Spacecraft Homography Pose Estimation with Single-Stage Deep Convolutional Neural Network.

Spacecraft pose estimation using computer vision has garnered increasing attention in research areas such as automation system theory, control theory, sensors and instruments, robot technology, and automation software. Confronted with the extreme environment of space, existing spacecraft pose estimation methods are predominantly multi-stage networks with complex operations. In this study, we propose an approach for spacecraft homography pose estimation with a single-stage deep convolutional neural network for the first time. We formulated a homomorphic geometric constraint equation for spacecraft with planar features. Additionally, we employed a single-stage 2D keypoint regression network to obtain homography 2D keypoint coordinates for spacecraft. After decomposition to obtain the rough spacecraft pose based on the homography matrix constructed according to the geometric constraint equation, a loss function based on pixel errors was employed to refine the spacecraft pose. We conducted extensive experiments using widely used spacecraft pose estimation datasets and compared our method with state-of-the-art techniques in the field to demonstrate its effectiveness.

Global Analysis of the WOX Transcription Factor Family in Akebia trifoliata.

Akebia trifoliata is an economically important, self-incompatible fruit tree in the Lardizabalaceae family. Asexual propagation is the main strategy used to maintain excellent agronomic traits. However, the generation of adventitious roots during asexual propagation is very difficult. To study the important role of the WUSCHEL-related homeobox (WOX) transcription factor in adventitious root growth and development, we characterized this transcription factor family in the whole genome of A. trifoliata. A total of 10 AktWOXs were identified, with the following characteristics: length (657~11,328 bp), exon number (2~5), isoelectric point (5.65~9.03), amino acid number (176~361 AA) and molecular weight (20.500~40.173 kDa), and their corresponding expression sequence could also be detectable in the public transcriptomic data for A. trifoliata fruit. A total of 10 AktWOXs were classified into modern (6), intermediate (2) and ancient clades (2) and all AktWOXs had undergone strong purifying selection during evolution. The expression profile of AktWOXs during A. trifoliata adventitious root formation indicated that AktWOXs play an important role in the regulation of adventitious root development. Overall, this is the first study to identify and characterize the WOX family in A. trifoliata and will be helpful for further research on A. trifoliata adventitious root formation.

Pulse Design of Constant Strain Rate Loading in SHPB Based on Pulse Shaping Technique.

The Split Hopkinson pressure bar (SHPB) is widely used for characterizing the mechanical behavior of materials at high strain rates. One of the most challenging factors is achieving constant strain rate (CSR) loading of the specimen at a certain strain rate. Obtaining the effective incident pulse based on the experimental material for achieving CSR loading remains unresolved. This research focuses on obtaining the proper incident pulse for achieving constant strain rate loading using the pulse-shaping technique. A parameterized objective incident model in terms of the strain rate and quasi-static (or dynamic stress-strain) behavior of the material is established utilizing the three-wave method. Experimental pulses that closely resemble the desired objective pulses can be generated by adjusting parameters such as the geometry of the shaper, the shaper material, striker velocities, and the length of the striker according to the pulse-shaping model. The model is applied to the design of the incident pulse for B4CP/2024Al composite material, and the dynamic stress-strain curves at different strain rates are obtained under CSRs. This model provides effective guidance for selecting an appropriate shaper and achieving CSR loading in SHPB tests.

A Novel Multi-Scale Ceramic-Based Array (SiCb+B4Cp)/7075Al as Promising Materials for Armor Structure.

Ceramic panel collapse will easily lead to the failure of traditional targets. One strategy to solve this problem is to use separate ceramic units as armor panels. Based on this idea, we propose an aluminum matrix composite using pressure infiltration, containing an array of ceramic balls, the reinforcement of which consists of centimeter-scale SiC balls and micron-scale B4C particles. Three different array layouts were designed and fabricated: compact balls in the front panel (F-C), non-compact balls in the front panel (F-NC), and compact balls inside the target (I-C). The penetration resistance properties were tested using a 12.7 mm armor-piercing incendiary (API). The results show that there are no significant internal defects, and the ceramic balls are well-bonded with the matrix composite. The F-NC structure behaves the best penetration resistance with minimal overall damage; the I-C structure has a large area of spalling and the most serious damage. Finite element simulation reveals that the ceramic balls play a major role in projectile erosion; in the non-compact structure, the composite materials between the ceramic balls can effectively disperse the stress, thereby avoiding the damage caused by direct contact between ceramic balls and improving the efficiency of ceramic ball erosion projectiles. Furthermore, it is essential to have a certain thickness of supporting materials to prevent spalling failure caused by stress wave transmission during penetration. This multi-scale composite exhibits excellent ballistic performance, providing valuable insights for developing anti-penetration composite armor in future applications.

