Set Of Best-fit Parameters Research Articles

A new solution for the observed isotropic cosmic birefringence angle and its implications for the anisotropic counterpart through a Boltzmann approach

Abstract Cosmic Birefringence (CB) is a phenomenon in which the polarization of the Cosmic Microwave Background (CMB) radiation is rotated as it travels through space due to the coupling between photons and an axion-like field. We look for a solution able to explain the result obtained from the Planck Public Release 4 (PR4), which has provided a hint of detection of the CB angle, α = (0.30 ± 0.11)∘. In addition to the solutions, already present in the literature, which need a non-negligible evolution in time of the axion-like field during recombination, we find a new region of the parameter space that allows for a nearly constant time evolution of such a field in the same epoch. The latter reinforces the possibility to employ the commonly used relations connecting the observed CMB spectra with the unrotated ones, through trigonometric functions of the CB angle. However, if the homogeneous axion field sourcing isotropic birefringence is almost constant in time during the matter-dominated era, this does not automatically imply that the same holds also for the associated inhomogeneous perturbations. For this reason, in this paper we present a fully generalized Boltzmann treatment of this phenomenon, that is able, for the first time to our knowledge to deal with the time evolution of anisotropic cosmic birefringence (ACB). We employ this approach to provide predictions of ACB, in particular for the set of best-fit parameters found in the new solution of the isotropic case. If the latter is the correct model, we expect an ACB spectrum of the order of (10-15 ÷ 10-32) deg2 for the auto-correlation, and (10-7 ÷ 10-17) μK·deg for the cross-correlations with the CMB T and E fields, depending on the angular scale.

Development and calibration of a mathematical model of HIV outcomes among Rwandan adults: informing equitable achievement of targets in Rwanda.

We developed and calibrated the Central Africa-International epidemiology Databases to Evaluate AIDS (CA-IeDEA) HIV policy model to inform equitable achievement of global goals, overall and across sub-populations, in Rwanda. We created a deterministic dynamic model to project adult HIV epidemic and care continuum outcomes, overall and for 25 subpopulations (age group, sex, HIV acquisition risk, urbanicity). Data came from the Rwanda cohort of CA-IeDEA, 2004-2020; Rwanda Demographic and Health Surveys, 2005, 2010, 2015; Rwanda Population-based HIV Impact Assessment, 2019; and the literature and reports. We calibrated the model to 47 targets by selecting the 50 best-fitting parameter sets among 20,000 simulations. Calibration targets reflected epidemic (HIV prevalence, incidence), global goals (percentage on antiretroviral therapy (ART) among diagnosed, percentage virally suppressed among on ART) and other (number on ART, percentage virally suppressed) indicators, overall and by sex. Best-fitting sets minimized the summed absolute value of the percentage deviation (AVPD) between model projections and calibration targets. Good model performance was mean AVPD ≤5% across the 50 best-fitting sets and/or projections within the target confidence intervals; acceptable was mean AVPD >5% and ≤15%. Across indicators, 1,841 of 2,350 (78.3%) model projections were a good or acceptable fit to calibration targets. For HIV epidemic indicators, 256 of 300 (85.3%) projections were a good fit to targets, with the model performing better for women (83.3% a good fit) than for men (71.7% a good fit). For global goals indicators, 96 of 100 (96.0%) projections were a good fit; model performance was similar for women and men. For other indicators, 653 of 950 (68.7%) projections were a good or acceptable fit. Fit was better for women than for men (percentage virally suppressed only) and when restricting targets for number on ART to 2013 and beyond. The CA-IeDEA HIV policy model fits historical data and can inform policy solutions for equitably achieving global goals to end the HIV epidemic in Rwanda. High-quality, unbiased population-based data, as well as novel approaches that account for calibration target quality, are critical to ongoing use of mathematical models for programmatic planning.

