Miracle-dz/UniFAR-FTUs huggingface dataset:
Biogeosciences Towards ground-truthing of spaceborne estimates of above-ground life biomass and leaf area index in tropical rain forests

The canopy height h of forests is a key variable which can be obtained using airor spaceborne remote sensing techniques such as radar interferometry or LIDAR. If new allometric relationships between canopy height and the biomass stored in the vegetation can be established this would offer the possibility for a global monitoring of the above-ground carbon content on land. In the absence of adequate field data we use simulation results of a tropical rain forest growth model to propose what degree of information might be generated from canopy height and thus to enable ground-truthing of potential future satellite observations. We here analyse the correlation between canopy height in a tropical rain forest with other structural characteristics, such as above-ground life biomass (AGB) (and thus carbon content of vegetation) and leaf area index (LAI) and identify how correlation and uncertainty vary for two different spatial scales. The process-based forest growth model F ORMIND2.0 was applied to simulate (a) undisturbed forest growth and (b) a wide range of possible disturbance regimes typically for local tree logging conditions for a tropical rain forest site on Borneo (Sabah, Malaysia) in South-East Asia. In both undisturbed and disturbed forests AGB can be expressed as a power-law function of canopy height(AGB = a ·h) with an r2 ∼ 60% if data are analysed in a spatial resolution of 20 m× 20 m (0.04 ha, also called plot size). The correlation coefficient of the regression is becoming significant better in the disturbed forest sites ( r2 = 91%) if data are analysed hectare wide. There seems to exist no functional dependency between LAI and canopy height, but there is also a linear correlation (r2 ∼ 60%) between AGB and the area fraction of Correspondence to: P. Köhler (peter.koehler@awi.de) gaps in which the canopy is highly disturbed. A reasonable agreement of our results with observations is obtained from a comparison of the simulations with permanent sampling plot (PSP) data from the same region and with the large-scale forest inventory in Lambir. We conclude that the spaceborne remote sensing techniques such as LIDAR and radar interferometry have the potential to quantify the carbon contained in the vegetation, although this calculation contains due to the heterogeneity of the forest landscape structural uncertainties which restrict future applications to spatial averages of about one hectare in size. The uncertainties in AGB for a given canopy height are here 20 −40% (95% confidence level) corresponding to a standard deviation of less than ± 10%. This uncertainty on the 1 ha-scale is much smaller than in the analysis of 0.04 ha-scale data. At this small scale (0.04 ha) AGB can only be calculated out of canopy height with an uncertainty which is at least of the magnitude of the signal itself due to the natural spatial heterogeneity of these forests.
Artigo EXPERIMENTAL ASSESSMENT OF TECHNIQUES FOR FISHEYE CAMERA CALIBRATION Avaliação experimental de técnicas de calibração de câmaras com objetiva olho de peixe

Fisheye lens cameras enable to increase the Field of View (FOV), and consequently they have been largely used in several applications like robotics. The use of this type of cameras in closerange Photogrammetry for high accuracy applications, requires rigorous calibration. The main aim of this work is to present the calibration results of a Fuji Finepix S3PRO camera with Samyang 8mm fisheye lens using rigorous mathematical models. Mathematical models based on Perspective, Stereo-graphic, Equi-distant, Orthogonal and Equi-solid-angle projections were implemented and used in the experiments. The fisheye lenses are generally designed following one of the last four models, and Bower-Samyang 8mm lens is based on Stereo-graphic projection. These models were used in combination with symmetric radial, decentering and affinity distortion models. Experiments were performed to verify which set of IOPs (Interior Orientation Parameters) presented better results to describe the camera inner geometry. Collinearity mathematical model, which is based on perspective projection, presented the less accurate results, which was expected because fisheye lenses are not designed following the perspective projection. Stereo-graphic, Equi-distant, Orthogonal and Equi-solid-angle projections presented similar results even considering that Bower-Samyang fisheye lens was built based on Stereo-graphic projection. The experimental results also demonstrated a small correlation between IOPs and EOPs (Exterior Orientation Parameters) for Bower-Samyang lens.
Characterization of vaginal microbiota in Thai women

