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Abstract Objective To analyze the efficacy and associated factors affecting the prognosis in patients with disturbance of consciousness after hyperbaric oxygen (HBO) treatment. Methods A retrospective study was carried out on patients with disorders of consciousness (DOC) receiving HBO treatment from January to January 2022 in the Second Department of Rehabilitation Medicine of the Second Hospital of Hebei Medical University, China. Results HBO therapy improved the Glasgow Coma Scale (GCS) and Chinese Nanjing Persistent Vegetative State Scale (CNPVSS), as well as the clinical efficacy in patients with DOC. The comparison of GCS and CNPVSS scores in patients with DOC before and after HBO treatment was all statistically significant, with 325 patients (67.1%) showing effective results and 159 patients (32.9%) having unchanged outcomes. Univariate analysis indicated that there were statistically significant differences in age, HBO intervention time, HBO treatment times, pre‐treatment GCS score, and etiology and underlying diseases between the good and poor prognoses groups. Multivariate regression analysis showed that HBO intervention time ≤7 days, HBO treatment ＞ times, high GCS score before HBO treatment, and brain trauma were independent influencing factors in achieving a good prognosis for patients with DOC. Low pre‐treatment GCS scores were an independent risk factor for a poor prognosis in patients with brain trauma while being male, late HBO intervention time, fewer HBO treatment times, and low pre‐treatment GCS scores were independent risk factors for a poor prognosis in patients with DOC after a stroke. Being ≥50 years of age, late HBO intervention time, and low pre‐treatment GCS scores were independent risk factors for a poor prognosis in patients with DOC after hypoxic‐ischaemic encephalopathy. Conclusion HBO therapy can improve the GCS, CNPVSS scores and clinical efficacy in patients with DOC, and the timing of HBO intervention ≤7 days, times of HBO treatment, high pre‐treatment GCS score, and brain trauma were the independent influencing factors of good prognosis in patients with DOC.

Chronic pain is a prevalent and persistent ailment that affects individuals worldwide. Conventional medications employed in the treatment of chronic pain typically demonstrate limited analgesic effectiveness and frequently give rise to debilitating side effects, such as tolerance and addiction, thereby diminishing patient compliance with medication. Consequently, there is an urgent need for the development of efficacious novel analgesics and innovative methodologies to address chronic pain. Recently, a growing body of evidence has suggested that multireceptor ligands targeting opioid receptors (ORs) are favorable for improving analgesic efficacy, decreasing the risk of adverse effects, and occasionally yielding additional advantages. In this study, the intrathecal injection of a recently developed peptide (VYWEMEDKN) at nanomolar concentrations decreased pain sensitivity in naïve mice and effectively reduced pain-related behaviors in nociceptive pain model mice with minimal opioid-related side effects. Importantly, the compound exerted significant rapid-acting antidepressant effects in both the forced swim test and tail suspension test. It is possible that the rapid antihyperalgesic and antidepressant effects of the peptide are mediated through the OR pathway. Overall, this peptide could both effectively provide pain relief and alleviate depression with fewer side effects, suggesting that it is a potential agent for chronic pain and depression comorbidities from the perspective of pharmaceutical development.

The pyrolysis of siloxane precursors, such as tetraethoxysilane (TEOS), is commonly employed in the flame synthesis and chemical vapor deposition of silica nanoparticles. In this work, the flow reactor pyrolysis of TEOS is studied using gas chromatography (GC) and synchrotron vacuum ultraviolet photoionization mass spectrometry (SVUV-PIMS), and the congener substitution effects from the central C atom to the central Si atom are investigated through comparison with its hydrocarbon counterpart tetraethoxymethane (TEOM). Pyrolysis models of TEOS and TEOM are constructed and validated against the measured results. Modeling analysis, including rate of production analysis and sensitivity analysis, provides insights into chemistry in fuel consumption and product formation. In contrast, the observations of silicon-containing products in SVUV-PIMS experiments provide evidence for crucial decomposition pathways of TEOS. It is observed that TEOS exhibits significantly higher stability than TEOM under pyrolysis conditions. The most abundant products in the pyrolysis of TEOS and TEOM are ethylene and ethanol, and TEOS produces more hydrocarbon products than TEOM. The lower pyrolysis reactivity of TEOS is attributed to the slower unimolecular decomposition reaction which dominates the decomposition of TEOS than TEOM. This can be explained by the hindrance of the extremely strong Si-O bond resulting from the significantly different electronegativity between Si and O. The higher initial decomposition temperature of TEOS enhances the contribution of other decomposition channels, such as C-C bond dissociation and H-abstraction reactions, in TEOS consumption. This leads to the abundant formation of hydrocarbon productions such as methane, ethane, and acetaldehyde. As the main pyrolysis product, the ethanol produced by TEOM pyrolysis is four times that of TEOS due to the congener substitution effects. The ethanol formation pathway in TEOS pyrolysis is different from that in TEOM pyrolysis, which is mainly formed via a newly proposed multi-step mechanism, resulting in a lower yield in TEOS pyrolysis.

Land Surface Temperature (LST) is important for diagnosing surface energy balance in land surface models (LSMs). However, LST simulation in current LSMs tends to show large cold biases, partially due to the reason that the model's prescribed vegetation parameters (e.g., Leaf Area Index (LAI) and Fraction of Vegetation Cover (FVC)) are misrepresented, especially in regions with complex topography and climate such as Tibetan Plateau. Recent advancements in remote sensing technologies provide a unique opportunity to improve the model's vegetation parameters at large scales. In this study, we practice two experiments to improve LST simulations in Noah-MP LSM by (1) incorporating LAI and FVC from the Global Land Surface Satellite (GLASS) remote sensing product (exp_RS); and (2) incorporating an empirical LAI and FVC parameterization scheme based on the soil temperature stress factor (exp_RL02). Results show that the effect of vegetation on simulated LST is the most significant in summer season when the model-satellite LAI and FVC differences are the largest. Compared to the default experiment that uses static LAI and FVC values from the model's look-up table (exp_CTL), the results in exp_RS and exp_RL02 show domain-wide improvement of the simulated LST. The LAI and FVC effect on LST are also well reflected in model's energy budget components (i.e., longwave emissivity, sensible and latent heat fluxes, etc). Validation of the model simulated soil temperature with in-situ observations further demonstrate the model improvements. Our study underscores the important role of vegetation in regulating surface energy transfer processes. Our study also highlights the feasibility and benefit of incorporating remote sensing data in improving land surface model simulations.

The number of wheat spikes has an important influence on wheat yield, and the rapid and accurate detection of wheat spike numbers is of great significance for wheat yield estimation and food security. Computer vision and machine learning have been widely studied as potential alternatives to human detection. However, models with high accuracy are computationally intensive and time consuming, and lightweight models tend to have lower precision. To address these concerns, YOLO-FastestV2 was selected as the base model for the comprehensive study and analysis of wheat sheaf detection. In this study, we constructed a wheat target detection dataset comprising 11,451 images and 496,974 bounding boxes. The dataset for this study was constructed based on the Global Wheat Detection Dataset and the Wheat Sheaf Detection Dataset, which was published by PP Flying Paddle. We selected three attention mechanisms, Large Separable Kernel Attention (LSKA), Efficient Channel Attention (ECA), and Efficient Multi-Scale Attention (EMA), to enhance the feature extraction capability of the backbone network and improve the accuracy of the underlying model. First, the attention mechanism was added after the base and output phases of the backbone network. Second, the attention mechanism that further improved the model accuracy after the base and output phases was selected to construct the model with a two-phase added attention mechanism. On the other hand, we constructed SimLightFPN to improve the model accuracy by introducing SimConv to improve the LightFPN module. The results of the study showed that the YOLO-FastestV2-SimLightFPN-ECA-EMA hybrid model, which incorporates the ECA attention mechanism in the base stage and introduces the EMA attention mechanism and the combination of SimLightFPN modules in the output stage, has the best overall performance. The accuracy of the model was P=83.91%, R=78.35%, AP= 81.52%, and F1 = 81.03%, and it ranked first in the GPI (0.84) in the overall evaluation. The research examines the deployment of wheat ear detection and counting models on devices with constrained resources, delivering novel solutions for the evolution of agricultural automation and precision agriculture.

