Miracle-dz/UniFAR-FTUs huggingface dataset:
Multisensor integrated stair recognition and parameters measurement system for dynamic stair climbing robots

In this paper, we develop an online real-time system using Kinect and inertial measurement unit (IMU) to recognize and measure stairs for stair climbing tasks of erect mobile robots. This system combines the ideas of statistical characteristics of 3D point cloud data and adjustable geometric models for stair recognition tasks. Through this system, we not only verify the advantages of statistics methods in 3D environment perception process, but also realize the idea of using adjustable geometric models to fit 3D perception data correctly and efficiently. Because our stair recognition system keeps good quality results (average errors within ±0.4 cm) and less time consumption (less than 0.1 second per frame) even under dynamic situations, it is expected that it can help mobile robots to achieve online dynamic stair climbing tasks.
Grasslands Kara cocksfoot : a productive cultivar under lax grazing

Field testing compared the agronomic performance of Grasslands Kara cocksfoot (Dactylis glomera&a L.) with other commercially available cocksfoot cultivars and perennial ryegrass (Ldium perenne L.) in Southland and Canterbury. Animal performance was also assessed in southland. Kara cocksfoot had the highest establishment score of the cocksfoot cultivars in Canterbury but was slower to establish than ryegrass. Annual yields of Kara cocksfoot were 7% lower than Wana in Southland. The yield of Kara in Canterbury was 131 and 74% greater than ryegrass in a dry summer and autumn respectively. In Southland the pasture production from Kara under goat grazing was never significantly different from that of Nui ryegrass. The liveweight gains of both sheep and goats on Kara pastures were similar to those on ryegrass. Pasture digestibility was lower for Kara than Nui ryegrass pastures in spring but similar in summer and autumn. Pasture protein content was higher for Kara than Nui pastures in spring and similar in summer and autumn. The leaf-stem ratio of Kara was higher than Nui in spring but similar in summer and autumn. Rust tolerance of Kara was high and similar to Wana and Porto. The results from animal performance and pasture parameters show that Kara has a high feeding value. The effects of winter frost damage were greater on Kara and Wana than on Apanui due to their winter activity.
Robust Retinal Vessel Segmentation via Locally Adaptive Derivative Frames in Orientation Scores

This paper presents a robust and fully automatic filter-based approach for retinal vessel segmentation. We propose new filters based on 3D rotating frames in so-called orientation scores, which are functions on the Lie-group domain of positions and orientations ℝ2 × S1. By means of a wavelet-type transform, a 2D image is lifted to a 3D orientation score, where elongated structures are disentangled into their corresponding orientation planes. In the lifted domain ℝ2 × S1, vessels are enhanced by means of multi-scale second-order Gaussian derivatives perpendicular to the line structures. More precisely, we use a left-invariant rotating derivative (LID) frame, and a locally adaptive derivative (LAD) frame. The LAD is adaptive to the local line structures and is found by eigensystem analysis of the left-invariant Hessian matrix (computed with the LID). After multi-scale filtering via the LID or LAD in the orientation score domain, the results are projected back to the 2D image plane giving us the enhanced vessels. Then a binary segmentation is obtained through thresholding. The proposed methods are validated on six retinal image datasets with different image types, on which competitive segmentation performances are achieved. In particular, the proposed algorithm of applying the LAD filter on orientation scores (LAD-OS) outperforms most of the state-of-the-art methods. The LAD-OS is capable of dealing with typically difficult cases like crossings, central arterial reflex, closely parallel and tiny vessels. The high computational speed of the proposed methods allows processing of large datasets in a screening setting.
Analyzing vehicle traces to find and exploit correlated traffic lights for efficient driving

