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| 1 | On a class of almost regular Landsberg metrics显示文摘There is a long existing 'unicorn' problem in Finsler geometry: whether or not any Landsberg metric is a Berwald metric? Some classes of metrics were studied in the past and no regular non-Berwaldian Landsberg metric was found. However, if the metric is almost regular(allowed to be singular in some directions),some non-Berwaldian Landsberg metrics were found in the past years. All of them are composed by Riemannian metrics and 1-forms. This motivates us to ?nd more almost regular non-Berwaldian Landsberg metrics in the class of general(α, β)-metrics. In this paper, we ?rst classify almost regular Landsberg general(α, β)-metrics into three cases and prove that those regular metrics must be Berwald metrics. By solving some nonlinear PDEs,some new almost regular Landsberg metrics are constructed which have not been described before. | Shasha Zhou Jiayue Wang Benling Li | 2019 | Science China Mathematics2019，62，5： | 2 |
| 2 | The role of chemotheraphy in brain metastases显示文摘 | | 2003 | Eur J Cancer2003，146，90： | 1 |
| 3 | Research on stock trend prediction method based on optimized random forest显示文摘As a complex hot problem in the financial field,stock trend forecasting uses a large amount of data and many related indicators;hence it is difficult to obtain sustainable and effective results only by relying on empirical analysis.Researchers in the field of machine learning have proved that random forest can form better judgements on this kind of problem,and it has an auxiliary role in the prediction of stock trend.This study uses historical trading data of four listed companies in the USA stock market,and the purpose of this study is to improve the performance of random forest model in medium-and long-term stock trend prediction.This study applies the exponential smoothing method to process the initial data,calculates the relevant technical indicators as the characteristics to be selected,and proposes the D-RF-RS method to optimize random forest.As the random forest is an ensemble learning model and is closely related to decision tree,D-RF-RS method uses a decision tree to screen the importance of features,and obtains the effective strong feature set of the model as input.Then,the parameter combination of the model is optimized through random parameter search.The experimental results show that the average accuracy of random forest is increased by 0.17 after the above process optimization,which is 0.18 higher than the average accuracy of light gradient boosting machine model.Combined with the performance of the ROC curve and Precision–Recall curve,the stability of the model is also guaranteed,which further demonstrates the advantages of random forest in medium-and long-term trend prediction of the stock market. | Lili Yin Benling Li Peng Li Rubo Zhang | 2023 | CAAI Transactions on Intelligence Technology2023，8，1： | 1 |
| 4 | Osmotic demyelination syndrome with a dysequilibrium syndrome:reversible findings显示文摘 | Angidere AM Benl S Erten Y | 1998 | Neuroradiology1998，40，： | 1 |
| 5 | Chamcterization of genetically transformed Sacerevisiae baker's yeasts able to metabolize melibiose显示文摘 | Gasent-Ramí fez J M Codón A C Benl tez T | 1995 | Appl Environ Microb1995，61，6： | 1 |
| 6 | Development and application of orgnic phase change Mixture in thermal storage gypsum wallboard显示文摘 | D Feldmna D Benl | 1995 | Solar Energy Materials & Solar Ceils1995，36，： | 1 |
| 7 | Hydroisomerization-cracking of n-octane on heteropolyacid H3PW12O40 supported on ZrO2,SiO2 and carbon effect of Pt incorporation on catalyst performance显示文摘 | Juan C Yori Javier M Grau Viviana M Benl'tez | 2005 | Appl Catal A2005，286，： | 1 |
| 8 | Direct determination of selenium in a wild fruit juice by electrothermal atomic absorption spectrometry显示文摘 | Yongming Liu Benling Gong Zhuanhe Li Yuli Xu Tiezheng Lin | 1996 | Talanta1996，，7： | 1 |
| 9 | On a class of projectively flat Finsler metrics with flag curvature K = 1显示文摘 | Bing Xu Benling Li | 2013 | Differential Geometry and its Applications2013，，： | 1 |
| 10 | Controllable persistent spin-polarized charge current in a Rashba ring显示文摘We theoretically predict the appearance of a persistent charge current in a Rashba ring with a normal and a ferromagnetic lead under no external bias.This charge current is the result of the breaking of the time inversion symmetry in the original persistent pure spin current induced by the Rashba spin-orbit coupling(RSOC) in the ring due to the existence of the ferromagnetic lead.With the Keldysh Green's function technique,we find that not only the magnitude and sign but also the spin polarization of the generated charge current is determined by the system parameters such as the magnetization direction of the ferromagnetic lead,the tunneling coefficient,the strength of the RSOC and the exchange energy of the ferromagnetic lead,which are all tunable in experiments,that is,a controllable persistent spin-polarized charge current can be obtained in such a device. | Feng Liang Benling Gao Jun Zhang Yu Gu | 2017 | Journal of Semiconductors2017，38，8： | 0 |
