Optical Control of Cellular ATP Levels with a Photocaged Adenylate Kinase

We have developed a new tool for the optical control of cellular ATP concentrations with a photocaged adenylate kinase (Adk). The photocaged Adk is generated by substituting a catalytically essential lysine with a hydroxycoumarin-protected lysine through site-specific unnatural amino acid mutagenesis in both E. coli and mammalian cells. Caging of the critical lysine residue offers complete suppression of Adk's phosphotransferase activity and rapid restoration of its function both in vitro and in vivo upon optical stimulation. Light-activated Adk renders faster rescue of cell growth than chemically inducible expression of wild-type Adk in E. coli as well as rapid ATP depletion in mammalian cells. Thus, caging Adk provides a new tool for direct conditional perturbation of cellular ATP concentrations thereby enabling the investigation of ATP-coupled physiological events in temporally dynamic contexts.     

Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.     

基于密度聚类与SVM的非法广播信号识别研究

针对非法广播信号的危害,以及传统人工检测效率低的问题,提出一种基于密度聚类与SVM的信号识别模型。首先,采用标准欧式距离对特征信号进行提取;其次,以聚类样本为基础,采用SVM分类器对信号分类;最后,以青海广播电视局中波台整点时刻前后300帧的数据为样本,以静音信号作为评价指标,对信号进行识别。结果表明,在正常信号中加入非法信号后,频谱中有少量的静音信号,且SVM训练时间和识别正确率都要优于传统算法。     

Synthesis and characterization of novel hyperbranched fluorescent polymers that can be precisely used for metal ion detection and quantification

Four novel hyperbranched polymers with 4 or 5 ring-closed rhodamine units in each were achieved through RAFT polymerization followed by modification with rhodamine moieties. The solubility, thermostability, and photophysical properties of the polymers were studied. The polymers showed high selectivity and sensitivity to Fe³⁺ among various metal ions in CH₃CN/H₂O (75/25, v/v) and could signal Fe³⁺ through multichannels: emerging a new absorption around 558 nm, over 30 nm fluorescence redshift and significant fluorescence enhancement (including 33–37 folds in intensity and 8.3–12.8 folds in quantum yield), accompanied by visual and fluorescent color changes. The polymers could be applied in the analysis of Fe³⁺ in real water samples. © 2020 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48933.     

基于电润湿效应的自变焦补偿光学系统

变焦光学系统是照相机、摄像机等许多光学器件中的关键元件，实现变焦光学系统的微小型化及增大系统的变倍比是一个长期目标。研制了一种三液体自变焦补偿透镜，可在外加电压作用下实现自变焦补偿功能，因此该透镜元件本身可以作为一个简单的变焦光学系统。通过高斯光学理论分析及Zemax模拟仿真验证了该系统的自变焦补偿功能。结果表明，该系统焦距变化范围为378～424 mm，变倍比为1.217，达到了预期目标，对变焦光学系统的研究具有一定的参考价值。     

Younger and older users׳ recognition of virtual agent facial expressions

As technology advances, robots and virtual agents will be introduced into the home and healthcare settings to assist individuals, both young and old, with everyday living tasks. Understanding how users recognize an agent׳s social cues is therefore imperative, especially in social interactions. Facial expression, in particular, is one of the most common non-verbal cues used to display and communicate emotion in on-screen agents (Cassell et al., 2000). Age is important to consider because age-related differences in emotion recognition of human facial expression have been supported (Ruffman et al., 2008), with older adults showing a deficit for recognition of negative facial expressions. Previous work has shown that younger adults can effectively recognize facial emotions displayed by agents (Bartneck and Reichenbach, 2005, Courgeon et al., 2009, Courgeon et al., 2011, Breazeal, 2003); however, little research has compared in-depth younger and older adults’ ability to label a virtual agent׳s facial emotions, an import consideration because social agents will be required to interact with users of varying ages. If such age-related differences exist for recognition of virtual agent facial expressions, we aim to understand if those age-related differences are influenced by the intensity of the emotion, dynamic formation of emotion (i.e., a neutral expression developing into an expression of emotion through motion), or the type of virtual character differing by human-likeness. Study 1 investigated the relationship between age-related differences, the implication of dynamic formation of emotion, and the role of emotion intensity in emotion recognition of the facial expressions of a virtual agent (iCat). Study 2 examined age-related differences in recognition expressed by three types of virtual characters differing by human-likeness (non-humanoid iCat, synthetic human, and human). Study 2 also investigated the role of configural and featural processing as a possible explanation for age-related differences in emotion recognition. First, our findings show age-related differences in the recognition of emotions expressed by a virtual agent, with older adults showing lower recognition for the emotions of anger, disgust, fear, happiness, sadness, and neutral. These age-related difference might be explained by older adults having difficulty discriminating similarity in configural arrangement of facial features for certain emotions; for example, older adults often mislabeled the similar emotions of fear as surprise. Second, our results did not provide evidence for the dynamic formation improving emotion recognition; but, in general, the intensity of the emotion improved recognition. Lastly, we learned that emotion recognition, for older and younger adults, differed by character type, from best to worst: human, synthetic human, and then iCat. Our findings provide guidance for design, as well as the development of a framework of age-related differences in emotion recognition.     

Magneto-polaron induced intersubband optical transition in a wide band gap II–VI semiconductor quantum dot

Effects of LO-phonon contribution on the electronic and the optical properties are investigated in a Cd_0.8Zn_0.2Se/ZnSe quantum dot in the presence of magnetic field strength. The magneto-polaron induced hydrogenic binding energy as a function of dot radius in the wide band gap quantum dot is calculated. The oscillator strength and the spontaneous lifetime are studied taking into account the spatial confinement, magnetic field strength and the phonon contribution. Numerical calculations are carried out using variational formulism within the single band effective mass approximation. The optical properties are computed with the compact density matrix method. The magneto-polaron induced optical gain as a function of photon energy is observed. The results show that the optical telecommunication wavelength in the fiber optic communications can be achieved using CdSe/ZnSe semiconductors and it can be tuned with the proper applications of external perturbations.     

A hand gesture recognition technique for human–computer interaction

We propose an approach to recognize trajectory-based dynamic hand gestures in real time for human–computer interaction (HCI). We also introduce a fast learning mechanism that does not require extensive training data to teach gestures to the system. We use a six-degrees-of-freedom position tracker to collect trajectory data and represent gestures as an ordered sequence of directional movements in 2D. In the learning phase, sample gesture data is filtered and processed to create gesture recognizers, which are basically finite-state machine sequence recognizers. We achieve online gesture recognition by these recognizers without needing to specify gesture start and end positions. The results of the conducted user study show that the proposed method is very promising in terms of gesture detection and recognition performance (73% accuracy) in a stream of motion. Additionally, the assessment of the user attitude survey denotes that the gestural interface is very useful and satisfactory. One of the novel parts of the proposed approach is that it gives users the freedom to create gesture commands according to their preferences for selected tasks. Thus, the presented gesture recognition approach makes the HCI process more intuitive and user specific.