Discrete Effects Research Articles

A randomized dietary intervention to increase colonic and peripheral blood SCFAs modulates the blood B- and T-cell compartments in healthy humans

SCFAs have immune-modulating effects in animal models of disease. However, there is limited evidence that this may occur in humans. This study aimed to determine the effects of increased exposure to SCFAs via dietary manipulation on colonic fermentation and adaptive immune cells. Twenty healthy young adults (18-45 y of age) underwent a blinded randomized crossover dietary intervention, consuming a high-SCFA diet and a matched low-SCFA diet for 21-d with a 21-d washout in between. SCFAs were provided through resistant starch, inulin, and apple cider vinegar. Blood and 3-d total fecal output were collected at baseline and at the end of each diet. GC was used to measure fecal and plasma SCFA. Flow cytometry was used for peripheral blood immunophenotyping. According to a paired samples Wilcoxon test, the high-SCFA diet was associated with significantly higher fecal SCFA concentrations [median (IQR); 86.6 (59.0) compared with 75.4 (56.2) µmol/g, P = 0.02] and lower fecal ammonia concentrations [26.2 (14.7) compared with 33.4 (18.5) µmol/g, P = 0.04] than the low-SCFA diet. Plasma propionate [9.87 (12.3) compared with 4.72 (7.6) µmol/L, P = 0.049] and butyrate [2.85 (1.35) compared with 2.02 (1.29) µmol/L, P = 0.03] were significantly higher after the high-SCFA diet than after the low-SCFA diet. Blood total B cells [184 (112) compared with 199 (143) cells/µL, P = 0.04], naive B cells [83 (66) compared with 95 (89) cells/µL, P = 0.02], Th1 cells [22 (19) compared with 29 (16) cells/µL, P = 0.03], and mucosal-associated invariant T cells [62 (83) compared with 69 (114) cells/µL, P = 0.02] were significantly lower after the high-SCFA diet than the low-SCFA diet. Increasing colonic and peripheral blood SCFA has discrete effects on circulating immune cells in healthy humans following 3-wk intervention. Further studies (e.g., in patients with inflammatory disease) are necessary to determine whether 1) these changes have immunomodulatory effects, 2) they are therapeutically beneficial, and 3) prolonged intake might be required. This trial is registered at the Australian New Zealand Clinical Trials Registry as ACTRN12618001054202.

Magnetic dipole moments as a strong signature for alpha -clustering in even-even self-conjugate nuclei

We investigate the magnetic dipole moments in even-even self-conjugate nuclei from ^{12}C to ^{48}Cr. For these nuclei, the measured gyromagnetic factors of excited states turn out to assume the same value of g approx + 0.5 within statistical errors. This peculiar feature can be interpreted on the basis of collective excitations of alpha -clusters. Analogously, the behaviour of the same observable is studied for all isotopes obtained by adding one or two neutrons to the considered self-conjugate nuclei. It is found that for the N = Z + 1 isotopes the alpha -cluster structure hardly contributes to the observed negative g- factor value, corroborating molecular alpha -cluster models. The addition of a further neutron, however, restores the original alpha -cluster g-factors, except for the semi-magic isotopes, in which the deviations from g approx + 0.5 can be associated with the relevant shell closures. Secondly, we analyze the same observable in the framework of a macroscopic alpha -cluster model on a finite lattice of side length L. We focus on the discretization effects induced in the magnetic dipole moments of the 2_1^+ and the 3_1^- states of ^{12}C at different values of the lattice spacing a.

Research Highlights

Research Highlights

Output error behavior for discretizations of ergodic, chaotic systems of ordinary differential equations

The use of numerical simulation for prediction of characteristics of chaotic dynamical systems inherently involves unpredictable processes. In this work, we develop a model for the expected error in the simulation of ergodic, chaotic ordinary differential equation (ODE) systems, which allows for discretization and statistical effects due to unpredictability. Using this model, we then generate a framework for understanding the relationship between the sampling cost of a simulation and the expected error in the result and explore the implications of the various parameters of simulations. Finally, we generalize the framework to consider the total cost—including unsampled spin-up timesteps—of simulations and consider the implications of parallel computational environments to give a realistic model of the relationship between wall-clock time and the expected error in simulation of a chaotic ODE system.

