Miracle-dz/UniFAR-FTUs huggingface dataset:
Physiological Responses of Forest Trees to Heat and Drought

: The heat wave of summer 2003 was the largest and the most persistent ever experienced in Central Europe and has fuelled concern about the effects of climate change on European ecosystems. Since forests constitute the most important European ecosystems, in this review article we assess current knowledge on the effects of heat and drought on key metabolic processes for growth and productivity of forest trees. In particular, the general consequences of heat and drought on (1) photo-synthesis and respiration at the cellular and community level, and (2) on nutrient uptake, partitioning and competition for nutrients are summarized. The latter are a major sink for photo-synthetic energy and, therefore, are indirectly but strongly connected to the performance of photosynthesis. In addition, the interaction of heat and drought with stress compensation mechanisms and emission of biogenic volatile organic compounds (BVOC) are discussed, since these processes are directly connected to carbon metabolism. Effects on the emission of BVOC are also included because they constitute an important feed-back mechanism on ozone formation and, thus, on atmospheric pollution. As far as available, data collected during the 2003 heat wave are included and discussed.
A semi-automated approach for the generation of a new land use and land cover product for Germany based on Landsat time-series and Lucas in-situ data

ABSTRACT Information on land cover and land use at high spatial resolutions is essential for advancing earth system science as well as for environmental monitoring to support decision-making and reporting processes. In view of this, we present the first version of the DFD Land Use and Land Cover Product for Germany, DFD-LULC_DE, for the year 2014, generated from 702 Landsat-7 and Landat-8 scenes at 30 m resolution. The results were derived based on a fully automated preprocessing chain that integrates data acquisition, radiometric, atmospheric and topographic correction, as well as spectral–temporal feature extraction for all Landsat surface reflectance bands, brightness temperature and various spectral indices. The classification followed a two-step approach: first, an initial classification is performed using a Random Forest classifier trained on ground truth data obtained from the LUCAS survey of EUROSTAT, followed by a semi-automated sampling of additional training data to further improve the initial classification results. Automatic selection of appropriate training samples is based on the vote entropy derived from the initial classification, thereby keeping manual user interaction low. The approach demonstrated is promising, also with respect to a European wide application, and contributes towards the advancement and enhancement of the DLR-DFD’s processing chains, which are directed towards the generation of land cover products at regular intervals being of central importance to related land monitoring and reporting services.
Simulation of Future Initial Margin along Low-Dimensional State Spaces

MVA is today’s price of the future costs generated by future initial margin postings. Computing MVA requires long-term risk neutral simulations of future initial margin amounts. The ISDA SIMM computes initial margin based on the portfolio’s sensitivity with respect to a high-dimensional vector of risk factors. In this note, we describe a way to approximate future SIMM based initial margin amounts in terms of regression functions with respect to a small number of explanatory variables. Our method uses principal components analysis, and it fits in naturally with American Monte Carlo techniques.
An Irrelevancy-Eliminating Translation of Pure Type Systems

I present an infinite-reduction-path-preserving typability-preserving translation of pure type systems which eliminates rules and sorts that are in some sense irrelevant with respect to normalization. This translation can be bootstrapped with existing results for the Barendregt-Geuvers-Klop conjecture, extending the conjecture to a larger class of systems. Performing this bootstrapping with the results of Barthe et al. [4] yields a new class of systems with dependent rules and non-negatable sorts for which the conjecture holds. To my knowledge, this is the first improvement in the state of the conjecture since the results of Roux and van Doorn [16] (which can be used for the same sort of bootstrapping argument) albeit a somewhat modest one; in essence, the translation eliminates clutter in the system that does not affect normalization. This work is done in the framework of tiered pure type systems, a simple class of persistent systems which is sufficient to study when concerned with questions about normalization.
The Anti-Social System Properties: Bitcoin Network Data Analysis

Bitcoin is a cryptocurrency and a decentralized semi-anonymous peer-to-peer payment system in which the transactions are verified by network nodes and recorded in a public massively replicated ledger called the blockchain. Bitcoin is currently considered as one of the most disruptive technologies. Bitcoin represents a paradox of opposing forces. On one hand, it is fundamentally social, allowing people to transact in a peer-to-peer manner to create and exchange value. On the other hand, Bitcoin’s core design philosophy and user base contain strong anti-social elements and constraints, emphasizing anonymity, privacy, and subversion of traditional centralized financial systems. We believe that the success of Bitcoin, and the financial ecosystem built around it, will likely rely on achieving an optimal balance between these social and anti-social forces. To elucidate the role of these forces, we analyze the evolution of the entire Bitcoin transaction graph from its inception, and quantify the evolution of its key structural properties. We observe that despite its different nature, the Bitcoin transaction graph exhibits many universal dynamics typical of social networks. However, we also find that Bitcoin deviates in important ways due to anonymity-seeking behavioral patterns of its users. As a result, the network exhibits a two-orders-of-magnitude larger diameter, sparse tree-like communities, and an overwhelming majority of transitional or intermediate accounts with incoming and outgoing edges but zero cumulative balances. These results illuminate the evolutionary dynamics of the most popular cryptocurrency, and provide us with initial understanding of social networks rooted in and driven by anti-social constraints.
Priming Mathematics Word Problem Structures in a Rural Elementary Classroom

