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Abstract Pulmonary arterial hypertension (PAH) is a fatal disease featured by high morbidity and mortality. Although Cordycepin is known for its anti-inflammatory, antioxidant and immune-enhancing effects, its role in PAH treatment and the underlying mechanisms remain unclear. The therapeutic effects of Cordycepin on rats with PAH were investigated using a monocrotaline (MCT)-induced rat model. The metabolic effects of Cordycepin were assessed based on the plasma metabolome. The potential mechanisms of Cordycepin in PAH treatment were investigated through transcriptome sequencing and validated in pulmonary artery smooth muscle cells (PASMC). Evaluations included hematoxylin and eosin staining for pulmonary vascular remodeling, CCK-8 assay, EDU, and TUNEL kits for cell viability, proliferation, and apoptosis, respectively, and western blot for protein expression. Cordycepin significantly reduced right ventricular systolic pressure (RVSP) and right ventricular hypertrophy index (RVHI) in PAH rats, and mitigated pulmonary vascular remodeling. Plasma metabolomics showed that Cordycepin could reverse the metabolic disorders in the lungs of MCT-induced PAH rats, particularly impacting linoleic acid and alpha-linolenic acid metabolism pathways. Transcriptomics revealed that the P53 pathway might be the primary pathway involved, and western blot results showed that Cordycepin significantly increased P53 and P21 protein levels in lung tissues. Integrated analysis of transcriptomics and metabolomics suggested that these pathways were mainly enriched in linoleic acid metabolism and alpha-linolenic acid metabolism pathway. In vitro experiments demonstrated that Cordycepin significantly inhibited the PDGFBB (PD)-induced abnormal proliferation and migration of PASMC and promoted PD-induced apoptosis. Meanwhile, Cordycepin enhanced the expression levels of P53 and P21 proteins in PD-insulted PASMC. However, inhibitors of P53 and P21 eliminated these effects of Cordycepin. Cordycepin may activate the P53–P21 pathway to inhibit abnormal proliferation and migration of PASMC and promote apoptosis, offering a potential approach for PAH treatment.

Purpose: This study aims to explore the key factors influencing design students' acceptance of AIGC-assisted design courses, providing specific strategies for course design to help students better learn this new technology and enhance their competitiveness in the design industry. The research focuses on evaluating technological and course-level factors, providing actionable insights for course developers. Design/methodology/approach: The research establishes and validates evaluation dimensions and indicators affecting acceptance using structured questionnaires to collect data and employs factor analysis and weight analysis to determine the importance of each factor. Findings: The results of the study reveal that the main dimensions influencing student acceptance include technology application and innovation, teaching content and methods, and extracurricular learning support and resources. Regarding indicators, data privacy, timeliness of extracurricular learning support, and availability of extracurricular learning resources are identified as the most critical factors. Originality: The uniqueness of this study lies in providing specific course design strategies for AIGC-assisted design courses based on the weight analysis results for different dimensions and indicators. These strategies aim to help students better adapt to these courses and enhance their acceptance. Furthermore, the conclusions and recommendations of this study offer valuable insights for educational institutions and instructors, promoting further optimization and development of AIGC-assisted design courses.

Diabetes can lead to a disorder of bone-fat balance, a significant cause of osteoporosis due to changes in environmental factors. Baicalin (Bai), an active ingredient of Scutellaria baicalensis, has been confirmed to possess antioxidant, hypoglycemic, and anti-osteoporotic effects. However, a comprehensive understanding of Bai's influence on diabetic osteoporosis (DOP), including its effects and underlying mechanisms, remains elusive. This study investigated Bai's impact on the bone-fat equilibrium in rats with DOP. The results indicated that Bai alleviated bone damage in DOP by promoting osteogenesis and inhibiting adipogenesis. Concurrently, through bioinformatics analysis, it was suggested that Bai's mechanism of action might involve the P38-MAPK pathway. In vitro, Bai was found to enhance the development of bone marrow mesenchymal stem cells (BMSCs) towards osteogenic lineages while suppressing their differentiation towards adipogenic lineages. It was discovered that Bai's promotion of BMSC osteogenic differentiation depends on the P38-MAPK pathway. Additionally, the synergistic effect mediated by Bai and P38-MAPK inhibitor suppressed BMSC adipogenic differentiation. Our research indicates that the P38-MAPK pathway play a role in Bai's effects on the osteogenic-adipogenic differentiation of BMSCs, showcasing the potential for DOP treatment. This study highlights Bai's ability to regulate the equilibrium between bone and fat, presenting a novel approach to adressing DOP.