Abstract Soil moisture (SM) plays an important role in regulating regional weather and climate. However, the simulations of SM in current land surface models (LSMs) contain large biases and model spreads. One primary reason contributing to such model biases could be the misrepresentation of soil texture in LSMs, since current available large‐scale soil texture data are often generated from extrapolation algorithm based on a scarce number of in‐situ geological measurements. Fortunately, recent advancements in satellite technology provide a unique opportunity to constrain the soil texture data sets by introducing observed information at large spatial scales. Here, two major soil texture baseline data sets (Global Soil Data sets for Earth system science, GSDE and Harmonized World Soil Data from Food and Agriculture Organization, HWSD) are optimized with satellite‐estimated soil hydraulic parameters. The optimized soil maps show increased (decreased) sand (clay) content over arid regions. The soil organic carbon (SOC) content increases globally especially over regions with dense vegetation cover. The optimized soil texture data sets are then used to run simulations in one example LSM, that is, Noah LSM with Multiple Parameters. Results show that the simulated SM with satellite‐optimized soil texture maps is improved at both grid and in‐situ scales. Intercase comparison analyses show the SM improvement differs between simulations using different soil maps and soil hydraulic schemes. Our results highlight the importance of incorporating observation‐oriented calibration on soil texture in current LSMs. This study also joins the call for a better soil profile representation in the next generation of Earth System Models (ESMs).

Abstract Background Continuous and noninvasive hemoglobin (Hb) monitoring during surgery is essential for anesthesiologists to make transfusions decisions. The aim of this study was to investigate the feasibility and accuracy of noninvasive and continuous Hb monitoring using transesophageal descending aortic photoplethysmography (dPPG) in porcine model. Methods Nineteen landrace pigs, aged 3 to 5 months and weighing 30 to 50 kg, were enrolled in this study. A homemade oximetry sensor, including red (660 nm) and infrared (940 nm) lights, was placed in the esophagus for dPPG signal detection to pair with the corresponding reference Hb values (Hbi−STAT) measured by blood gas analysis. The decrease and increase changes in Hb concentration were achieved by hemodilution and transfusion. Metrics, including alternating current (AC), direct current (DC), and AC/DC for both red and infrared light were extracted from the dPPG signal. A receiver operating characteristic (ROC) curve was built to evaluate the performance of dPPG metrics in predicting the Hb “trigger threshold” of transfusion (Hb 100 g/L). Agreement and trending ability between Hb measured by dPPG (HbdPPG) and by blood gas analysis were analyzed by Bland-Altman method and polar plot graph. Error grid analysis was also performed to evaluate clinical significance of HbdPPG measurement. Results The dPPG signal was successfully detected in all of the enrolled experimental pigs, without the occurrence of a continuous loss of dPPG signal for 2 min during the entire measurement. A total of 376 pairs of dPPG signal and Hbi−STAT were acquired. ACred/DCred and ACinf/DCinf had moderate correlations with Hbi−STAT, and the correlation coefficients were 0.790 and 0.782, respectively. The areas under the ROC curve for ACred/DCred and ACinf/DCinf in predicting Hbi−STAT < 60 g/L were 0.85 and 0.75, in predicting Hbi−STAT > 100 g/L were 0.90 and 0.83, respectively. Bland-Altman analysis and polar plot showed a small bias (1.69 g/L) but a wide limit of agreement (-26.02–29.40 g/L) and a poor trend ability between HbdPPG and Hbi−STAT. Clinical significance analysis showed that 82% of the data lay within the Zone A, 18% within the Zone B, and 0% within the Zone C. Conclusion It is feasible to establish a noninvasive and continuous Hb monitoring by transesophageal dPPG signal. The ACred/DCred extracted from the dPPG signal could provide a sensitive prediction of the Hb threshold for transfusion. The Hb concentration measured by dPPG signal has a moderate correlation with that measured by blood gas analysis. This animal study may provide an experimental basis for the development of bedside HbdPPG monitoring in the future.

Abstract Electrochemical nitrate reduction to ammonia offers an attractive solution to environmental sustainability and clean energy production but suffers from the sluggish *NO hydrogenation with the spin–state transitions. Herein, we report that the manipulation of oxygen vacancies can contrive spin−polarized Fe1−Ti pairs on monolithic titanium electrode that exhibits an attractive NH3 yield rate of 272,000 μg h−1 mgFe −1 and a high NH3 Faradic efficiency of 95.2% at −0.4 V vs. RHE, far superior to the counterpart with spin−depressed Fe1−Ti pairs (51000 μg h–1 mgFe –1) and the mostly reported electrocatalysts. The unpaired spin electrons of Fe and Ti atoms can effectively interact with the key intermediates, facilitating the *NO hydrogenation. Coupling a flow−through electrolyzer with a membrane-based NH3 recovery unit, the simultaneous nitrate reduction and NH3 recovery was realized. This work offers a pioneering strategy for manipulating spin polarization of electrocatalysts within pair sites for nitrate wastewater treatment.

Highlights Novel double-network (DN) ion-conducting hydrogel (ICH) based on a poly(ionic liquid)/MXene/poly(vinyl alcohol) system (named PMP DN ICH) was synthesized using freeze–thawing and ionizing radiation technology. The PMP DN ICH possesses a multiple cross-linking mechanism and exhibits outstanding ionic conductivity (63.89 mS cm−1), excellent temperature resistance (−60–80 °C) and decent mechanical performance. The well-designed PMP DN ICH shows considerable potential in wearable sensing, energy storage, and energy harvesting.

Abstract The breeding of crops with improved nitrogen use efficiency (NUE) is crucial for sustainable agriculture, but the involvement of epigenetic modifications remains unexplored. Here, we analyze the chromatin landscapes of two wheat cultivars (KN9204 and J411) that differ in NUE under varied nitrogen conditions. The expression of nitrogen metabolism genes is closely linked to variation in histone modification instead of differences in DNA sequence. Epigenetic modifications exhibit clear cultivar-specificity, which likely contributes to distinct agronomic traits. Additionally, low nitrogen (LN) induces H3K27ac and H3K27me3 to significantly enhance root growth in KN9204, while remarkably inducing NRT2 in J411. Evidence from histone deacetylase inhibitor treatment and transgenic plants with loss function of H3K27me3 methyltransferase shows that changes in epigenetic modifications could alter the strategy preference for root development or nitrogen uptake in response to LN. Here, we show the importance of epigenetic regulation in mediating cultivar-specific adaptation to LN in wheat.

Solar radiation is an important energy source, and accurately predicting it [daily global and diffuse solar radiation (Rs and Rd)] is essential for research on surface energy exchange, hydrologic systems, and agricultural production. However, Rs and Rd estimation relies on meteorological data and related model parameters, which leads to inaccuracy in some regions. To improve the estimation accuracy and generalization ability of the Rs and Rd models, 17 representative radiation stations in China were selected. The categorical boosting (CatBoost) feature selection algorithm was utilized to construct a novel stacking model from sample and parameter diversity perspectives. The results revealed that the characteristics related to sunshine duration (n) and ozone (O3) significantly affect solar radiation prediction. The proposed new ensemble model framework had better accuracy than base models in root mean square error (RMSE), coefficient of determination (R2), mean absolute error (MAE), and global performance index (GPI). The solar radiation prediction model is more applicable to coastal areas, such as Shanghai and Guangzhou, than to inland regions of China. The range and mean of RMSE, MAE, and R2 for Rs prediction are 1.5737–3.7482 (1.9318), 1.1773–2.6814 (1.4336), and 0.7597–0.9655 (0.9226), respectively; for Rd prediction, they are 1.2589–2.9038 (1.8201), 0.9811–2.1024 (1.3493), and 0.5153–0.9217 (0.7248), respectively. The results of this study can provide a reference for Rs and Rd estimation and related applications in China.

The oxygen reduction reaction (ORR) is one of the most critical reactions in energy conversion systems, and it facilitates the efficient conversion of chemical energy into electrical energy, which is necessary for modern technology. Developing efficient and cost-effective catalysts for ORRs is crucial for advancing and effectively applying renewable energy technologies such as fuel cells, metal–air batteries, and electrochemical sensors. In recent years, iron porphyrin-based composites have emerged as ideal catalysts for facilitating effective ORRs due to their unique structural characteristics, abundance, advances in synthesis, and excellent catalytic properties, which mimic natural enzymatic systems. However, many articles have focused on reviewing porphyrin-based frameworks or metalloporphyrins in general, necessitating research specifically addressing iron porphyrin. This review discusses iron porphyrin as an effective catalyst in ORRs. It provides a comprehensive knowledge of the application of iron porphyrin-based composites for electrocatalytic ORRs, focusing on their properties, synthesis, structural integration with conductive supports, catalytic mechanism, and efficacy. This review also discusses the challenges of applying iron porphyrin-based composites and provides recommendations to address these challenges.

