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How to enhance the desired signal with low signal-to-noise ratio (SNR) is a difficult problem in the estimation process of the direction-of-arrival (DOA) of the target scattering wave signal. In this paper, the feasibility of spatial spectrum estimation in the Range-Doppler (RD) domain is analyzed in principle, and the SNR gain expression of weak scattering wave signal is derived when constructing multi-snapshots virtual array data. On this basis, the mutual eigenvector singular value decomposition (MESVD) method based on RD domain mode excitation is proposed, which can robustly and effectively estimate the direction of the coherent weak signals. Simulation experiments verify that the RD domain spectral estimation method has the ability to simultaneously obtain the direction of multiple weak target scattering waves, and the direction-finding accuracy can reach the Cramer–Rao bound (CRB) of conventional spectral estimation method. The results of Monte Carlo experiments show that the root-mean-square-error (RMSE) of azimuth estimation of RD domain spatial spectrum estimation method is 5.76° lower than that of a conventional multiple signal classification (MUSIC) method. In addition, the practicability of the proposed method is demonstrated by comparing the DOA estimation results of a set of real data with Automatic Dependent Surveillance-Broadcast (ADS-B) data. [ABSTRACT FROM AUTHOR]

This paper investigates the nonlinear free vibration of spinning pre-twisted functionally graded material (FGM) plates in thermal environment. Based on the Kirchhoff plate theory and von Kármán large-deformation theory, the nonlinear dynamic model is established via the Lagrange equation, where the warping effect is taken into account. The material properties are related to temperature and change according to a power-law exponent distribution. The theoretical solution of nonlinear-free vibration is obtained using the multiple scale method. The effects of power-law exponent, temperature difference, spinning speed, hub radius ratio, and twist angle on nonlinear-free vibration characteristics of the spinning pre-twisted cantilever FGM plates are discussed. The results show that the spinning pre-twisted cantilever FGM plate exhibits nonlinear hardening-spring vibration behavior, while the characteristics weaken with the increase of spinning speed. The twist angle and setting angle have coupling effects on the nonlinear vibration characteristics of spinning pre-twisted FGM plates. [ABSTRACT FROM AUTHOR]

Feature selection in classification is a complex optimization problem that cannot be solved in polynomial time. Bi-objective feature selection, aiming to minimize both selected features and classification errors, is challenging due to the conflict between objectives, while one of the most effective ways to tackle this is to use multi-objective evolutionary algorithms. However, very few of these have ever reflected an evolutionary multi-tasking framework, despite the implicit parallelism offered by the population-based search characteristic. In this paper, a dynamic multi-tasking-based multi-objective evolutionary algorithm (termed DTEA) is proposed for handling bi-objective feature selection in classification, which is not only suitable for datasets with relatively lower dimensionality of features, but is also suitable for datasets with relatively higher dimensionality of features. The role and influence of multi-tasking on multi-objective evolutionary feature selection were studied, and a dynamic tasking mechanism is proposed to self-adaptively assign multiple evolutionary search tasks by intermittently analyzing the population behaviors. The efficacy of DTEA is tested on 20 classification datasets and compared with seven state-of-the-art evolutionary algorithms. A component contribution analysis was also conducted by comparing DTEA with its three variants. The empirical results show that the dynamic-tasking mechanism works efficiently and enables DTEA to outperform other algorithms on most datasets in terms of both optimization and classification. [ABSTRACT FROM AUTHOR]

Using a simple acid-base neutralization method, a Ch-PW solid catalyst was synthesized by mixing choline hydroxide (ChOH) and phosphotungstic acid (HPW) at a 2:1 molar ratio in an aqueous solution. This catalyst was combined with a 20 wt.% potassium peroxymonosulfate (PMS) solution, using acetonitrile (ACN) as the extraction solvent to create an extraction catalytic oxidative desulfurization system. The optimal desulfurization conditions were determined through response surface methodology, targeting the highest desulfurization rate: 0.99 g of Ch-PW, 1.07 g of PMS, 2.5 g of extraction solvent, at a temperature of 50.48 °C. The predicted desulfurization rate was 90.79%, compared to an experimental rate of 93.64%, with a deviation of 3.04%. A quadratic model correlating the desulfurization rate with the four conditions was developed and validated using ANOVA, which also quantified the impact of each factor on the desulfurization rate: PMS > ACN > Ch-PW > temperature. GC-MS analysis identified the main oxidation product as DBTO2, and the mechanism of desulfurization in this system was further explored. [ABSTRACT FROM AUTHOR]

To address the cost and efficiency issues of manually analysing requirement dependency in requirements engineering, a requirement dependency extraction method based on part-of-speech features and an improved stacking ensemble learning model (P-Stacking) is proposed. Firstly, to overcome the problem of singularity in the feature extraction process, this paper integrates part-of-speech features, TF-IDF features, and Word2Vec features during the feature selection stage. The particle swarm optimization algorithm is used to allocate weights to part-of-speech tags, which enhances the significance of crucial information in requirement texts. Secondly, to overcome the performance limitations of standalone machine learning models, an improved stacking model is proposed. The Low Correlation Algorithm and Grid Search Algorithms are utilized in P-stacking to automatically select the optimal combination of the base models, which reduces manual intervention and improves prediction performance. The experimental results show that compared with the method based on TF-IDF features, the highest F1 scores of a standalone machine learning model in the three datasets were improved by 3.89%, 10.68%, and 21.4%, respectively, after integrating part-of-speech features and Word2Vec features. Compared with the method based on a standalone machine learning model, the improved stacking ensemble machine learning model improved F1 scores by 2.29%, 5.18%, and 7.47% in the testing and evaluation of three datasets, respectively. [ABSTRACT FROM AUTHOR]

The h-BN/diamond mix-dimensional heterostructure has broad application prospects in the fields of optoelectronic devices and power electronic devices. In this paper, the electronic properties and band offsets of hexagonal boron nitride (h-BN)/(H, O, F, OH)-diamond (111) heterostructures were studied by first-principles calculations under biaxial strain. The results show that different terminals could significantly affect the interface binding energy and charge transfer of h-BN/diamond heterostructure. All heterostructures exhibited semiconductor properties. The h-BN/(H, F)-diamond systems were indirect bandgap, while h-BN/(O, OH)-diamond systems were direct bandgap. In addition, the four systems all formed type-II heterostructures, among which h-BN/H-diamond had the largest band offset, indicating that the system was more conducive to the separation of electrons and holes. Under biaxial strain the bandgap values of the h-BN/H-diamond system decreased, and the band type occurred direct–indirect transition. The bandgap of h-BN/(O, F, OH)-diamond system increased linearly in whole range, and the band type only transformed under large strain. On the other hand, biaxial strain could significantly change the band offset of h-BN/diamond heterostructure and promote the application of this heterostructure in different fields. Our work provides theoretical guidance for the regulation of the electrical properties of h-BN/diamond heterostructures by biaxial strain. [ABSTRACT FROM AUTHOR]

Evolutionary algorithms have been widely used for tackling multi-objective optimization problems, while feature selection in classification can also be seen as a discrete bi-objective optimization problem that pursues minimizing both the classification error and the number of selected features. However, traditional multi-objective evolutionary algorithms (MOEAs) can encounter setbacks when the dimensionality of features explodes to a large scale, i.e., the curse of dimensionality. Thus, in this paper, we focus on designing an adaptive MOEA framework for solving bi-objective feature selection, especially on large-scale datasets, by adopting hybrid initialization and effective reproduction (called HIER). The former attempts to improve the starting state of evolution by composing a hybrid initial population, while the latter tries to generate more effective offspring by modifying the whole reproduction process. Moreover, the statistical experiment results suggest that HIER generally performs the best on most of the 20 test datasets, compared with six state-of-the-art MOEAs, in terms of multiple metrics covering both optimization and classification performances. Then, the component contribution of HIER is also studied, suggesting that each of its essential components has a positive effect. Finally, the computational time complexity of HIER is also analyzed, suggesting that HIER is not time-consuming at all and shows promising computational efficiency. [ABSTRACT FROM AUTHOR]