Abstract Background Chronic Thromboembolic Pulmonary Hypertension (CTEPH) is a form of pulmonary hypertension with a high mortality rate. A new type of iron-mediated cell death is Ferroptosis, which is characterized by the accumulation of lethal iron ions and lipid peroxidation leading to mitochondrial atrophy and increased mitochondrial membrane density. Now, there is a lack of Ferroptosis-related biomarkers (FRBs) associated with pathogenic process of CTEPH. Methods The differentially expressed genes (DEGs) of CTEPH were obtained by GEO2R. Genes related to Ferroptosis were obtained from FerrDb database. The intersection of Ferroptosis and DEGs results in FRBs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed in Database for Annotation, Visualization and Integrated Discovery (DAVID) database. The optimal potential biomarkers for CTEPH were analyzed by least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) machine learning. The four hub genes were verified from the Gene Expression Omnibus (GEO) dataset GSE188938. Immune infiltration was analyzed by CIBERSORT. SPSS software was used to analyze the Spearman rank correlation between FRBs identified and infiltration-related immune cells, and p

Abstract Blue perovskite light-emitting diodes (PeLEDs) are essential in pixels of perovskite displays, while their progress lags far behind their red and green counterparts. Here, we focus on recent advances of blue PeLEDs and systematically review the noteworthy strategies, which are categorized into compositional engineering, dimensional control, and size confinement, on optimizing microstructures, energy landscapes, and charge behaviors of wide-bandgap perovskite emitters (bandgap >2.5 eV). Moreover, the stability of perovskite blue emitters and related devices is discussed. In the end, we propose a technical roadmap for the fabrication of state-of-the-art blue PeLEDs to chase and achieve comparable performance with the other two primary-color devices.

Abstract Background Patients with rheumatoid arthritis (RA) have a rising possibility of acquiring certain kinds of cancers than the general public. The causal risk association between RA and hepatocellular carcinoma (HCC) remains unknown. Methods Genetic summary data from genome-wide association study (GWAS), including RA (n = 19,190) and HCC (n = 197,611), was analyzed. The inverse-variance weighted (IVW) approach was used as the principal analysis, complemented with weighted median, weighted mode, simple median method, and MR-Egger analyses. The genetic data of RA (n = 212,453) was used to verify the results in eastern Asia populations. Results The results from the IVW methods indicated that genetically predicted RA was significantly linked with a declined possibility of HCC for East Asians (OR = 0.86; 95% CI: 0.78, 0.95; p = 0.003). The weighted median and the weighted mode also supported similar results (all p

Retinopathy is a chronic inflammatory disease whose prognosis could be improved with dietary interventions. However, the association between a pro-inflammatory diet and the prevalence of retinopathy has not been fully elucidated. We assess the association between the dietary inflammatory index (DII), which is a comprehensive index determining inflammatory potential derived from food parameters according to literature, and the prevalence of retinopathy based on the data from the National Health and Nutritional Examination Survey (NHANES) 2005–2008 involving 2,403 participants. Energy-adjusted DII (E-DII) was not related to the occurrence of retinopathy in the general, non-diabetic, or middle-aged participants. In the diabetic and aged participants, one unit increment of E-DII accounted for 14 and 15% higher the prevalence of retinopathy respectively. The highest E-DII group had a 78 and 79% higher prevalence of retinopathy than the lowest group respectively. After adjusting for several covariables, the highest E-DII group was still associated with a 68% increase in retinopathy in diabetic patients. These results suggest that E-DII is positively associated with the prevalence of diabetic retinopathy among diabetic patients.