To enhance the accuracy and efficiency of the deflection response measurement of concrete bridges with a non-contact scheme and address the ill-conditioned nature of the inverse problem in influence line (IL) identification, this study introduces a computer-vision-aided deflection IL identification method that integrates edge detection and time-domain forward inference (TDFI). The methodology proposed in this research leverages computer vision technology with edge detection to surpass traditional contact-based measurement methods, greatly enhancing the operational efficiency and applicability of IL identification and, in particular, addressing the challenge of accurately measuring small deflections in concrete bridges. To mitigate the limitations of the Lucas–Kanade (LK) optical flow method, such as unclear feature points within the camera’s field of view and occasional point loss in certain video frames, an edge detection technique is employed to identify maximum values in the first-order derivatives of the image, creating virtual tracking points at the bridge edges through image processing. By precisely defining the bridge boundaries, only the essential structural attributes are preserved to enhance the reliability of minimal deflection deformations under vehicular loads. To tackle the ill-posed nature of the inverse problem, a TDFI model is introduced to identify IL, recursively capturing the static bridge response generated by the bridge under the influence of successive axles of a multi-axle vehicle. The IL is then computed by dividing the response by the weight of the preceding axle. Furthermore, an axle weight ratio reduction coefficient is proposed to mitigate noise amplification issues, ensuring that the weight of the preceding axle surpasses that of any other axle. To validate the accuracy and robustness of the proposed method, it is applied to numerical examples of a simply supported concrete beam, indoor experiments on a similar beam, and field tests on a three-span continuous concrete beam bridge.

Bacteroides fragilis is a new generation of probiotics, and its probiotic effects on humans and some animals have been verified. However, research on B. fragilis in cattle is still lacking. In this study, 24 stool samples were collected from two large-scale cattle farms in Wuzhong, Ningxia, including 12 diarrheal and 12 normal stools. A non-toxigenic Bacteroides fragilis (NTBF) was isolated and identified by 16S rRNA high-throughput sequencing and named BF-1153; genome composition and genome functional analyses were carried out to reflect the biological characteristics of the BF-1153 strain. A cluster analysis of BF-1153 was performed using Mega X to explore its genetic relationship. In addition, Cell Counting Kit-8 (CCK8) was used to determine the toxic effects of the strain on human ileocecal colorectal adenocarcinoma cell line cells (HCT-8), Madin-Darby bovine kidney cells (MDBK), and intestinal porcine epithelial cells (IPECs). The results showed that BF-1153 conformed to the biological characteristics of B. fragilis. BF-1153 had no toxic effects on HCT-8, MDBK, and IPEC. Animal experiments have shown that BF-1153 has no toxic effects on healthy SPF Kunming mice. Notably, the supernatant of BF-1153 enhanced cell activity and promoted cell growth in all three cell lines. At the same time, a cluster analysis of the isolated strains showed that the BF-1153 strain belonged to the same branch as the B. fragilis strain 23212, and B. fragilis strain 22998. The results of the animal experiments showed that BF-1153 had a certain preventive effect on diarrhea symptoms in SPF Kunming mice caused by a bovine rotavirus (BRV). In summary, the strain BF-1153 isolated in this experiment is NTBF, which has no toxic effect on MDBK, HCT-8, and IPEC, and has obvious cell growth-promoting effects, especially on MDBK. BF-1153 promotes the growth and development of SPF Kunming mice when compared with the control group. At the same time, BF-1153 alleviated the diarrhea symptoms caused by BRV in SPF Kunming mice. Therefore, BF-1153 has the potential to be a probiotic for cattle.

Harnessing waste heat from environmental or industrial sources presents a promising approach to eco-friendly and sustainable chemical synthesis. In this study, we introduce a thermoelectrocatalytic (TECatal) system capable of utilizing even small amounts of heat for hydrogen peroxide (H2O2) production. We developed a nanohybrid structure, combining carbon nanotubes (CNTs) and Bi2Te3 nanoflakes (Bi2Te3/CNTs), through a one-pot synthesis method. Bi2Te3, as a thermoelectric (TE) material, generates charge carriers under a temperature gradient via the Seebeck effect, enabling them to participate in surface redox reactions. However, the rapid recombination of these charge carriers greatly limits the TECatal activity. In the Bi2Te3/CNTs nanohybrid system, the introduction of CNTs substantially enhances the efficiency of H2O2 production, as the strong bonding between CNTs and Bi2Te3, along with the excellent conductivity of CNTs, facilitates charge carrier separation and transport, as confirmed by TE electrochemical tests. This study underscores the significant potential of thermoelectric nanomaterials for converting waste heat into green chemical synthesis.

Fresh-cut fruits and vegetables have become more popular among consumers because of their nutritional value and convenience. However, the lower shelf life of fresh-cut fruits and vegetables due to processing and mechanical damage is a critical factor affecting their market expansion, and advances in preservation technology are needed to prolong their shelf life. Some traditional chemical preservatives are disliked by health-seeking consumers because of worries about toxicity. Chemical preservation is inexpensive and highly efficient, but sometimes it carries risks for human health. Biological preservation methods are safer and more appealing, but they are not applicable to large-scale production. Physical fresh-keeping methods have been used for the storage and transportation of fresh-cut fruits and vegetables due to the ease of application. This review discusses current research in fresh-keeping technology for the preservation of fresh-cut fruits and vegetables. Preservation methods include low temperature, modified atmosphere packaging, cold plasma, pulsed light, ultrasonics, ultraviolet light, and ozonated water. As promising alternatives to chemical methods, these novel processes have been evaluated singly or combined with natural preservatives or other methods to extend the shelf life of fresh-cut fruits and vegetables and to provide references and assessments for further development and application of fresh-cut fruit and vegetable preservation technology.

Proteins are the foundation of life, and designing functional proteins remains a key challenge in biotechnology. Before the development of AlphaFold2, the focus of design was primarily on structure-centric approaches such as using the well-known open-source software Rosetta3. Following the development of AlphaFold2, deep-learning techniques for protein design gained prominence. This study proposes a new method to generate functional proteins using the diffusion model and ESM2 protein language model. Diffusion models, which are widely used in image and natural language generation, are used here for protein design, facilitating the controlled generation of new sequences. The ESM2 model, trained on the basis of large-scale protein sequence data, provides a deep understanding of the context of the sequence, thus improving the model’s ability to generate biologically relevant proteins. In this study, we used the Protein A-like peptide as a model study object, combined the diffusion model and the ESM2 model to generate new peptide sequences from minimal input data, and verified their biological activities through experiments such as the BLI affinity test. In conclusion, we developed a new method for protein design that provides a novel strategy to meet the challenges of generic protein generation.

In the process of CO2 geological storage in the salt water layer, CO2 leakage along the wellbore will seriously affect the effective storage of CO2 in the target geological area. To solve this problem, based on the investigation of a large number of failure cases of CO2 storage along the wellbore and failure cases of gas storage wells in the injection stage of the wellbore, the influencing factors of CO2 leakage risk along the wellbore were investigated in detail. Based on the analytic hierarchy process (AHP) and extension theory, 17 basic evaluation indexes were selected from 6 perspectives to establish the evaluation index system of CO2 leakage risk along the wellbore. The established evaluation system was used to evaluate the leakage risk of a CO2 storage well in the X gas field of BZ Block. The results showed that the influencing factors of tubing had the smallest weight, followed by cement sheath, and the influencing factors of casing–cement sheath interface and cement sheath–formation interface had the largest weight, accounting for 23.73% and 34.32%, respectively. The CO2 storage well leakage risk evaluation grade was Ι, with minimal leakage risk. The CO2 storage effect was excellent. The evaluation system comprehensively considers the tubing string, cement sheath, and micro-annulus interface, which can provide a scientific basis for the risk assessment of CO2 leakage along the wellbore under the CO2 geological storage of the salt water layer.

With the advancement of computer vision technology, the demand for fruit recognition in agricultural automation is increasing. To improve the accuracy and efficiency of recognizing young red pears, this study proposes an improved model based on the lightweight YOLOv9s, termed YOLOv9s-Pear. By constructing a feature-rich and diverse image dataset of young red pears and introducing spatial-channel decoupled downsampling (SCDown), C2FUIBELAN, and the YOLOv10 detection head (v10detect) modules, the YOLOv9s model was enhanced to achieve efficient recognition of small targets in resource-constrained agricultural environments. Images of young red pears were captured at different times and locations and underwent preprocessing to establish a high-quality dataset. For model improvements, this study integrated the general inverted bottleneck blocks from C2f and MobileNetV4 with the RepNCSPELAN4 module from the YOLOv9s model to form the new C2FUIBELAN module, enhancing the model’s accuracy and training speed for small-scale object detection. Additionally, the SCDown and v10detect modules replaced the original AConv and detection head structures of the YOLOv9s model, further improving performance. The experimental results demonstrated that the YOLOv9s-Pear model achieved high detection accuracy in recognizing young red pears, while reducing computational costs and parameters. The detection accuracy, recall, mean precision, and extended mean precision were 0.971, 0.970, 0.991, and 0.848, respectively. These results confirm the efficiency of the SCDown, C2FUIBELAN, and v10detect modules in young red pear recognition tasks. The findings of this study not only provide a fast and accurate technique for recognizing young red pears but also offer a reference for detecting young fruits of other fruit trees, significantly contributing to the advancement of agricultural automation technology.

