It remains controversial whether patients with Stage II colorectal cancer would benefit from adjuvant chemotherapy after radical resection. The aim of this study was to establish two mathematical models to identify the suitable patients for adjuvant chemotherapy.The current study comprised of two steps. In the first step, 353 patients with Stage II colorectal cancer who underwent surgical procedures at the Third Affiliated Hospital of Sun Yat-sen University between June 2006 and December 2015 were entered and followed up for 6-120 months. Their clinical data were collected and enrolled into the database. We established two mathematical models by univariate and multivariate Cox regression analysis to identify the target patients; in the second step, 230 patients under the same standard between January 2012 and December 2016 were entered and followed up for 3-62 months to verify the two models' validation.In the first step, totally 340 surgical patients with Stage II colorectal cancer were finally enrolled in this study. Statistical analysis showed that tumor differentiation (TD) (P < 0.001), lymphovascular invasion (LVI) (P < 0.001), uncertain or positive margins (UPM) (P < 0.001), and fewer lymph nodes (LNs) (<12) retrieved (P < 0.001) were correlated with the overall survival (OS) and disease free survival (DFS). We obtained two models: (1) OS risk score = 1.116 × TD + 2.202 × LVI + 3.676 × UPM + 1.438 × LN - 0.493; (2) DFS risk score = 0.789 × TD + 2.074 × LVI + 3.183 × UPM + 1.329 × LN - 0.432. According to the models and cutoff points [(0.07, 1.33) and (-0.04, 1.30), respectively], patients can be divided into three groups: low-risk, moderate-risk, and high-risk. Moreover, the high-risk group patients could benefit from adjuvant chemotherapy. In the second step, totally 221 patients were finally used to verify the models' validation. The results proved that the models were accurate and feasible (P< 0.05).According to the predictive models, patients with Stage II colorectal cancer in the high-risk group are strongly recommended for adjuvant chemotherapy, thus facilitating the individualized and precise treatment.
We theoretically and numerically demonstrate that Fano-like resonance can induce a left-handed optical torque on a dipolar plasmonic core-shell nanoparticle in the interference optical field composed of two linearly polarized plane waves. It is shown that the optical torque on the dipolar plasmonic nanoparticle is significantly enhanced at the Fano-like resonance, and its direction is opposite to that of the angular momentum of the incident field, termed Fano-like resonance-induced left-handed optical torque. The extinction spectra exhibit that the Fano-like resonance stems from the coupling between a narrow electric quadrupole dark mode and a broad electric dipole bright mode. In addition, such Fano-like resonance-induced left-handed optical torque can flexibly be tailored by the particle morphology. To further trace the physical origin of the left-handed optical torque, we derive an analytical expression of optical torques up to electric quadrupole in generic monochromatic optical fields based on the multipole expansion theory. The results obtained from our analytical expression show that the left-handed optical torque comes completely from the electric quadrupole terms while other terms from the electric dipole make no contribution. Our results may open a new avenue for tailoring optical torques on plasmonic structures.
We demonstrate theoretically that the surface fluctuation can be used to launch the unidirectional electromagnetic edge mode for a Gaussian beam incident normal to the magnetic metamaterials (MMs) composed of an array of ferrite rods with the uppermost layer introduced position or size fluctuation in the coupling region. Such an edge mode is solely allowed to propagate in one direction due to the time-reversal symmetry breaking in MMs under the exertion of an external magnetic field, and it is substantially enhanced by the magnetic surface plasmon resonance. The nonreciprocal excitation of the edge states can also be understood by examining the scattering amplitudes of different partial waves, which indicate that the 1st order of the angular momentum channel plays a crucial role in realizing the nonreciprocity. The present research might be significant for the implementation of unidirectional absorption and the reexamination of bound states in the continuum in the context of MMs. In addition, the unique optical property can be exploited to design electromagnetic waveguide devices, such as one-way waveguide and wave bender, which are strongly robust against the obstacles placed in the channel of designed devices, facilitating to realize optical integrated circuits.
This paper considers the iterative learning control (ILC) problem for a class of uncertain linear distributed parameter systems with time delay. A P-type ILC scheme is presented for distributed parameter systems. Then, using a Lyapunov-like approach, we derive sufficient conditions for tracking error convergence in the sense of L 2 norm in terms of linear matrix inequalities based on rigorous analysis., which can also guarantee the monotonic convergence of the input error in some given norm. The results of numerical simulations are presented to illustrate the effectiveness of the proposed ILC approach.
The degradability characteristics of film with 4 kinds of methyl methacrylate coated urea amended with inhibitors were analyzed by FITR, which was purposed to supply theoretical basis for applying the FITR analysis method to film decomposition and methyl methacrylate coated urea fertilizers on farming. The result showed that the chemical component, molecule structure and material form of the membrane were not changed because of adding different inhibitors to urea. the main peaks of expressing film degradation process were brought by the -C-H of CH3 & CH2, -OH, C-O, C-C, C-O-C, C=O, C=C flexing vibrancy in asymmetry and symmetry in 3 479-3 195, 2 993--2 873, 1 741-1 564, 1 461-925 and 850-650 cm(-1). The peak value changed from smooth to tip, and from width to narrow caused by chemical structural transform of film The infrared spectrum of 4 kinds of fertilizers was not different remarkably before 60 days, and the film was slowly degraded. But degradation of the film was expedited after 60 days, it was most quickened at 120 day, and the decomposition rate of film was decreased at 310 day. The substantiality change of film in main molecule structure of 4 kinds of fertilizers didn't happen in 310 days. The main component of film materials was degraded most slowly in brown soil. The speed of film degradation wasn't heavily impacted by different inhibitors. The characteristic of film degradation may be monitored entirely by infrared spectrum. The degradation dynamic, chemical structure change, degradation speed difference of the film could be represented through infrared spectrum.
The responses of cortical neurons to a stimulus in a classical receptive field (CRF) can be modulated by stimulating the non-CRF (nCRF) of neurons in the primary visual cortex (V1). In the very early stages (at around 40 ms), a neuron in V1 exhibits strong responses to a small set of stimuli. Later, however (after 100 ms), the neurons in V1 become sensitive to the scene's global organization. As per these visual cortical mechanisms, a contour detection model based on the spatial summation properties is proposed. Unlike in previous studies, the responses of the nCRF to the higher visual cortex that results in the inhibition of the neuronal responses in the primary visual cortex by the feedback pathway are considered. In this model, the individual neurons in V1 receive global information from the higher visual cortex to participate in the inhibition process. Computationally, global Gabor energy features are involved, leading to the more coherent physiological characteristics of the nCRF. We conducted an experiment where we compared our model with those proposed by other researchers. Our model explains the role of the mutual inhibition of neurons in V1, together with an approach for object recognition in machine vision.
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