Bioinformatic workflow fragment discovery leveraging the social-aware knowledge graph.

Constructing a novel bioinformatic workflow by reusing and repurposing fragments crossing workflows is regarded as an error-avoiding and effort-saving strategy. Traditional techniques have been proposed to discover scientific workflow fragments leveraging their profiles and historical usages of their activities (or services). However, social relations of workflows, including relations between services and their developers have not been explored extensively. In fact, current techniques describe invoking relations between services, mostly, and they can hardly reveal implicit relations between services. To address this challenge, we propose a social-aware scientific workflow knowledge graph (S 2 KG) to capture common types of entities and various types of relations by analyzing relevant information about bioinformatic workflows and their developers recorded in repositories. Using attributes of entities such as credit and creation time, the union impact of several positive and negative links in S 2 KG is identified, to evaluate the feasibility of workflow fragment construction. To facilitate the discovery of single services, a service invoking network is extracted form S 2 KG, and service communities are constructed accordingly. A bioinformatic workflow fragment discovery mechanism based on Yen's method is developed to discover appropriate fragments with respect to certain user's requirements. Extensive experiments are conducted, where bioinformatic workflows publicly accessible at the myExperiment repository are adopted. Evaluation results show that our technique performs better than the state-of-the-art techniques in terms of the precision, recall, and F1.

Predictors of HBeAg seroconversion after long-term nucleos(t)ide analogues treatment for chronic hepatitis B: a multicenter study in real clinical setting.

AIMS: To evaluate the HBeAg seroconversion rate in real clinical setting and explore its predictors in long-term nucleos(t)ide analogues (NAs) treatment for chronic hepatitis B (CHB). METHODS: 251 patients were recruited from January 2001 to September 2009 in four hospitals in Hebei province, China, for this retrospective study. Clinical and laboratory data before and after treatment with lamivudine (LAM, 100mg daily), adefovir (ADV, 10mg daily), telbivudine (LDT, 600mg daily), entecavir (ETV, 0.5mg daily), and LAM/ADV combination were compared among three groups according to treatment outcomes: synchronous HBeAg loss and HBeAg seroconversion, anti-HBe development after treatment, and no anti-HBe. Adherence was also evaluated. RESULTS: In real clinical setting, cumulative HBeAg seroconversion rates were 14.3%, 32.7%, 43.0%, 46.9%, and 50.5% after 1, 2, 3, 5, and 8 years, respectively. 45 patients (17.9%) were non-adherent. Adherence (p<0.001, Hazard Ratio (HR)=2.203), elevated alanine aminotransferase (ALT) levels (p<0.001, HR=2.049), and non-vertical transmission (p=0.006, HR=1.656) were predictors of HBeAg seroconversion. CONCLUSION: Adherence, elevated ALT, and non-vertical transmission are predictors of HBeAg seroconversion in CHB patients treated with NAs.

Predictors of HBeAg seroconversion after long-term nucleos(t)ide analogues treatment for chronic hepatitis B: a multicenter study in real clinical setting

ABSTRACT Aims: To evaluate the HBeAg seroconversion rate in real clinical setting and explore its predictors in long-term nucleos(t)ide analogues (NAs) treatment for chronic hepatitis B (CHB). Methods: 251 patients were recruited from January 2001 to September 2009 in four hospitals in Hebei province, China, for this retrospective study. Clinical and laboratory data before and after treatment with lamivudine (LAM, 100 mg daily), adefovir (ADV, 10 mg daily), telbivudine (LDT, 600 mg daily), entecavir (ETV, 0.5 mg daily), and LAM/ADV combination were compared among three groups according to treatment outcomes: synchronous HBeAg loss and HBeAg seroconversion, anti-HBe development after treatment, and no anti-HBe. Adherence was also evaluated. Results: In real clinical setting, cumulative HBeAg seroconversion rates were 14.3%, 32.7%, 43.0%, 46.9%, and 50.5% after 1, 2, 3, 5, and 8 years, respectively. 45 patients (17.9%) were non-adherent. Adherence (p < 0.001, Hazard Ratio (HR) = 2.203), elevated alanine aminotransferase (ALT) levels (p < 0.001, HR = 2.049), and non-vertical transmission (p = 0.006, HR = 1.656) were predictors of HBeAg seroconversion. Conclusion: Adherence, elevated ALT, and non-vertical transmission are predictors of HBeAg seroconversion in CHB patients treated with NAs.