Orientation and Decision-Making for Soccer Based on Sports Analytics and AI:A Systematic Review

Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professional sports analytics realm but also the academic AI research community. AI brings gamechanging approaches for soccer analytics where soccer has been a typical benchmark for AI research. The combination has been an emerging topic. In this paper, soccer match analytics are taken as a complete observation-orientation-decision-action(OODA) loop.In addition, as in AI frameworks such as that for reinforcement learning, interacting with a virtual environment enables an evolving model. Therefore, both soccer analytics in the real world and virtual domains are discussed. With the intersection of the OODA loop and the real-virtual domains, available soccer data, including event and tracking data, and diverse orientation and decisionmaking models for both real-world and virtual soccer matches are comprehensively reviewed. Finally, some promising directions in this interdisciplinary area are pointed out. It is claimed that paradigms for both professional sports analytics and AI research could be combined. Moreover, it is quite promising to bridge the gap between the real and virtual domains for soccer match analysis and decision-making.

Maneuvering target tracking of UAV based on MN-DDPG and transfer learning

Tracking maneuvering target in real time autonomously and accurately in an uncertain environment is one of the challenging missions for unmanned aerial vehicles(UAVs).In this paper,aiming to address the control problem of maneuvering target tracking and obstacle avoidance,an online path planning approach for UAV is developed based on deep reinforcement learning.Through end-to-end learning powered by neural networks,the proposed approach can achieve the perception of the environment and continuous motion output control.This proposed approach includes:(1)A deep deterministic policy gradient(DDPG)-based control framework to provide learning and autonomous decision-making capability for UAVs;(2)An improved method named MN-DDPG for introducing a type of mixed noises to assist UAV with exploring stochastic strategies for online optimal planning;and(3)An algorithm of taskdecomposition and pre-training for efficient transfer learning to improve the generalization capability of UAV’s control model built based on MN-DDPG.The experimental simulation results have verified that the proposed approach can achieve good self-adaptive adjustment of UAV’s flight attitude in the tasks of maneuvering target tracking with a significant improvement in generalization capability and training efficiency of UAV tracking controller in uncertain environments.

Evaluation of cosmogenic activation of copper and germanium during production in Jinping Underground Laboratory

Intrinsic radiation of materials is one of the major backgrounds for many rare-event search experiments.Thus,the production of pure materials in an underground laboratory is a promising approach for eliminating cosmogenic radionuclides.In this paper,we demonstrate a procedure to evaluate the yields of cosmogenic radionuclides in copper and germanium in the second phase of the China Jinping Underground Laboratory.Our results show that for copper and germanium materials,the largest cosmogenic background comes from 3 H and57,58,60Co,and 3 H and 68Ge,respectively,which all have yields on the order of 10-7 kg-1 day-1.The corresponding radioactivities after 90 days pf exposure underground are estimated to be lower than 10-6μBq kg-1.

Methane dehydroaromatization with periodic CH_4-H_2 switch:A promising process for aromatics and hydrogen

Long-term stability test of Mo/HZSM-5-N catalysts（HZSM-5-N stands for nano-sized HZSM-5） in methane dehydroaromatization（MDA）reaction has been performed with periodic CH4-H2 switch at 1033-1073 K for more than 1000 h.During this test,methane conversion ranges from 13% to 16%,and mean yield to aromatics（i.e.benzene and naphthalene） exceeds 10%.N2-physisorption,XRD,NMR and TPO measurements were performed for the used Mo/HZSM-5 catalysts and coke deposition,and the results revealed that the periodic hydrogenation can effectively suppress coke deposition by removing the inert aromatic-type coke,thus ensuring Mo/HZSM-5 partly maintained its activity even in the presence of large amount of coke deposition.The effect of zeolite particle size on the catalytic activity was also explored,and the results showed that the nano-sized zeolite with low diffusion resistance performed better.It is recognized that the size effect was enhanced by reaction time,and it became more remarkable in a long-term MDA reaction even at a low space velocity.

Characterization of a broad-energy germanium detector for its use in CJPL

The broad-energy germanium(BEGe)detector,with the ability of background discrimination using pulse shape discrimination,is a competitive candidate for neutrinoless double beta decay(ovββ)experiments.In this paper,we report our measurements of key parameters for detector modeling in a commercial p-type BEGe detector.Point-like sources are used to investigate energy resolution and linearity of the detector.A cylindrical volume source is used for efficiency calibration.With an assembled device for source positioning and a collimated ^(133)Ba source,the detector is scanned to check its active volume.Using an^(241)Am point-like source,the dead layer thicknesses is measured at about 0.17 mm on the front and 1.18 mm on the side.The detector characterization is of importance for BEGe detectors to be used in the ovββ experiments at China JinPing underground Laboratory(CJPL).

