Innovation of Practice Education in Applied Universities： A Study on the ＂Base＂-driven Practice Education System in Zhejiang University City College

Practice education is an important part of application-oriented higher education. Yet it poses many challenges when the design of practice education is questioned concerning whether it actually fulfills the education purpose for high quality future professionals. This paper thus introduces an innovated ＂base＂-driven model of practice education in Zhejiang University City College in China, with a purpose to provide empirical experiences that may be valuable for the decision-making of practice education design in higher education institutions. The paper progresses by examining the philosophy of its innovated model, discussing the framework, and further highlights a strategic consideration when designing practice education activities in higher education institutions.

Superconductivity in kagome metal ThRu_(3)Si_(2)

We report the physical properties of ThRu_(3)Si_(2)featured with distorted Ru kagome lattice.The combined experiments of resistivity,magnetization and specific heat reveal bulk superconductivity with T_(c)=3.8 K.The specific heat jump and calculated electron–phonon coupling indicate a moderate coupled BCS superconductor.In comparison with LaRu_(3)Si_(2),the calculated electronic structure in ThRu_(3)Si_(2)shows an electron-doping effect with electron filling lifted from 100 meV below flat bands to 300 meV above it.This explains the lower superconducting transition temperature and weaker electron correlations observed in ThRu_(3)Si_(2).Our work suggests the Tc and electronic correlations in the kagome superconductor could have an intimate connection with the flat bands.

Three-dimensional elasticity solutions for bending of generally supported thick functionally graded plates

Three-dimensional elasticity solutions for static bending of thick functionally graded plates are presented using a hybrid semi-analytical approach-the state-space based differential quadrature method （SSDQM）. The plate is generally supported at four edges for which the two-way differential quadrature method is used to solve the in-plane variations of the stress and displacement fields numerically. An approximate laminate model （ALM） is exploited to reduce the inhomogeneous plate into a multi-layered laminate, thus applying the state space method to solve analytically in the thickness direction. Both the convergence properties of SSDQM and ALM are examined. The SSDQM is validated by comparing the numerical results with the exact solutions reported in the literature. As an example, the Mori-Tanaka model is used to predict the effective bulk and shear moduli. Effects of gradient index and aspect ratios on the bending behavior of functionally graded thick plates are investigated.

Can glial cells save neurons in epilepsy?

Epilepsy is a neurological disorder caused by the pathological hyper-synchronization of neuronal discharges.The fundamental research of epilepsy mechanisms and the targets of drug design options for its treatment have focused on neurons.However,approximately 30%of patients suffering from epilepsy show resistance to standard anti-epileptic chemotherapeutic agents while the symptoms of the remaining 70%of patients can be alleviated but not completely removed by the current medications.Thus,new strategies for the treatment of epilepsy are in urgent demand.Over the past decades,with the increase in knowledge on the role of glia in the genesis and development of epilepsy,glial cells are receiving renewed attention.In a normal brain,glial cells maintain neuronal health and in partnership with neurons regulate virtually every aspect of brain function.In epilepsy,however,the supportive roles of glial cells are compromised,and their interaction with neurons is altered,which disrupts brain function.In this review,we will focus on the role of glia-related processes in epileptogenesis and their contribution to abnormal neuronal activity,with the major focus on the dysfunction of astroglial potassium channels,water channels,gap junctions,glutamate transporters,purinergic signaling,synaptogenesis,on the roles of microglial inflammatory cytokines,microglia-astrocyte interactions in epilepsy,and on the oligodendroglial potassium channels and myelin abnormalities in the epileptic brain.These recent findings suggest that glia should be considered as the promising next-generation targets for designing anti-epileptic drugs that may improve epilepsy and drug-resistant epilepsy.

