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The lunar environment while in the Earth’s magnetosphere represents a unique plasma regime, in which we can directly detect the Moon’s effects on the ambient plasma environment. To a much greater degree than in the solar wind, the presence of the Moon and its exosphere perturb the ambient plasma environment. We identified and analyzed a variety of different effects of this interaction. We mapped four different interaction signatures and analyzed the solar and solar wind parameters during their occurrence. Confirming previous work, we found that the lunar events investigated in this paper tend to occur above the lunar dayside surface. In addition, we found that magnetospheric activity indices are higher during the categorized lunar events. This suggests that when the terrestrial magnetosphere is more active, as a result of solar wind activity, the terrestrial magnetospheric plasma and electromagnetic fields interact with lunar plasma to create the observed perturbations.

The Universal Soil Loss Equation (USLE) is the most frequently applied erosion prediction model and it is also implemented as official decision-making instrument for agricultural regulations. The USLE itself was already validated by different approaches. Additional errors, however, arise from input data and interpolation procedures that become necessary for field-specific predictions on a national scale for administrative purposes. In this study, predicted event soil loss using the official prediction system in Bavaria (Germany) was validated by comparison with aerial photo erosion classifications of 8100 fields. Values for the USLE factors were mainly taken from the official Bavarian high-resolution (5 x 5 m2) erosion cadastre. As series of erosion events were examined, the cover and management factor was replaced by the soil loss ratio. The event erosivity factor was calculated from high-resolution (1 x 1 km2, 5 min), rain gauge-adjusted radar rain data (RADOLAN). Aerial photo erosion interpretation worked sufficiently well and average erosion predictions and visual classifications correlated closely. This was also true for data broken down to individual factors and different crops. There was no reason to assume a general invalidity of the USLE and the official parameterization procedures. Event predictions mainly suffered from errors in the assumed crop stage period and tillage practices, which do not reflect interannual and farm-specific variation. In addition, the resolution of radar data (1 km2) did not seem to be sufficient to predict short-term erosion on individual fields given the strong spatial gradients within individual rains. The quality of the input data clearly determined prediction quality. Differences between USLE predictions and observations are most likely caused by parameterization weaknesses but not by a failure of the model itself.

The interplay between natural site conditions and farming raises erosion by water above geological background levels. We examined the hypothesis that farmers take erosion into account in their farming decisions and switch to farming practices with lower erosion risk the higher the site-specific hazard becomes. Erosion since the last tillage was observed from aerial orthorectified photographs for 8100 fields belonging to 1879 farmers distributed across Bavaria (South Germany) and it was modeled by the Universal Soil Loss Equation using highly detailed input data (e.g., digital terrain model with 5×5m2 resolution, rain data with 1×1km2 and 5min resolution, crop and cropping method from annual field-specific data from incentive schemes). Observed and predicted soil loss correlated closely, demonstrating the accuracy of this method. The close correlation also indicted that the farmers could easily observe the degree of recent erosion on their fields, even without modelling. Farmers clearly did not consider erosion in their decisions. When natural risk increased, e.g. due to steeper slopes, they neither grew crops with lower erosion potential, nor reduced field size, nor used contouring. In addition, they did not compensate for the cultivation of crops with higher erosion potential by using conservation techniques like mulch tillage or contouring, or by reducing field size. Only subsidized measures, like mulch tillage or organic farming, were applied but only at the absolute minimum that was necessary to obtain subsidies. However, this did not achieve the reduction in erosion that would be possible if these measures had been fully applied. We conclude that subsidies may be an appropriate method of reducing erosion but the present weak supervision, which assumes that farmers themselves will take erosion into account and that subsidies are only needed to compensate for any disadvantages caused by erosion-reducing measures, is clearly not justified.

In this paper we present the design and implementation of the Linpack benchmark for the IBM BladeCenter QS22, which incorporates two IBM PowerXCell 8i1processors. The PowerXCell 8i is a new implementation of the Cell Broadband Engine™2 architecture and contains a set of special-purpose processing cores known as Synergistic Processing Elements (SPEs). The SPEs can be used as computational accelerators to augment the main PowerPC processor. The added computational capability of the SPEs results in a peak double precision floating point capability of 108.8 GFLOPS. We explain how we modified the standard open source implementation of Linpack to accelerate key computational kernels using the SPEs of the PowerXCell 8i processors. We describe in detail the implementation and performance of the computational kernels and also explain how we employed the SPEs for high-speed data movement and reformatting. The result of these modifications is a Linpack benchmark optimized for the IBM PowerXCell 8i processor that achieves 170.7 GFLOPS on a BladeCenter QS22 with 32 GB of DDR2 SDRAM memory. Our implementation of Linpack also supports clusters of QS22s, and was used to achieve a result of 11.1 TFLOPS on a cluster of 84 QS22 blades. We compare our results on a single BladeCenter QS22 with the base Linpack implementation without SPE acceleration to illustrate the benefits of our optimizations.

