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M‐N‐C single‐atom catalysts (SACs) are promising electrode materials for many electro‐reduction reactions. However, their stability is far from practical applications, and their deactivation mechanism has been rarely investigated. Herein, we demonstrate the structural degradation of M‐N‐C (M=Co, Ni, and Fe) at industrial‐grade current density for long‐term electro‐reduction. Both M‐N and N‐C bonds are broken, resulting in the gradual hydrogenation and dissolution of N in the form of ammonia. The residual M is finally converted to M‐containing core–shell nanoparticles after sequential dissolution, redeposition, and electro‐reduction. The destruction of the M‐N‐C structure and the formation of nanoparticles greatly affect the electrocatalytic performance. Our work highlights the structural degradation and deactivation mechanism of M‐N‐C‐type SACs under strong reductive conditions and provides useful information for inspiring researchers to develop new strategies to improve the electrocatalytic stability of similar types of materials. [ABSTRACT FROM AUTHOR]

M‐N‐C single‐atom catalysts (SACs) are promising electrode materials for many electro‐reduction reactions. However, their stability is far from practical applications, and their deactivation mechanism has been rarely investigated. Herein, we demonstrate the structural degradation of M‐N‐C (M=Co, Ni, and Fe) at industrial‐grade current density for long‐term electro‐reduction. Both M‐N and N‐C bonds are broken, resulting in the gradual hydrogenation and dissolution of N in the form of ammonia. The residual M is finally converted to M‐containing core–shell nanoparticles after sequential dissolution, redeposition, and electro‐reduction. The destruction of the M‐N‐C structure and the formation of nanoparticles greatly affect the electrocatalytic performance. Our work highlights the structural degradation and deactivation mechanism of M‐N‐C‐type SACs under strong reductive conditions and provides useful information for inspiring researchers to develop new strategies to improve the electrocatalytic stability of similar types of materials. [ABSTRACT FROM AUTHOR]

Background: With the advent of the smart phone era, managing blood glucose at home through apps will become more common for older individuals with diabetes. Adult children play important roles in glucose management of older parents. Few studies have explored how adult children really feel about engaging in the glucose management of their older parents with type 2 diabetes mellitus (T2DM) through mobile apps. This study provides insights into the role perceptions and experiences of adult children of older parents with T2DM participating in glucose management through mobile apps. Methods: In this qualitative study, 16 adult children of older parents with T2DM, who had used mobile apps to manage blood glucose for 6 months, were recruited through purposive sampling. Semi-structured, in-depth, face-to-face interviews to explore their role perceptions and experiences in remotely managing their older parents' blood glucose were conducted. The Consolidated Criteria for Reporting Qualitative Research (COREQ) were followed to ensure rigor in the study. The data collected were analyzed by applying Colaizzi's seven-step qualitative analysis method. Results: Six themes and eight sub-themes were identified in this study. Adult children's perceived roles in glucose management of older parents with T2DM through mobile apps could be categorized into four themes: health decision-maker, remote supervisor, health educator and emotional supporter. The experiences of participation could be categorized into two themes: facilitators to participation and barriers to participation. Conclusion: Some barriers existed for adult children of older parents with T2DM participating in glucose management through mobile apps; however, the findings of this study were generally positive. It was beneficial and feasible for adult children to co-manage the blood glucose of older parents. Co-managing blood glucose levels in older parents with T2DM can enhance both adherence rates and confidence in managing blood glucose effectively. [ABSTRACT FROM AUTHOR]

Two‐dimensional (2D) non‐layered materials, along with their unique surface properties, offer intriguing prospects for sensing applications. Introducing mechanical degrees of freedom is expected to enrich the sensing performances of 2D non‐layered devices, such as high frequency, high tunability, and large dynamic range, which could lead to new types of high performance nanosensors. Here, we demonstrate 2D non‐layered nanomechanical resonant sensors based on β‐In2S3, where the devices exhibit robust nanomechanical vibrations up to the very high frequency (VHF) band. We show that such device can operate as pressure sensor with broad range (from 10−3 Torr to atmospheric pressure), high linearity (with a nonlinearity factor as low as 0.0071), and fast response (with an intrinsic response time less than 1 μs). We further unveil the frequency scaling law in these β‐In2S3 nanomechanical sensors and successfully extract both the Young's modulus and pretension for the crystal. Our work paves the way towards future wafer‐scale design and integrated sensors based on 2D non‐layered materials. [ABSTRACT FROM AUTHOR]

The combination of satellite laser ranging (SLR) observations to various low earth orbit (LEO) satellites can enhance the accuracy and robustness of SLR-derived geodetic parameters, benefiting the realization of the International terrestrial reference frames. Observation stochastic models play a critical role in the integrated processing of SLR observations to multiple LEO satellites. The consideration of precision in heterogeneous SLR observations from various satellites is essential. In this study, we aim to improve the combination of multi-LEO SLR observations for geodetic parameters determination by optimizing the stochastic model using variance component estimation (VCE). We perform weekly estimates of the geodetic parameters, including station coordinates, Earth rotation parameters, and geocenter coordinates (GCC), using three years of SLR observations to seven LEO satellites at different orbits. The satellite-dependent, station-dependent, and satellite–station-dependent variance components are separately estimated through VCE processing to refine the stochastic models. Given the fact that the precision of SLR observations significantly differs in satellites and stations, the multiple LEO combination can be significantly improved with the implementation of VCE. Satellite–station-pair-dependent variance components are more suitable to the SLR VCE and the accuracy of station coordinates, pole coordinates, and length of day can be averagely improved by 8.4, 22.6, and 21.9%, respectively, compared to the equal-weight solution. Our result also indicates that the observation insufficiency for some stations may result in an unreliable VCE estimation, and eventually leads to an accuracy degradation for station coordinates. To overcome this deficiency, we adopt the variance components derived from the monthly solutions to build the stochastic model in the weekly solutions. The application of monthly weights can effectively mitigate the accuracy deterioration of station coordinates, improving the repeatability of the station coordinates by 15.9, 14.6, and 9.2% with respect to the equal-weight solution in E, N, and U components. The global geodetic parameters also benefit from this processing. The import of monthly weight decreases the outliers in the GCC series, especially in the X and Y components. [ABSTRACT FROM AUTHOR]

The Tree-Seed Algorithm (TSA) has been effective in addressing a multitude of optimization issues. However, it has faced challenges with early convergence and difficulties in managing high-dimensional, intricate optimization problems. To tackle these shortcomings, this paper introduces a TSA variant (DTSA). DTSA incorporates a suite of methodological enhancements that significantly bolster TSA's capabilities. It introduces the PSO-inspired seed generation mechanism, which draws inspiration from Particle Swarm Optimization (PSO) to integrate velocity vectors, thereby enhancing the algorithm's ability to explore and exploit solution spaces. Moreover, DTSA's adaptive velocity adaptation mechanism based on count parameters employs a counter to dynamically adjust these velocity vectors, effectively curbing the risk of premature convergence and strategically reversing vectors to evade local optima. DTSA also integrates the trees population integrated evolutionary strategy, which leverages arithmetic crossover and natural selection to bolster population diversity, accelerate convergence, and improve solution accuracy. Through experimental validation on the IEEE CEC 2014 benchmark functions, DTSA has demonstrated its enhanced performance, outperforming recent TSA variants like STSA, EST-TSA, fb-TSA, and MTSA, as well as established benchmark algorithms such as GWO, PSO, BOA, GA, and RSA. In addition, the study analyzed the best value, mean, and standard deviation to demonstrate the algorithm's efficiency and stability in handling complex optimization issues, and DTSA's robustness and efficiency are proven through its successful application in five complex, constrained engineering scenarios, demonstrating its superiority over the traditional TSA by dynamically optimizing solutions and overcoming inherent limitations. [ABSTRACT FROM AUTHOR]

