Return to the Moon: New perspectives on lunar exploration.

Lunar exploration is deemed crucial for uncovering the origins of the Earth-Moon system and is the first step for advancing humanity's exploration of deep space. Over the past decade, the Chinese Lunar Exploration Program (CLEP), also known as the Chang'e (CE) Project, has achieved remarkable milestones. It has successfully developed and demonstrated the engineering capability required to reach and return from the lunar surface. Notably, the CE Project has made historic firsts with the landing and on-site exploration of the far side of the Moon, along with the collection of the youngest volcanic samples from the Procellarum KREEP Terrane. These achievements have significantly enhanced our understanding of lunar evolution. Building on this success, China has proposed an ambitious crewed lunar exploration strategy, aiming to return to the Moon for scientific exploration and utilization. This plan encompasses two primary phases: the first crewed lunar landing and exploration, followed by a thousand-kilometer scale scientific expedition to construct a geological cross-section across the lunar surface. Recognizing the limitations of current lunar exploration efforts and China's engineering and technical capabilities, this paper explores the benefits of crewed lunar exploration while leveraging synergies with robotic exploration. The study refines fundamental lunar scientific questions that could lead to significant breakthroughs, considering the respective engineering and technological requirements. This research lays a crucial foundation for defining the objectives of future lunar exploration, emphasizing the importance of crewed missions and offering insights into potential advancements in lunar science.

Petrographic characterization to build an accurate rock model using micro-CT: Case study on low-permeable to tight turbidite sandstone from Eocene Shahejie Formation.

Pore scale flow simulations heavily depend on petrographic characterizing and modeling of reservoir rocks. Mineral phase segmentation and pore network modeling are crucial stages in micro-CT based rock modeling. The success of the pore network model (PNM) to predict petrophysical properties relies on image segmentation, image resolution and most importantly nature of rock (homogenous, complex or microporous). The pore network modeling has experienced extensive research and development during last decade, however the application of these models to a variety of naturally heterogenous reservoir rock is still a challenge. In this paper, four samples from a low permeable to tight sandstone reservoir were used to characterize their petrographic and petrophysical properties using high-resolution micro-CT imaging. The phase segmentation analysis from micro-CT images shows that 5-6% microporous regions are present in kaolinite rich sandstone (E3 and E4), while 1.7-1.8% are present in illite rich sandstone (E1 and E2). The pore system percolates without micropores in E1 and E2 while it does not percolate without micropores in E3 and E4. In E1 and E2, total MICP porosity is equal to the volume percent of macrospores determined from micro-CT images, which indicate that the macropores are well connected and microspores do not play any role in non-wetting fluid (mercury) displacement process. Whereas in E3 and E4 sandstones, the volume percent of micropores is far less (almost 50%) than the total MICP porosity which means that almost half of the pore space was not detected by the micro-CT scan. PNM behaved well in E1 and E2 where better agreement exists in PNM and MICP measurements. While E3 and E4 exhibit multiscale pore space which cannot be addressed with single scale PNM method, a multiscale approach is needed to characterize such complex rocks. This study provides helpful insights towards the application of existing micro-CT based petrographic characterization methodology to naturally complex petroleum reservoir rocks.

Optimizing the hierarchical prediction and coding in HEVC for surveillance and conference videos with background modeling.

For the real-time and low-delay video surveillance and teleconferencing applications, the newly video coding standard HEVC can achieve much higher coding efficiency over H.264/AVC. However, we still argue that the hierarchical prediction structure in the HEVC low-delay encoder still does not fully utilize the special characteristics of surveillance and conference videos that are usually captured by stationary cameras. In this case, the background picture (G-picture), which is modeled from the original input frames, can be used to further improve the HEVC low-delay coding efficiency meanwhile reducing the complexity. Therefore, we propose an optimization method for the hierarchical prediction and coding in HEVC for these videos with background modeling. First, several experimental and theoretical analyses are conducted on how to utilize the G-picture to optimize the hierarchical prediction structure and hierarchical quantization. Following these results, we propose to encode the G-picture as the long-term reference frame to improve the background prediction, and then present a G-picture-based bit-allocation algorithm to increase the coding efficiency. Meanwhile, according to the proportions of background and foreground pixels in coding units (CUs), an adaptive speed-up algorithm is developed to classify each CU into different categories and then adopt different speed-up strategies to reduce the encoding complexity. To evaluate the performance, extensive experiments are performed on the HEVC test model. Results show our method can averagely save 39.09% bits and reduce the encoding complexity by 43.63% on surveillance videos, whereas those are 5.27% and 43.68% on conference videos.

