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This paper studied an integrated process planning and scheduling problem from a machining workshop for large-size valves in a valve manufacturing plant. Large-size valves usually contain several key parts and are generally produced in small-series production. Almost all the parts need to be manufactured in the same workshop at the same time in the plant. Facilities have to handle various items in one order, including different models, sizes, and types. It is a classical NP-hard problem on a large scale. An improved NSGA-II algorithm is suggested to obtain satisfactory solutions for makespan and manufacturing costs, which involve large optimization parameters and interactions. A two-section encoding method and an inserting greedy decoding method are chosen to enable the algorithm. The dynamic population update strategy based on dynamic population update and the adaptive mutation technique depending on the population entropy changing rate are selected for enhancing both the solution quality and population diversity. The methodology was successfully implemented in a real-life case at a major valve machining workshop operated by Yuanda Valve Company in China. By taking into account realistic factors and restrictions that have been identified from a real-world manufacturing setting, this technique aids in bridging the knowledge gap between present IPPS research and practical valve production implementations.

This study investigates the influence of SiO2/Al2O3 molar ratios (2.25–3.00) and the replacement of red mud (RM) with GGBS (50–63%) on the performance of RM-based geopolymers to address the environmental issues posed by RM, including its high alkalinity and heavy metal content. The results indicated that increasing the SiO2/Al2O3 ratio and incorporating GGBS reduced the fresh properties of the geopolymers. A higher SiO2/Al2O3 ratio promoted the development of compressive strength, likely due to the elevated concentration of soluble silicates. The RM-based geopolymers with higher GGBS content also exhibited greater compressive strength. Moreover, the drying shrinkage and water permeability of RM-based geopolymers increased as the SiO2/Al2O3 ratio and the GGBS content increased. The sustainability assessment revealed that CO2 emissions were influenced by the SiO2/Al2O3 ratio. In comparison to other RM-based geopolymers, the CO2 emissions and costs in this study were reduced by 13.13–44.33% and 3.64–39.68%, respectively. This study discusses the effects of the SiO2/Al2O3 molar ratios on the reaction process and strength formation mechanism of RM-based geopolymers, which provides an effective strategy for the resource utilization of RM.

The contradictory nature of increasing the crystallization speed while extending the amorphous stability for phase-change materials (PCMs) has long been the bottleneck in pursuing ultrafast yet persistent phase-change random-access memory. Scandium antimony telluride alloy (ScxSb2Te3) represents a feasible route to resolve this issue, as it allows a subnanosecond SET speed but years of reliable retention of the RESET state. To achieve the best device performances, the optimal composition and its underlying working mechanism need to be unraveled. Here, by tuning the doping dose of Sc, we demonstrate that Sc0.3Sb2Te3 has the fastest crystallization speed and fairly improved data nonvolatility. The simultaneous improvement in such ‘conflicting’ features stems from reconciling two dynamics factors. First, promoting heterogeneous nucleation at elevated temperatures requires a higher Sc dose to stabilize more precursors, which also helps suppress atomic diffusion near ambient temperatures to ensure a rather stable amorphous phase. Second, however, enlarging the kinetic contrast through a fragile-to-strong crossover in the supercooled liquid regime should require a moderate Sc content; otherwise, the atomic mobility for crystal growth at elevated temperatures will be considerably suppressed. Our work thus reveals the recipe by tailoring the crystallization kinetics to design superior PCMs for the development of high-performance phase-change working memory technology.Phase-change memory materials: a faster and more stable changeOptimizing the composition of an alloy provides a route to ultrafast and stable non-magnetic electronic memories according to research from China. The atoms in many materials can stably exist in either an organized crystalline or a disorganized amorphous arrangement. Phase-change materials, which quickly and reversibly switch between the two states, are being developed as digital memories: small regions of the material are encoded in crystalline or amorphous states just as ones and zeros are stored in a magnetic memory. Feng Rao from Shenzhen University and co-workers developed an approach for creating phase-change memory materials that change phase quickly and retain a phase for a long time. The team identified the optimum scandium content in the alloy scandium antimony telluride and showed that this led to faster crystallization and improved data stability.

