Miracle-dz/UniFAR-FTUs huggingface dataset:
Regional inversion of CO2 ecosystem fluxes from atmospheric measurements: reliability of the uncertainty estimates

Abstract. The Bayesian framework of CO 2 flux inversions permits estimates of the retrieved flux uncertainties. Here, the reliability of these theoretical estimates is studied through a comparison against the misfits between the inverted fluxes and independent measurements of the CO 2 Net Ecosystem Exchange (NEE) made by the eddy covariance technique at local (few hectares) scale. Regional inversions at 0.5° resolution are applied for the western European domain where ~ 50 eddy covariance sites are operated. These inversions are conducted for the period 2002–2007. They use a mesoscale atmospheric transport model, a prior estimate of the NEE from a terrestrial ecosystem model and rely on the variational assimilation of in situ continuous measurements of CO 2 atmospheric mole fractions. Averaged over monthly periods and over the whole domain, the misfits are in good agreement with the theoretical uncertainties for prior and inverted NEE, and pass the chi-square test for the variance at the 30% and 5% significance levels respectively, despite the scale mismatch and the independence between the prior (respectively inverted) NEE and the flux measurements. The theoretical uncertainty reduction for the monthly NEE at the measurement sites is 53% while the inversion decreases the standard deviation of the misfits by 38%. These results build confidence in the NEE estimates at the European/monthly scales and in their theoretical uncertainty from the regional inverse modelling system. However, the uncertainties at the monthly (respectively annual) scale remain larger than the amplitude of the inter-annual variability of monthly (respectively annual) fluxes, so that this study does not engender confidence in the inter-annual variations. The uncertainties at the monthly scale are significantly smaller than the seasonal variations. The seasonal cycle of the inverted fluxes is thus reliable. In particular, the CO 2 sink period over the European continent likely ends later than represented by the prior ecosystem model.
BAK-SNEPPEN MODELS FOR THE EVOLUTION OF STRUCTURED KNOWLEDGE

Scientific knowledge is subject to a twin evolution, since its development towards novelty creates disconnections and inconsistencies, while the need of structure requires order and method so that transmission and comprehension can be ensured. Models of biological evolution can help to understand many social and economical phenomena where the search for optimality is hindered by voluntary or random competition. Bak-Sneppen is one of the most significant models because it balances at best explication power and simplicity. Unlike cellular automata models, Bak-Sneppen models join locality and globality. The authors try to re-read these models in the framework of mathematics, where, despite its high developped structure, knowledge waves can hinder comprehension both of pupils and of scholars. Some paradoxes are shown, where a greater knowledge diminishes efficiency and capability.
Crime Time: How Ambient Light Affects Crime

This paper studies the effect of ambient light on crime, taking advantage of the daylight saving time (DST) policy, which imposes exogenous variations in daylight exposure at specific hours of the day. The paper uses a rich administrative database managed by Chile’s national police, a centralized agency that collects detailed information regarding each crime incident. A 20% decrease (increase) in crimes is found when the DST transition increases (decreases) the amount of sunlight by one hour during the 7-9 p.m. period. Importantly, no significant response is detected induced by DST associated with a plausible demand-side response such as the population’s commuting time pattern, and no substantial short-term displacement is found. Most of the changes in property crime due to the DST policy are driven by robbery in residential areas.
Influence of Electromagnetic Fieldson Prooxidant/Antioxidant Balancein Rat Liver

