North China University of Science and Technology

Yang Y., Zhang R., Li L., Wang H.

Interdisciplinary teaching is a pivotal strategy for deepening disciplinary theory and broadening students’ cognitive boundaries, crucial for the sustainability of education. By considering scientific knowledge’s humanistic background and technological evolution, this study proposes a novel interdisciplinary teaching framework based on the Source–Knowledge–Use (SKU) paradigm. Then, taking fuzzy mathematics as a case, the Humanities–Science–Technology Model (HSTM), based on a tripartite progression from humanistic foundations to scientific principles and then to technological applications, was established. This study systematically expounds the HSTM’s framework, contents, and implementation design, while critically examining potential challenges and corresponding mitigation strategies. The proposed SKU-based interdisciplinary teaching framework not only provides methodological guidance for interdisciplinary instruction in fuzzy mathematics but also offers transferable insights for cognate disciplines seeking to implement sustainable educational practices.

Li J., Wu H., Wang B., He Q., Guo C., Lei W., Li J., Liu Z., Shen Y.

Near-infrared long-afterglow materials present significant promise for applications in tracking and imaging technologies. Among these materials, chromium-doped stannates and gallium germanates are crucial, with Mn2+-doped magnesium germanate standing out for its intense afterglow within the 650–1100 nm spectrum, ideal for biomedical use. However, conventional high-temperature synthesis techniques yield particles that are too large for effective biomedical applications. To surmount this challenge, this article turned to hydrothermal synthesis to produce MgGeO3:Mn2+,Yb3+ with enhanced properties. In order to further the research the impact of pH levels and chelating agent ratios on the material's structure, as well as delved into the intricacies of their luminescence mechanisms and structural attributes.

Li D., Ye S., Ge C.

Li X., Qiu Y., Deng Z., Liu X., Huang X.

Wang X., Shen S., Fu Y., Cao R., Wei Y., Song X.

Sechium edule (chayote) is an important vegetable crop belonging to the Cucurbitaceae family. To decipher the chayote genome, a high-quality chromosome-level chayote genome was obtained by genome sequencing and bioinformatic analysis. The total length was 612.91 Mb, and 25 755 genes were detected in the chayote genome. The contig N50 was more than 20.01 Mb, and the scaffold N50 was over 47.11 Mb. Of the genome, 60.35% were composed of repetitive sequences, and 31.18% of genome sequences belonged to long-terminal repeats.A global alignment of homologous regions in chayote and other Cucurbitaceae plant genomes was constructed using grape as a reference. Based on this genome-wide and global alignment map, researchers can easily identify homologous collinear genes of the studied genomes in most Cucurbitaceae species. Twenty-five chayote accessions were divided into two subgroups based on phylogenetic tree, population structure analysis, and principal component analysis using genome re-sequencing data. The chayote genome, re-sequencing dataset, and comprehensive genomic analysis will accelerate comparative and functional genomic analysis of chayote and other Cucurbitaceae species in the future.

Yang C., Chen Y., Tao T., Xu P., Li M., Deng B., Lu S., Yang M., Wang W., Wang J., Liu S.