Conventional coalbed methane (CBM) reservoir models for injection fall-off testing often disregard the quadratic pressure gradient's impact. This omission leads to discrepancies in simulating the transient behavior of formation fluids and extracting critical reservoir properties. Accurate determination of permeability, storability, and other properties is crucial for effective reservoir characterization and production forecasting. Inaccurate estimations can lead to suboptimal well placement, ineffective production strategies, and ultimately, missed economic opportunities. To address this shortcoming, we present a novel analytical model that explicitly incorporates the complexities of the quadratic pressure gradient and dual-permeability flow mechanisms, prevalent in many CBM formations where nanopores are rich, presenting a kind of natural nanomaterial. This model offers significant advantages over traditional approaches. By leveraging variable substitution, it facilitates the derivation of analytical solutions in the Laplace domain, subsequently converted to real-space solutions for practical application. These solutions empower reservoir engineers to generate novel type curves, a valuable tool for analyzing wellbore pressure responses during injection fall-off tests. By identifying distinct flow regimes within the reservoir based on these type curves, engineers gain valuable insights into the dynamic behavior of formation fluids. This model goes beyond traditional approaches by investigating the influence of the quadratic pressure gradient coefficient, inter-porosity flow coefficient, and storability ratio on the pressure response. A quantitative comparison with traditional models further elucidates the key discrepancies caused by neglecting the quadratic pressure gradient. The results demonstrate the proposed model's ability to accurately depict the non-linear flow behavior observed in CBM wells. This translates to more reliable pressure and pressure derivative curves that account for the impact of the quadratic pressure gradient. [ABSTRACT FROM AUTHOR]

Covalent organic frameworks (COFs) with large specific surface areas, high porosity, good stability, and designable structure are promising carriers for immobilized enzymes. It is important to explore lipase inhibitors from natural foods as lipase inhibitors are closely related to the treatment of obesity. In this work, a carboxyl functionalized covalent organic framework (TpBD-3COOH) was prepared by solvothermal method for covalent immobilization of porcine pancreatic lipase (PPL) and obtained the enzyme-decorated COF (PPL@COF). The immobilized lipase showed wider pH and temperature tolerance with the same optimal pH and temperature of 7.5 and 50 ℃ compared to free lipase. After 6 successive reuses, the PPL@COF maintained 53.0% of its original activity. Immobilized lipase also displayed enhanced storage stability (55.4% after 14 days at 4 ℃). When p-nitrophenyl acetate was applied as the substrate, the calculated Michaelis constant was 3.57 mM and the half maximal inhibitory concentration of orlistat was 3.20 μM. Finally, the PPL@COF was used for enzyme inhibitors screening from natural foods combined with UV spectrophotometry, and Hawthorn was screened for excellent lipase inhibitory activity. [ABSTRACT FROM AUTHOR]

In order to meet the time-critical and high-precision positioning demands of massive market applications, real-time Precise Point Positioning (PPP) technology has been continuously developed and can achieve a high level of accuracy now. Beyond precision, it is also crucial to ensure the security and stability of real-time high-precision positioning services. Nevertheless, there are few studies that addressed the fault detection and exclusion (FDE) of real-time PPP correction service to protect users from potential faults in the GNSS satellites. This paper introduces a new real-time products quality monitoring method that could effectively identify the potential fault of GNSS satellite corrections using an unsupervised learning algorithm and provide means to alert the real-time PPP users. The ambiguity-fixed Un-differenced Carrier-phase Residual Statistics (UCRS) of large-scale regional stations are first constructed to reflect the status of satellite corrections accurately. A machine learning technique, known as Isolation Forest, is employed to identify outliers in the UCRS to detect situations of potential satellite faults. Then, the UCRS alarm factors are transmitted to users for PPP processing with a modified weighting scheme based on alert information. Experimental validation utilizing 30 monitoring stations in China demonstrates a detection success rate exceeding 95% for orbit faults larger than 5 cm and clock faults larger than 0.2 ns. It is also proved that this method can effectively identify orbit and clock jump in real-time GNSS products that cause additional positioning errors. With the alert information broadcasted by the server, the PPP after FDE (PPP-FDE) presents a significant accuracy improvement of 27–71% compared with traditional PPP processing. [ABSTRACT FROM AUTHOR]

Alligator weed (Alternanthera philoxeroides) is a highly invasive species that has successfully established in numerous tropical and subtropical regions worldwide. Previous literature suggests that alligator weed was introduced to China in the 1930s as fodder for military horses by Japanese, while its presence in Japan only became apparent in the 1990s. Consequently, the introduction and genetic relationship between alligator weed populations in China and Japan remain uncertain, and the native source population is still unidentified. This study aimed to characterize the genetic diversity and structure of populations within the introduced range of China and Japan, as well as the native range of Argentina, using amplified fragment length polymorphism (AFLP) markers. Nine primer pairs were employed, resulting in a total of 573 distinct amplified bands for the China and Japan populations. However, none of these bands displayed polymorphism, indicating a uniform genetic background across all sampled populations in China and Japan. In contrast, the Argentine populations yielded 251 identifiable amplified bands using four well-performing primer pairs, of which 209 (80.69%) were found to be polymorphic. Genetic relationship and population structure analyses based on AFLP data revealed that the population from Jujuy, Argentina, exhibited the closest genetic affinity to the invasive populations in China and Japan, as indicated by Nei's genetic identity value of 0.9281. Additionally, using methylation-sensitive amplified polymorphism (MSAP), we identified 258 epigenetic variation sites using five primer pairs in the Chinese and Japanese populations. Principal coordinate analysis (PCoA) based on the MSAP data revealed a geographic epigenetic structure within the alligator weed populations of China and Japan, with DNA methylation variation patterns exhibiting correlation with geographic distribution, thus implying their potential involvement in environmental adaptation. This research enhances our understanding of the invasion mechanisms of alligator weed and provides valuable insights into the roles of epigenetic factors in its successful spread. [ABSTRACT FROM AUTHOR]

Real-time precise orbits of low earth orbit (LEO) satellites are becoming indispensable with the rapid development of real-time Earth observation application and LEO enhanced precise point positioning. Currently, GNSS-based precise orbit determination is a widely used method for LEO onboard navigation. However, the real-time LEO satellite orbits are usually obtained by ambiguity-float solution even when the GNSS augmentation corrections are considered. In this study, we perform LEO ambiguity-fixed multi-GNSS real-time precise orbit determination (RTPOD) based on square root information filter. One month of onboard GPS + Galileo observations from Sentinel-6A and real-time products of the Centre National d’Etudes Spatiales (CNES) are used to investigate the contribution of integer ambiguity resolution (IAR). The benefit of dual-system combination on LEO RTPOD is firstly evaluated. The combination of GPS and Galileo dual-system contributes to more visible GNSS satellites and better observation geometry for LEO RTPOD, which results in an evident accuracy improvement of 19% over GPS and a convergence time reduction of 43% and 41% compared to the GPS and Galileo solutions respectively. Considering the short arc of onboard GNSS observations and imperfections in GNSS real-time products, we propose a strict IAR quality control method to avoid fixing the ambiguity to the wrong values. The results indicate that the IAR quality control method we used can effectively reduce the wrong fixing risk and increase the robustness of the IAR solution. Using onboard GPS and Galileo observations, the 3D orbit accuracy of the ambiguity-fixed solution is significantly improved from 5.17 to 3.61cm, by 30%, compared to the ambiguity-float solution. Furthermore, the application of IAR also achieves a faster convergence to the centimeter-level orbit. [ABSTRACT FROM AUTHOR]

