项目驱动法在Linux操作系统课程实验教学中的应用策略

随着信息技术的快速发展,Linux操作系统在教育领域的应用日益广泛。本文探讨了项目驱动法在Linux操作系统课程实验教学中的应用策略,旨在通过实际项目提高学生的实践能力和创新能力。本文阐述了项目设计需紧贴课程目标与行业需求、项目难度应循序渐进、注重项目的实用性与创新性等原则;以Samba服务配置为例,展示了项目实践的具体步骤和评估反思方法。本文将项目驱动法系统地应用于Linux操作系统课程实验教学中提供了具体的实施策略和评估方法。

量化计算揭示出实验现象背后的细节

化学已不再是纯粹的实验科学,理论计算与化学实验可以从不同角度对化合物性能及化学变化过程进行研究,成为化学研究的一个重要分支。本文通过一例具体的苯胺CO_(2)功能化还原反应机理的计算研究,介绍了量化计算的基本方法和过程,通过对计算结果的分析,揭示了实验过程中很容易被忽视或者根本就发现不了的反应细节。

Channel Estimation with an Interpolation Trained Deep Neural Network

This paper proposes a deep learning-based channel estimation method for orthogonal frequency-division multiplexing (OFDM) systems. The existing OFDM receiver has low estimation accuracy when estimating channel state information (CSI) with fewer pilots. To tackle the problem, in this paper, a deep learning model is first trained by the interpolated channel frequency responses (CFRs) and then used to denoise the CFR estimated by least square (LS) estimation. The proposed deep neural network (DNN) can also be trained in a short time because it only learns the CFR and the network structure is simple. According to the simulation results, the performance of the DNN estimator can be compared with the minimum mean-square error (MMSE) estimator. Furthermore, the DNN approach is more robust than conventional methods when fewer pilots are used. In summary, deep learning is a promising tool for channel estimation in wireless communications.

Multi-Scale and Multi-Channel Networks for CSI Feedback in Massive MIMO System

In the frequency division duplex (FDD) mode of the massive MIMO system, the system needs to perform coding through channel state information (CSI) to obtain performance gains. However, the number of antennas of the base station has been greatly increased, resulting in a rapid increase in the overhead for the user terminal to feedback CSI to the base station. In this article, we propose a method based on multi-task CNN to achieve compression and reconstruction of channel state information through a multi-scale and multi-channel convolutional neural network. We also introduce a dynamic learning rate model to improve the accuracy of channel state information reconstruction. The simulation results show that compared with the original CsiNet and other work, the proposed CSI feedback network has better reconstruction performance.

Curing Behaviour of MUF Resin in the Presence of Less Desirable Wood Material

In order to investigate the effect of different wood species on the curing of MUF resin,DSC spectroscopic analysis and a new procedure are used, an important component in wood composites manufacturing. The MUF resin is synthesised with an initial weak acidic condition. The final molar ratios of F /( M+U) and M / U are 1. 37 and 0. 32,respectively. Samples are prepared by mixing MUF resin with wood flours from different wood species. The curing behaviour and transformation of chemical groups are analysed by DSC. The curing activation energy of MUF resin generally decreases when the resin is mixed with wood flours due to the influence of wood extracts. When the heat rate is 5 ℃ / min,the relationship between the peak temperature of the MUF resin and p H values or base buffer capacities is observed.

Comparison between Cystatin C and Traditional GFR Endogenous Markers

During the tests of glomerular filtration function,serum creatinine,urea and endogenous creatinine clearance rate are the most commonly used indicators,which possess many disadvantages.Currently,a large number of studies have been conducted on investigating new indicators reflecting changes in glomerular filtration rate.As a low-molecular weight protein,cystatin C is a member of cysteine protease inhibitor superfamily,which can be produced by all the nucleated cells in vivo with a stable generation rate.In the circulation process in vivo,cystatin C can only be removed via glomerular filtration,which is an ideal endogenous marker reflecting changes in glomerular filtration rate.Serum cystatin C concentration is superior to serum creatinine concentration in renal function tests.

User Grouping and Scheduling for Joint Spatial Division and Multiplexing in FDD Massive MIMO System

Massive multiple-input multiple-output (MIMO) is a key technology for the 5th Generation wireless communication systems. Joint spatial division and multiplexing (JSDM) method can reduce the cost of downlink training and feedback for CSIT of frequency-division duplexing (FDD) system. In this paper, we studied user grouping and user scheduling problems based on JSDM, and proposed an improved greedy user scheduling algorithm with lower complexity. Numerical results show that the user grouping and scheduling based on the proposed improved algorithm have much lower computational complexity while resulting in only a slight loss in system performance.