The potential health consequences of common exposure of human organisms to high-voltage industrial frequency and radio-frequency electromagnetic fields have not yet been completely recognized. The aim of this study was to evaluate the impact of a 50 Hz electromagnetic field generated by high-voltage alternating electric current transmission lines, a 900 MHz electromagnetic field emitted by mobile phones, and simultaneous exposure to those forms of electromagnetic fields on prooxidant and antioxidant processes in the liver tissue of 40 male rats randomly divided into three experimental groups exposed to different forms of electromagnetic fields and a control sham-exposed one. After completing 28 daily exposures in obtained liver tissue homogenates we determined the contents of markers of prooxidant processes (total oxidant capacity and malone dialdehyde), as well as activity of selected antioxidant enzymes (superoxide dismutase, its isoenzymes Cu,Zn-SOD and Mn-SOD, catalase and glutathione peroxidase). Moreover, cell ultrastructures in specimens from liver samples were examined under an electron microscope. A four-week exposure to a high-voltage 50 Hz electromagnetic field did not affect the prooxidant/antioxidant balance in the liver tissue of rats, while exposure to the radiofrequency electromagnetic field emitted by a mobile phone and simultaneous exposure to both forms of electromagnetic field significantly inhibited the intensity of prooxidant processes and decreased the activity of antioxidant enzymes in liver tissue, especially in the case of simultaneous action of both fields – probably due to their excessive use for restoring *e-mail: jarus_tomus@o2.pl DOI: 10.15244/pjoes/64747 280 Sieroń-Stołtny K. , et al.
RefleX: X-ray absorption and reflection in active galactic nuclei for arbitrary geometries

Reprocessed X-ray radiation carries important information about the structure and physical characteristics of the material surrounding the supermassive black hole (SMBH) in active galactic nuclei (AGN). We report here on a newly developed simulation platform, RefleX, which allows to reproduce absorption and reflection by quasi-arbitrary geometries. We show here the reliability of our approach by comparing the results of our simulations with existing spectral models such as pexrav, MYTorus and BNTorus. RefleX implements both Compton scattering on free electrons and Rayleigh scattering and Compton scattering on bound electrons. We show the effect of bound-electron corrections on a torus geometry simulated like in MYTorus. We release with this paper the RefleX executable, as well as RXTorus, a model that assumes absorption and reflection from a torus with a varying ratio of the minor to major axis of the torus. To allow major flexibility RXTorus is also distributed in three components: absorbed primary emission, scattered radiation and fluorescent lines. RXTorus is provided for different values of the abundance, and with (atomic configuration) or without (free-electron configuration) taking into account Rayleigh scattering and bound electrons. We apply the RXTorus model in both configurations on the XMM-Newton and NuSTAR spectrum of the Compton-thick AGN NGC 424 and find that the models are able to reproduce very well the observations, but that the assumption on the bound or free state of the electrons has significant consequences on the fit parameters.
Bootstrapping in dara analysis: a matlab approach

The bootstrap is a non-parametric but computer intensive method for making probability-based inferences about population parameters without theoretical assumptions. However, due to its complexity and a lack of understanding, the bootstrap has not been widely used in social science fields. Using Lotus 1-2-3 in bootstrapping is helpful but still somewhat ineffective. The purpose of this paper is to introduce and explain how the bootstrap method can be applied much easier using MATLAB computer language.
Non-U.S. Asset-Backed Securities: Spread Determinants and Over-Reliance on Credit Ratings

In this paper, we empirically investigate two economic issues (1) the factors that affect the primary market spread on non-U.S. asset-backed securities and (2) whether investors rely solely on credit ratings and ignore other credit-related factors. We do so by using a panel-data fixed-effects model of primary market spreads for tranches of non-mortgage-related asset-backed securities issued over the period 1999-2006. With respect to the determinants of the primary market spread, we find that spread can be explained in terms of two factors credit rating and bond market conditions. Our tests support the hypothesis that despite heavy reliance on credit ratings, investors do consider factors that the rating agencies state that they consider in assigning ratings. Hence, there is reason to suspect that the notion of pure reliance on assigned ratings that has been popularized in the market may be overstated.
Simulations of long range beam-beam effects in CESR in a strong-strong scenario

The Long Range Beam-Beam Interaction (LRBBI) is one of major limiting factor to the performance of a pretzel collider machine like CESR in which each bunch has several tens parasitic crossing points along the ring. To investigate the effects due to LRBBI, simulation studies are done with new simulation code in weak-strong and strong-strong scenarios. The precise simulations reveal that LRBBI, in the case of CESR, has significant effects on machine parameters. Especially the bunch-by-bunch differences, which can hardly be compensated by routine adjustments of operation conditions, may affect the luminosity performance directly. In future, with possibly higher current, more bunches or higher current/energy ratio, the dedicated compensation schemes are necessary.
POLARIZATION AND POLARIMETRY: A REVIEW

