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At present, in the society including the education industry, the competition is increasingly fierce, and the traditional education models of universities mostly emphasize theoretical research over practice, and even some universities have no practical arrangements at all, it is difficult for talents trained to fit in with the rapid growth of the current society. Therefore, based on mobile Internet technology, this paper focuses on designing a platform designed to improve the information communication between universities and enterprises, so as to effectively realize the win-win mode of school-enterprise resource sharing and deliver professional talents to the society. This paper first discusses the in-depth analysis of mobile Internet technology, then expounds the technical support used by the platform, optimizes and designs the development functions according to the existing school-enterprise cooperation information service platform, and finally collects the use feelings of the main service objects of the platform and the feedback evaluation. According to the survey, prospective personal users praised the platform for 30%; universities received 29%; the partners received 24% on the platform and 17%. Therefore, it can be concluded that the intended individual users and universities ‘ use experience of the school-enterprise cooperation information system is more significant.

Negative temperature coefficient (NTC) ceramics based on simple ZnO were prepared and investigated in present work, where slight amount of Al- and La- ions were added as semiconductor dopants, and Cu-ions were selected as the sintering agent and property modificator. All the prepared ZnO-based ceramics have a wurtzite structure and show typical NTC characteristic. For various contents of Al-, La- and Cu- ions in ZnO-based ceramics, ρ25 can be adjusted from 0.65 kΩ cm to 3.28 MΩ cm, and B values were obtained in range of 2500 K to 5850 K. The ageing treatment at 125 °C for 600 h in air revealed that the ZnO-based ceramics have high thermal stability with the resistance shift

The high energy storage devices such as lithium-ion batteries (LIBs) have recently attracted extensive attention, and massive efforts have been made to synthesize the high-performance electrodes for Li-ion storage. Here, a facile in situ synthesis method was proposed to prepare the NiO/Ni nanocomposites embedded in three-dimensional (3D) porous carbon network (denoted as NiO/Ni⊕C). The phase component and microstructure of the NiO/Ni⊕C were detected by using X-ray diffraction, scanning electron microscope and transmission electron microscopy. The NiO/Ni nanocomposites with the particle size of approximately 20–50 nm were uniformly dispersed in the 3D porous carbon matrix. The 3D carbon network is in favor of electrical conductivity, and effectively alleviates the volume effect during lithiation–delithiation processes, and thus help the electrode achieve high electrochemistry performance. The NiO/Ni⊕C electrodes possess a reversible specific capacity of 934 mAh g−1 at a current density of 300 mA g−1, and exhibit a superior rate performance with a specific capacity of 505 mAh g−1 at a current density of 2 A g−1. The NiO/Ni⊕C electrodes maintained a specific capacity of up to 683 mAh g−1 even after 1000 cycles at a current density of 1 A g−1.

The stability issue is still one of the main limitations of the commercialization of perovskite photovoltaics. The mixed cation FA

Effectively carrying out classroom teaching management under the objective law of teaching activities can further enhance the teaching effect. The digital signal processing course attracts much attention because of its versatility, comprehensiveness, strong frontier, and practicality, but because of its abstract concept, cumbersome formulas, using mainstream education methods such as blackboard, and PPT, the teaching results are not ideal and the students have limited harvest. Taking information technology as the traction and intelligent interactive whiteboard system as the platform, through the effective classroom management, an in-depth interactive teaching method based on intelligent interactive whiteboard is constructed. Practice shows that in-depth interactive teaching methods can break the traditional one-way teaching and realize the two-way interaction between teachers and students. That is to say, through this teaching method, teachers can vividly expound the key teaching contents, clearly explain the arguments, and perform the image interpretation. Students become passive and active, actively participate, can actively think and feedback, and practice multidimensional model thinking through in-depth interactive teaching, and extract methods from it. In addition, under the effective classroom management constraints, in-depth interactive teaching enhances the fun of teaching and learning, turning the classroom into a real interactive classroom, and its results can promote the development of education and teaching of digital signal processing courses.

