Face2Multi-modal: in-vehicle multi-modal predictors via facial expressions

Towards intelligent Human-Vehicle Interaction systems and innovative Human-Vehicle Interaction designs, in-vehicle drivers' physiological data has been explored as an essential data source. However, equipping multiple biosensors is considered the limited extent of user-friendliness and impractical during the driving procedure. The lack of a proper approach to access physiological data has hindered wider applications of advanced biosignal-driven designs in practice (e.g. monitoring systems and etc.). Hence, the demand for a user-friendly approach to measuring drivers' body statuses has become more intense. In this Work-In-Progress, we present Face2Multi-modal, an In-vehicle multi-modal Data Streams Predictors through facial expressions only. More specifically, we have explored the estimations of Heart Rate, Skin Conductance, and Vehicle Speed of the drivers. We believe Face2Multi-modal provides a user-friendly alternative to acquiring drivers' physiological status and vehicle status, which could serve as the building block for many current or future personalized Human-Vehicle Interaction designs. More details and updates about the project Face2Multi-modal is online at https://github.com/unnc-ucc/Face2Multimodal/

CEACAM1 Negatively Regulates IL-1β Production in LPS Activated Neutrophils by Recruiting SHP-1 to a SYK-TLR4-CEACAM1 Complex

LPS-activated neutrophils secrete IL-1β by activation of TLR-4. Based on studies in macrophages, it is likely that ROS and lysosomal destabilization regulated by Syk activation may also be involved. Since neutrophils have abundant expression of the ITIM-containing co-receptor CEACAM1 and Gram-negative bacteria such as Neisseria utilize CEACAM1 as a receptor that inhibits inflammation, we hypothesized that the overall production of IL-1β in LPS treated neutrophils may be negatively regulated by CEACAM1. We found that LPS treated neutrophils induced phosphorylation of Syk resulting in the formation of a complex including TLR4, p-Syk, and p-CEACAM1, which in turn, recruited the inhibitory phosphatase SHP-1. LPS treatment leads to ROS production, lysosomal damage, caspase-1 activation and IL-1β secretion in neutrophils. The absence of this regulation in Ceacam1−/− neutrophils led to hyper production of IL-1β in response to LPS. The hyper production of IL-1β was abrogated by in vivo reconstitution of wild type but not ITIM-mutated CEACAM1 bone marrow stem cells. Blocking Syk activation by kinase inhibitors or RNAi reduced Syk phosphorylation, lysosomal destabilization, ROS production, and caspase-1 activation in Ceacam1−/− neutrophils. We conclude that LPS treatment of neutrophils triggers formation of a complex of TLR4 with pSyk and pCEACAM1, which upon recruitment of SHP-1 to the ITIMs of pCEACAM1, inhibits IL-1β production by the inflammasome. Thus, CEACAM1 fine-tunes IL-1β production in LPS treated neutrophils, explaining why the additional utilization of CEACAM1 as a pathogen receptor would further inhibit inflammation

Physical and mathematical modeling of gas production in shale matrix

Shale gas mainly stores in shale matrix, and gas production in shale matrix is very important during exploration. In order to clarify gas production and transport mechanism in shale matrix, an experimental modeling of gas production in shale matrix was designed and conducted with Longmaxi shale samples collected from South of Sichuan. The experimental results show that gas production decline curve displays a “L” pattern which indicates initial production is high and declines rapidly, while late production is low and declines moderately; meanwhile, pressure propagation in shale matrix is quite slow due to ultralow permeability. Based on the results, a mathematical model was derived to describe gas production in shale matrix. The comparison between numerical solution of mathematical model and experimental results shows that the mathematical model can well describe gas transport in shale matrix. In addition, factors affecting gas production were investigated on the basis of the mathematical model. Adsorbed gas can replenish gas pressure in pores by desorption and delay pressure propagation, and gas production decreases very quickly when there is no adsorbed gas. Other parameters (diffusion coefficient, permeability and porosity) also need to be considered in shale gas development

Physical and mathematical modeling of gas production in shale matrix

Shale gas mainly stores in shale matrix, and gas production in shale matrix is very important during exploration. In order to clarify gas production and transport mechanism in shale matrix, an experimental modeling of gas production in shale matrix was designed and conducted with Longmaxi shale samples collected from South of Sichuan. The experimental results show that gas production decline curve displays a “L” pattern which indicates initial production is high and declines rapidly, while late production is low and declines moderately; meanwhile, pressure propagation in shale matrix is quite slow due to ultralow permeability. Based on the results, a mathematical model was derived to describe gas production in shale matrix. The comparison between numerical solution of mathematical model and experimental results shows that the mathematical model can well describe gas transport in shale matrix. In addition, factors affecting gas production were investigated on the basis of the mathematical model. Adsorbed gas can replenish gas pressure in pores by desorption and delay pressure propagation, and gas production decreases very quickly when there is no adsorbed gas. Other parameters (diffusion coefficient, permeability and porosity) also need to be considered in shale gas development

Impact of temperature on the isothermal adsorption/desorption of shale gas

Isothermal adsorption and desorption experiments under different temperatures were carried out with the Longmaxi Formation shale samples collected from southern Sichuan. The experimental results show that temperature affects the adsorption and desorption capacity of shale, the adsorption capacity of shale decreases with temperature increase. The adsorption curve and desorption curve of shale are not coincident and the thermodynamic reason for the hysteresis of the desorption curve is that the isosteric heat of the shale adsorption process is greater than that of the desorption process. The Langmuir model and desorption model can describe the isothermal adsorption and desorption processes very well, respectively. Isothermal adsorption and desorption curves under different temperatures can be predicted by isosteric heat curves which match the experimental results. Shale gas production is a process of gas desorption and the desorption characteristics directly impact the production of shale gas, so the desorption model should be taken into consideration in the shale gas production forecast and numerical simulation. Key words: shale, temperature, adsorption, desorption, isosteric adsorption hea