Patients with breast cancer undergoing chemotherapy are susceptible to prolonged and severe neutropenia. Multiple biosimilars of long-acting granulocyte colony-stimulating factors (LA-G-CSFs) have been newly developed to prevent this disease. Nonetheless, which LA-G-CSF regimen has the optimal balance of efficacy and safety remains controversial. Moreover, there is a lack of evidence supporting clinical decisions on LA-G-CSF dose escalation in poor conditions. PubMed, Embase, Cochrane Library, Web of Science, and several Chinese databases were searched (December 2022) to collect randomized controlled trials (RCTs) about LA-G-CSFs preventing chemotherapy-induced neutropenia in breast cancer patients. No restrictions were imposed on language. A Bayesian network meta-analysis was performed. We assessed the incidence of severe neutropenia (SN) and febrile neutropenia (FN), the duration of SN (DSN), and the absolute neutrophil account recovery time (ANCrt) for efficacy, while the incidence of severe adverse events (SAE) was assessed for safety. The study was registered in PROSPERO (CRD42022361606). A total of 33 RCTs were included. Our network meta-analysis demonstrated that lipegfilgrastim 6 mg and eflapegrastim 13.2 mg outperformed other LA-G-CSFs with high efficacy rates and few safety concerns (SUCRA of lipegfilgrastim 6 mg: ANC rt 95.2%, FN 97.4%; eflapegrastim 13.2 mg: FN 87%, SN 89.3%). Additionally, 3.6 mg, 4.5 mg, 6 mg, and 13.2 mg dosages all performed significantly better than 1.8 mg in reducing the duration of SN (3.6 mg: DSN, SMD −0.68 [−1.13, −0.22; moderate]; 4.5 mg: −0.87 [−1.57, −0.17; low]; 6 mg: −0.89 [−1.49, −0.29; moderate]; 13.2 mg: −1.02 [1.63, −0.41; high]). Increasing the dosage from the guideline-recommended 6 mg to 13.2 mg can reduce both the duration and incidence of SN (SMD −0.13 [−0.24 to −0.03], RR 0.65 [0.43 to 0.96], respectively), with no significant difference in SAE. For patients with breast cancer, lipegfilgrastim 6 mg and eflapegrastim 13.2 mg might be the most effective regimen among LA-G-CSFs. Higher doses of LA-G-CSF may enhance efficacy without causing additional SAEs.

Abstract Background Urine albumin/creatinine ratio (UACR) is an important marker of early renal damage (ERD) caused by hypertension. Recent studies showed that blood pressure was a significant inverse association with temperature and climate. The purposes of our study were sought to explore the association of common medical comorbidities with ERD, and find independent risk factors to ERD in Chinese tropics with essential hypertension. Methods From January 2018 to December 2019, we assessed UACR in a total of 599 hypertensive Chinese Hainan patients. We defined ERD as a UACR between 30 mg/g and 300 mg/g. We analysed differences between qualitative variables using the chi-squared (χ2) test. We calculated correlations between UACR and age, hypertension duration (HD), systolic blood pressure (SBP), and diastolic blood pressure (DBP) using the Spearman’s rho test. To determine the odds ratio (OR), we evaluated binary logistic regression models. Results Among the 599 patients, 281 (46.9%) were found to have ERD. ERD and factors related to sex, body mass index (BMI), and SBP did not differ significantly (all, p>0.05). Our main findings showed that age, HD, and DBP were associated with ERD (p

BackgroundExploring the cancer risks of rheumatoid arthritis (RA) patients with disease-modifying anti-rheumatic drugs (DMARDs) can help detect, evaluate, and treat malignancies at an early stage for these patients. Thus, a comprehensive analysis was conducted to determine the cancer risk of RA patients using different types of DMARDs and analyze their relationship with tumor mutational burdens (TMBs) reflecting immunogenicity.MethodsA thorough search of PubMed, EMBASE, Web of Science, and Medline was conducted up to 20 August 2022. Standardized incidence ratios (SIRs) were constructed with a random-effect model to determine risks for different types of malignancies in comparison with the general population. We also analyzed the correlation between SIRs and TMBs using linear regression (LR).ResultsFrom a total of 22 studies, data on 371,311 RA patients receiving different types of DMARDs, 36 kinds of malignancies, and four regions were available. Overall cancer risks were 1.15 (SIR 1.15; 1.09–1.22; p < 0.001) and 0.91 (SIR 0.91; 0.72–1.14; p = 0.402) in RA populations using conventional synthetic DMARDs (csDMARDs) and biologic DMARDs (bDMARDs), respectively. RA patients taking csDMARDs displayed a 1.77-fold lung cancer risk (SIR 1.77; 1.50–2.09; p < 0.001), a 2.15-fold lymphoma risk (SIR 2.15; 1.78–2.59; p < 0.001), and a 1.72-fold melanoma risk (SIR 1.72; 1.26–2.36; p = 0.001). Correlation coefficients between TMBs and SIRs were 0.22 and 0.29 from those taking csDMARDs and bDMARDs, respectively.ConclusionWe demonstrated a cancer risk spectrum of RA populations using DMARDs. Additionally, TMBs were not associated with elevated cancer risks in RA patients following immunosuppressive therapy, which confirmed that iatrogenic immunosuppression might not increase cancer risks in patients with RA.InterpretationChanges were similar in cancer risk after different immunosuppressive treatments, and there was a lack of correlation between SIRs and TMBs. These suggest that we should look for causes of increased risks from the RA disease itself, rather than using different types of DMARDs.