Background-Modeling-Based Adaptive Prediction for Surveillance Video Coding.

The exponential growth of surveillance videos presents an unprecedented challenge for high-efficiency surveillance video coding technology. Compared with the existing coding standards that were basically developed for generic videos, surveillance video coding should be designed to make the best use of the special characteristics of surveillance videos (e.g., relative static background). To do so, this paper first conducts two analyses on how to improve the background and foreground prediction efficiencies in surveillance video coding. Following the analysis results, we propose a background-modeling-based adaptive prediction (BMAP) method. In this method, all blocks to be encoded are firstly classified into three categories. Then, according to the category of each block, two novel inter predictions are selectively utilized, namely, the background reference prediction (BRP) that uses the background modeled from the original input frames as the long-term reference and the background difference prediction (BDP) that predicts the current data in the background difference domain. For background blocks, the BRP can effectively improve the prediction efficiency using the higher quality background as the reference; whereas for foreground-background-hybrid blocks, the BDP can provide a better reference after subtracting its background pixels. Experimental results show that the BMAP can achieve at least twice the compression ratio on surveillance videos as AVC (MPEG-4 Advanced Video Coding) high profile, yet with a slightly additional encoding complexity. Moreover, for the foreground coding performance, which is crucial to the subjective quality of moving objects in surveillance videos, BMAP also obtains remarkable gains over several state-of-the-art methods.

[Analysis of deaths caused by secondary damages of road traffic accidents: 17 fatal cases].

OBJECTIVE: To explore the forensic identification points of deaths caused by secondary damages of road traffic accidents. METHODS: Seventeen deaths caused by secondary damages of road traffic accidents were collected. Through scene investigation and necropsy, the basic information of the accidents, distribution and property of the injuries, and other information were collected. According to the collected data, the scene was reconstructed in order to confirm the injury process, analyze the way, mechanism and severity of injury, distinguish antemortem injury from postmortem injury, and determine the cause of deaths. RESULTS: Certain features such as serious injuries, multiple traumas, combined injuries, co-existence of antemortem and postmortem injuries, multiple causes of wounds, complex injury mechanism, as well as the mutual damaging and overlapping injuries were quite characteristically noted in these secondary traffic accident cases. CONCLUSION: Forensic assessment of deaths caused by secondary damages of road traffic accidents should be synthetically analyzed and judged through scene investigation and necropsy.

[Disability evaluation of 204 cases of children with brain injury in road traffic accidents].

OBJECTIVE: To study the types, characteristics and common complications as well as disability assessment for the children with craniocerebral injury in the road traffic accidents. METHODS: Data from 204 cases of children with cranio-injury in road traffic accidents were collected and were statistically analyzed according to the location injured, complication, the type of complication and the severity of disability. RESULTS: There were 64 cases of simple diffuse primary craniocerebral injury, 80 cases of simple local primary cranio-injury, 24 cases of diffuse secondary craniocerebral injury and 36 cases of local secondary cranio-injury. The main complications included traumatic epilepsy (14, 6.9%), traumatic cerebral infarction (9, 4.4%), traumatic hydrocephalus (7, 3.4%) and traumatic mental disorder (5, 2.5%). CONCLUSION: Among the children with cranio-injury due to road traffic accidents, simple primary cranio-injury was the most common result, whereas the traumatic epilepsy and traumatic cerebral infarction were the major types of complications. The assessment criteria for body impairment of the children with craniocerebral injury in the road traffic accidents should be broadened accordingly, with addition of certain specific items for children.

[Epidemiological research and analysis on the impaired person in road traffic accident in Chengdu area].

OBJECTIVE: To analyze epidemiological characteristics of road traffic accidents that resulted in injuries in Chengdu area, to find out the cause and to provide scientific a base for accident prevention. METHODS: Appraisal data of the injured in road traffic accident from January 2003 to October 2006 were re-examined. Detailed statistics were made which include gender, age, transportation mode, person types, the accident date and day, and location. RESULTS: Six thousand three hundred and sixty four cases involving road traffic accident were analyzed. Among the injured, male to female ratio was 1.84:1, and the age group of 18-50 were the largest proportion (66.34%). Bicyclists, motorcyclists and pedestrians made up 80.90% of the injured persons. Different age groups, different genders and those who were injured in different regions varied greatly in terms of transport modes they employed. In terms of injured parts, lower limb injury took up the highest proportion (39.49%), with cranium & cerebrum ranking second (22.77%). CONCLUSION: Different approaches and measures shall be taken in regard to different age groups, different regions, different times and different transport modes, and corresponding policies shall be adopted.