A charged-particle microbeam .2. A single-particle micro-collimation and detection system.

The use of a charged-particle microbeam provides a unique opportunity to control precisely, the number of particles traversing individual cells and the localization of dose within the cell. The accuracy of 'aiming' and of delivering a precise number of particles crucially depends on the design and implementation of the collimation and detection system. This report describes the methods available for collimating and detecting energetic particles in the context of a radiobiological microbeam. The arrangement developed at the Gray Laboratory uses either a 'V'-groove or a thick-walled glass capillary to achieve 2-5 mu m spatial resolution. The particle detection system uses an 18 mu m thick transmission scintillator and photomultiplier tube to detect particles with >99% efficiency.

Investigating the efficiency of fitting Coxian phase-type distributions to health care data

Coxian phase-type distributions are becoming a popular means of representing survival times within a health care environment. They are favoured as they show a distribution as a system of phases and can allow for an easy visual representation of the rate of flow of patients through a system. Difficulties arise, however, in determining the parameter estimates of the Coxian phase-type distribution. This paper examines ways of making the fitting of the Coxian phase-type distribution less cumbersome by outlining different software packages and algorithms available to perform the fit and assessing their capabilities through a number of performance measures. The performance measures rate each of the methods and help in identifying the more efficient. Conclusions drawn from these performance measures suggest SAS to be the most robust package. It has a high rate of convergence in each of the four example model fits considered, short computational times, detailed output, convergence criteria options, along with a succinct ability to switch between different algorithms.

NO3- transport across the plasma membrane of Arabidopsis thaliana root hairs:Kinetic control by pH and membrane voltage

High-affinity nitrate transport was examined in intact root hair cells of Arabidopsis thaliana using electrophysiological recordings to characterise the response of the plasma membrane to NO₃^-challenge and to quantify transport activity. The NO₃^--associated membrane current was determined using a three-electrode voltage clamp to bring membrane voltage under experimental control and to compensate for current dissipation along the longitudinal cell axis. Nitrate transport was evident in the roots of seedlings grown in the absence of a nitrogen source, but only 4-6 days postgermination. In 6-day-old seedlings, additions of 5-100 μm NO₃^-to the bathing medium resulted in membrane depolarizations of 8-43 mV, and membrane voltage (V_m) recovered on washing NO₃^-from the bath. Voltage clamp measurements carried out immediately before and following NO₃^-additions showed that the NO₃^--evoked depolarizations were the consequence of an inward-directed current that appeared across the entire range of accessible voltages (-300 to +50 mV). Both membrane depolarizations and NO₃^--evoked currents recorded at the free-running voltage displayed quasi-Michaelian kinetics, with apparent values for K_m of 23 ± 6 and 44 ± 11 μm, respectively and, for the current, a maximum of 5.1 ± 0.9 μA cm^-2. The NO₃^-current showed a pronounced voltage sensitivity within the normal physiological range between -250 and -100 mV, as could be demonstrated under voltage clamp, and increasing the bathing pH from 6.1 to 7.4-8.0 reduced the current and the associated membrane depolarizations 3- to 8-fold. Analyses showed a well-defined interaction between the kinetic variables of membrane voltage, pH_o and [NO₃^-]_o. At a constant pH_o of 6.1, depolarization from -250 to -150 mV resulted in an approximate 3-fold reduction in the maximum current but a 10% rise in the apparent affinity for NO₃^-. By contrast, the same depolarization effected an approximate 20% fall in the K_m for transport as a function in [H⁺]_o. These, and additional characteristics of the transport current implicate a carrier cycle in which NO₃^-binding is kinetically isolated from the rate-limiting step of membrane charge transit, and they indicate a charge-coupling stoichiometry of 2(H⁺) per NO₃^-anion transported across the membrane. The results concur with previous studies showing a high-affinity NO₃^-transport system in Arabidopsis that is inducible following a period of nitrogen-limiting growth, but they underline the importance of voltage as a kinetic factor controlling NO₃^-transport at the plant plasma membrane. © 1995 Springer-Verlag New York Inc.

VLSI module for high-performance multiply, square root and divide

A high-performance VLSI architecture to perform multiply-accumulate, division and square root operations is proposed. The circuit is highly regular, requires only minimal control and can be pipelined right down to the bit level. The system can also be reconfigured on every cycle to perform any one of these operations. The gate count per row has been estimated at (27n+70) gate equivalents where n is the divisor wordlength. The throughput rate, which equals the clock speed, is the same for each operation and is independent of the wordlength. This is achieved through the combination of pipelining and redundant arithmetic. With a 1.0 µm CMOS technology and extensive pipelining, throughput rates in excess of 70 million operations per second are expected.