The heating oil circuit plays an essential role in the heating calendering roller for the lithium battery pole piece. To achieve the optimization of the heating oil circuit, a fluid-thermal-structural coupling method and a multi-objective optimization procedure are proposed to obtain the optimal solution. A fluid–thermal–structural coupling flowchart based on the numerical modeling for the calendering roller temperature distribution is created to automate the analysis processes in the optimization iteration. In the multi-objective optimization procedure, an integrated optimization framework is established by the prebuilt CAD module and the FEM module in the commercial software. Then, the improved NSGA-II algorithm is selected to execute the optimization loop. The methodology was successfully implemented in a redesigned case of a lithium battery rolling equipment company in China. After redesigning the heating oil circuit inside a calendering roller, both the maximum surface temperature non-uniformity and the maximum surface radial thermal deformation of the roller are reduced remarkably by 29.8% and 13.2%, respectively. The results indicate that the proposed method is feasible and makes designing the heating oil circuit easier. The case illustrates that this method can be extended to practical cases of heating oil circuit design for the lithium battery calendering roller.

A high-precision micro-displacement sensor based on tunnel magneto-resistance effect is reported.We designed and simulated magnetic characteristics of the sensor, and employed chip-level Au-In bonding to implement low-temperature assembly of the TMR devices. We employed the subdivision interpolation technique to enhance the resolution by translating the sine-cosine outputs of a TMR sensor into an output that varies linearly with the displacement. Simultaneously, using the multi-bridge circuit method to suppress external magnetic and geomagnetic interference. Experimental result shows that the micro-displacement sensor has a resolution of 800 nm, accuracy of 0.14 % and a full-scale range of up to millimeter level. This work enables a high-performance displacement sensor, and provides a significant guide for the design of a micro-displacement sensor in practical applications.

With the continuous operation of oil and gas stations and petrochemical equipment, it has been found that steel small bore pipelines have different degrees of corrosion defects, which have led to pipeline cracking and medium leakage, and have increasingly attracted great attention of their oil and gas and chemical enterprises. In order to ensure the safe operation of the small diameter pipes with external surface corrosion defects, the influence law of the size of corrosion defects on the bearing capacity of the small diameter pipes were studied by finite element analysis and test simulation method, and the damage mechanism and failure form were analyzed, and the failure pressure prediction formula of the small diameter pipes with defects was fitted. It provides technical guidance for the applicability evaluation of corrosion-containing steel small diameter pipes in oil and gas chemical stations or installations.

Background Identifying the interactions between proteins and long non-coding RNAs (lncRNAs) is of great importance to decipher the functional mechanisms of lncRNAs. However, current experimental techniques for detection of lncRNA-protein interactions are limited and inefficient. Many methods have been proposed to predict protein-lncRNA interactions, but few studies make use of the topological information of heterogenous biological networks associated with the lncRNAs. Results In this work, we propose a novel approach, PLIPCOM, using two groups of network features to detect protein-lncRNA interactions. In particular, diffusion features and HeteSim features are extracted from protein-lncRNA heterogenous network, and then combined to build the prediction model using the Gradient Tree Boosting (GTB) algorithm. Our study highlights that the topological features of the heterogeneous network are crucial for predicting protein-lncRNA interactions. The cross-validation experiments on the benchmark dataset show that PLIPCOM method substantially outperformed previous state-of-the-art approaches in predicting protein-lncRNA interactions. We also prove the robustness of the proposed method on three unbalanced data sets. Moreover, our case studies demonstrate that our method is effective and reliable in predicting the interactions between lncRNAs and proteins. Availability The source code and supporting files are publicly available at: http://denglab.org/PLIPCOM/ .