BackgroundAs increasing experimental evidence suggests that iron metabolism play crucial roles in cancer and non-cancer conditions, there is a lack of data on serum soluble transferrin receptor (sTfR), a promising marker representing unmet cellular iron demands, between cancer risk from epidemiological studies. Here, we aimed to evaluate the predictive value of sTfR and cancer prevalence.Materials and methodsWe analyzed on 5,480 adult participants from 2015 to 2018 National Health and Nutrition Examination Survey (NHANES). Spearman correlation analysis was performed to investigate the correlations between sTfR and other characteristics. To identify the associations between sTfR and the prevalence of cancers, stratified multivariable logistic regression models, subgroup and sensitivity analyses were also performed.ResultsIn tertile analyses, participants in the highest level of sTfR were significantly associated with increased prevalence of total cancers [odds ratio (OR) = 1.53, 95% confidence interval (CI): 1.15-2.02] as compared with those at the lowest tertile. Each unit increment in ln-transformed sTfR concentration was shown to be associated with 39% increased risks of total cancers. Similar associations were found in males rather than females. Further subgroup and sensitivity analyses indicated that, in continuous and tertile analyses, sTfR was more closely associated with male- and female-specific cancers of prostate and testis (2.35: 1.03-5.40; 2.03: 1.00-4.09; respectively), and breast, cervix, ovary and uterus (1.92: 1.11-3.35; 1.66: 1.02-2.69; respectively).ConclusionsOur findings suggested that elevated level of sTfR was associated with the prevalence of cancers, especially in sex-specific cancers. In order to better determine them, further research in humans will be required.

Background: Septic shock has increasingly become a cause of death threatening human survival. Shenfu Injection (SFI), a patented Chinese medicine, has been widely used in the treatment of patients with sepsis and cardiovascular diseases domestically. We sought to examine whether combination therapy with SFI can improve clinical outcomes in critically ill patients undergoing mechanical ventilation (MV).Methods: This real-world, multicenter retrospective trial enrolled consecutive adult patients with sepsis requiring MV from four medical/surgical intensive care units (ICUs) in China between August 2016 and September 2021. Patients were identified from the medical information department database of each center and assigned to either of two groups (SFI or control) on the basis of the initial treatment received. The primary outcome was 28-day all-cause mortality, and the durations of vasopressor therapy and MV, the ICU length of stay, and costs were assessed as secondary outcomes. Subsequently, we performed a meta-analysis of randomized controlled trials (RCTs) on SFI published before July 2021 to verify our conclusions.Results: 2311 mechanically ventilated patients with septic shock (1128 patients in the SFI group and 1183 in the control group) were analyzed. The survival probability during the first 28 days after admission in the SFI group was greater than that in the control group [p < 0.01 by log-rank test; hazard ratio (HR), 0.56; 95% confidence interval (CI), 0.39–0.72]. Patients in the SFI group also experienced a significantly reduced duration of vasopressor therapy [7.28 (95% CI, 6.14–8.42) vs. 12.06 (95% CI, 10.71–13.41) days, p < 0.001], more ventilator-free days [6.49 (95% CI, 5.42–7.55) vs. 10.84 (95% CI, 9.59–12.09) days, p < 0.001], a shorter ICU length of stay [18.48 (95% CI, 17.59–19.38) vs. 23.77 (95% CI, 22.47–25.07) days, p < 0.001], and more time free from organ failure [14.23 (95% CI, 12.94–15.52) vs. 19.07 (95% CI, 16.09–22.05) days, p < 0.001]. No major adverse effects were reported in either group.Conclusion: Among critically ill patients requiring MV, combination therapy with SFI can improve the survival probability without any obvious adverse reactions.

