Consumer Research in Omnichannel Retailing: A Systematic Analysis

Lu LUO(Lu LUO),Yi Peng SHENG(Yi Peng SHENG) 한국유통과학회 2023 유통과학연구 Vol.21 No.7

Trajectory Planning for Energy Minimization of Industry Robotic Manipulators Using the Lagrange Interpolation Method

Lu-Ping Luo,Hanyang Universit,Rui-Jun Yan,Quan Yuan,Jing Wu,신규식,한창수 한국정밀공학회 2015 International Journal of Precision Engineering and Vol. No.

We propose to use Lagrange interpolation method to express each joint trajectory function to realize trajectory planning for energy minimization of industrial robotic manipulators. We give the position constraints to the industrial robotic manipulators and the stability of the industrial robotic manipulators should be satisfied. In order to avoid Runge’s phenomenon of Lagrange interpolation method, we use the Chebyshev interpolation points for our approach. Through derivation, the angular velocity functions and angular acceleration functions can be obtained. Lagrange interpolation method can satisfy position constraints, and ensure the smoothness of joint angular positions, velocities, accelerations, and joint torques. By taking these functions into the Performance Index (PI) of energy minimization, as well as the direct iteration method used for optimization of energy consumption, we can obtain the optimal trajectory for industrial robotic manipulators.

Research Progress in Applying Proteomics Technology to Explore Early Diagnosis Biomarkers of Breast Cancer, Lung Cancer and Ovarian Cancer

Luo, Lu,Dong, Li-You,Yan, Qi-Gui,Cao, San-Jie,Wen, Xin-Tian,Huang, Yong,Huang, Xiao-Bo,Wu, Rui,Ma, Xiao-Ping Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.20

According to the China tumor registry 2013 annual report, breast cancer, lung cancer, and ovarian cancer are three common cancers in China nowadays, with high mortality due to the absence of early diagnosis technology. However, proteomics has been widespreadly implanted into every field of life science and medicine as an important part of post-genomics era research. The development of theory and technology in proteomics has provided new ideas and research fields for cancer research. Proteomics can be used not only for elucidating the mechanisms of carcinogenesis focussing on whole proteins of the tissue or cell, but also seeking the biomarkers for diagnosis and therapy of cancer. In this review, we introduce proteomics principles, covering current technology used in exploring early diagnosis biomarkers of breast cancer, lung cancer and ovarian cancer.

Genetic Variant in CLPTM1L Confers Reduced Risk of Lung Cancer: a Replication Study in Chinese and a Meta-analysis

Luo, Xia,Lamsal, Laxmi Pangeni,Xu, Wen-Juan,Lu, Jie,Lu, Yan-Jun,Shen, Ying,Guan, Qing Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.21

Background: Rs31489 in the cleft lip and palate transmembrane1-like gene (CLPTM1L) has been identified to be associated with lung cancer through genome-wide association studies (GWAS). However, some recent replication studies yielded inconclusive results. Thus, we undertook this study to investigate the precise effect of rs31489 on lung cancer susceptibility. Materials and Methods: A hospital-based case-control study in 1,673 Chinese subjects (611 individuals with lung cancer and 1,062 controls) and a meta-analysis among 32,199 subjects (16,364 cases and 15,835 controls) were performed in this study. Results: In our case-control study, rs31489 was inversely associated with lung cancer (AC versus CC: OR=0.68, 95%CI=0.52-0.88; additive model: OR=0.68, 95%CI=0.54-0.85; dominant model: OR=0.65, 95%CI =0.51-0.84). Stratification analysis by smoking status showed a significant association and strong genetic effect in non-smokers but not in smokers. Our meta-analysis further confirmed the association, although with significant heterogeneity contributed by study design and source of controls, as shown by stratified analysis. Sensitive and cumulative analyses both indicated robust stability of our results. In addition, there was no observable publication bias in our meta-analysis. Conclusions: Overall, the findings from our replication study and meta-analysis demonstrated that CLPTM1L gene rs31489 is significantly associated with lung cancer.

