MonALISA : A Distributed Monitoring Service Architecture

The MonALISA (Monitoring Agents in A Large Integrated Services Architecture) system provides a distributed monitoring service. MonALISA is based on a scalable Dynamic Distributed Services Architecture which is designed to meet the needs of physics collaborations for monitoring global Grid systems, and is implemented using JINI/JAVA and WSDL/SOAP technologies. The scalability of the system derives from the use of multithreaded Station Servers to host a variety of loosely coupled self-describing dynamic services, the ability of each service to register itself and then to be discovered and used by any other services, or clients that require such information, and the ability of all services and clients subscribing to a set of events (state changes) in the system to be notified automatically. The framework integrates several existing monitoring tools and procedures to collect parameters describing computational nodes, applications and network performance. It has built-in SNMP support and network-performance monitoring algorithms that enable it to monitor end-to-end network performance as well as the performance and state of site facilities in a Grid. MonALISA is currently running around the clock on the US CMS test Grid as well as an increasing number of other sites. It is also being used to monitor the performance and optimize the interconnections among the reflectors in the VRVS system.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 8 pages, pdf. PSN MOET00

The African Lungfish (\u3cem\u3eProtopterus dolloi\u3c/em\u3e): Ionoregulation and Osmoregulation in a Fish out of Water

Although urea production and metabolism in lungish have been thoroughly studied, we have little knowledge of how internal osmotic and electrolyte balance are controlled during estivation or in water. We tested the hypothesis that, compared with the body surface of teleosts, the slender African lungfish (Protopterus dolloi) body surface was relatively impermeable to water, Na+ and Cl- due to its greatly reduced gills. Accordingly, we measured the tritiated water (3H-H2O) flux in P. dolloi in water and during air exposure. In water, 3H-H2O efflux was comparable with the lowest measurements reported in freshwater teleosts, with a rate constant (K) of 17.6% body water h-1. Unidirectional ion fluxes, measured using 22Na+ and 36Cl-, indicated that Na+ and Cl- influx was more than 90% lower than values reported in most freshwater teleosts. During air exposure, a cocoon formed within 1 wk that completely covered the dorsolateral body surface. However, there were no disturbances to blood osmotic or ion (Na+, Cl-) balance, despite seven- to eightfold increases in plasma urea after 20 wk. Up to 13-fold increases in muscle urea (on a dry-weight basis) were the likely explanation for the 56% increase in muscle water content observed after 20 wk of air exposure. The possibility that muscle acted as a “water reservoir” during air exposure was supported by the 20% decline in body mass observed during subsequent reimmersion in water. This decline in body mass was equivalent to 28 mL water in a 100-g animal and was very close to the calculated net water gain (approximately 32 mL) observed during the 20-wk period of air exposure. Tritiated water and unidirectional ion fluxes on air-exposed lungfish revealed that the majority of water and ion exchange was via the ventral body surface at rates that were initially similar to aquatic rates. The 3H-H2O flux declined over time but increased upon reimmersion. We conclude that the slender lungfish body surface, including the gills, has relatively low permeability to water and ions but that the ventral surface is an important site of osmoregulation and ionoregulation. We further propose that an amphibian-like combination of ventral skin water and ion permeability, plus internal urea accumulation during air exposure, allows P. dolloi to extract water from its surroundings and to store water in the muscle when the water supply becomes limited

A quasiconformal Hopf soap bubble theorem

We show that any compact surface of genus zero in Euclidean 3-space that satisfies a quasiconformal inequality between its principal curvatures is a round sphere. This solves an old open problem by H. Hopf, and gives a spherical version of Simon's quasiconformal Bernstein theorem. The result generalizes, among others, Hopf's theorem for constant mean curvature spheres, the classification of round spheres as the only compact elliptic Weingarten surfaces of genus zero, and the uniqueness theorem for ovaloids by Han, Nadirashvili and Yuan. The proof relies on the Bers-Nirenberg representation of solutions to linear elliptic equations with discontinuous coefficients.Comment: 19 pages, 3 figure

Evolutionary 3D Image Segmentation of Curve Epithelial Tissues of Drosophila melanogaster

