Search

This article is devoted to the event‐triggered practical tracking control for a class of high‐order nonlinear systems with serious uncertainties. Remarkably, the serious uncertainties are greatly reflected from the unknown control directions and input powers which give rise to essential obstacles in control design and hence lead to incapability of the traditional control methods on this topic. To solve the control problem, a novel switching event‐triggered control scheme is proposed by a skillful incorporation of logic‐based switching mechanism into the event‐triggered one. Specifically, two pivotal events are smartly chosen to give the event‐triggered mechanism for the determination of the sampling times. In particular, one of the events is used to give the switching varying mechanism, by which the controller parameters are respectively switched in two groups of sequences which are carefully chosen for the compensation of serious uncertainties. Under the proposed switching event‐triggered mechanism, a state‐feedback controller is designed which guarantees that all the signals of the closed‐loop system are bounded while system output practically tracks the reference signal, along with a finite number of switching of controller parameters as well as the exclusion of the Zeno phenomenon. Finally, simulation examples are provided to validate the effectiveness of the proposed theoretical results. [ABSTRACT FROM AUTHOR]

Most geophysical and geochemical data are commonly acknowledged to exhibit fractal and multifractal properties, but the fractal characteristics of polarizability have received limited attention from the literature. The present study demonstrates that the polarizability data of the graphite deposits have fractal characteristics and introduces the fractal method for its quantitative analysis to indicate and predict the properties of graphite deposits. The results show that the concentration-area (C-A) method is superior to classical interpolation in anomaly extraction but inferior to the spectrum-area (S-A) method in the coverage region. Because the type of graphite ore is sedimentary-metamorphic in this area, the graphite ore-bodies can be regarded as a special stratum, which is different from most metal deposits, and the anomaly of graphite ore are shown in the background mode of the S-A method. The high values of the background mode effectively indicate the potential areas where the graphite-bearing strata occur, while observing a decrease in the power-law exponent (β) of the background mode as the width of ore-bodies increases. The validity of this conclusion was confirmed based on the vertical profiles of the predicted area, and the uncharted ore vein was thereby identified. Furthermore, it was found that the anomaly mode can serve as a grade indicator of graphite ore rather than delineating the fault. By integrating the background and anomaly modes of the S-A method, we can quantitatively predict and effectively identify high-grade targets from sedimentary deposits containing minerals in future exploration. [ABSTRACT FROM AUTHOR]

Wavelet transformation has been widely used in geophysical and geochemical exploration, and the fractal feature of wavelet coefficients has recently stood out from many wavelet threshold methods. We introduced the wavelet–fractal method to analyze the polarizability and resistivity of graphite deposits. Due to the unique nature of graphite-bearing gneiss, characterized by high polarizability and low resistivity, we concluded that the polarizability background mode is better suited to depict the morphology of the graphite-bearing formation, with the resistivity background mode serving as complementary information for verification. Symlets5 is regarded as the optimal mother wavelet to indicate the characteristics of graphite ore by means of comparison and analysis. The polarizability anomalies showed two different linear forms: the direction of the measuring line and the strike of the ore bodies. According to the data of drill holes on the profile, we inferred that the high values of the anomaly mode can be used to delineate the target area where the graphite is enriched. Combining the application of both modes, we used the wavelet–fractal method for the quantitative prediction and effective selection of a potential area with a high grade. The approach used in this current study can be extended to the prospecting of other graphite deposits or sedimentary–metamorphic deposits containing conductive minerals, where geochemical and geophysical data are available. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to systematically explore the inclination of the lower central incisor and symphysis in alveolar bone in severe skeletal class III patients. Materials and methods: A total of 198 severe skeletal class III patients (ANB ≤ -4°) who underwent combined orthodontic and orthognathic treatment were divided into three groups based on the mandibular plane angle (MP-SN). Pretreatment lateral cephalograms were analysed and compared among the three groups. We also assessed cone-beam computed tomography (CBCT) images of 11 samples to investigate the reliability of the cephalometric analysis. Results: ANOVA showed no statistically significant differences in the angle between the long axis of the mandibular symphysis and the long axis of the lower central incisor (MIA) among the low-angle, normal-angle and high-angle groups (P > 0.05), while significant differences were found in the angle between the axis of the lower incisor and the mandibular plane (IMPA) among the three groups (P < 0.001). The mean IMPA decreased with increasing MP-SN in the 198 patients. The mean MIA in the low-angle and normal-angle groups was 3.70° and 3.52°, respectively, while the value (2.33°) was smaller in the high-angle group. Paired-samples t test showed no statistically significant differences between the cephalometric and CBCT measurements of the MP-SN, the angle between the mandibular plane and the Frankfort plane (FH-MP) and the MIA (P > 0.05). Conclusions: In severe skeletal class III patients, the long axis of the lower central incisor was highly consistent with the long axis of the mandibular symphysis, which was more obvious in the high-angle subjects. The MIA reflects the physiological inclination of the lower central incisor better than the IMPA. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to systematically explore the inclination of the lower central incisor and symphysis in alveolar bone in severe skeletal class III patients. Materials and methods: A total of 198 severe skeletal class III patients (ANB ≤ -4°) who underwent combined orthodontic and orthognathic treatment were divided into three groups based on the mandibular plane angle (MP-SN). Pretreatment lateral cephalograms were analysed and compared among the three groups. We also assessed cone-beam computed tomography (CBCT) images of 11 samples to investigate the reliability of the cephalometric analysis. Results: ANOVA showed no statistically significant differences in the angle between the long axis of the mandibular symphysis and the long axis of the lower central incisor (MIA) among the low-angle, normal-angle and high-angle groups (P > 0.05), while significant differences were found in the angle between the axis of the lower incisor and the mandibular plane (IMPA) among the three groups (P < 0.001). The mean IMPA decreased with increasing MP-SN in the 198 patients. The mean MIA in the low-angle and normal-angle groups was 3.70° and 3.52°, respectively, while the value (2.33°) was smaller in the high-angle group. Paired-samples t test showed no statistically significant differences between the cephalometric and CBCT measurements of the MP-SN, the angle between the mandibular plane and the Frankfort plane (FH-MP) and the MIA (P > 0.05). Conclusions: In severe skeletal class III patients, the long axis of the lower central incisor was highly consistent with the long axis of the mandibular symphysis, which was more obvious in the high-angle subjects. The MIA reflects the physiological inclination of the lower central incisor better than the IMPA. [ABSTRACT FROM AUTHOR]