A phase-resolved Fermi-LAT analysis of the mode-changing pulsar PSR J2021+4026 shows hints of a multipolar magnetosphere

Context. The radio-quiet γ-ray pulsar PSR J2021+4026 is a peculiar Fermi-LAT pulsar showing repeated and quasi-periodic mode changes. Its γ-ray flux shows repeated variations between two states at intervals of ∼3.5 years. These events occur over timescales < 100 days and are correlated with sudden changes in the spin-down rate. Multiwavelength observations also revealed an X-ray phase shift relative to the γ-ray profile for one of the events. PSR J2021+4026 is currently the only known isolated γ-ray pulsar showing significant variability, and thus it has been the object of thorough investigations. Aims. The goal of our work is to study the mode changes of PSR J2021+4026 with improved detail. By accurately characterizing variations in the γ-ray spectrum and pulse profile, we aim to relate the Fermi-LAT observations to theoretical models. We also aim to interpret the mode changes in terms of variations in the structure of a multipolar dissipative magnetosphere. Methods. We continually monitored the rotational evolution and the γ-ray flux of PSR J2021+4026 using more than 13 years of Fermi-LAT data with a binned likelihood approach. We investigated the features of the phase-resolved spectrum and pulse profile, and from these we inferred the macroscopic conductivity, the electric field parallel to the magnetic field, and the curvature radiation cutoff energy. These physical quantities are related to the spin-down rate and the γ-ray flux and therefore are relevant to the theoretical interpretation of the mode changes. We introduced a simple magnetosphere model that combines a dipole field with a strong quadrupole component. We simulated magnetic field configurations to determine the positions of the polar caps for different sets of parameters. Results. We clearly detect the previous mode changes and confirm a more recent mode change that occurred around June 2020. We provide a full set of best-fit parameters for the phase-resolved γ-ray spectrum and the pulse profile obtained in five distinct time intervals. We computed the relative variations in the best-fit parameters, finding typical flux changes between 13% and 20%. Correlations appear between the γ-ray flux and the spectral parameters, as the peak of the spectrum shifts by ∼10% toward lower energies when the flux decreases. The analysis of the pulse profile reveals that the pulsed fraction of the light curve is larger when the flux is low. Finally, the magnetosphere simulations show that some configurations could explain the observed multiwavelength variability. However, self-consistent models are required to reproduce the observed magnitudes of the mode changes.

Population health impact, cost-effectiveness, and affordability of community-based HIV treatment and monitoring in South Africa: A health economics modelling study.

Community-based delivery and monitoring of antiretroviral therapy (ART) for HIV has the potential to increase viral suppression for individual- and population-level health benefits. However, the cost-effectiveness and budget impact are needed for public health policy. We used a mathematical model of HIV transmission in KwaZulu-Natal, South Africa, to estimate population prevalence, incidence, mortality, and disability-adjusted life-years (DALYs) from 2020 to 2060 for two scenarios: 1) standard clinic-based HIV care and 2) five-yearly home testing campaigns with community ART for people not reached by clinic-based care. We parameterised model scenarios using observed community-based ART efficacy. Using a health system perspective, we evaluated incremental cost-effectiveness and net health benefits using a threshold of $750/DALY averted. In a sensitivity analysis, we varied the discount rate; time horizon; costs for clinic and community ART, hospitalisation, and testing; and the proportion of the population receiving community ART. Uncertainty ranges (URs) were estimated across 25 best-fitting parameter sets. By 2060, community ART following home testing averted 27.9% (UR: 24.3-31.5) of incident HIV infections, 27.8% (26.8-28.8) of HIV-related deaths, and 18.7% (17.9-19.7) of DALYs compared to standard of care. Adolescent girls and young women aged 15-24 years experienced the greatest reduction in incident HIV (30.7%, 27.1-34.7). In the first five years (2020-2024), community ART required an additional $44.9 million (35.8-50.1) annually, representing 14.3% (11.4-16.0) of the annual HIV budget. The cost per DALY averted was $102 (85-117) for community ART compared with standard of care. Providing six-monthly refills instead of quarterly refills further increased cost-effectiveness to $78.5 per DALY averted (62.9-92.8). Cost-effectiveness was robust to sensitivity analyses. In a high-prevalence setting, scale-up of decentralised ART dispensing and monitoring can provide large population health benefits and is cost-effective in preventing death and disability due to HIV.

