Genetically modified human umbilical cord blood cells as a promising strategy for treatment of spinal cord injury

Spinal cord injury （SCI） continues to be a pressing health and social problem. The injury leads to neuronal and glial cell death accompanied by degeneration of nerve fibers. There are currently no particularly effective treatments. SCI causes profound disabil- ity of people affected and has attracted increased attention in the international field of neuroregeneration. For the past two decades, much hope has been placed in cell therapies for the restoration of both structure and function of the injured spinal cord. Embryonic and neural stem cells, olfactory ensheathing cells, microglia-like cells, Schwann cells, mesenchymal stem cells.

Advances and prospects of PVDF based polymer electrolytes

Exploring highly foldable batteries with no safety hazard is a crucial task for the realization of portable,wearable,and implantable electric devices.Given these concerns,developing solid-state batteries is one of the most promising routes to achieve this aspiration.Because of the excellent flexibility and processability,polyvinylidene fluoride(PVDF) based electrolytes possess great potential to pack high energy density flexible batteries,however,suffers the various intrinsic shortcomings such as inferior ionic conductivity,a high degree of crystallinity,and lack of reactive groups.Clearing the progress of the present state and concluding the specific challenges faced by PVDF based electrolytes will help to develop PVDF based polymer batteries.In this review,we summarize the recent progress of gel polymer electrolytes and all solid polymer electrolytes based on PVDF.The ion transport mechanisms and preparation methods of PVDF based electrolytes are briefly introduced.Meanwhile,the current design principle and properties of electrolytes are highlighted and systematically discussed.Some peculiar modified strategies performed in lithium-sulfur batteries and lithium-oxygen batteries are also included.Finally,this review describes the challenges and prospects of some solid-state electrolytes to provide strategies for manufacturing high-performance PVDF electrolytes aimed at practical application with flexible requirements.

Ensemble deep transfer learning driven by multisensor signals for the fault diagnosis of bevel-gear cross-operation conditions

The existing intelligent fault diagnosis techniques of bevel gear focus on single-sensor signal analysis under the steady operation condition.In this study,a new method is proposed based on ensemble deep transfer learning and multisensor signals to enhance the fault diagnosis adaptability and reliability of bevel gear under various operation conditions.First,a novel stacked autoencoder(NSAE)is constructed using a denoising autoencoder,batch normalization,and the Swish activation function.Second,a series of source-domain NSAEs with multisensor vibration signals is pretrained.Third,the good model parameters provided by the source-domain NSAEs are transferred to initialize the corresponding target-domain NSAEs.Finally,a modified voting fusion strategy is designed to obtain a comprehensive result.The multisensor signals collected under the different operation conditions of bevel gear are used to verify the proposed method.The comparison results show that the proposed method can diagnose different faults in an accurate and stable manner using only one target-domain sample,thereby outperforming the existing methods.