The moderating effect of managerial discretion on cross-border knowledge search and the innovation quality of high-tech firms in a global health emergency: evidence from China

PurposeThis study aims to analyze the moderating effect of managerial discretion on the relationship between cross-border knowledge search and the high-tech firms’ innovation quality in a global health emergency and addresses the following issues: the influence mechanism of different types of cross-border knowledge search on the high-tech firms’ innovation quality in a global health emergency; and the moderating role of different dimensions of manager discretion on the above relationship.Design/methodology/approachBased on the firms’ strategy selection methods, the authors divided cross-border knowledge search into three aspects, namely, breadth, depth and balance, and analyzed the impact of cross-border knowledge search on the innovation quality of high-tech firms in a global health emergency, taking managerial discretion as the moderating variable, and divided it into position rights, pay rights and operation rights according to the key rights of firms’ strategic management. Furthermore, the authors constructed a theoretical model, and for an analysis sample, the authors collected data from Chinese high-tech firms from 2013 to 2021.FindingsThe empirical results show that there is an inverted U-shaped relationship between cross-border knowledge search breadth, depth and balance and the innovation quality of high-tech firms. The position rights, pay rights and operation rights of managerial discretion have partially significant moderating effects on the relationship between cross-border knowledge search breadth, depth and balance and the high-tech firms’ innovation quality.Originality/valueConsiderable literature has grown around the theme of the impact of knowledge search on the firms’ innovation quality. Nevertheless, only a few studies draw on the combination of global health emergency, cross-border knowledge search and the innovation quality; in particular, no literature has analyzed the relationship between the three from the managerial discretion perspective. Exploring the above relationships has great theoretical value for enriching and improving knowledge management and innovation management theories and provides a theoretical basis and practical support for high-tech firms to face challenges of a global health emergency and to break through the innovation dilemma.

G protein–biased GPR3 signaling ameliorates amyloid pathology in a preclinical Alzheimer’s disease mouse model

Biased G protein-coupled receptor (GPCR) ligands, which preferentially activate G protein or β-arrestin signaling pathways, are leading to the development of drugs with superior efficacy and reduced side effects in heart disease, pain management, and neuropsychiatric disorders. Although GPCRs are implicated in the pathophysiology of Alzheimer's disease (AD), biased GPCR signaling is a largely unexplored area of investigation in AD. Our previous work demonstrated that GPR3-mediated β-arrestin signaling modulates amyloid-β (Aβ) generation invitro and that Gpr3 deficiency ameliorates Aβ pathology invivo. However, Gpr3-deficient mice display several adverse phenotypes, including elevated anxiety-like behavior, reduced fertility, and memory impairment, which are potentially associated with impaired G protein signaling. Here, we generated a G protein-biased GPR3 mouse model to investigate the physiological and pathophysiological consequences of selective elimination of GPR3-mediated β-arrestin signaling invivo. In contrast to Gpr3-deficient mice, G protein-biased GPR3 mice do not display elevated anxiety levels, reduced fertility, or cognitive impairment. We further determined that G protein-biased signaling reduces soluble Aβ levels and leads to a decrease in the area and compaction of amyloid plaques in the preclinical AppNL-G-F AD mouse model. The changes in amyloid pathology are accompanied by robust microglial and astrocytic hypertrophy, which suggest a protective glial response that may limit amyloid plaque development in G protein-biased GPR3 AD mice. Collectively, these studies indicate that GPR3-mediated G protein and β-arrestin signaling produce discrete and separable effects and provide proof of concept for the development of safer GPCR-targeting therapeutics with more directed pharmacological action for AD.

A posteriori error estimator for a multiscale hybrid mixed method for Darcy's flows

AbstractThis article presents a computable and efficient procedure for a posteriori error estimations of approximate solutions of Darcy's flows given by a Multiscale Hybrid Mixed method. Based on a partition of the domain by polytopal macro subregions, this is a strategy for efficient simulations of problems with strongly varying solutions. The flux approximations interacting with the skeleton (subregion boundaries) are strongly constrained by a given trace space. Whilst the dimension of the piecewise polynomial trace space is expected to be as low as possible, the small‐scale features of the solution are supposed to be accurately resolved by completely independent local stable mixed solvers, the trace variable playing the role of Neumann boundary data. As the method already gives an equilibrated global H(div)‐conforming flux approximation, the methodology for the error estimation only requires a potential reconstruction. In addition to usual residual errors and indicators associated with the potential reconstruction, the estimation also takes into account the effect of discretizations of practical nonhomogeneous Dirichlet and Neumann boundary conditions. Based on the proposed a posteriori error estimator, ‐adaptive algorithms are constructed to guide a proper choice of the trace space. The performance of the error estimator and the adaptive scheme is numerically investigated through a set of illustrating test problems.

