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Spherical steel bearings play an important role in the normal longitudinal expansion of the main girders of long-span bridges. With the increase in service time, the wear damage will deteriorate the longitudinal slip performance of spherical steel bearings. In this research, a method of real-time quantitative evaluation on longitudinal slip performance is proposed through monitoring data analysis, correlation analysis, damage evaluation analysis, and experiment data analysis. Monitoring data analysis shows that the temperature field has a good linear relationship with longitudinal displacement. Correlation analysis shows that this relationship is well described by a time-varying multiple linear regression model. Furthermore, bearing friction is used as an index for real-time quantitative evaluation, and a large value of bearing friction indicates serious damage. An evaluation model considering the influence of temperature field and bearing frictions is proposed. The time-varying values of bearing frictions are calculated through Kalman filtering analysis. Experimental results show that the maximum evaluation error of this method is less than 5%, verifying that the proposed method is feasible for real-time quantitative evaluation on the longitudinal slip performance of bridge bearings.

Abstract Background Typical chronic myelogenous leukemia (CML) is a myeloproliferative neoplasm caused by t(9; 22)(q34; q11) translocation. This chromosomal translocation forms the BCR::ABL1 fusion gene. The tyrosine kinase encoded by the BCR::ABL1 is considered to be the main pathogenic diver. BCR::ABL1 is not only a therapeutic target, but also a monitoring target. Monitoring of BCR::ABL1 reveals the progression of the disease and guides the next treatment. Now for CML, the target of treatment has been focused on treatment‐free remission (TFR). Methods We conducted a literature review of current developments of treatment‐free remission and molecular monitoring methods. Results More effective and sensitive CML monitoring methods such as digital droplet PCR (ddPCR) and next generation sequencing (NGS) have further studied the measurable residual disease (MRD) and clonal heterogeneity, which provides strong support for the exploration of TFR. We discussed some of the factors that may be related to TFR outcomes at the molecular level, along with some monitoring strategies. Conclusion Currently, predictive indicators for treatment‐free remission outcomes and recurrence are lacking in clinical practice. In future, treatment‐free remission research should focus on combining the clinical indicators with molecular monitoring and biological markers to personalize patient conditions and guide clinicians to develop individualized treatment plans, so that more patients with CML can achieve safer and stabler treatment‐free remission.

Abstract Precise control of exciton confinement in metal halide perovskites is critical to the development of high‐performance, stable optoelectronic devices. A significant hurdle is the swift completion of ionic metathesis reactions, often within seconds, making consistent control challenging. Herein, the introduction of different steric hindrances in a Cs+ sublattice within CsYb2F7 is reported, which effectively modulates the reaction rate of Cs+ with lead (Pb2+) and halide ions in solution, extending the synthesis time for perovskite nanostructures to tens of minutes. Importantly, the Cs+ sublattice provides a crystal facet‐dependent preference for perovskite growth and thus exciton confinement, allowing the simultaneous occurrence of up to six emission bands of CsPbBr3. Moreover, the rigid CsYb2F7 nano template offers high activation energy and enhances the stability of the resulting perovskite nanostructures. This methodology provides a versatile approach to synthesizing functional heterostructures. Its robustness is demonstrated by in‐situ growth of perovskite nanostructures on Cs+‐mediated metal‐organic frameworks.

Coridius chinensis is a traditional insect medicine in China. It is the dried whole insect of Coridius chinensis (Dallas) form the Pentatomidae family. Modern medical and pharmaceutical studies have successfully isolated and identified over 100 natural small molecular compounds from Coridius chinensis. These studies have also confirmed its various pharmacological activities, including analgesic, antioxidant, anticancer, anticoagulant, and antibacterial properties. Coridius chinensis is commonly used in traditional Chinese medicine preparations to treat impotence, hemangioma, pain and other diseases. However, more research is needed to fully explore the pharmacological effects of this herbal medicine. This paper aims to summarize both domestic and international research literature on Coridius chinensis, focusing on its main components, pharmacological activity and clinical application. The findings will provide valuable references for further research and development of Coridius chinensis as a traditional Chinese medicine resource.

Abstract Gastric‐type endocervical adenocarcinoma (GEA) is the second most common subtype of endocervical adenocarcinoma and has a poor prognosis. Anti‐programmed death‐1 and anti‐programmed death‐ligand 1 (PD‐L1) inhibitors have emerged as a major treatment option for GEA; however, data on the expression of other immune checkpoints in GEA are limited. We analyzed the expression of T‐cell immunoglobulin and mucin‐domain containing‐3 (TIM‐3) and B7 homolog 3 protein (B7‐H3) in 58 GEA and investigated their prognostic significance as well as association with PD‐L1 expression and other known prognostic factors. Applying the tumor proportion score (TPS) with a cutoff of 1%, B7‐H3 and TIM‐3 were present in 48.3% and 17.2% of cases, respectively. Applying the combined positive score (CPS) with a cutoff of 1, TIM‐3 expression was present in 70.7% of cases. Moreover, the expression of three checkpoints (B7‐H3, TIM‐3, and PD‐L1) was incompletely overlapping. Patients with B7‐H3 positive tumors (by TPS) or TIM‐3 positive tumors (by TPS) had significantly worse recurrence‐free survival (RFS) and overall survival (OS) (log‐rank). Using CPS, patients with TIM‐3 positive tumors showed significantly worse RFS (log‐rank). Similarly, B7‐H3 positivity (by TPS) and TIM‐3 positivity (by TPS) were associated with worse RFS and OS in univariate analysis. TIM‐3 positivity (by CPS) was associated with worse RFS in univariate analysis and the final Cox multivariate analysis. In conclusion, our results show that (1) B7‐H3 and TIM‐3 are frequently expressed in GEA and their expression overlaps incompletely with PD‐L1; and (2) both B7‐H3 and TIM‐3 are independent negative prognostic markers in GEA.

Summary: Endoplasmic reticulum membrane protein complex subunit 6 (EMC6) plays an important function in both physiological and pathological states of cells. Nevertheless, there are few studies focused on the role of EMC6 in tumors. At first, we performed a series of bioinformatics analyses on 33 kinds of cancers, including differential expression analysis, tumor mutational burden analysis, prognostic analysis, and clinicopathological staging analysis. Then, we corroborated the important role of EMC6 in lung cancer by cytological and in vivo experiments. We found that the reduction of EMC6 expression did effectively inhibit the proliferation, invasion, and metastasis of A549. Finally, EMC6 is indeed involved in the regulation of ferroptosis, cuproptosis, and immune response in LUAD. In a word, our study not only comprehensively analyzed the functional mechanisms of EMC6 in all cancers but also validated the regulatory role of EMC6 in lung cancer for the first time.