Angiogenesis is a pivotal mechanism driving tumor proliferation, and the epigenetic regulation of angiogenesis represents a cutting-edge area of current research in multiple myeloma (MM). High-throughput sequencing was carried out to detect the cargos of exosomes from clinical serum and U266 cells, then GSE108824 database was analyzed for the finding of differentially expressed genes (DEGs). The intersect set was made based on the three gene sets. The clinical features of Metastasis-Associated Lung Adenocarcinoma Transcript 1 (MALAT1)were verified through GEO and clinicopathological data analyses. Cell viability, tube formation assay, level of MALAT1 and VEGFA were used to evaluate the effect of U266 exosome pretreated with or without paeoniflorin (PF) on angiogenesis in HUVEC cells. Subcutaneous tumor-bearing mice were established by injection of U266 cells and exosomes derived from U266 cells which pretreated with or without PF. Tumor size, HE staining, analysis of MALAT1 and VEGFA levels, as well as IHC staining for VEGFA, CD31, and Ki67 were performed to evaluate the in vivo effects of PF. The interactions between MALAT1, VEGFA, and microRNAs were demonstrated by TargetScan, MiRanda databases and Luciferase reporter assay. Furthermore, network pharmacology and RROMO, Genecards, AnimalTFDB, JASPAR databases were combinedto predict transcription factors (TF) associated with MALAT1 and analyze the binding sites between PF and these transcription factors. The validation of PF effect on TF was conducted by WB and PCR. Clinical studies indicated a notable positive correlation between MALAT1 level and VEGFA, CD31 expression, moreover, the high MALAT1 level is closely related to poor prognosis of MM. We demonstrated that MALAT1 was the highest expression linear RNA in U266 exosomes and could be transported to HUVEC cells through exosomes, promoting HUVEC cells differentiation and angiogenesis by stimulating VEGFA expression. The tube formation could be blocked if we knockdown the MALAT1 in U266 exosome. It was also proved that this pathological process can be blocked by PF in vitro and in vivo experiments. The ceRNA mechanism in MALAT1/miR-17/VEGFA was predicted and then confirmed by luciferase reporter assay. 2548 PF target genes were retrieved from databases, and the intersections with MALAT1-related differentially expressed proteins, mRNA and TF gene were identified Venn diagaram. MEF2A binding sites were predicted JASPAR, finally molecular docking showed strong affinity between PF and MEF2A (-16.5 kcal/mol).Then the effect of PF on MEF2A/MALAT1 was confirmed by WB or PCR test. To summarize, our study revealed that myeloma cells can increase angiogenesis by releasing exosome to influence the endothelial cells. The MALAT1 from myeloma cells is the crucial factor in this pathological process. PF can obstruct this process by intervening in the MEF2A/MALAT1 in myeloma cells.

The current effect of passive devices is crucial for device testing. The current effect of a suspended graphene pressure sensor in the range of 0–2 mA is studied in this paper. The results show that the resistance of graphene films and the piezoresistive effect of devices exhibit stable performance within the current threshold range of 400 μA and 300 μA, respectively. Auger electron spectroscopy and Raman spectroscopy tests indicate that the resistance of graphene increases first and then decreases at high current intensity, resulting from the electrostatic adsorption of oxygen atoms in the initial phase of electrification and the Joule-induced desorption in the later phase. This study presents guiding significance for the electrical testing of suspended graphene devices.

Fusarium head blight (FHB), caused primarily by ( ), poses a significant threat to wheat production. It is necessary to deeply understand the molecular mechanisms underlying FHB resistance in wheat breeding. In this study, the transcriptomic responses of two Chinese wheat landraces-Wuyangmai (WY, resistant) and Chinese Spring (CS, susceptible)-to infection were examined using RNA sequencing (RNA-seq). Differential expression of mRNAs, long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and microRNAs (miRNAs) was analyzed at 3 and 5 days post- inoculation (dpi). The results showed that WY exhibited a targeted miRNA response, primarily modulating defense-related pathways such as glutathione metabolism and phenylpropanoid biosynthesis, which are crucial for oxidative stress regulation and pathogen defense response. In contrast, CS displayed a broader transcriptional response, largely linked to general metabolic processes rather than immune activation. Notably, the up-regulation of genes involved in oxidative stress and immune defense in WY confirmed its enhanced resistance to FHB. The integrated analysis of miRNA-mRNA interactions highlighted miRNAs as central regulators of defense mechanisms in WY, particularly at later stages of infection. These miRNAs targeted genes involved in immune responses, while lncRNAs and circRNAs played a more limited role in the regulation of defense responses. The GO and KEGG pathway enrichment analyses further revealed that WY enriched for plant-pathogen interaction and secondary metabolite biosynthesis pathways, which are crucial for pathogen resistance. In contrast, CS prioritized metabolic homeostasis, suggesting a less effective defense strategy. Overall, this study underscores the critical role of miRNA-mediated regulation in FHB resistance in WY. These insights into miRNA-mediated regulatory mechanisms provide a molecular basis for breeding FHB-resistant wheat varieties and highlight miRNA-mRNA interactions as promising targets for enhancing disease resilience.