Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model

Abstract. Global, spatially and temporally explicit estimates of carbon and water fluxes derived from empirical up-scaling eddy covariance measurements would constitute a new and possibly powerful data stream to study the variability of the global terrestrial carbon and water cycle. This paper introduces and validates a machine learning approach dedicated to the upscaling of observations from the current global network of eddy covariance towers (FLUXNET). We present a new model TRee Induction ALgorithm (TRIAL) that performs hierarchical stratification of the data set into units where particular multiple regressions for a target variable hold. We propose an ensemble approach (Evolving tRees with RandOm gRowth, ERROR) where the base learning algorithm is perturbed in order to gain a diverse sequence of different model trees which evolves over time. We evaluate the efficiency of the model tree ensemble (MTE) approach using an artificial data set derived from the Lund-Potsdam-Jena managed Land (LPJmL) biosphere model. We aim at reproducing global monthly gross primary production as simulated by LPJmL from 1998–2005 using only locations and months where high quality FLUXNET data exist for the training of the model trees. The model trees are trained with the LPJmL land cover and meteorological input data, climate data, and the fraction of absorbed photosynthetic active radiation simulated by LPJmL. Given that we know the "true result" in the form of global LPJmL simulations we can effectively study the performance of the MTE upscaling and associated problems of extrapolation capacity. We show that MTE is able to explain 92% of the variability of the global LPJmL GPP simulations. The mean spatial pattern and the seasonal variability of GPP that constitute the largest sources of variance are very well reproduced (96% and 94% of variance explained respectively) while the monthly interannual anomalies which occupy much less variance are less well matched (41% of variance explained). We demonstrate the substantially improved accuracy of MTE over individual model trees in particular for the monthly anomalies and for situations of extrapolation. We estimate that roughly one fifth of the domain is subject to extrapolation while MTE is still able to reproduce 73% of the LPJmL GPP variability here. This paper presents for the first time a benchmark for a global FLUXNET upscaling approach that will be employed in future studies. Although the real world FLUXNET upscaling is more complicated than for a noise free and reduced complexity biosphere model as presented here, our results show that an empirical upscaling from the current FLUXNET network with MTE is feasible and able to extract global patterns of carbon flux variability.
A systems dynamics model for the urban travel system

This paper describes the development of a model architecture based on systems dynamics and econometrics. The purpose of the system of models is to simulate the medium­ and long­term effects of urban transport policies with reference to sustainable travel. Three models are presented successively with some results from simulation. The first model relates to the regulation of public transport finance and allows for the constraint of the scarcity of public funds. The second is a modal split model based on price­time modelling. The third is a combined assignment and time of departure choice model based on a queuing representation of congestion. Finally, the coupling between the last two models is described.
Bayes linear analysis of imprecision in computer models, with application to understanding galaxy formation.

Imprecision arises naturally in the context of computer models and their relation to reality. An imprecise treatment of general computer models is presented, illustrated with an analysis of a complex galaxy formation simulation known as Galform. The analysis involves several di! erent types of uncertainty, one of which (the Model Discrepancy) comes directly from expert elicitation regarding the deficiencies of the model. The Model Discrepancy is therefore treated within an Imprecise framework to reflect more accurately the beliefs of the expert concerning the discrepancy between the model and reality. Due to the conceptual complexity and computationally intensive nature of such a Bayesian imprecise uncertainty analysis, Bayes Linear Methodology is employed which requires consideration of only expectations and variances of all uncertain quantities. Therefore incorporating an Imprecise treatment within a Bayes Linear analysis is shown to be relatively straightforward. The impact of an imprecise assessment on the input space of the model is determined through the use of an Implausibility measure.
Global magnetohydrodynamical models of turbulence in protoplanetary disks. I. A cylindrical potentia

