Miracle-dz/UniFAR-FTUs huggingface dataset:
SEASONAL POPULATION DYNAMICS, NEST SITE SELECTION, SEX-RATIO AND CLUTCH SIZE OF THE GREAT BUSTARD OTIS TARDA IN TWO ADJACENT LEKKING AREAS

SUMMARY. —Seasonal population dynamics, nest site selection, sex-ratio and clutch size of the Great Bustard Otis tarda in two adjacent lekking areas. This paper describes the seasonal variation in Great Bustard Otis tarda numbers in two adjacent lekking areas within Castro Verde, the most important site for this species in Portugal. Furthermore, the first data on the breeding biology of the species in the region are presented. The pattern of flock size variation was similar to the one observed in other areas of the Iberian Peninsula, with larger flocks occurring during winter. The use of the two lekking areas was distinct, with one area having more birds during the breeding season (more important as display ground) and another during winter (more important as feeding ground). Cereal fields were the most important nesting habitat for Great Bustards, followed by first year fallow fields. Mean clutch size was 2.6 eggs/nest.
Solar ultraviolet-B radiation and aquatic primary production: damage, protection, and recovery

The continuing degradation of the Earth's ozone layer by atmospheric pollutants has generated concern about the impact of increased solar ultraviolet-B radiation (UV-B) on aquatic ecosystems. UV-B is a small (less than 1% of total energy) but highly active component of the solar spectrum that can penetrate to biologically significant depths in lakes and oceans. It has the potential to cause wide-ranging effects, including mutagenesis, chronic depression of key physiological processes, and acute physiological stress that may result in death. There are major uncertainties at present about the appropriate time scales and bioassay protocols for assessing such effects. Algal and cyanobacterial cells have four lines of defence against the toxic effects of UV-B. Some species avoid UV exposure by their choice of habitat or by migration strategies. Many species produce sunscreening pigments that filter out UV wavelengths; mycosporine-like amino acids are an especially important and ubiquitous class of such compounds. Most cells have a variety of defences against the toxic end products of UV radiation, such as radical scavenging by carotenoid pigments and superoxide dismutase. Finally, most cells have at least some ability to identify and repair the UV damage of DNA and other biomolecules. There is a large interspecific variability in the extent of each of these defence strategies. Continuing ozone depletion is not likely to cause an abrupt collapse of photosynthetic production, but may result in subtle, community-level responses that could ultimately impact on higher trophic levels.
Fizeau interferometry of Io volcanism with LBTI / LMIRcam

The Large Binocular Telescope (LBT) houses two 8.4-meter mirrors separated by 14.4 meters on a common mount. Coherent combination of these two AO-corrected apertures via the LBT Interferometer (LBTI) produces Fizeau interferometric images with a spatial resolution equivalent to that of a 22.8-meter telescope and the lightgathering power of single 11.8-meter mirror. Capitalizing on these unique capabilities, we used LBTI/LMIRcam to image thermal radiation from volcanic activity on the surface of Io at M -Band (4.8 μm) over a range of parallactic angles. We compare two deconvolution routines in order to recover the full spatial resolution of the combined images, resolving at least fifteen known volcanic hot spots. Coupling these observations with advanced image reconstruction algorithms demonstrates the versatility of Fizeau interferometry and realizes the LBT as the first in a series of extremely large telescopes.
Accelerated Volumetric Next-Best-View Planning in 3D Mapping

The Next-Best-View (NBV) problem plays an important part in automatic 3D object reconstruction and exploration applications. This thesis presents a novel approach of ray-casting in Occupancy Grid Maps (OGM) in the context of solving the NBV problem in a 3D-exploration setting. The proposed approach utilizes the structure of an octree-based OGM to perform calculations of potential information gain. The computations are significantly faster than current methods, without decreasing mapping quality. Performance, both in terms of mapping quality, coverage and computational complexity, is experimentally verified through a comparison with existing state-of-the-art methods using high-resolution point cloud data generated using time-of-flight laser range scanners.Current methods for viewpoint ranking focus either heavily on mapping performance or computation speed. The results presented in this thesis indicate that the proposed method is able to achieve a mapping performance similar to the performance-oriented approaches while maintaining the same low computation speed as more approximative methods.
Posterior reversible encephalopathy syndrome ( PRES ) : Features on CT and MR imaging

a Radiology and Medical Imaging Department, Clermont-Ferrand University Hospital, Estaing University Hospital, 1, place Lucie-Aubrac, 63003 Clermont-Ferrand cedex 1, France b Anaesthetics and Intensive Care Department, Clermont-Ferrand University Hospital, Gabriel-Montpied, rue Montalembert, BP 69, 63003 Clermont-Ferrand cedex 1, France c Radiology A, Neuroradiology Department, Clermont-Ferrand University Hospital, Gabriel-Montpied, rue Montalembert, BP 69, 63003 Clermont-Ferrand cedex 1, France
A SURVEY ON DYNAMIC VM CONSOLIDATION TECHNIQUE IN CLOUD

