Traveling wave phenomena in a nonlocal dispersal predator-prey system with the Beddington-DeAngelis functional response and harvesting

This paper is devoted to studying the existence and nonexistence of traveling wave solution for a nonlocal dispersal delayed predator-prey system with the Beddington-DeAngelis functional response and harvesting. By constructing the suitable upper-lower solutions and applying Schauder\u27s fixed point theorem, we show that there exists a positive constant c∗ such that the system possesses a traveling wave solution for any given c\u3ec∗. Moreover, the asymptotic behavior of traveling wave solution at infinity is obtained by the contracting rectangles method. The existence of traveling wave solution for c=c∗ is established by means of Corduneanu\u27s theorem. The nonexistence of traveling wave solution in the case of

Intergenerational Test Generation for Natural Language Processing Applications

The development of modern NLP applications often relies on various benchmark datasets containing plenty of manually labeled tests to evaluate performance. While constructing datasets often costs many resources, the performance on the held-out data may not properly reflect their capability in real-world application scenarios and thus cause tremendous misunderstanding and monetary loss. To alleviate this problem, in this paper, we propose an automated test generation method for detecting erroneous behaviors of various NLP applications. Our method is designed based on the sentence parsing process of classic linguistics, and thus it is capable of assembling basic grammatical elements and adjuncts into a grammatically correct test with proper oracle information. We implement this method into NLPLego, which is designed to fully exploit the potential of seed sentences to automate the test generation. NLPLego disassembles the seed sentence into the template and adjuncts and then generates new sentences by assembling context-appropriate adjuncts with the template in a specific order. Unlike the taskspecific methods, the tests generated by NLPLego have derivation relations and different degrees of variation, which makes constructing appropriate metamorphic relations easier. Thus, NLPLego is general, meaning it can meet the testing requirements of various NLP applications. To validate NLPLego, we experiment with three common NLP tasks, identifying failures in four state-of-art models. Given seed tests from SQuAD 2.0, SST, and QQP, NLPLego successfully detects 1,732, 5301, and 261,879 incorrect behaviors with around 95.7% precision in three tasks, respectively

Unveiling the nucleon tensor charge at Jefferson Lab: A study of the SoLID case

Future experiments at the Jefferson Lab 12 GeV upgrade, in particular, the Solenoidal Large Intensity Device (SoLID), aim at a very precise data set in the region where the partonic structure of the nucleon is dominated by the valence quarks. One of the main goals is to constrain the quark transversity distributions. We apply recent theoretical advances of the global QCD extraction of the transversity distributions to study the impact of future experimental data from the SoLID experiments. Especially, we develop a simple strategy based on the Hessian matrix analysis that allows one to estimate the uncertainties of the transversity quark distributions and their tensor charges extracted from SoLID data simulation. We find that the SoLID measurements with the proton and the effective neutron targets can improve the precision of the u- and d-quark transversity distributions up to one order of magnitude in the range 0.05 < x < 0.6.Comment: 11 pages, 3 figures, published on Physics Letters

Prognostic nomogram for bladder cancer with brain metastases: a National Cancer Database analysis.

BACKGROUND: This study aimed to establish and validate a nomogram for predicting brain metastasis in patients with bladder cancer (BCa) and assess various treatment modalities using a primary cohort comprising 234 patients with clinicopathologically-confirmed BCa from 2004 to 2015 in the National Cancer Database. METHODS: Machine learning method and Cox model were used for nomogram construction. For BCa patients with brain metastasis, surgery of the primary site, chemotherapy, radiation therapy, palliative care, brain confinement of metastatic sites, and the Charlson/Deyo Score were predictive features identified for building the nomogram. RESULTS: For the original 169 patients considered in the model, the areas under the receiver operating characteristic curve (AUC) were 0.823 (95% CI 0.758-0.889, P \u3c 0.001) and 0.854 (95% CI 0.785-0.924, P \u3c 0.001) for 0.5- and 1-year overall survival respectively. In the validation cohort, the nomogram displayed similar AUCs of 0.838 (95% CI 0.738-0.937, P \u3c 0.001) and 0.809 (95% CI 0.680-0.939, P \u3c 0.001), respectively. The high and low risk groups had median survivals of 1.91 and 5.09 months for the training cohort and 1.68 and 8.05 months for the validation set, respectively (both P \u3c 0.0001). CONCLUSIONS: Our prognostic nomogram provides a useful tool for overall survival prediction as well as assessing the risk and optimal treatment for BCa patients with brain metastasis

Power Allocation Strategies for Secure Spatial Modulation

In this paper, power allocation (PA) strategies in secure spatial modulation networks, are investigated under the total power constraint. Considering that there is no closed-form expression for secrecy rate (SR), an approximate closed-form expression of SR is derived as an efficient metric to optimize PA factor, which can greatly reduce the computation complexity. Based on this expression, a convex optimization (CO) method of maximizing SR (Max-SR) is proposed accordingly. Furthermore, a method of maximizing the product of signal-to-leakage and noise ratio (SLNR) and artificial noise-to-leakage and noise ratio (Max-P-SAN) is proposed to provide an analytic solution for PA factor with extremely low complexity. Simulation results demonstrate that the SR performance of the proposed CO method is close to that of the optimal PA strategy with exhaustive search, and is better than that of Max-P-SAN in the high signal-to-noise ratio (SNR) region. However, in the low and medium SNR regions, the proposed Max-P-SAN slightly outperforms the proposed CO scheme in terms of SR performance

Effects of Excitation Angle on Air-Puff-Stimulated Surface Acoustic Wave-Based Optical Coherence Elastography (SAW-OCE)

Increased stiffness of tissues has been recognised as a diagnostic feature of pathologies. Tissue stiffness characterisation usually involves the detection of tissue response from mechanical stimulation. Air-puff optical coherence elastography (OCE) can generate impulse surface acoustic waves (SAWs) on tissue surface without contact and evaluate the mechanical properties of tissue. This study endeavours to explore the optimal excitation angle for air-puff OCE, a parameter that lacks standardisation at present, by investigating the relationship between the frequency bandwidth and peak-to-peak signal-to-noise ratio (SNR) of SAWs for different excitation angles (relative to the normal surface) of air-puff on the sample, from 5° to 85°, with an interval of 5° applied on the phantom. Due to the unevenness of human hands, 20°, 45° and 70° angles were employed for human skin (10 healthy adults). The results show that a smaller excitation angle could produce higher wave frequency bandwidth; a 5° angle generated an SAW with 1747 Hz frequency bandwidth, while an 85° angle produced an SAW with 1205 Hz. Significant differences were not shown in peak-to-peak SNR comparison between 5° and 65° on the phantom, but between 65° and 85° at the excitation position, a reduction of 48.6% was observed. Furthermore, the group velocity of the SAWs was used to evaluate the bulk Young’s modulus of the human tissue. The outcomes could provide essential guidance for air-puff-based elastography studies in clinical applications and future tissue research.<br/