Parentage testing in alpacas (Vicugna pacos) using semi-automated fluorescent multiplex PCRs with 10 microsatellite markers

The aim of this study was to assess and apply a microsatellite multiplex system for parentage determination in alpacas. An approach for parentage testing based on 10 microsatellites was evaluated in a population of 329 unrelated alpacas from different geographical zones in Peru. All microsatellite markers, which amplified in two multiplex reactions, were highly polymorphic with a mean of 14.5 alleles per locus (six to 28 alleles per locus) and an average expected heterozygosity (H-E) of 0.8185 (range of 0.698-0.946). The total parentage exclusion probability was 0.999456 for excluding a candidate parent from parentage of an arbitrary offspring, given only the genotype of the offspring, and 0.999991 for excluding a candidate parent from parentage of an arbitrary offspring, given the genotype of the offspring and the other parent. In a case test of parentage assignment, the microsatellite panel assigned 38 (from 45 cases) offspring parentage to 10 sires with LOD scores ranging from 2.19 x 10(+13) to 1.34 x 10(+15) and Delta values ranging from 2.80 x 10(+12) to 1.34 x 10(+15) with an estimated pedigree error rate of 15.5%. The performance of this multiplex panel of markers suggests that it will be useful in parentage testing of alpacas.

Flight testing of an augmented separation management system providing separation protection during failure of the central communication network

Future air traffic management concepts often involve the proposal of automated separation management algorithms that replaces human air traffic controllers. This paper proposes a new type of automated separation management algorithm (based on the satisficing approach) that utilizes inter-aircraft communication and a track file manager (or bank of Kalman filters) that is capable of resolving conflicts during periods of communication failure. The proposed separation management algorithm is tested in a range of flight scenarios involving during periods of communication failure, in both simulation and flight test (flight tests were conducted as part of the Smart Skies project). The intention of the conducted flight tests was to investigate the benefits of using inter-aircraft communication to provide an extra layer of safety protection in support air traffic management during periods of failure of the communication network. These benefits were confirmed.

Effect of caffeine on adenosine-induced reversible perfusion defects assessed by automated analysis

Objectives This prospective study investigated the effects of caffeine ingestion on the extent of adenosine-induced perfusion abnormalities during myocardial perfusion imaging (MPI). Methods Thirty patients with inducible perfusion abnormalities on standard (caffeine-abstinent) adenosine MPI underwent repeat testing with supplementary coffee intake. Baseline and test MPIs were assessed for stress percent defect, rest percent defect, and percent defect reversibility. Plasma levels of caffeine and metabolites were assessed on both occasions and correlated with MPI findings. Results Despite significant increases in caffeine [mean difference 3,106 μg/L (95% CI 2,460 to 3,752 μg/L; P < .001)] and metabolite concentrations over a wide range, there was no statistically significant change in stress percent defect and percent defect reversibility between the baseline and test scans. The increase in caffeine concentration between the baseline and the test phases did not affect percent defect reversibility (average change −0.003 for every 100 μg/L increase; 95% CI −0.17 to 0.16; P = .97). Conclusion There was no significant relationship between the extent of adenosine-induced coronary flow heterogeneity and the serum concentration of caffeine or its principal metabolites. Hence, the stringent requirements for prolonged abstinence from caffeine before adenosine MPI—based on limited studies—appear ill-founded.

Testing second order cyclostationarity in the squared envelope spectrum of non-white vibration signals

Cyclostationary models for the diagnostic signals measured on faulty rotating machineries have proved to be successful in many laboratory tests and industrial applications. The squared envelope spectrum has been pointed out as the most efficient indicator for the assessment of second order cyclostationary symptoms of damages, which are typical, for instance, of rolling element bearing faults. In an attempt to foster the spread of rotating machinery diagnostics, the current trend in the field is to reach higher levels of automation of the condition monitoring systems. For this purpose, statistical tests for the presence of cyclostationarity have been proposed during the last years. The statistical thresholds proposed in the past for the identification of cyclostationary components have been obtained under the hypothesis of having a white noise signal when the component is healthy. This need, coupled with the non-white nature of the real signals implies the necessity of pre-whitening or filtering the signal in optimal narrow-bands, increasing the complexity of the algorithm and the risk of losing diagnostic information or introducing biases on the result. In this paper, the authors introduce an original analytical derivation of the statistical tests for cyclostationarity in the squared envelope spectrum, dropping the hypothesis of white noise from the beginning. The effect of first order and second order cyclostationary components on the distribution of the squared envelope spectrum will be quantified and the effectiveness of the newly proposed threshold verified, providing a sound theoretical basis and a practical starting point for efficient automated diagnostics of machine components such as rolling element bearings. The analytical results will be verified by means of numerical simulations and by using experimental vibration data of rolling element bearings.