The challenges associated with the assessment of immune checkpoint inhibitor (ICI) therapy and low immunotherapy response observed in patients with poorly immunogenic tumors are addressed. A smart‐responsive nanoprobe MZF@Gd is synthetized based on magnetic resonance tuning (MRET). The nanoprobe is designed to be targeted and cleaved by granzyme B, a marker of cytotoxic T‐cell activation. MZF@Gd consisted of superparamagnetic Mn‐ and Zn‐doped ferrite magnetic nanoparticles (MZF‐MNPs) with a magnetocaloric effect and a paramagnetic contrast agent gadolinium‐diethylenetriamine penta‐acetic acid (Gd‐DTPA). These components are connected by the granzyme B substrate peptides. The activation of the T1WI signal through MRET, following the cleavage of the probe by granzyme B, enabled the accurate evaluation of the ICI therapeutic effect. Subsequently, an active‐targeting magnetothermally responsive nanotheranostic agent FA‐P(MZF@Gd/JQ1) is fabricated. This agent incorporated the MRET probe MZF@Gd, JQ‐1 (an inhibitor of PD‐L1), the thermosensitive copolymer PCL‐b‐P(MEO2MA‐co‐OEGMA), and folic acid on the surface. Nanotheranostic agents killed tumor cells through magnetocaloric effects, stimulated antitumor immunity, and regulated the drug release, thereby achieving a synergistic effect between hyperthermia and immunotherapy. Moreover, MZF@Gd released from the agent sensitively detected the presence of granzyme B at the tumor site, thereby enabling an effective assessment of therapeutic efficacy. [ABSTRACT FROM AUTHOR]

The plant hormone jasmonic acid plays an important role in plant growth and development, participating in many physiological processes, such as plant disease resistance, stress resistance, organ development, root growth, and flowering. With the improvement in living standards, people have higher requirements regarding the quality of vegetables. However, during the growth process of vegetables, they are often attacked by pests and diseases and undergo abiotic stresses, resulting in their growth restriction and decreases in their yield and quality. Therefore, people have found many ways to regulate the growth and quality of vegetable crops. In recent years, in addition to the role that JA plays in stress response and resistance, it has been found to have a regulatory effect on crop quality. Therefore, this study aims to review the jasmonic acid accumulation patterns during various physiological processes and its potential role in vegetable development and quality formation, as well as the underlying molecular mechanisms. The information provided in this manuscript sheds new light on the improvements in vegetable yield and quality. [ABSTRACT FROM AUTHOR]

The besiege and conquer algorithm has shown excellent performance in single-objective optimization problems. However, there is no literature on the research of the BCA algorithm on multi-objective optimization problems. Therefore, this paper proposes a new multi-objective besiege and conquer algorithm to solve multi-objective optimization problems. The grid mechanism, archiving mechanism, and leader selection mechanism are integrated into the BCA to estimate the Pareto optimal solution and approach the Pareto optimal frontier. The proposed algorithm is tested with MOPSO, MOEA/D, and NSGAIII on the benchmark function IMOP and ZDT. The experiment results show that the proposed algorithm can obtain competitive results in terms of the accuracy of the Pareto optimal solution. [ABSTRACT FROM AUTHOR]

Intelligent monitoring technology plays an important role in promoting the development of coal mine safety management. Low illumination in the coal mine underground leads to difficult recognition of monitoring images and poor personnel detection accuracy. To alleviate this problem, a low illuminance image enhancement method proposed for personnel safety monitoring in underground coal mines. Specifically, the local enhancement module maps low illumination to normal illumination at pixel level preserving image details as much as possible. The transformer-based global adjustment module is applied to the locally enhanced images to avoid over-enhancement of bright areas and under-illumination of dark areas, and to prevent possible color deviations in the enhancement process. In addition, a feature similarity loss is proposed to constrain the similarity of target features to avoid the possible detrimental effect of enhancement on detection. Experimental results show that the proposed method improves the detection accuracy by 7.1% on the coal mine underground personal dataset, obtaining the highest accuracy compared to several other methods. The proposed method effectively improves the visualization and detection performance of low-light images, which contributes to the personnel safety monitoring in underground coal mines. [ABSTRACT FROM AUTHOR]

Typhoon trajectory related data involve many factors, such as atmospheric factors, oceanic factors, and physical factors. It has the characteristics of high dimension, strong spatio-temporal correlation, and nonlinear correlation, which increases the difficulty of typhoon trajectory prediction. Using feature selection approaches to select appropriate prediction factors becomes an important means to reduce the dimension of typhoon trajectory related data and improve the performance and accuracy of typhoon trajectory prediction methods. However, the existing feature selection methods based on linear correlation analysis cannot well depict the nonlinear correlation between data features, which results in low accuracy of feature selection. The feature selection methods based on nonlinear correlation analysis are computationally expensive, which affects the timeliness of feature selection. To solve the problem, we propose a parallel feature selection method NX-Spark-DC based on the Spark platform for typhoon trajectory related data. The method firstly filters out the redundant features of typhoon related data by normalized mutual information (NMI) method, subsequently eliminates the useless features by XGBoost machine learning model, and thus reducing the dimension of typhoon related data. On this basis, an improved Spark-based parallel distance correlation algorithm (Spark-DC) is proposed to select the feature combinations with strong correlation. A series of experimental results show that NX-Spark-DC method has high execution efficiency and accuracy, which is significantly better than the existing methods. [ABSTRACT FROM AUTHOR]

The new Global Navigation Satellite System (GNSS) satellites, including GLONASS, Galileo, and BeiDou system, are equipped with Laser Retroreflector Arrays (LRA) to support Satellite Laser Ranging (SLR) tracking, which contributes to the estimation of global geodetic parameters. In this study, we estimate the global geodetic parameters using the SLR observations to GNSS satellites and also investigate the effects of different data processing strategies on the estimated Earth Rotation Parameters (ERP), geocenter motion, and terrestrial scale. The results indicate that setting range bias parameters for each satellite-station pair can effectively account for the satellite-specific biases induced by LRAs, leading to smaller Root Mean Square Errors (RMSE) of the post-fit SLR residuals. Furthermore, estimating the range biases for each satellite-station pair improves the accuracy of the estimated station coordinates and ERP. We also examine the impact of different arc lengths on the estimates of ERP, geocenter motion, and terrestrial scale. The results show that extending arc length can significantly reduce the formal error of ERP. The 7-day strategy produces the smallest RMSEs of 473 microarcseconds and 495 microarcseconds for the estimated X- and Y-component of pole coordinates, and 52 microseconds for length-of-day, respectively. However, the estimated geocenter motion is less affected by the arc length, even the shortest 1-day arc strategy can capture the seasonal variations of geocenter motion in Z component. For scale estimation, extending the arc length notably improves the accuracy of the estimated station coordinates and scale, but this advantage becomes less noticeable in longer arcs. The 7-day solution also obtains the closet scale results compared to ITRF2014, with the RMSE of 2.10 × 10–9. [ABSTRACT FROM AUTHOR]