Objectives: To investigate the efficacy and safety of nimotuzumab (NTZ) combined with concurrent chemo-radiotherapy (CCRT) in induction chemotherapy (IC) resistant locally advanced nasopharyngeal carcinoma (LANPC). Materials and methods: A single-arm, open-label phase II clinical trial was conducted (NCT04508816). Eligible patients were 18–70 years old, pathologically confirmed NPC at stage III-IVA, stable disease or progressive disease after IC by imaging evaluation, and ECOG performance status with 0–1. All patients received intensity-modulated radiotherapy (IMRT) concurrent with chemotherapy and NTZ (200 mg/w). The primary endpoint was progression-free survival (PFS). The secondary endpoints were overall survival (OS), objective response rate (ORR) and safety. Results: From May 2015 to July 2020, 56 NPC patients were enrolled. With the median follow-up of 34 months (range from 8 to 77 months), the 3-year and 5-year PFS and OS rates were 79.3 % and 72.1 %, 94.0 % and 87.2 %, respectively. ORR of the nasopharynx and cervical lymph nodes involvement were 98.2 % and 98.1 % three months after IMRT. Univariate analysis revealed that pretreatment PET/CT was the factor that influenced PFS (P = 0.038). Patients treated with ≥6 weeks of NTZ showed improved 3‐year PFS rate (83.0% vs. 73.9 %, P > 0.05) and 5-year PFS rate (83.0% vs. 61.6 %, P>0.05) compared with

Following the final biological treatment, the oil wastewater is intended for reuse in factory floor cleaning. However, the presence of varying concentrations of oil-in-iron characteristic wastewater has led to a sudden surge in sludge SV to 90%, adversely affecting water treatment efficiency. In this study, we conducted an analysis of microbial community structure and selected pepA and 16S rRNA primers to assess the proportions of zoogloea and total bacteria in sludge bulking. Iron concentration plays a pivotal role, and it should be maintained at or 0.6 mgL−1. By selective discharging of sludge to maintain 1,700 mgL−1, we minimized iron enrichment, thereby enhancing the sludge settling performance. Maintaining dissolved oxygen (DO) at 3.5 mgL−1 supports the aerobic sludge's ability to replenish iron in its system, while the oil content should be controlled at 145.33 mgL−1 to reduce the release of iron into the water. The order of significance is as follows: sludge concentration > Fe amount > DO > oil content. Implementing this approach was applied in the field for 1 week and effectively reduced the SV from 90% to approximately 43%. The interaction between quorum sensing molecules related to sludge bulking and iron, leading to the formation of complexes, underscores the significance of controlling iron levels. This study offers a valuable case for practical application of quorum quenching technology in oil wastewater, presenting a rapid, efficient, and cost-effective solution to address the issue of sludge bulking.

The balance of CO2 during abundant basaltic magma production is an important factor of volcanic hazards and climate. In particular, this can be explored based on CO2-rich mantle-derived magmas or carbonate assimilation by basaltic melts. To reconstruct the origin of Fe-rich carbonates hosted by Cenozoic basalts from Wangtian’e volcano (northeast China), we studied elemental compositions of melt, crystalline and fluid inclusions in magmatic minerals as well as the oxygen and carbon isotope compositions of the plagioclase and carbonates from basalts. The crystallization of basaltic magmas occurred in shallow chamber (∼4 km) at temperatures of 1,180°C–1,200°C and a pressure of 0.1 ± 0.01 GPa. Stable Fe-rich carbonates occur in the Wangtian’e tholeiite basalts as groundmass minerals, crystalline inclusions in plagioclase and globules in melt inclusions, which suggests that they crystallized from a ferrocarbonate melt. The values of δ18О and δ13С in the minerals analyzed by laser fluorination method are in line with the sedimentary source of Fe-rich carbonates, indicating assimilation and partial decomposition of carbonate phases. The parent ferrocarbonate melt could be produced during interactions between the basaltic magma and the crustal marbles. The phase diagram and thermodynamic calculations show that the ferrocarbonate melt is stable at a temperature of 1,200°C and a pressure of 0.1 GPa. Our thermodynamic calculations show that carbonate melt containing 73 wt% FeCO3, 24 wt% MgCO3 and 3 wt% CaCO3 is in thermodynamic equilibrium with silicate melt in agreement with our natural observations. The proposed mechanism is crustal carbonate sediment assimilation by the intraplate basaltic magma resulting in the melt immiscibility, production of the ferrocarbonate melt and the following Fe-rich carbonate mineral crystallization during magma residence and cooling.

Abstract Soft and conductive materials are highly desirable for wearable electronics. In particular, anti‐freezing, long‐water retention, and highly conductive gels with Young's modulus matching that of biological tissues, show promise in bioelectronics. Herein, soft organohydrogels obtained by mixing poly (3,4‐ethylenedioxythiophene) doped with polystyrene sulfonate (PEDOT:PSS), ethylene glycol (EG), and tannic acid (TA) are reported. The PEDOT/EG/TA organohydrogels exhibit a low compressive Young's modulus of ≈20 kPa, a conductivity of ≈6 S cm−1, as well as anti‐freezing and water retention properties. Epidermal patch electrodes prepared using the PEDOT/EG/TA gel exhibit low skin–electrode impedance at low frequency (1–100 Hz) and high‐quality electrocardiography (ECG) and electromyography signal recordings. Moreover, these gels demonstrate long‐term stability with high ECG recording quality after being placed under ambient conditions for seven days.

Introduction Attempted suicide among older adults represents a significant mental health concern that has witnessed a rising incidence within this demographic in recent years. Research indicates that attempted suicide among the older population serves as a primary risk factor for completed suicide. Consequently, the objective of this study is to provide a comprehensive overview of the prevailing factors that influence suicide attempts among older adults, thereby offering evidence to guide healthcare professionals in designing targeted interventions.Methods and analysis This study will adhere to the Joanna Briggs Institute framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols. We will synthesise qualitative studies using a comprehensive and inclusive bibliographic search strategy. The following databases will be searched: PubMed, Embase, Web of Science, CINAHL and the Cochrane Library. The quality of the articles will be assessed using the 10-item Joanna Briggs Institute Critical Appraisal Checklist for Qualitative Research. At the same time, data extraction will be performed using the Qualitative Assessment and Review Instrument data extraction form proposed by the Joanna Briggs Institute for Evidence-Based Practice. The synthesis of findings will adhere to the principles and procedures of Thomas and Hardens' three-stage thematic synthesis approach.Ethics and dissemination Ethical approval will not be required for this study, as it solely encompasses data derived from previously published research. The findings will be disseminated through publication in a peer-reviewed journal. Moreover, the results will be presented at relevant academic conferences to guarantee that the study’s outcomes reach pertinent stakeholders. This protocol is registered with the PROSPERO prospective database for systematic review.PROSPERO registration number CRD42023408385.

Objective Peritoneal dialysis (PD) requires high patient conscientiousness. Therefore, we aimed to investigate the relationship between conscientiousness score and prognosis in PD patients.Methods The ten-item Big Five Personality Inventory’s Chinese version was used to assess the conscientiousness score. Basic clinical information, prior medical history, hematological examination results, the occurrence of the first peritonitis and catheter-related infection, the start of hemodialysis, and the time of renal transplantation were collected. The patients were split into two groups, high and low conscientiousness groups, based on the mean value of the conscientiousness score. The differences in prognostic indicators were compared between groups, and the association between conscientiousness score and prognostic indicators in PD patients was assessed.Results Enrolled PD patients were divided into low conscientiousness group 103 and high conscientiousness group 98. There were significant differences in serum albumin (p = 0.021) and iPTH (p = 0.045) between the two groups. Multivariate Cox regression analysis identified conscientiousness score as an independent risk factor for the development of first peritonitis (HR = 0.558, 95% CI 0.400–0.779, p = 0.001) and first catheter-related infection (HR = 0.544, 95% CI 0.308–0.962, p = 0.036) in PD patients. Conscientiousness score (HR = 2.377, 95% CI 1.109–5.095, p = 0.026) was independently associated with renal transplantation.Conclusion Conscientiousness personality is closely related to the prognosis of PD patients.

