation to a global minimizer. The dynamics is further perturbed by an anisotropic random vector field to favor exploration. The main results of this paper are about the proof of convergence of the numerical scheme to global minimizers provided conditions of well-preparation of the initial datum. The proof of convergence combines a mean-field limit result with a novel asymptotic analysis, and classical convergence results of numerical methods for SDE. The main innovation with respect to previous work is the introduction of an anisotropic stochastic term, which allows us to ensure the independence of the parameters of the algorithm from the dimension and to scale the method to work in very high dimension. We present several numerical experiments, which show that the algorithm proposed in the present paper is extremely versatile and outperforms previous formulations with isotropic stochastic noise.

Polyethylene Glycol 3350 (PEG 3350) as a Practical Vehicle for Rapid Reconstitution of PARPi-FL Formulations for Clinical Use.

PARPi-FL is a molecularly specific fluorescent agent that targets poly ADP-ribose polymerase 1, a DNA repair enzyme overexpressed in the nuclei of tumor cells. This imaging agent is being investigated in a clinical trial (NCT03085147) for the detection of oral cancer. The PARPi-FL mouthwash formulation currently being used in the phase I/II clinical trial comprises 1,000nM of PARPi-FL dissolved first in 4.5ml of polyethylene glycol (PEG) 300 and then in 9.5ml of water. This formulation requires a 2-step process that can be cumbersome for routine clinical use. To minimize errors and simplify the formulation process, we have developed a new one-step formulation, which requires only the direct addition of water into a vial containing a mixture of the PARPi-FL and PEG 3350, which is also a powder. In a series of analytical and preclinical studies, we demonstrate that the new formulation of PARPi-FL is stable over 365days, sustains its characteristics, and performs similar to the previous formulation. Moving forward, the new formulation of the PARPi-FL will be used for patients accrued in the phase II clinical trial.

Enhanced formulation for the Guillotine 2D Cutting Knapsack Problem

We advance the state of the art in Mixed-Integer Linear Programming formulations for Guillotine 2D Cutting Problems by (i) adapting a previously-known reduction to our preprocessing phase (plate-size normalization) and by (ii) enhancing a previous formulation (PP-G2KP from Furini et alli) by cutting down its size and symmetries. Our focus is the Guillotine 2D Knapsack Problem with orthogonal and unrestricted cuts, constrained demand, unlimited stages, and no rotation – however, the formulation may be adapted to many related problems. The code is available. Concerning the set of 59 instances used to benchmark the original formulation, the enhanced formulation takes about 4 hours to solve all instances while the original formulation takes 12 hours to solve 53 of them (the other six runs hit a three-hour time limit each). We integrate, to both formulations, a pricing framework proposed for the original formulation; the enhanced formulation keeps a significant advantage in this situation. Finally, in a recently proposed set of 80 harder instances, the enhanced formulation (with and without the pricing framework) found: 22 optimal solutions (5 already known, 17 new); better lower bounds for 25 instances; better upper bounds for 58 instances.

A Consistent Framework for Coupling Basal Friction With Subglacial Hydrology on Hard-Bedded Glaciers.

Below hard‐bedded glaciers, both basal friction and distributed subglacial drainage are thought to be controlled by a network of cavities. Previous coupled hydro‐mechanical models, however, describe cavity‐driven friction and hydraulic transmissivity independently, resulting in a physically inconsistent cavity evolution between the two components of the models. Here, we overcome this issue by describing the hydro‐mechanical system using a common cavity‐evolution description, that governs both transient friction and hydraulic transmissivity. We show that our coupling approach is superior to previous formulations in explaining a unique observation record of glacier sliding speed from the French Alps. We find that, at multi‐day to multi‐decadal timescales, sliding speed can be expressed as a direct function of basal shear stress and water discharge, without accounting for water pressure, which simply adjusts to maintain the cavitation ratio needed to accommodate the water supply.

