Miracle-dz/UniFAR-FTUs huggingface dataset:
Nitrogen retention and transport differ by hillslope aspect at the rain‐snow transition of the Colorado Front Range

Over a decade of research in the alpine zone of the Colorado Front Range has shown that atmospheric nitrogen (N) deposition originating from source areas in low elevation, developed areas, has changed ecosystem stoichiometry, nutrient transformations, and aquatic community structure. Less research has occurred in the montane zone, which sits at the current rain‐snow transition and is vulnerable to climate change, land cover disturbances, and increased N loading. We conducted lithium bromide and 15N‐nitrate (15NO3−) tracer studies during spring snowmelt to determine the immediate fate of N in a forested catchment. Measurements of N species and applied tracers in ecosystem pools and soil solution on north and south facing slopes provided a means of determining export pathways and uptake of deposited N. Our results indicate that NO3− residence time is longer within north than south facing slope soils, due to longer contact with the soil matrix, greater microbial biomass N, and a larger soil organic matter pool. On the north facing slope, >50% of the 1 kg ha−1 of 15NO3− applied was retained in soil and vegetation pools. On the south facing slope, rapid transport during sporadic snowmelt events reduced total recovery of the 15N label in ecosystem pools to 16–34%. Our results suggest that snowmelt events quickly transport N through south facing slope soils, potentially contributing more N to aquatic systems than north facing slopes. Thus, it is important to consider how the fate of N differs by hillslope aspect when predicting catchment‐scale N export and determining ecosystem N status across the Colorado Front Range.
Isotopic composition of H2 from CH4 oxidation in the stratosphere and the troposphere

[1] Enrichment in deuterium (D) of stratospheric H2 is investigated using new and published data. Applying a Rayleigh model to account for the isotopic fractionations in the photochemical chain reactions from CH4 to the final product H2O via H2 reveals a strong enrichment of photochemically produced H2. This is consistent with previous studies, but the degree of enrichment obtained in this study appears to be 100–120‰ larger than the previous estimates on average. The discrepancy primarily stems from the former use of either an isotopic fractionation factor of H2 that does not take into account the effect of stratospheric transport or an H2 yield from CH2O photolysis that is not applicable to stratospheric conditions. We further investigate the same isotopic fractionation process under tropospheric conditions by considering the differences in both the species and amounts of oxidizing agents and the wavelengths that are effective in the photolysis of CH2O. These were not considered in the former studies when they derived the δD value under the tropospheric conditions. We thereby anticipate the δD value of H2 from photochemical oxidation of CH4 in the troposphere to be 190 (±50)‰.
Focusing on Persons: Colorizing Old Images Learning from Modern Historical Movies

In industry, there exist plenty of scenarios where old gray photos need to be automatically colored, such as video sites and archives. In this paper, we present the HistoryNet focusing on historical person's diverse high fidelity clothing colorization based on fine grained semantic understanding and prior. Colorization of historical persons is realistic and practical, however, existing methods do not perform well in the regards. In this paper, a HistoryNet including three parts, namely, classification, fine grained semantic parsing and colorization, is proposed. Classification sub-module supplies classifying of images according to the eras, nationalities and garment types; Parsing sub-network supplies the semantic for person contours, clothing and background in the image to achieve more accurate colorization of clothes and persons and prevent color overflow. In the training process, we integrate classification and semantic parsing features into the coloring generation network to improve colorization. Through the design of classification and parsing subnetwork, the accuracy of image colorization can be improved and the boundary of each part of image can be more clearly. Moreover, we also propose a novel Modern Historical Movies Dataset (MHMD) containing 1,353,166 images and 42 labels of eras, nationalities, and garment types for automatic colorization from 147 historical movies or TV series made in modern time. Various quantitative and qualitative comparisons demonstrate that our method outperforms the state-of-the-art colorization methods, especially on military uniforms, which has correct colors according to the historical literatures.
Predicting high-risk opioid prescriptions before they are given

Significance We describe a hypothetical preventative policy solution to address the opioid crisis using an integrated administrative database developed in collaboration with the State of Rhode Island. Machine learning algorithms trained on observations of past opioid prescription accurately predict adverse opioid-related outcomes among Medicaid recipients even before their initial opioid prescription is written. Although these models are limited to individuals who have been selected for opioid prescription, they suggest a feasible path forward for using administrative data to inform prescription risk. Under the assumption that the cost of diverting individuals from opioid therapy to an alternative therapy is homogenous across individuals, we simulate a hypothetical policy for restricting opioid prescriptions based on risk that is likely net-beneficial given current cost estimates. Misuse of prescription opioids is a leading cause of premature death in the United States. We use state government administrative data and machine learning methods to examine whether the risk of future opioid dependence, abuse, or poisoning can be predicted in advance of an initial opioid prescription. Our models accurately predict these outcomes and identify particular prior nonopioid prescriptions, medical history, incarceration, and demographics as strong predictors. Using our estimates, we simulate a hypothetical policy which restricts new opioid prescriptions to only those with low predicted risk. The policy’s potential benefits likely outweigh costs across demographic subgroups, even for lenient definitions of “high risk. ” Our findings suggest new avenues for prevention using state administrative data, which could aid providers in making better, data-informed decisions when weighing the medical benefits of opioid therapy against the risks.
The Radial Distribution of Galaxies in Λ Cold Dark Matter Clusters

