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Pregnancy is a sensitive window period for bisphenol A (BPA) exposure. BPA can pass through the placenta and cause reproductive damage in offspring female mice. Even BPA that is not metabolized during lactation can be passed through milk. Cuscuta chinensis flavonoids (CCFs) can alleviate reproductive damage caused by BPA, but the mechanism of action is unclear. To investigate the potential mitigating impact of CCFs on ovarian damage resulting from BPA exposure during pregnancy, we administered BPA and CCFs to pregnant mice during the gestational period spanning from 0.5 to 17.5 days. Aseptic collection of serum and ovaries from female mice was conducted on postnatal day 21 (PND21). Serum hormone levels and tissue receptor levels were quantified utilizing ELISA and PCR, while ovaries underwent sequencing and analysis through transcriptomics and metabolomics techniques. Additionally, the assessment of ovarian oxidative stress levels was carried out as part of the comprehensive analysis. The results showed that CCFs administration mitigated the adverse effects induced by BPA exposure on ovarian index, hormone levels, receptor expression, and mRNA expression levels in female offspring mice. The joint analysis of transcriptome and metabolome revealed 48 enriched pathways in positive ion mode and 44 enriched pathways in negative ion mode. Among them, the central carbon metabolism pathway is significantly regulated by BPA and CCFs. The screened sequencing results were verified through qPCR and biochemical kits. In this study, CCFs may participate in the central carbon metabolism pathway by reducing the expression of Kit proto-oncogene (Kit), hexokinase 1 gene (Hk1) and pyruvate kinase M (Pkm) mRNA and increasing the expression of h-ras proto-oncogene (Hras), sirtuin 3 (Sirt3), sirtuin 6 (Sirt6) and TP53 induced glycolysis regulatory phosphatase gene (Tigar) mRNA, thereby resisting the effects of BPA on the body. At the same time, the metabolic levels of D-Fructose 1,6-bisphosphate and L-Asparagine tend to be stable. Moreover, CCFs demonstrated a capacity to diminish the BPA-induced escalation in reactive oxygen species (ROS) and malondialdehyde (MDA). Simultaneously, it exhibited the ability to elevate levels of glutathione (GSH) and catalase (CAT), thereby effectively preventing peroxidation. In summary, CCFs alleviate BPA-induced ovarian damage in offspring female mice by regulating the central carbon metabolism pathway. This study will improve the information on BPA reproductive damage antagonist drugs and provide a theoretical basis for protecting animal reproductive health.

The demand for advanced materials capable of withstanding extreme high-temperature conditions has led to the development of novel High-Entropy Alloys (HEAs). Recent works indicate that forming a CrTaO4 protection layer gives HEAs excellent long-term oxidation resistance. In this study, the high-temperature oxidation resistance properties of CrTaTiMo Refractory Medium-Entropy Alloys (RMEAs) were assessed by Density Functional Theory (DFT) and ab initio Molecular Dynamics (AIMD). Through the oxygen adsorption and diffusion calculations, we demonstrated the preferential oxygen adsorption sequence on the surface of the RMEA as Ti, Ta, Cr, and Mo. Furthermore, our analysis identified the sites featuring Ta as subsurface atoms were the weakest locations for oxygen atom diffusion. The dynamic oxidation mechanism of oxygen molecules on CrTaTiMo RMEA was investigated by AIMD simulations. The results confirmed that the adsorption and dissociation of O2 molecules on the alloy surface. Additionally, the diffusion of the O atom took place at temperatures greater than 873 K and confirmed the O-attracting feature of Ta atoms. Moreover, electronic structure calculations confirmed the bonding of oxygen atoms with those four metal elements. This study could serve as a valuable reference for the strategic development of the CrTaTiMo-based RMEAs or RHEAs for high-temperature, long-term oxidation resistance applications.

Abstract Background Clinical nurses are susceptible to compassion fatigue when exposed to various types of traumatic events in patients for extended periods of time. However, the developmental process, staging, and psychological responses distinct to each stage of compassion fatigue in nurses are not fully clarified. This study aimed to explore the processes of compassion fatigue and the psychological experiences specific to each phase of compassion fatigue among clinical nurses. Methods Charmaz’s Constructivist Grounded Theory methodology was used in this qualitative research. Semi-structured interviews were conducted with 13 clinical nurses with varying degrees of compassion fatigue from December 2020 to January 2021. Interview data were analyzed using grounded theory processes. Results The data were categorized into five separate categories and 22 sub-categories. This study found that the process of compassion fatigue is dynamic and cumulative, which was classified into five phases: compassion experience period, compassion decrement period, compassion discomfort period, compassion distress period, and compassion fatigue period. Conclusion Clinical nurses who experience compassion fatigue may go through five stages that are stage-specific and predictable. The findings can shed light on local and global applications to better understand the problem of nurses’ compassion fatigue. The interventions for addressing compassion fatigue in clinical nurses should be stage-specific, targeted, and individualized.

Abstract In existing remote sensing image retrieval (RSIR) datasets, the number of images among different classes varies dramatically, which leads to a severe class imbalance problem. Some studies propose to train the model with the ranking‐based metric (e.g., average precision [AP]), because AP is robust to class imbalance. However, current AP‐based methods overlook an important issue: only optimising samples ranking before each positive sample, which is limited by the definition of AP and is prone to local optimum. To achieve global optimisation of AP, a novel method, namely Optimising Samples after positive ones & AP loss (OSAP‐Loss) is proposed in this study. Specifically, a novel superior ranking function is designed to make the AP loss differentiable while providing a tighter upper bound. Then, a novel loss called Optimising Samples after Positive ones (OSP) loss is proposed to involve all positive and negative samples ranking after each positive one and to provide a more flexible optimisation strategy for each sample. Finally, a graphics processing unit memory‐free mechanism is developed to thoroughly address the non‐decomposability of AP optimisation. Extensive experimental results on RSIR as well as conventional image retrieval datasets show the superiority and competitive performance of OSAP‐Loss compared to the state‐of‐the‐art.

Abstract Background Sporadic studies have examined the impact of OSA on ACS patients by homocysteine (Hcy) level. This study attempted to comprehensively evaluate the effects of the interaction between Hcy and OSA on long-term cardiovascular outcomes in ACS patients. Methods In this prospective, large-scale cohort study, 2160 patients admitted for ACS were recruited to undergo overnight sleep monitoring. OSA was diagnosed when apnea–hypopnea index ≥ 15 events/h. Patients with normohomocysteinemia (NHcy) were defined as having serum Hcy ≤ 15 μmol/L, and the others had hyperhomocysteinemia (HHcy). The primary endpoint was major adverse cerebrocardiovascular event (MACCE), a composite of cardiovascular death, myocardial infarction, stroke, ischemia-driven revascularization and hospitalization for unstable angina and heart failure. Results A total of 1553 eligible ACS patients (average age: 56.3 ± 10.5 years) were enrolled, among which 819 (52.7%) had OSA, and 988 (63.6%) were with NHcy. OSA did not significantly affect the level of Hcy. During a median follow-up of 2.9 (1.6, 3.5) years, after adjustment for clinical confounders, OSA was associated with increased risk for MACCE occurrence versus non-OSA ones in ACS patients with NHcy (adjusted hazard ratio [HR] = 1.36, 95% confidence interval [CI] 1.02–1.83, P = 0.039), but not in those with HHcy (adjusted HR = 0.92, 95%CI 0.62–1.36, P = 0.668). There was an absence of interaction between homocysteine level and OSA in relation to MACCE (interaction P = 0.106). Conclusions OSA was independently associated with worse prognosis in ACS patients with NHcy. Our study emphasized the necessity to identify potential presence of OSA in such a population. Trial registration: ClinicalTrials.gov; Number: NCT03362385; URL: www.clinicaltrials.gov .