Effective Forchheimer Coefficient for Layered Porous Media

Inertial flow in porous media, governed by the Forchheimer equation, is affected by domain heterogeneity at the field scale. We propose a method to derive formulae of the effective Forchheimer coefficient with application to a perfectly stratified medium. Consider uniform flow under a constant pressure gradient Delta P/L in a layered permeability field with a given probability distribution. The local Forchheimer coefficient beta is related to the local permeability k via the relation beta =a/k^c, where a>0 being a constant and cin [0,2]. Under ergodicity, an effective value of beta is derived for flow (i) perpendicular and (ii) parallel to layers. Expressions for effective Forchheimer coefficient, beta _e, generalize previous formulations for discrete permeability variations. Closed-form beta _e expressions are derived for flow perpendicular to layers and under two limit cases, Fll 1 and Fgg 1, for flow parallel to layering, with F a Forchheimer number depending on the pressure gradient. For F of order unity, beta _e is obtained numerically: when realistic values of Delta P/L and a are adopted, beta _e approaches the results valid for the high Forchheimer approximation. Further, beta _{e} increases with heterogeneity, with values always larger than those it would take if the beta - k relationship was applied to the mean permeability; it increases (decreases) with increasing (decreasing) exponent c for flow perpendicular (parallel) to layers. beta _{e} is also moderately sensitive to the permeability distribution, and is larger for the gamma than for the lognormal distribution.

A structured model and likelihood approach to estimate yeast prion propagon replication rates and their asymmetric transmission.

Prion proteins cause a variety of fatal neurodegenerative diseases in mammals but are generally harmless to Baker’s yeast (Saccharomyces cerevisiae). This makes yeast an ideal model organism for investigating the protein dynamics associated with these diseases. The rate of disease onset is related to both the replication and transmission kinetics of propagons, the transmissible agents of prion diseases. Determining the kinetic parameters of propagon replication in yeast is complicated because the number of propagons in an individual cell depends on the intracellular replication dynamics and the asymmetric division of yeast cells within a growing yeast cell colony. We present a structured population model describing the distribution and replication of prion propagons in an actively dividing population of yeast cells. We then develop a likelihood approach for estimating the propagon replication rate and their transmission bias during cell division. We first demonstrate our ability to correctly recover known kinetic parameters from simulated data, then we apply our likelihood approach to estimate the kinetic parameters for six yeast prion variants using propagon recovery data. We find that, under our modeling framework, all variants are best described by a model with an asymmetric transmission bias. This demonstrates the strength of our framework over previous formulations assuming equal partitioning of intracellular constituents during cell division.

Disclosure of Ijtihad: The Changes of the Early Time of Dawn as a Sharia and Science Integration Effort

This article elaborates how ijtihad to changes in the dawn as an effort to integrate sharia and science. With a bibliographic qualitative research method, the author wants to describe how the early dawn changes have been used as guidelines for Muslims. Fajr's schedule has been considered too fast so that it is not in line with the provisions of the texts and the findings of modern science. Muhammadiyah, in its ijtihad, responded openly by making changes to the previous decision compared to the Ministry of Religion and Nadhatul Ulama, which remained in the previous formulation. The study results concluded that reviewing the dawn error at Muhammadiyah had begun in 2016 until it reached maturity in 2020. The results were confirmed at the 31st Tarjih National Conference in 2021 and by the Muhammadiyah Central Executive on March 20, 2021. Effective starting from January 2021, together with the publication of the Muhammadiyah calendar. The Sun's height is the initial criterion for the dawn of time from the original -200. After review, it becomes -180. This change in criteria implies a delay of the early dawn of about eight minutes from the previous one. This change was made to combine aspects of sharia and science with an integrated approach of Bayani, Irfani, and Burhani, considering the benefit of the community.

Stronger mixed-integer programming-formulations for order- and rack-sequencing in robotic mobile fulfillment systems

This paper addresses the order- and rack-sequencing problem at a single picking station in the context of robotic mobile fulfillment systems, a warehouse technology typically applied in large distribution centers. Following the parts-to-picker concept, items are stored on movable racks that are lifted and transported by automated guided vehicles from the storage area to picking stations for order-processing. The order-picking process involves two linked decisions: How to sequence the processing of orders and how to sequence the rack visits to supply the picking station with the requested items. We present a novel mixed-integer linear programming formulation achieving stronger linear programming bounds than a previous formulation. Including preprocessing techniques it quickly solves instances of medium-size to proven optimality for the first time in literature. For large real-world instances, we provide a three-stage heuristic solution procedure suitable in a dynamic environment, while providing competitive solutions within a short run time. Computational experiments on a broad set of benchmark instances and a comparative study with approaches from literature verify our results.

