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In this paper, we propose a gate recurrent unit (GRU) method to forecast ionospheric the total electron content (TEC) at different latitudes and longitudes. This method aims to address the issues of low accuracy in traditional neural networks and the challenges faced in training long-term time series. We construct a GRU model using TEC data from the European Orbit Determination Center (CODE) for the years 2016 to 2018, geomagnetic indices, and solar activity indices (16 points along the latitude and longitude lines of 120°E and 30°N). Comparative experiments are carried out with the international reference ionosphere (IRI) model and the long short-term memory (LSTM) model. The results show that the GRU model outperforms other models in terms of accuracy. On geomagnetic quiet days, the 5-day predicted average residual can reach 0.51 TECU, while on storm days it can reach 0.72 TECU. The root mean square error (RMSE) for these days is 0.64 TECU and 1.01 TECU, respectively. The correlation coefficients are 0.98 and 0.93, respectively. The RMSE of the GRU model ranges from 0.60 TECU to 2.62 TECU for both geomagnetic quiet days and storm days. In terms of TEC forecast accuracy in 2018, the RMSE of the GRU model is 1.6 TECU, which is smaller than that of the IRI model and LSTM model. These results demonstrate that the GRU model performs better than the IRI model and LSTM model. [ABSTRACT FROM AUTHOR]

The total electron content (TEC) of the ionosphere is an important parameter to describe the ionosphere, and it is a great significance to monitor and predict it accurately. In this paper, a hybrid ionospheric TEC prediction model based on the least squares support vector machine (LSSVM) and the Moth-Flame Optimization (MFO) algorithm is proposed. The parameters of the LSSVM model are optimized by the MFO algorithm. We use observation data of 15 GNSS stations from the Crustal Movement Observation Network of China (CMONOC) to extract ionospheric TEC from 2012 to 2019. The ionospheric TEC is forecasted using solar and geomagnetic activity indices in both the low solar activity year (2019) and the high solar activity year (2015). The results show that the prediction performance of the MFO_LSSVM model is significantly better than that of the IRI model, SVM model, and LSSVM model. Compared with the other three models, there are more stable prediction results in the low and high solar activity years. At the same time, the predicted value of the MFO_LSSVM model has a good correlation with the measured value, and it also has good prediction potential in areas with active geomagnetic activity. The comparison with the Long Short-Term Memory (LSTM) model shows that the MFO_LSSVM model has better performance than the single LSTM model. In conclusion, the MFO_LSSVM model can accurately predict ionospheric TEC in China, and has better accuracy than traditional long-term and short-term models. [ABSTRACT FROM AUTHOR]

Summary The N6‐methyladenosine (m6A) mRNA modification is crucial for plant development and stress responses. In rice, the male sterility resulting from the deficiency of OsFIP37, a core component of m6A methyltransferase complex, emphasizes the significant role of m6A in male fertility. m6A is reversible and can be removed by m6A demethylases. However, whether mRNA m6A demethylase regulates male fertility in rice has remained unknown. Here, we identify the mRNA m6A demethylase OsALKBH9 and demonstrate its involvement in male fertility regulation. Knockout of OsALKBH9 causes male sterility, dependent on its m6A demethylation activity. Cytological analysis reveals defective tapetal programmed cell death (PCD) and excessive accumulation of microspores exine in Osalkbh9‐1. Transcriptome analysis of anthers shows up‐regulation of genes involved in tapetum development, sporopollenin synthesis, and transport pathways in Osalkbh9‐1. Additionally, we demonstrate that OsALKBH9 demethylates the m6A modification in TDR and GAMYB transcripts, which affects the stability of these mRNAs and ultimately leads to excessive accumulation of pollen exine. Our findings highlight the precise control of mRNA m6A modification and reveal the pivotal roles played by OsALKBH9‐mediated m6A demethylation in tapetal PCD and pollen exine accumulation in rice. [ABSTRACT FROM AUTHOR]

For this study, we employed intense 400 nm, 100 fs pulses linearly propagated through a 50 cm water medium, initially self-stretching the excitation pulses to 2.50 ps. Subsequently, the self-stretched 2.50 ps pulses were focused into deionized water, and we conducted transient absorption experiments to measure and investigate the dynamics of hydrated electrons in water. The excess electrons generated were injected into the hydrogen bond network of the water cluster, leading to the observation of saturated hydrated electrons. Additionally, we observed the emergence of the forward stimulated Raman scattering (SRS) of water molecules. We report the experimental observation of a weak forward SRS emission at 463 nm (corresponding to 3400 cm−1), indicative of the ordinary OH stretching vibration in the liquid phase. Moreover, we observed an intense forward SRS emission at 460 nm in water, corresponding to two anomalous Raman shifts at 3260 cm−1 and 3355 cm−1. These anomalous Raman shifts resulted from changes in the hydrogen bond network structure. We determine that the formation of not fully hydrated and saturated hydrated electrons plays a crucial role in producing this phenomenon. [ABSTRACT FROM AUTHOR]

Hafnia‐based ceramic coating is considered one of the candidates to substitute yttria partially stabilized zirconia material as thermal barrier coating working above 1200°C. In this work, a series of TiO2‐doped HfO2 ceramics (Hf1–xTixO2, x = 0%, 5%, 10%, 15%, 20%, and 40%) were fabricated by solid‐state reaction. The microstructure, fracture toughness, and thermal conductivity were systematically investigated. The results show that Hf1–xTixO2 ceramics are comprised of monoclinic HfO2 and orthorhombic HfTiO4 phases when Ti4+ doping amount is between 5% and 20%, and the weight fraction of HfTiO4 phase linearly increases with the Ti4+ content and finally reaches 100% for Hf0.6Ti0.4O2. The fracture toughness of TiO2‐doped HfO2 ceramic is higher than 1.75 MPa m.5 when TiO2 content is no more than 15% and decreases below 1.5 MPa m0.5 if TiO2 content further increases. The thermal conductivity is significantly decreased by TiO2 doping attributed to the precipitated HfTiO4 phase. Considering the mechanical properties and thermal insulation capacity, the doping of 15% TiO2 would be beneficial for the HfO2‐based ceramics. [ABSTRACT FROM AUTHOR]

In recent years, the application of deep learning models for underwater target recognition has become a popular trend. Most of these are pure 1D models used for processing time-domain signals or pure 2D models used for processing time-frequency spectra. In this paper, a recent temporal 2D modeling method is introduced into the construction of ship radiation noise classification models, combining 1D and 2D. This method is based on the periodic characteristics of time-domain signals, shaping them into 2D signals and discovering long-term correlations between sampling points through 2D convolution to compensate for the limitations of 1D convolution. Integrating this method with the current state-of-the-art model structure and using samples from the Deepship database for network training and testing, it was found that this method could further improve the accuracy (0.9%) and reduce the parameter count (30%), providing a new option for model construction and optimization. Meanwhile, the effectiveness of training models using time-domain signals or time-frequency representations has been compared, finding that the model based on time-domain signals is more sensitive and has a smaller storage footprint (reduced to 30%), whereas the model based on time-frequency representation can achieve higher accuracy (1–2%). [ABSTRACT FROM AUTHOR]

Bipedal robots have long been a focal point of robotics research with an unwavering emphasis on platform stability. Achieving stability necessitates meticulous design considerations at every stage, encompassing resilience against environmental disturbances and the inevitable wear associated with various tasks. In pursuit of these objectives, here, the bipedal L04 Robot is introduced. The L04 Robot employs a groundbreaking approach by compactly enclosing the hip joints in all directions and employing a coupled joint design. This innovative approach allows the robot to attain the traditional 6 degrees of freedom in the hip joint while using only four motors. This design not only enhances energy efficiency and battery life but also safeguards all vulnerable motor reducers. Moreover, the double-slider leg design enables the robot to simulate knee bending and leg height adjustment through leg extension. This simulation can be mathematically modeled as a linear inverted pendulum (LIP), rendering the L04 Robot a versatile platform for research into bipedal robot motion control. A dynamic analysis of the bipedal robot based on this structural innovation is conducted accordingly. The design of motion control laws for forward, backward, and lateral movements are also presented. Both simulation and physical experiments corroborate the excellent bipedal walking performance, affirming the stability and superior walking capabilities of the L04 Robot. [ABSTRACT FROM AUTHOR]

