Miracle-dz/UniFAR-FTUs huggingface dataset:
Revisiting the status of space-borne lidar missions for assessing structural and biophysical forest parameters in the context of sustainable management of Earth resources.

Assessing forest aboveground biomass at global scale is crucial to address the challenge of sustainable management of forest resources and to strengthen forest-based climate change mitigation. To achieve this goal relying on spaceborne lidar missions is acknowledged to be a highly relevant solution. However, if this is taken as a given from the measurement point of view, the premise that spaceborne observation is the most suitable solution to provide information for sustainable management of forest resources is worth discussing. In this paper we suggest to take a fresh look at measurement processes designed to support the monitoring of Earth resources. We discuss the sustainability of Earth observation from space considering (1) issues that call into question the assumption that Earth-orbiting platform will always be available to the civilian remote sensing community and (2) issues concerning environmental impacts of space activity on the Earth. This leads us to suggest some actions that could help to design future observation systems in a more sustainable way in order to strengthen the capacity of measurement processes to meet their stated functional goal, i.e. sustainable management of forest resources.
Mining Check-In History for Personalized Location Naming

Many innovative location-based services have been established to offer users greater convenience in their everyday lives. These services usually cannot map user's physical locations into semantic names automatically. The semantic names of locations provide important context for mobile recommendations and advertisements. In this article, we proposed a novel location naming approach which can automatically provide semantic names for users given their locations and time. In particular, when a user opens a GPS device and submits a query with her physical location and time, she will be returned the most appropriate semantic name. In our approach, we drew an analogy between location naming and local search, and designed a local search framework to propose a spatiotemporal and user preference (STUP) model for location naming. STUP combined three components, user preference (UP), spatial preference (SP), and temporal preference (TP), by leveraging learning-to-rank techniques. We evaluated STUP on 466,190 check-ins of 5,805 users from Shanghai and 135,052 check-ins of 1,361 users from Beijing. The results showed that SP was most effective among three components and that UP can provide personalized semantic names, and thus it was a necessity for location naming. Although TP was not as discriminative as the others, it can still be beneficial when integrated with SP and UP. Finally, according to the experimental results, STUP outperformed the proposed baselines and returned accurate semantic names for 23.6% and 26.6% of the testing queries from Beijing and Shanghai, respectively.
Spectral atlas of massive stars around He I 10830 A

We present a digital atlas of peculiar, high-luminosity massive stars in the near-infrared region (10470-11000 A) at medium resolution (R~7000). The spectra are centered around He I 10830 A, which is formed in the wind of those stars, and is a crucial line to obtain their physical parameters. The instrumental configuration also sampled a rich variety of emission lines of Fe II, Mg II, C I, N I and Pa gamma. Secure identifications for most spectral lines are given, based on synthetic atmosphere models calculated by our group. We also propose that two unidentified absorption features have interstellar and/or circumstellar origin. For the strongest one (10780 A) an empirical calibration between E(B-V) and equivalent width is provided. The atlas displays the spectra of massive stars organized in four categories, namely Be stars, OBA Iape (or luminous blue variables, LBV candidates and ex/dormant LBVs), OB supergiants and Wolf-Rayet stars. For comparison, the photospheric spectra of non emission-line stars are presented. Selected LBVs were observed in different epochs from 2001 to 2004, and their spectral variability reveals that some stars, such as Eta Car, AG Car and HR Car, suffered dramatic spectroscopic changes during this time interval.
The Mediating Effect of Commitment on Customer Loyalty in eBrokerage: An Enhanced Investment Model

Customers could switch service provider easily because of lower searching cost and identical service in online environment. Most marketing research for customer loyalty emphasizes the effect of satisfaction and switching barrier, derived from investment model. However, how satisfaction and switching barrier influence customer loyalty has been less conclusive. The possible reason is neglect of commitment. We inject the concept of commitment in relationship marketing, which consists of affective and continuous commitment, into investment model for enhancing mediating role of commitment. Empirical results gathered from online survey in virtual financial communities show that commitment is the essential mediator in cultivating customer loyalty. Besides, satisfaction and switching barrier influence loyalty by different component of commitment, affective continuous commitment respectively. Affective commitment is more important than continuous commitment. E-brokerage should pay attention to earning customers’ commitment for retaining customers.
Molecular mechanisms of master regulator VqsM mediating quorum-sensing and antibiotic resistance in Pseudomonas aeruginosa