Research on the Application of Super Resolution Reconstruction Algorithm for Underwater Image

Underwater imaging is widely used in ocean,river and lake exploration,but it is affected by properties of water and the optics.In order to solve the lower-resolution underwater image formed by the influence of water and light,the image super-resolution reconstruction technique is applied to the underwater image processing.This paper addresses the problem of generating super-resolution underwater images by convolutional neural network framework technology.We research the degradation model of underwater images,and analyze the lower-resolution factors of underwater images in different situations,and compare different traditional super-resolution image reconstruction algorithms.We further show that the algorithm of super-resolution using deep convolution networks(SRCNN)which applied to super-resolution underwater images achieves good results.

Massive Power Device Condition Monitoring Data Feature Extraction and Clustering Analysis using MapReduce and Graph Model

Effective storage,processing and analyzing of power device condition monitoring data faces enormous challenges.A framework is proposed that can support both MapReduce and Graph for massive monitoring data analysis at the same time based on Aliyun DTplus platform.First,power device condition monitoring data storage based on MaxCompute table and parallel permutation entropy feature extraction based on MaxCompute MapReduce are designed and implemented on DTplus platform.Then,Graph based k-means algorithm is implemented and used for massive condition monitoring data clustering analysis.Finally,performance tests are performed to compare the execution time between serial program and parallel program.Performance is analyzed from CPU cores consumption,memory utilization and parallel granularity.Experimental results show that the designed framework and parallel algorithms can efficiently process massive power device condition monitoring data.

On-Line Photoionization Mass Spectrometric Study on Behavior of Ammonia Poisoning on H-Form Ultra Stable Y Zeolite for Catalytic Pyrolysis of Polypropylene

在这个工作，热分解光电游离 time-of-flight 团 spectrometry (Py-PI-TOFMS ) 被使用学习为聚丙烯(PP ) 的催化热分解在 H 形式极端稳定的 Y (HUSY ) 沸石上毒害的氨的行为。第一，在 HUSY 上毒害的氨被执行与酸地点的不同力量和数量获得合适的催化剂。第二，为有各种各样的酸力量的 PP 和 HUSY 的热分解产品的联机光电游离团系列在不同热分解温度被记录。最后，有温度的增加的 PP/HUSY 的各种各样的 pyrolysates 的形成曲线是坚定的。我们的结果显示 PP 的热分解产品的形成温度，收益和选择与 HUSY 的酸力量表明明显的关系。

Quantifying the Effects of Climate Change and Land Management on Vegetation Dynamics from 1982 to 1985 in the Source Region of Three-Rivers, China

Vegetation dynamics under a warming climate in the source region of the Three Rivers (SRTR) and its ecological impacts are a source of serious concern. In this study, we investigated the spatial and temporal variations of normalized difference vegetation index during the growing season (NDVIgr) and the start of the vegetation growing season (SOS) for six ecosystems. We examined the relationships between vegetation parameters, air temperature, precipitation and land management using residual trend method from 1982 to 2015. The NDVIgr increased at a rate of 0.0061/10a, and SOS advanced by 0.96 d/10a during the study period. The NDVIgr increased for the all six vegetation ecosystem from 1982 to 2015. The SOS showed advancing trend for the vegetation types for meadow (0.1236 d/a) and steppe (0.3480 d/a), but showing delaying trends for forest, shrub, barren land and alpine vegetation. The results of the correlation analysis indicate an increase in the air temperature in the SRTR is the main factor explaining increases in the NDVI and advancement of the SOS. In general, awarming-wetting climate and reasonable human activities had positive effects on vegetation growth, while the positive impact of human activities was weaker than that of climatic factors. This study provides a necessary basis for research on and the prediction of vegetation changes and their response to the climate warming of the SRTR in the Qinghai-Tibet Plateau (QTP).

Chickpea C2H2-Type Zinc Finger Protein ZF2 is a Positive Regulator in Drought Response in Arabidopsis

Drought is a major abiotic stress limiting agricultural crops production worldwide.In our study,we isolated a novel C2H2-type zinc finger protein gene ZF2 from chickpea.ZF2 consisted of 232 amino acids with two QALGGH motifs in Cys2/His2 zinc finger domain.Transient expression analysis of ZF2:GFP fusion protein showed that ZF2 was a nuclear localized protein.In the yeast assay system,the full-length of ZF2 did not show transcriptional activation.Expression of ZF2 gene was enhanced by treatments of several abiotic stresses and phytohormones.The promoter region of ZF2 contained multiple stress-and hormone-related cis-elements.Overexpression of ZF2 in Arabidopsis significantly improved the root length and fresh weight at seedling stage and enhanced the survival rates and proline content under drought treatment.These results indicated that ZF2 functioned as a positive regulator in drought response.

