A Spatio-Temporal Capsule Neural Network with Self-Correlation Routing for EEG Decoding of Semantic Concepts of Imagination and Perception Tasks.

Decoding semantic concepts for imagination and perception tasks (SCIP) is important for rehabilitation medicine as well as cognitive neuroscience. Electroencephalogram (EEG) is commonly used in the relevant fields, because it is a low-cost noninvasive technique with high temporal resolution. However, as EEG signals contain a high noise level resulting in a low signal-to-noise ratio, it makes decoding EEG-based semantic concepts for imagination and perception tasks (SCIP-EEG) challenging. Currently, neural network algorithms such as CNN, RNN, and LSTM have almost reached their limits in EEG signal decoding due to their own short-comings. The emergence of transformer methods has improved the classification performance of neural networks for EEG signals. However, the transformer model has a large parameter set and high complexity, which is not conducive to the application of BCI. EEG signals have high spatial correlation. The relationship between signals from different electrodes is more complex. Capsule neural networks can effectively model the spatial relationship between electrodes through vector representation and a dynamic routing mechanism. Therefore, it achieves more accurate feature extraction and classification. This paper proposes a spatio-temporal capsule network with a self-correlation routing mechaninsm for the classification of semantic conceptual EEG signals. By improving the feature extraction and routing mechanism, the model is able to more effectively capture the highly variable spatio-temporal features from EEG signals and establish connections between capsules, thereby enhancing classification accuracy and model efficiency. The performance of the proposed model was validated using the publicly accessible semantic concept dataset for imagined and perceived tasks from Bath University. Our model achieved average accuracies of 94.9%, 93.3%, and 78.4% in the three sensory modalities (pictorial, orthographic, and audio), respectively. The overall average accuracy across the three sensory modalities is 88.9%. Compared to existing advanced algorithms, the proposed model achieved state-of-the-art performance, significantly improving classification accuracy. Additionally, the proposed model is more stable and efficient, making it a better decoding solution for SCIP-EEG decoding.

Introduction to the Meta-analysis method of functional magnetic resonance imaging research and the exploration of its application in the field of acupuncture. / åŠŸèƒ½ç£å ±æŒ¯ç ”ç©¶å ƒåˆ†æžæ–¹æ³•ä»‹ç»åŠå ¶åœ¨é’ˆåˆºé¢†åŸŸçš„åº”ç”¨æŽ¢æž.

In recent years, the number of functional magnetic resonance imaging (fMRI) research in acupuncture grows increasingly. However, due to the differences in acupoint selection, acupuncture technique and sample size, the problems get more prominent in terms of the diverse results and the lack of common rules of acupuncture among researches. By taking the fMRI research for post-stroke motor dysfunction (PSMD) treated with acupuncture as the example, this paper introduces the fMRI Meta-analysis technology for integrating the relevant research results and extracting the common rules, namely image-based Meta-analysis (IBMA) and coordinate-based Meta-analysis (CBMA). Considering the higher feasibility of CBMA, three available CBMA methods are explained specially, including activation likelihood estimation (ALE), kernel density analysis (KDA), and seed-based d mapping (SDM). Focusing on the precautions and operation procedure of CBMA, the review is conducted systematically on the type of fMRI research, task design, analytical method, and the thinking integrity of fMRI Meta-analysis, and the review findings are collated in charts. It aims to assist readers to understand the abstract and complex theories and practical information of this technology efficiently, conveniently and systematically, and hopes to provide the references for the future learning and the application.

Dynamic analysis of soil erosion in the affected area of the lower Yellow River based on RUSLE model.

With the accelerated development of urbanization, the exploration and usage of land resources is becoming more and more frequent, which leads to the decline of soil quality, resulting in a series of soil ecological issues, such as soil nutrient loss, soil quality degradation and destruction. At present, the contradiction between soil erosion and sustainable development of human society has become one of the hot issues studied by scholars. The Yellow River Basin is an important experimental area for high-quality development in China, constructing the Yellow River Ecological Economic Belt play an important role in China's regional coordinated development. Although most of the affected area of the Lower Yellow River (AALYR) is in the plain, they have a large population density and are in the historical farming area. In latest years, because of the development and transformation of modern society, their ecological environment has become more fragile and soil erosion problems has become increasingly serious. Studying and analyzing soil erosion is of vital meaning for ecological protection and can provide scientific support for soil conservation work. Depending on the data of precipitation, soil properties, land use, population, etc., this paper studies and analyzes the soil erosion in AALYR from 2000 to 2020 through the RUSLE. We found that during the 20 years the proportion of very slight and slight grade area increased, and the distribution of moderate and above erosion grade was less, mainly in Zibo, Jinan, Anyang, Zhengzhou, and Tai 'an. Nearly three quarters of the regional soil erosion grade didn't change, apart from the increase of slight grade area, the other erosion grades area showed a downward trend. We take the city, county and town zoning analysis find that as the scale decreases, the area of serious erosion grades increases, and the distribution is gradually detailed. Land use is the main influencing factor of erosion except DEM. Forestland and grassland are larger of the soil erosion in various types of land use. Through these conclusions in this paper, it is promising to provide theoretical references for the ecological environment governance and high-quality and sustainable development of great river basins of the world and similar regions.

