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Avian Research 2023年第4期14卷 663-670页

作者： Na Zhu Jing Shang Shuping Zhang Key Laboratory of Ecology and Environment in Minority Areas(National Ethnic Affairs Commission) Minzu University of ChinaBeijing 100081China College of Life and Environmental Sciences Minzu University of ChinaBeijing 100081China

Night lighting has been shown to affect wild animals.To date,the effects of night lighting on the metabolic homeostasis of birds that spend short time in urban environments remain unclear.Using model bird species Zebra Finch(Taeniopygia guttata),we investigated the effects of short-term night lighting on liver transcriptome,blood glucose,triglyceride,and thyroxine(T4 and T3)levels in birds exposed to two different night lighting duration periods(three days and six days).After three days of night lighting exposure,the expression of genes involved in fat synthesis in the liver was upregulated while the expression of genes involved in fatty acid oxidation and triglyceride decomposition was downregulated.There was also a reduction in blood triglyceride,glucose,and T3 concentrations.However,after six days of night lighting,the expression of genes associated with fatty acid decomposition and hyperglycemia in the liver was upregulated,while the expression of genes involved in fat synthesis was downregulated.Simultaneously,blood glucose levels and T3 concentration increased.These findings indicate that short-term exposure to night lighting can disrupt the lipid and glucose metabolism of small passerine birds,and longer stopovers in urban area with intense night lighting may cause birds to consume more lipid energy.

关键词： Birds Glucose Lipid Metabolism Night lighting short-term

利用长短期记忆网络LSTM对赤道太平洋海表面温度短期预报

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大气科学 2024年第2期48卷 745-754页

作者：张桃林鹏飞刘海龙郑伟鹏王鹏飞徐天亮李逸文刘娟陈铖中国科学院大气物理研究所大气科学与地球物理流体动力学数值模拟国家重点实验室北京100029 中国科学院大学地球与行星科学学院北京100049 哈尔滨工业大学电子与信息工程学院哈尔滨150001 北京应用气象研究所北京100029 西北工业大学航海学院西安710072

海表面温度作为海洋中一个最重要的变量,对全球气候、海洋生态等有很大的影响,因此十分有必要对海表面温度(SST)进行预报。深度学习具备高效的数据处理能力,但目前利用深度学习对整个赤道太平洋的SST短期预报及预报技巧的研究仍较少。... 详细信息

海表面温度作为海洋中一个最重要的变量,对全球气候、海洋生态等有很大的影响,因此十分有必要对海表面温度(SST)进行预报。深度学习具备高效的数据处理能力,但目前利用深度学习对整个赤道太平洋的SST短期预报及预报技巧的研究仍较少。本文基于最优插值海表面温度(OISST)的日平均SST数据,利用长短期记忆(LSTM)网络构建了未来10天赤道太平洋(10°S~10°N,120°E~80°W)SST的逐日预报模型。LSTM预报模型利用1982~2010年的观测数据进行训练,2011~2020年的观测数据作为初值进行预报和检验评估。结果表明:赤道太平洋东部地区预报均方根误差(RMSE)大于中、西部,东部预报第1天RMSE为0.6℃左右,而中、西部均小于0.3℃。在不同的年际变化位相,预报RMSE在拉尼娜出现时期最大,正常年份次之,厄尔尼诺时期最小,RMSE在拉尼娜时期比在厄尔尼诺时期可达20%。预报偏差整体表现为东正、西负。相关预报技巧上,中部最好,可预报天数基本为10天以上,赤道冷舌附近可预报天数为4~7天,赤道西边部分地区可预报天数为3天。预报模型在赤道太平洋东部地区各月份预报技巧普遍低于西部地区,相比较而言各区域10、11月份预报技巧最低。总的来说,基于LSTM构建的SST预报模型能很好地捕捉到SST在时序上的演变特征,在不同案例中预报表现良好。同时该预报模型依靠数据驱动,能迅速且较好地预报未来10天以内的日平均SST的短期变化。

关键词：海表面温度 LSTM (long short-term memory) 短期预报赤道太平洋

A mathematical model of synaptotagmin 7 revealing functional importance of short-term synaptic plasticity