Exploring high-performance carbon anodes that are low-cost and easily accessible is the key to the commercialization of sodium-ion batteries. Producing carbon materials from bio by-products is an intriguing strategy for sodium-ion battery anode manufacture and for high-value utilization of biomass. Herein, a novel hard carbon (PPHC) was prepared via a facile pyrolysis process followed by acid treatment using biowaste pomegranate peel as the precursor. The morphology and structure of the PPHC were influenced by the carbonization temperature, as evidenced by physicochemical characterization. The PPHC pyrolyzed at 1100 °C showed expanded interlayer spacing and appropriate oxygen group content. When used as a sodium ion battery anode, the PPHC-1100 demonstrated a reversible capacity of up to 330 mAh g−1, maintaining 174 mAh g−1 at an increased current rate of 1 C. After 200 cycles at 0.5 C, the capacity delivered by PPHC-1100 was 175 mAh g−1. The electrochemical behavior of PPHC electrodes was investigated, revealing that the PPHC-1100 possessed increased capacitive-controlled energy storage and improved ion transport properties, which explained its excellent electrochemical performance. This work underscores the feasibility of high-performance sodium-ion battery anodes derived from biowaste and provides insights into the sodium storage process in biomass-derived hard carbon.

Abstract: This study addresses the current difficulties in accurately controlling the indoor temperature of double-skin facades (DSFs), and its optimization, with a focus on the window opening angles of double-skin facades. The Spearman correlation coefficient method was used to select the main meteorological factors, including outdoor temperature, dew point temperature, scattered radiation, direct radiation, and window opening angle. A modified random forest algorithm was used to construct the optimization model and 80% of the data were used for model training. In the experiments, the average accuracy of the optimization model was as high as 93.5% for all window opening angles. This study provides a data-driven method for application to double-skin facades, which can effectively determine and control the window opening angles of double-skin facades to achieve energy saving and emission reduction, reduce indoor temperature, improve comfort, and provide a practical basis for decision-making. Future research will further explore the applicability and accuracy of the model under different climatic conditions.

Abstract Double holography offers a profound understanding of the island formula by describing a gravitational system on AdS d coupled to a conformal field theory on ℝ1,d−1, dual to an AdS d+1 spacetime with an end-of-the-world (EOW) brane. In this work, we extend the proposal in [12] by considering that the dual bulk spacetime has two EOW branes: one with a gravitational system and the other with a thermal bath. We demonstrate an equivalence between this proposal and the wedge holographic theory. We examine it in both Anti-de Sitter gravity and de Sitter gravity by calculating the entanglement entropy of the Hawking radiation. Finally, we employ the doubly holographic model to verify the formula for the entanglement entropy in a subregion within conformally flat spacetime.

In order to solve the problems of low thermal conductivity and easy liquid leakage of a stearic acid (SA), the composite phase change material(PCM) was prepared by adding boron nitride (BN) and expanded graphite (EG) to melted SA, and its thermal conductivity, crystal structure, chemical stability, thermal stability, cycle stability, leakage characteristics, heat storage/release characteristics, and temperature response characteristics were characterized. The results showed that the addition of BN and EG significantly improved the thermal conductivity of the material, and they efficiently adsorbed melted SA. The maximum load of SA was 76 wt. % and there was almost no liquid leakage. Moreover, the melting enthalpy and temperature were 154.20 J • g − 1 and 67.85°C, respectively. Compared with pure SA, the SA/BN/EG composite showed a lower melting temperature and a higher freezing temperature. In addition, when the mass fraction of BN and EG was 12 wt. %, the thermal conductivity of the composite was 6.349 W • m−1 • K−1, which was 18.619 times that of SA. More importantly, the composite showed good stability for 50 cycles of heating and cooling, and the SA / BN / EG-12 hardly decomposes below 200°C, which implies that the working performance of the composite PCM is relatively stable within the temperature range of 100°C. Therefore, the composite can exhibit excellent thermal stability in the field of building heating.

Abstract A sustainable future depends on increasing agricultural carbon (C) and nitrogen (N) sequestration. Winter rapeseeds are facing severe yield loss after waterlogging due to the effects of extreme rainfall, especially in the seedling stage, where rainfall is most sensitive. Uncertainty exists over the farming greenhouse gas (GHG) release of rapeseed seedlings following the onset of waterlogging. The effect of waterlogging on GHG release and leaf gas exchange in winter rapeseed was examined in a pot experiment. The experiment included waterlogging treatments lasting 7-day and 21-day and normal irrigation as a control treatment. According to our findings, (1) The ecosystem of rapeseed seedlings released methane (CH4) and nitrous oxide (N2O) in a clear up change that was impacted by ongoing waterlogging. Among them, N2O release had a transient rise during the early stages under the effect of seedling fertilizer. (2) The net photosynthetic rate, transpiration rate, stomatal conductance, plant height, soil moisture, and soil oxidation–reduction potential of rapeseed all significantly decreased due to the ongoing waterlogging. However, rapeseed leaves showed a significant increase in intercellular carbon dioxide (CO2) concentration and leaf chlorophyll content values after waterlogging. Additionally, the findings demonstrated an extremely significant increase in the sustained-flux global warming potential of the sum CO2-eq of CH4 and N2O throughout the entire waterlogging stress period. Therefore, continuous waterlogging can increase C and N release from rapeseed seedlings ecosystem and decrease yield. Therefore, we suggest increasing drainage techniques to decrease the release of agricultural GHGs and promote sustainable crop production.

This paper proposes regarding economic dispatch problem as learning problem not optimization problem that develops adaptive Long Short-term Memory (LSTM) neural network to construct perfect dispatch learning model for each dispatch instant. First, matrix correlation analysis is performed to select critical historical instants for each dispatch instant. Then, according to matrix correlation analysis results, the structure of LSTM neural network at each instant is determined. Finally, the structures of LSTM learning models are adaptive for different dispatch instants. The differentiated training sets are constructed for adaptive LSTM learning models. The WSCC 9-bus system and the IEEE 118-bus system are used to verify the effectiveness of the proposed method. Study results indicate that the generation dispatch schedule obtained by the proposed LSTM learning model is closer to the perfect dispatch schedule than the generation dispatch schedule obtained by solving non-linear optimization problem.

Objective: To achieve the application of rice dreg glutelin in emulsions system. Methods: This paper selected alkali-heat modified rice dregs glutenin and span80 as emulsifiers to prepare W/O/W double emulsions by one-step emulsification method, and investigated the effect of protein concentration on the stability of double emulsions to provide the theoretical reference for the preparation of stable double emulsions by one-step emulsification. Results: When the protein mass fraction increased from 0.5% to 2.5%, the large particle size peak disappears in emulsion, the apparent viscosity and viscoelasticity of emulsions were improved, the centrifugal stability and storage stability were enhanced, enhanced dual structure of droplets in microstructure. When the protein mass fraction reached 2.5%, after centrifugation, the whey precipitation index decreased from 37.21% to 10.56%, and the layering time was extended from 6 hours to 96 h. Protein and span80 formed a composite membrane to jointly stabilize the oil-water interface, and formed an intermediate droplet. When the interface protein was enough to form a rigid boundary facial mask, the droplet changed from the intermediate state to a stable dual structure. When the protein mass fraction reached 3.0%, the flocculation of the double emulsions led to the reappearance of the large particle size peak, and the stability was reduced. After centrifugation, the emulsion index was 16.48%, and about 96 hours after preparation, the excess protein was partially involved in the construction of the internal phase droplets, and the other part was separately formed into W/O droplets and adsorbed on the outside of the large volume droplets. Conclusion: Under one-step emulsification method, when the protein content is 2.5%, stable double emulsions can be prepared.

