Characteristic odor of Osmoderma eremita identified as a male-released pheromone

Osmoderma eremita (Scopoli) is an endangered scarab beetle living in hollow trees. It has mainly been known for its characteristic odor, typically described as a fruity, peachlike or plumlike aroma. The odor emanating from a single beetle can sometimes be perceived from a distance of several meters. In this paper, we show that the characteristic odor from O. eremita is caused by the compound (R)-(+)--decalactone, released in large quantities mainly or exclusively by male beetles. Antennae from male and female beetles responded in a similar way to (R)-(+)--decalactone in electroantennographic recordings. Field trapping experiments showed that (R)-(+)--decalactone is a pheromone attracting female beetles. Lactones similar to (R)-(+)--decalactone are frequently used as female-released sex pheromones by phytophagous scarabs. This is, however, the first evidence of a lactone used as a male-produced pheromone in scarab beetles. We propose that the strong signal from males is a sexually selected trait used to compete for females and matings. The signal could work within trees but also act as a guide to tree hollows, which are an essential resource for O. eremita. Males may, thus, attract females dispersing from their natal tree by advertising a suitable habitat. This signal could also be exploited by other males searching for tree hollows or for females, which would explain the catch of several males in our traps.     

Circular economy in cementitious ceramics: Replacement of hydrated lime with a stoichiometric balanced combination of clay and marble waste

Cementitious ceramics, produced from the hydration of cement and hydrated lime, are responsible for a great deal of damage to the environment due to the high emission of CO₂ that occurs in the production of cement and lime. Therefore, the objective of this work was to substitute the hydrated lime with a combination of clay residue and marble waste extracted from ceramic and ornamental rock producing industries, respectively, which constitutes a circular economy for the ceramic industry related to masonry applications. Ceramics were produced in the proportion 1:1:6:1.5 (cement:lime:sand:water), through the molding procedure, and were studied by replacing hydrated lime with 100% clay residue and 100% marble residue, in addition to stoichiometric calculated parts of marble to clay. The molar ratios used were 1:1, 1:2, and 2:1 (marble:clay). Tests of consistency, incorporated air content, water retention, compression strength, density, water absorption by capillarity, adhesion, and electrical resistivity were performed. The results obtained demonstrate that the use of residue of marble and clay together, as long as they are correctly balanced, provides a high gain in technological properties, enabling the circular economy of cementitious ceramics, mainly for the composition 1 marble:1clay, which presented the best properties, both in the fresh and hardened state. The economic analysis carried out proved the financial gains for the industrial sectors involved (civil construction, ornamental rock, and ceramic).     

Monte Carlo implementation of financial simulation on Cell/B.E. multi-core processor

The processor evolution has reached a critical moment in time where it will soon be impossible to increase the frequency much further. Processor designers such as Motorola, Intel and IBM have all realised that the only way to improve the FLOP/Watt ratio is to develop multi-core devices. One of the most current examples of multi-core processors is the new Sony/Toshiba/IBM Cell/B.E. multi-core processor. For the suitability to run in parallel, Monte Carlo methods are often considered embarrassingly parallel. This paper describes how a common Monte Carlo based financial simulation can be calculated in parallel using the Cell/B.E. multi-core processor. The measured performance with the achieved multi-core speed-up is also presented. With the recent availability of this increasingly available technology, financial simulations can now be performed in a fraction of the time it used to. This can also be achieved with a limited power and volume budget using commercially available technology. The main challenge with multi-core devices is clearly the programmability. The work presented here describes how this challenge could be dealt with.A basic MPI library has been developed to handle the partitioning and communication of data. The thread creation follows a POSIX thread creation model. MPI together with POSIX make the application portable in between various multi-processor systems and multi-core devices. The conclusions made indicate that a function offload MPI implementation on the Cell/B.E. multi-core processor can efficiently be used to speed-up the Monte Carlo solution of financial simulations. The conclusions made herein are also applicable to other situations where an algorithm can be easily parallelized.     

