Miracle-dz/UniFAR-FTUs huggingface dataset:
Lidar Remote Sensing for Ecosystem Studies

R sensing has facilitated extraordinary advances in the modeling, mapping, and understanding of ecosystems. Typical applications of remote sensing involve either images from passive optical systems, such as aerial photography and Landsat Thematic Mapper (Goward and Williams 1997), or to a lesser degree, active radar sensors such as RADARSAT (Waring et al. 1995). These types of sensors have proven to be satisfactory for many ecological applications, such as mapping land cover into broad classes and, in some biomes, estimating aboveground biomass and leaf area index (LAI). Moreover, they enable researchers to analyze the spatial pattern of these images. However, conventional sensors have significant limitations for ecological applications. The sensitivity and accuracy of these devices have repeatedly been shown to fall with increasing aboveground biomass and leaf area index (Waring et al. 1995, Carlson and Ripley 1997, Turner et al. 1999). They are also limited in their ability to represent spatial patterns: They produce only two-dimensional (x and y) images, which cannot fully represent the three-dimensional structure of, for instance, an old-growth forest canopy.Yet ecologists have long understood that the presence of specific organisms, and the overall richness of wildlife communities, can be highly dependent on the three-dimensional spatial pattern of vegetation (MacArthur and MacArthur 1961), especially in systems where biomass accumulation is significant (Hansen and Rotella 2000). Individual bird species, in particular, are often associated with specific three-dimensional features in forests (Carey et al. 1991). In addition, other functional aspects of forests, such as productivity, may be related to forest canopy structure. Laser altimetry, or lidar (light detection and ranging), is an alternative remote sensing technology that promises to both increase the accuracy of biophysical measurements and extend spatial analysis into the third (z) dimension. Lidar sensors directly measure the three-dimensional distribution of plant canopies as well as subcanopy topography, thus providing high-resolution topographic maps and highly accurate estimates of vegetation height, cover, and canopy structure. In addition, lidar has been shown to accurately estimate LAI and aboveground biomass even in those high-biomass ecosystems where passive optical and active radar sensors typically fail to do so. Lidar sensors The basic measurement made by a lidar device is the distance between the sensor and a target surface, obtained by determining the elapsed time between the emission of a shortduration laser pulse and the arrival of the reflection of that pulse (the return signal) at the sensor’s receiver. Multiplying this time interval by the speed of light results in a measurement of the round-trip distance traveled, and dividing that figure by two yields the distance between the sensor and the target (Bachman 1979). When the vertical distance between a sensor contained in a level-flying aircraft and the Earth’s sur-
Fatigue Crack Growth Behavior in Dissimilar Metal Weldment of Stainless Steel and Carbon Steel

Constant amplitude fatigue crack growth (FCG) tests were performed on dissimilar metal welded plates of Type 316L Stainless Steel (SS) and IS 2062 Grade A Carbon steel (CS). The plates were welded by TIG welding using SS E309 as electrode. FCG tests were carried on the Side Edge Notch Tension (SENT) specimens of 5 mm thickness, with crack initiator (notch) at base metal region (BM), weld metal region (WM) and heat affected zones (HAZ). The tests were performed at a test frequency of 10 Hz and at load ratios (R) of 0.1 & 0.6. FCG rate was found to increase with stress ratio for weld metals and base metals, where as in case of HAZ, FCG rates were almost equal at high ΔK. FCG rate of HAZ of stainless steel was found to be lowest at low and high ΔK. At intermediate ΔK, WM showed the lowest FCG rate. CS showed higher crack growth rate at all ΔK. However, the scatter band of data was found to be narrow. Fracture toughness (Kc) was found to vary in different locations of weldments. Kc was found lowest for the weldment and highest for HAZ of stainless steel. A novel method of characterizing the FCG behavior using an Infrared thermography (IRT) camera was attempted. By monitoring the temperature rise at the fast moving crack tip region, the amount of plastic deformation was estimated. Keywords—Dissimilar metal weld, Fatigue Crack Growth,
Speaker identification in noisy environments using dynamic Bayesian networks

