Deep learning algorithms have been widely used in computer vision,natural language processing and other fields.However,due to the ever-increasing scale of the deep learning model,the requirements for storage and compu...Deep learning algorithms have been widely used in computer vision,natural language processing and other fields.However,due to the ever-increasing scale of the deep learning model,the requirements for storage and computing performance are getting higher and higher,and the processors based on the von Neumann architecture have gradually exposed significant shortcomings such as consumption and long latency.In order to alleviate this problem,large-scale processing systems are shifting from a traditional computing-centric model to a data-centric model.A near-memory computing array architecture based on the shared buffer is proposed in this paper to improve system performance,which supports instructions with the characteristics of store-calculation integration,reducing the data movement between the processor and main memory.Through data reuse,the processing speed of the algorithm is further improved.The proposed architecture is verified and tested through the parallel realization of the convolutional neural network(CNN)algorithm.The experimental results show that at the frequency of 110 MHz,the calculation speed of a single convolution operation is increased by 66.64%on average compared with the CNN architecture that performs parallel calculations on field programmable gate array(FPGA).The processing speed of the whole convolution layer is improved by 8.81%compared with the reconfigurable array processor that does not support near-memory computing.展开更多
橡胶树棒孢霉落叶病(Corynespora leaf fall disease,CLFD)是全球主要植胶国最为严重的叶部病害之一,可造成严重的产量和经济损失,而抗病种质鉴选与创制利用是该病最为有效的防治策略。本研究对云研277-5×IAN 873、RRIC103×热...橡胶树棒孢霉落叶病(Corynespora leaf fall disease,CLFD)是全球主要植胶国最为严重的叶部病害之一,可造成严重的产量和经济损失,而抗病种质鉴选与创制利用是该病最为有效的防治策略。本研究对云研277-5×IAN 873、RRIC103×热研8-79和云研277-5×热垦525三个杂交组合的821份F_(1)代群体进行了抗棒孢霉落叶病的评价,明确了F_(1)代群体的抗病性水平,并从符合正态分布的2个杂交组合中筛选出32份候选F_(1)代单株进行芽接,再分别利用3个亚型的多主棒孢病菌和2种评价方法对候选F_(1)代无性系种苗进行抗病性复筛,最终获得5份抗病性较好的F_(1)代新种质。通过对5份抗病新种质防御酶活性的测定,以及抗病相关基因表达特性的分析,进一步证实了5份抗病新种质与多主棒孢病菌在侵染过程中的互作关系,明确了其在病原菌接种不同时间段的差异表达特征。本研究为橡胶树棒孢霉落叶病抗病性早期鉴选、抗病种质培育与创制利用提供了很好的种质材料和理论支撑。展开更多
目的以阳性药物为对照,评价格隆溴铵预防新斯的明诱导心率减慢的有效性和安全性。方法择期行全身麻醉非心脏手术的患者,中心化随机分组方法分为试验组(123例)和对照组(124例)。手术结束时,试验组给予格隆溴铵0.008 mg/kg+新斯的明0.04 m...目的以阳性药物为对照,评价格隆溴铵预防新斯的明诱导心率减慢的有效性和安全性。方法择期行全身麻醉非心脏手术的患者,中心化随机分组方法分为试验组(123例)和对照组(124例)。手术结束时,试验组给予格隆溴铵0.008 mg/kg+新斯的明0.04 mg/kg,对照组给予阿托品0.016 mg/kg+新斯的明0.04 mg/kg,推注时间1 min,用于拮抗肌肉松弛(肌松)药残留作用。比较给药后15 min内心率与基线心率差值的时间曲线下面积(area under the time ceurve,AUC)、每分钟心率的实测值、每分钟心率与基线比较的变化值,给药后阿托品补救治疗使用率和剂量,术后24 h内不良事件。结果试验组给药后15 min内心率较基线心率变化值的AUC小于对照组,差异有统计学意义(P<0.05);各时间点心率的实测值变化幅度小于对照组;试验组心率维持在基线水平的时间长于对照组,试验组心率变化的速度小于对照组(P<0.05)。两组患者阿托品补救治疗使用率和剂量差异均无统计学意义(P>0.05)。两组患者的不良反应发生率差异无统计学意义(P>0.05)。结论格隆溴铵与阿托品均可安全地用于预防非去极化肌松药拮抗剂新斯的明诱导的心率减慢,格隆溴铵更有利于患者的心率维持稳定。展开更多
基金Supported by the National Natural Science Foundation of China(No.61802304,61834005,61772417,61602377)the Shaanxi Province KeyR&D Plan(No.2021GY-029)。
文摘Deep learning algorithms have been widely used in computer vision,natural language processing and other fields.However,due to the ever-increasing scale of the deep learning model,the requirements for storage and computing performance are getting higher and higher,and the processors based on the von Neumann architecture have gradually exposed significant shortcomings such as consumption and long latency.In order to alleviate this problem,large-scale processing systems are shifting from a traditional computing-centric model to a data-centric model.A near-memory computing array architecture based on the shared buffer is proposed in this paper to improve system performance,which supports instructions with the characteristics of store-calculation integration,reducing the data movement between the processor and main memory.Through data reuse,the processing speed of the algorithm is further improved.The proposed architecture is verified and tested through the parallel realization of the convolutional neural network(CNN)algorithm.The experimental results show that at the frequency of 110 MHz,the calculation speed of a single convolution operation is increased by 66.64%on average compared with the CNN architecture that performs parallel calculations on field programmable gate array(FPGA).The processing speed of the whole convolution layer is improved by 8.81%compared with the reconfigurable array processor that does not support near-memory computing.