Introduction: Retroperitoneal schwannomas are rare pelvic tumors that arise from Schwann nerve sheath cells. Although primary retroperitoneal schwannomas have been reported in the adrenal glands and gastrointestinal tract, very few reports have described this lesion in association with the female genital tract. Case Report: In this paper, we present a case involving a 59-year-old woman who presented with a 5 × 6 cm retroperitoneal mass in 2006. An initial radiologic evaluation suggested a left ovarian lesion. The patient underwent a laparotomy to resect the retroperitoneal mass. A final pathology revealed primary retroperitoneal schwannoma. The patient developed a partial right femoral neuropathy postoperatively, which improved gradually with observation. Conclusions: Retroperitoneal schwannomas are very rare lesions that are infrequently associated with the gynecologic tract. Although these tumors are primarily benign, experience with pelvic surgery is essential to minimize the risk of intraoperative vas...

We study the performance benefits of speculation in a release consistent software distributed shared memory system. We propose a new protocol, speculative home-based release consistency (SHRC) that speculatively updates data at remote nodes to reduce the latency of remote memory accesses. Our protocol employs a predictor that uses patterns in past accesses to shared memory to predict future accesses. We have implemented our protocol in a release consistent software distributed shared memory system that runs on commodity hardware. We evaluate our protocol implementation using eight software distributed shared memory benchmarks and show that it can result in significant performance improvements.

Finite element (FE) analysis is an important computational tool in biomechanics. However, its adoption into clinical practice has been hampered by its computational complexity and required high technical competences for clinicians. In this paper we propose a supervised learning approach to predict the outcome of the FE analysis. We demonstrate our approach on clinical CT and X-ray femur images for FE predictions ( FEP), with features extracted, respectively, from a statistical shape model and from 2D-based morphometric and density information. Using leave-one-out experiments and sensitivity analysis, comprising a database of 89 clinical cases, our method is capable of predicting the distribution of stress values for a walking loading condition with an average correlation coefficient of 0.984 and 0.976, for CT and X-ray images, respectively. These findings suggest that supervised learning approaches have the potential to leverage the clinical integration of mechanical simulations for the treatment of musculoskeletal conditions.

In this paper, we put forward the notion that systems management for large masses of virtual machines in data centers is going to be done differently in the short to medium term future-through smart phones and through controlled crowdsourcing to a variety of experts within an organization, rather than dedicated system administrators alone. We lay out the research and practitioner challenges this model raises and give some preliminary solution directions that are being developed, here at IBM and elsewhere.

In this paper we describe our experiences with a new full-system simulator for the Power™ architecture that achieves a high-level of simulation performance through careful design and the application of dynamic binary translation. Our simulator is written entirely in Java and can run simple applications and also boot whole operating systems. We chose Java because it has a wide developer base, portability, support for modern programming features such as inheritance, ease of scripting, built in serialization, and a broad selection of robust developer tools. To improve simulation performance, we treat the byte code for our instruction interpreter as an intermediate representation to drive dynamic binary translation. When running as a pure instruction interpreter, the simulator can achieve simulation speeds of over 100 MIPS. For simple applications, dynamic binary translation can improve simulation performance by a factor of 2 or more, to over 200 MIPS. We continue to work on dynamic binary translation for booting a full operating system, and we are also exploring dynamic translation of Java byte code directly to host object code.