Abstract Purpose Furosemide, a frequently prescribed diuretic for managing congestive heart failure and edema, remains a topic of debate regarding its potential risk of inducing acute kidney injury (AKI) in patients. Consequently, this study aims to examine the occurrence of hospital-acquired AKI (HA-AKI) in hospitalized patients who are administered furosemide and to investigate potential risk factors associated with this outcome. Methods This study encompassed a cohort of 22374 hospitalized patients who either received furosemide treatment or not from June 1, 2012, to December 31, 2017. Propensity score matching was employed to establish comparability between the two groups regarding covariates. Subsequently, a nomogram was constructed to predict the probability of AKI occurrence among patients who underwent furosemide treatment. Results The regression analysis identified the single-day total dose of furosemide as the most significant factor for AKI, followed by ICU administration, estimated glomerular filtration rate, antibiotic, statin, NSAIDs, β-blockers, proton pump inhibitor, chronic kidney disease, and 7 other indicators. Subgroup analysis revealed a synergistic effect of furosemide with surgical operation, previous treatment with β-blockers, ACEI/ARB and antibiotics, leading to an increased risk of AKI when used in combination. Subsequently, a visually represented prognostic nomogram was developed to predict AKI occurrence in furosemide users. The predictive accuracy of the nomogram was assessed through calibration analyses, demonstrating an excellent agreement between the nomogram predictions and the actual likelihood of AKI, with a probability of 77.40%. Conclusions Careful consideration of factors such as dosage, concurrent medication use, and renal function of the patient is necessary for clinical practice when using furosemide. Our practical prognostic model for HA-AKI associated with furosemide use can be utilized to assist clinicians in making informed decisions about patient care and treatment.

Abstract Background Immunosuppression induced by programmed cell death protein 1 (PD1) presents a significant constraint on the effectiveness of chimeric antigen receptor (CAR)-T therapy. The potential of combining PD1/PDL1 (Programmed cell death 1 ligand 1) axis blockade with CAR-T cell therapy is promising. However, developing a highly efficient and minimally toxic approach requires further exploration. Our attempt to devise a novel CAR structure capable of recognizing both tumor antigens and PDL1 encountered challenges since direct targeting of PDL1 resulted in systemic adverse effects. Methods In this research, we innovatively engineered novel CARs by grafting the PD1 domain into a conventional second-generation (2G) CAR specifically targeting CD19. These CARs exist in two distinct forms: one with PD1 extramembrane domain (EMD) directly linked to a transmembrane domain (TMD), referred to as PE CAR, and the other with PD1 EMD connected to a TMD via a CD8 hinge domain (HD), known as PE8HT CAR. To evaluate their efficacy, we conducted comprehensive assessments of their cytotoxicity, cytokine release, and potential off-target effects both in vitro and in vivo using tumor models that overexpress CD19/PDL1. Results The findings of our study indicate that PE CAR demonstrates enhanced cytotoxicity and reduced cytokine release specifically towards CD19 + PDL1 + tumor cells, without off-target effects to CD19-PDL1 + tumor cells, in contrast to 2G CAR-T cells. Additionally, PE CAR showed ameliorative differentiation, exhaustion, and apoptosis phenotypes as assessed by flow cytometry, RNA-sequencing, and metabolic parameter analysis, after encountering CD19 + PDL1 + tumor cells. Conclusion Our results revealed that CAR grafted with PD1 exhibits enhanced antitumor activity with lower cytokine release and no PD1-related off-target toxicity in tumor models that overexpress CD19 and PDL1. These findings suggest that our CAR design holds the potential for effectively addressing the PD1 signal.

Abstract Introduction Hexarelin exhibits significant protection against organ injury in models of ischemia/reperfusion (I/R)-induced injury (IRI). Nevertheless, the impact of Hexarelin on acute kidney injury (AKI) and its underlying mechanism remains unclear. In this study, we investigated the therapeutic potential of Hexarelin in I/R-induced AKI and elucidated its molecular mechanisms. Methods We assessed the protective effects of Hexarelin through both in vivo and in vitro experiments. In the I/R-induced AKI model, rats were pretreated with Hexarelin at 100 μg/kg/d for 7 days before being sacrificed 24 h post-IRI. Subsequently, kidney function, histology, and apoptosis were assessed. In vitro, hypoxia/reoxygenation (H/R)-induced HK-2 cell model was used to investigate the impact of Hexarelin on apoptosis in HK-2 cells. Then, we employed molecular docking using a pharmmapper server and autodock software to identify potential target proteins of Hexarelin. Results In this study, rats subjected to I/R developed severe kidney injury characterized by tubular necrosis, tubular dilatation, increased serum creatinine levels, and cell apoptosis. However, pretreatment with Hexarelin exhibited a protective effect by mitigating post-ischemic kidney pathological changes, improving renal function, and inhibiting apoptosis. This was achieved through the downregulation of conventional apoptosis-related genes, such as Caspase-3, Bax and Bad, and the upregulation of the anti-apoptotic protein Bcl-2. Consistent with the in vivo results, Hexarelin also reduced cell apoptosis in post-H/R HK-2 cells. Furthermore, our analysis using GSEA confirmed the essential role of the apoptosis pathway in I/R-induced AKI. Molecular docking revealed a strong binding affinity between Hexarelin and MDM2, suggesting the potential mechanism of Hexarelin’s anti-apoptosis effect at least partially through its interaction with MDM2, a well-known negative regulator of apoptosis-related protein that of p53. To validate these findings, we evaluated the relative expression of MDM2 and p53 in I/R-induced AKI with or without Hexarelin pre-administration and observed a significant suppression of MDM2 and p53 by Hexarelin in both in vivo and in vitro experiments. Conclusion Collectively, Hexarelin was identified as a promising medication in protecting apoptosis against I/R-induced AKI.

Context: Deficit drip irrigation is an advanced agricultural technology widely promoted and applied around the world to maintain/increase yield and quality while simultaneously minimizing water consumption. However, there is still a lack of comprehensive research on the effects of deficit drip irrigation at different stages on apple yield, water productivity, and quality. Objective: The aim was to investigate the effects of deficit drip irrigation treatments (DDITs) on apple yield, quality, and water productivity (WP), and optimize the deficit drip irrigation strategy for apples in the Loess Plateau of China. Methods: a two-year field experiment was conducted with 17 irrigation treatments, including a control treatment (CK, full irrigation (FI)) and four DDITs (D15%, D30%, D45%, D60%) during the bud burst to leafing stage (I), flowering to fruit set stage (II), fruit expansion stage (III), and fruit maturation stage (IV). The optimal irrigation management was determined using the fuzzy Borda combined model, which was based on four different single evaluation models of the TOPSIS method, principal component analysis (PCA), grey correlation analysis (GCA), and membership function analysis (MFA). Results: The DDITs at stage IV decreased midday leaf water potential (Ψs) by 2.57–20.00% compared with CK, and the difference of Ψs between IV-D30%, IV-D45%, IV-D60%, and CK were significant in two years (P

Accurate evapotranspiration (ET) estimation is paramount for effective agricultural water management. As the key parameter of surface resistance (rs)-based ET models, the direct acquisition of canopy resistance (rc) remains challenge. Moreover, the applicability of rc models and rs-based ET models has not been fully validated on kiwifruit. To address above problems, this study investigates tree growth patterns, water consumption change, and soil water content (SWC) dynamics under different irrigation strategies based on a two-year experiment in Northwest China. Subsequently, the Whale Algorithm (WOA), Quantum Whale Algorithm (QWOA), and Differential Whale Algorithm (DWOA) were employed to optimize Jarvis-type rc models (JA) constructed by different constraint functions of SWC. After internal comparison within Jarvis-type models and external comparison with Kelliher-Perrier (KP), Faria (FA), and Stannard (ST) model, the recommended rc model was integrated into Penman-Monteith (PM), Shuttleworth-Wallace (SW), and Clumping (CL) to select most suitable kiwifruit ET model. The results indicated that the water stress coefficient is suitable for JA model as a constraint function of SWC, achieving R2, NSE, RMSE, and MAPE of 0.782–0.805, 0.672–0.737, 654.191–3396.594 s m−1, and 0.102–0.183 under sufficient irrigation strategy, respectively. Under deficit irrigation strategies, the corresponding R2, NSE, RMSE, and MAPE ranged 0.886–0.917, 0.828–0.885, 325.736–3251.434 s m−1, and 0.111–0.166, respectively. Besides, DWOA is the best algorithm during whole growth period, which improved original JA by 13.2–32.9% for R2, 23.0–60.2% for NSE, 26.8–36.8% for RMSE, and 17.5–36.2%, respectively. Regarding rs-based ET models, the CL performed best under various irrigation conditions, with values of R2, NSE, RMSE, and MAPE ranging 0.908–0.961, 0.842–0.947, 0.311–0.808 mm, and 0.088–0.197, respectively. Overall, the CL integrated with DWOA-JA3 is most recommended for estimating kiwifruit ET under different irrigation strategies, which is helpful for orchardists to enhance agricultural water utilization efficiency and promote sustainable kiwifruit production.