In this paper, a biped robot system for dynamic walking is presented. It has two 2-degree-of-freedom (DOF) lightweight legs and a 6-DOF hip. All the joint pulleys of the legs are driven by motors that are placed at the hip using steel cables. Since all the heavy motors are mounted at the hip, the biped robot has remarkably low-mass legs beyond the hip, which guarantees low inertia during walking at high speeds. Utilizing cable-amplification mechanisms, high stiffness and strength are achieved, resulting in better control performance compared to conventional direct-driven methods. Techniques are developed to estimate joint-angle errors caused by the elastic deformation of the cables. To achieve smooth control, we introduce the concept of a virtual leg, which is an imaginary leg connecting the hip joint and the ankle joint. A robust control approach based on the "virtual leg" is presented, which considers the variances of the virtual leg length during walking. Experiments are conducted to validate the effectiveness of the mechanical design and the proposed control approach. [ABSTRACT FROM AUTHOR]

The Harris Hawks Optimization algorithm (HHO) is a sophisticated metaheuristic technique that draws inspiration from the hunting process of Harris hawks, which has gained attention in recent years. However, despite its promising features, the algorithm exhibits certain limitations, including the tendency to converge to local optima and a relatively slow convergence speed. In this paper, we propose the multi-strategy improved HHO algorithm (MSI-HHO) as an enhancement to the standard HHO algorithm, which adopts three strategies to improve its performance, namely, inverted S-shaped escape energy, a stochastic learning mechanism based on Gaussian mutation, and refracted opposition-based learning. At the same time, we conduct a comprehensive comparison between our proposed MSI-HHO algorithm with the standard HHO algorithm and five other well-known metaheuristic optimization algorithms. Extensive simulation experiments are conducted on both the 23 classical benchmark functions and the IEEE CEC 2020 benchmark functions. Then, the results of the non-parametric tests indicate that the MSI-HHO algorithm outperforms six other comparative algorithms at a significance level of 0.05 or greater. Additionally, the visualization analysis demonstrates the superior convergence speed and accuracy of the MSI-HHO algorithm, providing evidence of its robust performance. [ABSTRACT FROM AUTHOR]

Background: Disulfidptosis is a type of programmed cell death caused by excessive cysteine-induced disulfide bond denaturation leading to actin collapse. Liver cancer has a poor prognosis and requires more effective intervention strategies. Currently, the prognostic and therapeutic value of disulfidptosis in liver cancer is not clear. Methods: We investigated the features of 16 disulfidptosis-related genes (DRGs) of HCC patients in the TCGA and classified the patients into two disulfidptosis pattern clusters by consensus clustering analysis. Then, we constructed a prognostic model using LASSO Cox regression. Next, the microenvironment and drug sensitivity were evaluated. Finally, we used qPCR and functional analysis to verify the reliability of hub DRGs. Results: Most of the DRGs showed significantly higher expression in cancer tissues than in adjacent tissues. Our prognostic model, the DRG score, can well predict the survival of HCC patients. There were significant differences in survival, features of the microenvironment, effects of immunotherapy, and drug sensitivity between the high- and low-DRG score groups. Ultimately, we demonstrated that a few hub DRGs have differential mRNA expression between liver cancer cells and normal cells and that the protective gene LCAT can inhibit liver cancer metastasis in vitro. Conclusion: We established a novel risk model based on DRG scores to predict HCC patient prognosis, drug sensitivity and immunotherapy efficacy, which provides new insight into the relationship between disulfidptosis and HCC and provides valuable assistance for the personalized treatment of HCC. [ABSTRACT FROM AUTHOR]

Background: Mechanical ventilation (MV) is essential in the management of critically ill neonates, especially preterm infants. However, inappropriate or prolonged use of invasive MV may result in ventilator-associated lung injury. A systemic review comparing pressure control ventilation (PCV) with volume-targeted ventilation mode (VTV) approved that VTV reduces the incidence of death or bronchopulmonary dysplasia (BPD) in neonates; however, this study did not analyze subgroups of very low birthweight (VLBW) infants. Therefore, the aim of this study was to compare the use of VTV and PCV in VLBW infants and to provide clinical evidence for reducing mortality and complications of MV in VLBW infants. Method: A single-center randomized controlled trial will be performed. All eligible infants will be randomized and assigned to either VTV or PCV group with 1:1 ratio using sealed envelopes. Death or BPD at 36 weeks' postmenstrual age will be used as the primary outcome. Secondary outcomes include BPD, death, length of invasive MV, noninvasive mechanical ventilation, and oxygen use, length of hospital stay, failure of conventional MV, rate of using high-frequency oscillatory ventilation (HFOV) as rescue therapy, rate of reintubation within 48 h, and hospital expenses. Discussion: Systemic review suggested that VTV decreases the incidence of death or BPD in neonates compared to PLV; however, this study did not specifically analyze subgroups of VLBW infants. We designed this single-center randomized controlled trials (RCT) to add a significant contribution regarding the benefits of VTV for VLBW patients. [ABSTRACT FROM AUTHOR]

This paper presents the development, modeling, and control of L03, an underactuated 3D bipedal robot with symmetrical hips and straight legs. This innovative design requires only five actuators, two for the legs and three for the hips. This paper is divided into three parts: (1) mechanism design and kinematic analysis; (2) trajectory planning for the center of mass and foot landing points based on the Divergent Component of Motion (DCM), enabling lateral and forward walking capabilities for the robot; and (3) gait stability analysis through prototype experiments. The primary focus of this study is to explore the application of underactuated symmetrical designs and determine the number of motors required to achieve omnidirectional movement of a bipedal robot. Our simulation and experimental results demonstrate that L03 achieves simple walking with a stable and consistent gait. Due to its lightweight construction, low leg inertia, and straight-legged design, L03 can achieve ground perception and gentle ground contact without the need for force sensors. Compared to existing bipedal robots, L03 closely adheres to the characteristics of the linear inverted pendulum model, making it an invaluable platform for future algorithm research. [ABSTRACT FROM AUTHOR]

A robust ionospheric model is indispensable for providing the atmospheric delay corrections for global navigation satellite system (GNSS) navigation and positioning and forecasting the space environment. The accuracy of ionospheric models is limited due to the simplified model structures. Complicated spatiotemporal variations in total electron content (TEC) biases between GNSS and international reference ionosphere (IRI) suggest a robust strategy to optimally combine GNSS and IRI TEC for high-precision modeling. In this paper, we propose a novel ionospheric data assimilation method, which is a local ensemble transform Kalman filter (LETKF), to construct an ionospheric model over Yunnan in southwestern China. We used the LETKF method to assimilate the ionospheric TEC extracted from GNSS observations in Yunnan into the IRI-2016 model. The experimental results indicate that the ionospheric data assimilation has a more pronounced improvement effect on the IRI empirical model during periods of geomagnetic quiet than during periods of geomagnetic disturbance. On quiet magnetic days, the skill score (SKS) of the assimilation is 0.60 and the root mean square error (RMSE) values before and after assimilation are 5.08 TECU and 2.02 TECU, respectively. The correlation coefficient after assimilation increases from 0.94 to 0.99. On magnetic storm days, the SKS of the assimilation is 0.42 and the RMSE values before and after assimilation are 5.99 TECU and 3.46 TECU, respectively. The correlation coefficient after assimilation increases from 0.98 to 0.99. The results suggest that the LETKF algorithm can be considered an effective method for ionospheric data assimilation. [ABSTRACT FROM AUTHOR]