The paper analyzes the characteristics of the digital signal processing course, takes the mural construction as the research object, and analyzes the necessity and technical requirements of the digital signal processing. Then this paper analyzes the knowledge management related to the content of the digital signal processing MOOC, including the structure of knowledge points and the key and difficult points of this course. The research of the thesis has reference significance for the construction of digital signal processing.

In order to optimize classroom management and improve teaching quality further, this paper has improved the teaching methods of the core content of digital signal processing courses: discrete Fourier transform (DFT) and fast Fourier transform (FFT). The traditional teaching method first throws the concept theorem and then uses the formula to derive the calculation. This method has problems that students cannot accept immediately in class, and it is difficult to understand in class. Aiming at the shortcomings of traditional teaching in management, this paper proposes a fast algorithm based on the mastery of students’ knowledge, through matrix analysis of DFT, and using heuristic teaching method to guide students to think about DFT from matrix theory. The same calculation effect and complexity of the algorithm can achieve better teaching results. This paper explores and practices this teaching method, realizes the penetration of heuristic teaching in management teaching, and effectively improves students’ learning autonomy and comprehensive ability. The results can promote the education and teaching development of digital signal processing courses.

Digital signal processing is a required course for professional communication in navigation, navigation, radar engineering, etc. Although the professional basic status of the course is beyond doubt, some problems in the teaching of this course still affect and restrict its professional basic teaching effect. This article starts from the practical teaching of how the instructors can carry out the basic course of digital signal processing for different professions, and through the corresponding teaching research, promotes the young teachers to improve the practical teaching effect, and lays a solid foundation for the students of many majors before taking up the post in the study position. Strive to truly achieve teaching and learning and effectively improve the quality of teaching.

Semitransparent photovoltaic devices can open a window for the photovoltaic application, such as building-integrated photovoltaics (BIPVs) and portable photovoltaic chargers and so on. We demonstrated a classical visible non-fullerene acceptor IT-M was incorporated into binary blend, and the new ternary blend (PM6:Y6:IT-M) film achieved a smooth surface morphology and a balanced charge transport compared to binary blend films. The ternary devices exhibit increased JSC of 26.44 mA cm−2 and PCE of 15.78% while remaining high VOC of 0.87 V. As a result, the ternary blend (PM6:Y6:IT-M) semitransparent devices achieved optimal PCE of 11.67% and AVT of 22.20%.

A lot of binary copolymers have been designed and synthesized for non-fullerene polymer solar cells (PSCs). However, some binary donor-acceptor copolymers exhibited unsatisfactory optical absorption and photovoltaic performance, which are based on 2D-conjugated bithienyl-benzodithiophene (BDTT) and fluorobenzotriazole. Herein, we employed random copolymerization approach to construct terpolymers (named as J28, J55, J82), which outperform binary copolymers in non-fullerene PSCs. Non-fullerene PSCs based on J55: ITIC (1.0:1.0) without any additive (DIO) demonstrate a VOC of 0.83 V, a JSC of 17.23 mA cm−2, a FF of 63.67% and a PCE of 9.19% (a PCE of 5.85% for J52:ITIC, 1.0:1.0; a PCE of 8.16% for J60:ITIC, 1.0:1.0). Semitransparent polymer solar cells (ST-PSCs) based on J55:ITIC showed a VOC of 0.84 V, a JSC of 15.60 mA cm−2, a FF of 51.19%, a PCE of 6.73% with an AVT of 22.06%. This work demonstrates that fluorobenzotriazole and BDTT with branched alkyl and branched alkylthio based terpolymers could have higher photovoltaic performance via random copolymer approach and also meet the balance of two key parameters of power conversion efficiencies and average visible transmittance in ST-PSCs.

Ternary polymer solar cells (PSCs) are one of the most promising high-efficiency photovoltaic devices with advantages of simple solution fabrication and single-junction structure. Herein, we fabricated ternary PSCs with PC71BM as the third component, and ester-polymer PFTzTT-3TC as donor and ITIC as host acceptor. So after treatment-annealing, ternary devices based on PFTzTT-3TC: ITIC: PC71BM (1:1:0.05) exhibited a prominently increased VOC of 0.93 V and PCE of 8.87%. The optimal devices (1:1:0.30) delivers a state of art FF of 71.76%, which is over 22% higher than the value of 58.40% in binary devices. Ternary semitransparent solar cells (1:1:0.25, 15 and 20 nm Ag as cathode) produced a PCE of 6.49% and 7.18% and an AVT of 11.91% and 9.29%, respectively. Our work demonstrated that ternary strategy is a promising solution to improve photovoltaic parameters simultaneously though rational selection of matched fullerene and non-fullerene acceptors.

