高校知识产权管理实践与探索——以重庆大学为例

知识产权管理工作是推动高校科技创新能力建设的重要部分。文中以重庆大学为例,通过对知识产权管理建设情况及近5年来专利申请、获权和转化情况的分析,发现目前存在知识产权的相关制度不完善,知识产权管理队伍亟待充实,专利申请的质量有待提高,科技成果孵化和市场化机制不健全,成果转化率低,实施推进力度有待加强等一系列的问题。为了提高知识产权运用水平和能力,学校实施完善科技成果转移转化制度,优化横向项目经费的管理与使用,简化科技成果转化的流程审批和优化知识产权管理模式,大力促进成果产业化等相应的改革举措。通过重庆大学的实践与探索,为高校知识产权管理工作提出了几点建议,包括开展知识产权教育,培养知识产权管理人才,强化知识产权价值导向,加强知识产权保护力度,健全激励评价机制和大力实施成果转化等等。

CFSv2模式对春季逐月南极涛动预测效能及成因分析

系统评估了美国第二代气候预测系统(CFSv2)对1983~2019年北半球春季逐月南极涛动(AAO)的预测效能及可能成因。结果表明,CFSv2模式对3月、4月和5月AAO空间模态预测效能较好,但是耦合模式仅对3月的AAO年际变化具有较好的预测能力,对4月和5月AAO年际变化的预测能力较差。热带中东太平洋和澳大利亚以东太平洋海温异常有可能是3月AAO年际变化的可预测性来源。一方面,3月厄尔尼诺—南方涛动(ENSO)与AAO之间关系显著,而4、5月两者之间关系减弱。3月ENSO激发PSA(Pacific–South American)波列传播到南太平洋上,通过影响南太平洋海温异常以及低层气旋性环流异常影响3月AAO的年际变化。另一方面,3月澳大利亚以东太平洋海温异常在副热带急流核心区域激发活跃的Rossby波列,该波列由澳大利亚东部向东南频散到南太平洋中高纬地区,造成该地区位势高度异常,使得副热带地区30°S西风减弱,南半球高纬60°S西风加强,进而影响AAO的变化。CFSv2对3月AAO的预测效能高于4月和5月的主要原因是CFSv2模式能够很好再现3月AAO与ENSO、澳大利亚以东海温之间的关系及其影响机制。

Feature extraction of partial discharge in low-temperature composite insulation based on VMD-MSE-IF

Low-temperature composite insulation is commonly applied in high-temperature super-conducting apparatus while partial discharge(PD)is found to be an important indicator to reveal insulation statues.In order to extract feature parameters of PD signals more effectively,a method combined variational mode decomposition with multi-scale entropy and image feature is proposed.Based on the simulated test platform,original and noisy signals of three typical PD defects were obtained and decomposed.Accordingly,relative moments and grayscale co-occurrence matrix were employed for feature extraction by K-modal component diagram.Afterwards,new PD feature vectors were obtained by dimension reduction.Finally,effectiveness of different feature extraction methods was evaluated by pattern recognition based on support vector machine and K-nearest neighbour.Result shows that the proposed feature extraction method has a higher recognition rate by comparison and is robust in processing noisy signals.

Multi-Scale Blind Image Quality Predictor Based on Pyramidal Convolution

Traditional image quality assessment methods use the hand-crafted features to predict the image quality score,which cannot perform well in many scenes.Since deep learning promotes the development of many computer vision tasks,many IQA methods start to utilize the deep convolutional neural networks(CNN)for IQA task.In this paper,a CNN-based multi-scale blind image quality predictor is proposed to extract more effectivity multi-scale distortion features through the pyramidal convolution,which consists of two tasks:A distortion recognition task and a quality regression task.For the first task,image distortion type is obtained by the fully connected layer.For the second task,the image quality score is predicted during the distortion recognition progress.Experimental results on three famous IQA datasets show that the proposed method has better performance than the previous traditional algorithms for quality prediction and distortion recognition.

Media Access with Spatial Reuse for Cooperative Spectrum Sensing

The increasing interest for wireless communication services and scarcity of radio spectrum resources have created the need for a more flexible and efficient usage of the radio frequency bands. Cognitive Radio (CR) emerges as an important trend for a solution to this problem. Spectrum sensing is a crucial function in a CR system. Cooperative spectrum sensing can overcome fading and shadowing effects, and hence increase the reliability of primary user detection. In this paper we consider a system model of a dedicated detect-andforward wireless sensor network (DetF WSN) for cooperative spectrum sensing with k-out-of-n decision fusion in the presence of reporting channels errors. Using this model we consider the design of a spatial reuse media access control (MAC) protocol based on TDMA/OFDMA to resolve conflicts and conserve resources for intra-WSN communication. The influence of the MAC protocol on spectrum sensing performance of the WSN is a key consideration. Two design approaches, using greedy and adaptive simulated annealing (ASA) algorithms, are considered in detail. Performance results assuming a grid network in a Rician fading environment are presented for the two design approaches.

Growth of Ag/g-C_(3)N_(4) nanocomposites on nickel foam to enhance photocatalytic degradation of formaldehyde under visible light

Formaldehyde is a pollutant that significantly affects the indoor air quality.However,conventional remediation approaches can be challenging to deal with low-concentration formaldehyde in an indoor environment.In this study,Photocatalysts of Ag/graphitic carbon nitride(g-C_(3)N_(4))/Ni with 3D reticulated coral structure were prepared by thermal polymerization and liquid phase photo-deposition,using nickel foam(NF)as the carrier.Experiments demonstrated that when the Ag concentration was 3%,and the relative humidity was 60%,the Ni/Ag/g-C_(3)N_(4)showed the maximum degradation rate of formaldehyde at 90.19%under visible light irradiation,and the formaldehyde concentration after degradation was lower than the Hygienic standard stated by the Chinese Government.The porous structure of Ni/Ag/g-C_(3)N_(4)and the formation of Schottky junctions promoted the Adsorption efficiency and degradation of formaldehyde,while the nickel foam carrier effectively promoted the desorption of degradation products.Meanwhile,the degradation rate was only reduced by3.4%after 16 recycles,the three-dimensional porous structure extended the lifetime of the photocatalyst.This study provides a new strategy for the degradation of indoor formaldehyde at low concentrations.

上前牙复合牙外伤的多学科治疗1例

目的:本文通过汇报1例多颗上前牙复合牙外伤的多学科综合治疗及1年随访复查病例,以期为牙外伤的综合诊治提供参考。诊疗经过:女性患者,21岁,因外伤致多颗上前牙脱出及折断,口腔医师通过牙再植及复位固定、根管治疗、改良冠延长术、断冠粘接术、桩核冠修复术等术式,对其进行多学科综合治疗。结果:术后1年复查,上前牙全冠修复密合,龈缘位置稳定,牙龈无黑三角。结论:通过多学科综合诊疗复合牙外伤可实现较为理想的治疗效果,从而最大限度地保存天然牙。