In this paper, we forecasted the ionospheric total electron content (TEC) over the region of China using the bidirectional convolutional gated recurrent unit (BiConvGRU) model. We first generated the China Regional Ionospheric Maps (CRIMs) using GNSS observations provide by the Crustal Movement Observation Network of China (CMONOC). We then used gridded TEC maps from 2015 to 2018 with a 1 h interval from the CRIMs as the dataset, including quiet periods and storm periods of ionospheric TEC. The BiConvGRU model was then utilized to forecast the ionospheric TEC across China for the year 2018. The forecasted TEC was compared with the TEC from the International Reference Ionosphere (IRI-2016), Convolutional Long Short-Term Memory (ConvLSTM), Convolutional Gated Recurrent Unit (ConvGRU), Bidirectional Convolutional Long Short-Term Memory (BiConvLSTM), and the 1-day Predicted Global Ionospheric Map (C1PG) provided by the Center for Orbit Determination in Europe (CODE). In addition, indices including Kp, ap, Dst and F10.7 were added to the training dataset to improve the forecasting accuracy of the model (-A indicates no indices, while -B indicates with indices). The results verified that the prediction accuracies of the models integrated with these indices were significantly improved, especially during geomagnetic storms. The BiConvGRU-B model presented a decrease of 41.5%, 22.3%, and 13.2% in the root mean square error (RMSE) compared to the IRI-2016, ConvGRU, and BiConvLSTM-B models during geomagnetic storm days. Furthermore, at a specific grid point, the BiConvGRU-B model showed a decrease of 42.6%, 49.1%, and 31.9% in RMSE during geomagnetic quiet days and 30.6%, 34.1%, and 15.1% during geomagnetic storm days compared to the IRI-2016, C1PG, and BiConvLSTM-B models, respectively. In the cumulative percentage analysis, the BiConvGRU-B model had a significantly higher percentage of mean absolute error (MAE) within the range of 0–1 TECU in all seasons compared to the BiConvLSTM-B model. Meanwhile, the BiConvGRU-B model outperformed the BiConvLSTM-B model with lower RMSE for each month of 2018. [ABSTRACT FROM AUTHOR]

This study proposes a remaining useful life (RUL) prediction method using limited degradation data with an unknown degradation model for hydraulic pumps with long service lives and no failure data in turbine control systems. The volumetric efficiency is calculated based on real-time monitoring signal data, and it is used as the degradation indicator. The optimal degradation curve is established using the degradation trajectory model, and the optimal probability distribution model is selected via the K-S test. The above process was repeated to optimize the degradation model and update parameters in different performance degradation stages of the hydraulic pump, providing quantification of the prediction uncertainty and enabling accurate online prediction of the hydraulic pump's RUL. Finally, an RUL test bench for hydraulic pumps is built for verification. The results show that the proposed method is convenient, efficient, and has low model complexity. The method enables online accurate prediction of the RUL of hydraulic pumps using only limited degradation data, with a prediction accuracy of over 85%, which meets practical application requirements. [ABSTRACT FROM AUTHOR]

Goose is an important poultry commonly raised for meat. The early growth performance of geese significantly influences their market weight and slaughter weight, affecting the poultry industry's economic benefits. To identify the growth surge between the Shitou goose and the Wuzong goose, we collected the early growth body traits from 0 to 12 weeks. In addition, we investigated the transcriptomic changes in leg muscles at the high growth speed period to reveal the difference between the two geese breeds. We also estimated the growth curve parameters under three models, including the logistic, von Bertalanffy, and Gompertz models. The results showed that except for body length and keel length, the best-fitting model between the body weight and body size of the Shitou and Wuzong was the logistic model. The growth turning points of Shitou and Wuzong were 5.954 and 4.944 weeks, respectively, and the turning point of their body weight was 1459.01 g and 478.54 g, respectively. Growth surge occurred at 2–9 weeks in Shitou goose and at 1–7 weeks in Wuzong goose. The body size traits of the Shitou goose and Wuzong goose showed a trend of rapid growth in the early stage and slow growth in the later stage, and the Shitou goose growth was higher than the Wuzong goose. For transcriptome sequencing, a total of 87 differentially expressed genes (DEGs) were identified with a fold change ≥ 2 and a false discovery rate < 0.05. Many DEGs have a potential function for growth, such as CXCL12, SSTR4, FABP5, SLC2A1, MYLK4, and EIF4E3. KEGG pathway analysis identified that some DEGs were significantly enriched in the calcium signaling pathway, which may promote muscle growth. The gene–gene interaction network of DEGs was mainly related to the transmission of cell signals and substances, hematological system development, and functions. This study can provide theoretical guidance for the production and breeding management of the Shitou goose and Wuzong goose and help reveal the genetic mechanisms underlying diverse body sizes between two goose breeds. [ABSTRACT FROM AUTHOR]

The use of artificial intelligence (AI) to detect phishing emails is primarily dependent on large-scale centralized datasets, which has opened it up to a myriad of privacy, trust, and legal issues. Moreover, organizations have been loath to share emails, given the risk of leaking commercially sensitive information. Consequently, it has been difficult to obtain sufficient emails to train a global AI model efficiently. Accordingly, privacy-preserving distributed and collaborative machine learning, particularly federated learning (FL), is a desideratum. As it is already prevalent in the healthcare sector, questions remain regarding the effectiveness and efficacy of FL-based phishing detection within the context of multi-organization collaborations. To the best of our knowledge, the work herein was the first to investigate the use of FL in phishing email detection. This study focused on building upon a deep neural network model, particularly recurrent convolutional neural network (RNN) and bidirectional encoder representations from transformers (BERT), for phishing email detection. We analyzed the FL-entangled learning performance in various settings, including (i) a balanced and asymmetrical data distribution among organizations and (ii) scalability. Our results corroborated the comparable performance statistics of FL in phishing email detection to centralized learning for balanced datasets and low organizational counts. Moreover, we observed a variation in performance when increasing the organizational counts. For a fixed total email dataset, the global RNN-based model had a 1.8% accuracy decrease when the organizational counts were increased from 2 to 10. In contrast, BERT accuracy increased by 0.6% when increasing organizational counts from 2 to 5. However, if we increased the overall email dataset by introducing new organizations in the FL framework, the organizational level performance improved by achieving a faster convergence speed. In addition, FL suffered in its overall global model performance due to highly unstable outputs if the email dataset distribution was highly asymmetric. [ABSTRACT FROM AUTHOR]

The epoxidation of styrene is an important route to synthesize organic intermediate, but how to effectively promote the formation of target superoxide radicals and then regulate the production of styrene oxide in two-phase reaction system remains an urgent challenge. In this study, MnO x nanocatalysts with abundant oxygen vacancies were fabricated using reverse-micelle as template, and then were endowed with an amphiphilic surface through post-modification. With such MnO x catalysts, Pickering emulsion could be formulated, in which numerous compartmentalized droplet microreactors were created for the epoxidation of styrene. The rich oxygen defects on MnO x were found to be useful to improve the chemisorption of t -butylhydroperoxide, and the active complexes formed by coordination of Mn3+ with N, N-dimethylformamide favored the generation of preferable superoxide radicals for the synthesis of styrene oxide. Moreover, it was also found that compartmentalization effects arising from Pickering emulsion droplets modifies the radicals reaction path, significantly improving the catalytic efficiency and selectivity. As a result, in the Pickering emulsion system, 90.0% selectivity towards styrene oxide and a turnover frequency of 581 h−1 could be obtained, which were higher than ever reported results. The Pickering emulsion-based compartmentalized microreactors can provide versatile platforms to efficiently control the epoxidation of styrene involving free radicals. [Display omitted] • MnO x with rich oxygen vacancies were fabricated by a reverse-micelle method. • Abundant oxygen vacancies was found to promote the chemisorption of TBHP. • The complexes of Mn3+/DMF favor the generation of HO 2 ∙ for epoxidation of styrene. • 90% SO yield was obtained by the compartmentalization effect of Pickering emulsions. [ABSTRACT FROM AUTHOR]