Background The vaginal microbiota (VMB) plays a key role in women’s reproductive health. VMB composition varies with ethnicity, making it necessary to characterize the VMB of the target population before interventions to maintain and/or improve the vaginal health are undertaken. Information on the VMB of Thai women is currently unavailable. We therefore characterized the VMB in normal Thai women. Methods Vaginal samples derived from 25 Thai women were subjected to 16S rRNA gene next-generation sequencing (NGS) on the Ion Torrent PGM platform. Results Two groups of VMB were detected, lactobacilli-dominated (LD) and non-lactobacilli dominated (NLD) groups. Lactobacillus iners was the most common species found in the LD group while Gardnerella vaginalis followed by Atopobium vaginae and Pseudumonas stutzeri were commonly found in the NLD group. Conclusions The VMB patterns present in normal Thai women is essential information to further determine the factors associated with VMB patterns in vaginal health and disease and to develop proper management of reproductive health of Thai women.
Cultivating Common Ground: Integrating Standards-Based Visual Arts, Math and Literacy in High-Poverty Urban Classrooms.

The Framing Student Success: Connecting Rigorous Visual Arts, Math and Literacy Learning experimental demonstration project was designed to develop and test an instructional program integrating high-quality, standards-based instruction in the visual arts, math, and literacy. Developed and implemented by arts-in-education organization Studio in a School (STUDIO), in partnership with the New York City Department of Education, the Framing Student Success curriculum was designed by experienced professional artist instructors collaborating with school-based visual arts, math, and literacy specialists and classroom teachers. The Framing Student Success curriculum units were designed to make explicit connections between subjects (visual arts and ELA or math), while maintaining the integrity, depth and rigor of instruction in both subject areas. While students were receiving arts-integrated instruction during each of the twelve six-week units, classroom teachers and arts specialists were receiving embedded professional development. Regular cross-site professional development was also provided for teachers, specialists, and school administrators. As a randomized control trial study, the three-year Framing Student Success study provides robust evidence of the potential impacts of an interdisciplinary, arts-integrated curriculum for students growing up in poverty. The mixed-method study assessed the effects of staff professional development and standards-based arts-integrated instruction in three urban, high-poverty elementary schools. Results indicate that rigorous interdisciplinary instruction that links visual arts, literacy, and math skills, and supports cognitive skill development, can increase students’ literacy and math learning while nurturing their art making skills and enhancing their ability to meaningfully reflect on their own work and that of their peers. Qualitative findings suggest that interdisciplinary educator collaborations were critical to project success, and highlight the project’s successful engagement of lower-performing students and students with disabilities. Survey and focus group results suggest that training can build the capacities of teachers, arts specialists, and administrators to implement an interdisciplinary curriculum, providing educators with additional tools to teach engaging, Common Core aligned lessons addressing academic and cognitive competencies.
Speaker Recognition under Stress Conditions

Speaker Recognition systems exhibit a decrease in performance when the input speech is not in optimal circumstances, for example when the user is under emotional or stress conditions. The objective of this paper is measuring the effects of stress on speech to ultimately try to mitigate its consequences on a speaker recognition task. On this paper, we develop a stress-robust speaker identiﬁcation system using data selection and augmentation by means of the manipulation of the original speech utterances. An extensive experimentation has been carried out for assessing the effectiveness of the proposed techniques. First, we concluded that the best performance is always obtained when naturally stressed samples are included in the training set, and second, when these are not available, their substitution and augmentation with synthetically generated stress-like samples, improves the performance of the system.
Remaining useful life prediction of the ball screw system based on weighted Mahalanobis distance and an exponential model