To respond to travel demand in the MaaS system, improve transport efficiency, and optimize the framework of MaaS, we propose a travel demand response model based on a spatiotemporal preference clustering algorithm that considers the impact of travel preferences and features of the MaaS system to improve travel demand response and achieve full coverage of travel demands. Specifically, in the MaaS system, the time preference hierarchical clustering algorithm is optimized with travel preference as the perception factor and preference priority order as the iteration index. Then, we cluster the departure and arrival times of reservation demand points and iteratively analyze the discrete points to obtain the set of reservation demand points with convergent time dimensions under similar preferences. Then, the spatial preference DBSCAN clustering algorithm is improved with travel preference and preference priority order as the iteration indices, and spatial clustering of the time-dense points are updated by the silhouette coefficient to obtain reservation demand points with similar spatiotemporal preference and respond to the demands. Meanwhile, traffic resources are coordinated by the MaaS system and the flexible means of transport are deployed to spatiotemporal discrete points to achieve full coverage of travel demand. Simulation shows that when the neighborhood range is 0.5 km and the least number of reservation demand sites is 3, our spatiotemporal model achieves a response rate of reservation demand points at 95%, and a demand coverage rate of 100%, which is 15% and 6.7% higher than the hierarchical clustering model and the DBSCAN clustering model, respectively. The demand response rate is also improved compared to the spatiotemporal clustering model in the customized bus model. The model and algorithm have some applicability and can be applied to areas with fixed, semifixed and flexible route transport, thereby considerably improving the travel demand response efficiency and transport service quality. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is a common malignant tumor around the world. Studying the unique constitution of CRC patients is conducive to the application of personalized medical treatment for CRC. The most common types of constitution in CRC are cold and heat constitution. A previous study has suggested that the malignant progression in cold and heat constitution CRC are different; however, the mechanism remains unclear. The tumor microenvironment (TME) is likely to vary with each individual constitution, which may affect the tumor growth in different constitutions. The extracellular matrix (ECM), the most important component of TME, plays a critical role in disease progression and outcome in patients with CRC. Moreover, collagen, the major component of the ECM, determines the main functional characteristics of ECM and tissue fibrosis caused by collagen deposition, which is one of the signs of CRC malignant progression. This study aimed to explore the mechanisms leading to different colorectal carcinogenesis paradigms between the cold constitution and heat constitution within the context of ECM collagen deposition. We established the CRC rat models and enrolled 30 CRC patients with cold and heat constitution. The collagen-related parameters were detected by using Sirius red staining combined with polarized light microscope, and expressions of collagen (COL I and COL III) and lysyl oxidase (LOX and LOXL2) were determined using immunohistochemistry, while the mRNA levels of COL1A1, COL3A1, LOX, and LOXL2 were measured by qRT-PCR. We found that a higher degree of collagen deposition in the cold-constitution group. The results suggest cold and heat constitution may affect the colorectal carcinogenesis paradigm by influencing the early collagen deposition in colon tissue. The study may provide an effective idea for clinicians to improve the prognosis of CRC patients with different constitutions. [ABSTRACT FROM AUTHOR]

