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Abstract Postoperative pneumonia (POP) is a common complication after hip fracture surgery and is associated with increased mortality and other complications in elderly patients. This study aims to evaluate biomarkers, especially the glucose-albumin ratio (GAR), for predicting POP in elderly hip fracture patients. A total of 1279 elderly patients admitted to our hospital with hip fractures were included. We assessed 29 biomarkers and focused on GAR to determine its prognostic and predictive value for POP. Multivariable logistic regression and propensity score-matched analyses were conducted to calculate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for POP, adjusting for potential confounders. Receiver operating characteristic (ROC) curves were utilized to determine the optimal cut-off of GAR for predicting POP. Among the biomarkers and combinations assessed, GAR demonstrated superior predictive capability for POP in elderly hip fracture patients. ROC analyses showed moderate predictive accuracy of GAR for POP, with an area under the curve of 0.750. Using the optimal cut-off of 0.175, the high GAR group was significantly associated with increased odds of POP (adjusted OR 2.14, 95%, CI 1.50–3.05). These associations remained significant after propensity score matching and subgroup analyses. Dose–response relationships between GAR and POP were observed. In conclusion, GAR may be a promising biomarker to predict POP risk in elderly hip fracture patients. Further studies are warranted to validate its clinical utility. However, this study has certain limitations, including its retrospective design, potential for selection bias due to the exclusion criteria, and the single-center nature of the study, which should be addressed in future prospective, multicenter studies.

Sugarcane has recently attracted increasing attention for its potential as a source of sugar and bioethanol, so increasing its yield is essential to ensure the sugar security and bioenergy production. Intergeneric hybridization is a highly efficient method to produce new genetic variants of crop plants, particularly those species with high ploidy such as sugarcane (Saccharum spp.). Tripidium arundinaceum exhibits many desirable agronomic traits, and has been widely studied to produce hybrids with improved stress tolerance and other characteristics in sugarcane breeding. However, the genetic relationship between T. arundinaceum and Saccharum species, and the individual T. arundinaceum chromosomal compositions in sugarcane hybrids are still elusive. Here we used whole-genome single-nucleotide polymorphisms (SNPs) to ascertain the phylogenetic relationships between these species and found that T. arundinaceum is more closely related to Saccharum than Sorghum, in contrast to the previous narrow genetic analyses using chloroplast DNA. Additionally, oligonucleotide (oligo)-based chromosome-specific painting derived from Saccharum officinarum was able to distinctly identify the chromosomes of T. arundinaceum. We developed the oligo-genomic in situ hybridization (GISH) system for the first time, to unveil the novel chromosome translocations and the transmission of individual T. arundinaceum chromosomes in sugarcane progeny. Notably, we discovered that the chromosomal transmission of T. arundinaceum exhibited several different inheritance modes, including n, 2n, and over 2n in the BC1 progenies. Such inheritance patterns may have resulted from first division restitution (FDR) or FDR+nondisjunction of a chromosome with the sister chromatids in the second meiosis division/second division restitution (FDR+NSC/SDR) model during meiosis. These results will be of substantial benefit for the further selection of T. arundinaceum chromosomes for sugarcane genetic improvement.

Contradiction between ultrafast nucleation and deposition rates of lithium (Li) crystals at high rate and heterogeneity of Li+ flux resulting from concentration polarization has compromised the performance of Li metal anodes especially at high areal capacity and current density. Here, multifunctional protective layer consisting of MoO3 nanobelt films (MoO3-NF) is introduced on the surface of Li by a simple rolling method. The strong binding energy between Li and MoO3 guides the homogeneous nucleation and deposition of Li, while the nanobelt networks provide effective ion channels for uniform distribution of the Li+ flux. Because of the novel multifunctional protective layer, the MoO3-NF@Li anodes demonstrate a remarkable stability for 800 h with ultralow overpotential of 159 mV at extreme harsh conditions of 60 mA·h/cm2 and 60 mA/cm2. MoO3-NF@Li||LiNi0.6Co0.2Mn0.2O2 full-cells can run 100 cycles with a superior capacity retention of 84.2% under practical test conditions, demonstrating great potential for high output and energy-density metal batteries.

Abstract Introduction Concentrated Growth Factor (CGF), rich in CD34 + stem cells, is widely used in treatments for androgenetic alopecia and skin rejuvenation due to its immune-modulating properties. Psoriasis, a chronic inflammatory skin condition, presents significant treatment challenges, particularly for patients who cannot use biologics due to conditions such as cancer and lesions resistant to treatments. The potential of CGF in treating psoriasis is promising, given its broad immunoregulatory effects which confirmed in our previous androgenetic alopecia work. Methods We evaluated the impact of CGF on IL-17 levels in two contexts: patients treated for androgenetic alopecia and a psoriasis mouse model. Twelve patients received three monthly injections of CGF, with serum IL-17 levels measured before and after treatment. In the psoriasis mouse model, groups were treated with CGF, and outcomes were assessed using the Psoriasis Area and Severity Index (PASI), skin barrier scores, histological analysis, and RNA sequencing. Additionally, in vitro experiments applied CD34 + cells from CGF to keratinocytes to measure levels of TNF-α, IFN-γ, IL-23, and IL-17. Results In patients with androgenetic alopecia, three monthly CGF injections resulted in significantly reduced serum IL-17 levels. In the psoriatic mouse model, CGF-treated groups exhibited lower PASI scores and improved skin barrier scores compared to controls. Histological analysis revealed enhanced skin characteristics, while RNA sequencing demonstrated downregulated IL-17 and upregulated CD34 expression, as well as improved expression of barrier-related genes. In vitro, the application of CD34 + cells from CGF to keratinocytes led to a significant reduction in TNF-α, IFN-γ, IL-23, and IL-17 levels, indicating strong anti-inflammatory effects. A clinical case of a psoriasis patient unresponsive to IL-23 therapy (Guselkumab) showed significant improvement following CGF treatment. Conclusion These findings indicate that CGF could serve as an effective and versatile treatment for psoriasis, especially for patients who have already undergone biologic therapies but continue to experience resistant lesions.

Abstract This study aimed to design a VEGFR-targeting peptide–drug conjugate with the ability to decrease tumor burden and suppress tumor angiogenesis, and to further evaluate the therapeutic effect of anti-PD-1 antibody in HCC therapy. A VEGFR-targeting peptide VEGF125 − 136 (QR) was conjugated with a lytic peptide (KLU) to form a peptide–drug conjugate QR-KLU. And the efficacy of QR-KLU in combination with anti-PD-1 antibody for HCC therapy in vivo and in vitro were evaluated. QR-KLU inhibited the proliferation and migration of mouse HCC cell line (Hepa1–6) cells under normoxic and hypoxic conditions in a dose-dependent manner. In the subcutaneous Hepa1–6 tumor model, QR-KLU combined with the anti-PD-1 antibody substantially inhibited tumor growth, promoted tumor necrosis, and prolonged the survival time of tumor-bearing mice. QR-KLU substantially inhibited hypoxia-induced expression of VEGF, promoted tumor vascular normalization, and increased cluster of differentiation 8+ (CD8+) T cell infiltration in the tumor. In addition, QR-KLU and anti-PD-1 antibody demonstrated a strong synergistic effect in promoting the activation of intratumoral CD8+ T cells, reducing the expression of immune-inhibitory factors, and increasing the expression of immune-stimulatory factors. This study proposed a novel approach for enhancing the efficacy of anti-PD-1 antibody using a VEGFR-targeting peptide–drug conjugate in HCC therapy.