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Neural Regeneration Research 2019年第4期14卷 621-631页

作者： Yao He Don Kulasiri Jingyi Liang Center for Advanced Computational Solutions (C-fACS) Lincoln UniversityChristchurch New Zealand

Synaptotagmin 7(Syt7), a presynaptic calcium sensor, has a significant role in the facilitation in shortterm synaptic plasticity: Syt7 knock out mice show a significant reduction in the facilitation. The functional importance of short-term synaptic plasticity such as facilitation is not well understood. In this study, we attempt to investigate the potential functional relationship between the short-term synaptic plasticity and postsynaptic response by developing a mathematical model that captures the responses of both wild-type and Syt7 knock-out mice. We then studied the model behaviours of wild-type and Syt7 knock-out mice in response to multiple input action potentials. These behaviors could establish functional importance of short-term plasticity in regulating the postsynaptic response and related synaptic properties. In agreement with previous modeling studies, we show that release sites are governed by non-uniform release probabilities of neurotransmitters. The structure of non-uniform release of neurotransmitters makes shortterm synaptic plasticity to act as a high-pass filter. We also propose that Syt7 may be a modulator for the long-term changes of postsynaptic response that helps to train the target frequency of the filter. We have developed a mathematical model of short-term plasticity which explains the experimental data.

关键词： synapse short-term plasticity short-term facilitation and depression mathematical model low-frequency stimulation high-frequency stimulation

Simulation and optimization approach for uncertainty-based short-term planning in open pit mines

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International Journal of Mining Science and Technology 2018年第2期28卷 153-166页

作者： Shiv Prakash Upadhyay Hooman Askari-Nasab Department of Civil and Environment Engineering School of Mining and Petroleum Engineering University of Alberta

Accuracy in predictions leads to better planning with a minimum of opportunity lost. In open pit mining,the complexity of operations, coupled with a highly uncertain and dynamic production environment,limit the accuracy of predictions and force a reactive planning approach to mitigate deviations from original plans. A simulation optimization framework/tool is presented in this paper to account for uncertainties in mining operations for robust short-term production planning and proactive decision making. This framework/tool uses a discrete event simulation model of mine operations, which interacts with a goalprogramming based mine operational optimization tool to develop an uncertainty based short-term schedule. Using scenario analysis, this framework allows the planner to make proactive decisions to achieve the mine's operational and long-term objectives. This paper details the development of simulation and optimization models and presents the implementation of the framework on an iron ore mine case study for verification through scenario analysis.

关键词： Scheduling Simulation optimization short-term planning Mine operational planning Truck-shovel allocation

Real-time anomaly detection for very short-term load forecasting

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Journal of Modern Power Systems and Clean Energy 2018年第2期6卷 235-243页

作者： Jian LUO Tao HONG Meng YUE School of Management Science and Engineering Dongbei University of Finance and Economics Department of Systems Engineering and Engineering Management University of North Carolina at Charlotte Brookhaven National Laboratory

Although the recent load information is critical to very short-term load forecasting(VSTLF), power companies often have difficulties in collecting the most recent load values accurately and timely for VSTLF applications.This paper tackles the problem of real-time anomaly detection in most recent load information used by VSTLF.This paper proposes a model-based anomaly detection method that consists of two components, a dynamic regression model and an adaptive anomaly threshold. The case study is developed using the data from ISO New England. This paper demonstrates that the proposed method significantly outperforms three other anomaly detection methods including two methods commonly used in the field and one state-of-the-art method used by a winning team of the Global Energy Forecasting Competition 2014. Finally, a general anomaly detection framework is proposed for the future research.