Fractional vegetation coverage (FVC) is an important ecological parameter reflecting the growth of regional plants. Existing FVC estimation is often based on vegetation indices, especially the Normalized Difference Vegetation Index (NDVI). However, NDVI can be oversaturated and easily affected by problems such as ‘shadow’ in images, which leads to a decrease in the precision of FVC estimation. In this study, the Normalized Shaded Vegetation Index (NSVI) was used to comprehensively compare the estimation ability of FVC with NDVI, and the differences in FVC estimation ability between NSVI and NDVI were explored. Based on two dimensions of ‘bright’ and ‘shadow’ hierarchies and FVC ranks, four evaluation systems of signal-to-noise ratio (SNR), index range, statistical model and dimidiate pixel model were selected from Sentinel-2A MSI, Landsat-8 OLI and Resource-1-02D (ZY1-02D) images and covered a variety of topographic landscapes. The results showed that: (1) the ability of NSVI to resist soil background is slightly smaller than NDVI; (2) the range of NSVI and NDVI in hyperspectral images is slightly larger than multispectral images, and the ability of NSVI to detect vegetation information in medium-high-rank and high-rank FVC areas has obvious advantages; (3) in the same kind of regression model, the goodness of fit of NSVI, NDVI and FVC was slightly higher in bright areas than in shaded areas, and the goodness of fit of the five regression models obtained from NSVI showed a significant advantage in bright areas compared with NDVI, with the best fit of the cubic curve model; (4) the estimation accuracy of the dimidiate pixel model based on NSVI and NDVI is slightly higher in bright areas than in shaded areas, and the estimation ability of NSVI is slightly better than that of NDVI in bright areas with medium-high-rank and high-rank FVC. NSVI and NDVI have their own advantages in SNR, index range, statistical model and dimidiate pixel model, so it is suggested that when remote sensing estimation of FVC is carried out, NSVI should be preferred in medium-high-rank and high-rank FVC areas, and NDVI should be preferred in low-rank FVC areas in shaded areas.

Background Hepatic ischemia-reperfusion injury (IRI) is a common innate immune-mediated sterile inflammatory response in liver transplantation and liver tumor resection. Neutrophil extracellular traps (NETs) can aggravate liver injury and activates innate immune response in the process of liver IRI. However, Curcumin (Cur) can reverse this damage and reduce NETs formation. Nevertheless, the specific regulatory mechanism is still unclear in liver IRI. This study aimed to explore the potential mechanisms that how does Cur alleviate hepatic IRI by inhibits NETs production and develop novel treatment regimens. Methods We established a hepatic IRI model by subjecting C57BL/6J mice to 60 min of ischemia, followed by reperfusion for 2 h, 6 h, 12 h, and 24 h respectively. Subsequently, we were separated into 5 groups, namely the I/R group, Cur group, DNase-1 group, Cur + DNase1 group and sham operation group. Serum alanine aminotransferase (ALT) and aspartate transaminase (AST), Hematoxylin-eosin staining, immunofluorescence, and TUNEL analysis were applied to assess liver injury degree and NETs levels. Western blot assay was used to detect the protein levels of apoptosis-related proteins and MEK pathway proteins. Results Cur could alleviate hepatic IRI by inhibiting the generation of NETs via suppressing the MEK/ERK pathway. In addition, this study also revealed that DNase-1 is vital for alleviating hepatic IRI by reducing the generation of NETs. Conclusions Cur combined with DNase-1 was more effective than the two drugs administered alone in alleviating hepatic IRI by inhibiting the generation of NETs. These results also suggested that curcumin combined with DNase-1 was a potential therapeutic strategy to mitigate hepatic IRI.

ABSTRACTObjective: To explore the prognostic value of the Mayo Additive Staging System (MASS) in real-world patients with newly diagnosed multiple myeloma(MM).Methods: The clinical data of 307 patients with newly diagnosed MM from August 2015 to June 2022 were retrospectively analyzed. Survival analysis was conducted for each subgroup according to the MASS. The MASS was compared to the original staging systems to evaluate its prognostic value. Patients in the high-risk group were further stratified.Results: Patients were divided into MASS stages I (93 cases), II (91 cases), and III (123 cases), with differences in overall survival (OS) and progression-free survival (PFS) among all groups (p

ABSTRACTCandida albicans (C. albicans) is a ubiquitous fungal commensal component of the human microbiota, and under certain circumstances, such as during an immunocompromised state, it may initiate different types of infection. Moreover, C. albicans continuously and reciprocally interacts with the host immune system as well as with other elements of the gut microbiota, thus contributing significantly to both gut homeostasis and host immunity. People living with HIV (PLWH), including those receiving antiretroviral therapy, are characterized by a depletion of CD4 + T-cells and dysbiosis in their gut. C. albicans colonization is frequent in PLWH, causing both a high prevalence and high morbidity. Gut barrier damage and elevated levels of microbial translocation are also fairly common in this population. Herein, we take a closer look at the reciprocity among C. albicans, gut microbiota, HIV, and the host immune system, thus throwing some light on this complex interplay.

Abstract Blood vessels play a role in osteogenesis and osteoporosis; however, the role of vascular metabolism in these processes remains unclear. The present study finds that ovariectomized mice exhibit reduced blood vessel density in the bone and reduced expression of the endothelial glycolytic regulator pyruvate kinase M2 (PKM2). Endothelial cell (EC)‐specific deletion of Pkm2 impairs osteogenesis and worsens osteoporosis in mice. This is attributed to the impaired ability of bone mesenchymal stem cells (BMSCs) to differentiate into osteoblasts. Mechanistically, EC‐specific deletion of Pkm2 reduces serum lactate levels secreted by ECs, which affect histone lactylation in BMSCs. Using joint CUT&Tag and RNA sequencing analyses, collagen type I alpha 2 chain (COL1A2), cartilage oligomeric matrix protein (COMP), ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1), and transcription factor 7 like 2 (TCF7L2) as osteogenic genes regulated by histone H3K18la lactylation are identified. PKM2 overexpression in ECs, lactate addition, and exercise restore the phenotype of endothelial PKM2‐deficient mice. Furthermore, serum metabolomics indicate that patients with osteoporosis have relatively low lactate levels. Additionally, histone lactylation and related osteogenic genes of BMSCs are downregulated in patients with osteoporosis. In conclusion, glycolysis in ECs fuels BMSC differentiation into osteoblasts through histone lactylation, and exercise partially ameliorates osteoporosis by increasing serum lactate levels.

