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The 2021 Ms 6.4 Yangbi earthquake, Yunnan, China, was recorded by the Dali Global Positioning System (GPS) network comprising 37 permanent stations within 100 km of the epicenter. All of these GPS stations recorded 1 Hz data, and 12 of them also recorded 5 Hz data. Using sophisticated data processing strategies, especially the method to overcome ionospheric and multipath errors, near-field waveforms of epoch-by-epoch displacement of all of the GPS stations within an epicentral distance of ∼50 km were derived from high-rate GPS observations with a root mean square error of 3.8, 4.2, and 8.2 mm for the east–west, north–south, and up components, respectively. The peak ground displacement of up to 14 cm in the horizontal direction and 4.2 cm in the vertical direction and the largest coseismic displacement of 3.1 cm in the horizontal direction and 3.2 cm in the vertical direction were observed for the stations within 6–9 km of the epicenter. The waveforms, with dominant periods between 7 and 10 s, present a systematic change in shape as a function of distance from the source, which demonstrates that the high-rate GPS observations can provide reliable relative-displacement response spectra at the periods needed in the design of large structures for resisting strong earthquakes. Comparisons of the GPS displacement time series at 1, 2.5, and 5 Hz suggest that 5 Hz data are able to capture strong ground information that are of interest to both earthquake seismologists and engineers. We conclude that the displacement waveforms and motion trajectories from high-rate GPS observations provide unique additional information of the near-field strong ground motion that is valuable to seismologists in unraveling the dynamic process of fault rupture and to engineers for designing large structures with very long period response.

The 2021 Yangbi Ms 6.4 earthquake in Yunnan, China, occurred in an area where the Global Positioning System (GPS) geodetic observations are particularly intensive. Based on a detailed retrospective analysis of the GPS observations of about 133 stations distributed in the proximately 400 km × 400 km region that contains the area affected by the earthquake., we obtain a high-resolution GPS velocity field and strain rate field and then derive the present-day slip rates of major faults in the region with the commonly used half-space elastic dislocation model and constraints from the GPS velocity field. Furthermore, by calculating the seismic moment accumulation and release and deficit rates in the main fault segments and combining with the distribution characteristics of small earthquakes, we evaluate the regional seismic risk. The results show that (1) there was a localized prominent strain accumulation rate around the seismogenic area of the impending Yangbi Ms 6.4 earthquake, although this was not the only area with a prominent strain rate in the whole region. (2) The seismogenic area of the earthquake was just located where the strain direction was deflected, which, together with the localized outstanding maximum shear strain and dilatation rates, provides us with important hints to determine the potential areas of future strong earthquakes. (3) Of all the seismogenic fault segments with relatively high potentials, judged using the elapsed time of historical earthquakes and effective strain accumulation rate, the middle section of the Weixi–Qiaohou fault has a higher earthquake risk than the southern section, the Midu–Binchuan section of the Chenghai fault has a higher risk than the Yongsheng section and the Jianchuan section of the Jianchuan–Qiaohou–Lijiang–Xiaojinhe fault has a higher risk than the Lijiang section.

Brain electroencephalography (EEG), the complex, weak, multivariate, nonlinear, and nonstationary time series, has been recently widely applied in neurocognitive disorder diagnoses and brain-machine interface developments. With its specific features, unlabeled EEG is not well addressed by conventional unsupervised time-series learning methods. In this article, we handle the problem of unlabeled EEG time-series clustering and propose a novel EEG clustering algorithm, that we call mwcEEGc. The idea is to map the EEG clustering to the maximum-weight clique (MWC) searching in an improved Fréchet similarity-weighted EEG graph. The mwcEEGc considers the weights of both vertices and edges in the constructed EEG graph and clusters EEG based on their similarity weights instead of calculating the cluster centroids. To the best of our knowledge, it is the first attempt to cluster unlabeled EEG trials using MWC searching. The mwcEEGc achieves high-quality clusters with respect to intracluster compactness as well as intercluster scatter. We demonstrate the superiority of mwcEEGc over ten state-of-the-art unsupervised learning/clustering approaches by conducting detailed experimentations with the standard clustering validity criteria on 14 real-world brain EEG datasets. We also present that mwcEEGc satisfies the theoretical properties of clustering, such as richness, consistency, and order independence.