We study the radial distribution of subhalos and galaxies using high-resolution cosmological simulations of galaxy clusters formed in the concordance Λ cold dark matter cosmology. In agreement with previous studies, we find that the radial distribution of subhalos is significantly less concentrated than that of the dark matter, when subhalos are selected using their present-day gravitationally bound mass. We show that the difference in the radial distribution is not a numerical artifact and is due to tidal stripping. The subhalos in the cluster core lose more than 70% of their initial mass since accretion, while the average tidal mass loss for halos near the virial radius is ≈30%. This introduces a radial bias in the spatial distribution of subhalos when the subhalos are selected using their tidally truncated mass. We demonstrate that the radial bias disappears almost entirely if subhalos are selected using their mass or circular velocity at the accretion epoch. The comparisons of the results of dissipationless simulations to the observed distribution of galaxies in clusters are therefore sensitive to the selection criteria used to select subhalo samples. Using simulations that also include cooling and star formation, we show that the radial distribution of subhalos is in reasonable agreement with the observed radial distribution of galaxies in clusters over the entire radial range probed by the simulations, 0.1 < R/R200 < 2.0, if subhalos are selected using the stellar mass of galaxies that they harbor. The radial bias is minimized in this case because the stars are located in the centers of dark matter subhalos and are tightly bound. The stellar mass of an object is therefore approximately conserved as the dark matter is stripped from the outer regions. Nevertheless, the concentration of the radial distribution of simulated galaxies is systematically lower than that of the dark matter. Finally, we find that the baryon dissipation does enhance the survival of subhalos, especially in the cluster cores. However, the effect is relatively weak because the baryon dissipation affects the density distribution only at small radii.
Genetic algorithm solution of groundwater management models

Groundwater simulation models have been incorporated into a genetic algorithm to solve three groundwater management problems: maximum pumping from an aquifer; minimum cost water supply development; and minimum cost aquifer remediation. The results show that genetic algorithms can effectively and efficiently be used to obtain globally (or, at least near globally) optimal solutions to these groundwater management problems. The formulation of the method is straightforward and provides solutions which are as good as or better than those obtained by linear and nonlinear programming. Constraints can be incorporated into the formulation and do not require derivatives with respect to decision variables as in nonlinear programming. More complicated problems, such as transient pumping and multiphase remediation, can be formulated and solved using this method. The computational time required for the solution of genetic algorithm groundwater management models increases with the complexity of the problem. The speedup attainable by solving genetic algorithm problems on massively parallel computers is significant for problems where the simulation time required to complete each generation is high. 47 refs., 9 figs., 5 tabs.
Continental-Scale River Flow in Climate Models

Abstract The hydrologic cycle is a major part of the global climate system. There is an atmospheric flux of water from the ocean surface to the continents. The cycle is closed by return flow in rivers. In this paper a river routing model is developed to use with grid box climate models for the whole earth. The routing model needs an algorithm for the river mass flow and a river direction file, which has been compiled for 4°×5° and 20°×2.5° resolutions. River basins are defined by the direction files. The river flow leaving each grid box depends on river and lake mass, downstream distance, and an effective flow speed that depends on topography. As input the routing model uses monthly land source runoff from a 5-yr simulation of the NASA/GISS atmospheric climate model (Hansen et al.). The land source runoff from the 4°×5° resolution model is quartered onto a 2°×2.5° grid, and the effect of grid resolution is examined. Monthly flow at the mouth of the world's major rivers is compared with observations, and a.
Convergence of a Newton algorithm for semi-discrete optimal transport

