LRC渐进协作教学体系在眼科培训中的设计与实践

目的:以提升进行住院医师规范化培训(住培)的眼科医生临床诊疗思维能力为导向,建立LRC渐进协作教学体系(LRC Stepwise Collaborative Learning Model)。方法:2023年7月—2023年12月,以26名进行眼科住培的医生为试验组的研究对象,采用小讲课(Lecture)、教学查房(Rounds)及病例讨论(Case discussion)的LRC渐进协作教学体系,通过定量分析方法评估教学效果。结果:实施LRC渐进协作教学模式后,住培医生平均成绩由培训前的50.00(40,50)分提高至培训后的90.00(80,100)分,差异具有统计学意义(P<0.001)。问卷调查满分5分,小讲课、教学查房和病例讨论三种教学形式的满意度满分比例分别为92.3%(24/26),84.6%(22/26)、76.9%(20/26),三种教学形式的满意评分分别为5.00(5.00,5.00)、5.00(5.00,5.00)、5.00(4.75,5.00)分。结论:LRC渐进协作教学体系作为住培教学新体系,得到眼科住培医生的认可,促进临床诊疗思维的整体提升,有助于岗位胜任力的培养,为未来教学模式的设计与实施提供了重要参考。

LRCRaft:支持节点数据快速恢复的共识协议

在支持纠删码的分布式存储系统中,最常用的编码是RS(Reed-Solomon)码.对于一个RS(k,m)编码条带,常见的配置是一个节点仅存储条带中的一个分片,这导致在节点出现故障的情况下,对其存储分片的恢复需要跨多个节点读取分片并重新编码生成恢复分片,容易造成系统网络拥塞.在需要恢复大量数据的场合,系统在恢复期间会处于较长时间的脆弱期,容错能力和吞吐量下降、读写时延升高时有发生.LRCRaft是一个基于LRC(local reconstruction code)的改进Raft共识协议,通过在Raft中引入LRC码、动态日志增补、状态机删减和分片版本一致性等机制,降低了Raft的读写时延,缩短了节点故障恢复时间.实验结果表明,相较于Raft,LRCRaft在不同恢复模式中恢复一个单节点故障数据时,恢复用时有着49.25%–74.97%的减少.

Efficient unequal error protection for online fountain codes

In this paper,an efficient unequal error protection(UEP)scheme for online fountain codes is proposed.In the buildup phase,the traversing-selection strategy is proposed to select the most important symbols(MIS).Then,in the completion phase,the weighted-selection strategy is applied to provide low overhead.The performance of the proposed scheme is analyzed and compared with the existing UEP online fountain scheme.Simulation results show that in terms of MIS and the least important symbols(LIS),when the bit error ratio is 10-4,the proposed scheme can achieve 85%and 31.58%overhead reduction,respectively.

CodeScore-R:用于评估代码合成功能准确性的自动化鲁棒指标

评估指标在代码合成领域中至关重要.常用的代码评估指标可以分为3种类型:基于匹配、基于语义和基于执行.其中,基于执行的Pass@k指标通过执行测试用例,能够准确判断预测代码的功能准确性.然而,该指标的计算需要大量开销,因此亟需设计一种自动化评估指标,在无需测试用例时仍可评估预测代码的功能准确性.此外,好的评估指标应当具有鲁棒性,即预测代码发生微小改变时,评估指标仍能保持其准确性.为此,提出了一种基于UniXcoder和对比学习的自动化鲁棒指标CodeScore-R,用于评估代码合成的功能准确性. CodeScore-R采用草图化处理、语法等价转换和变异测试等技术手段,有效减轻了标识符、语法结构和运算符对评估结果的干扰.实验结果表明,在Java和Python语言上的代码生成和迁移任务中,CodeScore-R的表现优于其他无需测试用例的评估指标,且更接近Pass@k指标,并具有更强的鲁棒性.

Improved Belief Propagation Decoder for LDPC-CRC-Polar Codes with Bit-Freezing

Though belief propagation bit-flip(BPBF)decoding improves the error correction performance of polar codes,it uses the exhaustive flips method to achieve the error correction performance of CA-SCL decoding,thus resulting in high decoding complexity and latency.To alleviate this issue,we incorporate the LDPC-CRC-Polar coding scheme with BPBF and propose an improved belief propagation decoder for LDPC-CRC-Polar codes with bit-freezing(LDPCCRC-Polar codes BPBFz).The proposed LDPCCRC-Polar codes BPBFz employs the LDPC code to ensure the reliability of the flipping set,i.e.,critical set(CS),and dynamically update it.The modified CS is further utilized for the identification of error-prone bits.The proposed LDPC-CRC-Polar codes BPBFz obtains remarkable error correction performance and is comparable to that of the CA-SCL(L=16)decoder under medium-to-high signal-to-noise ratio(SNR)regions.It gains up to 1.2dB and 0.9dB at a fixed BLER=10-4compared with BP and BPBF(CS-1),respectively.In addition,the proposed LDPC-CRC-Polar codes BPBFz has lower decoding latency compared with CA-SCL and BPBF,i.e.,it is 15 times faster than CA-SCL(L=16)at high SNR regions.