The multi-objective evolutionary algorithm optimization (MOEA) is a challenging but critical approach for tackling complex data analysis problems. However, prevailing MOEAs often rely on single strategies to obtain optimal solutions, leading to concerns such as premature convergence and insufficient population diversity, particularly in high-dimensional data scenarios. In this paper, we propose a novel adversarial population generation algorithm, APG-SMOEA, which synergistically combines the benefits of MOEAs and Generative Adversarial Networks (GANs) to address these limitations. In order to balance the efficiency and quality of offspring selection, we introduce an adaptive population entropy strategy, which includes control parameters based on population entropy and a learning pool for storing and retrieving optimal solutions. Additionally, we attempt to alleviate the training complexity and model collapse problems common in GANs with APG-SMOEA. Experimental results on benchmarks demonstrate that the proposed algorithm is superior to the existing algorithms in terms of solution quality and diversity of low-dimensional or high-dimensional complex data. [ABSTRACT FROM AUTHOR]

Optimal integration of transcriptomics data and associated spatial information is essential towards fully exploiting spatial transcriptomics to dissect tissue heterogeneity and map out inter-cellular communications. We present SEDR, which uses a deep autoencoder coupled with a masked self-supervised learning mechanism to construct a low-dimensional latent representation of gene expression, which is then simultaneously embedded with the corresponding spatial information through a variational graph autoencoder. SEDR achieved higher clustering performance on manually annotated 10 × Visium datasets and better scalability on high-resolution spatial transcriptomics datasets than existing methods. Additionally, we show SEDR's ability to impute and denoise gene expression (URL: https://github.com/JinmiaoChenLab/SEDR/). [ABSTRACT FROM AUTHOR]

Simple Summary: The circadian clock plays a crucial role in helping plants to effectively acclimate to ever-changing environmental conditions. The proper functioning of the circadian clock is integral to the growth and development of plants. In crops, the circadian clock system exerts a multifaceted influence on yield and the response to abiotic stress. This review provides a comprehensive overview of the mechanisms through which the components of a crop's circadian clock impact its response to abiotic stress and yield. We propose that the circadian clock may orchestrate the balance between abiotic stresses and yield in crops, which is useful for the future molecular design of crop breeding. Plants have evolved a circadian clock to adapt to ever-changing diel and seasonal environmental conditions. The circadian clock is generally considered an internal system that has evolved to adapt to cyclic environmental cues, especially diel light and temperature changes, which is essential for higher plants as they are sessile organisms. This system receives environmental signals as input pathways which are integrated by circadian core oscillators to synchronize numerous output pathways, such as photosynthesis, the abiotic stress response, metabolism, and development. Extreme temperatures, salinity, and drought stresses cause huge crop losses worldwide, imposing severe pressure on areas of agricultural land. In crop production, the circadian system plays a significant role in determining flowering time and responding to external abiotic stresses. Extensive studies over the last two decades have revealed that the circadian clock can help balance the tradeoff between crop yield-related agronomic traits and adaptation to stress. Herein, we focus on summarizing how the circadian clock coordinates abiotic stress responses and crop yield. We also propose that there might be an urgent need to better utilize circadian biology in the future design of crop breeding to achieve high yields under stress conditions. [ABSTRACT FROM AUTHOR]

Estimating the gamma dose rate at one meter above ground level and determining the distribution of radioactive pollution from aerial radiation monitoring data are the core technical issues of unmanned aerial vehicle nuclear radiation monitoring. In this paper, a reconstruction algorithm of the ground radioactivity distribution based on spectral deconvolution was proposed for the problem of regional surface source radioactivity distribution reconstruction and dose rate estimation. The algorithm estimates unknown radioactive nuclide types and their distributions using spectrum deconvolution and introduces energy windows to improve the accuracy of the deconvolution results, achieving accurate reconstruction of multiple continuous distribution radioactive nuclides and their distributions, as well as dose rate estimation of one meter above ground level. The feasibility and effectiveness of the method were verified through cases of single-nuclide (137Cs) and multi-nuclide (137Cs and 60Co) surface sources by modeling and solving them. The results showed that the cosine similarities between the estimated ground radioactivity distribution and dose rate distribution with the true value were 0.9950 and 0.9965, respectively, which could prove that the proposed reconstruction algorithm would effectively distinguish multiple radioactive nuclides and accurately restore their radioactivity distribution. Finally, the influences of statistical fluctuation levels and the number of energy windows on the deconvolution results were analyzed, showing that the lower the statistical fluctuation level and the more energy window divisions, the better the deconvolution results. [ABSTRACT FROM AUTHOR]

Fiber Optic Gyroscope Inertial Navigation System (FOG-INS) is a navigation system using fiber optic gyroscopes and accelerometers, which can offer high-precision position, velocity, and attitude information for carriers. FOG-INS is widely used in aerospace, marine ships, and vehicle navigation. In recent years, it has also played an important role in underground space. For example, in the deep earth, FOG-INS can be used in directional well drilling, which can enhance recovery in resource exploitation. While, in shallow earth, FOG-INS is a high-precision positioning technique that can guide construction in trenchless underground pipelaying. This article extensively reviews the application status and latest progress of FOG-INS in underground space from three aspects—FOG inclinometer, FOG drilling tool attitude measurement while drilling (MWD) unit, and FOG pipe-jacking guidance system. First, measurement principles and product technologies are introduced. Second, the research hot spots are summarized. Finally, the key technical issues and future trends for development are put forward. The findings of this work are useful for further research in the field of FOG-INS in underground space, which not only provides new ideas and directions for scientific research, but also offers guidance for subsequent engineering applications. [ABSTRACT FROM AUTHOR]

Due to frequent human disturbance and the influence of crop growth and development, the migration of soil organic carbon (SOC) in sloping farmland is considerably different to those in other ecosystems. The impacts of maize over its entire growth period on the SOC loss in sloping farmland on purple soils under different erosion stages were investigated, in 2016. This was undertaken using rainfall simulation tests on 15° slopes with a rainfall intensity of 1.5 mm·min−1, in Sichuan Province, China. In this study, erosion development, fluctuating increasing trends in the surface runoff yield, interflow runoff yield, sediment yield, and dissolved organic carbon (DOC) migration flux were observed. Opposite trends were observed in the DOC mass concentration, total soil organic carbon (TOC) content of the sediment, the SOC content of sediment particle state, the DOC content of the sediment, and the SOC enrichment ratio. The DOC migration flux in the surface runoff and in interflow of the rill erosion stage was 1.39–2.84, 3.22–7.78 times significantly higher than that of the sheet erosion stage at each maize growth stage, respectively (p < 0.05). The average DOC mass concentration in the surface runoff, the total DOC content of the sediment, and the SOC enrichment ratio in the sheet erosion stage increased by 100.58–146.44%, 44.44–126.15%, 141.32–191.26%, respectively, compared with the rill erosion stage. Under the experimental conditions, we found that DOC loss mainly occurred at the seedling and mature stages for maize. We also found that maize growth could promote the production of soil interflow, leading to intense soil loss occurring at the subsurface. Compared with DOC mass concentrations in the surface runoff, there was an increase of 4.90–28.29% in the soil interflow, indicating that soil interflow plays a more important role in DOC loss. The growth of maize could impact formation of surface runoff and interflow, reducing the loss of SOC caused by soil erosion. This study helps to understand the carbon loss process in agricultural production in purple soil areas. [ABSTRACT FROM AUTHOR]