A hydroponic method was conducted to test whetherPhytoremediation is an economical and environmentally friendly technology for the alleviation of heavy metal (HM)-contaminated soil. Improving bioremediation efficiency is crucial for this kind of technology. Many studies have shown that silicon plays a novel role in plant growth and adversity responses, but studies in the field of phytoremediation are limited. In addition, phytoremediation plant species are usually hyperaccumulators or may be tolerant crops, commercial crops, or wild species from mining areas, and the use of landscape species in phytoremediation is limited. This is the first report on the effects of silicate on the multi-HM bioaccumulation characteristics of a garden plant (

The present-day Global Positioning System (GPS) velocity field shows that the Indian Plate is not a complete rigid block, as its northeastern corner has been torn off and clockwise rotating relative to the main part. With the updated GPS velocity data, the Euler vector of the northeastern corner of the Indian Plate relative to the stable main plate is deduced as (89.566 ± 0.06° E, 26.131 ± 0.05° N, 1.34 ± 0.11°/Myr). The peak area of the present-day crustal deformation is located in the Chayu deformation belt with the compressional dilation strain rate over 160 nanostrain/yr. However, the Namche-Barwa Syntaxis with the massive crustal thickening and intense surface erosion is generally considered to be the previous locus of the strongest compressional stress in the Eastern Himalayan Syntaxis over long geological timescales. Thus, there is a discrepancy between the previous and present-day crustal deformation peak areas. We argue the migration of the crustal deformation peak area with a total distance of about 120 km and ascribe it to the variation of stress conditions caused by northeast India's clockwise rotation.

This article explores valid brain electroencephalography (EEG) selection for EEG classification with different classifiers, which has been rarely addressed in previous studies and is mostly ignored by existing EEG processing methods and applications. Importantly, traditional selection methods are not able to select valid EEG signals for different classifiers. This article focuses on a source control-based valid EEG selection to reduce the impact of invalid EEG signals and aims to improve EEG-based classification performance for different classifiers. We propose a novel centroid-based EEG selection approach named CenEEGs, which uses a scale-and-shift-invariance similarity metric to measure similarities of EEG signals and then applies a globally optimal centroid strategy to select valid EEG signals with respect to a similarity threshold. A detailed comparison with several state-of-the-art time series selection methods by using standard criteria on 8 EEG datasets demonstrates the efficacy and superiority of CenEEGs for different classifiers.

Bariatric surgery increases the risk of postoperative gallstone formation. Many studies have proposed ursodeoxycholic acid (UDCA) as a preventive agent for postoperative gallstone formation. This study aimed to investigate the effect of UDCA on gallstone formation after bariatric surgery in patients without preoperative gallstones.PubMed, the Web of Science, the Cochrane Library, and EBSCO were searched for articles assessing the effect of UDCA on gallstone formation after bariatric surgery. The outcome was the incidence of postoperative gallstones. Odds ratios were used to assess dichotomous variables, and random-effects models were used for statistical analyses.A total of 18 studies including 4,827 participants met the inclusion criteria. The statistical results showed that the incidence of gallstones in the UDCA group was significantly lower than in the control group. Furthermore, the occurrence of symptomatic gallstones and cholecystectomy was significantly reduced.In patients without preoperative gallstones, UDCA can effectively prevent the formation of gallstones after bariatric surgery. In addition, UDCA can significantly reduce the occurrence of symptomatic gallstones and the risk of postoperative cholecystectomy. Doses of 500 to 600 mg/d can be used as a measure to prevent postoperative gallstone formation.

Currently, electroencephalogram (EEG) is mostly analyzed in a supervised way, which requires EEG labels (e.g., EEG classification). With the ever-increasing amount of unlabeled/mislabeled EEG in neuropsychiatric disorder diagnosis, BCI, and rehabilitation, manually labeling of EEG data is a labor intensive and time-consuming process, and few labs have developed algorithms to analyze EEG in an unsupervised manner (i.e., EEG clustering). In this paper, we propose a cooperative game inspired approach to cluster multi-trial EEG data. The idea is to map multi-trial EEG clustering to the coalition formation in a cooperative game, and then identify cluster center (the EEG trial with highest Shapley value) and assign EEG trials into proper clusters based on their cross correlation-transformed Shapley values. We demonstrate the mapped EEG cooperative game is convex, and it leads to an algorithm for multi-trial EEG clustering named CoGEEGc. The CoGEEGc yields high-quality multi-trial EEG clustering with respect to intra-cluster compactness and inter-cluster scatter. We show that CoGEEGc outperforms 15 state-of-the-art EEG or time series clustering approaches through detailed experimentation on real-world multi-trial EEG datasets. Comparison against 15 methods with four theoretical properties of clustering further illustrates the superiority of CoGEEGc, as it satisfies two properties while other approaches only satisfy one.

