Monitoring strip mining and reclamation with LANDSAT data in Belmont County, Ohio

The utility of LANDSAT digital data for mapping and monitoring surface mines in Belmont County, Ohio was investigated. Two data sets from 1976 and 1979 were processed to classify level 1 land covers and three strip mine categories in order to examine change over time and assess reclamation efforts. The two classifications were compared with aerial photographs. Results of the accuracy assessment show that both classifications are approximately 86 per cent correct, and that surface mine change detection (date-to-date comparison) is facilitated by the digital format of LANDSAT data

Emotional expressiveness of 5–6 month-old infants born very premature versus full-term at initial exposure to weaning foods

Facial expressions of 5–6 month-old infants born preterm and at term were compared while tasting for the first time solid foods (two fruit and two vegetable purées) given by the mother. Videotapes of facial reactions to these foods were objectively coded during the first six successive spoons of each test food using Baby FACS and subjectively rated by naïve judges. Infant temperament was also assessed by the parents using the Infant Behaviour Questionnaire. Contrary to our expectations, infants born preterm expressed fewer negative emotions than infants born full-term. Naïve judges rated infants born preterm as displaying more liking than their full-term counterparts when tasting the novel foods. The analysis of facial expressions during the six spoonfuls of four successive meals (at 1-week intervals) suggested a familiarization effect with the frequency of negative expressions decreasing after tasting the second spoon, regardless of infant age, type of food and order of presentation. Finally, positive and negative dimensions of temperament reported by the parents were related with objective and subjective coding of affective reactions toward foods in infants born preterm or full-term. Our research indicates that premature infants are more accepting of novel foods than term infants and this could be used for supporting the development of healthy eating patterns in premature infants. Further research is needed to clarify whether reduced negativity by infants born prematurely to the exposure to novel solid foods reflects a reduction of an adaptive avoidant behaviour during the introduction of novel foods

The rarity of terrestrial gamma-ray flashes

We report on the first search for Terrestrial Gamma-ray Flashes (TGFs) from altitudes where they are thought to be produced. The Airborne Detector for Energetic Lightning Emissions (ADELE), an array of gamma-ray detectors, was flown near the tops of Florida thunderstorms in August/September 2009. The plane passed within 10 km horizontal distance of 1213 lightning discharges and only once detected a TGF. If these discharges had produced TGFs of the same intensity as those seen from space, every one should have been seen by ADELE. Separate and significant nondetections are established for intracloud lightning, negative cloud-to-ground lightning, and narrow bipolar events. We conclude that TGFs are not a primary triggering mechanism for lightning. We estimate the TGF-to-flash ratio to be on the order of 10^(−2) to 10^(−3) and show that TGF intensities cannot follow the well-known power-law distribution seen in earthquakes and solar flares, due to our limits on the presence of faint events

Survey: Robot Programming by Demonstration

Robot PbD started about 30 years ago, growing importantly during the past decade. The rationale for moving from purely preprogrammed robots to very flexible user-based interfaces for training the robot to perform a task is three-fold. First and foremost, PbD, also referred to as {\em imitation learning} is a powerful mechanism for reducing the complexity of search spaces for learning. When observing either good or bad examples, one can reduce the search for a possible solution, by either starting the search from the observed good solution (local optima), or conversely, by eliminating from the search space what is known as a bad solution. Imitation learning is, thus, a powerful tool for enhancing and accelerating learning in both animals and artifacts. Second, imitation learning offers an implicit means of training a machine, such that explicit and tedious programming of a task by a human user can be minimized or eliminated (Figure \ref{fig:what-how}). Imitation learning is thus a ``natural'' means of interacting with a machine that would be accessible to lay people. And third, studying and modeling the coupling of perception and action, which is at the core of imitation learning, helps us to understand the mechanisms by which the self-organization of perception and action could arise during development. The reciprocal interaction of perception and action could explain how competence in motor control can be grounded in rich structure of perceptual variables, and vice versa, how the processes of perception can develop as means to create successful actions. PbD promises were thus multiple. On the one hand, one hoped that it would make the learning faster, in contrast to tedious reinforcement learning methods or trials-and-error learning. On the other hand, one expected that the methods, being user-friendly, would enhance the application of robots in human daily environments. Recent progresses in the field, which we review in this chapter, show that the field has make a leap forward the past decade toward these goals and that these promises may be fulfilled very soon