Aims. We present global 3D MHD simulations of disks of gas and solids, aiming at developing models that can be used to study various scenarios of planet formation and planet-disk interaction in turbulent accretion disks. A second goal is to demonstrate that Cartesian codes are comparable to cylindrical and spherical ones in handling the magnetohydrodynamics of the disk simulations while offering advantages, such as the absence of a grid singularity, for certain applications, e.g., circumbinary disks and disk-jet simulations. Methods. We employ the PENCIL CODE, a 3D high-order finite-difference MHD code using Cartesian coordinates. We solve the equations of ideal MHD with a local isothermal equation of state. Planets and stars are treated as particles evolved with an N-body scheme. Solid boulders are treated as individual superparticles that couple to the gas through a drag force that is linear in the local relative velocity between gas and particle. Results. We find that Cartesian grids are well-suited for accretion disk problems. The disk-in-a-box models based on Cartesian grids presented here develop and sustain MHD turbulence, in good agreement with published results achieved with cylindrical codes. Models without an inner boundary do not show the spurious build-up of magnetic pressure and Reynolds stress seen in the models with boundaries, but the global stresses and alpha viscosities are similar in the two cases. We investigate the dependence of the magnetorotational instability on disk scale height, finding evidence that the turbulence generated by the magnetorotational instability grows with thermal pressure. The turbulent stresses depend on the thermal pressure obeying a power law of 0.24 ± 0.03, compatible with the value of 0.25 found in shearing box calculations. The ratio of Maxwell to Reynolds stresses decreases with increasing temperature, dropping from 5 to 1 when the sound speed was raised by a factor 4, maintaing the same field strength. We also study the dynamics of solid boulders in the hydromagnetic turbulence, by making use of 10 6 Lagrangian particles embedded in the Eulerian grid. The effective diffusion provided by the turbulence prevents settling of the solids in a infinitesimally thin layer, forming instead a layer of solids of finite vertical thickness. The measured scale height of this diffusion-supported layer of solids implies turbulent vertical diffusion coefficients with globally averaged Schmidt numbers of 1.0 ± 0.2 for a model with a ≈ 10 -3 and 0.78 ± 0.06 for a model with a ≈ 10 -1 . That is, the vertical turbulent diffusion acting on the solids phase is comparable to the turbulent viscosity acting on the gas phase. The average bulk density of solids in the turbulent flow is quite low (pp = 6.0 x 10 -11 kg m -3 ), but in the high pressure regions, significant overdensities are observed, where the solid-to-gas ratio reached values as great as 85, corresponding to 4 orders of magnitude higher than the initial interstellar value of 0.01.
The Determinants of the Variability of Stock Market Prices

The most familiar interpretation for the large and unpredictable swings that characterize common stock price indices is that price changes represent the efficient discounting of "new information" It is remarkable given the popularity of this interpretation that it has never been established what this information is about. Recent work by Shiller, and Stephen LeRoy and Richard Porter, has shown evidence that the variability of stock price indices cannot be accounted for by information regarding future dividends since dividends just do not seem to vary enough to justify the price movement. These studies assume a constant discount factor. In this paper, we consider whether the variability of stock prices can be attributed to information regarding discount factors (i.e., real interest rates), which are in turn related to current and future levels of economic activity. The appropriate discount factor to be applied to dividends which are received k years from today is the marginal rate of substitution between consumption today and consumption k periods from today, We use historical data on per capita consumption from 1890-1979 to estimate the realized value of these marginal rates of substitution. Theoretically, as LeRoy and C. J. La Civita have also noted independently of us, consumption variability may induce stock price variability whose magnitude depends on the degree of risk aversion.
Psychomotor slowing as a predictor of fluoxetine nonresponse in depressed outpatients.