The Pseudomonas aeruginosa quorum-sensing (QS) systems contribute to bacterial homeostasis and pathogenicity. Although the AraC-family transcription factor VqsM has been characterized to control the production of virulence factors and QS signaling molecules, its detailed regulatory mechanisms still remain elusive. Here, we report that VqsM directly binds to the lasI promoter region, and thus regulates its expression. To identify additional targets of VqsM in P. aeruginosa PAO1, we performed chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-seq) and detected 48 enriched loci harboring VqsM-binding peaks in the P. aeruginosa genome. The direct regulation of these genes by VqsM has been confirmed by electrophoretic mobility shift assays and quantitative real-time polymerase chain reactions. A VqsM-binding motif was identified by using the MEME suite and verified by footprint assays in vitro. In addition, VqsM directly bound to the promoter regions of the antibiotic resistance regulator NfxB and the master type III secretion system (T3SS) regulator ExsA. Notably, the vqsM mutant displayed more resistance to two types of antibiotics and promoted bacterial survival in a mouse model, compared to wild-type PAO1. Collectively, this work provides new cues to better understand the detailed regulatory networks of QS systems, T3SS, and antibiotic resistance.
Comparison of intravenous aminophylline and salbutamol in severe asthma.

Twenty hospital patients with severe asthma, with a pulse rate of > 120/ min, peak flow rate (PFR) <25°' predicted, and Pao2 <93 kPa (69-8 mm Hg) gave informed consent. All were given 1 g of hydrocortisone intravenously initially and oxygen by 28%h Ventimask (except during the five minutes before each arterial puncture). Either aminophylline 0-5 g or salbutamol 500 ,ig was given intravenously over one hour by constant rate infusion pump. They were dispensed in identical ampoules, labelled by number, and allocated randomly and double blind. Response to treatment was measured by a Wright peak flow meter, the best of three readings taken 10 and 5 minutes before treatment and every 10 minutes during the infusion, and arterial gases (Astrup micro-method) at 0, 15, and 60 minutes. Pulse and blood pressure were recorded every 10 minutes and the electrocardiograph monitored continually. Patients given an intravenous bronchodilator within 3 hours before admission were excluded. Results were analysed as the mean peak increase or decrease during drug administration and also as the average increase (or area under the curve), using a t test for unpaired samples. Eleven patients received salbutamol and 9 aminophylline. Both drugs produced a significant increase in PFR, greater after salbutamol, though the difference between the drugs was not statistically significant (see table). Pulse rate fell after aminophylline but not after salbutamol, the difference between the two being significant. The diastolic blood pressure fell after salbutamol but not after aminophylline. No significant changes in blood gases occurred after either drug. Side effects occurred in 7 of the 9 patients given aminophylline and in 5 of the 11 given salbutamol. Two given aminophylline and 3 given salbutamol experienced headache. Three of the aminophylline group and 2 of the salbutamol group experienced tremor. Nausea (4 patients), vomiting (1 patient), and ventricular extrasystoles (4 patients) occurred only in those given aminophylline. In one patient, who also had mitral valve disease, the ventricular extrasystoles became fewer during the salbutamol infusion. No significant changes occurred in the serum potassium during the infusion in either group.
CS 348 b Final Project : Ray-tracing Interference and Diffraction

Although inherently a wave phenomena, diffraction can be implemented in a ray tracer by taking advantage of a combination of Geometric Diffraction Theory and the Huygens’-Fresnel Principle. In this paper we show how to implement interference and diffraction in a computationally tractable manner, while retaining the properties of the full volume integration solution.
An efficient low-complexity joint multi-user power control and partial crosstalk cancellation in xDSL systems

Perfect crosstalk cancellation techniques have been proposed to mitigate the effect of crosstalk. However, the online complexity of these crosstalk cancellation techniques grows with the square of the number of lines in the binder. Fortunately, most of the crosstalk originates from a limited number of lines on a limited number of tones. As a result, a fraction of the complexity of perfect crosstalk cancellation suffices to cancel most of the crosstalk. This is known as partial crosstalk cancellation. Because the crosstalk profile changes over time, there is additional requirement that partial crosstalk cancellation provide a very low pre-processing complexity. Also, a much lower online complexity can be obtained if the multi-user power control and partial crosstalk cancellation problems are solved jointly. Currently, this joint problem is formulated as a constrained optimization problem and solved by employing Lagrange dual decomposition method. However, it suffers from per-tone exhaustive search because of non-convexity of its per-tone problem. This paper presents a solution for the joint multi-user power control and partial crosstalk cancellation problem with significantly lower pre-processing complexity than the currently proposed algorithms. The problem is considered as a mixed binary-non-convex problem. Then it is reformulated as a mixed binary-convex problem via a successive convex relaxation. Finally it is solved by an efficient branch and bound method. The complexity analysis of our algorithm shows that it provide much lower pre-processing complexity than currently proposed algorithms, allowing it to work efficiently in time-varying crosstalk environment. Moreover, the analytical and simulation results demonstrate that our algorithm is close to the optimal solution from the crosstalk cancellation point of view.
Modeling inter-speaker variability in speech recognition