Aphis gossypii Glover is an important pest in cotton plantations. Medicago sativa L. (alfalfa) is a host plant for the aphid Aphis craccivora Koch and may prove to be an important reservoir of natural enemies to combat this pest. The objective of this study was to analyze the impact of different mowing frequencies of alfalfa traps on A. gossypii and their natural enemies, using both ground survey data and UAV remote sensing data. The alfalfa was mowed twice to facilitate the transfer of this primary natural enemy to the cotton fields. Ground surveys were carried out every five days to gather data, while temporal niche and niche overlap methods were used for further analysis. Findings collected over a period ranging from day 31 to day 91 indicated that compared to their counterparts with no alfalfa traps, the cotton fields containing these pest control measures demonstrated a reduction in the A. gossypii population of approximately 16%. A survey conducted 5 days after mowing the alfalfa on days 61 and 71 found that the cotton fields with alfalfa traps experienced a 24.14% and 26.09% reduction in A. gossypii numbers. In contrast, the cotton fields without alfalfa traps experienced a 76.92% and 55.08% increase in cotton aphid numbers during the same period. It is noteworthy that the cotton fields with alfalfa traps showed a delayed onset of cotton aphid damage of approximately 5 days compared to the fields without alfalfa traps. This discovery has significant implications for understanding the ecological control mechanism of A. gossypii within alfalfa traps. Planting alfalfa traps around fields in Xinjiang could be promoted as a method to prevent and control aphid damage. [ABSTRACT FROM AUTHOR]

In recent decades, loess landslide events have attracted increasing attention in the South Jingyang tableland. To elucidate the mechanical mechanism of landslide initiation in the region, this work collected undisturbed loess and paleosol samples taking from the Q2 strata in the South Jingyang tableland. A range of direct shear tests were carried out to explore the strength evolution law of shear zone soil subjected to a varying initial moisture content. In addition, soil water characteristic curves (SWCCs) were also charted and used for predicting the unsaturated shear strength. The findings show that the basic physical properties of the paleosol are different from those of loess due to their different pedogenic environments. The normal stress level and initial moisture content jointly determine whether the shear behavior is strain hardening or strain softening. The shear strength and strength parameters evidently diminish with an increasing initial moisture content, and cohesion contributes to the vast majority of strength attenuation. Paleosol samples possess higher values in shear strength and strength parameters than loess samples due to their stronger inter-particle cementation. The predictive formulas of unsaturated shear strength for undisturbed loess and paleosol are proposed, respectively, based on the Vanapalli model, and the calculated values of the strength prediction model are in perfect agreement with the experimental values. [ABSTRACT FROM AUTHOR]

Integer Ambiguity Resolution (IAR) can significantly improve the accuracy of GNSS Precise Orbit Determination (POD). Traditionally, the IAR in POD is achieved at the Double Differenced (DD) level. In this contribution, we develop an Un-Differenced (UD) IAR method for Global Positioning System (GPS)+ BeiDou Navigation Satellite System (BDS) + Galileo navigation satellite system (Galileo)+ Global'naya Navigatsionnaya Sputnikovaya Sistema (GLONASS) quad-system POD by calibrating UD ambiguities in the raw carrier phase and generating the so-called carrier range. Based on this method, we generate the UD ambiguity-fixed orbit and clock products for the Wuhan Innovation Application Center (IAC) of the International GNSS Monitoring and Assessment System (iGMAS). One-year observations in 2020 from 150 stations are employed to investigate performance of orbit and clock products. Notably, the UD Ambiguity Resolution (AR) yields more resolved integer ambiguities than the traditional DD AR, scaling up to 9%, attributable to its avoidance of station baseline formation. Benefiting from the removal of ambiguity parameters, the computational efficiency of parameter estimation undergoes a substantial 70% improvement. Compared with the float solution, the orbit consistencies of UD AR solution achieve the accuracy of 1.9, 5.2, 2.8, 2.1, and 2.7 cm for GPS, BeiDou-2 Navigation Satellite System (BDS-2), BeiDou-3 Navigation Satellite System (BDS-3), Galileo, and GLONASS satellites respectively, reflecting enhancements of 40%, 24%, 54%, 34%, and 42%. Moreover, the standard deviations of Satellite Laser Ranging (SLR) residuals are spanning 2.5–3.5 cm, underscoring a comparable accuracy to the DD AR solution, with discrepancies below 5%. A notable advantage of UD AR lies in its capability to produce the Integer Recovered Clock (IRC), facilitating Precise Point Positioning (PPP) AR without requiring additional Uncalibrated Phase Delay (UPD) products. To assess the performance of quad-system kinematic PPP based on IRC, a network comprising 120 stations is utilized. In comparison to the float solution, the IRC-based PPP AR accelerates convergence time by 31% and enhance positioning accuracy in the east component by 54%. [ABSTRACT FROM AUTHOR]

Although reducing students' aggressive behaviors and improving their creativity are both important commitments of educators, they are usually treated independently as unrelated tasks. However, cumulative evidence suggests potential links between aggression and creativity, not only from the perspectives of personality traits and psychological development, but also from their shared cognitive mechanisms. This implies that there may be an approach to achieving these two goals through a single intervention. Moreover, this new approach may overcome the limitation of the usually adopted aggression intervention, which is limited in its regulatory effectiveness and might bring about some disadvantageous impacts on creativity that are closely associated with aggression. To test this possibility, the present study implemented a four‐session, 2‐week creative thinking training (CTT) intervention for students with high aggression scores to examine whether it could simultaneously downregulate aggression and increase creativity. Our results demonstrate that, compared to the control group, the intervention group experienced significant improvements in creativity and a reduction in aggression following the CTT intervention. Furthermore, our findings suggest that this regulatory effect can persist for up to 6 months. The CTT‐induced creativity change (increase) could significantly correlate with and predict the CTT‐induced aggression decrease, thus suggesting that the CTT could transform aggression into creativity. [ABSTRACT FROM AUTHOR]

In this study, we developed a rapid and effective method for enriching the culture of nitrifying bioflocs (NBF) from aquacultural brackish water. The self-designed mixotrophic mediums with a single or mixed addition of sodium acetate, sodium citrate, and sucrose were used to investigate the enrichment process and nitrification efficiency of NBF in small-scale reactors. The results showed that NBF with an MLVSSs from 1170.4 mg L−1 to 2588.0 mg L−1 were successfully enriched in a period of less than 16 days. The citrate group performed the fastest enrichment time of 10 days, while the sucrose group had the highest biomass of 2588.0 ± 384.7 mg L−1. In situ testing showed that the highest nitrification efficiency was achieved in the citrate group, with an ammonia oxidation rate of 1.45 ± 0.34 mg N L−1 h−1, a net nitrification rate of 2.02 ± 0.20 mg N L−1 h−1, and a specific nitrification rate of 0.72 ± 0.14 mg N g−1 h−1. Metagenomic sequencing revealed that Nitrosomonas (0.0~1.0%) and Nitrobacter (10.1~26.5%) were dominant genera for AOB and NOB, respectively, both of which had the highest relative abundances in the citrate group. Linear regression analysis further demonstrated significantly positive linear relations between nitrification efficiencies and nitrifying bacterial genera and gene abundance in NBF. The results of this study provide an efficient enrichment culture method of NBF for the operation of biofloc technology aquaculture systems, which will further promote its wide application in modern intensive aquaculture. [ABSTRACT FROM AUTHOR]

This study constructs a power switching device open-circuit fault diagnosis model for a three-level neutral point clamped inverter based on the multi-scale shuffled convolutional neural network (MSSCNN) and extracts and classifies the fault information contained in the output current of inverters. The model employs depthwise separable convolution and channel shuffle techniques to improve diagnostic accuracy and reduce model complexity. The experimental results show that the new model has lower model complexity, better noise resistance and higher average diagnostic accuracy compared with fault diagnosis models based on CNN, ResNet, ShuffleNet V2 and Mobilenet V3 networks. [ABSTRACT FROM AUTHOR]