A multimodal MRI study of XNKQ acupuncture for limb dysfunction after ischemic stroke: a randomized controlled study protocol.

Introduction: Limb motor dysfunction is one of the challenges in rehabilitation after cerebral ischemic stroke (CIS) and greatly affects the quality of life of patients. This study aims to investigate the central mechanisms of the curative effect with multimodal magnetic resonance imaging (MRI), which will provide additional evidence to support the application of Xingnao Kaiqiao (XNKQ) acupuncture. Methods and analysis: This trial is a randomized controlled trial. Patients who meet the criteria will be recruited and randomly divided into 2 groups. One group will receive acupuncture treatment and another group will not receive acupuncture treatment. Both groups will receive conventional treatment. In addition, 20 healthy individuals will be recruited who will not receive any treatment. The total course of treatment is 14 days. The primary outcome is multimodal MRI analysis. For safety assessment, adverse events will be observed and recorded. Ethics and dissemination: The study involving human subjects was reviewed and approved by the Ethics Committee of IRB of The First Teaching Hospital of Tianjin University of TCM (TYLL2023[K]031). This study complied with the Declaration of Helsinki. Written informed consent about this study was provided by the participants. The results of this study will be published in a peer-reviewed journal. Clinical trial registration: Chinese Clinical Trial Registration Center (ChiCTR2300078315) https://www.chictr.org.cn/.

Multiple scenario land use simulation based on a coupled MOGA-PLUS model: a case of the Yellow River Basin.

Land use changes have profoundly influenced global environmental dynamics. The Yellow River (YR), as the world's fifth-longest river, significantly contributes to regional social and economic growth due to its extensive drainage area, making it a key global player. To ensure ecological stability and coordinate land use demand, modeling the future land allocation patterns of the Yellow River Basin (YRB) will assist in striking a balance between land use functions and the optimization of its spatial design, particularly in water and sand management. In this research, we used a multi-objective genetic algorithm (MOGA) with the PLUS model to simulate several different futures for the YRB's land use between 1990 and 2020 and predict its spatial pattern in 2030. An analysis of the spatiotemporal evolution of land use changes in the YRB indicated that construction land expansion is the primary driver of landscape pattern and structure changes and ecological degradation, with climate change also contributing to the expansion of the watershed area. On the other hand, the multi-scenario simulation, constrained by specific targets, revealed that economic development was mainly reflected in land expansion for construction. At the same time, grassland and woodland were essential pillars to support the region's ecological health, and increasing the development of unused land emerged as a potential pathway towards sustainable development in the region. This study could be used as a template for the long-term growth of other large river basins by elucidating the impacts of human activities on land use and rationalizing land resource allocation under various policy constraints.

To explore the pathogenesis of Bell's palsy using diffusion tensor image.

To explore the pathogenesis of Bell's palsy using the diffusion tensor image on 3.0 T MR. The healthy people and the patients with Bell's palsy underwent intraparotid facial nerve scanning by using the DTI and T1 structural sequence at 3.0 T MR. The raw DTI data were performed affine transformation and nonlinear registration in the common MNI152_T1 space and resampled to the 0.4 mm3 voxel size. A group of 4 spherical seed regions were placed on the intratemporal facial nerves in the common space, bilaterally and symmetrically. The DTI data in the common space were used to track the intratemporal facial nerve fibers by using TrackVis and its Diffusion Toolkit. Each tractography was used to construct the maximum probability map (MPM) according to the majority rule. The fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) were calculated and extracted on the basis of MPM. For healthy people, there was no significant difference in FA, MD, RD and AD of bilateral facial nerves. For patients with Bell's palsy, there was no significant difference in AD, there was significant difference in FA, MD and RD between the affected nerve and the healthy nerve (P < 0.02). This study showed that the myelin sheath injury of the intratemporal facial nerve is the main cause of Bell's palsy. Most neural axons are not damaged. The results may explain the pathogenesis of the Bell's palsy, which is self-limited for most cases.