The intermediate di-[EMIM]Cl was synthesized from methyl imidazole and 1,4-dichlorobutane and then reacted with cobalt chloride at 105 °C to prepare a bi-[EMIM]CoCl3 ionic liquid catalyst. The di-[EMIM]CoCl3 catalyst coupled with oxone to remove sulfur-containing organics in octane. The di-[EMIM]CoCl3 catalyst was characterized by HNMR, FTIR, TG, and SEM–EDS. The dibenzothiophene (DBT) was dissolved in octane to prepare a model oil with an initial sulfur content of 500 ppm. Six grams of the model oil was added. The results showed that the optimal dosages of di-[EMIM]CoCl3, oxone (20 wt%), and [BMIM]BF4 extractant were 1 g, 2 g, and 2 g, respectively. At the optimum temperature of 45 °C, 100% of sulfur was removed after 40 min. After di-[EMIM]CoCl3 was recycled five times, the sulfur removal percentage remained above 91%. The sulfur removal percentages for different sulfur-containing organics followed the order of dibenzothiophene (DBT) > benzothiophene (BT) > 4,6-dimethyldibenzothiophene (4,6-DMDBT). The oxidation product was determined to be DBTO2 by GC–MS analysis, and the oxidation mechanism was discussed. The active oxygen atoms of oxone oxidized DBT to form DBTO, and then persulfate oxidized DBTO to DBTO2 via an identical oxidation mechanism. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the discriminatory capability of spectral CT-based radiomics to distinguish benign from malignant solitary pulmonary solid nodules (SPSNs). Materials and methods: A retrospective study was performed including 242 patients with SPSNs who underwent contrast-enhanced dual-layer Spectral Detector CT (SDCT) examination within one month before surgery in our hospital, which were randomly divided into training and testing datasets with a ratio of 7:3. Regions of interest (ROIs) based on 40-65 keV images of arterial phase (AP), venous phases (VP), and 120kVp of SDCT were delineated, and radiomics features were extracted. Then the optimal radiomics-based score in identifying SPSNs was calculated and selected for building radiomics-based model. The conventional model was developed based on significant clinical characteristics and spectral quantitative parameters, subsequently, the integrated model combining radiomics-based model and conventional model was established. The performance of three models was evaluated with discrimination, calibration, and clinical application. Results: The 65 keV radiomics-based scores of AP and VP had the optimal performance in distinguishing benign from malignant SPSNs (AUC65keV-AP = 0.92, AUC65keV-VP = 0.88). The diagnostic efficiency of radiomics-based model (AUC = 0.96) based on 65 keV images of AP and VP outperformed conventional model (AUC = 0.86) in the identification of SPSNs, and that of integrated model (AUC = 0.97) was slightly further improved. Evaluation of three models showed the potential for generalizability. Conclusions: Among the 40-65 keV radiomics-based scores based on SDCT, 65 keV radiomics-based score had the optimal performance in distinguishing benign from malignant SPSNs. The integrated model combining radiomics-based model based on 65 keV images of AP and VP with Zeff-AP was significantly superior to conventional model in the discrimination of SPSNs. [ABSTRACT FROM AUTHOR]

NK-lysin (NKL) is a family of antimicrobial proteins with an important role in innate and adaptive immunity. In this study, a non-canonical NK-lysin (NKLnc) was identified in the Japanese flounder (Paralichthys olivaceus), which shares low sequence identities (15.8–20.6%) with previously reported fish NKLs and was phylogenetically separated from the canonical NKLs in teleost. NKLnc expression was upregulated in flounder tissues during bacterial infection, and interference with NKLnc expression impaired the ability of flounder cells to eliminate invading bacteria. When expressed in Escherichia coli, NKLnc was detrimental to the host cells. P35, a peptide derived from the saposin B domain (SapB) of NKLnc, bound major bacterial surface molecules and killed both Gram-negative and Gram-positive bacteria by inflicting damage to bacterial cell structure and genomic DNA. The bactericidal activity, but not the bacteria-binding capacity, of P35 required the structural integrity of the alpha 2/3 helices in SapB. Furthermore, P35 induced the migration of flounder peripheral blood leukocytes, inhibited bacterial dissemination in fish tissues, and facilitated fish survival after bacterial challenge. Together our study reveals that NKLnc plays an important part in flounder immune defense, and that NKLnc peptide exerts an antimicrobial effect via multiple mechanisms by targeting both bacteria and fish cells. [ABSTRACT FROM AUTHOR]

The magnetized Jeffery–Hamel flow due to a point sink or source in convergent and divergent channels is studied. Such viscous flow plays an important role in understanding rivers and canals, human anatomy, and the connection between capillaries and arteries. The simplified governing equation ruled by the Reynolds number, the Hartmann number and the divergent–convergent angle with appropriate boundary conditions is solved by the newly proposed Coiflet wavelet-homotopy analysis method (CWHAM). A highly accurate solution is obtained, whose accuracy is rigidly checked. Our proposed method combines the advantages of the homotopy analysis method for strong nonlinearity and the Coiflet wavelet method for excellent local expression capability so that it holds higher computational efficiency, larger applicable range of physical parameters, and better nonlinear processing capability. Different from the previously published research on the CWHAM, we focus on establishing the solution process of nonlinear flow problems with extreme physical parameters, which is not considered before. [ABSTRACT FROM AUTHOR]

In order to solve the problem of low electrical conductivity of carbon nanofiber membranes, a novel triple crosslinking strategy, including pre-rolling, solvent and chemical imidization crosslinking, was proposed to prepare carbon nanofiber membranes with a chemical crosslinking structure (CNMs-CC) derived from electrospinning polyimide nanofiber membranes. The physical-chemical characteristics of CNMs-CC as freestanding anodes for lithium-ion batteries were investigated in detail, along with carbon nanofiber membranes without a crosslinking structure (CNMs) and carbon nanofiber membranes with a physical crosslinking structure (CNMs-PC) as references. Further investigation demonstrates that CNMs-CC exhibits excellent rate performance and long cycle stability, compared with CNMs and CNMs-PC. At 50 mA g−1, CNMs-CC delivers a reversible specific capacity of 495 mAh g−1. In particular, the specific capacity of CNMs-CC is still as high as 290.87 mAh g−1 and maintains 201.38 mAh g−1 after 1000 cycles at a high current density of 1 A g−1. The excellent electrochemical performance of the CNMs-CC is attributed to the unique crosslinking structure derived from the novel triple crosslinking strategy, which imparts fast electron transfer and ion diffusion kinetics, as well as a stable structure that withstands repeated impacts of ions during charging and discharging process. Therefore, CNMs-CC shows great potential to be the freestanding electrodes applied in the field of flexible lithium-ion batteries and supercapacitors owing to the optimized structure strategy and improved properties. [ABSTRACT FROM AUTHOR]