Efficient aircraft turnaround operations at airports are vital to ensure overall air traffic network performance. After the outbreak of COVID-19, the traditional aircraft ground handling process has changed significantly due to new requirements put forward by the pandemic prevention and control policy. To better understand how COVID-19 has affected ground handling operations, a discrete-event simulation model of turnaround is established to analyze the change in the whole turnaround process before and after the pandemic. The critical path of turnaround operations was used to identify the significantly affected subprocesses to which airports should pay attention. For a case study on the two busiest airports in China, the aircraft turnaround time increased by about 18% after COVID-19. Cabin cleaning, catering, and passenger embarking were the main processes in causing this increase. By evaluating the impact mechanism of COVID-19 on turnaround operations, the study sheds light on strategic, tactical, and operational approaches for relevant authorities. [ABSTRACT FROM AUTHOR]

Photocatalytic H2O2 generation is compelling for sustainable solar-to-chemical conversion, but it is an emerging challenge to realize efficient conversion without the consumption of any alcohols. Also, the in-depth mechanism for the structure-induced activity enhancement is still unclear but remains pivotal for practical application. Herein, cyano groups and S atoms were collectively introduced into carbon nitride (MTCN), and the vital roles and detailed mechanism were investigated. Specifically, MTCN exhibited a laudable H2O2 generation of 68.12 mM gcat−1 h−1, together with an apparent quantum yield of 49.01% at 420 nm. Intriguingly, it was observed that the existence of some contaminants can promote H2O2 generation and, in turn, accelerate degradation. Additionally, it is revealed that the S atoms and cyano group could facilitate oxygen adsorption and H+ adsorption, respectively. This study shows a promising strategy to construct modified g-C3N4 and exhibits a clear mechanism for H2O2 generation paired with simultaneous contaminant treatment. [ABSTRACT FROM AUTHOR]

Purpose: Rectal tumor segmentation on post neoadjuvant chemoradiotherapy (nCRT) magnetic resonance imaging (MRI) has great significance for tumor measurement, radiomics analysis, treatment planning, and operative strategy. In this study, we developed and evaluated segmentation potential exclusively on post-chemoradiation T2-weighted MRI using convolutional neural networks, with the aim of reducing the detection workload for radiologists and clinicians. Methods: A total of 372 consecutive patients with LARC were retrospectively enrolled from October 2015 to December 2017. The standard-of-care neoadjuvant process included 22-fraction intensity-modulated radiation therapy and oral capecitabine. Further, 243 patients (3061 slices) were grouped into training and validation datasets with a random 80:20 split, and 41 patients (408 slices) were used as the test dataset. A symmetric eight-layer deep network was developed using the nnU-Net Framework, which outputs the segmentation result with the same size. The trained deep learning (DL) network was examined using fivefold cross-validation and tumor lesions with different TRGs. Results: At the stage of testing, the Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and mean surface distance (MSD) were applied to quantitatively evaluate the performance of generalization. Considering the test dataset (41 patients, 408 slices), the average DSC, HD95, and MSD were 0.700 (95% CI: 0.680–0.720), 17.73 mm (95% CI: 16.08–19.39), and 3.11 mm (95% CI: 2.67–3.56), respectively. Eighty-two percent of the MSD values were less than 5 mm, and fifty-five percent were less than 2 mm (median 1.62 mm, minimum 0.07 mm). Conclusions: The experimental results indicated that the constructed pipeline could achieve relatively high accuracy. Future work will focus on assessing the performances with multicentre external validation. [ABSTRACT FROM AUTHOR]

Summary: This study aimed to investigate how kombucha bacterial cellulose (KBC) affects the characteristics of dough. Wheat flour was substituted with different proportions of KBC (0%, 1%, 3%, 5%, 7%, and 9%), and the chemical components of KBC and the mixed powder were analysed at various substitution levels. The findings indicated that using KBC led to extended durations and enhanced stability of dough formation, decreased degree of weakening, increased relaxing time, and significantly reduced peak viscosity, trough viscosity, and final viscosity. Additionally, the process of gelatinisation was impeded. Unlike other dietary fibres, adding low amounts of KBC to flour and dough not only maintains their quality but also improved many other characteristics. When added in low quantities of 1% and 3%, KBC improved various dough properties, including enhancing gluten strength, stabilising the gluten structure, and improving viscoelasticity. Overall, this study provided insights into the impact of KBC on the dough structure. [ABSTRACT FROM AUTHOR]

In this paper, we propose a projection-based hybrid spectral gradient algorithm for nonlinear equations with convex constraints, which is based on a certain line search strategy. Convex combination technique is used to design a novel spectral parameter that is inspired by some classical spectral gradient methods. The search direction also meets the sufficient descent condition and trust region feature. The global convergence of the proposed algorithm has been established under reasonable assumptions. The results of the experiment demonstrate the proposed algorithm is both more promising and robust than some similar methods, and it is also capable of handling large-scale optimization problems. Furthermore, we apply it to problems involving sparse signal recovery and blurred image restoration. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to investigate the influencing mechanism of consumers' continuous purchase intention toward the subscriber-based knowledge payment platforms (SBKPPs). Design/methodology/approach: This study obtained 226 valid samples through questionnaire surveys and used partial least square structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) methods to elucidate the complex causal patterns of consumers' continuous purchase intention toward the SBKPPs. Findings: The findings revealed that perceived utilitarian value, perceived hedonic value and perceived social value directly affected consumers' continuous purchase intention, while content quality and service quality indirectly affected consumers' continuous purchase intention. In addition, this study also demonstrated that all factors must be combined to play a role, and there exist four configurations resulting in consumers' continuous purchase intention toward the SBKPPs. Research limitations/implications: The results can help researchers and practitioners better understand the causal patterns of consumers' continuous purchase intention toward the SBKPPs. Originality/value: This study contributes to the knowledge payment literature by investigating consumers' continuous purchase intention toward the SBKPPs. This study also provides practical enlightenment for the SBKPPs' marketing. [ABSTRACT FROM AUTHOR]

Objective To investigate the expression of SLC35A2 and PFDN2 in breast cancer and their relationship with clinical indicators and prognosis. Methods TCGA database and TIMER 2.0 database were used to analyze the differences of SLC35A2 and PFDN2 expression in breast cancer tissues and paracancerous tissues ; K-M database was used to create the survival curves of patients in the high and low expression groups of the two. qRT-PCR and immunohistochemistry were used to detect the expression of SLC35A2 and PFDN2 in the cancerous and paracancerous tissues, and the expression differences, the relationship between their expression levels and the clinical observation indexes were statistically analyzed, and the independent prognostic factors of breast cancer were screened out; K-M survival analysis was used to compare the prognostic differences between the groups and create the survival curves. Results The expression levels of SLC35A2 and PFDN2 in breast cancer tissues were significantly higher than those in paracancerous tissues according to the results of biopsy, qRT-PCR and immunohistochemistry, and the expression levels of SLC35A2 were significantly correlated with lymph node metastasis, while the expression of PFDN2 was significantly correlated with the diameter of the tumor and the metastasis of lymph nodes, and the expression of SLC35A2 and PFDN2 was an independent prognostic factor for breast cancer. patients had the worst prognosis. Conclusion The expression of SLC35A2 and PFDN2 in breast cancer tissues was closely related to clinical indicators and prognosis of breast cancer, and could be used as a potential target for breast cancer treatment. [ABSTRACT FROM AUTHOR]

