The PD-Utility Function for Prospect Behavior and Related Researches

Based on Partial Distribution [11],[12], we put forward a PD-utility function of prospect behavior for the first time, the profiting utility function and losing utility function. The PD-utility function can reflect sufficiently the human¡¯s risk preferences properties to profiting or losing, describe and bring to light availably the important relations between profiting utility and losing utility, and interpret many conclusions in Daniel Kahneman¡¯s prospect theory in analytic way. Also we present the concepts and analytic expressions of essential indexes of realized level for prospect behavior, the limit value, the balanced value, and focus value, especially the method of calculating them. The limit level is beneficial to judge the reversal position of reality movement trend, and the latter is beneficial to judge that the focus of current reality is reasonableness or not. And we give out the calculating formula for the optimal value of realized level for prospect with its appearing probability.partial distribution, PD-utility function, prospect behavior, essential indexes, optimal value

Vehicular Fog Computing Enabled Real-time Collision Warning via Trajectory Calibration

Vehicular fog computing (VFC) has been envisioned as a promising paradigm for enabling a variety of emerging intelligent transportation systems (ITS). However, due to inevitable as well as non-negligible issues in wireless communication, including transmission latency and packet loss, it is still challenging in implementing safety-critical applications, such as real-time collision warning in vehicular networks. In this paper, we present a vehicular fog computing architecture, aiming at supporting effective and real-time collision warning by offloading computation and communication overheads to distributed fog nodes. With the system architecture, we further propose a trajectory calibration based collision warning (TCCW) algorithm along with tailored communication protocols. Specifically, an application-layer vehicular-to-infrastructure (V2I) communication delay is fitted by the Stable distribution with real-world field testing data. Then, a packet loss detection mechanism is designed. Finally, TCCW calibrates real-time vehicle trajectories based on received vehicle status including GPS coordinates, velocity, acceleration, heading direction, as well as the estimation of communication delay and the detection of packet loss. For performance evaluation, we build the simulation model and implement conventional solutions including cloud-based warning and fog-based warning without calibration for comparison. Real-vehicle trajectories are extracted as the input, and the simulation results demonstrate that the effectiveness of TCCW in terms of the highest precision and recall in a wide range of scenarios

Frequency Compensated Diffusion Model for Real-scene Dehazing

Due to distribution shift, deep learning based methods for image dehazing suffer from performance degradation when applied to real-world hazy images. In this paper, we consider a dehazing framework based on conditional diffusion models for improved generalization to real haze. First, we find that optimizing the training objective of diffusion models, i.e., Gaussian noise vectors, is non-trivial. The spectral bias of deep networks hinders the higher frequency modes in Gaussian vectors from being learned and hence impairs the reconstruction of image details. To tackle this issue, we design a network unit, named Frequency Compensation block (FCB), with a bank of filters that jointly emphasize the mid-to-high frequencies of an input signal. We demonstrate that diffusion models with FCB achieve significant gains in both perceptual and distortion metrics. Second, to further boost the generalization performance, we propose a novel data synthesis pipeline, HazeAug, to augment haze in terms of degree and diversity. Within the framework, a solid baseline for blind dehazing is set up where models are trained on synthetic hazy-clean pairs, and directly generalize to real data. Extensive evaluations show that the proposed dehazing diffusion model significantly outperforms state-of-the-art methods on real-world images.Comment: 16 page

Key issues and development direction of petroleum geology research of source rock strata in China

After more than 20 years of technological advancements, the novel field of oil and gas production from source rock strata, which comprise tight and shale oil and gas reservoirs, has become the major contributor to the increase in unconventional oil and gas reserves in China. Accordingly, this field has gradually entered a new stage of revolutionary development. The oil and gas production in China from source rock strata will achieve sustainable development in the future. Different types of source rock strata present distinct challenges and require diverse development paths. Based on the geological conditions of source rock strata in China, this study focuses on identifying the “sweet areas” among hydrocarbon accumulations. It specifically analyzes the key development issues of tight oil, tight gas, shale oil, shale gas, and coal-bed methane, while proposing potential solutions and identifying the possible directions for future development. This study aims to provide a reference for scientists concerned with the development of unconventional oil and gas reserves in China.Cited as: Li, J., Yang, Z., Wu, S., Pan, S. Key issues and development direction of petroleum geology research on source rock strata in China. Advances in Geo-Energy Research, 2021, 5(2): 121-126, doi: 10.46690/ager.2021.02.0

Characterization of mineral and pore evolution under CO2-brine-rock interaction at in-situ conditions

Herein, a method of physical modeling of CO2-brine-rock interaction and in-situ characterization of mineral and pore evolution is established. The nested preparation and installation of the same sample with different sizes could protect and keep the integrality of the millimeter-size sample in conventional high-temperature and high-pressure reactors. This paper establishes a procedure to obtain the three-dimensional in-situ comparison of minerals and pores before and after the reaction. The resolution is updated from 5-10 µ m to 10 nm, which could be helpful for modeling CO2-brine-rock interaction in unconventional tight reservoirs. This method could be applied to CO2-enhanced oil recovery as well as CO2 capture, utilization, and storage scientific research. Furthermore, it may shed light on the carbon sequestration schemes in the Chinese petroleum industry.Cited as: Wu, S., Yu, C., Hu, X., Yu, Z., Jiang, X. Characterization of mineral and pore evolution under CO2-brine-rock interaction at in-situ conditions. Advances in Geo-Energy Research, 2022, 6(2): 177-178. https://doi.org/10.46690/ager.2022.02.0