An improved HLLC-type solver for incompressible two-phase fluid flows

In this paper, an HLLC-type contact preserving Riemann solver for incompressible two-phase flows using the artificial compressibility formulation is presented. This formulation is an improvement over the previous HLLC-VOF formulation (Bhat and Mandal, 2019). In this work, unlike the previous formulation, the variation of the volume fraction is taken into account when calculating the eigenvalues and eigenvectors. Hence, the equations for the intermediate states and the intermediate wave speed are closely-coupled with density variation during pseudo-time evolution of the solution. Additionally, an interface compression algorithm is used in tandem to ensure sharp interfaces. This modified Riemann solver (called HLLC-VOF-M) is found to be more robust and accurate compared to the older HLLC-VOF solver and the non-contact preserving HLL solver. Several test problems in two- and three-dimensions are solved to demonstrate and evaluate the efficacy of the solver on structured and unstructured meshes.

Coherent state representation of thermal correlation functions with applications to rate theory.

A coherent state phase space representation of operators, based on the Husimi distribution, is used to derive an exact expression for the symmetrized version of thermal correlation functions. In addition to the time and temperature independent phase space representation of the two operators whose correlation function is of interest, the integrand includes a non-negative distribution function where only one imaginary time and one real time propagation are needed to compute it. The methodology is exemplified for the flux side correlation function used in rate theory. The coherent state representation necessitates the use of a smeared Gaussian flux operator whose coherent state phase space representation is identical to the classical flux expression. The resulting coherent state expression for the flux side correlation function has a number of advantages as compared to previous formulations. Since only one time propagation is needed, it is much easier to converge it with a semiclassical initial value representation. There is no need for forward-backward approximations, and in principle, the computation may be implemented on the fly. It also provides a route for analytic semiclassical approximations for the thermal rate, as exemplified by a computation of the transmission factor through symmetric and asymmetric Eckart barriers using a thawed Gaussian approximation for both imaginary and real time propagations. As a by-product, this example shows that one may obtain "good" tunneling rates using only above barrier classical trajectories even in the deep tunneling regime.

A Formalization of Finite Group Theory

Previous formulations of group theory in ACL2 and Nqthm, based on either "encapsulate" or "defn-sk", have been limited by their failure to provide a path to proof by induction on the order of a group, which is required for most interesting results in this domain beyond Lagrange's Theorem (asserting the divisibility of the order of a group by that of a subgroup). We describe an alternative approach to finite group theory that remedies this deficiency, based on an explicit representation of a group as an operation table. We define a "defgroup" macro for generating parametrized families of groups, which we apply to the additive and multiplicative groups of integers modulo n, the symmetric groups, arbitrary quotient groups, and cyclic subgroups. In addition to a proof of Lagrange's Theorem, we present an inductive proof of the abelian case of a theorem of Cauchy: If the order of a group G is divisible by a prime p, then G has an element of order p.

Modelling general-relativistic plasmas with collisionless moments and dissipative two-fluid magnetohydrodynamics

ABSTRACT Relativistic plasmas are central to the study of black hole accretion, jet physics, neutron star mergers, and compact object magnetospheres. Despite the need to accurately capture the dynamics of these plasmas and the implications for relativistic transients, their fluid modelling is typically done using a number of (overly) simplifying assumptions, which do not hold in general. This is especially true when the mean free path in the plasma is large compared to the system size, and kinetic effects start to become important. Going beyond common approaches used in the literature, we describe a fully relativistic covariant 14-moment based two-fluid system appropriate for the study of electron–ion or electron–positron plasmas. This generalized Israel-Stewart-like system of equations of motion is obtained directly from the relativistic Boltzmann–Vlasov equation. This new formulation can account for non-ideal effects, such as anisotropic pressures and heat fluxes, not present in previous formulations of two-fluid magnetohydrodynamics. We show that a relativistic two-fluid plasma can be recast as a single fluid coupled to electromagnetic fields with (potentially large) out-of-equilibrium corrections. We keep all electron degrees of freedom, which provide self-consistent evolution equations for electron temperature and momentum. The out-of-equilibrium corrections take the form of a collisional 14-moment closure previously described in the context of viscous single fluids. The equations outlined in this paper are able to capture the full two-fluid character of collisionless plasmas found in black hole accretion and flaring processes around compact objects, as well Braginskii-like two-fluid magnetohydrodynamics applicable to weakly collisional plasmas inside accretion discs.