Trajectory for Robotic Manipulators with Torque Minimization by Using Hermit Interpolation Method

Lu-Ping Luo,Chao Yuan,Kyoo-Sik Shin,Chang-Soo Han 제어로봇시스템학회 2013 제어로봇시스템학회 국제학술대회 논문집 Vol.2013 No.10

In this paper, we present a new method to get the trajectory of robotic manipulators with torque minimized. For the robotic manipulators for our research, just the position and velocity of the start and the final point are given. With given conditions and arbitrary chosen mutative points, we get the Hermite interpolation method used. Beside the start point and the final point, we will search for middle arbitrary chosen mutative points. Then the Hermite interpolation method is used to make sure the positions and velocities of the links satisfy the given conditions. With the change of position and velocity on the arbitrary chosen mutative points, with which taken into performance Index, the trajectory for torque minimization can be got.

Mammalian Mediator 19 Mediates H1299 Lung Adenocarcinoma Cell Clone Conformation, Growth, and Metastasis

Xu, Lu-Lu,Guo, Shu-Liang,Ma, Su-Ren,Luo, Yong-Ai Asian Pacific Journal of Cancer Prevention 2012 Asian Pacific journal of cancer prevention Vol.13 No.8

Mammalian mediator (MED) is a multi-protein coactivator that has been identified by several research goups. The involvement of the MED complex subunit 19 (MED 19) in the metastasis of lung adenocarcinoma cell line (H1299), which expresses the MED 19 subunit, was here investigated. When MED 19 expression was decreased by RNA interference H1299 cells demonstrated reduced clone formation, arrest in the S phase of the cell cycle, and lowered metastatic capacity. Thus, MED 19 appears to play important roles in the biological behavior of non-small cell lung carcinoma cells. These findings may be important for the development of novel lung carcinoma treatments.

Numerical Simulation on Energy Concentration and Release Process of Strain Rockburst

Ang Lu,Peng Yan,Wenbo Lu,Ming Chen,Gaohui Wang,Sheng Luo,Xiao Liu 대한토목학회 2021 KSCE JOURNAL OF CIVIL ENGINEERING Vol.25 No.10

Rockburst mechanism has been a hot topic in the stability analysis of underground carven excavation, and the accurate description of energy evolution process is very critical to rockburst prediction. To study the evolution process of rockburst, such as V-shaped rockburst pit, theoretical formula derivation and numerical simulation are adopted to research the dynamic response characteristics during the formation process of rockburst pits quantitatively. The results show that rockburst intensity distribution varies with failure depth. It can be divided into three zone: slow-increase, rapid-increase and slow-decrease. For a circular tunnel with radius R, the strain energy release rate and vibration response of surrounding rock increases gradually within (0 − 0.06) R; reaches the peak value around (0.06 − 0.1) R and drops to a balance beyond 0.1R. Due to the same law of them, the rockburst risk can be conveniently predicted by monitoring vibration of surrounding rock with a certain depth. This work is beneficial to provide a good reference for rockburst prediction.

라그랑지 보간법을 이용한 로봇 매니퓰레이터의 토크 최소화를 위한 궤적계획

라로평(Luo, Lu-Ping),황순웅(Hwang, Soon-Woong),한창수(Hahn Chang-Su) 한국산학기술학회 2015 한국산학기술학회논문지 Vol.16 No.4

본 논문에서는 로봇 매니퓰레이터의 토크 최소화를 위한 궤적계획을 위해 라그랑지 보간법을 이용한 Algorithm을 제안하였다. 이를 위해 로봇 매니퓰레이터의 위치에 대한 구속조건이 주어지고 안정성이 보장되어야 한다. 라그랑지 보간법 의 Runge’s 현상을 회피하기 위해 Chebyshev 보간점을 이용하여 시간 보간점을 설정하였고, 이에 대응하는 최적각도를 찾아 내어 라그랑지 보간법을 이용한 매끄러운 관절의 각도, 속도, 가속도 궤적을 얻을 수 있다. 로봇 매니퓰레이터의 토크 소비 최적화를 위한 성능지표를 선정하였으며, 계산된 궤적을 통해 이 성능지표가 최소값을 가지도록 반복 계산하는 과정을 거친 다. 이를 통해, 토크와 성능지표를 최소화 시키는 최적의 궤적을 얻을 수 있으며, 로봇 매니퓰레이터가 작업을 수행하기 위한 움직임의 안전성을 보장한다. This paper proposes an algorithm using Lagrange interpolation method to realize trajectory planning for torque minimization of robot manipulators. For the algorithm, position constraints of robot manipulators should be given and the stability of robot manipulators should be satisfied. In order to avoid Runge’s phenomenon, we set up time interpolation points using Chebyshev interpolation points. After that, we found suitable angle which corresponds to the points and then we got trajectories of joint's angle, velocity, acceleration using Lagrange interpolation method. We selected performance index for torque consumption optimization of robot manipulator. The method went through repetitive computation process to have minimum value of the performance index by calculated trajectory. Through the process, we could get optimized trajectory to minimize torque and performance index and guarantee safety of the motion for manipulator performance.