With the increasing complexity of the modern electronic countermeasure environment, radar signal sorting faces serious challenges in ensuring effectiveness. At present, the conventional inter-pulse parameters or intra-pulse features are used, or the two directly form a vector to achieve signal sorting, but they all have certain problems. This paper proposes a radar signal sorting technology based on core cluster support vector clustering (CCSVC), which not only overcomes the existing technology or limited application scope, or computational complexity, or is not conducive to engineering implementation.

With the complexity of the radar system, radar signal sorting is facing an increasingly severe form. Therefore, the research on radar emitter signal sorting model and algorithm based on intentional modulation feature and clustering in the current stage has important theoretical and practical significance. This paper studies the meaning, research methods of intentional modulation features and clustering sorting method.

Radar signal sorting based on intra-pulse parameters is applied in complex electromagnetic environment well. This method provides a new basis and ideas for the sorting and identification of radiation source signals, and also a possible way to improve the current sorting ability of radiation source signals. This paper discusses several aspects from domain analysis, frequency-domain analysis, time–frequency analysis, wavelet analysis, atomic decomposition, high-order statistical analysis, and nonlinear dynamic analysis methods.

With the increasing complexity of radar waveform design, traditional radar signals such as fixed-frequency, jagged, and jitter are becoming less and less common in modern radar design, and complex repeat frequency patterns such as agile and random repeat frequency become the current radar. Therefore, the sorting algorithm based on PRI has been difficult to adapt to the radar signal sorting of complex systems. In addition, the PRI-based sorting algorithm also has the problems of slow speed and poor sorting effect. In contrast, multi-parameter-based sorting method could achieve better results.

The complexity and computational complexity of the radar receiver signal processing are mainly concentrated on the signal sorting process. The precondition of radar signal sorting is to extract signal features and then to select key features for sorting. This paper discusses several aspects from feature extraction technology and feature selection technology.

As an important part of electronic intelligence (ELINT) and electronic support measurement (ESM) systems, radar signal sorting directly affects the performance of electronic reconnaissance equipment and is a key technology for decision making. This paper discusses several clustering methods which could be used for radar signal sorting. The discussion includes artificial neural networks, classical clustering algorithm and its improvement, and support vector clustering.

Background Patients with ovarian cancer commonly have a poor prognosis, owing to its invasiveness and distant metastasis. Studies have found TM4SF1 participates in regulating tumor cell invasion and migration. Therefore, it is expected to become a target for anti-invasion and metastasis in ovarian cancer. Methods The expression of TM4SF1 in normal ovarian epithelial tissues, benign ovarian tumor tissues, primary foci of epithelial ovarian cancer and the matched lymph mode metastatic foci was detected using immunohistochemistry to analyze its association with prognosis. The expression of TM4SF1 in HO8910PM, SKOV3 was inhibited using RNAi, and the growth, proliferation, migration, invasion abilities of HO8910PM and SKOV3 cells and the growth of xenograft tumors in nude mice were examined. Results (1) The positive expression rate of TM4SF1 protein in epithelial ovarian cancer tissues (90.90%) was higher than that in benign ovarian tumor tissues (65.22%) and normal ovarian epithelial tissues (31.25%), and both differences were significant (P 0.05). (3) Silencing TM4SF1 expression did not affect growth, proliferation, or cell cycle distribution but inhibited the migration and invasion abilities of HO8910PM and SKOV3 cells. Silencing TM4SF1 expression inhibited the growth of xenograft tumors in nude mice. Conclusion TM4SF1 is a potential target for anti-invasion and metastasis in ovarian cancer.