Abstract Little is known about the prospective association between autosomal mosaic chromosomal alterations (mCAs), a group of large-scale somatic mutations on autosomes, and bladder cancer. Here we utilized data from 99,877 participants who were free of physician-diagnosed cancer at baseline (2004–2008) of the China Kadoorie Biobank to estimate the associations between autosomal mCAs and bladder cancer (ICD-10: C67). A total of 2874 autosomal mCAs events among 2612 carriers (2.6%) were detected. After a median follow-up of 12.4 years, we discovered that participants with all autosomal mCAs exhibited higher risks of bladder cancer, with a multivariable-adjusted hazard ratio (HR) (95% confidence interval [CI]) of 2.60 (1.44, 4.70). The estimate of such association was even stronger for mosaic loss events (HR [95% CI]: 6.68 [2.92, 15.30]), while it was not significant for CN-LOH events. Both expanded (cell fraction ≥10%) and non-expanded autosomal mCAs, as well as mosaic loss, were associated with increased risks of bladder cancer. Of interest, physical activity (PA) significantly modified the associations of autosomal mCAs and mosaic loss (P interaction = 0.038 and 0.012, respectively) with bladder cancer. The increased risks of bladder cancer were only observed with mCAs and mosaic loss among participants with a lower level of PA (HR [95% CI]: 5.11 [2.36, 11.09] and 16.30 [6.06, 43.81]), but not among participants with a higher level of PA. Our findings suggest that peripheral leukocyte autosomal mCAs may represent a novel risk factor for bladder cancer, and PA may serve as a potential intervention target for mCAs carriers.

Abstract Background F-627 (efbemalenograstim alfa) is a novel long acting granulocyte colony-stimulating factor (G-CSF) that contains two human G-CSF fused to a human immunoglobulin G2 (hIgG2) -Fc fragment with a peptide linker. This studyevaluated the efficacy and safety of F-627, also known as efbemalenograstim alfa (Ryzneuta®) in reducing neutropenia compared with filgrastim (GRAN®). Methods This was a multicenter, randomized, open-label, active-controlled non-inferiority study. Two hundred thirty nine (239) patients were enrolled in thirteen centers and received the chemotherapy with epirubicin (100 mg/m2) and cyclophosphamide (600 mg/m2) on day 1 of each cycle for a maximum of four cycles. Patients were randomized to receive either a single 20 mg subcutaneous (s.c.) injection of F-627 on day 3 of each cycle or daily s.c. injection of filgrastim 5 µg/kg/d starting from day 3 of each cycle. The primary endpoint was the duration of grade 3 or 4 neutropenia in cycle 1. The safety profile was also evaluated. Results The mean (SD) duration of grade 3 or 4 neutropenia in cycle 1 was 0.68 (1.10) and 0.71 (0.95) days for the F-627 and the filgrastim groups, respectively. The Hodges-Lehmann estimate of the between-group median difference (F-627 vs filgrastim) in the duration of grade 3 or 4 neutropenia in cycle 1 was 0 day and the upper limit of the one-sided 97.5% CI was 0 day, which was within the prespecified non-inferiority margin of 1-day. Results for all efficacy endpoints in cycles 2 − 4 were consistent with the results in cycle 1, however a trend towards a lower incidence and a shorter duration of grade 3 or 4 neutropenia and grade 4 neutropenia was observed in the F-627 group compared with the filgrastim group. The ANC nadir in the F-627 group was significantly higher than that in the filgrastim group in each cycle. A single fixed dose of F-627 was well tolerated and as safe as standard daily filgrastim. Conclusions A single fixed dose of 20 mg of F-627 in each cycle was as safe and effective as a daily dose of filgrastim 5 µg/kg/d in reducing neutropenia and its complications in patients who received four cycles of EC. Trial registration ClinicalTrials.gov: NCT04174599, on 22/11/2019.

Abstract Plants NADP-malic enzymes (NADP-MEs) act as a class of oxidative decarboxylase to mediate malic acid metabolism in organisms. Despite NADP-MEs have been demonstrated to play pivotal roles in regulating diverse biological processes, the role of NADP-MEs involving in plant growth and development remains rarely known. Here, we characterized the function of rice cytosolic OsNADP-ME2 in regulating plant height. The results showed that RNAi silencing and knock-out of OsNADP-ME2 in rice results in a dwarf plant structure, associating with significant expression inhibition of genes involving in phytohormone Gibberellin (GA) biosynthesis and signaling transduction, but with up-regulation for the expression of GA signaling suppressor SLR1. The accumulation of major bioactive GA1, GA4 and GA7 are evidently altered in RNAi lines, and exogenous GA treatment compromises the dwarf phenotype of OsNADP-ME2 RNAi lines. RNAi silencing of OsNADP-ME2 also causes the reduction of NADP-ME activity associating with decreased production of pyruvate. Thus, our data revealed a novel function of plant NADP-MEs in modulation of rice plant height through regulating bioactive GAs accumulation and GA signaling, and provided a valuable gene resource for rice plant architecture improvement.

MicroRNAs (miRNAs) play an essential regulatory role in plant-virus interaction. However, few studies have focused on the roles of miRNAs and their targets after sugarcane mosaic virus (SCMV) infection in sugarcane. To address this issue, we conducted small RNA (sRNA) and degradome sequencing on two contrasting sugarcanes (SCMV-resistant ‘Fuoguo1’ [FG1] and susceptible ‘Badila’) infected by SCMV at five time points. A total of 1,578 miRNAs were profiled from 30 sRNA libraries, comprising 660 known miRNAs and 380 novel miRNAs. Differential expression analysis of miRNAs revealed that most were highly expressed during the SCMV exponential phase in Badila at 18 h postinfection, with expression profiles positively correlated with virus replication dynamics as observed through clustering. Analysis of degradome data indicated a higher number of differential miRNA targets in Badila compared to FG1 at 18 h postinfection. Gene ontology (GO) enrichment analysis significantly enriched the stimulus-response pathway, suggesting negative regulatory roles to SCMV resistance. Specifically, miR160 upregulated expression patterns and validated in Badila through quantitative real-time PCR (qRT-PCR) in the early stages of SCMV multiplication. Our research provides new insights into the dynamic response of plant miRNA and virus replication and contributes valuable information on the intricate interplay between miRNAs and SCMV infection dynamics. [Graphic: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Abstract Rheumatoid arthritis (RA) is a chronic systemic inflammatory autoimmune disease. However, the relationship between the systemic immune-inflammation index (SII) and the prognosis of RA patients remains unclear. This study aimed to investigate the association between inflammatory biomarker SII and all-cause and cardiovascular mortality in RA patients. A retrospective analysis was conducted using data from the National Health and Nutrition Examination Survey database spanning from 1999 to March 2020. We assessed the association between the SII and all-cause as well as cardiovascular mortality in RA patients employing multivariable Cox proportional hazards regression analysis and restricted cubic spline plots. Receiver operating characteristic curves were employed to evaluate the prognostic capacity of SII in predicting outcomes in both the RA patients and the general population, alongside its predictive performance compared to other markers. This study comprised 2247 RA patients and a control cohort of 29,177 individuals from the general population. Over a 20-year follow-up period, 738 all-cause deaths and 215 deaths attributable to cardiovascular disease were documented in RA patients. We observed a nonlinear positive correlation between the SII and both all-cause and cardiovascular mortality in RA patients. Of significance, at an SII level of 529.7, the hazard ratio reached 1, signifying a transition from low to high mortality risk. Moreover, subgroup analysis did not reveal any potential interactions. Our study findings indicate a nonlinear positive correlation between the inflammatory biomarker SII and both all-cause and cardiovascular mortality in patients with RA.

Abstract Leaf scald, caused by Xanthomonas albilineans, is a severe disease affecting sugarcane worldwide. One of the most practical ways to control it is by developing resistant sugarcane cultivars. It is essential to identify genes associated with the response to leaf scald. A panel of 170 sugarcane genotypes was evaluated for resistance to leaf scald in field conditions for 2 years, followed by a 1-year greenhouse experiment. The phenotypic evaluation data showed a wide continuous distribution, with heritability values ranging from 0.58 to 0.84. Thirteen single nucleotide polymorphisms (SNPs) were identified, significantly associated with leaf scald resistance. Among these, eight were stable across multiple environments and association models. The candidate genes identified and validated based on RNA-seq and qRT-PCR included two genes that encode NB-ARC leucine-rich repeat (LRR)-containing domain disease-resistance protein. These findings provide a basis for developing marker-assisted selection strategies in sugarcane breeding programs.

