Impact of perioperative infarcts after cardiac surgery

Background and Purpose: Brain injury after cardiac surgery is a serious concern for patients and their families. The purpose of this study was to use 3-T fluid attenuated inversion recovery MRI to characterize new and preexisting cerebral ischemic lesions in patients undergoing cardiac surgery and to test whether the accumulation of new ischemic lesions adversely affects cognition. Methods: Digital comparison of before and after fluid attenuated inversion recovery MRI images was performed for 77 cardiac surgery patients. The burden of preexisting versus new ischemic lesions was quantified and compared with the results of baseline and postoperative neuropsychological testing. Results: After surgery, new lesions were identified in 31% of patients, averaging 0.5 lesions per patient (67 mm3 [0.004%] of brain tissue). Patients with preexisting lesions were 10× more likely to receive new lesions after surgery than patients without preexisting lesions. Preexisting ischemic lesions were observed in 64% of patients, averaging 19.4 lesions (1542 mm3 [0.1%] of brain tissue). New lesions in the left hemisphere were significantly smaller and more numerous (29 lesions; median volume, 44 mm3; volume range, 5–404 mm3) than those on the right (10 lesions; median volume, 128 mm3; volume range, 13–1383 mm3), which is consistent with a cardioembolic source of particulate emboli. Overall, the incidence of postoperative cognitive decline was 46% and was independent of whether new lesions were present. Conclusions: New lesions after cardiac surgery added a small (≈4%) contribution to the burden of preexisting cerebrovascular disease and did not seem to affect cognitive function

Combined search for the quarks of a sequential fourth generation

Results are presented from a search for a fourth generation of quarks produced singly or in pairs in a data set corresponding to an integrated luminosity of 5 inverse femtobarns recorded by the CMS experiment at the LHC in 2011. A novel strategy has been developed for a combined search for quarks of the up and down type in decay channels with at least one isolated muon or electron. Limits on the mass of the fourth-generation quarks and the relevant Cabibbo-Kobayashi-Maskawa matrix elements are derived in the context of a simple extension of the standard model with a sequential fourth generation of fermions. The existence of mass-degenerate fourth-generation quarks with masses below 685 GeV is excluded at 95% confidence level for minimal off-diagonal mixing between the third- and the fourth-generation quarks. With a mass difference of 25 GeV between the quark masses, the obtained limit on the masses of the fourth-generation quarks shifts by about +/- 20 GeV. These results significantly reduce the allowed parameter space for a fourth generation of fermions.Comment: Replaced with published version. Added journal reference and DO

Measurements of branching fraction ratios and CP-asymmetries in suppressed B^- -> D(-> K^+ pi^-)K^- and B^- -> D(-> K^+ pi^-)pi^- decays

We report the first reconstruction in hadron collisions of the suppressed decays B^- -> D(-> K^+ pi^-)K^- and B^- -> D(-> K^+ pi^-)pi^-, sensitive to the CKM phase gamma, using data from 7 fb^-1 of integrated luminosity collected by the CDF II detector at the Tevatron collider. We reconstruct a signal for the B^- -> D(-> K^+ pi^-)K^- suppressed mode with a significance of 3.2 standard deviations, and measure the ratios of the suppressed to favored branching fractions R(K) = [22.0 \pm 8.6(stat)\pm 2.6(syst)]\times 10^-3, R^+(K) = [42.6\pm 13.7(stat)\pm 2.8(syst)]\times 10^-3, R^-(K)= [3.8\pm 10.3(stat)\pm 2.7(syst]\times 10^-3, as well as the direct CP-violating asymmetry A(K) = -0.82\pm 0.44(stat)\pm 0.09(syst) of this mode. Corresponding quantities for B^- -> D(-> K^+ pi^-)pi^- decay are also reported.Comment: 8 pages, 1 figure, accepted by Phys.Rev.D Rapid Communications for Publicatio

Maternal educational level and risk of gestational hypertension: the Generation R Study.

