Double Degenerate Stars

Regardless of the formation mechanism, an exotic object, Double Degenerate Star (DDS), is introduced and investigated, which is composed of baryonic matter and some unknown fermion dark matter. Different from the simple White Dwarfs (WDs), there are additional gravitational force provided by the unknown fermion component inside DDSs, which may strongly affect the structure and the stability of such kind of objects. Many possible and strange observational phenomena connecting with them are concisely discussed. Similar to the normal WD, this object can also experience thermonuclear explosion as type Ia supernova explosion when DDS's mass exceeds the maximum mass that can be supported by electron degeneracy pressure. However, since the total mass of baryonic matter can be much lower than that of WD at Chandrasekhar mass limit, the peak luminosity should be much dimmer than what we expect before, which may throw a slight shadow on the standard candle of SNIa in the research of cosmology.Comment: 8 pages, 2 figures, 1 Table, uses iopar

Deep Learning Based Robot for Automatically Picking up Garbage on the Grass

This paper presents a novel garbage pickup robot which operates on the grass. The robot is able to detect the garbage accurately and autonomously by using a deep neural network for garbage recognition. In addition, with the ground segmentation using a deep neural network, a novel navigation strategy is proposed to guide the robot to move around. With the garbage recognition and automatic navigation functions, the robot can clean garbage on the ground in places like parks or schools efficiently and autonomously. Experimental results show that the garbage recognition accuracy can reach as high as 95%, and even without path planning, the navigation strategy can reach almost the same cleaning efficiency with traditional methods. Thus, the proposed robot can serve as a good assistance to relieve dustman's physical labor on garbage cleaning tasks.Comment: 8 pages, 13 figures,TCE accepte

Smart Guiding Glasses for Visually Impaired People in Indoor Environment

To overcome the travelling difficulty for the visually impaired group, this paper presents a novel ETA (Electronic Travel Aids)-smart guiding device in the shape of a pair of eyeglasses for giving these people guidance efficiently and safely. Different from existing works, a novel multi sensor fusion based obstacle avoiding algorithm is proposed, which utilizes both the depth sensor and ultrasonic sensor to solve the problems of detecting small obstacles, and transparent obstacles, e.g. the French door. For totally blind people, three kinds of auditory cues were developed to inform the direction where they can go ahead. Whereas for weak sighted people, visual enhancement which leverages the AR (Augment Reality) technique and integrates the traversable direction is adopted. The prototype consisting of a pair of display glasses and several low cost sensors is developed, and its efficiency and accuracy were tested by a number of users. The experimental results show that the smart guiding glasses can effectively improve the user's travelling experience in complicated indoor environment. Thus it serves as a consumer device for helping the visually impaired people to travel safely.Comment: 9 pages,15 figures, IEEE transaction on consumer electronics receive

Facial Pose Estimation by Deep Learning from Label Distributions

Facial pose estimation has gained a lot of attentions in many practical applications, such as human-robot interaction, gaze estimation and driver monitoring. Meanwhile, end-to-end deep learning-based facial pose estimation is becoming more and more popular. However, facial pose estimation suffers from a key challenge: the lack of sufficient training data for many poses, especially for large poses. Inspired by the observation that the faces under close poses look similar, we reformulate the facial pose estimation as a label distribution learning problem, considering each face image as an example associated with a Gaussian label distribution rather than a single label, and construct a convolutional neural network which is trained with a multi-loss function on AFLW dataset and 300W-LP dataset to predict the facial poses directly from color image. Extensive experiments are conducted on several popular benchmarks, including AFLW2000, BIWI, AFLW and AFW, where our approach shows a significant advantage over other state-of-the-art methods.Comment: 9 pages,5 figures, Accepted by ICCV 2019 worksho

Spreading of infectious diseases on complex networks with non-symmetric transmission probabilities

We model the spread of a SIS infection on Small World and random networks using weighted graphs. The entry $w_{ij}$ in the weight matrix W holds information about the transmission probability along the edge joining node $v_i$ and node $v_j$. We use the analogy between the spread of a disease on a network and a random walk performed on this network to derive a master equation describing the dynamics of the process. We find conditions under which an epidemic does not break out and investigate numerically the effect of a non-symmetric weight distribution of the initially infected individual on the dynamics of the disease spread.Comment: 32 pages, 1 figur

Wearable Travel Aid for Environment Perception and Navigation of Visually Impaired People

This paper presents a wearable assistive device with the shape of a pair of eyeglasses that allows visually impaired people to navigate safely and quickly in unfamiliar environment, as well as perceive the complicated environment to automatically make decisions on the direction to move. The device uses a consumer Red, Green, Blue and Depth (RGB-D) camera and an Inertial Measurement Unit (IMU) to detect obstacles. As the device leverages the ground height continuity among adjacent image frames, it is able to segment the ground from obstacles accurately and rapidly. Based on the detected ground, the optimal walkable direction is computed and the user is then informed via converted beep sound. Moreover, by utilizing deep learning techniques, the device can semantically categorize the detected obstacles to improve the users' perception of surroundings. It combines a Convolutional Neural Network (CNN) deployed on a smartphone with a depth-image-based object detection to decide what the object type is and where the object is located, and then notifies the user of such information via speech. We evaluated the device's performance with different experiments in which 20 visually impaired people were asked to wear the device and move in an office, and found that they were able to avoid obstacle collisions and find the way in complicated scenarios.Comment: 7 pages, 12 figure

