90 research outputs found
Amplification of light pulses with orbital angular momentum (OAM) in nitrogen ions lasing
Nitrogen ions pumped by intense femtosecond laser pulses give rise to optical
amplification in the ultraviolet range. Here, we demonstrated that a seed light
pulse carrying orbital angular momentum (OAM) can be significantly amplified in
nitrogen plasma excited by a Gaussian femtosecond laser pulse. With the
topological charge of +1 and -1, we observed an energy amplification of the
seed light pulse by two orders of magnitude, while the amplified pulse carries
the same OAM as the incident seed pulse. Moreover, we show that a spatial
misalignment of the plasma amplifier with the OAM seed beam leads to an
amplified emission of Gaussian mode without OAM, due to the special spatial
profile of the OAM seed pulse that presents a donut-shaped intensity
distribution. Utilizing this misalignment, we can implement an optical switch
that toggles the output signal between Gaussian mode and OAM mode. This work
not only certifies the phase transfer from the seed light to the amplified
signal, but also highlights the important role of spatial overlap of the
donut-shaped seed beam with the gain region of the nitrogen plasma for the
achievement of OAM beam amplification.Comment: 10 pages, 7 figure
Reliable Detection of Myocardial Ischemia Using Machine Learning Based on Temporal-Spatial Characteristics of Electrocardiogram and Vectorcardiogram
Background: Myocardial ischemia is a common early symptom of cardiovascular disease (CVD). Reliable detection of myocardial ischemia using computer-aided analysis of electrocardiograms (ECG) provides an important reference for early diagnosis of CVD. The vectorcardiogram (VCG) could improve the performance of ECG-based myocardial ischemia detection by affording temporal-spatial characteristics related to myocardial ischemia and capturing subtle changes in ST-T segment in continuous cardiac cycles. We aim to investigate if the combination of ECG and VCG could improve the performance of machine learning algorithms in automatic myocardial ischemia detection. Methods: The ST-T segments of 20-second, 12-lead ECGs, and VCGs were extracted from 377 patients with myocardial ischemia and 52 healthy controls. Then, sample entropy (SampEn, of 12 ECG leads and of three VCG leads), spatial heterogeneity index (SHI, of VCG) and temporal heterogeneity index (THI, of VCG) are calculated. Using a grid search, four SampEn and two features are selected as input signal features for ECG-only and VCG-only models based on support vector machine (SVM), respectively. Similarly, three features (S ( I ), THI, and SHI, where S ( I ) is the SampEn of lead I) are further selected for the ECG + VCG model. 5-fold cross validation was used to assess the performance of ECG-only, VCG-only, and ECG + VCG models. To fully evaluate the algorithmic generalization ability, the model with the best performance was selected and tested on a third independent dataset of 148 patients with myocardial ischemia and 52 healthy controls. Results: The ECG + VCG model with three features (S ( I ),THI, and SHI) yields better classifying results than ECG-only and VCG-only models with the average accuracy of 0.903, sensitivity of 0.903, specificity of 0.905, F1 score of 0.942, and AUC of 0.904, which shows better performance with fewer features compared with existing works. On the third independent dataset, the testing showed an AUC of 0.814. Conclusion: The SVM algorithm based on the ECG + VCG model could reliably detect myocardial ischemia, providing a potential tool to assist cardiologists in the early diagnosis of CVD in routine screening during primary care services
Progress on China nuclear data processing code system
China is developing the nuclear data processing code Ruler, which can be used for producing multi-group cross sections and related quantities from evaluated nuclear data in the ENDF format [1]. The Ruler includes modules for reconstructing cross sections in all energy range, generating Doppler-broadened cross sections for given temperature, producing effective self-shielded cross sections in unresolved energy range, calculating scattering cross sections in thermal energy range, generating group cross sections and matrices, preparing WIMS-D format data files for the reactor physics code WIMS-D [2]. Programming language of the Ruler is Fortran-90. The Ruler is tested for 32-bit computers with Windows-XP and Linux operating systems. The verification of Ruler has been performed by comparison with calculation results obtained by the NJOY99 [3] processing code. The validation of Ruler has been performed by using WIMSD5B code
Acceleration and execution of relational queries using general purpose graphics processing unit (GPGPU)
This thesis first maps
the relational computation onto Graphics Processing Units (GPU)s by designing a
series of tools and then
explores the different opportunities of reducing the limitation brought by the
memory hierarchy across the CPU and GPU system.
First, a complete end-to-end compiler and runtime infrastructure, Red Fox, is proposed. The
evaluation on the full set of
industry standard TPC-H queries on a single node GPU
shows on average Red Fox is 11.20x faster compared with a commercial database system on a state
of art CPU machine.
Second, a new compiler technique called kernel fusion is designed to fuse the code bodies of several
relational operators to reduce data movement. Third, a multi-predicate join algorithm is
designed for GPUs which can provide much better performance and be used with
more flexibility compared with kernel fusion.
Fourth, the GPU optimized multi-predicate join is integrated into a
multi-threaded CPU database runtime system that supports out-of-core
data set to solve real world problem.
This thesis presents key insights, lessons learned, measurements from the
implementations, and opportunities for further improvements.Ph.D
ThreadMarks: A Framework for Input-Aware Prediction of Parallel Application Behavior
Chip-multiprocessors (CMPs) are quickly becoming entrenched as the main-stream architectural platform in computer
systems. One of the critical challenges facing CMPs is designing applications to effectively leverage the computational
resources they provide. Modifying applications to effectively run on CMPs requires understanding the
bottlenecks in applications, which necessitates a detailed understanding of architectural features. Unfortunately,
identifying bottlenecks is complex and often requires enumerating a wide range of behaviors.
To assist in identifying bottlenecks, this paper presents a framework for developing analytical models based on
dynamic program behaviors. That is, given a program and set of training inputs, the framework will generate several
analytical models that accurately predict online program behaviors such as memory utilization and synchronization
overhead, while taking program input into consideration. These models can prove invaluable for online optimization
systems and input-specific analysis of program behavior. We demonstrate that this framework is practical and accurate
on a wide range of synthetic and real-world parallel applications over various workloads
A stress test on 235U(n, f) in adjustment with HCI and HMI benchmarks
To understand how compensation errors occur in a nuclear data adjustment mostly devoted to U-Pu fuelled fast critical experiments and with only limited information on U-235 data, a stress test on 235U(n,f) was suggested, using critical benchmarks sensitive to 235U(n,f) in 1∼ 10 keV region. The adjustment benchmark exercise with 20 integral data suggested by the NEA WPEC/SG33 was used as the reference, where practically only one experiment did give information on U-235 data. The keff of HCI4.1 and HCI6.2 experimental benchmarks were used as the 21st and 22nd integral data separately to perform stress tests. The adjusted integral values and cross sections based on 20, 21 and 22 integral data using the same nuclear data and covariance data sets were compared. The results confirm that compensation errors can be created by missing essential constraints
- …