Variation of Main Phenophases in Phenological Calendar in East China and Their Response to Climate Change

Based on the phenological data from China Phenological Observation Network, we compiled the phenological calendars of 3 phenological observation stations (Shanghai, Nanjing, and Hefei) in East China for 1987–1996 and 2003–2012 according to the sequences of mean phenophases. We calculated the correlated coefficient and the root mean square error (RMSE) between phenophases and the beginning of meteorological seasons to determine the beginning date of phenological season. By comparing new phenological calendars with the old ones, we discussed the variation of phenophases and their responses to temperature. The conclusions are as follows. (1) The beginning dates of spring and summer advanced, while those of autumn and winter delayed. Thus, summers got longer and winters got shorter. (2) The beginning time of the four phenological seasons was advancing during 1987–1996, while it was delaying during 2003–2012. (3) Most spring and summer phenophases occur earlier and most autumn and winter phenophases occur later in 2003–2012 than in 1987–1996. (4) The beginning time of phenological seasons was significantly correlated with temperature. The phenological sensitivities to temperature ranged from −6.49 to −6.55 days/°C in spring, −3.65 to −5.02 days/°C in summer, 8.13 to 10.27 days/°C in autumn, and 4.76 to 10.00 days/°C in winter

The Gap between Intelligence and Mind

The feeling (quale) brings the "Hard Problem" to philosophy of mind. Does the subjective feeling have a non-ignorable impact on Intelligence? If so, can the feeling be realized in Artificial Intelligence (AI)? To discuss the problems, we have to figure out what the feeling means, by giving a clear definition. In this paper, we primarily give some mainstream perspectives on the topic of the mind, especially the topic of the feeling (or qualia, subjective experience, etc.). Then, a definition of the feeling is proposed through a thought experiment, the "semi-transparent room". The feeling, roughly to say, is defined as "a tendency of changing input representations by representing its inner state". Also, a formalized definition is given. The definition does not help to verify "having the feeling", but it helps to provide evidence. Based on the definition, we think these are the hard problems of intelligence — whether the "innate" feeling plays an important role in Intelligence, whether the difference between the "simulated" feeling and the "innate" feeling will have a significant influence on Artificial General Intelligence (AGI), and, if so, where the "innate" feeling comes from and how to make an artificial agent possess it

Extremely large magnetoresistance in topologically trivial semimetal α\alpha-WP2_2

Extremely large magnetoresistance (XMR) was recently discovered in many non-magnetic materials, while its underlying mechanism remains poorly understood due to the complex electronic structure of these materials. Here, we report an investigation of the $\alpha$-phase WP$_2$, a topologically trivial semimetal with monoclinic crystal structure (C2/m), which contrasts to the recently discovered robust type-II Weyl semimetal phase in $\beta$-WP$_2$. We found that $\alpha$-WP$_2$ exhibits almost all the characteristics of XMR materials: the near-quadratic field dependence of MR, a field-induced up-turn in resistivity following by a plateau at low temperature, which can be understood by the compensation effect, and high mobility of carriers confirmed by our Hall effect measurements. It was also found that the normalized MRs under different magnetic fields has the same temperature dependence in $\alpha$-WP$_2$, the Kohler scaling law can describe the MR data in a wide temperature range, and there is no obvious change in the anisotropic parameter $\gamma$ value with temperature. The resistance polar diagram has a peanut shape when field is rotated in $\textit{ac}$ plane, which can be understood by the anisotropy of Fermi surface. These results indicate that both field-induced-gap and temperature-induced Lifshitz transition are not the origin of up-turn in resistivity in the $\alpha$-WP$_2$ semimetal. Our findings establish $\alpha$-WP$_2$ as a new reference material for exploring the XMR phenomena.Comment: 18 pages, 12 figure

Intrinsic and tunable quantum anomalous Hall effect and magnetic topological phases in XYBi2Te5

By first-principles calculations, we study the magnetic and topological properties of XYBi2Te5-family (X, Y = Mn, Ni, V, Eu) compounds. The strongly coupled double magnetic atom-layers can significantly enhance the magnetic ordering temperature while keeping the topologically nontrivial properties. Particularly, NiVBi2Te5 is found to be a magnetic Weyl semimetal in bulk and a Chern insulator in thin film with both the Curie temperature (~150 K) and full gap well above 77 K. Ni2Bi2Te5, MnNiBi2Te5, NiVBi2Te5 and NiEuBi2Te5 exhibits intrinsic dynamic axion state. Among them, MnNiBi2Te5 has a Neel temperature over 200 K and Ni2Bi2Te5 even demonstrates antiferromagnetic order above room temperature. These results indicate an approach to realize high temperature quantum anomalous Hall effect and other topological quantum effects for practical applications

Based on the phenological data from China Phenological Observation Network, we compiled the phenological calendars of 3 phenological observation stations

according to the sequences of mean phenophases. We calculated the correlated coefficient and the root mean square error (RMSE) between phenophases and the beginning of meteorological seasons to determine the beginning date of phenological season. By comparing new phenological calendars with the old ones, we discussed the variation of phenophases and their responses to temperature. The conclusions are as follows

Unusual Fermi Surface Sheet-Dependent Band Splitting in Sr2RuO4 Revealed by High Resolution Angle-Resolved Photoemission