From dynamic movement primitives to associative skill memories

In recent years, research on movement primitives has gained increasing popularity. The original goals of movement primitives are based on the desire to have a sufficiently rich and abstract representation for movement generation, which allows for efficient teaching, trial-and-error learning, and generalization of motor skills (Schaal 1999). Thus, motor skills in robots should be acquired in a natural dialog with humans, e.g., by imitation learning and shaping, while skill refinement and generalization should be accomplished autonomously by the robot. Such a scenario resembles the way we teach children and connects to the bigger question of how the human brain accomplishes skill learning. In this paper, we review how a particular computational approach to movement primitives, called dynamic movement primitives, can contribute to learning motor skills. We will address imitation learning, generalization, trial-and-error learning by reinforcement learning, movement recognition, and control based on movement primitives. But we also want to go beyond the standard goals of movement primitives. The stereotypical movement generation with movement primitives entails predicting of sensory events in the environment. Indeed, all the sensory events associated with a movement primitive form an associative skill memory that has the potential of forming a most powerful representation of a complete motor skill.     

Formal concept analysis in knowledge processing: A survey on applications

This is the second part of a large survey paper in which we analyze recent literature on Formal Concept Analysis (FCA) and some closely related disciplines using FCA. We collected 1072 papers published between 2003 and 2011 mentioning terms related to Formal Concept Analysis in the title, abstract and keywords. We developed a knowledge browsing environment to support our literature analysis process. We use the visualization capabilities of FCA to explore the literature, to discover and conceptually represent the main research topics in the FCA community. In this second part, we zoom in on and give an extensive overview of the papers published between 2003 and 2011 which applied FCA-based methods for knowledge discovery and ontology engineering in various application domains. These domains include software mining, web analytics, medicine, biology and chemistry data.     

Seasonal variation of coherence in SAR interferograms in Kiruna,Northern Sweden

This article presents the results of a study conducted to quantify the seasonal variation of coherence in synthetic aperture radar (SAR) interferograms in Kiruna, Northern Sweden. In SAR interferometry (InSAR), coherence is an important concept that provides a good indication of the phase stability of the scatterers. Therefore, in this study, the degree of coherence is used as a parameter to identify the seasonal variation interferograms. For this study, 34 Radarsat-2 ultra-fine beam mode (U6D) images of the Kiruna area (67°51?N, 20°14?E) and the improved digital elevation model (DEM) created by merging the Radarsat-2 DEM and ASTER DEM were used to produce 561 differential interferograms. The interferograms were arranged in three different ways for the analysis, with the first including common master interferograms (with the summer master image), the second including the sequential interferograms that have the shortest temporal baseline, and the third accounting for all possible combinations of the interferograms (full network of interferograms). Following this step, the variation of coherence for forest areas, urban areas, and flat waste rock areas was studied. This study shows that interferograms generated for the Kiruna region exhibit seasonal variations in coherence due to the ground snow layer in winter. Furthermore, when there is water on the ground due to the melting of the snow layer (in the spring) or due to rains in autumn, the coherence is reduced considerably. Another significant feature is that there is a significant change in summer-to-summer coherence for some regions even over the course of a few years. Based on this study, it is clear that the winter Radarsat-2 U6D beam mode images are not suitable for differential interferometric SAR (DInSAR) deformation measurements in flat waste rock regions in Kiruna. It is expected that even with winter images, PSInSAR or CTM techniques will be able to provide better deformation measurements, but, in this study, those techniques were not assessed. The next step will be to study the seasonal variations in coherence in natural or man-made targets/persistent scatterers using persistent scatter InSAR (PSInSAR) or coherence target monitoring (CTM) techniques.     

