The locations of the fiducial facial landmark points around facial components and facial contour capture the rigid and non-rigid facial deformations due to head movements and facial expressions. They ...are hence important for various facial analysis tasks. Many facial landmark detection algorithms have been developed to automatically detect those key points over the years, and in this paper, we perform an extensive review of them. We classify the facial landmark detection algorithms into three major categories: holistic methods, Constrained Local Model (CLM) methods, and the regression-based methods. They differ in the ways to utilize the facial appearance and shape information. The holistic methods explicitly build models to represent the global facial appearance and shape information. The CLMs explicitly leverage the global shape model but build the local appearance models. The regression based methods implicitly capture facial shape and appearance information. For algorithms within each category, we discuss their underlying theories as well as their differences. We also compare their performances on both controlled and in the wild benchmark datasets, under varying facial expressions, head poses, and occlusion. Based on the evaluations, we point out their respective strengths and weaknesses. There is also a separate section to review the latest deep learning based algorithms. The survey also includes a listing of the benchmark databases and existing software. Finally, we identify future research directions, including combining methods in different categories to leverage their respective strengths to solve landmark detection “in-the-wild”.
•The COVID-19 pandemic has significant impacts on global financial markets.•Substantial increases of volatility are found in global markets due to the outbreak.•Global stock markets linkages display ...clear different patterns before and after the pandemic announcement.•Policy responses may create further uncertainties in the global financial markets.
The rapid spread of coronavirus (COVID-19) has dramatic impacts on financial markets all over the world. It has created an unprecedented level of risk, causing investors to suffer significant loses in a very short period of time. This paper aims to map the general patterns of country-specific risks and systemic risks in the global financial markets. It also analyses the potential consequence of policy interventions, such as the US’ decision to implement a zero-percent interest rate and unlimited quantitative easing (QE), and to what extent these policies may introduce further uncertainties into global financial markets.
Tea plant (Camellia sinensis) is an economically important beverage crop. Drought stress (DS) seriously limits the growth and development of tea plant, thus affecting crop yield and quality. To ...elucidate the molecular mechanisms of tea plant responding to DS, we performed transcriptomic analysis of tea plant during the three stages control (CK) and during DS, and recovery (RC) after DS using RNA sequencing (RNA-Seq). Totally 378.08 million high-quality trimmed reads were obtained and assembled into 59,674 unigenes, which were extensively annotated. There were 5,955 differentially expressed genes (DEGs) among the three stages. Among them, 3,948 and 1,673 DEGs were up-regulated under DS and RC, respectively. RNA-Seq data were further confirmed by qRT-PCR analysis. Genes involved in abscisic acid (ABA), ethylene, and jasmonic acid biosynthesis and signaling were generally up-regulated under DS and down-regulated during RC. Tea plant potentially used an exchange pathway for biosynthesis of indole-3-acetic acid (IAA) and salicylic acid under DS. IAA signaling was possibly decreased under DS but increased after RC. Genes encoding enzymes involved in cytokinin synthesis were up-regulated under DS, but down-regulated during RC. It seemed probable that cytokinin signaling was slightly enhanced under DS. In total, 762 and 950 protein kinases belonging to 26 families were differentially expressed during DS and RC, respectively. Overall, 547 and 604 transcription factor (TF) genes belonging to 58 families were induced in the DS vs. CK and RC vs. DS libraries, respectively. Most members of the 12 TF families were up-regulated under DS. Under DS, genes related to starch synthesis were down-regulated, while those related to starch decomposition were up-regulated. Mannitol, trehalose and sucrose synthesis-related genes were up-regulated under DS. Proline was probably mainly biosynthesized from glutamate under DS and RC. The mechanism by which ABA regulated stomatal movement under DS and RC was partly clarified. These results document the global and novel responses of tea plant during DS and RC. These data will serve as a valuable resource for drought-tolerance research and will be useful for breeding drought-resistant tea cultivars.
•We investigate listed manufacturing firms in China for 2000–2010.•Green patenting and firm performance are positively related.•This positive relationship is more pronounced among SOEs.•This positive ...relationship among SOEs is more pronounced after 2006.
This paper focuses on how green patenting influences a firm’s subsequent performance. By investigating listed manufacturing firms in China for the 2000–2010 period, we find a positive and significant relationship between green patenting and firm performance. Moreover, our research reveals that green growth is mainly driven by green utility-model patents and that this positive relationship only exists among state-owned enterprises (SOEs), which are more capable of leveraging green innovation through their close relationship with the government. Furthermore, the positive relationship is found to exist primarily after 2006, when the government began to provide formal legislative support to green industry.