This paper describes the theory and implementation of dynamic Bayesian networks in the context of speaker identification. Dynamic Bayesian networks provide a succinct and expressive graphical language for factoring joint probability distributions, and we begin by presenting the structures that are appropriate for doing speaker identification in clean and noisy environments. This approach is notable because it expresses an identification system using only the concepts of random variables and conditional probabilities. We present illustrative experiments in both clean and noisy environments and our experiments show that this new approach is very promising in the field of speaker identification.
Complex analysis of intracranial hypertension using approximate entropy*

Objective:To determine whether decomplexification of intracranial pressure dynamics occurs during periods of severe intracranial hypertension (intracranial pressure >25 mm Hg for >5 mins in the absence of external noxious stimuli) in pediatric patients with intracranial hypertension. Design:Retrospective analysis of clinical case series over a 30-month period from April 2000 through January 2003. Setting:Multidisciplinary 16-bed pediatric intensive care unit. Patients:Eleven episodes of intracranial hypertension from seven patients requiring ventriculostomy catheter for intracranial pressure monitoring and/or cerebral spinal fluid drainage. Interventions:None. Measurements and Main Results:We measured changes in the intracranial pressure complexity, estimated by the approximate entropy (ApEn), as patients progressed from a state of normal intracranial pressure (<25 mm Hg) to intracranial hypertension. We found the ApEn mean to be lower during the intracranial hypertension period than during the stable and recovering periods in all the 11 episodes (0.5158 ± 0.0089, 0.3887 ± 0.077, and 0.5096 ± 0.0158, respectively, p < .01). Both the mean reduction in ApEn from the state of normal intracranial pressure (stable region) to intracranial hypertension (−0.1271) and the increase in ApEn from the ICH region to the recovering region (0.1209) were determined to be statistically significant (p < .01). Conclusions:Our results indicate that decreased complexity of intracranial pressure coincides with periods of intracranial hypertension in brain injury. This suggests that the complex regulatory mechanisms that govern intracranial pressure may be disrupted during acute periods of intracranial hypertension. This phenomenon of decomplexification of physiologic dynamics may have important clinical implications for intracranial pressure management.
Taylor series expansions for stationary Markov chains

We study Taylor series expansions of stationary characteristics of general-state-space Markov chains. The elements of the Taylor series are explicitly calculated and a lower bound for the radius of convergence of the Taylor series is established. The analysis provided in this paper applies to the case where the stationary characteristic is given through an unbounded sample performance function such as the second moment of the stationary waiting time in a queueing system.
Expression Analysis of Genes Involved in the RB/E2F Pathway in Astrocytic Tumors

Astrocytic gliomas, which are derived from glial cells, are considered the most common primary neoplasias of the central nervous system (CNS) and are histologically classified as low grade (I and II) or high grade (III and IV). Recent studies have shown that astrocytoma formation is the result of the deregulation of several pathways, including the RB/E2F pathway, which is commonly deregulated in various human cancers via genetic or epigenetic mechanisms. On the basis of the assumption that the study of the mechanisms controlling the INK4/ARF locus can help elucidate the molecular pathogenesis of astrocytic tumors, identify diagnostic and prognostic markers, and help select appropriate clinical treatments, the present study aimed to evaluate and compare methylation patterns using bisulfite sequencing PCR and evaluate the gene expression profile using real-time PCR in the genes CDKN2A, CDKN2B, CDC6, Bmi-1, CCND1, and RB1 in astrocytic tumors. Our results indicate that all the evaluated genes are not methylated independent of the tumor grade. However, the real-time PCR results indicate that these genes undergo progressive deregulation as a function of the tumor grade. In addition, the genes CDKN2A, CDKN2B, and RB1 were underexpressed, whereas CDC6, Bmi-1, and CCND1 were overexpressed; the increase in gene expression was significantly associated with decreased patient survival. Therefore, we propose that the evaluation of the expression levels of the genes involved in the RB/E2F pathway can be used in the monitoring of patients with astrocytomas in clinical practice and for the prognostic indication of disease progression.
Reflections on reflexions — I. Light echoes in Type Ia supernovae

