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The reconstruction control of modular self-reconfigurable spacecraft (MSRS) is addressed using an adaptive sliding mode control (ASMC) scheme based on time-delay estimation (TDE) technology. In contrast to the ground, the base of the MSRS is floating when assembled in orbit, resulting in a strong dynamic coupling effect. A TED-based ASMC technique with exponential reaching law is designed to achieve high-precision coordinated control between the spacecraft base and the robotic arm. TDE technology is used by the controller to compensate for coupling terms and uncertainties, while ASMC can augment and improve TDE’s robustness. To suppress TDE errors and eliminate chattering, a new adaptive law is created to modify gain parameters online, ensuring quick dynamic response and high tracking accuracy. The Lyapunov approach shows that the tracking errors are uniformly ultimately bounded (UUB). Finally, the on-orbit assembly process of MSRS is simulated to validate the efficacy of the proposed control scheme. The simulation results show that the proposed control method can accurately complete the target module’s on-orbit assembly, with minimal perturbations to the spacecraft’s attitude. Meanwhile, it has a high level of robustness and can effectively eliminate chattering.

Three-dimensional printing (3DP) has high flexibility and controllability, and has attracted extensive attention in the biomedical field. However, the scaffolds prepared only by 3D bioprinting have poor mechanical properties, and they cannot effectively carry the required drugs. At the same time, compared with the size of cells, the pore size of 3D printed scaffolds is relatively large, and the efficiency of cell inoculation and tissue formation are still limited by the pore resolution of scaffolds. Therefore, a new method of forming 3D printing trachea composites is proposed. When combined, 3D bioprinting and electrospinning (ESP) can overcome the issues associated with scaffolds prepared by 3D bioprinting alone. Nanofibers create a suitable environment for cell growth. In terms of material use, Polycaprolactone (PCL) is commonly used as an ideal material source for 3D printing, but its biomechanical properties are insufficient. Cellulose nanocrystals (CNC) can effectively improve the properties of polymers such as PCL. Therefore, the inner layer of the scaffold used in tracheal surgery is created from PCL/CNC composite by 3D bioprinting, and the outer nano-cellulose film is deposited on the inner surface by electrospinning. Mechanical properties and cell adhesion/growth of scaffolds prepared by 3D bioprinting combined with electrospinning were found to be superior to those of scaffolds prepared by 3D bioprinting.

Abstract Background In the CRISPR-Cas9 system, the efficiency of genetic modifications has been found to vary depending on the single guide RNA (sgRNA) used. A variety of sgRNA properties have been found to be predictive of CRISPR cleavage efficiency, including the position-specific sequence composition of sgRNAs, global sgRNA sequence properties, and thermodynamic features. While prevalent existing deep learning-based approaches provide competitive prediction accuracy, a more interpretable model is desirable to help understand how different features may contribute to CRISPR-Cas9 cleavage efficiency. Results We propose a gradient boosting approach, utilizing LightGBM to develop an integrated tool, BoostMEC (Boosting Model for Efficient CRISPR), for the prediction of wild-type CRISPR-Cas9 editing efficiency. We benchmark BoostMEC against 10 popular models on 13 external datasets and show its competitive performance. Conclusions BoostMEC can provide state-of-the-art predictions of CRISPR-Cas9 cleavage efficiency for sgRNA design and selection. Relying on direct and derived sequence features of sgRNA sequences and based on conventional machine learning, BoostMEC maintains an advantage over other state-of-the-art CRISPR efficiency prediction models that are based on deep learning through its ability to produce more interpretable feature insights and predictions.

Objective: To obtain information on the current clinical research training status and evaluate the training needs comprehensively for medical staff in hospitals. Methods: This survey was initiated and conducted by the Health and Family Planning Commission of Shenzhen in conjunction with the Peking University Clinical Research Institute (Shenzhen) from Sep 2016 through Nov 2016. It was planned that no less than 10% of the total staff from each participating hospital were invited to complete the survey. All participants filled out the questionnaire anonymously and voluntarily. Results: A total of 644 subjects from 12 hospitals completed the survey with the response rate of 28.7%. The majority of respondents (80%) have attended training related to clinical research knowledge and skills, however, medical research ethical aspects and statistics knowledge have been provided only for 40% and 27% of respondents, respectively. With regard to preference on training subjects and contents, Protocol design and development (74%) is ranked first, followed by the data analysis and summary (59%) among those researchers from medical professions. Project management and quality control course are mostly demanded for technicians and nurses (53%). Unpredictably, no more than 40% of the respondents consider that it is necessary to receive "Regulation and Research ethics" course even for those Principal investigators. Conclusions: Our survey results indicated that training subjects on protocol design and research ethics are urgently needed and relatively inadequate in China. An appropriate clinical research competency training model should be developed and provided for hospital staffs in China.

Excessive use of nitrogen fertilizer in China and its adverse effects on agricultural production have been a national and global concern. In addition to massive public initiatives to promote sustainable farm practices, grass-rooted innovations are emerging in the niche, many of which take the forms of information and communication technologies (ICT) and digital services. This study examines the effects of ICT-based extension services provided by an entrepreneurial startup on adopting sustainable farming practices. We found no significant reduction in N-fertilizer use for wheat production. But the ICT-based services promoted farmers to adapt N-fertilizer use towards site-specific management. The business model of the entrepreneurial venture faces great challenges in becoming participatory and financially sustainable.