Doped low-density parity-check codes

In this paper,we propose a doping approach to lower the error floor of Low-Density Parity-Check(LDPC)codes.The doping component is a short block code in which the information bits are selected from the coded bits of the dominant trapping sets of the LDPC code.Accordingly,an algorithm for selecting the information bits of the short code is proposed,and a specific two-stage decoding algorithm is presented.Simulation results demonstrate that the proposed doped LDPC code achieves up to 2.0 dB gain compared with the original LDPC code at a frame error rate of 10^(-6)Furthermore,the proposed design can lower the error floor of original LDPC Codes.

A free monoid containing all prefix codes

In this paper,we exhibit a free monoid containing all prefix codes in connection with the sets of i-th powers of primitive words for all i≥2.This extends two results given by Shyr and Tsai in 1998 at the same time.

Blind Recognition of Non-Binary LDPC Codes Based on Ant Colony Optimization

This paper introduces a novel blind recognition of non-binary low-density parity-check(LDPC)codes without a candidate set,using ant colony optimization(ACO)algorithm over additive white Gaussian noise(AWGN)channels.Specifically,the scheme that effectively combines the ACO algorithm and the non-binary elements over finite fields is proposed.Furthermore,an improved,simplified elitist ACO algorithm based on soft decision reliability is introduced to recognize the parity-check matrix over noisy channels.Simulation results show that the recognition rate continuously increases with an increased signalto-noise ratio(SNR)over the AWGN channel.

Quantized Decoders that Maximize Mutual Information for Polar Codes

In this paper,we innovatively associate the mutual information with the frame error rate(FER)performance and propose novel quantized decoders for polar codes.Based on the optimal quantizer of binary-input discrete memoryless channels(BDMCs),the proposed decoders quantize the virtual subchannels of polar codes to maximize mutual information(MMI)between source bits and quantized symbols.The nested structure of polar codes ensures that the MMI quantization can be implemented stage by stage.Simulation results show that the proposed MMI decoders with 4 quantization bits outperform the existing nonuniform quantized decoders that minimize mean-squared error(MMSE)with 4 quantization bits,and yield even better performance than uniform MMI quantized decoders with 5 quantization bits.Furthermore,the proposed 5-bit quantized MMI decoders approach the floating-point decoders with negligible performance loss.

Application of maximum rank distance codes in designing of STBC-OFDM system for next-generation wireless communications

Space-Time Block Coded(STBC)Orthogonal Frequency Division Multiplexing(OFDM)satisfies higher data-rate requirements while maintaining signal quality in a multipath fading channel.However,conventional STBCs,including Orthogonal STBCs(OSTBCs),Non-Orthogonal(NOSTBCs),and Quasi-Orthogonal STBCs(QOSTBCs),do not provide both maximal diversity order and unity code rate simultaneously for more than two transmit antennas.This paper targets this problem and applies Maximum Rank Distance(MRD)codes in designing STBCOFDM systems.By following the direct-matrix construction method,we can construct binary extended finite field MRD-STBCs for any number of transmitting antennas.Work uses MRD-STBCs built over Phase-Shift Keying(PSK)modulation to develop an MRD-based STBC-OFDM system.The MRD-based STBC-OFDM system sacrifices minor error performance compared to traditional OSTBC-OFDM but shows improved results against NOSTBC and QOSTBC-OFDM.It also provides 25%higher data-rates than OSTBC-OFDM in configurations that use more than two transmit antennas.The tradeoffs are minor increases in computational complexity and processing delays.