High energy consumption in cloud data center is growing rapidly because of data center size is becoming larger and larger. To save energy in data center Dynamic consolidation of virtual machine presents a significant opportunity. A live VM migration is one of VM consolidation approach that helps to identify underloaded physical machines which can be switched-off or put into a low-power mode. On the other side, achieving quality of service at the desired level between cloud service providers and end user is critical. Therefore main challenges are reaching desired level Quality of Service and at same time reduce in energy consumption. In this paper, we studied the Dynamic VM consolidation techniques used by various author. We have summarized in the table, the performance metric and tool used for evaluation.
Improved ANS Lightning Predictors Using Additional Surface Wind and Electric Field Data

Abstract : Because of the destruction by lightning of Atlas-Centaur 67 and its communication satellite payload on 27 March 1987, new launch commit criteria with respect to lightning were imposed by NASA and the Air Force for missile launches from the national ranges. These criteria are very conservative and restrict the available launch windows, especially during summer months at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) in Florida. In an effort to expand the launch windows while maintaining safety, we show that neural networks can be trained to generate spatio-temporal maps of predicted probabilities of lightning over the CCAFS/KSC complex. Input data used for training and testing the neural networks include the five minute averages from all 53 wind sensors, the Total Area Divergence product calculated by Watson, the occurrence of lightning strikes as recorded by magnetic direction finders, and most recently, the electric field mill data. Training the neural network lightning predictor with wind data spanning two days of data and the divergence product increased the PoD to 0.65. The predictor's best performance is at 30 - 60 minutes in the future. We except the electric field data to affect near term prediction more than later times.
UMETRICS as a tool for quantifying the value of research and assessing underrepresentation

Figure 1 shows one faculty member (the large blue node), all of the people supported on grants with him, and all the people supported directly on grants with those people. In this image nodes represent individuals (red indicates female and blue indicates male) and shapes represent occupations. The figure shows that among the faculty (circles) and graduate students (squares), many of the women are connected to each other and less central to this portion of the network. While this figure represents just a small portion of the network at a single university, which may or may not be representative, such methods allow researchers to characterize the collaborative structure of science in very fine detail. We argue that these communities are the primary environment for research training and hence the appropriate level of analysis for research linking environmental differences to disparities in access or outcomes. This data can, in turn, be linked to a wide range of (i) naturally occurring data on research materials, including dissertations, publications, citations, funded grants, and patents as well as (ii) survey and administrative data held at the Census Bureau on job placements within the United States, as well as many business start-ups.
Broadband spectral measurements of diffuse optical properties by an integrating sphere instrument at the National Institute of Standards and Technology

Diffuse materials that approximate the optical properties of human tissue are commonly used as phantoms. In order to use the phantoms in a manner that provides consistent results relative to independent measurements, the optical properties need to be tied to a physics based scale. Such a scale is needed for volume scattering of diffuse materials and this is currently being addressed by the development of a sphere based optical scattering reference instrument at the National Institute of Standards and Technology (NIST). Previous work towards that goal was constrained to the use of several laser lines at discrete wavelengths. Current work has expanded the spectral range for contiguous coverage. Here we report measurement results of the optical properties of solid phantoms, using two different base materials, acquired using NISTs diffuse optical properties reference instrument with visible or near infrared broadband illumination. The measurements of diffuse hemispherical reflectance and transmittance are analyzed using a custom inversion algorithm of the adding-doubling routine, and the expanded uncertainties on the results are provided. The broadband diffuse optical properties measured with the improved system agree to within the estimated uncertainty of the discrete measurements from two other institutes using alternative methods. This work expands the capabilities of the facility and can provide services for a wider range of applications.
Modelling of the Spectral Energy Distribution of Fornax A : Leptonic and Hadronic Production of High Energy Emission from the Radio Lobes