The ball screw system is one of the crucial components of machine tools and predicting its remaining useful life (RUL) can enhance the reliability and safety of the entire machine tool and reduce maintenance costs. Although quite a few techniques have been developed for the fault diagnosis of the ball screw system, forecasting the RUL of the ball screw system is a remaining challenge. To make up for this deficiency, we present a model-based method to predict the RUL of the ball screw system, which consists of two parts: health indicator (HI) construction and RUL prediction. First, we develop a novel HI, weighted Mahalanobis distance (WDMD). Unlike the Mahalanobis distance (MD), which is constructed by fusing original features directly, the WDMD is formed with some selected features only, and the features are weighted before integration. Second, an exponential model is developed to describe the degradation path of the ball screw system. Then, the particle filtering algorithm is employed to combine the WDMD and the degradation model for state estimation and RUL prediction. The proposed approach is verified by a dataset obtained from an experimental system designed for accelerated life tests of the ball screw system. The results show that the WDMD has a more apparent deterioration trend than the MD and the proposed exponential model performs better than both the linear model and the nonlinear model in RUL prediction.
A survey on current distribution and habitat suitability of the Great Bustard in West Azerbaijan, Iran

Great Bustard (Otis tarda) as a vulnerable species is exposed to the extinction risk mainly due to habitat destruction and hunting pressure. This study was conducted to assess the species current geographical range and its habitat suitability in north western parts of Iran. Based on previous investigations and observations, I mapped current habitats of the species using GIS and the important ecological variables affecting the species habitat usage were modeled by Ecological Niche factor Analysis (ENFA). The results show that the species geographical range is limited to the areas habitats like Sutav, Yngijeh, Alblagh, and Qazelian Plains. ENFA analysis indicated that Great Bustard tends to live in marginal habitats and is a very sensitive species in the study area. The suitability map depicts that 6.5% of the study area is the suitable for the species, however, this value is not consistent with the current habitats in terms of area and location.
An overview of ozone therapy in equine- an emerging healthcare solution

The significance of ozone therapy has been increasingly realised in recent times particularly in equine medicine. The beneficial effects of ozone therapy are basically engendered by the mild oxidative stress it creates upon interacting with the extra-cellular and intracellular components. However therapeutic benefits of treatment could be obtained only when it is used within the therapeutic window. Higher doses may be counterproductive and lower doses ineffective. It is now well proved that it up regulates the antioxidant system of the patient and may provide relief from many chronic degenerative diseases upon prolonged use. Ozone therapy has shown encouraging results in the treatment of wide spectrum of diseases and disorders in equines including bacterial and viral infections. Obvious benefits of ozone therapy have been reported in Equine infectious anemia, chlamydial abortions, lymphomas and equine ehrlichiosis. This article provides an insight into the mechanism of action involved in ozone therapy and reviews various conditions which could be treated with the use of ozone therapy in equines. Jyotsana Bhatt 1,* , Abas Rashid Bhat 1 , Kuldeep Dhama 2 and Amarpal 3
Classifying Political Similarity of Twitter Users

The emergence of large scale social networks has led to research in approaches to classify similar users on a network. While many such approaches use data mining techniques, recent efforts have focused on measuring the similarity of users using structural properties of the underlying graph representing the network. In this paper, we identify the Twitter followers of the 2016 presidential candidates and classify them as Democrat, Republican or Bipartisan. We did this by designing a new approach to measuring structural similarity, PolRANK. PolRANK computes the similarity of a pair of users by accounting for both the number of candidates they follow from each party and the specific candidates they follow. To test our algorithm, we crawled a data set of all followers of every presidential candidate in June 2015 and then ran experiments on a random subset of 10% of that data. When tested against similar algorithms, PolRANK outperforms SimRank[1], P-Rank[2] and Cosine-Similarity as it is more efficient when used in large data sets. This efficiency is due to PolRANK’s ability to calculate similarity independent of other users. The time complexity of P-Rank is O(n 4 ) while the time complexity of PolRANK is O(n 3 ).
Interactive Visualization for Understanding and Analysing Medical Data