Objective: Measurements utilizing commercially available sets of reagents for determination of steroid hormone profiles by liquid chromatography–tandem mass spectrometry (LC-MS/MS) have become increasingly important for routine laboratories. However, method-specific publications of reference intervals obtained from sufficiently large studies are often missing. Methods: After validation of performance characteristics, a widely available kit for steroid analysis by LC-MS/MS was used to measure concentrations of 15 endogenous steroids (aldosterone, cortisol, cortisone, corticosterone, 11-deoxycortisol, 21-deoxycortisol, dehydroepiandrosterone sulfate, estradiol, testosterone, androstenedione, dihydrotestosterone, dehydroepiandrosterone, 17-hydroxyprogesterone, 11-deoxycorticosterone, progesterone) in more than 500 blood samples from a population-based study. While randomly selected from a larger cohort, the samples equally represented both sexes and covered a wide range of adult age groups. Age- and sex-specific reference intervals were calculated, and correlation with BMI was assessed. Results: Performance characteristics of the assay matched expectations for 9 of 15 steroids. For most of them, reference intervals obtained from our study population were comparable to those reported by others, with age and sex being the major determinants. A sex-specific correlation with BMI was found for seven steroids. We identified limitations regarding sensitivity of the method for quantification of progesterone in males and postmenopausal females. Concentrations of aldosterone, 21-deoxycortisol, estradiol, 11-deoxycorticosterone, and dihydrotestosterone could not be quantified in a large percentage of samples. Conclusions: The reference intervals for nine steroids will support meaningful interpretation for steroid profiles as measured by a widely used kit for LC-MS/MS-based quantification. Laboratories using such kits must be aware of potential limitations in sensitivity for some steroids included in the profile. Significance Statement Quantification of steroid hormones is a cornerstone for diagnosis of several diseases. Commonly used immunoassays have limitations in specificity. Liquid chromatography–tandem mass spectrometry (LC-MS/MS) is a promising alternative, particularly if methods are harmonized across laboratories. The use of kits from commercial suppliers might support this. Clinical interpretation of steroid concentrations requires availability of appropriate reference intervals (RIs), but studies on RIs reported in the literature differ in preanalytical and analytical procedures. Here, we provide RIs for steroids measured by a widely available kit under preanalytical conditions mirroring common clinical practice. Such RIs might facilitate interpretation for those using the same method and comparable conditions in clinical routine.

The purpose of this experiment was to optimize the extraction process of total flavonoids from Scutellaria barbata and to evaluate the antioxidant and antitumor activity of total flavonoids. A single factor experiment combined with a response surface Box-Behnken design was used to study the extraction process of total flavonoids from Scutellaria barbata. The effects of extraction time, material-to-liquid ratio, extraction temperature and volume fraction of ethanol on the yield of flavonoids were investigated to arrive at the optimal extraction process of total flavonoids from Scutellaria barbata. The antioxidant activity of total flavonoids from Scutellaria barbata was detected by DPPH and ABTS methods, and the effect of purified products on the proliferation of NCI-H1299, HepG2, MHCC-97H and HuH-7 cells were analyzed using the MTT assay. The results showed that the optimum extraction conditions of total flavonoids from Scutellaria barbata were as follows: Extraction time 93 min, ratio of material to liquid 1:41 (g/mL), extraction temperature 68 ℃, volume fraction of ethanol 75%. Under these conditions, the yield of total flavonoids was 26.46 mg/g. The results of antioxidant experiments showed that the purified total flavonoids of Scutellaria barbata had good scavenging effects on DPPH and ABTS+ radicals, with IC50 values of 25.41 and 70.41 μg/mL, respectively. The results of anti-tumor experiments showed that the purified total flavonoids of Scutellaria barbata at different mass concentrations within a certain concentration range had certain inhibitory effects on the proliferation of tumor cells, with the IC50 values of NCI-H1299, HepG2, MHCC-97H and HuH-7 cells were 168.6, 330.5, 269.2 and 335.8 μg/mL, respectively. In summary, it could be concluded that the method was stable and feasible, reproducible, and could effectively extract the total flavonoid components from Scutellaria barbata, and the purified Scutellaria barbata total flavonoids had good antioxidant and antitumor activities, which could be used for the development of functional foods or pharmaceuticals.

AbstractContext Tormentic acid (TA), an effective triterpenoid isolated from Chaenomeles speciosa (Sweet) Nakai (Rosaceae) fruits, exerts an effective treatment for gastric damage.Objective To investigate the gastroprotective effect of TA on indomethacin (IND) damaged GES-1 cells and rats, and explore potential mechanisms.Materials and methods TA concentrations of 1.563–25 µM were used. Cell proliferation, apoptosis and migration were performed using MTT, colony formation, wound healing, migration, Hoechst staining assays. SD rats were divided into control, IND, TA (1, 2 and 4 mg/kg) + IND groups, once a day for 21 continuous days. Twenty-four hours after the last administration, all groups except the control group were given IND (100 mg/kg) by gavage. Gastric juice parameters, gastric ulcer, gastric blood flow (GBF), blood biochemical parameters and cytokine analysis and gastric mucosal histopathology were detected for 2 h and 6 h after IND oral administration. The mRNA and protein expression of miR-139 and the CXCR4/CXCL12/PLC/PKC/Rho A/MLC pathway were analyzed in the IND-damaged GES-1 cells and gastric tissue of rats.Results TA might ameliorate the gastric mucosal injury by accelerating the IND-damaged GES-1 cell proliferation and migration, ameliorating GBF, ulcer area and pathologic changes, the redox system and cytokine levels, the gastric juice parameters, elevating the gastric pH in IND damaged rats; suppressed miR-139 mRNA expression, elevated CXCR4 and CXCL12 mRNA and protein expression, p-PLC, p-PKC, Rho A, MLCK and p-MLC protein expression.Discussion and conclusions TA may have potential use as a clinical drug candidate for gastric mucosal lesion treatment.

Abstract Metallosalen-covalent organic frameworks have recently gained attention in photocatalysis. However, their use in CO2 photoreduction is yet to be reported. Moreover, facile preparation of metallosalen-covalent organic frameworks with good crystallinity remains considerably challenging. Herein, we report a series of metallosalen-covalent organic frameworks produced via a one-step synthesis strategy that does not require vacuum evacuation. Metallosalen-covalent organic frameworks possessing controllable coordination environments of mononuclear and binuclear metal sites are obtained and act as photocatalysts for tunable syngas production from CO2. Metallosalen-covalent organic frameworks obtained via one-step synthesis exhibit higher crystallinity and catalytic activities than those obtained from two-step synthesis. The optimal framework material containing cobalt and triazine achieves a syngas production rate of 19.7 mmol g−1 h−1 (11:8 H2/CO), outperforming previously reported porous crystalline materials. This study provides a facile strategy for producing metallosalen-covalent organic frameworks of high quality and can accelerate their exploration in various applications.

Abstract Because of their tissue‐like mechanical performances, high biocompatibility, and adjustable functionality, hydrogels have become increasingly attractive materials for promoting wound healing. Chronic wounds include burn, diabetic, and infected wounds. Unlike common incision wounds, chronic wounds are more challenging to heal. To meet the clinical needs, multifunctional hydrogels should be fabricated and investigated. To guide future studies on the fabrication of hydrogel‐based chronic wound dressings, a review of advanced multifunctional hydrogels is necessary. Various hydrogels with advanced properties, such as antibacterial, antioxidant, bioadhesive, anti‐inflammatory, and wound healing properties, that can be used for skin burn wounds and diabetic wounds are summarised. Lastly, the prospects of advanced hydrogels for wound healing are elaborated.