Extracellular vesicles (EVs) are lipid-bilayer membrane-enclosed vesicles that are secreted by all cell types. Natural EVs contain biological information such as proteins, nucleic acids, and lipids from their parent cells. Therefore, EVs have been extensively studied as diagnostic biomarkers and therapeutic tools under normal and pathological conditions. However, some drawbacks, including low yield, poor therapeutic effects, lack of imaging, and targeting capacity of natural EVs, still need to be improved. Emerging engineering technologies have rendered EVs new properties or functionalities that broadened their applications in the biomedical field. Herein, in this review, we gave a brief overview of advanced strategies for EV engineering. We focused on pre-treatment of parent cells to regulate their released EVs. Meanwhile, we summarized and discussed the direct modification of EVs to achieve drug loading, imaging, and targeting functionalities for downstream applications.

BackgroundLittle is known on how metabolic reprogramming potentially prompts transition of activated and resting CD4+ memory T cells infiltration in tumor microenvironment of gastric cancer (GC). The study aimed to evaluate their interactions and develop a risk model for predicting prognosis in GC.MethodsExpression profiles were obtained from TCGA and GEO databases. An immunotherapeutic IMvigor210 cohort was also enrolled. CIBERSORT algorithm was used to evaluate the infiltration of immune cells. The ssGSEA method was performed to assess levels of 114 metabolism pathways. Prognosis and correlation analysis were conducted to identify metabolism pathways and genes correlated with activated CD4+ memory T cells ratio (AR) and prognosis. An AR-related metabolism gene (ARMG) risk model was constructed and validated in different cohorts. Flow cytometry was applied to validate the effect of all-trans retinoic acid (ATRA) on CD4+ memory T cells.ResultsSince significantly inverse prognostic value and negative correlation of resting and activated CD4+ memory T cells, high AR level was associated with favorable overall survival (OS) in GC. Meanwhile, 15 metabolism pathways including retinoic acid metabolism pathway were significantly correlated with AR and prognosis. The ARMG risk model could classify GC patients with different outcomes, treatment responses, genomic and immune landscape. The prognostic value of the model was also confirmed in the additional validation, immunotherapy and pan-cancer cohorts. Functional analyses revealed that the ARMG model was positively correlated with pro-tumorigenic pathways. In vitro experiments showed that ATRA could inhibit levels of activated CD4+ memory T cells and AR.ConclusionOur study showed that metabolic reprogramming including retinoic acid metabolism could contribute to transition of activated and resting CD4+ memory T cells, and affect prognosis of GC patients. The ARMG risk model could serve as a new tool for GC patients by accurately predicting prognosis and response to treatment.

BackgroundImproving job performance has a significant effect on the quality of medical services and ensuring people’s health.PurposeThis study explores the influence and mechanism of the character strengths and career callings of medical staff as well as the intermediary role of such career calling.MethodologyA cross-sectional survey was conducted of 414 healthcare staff members in public hospitals in Hangzhou. Descriptive statistics and hierarchical linear regressions were used to analyze the medical staff’s job performance and related factors, and structural equation modeling path analysis was used to explore and validate the influence and mechanism of character advantage and career calling on job performance.ResultsThe results show that medical staff character strengths have a positive impact on job performance. Path analysis shows that character strengths indirectly affect job performance, and career calling plays a partial mediating role in character strengths and job performance.ConclusionThe results show that good personalities promote job performance, and the association is more significant under a high sense of career calling.

Honeycomb structures serve as the core of sandwich structures in various industries, such as aerospace and rail transit. In this study, a novel design was introduced where hexagonal honeycomb cores were flattened in specific areas to form S-shaped reinforced cores. Compression tests were conducted on S-shaped reinforced honeycomb cores with different rotational structures – left-hand, right-hand, and mixed rotation. The deformation process of these cores was thoroughly investigated. Additionally, a theoretical prediction model was proposed to determine the Young's modulus and peak load of S-shaped reinforced honeycomb cores. The experimental data was compared with the theoretical model to validate its accuracy. Moreover, the study examined the effects of changing the relative density and cell wall angle of S-shaped reinforced honeycomb cores on the peak and specific peak loads. The results demonstrated that the use of S-shaped reinforced structures successfully altered the deformation mode of the honeycomb cores. In particular, the peak loads of S-LL and S-LR specimens were 29.14% and 86.12% higher than that of plain honeycomb, respectively. In summary, increasing the relative density of S-shaped reinforced honeycomb cores proved to enhance the peak load and specific peak load, thereby augmenting the design capabilities of these cores.

BackgroundThe neutrophil-to-lymphocyte ratio (NLR) is recognized as a biomarker for systemic inflammation and immune activation. However, its connection with the mortality risk in individuals with rheumatoid arthritis (RA) is not well understood. This study aimed to investigate the association between NLR and all-cause and cardiovascular mortality risk in U.S. adults with RA.MethodsData were gathered from the National Health and Nutrition Examination Survey (NHANES) cycles spanning 1999 to March 2020. We included adults aged ≥20 years. The NLR was computed by dividing the neutrophil count by the lymphocyte count from complete blood counts. The maximally selected rank statistics method helped identify the optimal NLR cutoff value associated with significant survival outcomes. Multivariable logistic regression models were performed to investigate the relationship between the NLR and the all-cause and cardiovascular mortality of RA. Restricted cubic spline (RCS) analyses were utilized to detect whether there were linear or non-linear relationships between NLR and mortality.ResultsIn this study, 2002 adults with RA were included, with 339 having a higher NLR (≥3.28) and 1663 having a lower NLR (

Abstract Background The role of induction chemotherapy (IC) in oropharyngeal squamous cell carcinoma (OPSCC) remains controversial. Its interpretation can be confounded by heterogeneity in chemosensitivity and human papillomavirus (HPV) status. This study aimed to investigate the prognostic impact of IC response in HPV‐positive and ‐negative OPSCC. Methods Patients with OPSCC who underwent IC and concurrent chemoradiotherapy (CCRT) were retrospectively analyzed. Radiologic response to IC by ≥50% was defined as IC‐sensitive (IC‐s), while lesser response was deemed as IC‐resistant (IC‐r). Progression‐free survival (PFS) and overall survival (OS) were compared between subgroups. Results A total of 51 HPV‐positive and 57 HPV‐negative patients were included. IC‐s patients accounted for 55.6%, 62.7%, and 49.1% in the entire cohort, HPV‐positive, and HPV‐negative subgroup, respectively. Compared with IC‐r subgroup, IC‐s was associated with better clinical outcomes either in the entire cohort (3y‐PFS 91.7%vs.43.7%, P

Abstract Background Sperm is formed through spermiogenesis, a highly complex process involving chromatin condensation that results in cessation of transcription. mRNAs required for spermiogenesis are transcribed at earlier stages and translated in a delayed fashion during spermatid formation. However, it remains unknown that how these repressed mRNAs are stabilized. Results Here we report a Miwi-interacting testis-specific and spermiogenic arrest protein, Ck137956, which we rename Tssa. Deletion of Tssa led to male sterility and absence of sperm formation. The spermiogenesis arrested at the round spermatid stage and numerous spermiogenic mRNAs were down-regulated in Tssa −/− mice. Deletion of Tssa disrupted the localization of Miwi to chromatoid body, a specialized assembly of cytoplasmic messenger ribonucleoproteins (mRNPs) foci present in germ cells. We found that Tssa interacted with Miwi in repressed mRNPs and stabilized Miwi-interacting spermiogenesis-essential mRNAs. Conclusions Our findings indicate that Tssa is indispensable in male fertility and has critical roles in post-transcriptional regulations by interacting with Miwi during spermiogenesis.

