Ensemble learning models for large-scale time series forecasting in supply chain

Machine learning and AI techniques are transforming supply chain forecasting, driven by the expanding availability of data assets. These advanced methods offer powerful opportunities to optimize management processes, reduce operational costs, and enhance strategic decision-making, which is crucial for enterprise success. However, conventional statistical approaches, such as Autoregressive Integrated Moving Average Models (ARIMA), dynamic regression, and Unobserved Component Models (UCMs)—which have long dominated time series forecasting—often fall short in accuracy and scalability. These traditional models face limitations in batch processing, handling large-scale data, addressing uncertainty-induced disruptions, and synchronizing demand-supply scenarios. To address these challenges, a novel class of AI-powered ensemble techniques is introduced, integrating machine learning, particularly neural network, with baseline models. The approach starts with classification and segmentation, applying feature engineering to signal components such as spikes and anomalies, which are treated as outliers, to capture complex scenario hierarchies and identify patterns in categorical data. Next, an ensemble model incorporating AI-driven time-series pattern sensors automatically detects critical signal elements, including seasonality, promotions, trends, and intermittent or discontinued activities. An evaluation of eight widely used model categories shows that this AI-enhanced ensemble approach significantly outperforms individual baseline models and traditional univariate time-series algorithms in forecasting accuracy

Self-supervised transformer-based pre-training method with General Plant Infection dataset

Pest and disease classification is a challenging issue in agriculture. The performance of deep learning models is intricately linked to training data diversity and quantity, posing issues for plant pest and disease datasets that remain underdeveloped. This study addresses these challenges by constructing a comprehensive dataset and proposing an advanced network architecture that combines Contrastive Learning and Masked Image Modeling (MIM). The dataset comprises diverse plant species and pest categories, making it one of the largest and most varied in the field. The proposed network architecture demonstrates effectiveness in addressing plant pest and disease recognition tasks, achieving notable detection accuracy. This approach offers a viable solution for rapid, efficient, and cost-effective plant pest and disease detection, thereby reducing agricultural production costs. Our code and dataset will be publicly available to advance research in plant pest and disease recognition the GitHub repository at https://github.com/WASSER2545/GPID-22Comment: 14 pages, 5 figures, 4 tables, 3 formula

High Flow Nasal Catheter (HFNC) for Sepsis Induced Respiratory Failure After Extubation Meta Analysis of Clinical Control Studies on Reintubation Rate and Mortality

Objective: To analyze the reintubation rate and mortality of patients with sepsis complicated (or induced) respiratory failure after extubation, and to seek evidence-based basis for the efficacy of HFNC in the re intubation rate and mortality of sepsis induced respiratory failure after extubation. Methods: The databases of PubMed, EMBASE, Ovid, CNKI, CBM, VIP and Wanfang were searched to find the clinical studies of patients with sepsis and respiratory failure, and meta-analysis was carried out by Stata software. Results: Meta analysis showed that there was no significant difference between HFNC and noninvasive positive pressure ventilation (NPPV) in 72 hour reintubation rate, mortality during ICU and 28-day in hospital. Conclusion: The reintubation rate and mortality of HFNC after extubation in sepsis induced respiratory failure are equivalent to that of NPPV

Delivery of Quantum Dot-siRNA Nanoplexes in SK-N-SH Cells for BACE1 Gene Silencing and Intracellular Imaging