High-entropy perovskite thin films, as the prototypical representative of the high-entropy oxides with novel electrical and magnetic features, have recently attracted great attention. Here, we reported the electronic structure and charge transport properties of sol-gel-derived high-entropy Ba(Zr 0.2 Sn 0.2 Ti 0.2 Hf 0.2 Nb 0.2)O 3 thin films annealed at various temperatures. By means of X-ray photoelectron spectroscopy and absorption spectrum, it is found that the conduction-band-minimum shifts downward and the valence-band-maximum shifts upward with the increase of annealing temperature, leading to the narrowed band gap. Electrical resistance measurements confirmed a semiconductor-like behavior for all the thin films. Two charge transport mechanisms, i.e. , the thermally-activated transport mechanism at high temperatures and the activation-less transport mechanism at low temperatures, are identified by a self-consistent analysis method. These findings provide a critical insight into the electronic band structure and charge transport behavior of Ba(Zr 0.2 Sn 0.2 Ti 0.2 Hf 0.2 Nb 0.2)O 3 , validating it as a compelling high-entropy oxide material for future electronic/energy-related technologies. [ABSTRACT FROM AUTHOR]

Background: It remains controversial whether patients with Stage II colon cancer would benefit from chemotherapy after radical surgery. This study aims to assess the real effectiveness of chemotherapy in patients with stage II colon cancer undergoing radical surgery and to construct survival prediction models to predict the survival benefits of chemotherapy.Methods: Data for stage II colon cancer patients with radical surgery were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching (1:1) was performed according to receive or not receive chemotherapy. Competitive risk regression models were used to assess colon cancer cause-specific death (CSD) and non-colon cancer cause-specific death (NCSD). Survival prediction nomograms were constructed to predict overall survival (OS) and colon cancer cause-specific survival (CSS). The predictive abilities of the constructed models were evaluated by the concordance indexes (C-indexes) and calibration curves.Results: A total of 25,110 patients were identified, 21.7% received chemotherapy, and 78.3% were without chemotherapy. A total of 10,916 patients were extracted after propensity score matching. The estimated 3-year overall survival rates of chemotherapy were 0.7% higher than non- chemotherapy. The estimated 5-year and 10-year overall survival rates of non-chemotherapy were 1.3 and 2.1% higher than chemotherapy, respectively. Survival prediction models showed good discrimination (the C-indexes between 0.582 and 0.757) and excellent calibration.Conclusions: Chemotherapy improves the short-term (43 months) survival benefit of stage II colon cancer patients who received radical surgery. Survival prediction models can be used to predict OS and CSS of patients receiving chemotherapy as well as OS and CSS of patients not receiving chemotherapy and to make individualized treatment recommendations for stage II colon cancer patients who received radical surgery. [ABSTRACT FROM AUTHOR]

This paper is devoted to the event-triggered practical tracking control of a class of uncertain free-flying flexible-joint space robots (FFSRs) under unknown dead-zone input. The remarkable characteristics of the paper are reflected by the coarse information on the reference signal since its time derivatives are not necessarily available for feedback, and moreover, by the serious uncertainties which contain unknown nonlinear dynamics, parameters without known nominal parts, and the external disturbance. Then, the traditional control schemes on this topic become incapable. For this, a novel event-triggered control scheme is proposed by a skilful use of adaptive technique. Specifically, a dynamic gain with a smart choice of its updating law is incorporated into the vectorial backstepping framework, which not only overcomes the serious uncertainties contained in the system and dead-zone input but also handles the influence of sampling errors. Consequently, two adaptive event-triggered controllers are designed which ensure that all the states of the resulting closed-loop system are bounded while the system output practically tracks the reference signal, along with the exclusion of the Zeno phenomenon. Finally, an example is given to validate the effectiveness of the proposed theoretical results. [ABSTRACT FROM AUTHOR]