Traffic lights strongly impact vehicle movement and fuel consumption in cities. If drivers were aware of the situation at arrival time, they could adapt their velocity and thus reduce the number of unnecessary stops and fuel consumption. To predict the influence of the traffic light ahead on the velocity of an approaching vehicle, our vision is that drivers share their vehicle traces in a digital cloud, and in return benefit from algorithms evaluating the collected data. With Traffic Light Coordination Analysis (TLCorA), we present one such algorithm analyzing vehicle traces. When a vehicle is approaching a traffic light, TLCorA finds traces of vehicles similar to that of the vehicle at the previous traffic light, and calculates from their approach to the upcoming traffic light whether there is a representative approaching trace. For this purpose, TLCorA classifies the approaching traces with help of a clustering algorithm based on dynamic time warping. We implement TLCorA in simulations of different traffic light signalization algorithms, and study the calculated approach probabilities depending on the respective traffic light correlation level in the scenarios.
Inhibition of CETP by Torcetrapib Attenuates the Atherogenicity of Postprandial TG-Rich Lipoproteins in Type IIB Hyperlipidemia

Objective—The purpose of this study was to evaluate the impact of torcetrapib on atherogenic TG-rich lipoprotein subfractions in the postprandial phase in Type IIB hyperlipidemia. Methods and Results—The quantitative and qualitative features of the postprandial profile of TG-rich lipoproteins were determined at baseline, after treatment for 6 weeks with 10 mg/d atorvastatin, and subsequently with an atorvastatin/torcetrapib combination (10/60 mg/d) in Type IIB patients (n=18). After ingestion of a standardized mixed meal, TG-rich lipoprotein subfractions were evaluated over 8 hours after each experimental period. On a background of atorvastatin, torcetrapib significantly attenuated the incremental postprandial area under the curve (iAUC 0 to 8 hours) for VLDL-1 (−40%), and the AUC 0 to 8 hours for VLDL-2 (-53%), with minor effect on chylomicron iAUC (−24%); concomitantly, the CE/TG ratio in both VLDL-1 and VLDL-2 was significantly reduced (−27% to −42%). Such reduction was attributable to torcetrapib-mediated attenuation of postprandial CE transfer to Chylomicrons (−17%) and VLDL-1 (−33%). Marked reduction in postprandial VLDL-1 levels was associated with apoE enrichment. Conclusions—On a background of atorvastatin, torcetrapib attenuated the quantitative and qualitative features of the atherogenic postprandial profile of chylomicrons, VLDL-1 and VLDL-2. Such changes reflect the sum of torcetrapib-mediated effects on TG-rich lipoprotein production, intravascular remodeling, and catabolism.
Maize silage and winter crop options to maximise drymatter and energy for NZ dairy systems

Trade-offs in dry matter (DM) and metabolisable energy (ME) between combinations of three maize silage hybrids varying in maturity from 100-113 CRM and six winter forage options were investigated in a Waikato farmer’s field over 2 years. Winter crops were triticale, cut once; oats grazed 1-2 times; and Tama and Feast II Italian ryegrass, each cut or grazed 2-3 times. Greatest DM and ME production (38.9 t/ha; 396 GJ/ha) was from a 113 CRM hybrid followed by a single-cut triticale crop. The most economical sources of DM and ME were obtained from a 100 CRM maize hybrid plus grazed oats (11.8 c/ kg; 1.12 c/MJ), while the cheapest ME source among cut winter forages was a 113 CRM maize hybrid + triticale (1.18 c/MJ). Reliable annual silage production of 30 t DM/ha and 330 GJ ME/ha (or 3000 kg MS/ha) is possible using a late maturing maize hybrid combined with a winter forage crop such as triticale, although the low feed value of the triticale may limit its use as feed for milking cows.
Evaluation of Mucoadhesive Microspheres of Metronidazole Formulated Using Ionic Gelation Technique