Abstract Background The management of preoperative blood glucose levels in reducing the incidence of postoperative delirium (POD) remains controversial. This study aims to investigate the impact of preoperative persistent hyperglycemia on POD in geriatric patients with hip fractures. Methods This retrospective cohort study analyzed medical records of patients who underwent hip fracture surgery at a tertiary medical institution between January 2013 and November 2023. Patients were categorized based on preoperative hyperglycemia (hyperglycemia defined as ≥ 6.1mmol/L), clinical classification of hyperglycemia, and percentile thresholds. Multivariate logistic regression and propensity score matching analysis (PSM) were employed to assess the association between different levels of preoperative glucose and POD. Subgroup analysis was conducted to explore potential interactions. Results A total of 1440 patients were included in this study, with an incidence rate of POD at 19.1% (275/1440). Utilizing multiple logistic analysis, we found that patients with hyperglycemia had a 1.65-fold increased risk of experiencing POD compared to those with normal preoperative glucose levels (95% CI: 1.17–2.32). Moreover, a significant upward trend was discerned in both the strength of association and the predicted probability of POD with higher preoperative glucose levels. PSM did not alter this trend, even after meticulous adjustments for potential confounding factors. Additionally, when treating preoperative glucose levels as a continuous variable, we observed a 6% increase in the risk of POD (95% CI: 1-12%) with each 1mmol/L elevation in preoperative glucose levels. Conclusions There exists a clear linear dose-response relationship between preoperative blood glucose levels and the risk of POD. Higher preoperative hyperglycemia was associated with a greater risk of POD. Clinical trial number NCT06473324.

Understanding the effects of microwave irradiation and thermal treatment on the dynamic compression and fragmentation properties of rocks is essential to quantify energy consumption in rock engineering. In this study, Fangshan granite (FG) specimens were exposed to microwave irradiation and heat treatment. The damage of FG specimens induced by these two methods was compared using X-ray CT scanning and ultrasonic wave method. The temperatures of FG after microwave irradiation and thermal treatment were effectively evaluated using a newly proposed technique. A novelty method for precisely determining the geometric features of fragments is developed to estimate the fragmentation energy. Thus, the dynamic uniaxial compressive strength (UCS), the dynamic fragmentation characteristics, and the fragmentation energy of FG after these two pretreatment methods can be reasonably compared. The noticeable distinction of loading rate effect on the dynamic UCS of FG between these two pretreatment methods is first observed. A relationship is established between the dynamic UCS and the damage induced by microwave irradiation and heat treatment. Moreover, fragmentation energy fan analysis is introduced to accurately compare the fragmentation properties of FG after two pretreatment methods in dynamic compression tests.

Abstract Transjugular intrahepatic portosystemic shunt (TIPS) creation using the Viatorr stent remains relatively uncommon in underdeveloped and high-burden disease regions in Asia–Pacific, and there is a lack of comparative studies regarding its prognostic effects compared with the generic stent-graft/bare stent combination. The purpose of this retrospective study is to compare the prognostic endpoints of these two treatments in patients who underwent TIPS creation. Clinical data from 145 patients were collected, including 82 in the combination group and 63 in the Viatorr group. Differences in prognostic endpoints (shunt dysfunction, death, overt hepatic encephalopathy [OHE], rebleeding) between the two groups were analyzed using Kaplan–Meier curves. The Cox proportional hazards model was used to identify independent risk factors for post-TIPS shunt dysfunction. The TIPS procedure was successful in all patients. After TIPS creation, both groups showed a significant decrease in porto-caval pressure gradient compared to that before TIPS creation. The stent patency rates at 6, 12, and 18 months were high in both the combination and Viatorr groups (93.7%, 88.5%, and 88.5% vs. 96.7%, 93.4%, and 93.4%, respectively). The stent patency rates was higher in the combination group than in the Viatorr group, although not statistically significant (HR = 2.105, 95% CI 0.640–6.922, Log-rank P = 0.259). There were no significant differences in other prognostic endpoints (death, OHE, rebleeding) between the two groups. The Cox model identified portal vein diameter (HR = 0.807, 95% CI 0.658–0.990, P = 0.040) and portal vein thrombosis (HR = 13.617, 95% CI 1.475–125.678, P = 0.021) as independent risk factors for post-TIPS shunt dysfunction. The shunt patency rates between the Viatorr stent and the generic stent-graft/bare stent combination showed no significant difference and the generic stent-graft/bare stent combination may be a viable alternative in areas where the Viatorr stent is not yet available.

Abstract The Shuiluo River Catchment (SRC) is the front zone of the southeast compression and uplift of the Tibetan Plateau, with intense tectonic activity. In the basin, a series of regional large NW–SE trending active faults are developed. Studying clearly the geomorphic evolution of the SRC is conducive to further understanding the uplift and expansion mechanism of the SE edge of Tibetan Plateau. Our research was based on geographic information system, numerical analysis tool, and digital elevation model data, to extract six geomorpic parameters (hypsometric integral, asymmetry factor, basin shape ratio, valley floor width–valley height ratio, normalized channel steepness index and index of relative active tectonics) in SRC. After eliminating the impacts of climate, catchments area, and glacier, the geomorphic evolution of the SRC is mainly affected by geological structure and differential tectonic uplift movement; in the upstream and midstream (upper part), the shape of valleys and stream longitudinal profile shapes are affected by lithology; affected by geological structure and tectonic uplift, the tectonic activity in the midstream and downstream is relatively strong, and the intensity of activity in the downstream is stronger than that in the midstream, which may suggest that the faults’ activity in the downstream is stronger; the index of relative active tectonics values of the SRC are consistent with the regional seismic intensity, field-work and low-temperature thermochronology which indicates it is reasonable to use the fluvial geomorphic parameters to study the regional geomorphic evolution. The morphological parameters we extracted show different values in different regions of SRC, which may be the result of differential uplift in the southeastern of the Tibetan Plateau.

In recent years, global forests have faced frequent wildfires due to climate change, leading to significant ecological and economic losses. Traditional fire monitoring technologies like MODIS and VIIRS are often hindered by cloud cover and smoke. This study explores the potential of Global Navigation Satellite System Reflectometry (GNSS-R) for fire monitoring in complex environments. By analyzing cumulative burned areas in southeastern Brazil, a new fire detection method combining GNSS-R with Convolutional Neural Networks (CNN) is proposed to improve accuracy and response time. Results show high agreement between predicted and actual fire areas, with CNN outperforming Random Forest (RF) by 3.3% in prediction accuracy and achieving a 17.4% increase in model fitting. Error analysis indicates no systematic errors, with CNN exhibiting lower fire detection errors and better spatial alignment with actual conditions than RF, which tends to overestimate. This study provides a novel approach to fire detection using GNSS-R, with significant implications for fire prediction and management strategies.

Summary: Pancreatic cancer (PC) is one of the most lethal malignancies and new therapeutic strategies are urgently needed. β1,3-N-acetylglucosaminyltransferase V (B3GNT5) may be a potential option for cancer treatment, but its role in PC remains unknown. In this study, we first demonstrated through bioinformatics analysis that B3GNT5 was high expression in PC and predicted poor prognosis. We further constructed B3GNT5 overexpression or knockdown cell lines by employing lentivirus packaging techniques and confirmed that B3GNT5 could promote tumor cell viability and autonomous growth using cultured cells and vivo xenograft models. In addition, we found that knockdown of B3GNT5 in PC cells inhibited cell migration, invasion, and angiogenesis, as well as stemness of cancer stem cells and enhanced chemotherapy sensitivity to gemcitabine. Mechanistically, overexpression of the transcription factor STAT5B in PC cells enhanced the transcriptional activity of the B3GNT5 promoter. Our work confirmed a tumor-promotive role of B3GNT5 in PC pathogenesis.