Global climate change profoundly influences the patterns of vegetation growth. However, the disparities in vegetation responses induced by regional climate characteristics are generally weakened in large-scale studies. Meanwhile, distinct climatic drivers of vegetation growth result in the different reactions of different vegetation types to climate variability. Hence, it is an extraordinary challenge to detect and attribute vegetation growth changes. In this study, the spatiotemporal distribution and dynamic characteristics of climate change effects on vegetation growth from 2000 to 2020 were investigated by the normalized difference vegetation index (NDVI) dataset during the growing season (April–October). Meanwhile, we further detected the climate-dominated factor between different vegetation types (i.e., forest, shrub, and grass) within the Chaohe watershed located in temperate northern China. The results revealed a continuous greening trend over the entire study period, despite slowing down since 2007 (p < 0.05). Growing-season precipitation (P) was identified as the dominant climatic factor of the greening trend (p < 0.05), and approximately 34.83% of the vegetated area exhibited a significant response to increasing P. However, continued warming-induced intensive evaporation demand caused the vegetation growth to slow down. Hereinto, the areas with a significantly positive response of forest growth to temperature decreased from 24.38% to 18.06% (p < 0.05). In addition, solar radiation (SW) corresponds to the vegetation trend in the watershed (p < 0.05), and the significantly positive SW-influenced areas increased from 9.24% and 2.64% to 11.78% and 3.37% in forests and shrubland, respectively (p < 0.05). Our findings highlight the nonlinearity of long-term vegetation growth trends with climate variation and the cause of this divergence, which provide vital insights into forecasting vegetation responses to future climate change. [ABSTRACT FROM AUTHOR]

This study presents the time-dependent squeezing flow between parallel discs under the influence of various physical processes such as magnetohydrodynamics, micropolarity, thermophysics, homogeneous-heterogeneous chemical reactions, and bioconvection. The slip and permeability effects are considered at the boundaries. The nonlinear system is simplified through scaling transformations and subsequently solved numerically. Besides, an artificial neural network (ANN) model is developed to predict the values of skin-friction coefficients, heat transfer rates, and mass transfer rates at both discs. The performance of the ANN model is validated against the computational results, demonstrating robustness with correlation coefficients being almost close to 1. The ANN model performs more robustly for instance, skin-friction coefficient model revealed correlation (R) equaling 0.99775 and 0.99537 for the test data of the lower and upper discs, respectively. The values for heat and mass transfer observe as 0.99999, 0.99938, and 0.99839, 0.99167 for the test data of lower and upper discs. Parametric and sensitivity analyses produce results that are comparable to the numerical findings. Graphical and tabular representations are provided for various dimensionless parameters. Results indicate that the developed model is reliable and capable of accurately predicting multiple physical processes. [ABSTRACT FROM AUTHOR]

In order to prevent illegal intrusion, theft, and destruction, important places require stable and reliable human intrusion detection technology to maintain security. In this paper, a combined sensing system using anti-jamming random code signals is proposed and demonstrated experimentally to detect the human intruder in the protected area. This sensing system combines the leaky coaxial cable (LCX) sensor and the single-transmitter-double-receivers (STDR) radar sensor. They transmit the orthogonal physical random code signals generated by Boolean chaos as the detection signals. The LCX sensor realizes the early intrusion alarm at the protected area boundary by comparing the correlation traces before and after intrusion. Meanwhile, the STDR radar sensor is used to track the intruder's moving path inside the protected area by correlation ranging and ellipse positioning, as well as recognizing intruder's activities by time-frequency analysis, feature extraction, and support vector machine. The experimental results demonstrate that this combined sensing system not only realizes the early alarm and path tracking for the intruder with the 13 cm positioning accuracy, but also recognizes the intruder's eight activities including squatting, picking up, jumping, waving, walking forward, running forward, walking backward, and running backward with 98.75% average accuracy. Benefiting from the natural randomness and auto-correlation of random code signal, the proposed sensing system is also proved to have a large anti-jamming tolerance of 27.6 dB, which can be used in the complex electromagnetic environment. [ABSTRACT FROM AUTHOR]

Magnesium-rare earth (Mg-Re) alloys are very promising structural materials in lightweight industries, while the poor corrosion resistance limits their widespread application. In this work, to provide insights into the functions of precipitate characteristics on the corrosion behaviors of Mg-Re alloys, the influence of heat treatments on the corrosion behavior of Mg-11.46Gd-4.08Y-2.09Zn-0.56Zr alloy was investigated via an immersion test, electrochemical experiment and scanning electron microscope (SEM). The results showed that the corrosion rate of Mg-11.46Gd-4.08Y-2.09Zn-0.56Zr alloy specimens decreased by 17.58% and 20.44% after T5 and T6 heat treatment, respectively. In the heat-treated specimens, the corrosion did not extend further into the matrix but formed fine corrosion grooves along the extrusion direction. The improved homogeneity reduced the residual stress and the β' precipitate introduced as a corrosion barrier after T5 and T6 heat treatment reduced the corrosion rate of the studied Mg alloy. In addition, the volume fraction of the long-period stacking-ordered (LPSO) phase decreased after heat treatment, which effectively reduced galvanic corrosion and enhanced the protective effect on the Mg matrix. [ABSTRACT FROM AUTHOR]

In this work, we propose AGKN (attention-based graph learning kernel network), a novel framework to incorporate information of correlated firms of a target stock for its price prediction in an end-to-end way. We first construct a stock-axis attention module to extract dynamic and asymmetric spatial correlations through the kernel method and a graph learning module into which more accurate information can be integrated. An ensemble time-axis attention module is then applied to learn temporal correlations within each stock and market index. Finally, we utilize a transformer encoder to jointly attend to obtain information from different levels for correlations' aggregation and prediction. Experiments with data collected from the Chinese stock market show that AGKN outperforms state-of-the-art baseline methods, making up to 4.3% lower error than the best competitors. The ablation study shows that AGKN pays more attention to hidden correlation between stocks, which improves model's performance greatly. [ABSTRACT FROM AUTHOR]

The classic problem of mixed convection flow within an inclined square lid-driven cavity is extended to hybrid nanofluid case. The governed partial differential equations with non-homogeneous boundary conditions are studied by means of our proposed Coiflet wavelet-homotopy method. Highly accurate solutions with very clear vortex structures are obtained. The effectiveness and efficiency of these solutions are strictly checked through a series of comparisons with published ones in literature. Results show that our proposed approach holds both strong nonlinear processing capability and excellent local display characteristics so that it can be used to attack complicated nonlinear problems more efficiently and accurately than the traditional homotopy analysis method and the Coiflet wavelet analysis approach. Besides, physical properties of hybrid nanofluid behaviors are examined, it is noticed that, similar to nanofluids, the hybrid nanofluid is superior to traditional heat transfer fluids for heat transfer enhancement but it could be easier and cheaper. [ABSTRACT FROM AUTHOR]

[Display omitted] • An updated review of ultrasound-assisted membrane technology is provided. • Theoretical aspects of ultrasound are discussed. • Methods of ultrasound-assisted membrane fouling mitigation are reviewed. • Methods and mechanisms of ultrasound for flux enhancement are addressed. • Potential of UTDR for membrane health monitoring is discussed. In the previous decades, membrane-based separation technologies have found numerous applications in various industries. However, efficient membrane system operation necessitates cost-effective, environmentally friendly means with reduced consumption of chemicals and energy to address restrictions by polarization and membrane fouling. Ultrasound stands out as a distinct approach among current methods for manipulating the physics and chemistry of complex feed fluids in membrane filtration processes, exhibiting satisfactory performance in mass transfer and membrane cleaning. This review provides an overview of the current academic and practical insights, emphasizing physicochemical strategies for diverse ultrasound-assisted membrane systems. The objective is to summarize recent literature related to the use of ultrasound as kernel to improve the separation performance. Based on the technical perspective employing physics and chemistry principles in ultrasound for the liquid transfer, advanced ultrasound-assisted pressure-driven membrane system strategies, compatible ultrasonics applications in membrane bioreactors, and emerging ultrasound-assisted vapor pressure-driven membrane distillation are discussed. The study also covers theories and applications pertaining to acoustic cavitation, cavitation collapse, standing waves, and sonochemical radical effects. Finally, the limitations of current status are elaborated, and the deficiencies of present technologies are reflected upon for the sake of inspiration for novel ultrasound assisted membrane technologies development. [ABSTRACT FROM AUTHOR]