This study examined mathematics strategy instruction that primes the common underlying structures of word problems using explicit instruction in a rural elementary classroom with fourth- and fifth-grade students with and without disabilities (n = 27). Although intervention students did not outperform control condition students on a word problem solving (WPS) measure (p = .054), a statistically significant interaction effect was found (p = .003). Follow-up analyses revealed that the WPS pretest–posttest gain was significant for the intervention group only. Students with disabilities in both conditions did not improve performance. Implications for practice and research in rural school classrooms are presented.
An Action-Reaction Interpretation of the Interaction between Cosmic Expansion and Gravitation

An updated review is presented to demonstrate the impact an expanding cosmos on three approaches to analyzing gravity. 1) the General Relativity based tensor method, 2) the Escape Velocity based conservation of energy method, and 3) the Force-Balanced based action-reaction method. The only common solution from all three methods is a flat space result with critical matter density ρc=3H2/8πG where H is the Hubble parameter, and G is the gravitational constant. It is also shown that the use of a Force-Balance based analysis for action-reaction, derived from a conservation of energy baseline, is analytically equivalent to that of a General Relativity tensor-based analysis for a flat space solution. Galaxy-based energy conservation and force-balanced solutions in an expanding cosmos also indicate that cosmic expansion is the unique action-based cause of a gravitational reaction at a galaxy level. Friedmann solutions from General Relativity for open and closed space curvature, however, add a speed of light term to H that violates galaxy-based conservation of energy and action-reaction force balance requirements. Thus, such curved space solutions are not physically relevant in an expanding cosmos. Evidence from Guth-Linde Inflationary Universe models is also cited to support the validity of a unique galaxy-based flat space solution.
Homogenization of second order discrete model with local perturbation and application to traffic flow

The goal of this paper is to derive a traffic flow macroscopic model from a second order microscopic model with a local perturbation. At the microscopic scale, we consider a Bando model of the type following the leader, i.e the acceleration of each vehicle depends on the distance of the vehicle in front of it. We consider also a local perturbation like an accident at the roadside that slows down the vehicles. After rescaling, we prove that the "cumulative distribution functions" of the vehicles converges towards the solution of a macroscopic homogenized Hamilton-Jacobi equation with a flux limiting condition at junction which can be seen as a LWR (Lighthill-Whitham-Richards) model.
The Effect of Weak Resistivity and Weak Thermal Diffusion on Short-wavelength Magnetic Buoyancy Instability

Magnetic buoyancy instability in weakly resistive and thermally conductive plasma is an important mechanism of magnetic field expulsion in astrophysical systems. It is often invoked, e.g., in the context of the solar interior. Here, we revisit a problem introduc`ed by Gilman: the short-wavelength linear stability of a plane layer of compressible isothermal and weakly diffusive fluid permeated by a horizontal magnetic field of strength decreasing with height. In this physical setting, we investigate the effect of weak resistivity and weak thermal conductivity on the short-wavelength perturbations, localized in the vertical direction, and show that the presence of diffusion allows to establish the wavelength of the most unstable mode, undetermined in an ideal fluid. When diffusive effects are neglected, the perturbations are amplified at a rate that monotonically increases as the wavelength tends to zero. We demonstrate that, when the resistivity and thermal conduction are introduced, the wavelength of the most unstable perturbation is established and its scaling law with the diffusion parameters depends on gradients of the mean magnetic field, temperature, and density. Three main dynamical regimes are identified, with the wavelength of the most unstable mode scaling as either or or , where d is the layer thickness and is the ratio of the characteristic thermal diffusion velocity scale to the free-fall velocity. Our analytic results are backed up by a series of numerical solutions. The two-dimensional interchange modes are shown to dominate over three-dimensional ones when the magnetic field and/or temperature gradients are strong enough.
Improving particle filter performance with a generalized random field model of observation errors