Text mining for screening efficiency? Testing within a Cochrane public health review

Background The requirement for dual screening of titles and abstracts to select papers to examine in full text can create a huge workload, not least when the topic is complex and a broad search strategy is required, resulting in a large number of results. An automated system to reduce this burden, while still assuring high accuracy, has the potential to provide huge efficiency savings within the review process. Objectives To undertake a direct comparison of manual screening with a semi‐automated process (priority screening) using a machine classifier. The research is being carried out as part of the current update of a population‐level public health review. Methods Authors have hand selected studies for the review update, in duplicate, using the standard Cochrane Handbook methodology. A retrospective analysis, simulating a quasi‐‘active learning’ process (whereby a classifier is repeatedly trained based on ‘manually’ labelled data) will be completed, using different starting parameters. Tests will be carried out to see how far different training sets, and the size of the training set, affect the classification performance; i.e. what percentage of papers would need to be manually screened to locate 100% of those papers included as a result of the traditional manual method. Results From a search retrieval set of 9555 papers, authors excluded 9494 papers at title/abstract and 52 at full text, leaving 9 papers for inclusion in the review update. The ability of the machine classifier to reduce the percentage of papers that need to be manually screened to identify all the included studies, under different training conditions, will be reported. Conclusions The findings of this study will be presented along with an estimate of any efficiency gains for the author team if the screening process can be semi‐automated using text mining methodology, along with a discussion of the implications for text mining in screening papers within complex health reviews.

Measuring the traction profile on sportsfields: Equipment development and testing

Traction is recognised as an important component of the overall playability and safety of a sportsfield. It relates to the "grip", or footing, provided through an athlete's shoe when in contact with the surface, and is normally measured by the torque generated when a weighted studded disc apparatus is dropped onto the turf and twisted manually. This paper describes the development of an automated traction tester, which mechanises the dropping and twisting of the weighted studded disc. By standardising these operational stages, more repeatable and reliable results can be expected than from the original hand-operated design where positioning of the disc and speed of rotation are controlled manually and so can vary from one measurement to the next. As well as measuring the maximum torque reached during rotation of the studded disc, the automated traction tester generates a profile of torque showing changes over time and calculates the angle through which the studded disc moved before reaching maximum torque. These aspects are now covered by a utility patent (PAT/AU/2004270767). Use of the automated traction tester is illustrated by comparative data for a range of warm-season turfgrasses, by comparisons of traction under different surface conditions generated by wear on Cynodon dactylon cultivars, and by the effects of environment, management and playing patterns on traction across a multi-use sports stadium.

Automated estimation of fatigue crack length and closure/opening stress

An experimental technique is proposed for the estimation of crack length as well as crack closure/opening stress during fatigue crack growth. A specially designed, single cantilever, crack opening displacement gauge is used to monitor these variables during fatigue crack propagation testing. The technique was experimentally validated through electronfractography.

Automated feature engineering for HTTP tunnel detection

Generating discriminative input features is a key requirement for achieving highly accurate classifiers. The process of generating features from raw data is known as feature engineering and it can take significant manual effort. In this paper we propose automated feature engineering to derive a suite of additional features from a given set of basic features with the aim of both improving classifier accuracy through discriminative features, and to assist data scientists through automation. Our implementation is specific to HTTP computer network traffic. To measure the effectiveness of our proposal, we compare the performance of a supervised machine learning classifier built with automated feature engineering versus one using human-guided features. The classifier addresses a problem in computer network security, namely the detection of HTTP tunnels. We use Bro to process network traffic into base features and then apply automated feature engineering to calculate a larger set of derived features. The derived features are calculated without favour to any base feature and include entropy, length and N-grams for all string features, and counts and averages over time for all numeric features. Feature selection is then used to find the most relevant subset of these features. Testing showed that both classifiers achieved a detection rate above 99.93% at a false positive rate below 0.01%. For our datasets, we conclude that automated feature engineering can provide the advantages of increasing classifier development speed and reducing development technical difficulties through the removal of manual feature engineering. These are achieved while also maintaining classification accuracy.