Massive amounts of biomedical data generated by the latest high throughput technologies are challenging to analyze. Visual Analytics (VA) tools and techniques are intended to amplify medical researchers’ cognitive and perceptual capabilities and enable them to understand complex biomedical data. In this study, we explore how visualization tools can facilitate the exploratory analysis of this data. In order to assess and evaluate the effectiveness and usefulness of using visualization tools to enhance medical analysts’ data exploration, we analyzed the use of Tableau and iPCA by biomedical researchers to explore immunological data. Our findings reveal that VA tools are efficient and powerful tools that can be integrated into healthcare systems to help health researchers get insights and generate knowledge from their complex medical data.
Characterization of Escherichia coli Alkaline Phosphatase Response to Osmotic Stress Conditions in Limited and Rich Media

The pho regulon in Escherichia coli responds to osmotic stress. Previous studies indicated that in nutrient limited medium, expression of phoA, one gene of the pho regulon, increased as the osmolarity increased. By contrast, in nutrient complex medium, phoA expression was not directly proportional to osmolarity. In this experiment, the effect of supplementing nutrient-limited medium with either glutamate or proline was characterized to test the hypothesis that osmoprotectants in nutrient-complex medium may avert induction of phoA expression. Compared to nutrient-limited conditions, lower alkaline phosphatase specific activity was detected under nutrient rich condition suggesting the presence of osmoprotectants in the nutrient-rich medium. Our results suggest that, in addition to intended osmotic stress, starvation was unexpectedly induced. Consequently, conclusive results were difficult to deduce.
MinD-dependent conformational changes in MinE required for the Min oscillator to spatially regulate cytokinesis

MinD recruits MinE to the membrane leading to a coupled oscillation required for spatial regulation of the cytokinetic Z ring in E. coli. How these proteins interact, however, is not clear since the MinD binding regions of MinE are sequestered within a 6-stranded β-sheet and masked by N-terminal helices. Here, minE mutations are isolated that restore interaction to some MinD and MinE mutants. These mutations alter the MinE structure releasing the MinD binding regions and N-terminal helices that bind MinD and the membrane, respectively. Crystallization of MinDMinE complexes reveals a 4-stranded β-sheet MinE dimer with the released β strands (MinD binding regions) converted to α-helices bound to MinD dimers. These results suggest a 6 stranded, β-sheet dimer of MinE ‘senses’ MinD and switches to a 4-stranded β-sheet dimer that binds MinD and contributes to membrane binding. Also, the results indicate how MinE persists at the MinDmembrane surface.
Temporal alignment and latent Gaussian process factor inference in population spike trains

We introduce a novel scalable approach to identifying common latent structure in neural population spike-trains, which allows for variability both in the trajectory and in the rate of progression of the underlying computation. Our approach is based on shared latent Gaussian processes (GPs) which are combined linearly, as in the Gaussian Process Factor Analysis (GPFA) algorithm. We extend GPFA to handle unbinned spike-train data by incorporating a continuous time point-process likelihood model, achieving scalability with a sparse variational approximation. Shared variability is separated into terms that express condition dependence, as well as trial-to-trial variation in trajectories. Finally, we introduce a nested GP formulation to capture variability in the rate of evolution along the trajectory. We show that the new method learns to recover latent trajectories in synthetic data, and can accurately identify the trial-to-trial timing of movement-related parameters from motor cortical data without any supervision.
An R 2 Indicator and Decomposition Based Steady-State Evolutionary Algorithm for Many-Objective Optimization