Extending the Multiple Discrete Continuous (MDC) modelling framework to consider complementarity, substitution, and an unobserved budget

Many decisions can be represented as interrelated discrete and continuous choices, i.e. what and how much to choose from a set of finite alternatives (incidence and quantity of consumption). In the last twenty years, several models of Karush–Kuhn–Tucker demand systems have been developed and used to study these kinds of decisions. While strongly grounded in economic theory, most of these models have two limitations: they require specifying a budget, and usually omit any complementarity effects. In this paper, we propose two extensions to the Multiple Discrete Continuous (MDC) modelling framework: (i) an MDC model including explicit complementarity and substitution effects, and (ii) an MDC model with complementarity, substitution that requires no budget definition. Model (ii) relies on the hypothesis that total expenditure on the alternatives under consideration is small compared to the overall budget. This allows using a linear utility function for the numeraire good, leading to a likelihood function without the budget or numeraire good in it. The lack of a budget is specially useful when forecasting, as it avoids cascading errors due to an inaccurate budget specifications. The inclusion of complementarity and substitution effects enriches the interpretability of the models, while the resulting functional form avoids theoretical issues present in previous formulations. Alongside the derivation of the models, we discuss their main properties and propose an efficient forecasting algorithm for (ii). We also report four applications to datasets about time use, household expenditure, supermarket scanner data, and trip generation. Free estimation code for both models is made available online.

Adjustable frequency shift of laminated DNA microbeam under complex detection conditions by different packaging patterns

Packaging patterns have close correlation with thermoelastic properties of sensitive layer and relevant biodetection signals of laminated microbeam. In this paper, we present a cross-scale mechanical model to explore the possibility of adjusting thermoelastic properties of DNA adsorption film and the relevant signals of microbeam under complex detection conditions by different packaging patterns. First, considering microscale interactions in DNA solutions, a unified mesoscopic free energy is developed based on the previous formulations of Parsegian et al.; then, the thought experiment method for DNA film and the force balance method for nonlinear elastic network of DNA cylinders are combined to characterize elastic properties of adsorption film; finally, an effective macroscopic model for DNA microbeam is used to predict resonance frequency shift caused by DNA adsorption and temperature fluctuation in high-valent salt solutions. Results show that, compared with the properties of classical convex-packaged film, the thermal expansion coefficient of concave-packaged DNA film in high-valent salt solutions is smaller, and its elastic modulus and prestress have larger fluctuation ranges to environmental conditions, which provide a chance to improve detection sensitivity based on frequency shift. These results are expected to provide an option for design of DNA composite materials and microbeam sensors.

The effect of LDHs nanoparticles on the cellular behavior of stem cell-laden 3D-bioprinted scaffold.

Three-dimensional (3D)-bioprinting as an emerging approach for tissue engineering possesses the promise to create highly mimicked organs or tissues by using computer-aided design. For biomedical applications in tissue engineering in our previous work, we developed an optimized nanocomposite bioink based on methylacrylated gelatin (GelMA), methylacrylated chitosan (ChitMA), and double-layered hydroxide (LDHs) nanoparticles by using 3D-bioprinting technology. Herein, we used the previous formulation to fabricate human bone marrow mesenchymal stem cells (hBMMSCs)-laden nanocomposite bioinks. The effect of LDHs nanoparticles on the cellular behaviors of the encapsulated-hBMMSCs in the scaffolds was evaluated for the first time. Live/Dead, PrestoBlue, and DAPI/Actin analysis were carried out to assess the cell viability, proliferation rate, and cellular morphology of encapsulated hBMMSCs within the scaffolds. In addition, osteogenic differentiation studies were performed culturing the scaffolds for up to 21 days. Results show that LDHs nanoparticles in the GelMA/ChitMA scaffold formulation increased the viability of hBMMSCs, did not cause any adverse effect on the proliferation rate, cell morphology of the hBMMSCs, and increased the Runx2 protein expression of the encapsulated-hBMMSCs in the scaffolds. This study progresses the LDHs containing nanocomposite bioink for cell printing applications in tissue engineering.