The integration of large-scale photovoltaics (PVs) into the power grid has significantly altered the transient synchronization dynamics of traditional power systems dominated by synchronous generators (SGs) and posed great challenges to modeling and analysis of PVs integration. In this paper, the transient synchronization stability of the PV-SG system is studied using the singular perturbation technique. Firstly, a nonlinear model of a PV-SG system is established to reveal the multiscale transient synchronization characteristics. Further, the full system is decomposed into a slow subsystem and a fast subsystem by the singular perturbation technique. The fast subsystem containing the dynamics of the DC voltage control, terminal voltage control, and phase-locked loop, and the slow subsystem containing the dynamics of rotor motion can perfectly reflect the dynamics of the full system within the electromagnetic and electromechanical timescales, respectively. The proposed model provides a clearer physical picture of dynamics in the PV-SG system within the electromagnetic and electromechanical timescales. Subsequently, the stability of the slow and fast subsystems is investigated using the energy function and eigenvalue analysis methods, respectively. Meanwhile, the impacts of various operating, control, and structural parameters on the transient synchronization stability are uncovered. Different from the most existing research endeavors on the wide simulations of the PVs integration, the impact of PVs on the synchronization dynamics of SGs without considering the dynamical characteristics of the PV system, and the transient synchronization stability analyses of the PLL-based voltage source converter systems, it is the key contribution to study the transient synchronization dynamical characteristics of the PV system and its interaction with the SG under different timescales. All these are helpful and easy to extend to more complicated PV-SG systems. Finally, the analysis results are validated by extensive simulations. [ABSTRACT FROM AUTHOR]

Purpose: Heart failure (HF) is a serious and complex syndrome with a high mortality rate. In clinical diagnosis, the correct classification of HF is helpful. In our previous work, we proposed a self-supervised learning framework of HF classification (SSLHF) on cine cardiac magnetic resonance images (Cine-CMR). However, this method lacks the integration of three dimensions of spatial information and temporal information. Thus, this study aims at proposing an automatic 4D HF classification algorithm. Methods: To construct a 4D classification model, we proposed an extensional framework called 4D-SSLHF. It mainly consists of self-supervised image restoration and HF classification. The image restoration proxy task utilizes three image transformation methods to enhance the exploration of spatial and temporal information in the Cine-CMR. In the classification task, we proposed a Siamese Conv-LSTM network by combining the Siamese network and bi-directional Conv-LSTM to integrate the features of the four dimensions simultaneously. Results: Experimental results on 184 patients from Shanghai Chest Hospital achieved an AUC of 0.8794 and an ACC of 0.8402 in the five-fold cross-validation. Compared with our previous work, the improvements in AUC and ACC were 2.89 % and 1.94 %, respectively. Conclusions: In this study, we proposed a novel self-supervised learning framework named 4D-SSLHF for HF classification based on Cine-CMR. The proposed 4D-SSLHF can mine 3D spatial information and temporal information in Cine-CMR images well and accurately classify different categories of HF. The good classification results show our method's potential to assist physicians in choosing personalized treatment. [ABSTRACT FROM AUTHOR]

The South Jingyang tableland, located in Shaanxi Province, China, is composed of loess deposits. Agricultural irrigation in this area has caused the continuous rise of the groundwater table, which triggered a series of loess landslides. Although extensive research has been conducted on the effect of rising groundwater tables on induced loess landslides, less is known about the groundwater table distribution. This study jointly investigated the distribution of the groundwater table in the South Jingyang tableland using boreholes, electrical resistivity tomography (ERT), and laboratory tests. A qualitative analysis between the apparent resistivity and the water content was estimated at different depths, using the borehole data and ERT inversion data. A quantitative relationship between the resistivity and the water content was established in the laboratory tests. A combination of the qualitative analysis of the inversion results and the quantitative relationship was used to determine the distribution of the groundwater table. The groundwater table is present at the depth where the water content of the loess is 30% (liquid limit of loess) and the resistivity is 28.35 Ω m. The groundwater table elevation in the southern study area is higher than that of the northern study area and decreases in a stepwise gradient from south to north. This study not only identified the distribution of the groundwater table in the South Jingyang tableland, but also makes up for the limitation and inaccuracy in determining groundwater tables by relying solely on the borehole information or inversion results of ERT. The ascertained distribution characteristics of the groundwater table provides a basis for the analysis of the formation mechanism of landslides. [ABSTRACT FROM AUTHOR]

Background: Our previous studies demonstrated that divalent organic iron (Fe) proteinate sources with higher complexation or chelation strengths as expressed by the greater quotient of formation (Qf) values displayed higher Fe bioavailabilities for broilers. Sodium iron ethylenediaminetetraacetate (NaFeEDTA) is a trivalent organic Fe source with the strongest chelating ligand EDTA. However, the bioavailability of Fe when administered as NaFeEDTA in broilers and other agricultural animals remains untested. Herein, the chemical characteristics of 12 NaFeEDTA products were determined. Of these, one feed grade NaFeEDTA (Qf = 2.07 × 108), one food grade NaFeEDTA (Qf = 3.31 × 108), and one Fe proteinate with an extremely strong chelation strength (Fe-Prot ES, Qf value = 8,590) were selected. Their bioavailabilities relative to Fe sulfate (FeSO4·7H2O) for broilers fed with a conventional corn-soybean meal diet were evaluated during d 1 to 21 by investigating the effects of the above Fe sources and added Fe levels on the growth performance, hematological indices, Fe contents, activities and gene expressions of Fe-containing enzymes in various tissues of broilers. Results: NaFeEDTA sources varied greatly in their chemical characteristics. Plasma Fe concentration (PI), transferrin saturation (TS), liver Fe content, succinate dehydrogenase (SDH) activities in liver, heart, and kidney, catalase (CAT) activity in liver, and SDH mRNA expressions in liver and kidney increased linearly (P < 0.05) with increasing levels of Fe supplementation. However, differences among Fe sources were detected (P < 0.05) only for PI, liver Fe content, CAT activity in liver, SDH activities in heart and kidney, and SDH mRNA expressions in liver and kidney. Based on slope ratios from multiple linear regressions of the above indices on daily dietary analyzed Fe intake, the average bioavailabilities of Fe-Prot ES, feed grade NaFeEDTA, and food grade NaFeEDTA relative to the inorganic FeSO4·7H2O (100%) for broilers were 139%, 155%, and 166%, respectively. Conclusions: The bioavailabilities of organic Fe sources relative to FeSO4·7H2O were closely related to their Qf values, and NaFeEDTA sources with higher Qf values showed higher Fe bioavailabilities for broilers fed with a conventional corn-soybean meal diet. [ABSTRACT FROM AUTHOR]

Arbuscular mycorrhizal (AM) fungi are ubiquitous and impactful symbionts of most land plants and can regulate essential ecological processes. AM fungi can increase the cellulose content of root cell walls and hence the root tensile strength of grass. How AM fungi can alter other essential biomechanical properties is not clear. This study aims to study the contribution of AM fungi in altering biomechanical properties by comparing mycorrhizal and non‐mycorrhizal roots. We inoculated three fungal species to vetiver grass (Chrysopogon zizanioides) for comparison. Eight root biomechanical properties (i.e., yield strain, yield stress, break strain, tensile strength, Young's modulus, plastic modulus, plastic strain, and toughness) were determined for each root using a newly developed Fortran language‐based program. Inoculating AM fungi decreased both Young's modulus and plastic modulus by 23% and 17%, respectively, versus control, although it was species‐dependent. Yield stress was not significantly affected, but tensile strength was increased by 7%–17% upon fungal symbiosis. Together with the increases in break strain by 15%–20%, mycorrhizal roots possessed a notably higher toughness than non‐mycorrhizal roots by up to 36%. Greater root cohesion of mycorrhizal roots confirmed the enhanced (1.5‐fold) factor of safety in the soil‐root system. Our findings imply that AM fungi are of significant interest in plant biomechanics and geotechnical engineering. Applying AM fungi on soil slopes has considerable potential to improve vegetation and stability of green slopes. [ABSTRACT FROM AUTHOR]