Abstract Selenium (Se), a well‐known essential element in human health, plays a vital role in regulating metabolism owing to its antioxidative nature. However, organic Se compounds are toxic and cannot be used for biomedical applications. Selenium nanoparticles (SeNPs) exhibit low biological toxicity and high bioavailability; however, they are prone to aggregation and are extremely unstable, thereby diminishing their bioactivity and bioavailability. To overcome these limitations, ultra‐small, highly stable, and bioactive SeNPs were synthesised based on an in‐situ hybridisation strategy by using polyphenol‐grafted‐chitosan (GA‐CS) to control and restrict crystal growth of Se nanoparticles. The resultant GA‐CS@nSe exhibited an average particle size of ∼30 nm and was highly stable in aqueous solutions. In addition, GA‐CS@nSe displayed improved biocompatibility and enhanced antioxidative activity. Taken together, the authors provide a basis for polyphenol‐mediated construction of Se‐based particles with increased bioactivity.

Abstract Background Due to the heterogeneity of low‐grade gliomas (LGGs), the lack of randomized control trials, and strong clinical evidence, the effect of the extent of resection (EOR) is currently controversial. Aim To determine the best choice between subtotal resection (STR) and gross‐total resection (GTR) for individual patients and to identify features that are potentially relevant to treatment heterogeneity. Methods Patients were enrolled from the SEER database. We used a novel DL approach to make treatment recommendations for patients with LGG. We also made causal inference of the average treatment effect (ATE) of GTR compared with STR. Results The patients were divided into the Consis. and In‐consis. groups based on whether their actual treatment and model recommendations were consistent. Better brain cancer‐specific survival (BCSS) outcomes in the Consis. group was observed. Overall, we also identified two subgroups that showed strong heterogeneity in response to GTR. By interpreting the models, we identified numerous variables that may be related to treatment heterogeneity. Conclusions This is the first study to infer the individual treatment effect, make treatment recommendation, and guide surgical options through deep learning approach in LGG research. Through causal inference, we found that heterogeneous responses to STR and GTR exist in patients with LGG. Visualization of the model yielded several factors that contribute to treatment heterogeneity, which are worthy of further discussion.

The problem of constructing confidence intervals (CIs) for the difference between coefficients of variation of two zero-inflated gamma distributions was considered. As gamma distribution does not have closed form maximum likelihood estimators, the parameters of gamma distribution have to be estimated numerically. To this end, we proposed here four different generalized confidence intervals (GCIs) based on fiducial inference, Box-Cox transformation, parametric bootstrap and the method of variance of estimates recovery (MOVER). Performances of the four GCIs were evaluated and compared via extensive simulation. The simulation results showed that all four methods returned satisfactory results according to coverage probabilities, even for the setting of small sample sizes.

Abstract Background Clinical nurses are at high risk for compassion fatigue. Empathy is a prerequisite for compassion fatigue, and social support is an important variable in the process of reducing individual stress. However, the role of social support in the relationship between empathy and compassion fatigue remains unclear. This study explored whether social support mediates the relationship between empathy and compassion fatigue among clinical nurses. Methods A total of 992 clinical nurses were recruited through convenience sampling for a cross-sectional study in Central China. They completed the General Information Questionnaire, Perceived Social Support Scale, Professional Quality of Life Scale, and Jefferson Scale of Empathy. SPSS was used to conduct descriptive statistical analyses. Pearson’s or Spearman’s correlation analyses and AMOS were employed to build a structural equation model (SEM) to verify the mediating effect of social support on the relationship between empathy and compassion fatigue. Results The results indicated that the standardized direct effect of empathy on compassion fatigue was 0.127, and the standardized indirect effect of empathy on compassion fatigue through social support was 0.136. The mediation effect ratio between empathy and compassion fatigue was 51.7%. Conclusions Our findings show that social support mediates the relationship between empathy and compassion fatigue among clinical nurses. This finding suggests that increasing nurses’ social support can decrease the prevalence of compassion fatigue. Nursing managers should provide training related to flexibly adjusting empathy and educating nurses to establish effective social networks with family, friends, and colleagues to prevent compassion fatigue.

Urban water networks are important infrastructures for cities. However, urban water networks are vulnerable to natural disasters, causing interruptions in water. A timely analysis of the reliability of urban water networks to natural disasters can reduce the impact of natural disasters. In this paper, from the perspective of network reliability, the reliability analysis method of urban water networks under disaster is proposed. First, a reliability model is established with the flow rate of nodes in the water network as the index. Second, the user's demand is considered, as well as the impact of water pressure on water use. Therefore, a node failure model considering node water pressure and flow rate is established. The performance degradation of the urban water network is analyzed by analyzing the cascading failure process of the network. Third, the recovery process of the urban water network is analyzed, and the changes in the reliability of the urban water network before and after the disaster are analyzed to assess the ability of the urban water network to resist the disaster. Finally, an urban water network consisting of 28 nodes, 42 edges and 4 reservoirs is used to verify the effectiveness of the proposed method.

Accurate forecasting for photovoltaic power generation is one of the key enablers for the integration of solar photovoltaic systems into power grids. Existing deep-learning-based methods can perform well if there are sufficient training data and enough computational resources. However, there are challenges in building models through centralized shared data due to data privacy concerns and industry competition. Federated learning is a new distributed machine learning approach which enables training models across edge devices while data reside locally. In this paper, we propose an efficient semi-asynchronous federated learning framework for short-term solar power forecasting and evaluate the framework performance using a CNN-LSTM model. We design a personalization technique and a semi-asynchronous aggregation strategy to improve the efficiency of the proposed federated forecasting approach. Thorough evaluations using a real-world dataset demonstrate that the federated models can achieve significantly higher forecasting performance than fully local models while protecting data privacy, and the proposed semi-asynchronous aggregation and the personalization technique can make the forecasting framework more robust in real-world scenarios.

Abstract Background N6-methyladenosine (m6A) methylation modification is involved in the regulation of various biological processes, including inflammation, antitumor, and antiviral immunity. However, the role of m6A modification in the pathogenesis of autoimmune diseases has been rarely reported. Methods Based on a description of m6A modification and the corresponding research methods, this review systematically summarizes current insights into the mechanism of m6A methylation modification in autoimmune diseases, especially its contribution to rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). Results By regulating different biological processes, m6A methylation is involved in the pathogenesis of autoimmune diseases and provides a promising biomarker for the diagnosis and treatment of such diseases. Notably, m6A methylation modification is involved in regulating a variety of immune cells and mitochondrial energy metabolism. In addition, m6A methylation modification plays a role in the pathological processes of RA, and m6A methylation-related genes can be used as potential targets in RA therapy. Conclusions M6A methylation modification plays an important role in autoimmune pathological processes such as RA and SLE and represents a promising new target for clinical diagnosis and treatment, providing new ideas for the treatment of autoimmune diseases by targeting m6A modification-related pathways.