Fluorescence plays an important role in determining the color appearance of fluorescing minerals. This paper discusses the color mechanism in the red spinel and the color effects from the light source as well as the background on the spinel color. Excitation-Emission Matrices (EEMs) fluorescence spectroscopy was utilized to characterize the fluorescence of natural Cr-doped magnesia-alumina spinel from Myanmar. EMP, LA-ICP-MS, and optical spectroscopy were applied to study the spinel's chemical compositions and color mechanism. X-Rite Ci-7800 spectrophotometer, which is useful to measure colors for fluorescing minerals, was employed to acquire color data of spinel in daylight and incandescent light. The results indicated the higher value of Cr/Fe makes pinkish-red spinel has a much stronger red fluorescence effect than dark-red spinel. The two narrow absorption bands at ~ 25,500 cm−1 (with a broad absorption band at ~ 24,100 cm−1) and ~ 18,570 cm−1 in the optical absorption spectrum are assigned to spin-allowed electronic d-d transitions 4A2g → 4T1g(F) and 4A2g → 4T2g(F) in Cr3+ at the M site. The EEMs spectra of the pinkish-red spinels show twin emissions at 706 nm excited both by ~ 380 nm and ~ 535 nm radiations, which is the key to the bright neon red color in pinkish-red spinel. The colorimetry study suggests the strong red fluorescence produced by < 460 nm radiation contributes more than 10% lightness and chroma in pinkish-red spinel under daylight. The lightness and the chroma of the spinels grow with the decrease of the background grayscale. The differentiation of spinel colors in dark conditions is lower than that in a bright environment. [ABSTRACT FROM AUTHOR]

Eukaryotic genomes are prevalently transcribed into many types of RNAs that translate into proteins or execute gene regulatory functions. Many RNAs associate with chromatin directly or indirectly and are called chromatin-associated RNAs (caRNAs). To date, caRNAs have been found to be involved in gene and transcriptional regulation through multiple mechanisms and have important roles in different types of cancers. In this review, we first present different categories of caRNAs and the modes of interaction between caRNAs and chromatin. We then detail the mechanisms of chromatin-associated nascent RNAs, chromatin-associated noncoding RNAs and emerging m6A on caRNAs in transcription and gene regulation. Finally, we discuss the roles of caRNAs in cancer as well as epigenetic and epitranscriptomic mechanisms contributing to cancer, which could provide insights into the relationship between different caRNAs and cancer, as well as tumor treatment and intervention. [ABSTRACT FROM AUTHOR]

Background: It is important to determine the severity of inhalation injury in severely burned patients. The oxygenation index PaO2/FiO2(PF) ratio is a key clinical indicator of inhalation injury. Sequential organ failure assessment (SOFA) is developed to assess the acute incidence of critical illness in the population. We hope to provide an assessment of survival or prognostic factor for severely burned patients with inhalation injury based on the respiratory SOFA score. Methods: This is a retrospective cohort study of all admissions to Department of Burn and Plastic Surgery at West China Hospital of Sichuan University from July 2010 to March 2021. Data was analyzed using Cox regression models to determine significant predictors of mortality. Survival analysis with time to death event was performed using the Kaplan–Meier survival curve with the log-rank test. All potential risk factors were considered independent variables, while survival was considered the risk dependent variable. Results: One hundred eighteen severe burn patients with inhalation injury who met the inclusion and exclusion criteria were admitted, including men accounted for 76.3%. The mean age and length of stay were 45.9 (14.8) years and 44.3 (38.4) days. Flame burns are the main etiology of burn (74.6%). Patients with the respiratory SOFA score greater than 2 have undergone mechanical ventilation. Univariate Kaplan–Meier analysis identified age, total body surface area burned (TBSA), ICU admission and the respiratory SOFA score as significant factors on survival. Cox regression analysis showed that TBSA and the respiratory SOFA score were associated with patient survival (p < 0.001). In some patients with severe burns and inhalation damage, the survival probability drops to less than 10% (TBSA greater than 80%: 8.9% and respiratory SOFA score greater than 2: 5.6%). This study statistically found that the TBSA with the respiratory SOFA score model (AUROC: 0.955) and the rBaux score (AUROC: 0.927) had similar predictive value (p = 0.175). Conclusion: The study indicates that a high respiratory system SOFA score was identified as a strong and independent predictor of severely burned patients with inhalation injury during hospitalization. When combined with TBSA, the respiratory SOFA scores can dynamically assess the severity of the patient's lung injury and improve the predictive level. [ABSTRACT FROM AUTHOR]

The mRNA modification N6‐methyladenosine (m6A) plays vital roles in plant development and biotic and abiotic stress responses. The RNA m6A demethylase ALKBH9B can remove m6A in alfalfa mosaic virus RNA and plays roles in alfalfa mosaic virus infection in Arabidopsis. However, it is unknown whether ALKBH9B also exhibits demethylation activity and has a biological role in endogenous plant mRNA. We demonstrated here that mRNA m6A modification is induced by the phytohormone abscisic acid (ABA) and that ALKBH9B has m6A demethylation activity on endogenous mRNA. Knocking out ALKBH9B led to hypersensitivity to ABA treatment during seed germination and early seedling development. We further showed that ALKBH9B removes the m6A modification in the ABA INSENSITIVE 1 (ABI1) and BRI1‐EMS‐SUPPRESSOR 1 (BES1) transcripts following ABA treatment, affecting the stability of these mRNAs. Furthermore, we determined that ALKBH9B acts genetically upstream of the transcription factors ABI3 and ABI5, and its regulatory function in ABA responses depended on ABI3 and ABI5. Our findings reveal the important roles of the m6A modification in ABA responses and highlight the role of ALKBH9B‐mediated m6A demethylation in regulating ABA responses post‐transcriptionally. [ABSTRACT FROM AUTHOR]

In air and railway transportation, corrosion and wear lead to the rapid failure of equipment. Epoxy (EP)-based coatings are widely used in research on the anti-corrosion of organic coatings, but their application as materials for wear resistance is limited due to their non-abrasive properties. In this study, a novel high-performance epoxy-based composite coating was developed through the self-assembly of silicon carbide (SiC) and graphene oxide (GO) and the tuning of the interfacial structure with epoxy resin. The coatings were comprehensively characterized, including their electrochemical behavior, a salt spray test, and friction and wear experiments, and the optimal addition ratio of SiC-G@GO (SiC-G@GO was prepared by the self-assembly of γ-(2,3-epoxypropoxy) propytrimethoxysilane (KH560)-modified SiC (SiC-G) on the surface of GO sheets) in the epoxy coatings was explored. Benefiting from the labyrinth effect and their rolling-friction-like microstructure, the 1 wt% SiC-G@GO/EP coating exhibits excellent wear and corrosion resistance. Compared with pure epoxy resin, the 1 wt% SiC-G@GO/EP coating increased by 4 orders of magnitude after 10 days of immersion. The average friction coefficient was 41.5% lower than that of the pure EP coating, and the wear rate was 56.6% lower. This research has positive implications for the development and application of anti-corrosion and wear-resistant organic coatings. [ABSTRACT FROM AUTHOR]