Fast VLSI algorithms for division and square root

Real time digital signal processing demands high performance implementations of division and square root. This can only be achieved by the design of fast and efficient arithmetic algorithms which address practical VLSI architectural design issues. In this paper, new algorithms for division and square root are described. The new schemes are based on pre-scaling the operands and modifying the classical SRT method such that the result digits and the remainders are computed concurrently and the computations in adjacent rows are overlapped. Consequently, their performance exceeds that of the SRT methods. The hardware cost for higher radices is considerably more than that of the SRT methods but for many applications, this is not prohibitive. A system of equations is presented which enables both an analysis of the method for any radix and the parameters of implementations to be easily determined. This is illustrated for the case of radix 2 and radix 4. In addition, a highly regular array architecture combining the division and square root method is described. © 1994 Kluwer Academic Publishers.

PROSTATIC INTRAEPITHELIAL NEOPLASIA (PIN) - PERFORMANCE OF BAYESIAN BELIEF NETWORK FOR DIAGNOSIS AND GRADING

Prostatic intraepithelial neoplasia (PIN) diagnosis and grading are affected by uncertainties which arise from the fact that almost all knowledge of PIN histopathology is expressed in concepts, descriptive linguistic terms, and words. A Bayesian belief network (BBN) was therefore used to reduce the problem of uncertainty in diagnostic clue assessment, while still considering the dependences between elements in the reasoning sequence. A shallow network was used with an open-tree topology, with eight first-level descendant nodes for the diagnostic clues (evidence nodes), each independently linked by a conditional probability matrix to a root node containing the diagnostic alternatives (decision node). One of the evidence nodes was based on the tissue architecture and the others were based on cell features. The system was designed to be interactive, in that the histopathologist entered evidence into the network in the form of likelihood ratios for outcomes at each evidence node. The efficiency of the network was tested on a series of 110 prostate specimens, subdivided as follows: 22 cases of non-neoplastic prostate or benign prostatic tissue (NP), 22 PINs of low grade (PINlow), 22 PINs of high grade (PINhigh), 22 prostatic adenocarcinomas with cribriform pattern (PACcri), and 22 prostatic adenocarcinomas with large acinar pattern (PAClgac). The results obtained in the benign and malignant categories showed that the belief for the diagnostic alternatives is very high, the values being in general more than 0.8 and often close to 1.0. When considering the PIN lesions, the network classified and graded most of the cases with high certainty. However, there were some cases which showed values less than 0.8 (13 cases out of 44), thus indicating that there are situations in which the feature changes are intermediate between contiguous categories or grades. Discrepancy between morphological grading and the BBN results was observed in four out of 44 PIN cases: one PINlow was classified as PINhigh and three PINhigh were classified as PINlow. In conclusion, the network can grade PlN lesions and differentiate them from other prostate lesions with certainty. In particular, it offers a descriptive classifier which is readily implemented and which allows the use of linguistic, fuzzy variables.

EXPERT-SYSTEM SUPPORT USING BAYESIAN BELIEF NETWORKS IN THE DIAGNOSIS OF FINE-NEEDLE ASPIRATION BIOPSY SPECIMENS OF THE BREAST

Aim-To develop an expert system model for the diagnosis of fine needle aspiration cytology (FNAC) of the breast.

Methods-Knowledge and uncertainty were represented in the form of a Bayesian belief network which permitted the combination of diagnostic evidence in a cumulative manner and provided a final probability for the possible diagnostic outcomes. The network comprised 10 cytological features (evidence nodes), each independently linked to the diagnosis (decision node) by a conditional probability matrix. The system was designed to be interactive in that the cytopathologist entered evidence into the network in the form of likelihood ratios for the outcomes at each evidence node.

Results-The efficiency of the network was tested on a series of 40 breast FNAC specimens. The highest diagnostic probability provided by the network agreed with the cytopathologists' diagnosis in 100% of cases for the assessment of discrete, benign, and malignant aspirates. A typical probably benign cases were given probabilities in favour of a benign diagnosis. Suspicious cases tended to have similar probabilities for both diagnostic outcomes and so, correctly, could not be assigned as benign or malignant. A closer examination of cumulative belief graphs for the diagnostic sequence of each case provided insight into the diagnostic process, and quantitative data which improved the identification of suspicious cases.

Conclusion-The further development of such a system will have three important roles in breast cytodiagnosis: (1) to aid the cytologist in making a more consistent and objective diagnosis; (2) to provide a teaching tool on breast cytological diagnosis for the non-expert; and (3) it is the first stage in the development of a system capable of automated diagnosis through the use of expert system machine vision.