关键词： Real-time anomaly detection Very short-term load forecasting Multiple linear regression Data cleansing

short-term Outcomes of Laparoscopic vs.Open Hepatectomy for Primary Hepatocellular Carcinoma:A Prospective Comparative Study

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Current Medical Science 2019年第5期39卷 778-783页

作者： Li ZENG Min TIAN Si-si CHEN Yu-ting KE Li GENG Sheng-li YANG Lin YE Department of Hepatobiliary Surgery Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022China Union Hospital Tongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022China Cancer Center Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022China Department of Gastrointestinal Surgery Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022China

Laparoscopic hepatectomy(LH)is a newly developed technique associated with advantages as open surgery,but the study on outcome of liver function recovery was scarce.This preliminary report was aimed to comparatively assess the short?term outcomes between LH and open hepatectomy(OH)for primary hepatocellular carcinoma(PHC).This study retrospectively analyzed the demographic data and short-term outcomes of 81 patients who underwent LH or OH for the primary treatment of PHC between Oct.2017 and May 2018 at Union Hospital,Tongji Medical College,Huazhong University of Science and Technology(China).A total of 81 PHC patients who received major liver resection were enrolled.There were 38(47%)patients in the LH group and 43(53%)patients in the OH group.The operative time was significantly longer(373.53±173.38 vs.225.43±55.08,Pshorter in LH group than in OH group.The recovery of liver function was significantly faster in LH group,including higher serum albumin(P=0.002),higher ratio of albumin/globulin(P=0.029)and lower direct bilirubin(P=0.001)than in OH group.It is suggested that LH can serve as a fast recovery and cheap surgical procedure in the treatment of PHC,which is safe and feasible.

关键词： laparoscope open hepatectomy primary hepatocellular carcinoma short-term outcomes prospective comparative study

short-term power load forecasting using integrated methods based on long short-term memory

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Science China(Technological Sciences) 2020年第4期63卷 614-624页

作者： ZHANG WenJie QIN Jian MEI Feng FU JunJie DAI Bo YU WenWu State Grid Zhejiang Electric Power Corporation Information and Telecommunication Branch Hangzhou 310007China Jiangsu Provincial Key Laboratory of Networked Collective Intelligence School of MathematicsSoutheast UniversityNanjing 210096China

The development of power system informatization,the massive access of distributed power supply and electric vehicles have increased the complexity of power consumption in the distribution network,which puts forward higher requirements for the accuracy and stability of load forecasting.In this paper,an integrated network architecture which consists of the self-organized mapping,chaotic time series,intelligent optimization algorithm and long short-term memory(LSTM)is proposed to extend the load forecasting length,decrease artificial debugging,and improve the prediction precision for the short-term power load forecasting.Compared with LSTM prediction,the algorithm in this paper improves the prediction accuracy by 61.87%in terms of root mean square error(RMSE),and reduces the prediction error by 50%in the 40-fold forecast window under some circumstances.

关键词： long short-term memory chaotic time series intelligent optimization integrated network architecture

Volar locking distal radius plates show better short-term results than other treatment options: A prospective randomised controlled trial

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World Journal of Orthopedics 2016年第10期7卷 687-694页

作者： Herwig Drobetz Lidia Koval Patrick Weninger Ruth Luscombe Paula Jeffries Stefan Ehrendorfer Clare Heal Orthopaedic Department Mackay Base Hospital James Cook University School of Medicine and Dentistry Orthopaedic Department the Prince Charles Hospital Orthopaedic Hospital Speising Mathematical Science School Queensland University of Technology Orthopaedic Department Kantons Hospital Uri Department of General Practice Mackay Base Hospital James Cook University School of Medicine and Dentistry Anton Breinl Research Centre for Health Systems Strengthening James Cook University

AIM To compare the outcomes of displaced distal radius fractures treated with volar locking plates and with immediate postoperative mobilisation with the outcomes of these fractures treated with modalities that necessitate 6 wk wrist immobilisation.METHODS A prospective, randomised controlled single-centre trial was conducted with 56 patients who had a displaced radius fracture were randomised to treatment either with a volar locking plate(n = 29), or another treatment modality(n = 27; cast immobilisation with or without wires or external fixator). Outcomes were measured at 12 wk. Functional outcome scores measured were the Patient-Rated Wrist Evaluation(PRWE) Score; Disabilities of the Arm, Shoulder and Hand and activities of daily living(ADLs). Clinical outcomes were wrist range of motion and grip strength. Radiographic parameters were volar inclination and ulnar variance.RESULTS Patients in the volar locking plate group had significantly better PRWE scores, ADL scores, grip strength and range of extension at three months compared with the control group. All radiological parameters were significantly better in the volar locking plate group at 3 mo. CONCLUSION The present study suggests that volar locking plates produced significantly better functional and clinical outcomes at 3 mo compared with other treatment modalities. Anatomical reduction was significantly more likely to be preserved in the plating group. Level of evidence: Ⅱ.