Background: Statistical shape models are widely used in biomedical research. They are routinely implemented for automatic image segmentation or object identification in medical images. In these fields, however, the acquisition of the large training datasets, required to develop these models, is usually a time-consuming process. Even after this effort, the collections of datasets are often lost or mishandled resulting in replication of work. Objective: To solve these problems, the Virtual Skeleton Database (VSD) is proposed as a centralized storage system where the data necessary to build statistical shape models can be stored and shared. Methods: The VSD provides an online repository system tailored to the needs of the medical research community. The processing of the most common image file types, a statistical shape model framework, and an ontology-based search provide the generic tools to store, exchange, and retrieve digital medical datasets. The hosted data are accessible to the community, and collaborative research catalyzes their productivity. Results: To illustrate the need for an online repository for medical research, three exemplary projects of the VSD are presented: (1) an international collaboration to achieve improvement in cochlear surgery and implant optimization, (2) a population-based analysis of femoral fracture risk between genders, and (3) an online application developed for the evaluation and comparison of the segmentation of brain tumors. Conclusions: The VSD is a novel system for scientific collaboration for the medical image community with a data-centric concept and semantically driven search option for anatomical structures. The repository has been proven to be a useful tool for collaborative model building, as a resource for biomechanical population studies, or to enhance segmentation algorithms. [J Med Internet Res 2013;15(11):e245]

Introduction: Small animal models are widely used in basic research. However, experimental systems requiring extracorporeal circuits are frequently confronted with limitations related to equipment size. This is particularly true for oxygenators in systems with limited volumes. Thus we aimed to develop and validate an ultra mini-oxygenator for low-volume, buffer-perfused systems. Methods: We have manufactured a series of ultra mini-oxygenators with approximately 175 aligned, microporous, polypropylene hollow fibers contained inside a shell, which is sealed at each of the two extremities to isolate perfusate and gas compartments. With this construction, gas passes through hollow fibers, while perfusate circulates around fibers. Performance of ultra mini-oxygenators (oxygen partial pressure (PO2), gas and perfusate flow, perfusate pressure and temperature drop) were assessed with modified Krebs-Henseleit buffer in an in vitro perfusion circuit and an ex vivo rat heart preparation. Results: Mean priming volume of ultra mini-oxygenators was 1.2±0.5 mL and, on average, 86±6% of fibers were open (n=17). In vitro, effective oxygenation (PO2=400–500 mmHg) was achieved for all flow rates up to 50 mL/min and remained stable for at least 2 hours (n=5). Oxygenation was also effective and stable (PO2=456±40 mmHg) in the isolated heart preparation for at least 60 minutes (“venous” PO2=151±11 mmHg; n=5). Conclusions: We have established a reproducible procedure for fabrication of ultra mini-oxygenators, which provide reliable and stable oxygenation for at least 60–120 min. These oxygenators are especially attractive for pre-clinical protocols using small, rather than large, animals.

With the discovery of the structure of DNA and the development of new techniques for sequencing the entire genome of organisms, biology is rapidlymoving towards a data-intensive, computational science. Biologists search for biomolecular sequence data to compare with other known genomes in order to determine functions and improve understanding of biochemical pathways. Computational biology has been aided by recent advances in both algorithms and technology, such as the ability to sequence short contiguous strings of DNA and from these reconstruct a whole genome [1, 15, 16]. In the area of technology, high-speed micro-array gene and protein chips [12] have been developed for the study of gene expression and function determination. These high-throughput techniques have led to an exponential growth of available genomic data. As a result, the computational power needed by bioinformatics applications is growing exponentially and it is now apparent that this power will not be provided solely by traditional general-purpose processors.

This paper evaluates the performance of bioinformatics applications on the Cell Broadband Engine (Cell/B.E.) recently developed at IBM. In particular we focus on three highly popular bioinformatics applications - FASTA, ClustalW, and HMMER. The characteristics of these bioinformatics applications, such as small critical time-consuming code size, regular memory accesses, existing vectorized code and embarrassingly parallel computation, make them uniquely suitable for the Cell/B.E. processing platform. The price and power advantages afforded by the Cell/B.E. processor also make it an attractive alternative to general purpose processors. We report preliminary performance results for these applications, and contrast these results with the state-of-the-art hardware.

This paper examines the effect of technology scaling and microarchitectural trends on the rate of soft errors in CMOS memory and logic circuits. We describe and validate an end-to-end model that enables us to compute the soft error rates (SER) for existing and future microprocessor-style designs. The model captures the effects of two important masking phenomena, electrical masking and latching-window masking, which inhibit soft errors in combinational logic. We quantify the SER due to high-energy neutrons in SRAM cells, latches, and logic circuits for feature sizes from 600 nm to 50 nm and clock periods from 16 to 6 fan-out-of-4 inverter delays. Our model predicts that the SER per chip of logic circuits will increase nine orders of magnitude from 1992 to 2011 and at that point will be comparable to the SER per chip of unprotected memory elements. Our result emphasizes that computer system designers must address the risks of soft errors in logic circuits for future designs.