Highly expressed azo-reductase (AZOR) selectively reduces Azo-DON to DON in hypoxic tumor environments, impair glutamine metabolism in cancer cells, and promote tumor cell death without affecting T cell metabolism and proliferation, thereby generating strong antitumor immune responses. CB-PLG nanoparticles (CBP) mentioned in the paper can enhance the degree of hypoxia in normoxic tumors, which is conducive to efficient reduction of Azo-DON at tumor sites. [Display omitted] • Azo-DON is a novel hypoxia-active prodrug of glutamine antagonist. • Azo-DON selectively blocks tumor glutamine metabolism after reducing to DON. • T cells continue to proliferate and remain active when Azo-DON is reduced to DON. • CBP nanoparticles increase tumor hypoxia and facilitate the reduction of Azo-DON. Glutamine antagonists, such as 6-diazo-5-oxo-L-norleucine (DON), have demonstrated remarkable anti-tumor effects by blocking tumor glutamine metabolism, but their use is frequently causing toxicity. Despite the existence of multiple glutamine antagonist prodrug designs, a tumor-selective prodrug has yet to be developed. Herein, a novel prodrug of DON, Azo-DON, has been developed, which remains stable and inactive in normal tissues with sufficient oxygen levels, while can be selectively reduced to DON by highly expressed azo-reductase in hypoxic tumor environments. This leads to blockade of glutamine metabolism in cancer cells and promotes cell death without affecting T cell proliferation. In a high-hypoxic H22 hepatoma cancer model, Azo-DON showed a 1.8-fold enhancement in glutamine blockade compared to the control group, resulting in a tumor suppression rate (TSR) of 84.2% in vivo with no significant weight loss. In a low-hypoxic CT26 colon cancer model, when combined with vascular disrupting agent nanoparticles (CBP) to induce a hypoxic environment, Azo-DON exhibited a 4.6-fold enhancement in glutamine blockade over the control group, resulted in a remarkable TSR of 96.6% in vivo. This innovative approach represents a promising strategy for the application of broad-spectrum metabolic inhibitors in the field of precision cancer treatment. [ABSTRACT FROM AUTHOR]

The mixed convection flow of a hybrid nanofluid in an inclined channel with top wall-slip due to wall stripe and constant heat flux conditions is studied. Explicit analytical solutions are given to the flow velocity, temperature, as well as the pressure in non-dimensional forms. The flow regime domain, the velocity and temperature distributions, and the dependence of various physical parameters such as the hybrid nanoparticle volume fractions, the wall-slip, the Grashof number, the Reynolds number, and the inclined angle are analyzed and discussed. It is found that the hybrid nanofluid delays the appearance of flow reversal on both walls and the wall-slip postpones the flow reversal on the top wall. [ABSTRACT FROM AUTHOR]

Current treatment strategy for kidney renal clear cell carcinoma (KIRC) is limited. Tumor-associated antigens, especially neoantigen-based personalized mRNA vaccines represent new strategies and manifest clinical benefits in solid tumors, but only a small proportion of patients could benefit from them, which prompts us to identify effective antigens and suitable populations to facilitate mRNA vaccines application in cancer therapy. Through performing expression, mutation, survival and correlation analyses in TCGA-KIRC dataset, we identified four genes including DNA topoisomerase II alpha (TOP2A), neutrophil cytosol factor 4 (NCF4), formin-like protein 1 (FMNL1) and docking protein 3 (DOK3) as potential KIRC-specific neoantigen candidates. These four genes were upregulated, mutated and positively associated with survival and antigen-presenting cells in TCGA-KIRC. Furthermore, we identified two immune subtypes, named renal cell carcinoma immune subtype 1 (RIS1) and RIS2, of KIRC. Distinct clinical, molecular and immune-related signatures were observed between RIS1 and RIS2. Patients of RIS2 had better survival outcomes than those of RIS1. Further comprehensive immune-related analyses indicated that RIS1 is immunologically "hot" and represent an immunosuppressive phenotype, whereas RIS2 represents an immunologically "cold" phenotype. RIS1 and RIS2 also showed differential features with regard to tumor infiltrating immune cells and immune checkpoint-related genes. Moreover, the immune landscape construction identified the immune cell components of each KIRC patient, predicted their survival outcomes, and assisted the development of personalized mRNA vaccines. In summary, our study identified TOP2A, NCF4, FMNL1 and DOK3 as potential effective neoantigens for KIRC mRNA vaccine development, and patients with RIS2 tumor might benefit more from mRNA vaccination. [ABSTRACT FROM AUTHOR]

Prostate adenocarcinoma (PRAD) is a leading cause of death among men. Messenger ribonucleic acid (mRNA) vaccine presents an attractive approach to achieve satisfactory outcomes; however, tumor antigen screening and vaccination candidates show a bottleneck in this field. We aimed to investigate the tumor antigens for mRNA vaccine development and immune subtypes for choosing appropriate patients for vaccination. We identified eight overexpressed and mutated tumor antigens with poor prognostic value of PRAD, including KLHL17, CPT1B, IQGAP3, LIME1, YJEFN3, KIAA1529, MSH5 and CELSR3. The correlation of those genes with antigen-presenting immune cells were assessed. We further identified three immune subtypes of PRAD (PRAD immune subtype [PIS] 1–3) with distinct clinical, molecular, and cellular characteristics. PIS1 showed better survival and immune cell infiltration, nevertheless, PIS2 and PIS3 showed cold tumor features with poorer prognosis and higher tumor genomic instability. Moreover, these immune subtypes presented distinguished association with immune checkpoints, immunogenic cell death modulators, and prognostic factors of PRAD. Furthermore, immune landscape characterization unraveled the immune heterogeneity among patients with PRAD. To summarize, our study suggests KLHL17, CPT1B, IQGAP3, LIME1, YJEFN3, KIAA1529, MSH5 and CELSR3 are potential antigens for PRAD mRNA vaccine development, and patients in the PIS2 and PIS3 groups are more suitable for vaccination. [ABSTRACT FROM AUTHOR]

This work analyzes the free vibration of a spinning functionally graded graphene platelet-reinforced metal foam (FG-GPLRMF) beam. The differential transformation method is extended to analyze flap-wise bending vibration and chordwise bending vibration with Coriolis force effect for the first time. The beam is modeled using the Euler–Bernoulli beam theory. The Halpin–Tsai micromechanics model is utilized to predict effective material properties. Various types of graphene platelet (GPL) and porosity distributions are considered. The governing equations and corresponding boundary conditions of the FG-GPLRMF beam are obtained via Hamilton's principle. Results show that the vibration characteristics of the FG-GPLRMF beam are affected by the GPL geometry size, types of porosity, and GPL distributions. Among different types of porosity, the Porosity-A causes the highest fundamental natural frequency, while the Porosity-B corresponds to the lowest one of the spinning FG-GPLRMF beam in most cases. Moreover, the GPL pattern and porosity distribution have a coupled effect on the bending vibration of the spinning FG-GPLRMF beam. [ABSTRACT FROM AUTHOR]