Functional dyspepsia (FD) is a common functional gastrointestinal disorder. The pathophysiology remains poorly understood; however, alterations in the small intestinal microbiome have been observed. Current treatments for FD with drugs are limited, and there are certain safety problems. A class of active probiotic bacteria can control gastrointestinal homeostasis, nutritional digestion and absorption, and the energy balance when taken in certain dosages. Probiotics play many roles in maintaining intestinal microecological balance, improving the intestinal barrier function, and regulating the immune response. The presence and composition of intestinal microorganisms play a vital role in the onset and progression of FD and serve as a critical factor for both regulation and potential intervention regarding the management of this condition. Thus, there are potential advantages to alleviating FD by regulating the intestinal flora using probiotics, targeting intestinal microorganisms. This review summarizes the research progress of probiotics regarding improving FD by regulating intestinal flora and provides a reference basis for probiotics to improve FD. [ABSTRACT FROM AUTHOR]

A hydrophilic Al-MOFs composite was prepared using cheap and available reagents in water via a suitable large-scale production, an economical and environment-friendly method for capturing N-glycopeptides. The prepared Al-MOFs composite with high hydrolytically stable and hydrophilic 1D channels exhibits an ultralow detection limit (0.5 fmol/μL), and excellent reusability (at least 10 cycles) in the capture of N-glycopeptides from standard bio-samples. Interestingly, the Al-MOFs composite also shows remarkable performance in practical applications, where 300 N-glycopeptides ascribed to 124 glycoproteins were identified in 1 µL human serum and were successfully applied in profiling the differences of N-glycopeptides during diabetes progression. Moreover, 12 specific glycoproteins used as biomarkers to accurately distinguish the progression of diabetes are identified. The present work provides a potential commercial method for large-scale glycoproteomics research in complex clinical samples while offering new guidance for the precise diagnosis of diabetes progression. [ABSTRACT FROM AUTHOR]

BACKGROUND: Polyetheretherketone (PEEK) is a polyaromatic semi-crystalline thermoplastic polymer with mechanical and lubrication properties favorable for biomedical applications. Despite of its aesthetic appearance, ceramic brackets are unsatisfactory in brittleness and thickness, while PEEK is a potential material for aesthetic orthodontic brackets. OBJECTIVE: To fabricate a novel aesthetic orthodontic bracket and evaluate friction properties of PEEK and stainless steel wires. METHODS: All polyether ether ketone (PEEK) and ceramic samples disks were made into disks (diameter, 5 mm; thickness, 2 mm). The tested surfaces of PEEK were ground with #600, #800 and #1200 SiC papers, followed by polishing with Sof-Lex kit (3M ESPE, USA). The surface roughness was tested using a laser profilometer device (VK-X200, Keyence, Japan). The COFs of the specimens and stainless steel (SS) archwires were tested using a Universal Micro-Tribotester (UMT-3, Bruker, USA). The wear scratches on the materials' surfaces were examined by using a scanning electron microscope (SEM) (Hitachi SU8010). The elastic modulus and hardness of samples were examined with a nano-indenter (XP, Keysight Technologies, USA). RESULTS: The mean surface roughness of PEEK and Ceramic are 0.320 ± 0.028 μ m and 0.343 ± 0.044 μ m, respectively. PEEK has a lower Friction coefficient than Ceramic and the difference between the two groups was statistically significant (P < 0.05). The abrasive wear of Ceramic was the main wear style and was characterized by the observation of chipping fractures, while PEEK surface looked smooth without obvious scale-like desquamations and granular debris, indicating adhesive wear. CONCLUSION: Within the limitations of the present study, PEEK shows lower coefficient of friction than ceramic. PEEK has excellent properties such as low friction coefficient, smooth surface and good mechanical properties, and thus meets the requirements for orthodontic brackets. It is considered as a potential bracket material with both low friction and aesthetic performance. [ABSTRACT FROM AUTHOR]

Deep low-rank coalbed methane (CBM) resources are numerous and widely distributed in China, although their exploration remains in its infancy. In this work, gas adsorption (N2/CO2), mercury intrusion porosimetry, and 3D CT reconstruction were performed on five coal samples of deep and shallow low-rank coal from northeast China to analyze their pore structure. The impact of the features in the pore structure at full scale on the capacity for methane adsorption and seepage is discussed. The results indicate that there are significant differences between deep low-rank coal and shallow low-rank coal in terms of porosity, permeability, composition, and adsorption capacity. The full-scale pore distribution was dispersed over a broad range and exhibited a multi-peak distribution, with the majority of the peak concentrations occurring between 0.45–0.7 nm and 3–4 nm. Mesopores are prevalent in shallow coal rock, whereas micropores are the most numerous in deep coal rock. The primary contributors to the specific surface area of both deep and superficial coal rock are micropores. Three-dimensional CT reconstruction can characterize pores with pore size greater than 1 μm, while the dominating equivalent pore diameters (Deq) range from 1 to 10 μm. More mini-scale pores and fissures are observed in deep coal rock, while shallow coal rock processes greater total and connection porosity. Multifractal features are prevalent in the fractal qualities of all the numbered samples. An enhancement in pore structure heterogeneity occurs with increasing pore size. The pore structure of deep coal rock is more heterogeneous. Furthermore, methane adsorption capacity is favorably connected with D1 (0.4 nm < pore diameter ≤ 2 nm), D2 (2 nm < pore diameter ≤ 5 nm), micropore volume, and specific surface area and negatively correlated with D3 (5 nm < pore diameter ≤ 50 nm), showing that methane adsorption capability is primarily controlled by micropores and mesopores. Methane seepage capacity is favorably connected with the pore volume and connected porosity of macropores and negatively correlated with D4 (pore diameter > 50 nm), indicating that the macropores are the primary factor influencing methane seepage capacity. [ABSTRACT FROM AUTHOR]

A polyurethane (PU) mixture was used to replace the wearing course of asphalt pavement because of its excellent mechanical properties, which necessitated the selection of suitable interlayer bonding materials between the polyurethane mixture wearing course and the asphalt mixture bottom course. Five types of tack coat materials were designed, including styrene-butadiene-rubber modified emulsified asphalt (SBREA), waterborne epoxy resin modified emulsified asphalt (WEREA), waterborne polyurethane modified emulsified asphalt (WPUEA), polyurethane, and polyurethane-stabilized fine sand (PUFS). Their cohesion performance under elevated temperature, high-temperature immersion, and freeze–thaw conditions was evaluated with tensile tests and shear tests. The results show that PUFS has the best adhesive properties, followed by PU, WPUEA, WEREA, and SBREA. WPUEA offers remarkable high-temperature stability, but is greatly affected by moisture. PU and PUFS exhibit outstanding freeze–thaw resistance, with the residual tensile strength and shear strength remaining above 75%. By incorporating fine sand into the composition, PUFS enhances interfacial friction compared with PU. However, this modification results in a slight reduction in its water stability. [ABSTRACT FROM AUTHOR]