Pre-research on Enhanced Heat Transfer Method for Special Vehicles at High Altitude Based on Machine Learning

The performance of an integrated thermal management system signi?cantly in?uences the stability of special-purpose vehicles;thus,enhancing the heat transfer of the radiator is of great signi?cance.Common research methods for radiators include?uid mechanics numerical simulations and experimental measurements,both of which are time-consuming and expensive.Applying the surrogate model to the analysis of the?ow and heat transfer in louvered?ns can effectively reduce the computational cost and obtain more data.A simpli?ed louvered-?n heat transfer unit was established,and computational?uid dynamics(CFD)simulations were conducted to obtain the?ow and heat transfer characteristics of the geometric structure.A three-factor and six-level orthogonal design was established with three structural parameters:angleθ,length a,and pitch L_p of the louvered?ns.The results of the orthogonal design were subjected to a range analysis,and the effects of the three parametersθ,a,and L_p on the j,f,and JF factors were obtained.Accordingly,a proxy model of the heat transfer performance for louvered?ns was established based onthe arti?cial neural network algorithm,and the model was trained with the data obtained by the orthogonal design.Finally,the?n structure with the largest JF factor was realized.Compared with the original model,the optimizedmodel improved the heat transfer factor j by 2.87%,decreased the friction factor f by 30.4%,and increased the comprehensive factor JF by 15.7%.

Insights into cryptic speciation of quillworts in China

Cryptic species are commonly misidentified because of high morphological similarities to other species.One group of plants that may harbor large numbers of cryptic species is the quillworts(Isoetes spp.),an ancient aquatic plant lineage.Although over 350 species of Isoetes have been reported globally,only ten species have been recorded in China.The aim of this study is to better understand Isoetes species diversity in China.For this purpose,we systematically explored the phylogeny and evolution of Isoetes using complete chloroplast genome(plastome)data,spore morphology,chromosome number,genetic structure,and haplotypes of almost all Chinese Isoetes populations.We identified three ploidy levels of Isoetes in Chinaddiploid(2n=22),tetraploid(2n=44),and hexaploid(2n=66).We also found four megaspore and microspore ornamentation types in diploids,six in tetraploids,and three in hexaploids.Phylogenetic analyses confirmed that I.hypsophila as the ancestral group of the genus and revealed that Isoetes diploids,tetraploids,and hexaploids do not form monophyletic clades.Most individual species possess a single genetic structure;however,several samples have conflicting positions on the phylogenetic tree based on SNPs and the tree based on plastome data.All 36 samples shared 22 haplotypes.Divergence time analysis showed that I.hypsophila diverged in the early Eocene(~48.05 Ma),and most other Isoetes species diverged 3-20 Ma.Additionally,different species of Isoetes were found to inhabit different water systems and environments along the Yangtze River.These findings provide new insights into the relationships among Isoetes species in China,where highly similar morphologic populations may harbor many cryptic species.

Upregulation of β-catenin signaling represents a single common pathway leading to the various phenotypes of spinal degeneration and pain

Spine degeneration is an aging-related disease,but its molecular mechanisms remain unknown,although elevatedβ-catenin signaling has been reported to be involved in intervertebral disc degeneration.Here,we determined the role ofβ-catenin signaling in spinal degeneration and in the homeostasis of the functional spinal unit(FSU),which includes the intervertebral disc,vertebra and facet joint and is the smallest physiological motion unit of the spine.We showed that pain sensitivity in patients with spinal degeneration is highly correlated withβ-catenin protein levels.We then generated a mouse model of spinal degeneration by transgenic expression of constitutively activeβ-catenin in Col2^(+) cells.We found thatβ-catenin-TCF7 activated the transcription of CCL2,a known critical factor in osteoarthritic pain.Using a lumbar spine instability model,we showed that aβ-catenin inhibitor relieved low back pain.Our study indicates thatβ-catenin plays a critical role in maintaining spine tissue homeostasis,its abnormal upregulation leads to severe spinal degeneration,and its targeting could be an avenue to treat this condition.