Abstract Hyperglycemia impairs immune response; however, it remains unknown whether the anti-tumor effects of anti-programmed cell death-1 antibody (PD-1-Ab) treatment are changed in hyperglycemic conditions. We analyzed the effect of PD-1-Ab on tumor growth in streptozotocin-induced diabetic mice (STZ-mice) subcutaneously inoculated with MC38 (a colon carcinoma cell line). Furthermore, we assessed the expression of chemokines by polymerase chain reaction (PCR) array in tumor-draining lymph nodes (dLNs) of these mice and MC38 cells cultured in different glucose concentrations. The suppressive effect of PD-1-Ab on tumor growth was attenuated. This was accompanied by fewer tumor-infiltrating CD8+ T cells, and STZ-mice had fewer tumor-infiltrating CD11c+ dendritic cells (DCs) than normoglycemic mice. mRNA expression levels of CXCL9, a chemokine recruiting CD8+ T cells, were lower in dLNs of STZ-mice than in normoglycemic mice after PD-1-Ab treatment, and its protein was expressed in DCs. In MC38 cells cultured with 25 mM glucose, mRNA expression of CCL7, a chemokine recruiting DCs, was decreased compared to cells cultured with 5 mM glucose. These results suggest that the STZ-induced hyperglycemia impairs the effect of PD-1-Ab treatment on MC38 tumor growth, and is accompanied by reduced infiltration of DCs and CD8+ T cells and decreased expression of CCL7 and CXCL9.

Abstract Background The dentinogenesis differentiation of dental pulp stem cells (DPSCs) is controlled by the spatio-temporal expression of differentiation related genes. RNA N6-methyladenosine (m6A) methylation, one of the most abundant internal epigenetic modification in mRNA, influences various events in RNA processing, stem cell pluripotency and differentiation. Methyltransferase like 3 (METTL3), one of the essential regulators, involves in the process of dentin formation and root development, while mechanism of METTL3-mediated RNA m6A methylation in DPSC dentinogenesis differentiation is still unclear. Methods Immunofluorescence staining and MeRIP-seq were performed to establish m6A modification profile in dentinogenesis differentiation. Lentivirus were used to knockdown or overexpression of METTL3. The dentinogenesis differentiation was analyzed by alkaline phosphatase, alizarin red staining and real time RT-PCR. RNA stability assay was determined by actinomycin D. A direct pulp capping model was established with rat molars to reveal the role of METTL3 in tertiary dentin formation. Results Dynamic characteristics of RNA m6A methylation in dentinogenesis differentiation were demonstrated by MeRIP-seq. Methyltransferases (METTL3 and METTL14) and demethylases (FTO and ALKBH5) were gradually up-regulated during dentinogenesis process. Methyltransferase METTL3 was selected for further study. Knockdown of METTL3 impaired the DPSCs dentinogenesis differentiation, and overexpression of METTL3 promoted the differentiation. METTL3-mediated m6A regulated the mRNA stabiliy of GDF6 and STC1. Furthermore, overexpression of METTL3 promoted tertiary dentin formation in direct pulp capping model. Conclusion The modification of m6A showed dynamic characteristics during DPSCs dentinogenesis differentiation. METTL3-mediated m6A regulated in dentinogenesis differentiation through affecting the mRNA stability of GDF6 and STC1. METTL3 overexpression promoted tertiary dentin formation in vitro, suggesting its promising application in vital pulp therapy (VPT).

Abstract. The clinical efficacy of proprotein convertase subtilisin/kexin type 9 inhibitors (PCSK9i) in reducing major cardiovascular adverse events related to atherosclerotic cardiovascular disease (ASCVD) has been well established in recent large randomized outcome trials. Although the cardiovascular and all-cause mortality benefit of PCSK9i remains inconclusive, current cholesterol management guidelines have been modified toward more aggressive goals for lowering low-density lipoprotein cholesterol (LDL-C). Consequently, the emerging concept of “the lower the better” has become the paradigm of ASCVD prevention. However, there is evidence from observational studies of a U-shaped association between baseline LDL-C levels and all-cause mortality in population-based cohorts. Among East Asian populations, low LDL-C was associated with an increased risk for hemorrhagic stroke in patients not on antithrombotic therapy. Accumulating evidence showed that low LDL-C was associated with an enhanced bleeding risk in patients on dual antiplatelet therapy following percutaneous coronary intervention. Additionally, low LDL-C was associated with a higher risk for incident atrial fibrillation and thereby, a possible increase in the risk for intracranial hemorrhage after initiation of anticoagulation therapy. The mechanism of low-LDL-C-related bleeding risk has not been fully elucidated. This review summarizes recent evidence of low-LDL-C-related bleeding risk in patients on antithrombotic therapy and discusses potential measures for reducing this risk, underscoring the importance of carefully weighing the pros and cons of aggressive LDL-C lowering in patients on antithrombotic therapy.

Knowledge graph (KG) embedding is to embed the entities and relations of a KG into a low-dimensional continuous vector space while preserving the intrinsic semantic associations between entities and relations. One of the most important applications of knowledge graph embedding (KGE) is link prediction (LP), which aims to predict the missing fact triples in the KG. A promising approach to improving the performance of KGE for the task of LP is to increase the feature interactions between entities and relations so as to express richer semantics between them. Convolutional neural networks (CNNs) have thus become one of the most popular KGE models due to their strong expression and generalization abilities. To further enhance favorable features from increased feature interactions, we propose a lightweight CNN-based KGE model called IntSE in this paper. Specifically, IntSE not only increases the feature interactions between the components of entity and relationship embeddings with more efficient CNN components but also incorporates the channel attention mechanism that can adaptively recalibrate channel-wise feature responses by modeling the interdependencies between channels to enhance the useful features while suppressing the useless ones for improving its performance for LP. The experimental results on public datasets confirm that IntSE is superior to state-of-the-art CNN-based KGE models for link prediction in KGs.