Finding water resources is a crucial objective of lunar missions. However, both hydroxyl (OH) and natural water (H2O) have been reported to be scarce on the Moon. We propose a potential method for obtaining water on the Moon through H2O formation via endogenous reactions in lunar regolith (LR), specifically through the reaction FeO/Fe2O3 + H → Fe + H2O. This process is demonstrated using LR samples brought back by the Chang’E-5 mission. FeO and Fe2O3 are lunar minerals containing Fe oxides. Hydrogen (H) retained in lunar minerals from the solar wind can be used to produce water. The results of this study reveal that 51–76 mg of H2O can be generated from 1 g of LR after melting at temperatures above 1,200 K. This amount is ∼10,000 times the naturally occurring OH and H2O on the Moon. Among the five primary minerals in LR returned by the Chang’E-5 mission, FeTiO3 ilmenite contains the highest amount of H, owing to its unique lattice structure with sub-nanometer tunnels. For the first time, in situ heating experiments using a transmission electron microscope reveal the concurrent formation of Fe crystals and H2O bubbles. Electron irradiation promotes the endogenous redox reaction, which is helpful for understanding the distribution of OH on the Moon. Our findings suggest that the hydrogen retained in LR is a significant resource for obtaining H2O on the Moon, which is helpful for establishing a scientific research station on the Moon.

Abstract Neonicotinoid insecticides (NNIs), as a new type of insecticide, are widely used in agriculture and daily life. Because of the low volatility of NNIs, few studies have evaluated them in atmospheric particulate matter. In this study, 101 outdoor PM2.5 samples were collected from the Wuhan urban area from 2019 to 2021, leading to the detection of seven NNIs and three of their metabolites. The detection frequencies of all 10 substances were more than 60%, with DIN (dinotefuran) and IMI (imidacloprid) reaching 100%. DIN (52.4 pg/m3) and IMI (43.0 pg/m3) had higher median concentrations than other substances. Concentration distributions of the four substances ACE (acetamiprid), DIN, IMI, and 5-OH-IMI (5-Hydro-Imidacloprid) exhibited statistically significant differences (P

Abstract Numerous studies establish a significant correlation between autoimmune disorders (AIDs) and prostate cancer (PCa). Our Mendelian randomization (MR) analysis investigates the potential connection between rheumatoid arthritis (RA) and PCa, aiming to confirm causal links between systemic lupus erythematosus (SLE), hyperthyroidism, and PCa. Summary statistics from genome-wide association studies provided data on PCa and three AIDs. MR analysis, using IVW as the main approach, assessed causal relationships, validated by sensitivity analysis. IVW revealed a correlation between genetically anticipated RA and PCa, notably in Europeans (OR = 1.03; 95% CI 1.01–1.04, p = 2*10−5). Evidence supported a lower PCa risk in individuals with SLE (OR = 0.94; 95% CI 0.91–0.97, p = 2*10−4) and hyperthyroidism (OR = 0.02; 95% CI 0.001–0.2, p = 2*10−3). Weighted mode and median confirmed these findings. No pleiotropic effects were observed, and MR heterogeneity tests indicated dataset homogeneity. Our study establishes a causal link between RA, SLE, hyperthyroidism, and PCa.

The cost of building a lunar outpost can be greatly reduced by adopting melting of lunar regolith using concentrated solar energy beam based on in-situ additive manufacturing, there are still considerable obstacles to boosting the compactness and mechanical strength of the fabricated samples. The exploration of optimizing process parameters to address the above challenges are severely limited by solar time and space on Earth. Herein, a system for millimeter-scale energy beam melting of the lunar regolith simulant was set up to investigate the effects of process parameters, including laser power, scanning speed, hatching space (track overlapping ratio), and powder layer thickness (layer overlapping ratio) on the processes of single-track, multi-track, and multi-layer forming. The best range of single-track forming quality is the regular type with linear energy density of 27.5–100 J/mm. The surface is smooth and devoid of apparent fissures when the track overlapping rate is between 20% and 45% during the multi-track scanning procedure. For multi-layer sample forming, Samples with high density and few defects appear in the range of 45%–73% layer overlapping rate. The process parameters window for sample forming is determined by the combination of linear energy density, track overlapping rate, and layer overlapping rate. The relative density of single-track, multi-track, and multi-layer increases sequentially under the action of remelting, reaching 62.9%, 70%, and 86%, respectively. The average compressive strength of the test specimen is 5.6 MPa satisfies the specifications for the load-bearing structures on the moon. These results would provide essential data for the development of in-situ additive manufacturing.

Abstract Background Saccharum spontaneum L. is a closely related species of sugarcane and has become an important genetic component of modern sugarcane cultivars. Stem development is one of the important factors for affecting the yield, while the molecular mechanism of stem development remains poorly understanding in S. spontaneum. Phenylalanine ammonia-lyase (PAL) is a vital component of both primary and secondary metabolism, contributing significantly to plant growth, development and stress defense. However, the current knowledge about PAL genes in S. spontaneum is still limited. Thus, identification and characterization of the PAL genes by transcriptome analysis will provide a theoretical basis for further investigation of the function of PAL gene in sugarcane. Results In this study, 42 of PAL genes were identified, including 26 SsPAL genes from S. spontaneum, 8 ShPAL genes from sugarcane cultivar R570, and 8 SbPAL genes from sorghum. Phylogenetic analysis showed that SsPAL genes were divided into three groups, potentially influenced by long-term natural selection. Notably, 20 SsPAL genes were existed on chromosomes 4 and 5, indicating that they are highly conserved in S. spontaneum. This conservation is likely a result of the prevalence of whole-genome replications within this gene family. The upstream sequence of PAL genes were found to contain conserved cis-acting elements such as G-box and SP1, GT1-motif and CAT-box, which collectively regulate the growth and development of S. spontaneum. Furthermore, quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis showed that SsPAL genes of stem had a significantly upregulated than that of leaves, suggesting that they may promote the stem growth and development, particularly in the + 6 stem (The sixth cane stalk from the top to down) during the growth stage. Conclusions The results of this study revealed the molecular characteristics of SsPAL genes and indicated that they may play a vital role in stem growth and development of S. spontaneum. Altogether, our findings will promote the understanding of the molecular mechanism of S. spontaneum stem development, and also contribute to the sugarcane genetic improving.

Abstract Sugarcane is a vital crop with significant economic and industrial value. However, the cultivated sugarcane’s ultra-complex genome still needs to be resolved due to its high ploidy and extensive recombination between the two subgenomes. Here, we generate a chromosomal-scale, haplotype-resolved genome assembly for a hybrid sugarcane cultivar ZZ1. This assembly contains 10.4 Gb genomic sequences and 68,509 annotated genes with defined alleles in two sub-genomes distributed in 99 original and 15 recombined chromosomes. RNA-seq data analysis shows that sugar accumulation-associated gene families have been primarily expanded from the ZZSO subgenome. However, genes responding to pokkah boeng disease susceptibility have been derived dominantly from the ZZSS subgenome. The region harboring the possible smut resistance genes has expanded significantly. Among them, the expansion of WAK and FLS2 families is proposed to have occurred during the breeding of ZZ1. Our findings provide insights into the complex genome of hybrid sugarcane cultivars and pave the way for future genomics and molecular breeding studies in sugarcane.