In the last 10 yr, observational evidence has been steadily growing about a possible connection between Type Ia supernovae (SNe Ia) properties and the environment where they explode. In this paper, I discuss, from a theoretical point of view but with an observer's perspective, the usage of light echoes (LEs) to probe the circumstellar matter around SNe Ia because, in principle, they give us a unique opportunity for obtaining a three-dimensional description of the SN environment. In turn, this can be used to check the often suggested association of some SNe Ia with dusty/star-forming regions, which would point to a young population for the progenitors. After giving a brief introduction to the LE phenomenon in the single scattering approximation, I derive analytical and numerical solutions for the optical light and colour curves for a few simple dust geometries. A fully three-dimensional multiple scattering treatment has also been implemented in a Monte Carlo (MC) code, which I have used to investigate the effects of multiple scattering. In particular, I have explored in detail the LE colour dependency from time and dust distribution, because this is a promising tool to determine the dust density and derive the effective presence of multiple scattering from the observed properties. Finally, again by means of Monte Carlo simulations, I have studied the effects of multiple scattering on the LE linear polarization, analysing the dependences from the dust parameters and geometry. Both the analytical formalism and MC codes described in this paper can be used for any LE for which the light curve of the central source is known.
Transient DNMT1 suppression reveals hidden heritable marks in the genome

Genome-wide demethylation and remethylation of DNA during early embryogenesis is essential for development. Imprinted germline differentially methylated domains (gDMDs) established by sex-specific methylation in either male or female germ cells, must escape these dynamic changes and sustain precise inheritance of both methylated and unmethylated parental alleles. To identify other, gDMD-like sequences with the same epigenetic inheritance properties, we used a modified embryonic stem (ES) cell line that emulates the early embryonic demethylation and remethylation waves. Transient DNMT1 suppression revealed gDMD-like sequences requiring continuous DNMT1 activity to sustain a highly methylated state. Remethylation of these sequences was also compromised in vivo in a mouse model of transient DNMT1 loss in the preimplantation embryo. These novel regions, possessing heritable epigenetic features similar to imprinted-gDMDs are required for normal physiological and developmental processes and when disrupted are associated with disorders such as cancer and autism spectrum disorders. This study presents new perspectives on DNA methylation heritability during early embryo development that extend beyond conventional imprinted-gDMDs.
NADPH oxidase mediates hypersomnolence and brain oxidative injury in a murine model of sleep apnea.

RATIONALE Persons with obstructive sleep apnea may have significant residual hypersomnolence, despite therapy. Long-term hypoxia/reoxygenation events in adult mice, simulating oxygenation patterns of moderate-severe sleep apnea, result in lasting hypersomnolence, oxidative injury, and proinflammatory responses in wake-active brain regions. We hypothesized that long-term intermittent hypoxia activates brain NADPH oxidase and that this enzyme serves as a critical source of superoxide in the oxidation injury and in hypersomnolence. OBJECTIVES We sought to determine whether long-term hypoxia/reoxygenation events in mice result in NADPH oxidase activation and whether NADPH oxidase is essential for the proinflammatory response and hypersomnolence. METHODS NADPH oxidase gene and protein responses were measured in wake-active brain regions in wild-type mice exposed to long-term hypoxia/reoxygenation. Sleep and oxidative and proinflammatory responses were measured in adult mice either devoid of NADPH oxidase activity (gp91phox-null mice) or in which NADPH oxidase activity was systemically inhibited with apocynin osmotic pumps throughout hypoxia/reoxygenation. MAIN RESULTS Long-term intermittent hypoxia increased NADPH oxidase gene and protein responses in wake-active brain regions. Both transgenic absence and pharmacologic inhibition of NADPH oxidase activity throughout long-term hypoxia/reoxygenation conferred resistance to not only long-term hypoxia/reoxygenation hypersomnolence but also to carbonylation, lipid peroxidation injury, and the proinflammatory response, including inducible nitric oxide synthase activity in wake-active brain regions. CONCLUSIONS Collectively, these findings strongly support a critical role for NADPH oxidase in the lasting hypersomnolence and oxidative and proinflammatory responses after hypoxia/reoxygenation patterns simulating severe obstructive sleep apnea oxygenation, highlighting the potential of inhibiting NADPH oxidase to prevent oxidation-mediated morbidities in obstructive sleep apnea.
On the Worst-Case Approximability of Sparse PCA