The stability issue is still one of the main limitations of the commercialization of perovskite photovoltaics. The mixed cation FAx Cs1 -x PbI3 has shown great promise owing to its improved thermal and moisture stability. However, the study of FAx Cs1 -x PbI3 is concentrated on formamidine (FA)-rich perovskite, whereas cesium (Cs)-rich FAx Cs1 -x PbI3 perovskites are barely studied due to the inevitable phase separation when Cs > 30 mol%. Here, a Cs4 PbI6 -mediated method is developed to synthesize Cs-rich FAx Cs1 -x PbI3 perovskites. It is demonstrated that Cs4 PbI6 intermediate phase has a low Cs cation diffusion barrier and therefore offers a fast ion exchange with the preformed FA-rich perovskite phase to finally form the Cs-rich FAx Cs1 -x PbI3 perovskite. The results indicate that ≈15% alloying with organic FA cations can sufficiently stabilize the perovskite phase with excellent phase and UV-irradiation stability. The FA0.15 Cs0.85 PbI3 perovskite solar cells achieve a champion power conversion efficiency of 17.5%, showing the great potential of Cs-based perovskites for efficient and stable solar cells.

Radar signal sorting method based on traditional clustering algorithm takes on a high time complexity and has poor accuracy. Aimed at the problem, a new sorting method is researched based on improved cone cluster labelling (ICCL) method for SVC algorithm and grey correlation degree (GCD) index. The ICCL method relies on approximate coverings both in feature space and data space. By using ICCL the calculation of adjacency matrix is avoided. This method is interpreted in theory and is modified for lower complexity and high accuracy by handling the outliers. And a new cluster validity index, grey correlation degree (GCD) index, is proposed which assesses the compactness and separation of clusters using average grey relational degree. In this paper, the SVC sorting model is constructed to obtain the cluster division firstly with ICCL method. Secondly, grey correlation degree is designed to measure the similarity between clusters, and to verify the clustering validity. Thirdly, the clustering parameters are adjusted adaptively to achieve the best clusters division. Finally, clustering validity sorting experiments of interleaved pulse streams is implemented. The results show that this method can obtain better clustering results.

Coal of three kinds was burned in an oxygen-enriched atmosphere using a twin-fluidized bed solid circulation system under conditions of the Calcium Looping Process. This twin-fluidized bed system comprised a fast bed regenerator (calciner), into which fuel and oxygen-enriched gas were fed, and a bubbling bed absorber (carbonator), into which air was fed. Inert quartz sand was used as the bed material to evaluate the coal combustion behavior, including char transportation from regenerator to absorber and formation of CO and CO 2 there. First, the circulation rate and the residence time of solids in the regenerator (calciner) were measured to determine the suitable operation conditions. The effect of gas feed staging to the regenerator on the solid residence time was evaluated. By reducing the ratio of the primary gas feed rate to total gas feed rate to 0.5, average solid residence time of about 40 s was attained. Under this gas-feed condition, coal combustion experiments were conducted. Effects of volatile matter content of coal on CO and CO 2 formation in the absorber and NO x emissions from the regenerator were investigated. High-volatile matter coal was found to be favorable to reduce CO and CO 2 formation in the absorber, but conversion of the fuel-N to NO x of high-volatile matter coal was higher than that from low-volatile coal.

Coal of three kinds was burned in an oxygen-enriched atmosphere using two types of reactor both of which had the same fast fluidized bed for coal combustion. One was a dual-fluidized bed system (dual-FB), simulating Calcium Looping process comprised a fast fluidized bed regenerator and a bubbling bed carbonator. The other was a conventional single circulating fluidized bed combustor (single-CFBC). In both systems, coal combustion in oxygen-enriched atmosphere was carried out under regenerator temperature condition of Calcium Looping process. Inert quartz sand was used as the bed material to evaluate carbon consumption in the carbonator of dual-FB. Formation of NOx in the fast fluidized beds was measured for both reactors. For dual-FB, formation of CO and CO2 in the carbonator was also measured. High-volatile matter coal was found to be favorable to reduce CO and CO2 formation in the carbonator, but conversion of the fuel-N to NOx of high-volatile matter coal was higher than that from low-volatile coal. The emissions of NOx from single-CFBC were less than those from the regenerator of dual-FB under the same combustion condition. From the emissions of CO and CO2 from the carbonator, the decrease in char combustion in the regenerator of dual-FB was calculated. An empirical relationship between the conversion of fuel-N to NOx in the fast fluidized bed and the ratio of fixed carbon to volatile matter of the fuel was obtained.