High resolution angle-resolved photoemission measurements have been carried out on Sr2RuO4. We observe clearly two sets of Fermi surface sheets near the (\pi,0)-(0,\pi) line which are most likely attributed to the surface and bulk Fermi surface splitting of the \beta band. This is in strong contrast to the nearly null surface and bulk Fermi surface splitting of the \alpha band although both have identical orbital components. Extensive band structure calculations are performed by considering various scenarios, including structural distortion, spin-orbit coupling and surface ferromagnetism. However, none of them can explain such a qualitative difference of the surface and bulk Fermi surface splitting between the \alpha and \beta sheets. This unusual behavior points to an unknown order on the surface of Sr2RuO4 that remains to be uncovered. Its revelation will be important for studying and utilizing novel quantum phenomena associated with the surface of Sr2RuO4 as a result of its being a possible p-wave chiral superconductor and a topological superconductor.Comment: 13 pages, 4 figure

Self-healing law of mining fractured rock mass in Shendong coalfield

The objective phenomenon of seepage reduction and self-healing is easy to occur in the mining fractured rock mass after long-term evolution process of coal seam after mining. In survey of this phenomenon, taking the No. 12401 work face of Bulianta Coal Mine and the No. 52306 work face of Daliuta Coal Mine in Shendong as typical test areas, the engineering exploration and theoretical research on the self-healing law in different areas of overburden were carried out. The evolution law of long-term self-healing process of overburden after mining was revealed. The results show that the fractured overburden of the two coal mines had achieved good self-healing effects 15 years and 7.3 years after mining, respectively. The areas with water conduction within the original water-conducting fractured zone have been significantly reduced. Although the caved zone still conducts water, the height has also been reduced. By taking the ratio of the vertical length of the self-healing section in overburden from the original water diversion to the water isolation to the height of the water-conducting fractured zone as the self-healing recovery rate for statistics, it is obtained that the self-healing recovery rate of No. 12401 work face in the overburden near the mining boundary and in the middle of the dip has reached 59.5% and 53.5% respectively, and the self-healing recovery rate of 52306 work face in the corresponding area is 25.8% and 47.5% respectively. Due to that No. 12401 work face has mined for a longer time and has a larger coal seam burial depth, its self-healing effect of fractured overburden is obviously better. Affected by the occurrence difference of different strata in the vertical direction of the overburden and the initial damasge degree in different areas in the horizontal direction, the distribution of the self-healing area is often discrete and discontinuous, in which the interval of the unrepaired area generally corresponds to the position of the key stratum or thick and hard rock layer, and the shorter the post mining life and the closer to the mining boundary, the more significant the dispersion. The self-healing effect of mining fractured rock mass is actually a process of permeability reduction and evolution under the comprehensive influence of multiple factors. For the mining conditions in Shendong coalfield, the residual settlement caused by stress compaction plays a leading role in the initial process within 1.5 to 2 years after coal mining, which is relatively significant in the overburden in the middle of the mining area. Then, the self-healing process has been dominated by the water-rock or water-gas-rock interactions in goaf. That is, the filling and sealing effect of the derivatives produced in the relevant process on the fractures and the roughness reduction of the fracture surface induced by hydraulic erosion directly affect the self-healing results. Therefore, whether there is long-term water seepage in the overburden after mining determines the difficulty of self-healing of fractured rock mass. Water conducting fractures in the overburden of most mines in Shendong are generally directly connected to the Quaternary loose layer or surface, and in recent years, there is abundant rainfall, which provides superior conditions for the generation of water-rock or water-gas-rock interactions and the promotion of self-healing effect

Evaluation of petrophysical classification of strongly heterogeneous reservoirs based on the MRGC algorithm

The target formation in the study area of the Pearl River Mouth Basin is characterized by complex lithology and thin interbedded layers, with a large pore-permeability distribution range and strongly heterogeneous characteristics, which makes the reservoir pore structure and production capacity significantly different and brings research difficulties for reservoir logging evaluation and desert identification. The conventional reservoir classification method is mainly based on physical research, which requires developing extremely accurate formulas for calculating porosity and permeability; the calculation accuracy of pore permeability of low-porosity and low-permeability reservoirs is difficult to guarantee; and the conventional logging data cannot be comprehensively applied in reservoir classification. In this paper, taking Zhujiang and Zhuhai Formation reservoirs in the Huizhou M oilfield as an example, we integrated core analysis data such as core cast thin section, pore permeability data, rock electrical parameters, grain size, and relative permeability curves and combined with petrophysical parameters and pore structure characteristics to classify the reservoirs. The artificial neural network is used to predict the resistivity of saturated pure water (R0) to remove the influence of oil and gas on reservoir resistivity. The natural gamma ray (GR) “fluctuation” is used to calculate the variance root of variation (GS) to reflect the lithological variability and sedimentary heterogeneity of the reservoir, and then the conventional logging preferences, R0 and Gs (based on GR), are classified based on the automatic clustering MRGC algorithm to classify the logging facies. To classify the petrophysical phase reservoirs under the constraint of pore structure classification, we proposed a petrophysical classification logging model based on the natural gamma curve “fluctuation” intensity for strongly heterogeneous reservoirs. The learning model is extended to the whole area for training and prediction of desert identification, and the prediction results of the model are in good agreement with the actual results, which is important for determining favorable reservoirs in the area and the adjustment of oilfield development measures