Why does air passage over forest yield more rain? Examining the coupling between rainfall, pressure and atmospheric moisture content

The influence of forest loss on rainfall remains poorly understood. Addressing this challenge Spracklen et al. recently presented a pan-tropical study of rainfall and land-cover that showed that satellite-derived rainfall measures were positively correlated with the degree to which model-derived air trajectories had been exposed to forest cover. This result confirms the influence of vegetation on regional rainfall patterns suggested in previous studies. However, we find that the conclusion of Spracklen et al. -- that differences in rainfall reflect air moisture content resulting from evapotranspiration while the circulation pattern remains unchanged -- appears undermined by methodological inconsistencies. We identify methodological problems with the underlying analyses and the quantitative estimates for rainfall change predicted if forest cover is lost in the Amazon. We discuss some alternative explanations that include the distinct role of forest evapotranspiration in creating low pressure systems that draw moisture from the oceans to the continental hinterland. Our analysis of meteorological data from three regions in Brazil, including the central Amazon forest, reveal a tendency for rainy days during the wet season with column water vapor (CWV) exceeding 50 mm to have higher pressure than rainless days; while at lower CWV rainy days tend to have lower pressure than rainless days. The coupling between atmospheric moisture content and circulation dynamics underlines that the danger posed by forest loss is greater than suggested by focusing only on moisture recycling alone.Comment: 21 page, 8 figures, new data adde

Quantifying the global atmospheric power budget

The power of atmospheric circulation is a key measure of the Earth's climate system. The mismatch between predictions and observations under a warming climate calls for a reassessment of how atmospheric power $W$ is defined, estimated and constrained. Here we review published formulations for $W$ and show how they differ when applied to a moist atmosphere. Three factors, a non-zero source/sink in the continuity equation, the difference between velocities of gaseous air and condensate, and interaction between the gas and condensate modifying the equations of motion, affect the formulation of $W$. Starting from the thermodynamic definition of mechanical work, we derive an expression for $W$ from an explicit consideration of the equations of motion and continuity. Our analyses clarify how some past formulations are incomplete or invalid. Three caveats are identified. First, $W$ critically depends on the boundary condition for gaseous air velocity at the Earth's surface. Second, confusion between gaseous air velocity and mean velocity of air and condensate in the expression for $W$ results in gross errors despite the observed magnitudes of these velocities are very close. Third, $W$ expressed in terms of measurable atmospheric parameters, air pressure and velocity, is scale-specific; this must be taken into account when adding contributions to $W$ from different processes. We present a formulation of the atmospheric power budget, which distinguishes three components of $W$: the kinetic power associated with horizontal pressure gradients ($W_K$), the gravitational power of precipitation ($W_P$) and the condensate loading ($W_c$). We use MERRA and NCAR/NCEP re-analyses to evaluate the atmospheric power budget at different scales: $W_K$ increases with temporal resolution approaching our theoretical estimate for condensation-induced circulation when all convective motion is resolved.Comment: 55 pages, 14 figures; minor revisions after another discussion, see https://doi.org/10.5194/acp-2017-17-AC7 and www.bioticregulation.ru/ab.php?id=h

Information-driven Path Planning for Hybrid Aerial Underwater Vehicles

This paper presents a novel Rapidly-exploring Adaptive Sampling Tree (RAST) algorithm for the adaptive sampling mission of a hybrid aerial underwater vehicle (HAUV) in an air-sea 3D environment. This algorithm innovatively combines the tournament-based point selection sampling strategy, the information heuristic search process and the framework of Rapidly-exploring Random Tree (RRT) algorithm. Hence can guide the vehicle to the region of interest to scientists for sampling and generate a collision-free path for maximizing information collection by the HAUV under the constraints of environmental effects of currents or wind and limited budget. The simulation results show that the fast search adaptive sampling tree algorithm has higher optimization performance, faster solution speed and better stability than the Rapidly-exploring Information Gathering Tree (RIGT) algorithm and the particle swarm optimization (PSO) algorithm

Spatiotemporal relationships between sea level pressure and air temperature in the tropics

While surface temperature gradients have been highlighted as drivers of low-level atmospheric circulation, the underlying physical mechanisms remain unclear. Lindzen and Nigam (1987) noted that sea level pressure (SLP) gradients are proportional to surface temperature gradients if isobaric height (the height where pressure does not vary in the horizontal plane) is constant; their own model of low-level circulation assumed that isobaric height in the tropics is around 3 km. Recently Bayr and Dommenget (2013) proposed a simple model of temperature-driven air redistribution from which they derived that the isobaric height in the tropics again varies little but occurs higher (at the height of the troposphere). Here investigations show that neither the empirical assumption of Lindzen and Nigam (1987) nor the theoretical derivations of Bayr and Dommenget (2013) are plausible. Observations show that isobaric height is too variable to determine a universal spatial or temporal relationship between local values of air temperature and SLP. Since isobaric height cannot be determined from independent considerations, the relationship between SLP and temperature is not evidence that differential heating drives low-level circulation. An alternative theory suggests SLP gradients are determined by the condensation of water vapor as moist air converges towards the equator. This theory quantifies the meridional SLP differences observed by season across the Hadley cells reasonably well. Higher temperature of surface air where SLP is low may be determined by equatorward transport and release of latent heat below the trade wind inversion layer. The relationship between atmospheric circulation and moisture dynamics merits further investigation.Comment: 31 pages, 11 figures, 2 Table