Background: Hepatocellular carcinoma (HCC) has high morbidity and mortality worldwide. Excision repair cross-complement 3 (ERCC3), a key functional gene in the nucleotide excision repair (NER) pathway, is commonly mutated or overexpressed in cancers and is thought to be a key gene contributing to the development of HCC. The characteristics of immune cell infiltration in the global tumor microenvironment (TME) mediated by ERCC3 and its related key genes in HCC are still unclear. The aim of this study was to integrate the role of ERCC3-related key genes in assessing the TME cell infiltration characteristics, immunotherapy efficacy, and prognosis of HCC patients. This study provides a theoretical basis for the study of immunological mechanisms and prognosis prediction in HCC. Methods: The HCC cohort from the TCGA database included 50 normal samples and 374 tumor samples to compare the differences in ERCC3-related gene expression and prognosis between liver tumor tissues and normal liver tissues and to analyze the extent to which different genes infiltrated TME cells by quantifying the relative abundance of 24 cells through single-sample genome enrichment analysis (ssGSEA). A risk score associated with the ERCC3 gene was constructed using the least absolute shrinkage and selection operator (LASSO) Cox regression model. Results: The expression of 11 ERCC3-related genes was significantly upregulated in HCC tumor tissues compared to normal liver tissues, and high expression of these genes was significantly associated with poor prognosis in HCC patients. The key genes (11 ERCC3-related genes) were closely associated with the nucleic acid reduction signaling pathway in nucleic acid metabolism and the viral oncogenic pathway, suggesting that these key genes may play a role in tumor cell proliferation, migration, and invasion, as well as in the pathogenesis of virus-associated HCC. In addition, the infiltration characteristics of TME immune cells in normal and tumor tissues were different. Immune and mesenchymal activity was significantly lower in tumor tissues than in healthy liver tissues. This study revealed that key genes were significantly positively correlated with CTLA4 and enriched in central memory CD4 T cells, effector memory CD4 T cells, activated CD4 T cells, and type 2 T helper cells. The prognostic model constructed by regression analysis could better distinguish patients into high-risk and low-risk groups, and the survival analysis showed that the survival time of patients with high-risk score subtypes was significantly lower than that of patients with low-risk scores and that the high-risk group contained higher levels of immune-suppressive cells, which may be a mediator of immune escape. Moreover, multivariate analyses showed that the risk score profile is a reliable and unbiased biomarker for assessing the prognosis of HCC patients, and its value in predicting the outcome of immunotherapy was also confirmed. Conclusion: This study revealed a novel genetic signature that is significantly associated with TME cell infiltration and prognosis in HCC patients. It demonstrated that the combined action of multiple key genes associated with ERCC3 plays a crucial role in shaping the diversity and complexity of TME cell infiltrates. Evaluating the combined characteristics of multiple key genes associated with ERCC3 can help predict the outcome of immunotherapy in patients and provide new potential targets for immuno-individualized therapeutic studies on HCC.

Ji Z., Hao S., Pang J., Ganchev I.

This paper presents a self-developed automatic pulmonary nodule detection and management system, built and operating on top of the IoT platform EMULSION as an effective tool for physicians and patients to conduct preliminary diagnoses of lung diseases and detect potential pulmonary-nodule-related health issues. The elaborated system architecture is described, including its overall structure, main functional modules, and their display pages. Providing a more convenient way for physicians to systematically handle and cure their patients, the designed and implemented system helps alleviate the workload of physicians while also giving patients more opportunities for follow-up treatment.

Chen H., Xia M., Zhang Y., Zhao R., Song B., Bai Y.

Li Q., Wang P., Wang F., Zhang Y., Wang H., Xu Q., Xu M., Bai L.

The iron and steel industry (ISI) plays a significant role in carbon emissions, contributing approximately 15% of the nation’s total emissions in China. Transitioning to low-carbon practices is crucial for achieving the country’s carbon neutrality goals. This paper reviews the current state of China’s ISI and assesses the feasibility of various decarbonization technologies, including hydrogen utilization, biomass substitution, zero-carbon electricity, Carbon Capture, Utilization, and Storage (CCUS), as well as their combinations. The blast furnace–basic oxygen furnace (BF-BOF) process currently dominates the industry with an overwhelming share of around 90%, presenting significant challenges for decarbonization. In contrast, the Direct Reduced Iron–Electric Arc Furnace (DRI-EAF) process is still at the demonstration project stage, but it is rapidly growing and shows great potential for achieving net-zero emissions. Electric arc furnaces (EAFs) that use scrap steel account for about 9% of production and have the lowest energy consumption. However, their production capacity is limited by the availability of scrap steel. Among numerous options, blue hydrogen, carbon-neutral biomass, and CCUS technologies have relatively low costs and high technological maturity. Nevertheless, no single technology can currently achieve deep decarbonization while significantly reducing costs. The nation needs to select the most suitable decarbonization strategies based on geographical location, infrastructure, and economic conditions. The government should enact corresponding policies, provide economic incentives, and ensure mitigation of the environmental and social impacts during the decarbonization transition.

Yang Z., Dong G., Zeng L., Qiu Y., Guo C., Ma Z., Wang T., Yang X., Ran S., Zhao X.