It is well known that Sparse PCA (Sparse Principal Component Analysis) is NP-hard to solve exactly on worst-case instances. What is the complexity of solving Sparse PCA approximately? Our contributions include: 1) a simple and efficient algorithm that achieves an $n^{-1/3}$-approximation; 2) NP-hardness of approximation to within $(1-\varepsilon)$, for some small constant $\varepsilon > 0$; 3) SSE-hardness of approximation to within any constant factor; and 4) an $\exp\exp\left(\Omega\left(\sqrt{\log \log n}\right)\right)$ ("quasi-quasi-polynomial") gap for the standard semidefinite program.
Visual-Based Impedance Control of Out-of-Plane Cell Injection Systems

In this paper, a vision-based impedance control algorithm is proposed to regulate the cell injection force, based on dynamic modeling conducted on a laboratory test-bed cell injection system. The injection force is initially calibrated to derive the relationship between the force and the cell deformation utilizing a cell membrane point-load model. To increase the success rate of injection, the injector is positioned out of the focal plane of the camera, used to obtain visual feedback for the injection process. In this out-of-plane injection process, the total cell membrane deformation is estimated, based on the X-Y coordinate frame deformation of the cell, as measured with a microscope, and the known angle between the injector and the X-Y plane. Further, a relationship between the injection force and the injector displacement of the cell membrane, as observed with the camera, is derived. Based on this visual force estimation scheme, an impedance control algorithm is developed. Experimental results of the proposed injection method are given which validate the approach.
OFDM for next generation optical communication systems

A number of different forms of Orthogonal Frequency Division Multiplexing (OFDM) have recently been developed for application in a range of optical systems. In this presentation the key differences between these are explained. Analytical techniques developed for conventional optical modulation formats cannot always be applied successfully to optical OFDM. For example, in calculating the effect of nonlinearities in OFDM, the overall shrinkage or rotation of the constellation may be a significant effect. Depending on the properties of phase noise, the distortion caused may be easily corrected in the digital section of the OFDM receiver.
Towards a Tunable Multi-Backend Skeleton Programming Framework for Multi-GPU Systems

SkePU is a C++ template library that provides a simple and unified interface for specifying data-parallel computations with the help of skeletons on GPUs using CUDA and OpenCL. The interface is also general enough to support other architectures, and SkePU implements both a sequential CPU and a parallel OpenMP backend. It also supports multi-GPU systems. Currently available skeletons in SkePU include map, reduce, mapreduce, map-with-overlap, maparray, and scan. The performance of SkePU generated code is comparable to that of hand-written code, even for more complex applications such as ODE solving. In this paper, we describe how to make SkePU tunable, by adding the mechanism of execution plans that can configure a skeleton so that, at run time, the predicted best suitable resource and platform is chosen automatically, depending on operand data sizes. We also discuss how the approach can be extended to provide a fully auto-tunable skeleton programming system, which is a work in progress.
Comparison of Differential Evolution, Particle Swarm Optimization and Genetic Algorithms for the identification of Bouc-Wen hysteretic systems

In this paper, several variants of Differential Evolution, Particle Swarm Optimization and Genetic Algorithms are employed for the identification of a Bouc-Wen hysteretic system that represents a full-scale bolted-welded steel connection. The purpose of this work is to assess their comparative performance in a highly non-linear identification problem. Interesting results are produced that reveal the strengths and weaknesses of each algorithm.
A stochastic MIMO radio channel model with experimental validation

