3,153 research outputs found

    Synthesis of Boron-Containing Primary Amines

    Get PDF
    [[abstract]]In this study, boron-containing primary amines were synthesized for use as building blocks in the study of peptoids. In the first step, Gabriel synthesis conditions were modified to enable the construction of seven different aminomethylphenyl boronate esters in good to excellent yields. These compounds were further utilized to build peptoid analogs via an Ugi four-component reaction (Ugi-4CR) under microwave irradiation. The prepared Ugi-4CR boronate esters were then successfully converted to the corresponding boronic acids. Finally, the peptoid structures were successfully modified by cross-coupling to aryl/heteroaryl chlorides via a palladium-mediated Suzuki coupling reaction to yield the corresponding derivatives in moderate to good yields.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]紙

    Meshfree Model for Wave-Seabed Interactions Around Offshore Pipelines

    Get PDF
    The evaluation of the wave-induced seabed instability around a submarine pipeline is particularly important for coastal engineers involved in the design of pipelines protection. Unlike previous studies, a meshfree model is developed to investigate the wave-induced soil response in the vicinity of a submarine pipeline. In the present model, Reynolds-Averaged Navier-Stokes (RANS) equations are employed to simulate the wave loading, while Biot&rsquo s consolidation equations are adopted to investigate the wave-induced soil response. Momentary liquefaction around an offshore pipeline in a trench is examined. Validation of the present seabed model was conducted by comparing with the analytical solution, experimental data, and numerical models available in the literature, which demonstrates the capacity of the present model. Based on the newly proposed model, a parametric study is carried out to investigate the influence of soil properties and wave characteristics for the soil response around the pipeline. The numerical results conclude that the liquefaction depth at the bottom of the pipeline increases with increasing water period (T) and wave height (H), but decreases as backfilled depth ( H b ), degree of saturation ( S r ) and soil permeability (K) increase. Document type: Articl

    Frequency tracking by method of least squares combined with channel estimation for OFDM over mobile wireless channels

    Get PDF
    [[abstract]]To track frequency offset and time-varying channel in orthogonal frequency division multiplexing (OFDM) systems over mobile wireless channels, a common technique is, based on one OFDM training block sample, to apply the maximum-likelihood (ML) algorithm to perform joint frequency tracking and channel estimation employing some adaptive iteration processes. The major drawback of such joint estimation techniques is the local extrema problem arising from the highly nonlinear nature of the log-likelihood function. This makes the joint estimation process very difficult and complicated, and many a time the results are not very satisfactory if the algorithm is not well designed. In this study, rather than using the ML algorithm, we shall apply the method of least squares (LS) for frequency tracking utilizing repeated OFDM training blocks. As will be seen, by using such an LS approach, the frequency offset estimation requires no channel knowledge. The channel state can be estimated separately after the LS frequency offset correction. This not only circumvents the local extrema complication, but also obviates the need for the lengthy adaptive iteration process of joint estimation thus greatly simplifies the entire estimation process. Most importantly, our technique can achieve excellent estimation performance as compared to the usual ML algorithms.[[incitationindex]]SCI[[booktype]]紙

    Effects of manual lymphatic drainage on breast cancer-related lymphedema: a systematic review and meta-analysis of randomized controlled trials

    Get PDF
    BACKGROUND: Lymphedema is a common complication of axillary dissection for breast cancer. We investigated whether manual lymphatic drainage (MLD) could prevent or manage limb edema in women after breast-cancer surgery. METHODS: We performed a systematic review and meta-analysis of published randomized controlled trials (RCTs) to evaluate the effectiveness of MLD in the prevention and treatment of breast-cancer-related lymphedema. The PubMed, EMBASE, CINAHL, Physiotherapy Evidence Database (PEDro), SCOPUS, and Cochrane Central Register of Controlled Trials electronic databases were searched for articles on MLD published before December 2012, with no language restrictions. The primary outcome for prevention was the incidence of postoperative lymphedema. The outcome for management of lymphedema was a reduction in edema volume. RESULTS: In total, 10 RCTs with 566 patients were identified. Two studies evaluating the preventive outcome of MLD found no significant difference in the incidence of lymphedema between the MLD and standard treatment groups, with a risk ratio of 0.63 and a 95% confidence interval (CI) of 0.14 to 2.82. Seven studies assessed the reduction in arm volume, and found no significant difference between the MLD and standard treatment groups, with a weighted mean difference of 75.12 (95% CI, −9.34 to 159.58). CONCLUSIONS: The current evidence from RCTs does not support the use of MLD in preventing or treating lymphedema. However, clinical and statistical inconsistencies between the various studies confounded our evaluation of the effect of MLD on breast-cancer-related lymphedema