This article shows that generalized random field (GRF) models of additive observation error can reduce the ensemble size required to avoid collapse in particle filtering of spatially-extended dynamics. This kind of random field model has increasing variance at small scales, and realizations appear `jagged. ' Particle weights depend on how well a particular ensemble member agrees with the observations, and collapse occurs when a few ensemble members receive most of the weight. The GRF observation error model reduces the incidence of collapse by de-emphasizing small-scale differences between the ensemble members and the observations. This observation error model smooths the posterior mean, though it does not smooth the individual ensemble members. Two options for implementing the observation error model are described. Taking discretized elliptic differential operators as an observation error covariance matrix provides the desired jagged property of process realizations. This choice also introduces structure exploitable by scalable computation techniques, including multigrid solvers and multiresolution approximations to the corresponding integral operator. Alternatively the observations can be smoothed and then assimilated under the assumption of independent errors, which is equivalent to assuming large errors at small scales. The method is demonstrated on a linear stochastic partial differential equation, where it significantly reduces the occurrence of particle filter collapse while maintaining accuracy. It also improves continuous ranked probability scores by as much as 20\%, indicating an improvement in the quality of the probability distribution associated with the particle weights. The method is compatible with other techniques for improving the performance of particle filters.
Effect of charging on silicene with alkali metal atom adsorption

Based on first-principles calculations, we studied the effects of charging on the structure, binding energy and electronic properties of silicene with alkali metal (AM) atom (Li, Na or K) adsorption. In AMSi2, electron doping enlarges the lattice constant of silicene, while the influence of hole doping is non-monotonic. In AMSi8, the lattice constant increases/decreases almost linearly with the increase in electron/hole doping. In addition, the AM–Si vertical distance can be greatly enlarged by excessive hole doping in both AMSi2 and AMSi8 systems. When the hole doping is as large as +e per unit cell, both AMSi2 and AMSi8 can be transformed from metal to semiconductor. However, the binding energy would be negative in the AM+ Si2 semiconductor. It suggests AM+ Si2 is unstable in this case. In addition, the electron doping and the AM–Si vertical distance would greatly influence the band gap of silicene in LiSi8 and NaSi8, while the band gap in KSi8 is relatively stable. Therefore, KSi8 may be a more practicable material in nanotechnology.
A PDF-based parameterization of subgrid-scale hydrometeor transport in deep convection

AbstractA parameterization scheme is proposed for the subgrid-scale transport of hydrometeors in an assumed probability density function (PDF) scheme. Joint distributions of vertical velocity and hydrometeor mixing ratios are typically unknown, but marginal (1D) PDFs of these variables are available. The parameterization is developed using high-resolution simulations of continental and tropical deep convection. A 3D cloud-resolving model (CRM) providing benchmark solutions has a horizontal grid spacing of 250 m and employs the Morrison microphysics scheme, which treats prognostically mass and number mixing ratios for four types of precipitating hydrometeors (rain, graupel, snow, and ice) as well as cloud droplet number mixing ratio. The subgrid-scale hydrometeor transport scheme assumes input given in the form of marginal PDFs of vertical velocity and hydrometeor mixing ratios; in this study, these marginal distributions are provided by the cloud-resolving model. Conditional sampling and scaling are then .
86 GHz SiO maser survey of late-type stars in the inner galaxy. I. Observational data

We present 86 GHz ($v = 1, J = 2 \rightarrow 1$) SiO maser line observations with the IRAM 30-m telescope of a sample of 441 late-type stars in the Inner Galaxy ($ -4 \degr < l < +30 \degr$). These stars were selected on the basis of their infrared magnitudes and colours from the ISOGAL and MSX catalogues. SiO maser emission was detected in 271 sources, and their line-of-sight velocities indicate that the stars are located in the Inner Galaxy. These new detections double the number of line-of-sight velocities available from previous SiO and OH maser observations in the area covered by our survey and are, together with other samples of e.g. OH/IR stars, useful for kinematic studies of the central parts of the Galaxy.
Nonlinear Effects on the Convergence of Picard and Newton Iteration Methods in the Numerical Solution of One-Dimensional Variably Saturated–Unsaturated Flow Problems

Finite element discretization of the pressure head form of the Richards equation leads to a nonlinear model, which yields numerical convergence difficulties. When the numerical solution to this problem has either an extremely sharp moving front, infiltration into dry soil, flow domains containing materials with spatially varying properties, or involves time-dependent boundary conditions, the corrector iteration used in many time integrators can terminate prematurely, which leads to incorrect results. While the Picard and Newton iteration methods can solve this problem through tightening the tolerances provided to the solvers, there is a more efficient approach to overcome the convergence difficulties. Four tests examples are examined, and each test case is solved with five sufficiently small tolerances to demonstrate the effectiveness of convergence. The numerical results illustrate that the methods greatly improve the convergence and stability. Test experiments show that the Newton method is more complex and expensive on a per iteration basis than the Picard method for simulating variably saturated–unsaturated flow in one spatial dimension. Consequently, it is suggested that the resulting local and global mass balance is exact within the minimum specified accuracy.
The nonlinear interaction of Tollmien–Schlichting waves and Taylor-Görtler vortices in curved channel flows