A Semianalytical Formulation for Estimating Induced Surface Subsidence of a Poroelastic Reservoir

Summary Monitoring and controlling surface subsidence are important to the safety of production operations as well as to the compliance of environmental regulations. Quantitively predicting surface subsidence caused by subsurface pressure change due to well production or injection would be very useful for operators. However, running a 3D geomechanics simulation for such a purpose is technically demanding and computationally expensive. Currently, a quick and easy alternative to get accurate results to fulfill such a task is lacking. In this work, we propose a semianalytical formulation to efficiently calculate the surface subsidence of a reservoir during the primary and enhanced recovery processes. Our method is based on the Green’s function solution of the Navier-Beltrami-Michell equation of poroelastic rocks. It takes the pressure field from a reservoir simulator or an analytical solution as the input and calculates the surface displacement along the vertical direction. We benchmarked the proposed formulation with numerical methods on a refined grid as well as with a semianalytical solution to ensure its accuracy. We applied the developed formulation to optimize the injection well position and vertical injection zone for pressure management. Compared to the previous analytical formulations that are based on the average pressure decline of the reservoir, our method explicitly considers the spatial distribution of the pressure field and is therefore more accurate. Compared with numerical methods, our method avoids the discretization of the caprock region and is thus faster by several orders of magnitude.

Prospect of China's ambient air quality standards

Ambient air quality standards are the core strategic goal of ambient air quality management. Countries worldwide have given importance to research on the development of ambient air quality standards. To understand the history of the development of China's ambient air quality standards, this study analyzed the background associated with all previous formulations and revisions of the standards, classification of functional areas, standard grading, pollutants, and evolution of the standard limits over the past 40 years. The results show that since the initial release of the “Ambient Air Quality Standard” by China in 1982, it has been supplemented once, revised twice, and modified twice. The first ambient air quality standard specified the standard limits of six pollutants commonly found in ambient air. With the development of ambient air quality management, the number of pollutants has increased to ten. Since the release of the “Ambient Air Quality Standards” in 2012, the ambient air quality in China has significantly improved. However, the proportion of cities meeting these standards is still low. At present, China is suitably positioned to make the standards associated with 24 hr SO2 concentrations more stringent such that it meets the values defined in the World Health Organization (WHO) interim target-2 and the WHO air quality guideline (AQG). We further suggested that the SO2 standard should be revised promptly. Simultaneously, regions with a relatively high proportion of cities meeting the standard are encouraged to introduce more stringent interim target limits in due course to manage the local ambient air quality.

Bayesian sparse factor analysis with kernelized observations

Multi-view problems can benefit from latent representations since they find low-dimensional projections that fairly capture the correlations among the multiple views that characterise the data. On the other hand, high-dimensionality and non-linear issues are traditionally handled by kernel methods, inducing a (non)-linear function between the latent projection and the data itself. However, they usually come with exposition to overfitting. Here, we combine Bayesian factor analysis with what we refer to as kernelized observations, in which the proposed model focuses on reconstructing not the data itself, but its relationship with other data points measured by a kernel function. In turn, we extend previous Bayesian FA formulations to be able to model non-linear data relationships by means of kernelized data representations and, at the same time, include additional facilities to obtain compact kernel representations by means of an automatic selection of Bayesian Relevance Vectors (RVs), feature relevance analysis and, even, obtain an automatic multiple kernel learning approach. Besides, this is flexibly included into a modular framework where we can easily adapt the model capabilities to the data needs and, even, combine them with previous FA functionalities such as heterogeneous data representations or semi-supervised learning. Using several public databases, we demonstrate the potential of the approach (and its extensions) w.r.t. common multi-view learning models such as kernel canonical correlation analysis, heterogeneous incomplete – variational autoenconder or manifold relevance determination, where the proposed model shows its ability to outperform the baselines while indistinctly combining model extensions.

New International Formulation for the Thermal Conductivity of Heavy Water

The International Association for the Properties of Water and Steam has adopted new formulations for the thermodynamic and transport properties of heavy water. This manuscript describes the development of a formulation for the thermal conductivity of heavy water that was adopted as an international standard in 2021. It is consistent with the equation of state adopted in 2017, revised slightly in 2018, and is valid for fluid states up to 825 K and 250 MPa with uncertainties ranging from 1.5% to 6% depending on the state point. Comparisons with experimental data and with an earlier thermal-conductivity formulation are presented. The 2021 formulation accounts for the critical enhancement of the thermal conductivity, which was not incorporated in the previous formulation. Furthermore, in the zero-density limit, the 2021 formulation is based on thermal conductivity values at temperatures from 250 to 2500 K obtained from the kinetic theory of polyatomic gases. In addition, the 2021 formulation is applicable in a larger range of pressures than the previous formulation.