Nano-bubble irrigation, as a new irrigation technology, can deliver fertilizer-mixed oxygen-enriched water to the root zone of crops, representing a new means for increasing crop yield and carbon sequestration and emission reduction. To systematically analyze the effects of nano-bubble irrigation on crop yield, soil aeration, and soil greenhouse gas (GHG) emissions, as well as evaluating its contribution to the net greenhouse warming potential (NGWP) in greenhouse agriculture, this study was conducted in greenhouse facilities in Zhengzhou, China and focused on tomato plants. A 2-factor, 2-level, completely randomized trial of nitrogen application (low N1: 120 kg/hm2 and normal N2: 180 kg/hm2), conventional irrigation, and nano-bubble irrigation (C: 5 ppm and A: 15 ppm) was conducted. Compared with conventional irrigation, crop yield increased by 18.94% and 16.36% (p < 0.05), CO2 emission by 10.72% and 5.71% (p < 0.05), N2O emission by 29.76% and 35.74% (p < 0.05), and CH4 uptake by 300.67% and 327.67% (p < 0.05) under nano-bubble irrigation. The nano-bubble irrigation increased the crop yield, thus significantly improving the NGWP sink for greenhouse gases. The low-nitrogen and regular-nitrogen treatments increased NGWP by 22.69% and 14.52%, respectively (p < 0.05). This suggests that nano-bubble irrigation can significantly improve soil aeration, increase tomato yield and biomass, and significantly improve crop carbon sequestration. In the future, nano-bubble irrigation can be used along with soil amendments to achieve a more efficient increase in yield and enhance the ability of farmland to sequester carbon and reduce emissions. [ABSTRACT FROM AUTHOR]

As widely used commercial sensors, amperometric biosensors based on electrochemical (EC) reactions exhibit good linearity and reproducibility but suffer from a low dynamic range and poor limit of detection (LoD). In contrast, biosensors utilizing field‐effect transistors (FETs) demonstrate a wide detection range and ultralow LoDs but are susceptible to interferences or ionic strength influences and have poor quantitative accuracy due to their nonlinear response mechanism. Here, EC and carbon nanotube (CNT) FET‐based biosensors are integrated into one chip via a compatible fabrication process. The dual‐mode biosensing chip (DMSC) provides the advantages from both the EC biosensors and FET biosensors; these advantages include high reliability and accuracy for quantitatively detecting glucose, a dynamic detection range spanning 6 orders of magnitude, and a detection limit of 1 fM. The introduction of a time‐division multiplexing detection method enables the DMSC to carry out complementary detection of the same target, providing early warning of specific abnormal biomarkers and accurate determination of their concentration in real time. The DMSC approach is generally applicable to the detection of other biomarkers and provides exciting opportunities for more accurate self‐monitoring diagnostics in real situations. [ABSTRACT FROM AUTHOR]

• Smartphones show excellent ability to predict original soil properties. • Image segmentation significantly improves soil property prediction accuracy. • Significant differences in dominant regions between segmentation methods. • The K-means clustering segmentation method outperforms the OUST method. Prediction of soil properties based on images of original soil acquired from smartphones is considered a potential alternative to conventional soil property determination due to its convenience and low cost. However, images of the original soil may contain distracting information such as fissures, shadows, and rocks, which may affect the image feature extraction and property prediction results. Four unsupervised image segmentation methods, namely the maximum interclass variance (OUST) method, the local adaptive threshold segmentation (LATS) method, the K-means clustering segmentation (KMCS) method, and the natural break point segmentation (NBPS) method, were used to segment 62 images of original soil taken by smartphones in outdoor sunny conditions. The number of segmentation levels (N) for KMCS and NBPS varied from 2 to 10. The dominant region, determined as the region with the highest percentage of image area after segmentation, was selected for subsequent property prediction. The results of the segmentation methods revealed significant differences in the dominant regions, leading to significant variations in color and texture features (p < 0.05). The random forest approach was used to construct predictive models for soil Munsell colour, soil organic matter (SOM) content, and soil texture content. The validation results demonstrated that the image segmentation methods improved the prediction accuracy of all three soil properties compared to that of the unsegmented images. Among the segmentation methods, KMCS (N = 3 and 4) exhibited the highest segmentation performance, surpassing the widely used OUST method. This research highlights the significance of image segmentation methods in predicting soil properties based on images of original soil samples and recommended it as an essential process for future soil image processing. The findings of this study have the potential to advance the development of smartphone-based prediction of properties of original soils. [ABSTRACT FROM AUTHOR]