Changes in freezing and thawing indices over the source region of the Yellow River from 1980 to 2014

Freezing and thawing indices are not only of great significance for permafrost research but also are important indicators of the effects of climate change.However,to date,research on ground-surface freezing and thawing indices and their relationship with air indices is limited.Based on daily air and ground-surface temperatures collected from 11 meteorological stations in the source region of the Yellow River,the freezing and thawing indices were calculated,and their spatial distribution and trends were analyzed.The air-freezing index(AFI),air-thawing index(ATI),ground surface-freezing index(GFI),ground surface-thawing index(GTI),air thawing-freezing index ratio(Na)and surface ground thawing-freezing index ratio(Ng)were 1554.64,1153.93,1.55,2484.85,850.57℃-days and 3.44,respectively.Altitude affected the spatial distribution of the freezing and thawing indices.As the altitude increased,the freezing indices gradually increased,and the thawing indices and thawing-freezing index ratio decreased.From 1980 to 2014,the AFI and GFI decreased at rates of 8.61 and 11.06℃-days a^(-1),the ATI and GTI increased at 9.65 and 14.53℃-days a^(-1),and Na and Ng significantly increased at 0.21 and 0.79 decade^(-1).Changes in the freezing and thawing indices were associated with increases in the air and ground-surface temperatures.The rates of change of the ground surface freezing and thawing indices were faster than the air ones because the rate of increase of the groundsurface temperature was faster than that of the air and the difference between the ground surface and air increased.The change point of the time series of freezing and thawing indices occurred in 2000–2001.After 2000–2001,the AFI and GFI were lower than before the change point,and the changing trend was lower.The ATI,GTI,Na and Ng during 2001–2014 were higher,with faster rates than before.In addition,the annual thawing indices composed a greater proportion of the mean annual air temperature and mean annual ground surface temperature than the annual freezing indices.This study provides the necessary basis for research on and prediction of permafrost changes,especially changes in the depth of the active permafrost layer,climate change,and possible evolution of the ecological environment over the source region of the Yellow River on the Qinghai-Tibet Plateau.

Production of chitosan scaffolds by lyophilization or electrospinning: which is better for peripheral nerve regeneration?

Both lyophilization and electrospinning are commonly used to make chitosan scaffolds.However,it remains unknown which method is better for cell growth.In this study,we established the following groups:(1)lyophilization group-chitosan scaffolds were prepared by lyophilization method and seeded with Schwann cells from Sprague-Dawley rats aged 3-5 days;(2)electrospinning group-chitosan scaffolds were prepared by electrospinning method and seeded with Schwann cells;(3)control group-Schwann cells were cultured on culture dishes.The growth of Schwann cells was evaluated by immunofluorescence and scanning electron microscopy.Western blot assay was performed to explore the mechanism of Schwann cell growth.Both materials were non-toxic and suitable for the growth of Schwann cells.The pores produced by electrospinning were much smaller than those produced by lyophilization.The proliferation rate and adhesion rate of Schwann cells in the electrospinning group were higher than those in the lyophilization group.Schwann cells cultured on electrospinning scaffolds formed a Bungner band-like structure,and a much greater amount of brain-derived neurotrophic factor was secreted,which can promote the growth of neurons.Our findings show that the chitosan scaffold prepared by the electrospinning method has a nanofiber structure that provides an extracellular matrix that is more favorable for cell-cell interactions.The electrospinning method is more suitable for nerve regeneration than the lyophilization method.This research was approved by the Medical Ethical Committee of Dalian Medical University(approval No.AEE1-2016-045)on March 3,2016.