The tumor suppressor role and ceRNA network of miR-1294 in cancer

miRNAs are endogenous small RNAs that are important regulators of gene expression.miR-1294 was found to be significantly down-regulated in 15 cancers and regulated by 21 upstream regulators.miR-1294 affects the proliferation,migration,invasion,and apoptosis of cancer cells.The target genes of miR-1294 are involved in the PI3K/AKT/mTOR,RAS,and JAK/STAT signaling pathways.Six target genes of miR-1294 are the targets of a variety of drugs.Low expression of miR-1294 is associated with resistance to cisplatin and TMZ and a poorer prognosis in patients with ESCC,GC,EOC,PDAC,or NSCLC.Therefore,this work outlines the molecular mechanisms and provides a basis for the clinical significance of the tumor suppressor miR-1294 in cancer.

A New Method of Combination of Electroosmosis, Vacuum and Surcharge Preloading for Soft Ground Improvement

As a rapid and effective ground improvement method is urgently required for the booming land reclamation in China＇s coastal area, this study proposes a new combined method of electroosmosis, vacuum preloading and surcharge preloading. A new type of electrical prefabricated vertical drain （ePVD） and a new electroosmotic drainage system are suggested to allow the application of the new method. This combined method is then field-tested and compared with the conventional vacuum combined with surcharge preloading method. The monitoring and foundation test results show that the new method induces a settlement 20% larger than that of the conventional vacuum combined with surcharge preloading method in the same treatment period, and saves approximately half of the treatment time compared with the vacuum combined with surcharge preloading method according to the finite element prediction of the settlement. The proposed method also increases the vane shear strength of the soil significantly. The bearing capacity of the ground improved by use of the new proposed method raises 118%. In comparison, there is only a 75% rise when using the vacuum combined with surcharge preloading method during the same reinforcement period. All results indicate that the proposed combined method is effective and suitable for reinforcing the soft clay ground. Besides, the voltage applied between the anode and cathode increases exponentially versus treatment time when the output current of power supplies is kept constant. Most of the voltage potential in electroosmosis is lost at electrodes, leaving smaller than 50% of the voltage to be effectively transmitted into the soil.

A new extension algorithm for cubic B-splines based on minimal strain energy

Extension of a B-spline curve or surface is a useful function in a CAD system. This paper presents an algorithm for extending cubic B-spline curves or surfaces to one or more target points. To keep the extension curve segment GC^2-continuous with the original one, a family of cubic polynomial interpolation curves can be constructed. One curve is chosen as the solution from a sub-class of such a family by setting one GC^2 parameter to be zero and determining the second GC^2 parameter by minimizing the strain energy. To simplify the final curve representation, the extension segment is reparameterized to achieve C-continuity with the given B-spline curve, and then knot removal from the curve is done. As a result, a sub-optimized solution subject to the given constraints and criteria is obtained. Additionally, new control points of the extension B-spline segment can be determined by solving lower triangular linear equations. Some computing examples for comparing our method and other methods are given.

Investigation of feature contribution to shield tunneling-induced settlement using Shapley additive explanations method

Accurate prediction of shield tunneling-induced settlement is a complex problem that requires consideration of many influential parameters.Recent studies reveal that machine learning(ML)algorithms can predict the settlement caused by tunneling.However,well-performing ML models are usually less interpretable.Irrelevant input features decrease the performance and interpretability of an ML model.Nonetheless,feature selection,a critical step in the ML pipeline,is usually ignored in most studies that focused on predicting tunneling-induced settlement.This study applies four techniques,i.e.Pearson correlation method,sequential forward selection(SFS),sequential backward selection(SBS)and Boruta algorithm,to investigate the effect of feature selection on the model’s performance when predicting the tunneling-induced maximum surface settlement(S_(max)).The data set used in this study was compiled from two metro tunnel projects excavated in Hangzhou,China using earth pressure balance(EPB)shields and consists of 14 input features and a single output(i.e.S_(max)).The ML model that is trained on features selected from the Boruta algorithm demonstrates the best performance in both the training and testing phases.The relevant features chosen from the Boruta algorithm further indicate that tunneling-induced settlement is affected by parameters related to tunnel geometry,geological conditions and shield operation.The recently proposed Shapley additive explanations(SHAP)method explores how the input features contribute to the output of a complex ML model.It is observed that the larger settlements are induced during shield tunneling in silty clay.Moreover,the SHAP analysis reveals that the low magnitudes of face pressure at the top of the shield increase the model’s output。