We present new low-frequency observations of the nearby radio galaxy Fornax A at 154 MHz with the Murchison Widefield Array, microwave flux-density measurements obtained from WMAP and Planck data, and gamma-ray flux densities obtained from Fermi data. We also compile a comprehensive list of previously published images and flux-density measurements at radio, microwave and X-ray energies. A detailed analysis of the spectrum of Fornax A between 154 MHz and 1510 MHz reveals that both radio lobes have a similar spatially-averaged spectral index, and that there exists a steep-spectrum bridge of diffuse emission between the lobes. Taking the spectral index of both lobes to be the same, we model the spectral energy distribution of Fornax A across an energy range spanning eighteen orders of magnitude, to investigate the origin of the X-ray and gamma-ray emission. A standard leptonic model for the production of both the X-rays and gamma-rays by inverse-Compton scattering does not fit the multi-wavelength observations. Our results best support a scenario where the X-rays are produced by inverse-Compton scattering and the gamma-rays are produced primarily by hadronic processes confined to the filamentary structures of the Fornax A lobes.
BROADCAST BY FLOODING IMPROVEMENT IN IEEE 802 . 11 S BASED WIRELESS MESH NETWORKS

Network wide broadcasting in IEEE 802.11s based wireless mesh network provides a considerable amount of broadcast traffic that may lead to the broadcast storm problem and consequently degrade the network performance. Contention, collisions and redundancy are features of the broadcast storm problem that may hinder the transmission of unicast data packet if not a carefully designed scheme for managing broadcast traffic is adopted. In this paper, we develop and enhance our approach, namely Control of Broadcast Forwarding (CBF), which is a self-pruning method using 2-hop neighborhood knowledge to make decision on forwarding or filtering the received broadcast messages. We perform a deeply investigation including a comparison between CBF and the most suitable broadcasting techniques for wireless mesh networks according to various simulation environments. Simulations results reveal that CBF achieves comparatively better performance in term of average end to end delay and reachability. The only cost brought by CBF is a slightly increase in overhead and consequently in the number of retransmitting nodes.
Smart Chair for Monitoring of Sitting Behavior

Sitting is a common behavior of human body in daily life. It is found that poor sitting postures can link to pains and other complications for people in literature. In order to avoid the adverse effects of poor sitting behavior, we have developed a highly practical design of smart chair system in this paper, which is able to monitor the sitting behavior of human body accurately and non-invasively. The pressure patterns of eight standardized sitting postures of human subjects were acquired and transmitted to the computer for the automatic sitting posture recognition with the application of artificial neural network classifier. The experimental results showed that it can recognize eight sitting postures of human subjects with high accuracy. The sitting posture monitoring in the developed smart chair system can help or promote people to achieve and maintain healthy sitting behavior, and prevent or reduce the chronic disease caused by poor sitting behavior. These promising results suggested that the presented system is feasible for sitting behavior monitoring, which can find applications in many areas including healthcare services, human-computer interactions and intelligent environment.
An Efficient Product Hybrid Feature Classification on Opinion Mining using Ant Optimization Rule

Opinion mining refers to opinion retrieval with a set of searched results, produced for the customer’s depending on the product request demand. In general, opinion refers to a person’s perspective and mining is implied for identifying the result of the search query. Despite its promise, failure of clear product classification results in the ambiguity for obtaining additional product feature association. Also, several hybrid features related to the product were not classified with high efficiency rate. The list of product attributes classification (i.e., based on quality of products and specific feature selection of the products) with opinion mining algorithms was not investigated widely. To classify the product features based on the user behavior, an Ant Opinion Miner Classification Rule Learning (AOM-CRL) process is proposed in this paper. Initially, the process of Ant Opinion Miner helps to fetch the combination (i.e., hybrid) product features based on the user behavior. The Ant Opinion Miner involves the pheromone initialization, updation and fitness function for efficient classification of hybrid features. Pheromone initialization starts the process based on the user behavior with opinion patterns based classification on product features. Then the pheromone updating process is carried out with the same behavior for a set of hybrid features of the products. Both the initialization and updating uses the user behavior information to easily adopt the classification rule. The fitness function is employed in AOM-CRL process to produce quality result on classification process. In addition, different set of hybrid feature classification also produces high quality function value through ant-miner based classification rule. This ant-miner based classification rule integrates the Enhanced Rapid Repeated Attribute Reduction algorithm to improve the classification accuracy on opinion mining with minimal processing time. Experiment is conducted with classification rate on user opinions, false positive rate and precision rate on product result. KeywordsClassification Rule, Opinion Mining, Fitness Function, Pheromone Initialization, Pheromone updation, Enhanced Rapid Repeated Attribute Reduction
Designing and Testing a Model of Some Precedents and Consequences of Oppositional Defiant Disorder in High School Students