Understanding Relationships between Cultivated Land Pressure and Economic Development Level across Spatiotemporal Characteristics: Implications for Supporting Land-Use Management Decisions.

Food security is crucial to world peace. Economic development has posed a great threat to the protection of cultivated land. Considering 20 cities in the lower Yellow River (AALYR) as the study area, this study explored the spatial evolution of cultivated land pressure (CLP) and economic development from 1998 to 2018, revealing the spatiotemporal coupling characteristics of the CLP index and economic development. The main results are as follows: we discerned that CLP and economic development have an obvious spatiotemporal consistency during 1998-2018. The CLP showed a spatial pattern of overall stability, as well as local changes. Most prefecture-level cities experienced decreased significantly in CLP and improvements in food security. Overall, there were regional differences in the coupling relationships between CLP and economic development in the study area. The explanatory power of the proportion of secondary and tertiary industries were significantly higher than other driving factors. Therefore, while developing the economy rapidly, we should also protect cultivated land resources and improve the coordination level between them, which is essential to guarantee food security and a steady economic development.

Somatosensory Stimulation With XNKQ Acupuncture Modulates Functional Connectivity of Motor Areas.

Xingnao Kaiqiao (XNKQ) acupuncture is an acupuncture technique used for stroke patients. In 24 healthy volunteers, we applied this complex acupuncture intervention, which consists of a manual needle-stimulation on five acupuncture points (DU26 unilaterally, PC6, and SP6 bilaterally). XNKQ was compared to three control conditions: (1) insertion of needles on the XNKQ acupuncture points without stimulation, (2) manual needle-stimulation on five nearby non-acupuncture points, and (3) insertion of needles on the non-acupuncture points without stimulation. In a within-subject design, we investigated functional connectivity changes in resting-state functional magnetic resonance imaging (fMRI) by means of the data-driven eigenvector centrality (EC) approach. With a 2 × 2 factorial within-subjects design with two-factor stimulation (stimulation vs. non-stimulation) and location (acupuncture points vs. non-acupuncture points), we found decreased EC in the precuneus after needle-stimulation (stimulation

Effectiveness and Cost-Effectiveness of Tuina for Chronic Neck Pain: A Randomized Controlled Trial Comparing Tuina with a No-Intervention Waiting List.

OBJECTIVE: To evaluate whether tuina is more effective and cost-effective in reducing pain compared to no intervention in patients with chronic neck pain. DESIGN: Single-center randomized two-armed controlled trial. SETTING: University outpatient clinic specialized in Integrative Medicine. SUBJECTS: Outpatients with chronic neck pain were randomly allocated to tuina or no intervention. INTERVENTION: Six tuina treatments within 3 weeks. OUTCOME MEASURES: The primary outcome was the mean neck pain intensity during the previous 7 days on a visual analogue scale after 4 weeks (VAS, 0-100 mm, 0 = no pain, 100 = worst imaginable pain). Secondary outcomes included Neck Pain and Disability Scale (NPDS), Neck Disability Index (NDI), health-related quality of life (12-item quality-of-life questionnaire [SF-12]), medication intake, and cost-effectiveness after 4 and 12 weeks. Statistical analysis included analysis of covariance adjusted for baseline values and a full economic analysis from a societal perspective. RESULTS: Altogether, 92 outpatients were included (46 in both groups, 87% female, mean age 45.4 [standard deviation ±9.7], and mean VAS 57.7 ± 11.5). Tuina treatment led to a clinically meaningful reduction in neck pain intensity (group differences, 4 weeks: -22.8 mm [95% confidence interval, -31.7 to -13.8]; p < 0.001 and 12 weeks: -17.9 mm [-27.1 to -8.8], p < 0.001). No serious adverse events were observed. Total costs as well as quality-adjusted life years (QALYs) did not differ significantly between the groups. When taking group differences into account independently from their statistical significance, costs per QALY gained (incremental cost-effectiveness ratio) would range within a cost-effective area from €7,566 (for costs €10.28 per session) to €39,414 (cost €35 per session). CONCLUSION: An additional treatment with six tuina sessions over 3 weeks was effective, safe and relatively cost-effective for patients with chronic neck pain. A future trial should compare tuina to other best care options.