With the aim of adapting a source Text to Speech (TTS) model to synthesize a personal voice by using a few speech samples from the target speaker, voice cloning provides a specific TTS service. Although the Tacotron 2-based multi-speaker TTS system can implement voice cloning by introducing a d-vector into the speaker encoder, the speaker characteristics described by the d-vector cannot allow for the voice information of the entire utterance. This affects the similarity of voice cloning. As a vocoder, WaveNet sacrifices speech generation speed. To balance the relationship between model parameters, inference speed, and voice quality, a voice cloning method based on improved HiFi-GAN has been proposed in this paper. (1) To improve the feature representation ability of the speaker encoder, the x-vector is used as the embedding vector that can characterize the target speaker. (2) To improve the performance of the HiFi-GAN vocoder, the input Mel spectrum is processed by a competitive multiscale convolution strategy. (3) The one-dimensional depth-wise separable convolution is used to replace all standard one-dimensional convolutions, significantly reducing the model parameters and increasing the inference speed. The improved HiFi-GAN model remarkably reduces the number of vocoder model parameters by about 68.58% and boosts the model's inference speed. The inference speed on the GPU and CPU has increased by 11.84% and 30.99%, respectively. Voice quality has also been marginally improved as MOS increased by 0.13 and PESQ increased by 0.11. The improved HiFi-GAN model exhibits outstanding performance and remarkable compatibility in the voice cloning task. Combined with the x-vector embedding, the proposed model achieves the highest score of all the models and test sets. [ABSTRACT FROM AUTHOR]

The prevalence of tetracycline (TC) in aquatic environments has raised increasing concern due to its high ecotoxicology risk. The application of microalgae in the removal of antibiotics is a competitive alternative technology. However, the removal mechanism of TC by microalgae and its correlation with the ecotoxic response of microalgae are still not clear. In this study, the ecotoxicity of TC (0.5–10 mg L−1) and its removal by the freshwater alga Chlorella pyrenoidosa were investigated. The results show that TC has significant inhibitory effects on microalgal growth, photosynthetic pigment, and photosynthetic efficiency, with maximum inhibition rates of 49.68%, 62.54%, and 48.08%, respectively. However, the growth inhibition and photosynthesis impairment caused by TC seems to be reversible, as reflected by the decreased inhibition rates with prolonged exposure time. The simultaneous increases in the activities of superoxide dismutase (9.69–23.53%) and peroxidase (15.15–110.92%) and the contents of glutathione (17.62–64.17%) and malondialdehyde (25.16–35.25%) suggest that TC causes moderate oxidative stress. C. pyrenoidosa exhibits high removal efficiency (91.44–95.14%) for TC after 48 h of exposure with short half-lives of 11.31–13.48 h. Biodegradation (56.86–64.62%) is the primary removal mechanism of TC, accompanied by the abiotic process (24.68–40.97%), bioaccumulation (1.95–10.97%), and bioadsorption (0.09–0.38%). These findings demonstrate the toxicity resistance and high removal capacity of C. pyrenoidosa to TC, highlighting its potential application in the remediation of TC-contaminated water. [ABSTRACT FROM AUTHOR]

SUMMARY: Two factors are proposed to account for the unusual features of organellar genomes: the disruptions of organelle‐targeted DNA replication, repair, and recombination (DNA‐RRR) systems in the nuclear genome and repetitive elements in organellar genomes. Little is known about how these factors affect organellar genome evolution. The deep‐branching vascular plant family Selaginellaceae is known to have a deficient DNA‐RRR system and convergently evolved organellar genomes. However, we found that the plastid genome (plastome) of Selaginella sinensis has extremely accelerated substitution rates, a low GC content, pervasive repeat elements, a dynamic network structure, and it lacks direct or inverted repeats. Unexpectedly, its organelle DNA‐RRR system is short of a plastid‐targeted Recombinase A1 (RecA1) and a mitochondrion‐targeted RecA3, in line with other explored Selaginella species. The plastome contains a large collection of short‐ and medium‐sized repeats. Given the absence of RecA1 surveillance, we propose that these repeats trigger illegitimate recombination, accelerated mutation rates, and structural instability. The correlations between repeat quantity and architectural complexity in the Selaginella plastomes support these conclusions. We, therefore, hypothesize that the interplay of the deficient DNA‐RRR system and the high repeat content has led to the extraordinary divergence of the S. sinensis plastome. Our study not only sheds new light on the mechanism of plastome divergence by emphasizing the power of cytonuclear integration, but it also reconciles the longstanding contradiction on the effects of DNA‐RRR system disruption on genome structure evolution. Significance Statement: We hypothesize that the interplay of the deficient DNA replication, repair, and recombination system and the high repeat content has led to the extraordinary divergence of the Selaginella sinensis plastome. Our study not only sheds new light on the mechanism of plastome divergence by emphasizing the power of cytonuclear integration, but it also reconciles the longstanding contradiction on the effects of DNA replication, repair, and recombination system disruption on genome structure evolution. [ABSTRACT FROM AUTHOR]

Traditional thresholding methods are widely used to extract objects of interest from image backgrounds in various practical applications. However, these methods often face challenges in complex scenes due to poor uniformity, noise, and low contrast. To overcome these limitations, this paper proposes a peak-weaken Otsu method (PWOTSU) that improves the segmentation performance of the Otsu method for automatically extracting objects in complex scenes. The proposed approach uses a set of cross parameters as weights for the Otsu criterion function to adaptively weaken the between-class variance at the peak of the histogram. This ensures that an appropriate threshold value is always obtained for images with different types of histogram distribution. The improved criterion function has the advantage of obtaining a more accurate threshold value without the need for additional parameters, making it easily applicable to various practical applications. Experimental results demonstrate that the proposed method effectively improves the segmentation accuracy and robustness compared to the standard Otsu method and its modifications, as evidenced by qualitative and quantitative evaluations. [ABSTRACT FROM AUTHOR]

Metallic materials have attracted the considerable attentions owing to their remarkable tribological potentials, rendering them indispensable in the fields of manufacturing, aerospace, medical, and daily life. In the future, their utilization is poised to extend into electronic devices, energy storage, sensors, catalysts and other realms in order to enhance performance metrics, bolster stability and reduce costs. Notwithstanding various research have been undertaken on metal-based composites, the important influencing factors and wear mechanisms of metal-base friction interfaces have not been comprehensively reviewed. Therefore, this review summarizes these main influencing factors (e.g., material properties, service conditions, additives and energy effects) on tribological behaviors of metal interfaces, subsequently generalizes their wear mechanisms such as abrasion, adhesion, corrosion and fatigue. Finally, their development prospects and difficulties of the interface tribology are discussed in detail, thereby providing the in-depth insight of these fields for enriching actual applications. [ABSTRACT FROM AUTHOR]

Ionospheric total electron content (TEC) is important data for ionospheric morphology, and also an important parameter for ionospheric correction in Global Navigation Satellite System (GNSS) precise positioning, navigation, and radio science. In this study, we present a data assimilation model for regional ionosphere based on a local ensemble Kalman filter (LEnKF) with the International Reference Ionosphere 2016 (IRI-2016) model as the background, to assimilate ionospheric TEC observations from GNSS. To demonstrate the results, the TEC estimates from the Crustal Movement Observation Network of China (CMONOC), which is about 260 stations in China, are applied as observation. The assessments are performed against the TEC estimates from BeiDou Navigation Satellite System (BDS) geostationary earth orbit (GEO) and against the final products from the Center for Orbit Determination in Europe (CODE). The assimilation results are in good agreement with BDS GEO TEC and the CODE TEC on a quiet or disturbed day. The correlation coefficient after assimilation is increased by about 17% compared with that before assimilation, and the RMSE after assimilation is decreased by about 42% compared with that before assimilation. Furthermore, the assimilated method is also evaluated in the single-frequency precise point positioning (PPP). The experimental results indicate that the PPP/Assimilated method can improve the GNSS positioning accuracy more effectively in comparison to the PPP/CODE. These results reveal that the LEnKF method can be considered as a useful tool for ionospheric assimilation. [ABSTRACT FROM AUTHOR]