Understanding forest health is of great importance for the conservation of the integrity of forest ecosystems. The monitoring of forest health is, therefore, indispensable for the long-term conservation of forests and their sustainable management. In this regard, evaluating the amount and quality of dead wood is of utmost interest as they are favorable indicators of biodiversity. Apparently, remote sensing-based Machine Learning (ML) techniques have proven to be more efficient and sustainable with unprecedented accuracy in forest inventory. However, the application of these techniques is still in its infancy with respect to dead wood mapping. This study, for the first time, automatically categorizing individual coniferous trees (Norway spruce) into five decay stages (live, declining, dead, loose bark, and clean) from combined Airborne Laser Scanning (ALS) point clouds and color infrared (CIR) images using three different ML methods − 3D point cloud-based deep learning (KPConv), Convolutional Neural Network (CNN), and Random Forest (RF). First, CIR colorized point clouds are created by fusing the ALS point clouds and color infrared images. Then, individual tree segmentation is conducted, after which the results are further projected onto four orthogonal planes. Finally, the classification is conducted on the two datasets (3D multispectral point clouds and 2D projected images) based on the three ML algorithms. All models achieved promising results, reaching overall accuracy (OA) of up to 88.8%, 88.4% and 85.9% for KPConv, CNN and RF, respectively. The experimental results reveal that color information, 3D coordinates, and intensity of point clouds have significant impact on the promising classification performance. The performance of our models, therefore, shows the significance of machine/deep learning for individual tree decay stages classification and landscape-wide assessment of the dead wood amount and quality by using modern airborne remote sensing techniques. The proposed method can contribute as an important and reliable tool for monitoring biodiversity in forest ecosystems.

Objective The complex pore throat structure of tight sandstone leads to variable distribution of movable fluid, and the micropore structure and distribution characteristics of movable fluid are the focus of the study of tight sandstone reservoirs. Methods Based on the principle of the nuclear magnetic resonance (NMR) movable fluid test, the classification standard of pore structure of the He 8 reservoir in the Shenmu area was established using centrifugal test, high-pressure mercury injection, scanning electron microscope, X-ray diffraction and casting thin section. The pore structure parameters and pore throat types of the three types of rocks are defined, and a new method for measuring the conversion coefficient suitable for tight sandstone reservoirs was proposed. The distribution characteristics of movable fluid of three types of rocks were also quantitatively evaluated. Results The results reveal that the type Ⅰ and Ⅱ rock pores in the target reservoir are mainly residual intergranular pores with pore diameters greater than 10 μm and dissolution pores with pore diameters greater than 1 μm. The throats are mainly reduced and curved flaky throats, with good pore structure parameters, a high development degree of large pore space, good connectivity between pore throats, and a large amount of movable fluid.Most of the movable fluid occurs in the macropores corresponding to the right peak of the T2 spectrum, while the content of the movable fluid in the small pores corresponding to the left peak is low. The pore structure parameters of type Ⅲ rocks are poor, the percentage of movable fluid is low, and the pore throats are mainly intergranular pores and tube bundle throats. The average conversion coefficient of the target reservoir is 0.029 μm/ms, but the conversion coefficients of type Ⅰ and Ⅱ rocks are less than that of type Ⅲ rocks. The right peak of the T2 spectrum of type Ⅰ and Ⅱ rocks after conversion corresponds to the main peak of the mercury porosimetry pore radius distribution, while the left peak of the T2 spectrum of type Ⅲ rocks corresponds to the main peak of the distribution of mercury porosimetry pore radius. The percentage of movable fluid in the pores of type Ⅰ and type Ⅱ rocks with pore diameters greater than 1 μm is high, which is the main direction of exploration and development in the future. Conclusion The results provide a reference for improving the recovery of tight reservoirs.

Abstract Purpose This study aimed to evaluate the correlation admission albumin levels and 30-day readmission after hip fracture surgery in geriatric patients. Methods In this retrospective cohort study, 1270 geriatric patients admitted for hip fractures to a level I trauma center were included. Patients were stratified by clinical thresholds and albumin level quartiles. The association between admission albumin levels and 30-day readmission risk was assessed using multivariate logistic regression and propensity score-matched analyses. The predictive accuracy of albumin levels for readmission was evaluated by ROC curves. The dose–response relationship between albumin levels and readmission risk was examined. Results The incidence of 30-day readmission was significantly higher among hypoalbuminemia patients than those with normal albumin levels (OR = 2.090, 95%CI:1.296–3.370, p = 0.003). Furthermore, propensity score-matched analyses demonstrated that patients in the Q2(35.0–37.9 g/L) (OR 0.621, 95%CI 0.370–1.041, p = 0.070), Q3(38.0–40.9 g/L) (OR 0.378, 95%CI 0.199–0.717, p

Abstract As a major component of the digestive system malignancies, tumors originating from the hepatic and biliary ducts seriously endanger public health. The kinesins (KIFs) are molecular motors that enable the microtubule-dependent intracellular trafficking necessary for mitosis and meiosis. Normally, the stability of KIFs is essential to maintain cell proliferation and genetic homeostasis. However, aberrant KIFs activity may destroy this dynamic stability, leading to uncontrolled cell division and tumor initiation. In this work, we have made an integral summarization of the specific roles of KIFs in hepatocellular and biliary duct carcinogenesis, referring to aberrant signal transduction and the potential for prognostic evaluation. Additionally, current clinical applications of KIFs-targeted inhibitors have also been discussed, including their efficacy advantages, relationship with drug sensitivity or resistance, the feasibility of combination chemotherapy or other targeted agents, as well as the corresponding clinical trials. In conclusion, the abnormally activated KIFs participate in the regulation of tumor progression via a diverse range of mechanisms and are closely associated with tumor prognosis. Meanwhile, KIFs-aimed inhibitors also carry out a promising tumor-targeted therapeutic strategy that deserves to be further investigated in hepatobiliary carcinoma (HBC).

Networks haven been widely used to understand the spread of infectious disease. This study examines the properties of small-world networks in modeling infectious disease on campus. Two different small-world models are developed and the behaviors of infectious disease in the models are observed through numerical simulations. The results show that the behavior pattern of infectious disease in a small-world network is different from those in a regular network or a random network. The spread of the infectious disease increases as the proportion of long-distance connections p increasing, which indicates that reducing the contact among people is an effective measure to control the spread of infectious disease. The probability of node position exchange in a network (p2) had no significant effect on the spreading speed, which suggests that reducing human mobility in closed environments does not help control infectious disease. However, the spreading speed is proportional to the number of shared nodes (s), which means reducing connections between different groups and dividing students into separate sections will help to control infectious disease. In the end, the simulating speed of the small-world network is tested and the quadratic relationship between simulation time and the number of nodes may limit the application of the SW network in areas with large populations.

AbstractHoney adulteration has been on the rise with the increasing demand for high-quality honey, and the authentication of A. cerana honey is a major problem that the current bee industry needs to solve. The aim of this research was to establish the proofreading enzyme-mediated probe cleavage combined with ladder-shape melting temperature isothermal amplification (Proofman-LMTIA) method for the authentication of Apis cerana honey. The LMTIA primers were designed to target the specific 18S rRNA sequence of A. cerana, and the conditions for Proofman-LMTIA amplification were optimized. The specificity and sensitivity of the method were determined and compared with that of the droplet digital polymerase chain reaction (PCR). The optimal temperature of the established Proofman-LMTIA method was 62 °C. The method can specially to detect the A. cerana gene without cross-reactivity with the genomes from other animal and plant species, and the amplification reaction can be finished within 20 min with the sensitivity of 10 pg A. cerana genomic DNA, which was more sensitive than the droplet digital PCR method. The obtained results demonstrate that the established Proofman-LMTIA procedure was specific, sensitive, and rapid, and can be used for authentication of A. cerana honey.

ABSTRACTHoney adulteration has been on the rise with the increasing demand for high-quality honey. The ladders-shape melting temperature isothermal amplification (LMTIA) was a newly developed nucleic acid amplification technique, and the aim of this study was to establish a method combining the LMTIA with the proofreading enzyme-mediated probe cleavage (Proof-man probe) for detecting the thaumatin-like protein (TLP) genes of Brassica rapa var. oleifera in honey. The LMTIA primers was selected as a target to be designed, the temperature of the Proof-man LMTIA reaction was optimized, and the specificity, sensitivity, and applicability to the honey samples were determined. The results showed that the Proof-man LMTIA method was highly specific with a detection sensitivity of 30-40 copies genomic DNA/reaction at the optimal temperature of 60°C, and the amplification could be completed within 20 min. This method can detect the adulteration of low-price B. rapa honey into high-price honey.

