Objective
To assess the efficacy of intensive acupuncture (3 times weekly for 8 weeks) versus sham acupuncture for knee osteoarthritis (OA).
Methods
In this multicenter, randomized, sham‐controlled ...trial, patients with knee OA were randomly assigned to receive electroacupuncture (EA), manual acupuncture (MA), or sham acupuncture (SA) 3 times weekly for 8 weeks. Participants, outcome assessors, and statisticians were blinded with regard to treatment group assignment. The primary outcome measure was response rate, which is the proportion of participants who simultaneously achieved minimal clinically important improvement in pain and function by week 8. The primary analysis was conducted using a Z test for proportions in the modified intent‐to‐treat population, which included all randomized participants who had ≥1 post‐baseline measurement.
Results
Of the 480 participants recruited in the trial, 442 were evaluated for efficacy. The response rates at week 8 were 60.3% (91 of 151), 58.6% (85 of 145), and 47.3% (69 of 146) in the EA, MA, and SA groups, respectively. The between‐group differences were 13.0% (97.5% confidence interval 97.5% CI 0.2%, 25.9%; P = 0.0234) for EA versus SA and 11.3% (97.5% CI −1.6%, 24.4%; P = 0.0507) for MA versus SA. The response rates in the EA and MA groups were both significantly higher than those in the SA group at weeks 16 and 26.
Conclusion
Among patients with knee OA, intensive EA resulted in less pain and better function at week 8, compared with SA, and these effects persisted though week 26. Intensive MA had no benefit for knee OA at week 8, although it showed benefits during follow‐up.
The synaptic weight modification depends not only on interval of the pre‐/postspike pairs according to spike‐timing dependent plasticity (classical pair‐STDP), but also on the timing of the preceding ...spike (triplet‐STDP). Triplet‐STDP reflects the unavoidable interaction of spike pairs in natural spike trains through the short‐term suppression effect of preceding spikes. Second‐order memristors with one state variable possessing short‐term dynamics work in a way similar to the biological system. In this work, the suppression triplet‐STDP learning rule is faithfully demonstrated by experiments and simulations using second‐order memristors. Furthermore, a leaky‐integrate‐and‐fire (LIF) neuron is simulated using a circuit constructed with second‐order memristors. Taking the advantage of the LIF neuron, various neuromimetic dynamic processes, including local graded potential leaking out, postsynaptic impulse generation and backpropagation, and synaptic weight modification according to the suppression triplet‐STDP rule, are realized. The realized weight‐dependent pair‐ and triplet‐STDP rules are clearly in line with findings in biology. The physically realized triplet‐STDP rule is powerful in developing direction and speed selectivity for complex pattern recognition and tracking tasks. These scalable artificial synapses and neurons realized in second‐order memristors can intrinsically capture the neuromimetic dynamic processes; they are the promising building blocks for constructing brain‐inspired computation systems.
Compared with the classical pair‐spike‐timing dependent plasticity (STDP), the triplet‐STDP is an advanced synaptic plasticity that induces improved learning capability. The triplet‐STDP is physically demonstrated and a leaky‐integrate‐and‐fire (LIF) neuron is simulated using second‐order memristors. The biorealistic implementation of the triplet‐STDP and the LIF neuron offers an efficient approach to the artificial intelligence through a simple artificial neural network.
Human pose estimation is one of the key technologies in action recognition, motion analysis, human-computer interaction, animation generation etc. How to improve its performance has become a current ...research hotspot. Lite-HRNet establishes long range connections between keypoints and exhibits good performance in human pose estimation tasks. However, the scale of this method to extract features is relatively single and lacks sufficient information interaction channels. To solve this problem, we propose an improved lightweight high-resolution network based on multi-dimensional weighting, named MDW-HRNet, which is implemented by the following aspects: first, we propose global context modeling, which can learn multi-channel and multi-scale resolution information weights. Second, a cross-channel dynamic convolution module is designed, it performs inter-channel attention aggregation between dynamic and parallel kernels, replacing the basic convolution module. These make the network capable of channel weighting, spatial weighting and convolution weighting. At the same time, we simplify the network structure to perform information exchange and information compensation between high-resolution modules while ensuring speed and accuracy. Experimental results show that our method achieves good performance on both COCO and MPII human pose estimation datasets, and its accuracy surpasses mainstream lightweight pose estimation networks without increasing computational complexity.