Abstract Background The association between remnant cholesterol (RC) and diabetes remains unclear because of limited study and data. This study attempted to explore the association between RC and diabetes in a large sample, multicenter general population. Methods The current study included 36 684 participants from eight provinces across China. Subjects were quartered according to the RC quartile. Logistic regression analysis was used to evaluate the association between RC and diabetes. Results After adjusting for potential confounding factors, RC was still significantly associated with diabetes (Q4: odds ratio [OR]:1.147, 95% confidence interval [CI]: 1.049–1.254, p = .003). In addition, RC and diabetes were still significantly associated when triglycerides (TG) were

Abstract As significant posttranslational modifications, ubiquitination and deubiquitination, whose balance is modulated by ubiquitin-conjugating enzymes and deubiquitinating enzymes (DUBs), can regulate many biological processes, such as controlling cell cycle progression, signal transduction and transcriptional regulation. Belonging to DUBs, ubiquitin-specific protease 28 (USP28) plays an essential role in turning over ubiquitination and then contributing to the stabilization of quantities of substrates, including several cancer-related proteins. In previous studies, USP28 has been demonstrated to participate in the progression of various cancers. Nevertheless, several reports have recently shown that in addition to promoting cancers, USP28 can also play an oncostatic role in some cancers. In this review, we summarize the correlation between USP28 and tumor behaviors. We initially give a brief introduction of the structure and related biological functions of USP28, and we then introduce some concrete substrates of USP28 and the underlying molecular mechanisms. In addition, the regulation of the actions and expression of USP28 is also discussed. Moreover, we concentrate on the impacts of USP28 on diverse hallmarks of cancer and discuss whether USP28 can accelerate or inhibit tumor progression. Furthermore, clinical relevance, including impacting clinical prognosis, influencing therapy resistance and being the therapy target in some cancers, is depicted systematically. Thus, assistance may be given to future experimental designs by the information provided here, and the potential of targeting USP28 for cancer therapy is emphasized.

Abstract This study aimed to compare the peri- and postoperative outcomes of patients treated with conventional versus robot-assisted laparoendoscopic single-site radical prostatectomy (C-LESS-RP vs. R-LESS-RP). Data of patients with prostate cancer (106 who underwent C-LESS-RP, 124 underwent R-LESS-RP) were retrospectively collected and analyzed. All operations were performed by the same surgeon from January 8, 2018, to January 6, 2021, in the same institution. Information on clinical characteristics and perioperative outcomes was obtained from records at the medical institution. Postoperative outcomes were acquired from follow-up. Intergroup differences were retrospectively analyzed and compared. All patients had similar clinical characteristics in meaningful aspects. The perioperative outcomes were better with R-LESS-RP than with C-LESS-RP in terms of operation time (120 min vs. 150 min, p

Abstract Background EQ.PET is a software package that overcomes the reconstruction-dependent variation of standard uptake values (SUV). In this study, we validated the use of EQ.PET for harmonizing SUVs between different positron emission tomography/computed tomography (PET/CT) systems and reconstruction algorithms. Methods In this retrospective study, 49 patients with various cancers were scanned on a Biograph mCT (mCT) or Gemini TF 16 (Gemini) after [18F]FDG injections. Three groups of patient data were collected: Group 1, patients scanned on mCT or Gemini with data reconstructed using two parameters; Group 2, patients scanned twice on different PET scanners (interval between two scans, 68.9 ± 41.4 days); and Group 3, patients scanned twice using mCT with data reconstructed using different algorithms (interval between two scans, 109.5 ± 60.6 days). The SUVs of the lesions and background were measured, and the tumor-to-background ratios (TBRs) were calculated. In addition, the consistency between the two reconstruction algorithms and confounding factors were evaluated. Results In Group 1, the consistency of SUV and TBR between different reconstruction algorithms improved when the EQ.PET filter was applied. In Group 2, by comparing ΔSUV, ΔSUV%, ΔTBR, and ΔTBR% with and without the EQ.PET, the results showed significant differences (P

The tropical Pacific Ocean was dominated by La Niña-like conditions during the Medieval Warm Period, but El Niño-like conditions during the Little Ice Age and Industrial Period

Direct neural inputs to immune organs have been observed for decades, with their functions in neuroimmune regulation being increasingly appreciated. However, the current knowledge of such neural structures, particularly those in primate immune organs, remains incomplete. In this study, we comprehensively assessed the 3D anatomy of autonomic (i.e., sympathetic and parasympathetic) innervations in the immune organs of the rhesus macaque monkey and the human for the first time. Aided with the advanced technique of whole-tissue immunolabeling and lightsheet fluorescence imaging, we revealed the densely organized sympathetic architecture in the parenchyma of the adult monkey and human spleens. On the other hand, only sparse, if any, sympathetic inputs were observed inside the lymph nodes, Peyer's patches, or thymus. In contrast, there were minimal parasympathetic innervations in the parenchyma of these examined immune organs. Together, this work has documented the unique patterns of autonomic innervations in different immune organs of a non-human primate and the human, serving as an essential reference for future research on neuroimmune regulation in the field.

Abstract A visually meaningful double-image encryption scheme using 2D compressive sensing and multi-rule DNA encoding is presented. First, scrambling, diffusing and 2D compressive sensing are performed on the two plain images, and two privacy images are obtained, respectively. Then, the two privacy images are re-encrypted using DNA encoding theory to obtain two secret images. Finally, integer wavelet transform (IWT) is performed on the carrier image to obtain the wavelet coefficients, then the two secret images are embedded into the wavelet coefficients and 2k correction is performed, and the obtained result is processed by inverse IWT to obtain a visually meaningful encrypted image. DNA encoding rules selected for the pixel values of different positions in the two privacy images, and DNA operations performed between the two privacy images and the key streams at different positions are controlled by the chaotic system. The application of 2D compressive sensing reduces the amount of data, thus increasing the encryption capacity of the system. The introduction of DNA encoding theory and the double-image embedding process increases the security of the system. The simulation results demonstrate the feasibility of the scheme, and it has high data security and visual security.

Abstract Background Anillin is a F‐actin binding protein (ANLN) mainly involved in the process of cytokinesis and known to be dysregulated in diverse cancers. However, the role of ANLN in pan‐cancer prognosis and tumor immunity remains unclear. Methods Gene expression profiles of 31 solid tumors were downloaded from The Cancer Genome Atlas (TCGA) database. ANLN mRNA and protein expression were quantified using quantitative real‐time PCR (qRT‐PCR) and immunohistochemistry (IHC). Protein expression of ANLN was further confirmed in Human Protein Atlas (HPA) database. Cox regression and Kaplan–Meier analysis were utilized to assess the prognostic value of ANLN in pan‐cancer. The correlation between ANLN and different immune gene markers and infiltration cells was analyzed via ESTIMATE and CIBERSORT. A BLCA immunotherapy cohort: IMvigor (210) was used to confirm the role of ANLN in immune response. Results ANLN upregulation was detected in 21 types of cancers and was associated with poor overall survival (OS), disease‐free interval (DFI), and progression‐free interval (PFI) in most cancers except in THYM (Thymoma). Additionally, correlation analysis revealed a significantly positive association between ANLN expression and tumor mutation burden (TMB), microsatellite instability (MSI), immune cells infiltration. and immune checkpoint genes in various cancers. The BLCA immunotherapy cohort confirmed that patients with higher ANLN level had better immune responses and longer OS. Conclusion ANLN may serve as a prognostic biomarker for pan‐cancer. ANLN upregulation is associated with higher TMB, MSI, and immune cell infiltration in multiple types of tumors, shedding new light for cancer treatment.