DOI: 10.21276/sajp.2018. 7.12. 4 Abstract: Gastrointestinal drug delivery is a technique to prolong gastric residence time for site-specific targeted drug release. Mucoadhesive microsphere is an approach to achieve gastric retention for improved bioavailability. This study was aimed at preparing and evaluating metronidazole mucoadhesive microspheres using the ionic gelation technique. The microspheres were prepared by dispersing the polymers in distilled water followed by incorporation of the drug and extrusion into aqueous anhydrous calcium chloride solution. Different drug-polymer ratios were used for the process. The microspheres were evaluated for yield, compatibility studies using thin layer chromatography (TLC) and differential scanning calorimetry (DSC), swelling index, mucoadhesion, entrapment efficiency and drug release studies. Microspheres formulated exhibited no possible drug-polymer interactions. Retention factors of the microspheres were approximately the same with a deviation of ± 0.2 and this was corroborated by the information obtained from the DSC thermograms. Microspheres formulated using combinations of alginate and carbopol had higher swelling capacity up to 3 4 times their original weight. Percentage mucoadhesion was significant ranging from 48.50% 95% with combinations of alginate and carbopol adhering more. Entrapment efficiency was excellent ranging from 78.96% 92.35%. Drug release studies show sustained release of metronidazole and first order release with diffusion and erosion as the predominant release mechanism. Mucoadhesive microspheres of metronidazole can possibly be formulated using ionic gelation technique for site-specific targeted release. Metronidazole mucoadhesive microspheres may be used as an adjunct in the treatment of gastric ulcer, caused by Helicobacter pylori which reside mainly in the gastric mucosa.
Extraction And Determination Of Chlorophyll Content From Microalgae

In this experiment, we selected the two microalgae species, Chlorella and Nannochloropsis for their numerous benefits. The microalgae was cultured with Conway medium under laboratory condition to get biomass for the further experiments. The concentration of chlorophyll a and b was evaluated by these procedures; extraction of chlorophyll by solvent, determination of chlorophyll content by spectrophotometric method and calculation by SCOR-UNESCO equation. So, two types of chlorophyll a and b are present in the green microalgae. According to the results, Chlorella has chlorophyll a (8.45 μg/ml) and Chlorophyll b (4.33 μg/ml), Nannochloropsis has chlorophyll a (21.24 μg/ml) and chlorophyll b (9.66 μg/ml) respectively.
1 Multi-Battle Contests : An Experimental Study

We examine behavior of subjects in simultaneous and sequential multi-battle contests, where each individual battle is modeled as an all-pay auction with complete information. In simultaneous bestof-three contests, subjects are predicted to make positive bids in all three battles, but we find that subjects often make positive bids in only two battles. In sequential contests, theory predicts sizable bids in the first battle and no bids in the subsequent battles. Contrary to this prediction, subjects significantly underbid in the first battle and overbid in subsequent battles. Consequently, instead of always ending in the second battle, contests often proceeds to the third battle. Finally, although the aggregate bid in simultaneous contests is similar to that in sequential contests, in both settings, subjects make higher aggregate bids than predicted. The observed behavior of subjects can be rationalized by a combination of multi-dimensional iterative reasoning and a non-monetary utility of winning. JEL Classifications: C72, C91, D72
Influenza viral neuraminidase primes bacterial coinfection through TGF-β–mediated expression of host cell receptors

Significance Pneumonia caused by bacterial coinfection with influenza virus is the leading cause of mortality in influenza pandemics. TGF-β is known to be activated by influenza virus. In this study we demonstrated that cellular adhesins for bacteria, such as fibronectin and α5 integrin, are up-regulated in influenza viral infection. Inhibition of TGF-β impeded the up-regulation of these cellular adhesins and also influenza viral-enhanced bacterial adherence. In addition, we found that influenza viral-promoted bacterial adherence was dependent on bacterial fibronectin-binding protein. The results indicate that up-regulated expression of cellular adhesins by TGF-β, which is activated in influenza viral infection, increases host susceptibility to bacterial coinfection and suggest that TGF-β and host adhesion molecules are potential pharmaceutical targets for prevention of coinfection. Influenza infection predisposes the host to secondary bacterial pneumonia, which is a major cause of mortality during influenza epidemics. The molecular mechanisms underlying the bacterial coinfection remain elusive. Neuraminidase (NA) of influenza A virus (IAV) enhances bacterial adherence and also activates TGF-β. Because TGF-β can up-regulate host adhesion molecules such as fibronectin and integrins for bacterial binding, we hypothesized that activated TGF-β during IAV infection contributes to secondary bacterial infection by up-regulating these host adhesion molecules. Flow cytometric analyses of a human lung epithelial cell line indicated that the expression of fibronectin and α5 integrin was up-regulated after IAV infection or treatment with recombinant NA and was reversed through the inhibition of TGF-β signaling. IAV-promoted adherence of group A Streptococcus (GAS) and other coinfective pathogens that require fibronectin for binding was prevented significantly by the inhibition of TGF-β. However, IAV did not promote the adherence of Lactococcus lactis unless this bacterium expressed the fibronectin-binding protein of GAS. Mouse experiments showed that IAV infection enhanced GAS colonization in the lungs of wild-type animals but not in the lungs of mice deficient in TGF-β signaling. Taken together, these results reveal a previously unrecognized mechanism: IAV NA enhances the expression of cellular adhesins through the activation of TGF-β, leading to increased bacterial loading in the lungs. Our results suggest that TGF-β and cellular adhesins may be potential pharmaceutical targets for the prevention of coinfection.
TOWARDS OIC ECONOMIC COOPERATION: IMPACT OF DEVELOPING 8 (D-8) PREFERENTIAL TRADE AGREEMENT