Preliminary analysis of organic Rankine cycles to improve vehicle efficiency

This paper presents the background rationale and key findings for a model-based study of supercritical waste heat recovery organic Rankine cycles. The paper’s objective is to cover the necessary groundwork to facilitate the future operation of a thermodynamic organic Rankine cycle model under realistic thermodynamic boundary conditions for performance optimisation of organic Rankine cycles. This involves determining the type of power cycle for organic Rankine cycles, the circuit configuration and suitable boundary conditions. The study focuses on multiple heat sources from vehicles but the findings are generally applicable, with careful consideration, to any waste heat recovery system. This paper introduces waste heat recovery and discusses the general merits of organic fluids versus water and supercritical operation versus subcritical operation from a theoretical perspective and, where possible, from a practical perspective. The benefits of regeneration are investigated from an efficiency perspective for selected subcritical and supercritical conditions. A simulation model is described with an introduction to some general Rankine cycle boundary conditions. The paper describes the analysis of real hybrid vehicle data from several driving cycles and its manipulation to represent the thermal inertia for model heat input boundary conditions. Basic theory suggests that selecting the operating pressures and temperatures to maximise the Rankine cycle performance is relatively straightforward. However, it was found that this may not be the case for an organic Rankine cycle operating in a vehicle. When operating in a driving cycle, the available heat and its quality can vary with the power output and between heat sources. For example, the available coolant heat does not vary much with the load, whereas the quantity and quality of the exhaust heat varies considerably. The key objective for operation in the vehicle is optimum utilisation of the available heat by delivering the maximum work out. The fluid selection process and the presentation and analysis of the final results of the simulation work on organic Rankine cycles are the subjects of two future publications.

The Pan-STARRS Moving Object Processing System

We describe the Pan-STARRS Moving Object Processing System (MOPS), a modern software package that produces automatic asteroid discoveries and identifications from catalogs of transient detections from next-generation astronomical survey telescopes. MOPS achieves >99.5% efficiency in producing orbits from a synthetic but realistic population of asteroids whose measurements were simulated for a Pan-STARRS4-class telescope. Additionally, using a nonphysical grid population, we demonstrate that MOPS can detect populations of currently unknown objects such as interstellar asteroids. MOPS has been adapted successfully to the prototype Pan-STARRS1 telescope despite differences in expected false detection rates, fill-factor loss, and relatively sparse observing cadence compared to a hypothetical Pan-STARRS4 telescope and survey. MOPS remains highly efficient at detecting objects but drops to 80% efficiency at producing orbits. This loss is primarily due to configurable MOPS processing limits that are not yet tuned for the Pan-STARRS1 mission. The core MOPS software package is the product of more than 15 person-years of software development and incorporates countless additional years of effort in third-party software to perform lower-level functions such as spatial searching or orbit determination. We describe the high-level design of MOPS and essential subcomponents, the suitability of MOPS for other survey programs, and suggest a road map for future MOPS development.

On The Energy-Efficiency of Byte-Addressable Non-Volatile Memory

Non-Volatile Memory (NVM) technology holds promise to replace SRAM and DRAM at various levels of the memory hierarchy. The interest in NVM is motivated by the difficulty faced in scaling DRAM beyond 22 nm and, long-term, lower cost per bit. While offering higher density and negligible static power (leakage and refresh), NVM suffers increased latency and energy per memory access. This paper develops energy and performance models of memory systems and applies them to understand the energy-efficiency of replacing or complementing DRAM with NVM. Our analysis focusses on the application of NVM in main memory. We demonstrate that NVM such as STT-RAM and RRAM is energy-efficient for memory sizes commonly employed in servers and high-end workstations, but PCM is not. Furthermore, the model is well suited to quickly evaluate the impact of changes to the model parameters, which may be achieved through optimization of the memory architecture, and to determine the key parameters that impact system-level energy and performance.

HERQULES:System level cross-layer design exploration for efficient energy-quality trade-offs

In this paper, we present a unique cross-layer design framework that allows systematic exploration of the energy-delay-quality trade-offs at the algorithm, architecture and circuit level of design abstraction for each block of a system. In addition, taking into consideration the interactions between different sub-blocks of a system, it identifies the design solutions that can ensure the least energy at the "right amount of quality" for each sub-block/system under user quality/delay constraints. This is achieved by deriving sensitivity based design criteria, the balancing of which form the quantitative relations that can be used early in the system design process to evaluate the energy efficiency of various design options. The proposed framework when applied to the exploration of energy-quality design space of the main blocks of a digital camera and a wireless receiver, achieves 58% and 33% energy savings under 41% and 20% error increase, respectively. © 2010 ACM.