Theoretical and experimental studies of multiple-input/multiple-output (MIMO) radio channels are presented. A simple stochastic MIMO model channel has been developed. This model uses the correlation matrices at the mobile station (MS) and base station (BS) so that results of the numerous single-input/multiple-output studies that have been published in the literature can be used as input parameters. The model is simplified to the narrowband channels. The validation of the model is based upon data collected in both picocell and microcell environments. The stochastic model has also been used to investigate the capacity of MIMO radio channels, considering two different power allocation strategies, water filling and uniform and two different antenna topologies, 4/spl times/4 and 2/spl times/4. Space diversity used at both ends of the MIMO radio link is shown to be an efficient technique in picocell environments, achieving capacities within 14 b/s/Hz and 16 b/s/Hz in 80% of the cases for a 4/spl times/4 antenna configuration implementing water filling at a SNR of 20 dB.
The Physics of Galaxy Clustering. I. A Model for Subhalo Populations

We present a semianalytic model for cold dark matter halo substructure that can be used as a framework for studying the physics of galaxy formation and as an ingredient in halo models of galaxy clustering. The model has the following main ingredients: (1) extended Press-Schechter mass accretion histories, (2) host halo density profiles computed according to the trends observed in cosmological simulations, (3) distributions of initial orbital parameters of accreting subhalos measured in a high-resolution simulation of three Milky Way-size halos, and (4) integration of the orbital evolution of subhalos including the effects of dynamical friction and tidal mass loss. We perform a comprehensive comparison of the model calculations to the results of a suite of high-resolution cosmological simulations. The comparisons show that subhalo statistics such as the velocity and mass functions, the radial distributions, and the halo occupation distributions agree well over 3 orders of magnitude in host halo mass and at various redshifts. We find that both in the simulations and in our model the radial distributions of subhalos are significantly shallower than that of the dark matter density. The abundance of subhalos in a host is set by competition between tidal disruption and new accretion. Halos of high mass and halos at high redshift tend to host more subhalos because the subhalos have, on average, been accreted more recently. Similarly, at a fixed mass and epoch, halos that formed more recently host a larger number of subhalos. Observed "fossil groups" may represent an extreme tail of this correlation. We find a related correlation between host halo concentration and satellite abundance at fixed host mass, Nsat ∝ c, where a changes with redshift and host-to-subhalo mass ratio. Lastly, we use our substructure model to populate host halos in one of the high-resolution cosmological simulations, replacing the actual subhalos resolved in this simulation and using the host mass as the only input for the model calculation. We show that the resulting correlation function of such a hybrid halo ensemble is indistinguishable from that measured directly in the simulation. This supports one of the key tenets of the standard halo model, i.e., the assumption that the halo occupation distribution is statistically independent of the host halo environment.
Statistical Learning Algorithms Applied to Automobile Insurance Ratemaking

AbstractThe following sections are included:IntroductionConcepts of Statistical Learning TheoryHypothesis Testing: an ExampleParameter Optimization: an ExampleMathematical ObjectivesThe Precision CriterionThe Fairness CriterionMethodologyModelsConstant ModelLinear ModelTable-Based MethodsGreedy Multiplicative ModelGeneralized Linear ModelCHAID Decision TreesCombination of CHAID and Linear ModelOrdinary Neural NetworkHow Can Neural Networks Represent Nonlinear Interactions? Softplus Neural NetworkRegression Support Vector MachineMixture ModelsExperimental ResultsMean-Squared Error ComparisonsEvaluating Model FairnessComparison with Current PremiumsApplication to Risk Sharing Pool FacilitiesConclusionAppendixReferences
Evaluation of Visual Aid Enhancement Algorithms for Real-time Embedded Systems

Individuals with visual impairments often suffer from a loss of visual sensitivity to high spatial frequencies that cannot be effectively treated by traditional methods. Recent developments in digital image processing technologies have allowed new and effective visual enhancement techniques to be investigated resulting in augmented visual aid. Edge detection, a digital image processing technique, has become a critical stage in enhancing the visually lost high spatial frequency components for the visually impaired. Visual aid devices require effective and efficient implementation of edge detection for use within real-time embedded platforms. This paper evaluates multiple edge detection algorithms of various complexity realized within a 6416 DSP and a Virtex-5 FPGA. In addition, the mathematically complex Statistical edge detection technique is presented and optimized for use within embedded devices. The optimized FPGA realization demonstrates throughput improvements of 137.66% and is comparable to a FPGA implemented Canny edge detection throughput and resources.