OBJECTIVE This study examined the utility of baseline psychomotor speed, measured with neuropsychological tests, to predict fluoxetine response in moderately depressed outpatients. The authors hypothesized that since psychomotor slowing in depressed patients has been linked to reduced dopaminergic neurotransmission, patients with slowing would be unresponsive to fluoxetine, a selective serotonin reuptake inhibitor. METHOD After baseline neuropsychological testing, patients were treated openly with fluoxetine for 12 weeks. Thirty-seven patients completed the trial. RESULTS Compared to the 25 patients who responded, the 12 patients who did not respond to fluoxetine exhibited significantly poorer performance in verbal fluency on the Controlled Oral Word Association Test FAS and in color naming on the Stroop Color and Word Test. In addition, the nonresponders tended to perform worse than the responders on the Stroop Color and Word Test reading subtest and the WAIS-III digit symbol subtest. Differential treatment response was specific to psychomotor speed because responders and nonresponders did not perform differently on tasks of executive functioning, attention, visuospatial functioning, or verbal intelligence. CONCLUSIONS Psychomotor slowing may identify a subgroup of depressed patients who have a dopaminergic deficit that is unresponsive to fluoxetine monotherapy and who should therefore receive an alternative treatment.
The Impact of Human Resource Management Practices on Turnover, Productivity, and Corporate Financial Performance

This study comprehensively evaluated the links between systems of High Performance Work Practices and firm performance. Results based on a national sample of nearly one thousand firms indicate that these practices have an economically and statistically significant impact on both intermediate employee outcomes (turnover and productivity) and short- and long-term measures of corporate financial performance. Support for predictions that the impact of High Performance Work Practices on firm performance is in part contingent on their interrelationships and links with competitive strategy was limited. The impact of human resource management (HRM) policies and prac
Dolutegravir Plus Two Nucleoside Reverse Transcriptase Inhibitors versus Efavirenz Plus Two Nucleoside Reverse Transcriptase Inhibitors As Initial Antiretroviral Therapy for People with HIV: A Systematic Review

Background Dolutegravir (DTG) is a once-daily unboosted second-generation integrase-inhibitor that along with two nucleoside reverse transcriptase inhibitors is one of several regimens recommended by the United States, United Kingdom and European Union for first-line antiretroviral treatment of people with HIV infection. Our objective was to review the evidence for the efficacy and safety of DTG-based first-line regimens compared to efavirenz (EFV)-based regimens. Methods We conducted a systematic review. We comprehensively searched a range of databases as well as conference abstracts and a trials registry. We used Cochrane methods in screening and data collection and assessed each study’s risk of bias with the Cochrane tool. We meta-analyzed data using a fixed-effects model. We used GRADE to assess evidence quality. Results From 492 search results, we identified two randomized controlled trials, reported in five peer-reviewed articles and one conference abstract. One trial tested two DTG-based regimens (DTG + abacavir (ABC) + lamivudine (3TC) or DTG + tenofovir + emtricitabine) against an EFV-based regimen (EFV+ ABC+3TC). The other trial tested DTG+ABC+3TC against EFV+ABC+3TC. In meta-analysis, DTG-containing regimens were superior to EFV-containing regimens at 48 weeks and at 96 weeks (RR = 1.10, 95% CI 1.04–1.16; and RR = 1.12, 95% CI 1.04–1.21, respectively). In one trial, the DTG-containing regimen was superior at 144 weeks (RR = 1.13, 95% CI 1.02–1.24). DTG-containing regimens were superior in reducing treatment discontinuation compared to those containing EFV at 96 weeks and at 144 weeks (RR = 0.27, 95% CI 0.15–0.50; and RR = 0.28, 95% CI 0.16–0.48, respectively). Risk of serious adverse events was similar in each regimen at 96 weeks (RR = 1.15, 95% CI 0.80–1.63) and 144 weeks (RR = 0.93, 95% CI 0.68–1.29). Risk of bias was moderate overall, as was GRADE evidence quality. Conclusions DTG-based regimens should be considered in future World Health Organization guidelines for initial HIV treatment.
Constrained Regression for Interval-Valued Data