Shallow-water deltas are not only a hot spot for sedimentological research but also a key target for oil and gas exploration. In this paper, taking the third member (E1f3) of the Funing Formation in the Upper Jurassic as an example, based on observations made from core samples, well logging, cathode luminescence characteristics, and analytical assays, the development conditions, sedimentary characteristics, and sedimentary models of shallow-water deltas are summarized. These shallow-water deltas were deposited in conditions with the following characteristics: a gentle terrain platform, a subtropical climate with ample rainfall, an abundant source supply, strong hydrodynamic forces, shallow water bodies, and a frequently eustatic lake level. Shallow-water deltas are characterized by sediment deposition from traction currents, numerous underwater distributary channel scour structures, overlapping scouring structures, sand body distribution with planar features, underwater distributary channels as skeletal sand bodies, and undeveloped mouth bars. Based on these, it is believed that during the deposition period of E1f3, the Gaoyou Sag in the Subei Basin had favorable geological conditions for the development of shallow-water delta deposition. The shallow-water delta deposition that occurred during the sedimentary periods of the five major sand units in the Funing Formation is characterized by front subfacies, with underwater distributary channels as the framework for sand bodies, and multiple intermittent positive rhythms overlapping vertically with the Jianhu Uplift as the source of material supply. In this paper, a depositional model for shallow-water delta deposition during the E1f3 deposition period in the Gaoyou Sag is established, expanding the scope of oil reservoir exploration in the north slope region of the Gaoyou Sag and providing important geological evidence for the selection of favorable subtle zones.

Gong Y., Zhang Q., Ren Y., Liu Z., Abu Seman M.T.

The most important control parameters in the methanol distillation process, which are directly related to product quality and yield, are the temperature, pressure and water content of the finished product at the top of the column. In order to adapt to the development trend of modern industrial technology to be more accurate, faster and more stable, the fusion of multi-sensor data puts forward higher requirements. Traditional control methods, such as PID control and fuzzy control, have the disadvantages of low heterogeneous data processing capability, poor response speed and low control accuracy when dealing with complex industrial process detection and control. For the control of tower top temperature and pressure in the methanol distillation industry, this study innovatively combines generative artificial intelligence and a type II fuzzy neural network, using a GAN for data preprocessing and a type II fuzzy neural network for steady-state inverse prediction to construct the GAN-T2FNN temperature and pressure control model for an atmospheric pressure tower. Comparison experiments with other neural network models and traditional PID control models show that the GAN-T2FNN model has a better performance in terms of prediction accuracy and fitting effect, with a minimum MAE value of 0.1828, which is more robust, and an R2 Score of 0.9854, which is closer to 1, for the best overall model performance. Finally, the SHAP model was used to analyze the influence mechanism of various parameters on the temperature and pressure at the top of the atmospheric column, which provides a more comprehensive reference and guidance for the precise control of the methanol distillation process.

Zhang M., Ge J., Yu X., Wang T., Wang F., Kuchawo M.G., Ge L.

Objective: This review will synthesize evidence on the effectiveness, acceptability, and cost-effectiveness of digital health interventions in implementing and maintaining effective self-management among adults (≥ 18 years) with diabetes, with or without comorbid hypertension. Introduction: Diabetes and hypertension are becoming the most challenging global health burdens. Growing evidence underscores the effectiveness of digital health interventions for diabetes and hypertension. However, it is unclear whether these strategies can be recommended to improve diabetes self-management among adults with or without hypertension in primary health care. Inclusion criteria: We will include systematic reviews (with or without meta-analysis) examining the effectiveness, acceptability, and cost-effectiveness of digital health interventions in improving self-management behaviors among adults living with diabetes, with or without hypertension, in primary health care. There will be no gender, ethnicity, language, or geographic limitations. Methods: The review will follow the JBI methodology for umbrella reviews. MEDLINE (EBSCOhost), CINAHL (EBSCOhost), Embase, Epistemonikos, PsycINFO (EBSCOhost), Web of Science, Scopus, Cochrane Library, Campbell Systematic Reviews, and JBI EBP Database (Ovid) will be searched from the inception to the present to identify systematic reviews. Gray literature sources, including OpenGrey, ProQuest Dissertations and Theses, and Google Scholar, will be searched, followed by a manual search of reference lists of included articles. Two independent reviewers will perform screening, critical appraisal, and data extraction. The review results will be presented through various approaches, including a narrative synthesis, graphical representation, and tabular summary. The JBI critical appraisal checklist for systematic reviews and research syntheses will be applied. Certainty of evidence will be assessed following the GRADE approach. Systematic review registration number: PROSPERO CRD42023471615

