33 research outputs found
Evaluation of optimal irrigation scheduling and groundwater recharge at representative sites in the North China Plain with SWAP model and field experiments
Full text linkCoupled effects of canal lining and multi-layered soil structure on canal seepage and soil water dynamics
Full text linkA More Objective Quantification of Micro-Expression Intensity through Facial Electromyography
No full textMicro-expressions are facial expressions that individuals reveal when trying to hide their genuine emotions. It has potential applications in areas such as lie detection and national security. It is generally believed that micro-expressions have three essential characteristics: short duration, low intensity, and local asymmetry. Most previous studies have investigated micro-expressions based on the characteristic of short duration. To our knowledge, no empirical studies have been conducted on the low-intensity characteristic. In this paper, we use facial EMG for the first time to study the characteristic of low intensity for micro-expression. In our experiment, micro-expressions were elicited from subjects and simultaneously collected their facial EMG through the secondgeneration micro-expression elicitation paradigm. We collected and annotated 33 macro-expressions and 48 micro-expressions. By comparing the two indicators of EMG :(1) the percentage of apex value in maximum voluntary contraction (MVC%) and (2) the area under EMG signal curve (integrated EMG, iEMG), we found that the MVC% and iEMG of micro-expression were significantly smaller than that of macro-expression. The result demonstrates that the intensity of micro-expression is significantly smaller than that of macro-expression.</p
Development of SSR Molecular Markers and Genetic Diversity Analysis of TPS Gene Family in <i>Chimonanthus praecox</i>
No full textTerpene synthase (TPS) plays a key role in the biosynthesis of terpenoids, which are the most important components of the volatile compounds of wintersweet (Chimonanthus praecox). In this study, 52 CpTPS genes were found in wintersweet which were divided into 5 subfamilies. We identified 146 SSRs in the CpTPS genes, and obtained 33 pairs of SSR primers with good polymorphism through amplification in 6 wintersweet samples. Then, these primers were amplified in 69 samples from China’s main wintersweet production areas. Through structural analysis, 69 samples were divided into 2 clusters, and were divided into 4 groups in a genetic cluster analysis, of which SH-33 and SW were separate groups. Through AMOVA analysis, it was found that the variation mainly occurred in the population, and that the gene flow between populations was Nm > 1, so it might lead to population differentiation. In other words, these findings provided useful information for the biosynthesis of terpenoids, the construction of a genetic linkage map, the detection of quantitative trait loci, marker-assisted selection and other aspects of wintersweet
Electromyography-Based Intentional-Deception Behavior Analysis in an Interactive Social Context: Statistical Analysis and Machine Learning
No full textLying is a common social behavior, and accurate lie detection is crucial in areas such as national security. However, existing lie detection techniques have certain limitations. Therefore, more accurate and reliable tools and methods are needed to meet the practical needs of lie detection. In this context, this study discovered the potential value of electromyography (EMG) as a lie detection indicator. Specifically, this study used EMG for statistical analysis and machine learning recognition analysis of the lying process in an interactive scenario of active lying. Furthermore, we compared the performance of two traditional machine learning models and one deep learning model for lie detection based on EMG signals. In particular, time-dimensional and time-frequency-dimensional EMG features were used to mine and lie related features. Statistical results showed that compared to truth-telling, people tend to suppress their facial expressions when preparing to lie. Some facial muscle movements that were not be successfully suppressed after lying may be crucial for detecting lies. Moreover, our study offers theoretical hypotheses for the occurrence of micro-expressions and the feature of upper-lower facial asymmetry. Besides the statistic analysis, the analysis results of machine learning also demonstrated demonstrate the potential of machine learning models for EMG-based intelligent lying process analysis, particularly the RUSBoosted tree. In addition, our experiment result also proved that focusing on specific facial muscles, such as Corrugator supercilii, could improve the accuracy and efficiency of intelligent algorithms. In summary, our research results provide more insights into the cognitive and facial muscle movement patterns involved in lying based on statistical analysis and machine learning.</p
A new terminal converging adaptive control for 6-degree-of-freedom parallel robotic manipulators with bounded control inputs
Get PDF© IMechE 2017. In this study, a new terminal converging adaptive control approach with bounded control inputs is developed for the 6-degree-of-freedom parallel robot manipulator. The non-smooth feedback control principle is combined with particular bounded functions to define both the control input and associated adaptive law. The Lyapunov method is used to present a stability analysis in order to prove that the error trajectories are semi-globally asymptotically stable. Numerical simulation results relating to a 6-degree-of-freedom parallel robot are presented to validate the effectiveness of the proposed approach and to compare the performance obtained with other candidate control schemes. It is shown that the proposed scheme achieves more rapid error convergence and exhibits improved robustness while guaranteeing that the control signal remains within known bounds
CAS(ME)<sup>3</sup>: A Third Generation Facial Spontaneous Micro-Expression Database with Depth Information and High Ecological Validity.
No full textMicro-expression (ME) is a significant non-verbal communication clue that reveals one person's genuine emotional state. The development of micro-expression analysis (MEA) has just gained attention in the last decade. However, the small sample size problem constrains the use of deep learning on MEA. Besides, ME samples distribute in six different databases, leading to database bias. Moreover, the ME database development is complicated. In this article, we introduce a large-scale spontaneous ME database: CAS(ME)3. The contribution of this article is summarized as follows: (1) CAS(ME)3 offers around 80 hours of videos with over 8,000,000 frames, including manually labeled 1,109 MEs and 3,490 macro-expressions. Such a large sample size allows effective MEA method validation while avoiding database bias. (2) Inspired by psychological experiments, CAS(ME)3 provides the depth information as an additional modality unprecedentedly, contributing to multi-modal MEA. (3) For the first time, CAS(ME)3 elicits ME with high ecological validity using the mock crime paradigm, along with physiological and voice signals, contributing to practical MEA. (4) Besides, CAS(ME)3 provides 1,508 unlabeled videos with more than 4,000,000 frames, i.e., a data platform for unsupervised MEA methods. (5) Finally, we demonstrate the effectiveness of depth information by the proposed depth flow algorithm and RGB-D information.</p
Kruppel-Like Factor 2 Regulates Dendritic Cell Activation in Patients with Acute Coronary Syndrome
Get PDFObjective: Dendritic cells (DCs) activation is important in atherosclerosis and coronary heart disease, but the mechanisms regulating activation of dendritic cells remain largely unclear. The aim of this study was to evaluate the effect of transcription factor Kruppel-like factor 2 (KLF2) in the proinflammatory activation of DCs in acute coronary syndrome. Methods and Results: In this study, the expression of CD80 and KLF2 was detected in DCs in normal health controls, patients with stable angina (SA), and acute coronary syndrome (ACS). Our study found that compared with normal control and SA, KLF2 expression in DCs is reduced in patients with ACS. Moreover, the surface expression of CD80 was increased in ACS. In vitro experiment, we found that ox-LDL could increase CD80 expression and decrease KLF2 expression. Furthermore, down-regulated KLF2 could in turn increase CD80 expression via NF-κB pathway. Conclusions: These observations identify KLF2 as a novel negative regulator of DC function and it may play an essential role in DC activation in ACS
