This paper describes the airborne data collected during the 2002 and 2003 Cold Land Processes Experiment (CLPX). These data include gamma radiation observations, multi- and hyperspectral optical imaging, optical altimetry, and passive and active microwave observations of the test areas. The gamma observations were collected with the NOAA/National Weather Service Gamma Radiation Detection System (GAMMA). The CLPX multispectral optical data consist of very high-resolution color-infrared orthoimagery of the intensive study areas (ISAs) by TerrainVision. The airborne hyperspectral optical data consist of observations from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Optical altimetry measurements were collected using airborne light detection and ranging (lidar) by TerrainVision. The active microwave data include radar observations from the NASA Airborne Synthetic Aperture Radar (AIRSAR), the Jet Propulsion Laboratory’s Polarimetric Ku-band Scatterometer (POLSCAT), and airborne GPS bistatic radar data collected with the NASA GPS radar delay mapping receiver (DMR). The passive microwave data consist of observations collected with the NOAA Polarimetric Scanning Radiometer (PSR). All of the airborne datasets described here and more information describing data collection and processing are available online.

Cyclophosphamide continues to have an important role in the treatment of renal disease, including nephrotic syndrome and lupus nephritis, despite known complications of gonadotoxicity and potential infertility in both male and female patients. It is important that the physician recommending this therapy mitigates the effect of the drug on fertility by adhering to recommendations on dosing limits and offering fertility-preserving strategies. In addition to wellestablished methods, such as sperm banking and embryo cryopreservation, advances in reproductive technology have yielded strategies such as oocyte cryopreservation, resulting in more fertility-preserving options for the pediatric patient. Despite these advances, there continues to be a significant barrier to referral and access to sperm banks and fertility specialists. These issues are further complicated by ethical issues associated with the treatment of pediatric patients. In this review we explore the development of recommended dosing limits and include a discussion of the available fertility-preserving methods, strategies for increasing access to fertility specialists, and the ethical considerations facing the pediatric healthcare provider.

In this paper we describe a utility computing framework, consisting of a component model, a methodology, and a set of tools and common services for building utility computing systems. This framework facilitates the creation of new utility computing systems by providing a set of common functions, as well as a set of standard interfaces for those components that are specialized. It also provides a methodology and tools to assemble and re-use resource provisioning and management functions used to support new services with possibly different requirements. We demonstrate the benefits of the framework by describing two sample systems: a life-science utility computing service designed and implemented using the framework, and an on-line gaming utility computing service designed in compliance with the framework.We describe in this paper a utility computing framework (framework, for short) that consists of a component model, a methodology, and a set of tools and common services for building utility computing systems. A utility computing system (also referred to as a utility system, or simply a utility) is a system that can automatically create and manage multiple utility computing services (utilities services, for short) on a shared infrastructure. The infrastructure consists of pools of hardware resources, such as servers, storage, and network appliances, as well as software resources, such as operating systems, middleware, and applications. The utility services that can be created are not limited to a specific domain, and may range from e-commerce services, to scientific applications, to on-line gaming. A utility system ensures the smooth operation of the supported services by dynamically adjusting the allocation of resources. If the total demand for services exceeds the capacity of available resources, the utility system may dynamically procure and configure additional resources in order to support service level commitments. The utility system makes resource allocation and configuration decisions based on factors such as performance monitoring, SLA (service level agreement) goals, business objectives, or human interaction.Utility computing systems differ in the types of resources used, the topology of the network connecting these resources, the services offered, and the business and operational constraints that govern their operations. Figure 1 shows two examples of utility systems. Utility system 1 offers and manages services that perform scientific computations and queries. Instances of services, such as the protein folding service, are illustrated at the upper tier in Figure 1. Utility system 1 uses an infrastructure that includes IBM eServer* zSeries* servers, an Oracle** database, a SAN-(storage area network) based storage system, and a scientific application (these are shown at the bottom tier in Figure 1). Utility system 2 offers ecommerce services and on-line gaming services. It uses Intel** servers, an IBM DB2 Universal Database*, IBM WebSphere* application servers (WAS), and a NAS (network-attached storage) co...

Three algorithms based on geostationary visible and infrared (IR) observations are used to identify convective cells that do (or may) present a hazard to aviation over the oceans. The performance of these algorithms in detecting potentially hazardous cells is determined through verification with Tropical Rainfall Measuring Mission (TRMM) satellite observations of lightning and radar reflectivity, which provide internal information about the convective cells. The probability of detection of hazardous cells using the satellite algorithms can exceed 90% when lightning is used as a criterion for hazard, but the false-alarm ratio with all three algorithms is consistently large (∼40%), thereby exaggerating the presence of hazardous conditions. This shortcoming results in part from the algorithms’ dependence upon visible and IR observations, and can be traced to the widespread prevalence of deep cumulonimbi with weak updrafts but without lightning over tropical oceans, whose origin is attributed to significant entrainment during ascent.

No abstract