Aiming at a series of problems such as detection accuracy, calculation blocking, display delay, and so on in the ship detection of surveillance video, an improved YOLOv5 algorithm is proposed in this ...paper. First, to improve the detection performance, it is proposed to optimize the anchor box algorithm in the YOLOv5 network according to the ship target characteristics. Then, the t‐SNE algorithm is used to reduce and visualize the data set label information and perform weighted analysis on the processed features for low‐dimensional data. The mapped kernel k‐means clustering algorithm adaptively selects a more appropriate anchor box and considers the detection performance of large and small ship targets. Secondly, to improve the problem of computational blocking and delay, the BN scaling factor γ is used to compress the YOLOv5 network, so that the model can be reduced without reducing the detection performance. The optimized YOLOv5 framework is trained on the self‐integrated data set. The accuracy of the algorithm is increased by 2.34%, and the ship detection speed reaches 98 fps and 20 fps in the server environment and the low computing power version (Jetson nano), respectively.
In the intelligent traffic system, real-time and accurate detections of vehicles in images and video data are very important and challenging work. Especially in situations with complex scenes, ...different models, and high density, it is difficult to accurately locate and classify these vehicles during traffic flows. Therefore, we propose a single-stage deep neural network YOLOv3-DL, which is based on the Tensorflow framework to improve this problem. The network structure is optimized by introducing the idea of spatial pyramid pooling, then the loss function is redefined, and a weight regularization method is introduced, for that, the real-time detections and statistics of traffic flows can be implemented effectively. The optimization algorithm we use is the DL-CAR data set for end-to-end network training and experiments with data sets under different scenarios and weathers. The analyses of experimental data show that the optimized algorithm can improve the vehicles’ detection accuracy on the test set by 3.86%. Experiments on test sets in different environments have improved the detection accuracy rate by 4.53%, indicating that the algorithm has high robustness. At the same time, the detection accuracy and speed of the investigated algorithm are higher than other algorithms, indicating that the algorithm has higher detection performance.
Catalysts for CO oxidation reaction are mainly based on oxide/hydroxide materials with multicomponent active sites. Here, we report a nonoxide/hydroxide material, atomically dispersed dual-metal ...single sites (Fe–Co sites) on N-doped carbon support, as a highly active catalyst for CO oxidation. It can greatly lower the temperature for complete CO conversion as low as −73 °C with a turnover frequency of 0.096 s–1. X-ray absorption near-edge structure spectra, pulse-adsorption microcalorimetry, and density functional theory studies show that the Fe–Co sites synergistically catalyze CO oxidation facilely following the Langmuir–Hinshelwood (L-H) mechanism with CO preferentially adsorbing at the Co sites and O2 adsorbing at the Fe sites. These results, for the first time, reveal that the dual-metal single site on N-doped carbon can efficiency catalyze low-temperature CO oxidation reaction without the involvement of supports, such as oxygen vacancies and surface hydroxyl groups.
All-inorganic CsPbI3−xBrx perovskite solar cells (PSCs) are becoming increasingly mature due to their excellent optoelectronic properties. However, because of the poor environmental stability of the ...perovskite material, the device is susceptibly decomposed when exposed to moisture, high temperature, and high illumination. Therefore, a critical task is to address the problem of poor long-term stability in the environment, which serves as a significant obstacle impeding the commercialization of perovskite solar cells. This article introduces the incorporation of PEO into all-inorganic CsPbI3−xBrx perovskites with an advantageous thermal stability. PEO acts as a passivating agent near the grain boundary, and its high viscosity characteristics effectively improve the film-forming properties, leading to a substantial reduction in defects and to improving the surface uniformity. In addition, the grain boundaries that serve as water and oxygen penetration channels are filled, resulting in a substantial improvement in device stability. With 7.5 mg/mL PEO doping into CsPbI3−xBrx, the unencapsulated device maintained its original power conversion efficiency of 98% after being placed in a dark environment of 40% humidity and 25 °C for 10 days. Using PEO effectively enhanced the performance of the devices, with the highest PCE reaching 10.95%, significantly improving environmental stability.