We developed an integrated platform for analysis of parameterized data from human disease models. We report a non‐negative blind deconvolution (NNBD) approach to quantify calcium (Ca2+) handling, beating force and contractility in human‐induced pluripotent stem cell‐derived cardiomyocytes (iPSC‐CMs) at the single‐cell level. We employed CRISPR/Cas gene editing to introduce a dilated cardiomyopathy (DCM)‐causing mutation in troponin T (TnT), TnT‐R141W, into wild‐type control iPSCs (MUT). The NNDB‐based method enabled data parametrization, fitting and analysis in wild‐type controls versus isogenic MUT iPSC‐CMs. Of note, Cas9‐edited TnT‐R141W iPSC‐CMs revealed significantly reduced beating force and prolonged contractile event duration. The NNBD‐based platform provides an alternative framework for improved quantitation of molecular disease phenotypes and may contribute to the development of novel diagnostic tools. [ABSTRACT FROM AUTHOR]

In the field of cranes, unreasonable structure design leads to high energy consumption. In order to solve the problems of heavy weight and serious steel consumption of a crane structure, a green energy-saving design method based on computational intelligence is proposed. For minimizing the weight of a structure, two optimization models are proposed. The specular reflection algorithm is used to make the green and lightweight design. A multi-objective optimization model for the green design is constructed. The minimum waste generated in the manufacturing process is the objective function of this model. Fuzzy mathematics theory is utilized to comprehensively evaluate the impact of crane structure weight and processing waste on the environment, and a structural optimization model with fuzzy comprehensive evaluation indicators for the green design is introduced. The results indicate that compared with the original design, the processing waste after fuzzy comprehensive optimization is 63.43% lower and the cross-sectional area of the main girder is reduced by 27.03%. [ABSTRACT FROM AUTHOR]

The Great Wall of China is one of the largest architectural heritage sites globally, and its sustainability is a significant concern. However, its large extent and diverse characteristics are challenges for deformation monitoring. In this study, the Shanhaiguan section of the Great Wall was investigated in a case study to ascertain the damage and potential hazards of the architectural site. Two standard multi-temporal synthetic aperture radar interferometry (MTInSAR) technologies, including persistent scatterer SAR interferometry (PSInSAR) and small baseline subset (SBAS) SAR interferometry, were used for deformation monitoring using high-resolution TerraSAR-X data acquired in 2015–2017. The results of the two MTInSAR approaches reveal the health condition of the Great Wall. The Shanhaiguan section was stable, but local instabilities caused by rock falls were detected in some mountainous areas. In addition, the applicability of PSInSAR and SBAS was evaluated. The performance analysis of the two approaches indicated that a more reliable and adaptable MTInSAR technique needs to be developed for monitoring the Great Wall. This study demonstrates the potential of MTInSAR technology with high-resolution data for the health diagnosis of heritage sites with a linear structure, such as the Great Wall. [ABSTRACT FROM AUTHOR]

A Coiflet-type wavelet-homotopy approach is implemented to investigate the large deformation of a circular plate resting on different nonlinear foundations with various boundary parameters. A parameterized and continuous boundary model for circular plate with various constraints of rotation and translation has been proposed overlooked in previous studies. Parameterized wavelet approximation of arbitrary Robin-type boundary is reconstituted without variable substitution. Comprehensive analysis on the parameterized Robin-type boundaries is conducted by Linear Programming Approach, indicating the boundary singularities are actually false corresponding to the degenerated cases of Dirichlet-type and Neumann-type ones. Highly accurate Coiflet-type solutions of the coupled governing nonlinear differential equations with integration involving in extreme bending of circular plate have been obtained performing good computational efficiency in excellent agreement with other numerical results, which implies the wavelet scheme is a high precision computation method with great potential in giving highly accurate solutions of strongly nonlinear problems. • The new Coiflet-type wavelet approach for Robin boundary conditions is proposed. • Extreme large bending of a circular plate resting nonlinear foundations is analyzed. • Highly accurate solutions with integrations and singularities are obtained. • Parameterized Robin-type boundaries are conducted by Linear Programming Approach. • Validity and efficiency of the proposed technique is provided. [ABSTRACT FROM AUTHOR]

Numerical studies of flow in square enclosures attain great interest due to their wide applications in engineering, such as in the meteorology, navigation, mechanology and mining, etc. In this paper, the solutions are obtained to the square lid driven cavity describing classical mixed convection in the presence of an inclined magnetic field, chemical radiation and heat absorption/generation. The problem is mathematically reduced into Navier-Stokes equations. The Coiflet wavelet homotopy approach, a newly suggested computational technique, is then used to solve these nonlinear partial differential equations with their non-homogeneous boundary conditions. The numerical solutions for streamlines, isotherms, iso-concentrations contours, Nusselt number are carefully determined. The solutions so obtained are analyzed through various plots to demonstrate the effects of several physical parameters such as Reynolds numbers (Re), Richardson number (Ri), Grashof number (Gr), Hartman number (Ha), thermal radiation parameter (N R), chemical reaction coefficient (K), heat generation/absorption coefficient (Q h), the angle of inclination of magnetic field (γ), slipping parameter (λ) and Schmidt number (Sc) and their physical insights are also reported. Rigid comparison of with previous studies shows excellent computational effectiveness of newly proposed method. Additionally, according to the results, our recently proposed approach has superior characteristics and strong nonlinear processing capabilities, which render it more appropriate than the Coiflet wavelet analysis method and the traditional homotopy analysis method for tackling complex nonlinear problems. [ABSTRACT FROM AUTHOR]

Caspase (CASP) is a protease family that plays a vital role in apoptosis, development, and immune response. Herein, we reported the identification and characterization of two CASPs, AjCASPX1 and AjCASPX2, from the sea cucumber Apostichopus japonicus, an important aquaculture species. AjCASPX1/2 share similar domain organizations with the vertebrate initiator caspases CASP2/9, including the CARD domain and the p20/p10 subunits with conserved functional motifs. However, compared with human CASP2/9, AjCASPX1/2 possess unique structural features in the linker region between p20 and p10. AjCASPX1, but not AjCASPX2, induced marked apoptosis of human cells by activating CASP3/7. The recombinant proteins of AjCASPX2 and the CARD domain of AjCASPX2 were able to bind to a wide range of bacteria, as well as bacterial cell wall components, and inhibit bacterial growth. AjCASPX1, when expressed in Escherichia coli, was able to kill the host bacteria. Under normal conditions, AjCASPX1 and AjCASPX2 expressions were most abundant in sea cucumber muscle and coelomocytes, respectively. After bacterial infection, both AjCASPX1 and AjCASPX2 expressions were significantly upregulated in sea cucumber tissues and cells. Together, these results indicated that AjCASPX1 and AjCASPX2 were initiator caspases with antimicrobial activity and likely functioned in apoptosis and immune defense against pathogen infection. [ABSTRACT FROM AUTHOR]

This article presents the first report of a circularly polarized (CP) omnidirectional radiation antenna for wireless capsule endoscope (WCE) system applications. The proposed antenna incorporates an integrated design concept, and achieves operation at 0.915 GHz Industrial, Scientific, and Medical (ISM) band (0.902–0.928 GHz) with a compact size of π × 5.52 × 22 mm3. The simulation is performed in Ansys HFSS, with the antenna being placed in the center of a cylindrical homogeneous muscle tissue with a size of π × 552 × 80 mm3. The simulated results show that the capsule antenna has an impedance bandwidth (BW) (|S11| < −10 dB) from 0.82 to 0.99 GHz and a CP BW (AR < 3 dB) from 0.84 to 1.09 GHz. Moreover, the omnidirectional CP radiation properties remain stable for a very wide θ range (49°–144°) in the elevation plane. The robust CP performance and the integrated design concept make the proposed antenna suitable for advanced WCE systems. [ABSTRACT FROM AUTHOR]