Controllable discrete Talbot self-imaging effect in Hermitian and non-Hermitian Floquet superlattices.

We investigate the discrete Talbot self-imaging effect in Floquet superlattices based on a mesh of directional couplers with periodically varying separation between waveguides, both theoretically and numerically. The modulated discreteness of the lattices sets strong constraints to ensure the Talbot effect generation. We show that discrete Talbot effect occurs only if the incident periods are N = 1, 2, and 4 in dispersive regimes of the Hermitian superlattices. In both dynamic localized and rectification regimes, self-imaging effect can occur for arbitrary input period N. For the rectification case, Talbot distance equals the input period. In the regime of dynamical localization, the Talbot distance remains unchanged irrespective of the pattern period. For non-Hermitian Floquet superlattices, due to the non-zero imaginary part of quasi-energy spectrum arising at the center of the Brillouin zone, where the mode degeneracy occurs, Talbot revival is not preserved when the input period is an even number, and exists only as N = 1 in the dispersive regime. The theoretical calculations and numerical simulations verify each other completely.

Continuum limit of parton distribution functions from the pseudodistribution approach on the lattice

Precise quantification of the structure of nucleons is one of the crucial aims of hadronic physics for the coming years. The expected progress related to ongoing and planned experiments should be accompanied by calculations of partonic distributions from lattice QCD. While key insights from the lattice are expected to come for distributions that are difficult to access experimentally, it is important that lattice QCD can reproduce the well-known unpolarized parton distribution functions (PDFs) with full control over systematic uncertainties. One of the novel methods for accessing the partonic $x$-dependence is the pseudo-distribution approach, which employs matrix elements of a spatially-extended nonlocal Wilson-line operator of length $z$. In this paper, we address the issue of discretization effects, related to the necessarily nonzero value of the lattice spacing $a$, which start at first order in $a$ as a result of the nonlocal operator. We use twisted mass fermions simulated at three values of the lattice spacing, at a pion mass of 370 MeV, and extract the continuum limit of isovector unpolarized PDFs. We also test, for the first time in the pseudo-distribution approach, the effects of the recently derived two-loop matching. Finally, we address the issue of the reliability of the extraction with respect to the maximal value of $z$.

Study on lattice discreteness effect on superdislocation core properties of Ni3Al by improved semi-discrete variational Peierls-Nabarro model

Nickel-based superalloys (NBSAs) serve as hot-end component materials of aero engines. NBSAs generally consist of γ and γ′ phases, the γ′ phase (i.e. Ni3Al) presents anomalous yield strength and non-Schmid effect, influencing the mechanical behaviors of NBSAs significantly. These phenomena are closely related to the ⟨110⟩{111} superdislocations. In the present work, based on the quasiharmonic density functional theory (DFT), the improved semi-discrete variational Peierls-Nabarro (SVPN) model is employed to systematically investigate the properties of such superdislocations, in terms of dislocation density distribution, splitting distance (i.e., anti-phase boundary APB, super-lattice intrinsic stacking fault SISF and complex stacking fault width CSF), total energy, Peierls stress and so on. It is found that the predicted superdislocation characters, especially the Peierls stress, are in good agreement with previous experimental results, considering the lattice discreteness effect. This implies that the lattice discreteness plays an important role in the total dislocation energy and Peierls stress, which has however been ignored in previous studies. Although such superdislocation may have several possible core configurations, the dissociation of four 1/6⟨112⟩ Shockley partials separated by two CSFs and an APB may be more energetically favorable at both 300 K and 1200 K. In addition, the superdislocation properties with such the core structure may be easily affected by applied stress. The present work provides an improved SVPN model with consideration of lattice discreteness to describe the superdislocation properties in Ni3Al, which may be helpful for understanding the plastic deformation behavior of the γ′ phase and NBSAs.