We present an innovative approach to the production of single-crystal iron oxide nanorings employing a solution-based route. Single-crystal hematite (α-Fe2O3) nanorings were synthesized using a ...double anion-assisted hydrothermal method (involving phosphate and sulfate ions), which can be divided into two stages: (1) formation of capsule-shaped α-Fe2O3 nanoparticles and (2) preferential dissolution along the long dimension of the elongated nanoparticles (the c axis of α-Fe2O3) to form nanorings. The shape of the nanorings is mainly regulated by the adsorption of phosphate ions on faces parallel to c axis of α-Fe2O3 during the nanocrystal growth, and the hollow structure is given by the preferential dissolution of the α-Fe2O3 along the c axis due to the strong coordination of the sulfate ions. By varying the ratios of phosphate and sulfate ions to ferric ions, we were able to control the size, morphology, and surface architecture to produce a variety of three-dimensional hollow nanostructures. These can then be converted to magnetite (Fe3O4) and maghemite (γ-Fe2O3) by a reduction or reduction−oxidation process while preserving the same morphology. The structures and magnetic properties of these single-crystal α-Fe2O3, Fe3O4, and γ-Fe2O3 nanorings were characterized by various analytical techniques. Employing off-axis electron holography, we observed the classical single-vortex magnetic state in the thin magnetite nanorings, while the thicker rings displayed an intriguing three-dimensional magnetic configuration. This work provides an easily scaled-up method for preparing tailor-made iron oxide nanorings that could meet the demands of a variety of applications ranging from medicine to magnetoelectronics.
AIM To investigate whether micro RNA(mi R)-34 a mediates oxaliplatin(OXA) resistance of colorectal cancer(CRC) cells by inhibiting macroautophagy via the transforming growth factor(TGF)-β/Smad4 ...pathway.METHODS miR-34 a expression levels were detected in CRC tissues and CRC cell lines by quantitative real-time polymerase chain reaction. Computational search, functional luciferase assay and western blotting were used to demonstrate the downstream target of miR-34 a in CRC cells. Cell viability was measured with Cell Counting Kit-8. Apoptosis and macroautophagy of CRC cells were analyzed by flow cytometry and transmission electron microscopy, and expression of beclin I and LC3-II was detected by western blotting.RESULTS Expression of miR-34 a was significantly reduced while expression of TGF-β and Smad4 was increased in CRC patients treated with OXA-based chemotherapy. OXA treatment also resulted in decreased mi R-34 a levels and increased TGF-β and Smad4 levels in both parental cells and the OXA-resistant CRC cells. Activation of macroautophagy contributed to OXA resistance in CRC cells. Expression levels of Smad4 and miR-34 a in CRC patients had a significant inverse correlation and overexpressing mi R-34 a inhibited macroautophagy activation by directly targeting Smad4 through the TGF-β/Smad4 pathway. OXA-induced downregulation of miR-34 a and increased drug resistance by activating macroautophagy in CRC cells.CONCLUSION miR-34 a mediates OXA resistance of CRC by inhibiting macroautophagy via the TGF-β/Smad4 pathway.
Phosphate ions play a crucial role not only for the formation of the spindlelike precursors of the single‐crystalline hematite nanotubes that were synthesized by a facile hydrothermal method. They ...are also important for the adsorption and coordination effects. The mechanism of tube formation was deduced through EM observations as a coordination‐assisted dissolution process (see picture).
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