Lu C., Yang B., Liu Y., Liu W., Yan J., Guo C., Song T., Wang X.

Wang J., Dietz S., Han J.

Die Additive Fertigung verringert bereits in vielen Unternehmen den Materialbedarf und -bestand, z. B. für Ersatzteile oder für kundenangepasste Teile. Die Nachhaltigkeit steigt so im Vergleich zu Unternehmen mit konventioneller Herstellung. Diese Art der Fertigung kann allerdings bei Berücksichtigung im vorgelagerten Produktentwicklungsprozess der Konstruktion manche bei konventioneller Fertigungstechnik und Montage als unwirtschaftlich verworfene Lösungsidee doch noch wirtschaftlich werden lassen. Denn durch Integration mancher Montageprozesse in den Prozess der Additiven Fertigung werden die Gesamtkosten verringert. In diesem Beitrag wird das Potenzial der Additiven Fertigung anhand eines praktischen Beispiels aufgezeigt. Zunächst wird ein Einblick in die methodische Produktentwicklung unter besonderer Berücksichtigung der Additiven Fertigung gegeben. Schon hier offenbaren sich Einsparmöglichkeiten für die spätere Montage durch Integration der Montage in den Prozess der Additiven Fertigung. Es folgt die Beschreibung des Anwendungsbeispiels, des sogenannten RV-Untersetzungsgetriebes, das in Roboterarmen Einsatz findet. Durch das Ersetzen von Massivmaterialbereichen in konventioneller Bauweise durch Materialbereiche mit Leichtbaustrukturen ergibt sich die gewünschte nachhaltige Materialeinsparung. Um nachzuweisen, dass die Teilegestaltung auch die voraussichtlichen Belastungen während der Nutzungsphase berücksichtigt, folgt ein statischer Festigkeitsnachweis mithilfe der Finiten-Elemente-Methode. Hierzu werden Probekörper aus der gleichen Leichtbaustruktur additiv hergestellt und einem Druckversuch unterworfen. Die hieraus gewonnenen mechanischen Kennwerte wie E-Modul und Querkontraktionszahl fließen in den folgenden statischen Festigkeitsnachweis ein.

Wang X., Zhang H., Xu C., Gao X., Zhang Z., Li Y., Liu L.

The molecular dynamics simulation technique was utilized to examine the structural variations of the Cu95Fe5 alloy, as well as the precipitation and aggregation processes of Fe atoms during heat preservation. It is shown that the crystallization temperature of the Cu95Fe5 alloy under the condition of a 2 × 1010 K/s cooling rate is 882 K. Crystallization of the alloy occurs when it is insulated under the temperature conditions of 900 K, 1000 K, and 1100 K. The lower the holding temperature, the shorter the holding time required for the system to initiate crystallization. In other words, lower temperature holding facilitates easier crystallization. The formation process of Fe clusters has been investigated. The size and quantity of Fe clusters at various stages are influenced by the interatomic interaction forces between Fe atoms, the diffusion capabilities of Fe atoms, the local structural rearrangement of nondispersive atoms, and the interfacial energy between Fe clusters and the Cu matrix. The formation of Fe clusters in the insulation process mainly undergoes four stages: First, the initial small clusters are disassembled under the influence of molecular thermal motion and the attractive interactions between Fe atoms. This process leads to the formation and growth of new small clusters. Secondly, the clusters condense and grow under non-diffusive atomic local structure rearrangement. Third, the Fe clusters are sphericalized under Cu-Fe interfacial energy. Fourth, individual Fe atoms are diffused into large Fe clusters under the action of molecular thermal motion.