Abstract Background Breast cancer is, despite screening, not always detected early enough and is together with other tumor types known to shed genetic information in circulation. Unlike single-copy nuclear DNA, mitochondrial DNA (mtDNA) copies range from 100s to 10,000s per cell, thus providing a potentially alternative to identify potential missing cancer information in circulation at an early stage. Methods To characterize mitochondrial mutation landscapes in breast cancer, whole mtDNA sequencing and bioinformatics analyses were performed on 86 breast cancer biopsies and 50 available matched baseline cancer-free whole blood samples from the same individuals, selected from a cohort of middle-aged women in Sweden. To determine whether the mutations can be detected in blood plasma prior to cancer diagnosis, we further designed a nested case-control study (n = 663) and validated the shortlisted mutations using droplet digital PCR. Results We detected different mutation landscapes between biopsies and matched whole blood samples. Compared to whole blood samples, mtDNA from biopsies had higher heteroplasmic mutations in the D-loop region (P = 0.02), RNR2 (P = 0.005), COX1 (P = 0.037) and CYTB (P = 0.006). Furthermore, the germline mtDNA mutations had higher heteroplasmy level than the lost (P = 0.002) and de novo mutations (P = 0.04). The nonsynonymous to synonymous substitution ratio (dN/dS) was higher for the heteroplasmic mutations (P = 7.25 × 10−12) than that for the homoplasmic mutations, but the de novo (P = 0.06) and lost mutations (P = 0.03) had lower dN/dS than the germline mutations. Interestingly, we found that the critical regions for mitochondrial transcription: MT-HSP1 (odds ratio [OR]: 21.41), MT-TFH (OR: 7.70) and MT-TAS2 (OR: 3.62), had significantly higher heteroplasmic mutations than the rest of the D-loop sub-regions. Finally, we found that the presence of mt.16093T > C mutation increases 67% risk of developing breast cancer. Conclusions Our findings show that mitochondrial genetic landscape changes during cancer pathogenesis and positive selection of mtDNA heteroplasmic mutations in breast cancer. Most importantly, the mitochondrial mutations identified in biopsies can be traced back in matched plasma samples and could potentially be used as early breast cancer diagnostic biomarkers.

Because of its low concentration and low energy in an organic Rankine cycle (ORC) system, more than 50% of low-grade thermal energy with a temperature below 300 °C is not taken seriously. The relationship between changeable working condition parameters and operating parameters is typically not taken into account in a model while studying ORC systems. It is insufficient to analyze the system performance changes solely on changes in the performance parameters of the heat exchangers. Furthermore, a model perspective of the system control solution is absent from the steady-state control of the system when the heat source varies. In this paper, we created a system model for the application scenario of a 100–200 kW ORC system with brazed plate heat exchangers in order to address the aforementioned issues using MATLAB R2016b. Additionally, a sensitivity analysis of the system was conducted based on heat exchangers of performance variations. In addition, a modeling computation and adjustment scheme were put forth to guarantee that the system could continue to produce steady power production even when the temperature of the heat source fluctuated. Preliminary results showed that the system’s internal parameters included its evaporation pressure and condensation temperature. An increase in evaporation pressure will reduce the mass flow rate and heat flux of an evaporator, thus reducing the heat transfer coefficient. The two-phase region of the evaporator accounted for the highest proportion, of 70.22%, and continued to increase to 75.83%, followed by the supercooling region, and gradually decreasing. The utilization rate of the evaporator decreased from 74.85% to 38.32%. The system output power increased first and then decreased, with a maximum value of 153.11 kW. The system efficiency increased from 5.74% to 11.04%. The increase in condensation temperature increased the proportion of the two-phase region and the superheating region, and the mass flow rate did not change much. The increase in heat flux increased the heat transfer coefficient from 1721.31 W/(m2·K) to 2374.77 W/(m2·K), and the utilization rate of the evaporator decreased from 70.56% to 51.91%. The aforementioned change rules were used in the building of the steady-state regulation model to balance out the changes in the generating power as the heat source temperature increased. The model output was cross-checked and validated against pertinent experimental test literature data. The results of this research can serve as a valid and useful guide for ORC system design and practical applications.

Curcumin is widely recognized for its diverse antitumor properties, ranging from breast cancer to many other types of cancers. However, its role in the tumor microenvironment remains to be elucidated. In this study, we established a 3D tumor spheroids model that can simulate the growth environment of tumor cells and visualized the antitumor metabolic alteration caused by curcumin using mass spectrometry imaging technology. Our results showed that curcumin not only exerts a profound impact on the growth and proliferation of breast cancer cells but in situ multivariate statistical analysis also reveals the significant effect on the overall metabolic profile of tumor spheroids. Meanwhile, our visualization map characterized curcumin metabolic processes of reduction and glucuronidation in tumor spheroids. More importantly, abnormal metabolic pathways related to lipid metabolism and polyamine metabolism were also remodeled at the metabolite and gene levels after curcumin intervention. These insights deepen our comprehension of the regulatory mechanism of curcumin on the tumor metabolic network, furnishing powerful references for antitumor treatment.

High-entropy alloys (HEAs) have emerged as a novel class of materials with exceptional mechanical and corrosion properties, offering promising applications in various engineering fields. However, optimizing their performance through advanced manufacturing techniques, like laser cladding, remains an area of active research. This study investigated the effects of laser energy density on the mechanical and electrochemical properties of CoCrFeMnNi HEA coatings applied to Q235 substrates. Utilizing X-ray diffraction (XRD), this study confirmed the formation of a single-phase face-centered cubic (FCC) structure in all coatings. The hardness of the coatings peaked at 210 HV with a laser energy density of 50 J/mm2. Friction and wear tests highlighted that a coating applied at 60 J/mm2 exhibited the lowest wear rate, primarily due to adhesive and oxidative wear mechanisms, while the 55 J/mm2 coating showed increased hardness but higher abrasive wear. Electrochemical testing revealed superior corrosion resistance for the 60 J/mm2 coating, with a slow corrosion rate and minimal passivation tendency in contrast to the 55 J/mm2 coating. The comprehensive evaluation indicates that the HEA coating with an energy density of 60 J/mm2 exhibits exceptional wear and corrosion resistance.

The rapidly growing field of cannabinoid research is gaining recognition for its impact in neuropsychopharmacology and mood regulation. However, prenyltransferase (NphB) (a key enzyme in cannabinoid precursor synthesis) still needs significant improvement in order to be usable in large-scale industrial applications due to low activity and limited product range. By rational design and high-throughput screening, NphB’s catalytic efficiency and product diversity have been markedly enhanced, enabling direct production of a range of cannabinoids, without the need for traditional enzymatic conversions, thus broadening the production scope of cannabinoids, including cannabigerol (CBG), cannabigerolic acid (CBGA), cannabigerovarin (CBGV), and cannabigerovarinic acid (CBGVA). Notably, the W3 mutant achieved a 10.6-fold increase in CBG yield and exhibited a 10.3- and 20.8-fold enhancement in catalytic efficiency for CBGA and CBGV production, respectively. The W4 mutant also displayed an 9.3-fold increase in CBGVA activity. Molecular dynamics simulations revealed that strategic reconfiguration of the active site’s hydrogen bonding network, disulfide bond formation, and enhanced hydrophobic interactions are pivotal for the improved synthetic efficiency of these NphB mutants. Our findings advance the understanding of enzyme optimization for cannabinoid synthesis and lay a foundation for the industrial-scale production of these valuable compounds.

Green process innovation is an important strategy in the high-quality development of enterprises. Digital technology is becoming a key factor in helping businesses address environmental issues and contributes to their green process innovation and sustainable growth. Nevertheless, there is a lack of studies on how particular digital technology categories affect corporate green process innovation. Artificial intelligence (AI) is an important part of digitalization as it can provide new technical means and guidance for enterprise’s innovation of green processes. This study aims to fills this research gap by revealing the logical relationship between digital technology and the green development of enterprises. Using China’s A-share-listed companies as the research object from 2013 to 2022, this study employed a two-way fixed-effects model and investigated the impact of artificial intelligence (AI) on corporate green process innovation and the moderating effect of multidimensional intellectual capital. The results revealed that AI positively impacts corporate green process innovation. Human capital, structural capital, employed capital, and relational capital strengthen this positive effect. Robustness tests validated these conclusions. This study expands the literature on digital technology and corporate green innovation and provides a reference for enterprises to implement green practices using digital technology.