Determinants of root-associated fungal communities within Asteraceae in a semi-arid grassland

Summary

1.While plant–fungal interactions are important determinants of plant community assembly and ecosystem functioning, the processes underlying fungal community composition are poorly understood.
2.Here, we studied for the first time the root-associated eumycotan communities in a set of co-occurring plant species of varying relatedness in a species-rich, semi-arid grassland in Germany. The study system provides an opportunity to evaluate the importance of host plants and gradients in soil type and landscape structure as drivers of fungal community structure on a relevant spatial scale. We used 454 pyrosequencing of the fungal internal transcribed spacer region to analyse root-associated eumycotan communities of 25 species within the Asteraceae, which were sampled at different locations within a soil type gradient. We partitioned the variance accounted for by three predictors (host plant phylogeny, spatial distribution and soil type) to quantify their relative roles in determining fungal community composition and used null model analyses to determine whether community composition was influenced by biotic interactions among the fungi.
3.We found a high fungal diversity (156 816 sequences clustered in 1100 operational taxonomic units (OTUs)). Most OTUs belonged to the phylum Ascomycota (35.8%); the most abundant phylotype best-matched Phialophora mustea. Basidiomycota were represented by 18.3%, with Sebacina as most abundant genus. The three predictors explained 30% of variation in the community structure of root-associated fungi, with host plant phylogeny being the most important variance component. Null model analysis suggested that many fungal taxa co-occurred less often than expected by chance, which demonstrates spatial segregation and indicates that negative interactions may prevail in the assembly of fungal communities.
4.Synthesis. The results show that the phylogenetic relationship of host plants is the most important predictor of root-associated fungal community assembly, indicating that fungal colonization of host plants might be facilitated by certain plant traits that may be shared among closely related plant species.

Looking for free riding: Energy efficiency incentives and Italian homeowners

We examine the effect of energy efficiency incentives on household energy efficiency home improvements. Starting in February 2007, Italian homeowners have been able to avail themselves of tax credits on the purchase and installation costs of certain types of energy efficiency renovations. We examine two such renovations—door/window replacements and heating system replacements—using multi-year cross-section data from the Italian Consumer Expenditure Survey and focusing on a narrow period around the introduction of the tax credits. Our regressions control for dwelling and household characteristics and economy-wide factors likely to influence the replacement rates. The effects of the policy are different for the two types of renovations. With window replacements, the policy is generally associated with a 30 % or stronger increase in the renovation rates and number of renovations. In the simplest econometric models, the effect is not statistically significant, but the results get stronger when we allow for heterogeneous effects across the country. With heating system replacements, simpler models suggest that the tax credits policy had no effect whatsoever or that free riding was rampant, i.e., people are now accepting subsidies for replacements that they would have done anyway. Further examination suggests a strong degree of heterogeneity in the effects across warmer and colder parts of the country, and effects in the colder areas that are even more pronounced than those for window replacements. These results should, however, be interpreted with caution due to the low rates of renovations, which imply that the effects are estimated relatively imprecisely.

Optimizing the efficiency of the sub-map technique for large-scale simultaneous localization and mapping

A technique for optimizing the efficiency of the sub-map method for large-scale simultaneous localization and mapping (SLAM) is proposed. It optimizes the benefits of the sub-map technique to improve the accuracy and consistency of an extended Kalman filter (EKF)-based SLAM. Error models were developed and engaged to investigate some of the outstanding issues in employing the sub-map technique in SLAM. Such issues include the size (distance) of an optimal sub-map, the acceptable error effect caused by the process noise covariance on the predictions and estimations made within a sub-map, when to terminate an existing sub-map and start a new one and the magnitude of the process noise covariance that could produce such an effect. Numerical results obtained from the study and an error-correcting process were engaged to optimize the accuracy and convergence of the Invariant Information Local Sub-map Filter previously proposed. Applying this technique to the EKF-based SLAM algorithm (a) reduces the computational burden of maintaining the global map estimates and (b) simplifies transformation complexities and data association ambiguities usually experienced in fusing sub-maps together. A Monte Carlo analysis of the system is presented as a means of demonstrating the consistency and efficacy of the proposed technique.

Thermography-based virtual MPPT scheme for improving PV energy efficiency under partial shading conditions

This paper proposes a new thermography-based maximum power point tracking (MPPT) scheme to address photovoltaic (PV) partial shading faults. Solar power generation utilizes a large number of PV cells connected in series and in parallel in an array, and that are physically distributed across a large field. When a PV module is faulted or partial shading occurs, the PV system sees a nonuniform distribution of generated electrical power and thermal profile, and the generation of multiple maximum power points (MPPs). If left untreated, this reduces the overall power generation and severe faults may propagate, resulting in damage to the system. In this paper, a thermal camera is employed for fault detection and a new MPPT scheme is developed to alter the operating point to match an optimized MPP. Extensive data mining is conducted on the images from the thermal camera in order to locate global MPPs. Based on this, a virtual MPPT is set out to find the global MPP. This can reduce MPPT time and be used to calculate the MPP reference voltage. Finally, the proposed methodology is experimentally implemented and validated by tests on a 600-W PV array.