Distributed systems often consist of a large number of computing and data nodes, which makes it both significant and challenging to detect anomalies efficiently and accurately in distributed systems. Generally, we not only need to determine whether an anomaly has occurred at a certain time (the time level anomaly), but also need to detect whether anomalies occur in a node (the node level anomaly) and which key performance indicators (KPIs) are anomalies (the KPI level anomaly), that is, to perform multi-granular anomaly detection in distributed systems. However, most existing algorithms only focus on the time level anomalies in centralized systems. For distributed systems, a simple way is to train a model for each node and then detect anomalies independently. An obvious disadvantage is that the cost of model inferring is unacceptable in practice. Therefore, we propose a Multi-Granular Anomaly Detection (MGAD) framework that utilizes a tree structure to perform anomaly detection hierarchically from the node level to time and KPI levels, which greatly reduces the cost of model inferring. Specifically, at the time level, we propose a novel model named Masked Sliding Spatial-Temporal Adversarial Network (MS2TAN) that considers spatial and temporal dependencies simultaneously. Extensive experiments with real-world data offer insights into the performance of the proposals, showing that MGAD is at least 5× faster for inferring when compared with the baselines.

Abstract For the integrity monitoring of a multi-source PNT (Positioning, Navigation, and Timing) resilient fusion navigation system, a theoretical framework of multi-level autonomous integrity monitoring is proposed. According to the mode of multi-source fusion navigation, the framework adopts the top-down logic structure and establishes the navigation source fault detection model based on the multi-combination separation residual method to detect and isolate the fault source at the system level and subsystem level. For isolated non-redundant navigation sources, the system level recovery verification model is used. For the isolated multi-redundant navigation sources, the sensor fault detection model optimized with the dimension-expanding matrix is used to detect and isolate the fault sensors, and the isolated fault sensors are verified in real-time. Finally, according to the fault detection and verification results at each level, the observed information in the fusion navigation solution is dynamically adjusted. On this basis, the integrity risk dynamic monitoring tree is established to calculate the Protection Level (PL) and evaluate the integrity of the multi-source integrated navigation system. The autonomous integrity monitoring method proposed in this paper is tested using a multi-source navigation system integrated with Inertial Navigation System (INS), Global Navigation Satellite System (GNSS), Long Baseline Location (LBL), and Ultra Short Baseline Location (USBL). The test results show that the proposed method can effectively isolate the fault source within 5 s, and can quickly detect multiple faulty sensors, ensuring that the positioning accuracy of the fusion navigation system is within 5 m, effectively improving the resilience and reliability of the multi-source fusion navigation system.

Abstract Structural damage identification technology based on modal parameters is an extremely effective monitoring method. Because of the structural characteristics of the conductor, with its small diameter and long span, it is not easy to obtain the modal parameters by manual excitation. Here, a method for structural health monitoring of the conductor under wind load excitation is proposed. Firstly, the natural frequency change law of the conductor after broken strand damage is obtained by analyzing the conductor modal parameters calculation formula and IEEE standards. Then, the vibration characteristics are calculated by vibration experiments and finite element methods. Finally, through the broken strand experiment, this paper demonstrates how to determine the damage degree of the conductor using the modal parameters. And it is applied to online monitoring in the field. The results show that this method is convenient, fast, and accurate.

As a ligand-dependent transcription factor, retinoid-associated orphan receptor γt (RORγt) that controls T helper (Th) 17 cell differentiation and interleukin (IL)-17 expression plays a critical role in the progression of several inflammatory and autoimmune conditions. An emerging novel approach to the therapy of these diseases thus involves controlling the transcriptional capacity of RORγt to decrease Th17 cell development and IL-17 production. Several RORγt inhibitors including both antagonists and inverse agonists have been discovered to regulate the transcriptional activity of RORγt by binding to orthosteric- or allosteric-binding sites in the ligand-binding domain. Some of small-molecule inhibitors have entered clinical evaluations. Therefore, in current review, the role of RORγt in Th17 regulation and Th17-related inflammatory and autoimmune diseases was highlighted. Notably, the recently developed RORγt inhibitors were summarized, with an emphasis on their optimization from lead compounds, efficacy, toxicity, mechanisms of action, and clinical trials. The limitations of current development in this area were also discussed to facilitate future research.

Abstract Background Noninvasive respiratory support has been increasingly applied in the immediate postoperative period to prevent postoperative pulmonary complications (PPCs). However, the optimal approach remains uncertain. We sought to evaluate the comparative effectiveness of various noninvasive respiratory strategies used in the immediate postoperative period after cardiac surgery. Methods We conducted a frequentist random-effect network meta-analysis (NMA) of randomized controlled trials (RCTs) comparing the prophylactic use of noninvasive ventilation (NIV), continuous positive airway pressure (CPAP), high flow nasal cannula (HFNC), or postoperative usual care (PUC) in the immediate postoperative period after cardiac surgery. Databases were systematically searched through September 28, 2022. Study selection, data extraction, and quality assessment were performed in duplicate. The primary outcome was the incidence of PPCs. Results Sixteen RCTs enrolling 3011 patients were included. Compared with PUC, NIV significantly reduced the incidence of PPCs [relative risk (RR) 0.67, 95% confidence interval (CI): 0.49 to 0.93; absolute risk reduction (ARR) 7.6%, 95% CI: 1.6–11.8%; low certainty] and the incidence of atelectasis (RR 0.65, 95% CI: 0.45 to 0.93; ARR 19.3%, 95% CI: 3.9–30.4%; moderate certainty); however, prophylactic NIV was not associated with a decreased reintubation rate (RR 0.82, 95% CI: 0.29 to 2.34; low certainty) or reduced short-term mortality (RR 0.64, 95% CI: 0.16 to 2.52; very low certainty). As compared to PUC, the preventive use of CPAP (RR 0.85, 95% CI: 0.60 to 1.20; very low certainty) or HFNC (RR 0.74, 95% CI: 0.46 to 1.20; low certainty) had no significant beneficial effect on the incidence of PPCs, despite exhibiting a downward trend. Based on the surface under the cumulative ranking curve, the highest-ranked treatment for reducing the incidence of PPCs was NIV (83.0%), followed by HFNC (62.5%), CPAP (44.3%), and PUC (10.2%). Conclusions Current evidence suggest that the prophylactic use of NIV in the immediate postoperative period is probably the most effective noninvasive respiratory approach to prevent PPCs in patients undergoing cardiac surgery. Given the overall low certainty of the evidence, further high-quality research is warranted to better understand the relative benefits of each noninvasive ventilatory support. Clinical Trial Registration PROSPERO, https://www.crd.york.ac.uk/prospero/ , registry number: CRD42022303904.

On the basis of “Carbon Peak and Carbon Neutral” goals, carbon sequestration projects are increasing in China. The integrity of cement sheaths, as an important factor affecting carbon sequestration projects, has also received more attention and research. When CO2 is injected into the subsurface from sequestration wells, the cement sheath may mechanically fail due to the pressure accumulated inside the casing, which leads to the sealing of the cement sheath failing. The elasticity and strength parameters of the cement sheath are considered in this paper. The critical bottom-hole injection pressures of inclined well sections under anisotropic formation stresses at different depths were calculated for actual carbon-sealing wells in the X block—the CO2 sequestration target block. The sensitivity factors of the critical bottom-hole injection pressure were also analyzed. It was found that the cement sheath damage criterion was tensile damage. The Young’s modulus and tensile strength of the cement sheath are the main factors affecting the mechanical failure of the cement sheath, with Poisson’s ratio having the second highest influence. An increase in the Young’s modulus, Poisson’s ratio, and tensile strength of the cement sheath can help to improve the mechanical stability of cement sheaths in CO2 sequestration wells. This model can be used for the design and evaluation of cement in carbon sequestration wells.

The timing of potato tuberization is affected by potato ripeness, environmental factors, and polygene regulation. The accurate control of the transition to tuberization has both scientific and practical production value, but the key factors regulating this transition remain unclear. This study grafted an early-maturing potato variety (Favorita) scion to the late-maturing Qingshu 9 variety and demonstrated that a heterologous early-maturing scion can induce early potato formation on a late-maturing rootstock. The transcriptome of functional leaves and stolons of grafted plants was comprehensively analyzed and 593 differentially expressed genes (DEGs) were identified, including 38 transcription factors. Based on gene molecular function analysis and previous reports, we propose that PIF5, bHLH93, CBF3, ERF109, TCP19, and YABBY1 are the key DEGs that induce tuber formation in early- and late-maturing potatoes. The YABBY1 gene was subjected to functional verification. The leaf area of StYABBY1-overexpressing plants was smaller than the wild type and no potato tubercles were formed, while an RNA interference plant line showed no change in leaf area and formed tubers, indicating that StYABBY1 has a role in leaf size regulation and tuber formation.