Dorsal root ganglion-derived Schwann cells combined with poly(lactic-co-glycolic acid)/chitosan conduits for the repair of sciatic nerve defects in rats

Schwann cells, nerve regeneration promoters in peripheral nerve tissue engineering, can be used to repair both the peripheral and central nervous systems. However, isolation and puriifcation of Schwann cells are complicated by contamination with ifbroblasts. Current reported measures are mainly limited by either high cost or complicated procedures with low cell yields or purity. In this study, we collected dorsal root ganglia from neonatal rats from which we obtained highly puriifed Schwann cells using serum-free melanocyte culture medium. The purity of Schwann cells （〉95%） using our method was higher than that using standard medium containing fetal bovine serum. The obtained Schwann cells were implanted into poly（lactic-co-glycolic acid）/chi-tosan conduits to repair 10-mm sciatic nerve defects in rats. Results showed that axonal diameter and area were signiifcantly increased and motor functions were obviously improved in the rat sciatic nerve tissue. Experimental ifndings suggest that serum-free melanocyte culture medium is conducive to purify Schwann cells and poly（lactic-co-glycolic acid）/chitosan nerve conduits combined with Schwann cells contribute to restore sciatic nerve defects.

Research progress on properties of pre-gelatinized starch and its application in wheat flour products

Starch is the most abundant organic compound in nature,second only to cellulose.However,the conserved structure of native starches limits their properties and applications.Therefore,it is often necessary to modify them to obtain specific properties.As a common green and safe physical modification method,pre-gelatinization can improve the cold water solubility and swelling power of starch.The typical preparation methods of pre-gelatinized starch include spray drying,extrusion,and drum drying.Spray-dried pre-gelatinized starch still had good granule shape,but the increase of cold water solubility and cold paste viscosity was relatively small.Extruded and drum-dried pre-gelatinized starch showed serious structure destruction,significant increases in cold water solubility and cold paste viscosity,but relatively low hot paste viscosity.The properties of pre-gelatinized starch obtained by different methods are different,so do their effects on the quality of flour products.Wheat flour products,as one of the leading staple food for the people all over the world,play a vital role in people's daily life.With the improvement of people's living standards,more and more special flour products with unique features have received attentions of consumers and researchers.However,the sensory characteristics of special flour products are often inferior to traditional flour products,which limits its development.The unique functional characteristics of pre-gelatinized starch make it expected to play an essential role in the quality improvement of featured flour products.In this paper,the granule morphology,crystal structure,hydration and gelatinization properties of pre-gelatinized starch prepared by three common methods and their application in flour products were reviewed,which provides a theoretical basis for the application of pre-gelatinized starch in food industry.

The theory of compression–shear coupled composite wave propagation in rock

The wave velocity analysis of rock medium is the main method used to explore the internal compositions in the crust and research seismic.In this paper,a compression–shear coupled nonlinear elastic constitutive relation is established,which is consistent with the mechanical properties of rock and mineral medium under high pressure.On this basis,numerical solutions of the wave equation and plane wave analytical solutions for the primary and secondary wave velocities are obtained.As is indicated by the comparison with the linear elastic constitutive theory,the results reflect the compression–shear coupling characteristics of the rock,including the stress path effect and the compression–shear coupling wave effect.With different parameter values,the velocity of the secondary wave changes from lower than that of the elastic shear wave,to higher than that of the elastic shear wave.The research results are expected to provide meaningful explanations for the physical mechanisms of the supershear wave and sub-Rayleigh wave,and guidance for the detection of rock and soil composition and the observation of seismic waves.

Distributed Real-time Optimal Power Flow Strategy for DC Microgrid Under Stochastic Communication Networks

This paper addresses a distributed real-time optimal power flow(RTOPF) strategy for DC microgrids. In this paper, we focus on the scenarios where local information sharing is conducted in stochastic communication networks subject to random failures. Most existing real-time optimal power flow(OPF) algorithms for the DC microgrid require all controllers to work in concert with a fixed network topology to maintain a zero gap between estimated global constraint violations. Thus, the high reliability of communication is required to ensure their convergence. To address this issue, the proposed RTOPF strategy tolerates stochastic communication failures and can seek the optimum with a constant step size considering the operation limitations of the microgrid. These aspects make the strategy suitable for real-time optimization, particularly when the communication is not reliable. In addition, this strategy does not require information from non-dispatchable devices, thereby reducing the number of sensors and controllers in the system. The convergence of the proposed strategy and the optimal equilibrium points are theoretically proven. Finally, simulations of a 30-bus DC microgrid are performed to validate the effectiveness of the proposed designs.