Abstract Automatic License Plate detection and Recognition (ALPR) is a key problem in intelligent transportation systems with wide applications in traffic monitoring, electronic toll collection (ETC), intelligent parking lots (IPLs), and elsewhere. Although numerous methods have been proposed in the literature, it is still challenging to strike a good balance between the accuracy and efficiency of ALPR. In this paper, a novel end‐to‐end CNN‐based model is proposed, called Fast and Accurate Network with Feature Enhancement (FAFEnet), to jointly detect the license plates and recognize the characters with high accuracy and efficiency. Specifically, the FAFEnet model seamlessly integrates two CNN‐based models, namely the detection and recognition modules, into a unified framework to reduce accumulated errors and computational overheads in two separate steps. The detection module is a lightweight model with only seven convolutional layers yet achieves over 99.8% accuracy rates for license plate detection across all datasets. The recognition module utilizes two feature enhancement blocks to compensate and enhance the shallow character features extracted by the detection module. Furthermore, the joint optimization of detection and recognition modules exploits the feature association in two modules, and thus improves the prediction accuracy while reducing the execution time. Finally, extensive experimental results on several real‐world datasets demonstrate that FAFEnet outperforms all the competitors in terms of both accuracy and efficiency.

Abstract The amygdala, or an amygdala-like structure, is found in the brains of all vertebrates and plays a critical role in survival and reproduction. However, the cellular architecture of the amygdala and how it has evolved remain elusive. Here, we generated single-nucleus RNA-sequencing data for more than 200,000 cells in the amygdala of humans, macaques, mice, and chickens. Abundant neuronal cell types from different amygdala subnuclei were identified in all datasets. Cross-species analysis revealed that inhibitory neurons and inhibitory neuron-enriched subnuclei of the amygdala were well-conserved in cellular composition and marker gene expression, whereas excitatory neuron-enriched subnuclei were relatively divergent. Furthermore, LAMP5 + interneurons were much more abundant in primates, while DRD2 + inhibitory neurons and LAMP5 + SATB2 + excitatory neurons were dominant in the human central amygdalar nucleus (CEA) and basolateral amygdalar complex (BLA), respectively. We also identified CEA-like neurons and their species-specific distribution patterns in chickens. This study highlights the extreme cell-type diversity in the amygdala and reveals the conservation and divergence of cell types and gene expression patterns across species that may contribute to species-specific adaptations.

Abstract Previous studies suggested that upper and lower facial halves might be involved in the human holistic face processing differently. In this study, we replicated and extended the finding above. In Experiment 1, we used the standard composite-face task to measure holistic face processing when participants made judgements on the upper and lower facial halves separately. Results showed that the composite-face effect was stronger for the upper facial half compared to the lower half. In Experiment 2, we investigated how facial information was integrated when participants focused on different features, using the perceptual field paradigm. Results showed that: (1) more “peripheral faces” were chosen when participants fixated at the eyes than when they fixated at the mouth; (2) less “peripheral faces” were chosen for inverted faces regardless of the fixated features. Findings from both experiments together indicate that more peripheral facial information were integrated when participants focused on the upper facial half, highlighting the significance of focusing on the upper facial half in face processing.

A knowledge graph is a structured semantic network designed to describe physical entities and relations in the world. A comprehensive and accurate knowledge graph is essential for tasks such as knowledge inference and recommendation systems, making link prediction a popular problem for knowledge graph completion. However, existing approaches struggle to model complex relations among entities, which severely hampers their ability to complete knowledge graphs effectively. To address this challenge, we propose a novel hierarchical multi-head attention network embedding framework, called RiQ-KGC, which integrates different-grained contextual information of knowledge graph triples and models quaternion rotation relations between entities. Furthermore, we propose a relation instantiation method for alleviating the difficulty of expressing complex relations between entities. To enhance the expressiveness of relation representation, the relation is integrated by Transformer to obtain multi-hop neighbor information, so that one relation can be embedded into different embeddings according to different entities. Experimental results on four datasets demonstrate that RiQ-KGC exhibits strong competitiveness compared to state-of-the-art models in link prediction, while the ablation experiments reveal that the proposed relation instantiation method achieves great performance.

The AP2/ERF gene family, referring to an exclusive class of transcription factors unique to plants, is involved in various biological processes, including plant growth and responses to environmental stresses like high salt and drought. In this study, the AP2/ERF gene in M. notabilis was comprehensively identified and bioinformatically analyzed based on the genomic data of M. notabilis. 106 members in the MnAP2/ERF gene family were identified in the M. notabilis genome and were categorized into five subfamilies: ERF, AP2, DREB, RAV, and Soloist, with the ERF subfamily representing 80.19% of the total. The MnAP2/ERF gene family was observed to be distributed on six chromosomes of M. notabilis. Members in the MnAP2/ERF gene family exhibited obvious differences in amino acid number, molecular weight, isoelectric point, and other properties. Approximately 68.87% of the MnAP2/ERF proteins were acidic, all exhibiting hydrophilic characteristics. Differences in conserved sequences and arrangement of AP2 domains were observed among distinct subfamilies, with genes in the same subfamily sharing similar conserved domain compositions. There were 47 genes without untranslated regions and 44 genes with two untranslated regions. The upstream functions of promoters were concentrated on light reactions and plant hormones. Evolutionarily, significant structural differences were identified, and 28 MnAP2/ERF gene family proteins could interact with each other. Moreover, 35 family genes were involved in 22 fragment repeat events, and 55 MnAP2/ERF and 84 AtAP2/ERF genes showed collinearity. The expression of the MnAP2/ERF gene family was significantly different in different parts, indicating that these gene family members were involved in different physiological activities. These results established a theoretical foundation for investigating the functional and evolutionary aspects of AP2/ERF gene family genes in M. notabilis, as well as exploring the root morphogenesis of M. notabilis. Additionally, this study contributes to a basis for the improvement of cultivar stress resistance of M. notabilis.

Based on the definitions of fuzzy associative algebras and fuzzy ideals, it is proven that the intersections of fuzzy subalgebras are fuzzy subalgebras, and the intersections of fuzzy ideals are fuzzy ideals. Moreover, we prove that the kernels of fuzzy homomorphisms are fuzzy ideals. Using fuzzy ideals, the quotient structures of fuzzy associative algebras are constructed, their corresponding properties are discussed, and their homomorphism theorems are proven.

Crop classification is indispensable for agricultural monitoring and food security, but early-season mapping has remained challenging. Synthetic aperture radar (SAR), such as RADARSAT Constellation Mission (RCM) and Sentinel-1, can meet higher requirements on the reliability of satellite data acquisition with all-weather and all-day imaging capability to supply dense observations in the early crop season. This study applied the local window attention transformer (LWAT) to time-series SAR data, including RCM and Sentinel-1, for early-season crop classification. The performance of this integration was evaluated over crop-dominated regions (corn, soybean and wheat) in southwest Ontario, Canada. Comparative analyses against several machine learning and deep learning methods revealed the superiority of the LWAT, achieving an impressive F1-score of 97.96% and a Kappa coefficient of 97.08% for the northern crop region and F1-scores of 98.07% and 97.02% for the southern crop region when leveraging time-series data from RCM and Sentinel-1, respectively. Additionally, by the incremental procedure, the evolution of accuracy determined by RCM and Sentinel-1 was analyzed, which demonstrated that RCM performed better at the beginning of the season and could achieve comparable accuracy to that achieved by utilizing both datasets. Moreover, the beginning of stem elongation of corn was identified as a crucial phenological stage to acquire acceptable crop maps in the early season. This study explores the potential of RCM to provide reliable prior information early enough to assist with in-season production forecasting and decision making.