Many problems in geometric optics or convex geometry can be recast as optimal transport problems: this includes the far-field reflector problem, Alexandrov's curvature prescription problem, etc. A popular way to solve these problems numerically is to assume that the source probability measure is absolutely continuous while the target measure is finitely supported. We refer to this setting as semi-discrete optimal transport. Among the several algorithms proposed to solve semi-discrete optimal transport problems, one currently needs to choose between algorithms that are slow but come with a convergence speed analysis (e.g. Oliker-Prussner) or algorithms that are much faster in practice but which come with no convergence guarantees Algorithms of the first kind rely on coordinate-wise increments and the number of iterations required to reach the solution up to an error of $\epsilon$ is of order $N^3/\epsilon$, where $N$ is the number of Dirac masses in the target measure. On the other hand, algorithms of the second kind typically rely on the formulation of the semi-discrete optimal transport problem as an unconstrained convex optimization problem which is solved using a Newton or quasi-Newton method. The purpose of this article is to bridge this gap between theory and practice by introducing a damped Newton's algorithm which is experimentally efficient and by proving the global convergence of this algorithm with optimal rates. The main assumptions is that the cost function satisfies a condition that appears in the regularity theory for optimal transport (the Ma-Trudinger-Wang condition) and that the support of the source density is connected in a quantitative way (it must satisfy a weighted Poincar\'e-Wirtinger inequality).
An SME's Adoption of a Cloud Based Integrated Management System (IMS) When Certifying Against Management System Standards (MSS)

This case study introduces a four step approach used by a Singapore small and medium enterprise (SME) in implementing a cloud computing based integrated management system (IMS) to meet the ISO 9001, ISO 14001, and OHSAS 18001 certification requirements. The objectives of this case study are to study: (1) the challenges encountered by an SME during the IMS integration process at each of the four levels of integration (2) the extent which Frugal IT Innovation and Technology Acceptance Model (TAM3) concepts apply to our four step approach. The four step approach was assessed against a framework of four integration levels of the management systems (MS), and also the applicability of two IS theories (Frugal IT Innovation and TAM3). Data was collected via: (1) direct observations (2) participant observations; (3) interviews with key personnel involved in the project; and (4) analysis of documents pertaining to the project. This case study provides an exemplary model on using IS theories and public cloud technologies to develop an effective IMS that other SMEs can learn from.
Positioning Names on Maps

Prof. Dr. Eduard Imhof, dean of European cartographers, has been an astute student of the esthetic-scientific characteristics of the cartographic method. In this paper published 13 years ago, he draws upon his long experience in map design and production to formulate a series of precepts about positioning or locating the lettering on maps in relation to the various functional aspects of the map and the individual named features. Noting that legibility and clarity of the map depend on good name positioning—each name having only one optimum position on the map—he encourages the use of a graphic draft of lettering to determine this position.
Comparing occurrences and vertical structures of hydrometeors between eastern China and the Indian monsoon region using CloudSat/CALIPSO data.

Abstract Seasonal variations in the occurrence frequency, vertical location, and radar reflectivity factor (dBZ) of hydrometeors covering eastern China and the Indian monsoon region are described using two CloudSat standard products [Geometrical Profiling Product (GEOPROF) and GEOPROF-lidar] during the period July 2006–August 2007. The 14-month averaged hydrometeor occurrence frequency is 80% (for eastern China) and 70% (for Indian region), respectively, to which multilayer (mostly double or triple layers) hydrometeors contribute 37% and 47%. A significant increase in the multilayer hydrometeor amount from winter to summer in the Indian region causes a pronounced seasonal variation in its total hydrometeor amount. The nearly opposite phases in the seasonal variations of single- and multilayer hydrometeor amounts result in little change with season in total hydrometeor amount in eastern China. Although the passive sensor-based satellite cloud product is able to provide the major seasonal features in the hy.
Computation of the Kolmogorov-Sinai entropy using statis-titical mechanics : Application of an exchange Monte Carlo method

– We propose a method for computing the Kolmogorov-Sinai (KS) entropy of chaotic systems. In this method, the KS entropy is expressed as a statistical average over the canonical ensemble for a Hamiltonian with many ground states. This Hamiltonian is constructed directly from an evolution equation that exhibits chaotic dynamics. As an example, we compute the KS entropy for a chaotic repeller by evaluating the thermodynamic entropy of a system with many ground states. Chaotic systems are characterized by properties of O(e ) distinguishable trajectories over a time interval N in a phase space in which the limit of observational accuracy is given by some finite value ǫ [1–3]. In particular, if these trajectories are coded as sequences of symbols, the optimal compression ratio of such sequences is an important quantity from the point of view of information theory [4, 5]. This quantity corresponds to the Kolmogorov-Sinai (KS) entropy, hks. Although the KS entropy provides a simple characterization of chaotic systems, its direct numerical evaluation is not simple. One reason for this is that a precise mathematical definition of distinguishable trajectories relies on an (ǫ, N) separated set that is difficult to investigate numerically [1]. However, this difficulty can be overcome when a set of periodic orbits alone can provide information that is sufficient to obtain a useful characterization of the set of all distinguishable trajectories [6–8]. However, even in such cases, the difficulty involved in numerical computations remains, because the number of periodic orbits of period N increases exponentially as a function of N . Here, let us recall that such an exponential dependence of the number of explored states appears in the statistical mechanics of glassy systems [9] and decision problems [10]. Recently, efficient methods for computing thermodynamic quantities of glassy systems have been developed [11, 12] and applied to several problems [13–15]. Inspired by this success, in this (∗) E-mail:sasa@jiro.c. u-tokyo.ac. jp (∗∗) E-mail:hayashi@jiro.c. u-tokyo.ac. jp
Wind tunnel measurements of adobe abrasion by blown sand: profile characteristics in relation to wind velocity and sand flux