The origin of the soft X-ray excess in the narrow-line Seyfert 1 galaxy SBS 1353 + 564

ABSTRACT We present for the first time the timing and spectral analyses for a narrow-line Seyfert 1 galaxy, SBS 1353 + 564, using XMM-Newton and Swift multiband observations from 2007 to 2019. Our main results are as follows: (1) The temporal variability of SBS 1353+564 is random, while the hardness ratio is relatively constant over a time span of 13 yr; (2) We find a prominent soft X-ray excess feature below 2 keV that cannot be well described by a simple blackbody component; (3) After comparing the two most prevailing models for interpreting the origin of the soft X-ray excess, we find that the relativistically smeared reflection model is unable to fit the data above 5 keV well and the X-ray spectra do not show any reflection features, such as the Fe K α emission line. However, the warm corona model can obtain a good fitting result. For the warm corona model, we try to use three different sets of spin values to fit the data and derive different best-fitting parameter sets; (4) We compare the UV/optical spectral data with the extrapolated values of the warm corona model to determine which spin value is more appropriate for this source, and we find that the warm corona model with non-spin can sufficiently account for the soft X-ray excess in SBS 1353 + 564.

The clustering of galaxies in the DESI imaging legacy surveys DR8: I. The luminosity and color dependent intrinsic clustering

In a recent study, we developed a method that models the impact of photometric redshift uncertainty on the two-point correlation function (2PCF). Using this method, we simultaneously obtained both the intrinsic clustering strength and the photometric redshift errors by fitting the projected 2PCF with two integration depths along the line-of-sight. Herein, we apply this method to the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 8 (LS DR8), which is the largest galaxy sample currently available. We separate the galaxies into 20 samples in eight redshift bins, from z = 0.1 to z = 1.0, and several z-band absolute magnitude bins, with Mz ≤ −20. These galaxies are further divided into red and blue subsamples according to their M r 0.5 - M z 0.5 colors. We measure the projected 2PCFs for all these galaxy subsamples and fit them using our photometric redshift 2PCF model. We find that the photometric redshift errors are smaller in the red subsamples than in the overall population. In contrast, some systematic photometric redshift errors exist in the blue subsamples, such that some of the subsamples show a significantly enhanced 2PCF on large scales. Therefore, separately focusing only on the red subsamples and on all the subsamples, we find that the biases of the galaxies in these subsamples exhibit clear color, redshift, and luminosity dependencies; the brighter red galaxies at higher redshift are more biased than their bluer and low-redshift counterparts. Apart from the best-fit set of parameters, σz and b, from this state-of-the-art photometric redshift survey, we obtain high-precision intrinsic clustering measurements for these 40 red- and all-galaxy subsamples. These measurements, on large and small scales, hold important information regarding cosmology and galaxy formation that will be used in our subsequent probes in this series.

Cervical Cancer Elimination with Single-Visit Screening and Treatment Strategies in South Africa: Modeled Estimates in the Context of High HIV Prevalence