On 1 September 2022, a landslide in Hongya Village, Weiyuan Town, Huzhu Tu Autonomous County, Qinghai Province, caused significant casualties and economic losses. To mitigate such risks, InSAR technology is employed due to its wide coverage, all-weather operation, and cost-effectiveness in detecting landslides. In this study, focusing on the landslide in Hongya Village, SBAS-InSAR and Sentinel-1A satellite data from July 2021 to September/October 2022 were used to accurately identify the areas of active landslides and to analyze the landslide deformation trends, in combination with the geological characteristics of the landslides and rainfall data. The results showed that strong deformation was detected in the middle and back of the landslide in Hongya Village, with a maximum deformation rate of approximately -13 mm/year. The surface of the landslide consisted of mainly Upper Pleistocene wind-deposited loess, which is extremely sensitive to water. The deformation of the landslide was closely related to the rainfall, and the deformation of the landslide increased with the increase in rainfall. The research results prove that the combination of ascending and descending orbit data based on SBAS-InSAR technology is highly feasible in the field of landslide deformation monitoring and is of great practical significance for landslide disaster prevention and mitigation.

Rotor-type cross-media vehicles always induce considerably complex mixed air–water flows when approaching the water surface, resulting in relative thrust loss and structural damage on rotor. The interactions between a water surface and rotor wake bring potential risks to the cross-media process, which is known as the near-water effect of the rotor. In this paper, experimental investigations are used to explore the fluid dynamics of the near-water effect of the rotor. Qualitative droplet observation was carried out on the 0.25 m and 0.56 m diameter commercial rotor blades and the 0.07 m diameter ducted fan near the water surface first to gain a qualitative understanding of droplet characteristics. The results show that the rotor wake caused water surface deformation, droplet tearing off, splashing, and entrainment into the rotor disk. The depression formed by the rotor downwash flow impacting the water surface is named as three modes: dimpling, splashing, and penetrating, and the correlation between the depression modes and the aerodynamic characteristics of the rotor is primary analyzed. The flow mechanisms of dimpling mode were studied using the particle image velocimetry (PIV) technique. The results showed that the cavity and liquid crown obviously alter the flow direction of water surface jets, but not all rotors near water enter the vortex ring state. Two splashing mechanisms were revealed, including the direct ejection of droplets at the rim of depression and the tearing of liquid crown by the water surface jets. The blade tip vortex in the surface jet is a potential cause of entrainment into the rotor disk and secondary breakup of the droplet.

Our target USH reservoir in the D oilfield is characterized by “inverse rhythm” deposition with the noticeable features of “high porosity and low permeability”. The reservoir has been developed with waterflooding using horizontal wells. Due to the strong heterogeneity of the reservoir, water channeling is severe, and the water cut has reached 79%. Considering the high temperature and high salinity reservoir conditions, polymer microspheres (PMs) were selected to realize conformance control. In this study, characterization of the polymer microsphere suspension was achieved via morphology, size distribution, and viscosity measurement. Furthermore, a multi-scale visualization study of the reservoir development process, including waterflooding, polymer microsphere flooding, and subsequent waterflooding, was conducted using macro-scale coreflooding and calcite-etched micromodels. It was revealed that the polymer microspheres could swell in the high salinity brine (170,000 ppm) by 2.7 times if aged for 7 days, accompanied by a viscosity increase. This feature is beneficial for the injection at the wellbore while swelled to work as a profile control agent in the deep formation. The macro-scale coreflood with a 30 cm × 30 cm × 4.5 cm layer model with 108 electrodes installed enabled the oil distribution visualization from different perpendicular cross sections. In this way, the in situ conformance control ability of the polymer microsphere was revealed both qualitatively and quantitatively. Furthermore, building on the calcite-etched visible micro-model, the pore-scale variation of the residual oil when subjected to waterflooding, polymer microsphere waterflooding, and subsequent waterflooding was collected, which revealed the oil displacement efficiency increase by polymer microspheres directly. The pilot test in the field also proves the feasibility of conformance control by the polymer microspheres, i.e., more than 40,000 bbls of oil increase was observed in the produces, accompanied by an obvious water reduction.

To meet the demands for high-temperature performance and lightweight materials in aerospace engineering, the Au-Ni solder is often utilized for joining dissimilar materials, such as Ti3Al-based alloys and Ni-based high-temperature alloys. However, the interaction between Ti and Ni can lead to the formation of brittle phases, like Ti2Ni, TiNi, and TiNi3, which diminish the mechanical properties of the joint and increase the risk of crack formation during the welding process. Cu doping has been shown to enhance the mechanical properties and high-temperature stability of the Au-Ni brazed joint’s central area. Due to the difficulty in accurately controlling the solid solution content of Cu in the Au-Ni alloy, along with the high cost of Au, traditional experimental trial-and-error methods are insufficient for the development of Au-based solders. In this study, first principles calculations based on density functional theory were employed to analyze the effect of Cu content on the stability of the Au-2.0Ni-xCu (x = 0, 0.25, 0.5, 0.75, 1.0, 1.25 wt%) alloy phase structure. The thermal properties of the alloy were determined using Gibbs software fitting. The results indicate that the Au-2.0Ni-0.25Cu alloy exhibits the highest plastic toughness (B/G = 5.601, ν = 0.416, Cauchy pressure = 73.676 GPa) and a hardness of 1.17 GPa, which is 80% higher than that of Au-2.0Ni. This alloy balances excellent strength and plastic toughness, meeting the mechanical performance requirements of brazed joints. The constant pressure specific heat capacity (Cp) of the Au-2.0Ni-xCu alloy is higher than that of Au-2.0Ni and increases with Cu content. At 1000 K, the Cp of the Au-2.0Ni-0.25Cu alloy is 35.606 J·mol−1·K−1, which is 5.88% higher than that of Au-2.0Ni. The higher Cp contributes to enhanced high-temperature stability. Moreover, the linear expansion coefficient (CTE) of the Au-2.0Ni-0.25Cu alloy at 1000 K is 8.76 × 10−5·K−1, only 0.68% higher than Au-2.0Ni. The lower CTE helps to reduce the risk of solder damage caused by thermal stress. Therefore, the Au-2.0Ni-0.25Cu alloy is more suitable for brazing applications in high-temperature environments due to its excellent mechanical properties and thermal stability. This study provides a theoretical basis for the performance optimization and engineering application of the Au-2.0Ni-xCu alloy as a gold-based solder.

Numerical simulations are performed for flows over a circular cylinder at a Reynolds number ranging from 150 to 5000, and Mach number of 0.2, to assess the predictive capability of URANS and hybrid RANS/LES for acoustic waves generation and propagation. Complementary direct numerical simulations (DNS) are performed to generate validation datasets and to provide more insight into the problem. DNS predictions show that noise induced by the vortex shedding is radiated primarily at a 90-degree angle with respect to the wake direction and dictates the dominant frequency of the sound pressure waves. Turbulence dominates the noise in the near-field wake, resulting in a broadband pressure spectrum. URANS both underpredicts and overpredicts the noise levels in the wake region and in the direction normal to the freestream flow, respectively, which is attributed to its inability to accurately predict the turbulent kinetic energy content. Hybrid RANS/LES computations, using a second-order low-dissipation optimization-based gradient reconstruction scheme on a grid that is three times coarser than the DNS, provide an accurate prediction of the far-field noise levels, except in the wake region, where they are overpredictive.