To solve the problem of high-precision and fast initial alignment for the Strapdown Inertial Navigation System (SINS) under both dynamic and static conditions, the high-precision attitude measured by the celestial navigation system (CNS) is used as the reference information for the initial alignment. The alignment algorithm is derived in the Earth-centered inertial (ECI) frame. Compared with the alignment algorithm in the navigation frame, it is independent of position parameters and avoids the influence of the approximate error caused by the dynamic deflection angle. In addition, hull deformation is considered in attitude optimal estimation, which can realize initial the alignment of the SINS installed in various parts of the carrier. On this basis, the velocity measurement information is added to the alignment process, which further improves the accuracy and speed of the initial alignment under static conditions. The experimental results show that the algorithms proposed in this paper have better performance in alignment accuracy, speed, and stability. The attitude and velocity matching algorithm in the ECI frame can achieve alignment accuracy better than 0.6′. The attitude matching algorithm in the ECI frame has better robustness and can be used for both dynamic and static conditions, which can achieve alignment accuracy better than 1.3′. [ABSTRACT FROM AUTHOR]

Background: Cleft lip and/or palate (CL/P) are congenital cleft facial deformities that are abnormal developments caused by errors in the fusion process of the embryo's face. Surgery is an important treatment, but postoperative scars will still cause psychological shadows to patients. This study aimed to systematically evaluate the efficacy of Botulinum toxin type A (BTXA) in preventing and treating postoperative CL/P scars and improving scar quality. Methods: A systematic review was performed by searching PubMed, EMBASE, the Cochrane Library, and Web of Science for relevant trials. All relevant trials were performed before June 30, 2021. The data were entered into Revman 5.3 software, and a meta‐analysis was conducted by using the random‐effects model or fixed‐effects model. Results: Four randomized controlled trials involving 161 cases were included. Through quantitative analysis, BTXA showed significant differences in preventing and treating postoperative CL/P scars in terms of scar width (MD: −0.20; [95% CI, −0.30, –0.10], p < 0.0001) and the Visual Analog Scale (VAS) (MD: 1.30; [95% CI, 1.06, 1.55], p < 0.0001), although no significant difference was noted on the Vancouver Scar Scale (VSS) (MD: −0.75; [95% CI, −1.68, 0.19], p = 0.12) between the two groups. Conclusion: In preventing and treating postoperative CL/P scar hypertrophy, we found that BTXA injection can show better results. There was no statistically significant difference between the results after omitting Navarro's study or Chang's study because of the time of injection—before/during surgery or adult CL/P scars. [ABSTRACT FROM AUTHOR]

Ionospheric forecasts are critical for space-weather anomaly detection. Forecasting ionospheric total electron content (TEC) from the global navigation satellite system (GNSS) is of great significance to near-earth space environment monitoring. In this study, we propose a novel ionospheric TEC forecasting model based on deep learning, which consists of a convolutional neural network (CNN), long-short term memory (LSTM) neural network, and attention mechanism. The attention mechanism is added to the pooling layer and the fully connected layer to assign weights to improve the model. We use observation data from 24 GNSS stations from the Crustal Movement Observation Network of China (CMONOC) to model and forecast ionospheric TEC. We drive the model with six parameters of the TEC time series, Bz, Kp, Dst, and F10.7 indices and hour of day (HD). The new model is compared with the empirical model and the traditional neural network model. Experimental results show the CNN-LSTM-Attention neural network model performs well when compared to NeQuick, LSTM, and CNN-LSTM forecast models with a root mean square error (RMSE) and R2 of 1.87 TECU and 0.90, respectively. The accuracy and correlation of the prediction results remained stable in different months and under different geomagnetic conditions. [ABSTRACT FROM AUTHOR]

We present the ionospheric disturbance responses over low-latitude regions by using total electron content from Geostationary Earth Orbit (GEO) satellites of the BeiDou Navigation Satellite System (BDS), ionosonde data and Swarm satellite data, during the geomagnetic storm in August 2018. The results show that a prominent total electron content (TEC) enhancement over low-latitude regions is observed during the main phase of the storm. There is a persistent TEC increase lasting for about 1–2 days and a moderately positive disturbance response during the recovery phase on 27–28 August, which distinguishes from the general performance of ionospheric TEC in the previous storms. We also find that this phenomenon is a unique local-area disturbance of the ionosphere during the recovery phase of the storm. The enhanced f o F 2 and h m F 2 of the ionospheric F2 layer is observed by SANYA and LEARMONTH ionosonde stations during the recovery phase. The electron density from Swarm satellites shows a strong equatorial ionization anomaly (EIA) crest over the low-latitude area during the main phase of storm, which is simultaneous with the uplift of the ionospheric F2 layer from the SANYA ionosonde. Meanwhile, the thermosphere O/N2 ratio shows a local increase on 27–28 August over low-latitude regions. From the above results, this study suggests that the uplift of F layer height and the enhanced O/N2 ratio are possibly main factors causing the local-area positive disturbance responses during the recovery phase of the storm in August 2018. [ABSTRACT FROM AUTHOR]

• The MRT LB equations describing two-phase flows are modified to eliminate error terms. • Two wetting boundary schemes are developed for simulating contact-line motions of two-phase flows with large density ratios. • The requirement of virtual nodes in wetting boundary scheme is removed by a local scheme. • The developed wetting boundary schemes are validated by steady and dynamic simulations. • The contact angle hysteresis with large density and viscosity ratios can be successfully simulated. In this work, wetting boundary schemes in a modified phase-field lattice Boltzmann (LB) method are developed to simulate the contact-line motion and contact angle hysteresis of binary fluids with large density ratios. In the modified phase-field LB method, two multiple-relaxation-time (MRT) LB equations are utilized, one with a nondiagonal relaxation matrix used to solve the conserved Allen-Cahn (A-C) equation and the other with a modified discrete source term used to solve the incompressible Navier-Stokes (N-S) equations. Based on the idea of geometric formulation, two wetting boundary schemes corresponding to the modified phase-field LB model are proposed. In the first scheme, a layer of virtual nodes is utilized to realize the geometric formulation. The values of the order parameter at the virtual nodes are determined by the central difference method. In the second scheme, the geometric formulation is realized through a local scheme for the gradient terms of the order parameter where the nonequilibrium parts of the distribution function are utilized. Compared with the first wetting boundary scheme and some previous models, the second wetting boundary scheme does not require the virtual nodes and simplifies the numerical implementation. The developed two schemes are validated through a series of benchmark simulations, including droplet spreading on idea substrate, capillary intrusion and droplet shearing on nonideal substrate. It is found that satisfactory accuracy can be achieved by both two schemes, and the second scheme can obtain better stability while the first scheme shows better performance in simulating contact angle hysteresis. [ABSTRACT FROM AUTHOR]

Zoysiagrass (Zoysia japonica) is a popular turfgrass species and is widely used for sport turf and urban landscape. Zoysiagrass is often infected by Puccinia zoysiae, which causes a loss in turf quality. The physiological and molecular mechanisms of rust resistance are poorly understood in this species. In this study, the rust-resistant and susceptible lines of zoysiagrass were inoculated with P. zoysiae, and alterations of leaf cell structure, physiological indicators and transcriptomic response were investigated at the various stages of inoculation. After inoculation, the cell membranes, nucleus, mitochondria, and chloroplast were all impaired, followed by abnormal physiological metabolism. The damage occurred earlier and more severely in the susceptible line. Changes in electrolyte leakage and chlorophyll content varied with the genotype and the inoculation stages. The transcriptome analysis showed that plant hormones, MAPK signal transduction pathway, photosynthesis and energy generation pathways were significantly enriched in the early response, in both the resistant and susceptible lines. The results provided insights into the physiological and molecular mechanisms of rust disease resistance and would benefit the breeding of rust-resistant varieties in zoysiagrass and related turfgrass species. [ABSTRACT FROM AUTHOR]

Skeleton‐based action recognition is an inspired yet challenging task in computer vision. Recently, the latest graph convolutional network (GCN), which generalises well‐established convolutional neural networks to non‐Euclidean structures, is proven to be highly successful for action recognition from body skeleton data. However, the GCN architecture has not been fully studied. In this work, a Fisher vector (FV) encoding based GCN architecture (FV‐GCN) is proposed, which exceeds the limitations of existing GCN‐based methods by combining the GCN model with FV encoding. A channel‐wise spatial–temporal aggregation function to preserve spatial–temporal information in the whole action clip and integrate it into the FV‐GCN architecture is also presented. Since FV is different from the GCN structure, this hybrid architecture that incorporates the advantages of both algorithms can discover complementary information of feature representation effectively. On two challenging human action datasets, kinetics, and NTU‐RGBD, improved performance is demonstrated over the baseline method, and the FV‐GCN is better or comparable to some state‐of‐the‐art methods. [ABSTRACT FROM AUTHOR]