Abstract The purpose of epilepsy detection is to determine whether epilepsy has occurred by analysing the patient's electroencephalogram (EEG) signals. Compared to traditional methods, epilepsy detection methods based on deep learning have achieved significant improvements in detection accuracy. However, when the number of training samples is limited, the model's detection performance often significantly declines. To address this issue, here a sample enhancement method based on electroencephalogram signal channel swapping is proposed. This method generates new electroencephalogram samples by exchanging electroencephalogram sequences from different channels, thereby expanding the training set and improving epilepsy detection accuracy in few‐shot scenarios. Experiments using the Children's Hospital Boston and the Massachusetts Institute of Technology (CHB‐MIT) dataset show that for training sets with 100, 500, and 1000 samples, detection accuracy improves from 0.6797 to 0.7789, 0.6952 to 0.8210, and 0.7273 to 0.8517, respectively. Compared to the sliding window method, the proposed method demonstrates higher accuracy in extreme low sample sizes. Combining both methods can further enhances detection performance, showing an improvement of approximately 8% across various configurations.

PurposePostoperative urinary tract infections (UTIs) worsen the prognosis of elderly patients with hip fractures. This study aimed to assess the predictive ability of blood-based biomarkers, specifically the glucose-albumin ratio (GAR), in predicting postoperative UTIs.MethodsA retrospective observational study of 1,231 patients from a Level I trauma center was conducted. We evaluated the prognostic and predictive value of 15 biomarkers, including the glucose-albumin ratio, in elderly patients with hip fractures. The primary outcome measure was the incidence of postoperative UTIs.ResultsThe glucose to albumin ratio transformed into GAR was superior to any other biomarker in predicting postoperative UTIs in elderly hip fracture patients (AUC = 0.756, p < 0.001). Elevated GAR (using the best cut-off value of 0.18) was independently associated with postoperative UTIs (OR 3.20, 95% CI 2.23–4.58). Further analysis dividing GAR levels into four groups according to quartiles showed that compared to patients with GAR levels of Q1 (< 0.14), GAR levels of Q2 (0.14–0.17; OR 2.11, 95% CI 1.07–4.15), Q3 (0.17–0.21; OR 3.36, 95% CI 1.74–6.52) and Q4 (> 0.21; OR 7.55, 95% CI 3.84–14.83) patients had significantly higher odds of UTIs.ConclusionGAR holds potential as a novel biomarker for predicting postoperative UTIs in elderly patients with hip fractures.

Super-agile satellites with dynamic imaging capabilities can significantly improve the imaging efficiency of space-borne Earth observation. However, the image modulation transfer function (image MTF) of dynamic imaging varies dramatically with changes in the attitude maneuver status while improving observation efficiency. Therefore, both the observation efficiency and image MTF should be considered in the imaging mission planning of super-agile satellites. Existing imaging mission planning methods are mainly aimed at traditional agile satellites that are not capable of dynamic imaging, and the mainly optimization objectives are coverage revenue, spatial resolution, and task performance time, without considering the observation efficiency and image MTF as the optimization objectives. To overcome the problem of image MTF degradation caused by dynamic imaging, a mission planning method which considers the degradation of the image MTF and observation efficiency was proposed. Firstly, a mapping relationship between the angular velocity of the attitude maneuvering and the image MTF was constructed. On this basis, a Pareto multi-objective imaging mission planning model of partial order based was established. Considering the particularity of the model, the non-dominated sorting strategy of the NSGA-II algorithm was redesigned when solving the model using NSGA-II algorithm. Finally, the imaging tasks of different scales in single satellite and multi-satellite simulation scenes were set, and the proposed imaging mission planning method was verified. The planning results showed that the proposed method can achieve a balanced optimization of the image MTF and task efficiency under the premise of ensuing maximum observation coverage revenue.

Biliary atresia (BA) is a severe and progressive biliary obstructive disease in infants that requires early diagnosis and new therapeutic targets. This study employed bioinformatics methods to identify diagnostic biomarkers and potential therapeutic targets for BA. Our analysis of mRNA expression from Gene Expression Omnibus datasets revealed 3,273 differentially expressed genes between patients with BA and those without BA (nBA). Weighted gene coexpression network analysis determined that the turquoise gene coexpression module, consisting of 298 genes, is predominantly associated with BA. The machine learning method then filtered out the top 2 important genes, CXCL8 and TMSB10, from the turquoise module. The area under receiver operating characteristic curves for TMSB10 and CXCL8 were 0.961 and 0.927 in the training group and 0.819 and 0.791 in the testing group, which indicated a high diagnostic value. Besides, combining TMSB10 and CXCL8, a nomogram with better diagnostic performance was built for clinical translation. Several studies have highlighted the potential of CXCL8 as a therapeutic target for BA, while TMSB10 has been shown to regulate cell polarity, which was related to BA progression. Our analysis with qRT PCR and immunohistochemistry also confirmed the upregulation of TMSB10 at mRNA and protein levels in BA liver samples. These findings highlight the sensitivity of CXCL8 and TMSB10 as diagnostic biomarkers and their potential as therapeutic targets for BA.

IntroductionPorcine reproductive and respiratory syndrome virus (PRRSV) causes substantial economic losses in the global swine industry. The current vaccine options offer limited protection against PRRSV transmission, and there are no effective commercial antivirals available. Therefore, there is an urgent need to develop new antiviral strategies that slow global PRRSV transmission.MethodsIn this study, we synthesized a dicoumarol-graphene oxide quantum dot (DIC-GQD) polymer with excellent biocompatibility. This polymer was synthesized via an electrostatic adsorption method using the natural drug DIC and GQDs as raw materials.ResultsOur findings demonstrated that DIC exhibits high anti-PRRSV activity by inhibiting the PRRSV replication stage. The transcriptome sequencing analysis revealed that DIC treatment stimulates genes associated with the Janus kinase/signal transducer and activator of transcription (JAK/STAT) signalling pathway. In porcine alveolar macrophages (PAMs), DIC-GQDs induce TYK2, JAK1, STAT1, and STAT2 phosphorylation, leading to the upregulation of JAK1, STAT1, STAT2, interferon-β (IFN-β) and interferon-stimulated genes (ISGs). Animal challenge experiments further confirmed that DIC-GQDs effectively alleviated clinical symptoms and pathological reactions in the lungs, spleen, and lymph nodes of PRRSV-infected pigs.DiscussionThese findings suggest that DIC-GQDs significantly inhibits PRRSV proliferation by activating the JAK/STAT signalling pathway. Therefore, DIC-GQDs hold promise as an alternative treatment for PRRSV infection.

The precise and automated detection of epileptic seizures has become a focal point of research due to its potential to alleviate the severe consequences experienced by patients. Recent advancements in deep learning-based detection techniques utilizing electroencephalogram (EEG) signals have yielded state-of-the-art performance. However, these methods typically require a large number of training samples to effectively train the deep neural networks. Consequently, their performance can be compromised in scenarios where only a limited number of samples are available. This paper presents two novel approaches that aim to improve seizure detection accuracy in situations with a scarcity of data by harnessing the power of empirical mode decomposition (EMD) applied to EEG signals. Specifically, in both methods, the EMD of EEG signals and the power spectral density (PSD) of the resulting EMD components are employed as inputs for subsequent neural networks. Multiple convolutional neural networks (CNNs) are purposefully designed to perform seizure detection using these inputs. Experimental results demonstrate that our proposed methods achieve superior detection accuracy compared to traditional deep learning-based detection methods that do not incorporate EMD in few-shot scenarios. In particular, when the number of training samples is reduced to 10%, our method shows an improvement of 23%, 19%, and 26% in accuracy, sensitivity, and specificity, respectively, compared to the original EEG input across different networks.