Forward osmosis (FO) membranes have the advantages of low energy consumption, high water recovery rate, and low membrane pollution trend, and they have been widely studied in many fields. However, the internal concentration polarization (ICP) caused by the accumulation of solutes in the porous support layer will reduce permeation efficiency, which is currently unavoidable. In this paper, we doped Graphene oxide (GO) nanoparticles (50~150 nm) to a polyamide (PA) active layer and/or polysulfone (PSF) support layer, investigating the influence of GO on the morphology and properties of thin-film composite forward osmosis (TFC-FO) membranes. The results show that under the optimal doping amount, doping GO to the PA active layer and PSF support layer, respectively, is conducive to the formation of dense and uniform nano-scale water channels perpendicular to the membrane surface possessing a high salt rejection rate and low reverse solute flux without sacrificing high water flux. Moreover, the water channels formed by doping GO to the active layer possess preferable properties, which significantly improves the salt rejection and water permeability of the membrane, with a salt rejection rate higher than 99% and a water flux of 54.85 L·m−2·h−1 while the pure PSF-PA membrane water flux is 12.94 L·m−2·h−1. GO-doping modification is promising for improving the performance and structure of TFC-FO membranes.

In this paper, a novel multi-module neural network system named MMNNS is proposed to solve the imbalance problem in electrocardiogram (ECG) heartbeats classification. Four submodules are designed to construct the system: preprocessing, imbalance problem processing, feature extraction and classification. Imbalance problem processing module mainly introduces three methods: BLSM, CTFM and 2PT, which are proposed from three aspects of resampling, data feature and algorithm respectively. BLSM is used to synthesize virtual samples linearly around the minority samples. CTFM consists of DAE-based feature extraction part and QRS-based feature selection part, in which selected features and complete features are applied to determine the heartbeat class simultaneously. The processed data are fed into a convolutional neural network (CNN) by applying 2PT to train and fine-tune. MMNNS is trained on MIT-BIH Arrhythmia Database following AAMI standard, using intra-patient and inter-patient scheme, especially the latter which is strongly recommended. The comparisons with several state-of-the-art methods using standard criteria on three datasets demonstrate the superiority of MMNNS for improving detection of heartbeats and addressing imbalance in ECG heartbeats classification.

Large strike-slip faults play an important role in slip partitioning of the oblique convergence between the Indian plate and the Eurasian plate. The Karakorum-Jiali fault zone (KJFZ) is regarded as the southernmost major fault in the strike-slip faults system of the Tibetan plateau. The significance of the Jiali fault as the southern boundary of the eastward extrusion of the Tibetan plateau remains subject to debate due to the wide disagreements in its strike-slip rate. There is also a huge mismatch between its previously predicted low slip rate and the accommodation of the most significant compression in the frontal Eastern Himalayan Syntaxis. New GPS measurements suggest that the dextral strike-slip rate of the western segment, the middle segment, and the western part of the eastern segment of the Jiali fault is 5.0 ± 0.5 mm/yr, 2.4 ± 0.8 mm/yr, and 3.8 ± 0.9 mm/yr, respectively. As for the eastern segment of the Jiali fault, based on a two-dimensional elastic dislocation model, we search for the optimal solutions of the strike-slip rates along its two branch faults. They no longer accommodate strike-slip motion. But the diffuse active fault zone between the Mishimi and Puqu fault, inferred by the distribution of small earthquakes and systematic geologic mapping, may accommodate the strike slip motion with an estimated rate less than 5 mm/yr. Thus, it is predicted to have taken place the eastern segment. The eastern segment of the Jiali fault appears to have horizontally rotated clockwise around the Namche-Barwa Syntaxis.

A single-layer freeform reticulated shell with assembled double-ring joints was studied experimentally and numerically. Damping and static testing of a quarter-scale model was carried out. In addition, finite element models of the single-layer grid shells with double-ring joints and rigid joints were established, and the mechanical properties of the two shells were compared. The main conclusions are as follows. The eigenvalue buckling mode of the reticulated shell with double-ring joints is local buckling, and the double-ring joint is undamaged when the structure fails. The buckling capacity of the reticulated shell with a double-ring joint is approximately 70% of that of the rigidly jointed shell. The nonlinear buckling capacity and initial stiffness of the reticulated shell with a double-ring joint are approximately 66% of that of the rigidly jointed shell.