Korla fragrant pear is a high-quality local pear variety native to Xinjiang, China. Currently, the low fruit-setting rate and low calyx shedding rate problems in Korla fragrant pears have been highlighted, which seriously affect the fruit yield and quality. It is of great significance to research the fruiting characteristics and molecular-assisted identification of Korla fragrant pear bud mutation materials for enriching the germplasm resources of Korla fragrant pear. In this research, a natural pollination group (YB) of Korla fragrant pear bud mutation materials and a natural pollination group (CK) of Korla fragrant pears were established. On the fruiting characteristics, the fruit-setting rate and calyx-removal rate of the two groups were investigated. In terms of fruit quality, the fruit shape index, fruit specific gravity, soluble solids content, sugar:acid ratio, soluble sugar content, and other indicators were measured. For the anatomical structure of the calyx tube, the detachment cells were observed. The formation time of the two groups of detached cells was compared. In the GBS simplified genome sequencing, a phylogenetic tree was constructed based on the obtained SNP sites. A principal component analysis, population genetic structure analysis, and genetic diversity index analysis were carried out. In the aspect of SSR molecular marker identification, the SSR types were counted. Polyacrylamide gel electrophoresis was performed. The results demonstrate the following: (1) the fruit-setting rate (30.87%) and calyx-removal rate (68.11%) in the YB group were significantly higher than those in the CK group (19.37%) and the calyx-removal rate (55.18%). (2) There was no significant difference in fruit quality indexes, such as average fruit weight (127.10–130.00 g) and soluble sugar content (9.47–9.56%) between the two groups. (3) Abscission-layer cells were observed at 2, 4, 6, 8, and 10 h after calyx tube discoloration in the YB group and at 48, 72, and 96 h after calyx tube discoloration in the CK group. (4) The genetic background of the YB group and the CK group was similar at the GBS level, but there were differences at the DNA level. This research finally shows that Korla fragrant pear bud mutation material is a good germplasm resource. This germplasm resource can promote the structural optimization of Korla fragrant pear varieties and the healthy development of the industry.

LiDAR has emerged as one of the most pivotal sensors in the field of navigation, owing to its expansive measurement range, high resolution, and adeptness in capturing intricate scene details. This significance is particularly pronounced in challenging navigation scenarios where GNSS signals encounter interference, such as within urban canyons and indoor environments. However, the copious volume of point cloud data poses a challenge, rendering traditional iterative closest point (ICP) methods inadequate in meeting real-time odometry requirements. Consequently, many algorithms have turned to feature extraction approaches. Nonetheless, with the advent of diverse scanning mode LiDARs, there arises a necessity to devise unique methods tailored to these sensors to facilitate algorithm migration. To address this challenge, we propose a weighted point-to-plane matching strategy that focuses on local details without relying on feature extraction. This improved approach mitigates the impact of imperfect plane fitting on localization accuracy. Moreover, we present a classification optimization method based on the normal vectors of planes to further refine algorithmic efficiency. Finally, we devise a tightly coupled LiDAR-inertial odometry system founded upon optimization schemes. Notably, we pioneer the derivation of an online gravity estimation method from the perspective of S2 manifold optimization, effectively minimizing the influence of gravity estimation errors introduced during the initialization phase on localization accuracy. The efficacy of the proposed method was validated through experimentation employing various LiDAR sensors. The outcomes of indoor and outdoor experiments substantiate its capability to furnish real-time and precise localization and mapping results.

The identification and enumeration of peach seedling fruits are pivotal in the realm of precision agriculture, greatly influencing both yield estimation and agronomic practices. This study introduces an innovative, lightweight YOLOv8 model for the automatic detection and quantification of peach seedling fruits, designated as YOLO-Peach, to bolster the scientific rigor and operational efficiency of orchard management. Traditional identification methods, which are labor-intensive and error-prone, have been superseded by this advancement. A comprehensive dataset was meticulously curated, capturing the rich characteristics and diversity of peach seedling fruits through high-resolution imagery at various times and locations, followed by meticulous preprocessing to ensure data quality. The YOLOv8s model underwent a series of lightweight optimizations, including the integration of MobileNetV3 as its backbone, the p2BiFPN architecture, spatial and channel reconstruction convolution, and coordinate attention mechanism, all of which have significantly bolstered the model’s capability to detect small targets with precision. The YOLO-Peach model excels in detection accuracy, evidenced by a precision and recall of 0.979, along with an mAP50 of 0.993 and an mAP50-95 of 0.867, indicating its superior capability for peach sapling identification with efficient computational performance. The findings underscore the model’s efficacy and practicality in the context of peach seedling fruit recognition. Ablation studies have shed light on the indispensable role of each component, with MobileNetV3 streamlining the model’s complexity and computational load, while the p2BiFPN architecture, ScConv convolutions, and coordinate attention mechanism have collectively enhanced the model’s feature extraction and detection precision for minute targets. The implications of this research are profound, offering a novel approach to peach seedling fruit recognition and serving as a blueprint for the identification of young fruits in other fruit species. This work holds significant theoretical and practical value, propelling forward the broader field of agricultural automation.

The carbon factor is the core driving force behind the low-carbon transformation of the power system. The study of Emission Reduction Paths (ERPs) has become a key issue for the New-type Power System to achieve clean and low-carbon goals. In order to measure the relationship between ERP and the economy, this paper considers the retirement requirements of coal-fired power units and emission reduction requirements on a long cycle planning scale, and constructs a multi-scenario planning model that considers electric-thermal coupling, enabling the determination of installed capacity for power and heat sources each year. The effectiveness of the proposed model was verified using an improved IEEE-39 bus power system. A case study was conducted to analyze the economic performance of the system based on the selected ERP set. The results showed that under the rear acceleration’s ERP, the system could achieve optimal economic performance based on the selected ERP set.

As China's population continues to age rapidly, smart elderly care has become a crucial strategy for addressing this societal challenge. Smart home systems have the potential to significantly enhance the quality of life, safety, and autonomy of the elderly. However, the adoption rate of these systems in this demographic remains relatively low, requiring an exploration of the key factors influencing the behavioral intention to use such systems. This study developed a comprehensive model based on the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology. Through empirical analysis using partial least squares structural equation modeling, this study systematically examined the pathways through which various factors affected the behavioral intentions of the elderly. The findings revealed that perceived usefulness, facilitating conditions, compatibility, and perceived cost had significant direct effects on behavioral intention. Additionally, social influence, perceived trust, facilitating conditions, and compatibility indirectly influenced behavioral intention through perceived usefulness and perceived ease of use. Although perceived trust did not directly affect behavioral intention, it exerted an indirect influence through perceived usefulness. This comprehensive model provides theoretical insights into the behavioral intentions of the elderly toward smart home systems and offers practical guidance for developers, designers, and policymakers in the development, design, and promotion of these systems.

This study aimed to assess the impact of dietary selenoprotein extracts from Cardamine hupingshanensis (SePCH) on the growth, hematological parameters, selenium metabolism, immune responses, antioxidant capacities, inflammatory reactions and intestinal barrier functions in juvenile largemouth bass (Micropterus salmoides). The base diet was supplemented with four different concentrations of SePCH: 0.00, 0.30, 0.60 and 1.20 g/Kg (actual selenium contents: 0.37, 0.59, 0.84 and 1.30 mg/kg). These concentrations were used to formulate four isonitrogenous and isoenergetic diets for juvenile largemouth bass during a 60-day culture period. Adequate dietary SePCH (0.60 and 1.20 g/Kg) significantly increased weight gain and daily growth rate compared to the control groups (0.00 g/Kg). Furthermore, 0.60 and 1.20 g/Kg SePCH significantly enhanced amounts of white blood cells, red blood cells, platelets, lymphocytes and monocytes, and levels of hemoglobin, mean corpuscular volume and mean corpuscular hemoglobin in the hemocytes. In addition, 0.60 and 1.20 g/Kg SePCH increased the mRNA expression levels of selenocysteine lyase, selenophosphate synthase 1, 15 kDa selenoprotein, selenoprotein T2, selenoprotein H, selenoprotein P and selenoprotein K in the fish liver and intestine compared to the controls. Adequate SePCH not only significantly elevated the activities of antioxidant enzymes (Total superoxide dismutase, catalase, glutathione reductase, glutathione peroxidase), the levels of total antioxidant capacity and glutathione, while increased mRNA transcription levels of NF-E2-related factor 2, Cu/Zn-superoxide dismutase, catalase, glutathione reductase and glutathione peroxidase. However, adequate SePCH significantly decreased levels of malondialdehyde and H2O2 and the mRNA expression levels of kelch-like ECH-associated protein 1a and kelch-like ECH-associated protein 1b in the fish liver and intestine compared to the controls. Meanwhile, adequate SePCH markedly enhanced the levels of immune factors (alkaline phosphatase, acid phosphatase, lysozyme, complement component 3, complement component 4 and immunoglobulin M) and innate immune-related genes (lysozyme, hepcidin, liver-expressed antimicrobial peptide 2, complement component 3 and complement component 4) in the fish liver and intestine compared to the controls. Adequate SePCH reduced the levels of pro-inflammatory cytokines (tumour necrosis factor-α, interleukin 8, interleukin 1β and interferon γ), while increasing transforming growth factor β1 levels at both transcriptional and protein levels in the liver and intestine. The mRNA expression levels of mitogen-activated protein kinase 13 (MAPK 13), MAPK14 and nuclear factor kappa B p65 were significantly reduced in the liver and intestine of fish fed with 0.60 and 1.20 g/Kg SePCH compared to the controls. Histological sections also demonstrated that 0.60 and 1.20 g/Kg SePCH significantly increased intestinal villus height and villus width compared to the controls. Furthermore, the mRNA expression levels of tight junction proteins (zonula occludens-1, zonula occludens-3, Claudin-1, Claudin-3, Claudin-5, Claudin-11, Claudin-23 and Claudin-34) and Mucin-17 were significantly upregulated in the intestinal epithelial cells of 0.60 and 1.20 g/Kg SePCH groups compared to the controls. In conclusion, these results found that 0.60 and 1.20 g/Kg dietary SePCH can not only improve growth, hematological parameters, selenium metabolism, antioxidant capacities, enhance immune responses and intestinal functions, but also alleviate inflammatory responses. This information can serve as a useful reference for formulating feeds for largemouth bass.