More than 405 million people have contracted coronavirus disease 2019 (COVID-19) worldwide, and mycotic infection may be related to COVID-19 development. There are a large number of reports showing that COVID-19 patients with mycotic infection have an increased risk of mortality. However, whether mycotic infection can be considered a risk factor for COVID-19 remains unknown. We searched the PubMed and Web of Science databases for studies published from inception to December 27, 2021. Pooled effect sizes were calculated according to a random-effects model or fixed-effect model, depending on heterogeneity. We also performed subgroup analyses to identify differences in mortality rates between continents and fungal species. A total of 20 articles were included in this study. Compared with the controls, patients with mycotic infection had an odds ratio (OR) of 2.69 [95% confidence interval (CI): 2.22–3.26] for mortality and an OR of 2.28 (95% CI: 1.65–3.16) for renal replacement therapy (RRT). We also conducted two subgroup analyses based on continent and fungal species, and we found that Europe and Asia had the highest ORs, while Candida was the most dangerous strain of fungi. We performed Egger's test and Begg's test to evaluate the publication bias of the included articles, and the p-value was 0.423, which indicated no significant bias. Mycotic infection can be regarded as a risk factor for COVID-19, and decision makers should be made aware of this risk.

Introduction Sedation and analgesia are recommended to be employed in the intensive care unit (ICU) to enhance patient comfort and safety, facilitate mechanical ventilation and reduce oxygen demands. However, the increasing evidence demonstrates that excessive sedation and analgesia might prolong mechanical ventilation and increase costs and mortality. Acupuncture is known to be able to attenuate pain, anxiety and agitation symptoms while avoiding excessive sedation and analgesia caused by drugs. Therefore, we present a protocol to investigate whether acupuncture, used for sedation and analgesia, can reduce the duration of mechanical ventilation, save medical resources and reduce the mortality of critically ill patients receiving mechanical ventilation.Methods and analysis Prospective, randomised controlled trial is conducted on 180 adult medical/surgical ICU patients with mechanical ventilation needing sedation at 3 ICUs between 03 November 2021 and 16 August 2023. Patients will be treated with analgesia and sedation to achieve desired target sedation levels (Richmond Agitation Sedation Score of −2 to 1). Enrolled patients will be randomly assigned in a ratio of 1:1:1 to receive deep needle insertion with combined manual and alternating-mode electrical stimulation on acupoints (AC group), superficial needle insertion without manual stimulation and electrical stimulation on non-acupoints (SAC group), or no acupuncture intervention (NAC group). The primary outcome is the duration of mechanical ventilation from randomisation until patients are free of mechanical ventilation (including non-invasive) without reinstitution for the following 48 hours. Secondary endpoints include the dose of administered sedatives and analgesic at comparable sedation levels throughout the study, ICU length of stay, hospital length of stay. Additional outcomes include the prevalence and days of delirium in ICU, mortality in ICU and within 28 days after randomisation, and the number of ventilator free days in 28 days.Ethics and dissemination This trial was approved by the ethics committee at Guangdong Provincial Hospital of Chinese Medicine. We will publish the study results.Trial registration number ChiCTR2100052650.

The growth of Achnatherum splendens (A. splendens) inhibits the growth of dominant grassland herbaceous species, resulting in a loss of grassland biomass and a worsening of the grassland ecological environment. Therefore, it is crucial to identify the dynamic development of A. splendens adequately. This study intended to offer a transformer-based A. splendens detection model named YOLO-Sp through ground-based visible spectrum proximal sensing images. YOLO-Sp achieved 98.4% and 95.4% AP values in object detection and image segmentation for A. splendens, respectively, outperforming previous SOTA algorithms. The research indicated that Transformer had great potential for monitoring A. splendens. Under identical training settings, the AP value of YOLO-Sp was greater by more than 5% than that of YOLOv5. The model’s average accuracy was 98.6% in trials conducted at genuine test sites. The experiment revealed that factors such as the amount of light, the degree of grass growth, and the camera resolution would affect the detection accuracy. This study could contribute to the monitoring and assessing grass plant biomass in grasslands.