Background: In settings with high HIV prevalence, cervical cancer incidence rates are up to six-fold higher than the global average of 13.1/100,000 women-years. To achieve global cervical cancer elimination, it is critical to identify scalable prevention strategies that account for HIV-associated cancer risk and address barriers to healthcare while minimizing overtreatment. Methods: We developed a dynamic model of HIV-HPV co-infection and disease progression, which we calibrated to KwaZulu-Natal, South Africa. Our baseline scenario reflects current practice of HPV vaccination, cytology-based screening, and colposcopy triage. We evaluated nine comparator scenarios with increased vaccination coverage and one-time or repeat screening with single-visit strategies: HPV DNA testing, HPV genotyping, Automated Visual Evaluation (AVE), and HPV DNA with AVE triage. For each scenario, we simulated cancer incidence from 2021-2120 using the 25 best-fitting parameter sets. We present the median and range of model output. Findings: Continuing current cervical cancer and HIV prevention strategies is projected to decrease cervical cancer incidence by 87%, from an age-standardized rate per 100,000 women of 80.4 (range 58·2-112·1) to 10·7 (4·2-29·9) in 2120. Scaling up single-visit strategies result in incidence rates 29-34% lower in 2030 relative to the baseline scenario. Elimination (incidence <4/100,000) could be achieved with HPV DNA testing in 2095 and with AVE in 2114. HPV DNA with AVE triage optimizes the tradeoff between cancer cases averted and overtreatment. Interpretation: Single-visit screening strategies could avert a substantial burden of cervical cancer and accelerate progress towards elimination in high-burden settings. Funding: National Institutes of Health, World Health Organization. Declaration of Interest: NM receives research funding from Merck Ltd. RVB declares support from the National Institutes of Health and the Bill and Melinda Gates Foundation, and funding from Regeneron Pharmaceuticals for manuscript writing and abstract submission outside the submitted work. No authors have conflicts to declare.

Cost-effectiveness of maternal pertussis immunization: Implications of a dynamic transmission model for low- and middle-income countries

ObjectiveThis study evaluates the cost-effectiveness of maternal acellular pertussis (aP) immunization in low- and middle-income countries using a dynamic transmission model. MethodsWe developed a dynamic transmission model to simulate the impact of infant vaccination with whole-cell pertussis (wP) vaccine with and without maternal aP immunization. The model was calibrated to Brazilian surveillance data and then used to project health outcomes and costs under alternative strategies in Brazil, and, after adjusting model parameter values to reflect their conditions, in Nigeria and Bangladesh. The primary measure of cost-effectiveness is incremental cost (2014 USD) per disability-adjusted life-year (DALY). ResultsThe dynamic model shows that maternal aP immunization would be cost-effective in Brazil, a middle-income country, under the base-case assumptions, but would be very expensive at infant vaccination coverage in and above the threshold range necessary to eliminate the disease (90–95%). At 2007 infant coverage (DTP1 90%, DTP3 61% at 1 year of age), maternal immunization would cost < $4,000 per DALY averted. At high infant coverage, such as Brazil in 1996 (DTP1 94%, DTP3 74% at 1 year), cost/DALY increases to $1.27 million. When the model’s time horizon was extended from 2030 to 2100, cost/DALY increased under both infant coverage levels, but more steeply with high coverage. The results were moderately sensitive to discount rate, maternal vaccine price, and maternal aP coverage and were robust using the 100 best-fitting parameter sets. Scenarios representing low-income countries showed that maternal aP immunization could be cost-saving in countries with low infant coverage, such as Nigeria, but very expensive in countries, such as Bangladesh, with high infant coverage. ConclusionA dynamic model, which captures the herd immunity benefits of pertussis vaccination, shows that, in low- and middle-income countries, maternal aP immunization is cost-effective when infant vaccination coverage is moderate, even cost-saving when it is low, but not cost-effective when coverage levels pass 90–95%.

Bayesian calibration and sensitivity analysis of heat transfer models for fire insulation panels

A common approach to assess the performance of fire insulation panels is the component additive method (CAM). The parameters of the CAM are based on the temperature-dependent thermal material properties of the panels. These material properties can be derived by calibrating finite element heat transfer models using experimentally measured temperature records. In the past, the calibration of the material properties was done manually by trial and error approaches, which was inefficient and prone to error.In this contribution, the calibration problem is reformulated in a probabilistic setting and solved using the Bayesian model calibration framework. This not only gives a set of best-fit parameters but also confidence bounds on the latter. To make this framework feasible, the procedure is accelerated through the use of advanced surrogate modelling techniques: polynomial chaos expansions combined with principal component analysis. This surrogate modelling technique additionally allows one to conduct a variance-based sensitivity analysis at no additional cost by giving access to the Sobol’ indices. The calibration is finally validated by using the calibrated material properties to predict the temperature development in different experimental setups.