The fluorescent quantum dots (QDs) delivered small interfering RNAs (siRNAs) targeting β-secretase (BACE1) to achieve high transfection efficiency of siRNAs and reduction of β-amyloid (Aβ) in nerve cells. The CdSe/ZnS QDs with the conjugation of amino-polyethylene glycol (PEG) were synthesized. Negatively charged siRNAs were electrostatically adsorbed to the surface of QDs to develop QD-PEG/siRNA nanoplexes. The QD-PEG/siRNAs nanoplexes significantly promote the transfection efficiency of siRNA, and the siRNAs from non-packaged nanoplexes were widely distributed in cell bodies and processes and efficiently silenced BACE1 gene, leading to the reduction of Aβ. The biodegradable PEG polymer coating could protect QDs from being exposed to the intracellular environment and restrained the release of toxic Cd2+. Therefore, the QD-PEG/siRNA nanoplexes reported here might serve as ideal carriers for siRNAs. We developed a novel method of siRNA delivery into nerve cells. We first reported that the QD-PEG/siRNA nanoplexes were generated by the electrostatic interaction and inhibited the Alzheimer's disease (AD)-associated BACE1 gene. We also first revealed the dynamics of QD-PEG/siRNAs within nerve cells via confocal microscopy and the ultrastructural evidences under transmission electron microscopy (TEM). This technology might hold promise for the treatment of neurodegenerative diseases such as AD

Comparison of characteristics of cervical cancer screening history between cervical adenocarcinoma and cervical squamous cell carcinoma

Objective To comparatively analyze the characteristics of cervical cancer screening history between patients with cervical adenocarcinoma and cervical squamous cell carcinoma， and to preliminarily evaluate the efficacy of cervical cancer screening for precancerous lesions of cervical adenocarcinoma. Methods Clinical data of 117 patients with cervical adenocarcinoma and 712 patients with cervical squamous cell carcinoma were retrospectively analyzed， and the differences in cervical cancer screening history were statistically analyzed between two groups. Results The proportion of cervical adenocarcinoma patients receiving cervical cancer screening was 24.5%， significantly higher than 6.8% of those with cervical squamous cell carcinoma （P < 0.001）. The proportion of cervical adenocarcinoma patients receiving regular screening or above was 18.4%， significantly higher than 2.8% of those with cervical squamous cell carcinoma （P < 0.001）. The proportion of symptom-detected cervical squamous cell carcinoma was 91.6%， significantly higher than 79.1% of their counterparts with cervical adenocarcinoma cell carcinoma （P < 0.001）. The proportion of screening-detected stageⅠ-ⅡA cervical adenocarcinoma was 24.6%， significantly higher than 11.1% of those with screening-detected stage Ⅰ-ⅡA cervical squamous cell carcinoma （P = 0.004）. The proportion of screening-detected stageⅠ-ⅡA cervical adenocarcinoma was 24.6%， significantly higher than 4.0% of those with screening-detected stageⅡB-Ⅳ cervical adenocarcinoma （P = 0.022）. Conclusions Current cervical cancer screening regimen yields higher efficacy for precancerous lesions of cervical squamous cell carcinoma compared with cervical adenocarcinoma. However， it still contributes to the diagnosis of early cervical adenocarcinoma. Therefore， extensive attention should be paid to cervical cancer screening. Cervical cancer screening regimen remains to be further optimized

1-MCP maintains postharvest quality in winter jujube during low-temperature storage by regulating energy and sugar metabolism and enhancing antioxidant capacity

This study investigates the effects of 1-methylcyclopropene (1-MCP) treatment on postharvest storage of winter jujube. The results indicate that after 1-MCP treatment, the pyruvate (PA) content in winter jujube decreased by 20% at 30 days compared to the control. The energy charge (EC), ATP, and ADP levels increased by 7%, 17%, and 27%, respectively. Activities of key enzymes involved in energy metabolism, including succinate dehydrogenase (SDH), cytochrome c oxidase (COX), H+-ATPase, and Ca2+-ATPase were elevated. Furthermore, the activities of acid invertase (AI) and neutral invertase (NI) were 27% and 26% lower, respectively, than those in the control. Sucrose synthase (SS) activity increased by 52%, while the activities of hexokinase (HK) and phosphofructokinase (PFK) decreased by 19% each. Activities of key antioxidant enzymes-superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and glutathione reductase (GR)-were significantly enhanced. Non-enzymatic antioxidants, including vitamin C (VC), flavonoids, total phenols, and reduced glutathione (GSH) contents, were effectively retained, and suppressing the accumulation of the hydrogen peroxide (H2O2) and malondialdehyde (MDA). These findings suggest that 1-MCP treatment preserves the postharvest quality of winter jujube by enhancing energy metabolism, delaying sugar metabolism, and improving antioxidant capacity