Decoding topological XYZ^(2) codes with reinforcement learning based on attention mechanisms

Quantum error correction, a technique that relies on the principle of redundancy to encode logical information into additional qubits to better protect the system from noise, is necessary to design a viable quantum computer. For this new topological stabilizer code-XYZ^(2) code defined on the cellular lattice, it is implemented on a hexagonal lattice of qubits and it encodes the logical qubits with the help of stabilizer measurements of weight six and weight two. However topological stabilizer codes in cellular lattice quantum systems suffer from the detrimental effects of noise due to interaction with the environment. Several decoding approaches have been proposed to address this problem. Here, we propose the use of a state-attention based reinforcement learning decoder to decode XYZ^(2) codes, which enables the decoder to more accurately focus on the information related to the current decoding position, and the error correction accuracy of our reinforcement learning decoder model under the optimisation conditions can reach 83.27% under the depolarizing noise model, and we have measured thresholds of 0.18856 and 0.19043 for XYZ^(2) codes at code spacing of 3–7 and 7–11, respectively. our study provides directions and ideas for applications of decoding schemes combining reinforcement learning attention mechanisms to other topological quantum error-correcting codes.

Recurrent neural network decoding of rotated surface codes based on distributed strategy

Quantum error correction is a crucial technology for realizing quantum computers.These computers achieve faulttolerant quantum computing by detecting and correcting errors using decoding algorithms.Quantum error correction using neural network-based machine learning methods is a promising approach that is adapted to physical systems without the need to build noise models.In this paper,we use a distributed decoding strategy,which effectively alleviates the problem of exponential growth of the training set required for neural networks as the code distance of quantum error-correcting codes increases.Our decoding algorithm is based on renormalization group decoding and recurrent neural network decoder.The recurrent neural network is trained through the ResNet architecture to improve its decoding accuracy.Then we test the decoding performance of our distributed strategy decoder,recurrent neural network decoder,and the classic minimum weight perfect matching(MWPM)decoder for rotated surface codes with different code distances under the circuit noise model,the thresholds of these three decoders are about 0.0052,0.0051,and 0.0049,respectively.Our results demonstrate that the distributed strategy decoder outperforms the other two decoders,achieving approximately a 5%improvement in decoding efficiency compared to the MWPM decoder and approximately a 2%improvement compared to the recurrent neural network decoder.

Improved Segmented Belief Propagation List Decoding for Polar Codes with Bit-Flipping

Belief propagation list(BPL) decoding for polar codes has attracted more attention due to its inherent parallel nature. However, a large gap still exists with CRC-aided SCL(CA-SCL) decoding.In this work, an improved segmented belief propagation list decoding based on bit flipping(SBPL-BF) is proposed. On the one hand, the proposed algorithm makes use of the cooperative characteristic in BPL decoding such that the codeword is decoded in different BP decoders. Based on this characteristic, the unreliable bits for flipping could be split into multiple subblocks and could be flipped in different decoders simultaneously. On the other hand, a more flexible and effective processing strategy for the priori information of the unfrozen bits that do not need to be flipped is designed to improve the decoding convergence. In addition, this is the first proposal in BPL decoding which jointly optimizes the bit flipping of the information bits and the code bits. In particular, for bit flipping of the code bits, a H-matrix aided bit-flipping algorithm is designed to enhance the accuracy in identifying erroneous code bits. The simulation results show that the proposed algorithm significantly improves the errorcorrection performance of BPL decoding for medium and long codes. It is more than 0.25 d B better than the state-of-the-art BPL decoding at a block error rate(BLER) of 10^(-5), and outperforms CA-SCL decoding in the low signal-to-noise(SNR) region for(1024, 0.5)polar codes.

Polar codes based OFDM-PLC systems in the presence of impulsive noise

Power line communication(PLC)has the potential to become the preferred technique for providing broadband communication to homes and offices with advantage of eliminating the need for new wiring infrastructure and reducing the cost.But it suffers from the impulsive noise because it introduces significant time variance into the power line channel.In this paper,a polar codes based orthogonal frequency division multiplexing(OFDM)PLC system is proposed to deal with the impulsive noise and thereby improve the transmission performance.Firstly,the impulsive noise is modelled with a multi-damped sine function by analyzing the time behavior of impulse events.Then the polar codes are used to combat the impulsive noise of PLC channel,and a low complexity bit-flipping decoding method based on CRC-aided successive cancellation list(CA-SCL)decoding algorithm is proposed.Simulations evaluate the proposed decoding algorithm and the results validate the suggested polar codes based OFDM-PLC scheme which can improve the BER performance of PLC with impulsive interference.

