Vegetation NDVI Linked to Temperature and Precipitation in the Upper Catchments of Yellow River

Vegetation in the upper catchment of Yellow River is critical for the ecological stability of the whole watershed. The dominant vegetation cover types in this region are grassland and forest, which can strongly influence the eco-environmental status of the whole watershed. The normalized difference vegetation index (NDVI) for grassland and forest has been calculated and its daily correlation models were deduced by Moderate Resolution Imaging Spectroradiometer products on 12 dates in 2000, 2003, and 2006. The responses of the NDVI values with the inter-annual grassland and forest to three climatic indices (i.e., yearly precipitation and highest and lowest temperature) were analyzed showing that, except for the lowest temperature, the yearly precipitation and highest temperature had close correlations with the NDVI values of the two vegetation communities. The value of correlation coefficients ranged from 0.815 to 0.951 (p <0.01). Furthermore, the interactions of NDVI values of vegetation with the climatic indicators at monthly interval were analyzed. The NDVI of vegetation and three climatic indices had strong positive correlations (larger than 0.733, p <0.01). The monthly correlations also provided the threshold values for the three climatic indictors, to be used for simulating vegetation growth grassland under different climate features, which is essential for the assessment of the vegetation growth and for regional environmental management

Perturbative analysis of generally nonlocal spatial optical solitons

In analogy to a perturbed harmonic oscillator, we calculate the fundamental and some other higher order soliton solutions of the nonlocal nonlinear Schroedinger equation (NNLSE) in the second approximation in the generally nonlocal case. Comparing with numerical simulations we show that soliton solutions in the 2nd approximation can describe the generally nonlocal soliton states of the NNLSE more exactly than that in the zeroth approximation. We show that for the nonlocal case of an exponential-decay type nonlocal response the Gaussian-function-like soliton solutions can't describe the nonlocal soliton states exactly even in the strongly nonlocal case. The properties of such nonlocal solitons are investigated. In the strongly nonlocal limit, the soliton's power and phase constant are both in inverse proportion to the 4th power of its beam width for the nonlocal case of a Gaussian function type nonlocal response, and are both in inverse proportion to the 3th power of its beam width for the nonlocal case of an exponential-decay type nonlocal response.Comment: 13 pages, 16 figures, accepted by Phys. Rev.

Multi-term linear fractional nabla difference equations with constant coefficients

We shall consider a linear fractional nabla (backward) fractional difference equation of Riemann–Liouville type with constant coefficients. We apply a transform method to construct solutions. Sufficient conditions in terms of the coefficients are given so that the solutions are absolutely convergent. The method is known for two-term fractional difference equations; the method is new for fractional equations with three or more terms. As a corollary, we exhibit new summation representations of a discrete exponential function, at, t = 0; 1; : : :

A surface defect detection method of steel plate based on YOLOV3

At present, the steel plate surface defect detection technology based on machine vision and convolutional neural network (CNN) has achieved good results. However, these models are mostly two-stage methods, extracting features first and then classifying them, which is slow and inaccurate. Therefore, this paper proposes a single-stage surface defect detection method of steel plate based on yolov3, which can classify defects, determine the location of defects, and greatly improve the detection speed. It is of great significance to realize the automation of cold rolling production line. The experiment shows that the detection speed of this model reaches 62 fps and the accuracy reaches 73 %, which has a good prospect in industry

A surface defect detection method of steel plate based on YOLOV3

At present, the steel plate surface defect detection technology based on machine vision and convolutional neural network (CNN) has achieved good results. However, these models are mostly two-stage methods, extracting features first and then classifying them, which is slow and inaccurate. Therefore, this paper proposes a single-stage surface defect detection method of steel plate based on yolov3, which can classify defects, determine the location of defects, and greatly improve the detection speed. It is of great significance to realize the automation of cold rolling production line. The experiment shows that the detection speed of this model reaches 62 fps and the accuracy reaches 73 %, which has a good prospect in industry

Cooling a mechanical resonator via coupling to a tunable double quantum dot

We study the cooling of a mechanical resonator (MR) that is capacitively coupled to a double quantum dot (DQD). The MR is cooled by the dynamical backaction induced by the capacitive coupling between the DQD and the MR. The DQD is excited by a microwave field and afterwards a tunneling event results in the decay of the excited state of the DQD. An important advantage of this system is that both the energy level splitting and the decay rate of the DQD can be well tuned by varying the gate voltage. We find that the steady average occupancy, below unity, of the MR can be achieved by changing both the decay rate of the excited state and the detuning between the transition frequency of the DQD and the microwave frequency, in analogy to the laser sideband cooling of an atom or trapped ion in atomic physics. Our results show that the cooling of the MR to the ground state is experimentally implementable.Comment: 10 pages, 5 figure