Power management has traditionally focused on portable and handheld devices. This paper breaks with tradition and presents a case for managing power consumption in web servers. Web servers experience large periods of low utilization, presenting an opportunity for using power management to reduce energy consumption with minimal performance impact. We measured the energy consumption of a "typical" web server under a variety of workloads derived from access logs of real websites, including the 1998 Winter Olympics web site. Our measurements show that the CPU is the largest consumer of power for typical web servers today.We have also created a power simulator for web serving workloads that estimates CPU energy consumption with less than 5.7% error for our workloads. The simulator is fast, processing over 75,000 requests/second on a 866MHz uniprocessor machine. Using the simulator, we quantify the potential benefits of dynamically scaling the processor voltage and frequency, a power management technique that is traditionally found only in handheld devices. We find that dynamic voltage and frequency scaling is highly effective for saving energy with moderately intense web workloads, saving from 23% to 36% of the CPU energy while keeping server responsiveness within reasonable limits.

In the July 2011 issue of Respiratory Care we read with great consideration the paper from Marchese et al,[1][1] reporting the performance of 6 intensive-care ventilators currently available on the market. The present letter has no intention to contest the data reported in that paper;[1][1] instead

A FE model of each femur was built with a loading situation corresponding to normal walking [Heller 2005, Speirs 2007]. Additionally, the forces where related to the subject’s height and body weight [Bryan 2009]. The bone intensity values were converted into material properties (0.05GPa < E < 17GPa, = 0.3) [Morgan 2003, Schileo 2008] and mapped onto each node of the FE mesh which consisted of 129’600 C3D10 elements. The SMA was used to generate 1000 FE models of femurs, covering 75% of the variability of the training population. ABAQUS (Simulia Corp, USA) was used for the calculations. Predicted stresses and displacements were used to build a database of numerical results.

We describe the challenges and opportunities we encountered when developing a hybrid version of the Linpack benchmark for the Los Alamos National Laboratory Roadrunner supercomputing system, which combines traditional x86-64 host processors with IBM PowerXCell™ 8i accelerator processors. The challenges included determining the proper division of the host and accelerator roles in the computation, transfer of data between the host and accelerator memory domains, alignment of data for communication and computation, and data format differences between the two processors. We also describe our approach to modeling the performance of the hybrid system and compare our performance estimates to witnessed performance on the system at different scales and levels of memory consumption. Through careful attention to these issues, we have produced a hybrid version of the Linpack benchmark for the Roadrunner system that achieves 77.8% of peak performance on a single compute node and 74.6% of peak performance over the entire system, making this system the first to achieve a Linpack result exceeding one petaflops (1015 floating-point operations per second).

Made available in DSpace on 2018-11-26T15:27:30Z (GMT). No. of bitstreams: 0 Previous issue date: 2015-10-26 In attempts to elucidate the underlying mechanisms of spinal injuries and spinal deformities, several experimental and numerical studies have been conducted to understand the biomechanical behavior of the spine. However, numerical biomechanical studies suffer from uncertainties associated with hard- and soft-tissue anatomies. Currently, these parameters are identified manually on each mesh model prior to simulations. The determination of soft connective tissues on finite element meshes can be a tedious procedure, which limits the number of models used in the numerical studies to a few instances. In order to address these limitations, an image-based method for automatic morphing of soft connective tissues has been proposed. Results showed that the proposed method is capable to accurately determine the spatial locations of predetermined bony landmarks. The present method can be used to automatically generate patient-specific models, which may be helpful in designing studies involving a large number of instances and to understand the mechanical behavior of biomechanical structures across a given population. Swiss Fed Inst Technol, Robot Syst Lab, CH-1015 Lausanne, Switzerland Univ Bern, Grad Sch Cellular & Biomed Sci, Bern, Switzerland State Univ Sao Paulo, Dept Mat Sci, Sao Paulo, Brazil Univ Bern, Inst Surg Technol & Biomech, Bern, Switzerland Univ Childrens Hosp, Dept Orthopaed, Basel, Switzerland State Univ Sao Paulo, Dept Mat Sci, Sao Paulo, Brazil