200 research outputs found
Universal service obligations in developing countries
This paper develops a model to analyze the impacts of asymmetric information on optimal universal, service policy in the public utilities of developing countries. Optimal universal service policy is implemented using two regulatory instruments: pricing and network investment. Under discriminatory pricing asymmetric information leads to a higher price, and smaller network in the rural area, than under full information. Under uniform pricing, the price is also lower but the network is even smaller. In addition, under both pricing regimes, not only the firm, but also taxpayers have incentives to collude with the regulator.Environmental Economics&Policies,Knowledge Economy,Insurance&Risk Mitigation,Economic Theory&Research,Insurance Law,Education for the Knowledge Economy,Knowledge Economy,Economic Theory&Research,Environmental Economics&Policies,Geographical Information Systems
Growth, chemical components and ensiling characteristics of king grass at different cuttings
In order to effectively use and ensile king grass (Pennisetum purpureum × Pennisetum americanum), the present research investigated growth rate, yield, chemical components and silage fermentation quality of different cuttings. King grass was harvested four times, and the 1st and 3rd cuttings were ensiled directly or after wilting for 12 and 24 h. The results showed that the dry matter daily growth of 2nd cutting was significantly higher than that of other cuttings, and the 4th cutting was the lowest (P < 0.05). The contents of crude protein (CP), crude fat and water-soluble carbohydrates (WSC) tended to reduce, and crude ash tended to increase with the increase of cutting times. All four cuttings of king grass had higher WSC content, lower buffer capacity and much lactic acid bacteria, the silages made from unwilted 1st cutting and 3rd cutting were of good fermentation quality, indicated by low pH values and high V-scores. Wilting had different effects on the 1st cutting and 3rd cutting silages in pH value and NH3-N content, the 1st cutting silage tended to increase the pH values and NH3-N content, with moisture content reduction, while the 3rd cutting silage tended to reduce NH3-N content and its pH value was not affected by wilting (P > 0.05). Although the 3rd cutting silage had better aerobic stability than the 1st cutting silage, they all were not stable within 6 days of aerobic exposure. Considering the contents of CP, crude fat, crude fiber, crude ash and WSC, the 1st cutting of king grass might have best nutrient value, while the 4th cutting was contrary. Different cuttings of king grass could be well preserved by natural fermentation, but their aerobic stability was poor.Keywords: Cuttings, ensiling, king grass, nutrient component, wiltin
SVEIRS: A New Epidemic Disease Model with Time Delays and Impulsive Effects
We first propose a new epidemic disease model governed by system of impulsive delay differential equations. Then, based on theories for impulsive delay differential equations, we skillfully solve the difficulty in analyzing the global dynamical behavior of the model with pulse vaccination and impulsive population input effects at two different periodic moments. We prove the existence and global attractivity of the “infection-free” periodic solution and also the permanence of the model. We then carry out numerical simulations to illustrate our theoretical results, showing us that time delay, pulse vaccination, and pulse population input can exert a significant influence on the dynamics of the system which confirms the availability of pulse vaccination strategy for the practical epidemic prevention. Moreover, it is worth pointing out that we obtained an epidemic control strategy for controlling the number of population input
Resolution-Enhanced All-Optical Analog-to-Digital Converter Employing Cascade Optical Quantization Operation
In this paper, a cascade optical quantization scheme is proposed to realize all-optical analog-to-digital converter with efficiently enhanced quantization resolution and achievable high analog bandwidth of larger than 20 GHz. Employing the cascade structure of an unbalanced Mach-zehnder modulator and a specially designed optical directional coupler, we predict the enhancement of number-of-bits can be up to 1.59-bit. Simulation results show that a 25 GHz RF signal is efficiently digitalized with the signal-tonoise ratio of 33.58 dB and effective-number-of-bits of 5.28-bit
Rethinking Pseudo-LiDAR Representation
The recently proposed pseudo-LiDAR based 3D detectors greatly improve the
benchmark of monocular/stereo 3D detection task. However, the underlying
mechanism remains obscure to the research community. In this paper, we perform
an in-depth investigation and observe that the efficacy of pseudo-LiDAR
representation comes from the coordinate transformation, instead of data
representation itself. Based on this observation, we design an image based CNN
detector named Patch-Net, which is more generalized and can be instantiated as
pseudo-LiDAR based 3D detectors. Moreover, the pseudo-LiDAR data in our
PatchNet is organized as the image representation, which means existing 2D CNN
designs can be easily utilized for extracting deep features from input data and
boosting 3D detection performance. We conduct extensive experiments on the
challenging KITTI dataset, where the proposed PatchNet outperforms all existing
pseudo-LiDAR based counterparts. Code has been made available at:
https://github.com/xinzhuma/patchnet.Comment: ECCV2020. Supplemental Material attache
A stage-structured predator-prey si model with disease in the prey and impulsive effects
This paper aims to develop a high-dimensional SI model with stage structure for both the prey (pest) and the predator, and then to investigate the dynamics of it. The model can be used for the study of Integrated Pest Management (IPM) which is a combination of constant pulse releasing of animal enemies and diseased pests at two different fixed moments. Firstly, we use analytical techniques for impulsive delay differential equations to obtain the conditions for global attractivity of the ‘pest-free’ periodic solution and permanence of the population model. It shows that the conditions strongly depend on time delay, impulsive release of animal enemies and infective pests. Secondly, we present a pest management strategy in which the pest population is kept under the economic threshold level (ETL) when the pest population is permanent. Finally, numerical analysis is presented to illustrate our main conclusion
Dynamical Analysis of a Pest Management Model with Saturated Growth Rate and State Dependent Impulsive Effects
A new pest management mathematical model with saturated growth is proposed. The integrated pest management (IPM) strategy by introducing two state dependent pulses into the model is considered. Firstly, we analyze singular points of the model qualitatively and get the condition for focus point. Secondly, by using geometry theory of impulsive differential equation, the existence and stability of periodic solution of the system are discussed. Lastly, some examples and numerical simulations are given to illustrate our results
GUPNet++: Geometry Uncertainty Propagation Network for Monocular 3D Object Detection
Geometry plays a significant role in monocular 3D object detection. It can be
used to estimate object depth by using the perspective projection between
object's physical size and 2D projection in the image plane, which can
introduce mathematical priors into deep models. However, this projection
process also introduces error amplification, where the error of the estimated
height is amplified and reflected into the projected depth. It leads to
unreliable depth inferences and also impairs training stability. To tackle this
problem, we propose a novel Geometry Uncertainty Propagation Network (GUPNet++)
by modeling geometry projection in a probabilistic manner. This ensures depth
predictions are well-bounded and associated with a reasonable uncertainty. The
significance of introducing such geometric uncertainty is two-fold: (1). It
models the uncertainty propagation relationship of the geometry projection
during training, improving the stability and efficiency of the end-to-end model
learning. (2). It can be derived to a highly reliable confidence to indicate
the quality of the 3D detection result, enabling more reliable detection
inference. Experiments show that the proposed approach not only obtains
(state-of-the-art) SOTA performance in image-based monocular 3D detection but
also demonstrates superiority in efficacy with a simplified framework.Comment: 18 pages, 9 figure
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