Static floor field construction and fine discrete cellular automaton model: Algorithms, simulations and insights

While cellular automaton (CA) models have a broad range of applications in the field of pedestrian dynamics, there are still three significant issues (the efficient and accurate construction of the static floor field (SFF), the insufficient simulation accuracy, and the discretization effect) that have not been resolved or fully clarified yet. This work aims to tackle these challenges. First, a novel approximate algorithm that resolves the dilemma between accuracy and efficiency is proposed to construct the SFF, based on which the static navigation field is created by the proposed method. Then, a novel fine discrete CA model based on the desired direction is developed to capture the locomotion movement behaviour. The novel SFF construction algorithm and locomotion movement model are (theoretically and/or numerically) validated and compared to the state-of-the-art approaches in manifold scenarios. Later on, systematic simulation analyses are conducted to investigate the discretization effect at the micro and macro levels. The assessment metrics show that the performance of the proposed algorithm and model is superior over that of the state-of-the-art approaches. The proposed model can resolve the well-known diagonal movement artefact in the existing CA models and reproduce crowd movement and self-organized lane formation observed empirically. It is found that the non-isotropic SFF results in significantly biased and unrealistic evacuation movement. Moreover, the discretization degree is found to significantly affect the individual and crowd movement simulation outcomes, and the magnitude and direction of its effect depend on the used model and the setup of the scenarios. The proposed algorithm and model are promising tools in pedestrian modelling and simulation. The findings provide fresh insights into the development and application of CA models.

Quasilinear theory of general electromagnetic fluctuations including discrete particle effects for magnetized plasmas: General analysis

The general quasilinear Fokker–Planck kinetic equation for the gyrophase-averaged plasma particle distribution functions in magnetized plasmas is derived, making no restrictions on the energy of the particles and on the frequency of the electromagnetic fluctuations and avoiding the often made Coulomb approximation of the electromagnetic interactions. The inclusion of discrete particle effects breaks the dichotomy of nonlinear kinetic plasma theory divided into the test particle and the test fluctuation approximation because it provides expression of both the non-collective and collective electromagnetic fluctuation spectra in terms of the plasma particle distribution functions. Within the validity of the quasilinear approach, the resulting full quasilinear transport equation can be regarded as a determining nonlinear equation for the time evolution of the plasma particle distribution functions.

Impact of spatial discretization resolution on the hydrological performance of layout optimization of LID practices

• Four SWMM models with various spatial discretization resolutions were constructed. • The scale effects on the LID layout optimization are discussed. • Solutions optimized by the finest model performed best under small rainfall events. • Modelling scale had little impact on the layout optimization under a heavy rainstorm. • Layouts optimized by a coarse model overshadowed some types of LID practices. Climate change and increasing urbanization have worsened urban floods and other water problems, and it is generally accepted that the optimization of the spatial layout of low impact development (LID) practices is a promising solution. Existing studies have focused on coupling the hydrological model with optimization methods, but little is known about the effects of the spatial discretization of the model on the optimization results. In this study, the scale effects were examined in a case study in Guangzhou, China. Four models at various spatial discretization levels, namely models R1, R2, R3, and R4, with an average unit size of 0.022*10 4 , 0.405*10 4 , 2.43*10 4 , and 4.865*10 4 m 2 , respectively, were constructed to investigate the performance difference caused by delineation scales. The results show that the highest-resolution model R1 (one unit represented one type of land cover) provides more cost-effective layout schemes, but during a heavy rainstorm, the solution set provided by a coarser model are very similar to that generated by the finest model R1. A coarser model can provide wider solution sets, but most of these schemes overshadow some types of LID practices such rain garden and bio-retention cell, which also have a critical role in urban heat mitigation, air quality improvement, and so on. Due to the cumbersome work of catchment subdividing and time-consuming optimization process, a coarse model would be a good substitute to a large area. These findings provide new insights on how to achieve better performance by subdividing the catchment at a proper scale when optimizing the spatial layout of LID practices.

Semiparametric point process modeling of blinking artifacts in PALM

Photoactivated localization microscopy (PALM) is a powerful imaging technique for characterization of protein organization in biological cells. Due to the stochastic blinking of fluorescent probes and camera discretization effects, each protein gives rise to a cluster of artificial observations. These blinking artifacts are an obstacle for quantitative analysis of PALM data, and tools for their correction are in high demand. We develop the independent blinking cluster point process (IBCpp) family of models, which is suited for modeling of data from single-molecule localization microscopy modalities, and we present results on the mark correlation function. We then construct the PALM-IBCpp, a semiparametric IBCpp tailored for PALM data, and we describe a procedure for estimation of parameters which can be used without parametric assumptions on the spatial organization of proteins. Our model is validated on nuclear pore complex reference data, where the ground truth was accurately recovered, and we demonstrate how the estimated blinking parameters can be used to perform a blinking corrected test for protein clustering in a cell expressing the adaptor protein LAT. Finally, we consider simulations with varying degrees of blinking and protein clustering to shed light on the expected performance in a range of realistic settings.