Human activities expansion globally has exerted tremendous pressure on natural habitats and threatens the conservation of global biodiversity. Studying the impact of human activities expansion on natural habitats globally and in various biomes can provide scientific reference for differentiated approaches to global habitat restoration. However, previous studies still lack identification of the impact of global human activities expansion on natural habitats, especially in different biomes. Here we used the InVEST model to assess the changes in habitat quality globally and across biomes over the past 20 years and analyzed the impact of human activities expansion on them using Spearman correlation coefficients. The results showed an overall global degradation of natural habitats of 0.537% during 2000–2020, while human activities increased by 10.990%. Mangroves were the biomes with the most severe habitat degradation, while deserts and xeric shrublands were the biomes with the most significant habitat restoration. At the global scale, human activities had caused significant and growing negative impact on natural habitats, while in terms of different biomes, human activities may bring about habitat restoration. The findings of this study recommend the implementation of differentiated human activities regulation measures in different biomes to promote global habitat restoration. • Analyzed the degradation of natural habitats globally and in different biomes. • Habitat restoration tends to occur in areas of poor habitat such as deserts and tundra. • Human activities expansion has shown negative impacts on natural habitats globally. • Human activities can also contribute to habitat restoration in some biomes. [ABSTRACT FROM AUTHOR]

Convection resonance could be significant for strengthening heat and mass transfer rates in enclosure flows, such as electronic cooling, built air environment and green energy harvest. This paper presented a numerical investigation on the coupled heat and moisture transport and resonance phenomena in enclosures packed with discrete porous media, where natural convection dominated, mixing convection, and forced convection dominated domains could be covered. Various physical parameters were extensively investigated, including buoyancy ratio (−10 ≤ Br ≤ 10), permeability (10−6 ≤ Da ≤ 101), Richardson number (10−1 ≤ Ri ≤ 5), Reynolds number (50 ≤ Re ≤ 1000), enclosure tilting angle (0° ≤ Φ ≤ 180°), thermal conductivity (0.1 ≤ Kr ≤ 10), and frequency (10−2 ≤ ω ≤ 5). Present results showed that in a vertical enclosure, reduction of porous medium permeability and promotion of the ratio of Richardson number to floating force could enhance heat and mass transfer rates. In an inclined enclosure, the effect of buoyancy and inclination angle on heat and mass transfer processes and rates exhibits a centrally symmetric distribution. In addition, a dense porous media and cooperative heat and mass buoyancy force ratio were beneficial to reducing the total entropy production. Finally, the transient heat and moisture transport and resonance phenomena in discrete distributed porous media were investigated. The system exhibits significant self-excited oscillations at ω = 100, being evident whatever sparse or dense porous media. Heat and mass transfer pulse amplitude in a periodically varying heat source enclosure decays with increasing porous medium thermal conductivity ratio, whereas it increases with increasing buoyancy ratio and Reynolds numbers. The most significant heat and moisture resonance occurs in a mixed convection system with Da = 10 and Br = 4. Present oscillation and resonance researches could contribute to the development of electronic cooling or built ventilation with much low or free cost of thermal management. • Heat and moisture transports inside in an inclined porous enclosure were modelled. • Transient, oscillatory, and resonant states were observed for mixed convections. • Reduction of porous permeability and promotion of Ri and Br enhanced transport rates. • Dense porous media and cooperative Br aided entropy production in inclined enclosure. • Self-excited oscillation and resonance were fully analyzed by various parameters. [ABSTRACT FROM AUTHOR]

[Display omitted] • A heterogeneous catalyst was prepared by wrapping P[BVIM]CoCl 3 around the surface of Fe 3 O 4 @SiO 2. • Coupling of the catalyst with PMS as an oxidant for desulfurization. • A sulfur removal rate of over 98% at room temperature was obtained under optimal experimental conditions. • Identification of a two-step oxidation mechanism of DBT in a tandem reaction. • Obtaining some useful kinetic data for the two oxidation steps, including activation energies and reaction rates. A heterogeneous catalyst was prepared by wrapping a poly 3-butyl vinylimidazole cobalt chloride ionic liquid (P[BVIM]CoCl 3) around the surface of Fe 3 O 4 @SiO 2 magnetic nanoballs. This catalyst was coupled with the oxidant peroxymonosulfate (PMS) for extraction catalytic oxidation desulfurization (ECODS). The prepared desulfurization catalyst had superparamagnetic properties, with a saturation magnetization of 32.5 emu/g. Moreover, this caalyst was multi-porous material, ans it had a specific surface area and pore volume of 8.14 m2/g and 0.018 cc/g, respectively. The average pore diameter of catalyst was 3.9 nm. The optimal experimental conditions were as follows: the initial sulfur content of the oil was 500 ppm, the catalyst dosage was 30 mg, PMS (20 wt%) dosage was 0.6 g, the ACN dosage was 2 g, and the oil sample size was 6 g. After 20 min, a sulfur removal rate of over 98 % was achieved at 20 °C. Furthermore, the unpurified catalyst still maintained high desulfurization activity after being used for 5 times, demonstrating good stability. The desulfurization mechanism was divided into two steps: first, DBT was oxidized to DBTO by SO 4 − free radicals, and second, the DBTO was further oxidized to DBTO 2 by OH free radicals in a tandem reaction. The reaction rates for the two steps at 20 °C were 0.0144 sec−1 and 0.00115 sec−1, respectively. The activation energies associated with these steps were 65.65 kJ/mol and 105.22 kJ/mol, respectively. The quencher t-butanol had no effect on the first step but significantly inhibited the second step, meaning that DBTO became the main oxidation product. One potential application of this study is the utilization of t-butanol to regulate the oxygen content in organic sulfide oxidation products. [ABSTRACT FROM AUTHOR]

The Whitham-Broer-Kaup model is widely used to study the tsunami waves. The classical Whitham-Broer-Kaup equations are re-investigated in detail by the generalized projective Riccati-equation method. 20 sets of solutions are obtained of which, to the best of the authors' knowledge, some have not been reported in literature. Bifurcation analysis of the planar dynamical systems is then used to show different phase portraits of the traveling wave solutions under various parametric conditions. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is the fourth most lethal malignancy and is the second most common cause of cancer-associated mortality worldwide. The development of high-throughput sequencing has enabled the identification of potential biomarkers for the diagnosis and treatment of various types of cancer. Although microRNA-101 (miR-101) has been demonstrated to be a potential biomarker of CRC, its detailed mechanisms remain to be fully discovered. In the present study, overall survival analysis was applied to determine the association between miR-101 and CRC prognosis. Reverse transcription-quantitative PCR (RT-qPCR) was used to examine gene expression levels in tissues and cells. Cell proliferative and apoptotic activities were determined by MTT and flow cytometry assays, respectively. Wound healing and Transwell assays were used to examine CRC cell migration and invasion, respectively. In the present study, RT-qPCR analysis indicated that miR-101 was significantly downregulated in CRC tissues and cells. However, clinical data collected from The Cancer Genome Atlas revealed no significant association between the expression levels of miR-101 and the prognosis of CRC. Additionally, miR-101 inhibited the progression of CRC by directly binding to the 3′-untranslated region of Ras-related protein Rap1b (Rap1b). This was associated with downregulation of Rap1b expression. Furthermore, the overexpression of Rap1b promoted miR-101 mimic-attenuated CRC cell progression. The present study demonstrated that miR-101 may be involved in the repression of the CRC progression by forming a negative feedback loop with Rap1b. The findings revealed the interaction between miR-101 and Rap1b during the progression of CRC, which could aid the development of therapeutic strategies. [ABSTRACT FROM AUTHOR]