Neurons establish interactions with target cells via elongation and guidance of axons, and the growth cone plays pivotal roles in this process. Cyclin-dependent kinase 5 (Cdk5) is a key regulator of nervous system development. Cdk5 regulates several significant events by phosphorylating substrates that are involved in neurogenesis, and previous studies of Cdk5 have typically focused on single substrates. Here, we took a new approach to investigate Cdk5 substrates using mass spectrometry and bioinformatics analyses. Axonal growth cones were isolated and analyzed by HPLC-MALDI-MS/MS. In total, 178,617 MS/MS spectra were detected. Candidates were analyzed by GPS 2.1 and Scansite 3, which predicted that 2,664 and 275 sites, respectively, were potential phosphorylation sites of Cdk5. There were 190 overlapped phosphorylation sites, corresponding to 89 proteins. Those proteins correlated with axonal functions were classified, and two of them were verified using a classic site-specific mutation strategy. This is the first study in which the phosphoproteome of axonal growth cones was identified. The systematic examination of Cdk5 substrates could provide a reference for further study of molecular mechanisms of axonal growth cones, and new insights into treatments of neuronal disorders.

Digital mapping is a core and basic course for students who are majoring in Surveying and Mapping Engineering. The traditional teaching model, which is limited by classroom size, credit hours, and many other factors, can barely meet the teaching demands of a modern classroom. The continuous optimization of mobile techniques and the mobile environment has been witnessed in recent years. Several mobile terminals have emerged, which strongly support the future of micro-learning of digital mapping. This study builds a mobile digital mapping teaching system to explore effective learning models for mobile terminals. Content analysis is combined with questionnaire survey to analyze the basic characteristics of learners, learning content, learning behavior, and learning effects. Results suggest that the WeChat official account admin platform plays a positive role in attracting learners, spreading micro-content, promoting personalized learning, and evaluating real-time learning effects. In summary, this study enriches research on mobile teaching and provides teachers with new perspectives in teaching digital mapping and other specialized courses to Surveying and Mapping Engineering majors.

Raf kinase inhibitor protein (RKIP) is a major negative mediator of the extracellular signal-related kinase (ERK)/mitogen-activated protein kinase (MAPK) pathway. The downregulation of RKIP is correlated with many cancers, but the mechanisms that underlie this downregulation and its roles in the nervous system remain unclear. Here, we demonstrate that RKIP is a substrate of cyclin-dependent kinase 5 (CDK5) in neurons and that the phosphorylation of RKIP at T42 causes the release of Raf-1. Moreover, T42 phosphorylation promotes the exposure and recognition of the target motif "KLYEQ" in the C-terminus of RKIP by chaperone Hsc70 and the subsequent degradation of RKIP via chaperone-mediated autophagy (CMA). Furthermore, in the brain sample of Parkinson's disease (PD) patients and in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine hydrochloride-induced and transgenic PD models, we demonstrate that CDK5-mediated phosphorylation and autophagy of RKIP are involved in the overactivation of the ERK/MAPK cascade, leading to S-phase reentry and neuronal loss. These findings provide evidence for the role of the CDK5/RKIP/ERK pathway in PD pathogenesis and suggest that this pathway may be a suitable therapeutic target in PD.

With the expanding of network teaching, more and more college students begin to addict to the internet, so the design of more scientific network teaching environment is given more attention nowadays. In network teaching, not only the teaching content should be emphasized, but also a safe network teaching environment should be provided. This paper investigates the relationship between the network teaching environment and internet addiction and a model of network teaching environment is designed to enhance the environment and improve the effectiveness of the network teaching.

The formation and development of web-based instruction has already become an important component of modern educational system. With the development of science and technology, web-based instruction has obtained a considerable enhancement. However, the role of web-based instruction still needs further exploration. The article elaborates, from the perspective of cognitive psychology, theoretical models to promote the web-based instruction types, methods and media all based on the psychology theory.