Both low and high glycated hemoglobin A1c (HbA1c) levels are well-established causal risk factors for all-cause and cardiovascular mortality in the general population and diabetic patients. However, the relationship between HbA1c with all-cause and cardiovascular mortality among patients with hypertension is unclear. We used NHANES data from 1999 to 2014 as the basis for this population-based cohort study. Based on HbA1c levels (HbA1c > 5, HbA1c > 5.5, HbA1c > 6, HbA1c > 6.5, HbA1c > 7%), hypertensive patients were divided into five groups. An analysis of multivariable Cox proportional hazards was conducted based on hazard ratios (HRs) and respective 95% confidence intervals (CIs). The relationship between HbA1c and mortality was further explored using Kaplan–Meier survival curves, restricted cubic spline curves, and subgroup analyses. In addition, 13,508 patients with hypertension (average age 58.55 ± 15.56 years) were included in the present analysis, with 3760 (27.84%) all-cause deaths during a follow-up of 127.69 ± 57.9 months. A U-shaped relationship was found between HbA1c and all-cause and cardiovascular mortality (all p for likelihood ratio tests were 0.0001). The threshold value of HbA1c related to the lowest risk for all-cause and cardiovascular mortality was 5.3% and 5.7%, respectively. Below the threshold value, increased HbA1c levels reduced the risk of all-cause mortality (HR 0.68, 95% CI 0.51–0.90, p = 0.0078) and cardiovascular mortality (HR 0.77, 95% CI 0.57–1.05, p = 0.0969). Inversely, above the threshold value, increased HbA1c levels accelerated the risk of all-cause mortality (HR 1.14, 95% CI 1.11–1.18, p < 0.0001) and cardiovascular mortality (HR 1.22, 95% CI 1.16–1.29, p < 0.0001). In conclusion, A U-shape relationship was observed between HbA1c and all-cause and cardiovascular mortality among hypertensive patients.

Gelatin methacryloyl (GelMA) hydrogels have aroused considerable interests in the field of tissue engineering due to tunable physical properties and cell response parameters. A number of works have studied the impact of GelMA concentration, photo-initiator concentration, methacrylic anhydride (MA) concentration, cooling rate and temperature gradient on GelMA hydrogel generation, but little attention has been paid to the effect of the freezing temperatures and freezing time of GelMA prepolymer solution during preparation. In this study, GelMA hydrogels were synthesized with different freezing temperatures and time. It was found that the lower freezing temperatures and longer freezing time caused smaller pore sizes that realized higher cell viability and proliferation of MC3T3-E1 cells. The results showed that tunable microstructure of GelMA could be achieved by regulating the freezing conditions of GelMA, which provided a broad prospect for the applications of GelMA hydrogels in tissue engineering.

The construction industry is a high-energy-consumption industry. Nearly 40% of global carbon emissions derive from the construction industry. Prefabricated assembly technology is an effective means of carbon emission reduction, but the incremental cost of prefabricated components is much more expensive than that of cast-in-place components. It is not conducive for enterprises to choose prefabricated assembly technology to decrease emissions. Most of the current studies focus on the carbon-reduction effect of prefabricated assembled buildings, and there are fewer studies related to the impact of cost factors on enterprises’ participation in building carbon reduction. The cost factor will affect the choice of prefabricated assembly technology to reduce carbon emissions. Therefore, it is necessary to analyze the relationship between carbon emissions and costs in prefabricated buildings. Aiming at this problem, this paper proposes a dual-objective method to optimize cost and carbon emissions by using the improved optimization algorithm to solve the problem. Through the analysis of actual cases, the results show that when the prefabrication rate is 35–40%, enterprises can obtain a better carbon-emission-reduction effect by appropriately increasing the cost. When the prefabrication rate is higher than 40%, the carbon-reduction effect that can be obtained by greatly increasing the cost is limited. Therefore, when enterprises decide a prefabrication range of 35–40%, they are able to obtain the maximum carbon-reduction effect with the minimum cost. This study can provide a reference for the government to formulate relevant policies with energy conservation and emission reductions in prefabricated buildings and also can provide a reference for enterprises to make decisions between carbon emission reduction and cost.

In order to reduce the influence of abnormal data on load forecasting effects and further improve the training efficiency of forecasting models when adding new samples to historical data set, an ultra-short-term load dynamic forecasting method considering abnormal data reconstruction based on model incremental training is proposed in this paper. Firstly, aiming at the abnormal data in ultra-short-term load forecasting, a load abnormal data processing method based on isolation forests and conditional adversarial generative network (IF-CGAN) is proposed. The isolation forest algorithm is used to accurately eliminate the abnormal data points, and a conditional generative adversarial network (CGAN) is constructed to interpolate the abnormal points. The load-influencing factors are taken as the condition constraints of the CGAN, and the weighted loss function is introduced to improve the reconstruction accuracy of abnormal data. Secondly, aiming at the problem of low model training efficiency caused by the new samples in the historical data set, a model incremental training method based on a bidirectional long short-term memory network (Bi-LSTM) is proposed. The historical data are used to train the Bi-LSTM, and the transfer learning is introduced to process the incremental data set to realize the adaptive and rapid adjustment of the model weight and improve the model training efficiency. Finally, the real power grid load data of a region in eastern China are used for simulation analysis. The calculation results show that the proposed method can reconstruct the abnormal data more accurately and improve the accuracy and efficiency of ultra-short-term load forecasting.