The subcellular localization of messenger RNA (mRNA) not only helps us to understand the localization regulation of gene expression but also helps to understand the relationship between RNA localization pattern and human disease mechanism, which has profound biological and medical significance. Several predictors have been proposed for predicting the subcellular localization of mRNA. However, there is still considerable room for improvement in their predictive performance, especially regarding multi-label prediction. This study proposes a novel multi-label predictor, DRpred, for mRNA subcellular localization prediction. This predictor first utilizes Bayesian networks to capture the dependencies among labels. Subsequently, it combines these dependencies with features extracted from mRNA sequences using Word2vec, forming the input for the predictor. Finally, it employs a neural network combining BiLSTM and an attention mechanism to capture the internal relationships of the input features for mRNA subcellular localization. The experimental validation on an independent test set demonstrated that DRpred obtained a competitive predictive performance in multi-label prediction and outperformed state-of-the-art predictors in predicting single subcellular localizations, obtaining accuracies of 82.14%, 93.02%, 80.37%, 94.00%, 90.58%, 84.53%, 82.01%, 79.71%, and 85.67% for the chromatin, cytoplasm, cytosol, exosome, membrane, nucleolus, nucleoplasm, nucleus, and ribosome, respectively. It is anticipated to offer profound insights for biological and medical research.

To address the limitations of the Deep Deterministic Policy Gradient (DDPG) in robot path planning, we propose an improved DDPG method that integrates kinematic analysis and D* algorithm, termed D*-KDDPG. Firstly, the current work promotes the reward function of DDPG to account for the robot’s kinematic characteristics and environment perception ability. Secondly, informed by the global path information provided by the D* algorithm, DDPG successfully avoids getting trapped in local optima within complex environments. Finally, a comprehensive set of simulation experiments is carried out to investigate the effectiveness of D*-KDDPG within various environments. Simulation results indicate that D*-KDDPG completes strategy learning within only 26.7% of the training steps required by the original DDPG, retrieving enhanced navigation performance and promoting safety. D*-KDDPG outperforms D*-DWA with better obstacle avoidance performance in dynamic environments. Despite a 1.8% longer path, D*-KDDPG reduces navigation time by 16.2%, increases safety distance by 72.1%, and produces smoother paths.

Hawthorn (Crataegus pinnatifida Bunge) has been highlighted as an excellent source of a variety of bioactive polymers, which has attracted increasing research interest. Pectin, as a kind of soluble dietary fiber in hawthorn, is mainly extracted by hot water extraction and ultrasonic or enzymatic hydrolysis and is then extensively used in food, pharmaceutical, and nutraceutical industries. Numerous studies have shown that hawthorn pectin and its derived oligosaccharides exhibit a wide range of biological activities, such as antioxidant activity, hypolipidemic and cholesterol-reducing effects, antimicrobial activity, and intestinal function modulatory activity. As discovered, the bioactivities of hawthorn pectin and its derived oligosaccharides were mainly contributed by structural features and chemical compositions and were highly associated with the extraction methods. Additionally, hawthorn pectin is a potential resource for the development of emulsifiers and gelling agents, food packaging films, novel foods, and traditional medicines. This review provides a comprehensive summary of current research for readers on the extraction techniques, functional characteristics, structure–activity relationship, and applications in order to provide ideas and references for the investigation and utilization of hawthorn pectin and its derived oligosaccharides. Further research and development efforts are imperative to fully explore and harness the potential of hawthorn pectin-derived oligosaccharides in the food and medicine fields.

Landslides are most severe in the mountainous regions of southwestern China. While landslide identification provides a foundation for disaster prevention operations, methods for utilizing multi-source data and deep learning techniques to improve the efficiency and accuracy of landslide identification in complex environments are still a focus of research and a difficult issue in landslide research. In this study, we address the above problems and construct a landslide identification model based on the shifted window (Swin) transformer. We chose Ya’an, which has a complex terrain and experiences frequent landslides, as the study area. Our model, which fuses features from different remote sensing data sources and introduces a loss function that better learns the boundary information of the target, is compared with the pyramid scene parsing network (PSPNet), the unified perception parsing network (UPerNet), and DeepLab_V3+ models in order to explore the learning potential of the model and test the models’ resilience in an open-source landslide database. The results show that in the Ya’an landslide database, compared with the above benchmark networks (UPerNet, PSPNet, and DeepLab_v3+), the Swin Transformer-based optimization model improves overall accuracies by 1.7%, 2.1%, and 1.5%, respectively; the F1_score is improved by 14.5%, 16.2%, and 12.4%; and the intersection over union (IoU) is improved by 16.9%, 18.5%, and 14.6%, respectively. The performance of the optimized model is excellent.

The emerging upward shield method (USM) for constructing vertical shafts has been used in various projects, including the Midosuji utility tunnel in Japan. A scaled-down model testing system, featuring a geometric similarity ratio of 1:30, was developed specifically for studying the USM. This system incorporates sand inflow control, propulsion control, data acquisition, and water level control. It facilitates detailed observation and recording of parameters such as vertical displacement of surface soil layers, support force at the excavation face, and earth pressure within the model box. Consequently, it enables investigation into the excavation face instability process, modes, and the formation and evolution of the soil arch zone above the excavation face during upward shield tunneling. Additionally, through the application of particle image velocimetry (PIV) technology and GeoPIV-RG software v1.1, quantitative analysis of soil displacement fields during excavation face instability is conducted, capturing microscopic displacements and deformations of soil planes. This approach more accurately elucidates the accuracy of understanding the dynamic response of soil. Pre-test research using the model testing system explores the variation patterns of excavation face load displacement, vertical earth pressure within the failure zone, surface displacement, and internal soil displacement during the instability process. Analysis reveals that excavation face load variation typically progresses through three stages: rapid growth, slow growth, and descent. Moreover, vertical earth pressure shifts upward in tandem with excavation face displacement, while overall surface displacement initially shows slight settlement followed by accelerated uplift.

In response to the issue of weak laser connection strength between 304 stainless steel and the carbon fiber-reinforced polymer PCCF30, this study proposes the addition of a polyethylene terephthalate (PET) intermediate layer between 304 stainless steel and PCCF30, along with surface texture pretreatment of the stainless steel surface, to enhance the joint connection strength. First, three types of surface textures (vertical, wavy, and vertical plus wave) were investigated for their effect on joint quality. Once the optimal texture type was determined, the effect of texture scanning repetition on the surface morphology and groove cross-sectional geometry of 304 stainless steel was examined. The joint strengths achieved by adding intermediate layers and employing different surface texture treatment methods were compared, followed by a comparison of the joint strengths obtained from different pretreatment methods. Finally, the connection mechanism of the joint was analyzed. The results indicated that the maximum joint strength achieved through the vertical and wavy texture design was 4.39 MPa, which is 3.3 times greater than that achieved without reinforcement. Moreover, the maximum joint strength achieved with the addition of a PET intermediate layer and surface texture composite treatment was 11.85 MPa, which is approximately nine times greater than that achieved via direct connection. The inclusion of a PET intermediate layer enhances the fluidity of the molten polymer at the joint, facilitating better filling of the grooves with surface texture. This strengthens the mechanical anchoring effect of the joint and contributes to the improvement in the joint’s connection strength. An XPS analysis revealed that after multiple etchings of the joint interface with an added intermediate layer, the Cr in the stainless steel chemically bonded with the PET, resulting in the formation of Cr–O–C chemical bonds, which is advantageous for enhancing joint quality.