A Privacy-Based SLA Violation Detection Model for the Security of Cloud Computing

A Service Level Agreement(SLA) is a legal contract between any two parties to ensure an adequate Quality of Service(Qo S). Most research on SLAs has concentrated on protecting the user data through encryption. However, these methods can not supervise a cloud service provider(CSP) directly. In order to address this problem, we propose a privacy-based SLA violation detection model for cloud computing based on Markov decision process theory. This model can recognize and regulate CSP's actions based on specific requirements of various users. Additionally, the model could make effective evaluation to the credibility of CSP, and can monitor events that user privacy is violated. Experiments and analysis indicate that the violation detection model can achieve good results in both the algorithm's convergence and prediction effect.

Heisenberg algebra for noncommutative Landau problem

The Landau problem on non-commutative quantum mechanics is studied, where the Heisenberg algebra and the Landau energy levels as well as the non-commutative angular momentum are constructed in detail in non-commutative space and non-commutative phase space respectively.

Dynamic response of cylindrical cavity to anti-plane impact load by using analytical approach

The transient response of an unlimited cylindrical cavity buried in the infinite elastic soil subjected to an anti-plane impact load along the cavern axis direction was studied.Using Laplace transform combining with contour integral of the Laplace inverse transform specifically,the general analytical expressions of the soil displacement and stress are obtained in the time domain,respectively.And the numerical solutions of the problem computed by analytical expressions are presented.In the time domain,the dynamic responses of the infinite elastic soil are analyzed,and the calculation results are compared with those from numerical inversion proposed by Durbin and the static results.One observes good agreement between analytical and numerical inversion results,lending the further support to the method presented.Finally,some valuable shear wave propagation laws are gained: the displacement of the soil remains zero before the wave arrival,and after the shear wave arrival,the stress and the displacement at this point increase abruptly,then reduce and tend to the static value gradually at last.The wave attenuates along the radial,therefore the farther the wave is from the source,the smaller the stress and the displacement are,and the stress and the displacement are just functions of the radial distance from the axis.

An adaptive improvement on PageRank algorithm

In this article, we introduce the Google＇s method for quality ranking of web page in a formal mathematical format, use the power iteration to improve the PageRank, and also discuss the effect of different q to the PageRank, as well as how a PageRank will be changed if more links are added to one page or removed from some pages.

Observer-based Iterative and Repetitive Learning Control for a Class of Nonlinear Systems

In this paper, both output-feedback iterative learning control(ILC) and repetitive learning control(RLC) schemes are proposed for trajectory tracking of nonlinear systems with state-dependent time-varying uncertainties. An iterative learning controller, together with a state observer and a fully-saturated learning mechanism, through Lyapunov-like synthesis, is designed to deal with time-varying parametric uncertainties. The estimations for outputs, instead of system outputs themselves, are applied to form the error equation, which helps to establish convergence of the system outputs to the desired ones. This method is then extended to repetitive learning controller design. The boundedness of all the signals in the closed-loop is guaranteed and asymptotic convergence of both the state estimation error and the tracking error is established in both cases of ILC and RLC. Numerical results are presented to verify the effectiveness of the proposed methods.

Investigations on mesa width design for 4H–SiC trench super junction Schottky diodes

Mesa width （WM） is a key design parameter for SiC super junction （SJ） Schottky diodes （SBD） fabricated by the trench-etching-and-sidewall-implant method. This paper carries out a comprehensive investigation on how the mesa width design determines the device electrical performances and how it affects the degree of performance degradation induced by process variations. It is found that structures designed with narrower mesa widths can tolerant substantially larger charge imbalance for a given BV target, but have poor specific on-resistances. On the contrary, structures with wider mesa widths have superior on-state performances but their breakdown voltages are more sensitive to p-type doping variation. Medium WM structures （-2 p.m） exhibit stronger robustness against the process variation resulting from SiC deep trench etching. Devices with 2-p.m mesa width were fabricated and electrically characterized. The fabricated SiC SJ SBDs have achieved a breakdown voltage of 1350 V with a specific on-resistance as low as 0.98 mΩ2.cm2. The estimated specific drift on- resistance by subtracting substrate resistance is well below the theoretical one-dimensional unipolar limit of SiC material. The robustness of the voltage blocking capability against trench dimension variations has also been experimentally verified for the proposed SiC SJ SBD devices.