The effective segmentation of clouds and cloud shadows is crucial for surface feature extraction, climate monitoring, and atmospheric correction, but it remains a critical challenge in remote sensing image processing. Cloud features are intricate, with varied distributions and unclear boundaries, making accurate extraction difficult, with only a few networks addressing this challenge. To tackle these issues, we introduce a multi-scale receptive field aggregation network (MRFA-Net). The MRFA-Net comprises an MRFA-Encoder and MRFA-Decoder. Within the encoder, the net includes the asymmetric feature extractor module (AFEM) and multi-scale attention, which capture diverse local features and enhance contextual semantic understanding, respectively. The MRFA-Decoder includes the multi-path decoder module (MDM) for blending features and the global feature refinement module (GFRM) for optimizing information via learnable matrix decomposition. Experimental results demonstrate that our model excelled in generalization and segmentation performance when addressing various complex backgrounds and different category detections, exhibiting advantages in terms of parameter efficiency and computational complexity, with the MRFA-Net achieving a mean intersection over union (MIoU) of 94.12% on our custom Cloud and Shadow dataset, and 87.54% on the open-source HRC_WHU dataset, outperforming other models by at least 0.53% and 0.62%. The proposed model demonstrates applicability in practical scenarios where features are difficult to distinguish.

In the field of multi-view satellite photogrammetry, the neural radiance field (NeRF) method has received widespread attention due to its ability to provide continuous scene representation and realistic rendering effects. However, the satellite radiance field methods based on the NeRF are limited by the slow training speed of the original NeRF, and the scene reconstruction efficiency is low. Training for a single scene usually takes 8–10 h or even longer, which severely constrains the utilization and exploration of the NeRF approach within the domain of satellite photogrammetry. In response to the above problems, we propose an efficient neural radiance field method called SatelliteRF, which aims to quickly and efficiently reconstruct the earth’s surface through multi-view satellite images. By introducing innovative multi-resolution hash coding, SatelliteRF enables the model to greatly increase the training speed while maintaining high reconstruction quality. This approach allows for smaller multi-layer perceptron (MLP) networks, reduces the computational cost of neural rendering, and accelerates the training process. Furthermore, to overcome the challenges of illumination changes and transient objects encountered when processing multi-date satellite images, we adopt an improved irradiance model and learn transient embeddings for each image. This not only increases the adaptability of the model to illumination variations but also improves its ability to handle changing objects. We also introduce a loss function based on stochastic structural similarity (SSIM) to provide structural information of the scene for model training, which further improves the quality and detailed performance of the reconstructed scene. Through extensive experiments on the DFC 2019 dataset, we demonstrate that SatelliteRF is not only able to significantly reduce the training time for the same region from the original 8–10 h to only 5–10 min but also achieves better performance in terms of rendering and the reconstruction quality.

The Global Navigation Satellite System (GNSS) is widely used for its high accuracy, wide coverage, and strong real-time performance. However, limited by the navigation signal mechanism, satellite signals in urban canyons, bridges, tunnels, and other environments are seriously affected by non-line-of-sight and multipath effects, which greatly reduce positioning accuracy and positioning continuity. In order to meet the positioning requirements of human and vehicle navigation in complex environments, it was necessary to carry out this research on the integration of multiple signal sources. The Fifth Generation (5G) signal possesses key attributes, such as low latency, high bandwidth, and substantial capacity. Simultaneously, 5G Base Stations (BSs), serving as a fundamental mobile communication infrastructure, extend their coverage into areas traditionally challenging for GNSS technology, including indoor environments, tunnels, and urban canyons. Based on the actual needs, this paper proposes a system algorithm based on 5G and GNSS joint positioning, aiming at the situation that the User Equipment (UE) only establishes the connection with the 5G base station with the strongest signal. Considering the inherent nonlinear problem of user position and angle measurements in 5G observation, an angle cosine solution is proposed. Furthermore, enhancements to the Sage–Husa Adaptive Kalman Filter (SHAKF) algorithm are introduced to tackle issues related to observation weight distribution and adaptive updates of observation noise in multi-system joint positioning, particularly when there is a lack of prior information. This paper also introduces dual gross error detection adaptive correction of the forgetting factor based on innovation in the iterative Kalman filter to enhance accuracy and robustness. Finally, a series of simulation experiments and semi-physical experiments were conducted. The numerical results show that compared with the traditional method, the angle cosine method reduces the average number of iterations from 9.17 to 3 with higher accuracy, which greatly improves the efficiency of the algorithm. Meanwhile, compared with the standard Extended Kalman Filter (EKF), the proposed algorithm improved 48.66%, 35.17%, and 38.23% at 1σ/2σ/3σ, respectively.

To reduce the energy consumption of domestic hot water (DHW) production, it is necessary to reasonably select a water supply plan through early predictions of DHW consumption to optimize energy consumption. However, the fluctuations and intermittence of DHW consumption bring great challenges to the prediction of water consumption. In this paper, an ANN-LSTM-A water quantity prediction model based on attention mechanism (AM) enhancement is improved. The model includes an input layer, an AM layer, a hidden layer, and an output layer. Based on the combination of artificial neural network (ANN) and long short-term memory (LSTM) models, an AM is incorporated to address the issue of the traditional ANN model having difficulty capturing the long-term dependencies, such as lags and trends in time series, to improve the accuracy of the DHW consumption prediction. Through comparative experiments, it was found that the root mean square error of the ANN-LSTM-A model was 15.4%, 13.2%, and 13.2% lower than those of the ANN, LSTM, and ANN-LSTM models, respectively. The corresponding mean absolute error was 17.9%, 11.5%, and 8% lower than those of the ANN, LSTM, and ANN-LSTM models, respectively. The results showed that the proposed ANN-LSTM-A model yielded better performances in predicting DHW consumption than the ANN, LSTM, and ANN-LSTM models. This work provides an effective reference for the reasonable selection of the water supply plan and optimization of energy consumption.

The aim of topology optimisation is to determine the optimal distribution of material phases within the periodic cells of a microstructure. In this paper, the density of grid points under element volume fraction is constructed to replace the finite elements in the traditional SIMP framework, avoiding jagged and blurry boundaries in the computational process due to grid dependence. This is then combined with homogenisation theory, a microstructure topology optimisation algorithm with maximum bulk modulus under prescribed volume constraints is proposed, which can obtain 2D and 3D topologies with smooth boundaries. In addition, a closed form expression for the two-dimensional topological concave edge structure (taking the most typical topology as an example) was derived, and a compression experiment was conducted on the topological microstructure based on 3D metal printing technology. Scanning electron microscopy showed that the powder bonded on the surface of the printed structure was not completely melted and the step effect caused the finite element analysis results to be higher than the experimental results. Overall, the finite element simulation and experimental results of the concave surface structure have good consistency, with high strength and energy absorption effects. Topologies based on grid point density obtain microstructures with smooth boundaries, and the introduction of the Heaviside smoothing function and multiple filtering steps within this algorithm leads to more robust optimisation, facilitating 3D or 4D printing of microstructures that meet specific design requirements and confirming the feasibility of the proposed topology for lightweighting studies.