Gait parameter fitting and adaptive enhancement based on cerebral blood oxygen information

Accurate recognition of patients’ movement intentions and real-time adjustments are crucial in rehabilitation exoskeleton robots. However, some patients are unable to utilize electromyography (EMG) signals for this purpose due to poor or missing signals in their lower limbs. In order to address this issue, we propose a novel method that fits gait parameters using cerebral blood oxygen signals. Two types of walking experiments were conducted to collect brain blood oxygen signals and gait parameters from volunteers. Time domain, frequency domain, and spatial domain features were extracted from brain hemoglobin. The AutoEncoder-Decoder method is used for feature dimension reduction. A regression model based on the long short-term memory (LSTM) model was established to fit the gait parameters and perform incremental learning for new individual data. Cross-validation was performed on the model to enhance individual adaptivity and reduce the need for individual pre-training. The coefficient of determination (R2) for the gait parameter fit was 71.544%, with a mean square error (RMSE) of less than 3.321%. Following adaptive enhancement, the coefficient of R2 increased by 6.985%, while the RMSE decreased by 0.303%. These preliminary results indicate the feasibility of fitting gait parameters using cerebral blood oxygen information. Our research offers a new perspective on assisted locomotion control for patients who lack effective myoelectricity, thereby expanding the clinical application of rehabilitation exoskeleton robots. This work establishes a foundation for promoting the application of Brain-Computer Interface (BCI) technology in the field of sports rehabilitation

High-amylose starch-based gel as green adhesive for plywood:Adhesive property, water-resistance, and flame-retardancy

The escalating demand for environmentally sustainable and cost-effective adhesives in the wood processing and manufacturing sector has prompted exploration into innovative solutions. This study introduces a novel gel adhesive composed of chemically unmodified high-amylose starch (G70, with 68 % amylose content) with a minimal proportion of urea-formaldehyde (UF) (UF/starch = 1:10, w/w). This G70/UF gel demonstrates remarkable adhesive capabilities for wooden boards under both dry conditions (with a shear stress of 4.13 ± 0.12 MPa) and wet conditions (with a shear strength of 0.93 ± 0.07 MPa after 2 h of water soaking). The study unveils that the elevated amylose content in the starch, coupled with a meticulously controlled isothermal process during bonding, is crucial for these enhancements. Specifically, the robust cohesion of amylose chains expedites phase separation between starch and UF, while the isothermal process facilitates the migration and enrichment of UF molecules at the gel-board and gel-air interfaces. Lacking these mechanisms, conventional amylopectin-rich starch/UF gels (27 % amylose content) show minimal improvement. Moreover, the G70/UF gel showcases exceptional fire retardancy. In all, the G70/UF gel presents a promising alternative for plywood production, reducing reliance on unhealthy UF resin while offering satisfactory bonding resistance in diverse conditions and superior flame retardancy.</p

Modulation of thermoelectric performance of Cn-BTBT molecular junctions by engineering contact geometry

Organic molecular devices are promising candidates for thermoelectric applications. By using density functional theory combined with non-equilibrium Green’s function method, we have investigated the thermoelectric properties of a single-molecule junction, which is constructed by 2,7-dialkyl [1] benzothieno [3,2-b] [1] benzothiophene derivatives (Cn-BTBT) connected with zigzag graphene nanoribbon electrodes. It is found that the phonon thermal conductance decreases with the increase of alkyl edge branches due to the local resonance. And the thermoelectric performance can be enhanced significantly by substituting bithiophene or biphosphole bridge anchor groups. A good thermoelectric figure of merit about 0.56 can be obtained near Fermi level. Moreover, we also found that the molecular device can be changed from p-type into n-type by changing the contact points, resulting in the transformation of Seebeck coefficient from positive to negative

Palmitic Acid Inhibits the Growth and Metastasis of Gastric Cancer by Blocking the STAT3 Signaling Pathway

Lipidomic analyses have suggested that palmitic acid (PA) is linked to gastric cancer. However, its effects and action mechanisms remain unclear. Therefore, we evaluated the effects of PA on cell proliferation, invasion, and apoptosis in human gastric cancer, as well as the role of p-STAT3 in mediating its effects. The results of the MTT and colony formation assays revealed that PA blocked gastric cancer cell proliferation in a concentration-dependent manner. The EdU-DNA assay indicated that 50 μM of PA could block gastric cell proliferation by 30.6–80.0%. The Transwell assay also confirmed the concentration dependence of PA-induced inhibitory effect on cell invasion. The flow cytometry analysis indicated that PA treatment for 18 h could induce gastric cancer cell apoptosis. The immunohistochemical staining revealed that p-STAT3 levels were higher in the gastric cancer tissues than in the control tissues. We demonstrated that PA treatment for 12 h decreased the expressions of p-STAT3, p-JAK2, N-cadherin, and vimentin, and inhibited the nuclear expression of p-STAT3 in gastric cancer cells. Finally, PA treatment (50 mg/kg) decreased gastric cancer growth (54.3%) in the xenograft models. Collectively, these findings demonstrate that PA inhibits cell proliferation and invasion and induces human gastric cancer cell apoptosis