Abstract Objective This study aimed to systematically assess the incidence and risk factors for hospital-acquired pneumonia (HAP) in hip fracture patients by meta-analysis. Methods Systematically searched four English databases (PubMed, EMBASE, The Cochrane Library, and Web Of Science) and four Chinese databases (CNKI, CQVIP, Sinomed, and WAN FANG) from inception until 20 November 2023. All studies involving risk factors of HAP in patients with hip fractures were considered. Newcastle-Ottawa Scale was used to evaluate the quality of the included studies. The results were presented with the pooled odds ratio (OR) and 95% confidence interval (95% CI). Results Of 35 articles (337,818 patients) included in this study, the incidence of HAP was 89 per 1000 cases. Twenty-three risk factors were eventually involved in the meta-analysis, and 21 risk factors were significant. Our study has identified four significant risk factors (advanced age, preoperative time, COPD, and hypoalbuminemia) associated with HAP, as follows: Advanced age as a continuous variable (OR 1.07, 95% CI 1.05–1.10), Advanced age > 70 years (OR 2.34, 95% CI 1.77–3.09), Advanced age > 80 years (OR 2.98, 95% CI 2.06–4.31), Chronic obstructive pulmonary disease (COPD) (OR 3.44, 95% CI 2.83–4.19), Time from injury to operation as a continuous variable (OR 1.09, 95% CI 1.07–1.12), Time from injury to operation ≥48 h (OR 3.59, 95% CI 2.88–4.48), Hypoalbuminemia

The output of new energy represented by wind power and photovoltaic power features volatility and randomness. It is a practical approach to use the guaranteed rate with statistical characteristics to analyze the output coefficient of new energy. However, there is a lack of analysis and demonstration on the value of the new energy output guaranteed rate. To solve this problem, a selection method for the new energy output guaranteed rate considering optimal energy storage configuration is proposed. First, the influence of the new energy output guaranteed rate on the new energy output coefficient is analyzed. Secondly, with the goal of minimizing the comprehensive costs, an optimal configuration model of energy storage based on the output guaranteed rate of new energy is constructed, and particle swarm optimization is used for the optimization solution. Then, according to the optimal energy storage configuration results under different guaranteed rates, a reasonable new energy output guaranteed rate is determined by maximizing the comprehensive benefits obtained from energy storage. Finally, an example applied to the power grid in an area of Guangdong in Southern China is provided to illustrate the effectiveness of the proposed method.

Generator tripping scheme (GTS) is the most commonly used scheme to prevent power systems from losing safety and stability. Usually, GTS is composed of offline predetermination and real-time scenario match. However, it is extremely time-consuming and labor-intensive for manual predetermination for a large-scale modern power system. To improve efficiency of predetermination, this paper proposes a framework of knowledge fusion-based deep reinforcement learning (KF-DRL) for intelligent predetermination of GTS. First, the Markov Decision Process (MDP) for GTS problem is formulated based on transient instability events. Then, linear action space is developed to reduce dimensionality of action space for multiple controllable generators. Especially, KF-DRL leverages domain knowledge about GTS to mask invalid actions during the decision-making process. This can enhance the efficiency and learning process. Moreover, the graph convolutional network (GCN) is introduced to the policy network for enhanced learning ability. Numerical simulation results obtained on New England power system demonstrate superiority of the proposed KF-DRL framework for GTS over the purely data-driven DRL method.

This is an essay in the field of mineral processing engineering. Fluorite and calcite are calcium-bearing minerals with similar physical and chemical properties. Flotation separation of the two minerals has always been one of the difficult problems in the ore processing field. The effect of Fe3+ on flotation separation of fluorite and calcite in sodium silicate system and its mechanism was studied by flotation test, adsorption amount measurement, Zeta potential measurement and chemical calculation of flotation solution. The flotation test results show that, compared with sodium silicate, the addition of Fe3+ has a stronger inhibition effect on the flotation of calcite, but little effect on the flotation of fluorite, which can achieve the selective separation of the two minerals. The results of adsorption amount measurement, Zeta potential measurement and chemical calculation of flotation solution showed that after introducing Fe3+ into the sodium silicate system, Fe-(OH)X, Fe-sodium silicate polymer and Si(OH)4 were selectively adsorbed on the surface of calcite, which hindered the further adsorption of sodium oleate as collector, thus achieving the separation of fluorite and calcite.

This is an essay in the field of mineral processing engineering. In China, fluorite mainly exists in the form of concomitant deposits. In the flotation process, other useful minerals are usually preferentially floated, and a large amount of fluorite exists in tailings. In this paper, the restrained fluorite and calcite in the floating tungsten tailings are taken as objects, and ultrasonic wave is added to change the floatability of the two, so as to explore a method to optimize the comprehensive utilization level of fluorite in the floating tungsten tailings. After ultrasonic pretreatment of pulp inhibited by sodium humate for 39 min, the flotation recovery of fluorite reached 84.74%, while the flotation recovery of calcite was only 11.47%, with a difference of 73.27%. Exploring the mechanism of ultrasonic pretreatment, it is found that the absorption intensity of sodium humate on the surface of fluorite is lower than that of calcite in the infrared spectrum detection. Ultrasonic pretreatment can desorb the sodium humate on the surface of fluorite, increase the absorption amount of sodium oleate on the surface, and make the zeta potential move forward; In addition, ultrasonic pretreatment mainly affects the content of sodium humate on the mineral surface, but does not affect the content of sodium oleate on the mineral surface. If only sodium humate exists in the slurry system during ultrasonic pretreatment, the sodium humate desorption speed is faster, which is more conducive to adsorbing the sodium oleate added subsequently.

Technological advances have dramatically improved precision agriculture, and accurate crop classification is a key aspect of precision agriculture (PA). The flexibility and real-time nature of UAVs have led them to become an important tool for acquiring agricultural data and enabling precise crop classification. Currently, crop identification relies heavily on complex high-precision models that often struggle to provide real-time performance. Research on lightweight models specifically for crop classification is also limited. In this paper, we propose a crop classification method based on UAV visible-light images based on PP-LiteSeg, a lightweight model proposed by Baidu. To improve the accuracy, a pyramid pooling module is designed in this paper, which integrates adaptive mean pooling and CSPC (Convolutional Spatial Pyramid Pooling) techniques to handle high-resolution features. In addition, a sparse self-attention mechanism is employed to help the model pay more attention to locally important semantic regions in the image. The combination of adaptive average pooling and the sparse self-attention mechanism can better handle different levels of contextual information. To train the model, a new dataset based on UAV visible-light images including nine categories such as rice, soybean, red bean, wheat, corn, poplar, etc., with a time span of two years was created for accurate crop classification. The experimental results show that the improved model outperforms other models in terms of accuracy and prediction performance, with a MIoU (mean intersection ratio joint) of 94.79%, which is 2.79% better than the original model. Based on the UAV RGB images demonstrated in this paper, the improved model achieves a better balance between real-time performance and accuracy. In conclusion, the method effectively utilizes UAV RGB data and lightweight deep semantic segmentation models to provide valuable insights for crop classification and UAV field monitoring.

