基于双创教育背景下高等数学教育创新研究

伴随科技的全面进步,人们对创新创业方面的重视度有了显著提升,特别是双创教育,普遍学校都在这一方面增加了成本投入,并取得了较好的成绩。为此,相关人员就需要针对早期双创教育模式的不足予以深入探究,提出一些针对性处理方案,进而给学生们提供更为优质的服务内容。本篇文章主要描述了高等数学教学的现状,探讨了基于双创教育背景加强高等数学教学创新的重要性,并对于创新的方法发表一些个人的观点和看法。

Locating method of fire source for spontaneous combustion of sulfide ores

in order to achieve a more efficient way to accurately detect the position of the fire source of spontaneous combustion underground mine, a simple fire source locating method, based on infrared scanning system which can determine the point where the highest temperature on the surface of igniting ores occurs, was proposed. First, the differential equations that describe heat flow in ore body were presented and the relationship between the surface temperature distribution and the depth and intensity of inner fire source was established with a relatively simple heat transfer model. With the solution of equation, the expression of the relationship between the surface temperature distribution and the inner fire source was deduced and the mathematical-physical model of heat transfer process was set up. Then, with the model, visualization of fire source on the basis of MATLAB simulation platform was realized. The results show that： 1） within 10 m, when the detecting depth is less than 2 m, the temperature perturbation on ores surface can change rapidly, and then slowly; after 4 m, in contrast, it changes very little, and is even close to zero at 10 m; 2） When it is close to self-ignition duration and the detective depths are 2, 5 and 10 m, respectively, the maximum temperature differences are correspondingly 0.5, 0.04 and 0.005 ℃ in the scope of 1 m×1 m; under the same condition, the maximum temperature differences are 1.391, 0.136 and 0.018 ℃, respectively, in the scope of 2 m×2 m. Therefore, this system can be used to measure the temperature differences on the surface of ore body and determine the highest temperature point directly. Also, it is possible to determine the depth of fire source and its intensity by locating method of fire source indirectly.

Big Data for Precision Medicine

This article focuses on the potential impact of big data analysis to improve health, prevent and detect disease at an earlier stage, and personalize interventions. The role that big data analytics may have in interrogating the patient electronic health record toward improved clinical decision support is discussed. Weexamine developments in pharmacogenetics that have increased our appreciation of the reasons why patients respond differently to chemotherapy. We also assess the expansion of online health communications and the way in which this data may be capitalized on in order to detect public health threats and control or contain epidemics. Finally, we describe how a new generation of wearable and implantable body sensors may improve wellbeing, streamline management of chronic diseases, and improve the quality of surgical implants.

ADS-B Anomaly Data Detection Model Based on Deep Learning and Difference of Gaussian Approach

Due to the influence of terrain structure,meteorological conditions and various factors,there are anomalous data in automatic dependent surveillance-broadcast(ADS-B)message.The ADS-B equipment can be used for positioning of general aviation aircraft.Aim to acquire the accurate position information of aircraft and detect anomaly data,the ADS-B anomaly data detection model based on deep learning and difference of Gaussian(DoG)approach is proposed.First,according to the characteristic of ADS-B data,the ADS-B position data are transformed into the coordinate system.And the origin of the coordinate system is set up as the take-off point.Then,based on the kinematic principle,the ADS-B anomaly data can be removed.Moreover,the details of the ADS-B position data can be got by the DoG approach.Finally,the long short-term memory(LSTM)neural network is used to optimize the recurrent neural network(RNN)with severe gradient reduction for processing ADS-B data.The position data of ADS-B are reconstructed by the sequence to sequence(seq2seq)model which is composed of LSTM neural network,and the reconstruction error is used to detect the anomalous data.Based on the real flight data of general aviation aircraft,the simulation results show that the anomaly data can be detected effectively by the proposed method of reconstructing ADS-B data with the seq2seq model,and its running time is reduced.Compared with the RNN,the accuracy of anomaly detection is increased by 2.7%.The performance of the proposed model is better than that of the traditional anomaly detection models.