Development and Calibration of a Dynamic HIV Transmission Model for 6 US Cities.

Background. Heterogeneity in HIV microepidemics across US cities necessitates locally oriented, combination implementation strategies to prioritize resources. We calibrated and validated a dynamic, compartmental HIV transmission model to establish a status quo treatment scenario, holding constant current levels of care for 6 US cities. Methods. Built off a comprehensive evidence synthesis, we adapted and extended a previously published model to replicate the transmission, progression, and clinical care for each microepidemic. We identified a common set of 17 calibration targets between 2012 and 2015 and used the Morris method to select the most influential parameters for calibration. We then applied the Nelder-Mead algorithm to iteratively calibrate the model to generate 2000 best-fitting parameter sets. Finally, model projections were internally validated with a series of robustness checks and externally validated against published estimates of HIV incidence, while the face validity of 25-year projections was assessed by a Scientific Advisory Committee (SAC). Results. We documented our process for model development, calibration, and validation to maximize its transparency and reproducibility. The projected outcomes demonstrated a good fit to calibration targets, with a mean goodness-of-fit ranging from 0.0174 (New York City [NYC]) to 0.0861 (Atlanta). Most of the incidence predictions were within the uncertainty range for 5 of the 6 cities (ranging from 21% [Miami] to 100% [NYC]), demonstrating good external validity. The face validity of the long-term projections was confirmed by our SAC, showing that the incidence would decrease or remain stable in Atlanta, Los Angeles, NYC, and Seattle while increasing in Baltimore and Miami. Discussion. This exercise provides a basis for assessing the incremental value of further investments in HIV combination implementation strategies tailored to urban HIV microepidemics.

Validation and uncertainty analysis of a stormwater biofilter treatment model for faecal microorganisms

Stormwater biofilters, also known as rain gardens or bioretention systems, are effective stormwater treatment systems. This paper presents the validation, sensitivity and uncertainty analyses of a model for microbial removal in stormwater biofilters. The model, previously developed based on a rather limited laboratory study, was fully validated using the data collected in extensive laboratory experiments and field tests. The lab-scale and field-scale systems used for validation were of various designs (e.g., system size, plant type, media type), and have been operated under a wide range of operational conditions (e.g., length of antecedent dry period, and the inflow volume and concentration). For each tested biofilter design, the predicted E. coli concentrations in biofilters' outflow showed relatively good agreement with the measured ones: e.g., Nash-Sutcliffe Efficiency (Ec) ranged from 0.50 to 0.60 for the laboratory tests, and Ec = 0.55 for the field system. The results from sensitivity analysis confirmed the significance of adsorption and desorption processes, and also revealed the impact of temperature on microbial die-off (which was not fully represented in the model development stage). Finally, parameter transferability from one system to another with similar design was examined, achieving generally promising Ec values (0.04–0.56 with the best-fit parameter set for the other system; maximum value: 0.46–0.63) and acceptable uncertainties (intersection between prediction uncertainty band and observation: 50%–97%). Most importantly, the prediction of E. coli outflow concentrations from the field system was reasonably good when laboratory-determined parameter values were adopted: with the best-fit parameter set for the lab-scale system, Ec = 0.39; maximum Ec = 0.55; intersection between prediction and observation = 83%. These results suggested that the very rare biofilter model for microbial removal could provide reliable prediction for large scale field systems, by simply calibrating parameters with limited laboratory-scale experiments.

Multiobjective Calibration of Disease Simulation Models Using Gaussian Processes.