Polarization is a basic property of light and is fundamentally linked to the internal geometry of a source of radiation. Polarimetry complements photometric, spectroscopic, and imaging analyses of sources of radiation and has made possible multiple astrophysical discoveries. In this article I review (i) the physical basics of polarization: electromagnetic waves, photons, and parameterizations; (ii) astrophysical sources of polarization: scattering, synchrotron radiation, active media, and the Zeeman, GoldreichKylafis, and Hanle effects, as well as interactions between polarization and matter (like birefringence, Faraday rotation, or the Chandrasekhar-Fermi effect); (iii) observational methodology: on-sky geometry, influence of atmosphere and instrumental polarization, polarization statistics, and observational techniques for radio, optical, and X/ wavelengths; and (iv) science cases for astronomical polarimetry: solar and stellar physics, planetary system bodies, interstellar matter, astrobiology, astronomical masers, pulsars, galactic magnetic fields, gamma-ray bursts, active galactic nuclei, and cosmic microwave background radiation.
Skin Color detection Using Stepwise Neural Network and Color Mapping Co-occurrence Matrix

Skin color has been proven to be a useful and robust cue for face detection, human tracking, image content filtering, pornographic filtering, etc. Most of skin classification researches are focused on using pixel-based method to classify skin and non-skin pixels. This paper proposed a new technique for region-based skin color detection using texture information. The texture information was extracted from the color mapping co-occurrence matrix (CMCM). This technique is extension of gray level co-occurrence matrix (GLCM) which is introduced by Haralicket. al to compute second order statistical texture features. The new color mapping matrix (CMM) between color bands have been developed for skin and non-skin area for each skin image and then, the CMCM were computed at four direction with distance, d = 1, and angle, θ = 0o, 45o, 90o, and 135o. The thirteen Haralick’s textures have been computed and used for formulating a skin color classifiers using stepwise neural network (SNN). The performance of each skin color classifier was measured based on true and false positive value. Besides that, the benchmark datasets from Universidad de Chile and TDSD were also be employed to test the skin color classifiers ability. The results shown that the skin color classifier formulated with [RGB] CMCM at direction (1, 0o) most superior as compared to other direction. Its average of true positive and false positive are 98.38 percent and 3.67 percent, respectively. Meanwhile, the classifier formulated with [RGB] CMCM at direction (1, 90o) is totally failed to classify skin and non-skin colors. Meaning that, the texture features which are computed from [RGB] CMCM at direction (1, 90o) cannot represent skin and non-skin color at all.
A hydrological prediction system based on the SVS land-surface scheme: efficient calibration of GEM-Hydro for streamflow simulation over the Lake Ontario basin