We examined whether maternal educational level as an indicator of socioeconomic status is associated with gestational hypertension. We also examined the extent to which the effect of education is mediated by maternal substance use (that is smoking, alcohol consumption and illegal drug use), pre-existing diabetes, anthropometrics (that is height and body mass index (BMI)) and blood pressure at enrolment. This was studied in 3262 Dutch pregnant women participating in the Generation R Study, a population-based cohort study. Level of maternal education was established by questionnaire at enrolment, and categorized into high, mid-high, mid-low and low. Diagnosis of gestational hypertension was retrieved from medical records using standard criteria. Odds ratios (OR) of gestational hypertension for educational levels were calculated, adjusted for potential confounders and additionally adjusted for potential mediators. Adjusted for age and gravidity, women with mid-low (OR: 1.52; 95% CI: 1.02, 2.27) and low education (OR: 1.30; 95% CI: 0.80, 2.12) had a higher risk of gestational hypertension than women with high education. Additional adjustment for substance use, pre-existing diabetes, anthropometrics and blood pressure at enrolment attenuated these ORs to 1.09 (95% CI: 0.70, 1.69) and 0.89 (95% CI: 0.50, 1.58), respectively. These attenuations were largely due to the effects of BMI and blood pressure at enrolment. Women with relatively low educational levels have a higher risk of gestational hypertension, which is largely due to higher BMI and blood pressure levels from early pregnancy. The higher risk of gestational hypertension in these women is probably caused by pre-existing hypertensive tendencies that manifested themselves during pregnancy

Objective Assessment of Binaural Benefit from Acoustical Treatment in Real Primary School Classrooms

Providing students with an adequate acoustic environment is crucial for ensuring speech intelligibility in primary school classrooms. Two main approaches to control acoustics in educational facilities consist of reducing background noise and late reverberation. Prediction models for speech intelligibility have been developed and implemented to evaluate the effects of these approaches. In this study, two versions of the Binaural Speech Intelligibility Model (BSIM) were used to predict speech intelligibility in realistic spatial configurations of speakers and listeners, considering binaural aspects. Both versions shared the same binaural processing and speech intelligibility backend processes but differed in the pre-processing of the speech signal. An Italian primary school classroom was characterized in terms of acoustics before (reverberation, T20 = 1.6 ± 0.1 s) and after (T20 = 0.6 ± 0.1 s) an acoustical treatment to compare BSIM predictions to well-established room acoustic measures. With shorter reverberation time, speech clarity and definition improved, as well as speech recognition thresholds (SRTs) (by up to ~6 dB), particularly when the noise source was close to the receiver and an energetic masker was present. Conversely, longer reverberation times resulted (i) in poorer SRTs (by ~11 dB on average) and (ii) in an almost non-existent spatial release from masking at an angle (SRM)

Tensor based multichannel reconstruction for breast tumours identification from DCE-MRIs

A new methodology based on tensor algebra that uses a higher order singular value decomposition to perform three-dimensional voxel reconstruction from a series of temporal images obtained using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is proposed. Principal component analysis (PCA) is used to robustly extract the spatial and temporal image features and simultaneously de-noise the datasets. Tumour segmentation on enhanced scaled (ES) images performed using a fuzzy C-means (FCM) cluster algorithm is compared with that achieved using the proposed tensorial framework. The proposed algorithm explores the correlations between spatial and temporal features in the tumours. The multi-channel reconstruction enables improved breast tumour identification through enhanced de-noising and improved intensity consistency. The reconstructed tumours have clear and continuous boundaries; furthermore the reconstruction shows better voxel clustering in tumour regions of interest. A more homogenous intensity distribution is also observed, enabling improved image contrast between tumours and background, especially in places where fatty tissue is imaged. The fidelity of reconstruction is further evaluated on the basis of five new qualitative metrics. Results confirm the superiority of the tensorial approach. The proposed reconstruction metrics should also find future applications in the assessment of other reconstruction algorithms

A rotorcraft in-flight ice detection framework using computational aeroacoustics and Bayesian neural networks

This work develops a novel ice detection framework specifically suitable for rotorcraft using computational aeroacoustics and Bayesian neural networks. In an offline phase of the work, the acoustic signature of glaze and rime ice shapes on an oscillating wing are computed. In addition, the aerodynamic performance indicators corresponding to the ice shapes are also monitored. These performance indicators include the lift, drag, and moment coefficients. A Bayesian neural network is subsequently trained using projected Stein variational gradient descent to create a mapping from the acoustic signature generated by the iced wings to predict their performance indicators along with quantified uncertainty that is highly important for time- and safety-critical decision-making scenarios. While the training is carried out fully offline, usage of the Bayesian neural network to make predictions can be conducted rapidly online allowing for an ice detection system that can be used in real time and in-flight

Dynamic extensions of batch systems with cloud resources

Compute clusters use Portable Batch Systems (PBS) to distribute workload among individual cluster machines. To extend standard batch systems to Cloud infrastructures, a new service monitors the number of queued jobs and keeps track of the price of available resources. This meta-scheduler dynamically adapts the number of Cloud worker nodes according to the requirement profile. Two different worker node topologies are presented and tested on the Amazon EC2 Cloud service

Measurement of top quark–antiquark pair production in association with a W or Z boson in pp collisions at √s=8 TeV

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