Background. Developing efficient procedures of model calibration, which entails matching model predictions to observed outcomes, has gained increasing attention. With faithful but complex simulation models established for cancer diseases, key parameters of cancer natural history can be investigated for possible fits, which can subsequently inform optimal prevention and treatment strategies. When multiple calibration targets exist, one approach to identifying optimal parameters relies on the Pareto frontier. However, computational burdens associated with higher-dimensional parameter spaces require a metamodeling approach. The goal of this work is to explore multiobjective calibration using Gaussian process regression (GPR) with an eye toward how multiple goodness-of-fit (GOF) criteria identify Pareto-optimal parameters. Methods. We applied GPR, a metamodeling technique, to estimate colorectal cancer (CRC)-related prevalence rates simulated from a microsimulation model of CRC natural history, known as the Colon Modeling Open Source Tool (CMOST). We embedded GPR metamodels within a Pareto optimization framework to identify best-fitting parameters for age-, adenoma-, and adenoma staging-dependent transition probabilities and risk factors. The Pareto frontier approach is demonstrated using genetic algorithms with both sum-of-squared errors (SSEs) and Poisson deviance GOF criteria. Results. The GPR metamodel is able to approximate CMOST outputs accurately on 2 separate parameter sets. Both GOF criteria are able to identify different best-fitting parameter sets on the Pareto frontier. The SSE criterion emphasizes the importance of age-specific adenoma progression parameters, while the Poisson criterion prioritizes adenoma-specific progression parameters. Conclusion. Different GOF criteria assert different components of the CRC natural history. The combination of multiobjective optimization and nonparametric regression, along with diverse GOF criteria, can advance the calibration process by identifying optimal regions of the underlying parameter landscape.

Cross sections of α -induced reactions slightly below doubly magic Ca40 from the statistical model

New experimental data for the $^{38}$Ar($\alpha$,n)$^{41}$Ca and $^{38}$Ar($\alpha$,p)$^{41}$K reactions were used to find a best-fit set of parameters for statistical model calculations. The very good agreement between the experimental data and the best-fit calculation confirms the applicability of the statistical model for nuclei in the vicinity of the doubly-magic $^{40}$Ca despite of their relatively low level densities. The present study investigates the sensitivities and finds that the $\alpha$-nucleus and the nucleon-nucleus potentials are the most important ingredients for the calculation of ($\alpha$,n) and ($\alpha$,p) reactions in the statistical model. Furthermore, the width fluctuation correction plays an essential role in the peculiar case of $^{38}$Ar. The best-fit parameters from $^{38}$Ar are applied to the mirror nucleus $^{38}$Ca and the neighboring $^{36}$Ar and $^{40}$Ar nuclei. For $^{38}$Ca this results in an astrophysical reaction rate of the $^{38}$Ca($\alpha$,p)$^{41}$Sc reaction which has a flatter temperature dependence compared to all previous calculations. For $^{40}$Ar a better reproduction of $^{40}$Ar($\alpha$,p)$^{43}$K data from literature is obtained. The disagreement between calculation and an early experimental data point for the $^{36}$Ar($\alpha$,p)$^{39}$K reaction persists.

PUSHing core-collapse simulations to explosion

We report on the PUSH method for artificially triggering core-collapse supernova explosions of massive stars in spherical symmetry. The PUSH method increases the energy deposition in the gain region proportionally to the heavy flavor neutrino fluxes.We summarize the parameter dependence of the method and calibrate PUSH to reproduce SN 1987A observables. We identify a best-fit progenitor and set of parameters that fit the explosion properties of SN 1987A, assuming 0.1 M⊙ of fallback. For the explored progenitor range of 18-21 M⊙, we find correlations between explosion properties and the compactness of the progenitor model.

Simulating tubulin-associated unit transport in an axon: using bootstrapping for estimating confidence intervals of best-fit parameter values obtained from indirect experimental data.