文摘橡胶树棒孢霉落叶病(Corynespora leaf fall disease,CLFD)是全球主要植胶国最为严重的叶部病害之一,可造成严重的产量和经济损失,而抗病种质鉴选与创制利用是该病最为有效的防治策略。本研究对云研277-5×IAN 873、RRIC103×热研8-79和云研277-5×热垦525三个杂交组合的821份F_(1)代群体进行了抗棒孢霉落叶病的评价,明确了F_(1)代群体的抗病性水平,并从符合正态分布的2个杂交组合中筛选出32份候选F_(1)代单株进行芽接,再分别利用3个亚型的多主棒孢病菌和2种评价方法对候选F_(1)代无性系种苗进行抗病性复筛,最终获得5份抗病性较好的F_(1)代新种质。通过对5份抗病新种质防御酶活性的测定,以及抗病相关基因表达特性的分析,进一步证实了5份抗病新种质与多主棒孢病菌在侵染过程中的互作关系,明确了其在病原菌接种不同时间段的差异表达特征。本研究为橡胶树棒孢霉落叶病抗病性早期鉴选、抗病种质培育与创制利用提供了很好的种质材料和理论支撑。
文摘目的本研究通过列线图构建普通人群罹患重度阻塞性睡眠呼吸暂停(obstructive sleep apnea,OSA)风险的预测模型,探究重度OSA的独立危险因素,指导临床早期诊断和治疗。方法回顾性纳入1656名患者,并按7∶3将其随机分为训练集与验证集。根据呼吸暂停低通气指数>30次/h将患者分为重度OSA与非重度OSA组。用最小绝对收缩、选择算子(the least absolute shrinkage and selection operator,Lasso)和逻辑回归(logistic regression,LR)对所有备选预测因子进行进一步筛选,基于LR建立重度OSA患者的预测模型,在验证集中对列线图模型进行验证,使用C指数、校准曲线和决策曲线分析(Decision Curve Analysis,DCA)评价列线图的区分能力、校准性和临床有效性。此外,我们将该模型与临床上广泛使用的问卷,包括STOP-Bang、柏林问卷通过受试者工作曲线进行了比较。结果通过单因素及多因素Logistic回归分析和Lasso Logistic回归确定吸烟、憋气病史、BMI、腰围、打鼾病史、Epworth嗜睡量表(Epworth sleepiness scale,ESS)作为纳入列线图的预测因子。该模型曲线下面积(area under the curve,AUC)=0.795(95%CI:0.769~0.820),Hosmer-Lemeshow检验提示模型校准良好(χ2=3.942,P=0.862)。DCA曲线显示,该模型对患者是有益的,当阈值概率>18%时,该模型对患者的净获益优于柏林问卷或STOP-Bang量表。临床影响曲线(Clinical Impact Curve,CIC)分析显示了该预测模型的临床有效率,当阈值概率大于82%预测评分概率值时,预测模型判定为重度OSA高风险人群与实际罹患重度OSA人群高度匹配,证实该预测模型临床有效率较高。结论相较于临床常用量表,本研究建立的模型在预测重度OSA方面具有更好的识别能力,可应用于普通人群的OSA早期筛查,有助于及早识别重度OSA,保护患者免受OSA的严重后果,减轻社会负担。
文摘目的以阳性药物为对照,评价格隆溴铵预防新斯的明诱导心率减慢的有效性和安全性。方法择期行全身麻醉非心脏手术的患者,中心化随机分组方法分为试验组(123例)和对照组(124例)。手术结束时,试验组给予格隆溴铵0.008 mg/kg+新斯的明0.04 mg/kg,对照组给予阿托品0.016 mg/kg+新斯的明0.04 mg/kg,推注时间1 min,用于拮抗肌肉松弛(肌松)药残留作用。比较给药后15 min内心率与基线心率差值的时间曲线下面积(area under the time ceurve,AUC)、每分钟心率的实测值、每分钟心率与基线比较的变化值,给药后阿托品补救治疗使用率和剂量,术后24 h内不良事件。结果试验组给药后15 min内心率较基线心率变化值的AUC小于对照组,差异有统计学意义(P<0.05);各时间点心率的实测值变化幅度小于对照组;试验组心率维持在基线水平的时间长于对照组,试验组心率变化的速度小于对照组(P<0.05)。两组患者阿托品补救治疗使用率和剂量差异均无统计学意义(P>0.05)。两组患者的不良反应发生率差异无统计学意义(P>0.05)。结论格隆溴铵与阿托品均可安全地用于预防非去极化肌松药拮抗剂新斯的明诱导的心率减慢,格隆溴铵更有利于患者的心率维持稳定。
