Some studies verified that the pulsed current charging technique could extend the battery lifetime and improve the charging performance of lithium-ion batteries. However, some researchers are skeptical of this opinion because their studies have not found any advantages of pulsed current charging over conventional constant current (CC) charging. Positive pulsed current (PPC), the most common pulsed current mode, was selected for the investigation in this work. The effect of the PPC with various parameters, including the duty cycle, amplitude, and frequency, on the performance and lifetime of lithium-ion batteries, are investigated by experiments. According to the experimental results, the charging speed, charging capacity, and maximum rising temperature are mainly determined by the duty cycle and amplitude of the PPC. The battery lifetime with PPC under the frequency range from 0.05 Hz to 2 kHz has been verified to be extendable. Moreover, the battery lifetime extension can even be over 100% under a specific frequency PPC compared with CC charging. This is the first work that summarizes the law of the pulse frequency on battery lifetime extension. In the future, the pulsed current is expected to be used in fast charging technologies without compromising battery lifetime.

Objective: We developed two neural network models to estimate the three-dimensional ground reaction force (GRF) and center of pressure (COP) based on marker trajectories obtained from a markerless motion capture system. Methods: Gait data were collected using two cameras and three force plates. Each gait dataset contained kinematic data and kinetic data from the stance phase. A multi-layer perceptron (MLP) and convolutional neural network (CNN) were constructed to estimate each component of GRF and COP based on the three-dimensional trajectories of the markers. A total of 100 samples were randomly selected as the test set, and the estimation performance was evaluated using the correlation coefficient (r) and relative root mean square error (rRMSE). Results: The r-values for MLP in each GRF component ranged from 0.918 to 0.989, with rRMSEs between 5.06% and 12.08%. The r-values for CNN in each GRF component ranged from 0.956 to 0.988, with rRMSEs between 6.03–9.44%. For the COP estimation, the r-values for MLP ranged from 0.727 to 0.982, with rRMSEs between 6.43% and 27.64%, while the r-values for CNN ranged from 0.896 to 0.977, with rRMSEs between 6.41% and 7.90%. Conclusions: It is possible to estimate GRF and COP from markerless motion capture data. This approach provides an alternative method for measuring kinetic parameters without force plates during gait analysis.

Introduction: Emerging evidence has revealed that long noncoding RNA (lncRNA) play important role in almost all kinds of human cancers. LINC00908 has been reported to be involved in the development of prostate cancer, colorectal cancer and gastric cancer which was functioned as an oncogene. However, the potential biology role and molecular mechanism of LINC00908 in diffuse large B-cell lymphoma are still unclear. Methods: LINC00908 and miR-671-5p expression were evaluated in DLBCL tissues and cell lines using RT-qPCR. CCK-8 and transwell assay were used to analyze the in vitro role of LINC00908 in DLBCL progression. The xenograft model was used to explore the in vivo role of LINC00908 in DLBCL growth. The physical interaction between LINC00908 and miR-671-5p was confirmed using bioinformatics analysis and a dual luciferase assay, RIP and RNA pull down. Results: The expression of LINC00908 was markedly up-regulated in diffuse large B-cell lymphoma tissues and cell lines, and the decreased expression of LINC00908 significantly inhibited diffuse large B-cell lymphoma cell proliferation and invasion. Then, we revealed that LINC00908 directly interacted with miR-671-5p, which was down-regulated in diffuse large B-cell lymphoma cells and highly expressed with LINC00908 knockdown. Moreover, luciferase reporter assays and RNA immunoprecipitation (RIP) assay further proved that miR-671-5p is a direct target of LINC00908 in diffuse large B-cell lymphoma cells. Rescue experiments were also performed, and we confirmed that LINC00908 acts as an oncogene role in diffuse large B-cell lymphoma through miR-671-5p. Finally, the influence of LINC00908 silence significantly inhibited diffuse large B-cell lymphoma growth in vivo. Conclusion: LINC00908 promotes malignancy of diffuse large B-cell lymphoma through regulating miR-671-5p.