This paper details a method for taking into account variability influence in HMM-based speech recognition. The set of Gaussian components of the mixtures represents the entire acoustic space covered for all possible variability values. For each utterance to be recognized, the corresponding variability value is estimated and used to weight and/or constrain dynamically the acoustic space for each pdf. To do that, the weight coefficients of the Gaussian mixtures are set dependent on the variability value. As an example, the variability considered is the inter-speaker variability, and is handled through speaker classes. Taking into account for each utterance the four speaker classes that best match with the utterance signal leads to a significant word error rate reduction on a continuous speech recognition task, as compared to standard speaker-independent modeling.
The Food Security Policy Context in Brazil

Brazil currently offers an important conceptual framework for food and nutritional security, and a relevant context of related public policy and programming. Recently, moreover, the country included the right to food among the social rights stipulated in its constitution. These achievements are the result of a longstanding process of public intervention and broad social mobilisation that has involved a variety of stakeholders from the government and civil society. As far as public programming is concerned, several actions that may reflect on food and nutritional conditions were taken in Brazil throughout the twentieth century, such as the minimum wage in 1940, supply programmes, school meals and dining halls for workers in the 1950s, and food supplement programmes in the 1970s (CONSEA, 2009). (.)
Next generation image based lighting using HDR video

We present an overview of our recently developed systems pipeline for capture, reconstruction, modeling and rendering of real world scenes based on state-of-the-art high dynamic range video (HDRV). The reconstructed scene representation allows for photo-realistic Image Based Lighting (IBL) in complex environments with strong spatial variations in the illumination. The pipeline comprises the following essential steps: 1. ) Capture - The scene capture is based on a 4MPixel global shutter HDRV camera with a dynamic range of more than 24 f-stops at 30 fps. The HDR output stream is stored as individual un-compressed frames for maximum flexibility. A scene is usually captured using a combination of panoramic light probe sequences [1], and sequences with a smaller field of view to maximize the resolution at regions of special interest in the scene. The panoramic sequences ensure full angular coverage at each position and guarantee that the information required for IBL is captured. The position and orientation of the camera is tracked during capture. 2. ) Scene recovery - Taking one or more HDRV sequences as input, a geometric proxy model of the scene is built using a semi-automatic approach. First, traditional computer vision algorithms such as structure from motion [2] and Manhattan world stereo [3] are used. If necessary, the recovered model is then modified using an interaction scheme based on visualizations of a volumetric representation of the scene radiance computed from the input HDRV sequence. The HDR nature of this volume also enables robust extraction of direct light sources and other high intensity regions in the scene. 3. ) Radiance processing - When the scene proxy geometry has been recovered, the radiance data captured in the HDRV sequences are re-projected onto the surfaces and the recovered light sources. Since most surface points have been imaged from a large number of directions, it is possible to reconstruct view dependent texture maps at the proxy geometries. These 4D data sets describe a combination of detailed geometry that has not been recovered and the radiance reflected from the underlying real surfaces. The view dependent textures are then processed and compactly stored in an adaptive data structure. 4. ) Rendering - Once the geometric and radiometric scene information has been recovered, it is possible to place virtual objects into the real scene and create photo-realistic renderings as illustrated above. The extracted light sources enable efficient sampling and rendering times that are fully comparable to that of traditional virtual computer graphics light sources. No previously described method is capable of capturing and reproducing the angular and spatial variation in the scene illumination in comparable detail. We believe that the rapid development of high quality HDRV systems will soon have a large impact on both computer vision and graphics. Following this trend, we are developing theory and algorithms for efficient processing HDRV sequences and using the abundance of radiance data that is going to be available.
Abortion Law Reformed

This book is the first fully documented account of the 30-year campaign to replace Britain's severe and archaic abortion law. Starting with the work of the Abortion Law Reform Association in the 1930s, it reaches into the 19690s as change begins to become imminent thanks to a new generation of reformers. With an introduction by David Steel.
There Is No Logical Negation Here, But There Are Alternatives: Modeling Conversational Negation with Distributional Semantics