Background This study aimed to investigate the potential of a NAD+ metabolism-related lncRNA signature as a reliable prognostic biomarker for acute myeloid leukemia (AML).Methods Transcriptome profiles and clinical data of AML patients were obtained from The Cancer Genome Atlas (TCGA) database. NAD+ metabolism-related genes (NMRGs) were identified from the KEGG and Reactome databases. Coexpression analysis was used to screen NAD+ metabolism-related lncRNAs. The NAD+ metabolismrelated lncRNA signature was constructed using univariate analysis, LASSO regression, and multivariate analysis. High- and low-risk groups were compared for survival, tumor mutation burden, immune cell infiltration, and response to immunotherapy. Enrichment analysis explored the biological functions.Results LINC01679, AC079922.2, TRAF3IP2-AS1, and LINC02465 were identified to construct the risk model. The model exhibited good predictive power and outperformed age and gender as an independent prognostic marker. High-risk patients showed poorer survival, distinct TP53 mutations, and altered immune cell infiltration compared to low-risk patients. Additionally, low-risk patients exhibited greater sensitivity to immunotherapy. Enriched biological functions included leukocyte migration and positive regulation of cytokine production.Conclusions The NAD+ metabolism-related lncRNA signature shows promise in predicting clinical outcomes for AML patients.

Objective The present study investigated the specific mechanism by which mesenchymal stem cells (MSCs) protect against sepsis-associated acute kidney injury (SA-AKI).Methods Male C57BL/6 mice underwent cecal ligation and puncture surgery to induce sepsis and then received either normal IgG or MSCs (1 × 106 cells, intravenously) plus Gal-9 or soluble Tim-3 3 h after surgery.Results After cecal ligation and puncture surgery, the mice injected with Gal-9 or MSCs plus Gal-9 had a higher survival rate than the mice in the IgG treatment group. Treatment with MSCs plus Gal-9 decreased serum creatinine and blood urea nitrogen levels, improved tubular function recovery, reduced IL-17 and RORγt levels and induced IL-10 and FOXP3 expression. Additionally, the Th17/Treg cell balance was altered. However, when soluble Tim-3 was used to block the Gal-9/Tim-3 pathway, the septic mice developed kidney injury and exhibited increased mortality. Treatment with MSCs plus soluble Tim-3 blunted the therapeutic effect of MSCs, inhibited the induction of Tregs, and suppressed the inhibition of differentiation into Th17 cells.Conclusion Treatment with MSCs significantly reversed the Th1/Th2 balance. Thus, the Gal-9/Tim-3 pathway may be an important mechanism of MSC-mediated protection against SA-AKI.

Background The effects of serum uric acid (SUA) on clinical outcomes in patients with acute kidney injury (AKI) are unclear. The aim of this study was to investigate the association of SUA levels with clinical outcomes of AKI patients.Methods The data of AKI patients hospitalized in the Affiliated Hospital of Qingdao University were retrospectively reviewed. Multivariable logistic regression was utilized to assess the association between SUA levels and the clinical outcomes of AKI patients. Receiver operating characteristic (ROC) analysis was applied to assess the predictive ability of SUA levels for in-hospital mortality in patients with AKI.Results A total of 4,646 AKI patients were eligible for study inclusion. In multivariable analysis, after adjustment for various confounding factors in the fully adjusted model, a higher SUA level was found to be associated with increased in-hospital mortality of AKI patients with an odds ratio (OR) of 1.72 (95% CI, 1.21–2.33, p = 0.005) for the SUA level >5.1–6.9 mg/dl group and 2.75 (95% CI, 1.78–4.26, p 6.9 mg/dl group compared with the reference group (SUA ≤3.6 mg/dl). In the ROC analysis, the area under the curve (AUC) of SUA was 0.65 with a sensitivity of 51% and a specificity of 73%.Conclusions An elevated SUA level is associated with an increased risk of in-hospital mortality in patients with AKI, and it appears to be an independent prognostic marker for these patients.

Di-(2-ethylhexyl)-phthalate (DEHP), a common Phthalic acid ester (PAEs), has been reported to be associated with diabetes mellitus, yet the underlying mechanisms remain unknown. Combined nutrient interventions have been shown to alleviate the diabetic toxicity of DEHP. However, the effects and mechanisms of the combined intervention of Astragalus and vitamins (C and E) are currently unknown. In this study, we investigated the potential mechanisms of DEHP-induced diabetes mellitus through transcriptome analysis and vitro experiments using rat insulinoma cells (INS-1 cells). Furthermore, we explored the protection of the combined Astragalus, vitamin C, and vitamin E on DEHP-induced diabetes mellitus through these mechanisms. INS-1 cells in the logarithmic growth period were exposed to 125 umol/L DEHP followed by high-throughput sequencing analysis. The cell proliferation inhibition rate was determined using MTT assay for each group, and the cell apoptosis rate and intracellular ROS level were measured using flow cytometer. Finally, insulin levels and markers of oxidative stress were detected using ELISA kits in different groups. A total of 372 differentially expressed genes were found between the 125 umol/L DEHP and control groups, subsequent functional enrichment analyses indicated that DEHP induced oxidative stress and disturbed insulin levels. In INS-1 cells, the rate of cell proliferation inhibition, apoptosis, and the degree of oxidative stress increased concentration-dependently with increasing DEHP concentrations, while antioxidant intervention could reverse these changes. Insulin synthesis and secretion decreased after 240 μmol/L DEHP exposure stimulated by 25 mM glucose in INS-1 cells, also could antioxidant intervention alleviate these reductions. Based on these results, the underlying mechanism of DEHP impairing the function of INS-1 cells might be through apoptosis pathways induced by oxidative stress and direct reduction of insulin levels (both synthesis and secretion), while the optimal combination of Astragalus and vitamins (C and E) could exert an alleviating effect.

Ficus carica L. (dioecious), the most significant commercial species in the genus Ficus, which has been cultivated for more than 11,000 years and was one of the first species to be domesticated. Herein, we reported the most comprehensive F. carica genome currently. The contig N50 of the Orphan fig was 9.78 Mb, and genome size was 366.34 Mb with 13 chromosomes. Based on the high-quality genome, we discovered that F. carica diverged from Ficus microcarpa ~34 MYA, and a WGD event took place about 2─3 MYA. Throughout the evolutionary history of F. carica, chromosomes 2, 8, and 10 had experienced chromosome recombination, while chromosome 3 saw a fusion and fission. It is worth proposing that the chromosome 9 experienced both inversion and translocation, which facilitated the emergence of the F. carica as a new species. And the selections of F. carica for the genes of recombination chromosomal fragment are compatible with their goal of domestication. In addition, we found that the F. carica has the FhAG2 gene, but there are structural deletions and positional jumps. This gene is thought to replace the one needed for female common type F. carica to be pollinated. Subsequently, we conducted genomic, transcriptomic, and metabolomic analysis to demonstrate significant differences in the expression of CHS among different varieties of F. carica. The CHS playing an important role in the anthocyanin metabolism pathway of F. carica. Moreover, the CHS gene of F. carica has a different evolutionary trend compared to other Ficus species. These high-quality genome assembly, transcriptomic, and metabolomic resources further enrich F. carica genomics and provide insights for studying the chromosomes evolution, sexual system, and color characteristics of Ficus.