The one-dimensional nonlinear dynamical wave interactions in a system of quasineutral two-fluid plasma in a constant magnetic field are investigated. The existence of the travelling wave solutions is discussed. The modulation stability of linear waves and the modulation instability of weakly nonlinear waves are presented. Both suggest that the Korteweg-de Vries (KdV) system is modulationally stable. Besides, the wave interactions including the periodic wave interaction and the solitary wave interaction are captured and presented. It is shown that these interacting waves alternately exchange their energy during propagation. The Fourier spectrum analysis is used to depict the energy transformation between the primary and harmonic waves. It is known that the wave interactions in magnetized plasma play an important role in various processes of heating and energy transportation in space and astrophysical plasma. However, few researchers have considered such magnetohydrodynamic (MHD) wave interactions in plasma. It is expected that this work can provide additional insight into understanding of behaviors of MHD wave interactions. [ABSTRACT FROM AUTHOR]

Background. To evaluate Perioperative Surgical Home (PSH) practice model implementation in Crohn's disease (CD) patients undergoing disease-related surgery. Methods. A retrospective analysis of CD patients requiring disease-related surgery in the Shanghai Ninth People's Hospital was undertaken. Subjects were divided into a non-PSH group consisting of 49 patients (June 2016 to November 2017) and a PSH group consisting of 72 patients (December 2017 until May 2019). Conventional treatment was used for the non-PSH group, while in the PSH group, a standardized pre- and postoperative management routine was employed. The postoperative lengths of stay and incidences of postoperative complications were analyzed. Results. There were no significant differences in demographics, reasons for surgery, preoperative BMIs, and preoperative hemoglobin between the two groups (P > 0.05). The overall incidence of complications in the PSH group was dramatically lower than that in the non-PSH group (26.4% vs. 44.9%, P = 0.035). In the PSH group, postoperative length of stay was significantly shorter than that in the non-PSH group (11.5 ± 5.7 vs. 9.0 ± 6.8 , P < 0.001). Conclusions. The PSH conditioning routine in CD patients undergoing disease-related surgeries suggests a trend of fewer postoperative complications and shorter lengths of hospital stay. The PSH model may have clinical advantages when applied to CD patients. [ABSTRACT FROM AUTHOR]

Background. To evaluate Perioperative Surgical Home (PSH) practice model implementation in Crohn's disease (CD) patients undergoing disease-related surgery. Methods. A retrospective analysis of CD patients requiring disease-related surgery in the Shanghai Ninth People's Hospital was undertaken. Subjects were divided into a non-PSH group consisting of 49 patients (June 2016 to November 2017) and a PSH group consisting of 72 patients (December 2017 until May 2019). Conventional treatment was used for the non-PSH group, while in the PSH group, a standardized pre- and postoperative management routine was employed. The postoperative lengths of stay and incidences of postoperative complications were analyzed. Results. There were no significant differences in demographics, reasons for surgery, preoperative BMIs, and preoperative hemoglobin between the two groups (P > 0.05). The overall incidence of complications in the PSH group was dramatically lower than that in the non-PSH group (26.4% vs. 44.9%, P = 0.035). In the PSH group, postoperative length of stay was significantly shorter than that in the non-PSH group (11.5 ± 5.7 vs. 9.0 ± 6.8 , P < 0.001). Conclusions. The PSH conditioning routine in CD patients undergoing disease-related surgeries suggests a trend of fewer postoperative complications and shorter lengths of hospital stay. The PSH model may have clinical advantages when applied to CD patients. [ABSTRACT FROM AUTHOR]

The purpose of present work is to explore the features of homogeneous–heterogeneous reactions in peristalsis flow of Carreau magneto hybrid nanofluid with copper and silver nanoparticles in a symmetric channel. The velocity slip condition and thermal radiation effect is also taken in the simplified model. Thermodynamic optimization aspect is discussed through the entropy generation analysis. The proposed mathematical systems are modified by using a lubrication approach and solved by a homotopy-based package-BVPh 2.0. The impacts of different involved parameters on flow characteristics, thermal characteristics, chemically reactive concentration and entropy generation are scrutinized through analytic results. It reveals that the fluid velocity decreases with the increasing values of the Weissenberg and the Hartman numbers. Characteristics of the Brinkman and the thermal radiation numbers are quite reverse for the heat transfer rate. In addition, entropy generation decreases with thermal radiation and Weissenberg number. The main outcome signifies that hybrid nanofluid is better thermal conductor as compared to the conventional nanofluid. [ABSTRACT FROM AUTHOR]

In previous studies, the nonlinear problem of electrohydrodynamic (EHD) ion drag flows in a circular cylindrical conduit has been studied by several authors. However, those studies seldom involve the computation for large physical parameters such as the electrical Hartmann number and the magnitude parameter for the strength of the nonlinearity due to the existence of strong nonlinearity in these extreme cases. To overcome this faultiness, the newly-developed homotopy Coiflets wavelet method is extended to solve this EHD flow problem with strong nonlinearity. The validity and reliability of the proposed technique are verified. Particularly, the highly accurate homotopy-wavelet solution is obtained for extreme large parameters, which seems to be overlooked before. Discussion about the effects of related physical parameters on the axial velocity field is presented. [ABSTRACT FROM AUTHOR]

A forced convection flow driven in a microchannel by an applied pressure gradient that fluctuates with small amplitude harmonically in time in the presence of electrical double layer effects is investigated. An analytical expression for the electrostatic potential is obtained via Poisson's equation. Based on this solution, we further obtain analytical solutions for velocity and temperature for both the cases Pr ≠ 1 and Pr = 1. Results show that they match each other as Pr → 1− and Pr → 1+. The explicit expression of the transient Nusselt number is derived. We notice that the Debye–Hückel parameter γ and the angular velocity Ω are key factors for flow behaviours. Our proposed study adds some new insights by including the time-dependent pressure term that is usually overlooked in previous works. It is expected that this work could help to understand the transportal mechanisms of forced convection flow in microfluidic equipment and instruments. [ABSTRACT FROM AUTHOR]

The homogeneous-heterogeneous reaction in the boundary layer flow of a water-based nanofluid in the stagnation-point region of a plane surface is investigated. The type of small particles explored here is the single-walled carbon nanotubes. The homogeneous nanofluid model is employed for description of behaviours of nanofluids. Here, the homogeneous (bulk) reaction is isothermal cubic autocatalytic, while the heterogeneous (surface) reaction is single, isothermal, and first order. The steady state of this system is analysed in detail, with equal diffusion coefficients being considered for both reactants and autocatalysts. Multiple solutions of the reduced system are captured for some particular sets of physical parameters, which seem to be overlooked in all previous published works with regard to studies of homogeneous-heterogeneous reactions modeled by homogeneous nanofluid models. Besides, we discover the significant limitation of previous conclusion about that the solutions by homogeneous nanofluid flow models can be recovered from those by regular fluids. [ABSTRACT FROM AUTHOR]

The homogeneous and heterogeneous reactions in the boundary-layer of a flat surface are considered. The autocatalysts are assumed to be of regular sizes, while the solution is a dilute nanofluid. The heat release due to the chemical reactions is taken into account. The Buongiorno's model is used to describe the behaviors of this reaction system. This configuration makes the current model be different from all previous publications. Multiple solutions are given numerically to the rescaled nonlinear system, whose stability is verified. The results show that the strength coefficients of the homogeneous and heterogeneous reactions are key factors to cause the appearance of the multiple solutions in the distribution of the chemical reactions. Nanofluids enhance the diffusion of heat and help maintain the stability of chemical reactions. [ABSTRACT FROM AUTHOR]