Abstract. This work explores the potential of the distributed GEM-Hydro runoff modeling platform, developed at Environment and Climate Change Canada (ECCC) over the last decade. More precisely, the aim is to develop a robust implementation methodology to perform reliable streamflow simulations with a distributed model over large and partly ungauged basins, in an efficient manner. The latest version of GEM-Hydro combines the SVS (Soil, Vegetation and Snow) land-surface scheme and the WATROUTE routing scheme. SVS has never been evaluated from a hydrological point of view, which is done here for all major rivers flowing into Lake Ontario. Two established hydrological models are confronted to GEM-Hydro, namely MESH and WATFLOOD, which share the same routing scheme (WATROUTE) but rely on different land-surface schemes. All models are calibrated using the same meteorological forcings, objective function, calibration algorithm, and basin delineation. GEM-Hydro is shown to be competitive with MESH and WATFLOOD: the NSE √ (Nash–Sutcliffe criterion computed on the square root of the flows) is for example equal to 0.83 for MESH and GEM-Hydro in validation on the Moira River basin, and to 0.68 for WATFLOOD. A computationally efficient strategy is proposed to calibrate SVS: a simple unit hydrograph is used for routing instead of WATROUTE. Global and local calibration strategies are compared in order to estimate runoff for ungauged portions of the Lake Ontario basin. Overall, streamflow predictions obtained using a global calibration strategy, in which a single parameter set is identified for the whole basin of Lake Ontario, show accuracy comparable to the predictions based on local calibration: the average NSE √ in validation and over seven subbasins is 0.73 and 0.61, respectively for local and global calibrations. Hence, global calibration provides spatially consistent parameter values, robust performance at gauged locations, and reduces the complexity and computation burden of the calibration procedure. This work contributes to the Great Lakes Runoff Inter-comparison Project for Lake Ontario (GRIP-O), which aims at improving Lake Ontario basin runoff simulations by comparing different models using the same input forcings. The main outcome of this study consists in a new generalizable methodology for implementing a distributed hydrologic model with a high computation cost in an efficient and reliable manner, over a large area with ungauged portions, using global calibration and a unit hydrograph to replace the routing component.
Difference between the North Atlantic and Pacific meridional overturning circulation in response to the uplift of the Tibetan Plateau

Abstract. The role of the Tibetan Plateau (TP) in maintaining the large-scale overturning circulation in the Atlantic and Pacific is investigated using a coupled atmosphere–ocean model. For the present day with a realistic topography, model simulation shows a strong Atlantic meridional overturning circulation (AMOC) but a near absence of the Pacific meridional overturning circulation (PMOC), which are in good agreement with the present observations. In contrast, the simulation without the TP depicts a collapsed AMOC and a strong PMOC that dominates deep-water formation. The switch in deep-water formation between the two basins results from changes in the large-scale atmospheric circulation and atmosphere–ocean feedback over the Atlantic and Pacific. The intensified westerly winds and increased freshwater flux over the North Atlantic cause an initial slowdown of the AMOC, while the weakened East Asian monsoon circulation and associated decreased freshwater flux over the North Pacific give rise to the initial intensification of the PMOC. The further decreased heat flux and the associated increase in sea-ice fraction promote the final AMOC collapse over the Atlantic, while the further increased heat flux leads to the final PMOC establishment over the Pacific. Although the simulations were performed in a cold world, it still importantly implicates that the uplift of the TP alone could have been a potential driver for the reorganization of PMOC–AMOC between the late Eocene and early Oligocene.
AUTOMATED SHAPE-BASED PAVEMENT CRACK DETECTION APPROACH

Pavements are critical man-made infrastructure systems that undergo repeated traffic and environmental loadings. Consequently, they deteriorate with time and manifest certain distresses. To ensure long-lasting performance and appropriate level of service, they need to be preserved and maintained. Highway agencies routinely employ semiautomated and automated image-based methods for network-level pavement-cracking data collection, and there are different types of pavement-cracking data collected by highway agencies for reporting and management purposes. We design a shape-based crack detection approach for pavement health monitoring, which takes advantage of spatial distribution of potential cracks. To achieve this, we first extract Potential Crack Components (PCrCs) from pavement images. Next, we employ polynomial curve to fit all pixels within these components. Finally, we define a Shape Metric (SM) to distinguish crack blocks from background. We experiment the shape-based crack detection approach on different datasets, and compare detection results with an alternate method that is based on Support Vector Machines (SVM) classifier. Experimental results prove that our approach has the capability to produce higher detections and fewer false alarms. Additional research is needed to improve the robustness and accuracy of the developed approach in the presence of anomalies and other surface irregularities.
Four-Body Scattering of Light as a Method of Detection of Bose-Einstein Condensate of Excitons

Process of four-particle light scattering in molecular crystals with participation of the exciton Bose-condensate is considered. The intensities and tensor of scattering are found for this effect. The frequency and polarization characteristics of this process are studies. It is shown that the investigation of the spectrum shapes of scattered radiation allows one to find and prove the existence of the Bose-Einstein condensate of excitons.
Observed cases and hypothetical controls to study the influence of trees on understory vegetation