Current regression models for interval-valued data do not guarantee that the predicted lower bound of the interval is always smaller than its upper bound. We propose a constrained regression model that preserves the natural order of the interval in all instances, either for in-sample fitted intervals or for interval forecasts. Within the framework of interval time series, we specify a general dynamic bivariate system for the upper and lower bounds of the intervals. By imposing the order of the interval bounds into the model, the bivariate probability density function of the errors becomes conditionally truncated. In this context, the ordinary least squares (OLS) estimators of the parameters of the system are inconsistent. Estimation by maximum likelihood is possible but it is computationally burdensome due to the nonlinearity of the estimator when there is truncation. We propose a two-step procedure that combines maximum likelihood and least squares estimation and a modified two-step procedure that combines maximum likelihood and minimum-distance estimation. In both instances, the estimators are consistent. However, when multicollinearity arises in the second step of the estimation, the modified two-step procedure is superior at identifying the model regardless of the severity of the truncation. Monte Carlo simulations show good finite sample properties of the proposed estimators. A comparison with the current methods in the literature shows that our proposed methods are superior by delivering smaller losses and better estimators (no bias and low mean squared errors) than those from competing approaches. We illustrate our approach with the daily interval of low/high SP500 returns and find that truncation is very severe during and after the financial crisis of 2008, so OLS estimates should not be trusted and a modified two-step procedure should be implemented. Supplementary materials for this article are available online.
Stochastic and reactive methods for the determination of optimal calibration intervals

The length of calibration intervals or measurement instrumentations can be determined by means of several techniques. In this paper, three different methods are compared for the establishment of optimal calibration interval of atomic clocks. The first one is based on a stochastic model and provides the estimation of the calibration interval also in the transient situation, while the others, attain to the class of the so-called reactive methods, which determine the value of the optimal calibration interval on the basis of the last calibration outcomes. Algorithms have been applied to experimental data and obtained results have been compared in order to determine the most effective technique. Since the analyzed reactive methods presents a presents a large transient time, a new algorithm is proposed and applied to the available data.
Geoscientific Model Development The global chemistry transport model TM 5 : description and evaluation of the tropospheric chemistry version 3 . 0

We present a comprehensive description and benchmark evaluation of the tropospheric chemistry version of the global chemistry transport model TM5 (Tracer Model 5, version TM5-chem-v3.0). A full description is given concerning the photochemical mechanism, the interaction with aerosol, the treatment of the stratosphere, the wet and dry deposition parameterizations, and the applied emissions. We evaluate the model against a suite of ground-based, satellite, and aircraft measurements of components critical for understanding global photochemistry for the year 2006. The model exhibits a realistic oxidative capacity at a global scale. The methane lifetime is ∼ 8.9 years with an associated lifetime of methyl chloroform of 5.86 years, which is similar to that derived using an optimized hydroxyl radical field. The seasonal cycle in observed carbon monoxide (CO) is well simulated at different regions across the globe. In the Northern Hemisphere CO concentrations are underestimated by about 20 ppbv in spring and 10 ppbv in summer, which is related to missing chemistry and underestimated emissions from higher hydrocarbons, as well as to uncertainties in the Correspondence to: V. Huijnen (huijnen@knmi.nl) seasonal variation of CO emissions. The model also captures the spatial and seasonal variation in formaldehyde tropospheric columns as observed by SCIAMACHY. Positive model biases over the Amazon and eastern United States point to uncertainties in the isoprene emissions as well as its chemical breakdown. Simulated tropospheric nitrogen dioxide columns correspond well to observations from the Ozone Monitoring Instrument in terms of its seasonal and spatial variability (with a global spatial correlation coefficient of 0.89), but TM5 fields are lower by 25–40%. This is consistent with earlier studies pointing to a high bias of 0–30% in the OMI retrievals, but uncertainties in the emission inventories have probably also contributed to the discrepancy. TM5 tropospheric nitrogen dioxide profiles are in good agreement (within∼ 0.1 ppbv) with in situ aircraft observations from the INTEX-B campaign over (the Gulf of) Mexico. The model reproduces the spatial and seasonal variation in background surface ozone concentrations and tropospheric ozone profiles from the World Ozone and Ultraviolet Radiation Data Centre to within 10 ppbv, but at several tropical stations the model tends to underestimate ozone in the free troposphere. Published by Copernicus Publications on behalf of the European Geosciences Union. 446 V. Huijnen et al.: The global chemistry transport model TM5 The presented model results benchmark the TM5 tropospheric chemistry version, which is currently in use in several international cooperation activities, and upon which future model improvements will take place.
CloudSat observations of cloud-type distribution over the Indian summer monsoon region

