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