Morphology of living cells cultured on nanowire arrays with varying nanowire densities and diameters

Vertical nanowire arrays are increasingly investigated for their applications in steering cell behavior. The geometry of the array is an important parameter, which influences the morphology and adhesion of cells. Here, we investigate the effects of array geometry on the morphology of MCF7 cancer cells and MCF10A normal-like epithelial cells. Different gallium phosphide nanowire array-geometries were produced by varying the nanowire density and diameter. Our results show that the cell size is smaller on nanowires compared to flat gallium phosphide. The cell area decreases with increasing the nanowire density on the substrate. We observed an effect of the nanowire diameter on MCF10A cells, with a decreased cell area on 40 nm diameter nanowires, compared to 60 and 80 nm diameter nanowires in high-density arrays. The focal adhesion morphology depends on the extent to which cells are contacting the substrate. For low nanowire densities and diameters, ceils are lying on the substrate and we observed large focal adhesions at the cell edges. In contrast, for high nanowire densities and diameters, cells are lying on top of the nanowires and we observed point-like focal adhesions distributed over the whole cell. Our results constitute a step towards the ability to fine-tune cell behavior on nanowire arrays.

Thermal Analysis of Underground Power Cable System

The paper presents the application of Finite Element Method in thermal analysis of underground power cable system. The computations were performed for power cables buried in-line in the ground at a depth of 2 meters. The developed mathematical model allows determining the two-dimensional temperature distribution in the soil, thermal backfill and power cables. The simulations studied the effect of soil and cable backfill thermal conductivity on the maximum temperature of the cable conductor. Also, the effect of cable diameter on the temperature of cable core was studied. Numerical analyses were performed based on a program written in MATLAB.

What can we learn from the tension between PLANCK and BICEP2 data?

Recently BICEP2 collaboration has announced the detection of the primordial gravitational waves at high confidence level. In light of the results of B-modes power spectrum from BICEP2 and using the based ACDM, a constraint on the tensor-to-scalar ratio r = 0.20-0.05＋0.07 （68% C.L.） can be obtained, however, this result is in apparent tension with the limit on standard inflation models from the recent PLANCK measurement, r 〈 0.11 （95% C.L.）. Herein we review the recent progress on the cosmological studies after BICEP2 and discuss on different ways of reconciling the tension between PLANCK and BICEP2 data. We will discuss possible modifications on the standard cosmological model, such as including the running of scalar spectral index or other cosmological parameters correlated with inflationary cosmological parameters, or tilting the primordial power spectrum at large scales by introducing a cut off which can be predicted by bouncing cosmology. We will also comment on another possibility of generating extra B-modes of CMB polarization, namely by a non-zero polarization rotation angle during its transferring from the last scattering surface.

Lattice instability of V_2AlC at high pressure

We investigate the elastic and thermodynamic properties of nanolaminate VzA1C by using the ab initio pseudopotential total energy method. The axial compressibility shows that the c axis is always stiffer than a axis. The elastic constants revealed the structural instability at about 500 and 732 GPa. Furthermore, elastic constants C44 reached its maximum at about 550 GPa, dif- fering with the other four C^1, G2, C13 and 6＂33 constants. The Poisson＇s ratio investigations demonstrated that a higher ionic or weaker covalent contribution in intra-atomic bonding and the degree of ionicity increases with pressure. The G/B and B]C44 investigations revealed that VzAIC is brittle and the brittleness decreases with pressure. Also, we found that V2A1C is elastic anisotropic materials and the degree of anisotropy rapidly rises with pressure. Study on Debye temperature and Grtineisen pa- rameter observed weak temperature and strong pressure responses, whereas the sensitive dependence in the thermal expansion coefficient and Helmholtz free energy are clearly seen.