外泌体来源非编码RNA对骨关节炎微环境的作用及临床应用进展

背景:骨关节炎是一种常见的关节退行性疾病,其发生发展的病因学机制尚不清楚。早期骨关节炎的及时诊治十分重要,目前尚无确切有效的方法。外泌体来源广泛,其中包含非编码RNA(Non-coding RNAs,ncRNAs),如微小RNAs、环状RNAs和长链非编码RNAs。外泌体ncRNAs可直接从原始细胞递送至邻近或远程细胞,通过细胞间通讯调节细胞活性,在重塑骨关节微环境中具有重要的调控作用。目的:总结外泌体来源ncRNAs对骨关节炎关节内微环境的干预作用,以及在临床应用中取得的进展,阐明其在骨关节炎诊治方面的潜力。方法:以“exosomes,non-coding RNA,osteoarthritis,application,signal pathway,synovial fluid,cartilage cells,cartilage matrix,subchondral bone,mechanism”为检索词在PubMed数据库中进行检索,最终纳入66篇相关文献进行综述分析。结果与结论:①外泌体来源ncRNAs在骨关节炎的发病过程中对关节内微环境具有重要调控作用,主要体现在外泌体ncRNAs调控关节内炎症反应、软骨细胞及软骨基质的退化,软骨下骨重塑和细胞间通讯。②外泌体中的ncRNAs可以作为骨关节炎的生物标志物,帮助骨关节炎的早期诊断和监测疾病进展与预后。③外泌体ncRNAs可作为骨关节炎的治疗靶点,外泌体携带miRNAs递送到关节的软骨细胞及软骨基质,发挥调控作用。④外泌体ncRNAs可以通过调控基因表达、促进细胞间通讯,提高软骨组织工程的效果,修复或再生受损软骨。⑤未来研究者应继续发掘外泌体来源ncRNAs对骨关节炎的干预机制,并可结合最新软骨组织工程的研究成果应用到临床之中,这将有效帮助解决骨关节炎患者的病痛。

LRC数字电桥检测茶叶品质的研究

介绍了采用仪器进行客观、快速、正确测定茶叶品质的方法。包括测试仪器选择、传感器设计、品质数学模型的建立和测定方法。试验结果表明，采用ＬＲＣ数字电桥，对以电容为主要依据的多项电特性参数值的测定，能检测茶叶的综合品质，正确判别率达９４％以上。

一种规则变量节点度LT Codes编码方案

LT Codes差错平台(Erasure Floor)由变量节点的最小度决定,规则变量节点度LT Codes能够最大化变量节点的最小度,从而降低LT Codes的差错平台.该文提出一种新的规则变量节点度LT Codes编码方法,该编码方法省去了现有方法中对变量节点度值查找表的排序操作,降低了现有方案的编码复杂度;通过对度分布的修正增加低度校验节点,使得规则变量节点度LT Codes解码瀑布区域(雪崩区域)提前.仿真结果表明该文方法与现有方法相比有效减少了编码时间,降低了成功解码所需的平均传输开销,加快了误符号率收敛速度.

基于SPIHT图象压缩编码的Turbo codes编码

针对信源与信道编码的特点 ,提出了结合SPIHT(setpartitioninginhierarchicaltrees)算法和改进的TurboCodes的信源与信道联合编码方案 .这一方案充分考虑了SPIHT算法和TurboCodes的特性 ,根据信源编码后数据在重建时的重要程度 ,进行不同等纠错保护的信道编码 .实验表明 ,论文的方法能够使误码率与码长达到一个较好的平衡 。

一种改进的Turbo codes译码方法

Turbo码是一种目前研究比较多的纠错码,译码端采用了基于软判决信息输入/输出的反馈迭代结构,译码的迭代是其具有优越纠错性能的关键,也是造成其时延的问题所在,该文提出一种自适应选择迭代次数的方法,实验表明该方法能够在译码结果收敛时自动停止迭代,避免大量无谓的计算,同时保证译码的准确性。

基于修正LRC的响应分组法求解等效静力风荷载

对计算背景等效静力风荷载的传统LRC法进行修正,提出用修正LRC方法直接计算大跨结构的风致峰值响应,以避免求解大跨屋盖等效荷载多阶共振分量的繁琐过程。共振分量部分在背景等效风荷载中得到补偿,从而直接计算包含背景和共振分量的动力分量;补偿的方法是给背景分量的每个元素乘上一个待定的修正系数,该系数由数值方法来确定。基于修正LRC方法,提出了对目标等效响应的分组原则,即根据各组等效静力风荷载在其他响应上的等效精度来确定分组的标准,然后采用响应分组的思路求解等效静力风荷载。该方法可用于计算大跨结构的多个目标峰值响应,克服了传统方法仅能等效单个响应的缺陷。