Multi-Label Zero-Shot Learning with Structured Knowledge Graphs

In this paper, we propose a novel deep learning architecture for multi-label zero-shot learning (ML-ZSL), which is able to predict multiple unseen class labels for each input instance. Inspired by the way humans utilize semantic knowledge between objects of interests, we propose a framework that incorporates knowledge graphs for describing the relationships between multiple labels. Our model learns an information propagation mechanism from the semantic label space, which can be applied to model the interdependencies between seen and unseen class labels. With such investigation of structured knowledge graphs for visual reasoning, we show that our model can be applied for solving multi-label classification and ML-ZSL tasks. Compared to state-of-the-art approaches, comparable or improved performances can be achieved by our method.Comment: CVPR 201

An Output-Recurrent-Neural-Network-Based Iterative Learning Control for Unknown Nonlinear Dynamic Plants

We present a design method for iterative learning control system by using an output recurrent neural network (ORNN). Two ORNNs are employed to design the learning control structure. The first ORNN, which is called the output recurrent neural controller (ORNC), is used as an iterative learning controller to achieve the learning control objective. To guarantee the convergence of learning error, some information of plant sensitivity is required to design a suitable adaptive law for the ORNC. Hence, a second ORNN, which is called the output recurrent neural identifier (ORNI), is used as an identifier to provide the required information. All the weights of ORNC and ORNI will be tuned during the control iteration and identification process, respectively, in order to achieve a desired learning performance. The adaptive laws for the weights of ORNC and ORNI and the analysis of learning performances are determined via a Lyapunov like analysis. It is shown that the identification error will asymptotically converge to zero and repetitive output tracking error will asymptotically converge to zero except the initial resetting error

An Output-Recurrent-Neural-Network-Based Iterative Learning Control for Unknown Nonlinear Dynamic Plants

We present a design method for iterative learning control system by using an output recurrent neural network (ORNN). Two ORNNs are employed to design the learning control structure. The first ORNN, which is called the output recurrent neural controller (ORNC), is used as an iterative learning controller to achieve the learning control objective. To guarantee the convergence of learning error, some information of plant sensitivity is required to design a suitable adaptive law for the ORNC. Hence, a second ORNN, which is called the output recurrent neural identifier (ORNI), is used as an identifier to provide the required information. All the weights of ORNC and ORNI will be tuned during the control iteration and identification process, respectively, in order to achieve a desired learning performance. The adaptive laws for the weights of ORNC and ORNI and the analysis of learning performances are determined via a Lyapunov like analysis. It is shown that the identification error will asymptotically converge to zero and repetitive output tracking error will asymptotically converge to zero except the initial resetting error

Tropical Cyclones Disrupt the Relationship between Tree Height and Species Diversity: Comment

In a recent report on the patterns of tree species richness in eastern and western North America, Marks et al. (2016) claimed to have identified an operational indicator of environmental harshness (maximum tree height) and concluded that environmental stressors that limit tree height also act as ecological filters on species richness. Marks et al. (2017) attributed the positive association between species richness and maximum tree height to both the direct effects of environmental harshness on species richness and the indirect effects of environmental harshness on species richness as mediated by maximum tree height. This finding overlooked the fact that many environmental stressors such as cyclonic disturbance affect tree height and tree species diversity in different directions. In a study of elevational patterns in Taiwan, Chi et al. (2015) reported sharply contrasting relationships between tree species diversity and canopy tree height in sites that were subject to tropical cyclone disturbance vs. those that were not. In the mountains of southeastern China beyond the reach of tropical cyclones, both tree species richness and canopy tree height decreased with increasing elevation (Zheng et al. 2004, Chi et al. 2015), supporting the harshness hypothesis (Marks et al. 2016, 2017). In contrast, in Taiwan, where tropical cyclones occur annually, tree species richness decreased but maximum tree height increased with increasing elevation, the opposite of the predictions of the harshness hypothesis (Fig. 1). We attributed the contrasting elevational patterns and associations between tree diversity and canopy tree height in Taiwan to topographic mediation of tropical cyclone disturbance. The shorter tree stature in lower elevations was attributed to more severe tropical cyclone damage (Chi et al. 2015). Although tropical cyclones limit tree height, tree mortality is very low, possibly a result of both evolutional and ecological responses of these forest ecosystems through the long-term interaction between cyclones and the forest ecosystems (Lin et al. 2011). As an example, multiple category three tropical cyclones on the Saffir-Simpson scale (Simpson and Riehl 1981) caused \u3c2% tree mortality in low-elevation evergreen broadleaf forest in northeastern Taiwan in 1994, a record year of tropical cyclone frequency and intensity (Lin et al. 2011). However, taller trees were selectively killed and defoliation was severe, both of which contributed to the low stature of the forest even though the mean annual temperature (18°C) and precipitation (3800) mm are high (Lin et al. 2011). Cyclone disturbance limits vertical development of trees but does not lead to their elimination. Thus, more tropical cyclone disturbance at lower elevations overrides climatic controls on elevational patterns of tree height but does not change the elevational pattern of tree species richness. We suggest that there is an important difference between actual maximum tree height and potential maximum tree height in the presence of disturbance (e.g., tropical cyclone)