Brain signaling occurs across a wide range of spatial and temporal scales, and analysis of brain signal variability and synchrony has attracted recent attention as markers of intelligence, cognitive states, and brain disorders. However, current technologies to measure brain signals in humans have limited resolutions either in space or in time and cannot fully capture spatiotemporal variability, leaving it untested whether temporal variability and spatiotemporal synchrony are valid and reliable proxy of spatiotemporal variability in vivo. Here we used optical voltage imaging in mice under anesthesia and wakefulness to monitor cortical voltage activity at both high spatial and temporal resolutions to investigate functional connectivity (FC, a measure of spatiotemporal synchronization), Multi-Scale Entropy (MSE, a measure of temporal variability), and their relationships to Regional Entropy (RE, a measure of spatiotemporal variability). We observed that across cortical space, MSE pattern can largely explain RE pattern at small and large temporal scales with high positive and negative correlation respectively, while FC pattern strongly negatively associated with RE pattern. The time course of FC and small scale MSE tightly followed that of RE, while large scale MSE was more loosely coupled to RE. fMRI and EEG data simulated by reducing spatiotemporal resolution of the voltage imaging data or considering hemodynamics yielded MSE and FC measures that still contained information about RE based on the high resolution voltage imaging data. This suggested that MSE and FC could still be effective measures to capture spatiotemporal variability under limitation of imaging modalities applicable to human subjects. Our results support the notion that FC and MSE are effective biomarkers for brain states, and provide a promising viewpoint to unify these two principal domains in human brain data analysis. • Validated multiscale entropy and functional connectivity as proxy of spatiotemporal variability with voltage imaging. • Demonstrated that multiscale entropy and functional connectivity can reflect similar brain state differences. • Addressed the practical signal resolution of EEG and fMRI on the spatiotemporal variability assessments. • Provided a unified interpretation of multiscale entropy and functional connectivity measures. [ABSTRACT FROM AUTHOR]

In this study, we plan to utilize the plentiful oxygen-containing functional groups present on the surface of GO as an anchoring point for [PtCl 6 ]2−, thereby creating a highly dispersible electroplating material. [Display omitted] • Construction of [PtCl 6 ]2−-GO colloid based on anchoring strategy. • [PtCl 6 ]2−-GO colloid are utilized in a variety of electrodes. • Cluster-scale PtNPs (3 nm) were grown on the rGO surface under mild conditions. • The Pt-rGO-modified electrodes provide excellent sensing and HER performance. In this study, a bifunctional [PtCl 6 ]2−-GO colloidal material was prepared by anchoring [PtCl 6 ]2− by abundant oxygen-containing functional groups in protonated graphene oxide. Two modification strategies, surface overcoating and electrochemical in situ deposition, were adopted to modify the screen-printed carbon electrode (SPCE), foam electrodes (CuF, NiF), respectively, and Pt-rGO, which uniformly covered the electrode surface, was obtained by a simple onestep of reducing [PtCl 6 ]2−-GO. The effectiveness of the modified materials and electrode modification strategies prepared was validated by tinidazole electrochemical detection and hydrogen evolution reaction (HER). The results indicated that the Pt-rGO modified SPCE possessed lower LOD and higher sensitivity for the detection. Furthermore, as for HER, optimized Pt-rGO-modified NiF and CuF required only 26 mV and 76 mV overpotentials in alkaline and acidic solutions, respectively, to obtain current densities of 10 mA cm−2. This was largely ascribed to the synergistic interaction between platinum and rGO, with the synthesized platinum-rGO displaying stronger active sites and higher intrinsic activity. In particular, Pt, which acts as an active center, could offer part of its electron to H 2 O and adjacent reduced graphene oxide sites, thus promoting strong electrical connections and efficient HER kinetics. [ABSTRACT FROM AUTHOR]

Semiconductor metal oxides (SMOs) nanomaterials are a category of sensing materials that are widely applied to chemiresistive NO x gas sensors. However, there is much space to improve the sensing performance of SMOs nanomaterials. Therefore, how to improve the sensing performance of SMOs nanomaterials for NO x gases has always attracted the interest of researchers. Up to now, there are few reviews focus on the modification strategies of SMOs which applied to NO x gas sensors. In order to compensate for the limitation, this review summarizes the existing modification strategies of SMOs, hoping to provide researchers a view of the research progress in this filed as comprehensive as possible. This review focuses on the progress of the modification of SMOs nanomaterials for chemiresistive NO x (NO, NO 2) gas sensors, including the morphology modulation of SMOs, compositing SMOs, loading noble metals, doping metal ions, compositing with carbon nanomaterials, compositing with biomass template, and compositing with MXene, MOFs, conducting polymers. The mechanism of each strategy to enhance the NO x sensing performance of SMOs-based nanomaterials is also discussed and summarized. In addition, the limitations of some of the modification strategies and ways to address them are discussed. Finally, future perspectives for SMOs-based NO x gas sensors are also discussed. [Display omitted] • An overview of modification strategies for semiconductor metal oxides applied to chemiresistive NO x gas sensors. • The mechanisms of each modification strategy to enhance gas sensing performance are summarized. • The limitations of some modification methods are mentioned and solutions to improve them are discussed. [ABSTRACT FROM AUTHOR]