A Wireless Intrusion Alerts Clustering Method for Mobile Internet

With the rapid development of mobile Internet, people pay increasing attention to the wireless network security problem. But due to the specificity of the wireless network, at present it is rare to see the research of wireless intrusion alerts clustering method for mobile Internet. This paper proposes a Wireless Intrusion Alert Clustering Method(WIACM) based on the information of the mobile terminal. The method includes alert formatting, alert reduction and alert classification. By introducing key information of the mobile terminal device, this method aggregates the original alerts into hyper alerts. The experimental results show that WIACM would be appropriate for real attack scenarios of mobile Internet, and reduce the amount of alerts with more accuracy of alert analysis.

Automatic Sleep Staging Algorithm Based on Random Forest and Hidden Markov Model

In the field of medical informatics,sleep staging is a challenging and timeconsuming task undertaken by sleep experts.According to the new standard of the American Academy of Sleep Medicine(AASM),the stages of sleep are divided into wakefulness(W),rapid eye movement(REM)and non-rapid eye movement(NREM)which includes three sleep stages(N1,N2 and N3)that describe the depth of sleep.This study aims to establish an automatic sleep staging algorithm based on the improved weighted random forest(WRF)and Hidden Markov Model(HMM)using only the features extracted from double-channel EEG signals.The WRF classification model focuses on reducing the bias of the imbalance data,while the HMM model focuses on improving the detection rate of sleep staging through the relationship between adjacent sleep stages.In particular,the improved weighted RF classification model can increase the recognition rate of the N1 stage.In addition,the method of removing features with low variance is used to select meaningful and contributing feature parameters for model training.This is an innovative content of this paper.The sleep EEG data are first segmented into 30 s epochs,and the feature parameters of the epoch data are extracted from the double-channel by applying continuous wavelet packet transform(WPT).Each epoch is then segmented into 29 subepochs of 2 s long with 1 s overlap,and the frequency domain features and statistical features of each subepoch are extracted.The performance of the proposed method is tested by evaluating the accuracy(AC),Kappa coefficient,Recall(R),Precision(P)and F1-score(F1).In the Sleep-EDF database,the overall AC and Kappa coefficient obtained by WRF are 93.20%and 0.890,respectively using the subject-non-independent test.In the 10 sc*and 10 st*Sleep-EDF Expanded database,the overall AC and Kappa coefficient obtained by proposed method are 91.97%and 0.874,respectively using the subject-independent test.The best AC and Kappa coefficient of single subject can reach 96.3%and 0.912,respectively.Experimental results show that the performance of the proposed method is competitive with the most current methods and results,and the recognition rate of N1 stage is significantly improved.

Time-Critical Tasks Implementation in MEC Based Multi-Robot Cooperation Systems

Mobile edge computing(MEC) deployment in a multi-robot cooperation(MRC) system is an effective way to accomplish the tasks in terms of energy consumption and implementation latency. However, the computation and communication resources need to be considered jointly to fully exploit the advantages brought by the MEC technology. In this paper, the scenario where multi robots cooperate to accomplish the time-critical tasks is studied, where an intelligent master robot(MR) acts as an edge server to provide services to multiple slave robots(SRs) and the SRs are responsible for the environment sensing and data collection. To save energy and prolong the function time of the system, two schemes are proposed to optimize the computation and communication resources, respectively. In the first scheme, the energy consumption of SRs is minimized and balanced while guaranteeing that the tasks are accomplished under a time constraint. In the second scheme, not only the energy consumption, but also the remaining energies of the SRs are considered to enhance the robustness of the system. Through the analysis and numerical simulations, we demonstrate that even though the first policy may guarantee the minimization on the total SRs’ energy consumption, the function time of MRC system by the second scheme is longer than that by the first one.