The Developing 8 (D-8) comprises of eight developing countries (Turkey, Malaysia, Indonesia, Bangladesh, Pakistan, Iran, Egypt and Nigeria), all of which are OIC members with large Muslim populations. The D-8 has formed a freer trade alliance with the objectives to create new opportunities and enhance intra-trade relations while providing better standards of living for its citizens. This paper examines the trade impact of possible trade liberalization among the D-8 countries using a multi-country computable general equilibrium model, i.e., GTAP. Results indicate that while the D-8 intra-trade is expected to increase very substantially, not all member countries will experience a welfare gain under a free trade arrangement. Likewise, the impact on economic sectors differs substantially across countries.
1 An introduction to the formal approach to quantitative causal inference in epidemiology 1 . 1 Labels

Two recent articles, one by Vandenbroucke, Broadbent and Pearce (henceforth VBP) [1] and the other by Krieger and Davey Smith (henceforth KDS) [2], criticise what these two sets of authors characterise as the main stream of the modern “causal inference” school in epidemiology. The criticisms made by these authors are severe; VBP label the field as both “wrong in theory” and “wrong in practice”, whilst KDS—at least in some settings—feel that the field not only “bark[s] at the wrong tree” but “miss[es] the forest entirely”. More specifically, the school of thought, and the concepts and methods within it, are painted as being applicable only to a very narrow range of investigations, to the exclusion of most of the important questions and study designs in modern epidemiology, such as the effects of genetic variants, the study of ethnic and gender disparities, and the use of study designs that do not closely mirror RCTs. Furthermore, the concepts and methods are painted as being potentially highly misleading even within this narrow range in which they are deemed applicable. We believe that most of VBP’s and KDS’s criticisms stem from a series of misconceptions about the approach they criticise. In this response, therefore, we aim first to paint a more accurate picture of the formal causal inference approach (section 1), and then to outline the key misconceptions underlying VBP’s and KDS’s critiques (section 2). KDS, in particular, criticise DAGs using three examples to do so. Their discussion highlights further misconceptions concerning the role of DAGs in causal inference, and so we devote section 3 to addressing these. In our Discussion we present further objections we have to the arguments in the two papers before concluding that the clarity gained from adopting a rigorous framework is an asset, not an obstacle, to answering more reliably a very wide range of causal questions using data from observational studies of many different designs.
Universal critical adsorption profile from optical experiments.

The analysis of optical data for critical adsorption from a fluid (or fluid mixture) onto a wall or interface is discussed theoretically with emphasis on elucidating the universal, scaled adsorption profile P(z/\ensuremath{\xi}), where \ensuremath{\xi}(T) is the correlation length and z is the distance from the interface. A novel strategy, which embodies theoretically well-established features, is applied to recent reflectivity and ellipsometry experiments on binary mixtures against glass and vapor substrates. Overall, the data indicate relatively strong surface fields and clearly reveal crossover from a power-law regime, P(x)\ensuremath{\approxeq}${P}_{0}$/${x}^{\ensuremath{\beta}/\ensuremath{\nu}}$, as x-g0, to P(x)\ensuremath{\approxeq}${P}_{\ensuremath{\infty}}$${e}^{\mathrm{\ensuremath{-}}x}$, as x-g\ensuremath{\infty}, occurring around x\ensuremath{\simeq}1.4 with ${P}_{\ensuremath{\infty}}$/${P}_{0}$\ensuremath{\simeq}0.85. The relative merits of reflectivity and ellipsometry techniques are assessed (the latter currently proving more definitive) and various experimental issues are identified which must be resolved before more details of the adsorption profile could be extracted from further observations.
Towards Open-Ended Learning of Action Sequences with Hierarchical Predictive Self-Organization