Basic properties and exploitation strategies of source rock strata

Source rock strata are filled and aggregated with large-scale continuous hydrocarbon resources, including significant volumes of in-place retained, short-distance migrated and potentially generated hydrocarbons. Source rock strata simultaneously possess the properties of reservoirs and hydrocarbon source rocks, known as source-reservoir coexisting systems. Reservoir properties refer to the physical properties concerning the storage and transmission of oil and gas, while hydrocarbon source rock properties refer to the physicochemical properties related to governing the generation, retention and expulsion of oil and gas in the source rock strata. These properties fundamentally determine the technical path for the successful exploitation of petroleum and natural gas in the source rock strata. With regard to reservoir properties, in-depth research and development of the advanced energy-storing fracturing technology can aid the construction of complex fracture networks to overcome the limitations in the connectivity properties of source rock strata. Focusing on the hydrocarbon source rock properties, an underground in-situ conversion technology should be created and developed to alleviate the shortcomings of organic matter quantity and maturity properties of the source rock strata. Furthermore, selecting the appropriate exploitation path based on the property characteristics can promote the achievement of commercial and sustainable development of oil and gas in the source rock strata.Document Type: PerspectiveCited as: Yang, Z., Zou, C., Fan, Y., Wu, S., Liu, H., Wei, Q. Basic properties and exploitation strategies of source rock strata. Advances in Geo-Energy Research, 2023, 10(2): 77-83. https://doi.org/10.46690/ager.2023.11.0

Federated Learning over a Wireless Network: Distributed User Selection through Random Access

User selection has become crucial for decreasing the communication costs of federated learning (FL) over wireless networks. However, centralized user selection causes additional system complexity. This study proposes a network intrinsic approach of distributed user selection that leverages the radio resource competition mechanism in random access. Taking the carrier sensing multiple access (CSMA) mechanism as an example of random access, we manipulate the contention window (CW) size to prioritize certain users for obtaining radio resources in each round of training. Training data bias is used as a target scenario for FL with user selection. Prioritization is based on the distance between the newly trained local model and the global model of the previous round. To avoid excessive contribution by certain users, a counting mechanism is used to ensure fairness. Simulations with various datasets demonstrate that this method can rapidly achieve convergence similar to that of the centralized user selection approach

Paleoenvironment and chemostratigraphy heterogenity of the Cretaceous organic-rich shales

The Cretaceous Qingshankou Formation in the Songliao Basin is rich in shale oil resources, which has become one of the most important exploration targets of lacustrine shale oil in China. Based on X-ray fluorescence element analysis, X-ray diffraction analysis, total organic carbon, rock pyrolysis, scanning electron microscope and nitrogen adsorption, the Paleoenvironment was reconstructed by comprehensive utilization of integrated prediction error filter analysis of chemical stratigraphy, and its relationship with organic geochemistry, mineralogy and pore structure was discussed. The results indicated that the Qingshankou Formation was deposited in the environment with fresh water-brackish water, semi-deep/deep water and strong reduction. The evolution of Paleoenvironment during the deposition of Qingshankou Formation changed from bottom to top, with increasing water depth, decreasing salinity and oxygen content. Paleosalinity was positively correlated with total organic carbon, residual hydrocarbon and carbonate mineral content. From bottom to top, the contents of carbonate and chlorite decreased, while the contents of plagioclase and clay minerals increased slightly. The pores were dominated by intra-illite pores, intra-I/S mixed-layer pores and intra-pyrite pores. Some intra-plagioclase pores and calcite dissolution pores were developed, and the organic matter pores are slightly few. Nitrogen adsorption data showed that the dominate pore size was 40-53 nm. This study clarifies the Paleoenvironmental evolution of the Qingshankou Formation, and may shed lights on lacustrine shale oil accumulation and sweet-spotting.Cited as: Guan, M., Wu, S., Hou, L., Jiang, X., Ba, D., Hua, G. Paleoenvironment and chemostratigraphy heterogenity of the Cretaceous organic-rich shales. Advances in Geo-Energy Research, 2021, 5(4): 444-455, doi: 10.46690/ager.2021.04.0

Metro: Memory-Enhanced Transformer for Retrosynthetic Planning via Reaction Tree

Retrosynthetic planning plays a critical role in drug discovery and organic chemistry. Starting from a target molecule as the root node, it aims to find a complete reaction tree subject to the constraint that all leaf nodes belong to a set of starting materials. The multi-step reactions are crucial because they determine the flow chart in the production of the Organic Chemical Industry. However, existing datasets lack curation of tree-structured multi-step reactions, and fail to provide such reaction trees, limiting models' understanding of organic molecule transformations. In this work, we first develop a benchmark curated for the retrosynthetic planning task, which consists of 124,869 reaction trees retrieved from the public USPTO-full dataset. On top of that, we propose Metro: Memory-Enhanced Transformer for RetrOsynthetic planning. Specifically, the dependency among molecules in the reaction tree is captured as context information for multi-step retrosynthesis predictions through transformers with a memory module. Extensive experiments show that Metro dramatically outperforms existing single-step retrosynthesis models by at least 10.7% in top-1 accuracy. The experiments demonstrate the superiority of exploiting context information in the retrosynthetic planning task. Moreover, the proposed model can be directly used for synthetic accessibility analysis, as it is trained on reaction trees with the shortest depths. Our work is the first step towards a brand new formulation for retrosynthetic planning in the aspects of data construction, model design, and evaluation. Code is available at https://github.com/SongtaoLiu0823/metro