The ability to quickly and accurately determine soil organic matter (SOM) content is critical for effective soil management decisions. Using the colour of soil images captured by smartphones to predict SOM content has emerged as a promising alternative to traditional wet chemistry methods. However, natural environments can present a complex array of light conditions that can compromise the accuracy and consistency of soil image colour acquisition, thus limiting the method's applicability. To address this issue, we propose five colour calibration patterns (C0 (no calibration), C1 (neutral grey), C2 (RGB), C3 (RGBCMY), and C4 (24 colours)), based on a 24-colour standard card. These patterns were used to calibrate the images of 352 original soil samples obtained from smartphones in three different lighting environments - L1 (100–2000 lx), L2 (35,000–40,000 lx), and L3 (75,000–80,000 lx). Random forest models were used to construct predictive models of soil organic matter (SOM) content based on images. Our findings indicate that smartphones exhibit complex spectral response characteristics, which result in poor image accuracy and stability of uncalibrated (C0) images under varying lighting conditions. The uncalibrated (C0) soil images in different lighting environments exhibited high colour difference (∆E mean = 14.11), resulting in poor SOM model sharing performance (R2 mean = 0.52 and RMSE mean = 20.33 g/kg). The use of colour calibration methods reduced the colour difference between soil images (∆E mean = 8.19) and improved the shared accuracy of the model (R2 mean = 0.61 and RMSE mean = 12.00 g/kg). The pattern of colour calibration has a key impact on the performance of the model application. The model sharing accuracy was found to be higher for the same or similar colour calibration pattern combination compared to different combinations of colour calibration patterns. Overall, the richer the colour calibration blocks, the better the model's shared performance. The findings of this research can enhance the application performance of soil attribute prediction models based on the colour of objects captured by smartphones in natural environments. • Differences in light intensity affect the colour stability of smartphone images. • Colour calibration reduces image colour differences in different light for phones. • Colour calibration boosts the shared ability of the attribute prediction model. • Colour calibration patterns with rich colours for better model-sharing ability. [ABSTRACT FROM AUTHOR]

Predicting stock market trends is the basic daily routine task that investors should perform in the stock trading market. Traditional market trends prediction models are generally based on hand-crafted factors or features, which heavily rely on expensive expertise knowledge. Moreover, it is difficult to discover hidden features contained in the stock time series data, which are otherwise helpful for predicting stock market trends. In this paper, we propose a novel stock market trends prediction framework SMART with a self-supervised stock technical data sequence embedding model S3E. Specifically, the model encodes stock technical data sequences into embeddings, which are further trained with multiple self-supervised auxiliary tasks. With the learned sequence embeddings, we make stock market trends predictions based on an LSTM and a feed-forward neural network. We conduct extensive experiments on China A-Shares market and NASDAQ market to show that our model is highly effective for stock market trends prediction. We further deploy SMART in a leading financial service provider in China and the result demonstrates the effectiveness of the proposed method in real-world applications. [ABSTRACT FROM AUTHOR]

Can RNA transcripts of granulosa cells be used to assess oocyte quality? The possibility of predicting the developmental competence of oocytes by RNA sequencing analysis of granulosa cells was evaluated. Granulosa cell samples were collected from 29 women undergoing assisted reproductive technology treatment and divided into two groups: 14 samples from the high blastocyst rate group and 15 from the low blastocyst rate group. Ten samples from each group were selected for RNA sequencing. A total of 129 differentially expressed genes associated with high developmental competence of oocytes were identified. COL1A2 , renin and COL1A1 were selected and further examined by quantitative real-time polymerase chain reaction (qRT-PCR). Expression levels of COL1A2 and renin by qRT-PCR were consistent with the results of RNA sequencing. RNA sequencing data could provide novel marker genes for the non-invasive evaluation of oocyte quality and embryo developmental competence. [ABSTRACT FROM AUTHOR]