Accurate corrections for ionospheric total electron content (TEC) and early warning information are crucial for global navigation satellite system (GNSS) applications under the influence of space weather. In this study, we propose to use a new machine learning model—the Prophet model, to predict the global ionospheric TEC by establishing a short-term ionospheric prediction model. We use 15th-order spherical harmonic coefficients provided by the Center for Orbit Determination in Europe (CODE) as the training data set. Historical spherical harmonic coefficient data from 7 days, 15 days, and 30 days are used as the training set to model and predict 256 spherical harmonic coefficients. We use the predicted coefficients to generate a global ionospheric TEC forecast map based on the spherical harmonic function model and select a year with low solar activity (63.4 < F10.7 < 81.8) and a year with the high solar activity (79.5 < F10.7 < 255.0) to carry out a sliding 2-day forecast experiment. Meanwhile, we verify the model performance by comparing the forecasting results with the CODE forecast product (COPG) and final product (CODG). The results show that we obtain the best predictions by using 15 days of historical data as the training set. Compared with the results of CODE'S 1-Day (C1PG) and CODE'S 2-Day (C2PG). The number of days with RMSE better than COPG on the first and second day of the low-solar-activity year is 151 and 158 days, respectively. This statistic for high-solar-activity year is 183 days and 135 days. [ABSTRACT FROM AUTHOR]

Sweetpotato (Ipomoea batatas [L.] Lam) is a widely cultivated food crop with generally good adaptability. However, drought stress can cause a significant decline in yield. To reveal the response mechanism of sweetpotato to drought stress, an integrated physiological, proteomic and metabolomic investigation was conducted in leaves of two sweetpotato varieties with differing responses to drought stress, drought-resistant Wanzishu56 (WZ56) and a more sensitive variety, Ningzishu2(NZ2). Physiological analysis showed that the variety with better drought tolerance had superior performance in water retention capacity and photosynthetic efficiency under drought stress. A total of 1140 proteins were identified within the two varieties. Among them, 192 differentially expressed proteins were detected under drought conditions, including 97 that were up-regulated. Functional analysis showed that these up-regulated proteins were primarily involved in photosynthesis, reactive oxygen species metabolism, organonitrogen compound metabolism, and precursor metabolite catabolism and energy generation. All differentially expressed proteins in WZ56 that were involved in photosynthetic and glutathione metabolic processes were up-regulated. Enzyme activity assays were carried out to validate the proteomics data. Moreover, 75 metabolites were found to have a higher expression level in WZ56 than NZ2 under drought stress. The higher concentration of carbohydrates, amino acids, flavonoids and organic acids found in drought-stressed leaves of WZ56 suggested that these metabolites may improve the drought resistance of sweetpotato. This study uncovered specific-proteins and metabolites associated with drought resistance, providing new insights into the molecular mechanisms of drought tolerance in sweetpotato. [ABSTRACT FROM AUTHOR]

Smart energy plays an important role in alleviating energy poverty in China in the context of the new technological revolution and industrial change. This paper uses China's smart pilot policy as a quasi-natural experiment, employing China's provincial panel data from 2011 to 2022, measuring energy poverty indices based on a projection pursuit evaluation model, and conducting a quasi-natural experiment using a synthetic control method to assess the effect of smart energy on energy poverty and specific mechanisms of action. The study found that smart energy has a specific and significant impact on energy poverty, but the effect differs in different regions depending on the construction cycle and energy endowment. In the mechanism test, smart energy significantly alleviates energy poverty through the mechanisms of improving energy supply capacity, improving energy payment capacity, and improving energy cleanliness. The results of the study provide empirical references for regional solutions to energy poverty and the planning of smart energy construction. [ABSTRACT FROM AUTHOR]

[Display omitted] • Electrons are redistributed as Mg&MoP/CN loaded at a reverse interfacial position. • Interfacial MoP behaves as the electron collecting sites to improve the activity. • Exterior Mg functions as the catalyzing sites to tackle the selectivity challenge. • Selective and efficient CH 4 evolution are achieved by a Z-scheme reaction pathway. Constructing photocatalysts with dual-function active sites can coordinate the photogenerated electrons transfer and the adsorption energy of key intermediates, thereby converting CO 2 into valuable methane with high efficiency. However, the role that the interfacial position of functional catalysts played in determining the activity and selectivity of CO 2 photoreduction remains unclear. Herein, we regulated the action interface and synergistic effect of magnesium nitrate hydroxide and molybdenum phosphide (Mg & MoP) to modify polymeric carbon nitride (PCN), and found the function-oriented Mg-MoP/PCN exhibits superior performance for catalyzing CO 2 -to-CH 4 in pure water, with a rate of 24.45 μmol h−1 g−1 and 95.3 % selectivity. Theoretical and experimental studies reveal that interfacial layer of MoP promotes the evolutionary activity by facilitating the electron transfer while exterior layer of Mg functions as the catalyzing sites to tackle the selectivity challenge by promoting CO 2 adsorption and CO* stabilization. The synergistic interaction of function-oriented Mg&MoP realizes selective CH 4 evolution with high efficiency via a Z-scheme pathway. The interfacial position of bifunctional catalysts is vital for regulating CO 2 photoreduction activity and product selectivity. [ABSTRACT FROM AUTHOR]

Ovarian cancer is the fifth leading cause of cancer-related mortality in women worldwide. Despite the development of technologies over decades to improve the diagnosis and treatment of patients with ovarian cancer, the survival rate remains dismal, mainly because most patients are diagnosed at a late stage. Traditional treatment methods and biomarkers such as cancer antigen-125 as a cancer screening tool lack specificity and cannot offer personalized combinatorial therapy schemes. Circulating tumor DNA (ctDNA) is a promising biomarker for ovarian cancer and can be detected using a noninvasive liquid biopsy. A wide variety of ctDNA applications are being elucidated in multiple studies for tracking ovarian carcinoma during diagnostic and prognostic evaluations of patients and are being integrated into clinical trials to evaluate the disease. Furthermore, ctDNA analysis may be used in combination with multiple "omic" techniques to analyze proteins, epigenetics, RNA, nucleosomes, exosomes, and associated immune markers to promote early detection. However, several technical and biological hurdles impede the application of ctDNA analysis. Certain intrinsic features of ctDNA that may enhance its utility as a biomarker are problematic for its detection, including ctDNA lengths, copy number variations, and methylation. Before the development of ctDNA assays for integration in the clinic, such issues are required to be resolved since these assays have substantial potential as a test for cancer screening. This review focuses on studies concerning the potential clinical applications of ctDNA in ovarian cancer diagnosis and discusses our perspective on the clinical research aimed to treat this daunting form of cancer. [ABSTRACT FROM AUTHOR]

Aiming at the operation and maintenance requirements of the fault location of high-temperature superconducting cables, a fault location method of high-temperature superconducting cables based on the improved time-frequency domain reflection method and EEMD noise reduction is proposed. Considering the cross-term interference problem in the traditional time-frequency domain reflection method, this paper introduces the affine transformation to project the time-frequency distribution of the self-term and the cross term and further highlights the characteristic differences between the two through coordinate transformation, and the particle swarm algorithm is employed to solve the optimal stagger angle of the affine transformation. The unscented particle filter is adopted to separate the cross term, and EEMD noise reduction is introduced to solve the signal noise problem. Finally, two software programs, PSCAD and MATLAB, are employed for joint simulation to build a model of high-temperature superconducting cable. The simulation example shows that the proposed method in this paper can eliminate the cross-term interference of the traditional time-frequency domain reflection method, effectively locate the fault of the high-temperature superconducting cable, and improve the positioning accuracy. [ABSTRACT FROM AUTHOR]