Effect of Gray Value Discretization and Image Filtration on Texture Features of the Pancreas Derived from Magnetic Resonance Imaging at 3T.

Radiomics of pancreas magnetic resonance (MR) images is positioned well to play an important role in the management of diseases characterized by diffuse involvement of the pancreas. The effect of image pre-processing configurations on these images has been sparsely investigated. Fifteen individuals with definite chronic pancreatitis (an exemplar diffuse disease of the pancreas) and 15 healthy individuals were included in this age- and sex-matched case-control study. MR images of the pancreas were acquired using a single 3T scanner. A total of 93 first-order and second-order texture features of the pancreas were compared between the study groups, by subjecting MR images of the pancreas to 7 image pre-processing configurations related to gray level discretization and image filtration. The studied parameters of intensity discretization did not vary in terms of their effect on the number of significant first-order texture features. The number of statistically significant first-order texture features varied after filtering (7 with the use of logarithm filter and 3 with the use of Laplacian of Gaussian filter with 5 mm σ). Intensity discretization generally affected the number of significant second-order texture features more markedly than filtering. The use of fixed bin number of 16 yielded 42 significant second-order texture features, fixed bin number of 128–38 features, fixed bin width of 6–24 features, and fixed bin width of 42–26 features. The specific parameters of filtration and intensity discretization had differing effects on radiomics signature of the pancreas. Relative discretization with fixed bin number of 16 and use of logarithm filter hold promise as pre-processing configurations of choice in future radiomics studies in diffuse diseases of the pancreas.

Finding the Perfect Fit: Conformational Biosensors to Determine the Efficacy of GPCR Ligands.

G protein-coupled receptors (GPCRs) are highly druggable targets that adopt numerous conformations. A ligand's ability to stabilize specific conformation(s) of its cognate receptor determines its efficacy or ability to produce a biological response. Identifying ligands that produce different receptor conformations and potentially discrete pharmacological effects (e.g., biased agonists, partial agonists, antagonists, allosteric modulators) is a major goal in drug discovery and necessary to develop drugs with better effectiveness and fewer side effects. Fortunately, direct measurements of ligand efficacy, via receptor conformational changes are possible with the recent development of conformational biosensors. In this review, we discuss classical efficacy models, including the two-state model, the ternary-complex model, and multistate models. We describe how nanobody-, transducer-, and receptor-based conformational biosensors detect and/or stabilize specific GPCR conformations to identify ligands with different levels of efficacy. In particular, conformational biosensors provide the potential to identify and/or characterize therapeutically desirable but often difficult to measure conformations of receptors faster and better than current methods. For drug discovery/development, several recent proof-of-principle studies have optimized conformational biosensors for high-throughput screening (HTS) platforms. However, their widespread use is limited by the fact that few sensors are reliably capable of detecting low-frequency conformations and technically demanding assay conditions. Nonetheless, conformational biosensors do help identify desirable ligands such as allosteric modulators, biased ligands, or partial agonists in a single assay, representing a distinct advantage over classical methods.

Impacts of deficit irrigation and organic amendments on soil microbial populations and yield of processing tomatoes

Altered precipitation patterns and increased water demands from urban, industrial, and environmental needs often reduce the volume of irrigation water available for agriculture. Strategies that reduce irrigation water inputs, e.g., deficit irrigation (DI), need further evaluation to determine potential impacts on yield and soil microbial communities driving critical soil biogeochemical cycles. Whether soil organic amendments can stabilize DI effects on yield and microbial communities remains unknown. Processing tomato beds were established in a full factorial experimental design of soils unamended or amended with a one-time application—four to five years before sampling—of either biochar or biochar with compost and three irrigation regimes: full (100 % of plant water demand), or DI treatments at 75 % or 50 % of full irrigation. We profiled soil bacterial and archaeal community compositions for two growing seasons and determined soil C and N metabolic potentials and biomass of microbial groups using high throughput sequencing of 16S rRNA genes and phospholipid fatty acid analysis. We tested the discrete and interactive effects of DI and soil amendments on soil chemical and biological properties, and crop yield. DI had stronger effects on the bacterial and archaeal community composition than soil organic amendments. However, 75 % DI did not strongly affect bacterial and archaeal community composition or the total and individual biomass of microbial groups, but it increased irrigation water productivity of processing tomatoes. Although soil amendments did not stabilize the compositional shifts induced by DI, their recalcitrant C still had residual effects on the bacterial and archaeal community composition years after their incorporation. Furthermore, soil moisture correlated with bacterial and archaeal community's C and N metabolic potentials, likely augmenting the amendments' C and N residence time in DI soils. Our results provide insight into water-saving mechanisms that could increase profit margins in water-scarce years without affecting microbial populations that support plant growth and productivity.