The ecological stoichiometric characteristics of soil elements have greatly enhanced our understanding of the circulation of soil nutrients. However, there is limited knowledge regarding the alteration of carbon, nitrogen, and phosphorus stoichiometric ratios in deep soil after afforestation. To examine the variations in stoichiometric ratios of soil elements with different vegetation types, restoration times, and soil depths, we collected soil samples from grassland, Caragana korshinskii shrubland, and Picea asperata forestland at different stand ages (10a, 25a, and 40a) in Xining City, which is located on the Loess Plateau. Our results showed that, at 25a, the carbon-to-nitrogen (C:N) and carbon-to-phosphorus (C:P) ratios were significantly higher in the grassland soil than under other vegetation types, whereas the nitrogen-to-phosphorus (N:P) ratio had no significant difference among the three vegetation types. At 40a, the ratios of soil C:N, C:P, and N:P in the shrubland were the highest. With the increasing of the restoration time, the ratios of soil C:N, C:P, and N:P in grassland with 25a became higher than for 40a or 10a. The ratios in the shrubland were highest at 40a, followed by 25a and then 10a, while the ratios in the forestland showed no significant difference. At 40a, the soil C:N, C:P, and N:P ratios of shrubland were highest at the soil depth of 40–100 cm. The soil C:N, C:P, and N:P ratios showed positive correlations with soil ammonium nitrogen and nitrate nitrogen, and the soil N:P ratios showed a negative correlation with soil available phosphorus. Plant diversity significantly influenced the soil stoichiometric ratio of the upper soil layer. In the upper soil layer (0–40 cm), species richness showed a positive correlation with soil C:N, C:P, and N:P ratios, and the Margalef index exhibited a positive correlation with soil C:N and C:P ratios. The results of this study indicate that the stoichiometric ratio and nutrient availability of Caragana korshinskii shrubland were the highest over time. Therefore, these findings can be served as a valuable reference for local revegetation and ecological restoration.

Sixteen novel antioxidant peptides from Asian swamp eel (ASE) were identified in previous studies. However, their chemical and cellular antioxidant mechanisms remain unclear. Molecular docking of these peptides with ABTS and DPPH radicals revealed the critical role of hydrogen bonding and Pi–Pi stacking hydrophobic interactions between hydrophobic amino acid residues and free radicals. Residues, such as tryptophan, proline, leucine, and valine, played significant roles in these interactions. All these peptides exhibited notable erythrocyte morphoprotective effects in a model of AAPH-induced oxidative damage of human erythrocytes. Erythrocyte hemolysis was reduced primarily through the modulation of both non-enzymatic (GSH/GSSG) and enzymatic antioxidant systems (SOD, CAT, and GSH-Px) by these peptides. A decrease in levels of MDA, LDH release, and hemoglobin oxidation was observed. Among the peptides, VLYPW demonstrated superior chemical and cellular antioxidant activities, which may be attributed to its higher levels of tyrosine and tryptophan, as well as to its increased hydrophobic amino acid content.

To refine the grain size and improve the mechanical properties of ultrahigh-strength aluminum alloy (Al-10Zn-1.9Mg-1.6Cu-0.12Zr), the Al-Ti-B-Er grain refiner was prepared by the melt reaction method using the aluminum melt and Al + Ti + B precursor. The results exhibit that the Al-Ti-B-Er grain refiner is mainly composed of a block TiAl3 phase, and loose agglomerated nano-sized TiB2 and Al3Er phases. The microstructure of ultrahigh-strength aluminum is significantly affected by the Al-Ti-B-Er refiner, which changes from dendrite to equiaxial grain with increasing Al-Ti-B-Er content, and the size of the eutectic phase is significantly refined. The high-efficiency refinement of Al-Ti-B-Er is due to Er promoting the uniform distribution of TiAl3 particles and the formation of loose agglomerated nano-sized TiB2 particles. The optimal addition content of Al-Ti-B-Er into ultrahigh-strength aluminum alloys is 1 wt%, whose grain size is approximately 40 µm. Additionally, the strength and ductility of ultrahigh-strength aluminum alloys are simultaneously improved by adding 1wt% Al-Ti-B-Er after the T6 treatment, reaching 756 MPa and 20%, respectively. This enhancement in strength and ductility is mainly attributed to grain refinement and the eutectic phase refinement.

Ore is a crucial component in the process of industrialization, and its crushing is a practice that is inextricably linked to our society. This study aims to simulate the crushing process of minerals in a comminution device using the Discrete Element Method (DEM) by characterizing the bonding parameters of mineral particles. Utilizing the EDEM software (2018) for discrete element simulations, the study investigated the influence of bonding parameters on the compressive strength and other performance indicators of the particle bonding model. The study was executed through the application of a Box–Behnken Design (BBD) and Response Surface Methodology (RSM), which facilitated the construction of a second-order response surface regression model. The optimal values for normal stiffness per unit area, shear stiffness per unit area, critical normal stress, and critical shear stress were meticulously determined. The subsequent simulation experiments strongly verify the feasibility of the proposed characterization method for key parameters.

The accurate evaluation of aerodynamic characteristics is a prerequisite and foundation for the design of high-performance aerodynamic shapes, navigation guidance, and strength of projectiles. The nonlinearity of aerodynamic calculations for a projectile is high, and the modeling and simulation are difficult, especially under the high-angle of attack flight conditions. Small variations in flight conditions, and structural parameters, etc., may cause large deviations in aerodynamic responses. Taking a small cylindrical projectile as an example, and to realize its attitude control, it is necessary to conduct aerodynamic characteristics analysis on it and analyze the main influencing factors of its aerodynamic characteristics parameters. In this paper, the finite volume method is used to solve the three-dimensional unsteady N-S equation, combined with the SST k-ω turbulence model, the overlapping grid technology, and the forced pitching vibration method, and the aerodynamic characteristics analysis model of the projectile is established, which realizes the accurate simulation of the surrounding flow field, aerodynamic coefficients, and dynamic derivative of the projectile under different flight conditions. On this basis, the Sobol global sensitivity analysis method based on the augmented radial basis function surrogate model of aerodynamics characteristics and Latin hypercube sampling is used to efficiently analyze and obtain the main influence parameters of cylindrical projectile aerodynamic characteristics. This paper provides a basic theory and fast algorithm for subsequent engineering system design, which has important theoretical and engineering value.

This paper proposes an enhanced multi-strategy sparrow search algorithm to optimize the trajectory of a six-axis industrial robot, addressing issues of low efficiency and high vibration impact on joints during operation. Initially, the improved D-H parametric method is employed to establish both forward and inverse kinematic models of the robot. Subsequently, a 3-5-3 mixed polynomial interpolation trajectory planning approach is applied to the robot. Building upon the conventional sparrow algorithm, a two-dimensional Logistic chaotic system initializes the population. Additionally, a Levy flight strategy and nonlinear adaptive weighting are introduced to refine the discoverer position update operator, while an inverse learning strategy enhances the vigilante position update operator. These modifications boost both the local and global search capabilities of the algorithm. The improved sparrow algorithm, based on 3-5-3 hybrid polynomial trajectory planning, is then used for the time-optimal trajectory planning of the robot. This is compared with traditional sparrow search algorithm and particle swarm algorithm optimization results. The findings indicate that the proposed enhanced sparrow search algorithm outperforms both the standard sparrow algorithm and the particle swarm algorithm in terms of convergence speed and accuracy for robot trajectory optimization. This can lead to the increased work efficiency and performance of the robot.

The rational design of magnetic carbon composites, encompassing both their composition and microstructure, holds significant potential for achieving exceptional electromagnetic wave-absorbing materials (EAMs). In this study, FeCo@CM composites were efficiently fabricated through an advanced microwave plasma-assisted reduction chemical vapor deposition (MPARCVD) technique, offering high efficiency, low cost, and energy-saving benefits. By depositing graphitized carbon microspheres, the dielectric properties were significantly enhanced, resulting in improved electromagnetic wave absorption performances through optimized impedance matching and a synergistic effect with magnetic loss. A systematic investigation revealed that the laminar-stacked structure of FeCo exhibited superior properties compared to its spherical counterpart, supplying a higher number of exposed edges and enhanced catalytic activity, which facilitated the deposition of uniform and low-defect graphitized carbon microspheres. Consequently, the dielectric loss performance of the FeCo@CM composites was dramatically improved due to increased electrical conductivity and the formation of abundant heterogeneous interfaces. At a 40 wt% filling amount and a frequency of 7.84 GHz, the FeCo@CM composites achieved a minimum reflection loss value of −58.2 dB with an effective absorption bandwidth (fE) of 5.13 GHz. This study presents an effective strategy for developing high-performance EAMs.