Abstract Blown sand causes various damages, such as extensive abrasion to crops, structural wear of facilities and buildings, and abrasion of soil clods and clayey materials generating fine particulate matter. In this study, experiments conducted in a straight-line blowing wind tunnel confirmed field observations and provided useful information for understanding abrasion profiles created by sand drift. Abrasion rates of 20 adobe blocks in a pile 50 cm high were determined at wind velocities of 10, 12, 14, 16, 18, 20 and 22 m s−1. Wind velocities at eight different heights were measured with a wind profiler, and the transport rate of sand flux was determined by a step-like sand trap. The rate of abrasion and sand transport increased exponentially with increasing wind velocities. Abrasion profiles obtained in the wind tunnel showed good consistency with previous observations in the field. The height of maximum abrasion shifted upward from 5 to 12·5 cm as wind velocity increased. Also, as wind velocity increased, the relative amount of saltating sand decreased under the height of 5·0 cm, but increased above 7·5 cm. Comparison of the rate of abrasion with the mass transport rate yielded a strong linear relationship (r2=0·99). The abrasion capacity of the saltating sand (defined as the ratio of abrasion rate to aeolian sand transport rate) increased logarithmically with wind velocity, and its peak value occurred at a height of 20–22·5 cm. The experiment demonstrated that adobe abrasion by aeolian sand was affected by both abrasion capacity and the sand transport rate. Shifting of height of maximum abrasion with wind velocity was mainly due to a corresponding mass change in the structure of the aeolian sand flow.
Estimation of the earthquake recurrence parameters for unequal observation periods for different magnitudes

abstract Maximum likelihood estimation of the earthquake parameters N o and β in the relation N = N o exp (− βm ) is extended to the case of events grouped in magnitude with each group observed over individual time periods. Asymptotic forms of the equation for β reduce to the estimators given for different special cases by Aki (1965), Utsu (1965, 1966), and Page (1968). The estimates of β are only approximately chi-square distributed. For sufficiently large numbers of events, they can be estimated from the curvature of the log-likelihood function. Sample calculations for three earthquake source zones in western Canada indicate that for well-constrained data sets, the often-used, least-squares estimation procedures lead to compatible results, but for less well-defined data sets, the effect of subjective plotting and weighting methods used for least-squares fitting leads to appreciably different parameters.
Development and validation of Critical Thinking Disposition Inventory for Chinese medical college students (CTDI-M)

PURPOSE: Critical thinkers in medical context must be not only "able" but also "willing" to think critically. To develop and conduct psychometric testing of Critical Thinking Disposition Inventory which measure the critical thinking disposition of Chinese medical college students. METHODS: The study was conducted in two stages: (a) item generation and exploratory factor analysis (EFA) and (b) testing of psychometric properties (construct validity, split-half reliability and Cronbach's alpha, and test-retest reliability. The subjects were composed of 441 undergraduate medical and nursing students from a medical university in China. Test-retest reliability of the instrument was determined at two-week interval. Data was analyzed with SPSS13.0. RESULTS: Preliminary 264 items were obtained using an open-ended questionnaire; from which 61 items were reviewed through half open-ended questionnaire, and finally 18 items were chosen. Eighteen final items were sorted into 3 factors, which were identified as "Open-mindedness ", "Systematicity/analyticity" and "Truth seeking". The cumulative percent of variance was 57.66%. The Cronbach's alpha was 0.924 and the factors' alphas ranged from 0.824-0.862. Correlational analysis indicated moderate to high correlations between the subscales and total scores of the CTDI-CM. Our results indicated that open-mindedness and systematicity/analyticity were higher for medical students than nursing students. CONCLUSIONS: This study conducted in a Chinese medical college student population demonstrated a reliable and valid instrument for clinical thinking disposition, which measured motivation and cognitive components. The effect of enrollment year and major on the profiles of critical thinking dispositions was identified, emphasizing the importance of applying specialized teaching to students of different majors.