In this paper, we first develop a model of axonal transport of tubulin-associated unit (tau) protein. We determine the minimum number of parameters necessary to reproduce published experimental results, reducing the number of parameters from 18 in the full model to eight in the simplified model. We then address the following questions: Is it possible to estimate parameter values for this model using the very limited amount of published experimental data? Furthermore, is it possible to estimate confidence intervals for the determined parameters? The idea that is explored in this paper is based on using bootstrapping. Model parameters were estimated by minimizing the objective function that simulates the discrepancy between the model predictions and experimental data. Residuals were then identified by calculating the differences between the experimental data and model predictions. New, surrogate 'experimental' data were generated by randomly resampling residuals. By finding sets of best-fit parameters for a large number of surrogate data the histograms for the model parameters were produced. These histograms were then used to estimate confidence intervals for the model parameters, by using the percentile bootstrap. Once the model was calibrated, we applied it to analysing some features of tau transport that are not accessible to current experimental techniques.

Mars Express Lithium Ion Batteries Performance Analysis

Now more than 12 years in orbit, Mars Express battery telemetry during some of the deepest discharge cycles has been analysed with the help of the ESTEC lithium ion cell model. The best-fitting model parameter sets were then used to predict the energy that is expected to be available before the battery voltage drops below the minimum value that can support the power bus. This allows mission planners to determine what future power profiles could be supported without risk of entering safe mode. It also gives some more insights into the ageing properties of these batteries.

Application of an evolutionary algorithm for parameter optimization in a gully erosion model

Herein we demonstrate how to use model optimization to determine a set of best-fit parameters for a landform model simulating gully incision and headcut retreat. To achieve this result we employed the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), an iterative process in which samples are created based on a distribution of parameter values that evolve over time to better fit an objective function. CMA-ES efficiently finds optimal parameters, even with high-dimensional objective functions that are non-convex, multimodal, and non-separable. We ran model instances in parallel on a high-performance cluster, and from hundreds of model runs we obtained the best parameter choices. This method is far superior to brute-force search algorithms, and has great potential for many applications in earth science modeling. We found that parameters representing boundary conditions tended to converge toward an optimal single value, whereas parameters controlling geomorphic processes are defined by a range of optimal values.

Investigating the uncertainty and transferability of parameters in SWAT model under climate change

ABSTRACTThere is an implicit assumption in most work that the parameters calibrated based on observations remain valid for future climatic conditions. However, this might not be true due to parameter instability. This paper investigates the uncertainty and transferability of parameters in a hydrological model under climate change. Parameter transferability is investigated with three parameter sets identified for different climatic conditions, which are: wet, intermediate and dry. A parameter set based on the baseline period (1961–1990) is also investigated for comparison. For uncertainty analysis, a k-simulation set approach is proposed instead of employing the traditional optimization method which uses a single best-fit parameter set. The results show that the parameter set from the wet sub-period performs the best when transferred into wet climate condition, while the parameter set from the baseline period is the most appropriate when transferred into dry climate condition. The largest uncertainty of simulated daily high flows for 2011–2040 is from the parameter set trained in the dry sub-period, while that of simulated daily medium and low flows lies in the parameter set from the intermediate calibration sub-period. For annual changes in the future period, the uncertainty with the parameter set from the intermediate sub-period is the largest, followed by the wet sub-period and dry sub-period. Compared with high and medium flows/runoffs, the uncertainty of low flows/runoffs is much smaller for both simulated daily flows and annual runoffs. For seasonal runoffs, the largest uncertainty is from the intermediate sub-period, while the smallest is from the dry sub-period. Apart from that, the largest uncertainty can be observed for spring runoffs and the lowest one for autumn runoffs. Compared with the traditional optimization method, the k-simulation set approach shows many more advantages, particularly being able to provide uncertainty information to decision support for watershed management under climate change.EDITOR Z.W. Kundzewicz ASSOCIATE EDITOR not assigned

Cardiac Length-Dependent Activation: Weak Binding Hypothesis Tested by a Computational Sarcomere Model