The camera and projector are indispensable hardware parts of a color fringe projection 3D measurement system. Chromatic aberration between different color channels of the projector and camera has an impact on the measurement accuracy of the color fringe projection 3D profile measurement. There are many studies on camera calibration, but the chromatic aberration of the projector remains a question deserving of further investigation. In view of the complex system architecture and theoretical derivation of the traditional projector radial chromatic aberration method, a phase target based on projector radial chromatic aberration measurement and the correction method are proposed in this paper. This method uses a liquid crystal display with a holographic projection film as the phase target. The liquid crystal display sequentially displays red, green, and blue horizontal and vertical sinusoidal fringe images. The projector projects red, green, and blue horizontal and vertical sinusoidal fringe images to the phase target in turn, and calculates the absolute phases of the display fringes and reflection fringes, respectively. Taking the green channel as the reference channel, a phase coordinate system is established based on the phases of the vertical and horizontal directions displayed on the display screen, using the phase of the reflection fringes on the display screen as the ideal phase value of the phase point. Then, the phase coordinate system of the red and blue channels is transferred to the green phase coordinate system to calculate the chromatic aberration of the red-green channels and the blue-green channels, and pre-compensation is conducted. Experimental results prove that this method can measure and calibrate the radial chromatic aberration of the projector without being affected by the image quality of the camera. The correction effect of this method is that the maximum chromatic aberration of the red-green channel decreases from 1.9591/pixel to 0.5759/pixel, and the average chromatic aberration decreases from 0.2555/pixel to 0.1865/pixel. In addition, blue-green channel maximum chromatic aberration decreased from 1.8906/pixel to 0.5938/pixel, and the average chromatic aberration decreased from 0.2347/pixel to 0.1907/pixel. This method can improve the projection quality for fringe projection 3D profile measurement technology.

Background Hepatocellular carcinoma (HCC) with high heterogeneity is one of the most frequent malignant tumors throughout the world. However, there is no research to establish a ferroptosis-related lncRNAs (FRlncRNAs) signature for the patients with HCC. Therefore, this study was designed to establish a novel FRlncRNAs signature to predict the survival of patients with HCC. Method The expression profiles of lncRNAs were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. FRlncRNAs co-expressed with ferroptosis-related genes were utilized to establish a signature. Cox regression was used to construct a novel three FRlncRNAs signature in the TCGA cohort, which was verified in the GEO validation cohort. Results Three differently expressed FRlncRNAs significantly associated with prognosis of HCC were identified, which composed a novel FRlncRNAs signature. According to the FRlncRNAs signature, the patients with HCC could be divided into low- and high-risk groups. Patients with HCC in the high-risk group displayed shorter overall survival (OS) contrasted with those in the low-risk group (P 1, P 1, P

Grassland classification is crucial for grassland management. One commonly used method utilizes remote sensing vegetation indices (VIs) to map grassland classes at various scales. However, most grassland classifications were conducted as case studies in a small area due to lack of field data sources. At a small scale, classification is reliable; however, great uncertainty emerges when extended to other areas. In this study, large amounts of field observations (more than 30,000 aerial photos) were obtained using unmanned aerial vehicle photography in Inner Mongolia, China, during the peak period of grassland growth in 2018 and 2019. Then, four machine learning classification algorithms were constructed based on characteristic indices of MODIS NDVI in the growing season to map grassland classes of Inner Mongolia. Finally, the spatial distribution and temporal variation of temperate grassland classes were analyzed. Results showed that: (1) Among all characteristic indices, the maximum, average, and sum of MODIS NDVI from July to September during 2015 to 2019 greatly affected grassland classification. (2) The random forest method exhibited the best performance with overall accuracy and kappa coefficient being 72.17% and 0.62, respectively. (3) Compared with the grassland class mapped in the 1980s, 30.98% of grassland classes have been transformed. Our study provides a technological basis for effective and accurate classification of the temperate steppe class and a theoretical foundation for sustainable development and restoration of the temperate steppe ecosystem.