Analysing biological images coming from the microscope is challenging; not only is it complex to acquire the images, but also the three-dimensional shapes found on them. Thus, using automatic approaches that could learn and embrace that variance would be highly interesting for the field. Here, we use an evolutionary algorithm to obtain the 3D cell shape of curve epithelial tissues. Our approach is based on the application of a 3D segmentation algorithm called LimeSeg, which is a segmentation software that uses a particle-based active contour method. This program needs the fine-tuning of some hyperparameters that could present a long number of combinations, with the selection of the best parametrisation being highly time-consuming. Our evolutionary algorithm automatically selects the best possible parametrisation with which it can perform an accurate and non-supervised segmentation of 3D curved epithelial tissues. This way, we combine the segmentation potential of LimeSeg and optimise the parameters selection by adding automatisation. This methodology has been applied to three datasets of confocal images from Drosophila melanogaster, where a good convergence has been observed in the evaluation of the solutions. Our experimental results confirm the proper performing of the algorithm, whose segmented images have been compared to those manually obtained for the same tissues

Dispersal by cattle of salt-marsh and dune species into salt-marsh and dune communities

Seed dispersal via ingestion and defecation by large herbivores (endozoochory) plays a potentially important role in structuring plant communities. In the present study we tested whether cattle disperse seeds between different plant communities in a heterogeneous coastal habitat. We surveyed the seed contents of cattle dung collected from two habitat types within a grazing system, one in dunes and the other in salt-marsh. The dunes are characterized by sandy soil, and infrequent inundation by the sea, whereas the salt-marsh features clay deposited during inundations. Seeds of both salt-marsh and dune species were dispersed into salt-marsh and dune habitats. The seed content of cattle dung collected in salt-marsh and dunes was similar with respect to species composition and seed density. However, dispersal of dune species into salt-marsh and vice-versa did not result in establishment in those communities. Seed traits per se did not differ between dune species and salt-marsh species. Species abundance in the established vegetation and seed density in dung were positively correlated. Seed abundance for most species found in dung was consistent with the availability of viable seeds during the growing season. Seed mass, seed 'roundness' and seed release height were all negatively correlated with seed numbers in dung. An indirect factor, namely, forage quality of the plant, and hence attractiveness for herbivores, could explain the higher likelihood of seed dispersal of salt-marsh species than of dune species. The salt-marsh harbours species with higher forage quality than the dune species, as derived from Ellenberg nitrogen indicator values

Size-Controlled Water-Soluble Ag Nanoparticles

Ag nanoparticles of two different sizes (1 and 4 nm) were prepared within an apoferritin cavity by using an Ag+-loaded apoferritin as a nanoconfined environment for their construction. The initial amount of Ag' ions injected in the apoferritin cavity dictates the size of the final Ag particles. The protein shell prevents bulk aggregation of the metal particles, which renders them water soluble and extremely stable

Enfermedades y fisiopatías que afectan a la calidad del ajo en postcosecha

Las enfermedades y fisiopatías que afectan al ajo pueden llegar a ocasionar importantes pérdidas en postcosecha, de vital importancia cuando el producto se destina a la exportación a mercados que cada día son más exigentes. En 2008, distintos agricultores de varios municipios de Castilla y León detectaron bulbos de ajo que presentaban síntomas de podredumbre húmeda durante el almacenamiento. Posteriormente, en el año 2009, esta misma podredumbre se observó también en las provincias de Albacete y Cuenca y en muestras procedentes de Córdoba. Hasta la fecha se ha identificado a Fusarium proliferatum como el agente causal de la podredumbre del diente

Object Detection in X-ray Images Using Transfer Learning with Data Augmentation

Object detection in X-ray images is an interesting problem in the field of machine vision. The reason is that images from an X-ray machine are usually obstructed with other objects and to itself, therefore object classification and localization is a challenging task. Furthermore, obtaining X-ray data is difficult due to an insufficient dataset available compared with photographic images from a digital camera. It is vital to easily detect objects in an X-ray image because it can be used as decision support in the detection of threat items such as improvised explosive devices (IED’s) in airports, train stations, and public places. Detection of IED components accurately requires an expert and can be achieved through extensive training. Also, manual inspection is tedious, and the probability of missed detection increases due to several pieces of baggage are scanned in a short period of time. As a solution, this paper used different object detection techniques (Faster R-CNN, SSD, R-FCN) and feature extractors (ResNet, MobileNet, Inception, Inception-ResNet) based on convolutional neural networks (CNN) in a novel IEDXray dataset in the detection of IED components. The IEDXray dataset is an X-ray image of IED replicas without the explosive material. Transfer learning with data augmentation was performed due to limited X-ray data available to train the whole network from scratch. Evaluation results showed that individual detection achieved 99.08% average precision (AP) in mortar detection and 77.29% mAP in three IED components