Hierarchical Multiple Endmember Spectral Mixture Analysis (MESMA) of hyperspectral imagery for urban environments

Remote sensing has considerable potential for providing accurate, up-to-date information in urban areas. Urban remote sensing is complicated, however, by very high spectral and spatial complexity. In this paper, Multiple Endmember Spectral Mixture Analysis (MESMA) was applied to map urban land cover using HyMap data acquired over the city of Bonn, Germany. MESMA is well suited for urban environments because it allows the number and types of endmembers to vary on a per-pixel basis, which allows controlling the large spectral variability in these environments. We employed a hierarchical approach, in which MESMA was applied to map four levels of complexity ranging from the simplest level consisting of only two classes, impervious and pervious, to 20 classes that differentiated material composition and plant species. Lower levels of complexity, mapped at the highest accuracies, were used to constrain spatially models at higher levels of complexity, reducing spectral confusion between materials. A spectral library containing 1521 endmembers was created from the HyMap data. Three endmember selection procedures, Endmember Average RMS (EAR), Minimum Average Spectral Angle (MASA) and Count Based Endmember Selection (COB), were used to identify the most representative endmembers for each level of complexity. Combined two-, three- or four-endmember models - depending on the hierarchical level - were applied, and the highest endmember fractions were used to assign a land cover class. Classification accuracies of 97.2% were achieved for the two lowest complexity levels, consisting of impervious and pervious classes, and a four class map consisting of vegetation, bare soil, water and built-up. At the next level of complexity, consisting of seven classes including trees, grass, bare soil, river, lakes/basins, road and roof/building, classification accuracies remained high at 81.7% with most classes mapped above 85% accuracy. At the highest level, consisting of 20 land cover classes, a 75.9% classification accuracy was achieved. The ability of MESMA to incorporate within-class spectral variability, combined with a hierarchical approach that uses spatial information from one level to constrain model selection at a higher level of complexity was shown to be particularly well suited for urban environments.     

Performing the success of an innovation: the case of smallholder drip irrigation in Burkina Faso

Over the last 15 years, smallholder drip irrigation has gained almost unanimous popularity as an effective tool to achieve the combined goals of sustainable water use, food security and poverty alleviation in the developing world. Based on a study in Sub-Saharan Africa, this article shows that this popularity does not stem from what the technology does in farmers’ fields, but is the result of the concerted efforts of a number of key spokespersons to align it with the projects and interests of a variety of actors, including development agents, researchers, NGO staff and pilot farmers.     

Thermally Induced Flexo‐Type Effects in Nanopatterned Multiferroic Layers

The difficulty to generate and control large strain gradients in materials hinders the investigation and application of flexoelectricity and flexomagnetism. This work demonstrates that thermal expansion can be used to induce very large non‐uniform strains at the nanoscale, resulting in giant strain gradients at moderate temperatures. This is demonstrated in a nanopatterned multiferroic hybrid layer consisting of a regular array of ferromagnetic metallic nanocylinders embedded in a ferroelectric polymer matrix. The thermally‐induced strain gradients can fully depolarize the ferroelectric component, and modify the magnetization of the ferromagnetic component via flexoelectric and flexomagnetic effects, respectively. Finite‐element analysis provides a quantitative view on thermal expansion‐induced strains and strain gradients supporting the experimental findings. This work shows that nanoscale thermal strain engineering provides an additional degree of freedom to control electrical polarization and magnetization, which paves the way for the design and operation of novel functional devices and nanostructures.     

Single Sensor Compressive Light Field Video Camera

This paper presents a novel compressed sensing (CS) algorithm and camera design for light field video capture using a single sensor consumer camera module. Unlike microlens light field cameras which sacrifice spatial resolution to obtain angular information, our CS approach is designed for capturing light field videos with high angular, spatial, and temporal resolution. The compressive measurements required by CS are obtained using a random color-coded mask placed between the sensor and aperture planes. The convolution of the incoming light rays from different angles with the mask results in a single image on the sensor; hence, achieving a significant reduction on the required bandwidth for capturing light field videos. We propose to change the random pattern on the spectral mask between each consecutive frame in a video sequence and extracting spatio-angular-spectral-temporal 6D patches. Our CS reconstruction algorithm for light field videos recovers each frame while taking into account the neighboring frames to achieve significantly higher reconstruction quality with reduced temporal incoherencies, as compared with previous methods. Moreover, a thorough analysis of various sensing models for compressive light field video acquisition is conducted to highlight the advantages of our method. The results show a clear advantage of our method for monochrome sensors, as well as sensors with color filter arrays.