Open-ended learning is fundamental in autonomous robotics for the incremental acquisition of knowledge through experience. However, most of the proposed computational models for action recognition do not account for incremental learning, but rather learn a batch of training actions without adapting to new inputs presented after training sessions. Therefore, this is the need to provide robots with the ability to incrementally process a set of available perceptual cues and to adapt their behavioural responses over time. In this work, we propose a neural network architecture with multilayer-predictive processing for incrementally learning action sequences. Our architecture comprises a hierarchy of selforganizing networks that progressively learn the spatiotemporal structure of the input using Hebbian-like plasticity. Along the hierarchical flow with increasingly larger temporal receptive fields, feedback connections from higher-order networks carry predictions of lower-level neural activation patterns, whereas feedforward connections convey residual errors between the predictions and the lower-level activity. This mechanism is used to modulate the amount of learning necessary to adapt to the dynamic input distribution and develop robust action representations. We present a simplified hierarchical architecture with two layers and describe a number of planned experiments for classifying human actions in an open-ended learning scenario.
Metaphylogenomic and Potential Functionality of the Limpet Patella pellucida’s Gastrointestinal Tract Microbiome

This study investigated the microbial diversity associated with the digestive tract of the seaweed grazing marine limpet Patella pellucida. Using a modified indirect DNA extraction protocol and performing metagenomic profiling based on specific prokaryotic marker genes, the abundance of bacterial groups was identified from the analyzed metagenome. The members of three significantly abundant phyla of Proteobacteria, Firmicutes and Bacteroidetes were characterized through the literature and their predicted functions towards the host, as well as potential applications in the industrial environment assessed.
Document de Recherche n ° 2006-13 ing VaR Accuracy : A Simple and Powerful Test "

This paper proposes a new test of Value at Risk (VaR) validation. Our test exploits the idea that the sequence of VaR violations (Hit function) taking value 1 , if there is a violation, and otherwise for a nominal coverage rate veri es the properties of a martingale di¤erence if the model used to quantify risk is adequate (Berkowitz et al., 2005). More precisely, we use the Multivariate Portmanteau statistic of Li and McLeod (1981) extension to the multivariate framework of the test of Box and Pierce (1970) to jointly test the absence of autocorrelation in the vector of Hit sequences for various coverage rates considered as relevant for the management of extreme risks. We show that this shift to a multivariate dimension appreciably improves the power properties of the VaR validation test for reasonable sample sizes. Keywords : Value-at-Risk; Risk Management; Model Selection J.E. L Classi cation : C22, C52, G28 LEO, University of Orléans. Rue de Blois. BP 6739. 45067 Orléans Cedex 2. France. e-mail address: christophe.hurlin@univ-orleans.fr. yCorresponding author. LEO, University of Orléans. Rue de Blois. BP 6739. 45067 Orléans Cedex 2. France. e-mail address: sessi.tokpavi@univ-orleans.fr.
APPLICATION OF DSM THEORY FOR SAR IMAGE CHANGE DETECTION

Synthetic Aperture Radar (SAR) data enables direct observation of land surface at repetitive intervals and therefore allows temporal detection and monitoring of land changes. However, the problem of radar automatic change detection is made more dif cult, mainly with the presence of speckle noise. This paper presents a new method for SAR image change detection using the Dezert-Smarandache Theory (DSmT). First, a Gamma distribution function is used to characterize globally the radar texture data and allows mass assignment throw Kullback-Leibler distance. Then, local pixel measurements are introduced to re ne the mass attribution and take into account the context information. Finally, DSmT is carried out by comparing the modelling results between temporal images. The originality of the proposed method is on the one hand, the use of DSmT which achieve a plausible and paradoxical reasoning comparing to classical Dempster-Shafer Theory (DST). On the other hand, the given approach characterizes the radar texture data with a Gamma distribution which allows a better representation of the speckle. The radar texture is being usually modeled by a Gaussian model in previous DST and DSmT fusion works.