Copyright © 2018 Fei Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. An R2 indicator based selection method is a major ingredient in the formulation of indicator based evolutionary multiobjective optimization algorithms. The existing classical indicator based selection methodologies have demonstrated an excellent performance to solve low-dimensional optimization problems. However, the R2 indicator based evolutionary multiobjective optimization algorithms encounter enormous challenges in high-dimensional objective space. Our main purpose is to explore how to extend the R2 indicator to handle many-objective optimization problems. After analyzing the R2 indicator, the objective space partition strategy, and the decomposition method, we propose a steady-state evolutionary algorithm based on the R2 indicator and the decomposition method, named, R2-MOEA/D, to obtain well-converged and well-distributed Pareto front. The main contribution of this paper contains two aspects. (1) The convergence and diversity for the R2 indicator based selection are analyzed. Two improper selection situations will be properly solved via applying the decomposition method. (2) According to the position of a new individual in the steady-state evolutionary algorithm, two different objective space partition strategies and the corresponding selection methods are proposed. Extensive experiments are conducted on a variety of benchmark test problems, and the experimental results demonstrate that the proposed algorithm has competitive performance in comparison with several tailored algorithms for many-objective optimization.
Management of black sigatoka in Cameroon

In Cameroon, Mycosphaerella fijiensis was reported for the first time in 1981 and the control against black leaf streak disease represents the highest production cost which can attend up to 10% of total production cost. Towards the end of the 80s, a forecasting system using biological descriptors was elaborated and applied with success, reducing the number of treatments to 12 - 14 per year. Since 1996, the development of fungicide resistance lead to the progressive abandon of this rational strategy at the expense of systematic control methods. Thus in 2005, about 40-50 treatments were done on most of the plantations and the control program was based on the ratio of 90% of contact fungicides and 10% of systemic and penetrant fungicides. This evolution has lead to an important increase of the cost of disease control, but also to an increase of negative environmental effects. Material and Methods. In those conditions, research conducted in Cameroon is aimed to: (1) Experiment fungicides having less negative environmental effects; (2) Adapt control strategies to the situation of fungicide resistance; (3) Evaluate the adaptive potential of Mycosphaerella fijiensis populations in response to the use of systemic fungicides. Results. (1) Some of the new fungicides tested enabled an acceptable control of BLSD when they were used in oil. (2) Experiments realised in 2005 have shown that chlorothalonil applied on a systematic framework, and compared with penetrants used in a forecasting strategy, enabled a very good control of the disease, even in the rainy season: strong reduction of the Stage of Evolution of the disease, increase of phytosanitary level in the banana plantations (Youngest leaf spotted). (3) Very important fluctuations in the levels of resistance to systemic fungicide have been observed in Cameroon. Some observations clearly show that management of resistance should refer to the control of the disease in nurseries, and also to nurseries location. Discussion. New fungicides should be used in water alone to enable a rapid conversion to chlorotalonil applications and to reduce negative effects of oil when used in a systematic calendar (treatments every week). New strategies where the proportion of chlorothalonil would be rationalized to a minimum will be evaluated in the next year. We make the hypothesis that the fluctuations observed in the resistance frequency to systemic fungicides could result from a lower fitness of resistant strains, which could be counter- selected in the absence of the fungicide selection pressure and/or gene-flow between the treated and the untreated areas. (Resume d'auteur)
The Origin of the Optical Flashes: The Case Study of GRB 080319B and GRB 130427A

Correlations between optical flashes and gamma-ray emissions in gamma-ray bursts (GRBs) have been searched in order to clarify the question of whether these emissions occur at internal and/or external shocks. Among the most powerful GRBs ever recorded are GRB 080319B and GRB 130427A, which at early phases presented bright optical flashes possibly correlated with γ-ray components. Additionally, both bursts were fortuitously located within the field of view of the TeV γ-ray Milagro and HAWC observatories, and although no statistically significant excess of counts were collected, upper limits were placed on the GeV–TeV emission. Considering the synchrotron self-Compton emission from internal shocks and requiring the GeV–TeV upper limits, we found that the optical flashes and the γ-ray components are produced by different electron populations. Analyzing the optical flashes together with the multiwavelength afterglow observation, we found that these flashes can be interpreted in the framework of the synchrotron reverse shock model when outflows have arbitrary magnetizations.