Logical negation is a challenge for distributional semantics, because predicates and their negations tend to occur in very similar contexts, and consequently their distributional vectors are very similar. Indeed, it is not even clear what properties a “negated” distributional vector should possess. However, when linguistic negation is considered in its actual discourse usage, it often performs a role that is quite different from straightforward logical negation. If someone states, in the middle of a conversation, that “This is not a dog,” the negation strongly suggests a restricted set of alternative predicates that might hold true of the object being talked about. In particular, other canids and middle-sized mammals are plausible alternatives, birds are less likely, skyscrapers and other large buildings virtually impossible. Conversational negation acts like a graded similarity function, of the sort that distributional semantics might be good at capturing. In this article, we introduce a large data set of alternative plausibility ratings for conversationally negated nominal predicates, and we show that simple similarity in distributional semantic space provides an excellent fit to subject data. On the one hand, this fills a gap in the literature on conversational negation, proposing distributional semantics as the right tool to make explicit predictions about potential alternatives of negated predicates. On the other hand, the results suggest that negation, when addressed from a broader pragmatic perspective, far from being a nuisance, is an ideal application domain for distributional semantic methods.
Low-complexity supervised learning for gesture and shape recognition

Classi cation is a machine learning task in which the objective is to categorize given samples according to their attributes. Gesture Recognition (GR) and Shape Recognition (SR) are two classi cation examples. Some daily-life applications of these include Hand Gesture Recognition (HGR) and Optical Character Recognition (OCR). GR is a challenging classi cation problem often used in human-computer interaction applications to provide a natural interface between user and computer. Since the same gesture might be performed with di erent speeds, Dynamic Time Warping (DTW) is needed to nd the optimal alignment between two time sequences. Oftentimes a preprocessing of sequences is required to remove variations between the reference gestures and the test gestures. We discuss a set of pre-processing methods to make the gesture recognition mechanism robust to these variations. DTW computes a dissimilarity measure by time-warping the sequences on a per sample basis by using the distance between the current reference and test sequences. However, all body joints involved in a gesture are not equally important in computing the distance between two sequence samples. We propose a weighted DTW method that weights joints by optimizing a discriminant ratio. SR is another classi cation problem with increasing number of applications from OCR to pedestrian detection. Decision tree is a good choice of classi er for shape recognition because it is easy to implement and visualize and has lower computational complexity. Bagging randomized decision trees as random forests increases the accuracy rates if the trees are weakly correlated. We propose using random rectangles in combination with random forests and test our method on OCR and GR datasets. We show that the accuracy of our method is similar to the OCR state-of-the-art and better than the GR state-of-the-art, while executing signi cantly faster, which makes our proposed method a good t for real-time object/shape recognition. Then discuss how a simple feature such as a random rectangle can perform similar to the complex statistical and structural features designed for shape recognition. Finally we analyze the e ect of our parameters.
Complex Event Detection in Probabilistic Stream

Complex event detection in stream is an important problem in event stream processing field. In this paper, we propose a new complex event detection algorithm in probabilistic stream, Instance Pruning and Filter-Detection Algorithm (IPF-DA). This algorithm is based on a kind of data structure called Chain Instance Queues (CIQ), to detect complex events satisfying query requirements with single-scanning probabilistic stream. In the process of complex event detection, IPF-DA prunes unnecessary event instances with query requirements and achieves filter for complex events with the given threshold. And it further improves the efficiency by setting proper tolerance, while insuring high recall. In addition, we construct Bayesian network to express and infer the probability distribution of uncertain events. Conditional Probability Indexing-Tree (CPI-Tree) is defined to store conditional probabilities of Bayesian network, saving query time compared with traditional Conditional Probability Table (CPT). Experimental results show that a series of strategies proposed by this paper are effective for complex event detection in probabilistic stream.
Two ball juggling with high-speed hand-arm and high-speed vision system

Humans can perform fast and skillful manipulations using various parts of the body by effectively utilizing the dynamics of the targets. Visual sensation is the most important human sense used for such manipulations. Juggling is one such example involving skillful and dynamic manipulations, and visual information is essential for it to be successful. Previously, there have been several studies about robotic juggling. However, none of these studies have considered cases in which a human-like multifingered hand-arm is used for the robotic juggling. The purpose of this study is to achieve two-ball juggling using our robotic hand-arm, which has three general purpose fingers, and stereo vision. Image processing is executed at 500 fps using a high-speed vision system and graphics processing unit (GPU). The trajectory of the robotic hand-arm is generated based on the ball's estimated dropping position and moment, and the robot catches the ball. The juggling motion is achieved by repeating this cycle. Therefore, the results show that the robot successfully juggles two balls using our hand-arm system.