Complex and flexible catabolism in Aromatoleum aromaticum pCyN1

Large quantities of organic matter are continuously deposited, and (a)biotic gradients intersect in the soil-rhizosphere, where biodegradation contributes to the global cycles of elements. The betaproteobacterial genus Aromatoleum comprises cosmopolitan, facultative denitrifying degradation specialists. Aromatoleum aromaticum. pCyN1 stands out for anaerobically decomposing plant-derived monoterpenes in addition to monoaromatic hydrocarbons, polar aromatics and aliphatics. The catabolic network's structure and flexibility in A. aromaticum pCyN1 were studied across 34 growth conditions by superimposing proteome profiles onto the manually annotated 4.37 Mbp genome. Strain pCyN1 employs three fundamentally different enzymes for C-H-bond cleavage at the methyl groups of p-cymene/4-ethyltoluene, toluene and p-cresol respectively. Regulation of degradation modules displayed substrate specificities ranging from narrow (toluene and cyclohexane carboxylate) via medium-wide (one module shared by p-cymene, 4-ethyltoluene, alpha-phellandrene, alpha-terpinene, gamma-terpinene and limonene) to broad (central benzoyl-CoA pathway serving 16 aromatic substrates). Remarkably, three variants of ATP-dependent (class I) benzoyl-CoA reductase and four different beta-oxidation routes establish a degradation hub that accommodates the substrate diversity. The respiratory system displayed several conspicuous profiles, e.g. the presence of nitrous oxide reductase under oxic and of low-affinity oxidase under anoxic conditions. Overall, nutritional versatility in conjunction with network regulation endow A. aromaticum pCyN1 with broad adaptability

The Cosmic Background Imager

Design and performance details are given for the Cosmic Background Imager (CBI), an interferometer array that is measuring the power spectrum of fluctuations in the cosmic microwave background radiation (CMBR) for multipoles in the range 400 < l < 3500. The CBI is located at an altitude of 5000 m in the Atacama Desert in northern Chile. It is a planar synthesis array with 13 0.9-m diameter antennas on a 6-m diameter tracking platform. Each antenna has a cooled, low-noise receiver operating in the 26-36 GHz band. Signals are cross-correlated in an analog filterbank correlator with ten 1 GHz bands. This allows spectral index measurements which can be used to distinguish CMBR signals from diffuse galactic foregrounds. A 1.2 kHz 180-deg phase switching scheme is used to reject cross-talk and low-frequency pick-up in the signal processing system. The CBI has a 3-axis mount which allows the tracking platform to be rotated about the optical axis, providing improved (u,v) coverage and a powerful discriminant against false signals generated in the receiving electronics. Rotating the tracking platform also permits polarization measurements when some of the antennas are configured for the orthogonal polarization.Comment: 14 pages. Accepted for publication in PASP. See also http://www.astro.caltech.edu/~tjp/CBI

Le cerf

Synthèse des études disponibles sur le cerf en France (Génétique population, répartition, particularités morphologiques, particularités physiologiques, pathologie, utilisation de l'espace, utilisation du temps, alimentation, vie sociale, comportement reproducteur, relations interspécifiques, dynamique et structure des populations

Deep active learning for autonomous navigation.

Imitation learning refers to an agent's ability to mimic a desired behavior by learning from observations. A major challenge facing learning from demonstrations is to represent the demonstrations in a manner that is adequate for learning and efficient for real time decisions. Creating feature representations is especially challenging when extracted from high dimensional visual data. In this paper, we present a method for imitation learning from raw visual data. The proposed method is applied to a popular imitation learning domain that is relevant to a variety of real life applications; namely navigation. To create a training set, a teacher uses an optimal policy to perform a navigation task, and the actions taken are recorded along with visual footage from the first person perspective. Features are automatically extracted and used to learn a policy that mimics the teacher via a deep convolutional neural network. A trained agent can then predict an action to perform based on the scene it finds itself in. This method is generic, and the network is trained without knowledge of the task, targets or environment in which it is acting. Another common challenge in imitation learning is generalizing a policy over unseen situation in training data. To address this challenge, the learned policy is subsequently improved by employing active learning. While the agent is executing a task, it can query the teacher for the correct action to take in situations where it has low confidence. The active samples are added to the training set and used to update the initial policy. The proposed approach is demonstrated on 4 different tasks in a 3D simulated environment. The experiments show that an agent can effectively perform imitation learning from raw visual data for navigation tasks and that active learning can significantly improve the initial policy using a small number of samples. The simulated test bed facilitates reproduction of these results and comparison with other approaches

The Keck Low-Resolution Imaging Spectrometer

The Low Resolution Imaging Spectrometer (LRIS) for the Cassegrain focus of the Keck 10-m telescope on Mauna Kea is described. It has an imaging mode so it can also be used for taking direct images. The field of view in both spectrographic and imaging modes is 6 by 7.8 arcmin. It can be used with both conventional slits and custom-punched slit masks. The optical quality of the spectrograph is good enough to take full advantage of the excellent imaging properties of the telescope itself. The detector is a cooled back-illuminated Tektronics Inc. 2048 X 2048 CCD which gives a sampling rate of 4.685 pixels per arcsec. In the spectrographic mode the spectrograph has a maximum efficiency at the peak of the grating blaze of 32%-34% for the two lowest resolution gratings and 28% for the 1200 g mm^(-1) grating. This efficiency includes the detector but not the telescope or the atmosphere