Lunar rock investigation and tri-aspect characterization of lunar farside regolith by a digital twin.

Yutu-2 rover conducted an exciting expedition on the 41st lunar day to investigate a fin-shaped rock at Longji site (45.44°S, 177.56°E) by extending its locomotion margin on perilous peaks. The varied locomotion encountered, especially multi-form wheel slippage, during the journey to the target rock, established unique conditions for a fin-grained lunar regolith analysis regarding bearing, shear and lateral properties based on terramechanics. Here, we show a tri-aspect characterization of lunar regolith and infer the rock's origin using a digital twin. We estimate internal friction angle within 21.5°-42.0° and associated cohesion of 520-3154 Pa in the Chang'E-4 operational site. These findings suggest shear characteristics similar to Apollo 12 mission samples but notably higher cohesion compared to regolith investigated on most nearside lunar missions. We estimate external friction angle in lateral properties to be within 8.3°-16.5°, which fills the gaps of the lateral property estimation of the lunar farside regolith and serves as a foundational parameter for subsequent engineering verifications. Our in-situ spectral investigations of the target rock unveil its composition of iron/magnesium-rich low-calcium pyroxene, linking it to the Zhinyu crater (45.34°S, 176.15°E) ejecta. Our results indicate that the combination of in-situ measurements with robotics technology in planetary exploration reveal the possibility of additional source regions contributing to the local materials at the Chang'E-4 site, implying a more complicated geological history in the vicinity.

Light-triggered 2D electron gas in a GaN-based HEMT with sandwiched p-GaN layers.

In this work, a p-n junction-coupled metal-insulator-semiconductor (MIS) normally-off high-electron-mobility transistor (HEMT) UVPD is proposed. A two-dimensional electron gas (2DEG) at the AlN/U-GaN interface is entirely depleted with a dark current of 1.97 × 10-11 A because of the design of the sandwiched p-GaN layers. Under 365 nm illumination, the 2DEG is light triggered at Vds = 1 V with a high light on/off ratio of over 107 at a light power density of 286.39 mW·cm-2. Meanwhile, it exhibits fast rise and decay times of 248.39 and 584.79 µs, respectively. Moreover, a maximum responsivity (R) of 2.33 A/W, a maximum EQE of 793%, and a D* of 1.08 × 1013 Jones are obtained at Vds = 1 V. This can be attributed to the built-in electric fields in the configuration, which accelerate the flow of photogenerated carriers into the AlN/U-GaN channel. Additionally, the device showcases stable durability, repeatability, and a low driving voltage, making it highly suitable for applications in UV communication and space exploration.

Angle-Only Cooperative Orbit Determination Considering Attitude Uncertainty.

In this paper, a novel concept for cooperative orbit determination (OD) using inter-spacecraft angle-only measurements is proposed. Different from the conventional cooperative OD that only estimates orbit states, the attitude of the observer spacecraft is considered by incorporating the attitude into the estimated vector. The observability of a two-spacecraft system is analyzed based on the observability matrix. Observability analysis reveals that inter-spacecraft angle-only measurements are inadequate to estimate both the attitude and the orbit states in two-body dynamics. The observability of the two-spacecraft system can be improved by considering high-order gravitational perturbation or executing an attitude maneuver on the observer spacecraft. This is the first time that we present the observability analysis and orbit estimation results for a two-spacecraft system considering attitude uncertainty for the observer. Finally, simulation results demonstrate the effectiveness of the proposed method. The results in this paper can be potentially useful for autonomous managements of a spacecraft constellation and formation.

Real-Time Detection of Drones Using Channel and Layer Pruning, Based on the YOLOv3-SPP3 Deep Learning Algorithm.

Achieving a real-time and accurate detection of drones in natural environments is essential for the interception of drones intruding into high-security areas. However, a rapid and accurate detection of drones is difficult because of their small size and fast speed. In this paper a drone detection method as proposed by pruning the convolutional channel and residual structures of YOLOv3-SPP3. First, the k-means algorithm was used to cluster label the boxes. Second, the channel and shortcut layer pruning algorithm was used to prune the model. Third, the model was fine tuned to achieve a real-time detection of drones. The experimental results obtained by using the Ubuntu server under the Python 3.6 environment show that the YOLOv3-SPP3 algorithm is better than YOLOV3, Tiny-YOLOv3, CenterNet, SSD300, and faster R-CNN. There is significant compression in the size, the maximum compression factor is 20.1 times, the maximum detection speed is increased by 10.2 times, the maximum map value is increased by 15.2%, and the maximum precision is increased by 16.54%. The proposed algorithm achieves the mAP score of 95.15% and the detection speed of 112 f/s, which can meet the requirements of the real-time detection of UAVs.

Highly Accurate Visual Method of Mars Terrain Classification for Rovers Based on Novel Image Features.

It is important for Mars exploration rovers to achieve autonomous and safe mobility over rough terrain. Terrain classification can help rovers to select a safe terrain to traverse and avoid sinking and/or damaging the vehicle. Mars terrains are often classified using visual methods. However, the accuracy of terrain classification has been less than 90% in read operations. A high-accuracy vision-based method for Mars terrain classification is presented in this paper. By analyzing Mars terrain characteristics, novel image features, including multiscale gray gradient-grade features, multiscale edges strength-grade features, multiscale frequency-domain mean amplitude features, multiscale spectrum symmetry features, and multiscale spectrum amplitude-moment features, are proposed that are specifically targeted for terrain classification. Three classifiers, K-nearest neighbor (KNN), support vector machine (SVM), and random forests (RF), are adopted to classify the terrain using the proposed features. The Mars image dataset MSLNet that was collected by the Mars Science Laboratory (MSL, Curiosity) rover is used to conduct terrain classification experiments. The resolution of Mars images in the dataset is 256 × 256. Experimental results indicate that the RF classifies Mars terrain at the highest level of accuracy of 94.66%.