Artificial Intelligence in the Prediction of Gastrointestinal Stromal Tumors on Endoscopic Ultrasonography Images: Development, Validation and Comparison with Endosonographers

Lu Yi,Wu Jiachuan,Hu Minhui,Zhong Qinghua,Er Limian,Shi Huihui,Cheng Weihui,Chen Ke,Liu Yuan,Qiu Bingfeng,Xu Qiancheng,Lai Guangshun,Wang Yufeng,Luo Yuxuan,Mu Jinbao,Zhang Wenjie,Zhi Min,Sun Jiachen 거트앤리버 소화기연관학회협의회 2023 Gut and Liver Vol.17 No.6

Background/Aims: The accuracy of endosonographers in diagnosing gastric subepithelial lesions (SELs) using endoscopic ultrasonography (EUS) is influenced by experience and subjectivity. Artificial intelligence (AI) has achieved remarkable development in this field. This study aimed to develop an AI-based EUS diagnostic model for the diagnosis of SELs, and evaluated its efficacy with external validation. Methods: We developed the EUS-AI model with ResNeSt50 using EUS images from two hospitals to predict the histopathology of the gastric SELs originating from muscularis propria. The diagnostic performance of the model was also validated using EUS images obtained from four other hospitals. Results: A total of 2,057 images from 367 patients (375 SELs) were chosen to build the models, and 914 images from 106 patients (108 SELs) were chosen for external validation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the model for differentiating gastrointestinal stromal tumors (GISTs) and non-GISTs in the external validation sets by images were 82.01%, 68.22%, 86.77%, 59.86%, and 78.12%, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy in the external validation set by tumors were 83.75%, 71.43%, 89.33%, 60.61%, and 80.56%, respectively. The EUS-AI model showed better performance (especially specificity) than some endosonographers. The model helped improve the sensitivity, specificity, and accuracy of certain endosonographers. Conclusions: We developed an EUS-AI model to classify gastric SELs originating from muscularis propria into GISTs and non-GISTs with good accuracy. The model may help improve the diagnostic performance of endosonographers. Further work is required to develop a multi-modal EUS-AI system.

Taxonomy of fungal complex causing red-skin root of Panax ginseng in China

Lu, Xiao H.,Zhang, Xi M.,Jiao, Xiao L.,Hao, Jianjun J.,Zhang, Xue S.,Luo, Yi,Gao, Wei W. The Korean Society of Ginseng 2020 Journal of Ginseng Research Vol.44 No.3

Background: Red-skin root of Asian ginseng (Panax ginseng) significantly reduces the quality and limits the production of ginseng in China. The disease has long been thought to be a noninfectious physiological disease, except one report that proved it was an infectious disease. However, the causal agents have not been successfully determined. In the present study, we were to reveal the pathogens that cause red-skin disease. Methods: Ginseng roots with red-skin root symptoms were collected from commercial fields in Northeast China. Fungi were isolated from the lesion and identified based on morphological characters along with multilocus sequence analyses on internal transcription spacer, β-tubulin (tub2), histone H3 (his3), and translation elongation factor 1α (tef-1α). Pathogens were confirmed by inoculating the isolates in ginseng roots. Results: A total of 230 isolates were obtained from 209 disease samples. These isolates were classified into 12 species, including Dactylonectria sp., D. hordeicola, Fusarium acuminatum, F. avenaceum, F. solani, F. torulosum, Ilyonectria mors-panacis, I. robusta, Rhexocercosporidium panacis, and three novel species I. changbaiensis, I. communis, and I. qitaiheensis. Among them, I. communis, I. robusta, and F. solani had the highest isolation frequencies, being 36.1%, 20.9%, and 23.9%, respectively. All these species isolated were pathogenic to ginseng roots and caused red-skin root disease under appropriate condition. Conclusion: Fungal complex is the causal agent of red-skin root in P. ginseng.