Construction of an immune-related ceRNA network in cervical cancer based on HPV E6 splicing

BackgroundCervical cancer is one of the leading causes of cancer-related deaths worldwide. The unspliced human papillomavirus (HPV) E6 plays an important role in tumor progression and immune regulation. Improved immunotherapy implementation might benefit from a better knowledge of HPV E6 splicing-related immune gene expressions and immunocyte infiltration in cervical cancer. This study aimed to identify the potential therapeutic and prognostic roles of unspliced/spliced E6 ratio (E6 ratio) in cervical cancer.MethodsData from the TCGA were used to analyze the E6 condition and clinical information. Nomogram and K-M analysis were used to analyze assess the prognostic significance, IOBR was used to investigate immunological infiltrates. Functions and pathway enrichment analysis of DEGs were investigated through GO analysis and KEGG pathway analysis, respectively. A core module was taken from the competitive endogenous RNA (ceRNA) network and used to build a lncRNA-miRNA-mRNA network. QT-qPCR was used to detect the expression of genes. CCK-8, colony formation, wound healing and migration assays were used to detect cell functions.ResultsOur study found that HPV E6 ratio had significantly correlation with overall survival. In cervical cancer, a high E6 ratio was adversely linked with infiltrating levels of aDC, M1 macrophages, monocytes, NKT, and Tgd. High E6 ratio phenotypes were shown to be implicated in immune response regulation, cell adhesion, and Wnt signaling pathways, according to functional enrichment analysis. Subsequently, we constructed an immune-related ceRNA network based on E6 splicing in cervical cancer, including three lncRNA (LINC00943, LIFR-AS1, DANT2, and RASSF8-AS1), four miRNA (miR-205-5p, miR-181d-5p, miR-222-3p, and miR-221-3p), and seven mRNA (FGFR1, PRLR, CXCL2, ISG20, ISG15, SDC1, and NR2F2). Among them, CXCL2, SDC1, and miR-221-3p were associated with survival and immune cell infiltration.ConclusionsThese data imply that a high E6 ratio in cervical cancer contributes to the immune-related ceRNA network, resulting in a low amount of infiltrating effector immune cells and tumor growth. As a result, the E6 ratio might be employed as a biomarker in cervical cancer to determine prognosis and treatment success

Causal relationship between type 2 diabetes mellitus and aortic dissection: insights from two-sample Mendelian randomization and mediation analysis

ObjectiveSome evidence suggests a reduced prevalence of type 2 diabetes mellitus (T2DM) in patients with aortic dissection (AD), a catastrophic cardiovascular illness, compared to general population. However, the conclusions were inconsistent, and the causal relationship between T2DM and AD remains unclear.MethodsIn this study, we aimed to explore the causal relationship between T2DM and AD using bidirectional Mendelian randomization (MR) analysis. Mediation MR analysis was conducted to explore and quantify the possible mediation effects of 1400 metabolites in T2DM and AD.ResultsThe results of 26 datasets showed no causal relationship between T2DM and AD (P>0.05). Only one dataset (ebi-a-GCST90006934) showed that T2DM was a protective factor for AD (I9-AORTDIS) (OR=0.815, 95%CI: 0.692-0.960, P=0.014), and did not show horizontal pleiotropy (P=0.808) and heterogeneity (P=0.525). Vanillic acid glycine plays a mediator in the causal relationship between T2DM and AD. The mediator effect for vanillic acid glycine levels was -0.023 (95%CI: -0.066-0.021).ConclusionFrom the perspective of MR analysis, there might not be a causal relationship between T2DM and AD, and T2DM might not be a protective factor for AD. If a causal relationship does exist between T2DM and AD, with T2DM serving as a protective factor, vanillic acid glycine may act as a mediator and enhance such a protective effect