| 11 | The role of intestinal flora on tumorigenesis,progression,and the efficacy of PD-1/PD-L1 antibodies in colorectal cancer显示文摘Intestinal flora affects the maturation of the host immune system,serves as a biomarker and efficacy predictor in the immunotherapy of several cancers,and has an important role in the development of colorectal cancer(CRC).Anti-PD-1/PD-L1 antibodies have shown satisfactory results in MSI-H/d MMR CRC but performed poorly in patients with MSS/p MMR CRC.In recent years an increasing number of studies have shown that intestinal flora has an important impact on anti-PD-1/PD-L1 antibody efficacy in CRC patients.Preclinical and clinical evidence have suggested that anti-PD-1/PD-L1 antibody efficacy can be improved by altering the composition of the intestinal flora in CRC.Herein,we summarize the studies related to the influence of intestinal flora on anti-PD-1/PD-L1 antibody efficacy in CRC and discuss the potential underlying mechanism(s).We have focused on the impact of the intestinal flora on the efficacy and safety of anti-PD-1/PD-L1 antibodies in CRC and how to better utilize the intestinal flora as an adjuvant to improve the efficacy of anti-PD-1/PD-L1 antibodies.In addition,we have provided a basis for the potential of the intestinal flora as a new treatment modality and indicator for determining patient prognosis. | Sen Wang Benling Xu Yangyang Zhang Guangyu Chen Peng Zhao Quanli Gao Long Yuan | 2024 | Cancer Biology & Medicine2024，21，1： | 0 |
| 12 | Spectroelectrochemical Investigation on Neutral Red显示文摘Neutral Red can be used as an indicator, a stain reagent or a mediator compound in the studies of biological redox systems. No reports dealing with the electrode process of Neutral Red, especially, about its kinetics have been published. In this paper we report the determinations of formal reduction potentials, the number of electrons transferred, diffusion coefficient as well as the rate constant of heterogeneous electron | Shen Baoen, Zhang Ming, Tang Yinxuan and Li Benle (Department of Chemistry, Hangzhou University, Hangzhou) | 1992 | Chemical Research in Chinese Universities1992，8，1： | 0 |
| 13 | Dually flat general spherically symmetric Finsler metrics显示文摘Dually flat Finsler metrics arise from information geometry which has attracted some geometers and statisticians. In this paper, we study dually flat general spherically symmetric Finsler metrics which are defined by a Euclidean metric and two related 1-forms. We give the equivalent conditions for those metrics to be locally dually flat. By solving the equivalent equations, a group of new locally dually flat Finsler metrics is constructed. | Xiaoming Wang Wangfu Liu Benling Li | 2018 | Science China Mathematics2018，61，4： | 0 |
| 14 | Research on trend prediction of component stock in fuzzy time series based on deep forest显示文摘With the continuous development of machine learning and the increasing complexity of financial data analysis,it is more popular to use models in the field of machine learning to solve the hot and difficult problems in the financial industry.To improve the effectiveness of stock trend prediction and solve the problems in time series data processing,this paper combines the fuzzy affiliation function with stock-related technical indicators to obtain nominal data that can widely reflect the constituent stocks in the case of time series changes by analysing the S&P 500 index.Meanwhile,in order to optimise the current machine learning algorithm in which the setting and adjustment of hyperparameters rely too much on empirical knowledge,this paper combines the deep forest model to train the stock data separately.The experimental results show that(1)the accuracy of the extreme random forest and the accuracy of the multi-grain cascade forest are both higher than that of the gated recurrent unit(GRU)model when the un-fuzzy index-adjusted dataset is used as features for input,(2)the accuracy of the extreme random forest and the accuracy of the multigranular cascade forest are improved by using the fuzzy index-adjusted dataset as features for input,(3)the accuracy of the fuzzy index-adjusted dataset as features for inputting the extreme random forest is improved by 18.89% compared to that of the un-fuzzy index-adjusted dataset as features for inputting the extreme random forest and(4)the average accuracy of the fuzzy index-adjusted dataset as features for inputting multi-grain cascade forest increased by 5.67%. | Peng Li Hengwen Gu Lili Yin Benling Li | 2022 | CAAI Transactions on Intelligence Technology2022，7，4： | 0 |
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