SF3B1, an essential RNA splicing factor, is frequently mutated in various types of cancers, and the cancer-associated SF3B1 mutation causes aberrant RNA splicing. The aberrant splicing of several transcripts, including MAP3K7 , promotes tumorigenesis. Here, we identify a premature termination codon in the aberrantly spliced transcript of MAP3K7. Treatment of HEK293T cells transfected with the K700E-mutated SF3B1 with cycloheximide leads to increased accumulation of the aberrant spliced transcript of MAP3K7 , demonstrating that the aberrantly spliced transcript of MAP3K7 is targeted by nonsense-mediated decay. The aberrantly spliced MAP3K7 transcript uses an aberrant 3ʹ splice sites and an alternative branchpoint sequence. In addition, the aberrant splicing of MAP3K7 requires not only the polypyrimidine tract associated with normal splicing but also an alternative polypyrimidine tract upstream of the aberrant 3ʹ splice site. Other cancer-associated SF3B1 mutations also cause the aberrant splicing of MAP3K7 , which depends on the same sequence features. Our data provide a further understanding of the mechanisms underlying aberrant splicing induced by cancer-associated SF3B1 mutation, and reveal an important role of alternative polypyrimidine tract in diseases. [ABSTRACT FROM AUTHOR]

A novel heterotrophic nitrification and aerobic denitrification (HNAD) bacteria, identified as Bacillus thuringiensis strain WXN-23, was isolated from husk feed filtrate of a pig farm. It was the first report of Bacillus thuringiensis with the capability for HNAD and could adapt to the condition of low Carbon/Nitrogen (C/N) ratio. Nitrogen could be efficiently removed by the strain WXN-23 in simulated wastewater, be it in single or mixed form nitrogen sources. The nitrogen balance revealed that 63.5% of the initial nitrogen (5.32 mg) was lost in the form of N 2. The conditions for maximum total nitrogen (TN) removal efficiency (95.996%) were shaking speed of 126.89 r/min, a carbon C/N ratio of 5.91, the temperature of 32.81 °C, and a pH value of 8.17. The nitrification-denitrification metabolic pathway (NH 4 +–N→NH 2 OH→NO 2 −-N→NO 3 −-N→NO 2 −-N→NO→N 2 O→N 2) under aerobic conditions was determined on the basic of characteristic of N removal, N balance analysis, enzyme assay and functional genes amplification results. Strain WXN-23 was effective at wastewater treatment, with TN, NH 4 +-N, NO 3 −-N and NO 2 −-N removal efficiencies of 82.12%, 86.74%, 90.74% and 100%, respectively. • Found a heterotrophic nitrifying and aerobic denitrification Bacillus thuringiensis strain. • Bacillus thuringiensis strain WXN-23 can adapt to the condition of low C/N ratio. • Strain WXN-23 can efficiently remove nitrogen from water under aerobic conditions. • Hardly any greenhouse gas was generated by strain WXN-23 during nitrogen removal. [ABSTRACT FROM AUTHOR]

This study aimed to use different dose verification methods Treatment Planning System (TPS), thimble ionization chamber and two-dimensional matrix ionization chamber (MatriXX) to explore the compensating effects of several materials on high-energy electron beam irradiation. In this study, we positioned plexiglass panels, wet medical gauze, colloidal compensatory material and Vaseline compensator, all of the same thickness, flat on the surface of a MatriXX. The above four materials were placed on the surface of a thimble ionization chamber and irradiated with a linear accelerator. Under the same irradiation parameters, the compensation dose of of the tested materials was worked out by a dosimeter, which was connected at the thimble ionization chamber. Under vertical irradiation from the linear accelerator, the accelerator used the same irradiation conditions for the four materials, which were flat on the surface of the MatriXX, then determined the distribution of compensation doses by the soft system matching with the MatriXX. The results showed that the compensation dose of moist medical gauze was lower than the other three materials, the compensation dose of Plexiglass plate, colloidal compensatory material and vaseline compensation were approximate. The dose compensation effect of the vaseline compensation material made by our research group was close to the plexiglass plate and colloidal compensatory material used in radiotherapy in real life. Its physical and chemical properties are stable, easy to manufacture and store, and economical and practical. [ABSTRACT FROM AUTHOR]

This study investigated the process and mechanism of synergistically assisted hydrogen production from tailings and coal slurry. We have identified the optimal tailings as lead-zinc tailings through experimentation with different tailings mixed with pulverized coal. Furthermore, we have analyzed the electrochemical properties of Fe2+ and Fe3+ at different concentration gradients in a hydrochloric acid environment and our results have confirmed that the presence of Fe3+ in the simplified environment does not affect the electrochemical processes. to determine the respective roles and effects of the extract and residue of the lead-zinc tailings slurry with equal amounts of coal dust added to them, which has confirmed that it is the lead-zinc tailings extract that has the primary influence. In addition, the electrocatalysis of Fe3+ in the presence of both lead-zinc tailings and coal results in a small increase in current density, and the improvement in current density due to direct and indirect oxidation of coal particles is also extremely limited. Based on our analysis, we have concluded that the increase in current density brought about by the synergistic hydrogen production from lead-zinc tailings-supported coal is mainly due to the different oxidation processes of Fe2+. [Display omitted] • For the first time, tailings was used for assisted coal electrolysis to produce H 2. • Adding lead-zinc tailings improved the efficiency of coal electrolysis by 133.3%. • The reason for the significant increase in efficiency is the acceleration of the reaction by Fe2+ as an electron donor. [ABSTRACT FROM AUTHOR]