    KCNN2 polymorphisms and cardiac tachyarrhythmias

    Get PDF
    Potassium calcium-activated channel subfamily N member 2 (KCNN2) encodes an integral membrane protein that forms small-conductance calcium-activated potassium (SK) channels. Recent studies in animal models show that SK channels are important in atrial and ventricular repolarization and arrhythmogenesis. However, the importance of SK channels in human arrhythmia remains unclear. The purpose of the present study was to test the association between genetic polymorphism of the SK2 channel and the occurrence of cardiac tachyarrhythmias in humans. We enrolled 327 Han Chinese, including 72 with clinically significant ventricular tachyarrhythmias (VTa) who had a history of aborted sudden cardiac death (SCD) or unexplained syncope, 98 with a history of atrial fibrillation (AF), and 144 normal controls. We genotyped 12 representative tag single nucleotide polymorphisms (SNPs) across a 141-kb genetic region containing the KCNN2 gene; these captured the full haplotype information. The rs13184658 and rs10076582 variants of KCNN2 were associated with VTa in both the additive and dominant models (odds ratio [OR] 2.89, 95% confidence interval [CI] = 1.505-5.545, P = 0.001; and OR 2.55, 95% CI = 1.428-4.566, P = 0.002, respectively). After adjustment for potential risk factors, the association remained significant. The population attributable risks of these 2 variants of VTa were 17.3% and 10.6%, respectively. One variant (rs13184658) showed weak but significant association with AF in a dominant model (OR 1.91, CI = 1.025-3.570], P = 0.042). There was a significant association between the KCNN2 variants and clinically significant VTa. These findings suggest an association between KCNN2 and VTa; it also appears that KCNN2 variants may be adjunctive markers for risk stratification in patients susceptible to SCD

    Aorta Fluorescence Imaging by Using Confocal Microscopy

    Get PDF
    The activated leukocyte attacked the vascular endothelium and the associated increase in VEcadherin number was observed in experiments. The confocal microscopic system with a prism-based wavelength filter was used for multiwavelength fluorescence measurement. Multiwavelength fluorescence imaging based on the VEcadherin within the aorta segment of a rat was achieved. The confocal microscopic system capable of fluorescence detection of cardiovascular tissue is a useful tool for measuring the biological properties in clinical applications

    Iterative joint frequency offset and channel estimation for OFDM systems using first and second order approximation algorithms

    Get PDF
    [[abstract]]To implement an algorithm for joint estimation of carrier frequency offset (CFO) and channel impulse response (CIR) in orthogonal frequency division multiplexing (OFDM) systems, the maximum-likelihood criterion is commonly adopted. A major difficulty arises from the highly nonlinear nature of the log-likelihood function which renders local extrema or multiple solutions for the CFO and CIR estimators. Use of an approximation method coupled with an adaptive iteration algorithm has been a popular approach to ease problem solving. The approximation used in those existing methods is usually of the first order level. Here, in addition to a new first order approximation method, we also propose a second order approximation method. Further, for the part of the adaptive iteration algorithm, we adopt a new technique which will enable performance improvement. Our first order approximation method is found to outperform the existing ones in terms of estimation accuracies, tracking range, computation complexity, and convergence speed. As expected, our second order approximation method provides an even further improvement at the expense of higher computation complication.[[notice]]補正完畢[[journaltype]]國外[[incitationindex]]SCI[[booktype]]紙本[[booktype]]電子版[[countrycodes]]DE

    On the Efficiency of Integrating Self-supervised Learning and Meta-learning for User-defined Few-shot Keyword Spotting

    Full text link
    User-defined keyword spotting is a task to detect new spoken terms defined by users. This can be viewed as a few-shot learning problem since it is unreasonable for users to define their desired keywords by providing many examples. To solve this problem, previous works try to incorporate self-supervised learning models or apply meta-learning algorithms. But it is unclear whether self-supervised learning and meta-learning are complementary and which combination of the two types of approaches is most effective for few-shot keyword discovery. In this work, we systematically study these questions by utilizing various self-supervised learning models and combining them with a wide variety of meta-learning algorithms. Our result shows that HuBERT combined with Matching network achieves the best result and is robust to the changes of few-shot examples.Comment: Submitted to Interspeech 202
    corecore