An Approach for Predicting the Effective Stress Field in Low-Permeability Reservoirs Based on Reservoir-Geomechanics Coupling

Low-permeability reservoirs are important to the future growth of oil and gas reserves and production in China. Predicting the effective stress, σe, in reservoirs is vitally important due to its considerable impact on reservoir development through hydraulic fracturing. This paper presents methods for predicting the σe field in ultralow-permeability reservoirs through reservoir–geomechanics coupling, which involve the simulation and coupling of the tectonic stress σ and pore pressure Pp fields based on three-dimensional (3D) geological models. First, 3D geological models were constructed based on basic data for the oilfield where the reservoir of interest is located. Then, finite element and finite difference simulations were performed to construct the σ and Pp fields, respectively, in the reservoir. Different types of initial σe were coupled based on 3D geological models. Subsequently, a dynamic σe field in the reservoir was established based on oilfield production data in conjunction with the transformation, optimization, and coupling of specific grid property parameters obtained from different numerical methods. Finally, the proposed methods were tested on real-world data acquired from well area X in an oilfield in Shaanxi Province, China. The results show that the proposed methods can be used to establish the σ and Pp fields in a reservoir based on 3D geological models combined with different numerical methods, and subsequently predict the σe value in the reservoir

Geological and Engineering Integrated Shale Gas Sweet Spots Evaluation Based on Fuzzy Comprehensive Evaluation Method: A Case Study of Z Shale Gas Field HB Block

As an emerging unconventional energy resource, shale gas has great resource potential and developmental prospects. The effective evaluation of geological sweet spots (GSS), engineering sweet spots (ESS) and comprehensive sweet spots (CSS) is one of the main factors for a high-yield scale and economic production of shale gas. Sweet spot evaluation involves a comprehensive analysis based on multiple parameters. Conventional evaluation methods consider relatively simple or single factors. Although the main influencing factors are understood, the influence of different factors is as of yet unknown, and a comprehensive consideration may strongly affect the evaluation results. In this paper, the fuzzy mathematics method is introduced for shale gas sweet spot evaluation. With the help of fuzzy mathematics tools, such as membership function, the objective of comprehensive sweet spots evaluation based on multiple parameters is realized. Additionally, the reliability of the evaluation of sweet spots is improved. Firstly, previous research results are used for reference, and the evaluation factor system of geological and engineering sweet spots of shale gas is systematically analyzed and established. Then, the basic principle of the fuzzy comprehensive evaluation method is briefly introduced, and a geological engineering integrated shale gas sweet spots evaluation method, based on the fuzzy comprehensive evaluation method, is designed and implemented. Finally, the data from HB blocks in the Z shale gas field in China are adopted. According to the evaluation results, the modified method is tested. The results show that the method proposed in this paper can synthesize a number of evaluation indices, quickly and effectively evaluate the GSS, ESS and CSS in the target area, and the results have high rationality and accuracy, which can effectively assist in well-pattern deployment and fracture design

PPO-Exp: Keeping Fixed-Wing UAV Formation with Deep Reinforcement Learning

Flocking for fixed-Wing Unmanned Aerial Vehicles (UAVs) is an extremely complex challenge due to fixed-wing UAV’s control problem and the system’s coordinate difficulty. Recently, flocking approaches based on reinforcement learning have attracted attention. However, current methods also require that each UAV makes the decision decentralized, which increases the cost and computation of the whole UAV system. This paper researches a low-cost UAV formation system consisting of one leader (equipped with the intelligence chip) with five followers (without the intelligence chip), and proposes a centralized collision-free formation-keeping method. The communication in the whole process is considered and the protocol is designed by minimizing the communication cost. In addition, an analysis of the Proximal Policy Optimization (PPO) algorithm is provided; the paper derives the estimation error bound, and reveals the relationship between the bound and exploration. To encourage the agent to balance their exploration and estimation error bound, a version of PPO named PPO-Exploration (PPO-Exp) is proposed. It can adjust the clip constraint parameter and make the exploration mechanism more flexible. The results of the experiments show that PPO-Exp performs better than the current algorithms in these tasks

Research Status of and Trends in 3D Geological Property Modeling Methods: A Review

Three-dimensional (3D) geological property modeling is used to quantitatively characterize various geological attributes in 3D space based on geostatistics with the help of computer visualization technology, and the results are often stored in grid data. The 3D geological property modeling includes two main components, grid model generation and property interpolation. In this review article, the existing grid generation methods are systematically investigated, and both traditional and multiple-point geostatistical algorithms involved in interpolation methods are comprehensively analyzed. It is shown that considering the numerical simulation of oil reservoirs, the orthogonal hexahedral grid remains the most suitable grid model for simulations in petroleum exploration and development. For the interpolation methods aspect, most geological phenomena are nonstationary, to simulate various types of reservoirs; the main development trends are increasing geological constraints and reducing the limitation of stationarity. Both methods have certain constraints, and the multiscale problem of multiple-point geostatistics poses a main challenge to the field. In addition, the deep-learning based method is a new trend in geological property modeling