The stability of the reservoir bank landslide is affected by a variety of external factors, and the fluctuation of reservoir water level is one of the important influencing factors. The Erdaohe landslide is a typically colluvial landslide in the Three Gorges Reservoir area with periodic reservoir water level fluctuations. According to landslide displacement data, the displacement of the Erdaohe landslide exhibits the significantly stepwise feature. Its failure mechanism was analyzed using strength reduction method by the FLAC3D package in the case of reservoir water level changes. The results indicate that the hydrodynamic pressure has an important impact on the initialization of the landslide failure. When reservoir water level rises rapidly or maintains constant at the lower level, the landslide stability would be higher. When the reservoir water level decreases rapidly or maintains constant at the higher level, the landslide stability will be smaller. When the reservoir water level was in the lowest elevation, the factor of safety (FS) reached the minimum value of 1.11. Findings in this paper can provide guidelines for the risk assessment of colluvial landslides. [ABSTRACT FROM AUTHOR]

The large-scale rectangular pipe jacking technology has attracted more and more attention in the construction of urban underground pipe galleries, especially the problem of prediction and control of the surface settlement. Taking the pipe gallery project of Chengbei Road in Suzhou as an example, the settlement values of three groups of monitoring sections under the conditions of natural settlement and synchronous grouting are monitored, and the measured settlement values are compared with Peck formula and random medium theory. The results show that the Peck formula is more accurate in predicting the natural settlement within 1.5 times the pipe jacking width, while the stochastic medium theory is more accurate in predicting the settlement beyond the width. By comparing the field test and theory, the suggestions on the prediction of ground settlement of rectangular pipe jacking of large scale are put forward. The results of this study provide a basis for subsequent related research work and engineering applications. [ABSTRACT FROM AUTHOR]

The total electron content (TEC) is a critical parameter of ionosphere morphology. Precise modeling and prediction of the TEC time series can significantly aid the functioning of the Global Navigation Satellite System (GNSS), satellite as well as shortwave communications. An improved Transformer-based TEC prediction model (ITM) is proposed in this study, in response to the high noise characteristics of the temporal data for TEC in the global ionosphere. The ITM model forecasts the global ionospheric TEC data provided by the Center for Orbit Determination in Europe (CODE) for the year 2018. Experimental results indicate that the model obtains an annual average root mean square error of 1.4 TECU, which represents a 6.67 % advancement over the daily forecast product C1PG published by the CODE center. The model also attains an annual average mean absolute error of 1 TECU, representing a 9.09 % improvement over the accuracy of C1PG. The annual average correlation coefficient is 0.98, which indicates a 0.62 % upgrade in C1PG's accuracy. Additionally, the model exhibits a maximum increase of 23.53 % in monthly average root mean square error over C1PG, a maximum increase of 25 % in monthly average mean absolute error, and a maximum increase of 1.55 % in monthly average correlation coefficient. During the more geomagnetically active phases of 2018, the ITM model's forecast accuracy exhibited an overall improvement of 5 % in RMSE, 7.14 % in MAE, and 0.83 % in correlation coefficient R compared to the C1PG product. [ABSTRACT FROM AUTHOR]

Computerized ionospheric tomography is a highly ill-posed inverse problem, and regularization tends to stabilize the problem to provide a unique solution. When a regularization method is used, the choice of an optimal parameter is a key issue. In this article, we propose an adaptive regularization method for 3-D ionospheric tomography based on the U-curve. The proposed approach uses a U-curve method to determine the optimal regularization parameter from Global Navigation Satellite Systems (GNSS) observation data. Comparative case studies are investigated based on GNSS simulated observations and real measurements. The simulation results indicate that the proposed method is superior to the adaptive regularization method based on the L-curve. In addition, we further validate the tomographic results with actual ionosonde station data. The results demonstrate the reliability and superiority of the proposed method compared to traditional methods. [ABSTRACT FROM AUTHOR]

For the purpose of accurate measurement of regional systemic financial risks and prevention of regional economic turmoil, this paper proposes a new measure called the CoCVaR model, based on the tail mean loss, which is applied to measure the impact of stock returns of each listed company on the overall stock returns in Guangdong Province, China, from January 2010 to December 2020. It is found that there are significant CoVaR and CoCVaR for real estate, finance, utilities, and energy companies, while the risk spillover to the real economy market in Guangdong Province is more significant when companies in these industries are in extreme situations. There are insignificant CoCVaR for daily consumption, information technology, and health care. The risk spillover to the real economy market in Guangdong Province is smaller when companies in these industries are in crisis. [ABSTRACT FROM AUTHOR]

Insulin-like growth factor 1 (IGF1) is one of the endocrine hormones that plays an important role in regulating growth and development of animals. In this study, polymorphism in the 5 ′ UTR and 3 ′ UTR coding region and of the IGF1 gene was detected by DNA sequencing technology, and the abundance of IGF1 mRNA in various tissues at three growth stages of the Shitou goose was determined by quantitative real-time polymerase chain reaction (qRT-PCR). Moreover, the differential expression of IGF1 in various tissues between the Shitou goose and Wuzong goose was revealed. Two single nucleotide polymorphisms (SNPs) were found in the exon3 region of IGF1 in the Shitou goose. IGF1 mRNA was extensively expressed in various tissues of Shitou geese with high abundant expression in the liver, breast muscle and leg muscle at three growth stages. IGF1 mRNA expression showed a trend of first increase and then decrease in the pituitary, liver, subcutaneous fat and abdominal fat tissues, but it decreased in the breast muscle and leg muscle of a Shitou goose with growing age. Expression of IGF1 in the liver, leg muscle and pituitary tissues of the Shitou goose was significantly higher than that of the Wuzong goose. This provides a foundation for further study of regulatory mechanisms of IGF1 in the growth and development of geese. [ABSTRACT FROM AUTHOR]

Our previous studies showed that S100A9 was overexpressed in glioma and promoted tumor growth. However, S100A9 can also be secreted by tumor cells to regulate the tumor microenvironment (TME). In this study, we aimed to explore the functions of glioma derived-S100A9 in microglial M2 polarization, resulting in inhibition of CD8+ T lymphocytes and promotion of immunosuppression. We first showed that glioma exhibited higher expression and secretion of S100A9 than astrocytes. After knocking down S100A9 in two glioma cell lines, the secretion of S100A9 was repressed. Then, the medium was collected and considered as conditioned medium (CM), which was incubated with microglia. We found that glioma-derived S100A9 drove microglial M2 polarization and increased TGFβ1 secretion. These molecular mechanisms were related to the interaction of S100A9 with αvβ3 integrin and the subsequent activation of AKT1 in microglia. Furthermore, we demonstrated that S100A9-induced M2 microglia negatively affected cell viability, IL-2 and IFN-γ secretion, together with increased early apoptosis in CD8+T lymphocytes via TGFβ1. Additionally, glioma cells were implanted into mouse brains, and we confirmed that S100A9 stimulated microglial M2 polarization, enhanced TGFβ1 levels and repressed CD8+ T lymphocytes in orthotopically transplanted tumors. In human glioma samples, S100A9 expression was positively associated with CD206 expression, but negatively correlated with CD8+T lymphocyte accumulation in the TME. Our data indicated that glioma-derived S100A9 has a promising ability to manipulate non-malignant cells and promote immune evasion in the TME, providing valuable insight into the mechanism by which S100A9 participates in the progression of glioma. • Glioma-derived S100A9 polarizes microglia toward M2 via αvβ3 integrin/AKT1. • M2 microglia secretes TGFβ1 to inhibit immunocompetence of CD8+T lymphocyte. • Crosstalk among glioma, M2 microglia and CD8+T lymphocytes for immunosuppression. [ABSTRACT FROM AUTHOR]