Background: Eurotium cristatum (E. cristatum) is the probiotic fungus in Fu-brick tea, with which fermentation brings a unique flavor and taste and health-promoting effects. Tartary buckwheat leaves are rich in functional active substances such as flavonoids and phenolic compounds, yet are not effectively utilized. Methods: Tartary buckwheat leaves were processed into raw green tea first and subsequently fermented with E. cristatum to develop a novel fermented leaf tea. The tea quality was evaluated by the aspects of the sensory scores by E-tongue, the volatile compounds by HS-SPME-GC-MS, the non-volatile profile by biochemical and UPLC-MS/MS methods and the antioxidant activity by the colorimetric assay. Results: Fermented leaf tea displayed a golden yellow color, a unique “flower” aroma and a dark-tea taste, with an improved sensory acceptability. Fermentation raised the content of volatile heterocyclic and aromatic compounds, alkenes and other aromatic components, which produced a unique floral flavor. The proportion of sour, bitter and astringency accounting non-volatile compounds such as phenolic acids and amino acids decreased, while the proportion of umami and sweet accounting substances such as responsible amino acids increased. Fermented leaf tea displayed a relative stronger total antioxidant activity against ABTS. Conclusion: E. cristatum fermentation exerted positive effects on Tartary buckwheat leaf tea quality.

For conducting scientific research at depths in the ocean, deep-sea probes are essential pieces of equipment. The cylindrical shell is the most sensible and rational packaging structure for these detectors. New technical challenges for enhancing the pressure resistance and lightweight design of the pressure-resistant cylindrical shell arise from the need to ensure that the detector packaging structure can withstand the immense water pressure at tens of thousands of meters in the underwater environment, while simultaneously reducing the detector packaging structure’s self-weight. This article examines the detection system’s deep-sea pressure-resistant cylindrical shell. To address the issue of the pressure-resistant shell’s insufficient ability to counteract the overall instability caused by the inability to form unstable half-waves in the radial direction when the ring rib pressure-resistant shell experiences it, a design method for the ribs inside the unequal-stiffness pressure-resistant cylindrical shell is suggested. The shell’s instability pressure increases by 9.65 MPa following the stiffness adjustment. Simultaneously, in order to attain even more lightweight optimization, the optimal inner rib section was obtained by applying the orthogonal topology optimization method, which also reduced the weight by 106.8 g and effectively improved the compression stability of the high-pressure cylindrical shell structure. Based on this, key optimization variables were found by performing sensitivity analysis on the cylindrical shell structure’s parameters. Then, with lightweighting as the primary objective, the high-pressure-resistant cylindrical shell’s optimal structural parameters were found using a multi-objective optimization process using the second-generation fast non-dominated genetic algorithm (NSGA-2). This resulted in a weight reduction of 1.2492 kg, or 17.26% of the original pressure-resistant shell. This has led to the development of a lightweight, highly pressure-resistant method for packaging marine exploration equipment structures.

Seagrass serves as a quintessential reservoir for obligate marine Lulworthiaceae fungi. Our current knowledge of the mycological diversity associated with seagrass in Hong Kong remains poor. We analyzed the diversity of fungi associated with the most widely distributed seagrass species in Hong Kong Halophila ovalis (Hydrocharitaceae), using a combination of culture-based methods and high-throughput amplicon sequencing. Halophilomyces hongkongensis, a novel fungal species in a newly proposed genus within the Lulworthiaceae family, was isolated from H. ovalis roots and rhizomes. The novel fungus showed distinct morphological characteristics, while both combined 18S-28S and internal transcribed spacer (ITS) phylogenetic trees based on maximum likelihood and Bayesian methods supported its discrimination from other existing Lulworthiaceae members. The ITS2 region in the Illumina sequencing results of multiple H. ovalis compartments, water, and adjacent non-seagrass sediments revealed continuous recruitment of H. hongkongensis by H. ovalis throughout the year despite dramatically fluctuating environmental conditions, with remarkably high proportions of this taxon found in root and rhizome internal tissues, possibly indicating a strong and specialized relationship established between the Lulworthiaceae fungal partner and its seagrass host. The inhibitory abilities exhibited by H. hongkongensis against Staphylococcus aureus SA29213 and ATCC 43300 (methicillin-resistant) may imply its capacity in producing (novel) antibacterial compounds. The discovery of H. hongkongensis as the first novel Lulworthiaceae taxon in Hong Kong, along with its distributional pattern in the seagrass meadow, provides valuable insights into the systematics and ecology of this strictly marine fungal family.

Abstract Background In September 2019, the “4 + 7” centralized procurement pilot program was expanded nationwide aiming at reducing drug prices by means of volume-based procurement and using accredited generic drugs for branded drug substitutes. Given the current uncertain effect of the policy outside pilot areas, this study was conducted to evaluate the impact of the National Volume-based Procurement policy on the use of policy-related drugs after expansion. Method A single-group interrupted time series was applied using drug purchase data, covering 25 months from December 2018 to December 2020. Drugs related to the centralized procurement policy were selected as samples, including 25 first-batch policy-related drugs and 56 alternative drugs. Centralized procured drugs can be divided into bid-winning and non-winning products, where non-winning products were sorted into generic and branded drugs, and alternative products were classified according to different degrees of substitution. Purchase volume, expenditures, and daily costs were measured. Results After the implementation of the policy, a significant increase was associated with the volume of bid-winning drugs (p

Using the AlCoCrFeNi high entropy alloy to enhance 2124 aluminum alloy composites is an effective way to solve its application limitations in friction and wear. In this study, the composites were prepared by mechanical alloying and spark plasma sintering. The results show that the diffusion layer was formed at the interface between high entropy particles and the matrix, and there were dislocations and significant lattice distortions near the interface. In addition, the friction coefficient (0.399) and wear rate (7.05∗10−4 mm3 N−1 m−1) of the composites were lower than the 2124 aluminum alloys. Moreover, the yield strength, tensile strength and compressive strength of composites were 396.2 MPa, 498.3 MPa, and 560.5 MPa, respectively. And the yield strength of the composite was almost 2 times more than that of AA2124. This work discussed the effect of interface on mechanical properties and explain the formation of diffusion layer. The present study provides a strategy to solve the lack of wear resistance and strength of composites.

We study the existence of positive solutions for a class of one-dimensional superlinear $ (p, q) $ -Laplacian with Sturm-Liouville boundary conditions. We allow the reaction term to be singular at 0 with infinite semipositone behavior. Our approach depends on Amann's fixed point theorem.

Abstract Despite the accumulating evidence linking the development of Alzheimer’s disease (AD) to the aggregation of Aβ peptides and the emergence of Aβ oligomers, the FDA has approved very few anti-aggregation-based therapies over the past several decades. Here, we report the discovery of an Aβ peptide aggregation inhibitor: an ultra-small nanodot called C3N. C3N nanodots alleviate aggregation-induced neuron cytotoxicity, rescue neuronal death, and prevent neurite damage in vitro. Importantly, they reduce the global cerebral Aβ peptides levels, particularly in fibrillar amyloid plaques, and restore synaptic loss in AD mice. Consequently, these C3N nanodots significantly ameliorate behavioral deficits of APP/PS1 double transgenic male AD mice. Moreover, analysis of critical tissues (e.g., heart, liver, spleen, lung, and kidney) display no obvious pathological damage, suggesting C3N nanodots are biologically safe. Finally, molecular dynamics simulations also reveal the inhibitory mechanisms of C3N nanodots in Aβ peptides aggregation and its potential application against AD.