Background: Previous research has demonstrated that oppositional defiant disorder is a strong predictor of mental illness that causes significant distress for adolescents, who manifest this disorder and pose remarkable costs for the society. Objectives: The aim of this study was to design and test a model of some antecedents (secure attachment and insecure attachment, early trauma, behavioral activation system, behavioral inhibition system, schema, emotion regulation, and callous-unemotional) and consequences (aggression, conduct disorder, educational performance, and vandalism) of oppositional defiant disorder. Methods: The sample consisted of 320 high school students of Dezfoul, who were selected by multistage random sampling. The instruments included the oppositional defiant behavioral inventory, revised adult scale (RAAS), Early Trauma Inventory, Carver and White Behavioral Activation System/Behavioral Inhibition system, Young’s Schema Questionnaire - Short Form, difficulties in emotion regulation scale (DERS), Callous-Unemotional trait inventory, Boss and Perry aggression questionnaire, child behavior checklist (CBCL), and questionnaire of vandalism. Structural equation modeling through AMOS 22 and SPSS 22 were used for data analysis. Results: Results showed that the model with some modification had good fit with the data and model indicators (χ 2/df = 3.24, GFI= 0.90, RMSEA= 0.07) improved. Six out of 20 direct paths were not significant, and were omitted from the model. Two out of nine indirect paths were omitted and the rest of the paths were confirmed. Conclusions: The results showed that the model fitted the data with some amendments.
Self healing of defected graphene

For electronics applications, defects in graphene are usually undesirable because of their ability to scatter charge carriers, thereby reduce the carrier mobility. It would be extremely useful if the damage can be repaired. In this work, we employ Raman spectroscopy, X-ray photoemission spectroscopy, transmission electron microscopy, and electrical measurements to study defects in graphene introduced by argon plasma bombardment. We have found that majority of these defects can be cured by a simple thermal annealing process. The self-healing is attributed to recombination of mobile carbon adatoms with vacancies. With increasing level of plasma induced damage, the self-healing becomes less effective.
Alleviating inflation of conditional predictions q

Previous studies indicated that conditional predictions—the assessed probability that a certain outcome will occur given a certain condition—tend to be markedly inflated. Five experiments tested the effects of manipulations that were expected to alleviate this inflation by inducing participants to engage in analytic processing. Rewarding participants for accurate predictions proved ineffective. A training procedure in which participants assessed the likelihood of each of several outcomes before assessing the probability of a target outcome was partly effective in reducing overestimation. Most effective was the requirement to work in dyads and to come to an agreement about the assessed likelihood. Working in dyads helped alleviate prediction inflation even after participants made their individual predictions alone, and its debiasing effect also transferred to the estimates that were made individually on a new set of stimuli. The results were discussed in terms of the factors that make prediction inflation resistant to change. 2007 Elsevier Inc. All rights reserved.
Analyzing the influence of the water saturation on the strength of sandstones

Water content is one of the most important factors influencing rock strength. Considerable research has been carried out to investigate rock strength under both dry and water saturated conditions for different types of sandstones. According to these results, the petrophysical components of rocks (i.e. uniaxial compressive strength, elastic modulus, tensile strength) decrease with increasing water content and this can result in an increase in the mechanical compliance in some cases. In several cases, the strength decrease is remarkable after only 1% water saturation. For rock mechanics and rock engineering projects, it is strongly recommended that the dry uniaxial compressive strength is used for the purposes of strength classification, while for the actual engineering design it is essential to establish the wet strength and ideally the water sensitivity of the rock, in order to asses their potential change in strength and deformability. The goal of this paper is to show a method for calculating the sensitivity of sandstone rocks to water content, using the different published data. From measurements of the density and the uniaxial compressive strength in case of dry and saturated petrophysical states, the strength as a function of water content can be easily determined.
Nanomechanical Measurements of Viscoelastic Properties of Bacterial Cells: Effect of Antimicrobial Peptides and Challenges Associated with Measurements in Buffer

Nanomechanical Measurements of Viscoelastic Properties of Bacterial Cells: Effect of Antimicrobial Peptides and Challenges Associated with Measurements in Buffer Richard Parg Advisor: University of Guelph, 2016 John Dutcher The effectiveness of antimicrobial compounds can be easily screened; however, their mechanism of action is much more difficult to determine. Many compounds act by compromising the mechanical integrity of the bacterial cell, and we have developed an atomic force microscopy (AFM)-based creep-deformation technique to evaluate changes in the timedependent mechanical properties of bacterial cells upon exposure to antimicrobials. Measurements revealed large changes to the viscoelastic parameters including a distinctive signature for the loss of integrity of the bacterial cell envelope. This technique provides unique insight into the kinetics and action of antimicrobials on bacteria. Initial experiments were performed in Milli-Q water on Pseudomonas aeruginosa PAO1 bacteria, which can withstand large osmotic pressures. Subsequent experiments addressed the challenges of performing AFM creep deformation experiments on live cells in PBS buffer. We describe measurements of, and improvements to, the stability of the experimental set-up in an effort to facilitate these challenging experiments.