The control of soft surrounding rock stability has always been a hot academic issue. Soft rock has poor stability and low strength, and the deformation of a soft rock tunnel becomes more serious after it is affected by water for a long time. In this paper, the Jintong Coal Mine is taken as the research object, and nondestructive immersion experiments are used to study the change in mechanical properties of rock after being affected by water. The FLAC numerical model is used to analyze the stress evolution characteristics of the surrounding rock after being affected by water, and the results of the study show that the water absorption of siltstone is always higher than that of coarse-grained sandstone, and the uniaxial compressive strength of siltstone and coarse-grained sandstone decreases by 54.59% and 67.99%, respectively, under a state of saturated water compared with that under a state of dryness. Influenced by a T-shaped surface, the maximum principal stress concentration area occurs in the rock layer below the T-shaped surface and outside the joint. Concentrations of maximum shear stress occur within the “T” channel. Vertical stress concentration zones occur at the higher ground level and the bottom of the slope. The maximum shear stress of the roof fluctuates before the face reaches the surface of the “1” section, and continues to increase with and continues to increase with the distance of the face. After entering below the surface of the “1” section, the maximum shear stress of the roof increases rapidly, and the influence range is about 24 m. The maximum shear stress distribution plays a dominant role in the stability of the surrounding rocks of the two roadways. We analyze the principle of high-strength economic support, propose a “four-in-one” surrounding rock control technology based on “controlled hydrophobicity, structural adjustment, district management, and gradient control”, and propose a surrounding rock control scheme of district management. The measured data on site show that the roadway surrounding the rock is reasonably controlled. This provides a reference for the stable control of the surrounding rock of the roadway under similar conditions.

Preharvest crop yield estimation is crucial for achieving food security and managing crop growth. Unmanned aerial vehicles (UAVs) can quickly and accurately acquire field crop growth data and are important mediums for collecting agricultural remote sensing data. With the rapid development of machine learning, especially deep learning, research on yield estimation based on UAV remote sensing data and machine learning has achieved excellent results. This paper systematically reviews the current research of yield estimation research based on UAV remote sensing and machine learning through a search of 76 articles, covering aspects such as the grain crops studied, research questions, data collection, feature selection, optimal yield estimation models, and optimal growth periods for yield estimation. Through visual and narrative analysis, the conclusion covers all the proposed research questions. Wheat, corn, rice, and soybeans are the main research objects, and the mechanisms of nitrogen fertilizer application, irrigation, crop variety diversity, and gene diversity have received widespread attention. In the modeling process, feature selection is the key to improving the robustness and accuracy of the model. Whether based on single modal features or multimodal features for yield estimation research, multispectral images are the main source of feature information. The optimal yield estimation model may vary depending on the selected features and the period of data collection, but random forest and convolutional neural networks still perform the best in most cases. Finally, this study delves into the challenges currently faced in terms of data volume, feature selection and optimization, determining the optimal growth period, algorithm selection and application, and the limitations of UAVs. Further research is needed in areas such as data augmentation, feature engineering, algorithm improvement, and real-time yield estimation in the future.

As the scale of the marine economy continues to expand, the problems of environmental pollution and the over-exploitation of marine resources have become increasingly severe. The purpose of this study is to realize the sustainable growth of the marine economy, the rational utilization of resources, and the coordinated development of environmental protection. Method: This research first adopts the system dynamics (SD) model. It then uses the entropy method to weigh the evaluation indicators and create a coupling coordination degree (CCD) assessment simulation of the marine economic–resource–ecological environment. We use the created SD model to build and simulate four standard scenarios: current, economic, resource, and environmental. Finally, we propose suitable recommendations for the long-term development of the marine economy based on the coordination evaluation results of the CCD model. Results: Results show the following: (1) In the immediate term, the economic scenario is poorly coordinated, whereas the environmental scenario is more effectively coordinated. However, in the long-term development process, the resource scenario is reasonably well coordinated. (2) Priority attention must be given to improving the energy mix and protecting the natural environment to promote the sustainable development of the marine economy. (3) To achieve a virtuous cycle between marine economic development and environmental protection, governments, businesses, and all sectors of society need to work together to formulate and implement relevant policies and initiatives.

To improve the resource utilization of dredged silt and industrial waste, this study explores the efficacy of using ground granulated blast furnace slag (GGBS), active calcium oxide (CaO), and sodium silicate (Na2O·nSiO2) as alkali activators for silt stabilization. Through a combination of addition tests, response surface method experiments, and microscopic analyses, we identified key factors influencing the unconfined compressive strength (UCS) of stabilized silt, optimized material ratios, and elucidated stabilization mechanisms. The results revealed the following: (1) CaO exhibited the most pronounced stabilization effect, succeeded by Na2O·nSiO2, whereas GGBS alone displayed marginal efficacy. CaO-stabilized silt demonstrated rapid strength augmentation within the initial 7 d, while Na2O·nSiO2-stabilized silt demonstrated a more gradual strength enhancement over time, attributable to the delayed hydration of GGBS in non-alkaline conditions, with strength increments noticeably during later curing phases. (2) Response surface analysis demonstrated substantial interactions among GGBS-CaO and GGBS-Na2O·nSiO2, with the optimal dosages identified as 11.5% for GGBS, 4.1% for CaO, and 5.9% for Na2O·nSiO2. (3) X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses clarified that the hydration reactions within the GGBS-Na2O·nSiO2 composite cementitious system synergistically enhanced one another, with hydration products wrapping, filling, and binding the silt particles, thereby rendering the microstructure denser and more stable. Based on these experimental outcomes, we propose a microstructural mechanism model for the stabilization of dredged silt employing GGBS-CaO-Na2O·nSiO2.

BackgroundThis study aims to discern the significance of common hematological and biochemical parameters for predicting urinary tract infections in geriatric patients with hip fractures.MethodsMultivariable logistic regression and propensity score-matched analyses were conducted to calculate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for UTIs. The abilities of these parameters to predict UTIs were evaluated by receiver operating characteristic (ROC) curves. Dose–response relationships were assessed by categorizing hematological and biochemical parameters into quartiles. Subgroup analyses were further explored to investigate the relationship between these parameters and urinary tract infections.ResultsOut of the 1,231 participants, 23.2% were diagnosed with UTIs. Hyperglycemia, hypoproteinemia and hyperglobulinemia were risk factors for UTIs in multivariate analysis. After propensity score matching, hyperglycemia (OR 2.14, 95% CI 1.50–3.05, p

IntroductionField wheat ear counting is an important step in wheat yield estimation, and how to solve the problem of rapid and effective wheat ear counting in a field environment to ensure the stability of food supply and provide more reliable data support for agricultural management and policy making is a key concern in the current agricultural field.MethodsThere are still some bottlenecks and challenges in solving the dense wheat counting problem with the currently available methods. To address these issues, we propose a new method based on the YOLACT framework that aims to improve the accuracy and efficiency of dense wheat counting. Replacing the pooling layer in the CBAM module with a GeM pooling layer, and then introducing the density map into the FPN, these improvements together make our method better able to cope with the challenges in dense scenarios.ResultsExperiments show our model improves wheat ear counting performance in complex backgrounds. The improved attention mechanism reduces the RMSE from 1.75 to 1.57. Based on the improved CBAM, the R2 increases from 0.9615 to 0.9798 through pixel-level density estimation, the density map mechanism accurately discerns overlapping count targets, which can provide more granular information.DiscussionThe findings demonstrate the practical potential of our framework for intelligent agriculture applications.

Abstract Limestone forests are an unusual habitat for primates, especially fragmented limestone habitats. However, while some research has been conducted on François' langurs (Trachypithecus francois) in these habitats, there is still a need to improve the understanding of their behavioral adaptations to the fragmented limestone habitat. We collected data on the diet of François' langurs in a fragmented limestone habitat in Encheng National Nature Reserve, southwestern Guangxi, China using instantaneous scanning sampling, and their feeding adaptations to the fragmented forest were examined. The results indicated that a total of 101 species of plants were consumed by the langurs. They also fed on two non‐plant components, including cliff minerals and at least one species of insect. The langurs ate a higher number of food species in Encheng when compared with the other geographic populations, and they maintained a high level of food diversity and ate more vines. Moreover, they were highly selective in their use of vegetation in their home range, and fewer plants provided a high‐quality food source. During the season when food resources were scarce, the consumption of fruits and young leaves decreased as their availability decreased. This led to the use of other food components, such as mature leaves and seeds. The findings support that François' langurs adjust their feeding behavior to cope with seasonal and micro‐variations in their dietary requirements and to adapt to their particular environment.