Most available remote eye gaze trackers have two characteristics that hinder them being widely used as the important computer input devices for human computer interaction. First, they have to be ...calibrated for each user individually; second, they have low tolerance for head movement and require the users to hold their heads unnaturally still. In this paper, by exploiting the eye anatomy, we propose two novel solutions to allow natural head movement and minimize the calibration procedure to only one time for a new individual. The first technique is proposed to estimate the 3D eye gaze directly. In this technique, the cornea of the eyeball is modeled as a convex mirror. Via the properties of convex mirror, a simple method is proposed to estimate the 3D optic axis of the eye. The visual axis, which is the true 3D gaze direction of the user, can be determined subsequently after knowing the angle deviation between the visual axis and optic axis by a simple calibration procedure. Therefore, the gaze point on an object in the scene can be obtained by simply intersecting the estimated 3D gaze direction with the object. Different from the first technique, our second technique does not need to estimate the 3D eye gaze directly, and the gaze point on an object is estimated from a gaze mapping function implicitly. In addition, a dynamic computational head compensation model is developed to automatically update the gaze mapping function whenever the head moves. Hence, the eye gaze can be estimated under natural head movement. Furthermore, it minimizes the calibration procedure to only one time for a new individual. The advantage of the proposed techniques over the current state of the art eye gaze trackers is that it can estimate the eye gaze of the user accurately under natural head movement, without need to perform the gaze calibration every time before using it. Our proposed methods will improve the usability of the eye gaze tracking technology, and we believe that it represents an important step for the eye tracker to be accepted as a natural computer input device.
In this paper, we report on a fast second-order numerical integrator to solve the Lorentz force equations of a relativistic charged particle in electromagnetic fields. This numerical integrator shows ...less numerical error than the popular Boris algorithm in tracking the relativistic particle subject to electric and magnetic space-charge fields and requires less number of operations than another recently proposed relativistic integrator.
A system that could automatically analyze the facial actions in real time has applications in a wide range of different fields. However, developing such a system is always challenging due to the ...richness, ambiguity, and dynamic nature of facial actions. Although a number of research groups attempt to recognize facial action units (AUs) by improving either the facial feature extraction techniques or the AU classification techniques, these methods often recognize AUs or certain AU combinations individually and statically, ignoring the semantic relationships among AUs and the dynamics of AUs. Hence, these approaches cannot always recognize AUs reliably, robustly, and consistently. In this paper, we propose a novel approach that systematically accounts for the relationships among AUs and their temporal evolutions for AU recognition. Specifically, we use a dynamic Bayesian network (DBN) to model the relationships among different AUs. The DBN provides a coherent and unified hierarchical probabilistic framework to represent probabilistic relationships among various AUs and to account for the temporal changes in facial action development. Within our system, robust computer vision techniques are used to obtain AU measurements. Such AU measurements are then applied as evidence to the DBN for inferring various AUs. The experiments show that the integration of AU relationships and AU dynamics with AU measurements yields significant improvement of AU recognition, especially for spontaneous facial expressions and under more realistic environment including illumination variation, face pose variation, and occlusion.
Promoting the development of renewable energy has become the key factor to solve the problems of energy and climate change issues. However, its development is largely constrained by the prices of ...traditional fossil energy. This paper explores the influence of various fossil energy price changes on renewable energy stock returns using a network approach. Specifically, a positive and negative returns network and value-at-risk (VaR) network are constructed separately for identifying the asymmetric and extreme information spillover. Our findings show the fossil energy–renewable energy network system has a relatively high level of interdependence. The electricity market behaves as the major contributor to the changes of renewable energy returns in the returns connectedness network, while oil and coal contribute most to the changes of renewable energy returns in the VaR connectedness network. The dynamic results show that the contributions of fossil energy price changes to renewable energy returns have strong time-varying pattern with high volatility over time. The total connectedness in the positive returns network is slightly stronger than that in the negative returns network for most of the time during our sample period.
•The impacts of various fossil energy products on renewable energy are studied.•Four different information spillover networks are constructed.•The electricity market is the main contributor to renewable energy price changes.•The impacts of fossil energy on renewable energy present high volatility over time.•There is no significant asymmetry in the positive and negative returns networks.
In contrast to holistic methods, local matching methods extract facial features from different levels of locality and quantify them precisely. To determine how they can be best used for face ...recognition, we conducted a comprehensive comparative study at each step of the local matching process. The conclusions from our experiments include: (1) additional evidence that Gabor features are effective local feature representations and are robust to illumination changes; (2) discrimination based only on a small portion of the face area is surprisingly good; (3) the configuration of facial components does contain rich discriminating information and comparing corresponding local regions utilizes shape features more effectively than comparing corresponding facial components; (4) spatial multiresolution analysis leads to better classification performance; (5) combining local regions with Borda count classifier combination method alleviates the curse of dimensionality. We implemented a complete face recognition system by integrating the best option of each step. Without training, illumination compensation and without any parameter tuning, it achieves superior performance on every category of the FERET test: near perfect classification accuracy (99.5%) on pictures taken on the same day regardless of indoor illumination variations, and significantly better than any other reported performance on pictures taken several days to more than a year apart. The most significant experiments were repeated on the AR database, with similar results.
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