Curcumin-Induced Apoptosis in Human Hepatocellular Carcinoma J5 Cells: Critical Role of Ca+2-Dependent Pathway

The antitumor effects of curcumin, a natural biologically active compound extracted from rhizomes of Curcuma longa, have been studied in many cancer cell types including human hepatocellular carcinoma (HCC). Here, we investigated the effects of Ca2+ on curcumin-induced apoptosis in human HCC J5 cells. The abrogation of mitochondrial membrane potential (ΔΨm), the increase of reactive oxygen species (ROS) production, and calcium release were demonstrated with flow cytometry as early as 15 minutes after curcumin treatment. In addition, an increase level of cytochrome c in the cytoplasm which led to DNA fragmentation was observed. To verify the role of Ca2+ in curcumin-induced apoptosis, 1,2-bis(o-aminophenoxy)ethane-N,N,N′,N′-tetraacetic acid (BAPTA), an intracellular calcium chelator, was applied. Cell viability was increased, but ΔΨm, ROS production, activation of caspase 3, and cell death were decreased in J5 cells pretreated with BAPTA for 2 h followed by the treatment of 25 μM curcumin. These results suggest that the curcumin-induced apoptosis in human HCC J5 cells is via mitochondria-dependent pathway and is closely related to the level of intracellular accumulation of calcium

Peripheral Sympathectomy for Raynaud's Phenomenon: A Salvage Procedure

We retrospectively reviewed the effectiveness of peripheral sympathectomy for severe Raynaud's phenomenon. In this study, a total of 14 digits from six patients with chronic digital ischemic change were included. All patients had pain, ulcer, or gangrenous change in the affected digits and were unresponsive to pharmacologic or other nonsurgical therapies. In all cases, angiography showed multifocal arterial lesions, so microvascular reconstruction was unfeasible. Peripheral sympathectomy was performed as a salvage procedure to prevent digit amputation. The results were analyzed according to reduction of pain, healing of ulcers, and prevention of amputation. In 12 of the 14 digits, the ulcers healed and amputation was avoided. In the other two digits, the ulcers improved and progressive gangrene was limited. As a salvage procedure for Raynaud's phenomenon recalcitrant to conservative treatment, peripheral sympathectomy improves perfusion to ischemic digits and enables amputation to be avoided

Integration of Genetic Programming and TABU Search Mechanism for Automatic Detection of Magnetic Resonance Imaging in Cervical Spondylosis

Cervical spondylosis is a kind of degenerative disease which not only occurs in elder patients. The age distribution of patients is unfortunately decreasing gradually. Magnetic Resonance Imaging (MRI) is the best tool to confirm the cervical spondylosis severity but it requires radiologist to spend a lot of time for image check and interpretation. In this study, we proposed a prediction model to evaluate the cervical spine condition of patients by using MRI data. Furthermore, to ensure the computing efficiency of the proposed model, we adopted a heuristic programming, genetic programming (GP), to build the core of refereeing engine by combining the TABU search (TS) with the evolutionary GP. Finally, to validate the accuracy of the proposed model, we implemented experiments and compared our prediction results with radiologist’s diagnosis to the same MRI image. The experiment found that using clinical indicators to optimize the TABU list in GP+TABU got better fitness than the other two methods and the accuracy rate of our proposed model can achieve 88% on average. We expected the proposed model can help radiologists reduce the interpretation effort and improve the relationship between doctors and patients

Molecular population genetics and gene expression analysis of duplicated CBF genes of Arabidopsis thaliana

<p>Abstract</p> <p>Background</p> <p><it>CBF/DREB </it>duplicate genes are widely distributed in higher plants and encode transcriptional factors, or CBFs, which bind a DNA regulatory element and impart responsiveness to low temperatures and dehydration.</p> <p>Results</p> <p>We explored patterns of genetic variations of <it>CBF1, -2</it>, and -<it>3 </it>from 34 accessions of <it>Arabidopsis thaliana</it>. Molecular population genetic analyses of these genes indicated that <it>CBF2 </it>has much reduced nucleotide diversity in the transcriptional unit and promoter, suggesting that <it>CBF2 </it>has been subjected to a recent adaptive sweep, which agrees with reports of a regulatory protein of <it>CBF2</it>. Investigating the ratios of K_a/K_sbetween all paired <it>CBF </it>paralogus genes, high conservation of the AP2 domain was observed, and the major divergence of proteins was the result of relaxation in two regions within the transcriptional activation domain which was under positive selection after <it>CBF </it>duplication. With respect to the level of <it>CBF </it>gene expression, several mutated nucleotides in the promoters of <it>CBF3 </it>and <it>-1 </it>of specific ecotypes might be responsible for its consistently low expression.</p> <p>Conclusion</p> <p>We concluded from our data that important evolutionary changes in <it>CBF1, -2</it>, and -<it>3 </it>may have primarily occurred at the level of gene regulation as well as in protein function.</p