Optical responses of metallic plasmonic arrays under the localized excitation

The metallic plasmonic array that can support both propagating surface plasmon polaritons(PSPPs)and localized surface plasmon resonance(LSPR)possesses rich optical properties and remarkable optical performance,making it a powerful platform for applications in photonics,chemistry,and materials.For practical applications,the excitation spot is usually smaller than the area of metal arrays.It is thus imperative to address“how many array units are enough?”towards a rational design of plasmonic nanostructures.Herein,we employed focused ion beam(FIB)to precisely fabricate a series of plasmonic array structures with increased unit number.By utilizing photoluminescence(PL)and surface-enhanced Raman spectroscopy(SERS),we found that the array units outside the excitation spot still have a significant impact on the optical response within the spot.Combined with the numerical simulation,we found that the boundary of the finite array leads to the loss of PSPP outside the excitation point,which subsequently affects the coupling of PSPP and LSPR in the excitation spot,leading to variations in PL and SERS intensity.Based on the findings,we further tuned the LSPR mode of the metal arrays by electrodeposition to obtain strong near-field enhancement without any influence on the PSPP mode.This work advances the understanding of near-field and far-field optical behavior in finite-size array structures and provides guidance for designing highly-efficient photonic devices.

Development of single row automatic transplanting device for potted vegetable seedlings

In China,low degree of automation seriously affects the working efficiency and quality in vegetable transplanting.As one of the most important vegetables in China even in the world,tomato was taken as the research object in this study.An automatic single-row transplanting device was designed,based on the statistical analysis of the physical and mechanical properties of tomato seedlings of a typical variety.Based on the technology of mechatronics,the device integrated the functions of transporting seedling tray,automatic seedling extraction and mechanical planting.The kinematics orthogonality solution combined with the dynamic sequence solution method was used to optimize and analyze the kinematic parameters of the automatic seeding mechanism,and the“sickle”trajectory was obtained.According to the position and movement requirement for taking and dropping seedling,the mechanical conditions and the working parameters of key execution parts were obtained by using analytic drawing method to analyze the mechanical condition of seedling collecting mechanism.The transplanting experiment was conducted at room temperature of 25°C,and the age and moisture content of the seedlings were 40 d and 55%,respectively.The results showed that the highest success rate was 92.59%,and the lowest rate of leakage was 23.13%,when the transplanting frequency was 60 plants/min.The lowest success rate was 77.78%,and the highest rate of leakage was 38.75%,when transplanting frequency was 120 plants/min.When the transplanting frequency is between 60-90 plants/min,the device can meet the requirement of high speed transplanting for potted vegetable seedling.

湿度场与围压耦合作用下基于Weibull分布的岩石损伤本构模型研究

在地基开挖、地铁施工等地下工程中,岩石常常受到湿度场–围压耦合作用。耦合作用会加剧岩石内部损伤,对于损伤本构模型的研究可以进一步揭示岩石损伤机理。目前对于在湿度场–围压耦合作用下岩石的损伤本构模型研究尚不完善。本文基于Lemaitre应变等价性假设理论和SMP准则,引入双参数的Weibull分布,对岩石微元强度进行修正,建立了湿度场–围压耦合作用下的岩石损伤本构模型。然后,采用极值法得出所需的本构模型参数。对灰质泥岩的峰值应力和峰值应变进行理论与试验曲线对比研究,提出的理论模型表现出较好的吻合度,验证了该本构模型及参数的合理性以及适用性。本研究对软岩的损伤模型研究提供了参考,有一定的工程实用性和指导性。

Thermally Conductive Poly(lactic acid) Composites with Superior Electromagnetic Shielding Performances via 3D Printing Technology

This work proposes a facile fabrication strategy for thermally conductive graphite nanosheets/poly(lactic acid) sheets with ordered GNPs(o-GNPs/PLA) via fused deposition modeling(FDM) 3 D printing technology.Further combinations of o-GNPs/PLA with Ti_(3) C_(2) T_(x) films prepared by vacuum-assisted filtration were carried out by "layer-by-layer stacking-hot pressing" to be the thermally conductive Ti_(3) C_(2) T_(x)/(oGNPs/PLA) composites with superior electromagnetic interference shielding effectiveness(EMI SE).When the content of GNPs was 18.60 wt%and 4 layers of Ti_(3) C_(2) T_(x)(6.98 wt%) films were embedded,the in-plane thermal conductivity coefficient(λ_(Ⅱ)) and EMI SE(EMI SE_(Ⅱ)) values of the thermally conductive Ti_(3) C_(2) T_(x)/(o-GNPs/P LA) composites significantly increa sed to 3.44 W·m^(-1)·K^(-1) and 65 d B(3.00 mm),increased by 1223.1% and2066.7%,respectively,compared with λ_(Ⅱ)(0.26 W·m^(-1)·K^(-1)) and EMI SE_(Ⅱ)(3 d B) of neat PLA matrix.This work offers a novel and easily route for designing and manufacturing highly thermally conductive polymer composites with superior EMI SE for broader application.