关键词： Volar locking distal radius plate Prospective randomised controlled Postoperative mobilisation Distal radius fracture short-term outcome

Long short-term Memory Recurrent Neural Network-Based Acoustic Model Using Connectionist Temporal Classification on a Large-Scale Training Corpus

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China Communications 2017年第9期14卷 23-31页

作者： Donghyun Lee Minkyu Lim Hosung Park Yoseb Kang Jeong-Sik Park Gil-Jin Jang Ji-Hwan Kim Department of Computer Science and Engineering Sogang University Department of Information and Communication Engineering Yeungnam University School of Electronics Engineering Kyungpook National University

A Long short-term Memory(LSTM) Recurrent Neural Network(RNN) has driven tremendous improvements on an acoustic model based on Gaussian Mixture Model(GMM). However, these models based on a hybrid method require a forced aligned Hidden Markov Model(HMM) state sequence obtained from the GMM-based acoustic model. Therefore, it requires a long computation time for training both the GMM-based acoustic model and a deep learning-based acoustic model. In order to solve this problem, an acoustic model using CTC algorithm is proposed. CTC algorithm does not require the GMM-based acoustic model because it does not use the forced aligned HMM state sequence. However, previous works on a LSTM RNN-based acoustic model using CTC used a small-scale training corpus. In this paper, the LSTM RNN-based acoustic model using CTC is trained on a large-scale training corpus and its performance is evaluated. The implemented acoustic model has a performance of 6.18% and 15.01% in terms of Word Error Rate(WER) for clean speech and noisy speech, respectively. This is similar to a performance of the acoustic model based on the hybrid method.

关键词： acoustic model connectionisttemporal classification large-scale trainingcorpus long short-term memory recurrentneural network

short-term Dynamic Radar Quantitative Precipitation Estimation Based on Wavelet Transform and Support Vector Machine

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Journal of Meteorological Research 2020年第2期34卷 413-426页

作者： Changjiang ZHANG Huiyuan WANG Jing ZENG Leiming MA Li GUAN College of Physics and Information Engineering Zhejiang Normal UniversityJinhua 321004 Shanghai Meteorological Center Shanghai 200030

Currently,Doppler weather radar in China is generally used for quantitative precipitation estimation(QPE)based on the Z–R relationship.However,the estimation error for mixed precipitation is very large.In order to improve the accuracy of radar QPE,we propose a dynamic radar QPE algorithm with a 6-min interval that uses the reflectivity data of Doppler radar Z9002 in the Shanghai Qingpu District and the precipitation data at automatic weather stations(AWSs)in East China.Considering the time dependence and abrupt changes of precipitation,the data during the previous 30-min period were selected as the training data.To reduce the complexity of radar QPE,we transformed the weather data into the wavelet domain by means of the stationary wavelet transform(SWT)in order to extract high and low-frequency reflectivity and precipitation information.Using the wavelet coefficients,we constructed a support vector machine(SVM)at all scales to estimate the wavelet coefficient of precipitation.Ultimately,via inverse wavelet transformation,we obtained the estimated rainfall.By comparing the results of the proposed method(SWTSVM)with those of Z=300×R1.4,linear regression(LR),and SVM,we determined that the root mean square error(RMSE)of the SWT-SVM method was 0.54 mm per 6 min and the average Threat Score(TS)could exceed 40%with the exception of the downpour category,thus remaining at a high level.Generally speaking,the SWT-SVM method can effectively improve the accuracy of radar QPE and provide an auxiliary reference for actual meteorological operational forecasting.

关键词： short-term dynamic radar quantitative precipitation estimation stationary wavelet transform(SWT) support vector machine(SVM) Z-R relationship Threat Score