Efficient Temporal Piecewise-Linear Numeric Planning With Lazy Consistency Checking

Temporal planning often involves numeric effects that are directly proportional to their action's duration. These include continuous effects, where a numeric variable is subjected to a rate of change while the action is being executed, and discrete duration-dependent effects, where the variable is updated instantaneously but the magnitude of such change is computed from the action's duration. When these effects are linear, state--of--the--art temporal planners often make use of Linear Programming to ensure that these numeric updates are consistent with the chosen start times and durations of the plan's actions. This is typically done for each evaluated state as part of the search process. This exhaustive approach is not scalable to solve real-world problems that require long plans, because the linear program's size becomes larger and slower to solve. In this work we propose techniques that minimise this overhead by computing these checks more selectively and formulating linear programs that have a smaller footprint. The effectiveness of these techniques is demonstrated on domains that use a mix of discrete and continuous effects, which is typical of real-world planning problems. The resultant planner also outperforms most state-of-the-art temporal-numeric and hybrid planners, in terms of both coverage and scalability.

INVESTIGATION OF THERMO-MECHANICAL BEHAVIOR IN BRAKE DISC–PAD COUPLE USING THE FINITE ELEMENT METHOD

The braking system is the most significant active safety system that converts the vehicle’s mechanical energy into heat energy based on the braking pair’s friction. In this paper, temperature-friction coefficient variation, disc thickness variation, and coning are investigated with the Fade I test procedure is performed according to the SAE J2522 comprehensive brake efficiency test standard. In these investigations, the combined or discrete effects of the peripheral speed factor, the temperature increase with the braking time, thermal expansion and increased friction coefficient values have been decisive on the increase in the disc thickness variation from the inner part to the outer part. The thermo-mechanical behavior of the disc for the same test procedure is demonstrated in ANSYS® software using the finite element method. Steady-state thermal analysis method is chosen, and then total deformation and von Mises stress conditions are evaluated by using transient structural analysis with thermal analysis results and experimental data. At the end of braking, the deformation has reached its 0.28872 mm (maximum) at the outer radius where the pad and disc are in contact, and the maximum von Mises stress value (964.33 MPa) has been obtained. Furthermore, the deformations reached the maximum in the region where the disc temperature reached its maximum during braking revealing that the obtained results are interrelated.

Rapid Model Development for GSFLOW With Python and pyGSFLOW

Following the advancement of high-performance computing and sensor technology and the increased availability of larger climate and land-use data sets, hydrologic models have become more sophisticated. Instead of simple boundary conditions, these data sets are incorporated with the aim of providing more accurate insights into hydrologic processes. Integrated surface-water and groundwater models are developed to represent the most important processes that affect the distribution of water in hydrologic systems. GSFLOW is an integrated hydrologic modeling software that couples surface-water processes from PRMS and groundwater processes from MODFLOW and simulates feedbacks between both components of the hydrologic system. Development of GSFLOW models has previously required multiple tools to separately create surface-water and groundwater input files. The use of these multiple tools, custom workflows, and manual processing complicates reproducibility and confidence in model results. Based on a need for rapid, reproduceable, and robust methods, we present two example problems that showcase the latest updates to pyGSFLOW. The software package, pyGSFLOW, is an end-to-end data processing tool made from open-source Python libraries that enables the user to edit, write input files, run models, and postprocess model output. The first example showcases pyGSFLOW’s capabilities by developing a streamflow network in the Russian River watershed with an area of 3,850 km2 located on the coast of northern California. A second example examines the effects of model discretization on hydrologic prediction for the Sagehen Creek watershed with an area of 28 km2, near Lake Tahoe, California, in the northern Sierra Nevada.