It is known that a viscous fluid flow with curved streamlines can support both Tollmien-Schlichting and Taylor-Görtler instabilities. The question of which linear mode is dominant at finite values of the Reynolds numbers was discussed by Gibson & Cooke (Q. Jl Mech. appl. Math. 27, 149 (1974)). In a situation where both modes are possible on the basis of linear theory a nonlinear theory must be used, however, to determine the effect of the interaction of the instabilities. The details of this interaction are of practical importance because of its possible catastrophic effects on mechanisms used for laminar flow control. Here this interaction is studied in the context of fully developed flows in curved channels. Apart from technical differences associated with boundary-layer growth the structures of the instabilities in this flow can be very similar to those in the practically more important external boundary-layer situation. The interaction is shown to have two distinct phases depending on the size of the input disturbances. At very low amplitudes two oblique Tollmien–Schlichting waves interact with a Görtler vortex in such a manner that the scaled amplitudes become infinite at a finite time. This type of interaction is described by ordinary differential amplitude equations with quadratic nonlinearities. A stronger type of interaction occurs at larger input disturbance amplitudes and leads to a more complicated type of evolution equation. The solution of these equations now depends critically on the orientation of the wavefronts of the Tollmien–Schlichting waves to the Görtler vortex. Thus, if the angle between the directions of the vortex and the waves is greater than 41.6° this stronger interaction again terminates in a singularity at a finite time; otherwise the breakdown is exponential, taking an infinite time. Moreover, the stronger interaction can take place in the absence of curvature, in which case the longitudinal vortex is entirely driven by the Tollmien–Schlichting waves.
Adaptive Look-Ahead Distance Based on an Intelligent Fuzzy Decision for an Autonomous Vehicle

Autonomous vehicles use a set of perceptual and localization data proceeding from sensor measurements, in order to plan a certain trajectory based on decision-making, and finally to track the generated path. Trajectory following is performed by adjusting the steering angle generated by a lateral controller based on a geometric or non-geometric approach. The objective of the lateral controller is to minimize the lateral error between the vehicle and the path at a target point at a look-ahead distance from the vehicle. This paper investigates the look-ahead distance due to its high impact on performance alteration, and energy consumption. An intuitive analysis will be performed to study the effect of three varying parameters on the look-ahead distance, and the necessity to consider them. Then, a Fuzzy Logic approach will be established to adjust the look-ahead distance in accordance with three parameters: longitudinal velocity, road curvature, and original consideration of road adherence. Finally, a non-geometric model-based lateral controller will be developed based on the Super-Twisting Sliding Mode Control technique to control the steering angle via the Active Front Steering. The membership functions and the rules of the inputs and output of the Fuzzy Logic approach are implemented in a Matlab/Simulink environment and tested on a validated full non-linear vehicle model. Simulation results indicate the effectiveness of the fuzzy decision approach on the performance and energy consumption of the autonomous vehicle.
An intrusion detection system based on multiple interpretation methods

In recent years, many related researches on machine learning-based IDSs have achieved remarkable results. The researchers further focused on improving the interpretability of machine learning to increase the trustworthiness of the model. However, the discrepancy between the interpretation results and the expert knowledge also arises. In this paper we propose an Intrusion Detection System that combines multiple interpretable methods to achieve the best interpretation performance in terms of stability, loyalty and complexity, which makes the interpretation results closer to expert knowledge. This is the first study to combine multiple interpretation methods in the field of intrusion detection. Experiments show that the coincidence rate of the important features corresponding to four attacks given by our method and the artificially extracted expert knowledge increases by 26% and 46% on average compared with the results in SHAP-based-IDS and UFGM-IDS, respectively. NSL-KDD dataset is used as experimental validation in our experiment.
Students’ Reflective Abstraction in Solving Number Sequence Problems

This study is qualitative in nature, aims to describe students’ reflective abstraction in solving problems related to number sequence. As subjects of this study are 6 students, composed of 3 students (2 female and one male) from State Senior High School (SMAN) 1 Pasuruan, and 3 students (2 male and 1 female) from SMAN 1 Pandaan, East Java, Indonesia. In this study, the researchers were acted as human instruments. Narrative description was compiled by assembling descriptions of reflective abstraction stages associated with the criteria of high, intermediate, or low thinking processes, and the cognitive levels including knowledge application and reasoning. The results suggest that students’ strategies of problem solving are not directly proportional to their level of reflective abstraction. It was also found that students’ reflective abstraction furnish students’ individually unique solution, simply complicated, while interventions are important in its attainments.