Chondrocytes are the sole cellular constituents of normal cartilage. The degeneration and apoptosis of these cells are considered the main cause of osteoarthritis (OA). Previous studies have suggested that the enhancement of autophagy in chondrocytes can delay the progression of osteoarthritis by affecting intracellular metabolic activity, i.e., by regulating the metabolism of nutrients, which can delay cell aging and death. In this review, we explored the relationship between autophagy and chondrocyte metabolism and provided new ideas for the prevention and treatment of OA. [ABSTRACT FROM AUTHOR]

The arctic strain of Chlorella sp. (Chlorella-Arc) exists in the coldest and driest arctic ecosystems, and it is a new resource of active polysaccharides. The extraction of crude polysaccharide from Chlorella-Arc was optimized using the response surface methodology. A crude polysaccharide yield of approximately 9.62 ± 0.11% dry weight was obtained under these optimized conditions. Three fractions (P-I, P-II, and P-III) were present after purification by 2-diethylaminoethanol Sepharose Fast Flow and Sephadex G-100 chromatography. The P-IIa fraction demonstrated significant antioxidant activities. Moreover, P-IIa was an α- and β-type heteropolysaccharide with a pyran group and contained variable amounts of rhamnose, arabinose, glucose, and galactose based on fourier-transform infrared spectroscopy, high-performance liquid chromatography, and ¹H and 13C nuclear magnetic resonance imaging. Production of high amounts of polysaccharide may allow further exploration of the microalgae Chlorella-Arc as a natural antioxidant. [ABSTRACT FROM AUTHOR]

Ulcerative colitis (UC) with its rapidly increasing incidence has become an emerging challenge for public health. Therapeutic agents are required to be specifically delivered to colon epithelial cells and macrophages with controlled release in the cytoplasm for wound healing, inflammation alleviation, and microbiota rebalance. As a promising biomaterial for accomplishing this, Antheraea pernyi silk fibroin (ApSF) was selected and engineered to form nanoparticles (NPs) loaded with the anti-inflammatory drug, resveratrol (Res). The intrinsic features of these fabricated Res-ApNPs included targeting of colonic epithelial cells and macrophages, lysosomal escape capacity, and responsiveness to pH, reactive oxygen species (ROS), and glutathione, which were pertinent to their functional units such as arginine-glycine-aspartate tripeptides, α -helixes, β -sheets, and disulfide bonds, enabling on-demand release of Res molecules in the cytoplasm of target cells. The Res-ApNP treatment restored damaged colonic epithelial barriers, polarized macrophages to type M2, alleviated inflammatory reactions, and reduced the level of intracellular ROS. Oral treatment with chitosan-alginate hydrogels embedded with Res-ApNPs substantially relieved UC symptoms, as evidenced by decreased colonic inflammation, increased synthesis of tight-junction proteins, and rebalanced intestinal microbiota. Our findings suggest that these high-performance ApSF-based NPs can be developed as effective drug carriers for oral UC treatment. [Display omitted] [ABSTRACT FROM AUTHOR]

• Powder size and carbon matrix worked together to influence growth of SiC whiskers. • Hexagonal prism whiskers were bounded by (1 1 1) planes form to minimize total energy. • The morphology of SiC whisker was discussed from the perspective of atomic diffusion. The SiC whiskers were prepared on carbon matrix by high hydrogen-containing silicone oil (H-PSO) as raw materials. Based on the results of previous experiments, we further studied the effect of non-heat treatment factor on growth of SiC whiskers, including type and thickness of carbon matrix, size of embedded powders, and growth catalysts. The results showed that the powder particle size and the matrix should be properly matched to facilitate whisker growth. When grown on 2 mm graphite plate, the particle size was 150 μm-180 μm, the SiC whiskers were straight, smooth and homogeneous, showing hexagonal prisms morphology, which were bounded by low-energy (1 1 1) planes, rather than silicon oxide coating. The change of particle size led to the change of concentration of reaction gas and partial pressure of oxygen, which resulted in the difference content of silicon oxide in whiskers, showing hexagonal prisms or cylindrical morphology. Adding growth catalyst, the whisker morphology was not as good as the whisker grown without catalyst, and the growth mechanism had changed. [ABSTRACT FROM AUTHOR]