The relation between the presence of an understory vegetation species and the influence of tree species was studied using measurements gathered in plots distributed all over Finland. The presence of the understory was observed in several quadrats within each plot. The collective influence of the trees was quantified by the influence potential index, based on the size of the individual trees and their spatial distribution. Given the size of the study area, large scale factors, such as climate and latitude, were expected to be significant. To avoid such factors, a conditional logistic model was derived, where the probability of presence was conditioned on another event also subject to large-scale factors. The resulting model may be interpreted as a matched case-control study: the case is the observed set of quadrats in the plot in terms of absence and presence of the vegetation in the individual quadrats; and the controls are permutations of this set. The results from the odds ratio were valid for both conditional and unconditional logistic models. The analysis of Vaccinium vitis idaea indicated that the odds of presence decreased with the increasing influence of Scots pine and Norway spruce; for Calamagrostis arundinacea, the decrease was due to the influence of Norway spruce.
Consensus Information Filtering for Large-Scale Systems with Application to Heat Conduction Process

For large-scale distributed systems, the evolution of system dynamics is dominated by current states and boundary conditions simultaneously. This work describes a distributed consensus filtering for a class of large-scale distributed systems with unknown boundary conditions, which are monitored by a set of sensors. Because of the difference of spatial positions among the sensor network, only the single state variables or both the states and outside input jointly could be estimates with Kalman information filtering, respectively. On diffusion processing, we fuse the common state estimations of the local information filters using consensus averaging algorithms and algebraic graph theory. Stability and performance analysis is provided for this distributed filtering algorithm. Finally, we consider an application of distributed estimation to a heat conduction process. The performance of the proposed distributed algorithm is compared to the centralized Kalman filtering.
Estimation of the flower buttons per inflorescences of grapevine (Vitis vinifera L.) by image auto-assessment processing

The aim of this research is to develop a reliable tool by a special method, combining image processing based on watershed algorithm, and a predictive model to estimate automatically the flowers number per inflorescence. Eighty images of Vitis vinifera L. inflorescence (the Cardinal cultivar) were processed. Watershed algorithm was used for the image processing and this was followed by statistical analysis that provides robust predictive estimation of the flower button number. The results show a robust estimation, compared to manual flowers counting, with strong correlation. The developed algorithm shows that the watershed algorithm was able to provide an automatic assessment of the flower button number in the inflorescence. The method used is more robust and provides a more significant level compared with recent studies. In the applied research in viticulture, it is crucial to improve knowledge of yield forecasting and to study the fruit set rates estimation. The technique is used to determine, with a higher significance level, the fruitiness rate of grapevine at the early stage of flowering. Key words: Flower button, fruit set rate, grapevine, image processing, watershed.
Hepatoprotective effect of aqueous extract of Melothria perpusilla against carbon tetrachloride induced liver injury in albino rats

Background: In absence of reliable hepatoprotective drug in modern medicine, the traditional herbal medicines have been emphasized. Present study was designed to assess hepatoprotective effect of aqueous extract of Melothria perpusilla (AEMP) against carbon tetrachloride (CCl 4 ) induced liver injury. Methods: Five groups of animals with 6 rats in each were treated for 7 days. Group I received 1% gum acacia in distilled water (1 ml/200 g p.o.) daily. Group II, III, IV and V received CCl 4 in liquid paraffin (1 ml/kg s.c.) on day 2, 4 and 6. Group III, IV and V were treated respectively with silymarin (100 mg/kg p.o.), AEMP- 200 and 400 mg/kg p.o. daily. On day 8, liver injury was assessed by measuring serum ALT, AST, ALP and bilirubin. Results: ALT, AST, ALP and bilirubin were significantly reduced in groups receiving both CCl 4 and AEMP when compared with CCl 4 treated group. Conclusions: AEMP produced hepatoprotective effect against CCl 4 induced liver injury.