Does an increase in serum FGF21 level predict 28-day mortality of critical patients with sepsis and ARDS?

BACKGROUND: Sepsis may be accompanied by acute respiratory distress syndrome (ARDS) in patients admitted to intensive care units (ICUs). It is essential to identify prognostic biomarkers in patients with sepsis and ARDS. OBJECTIVE: Determine whether changes in the level of serum fibroblast growth factor 21 (FGF21) can predict the 28-day mortality of ICU patients with sepsis and ARDS. METHODS: Consecutive sepsis patients were divided into two groups (Sepsis + ARDS and Sepsis-only), and the Sepsis + ARDS group was further classified as survivors or non-survivors. Demographic data and comorbidities were recorded. The Sequential Organ Failure Assessment (SOFA) score and serum levels of cytokines and other biomarkers were recorded 3 times after admission. Multiple Cox proportional hazards regression was used to identify risk factors associated with 28-day mortality in the Sepsis + ARDS group. Multivariate receiver operating characteristic curve analysis was used to assess the different predictive value of FGF21 and SOFA. RESULTS: The Sepsis + ARDS group had a greater baseline SOFA score and serum levels of cytokines and other biomarkers than the Sepsis-only group; the serum level of FGF21 was almost twofold greater in the Sepsis + ARDS group (P < 0.05). Non-survivors in the Sepsis + ARDS group had an almost fourfold greater level of FGF21 than survivors in this group (P < 0.05). The serum level of FGF21 persistently increased from the baseline to the peak of shock and death in the non-survivors, but persistently decreased in survivors (P < 0.05). Changes in the serum FGF21 level between different time points were independent risk factors for mortality. No statistical difference was observed between the AUC of FGF21 and SOFA at baseline.  CONCLUSION: A large increase of serum FGF21 level from baseline is associated with 28-day mortality in ICU patients with sepsis and ARDS.

Predictive value of combined serum FGF21 and free T3 for survival in septic patients.

BACKGROUND: We examined the correlation between thyroid hormone (TH) concentrations and the serum fibroblast growth factor 21 (FGF21) concentration in septic patients and to assess the collaborative value of these factors in predicting 28-day mortality in septic patients. METHODS: A total of 120 consecutive patients with sepsis were divided into two groups according to their survival or death within 28 days after initial diagnosis of sepsis. RESULTS: Patients in the non-survivor group had significantly higher serum FGF21 concentrations but lower total and free triiodothyronine (T3) and tetraiodothyronine (T4) concentrations than those in the survivor group. Thyroid hormone concentrations, including T3, free T3, T4 and free T4, were significantly negatively correlated with the ∆SOFA and APACHE II scores as well as the serum FGF21, IL-6, tumor necrosis factor-α, IL-10, procalcitonin, and C-reactive protein concentrations. Logistic regression analysis showed that the ∆SOFA score, serum FGF21 concentration, and free T3 concentration were significant predictors of 28-day mortality. The model with variables of ∆SOFA score and serum FGF21 and free T3 concentrations had the greatest area under the curve of 0.969. CONCLUSION: The addition of free T3 and serum FGF21 to ∆SOFA score provided a significantly improved ability to predict 28-day mortality in septic patients.

Early increases in serum FGF21 levels predict mortality of septic patients.

BACKGROUND: Potential prognostic biomarkers for patients with sepsis have yet to be identified. The present study evaluated the prognostic value of fibroblast growth factor 21 (FGF21) levels in patients with sepsis. METHODS: A total of 120 consecutive Chinese patients with sepsis were prospectively included, and serum levels of FGF21 and biomarkers such as interleukin (IL)-6, tumor necrosis factor alpha (TNF-α), IL-10, procalcitonin (PCT), C-reactive protein (CRP), and lactate (LAC) were measured within 24 h after intensive care unit admission. The demographic and clinical characteristics including underlying diseases, Sequential Organ Failure Assessment (△SOFA), and acute physiology and chronic health evaluation II (APACHE II) scores were recorded. Patients were categorized into survival and non-survival groups according to the 28-day mortality. Correlations between FGF21, serum indicators, severity score and 28-day mortality were analyzed, and Cox regression analysis was performed to identify prognostic factors. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal cut-off of FGF21 for survival prediction. RESULTS: Non-survivors had significantly higher levels of FGF21, IL-6, TNF-α, IL-10, PCT, CRP, and LAC as well as higher SOFA and APACHE II scores compared with the survivors. FGF21 levels were positively correlated with age, waist circumference, levels of IL-6, IL-10, TNF- α, PCT, CRP, and LAC, △SOFA and APACHE II scores. ROC curves showed that FGF21 had a high sensitivity of 81.3% and specificity of 89.8% for predicting 28-day mortality. Patients with a FGF21 levels <3200 pg/ml had a significantly better survival rate than those with levels >3200 pg/ml, and thus, FGF21 was an independent prognostic factor for survival. CONCLUSION: FGF21 could serve as a new prognostic biomarker for sepsis survival.