青藏高原多年冻土微生物残体碳的分布特征及其驱动因素

微生物残体碳是土壤稳定碳库的重要组成部分,对土壤有机碳(soil organic carbon,SOC)的贡献可达50%以上.然而,由于缺乏大尺度观测证据,目前学术界对多年冻土微生物残体碳分布特征及其驱动因素的认识十分有限.本研究基于野外样带调查和室内分析相结合的方法,揭示了青藏高原多年冻土微生物残体碳的空间分布特征,对比了冻土层与活动层微生物残体碳对SOC的贡献差异.在此基础上,结合气候、土壤变量和微生物属性测定,探究了多年冻土微生物残体碳含量空间变异的驱动因素.结果显示,多年冻土总微生物残体碳、真菌和细菌残体碳含量均呈现自研究区西部向东部递增的趋势.平均而言,冻土层总微生物残体碳含量为2741.0±815.3 mg/kg(平均值±标准误差),占SOC的比例为13.2%±1.1%;真菌残体碳的含量及其对总微生物残体碳的贡献均显著高于细菌.冻土层总微生物残体碳和真菌残体碳的含量与贡献均显著低于活动层;冻土层细菌残体碳含量显著低于活动层,但其对SOC的贡献与活动层无显著差异.结构方程模型分析的结果显示,多年冻土含水率和微生物的生物量是影响多年冻土微生物残体碳含量空间变异的直接因素,气候因素则起着间接作用.总体来讲,上述结果意味着微生物残体碳是多年冻土碳的重要来源,其变化可能会影响多年冻土碳循环与气候变暖之间的正反馈关系.

Electromagnetic responses on microstructures of duplex stainless steels based on 3D cellular and electromagnetic sensor finite element models

Microstructures determine mechanical properties of steels,but in actual steel product process it is difficult to accurately control the microstructure to meet the requirements.General microstructure characterization methods are time consuming and results are not rep-resentative for overall quality level as only a fraction of steel sample was selected to be examined.In this paper,a macro and micro coupled 3D model was developed for nondestructively characterization of steel microstructures.For electromagnetic signals analysis,the relative permeability value computed by the micro cellular model can be used in the macro electromagnetic sensor model.The effects of different microstructure components on the relative permeability of duplex stainless steel(grain size,phase fraction,and phase distribu-tion)were discussed.The output inductance of an electromagnetic sensor was determined by relative permeability values and can be val-idated experimentally.The findings indicate that the inductance value of an electromagnetic sensor at low frequency can distinguish dif-ferent microstructures.This method can be applied to real-time on-line characterize steel microstructures in process of steel rolling.

Changes in soil microbial community structure and function following degradation in a temperate grassland

Aims Grassland degradation represents a major challenge in the maintenance of grassland productivity.This process has dramatic impacts on energy flows and soil nutrient dynamics,thus directly or indirectly influencing soil microbes.Here,we aim to(i)examine changes in soil microbial composition,diversity and functionality in response to different levels of grassland degradation(i.e.non-degraded,moderately and severely degraded)in a temperate grassland in Inner Mongolia,and(ii)elucidate biotic and abiotic factors that are responsible for these changes.Methods The composition structure of soil microbial community was determined by high-throughput sequencing.The functionality of bacterial communities was examined using the tool of FAPROTAX,and functional guilds of fungal communities were quantified using the FUNGuild pipeline.Important Findings Grassland degradation significantly decreased soil bacterial diversity but it did not affect fungal diversity.Belowground biomass,soil organic carbon and total nitrogen were positively related to changes in diversity of bacterial community.Grassland degradation significantly increased the relative abundance of Chloroflexi(from 2.48%to 8.40%)and decreased Firmicutes(from 3.62%to 1.08%)of bacterial community.Degradation also significantly increased the relative abundance of Glomeromycota(from 0.17%to 1.53%)and decreased Basidiomycota(from 19.30%to 4.83%)of fungal community.The relative abundance of pathogenic fungi(Didymella and Fusarium)was decreased significantly by degradation.In addition,degradation had a significant impact on putative functionality of soil bacteria related to soil carbon and nitrogen cycling.Our results suggest that soil bacterial community is more sensitive than fungal community in response to degradation in the temperate grassland.

森林生态系统细根周转规律及影响因素

根系周转是陆地生态系统碳循环的关键过程,对研究土壤碳库变化及全球气候变化均具有重要意义。然而由于根系周转率的测量计算方法较多,不同方法得出的结果差异较大,且目前对全球区域尺度上森林生态系统根系周转的研究还不够充分,使得全球森林生态系统根系周转变化规律仍不清楚。该研究通过收集文献数据并统一周转率计算方法,对全球5种森林类型的细根周转空间格局进行整合,同时结合土壤理化性质和气候数据,得出影响森林生态系统细根周转的因子。结果表明,不同森林类型细根周转率存在显著差异,且随着纬度的升高逐渐降低;森林生态系统细根周转率与年平均温度和年平均降水量呈正相关;森林生态系统细根周转率与土壤有机碳含量呈正相关但与土壤pH值呈负相关。该研究为揭示森林生态系统细根周转规律及机制提供了科学依据。