Advanced transmission electron microscope triboprobe with automated closed-loop nanopositioning

Here the design and operation of a novel transmission electron microscope (TEM) triboprobe instrument with real-time vision control for advanced in situ electron microscopy is demonstrated. The NanoLAB triboprobe incorporates a new high stiffness coarse slider design for increased stability and positioning performance. This is linked with an advanced software control system which introduces both new and flexible in situ experimental functional testing modes, plus an automated vision control feedback system. This advancement in instrumentation design unlocks new possibilities of performing a range of new dynamical nanoscale materials tests, including novel friction and fatigue experiments inside the electron microscope.

Design and fabrication of an automated temperature programmed reaction system to evaluate 3-way catalysts Ce1-x-y(La/Y)(x)PtyO2-delta

A completely automated temperature-programmed reaction (TPR) system for carrying out gas-solid catalytic reactions under atmospheric flow conditions is fabricated to study CO and hydrocarbon oxidation, and NO reduction. The system consists of an all-stainless steel UHV system, quadrupole mass spectrometer SX200 (VG Scientific), a tubular furnace and micro-reactor, a temperature controller, a versatile gas handling system, and a data acquisition and analysis system. The performance of the system has been tested under standard experimental conditions for CO oxidation over well-characterized Ce1-x-y(La/Y)(y)O2-delta catalysts. Testing of 3-way catalysis with CO, NO and C2H2 to convert to CO2, N-2 and H2O is done with this catalyst which shows complete removal of pollutants below 325 degrees C. Fixed oxide-ion defects in Pt substituted Ce1-y(La/Y)(y)O2-y/2 show higher catalytic activity than Pt ion-substituted CeO2

Design and fabrication of an automated temperature programmed reaction system to evaluate 3-way catalysts Ce1-x-y(La/Y)(x)PtyO2-delta

A completely automated temperature-programmed reaction (TPR) system for carrying out gas-solid catalytic reactions under atmospheric flow conditions is fabricated to study CO and hydrocarbon oxidation, and NO reduction. The system consists of an all-stainless steel UHV system, quadrupole mass spectrometer SX200 (VG Scientific), a tubular furnace and micro-reactor, a temperature controller, a versatile gas handling system, and a data acquisition and analysis system. The performance of the system has been tested under standard experimental conditions for CO oxidation over well-characterized Ce1-x-y(La/Y)(y)O2-delta catalysts. Testing of 3-way catalysis with CO, NO and C2H2 to convert to CO2, N-2 and H2O is done with this catalyst which shows complete removal of pollutants below 325 degrees C. Fixed oxide-ion defects in Pt substituted Ce1-y(La/Y)(y)O2-y/2 show higher catalytic activity than Pt ion-substituted CeO2.

Increasing the design strength of glass – fractography and stress testing

Brittleness is the unintended, but inevitable consequence of producing a transparent ceramic for architectural applications such as the soda-lime glass. Its tensile strength is particularly sensitive to surface imperfections, such as that from natural weathering and malicious damage. Although a significant amount of testing of new glass has been carried out, there has been surprisingly little testing on weathered glass. Due to the variable nature of the causes of surface damage, the lack of data on weathered glass leads to a considerable degree of uncertainty in the long-term strength of exposed glass. This paper presents the results of recent tests on weathered annealed glass which has been exposed to natural weathering for more than 20 years. The tests include experimental investigations using the co-axial ring setup as well as optical and atomic force microscopy of the glass surfaces. The experimental data from these tests is subsequently used to extend existing fracture mechanics-based models to predict the strength of weathered glass. It is shown that using an automated approach based directly on finite element analysis results can give an increase in effective design strength in the order of 70 to 100% when compared to maximum stress methods. It is also shown that by combining microscopy and strength test results, it is possible to quantitatively characterise the damage on glass surfaces.

automated test program generation for an industrial optimizing compiler

Association for Computing Machinery, ACM; IEEE; IEEE Computer Society; SIGSOFT

Biologically Inspired Approaches to Automated Feature Extraction and Target Recognition

Ongoing research at Boston University has produced computational models of biological vision and learning that embody a growing corpus of scientific data and predictions. Vision models perform long-range grouping and figure/ground segmentation, and memory models create attentionally controlled recognition codes that intrinsically cornbine botton-up activation and top-down learned expectations. These two streams of research form the foundation of novel dynamically integrated systems for image understanding. Simulations using multispectral images illustrate road completion across occlusions in a cluttered scene and information fusion from incorrect labels that are simultaneously inconsistent and correct. The CNS Vision and Technology Labs (cns.bu.edulvisionlab and cns.bu.edu/techlab) are further integrating science and technology through analysis, testing, and development of cognitive and neural models for large-scale applications, complemented by software specification and code distribution.