National higher education initiatives are government-led strategies designed to enhance university quality, international ranking, and competitiveness through targeted policy measures and investments. In order to improve human capital and global competitiveness, many countries worldwide such as China, Japan, Russia, and Germany have implemented national higher education initiatives in recent years. This study used panel data from the top universities in the QS ranking and ARWU ranking to evaluate the impact of these initiatives on university rankings using a Staggered Difference-in-Differences Model and explore the underlying reasons for heterogeneity in effectiveness across different regions and countries. It found that national higher education initiatives have a significant positive impact on universities' rankings by improving 12.1 to 17.7 places in QS and ARWU rankings respectively. Compared to European universities, universities in Asia-Pacific region improved rankings more obviously. The findings suggest that developing countries can learn from the experiences of other countries in implementing national higher education initiatives and improving higher education quality through encouraging competitiveness while offering autonomy, optimizing higher education management model, enhancing regular quality evaluations, and dynamic withdrawal mechanism. [ABSTRACT FROM AUTHOR]

BACKGROUND: The minimally invasive endodontics could retain more peri-cervical dentin (PCD) and other important dental structures, thus realizing the minimal loss of teeth structures and preserving the strength and function of the endodontically treated tooth (ETT). The search for abnormal root canals or calcified root canals could be quite time-consuming and increase the risk of perforation. OBJECTIVE: This study introduced a novel multifunctional 3D printing guided splint inspired by the dice, which can achieve the minimally invasive access cavity preparation and canal orifice identification. METHOD: Data were collected from an outpatient with dens invaginatus. Cone-beam Computed Tomography (CBCT) revealed a type III invagination. The CBCT data of the patient were imported into a computer-aided design (CAD) software (Exocad 3.0; Exocad GmbH) for the 3D reconstruction of jaw bones and teeth. The dice-inspired 3D printing guided splint consists of the sleeve and guided splint. The sleeve with minimal invasive opening channel and orifice locating channel were designed with a reverse-engineering software (Geomagic Wrap 2021). The reconstructed models in the Standard Template Library (STL) format were imported into a CAD software. The design of the template was aided by the dental CAD software in Splint Design Mode. The sleeve and splint were exported into the STL files separately. A 3D printer (ProJet ® 3600 3D Systems) was used to separately generate the sleeve and guided splint, and was made by stereolithography and processed in a medical resin (VisiJet M3 StonePlast). RESULTS: The novel multifunctional 3D printing guided splint could be set in position. The opening side in the sleeve was selected and the sleeve was inserted in place. The minimal invasive opening was made in the crown of the tooth to access the pulp. The sleeve was draw out and turned to the orifice location side, and then inserted in place. The target orifice was located rapidly. CONCLUSION: This novel dice-inspired multifunctional 3D printing guided splint allow dental practitioners to gain accurate, conservative, and safe cavity access from teeth with anatomical malformations. Complex operations might be carried out with less reliance on the operator's experience than with conventional access preparations. This novel dice-inspired multifunctional 3D printing guided splint would have a broad application in the dental field. [ABSTRACT FROM AUTHOR]

As the global warming crisis becomes increasingly serious, sustainable dispatch strategies that can reduce CO2 emissions are gradually developed. Aiming at the problems of poor synergy between carbon capture systems (CCS) and P2G as well as the potential of the source-load interaction of microgrids with electric vehicles for carbon reduction that needs to be explored, this paper proposes a source-load coordinated low-carbon economic dispatch strategy for microgrids, including electric vehicles. Firstly, considering the low-carbon operation characteristics of CCS and P2G, a comprehensively flexible and cooperative operation mode for CCS and P2G is constructed. Secondly, based on the carbon reduction potential of demand response on the energy consumption side, a demand response optimal scheduling model considering the participation of electric vehicles in the microgrid is established. Finally, based on the complementary characteristics of low-carbon resources on both sides of the microgrid, a source-load coordinated low-carbon economic dispatch strategy for the microgrid is proposed. The results show that the strategy proposed in this paper can fully use the energy time-shift advantage of CCS and P2G and can combine EVs and other load-side resources to flexibly participate in demand-side response, which effectively realizes source-load synergy and improves the low carbon and economy of the microgrid. [ABSTRACT FROM AUTHOR]

Background: The fusion of computed tomography (CT) and ultrasound (US) image can enhance lesion detection ability and improve the success rate of liver interventional radiology. The image‐based fusion methods encounter the challenge of registration initialization due to the random scanning pose and limited field of view of US. Existing automatic methods those used vessel geometric information and intensity‐based metric are sensitive to parameters and have low success rate. The learning‐based methods require a large number of registered datasets for training. Purpose: The aim of this study is to provide a fully automatic and robust US‐3D CT registration method without registered training data and user‐specified parameters assisted by the revolutionary deep learning‐based segmentation, which can further be used for preparing training samples for the study of learning‐based methods. Methods: We propose a fully automatic CT‐3D US registration method by two improved registration metrics. We propose to use 3D U‐Net‐based multi‐organ segmentation of US and CT to assist the conventional registration. The rigid transform is searched in the space of any paired vessel bifurcation planes where the best transform is decided by a segmentation overlap metric, which is more related to the segmentation precision than Dice coefficient. In nonrigid registration phase, we propose a hybrid context and edge based image similarity metric with a simple mask that can remove most noisy US voxels to guide the B‐spline transform registration. We evaluate our method on 42 paired CT‐3D US datasets scanned with two different US devices from two hospitals. We compared our methods with other exsiting methods with both quantitative measures of target registration error (TRE) and the Jacobian determinent with paired t‐test and qualitative registration imaging results. Results: The results show that our method achieves fully automatic rigid registration TRE of 4.895 mm, deformable registration TRE of 2.995 mm in average, which outperforms state‐of‐the‐art automatic linear methods and nonlinear registration metrics with paired t‐test's p value less than 0.05. The proposed overlap metric achieves better results than self similarity description (SSD), edge matching (EM), and block matching (BM) with p values of 1.624E‐10, 4.235E‐9, and 0.002, respectively. The proposed hybrid edge and context‐based metric outperforms context‐only, edge‐only, and intensity statistics‐only‐based metrics with p values of 0.023, 3.81E‐5, and 1.38E‐15, respectively. The 3D US segmentation has achieved mean Dice similarity coefficient (DSC) of 0.799, 0.724, 0.788, and precision of 0.871, 0.769, 0.862 for gallbladder, vessel, and branch vessel, respectively. Conclusions: The deep learning‐based US segmentation can achieve satisfied result to assist robust conventional rigid registration. The Dice similarity coefficient‐based metrics, hybrid context, and edge image similarity metric contribute to robust and accurate registration. [ABSTRACT FROM AUTHOR]

Color vision is mediated by the expression of different major visual pigment proteins (opsins) on retinal photoreceptors. Vertebrates have four classes of cone opsins that are most sensitive to different wavelengths of light: short wavelength sensitive 1 (SWS1), short wavelength sensitive 2 (SWS2), medium wavelength sensitive (RH2), and long wavelength sensitive (LWS). UV wavelengths play important roles in foraging and communication. However, direct evidence provide links between sws1 and first feeding is lacking. Here, CRISPR/Cas9 technology was performed to generate mutant zebrafish lines with sws1 deletion. sws1 mutant zebrafish larvae exhibited decreased sws1, rh2-2, and lws1 expression, and increased rod gene (rho and gnat1) expression. Furthermore, the sws1-deficient larvae exhibited significantly reduced food intake, and the orexigenic genes npy and agrp signaling were upregulated at 6 days postfertilization (dpf). The transcription expression of sws1 and rh2-3 genes decreased in sws1−/− adults compared to wild type. Surprisingly, the results of feeding at the adult stage were not the same with larvae. sws1 deficiency did not affect food intake and appetite gene expression at adult stages. These results reveal a role for sws1 in normal cone development and first feeding in larval zebrafish. [ABSTRACT FROM AUTHOR]