Abstract. The three-dimensional distribution of various cloud types over the Indian summer monsoon (ISM) region using five years (2006–2010) of CloudSat observations during June-July-August-September months is discussed for the first time. As the radiative properties, latent heat released and microphysical properties of clouds differ largely depending on the cloud type, it becomes important to know what types of clouds occur over which region. In this regard, the present analysis establishes the three-dimensional distribution of frequency of occurrence of stratus (St), stratocumulus (Sc), nimbostratus (Ns), cumulus (Cu), altocumulus (Ac), altostratus (As), cirrus (Ci) and deep convective (DC) clouds over the ISM region. The results show that the various cloud types preferentially occur over some regions of the ISM, which are consistent during all the years of observations. It is found that the DC clouds frequently occur over northeast of Bay of Bengal (BoB), Ci clouds over a wide region of south BoB–Indian peninsula–equatorial Indian Ocean, and Sc clouds over the north Arabian Sea. Ac clouds preferentially occur over land, and a large amount of As clouds are found over BoB. The occurrence of both St and Ns clouds over the study region is much lower than all other cloud types.The interannual variability of all these clouds including their vertical distribution is discussed. It is envisaged that the present study opens up possibilities to quantify the feedback of individual cloud type in the maintenance of the ISM through radiative forcing and latent heat release.
The Importance of Interstate Highways to Economic Development in Nebraska

This chapter focuses on one aspect of economic growth: the post-construction effect of interstate highways on income and sales expansion. Using data for all Nebraska and Iowa counties, interstate highways are found to have the most positive economic impact on areas with larger populations; small areas are not likely to experience much more than short-term gains. This finding has significant implications for the planned construction of a north-south, four-lane highway in Nebraska. The route of such a highway should be selected only after a careful look at the ability of local areas to capitalize on highway-induced growth impulses.
Andrographolide Suppress Tumor Growth by Inhibiting TLR4/NF-κB Signaling Activation in Insulinoma

Insulinomas are rare tumors, and approximately 10% of insulinomas are malignant. Accumulating evidence has implicated that we still lack effective therapy to treat the patients who are diagnosed with rare malignant insulinoma. Previous studies have reported that Andrographolide (Andro) could inhibit cell cycle progression, reduce cell invasion and induce cell apoptosis in many common cancer cells. However, the effects of andro are cell type-dependent. So we emplored the β-TC-6 cells and the RIP1-Tag2 transgenic mouse model of endogenously growing insulinoma model to elucidate the possible anti-cancer effect of Andro on insulinoma, an uncommon type of malignant cancers in this study. Our experiments revealed that Andro significantly inhibited tumor growth at both the early-stage and the advanced-stage of insulinoma through targeting the TLR4/NF-κB signaling pathway. This work initially provides the evidence that the TLR4/NF-κB signaling pathway might be vital as a potential therapeutic target, and also indispensable in Andro-mediated anti-cancer effect in insulinoma.
Stability Analysis of Fuzzy Systems: membership-shape and polynomial approaches

Abstract This paper outlines two contributions to stability analysis of fuzzy systems: knowledge of the membership function shape (actually, constraints on the membership function values) and polynomial approaches. Both ideas reduce the conservativeness in the stability analysis of a nonlinear system when expressed as a fuzzy model by using membership shape information and by allowing a more general class of “fuzzy” systems than the widely-used Takagi-Sugeno one with linear consequents. In this way, the gap between fuzzy and nonlinear control gets smaller.