Experiments suggest that length changes alter activation in cardiac sarcomeres within a few milliseconds (Mateja & deTombe, 2012). Thus, the mechanism producing length-dependent activation must occur early in the contractile cycle, such as during the formation of weakly bound crossbridges. We hypothesized that a decrease in the energy required to form weak crossbridges would lead to greater probability of their formation. Such decrease in energy at longer sarcomere lengths could occur via reduction in both: (1) radial distance a crossbridge stretches to attach to actin, due to lattice spacing; (2) radial elastic crossbridge stiffness, due to influence of sarcomere length on modulators such as titin, myosin light chains, or myosin binding protein-C. We have previously developed a compact kinetic model of cardiac sarcomere dynamics (Hunter, BPS Meeting 2015). Parameters in this model were adjusted to produce the best fit with five experimental measures at constant sarcomere length (from others’ published data): (1) F-pCa relation, (2) alteration in F-pCa with addition of NEM-S1 strong crossbridges, (3) relation between kinetics of tension recovery and calcium concentration [k(TR)-pCa relation], (4) alteration in k(TR)-pCa with addition of NEM-S1, (5) shape of F-Ca loops during twitches. All five of these sets of experimental data were reasonably matched by the model using the best-fit set of parameters. Holding all other best-fit parameters constant, we then modified just the binding constant for weak crossbridges. An increased binding constant (due to lower energy to form a weak crossbridge) reproduced both of the following effects of increased sarcomere length: (1) shifted mid-point of F-pCa relation to lower [Ca++], (2) increased maximum force at saturating [Ca++]. Both of these experimental effects of increased sarcomere length are well known from published data (Dobesh, Konhilas, deTombe, 2002).

Cobalt(II) and copper(II) assembling through a functionalized oxamate-type ligand

Two new metal complexes of formula {[Co(Hpcpa)(H2O)3]n·3/2nH2O} (1) and [Cu2(MeHpcpa)4(MeOH)2]·H2O·3.68 MeOH (2) [H3pcpa=N-(4-carboxyphenyl)oxamic acid and MeH2pcpa=methyl ester derivative of H3pcpa] have been synthesized and their structures determined by X-ray diffraction. 1 is a neutral zigzag chain of cobalt(II) ions bridged by Hpcpa2− ligands exhibiting the bidentate/monodentate coordination mode. Each cobalt(II) ion is six-coordinate with three mer positioned water molecules, two oxamate-oxygens from a Hpcpa2− ligand and a carboxylate-oxygen from another Hpcpa2− group building a somewhat distorted octahedral surrounding. The intrachain cobalt–cobalt separation is 11.326(2)Å. The structure of 2 consists of discrete syn–syn tetracarboxylate-bridged dicopper(II) units of the paddle wheel-type, the oxamate fragment of the MeHpcpa ligand being not involved in the coordination. Each copper(II) ion is five-coordinate in a distorted square pyramidal environment with four carboxylate-oxygens in the basal plane and a methanol molecule in the apical position. The intradimer copper–copper separation is 2.5974(11)Å. The magnetic properties of 1 and 2 have been investigated in the temperature range 1.9–300K. The magnetic behavior of 1 corresponds to that of a magnetically isolated high-spin cobalt(II) ion with an important orbital contribution. The analysis of its magnetic data through the Hamiltonian, H=−αλLCo·SCo+Δ[LZCo2−2/3]+βH(−αLCo+geSCo) leads to the following set of best-fit parameters: α=1.28(1), λ=−160(5)cm−1 and |Δ|=400(20)cm−1. The magnetic properties of 2 show the occurrence of a strong antiferromagnetic interaction between the two local spin doublets which lead to a ground singlet spin state [J=−315(2)cm−1, the Hamiltonian being defined as H=−JSA·SB]. This value is in the upper range of those previously reported for the large family of tetracarboxylate-bridged dicopper(II) complexes, the exchange pathway being provided by the four carboxylate bridges in the syn–syn conformation mode.