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To address the engineering challenge of installing sensors directly on aircraft lens frames for vibration measurement, this paper proposes a vibration response prediction model (CPO-BP) based on a Crested Porcupine Optimizer Algorithm (CPO)-enhanced Backpropagation (BP) neural network. The model employs a two-step optimization strategy: first, CPO optimizes the number of hidden layer neurons and the learning rate; subsequently, it refines the initial values of the network’s weights and biases, thereby improving both the model’s convergence speed and generalization capability. Experimental results demonstrate that the CPO-BP model achieves a high coefficient of determination (R 2 ) of 0.97976, with a mean absolute error (MAE) as low as 0.02020 and a mean squared error (MSE) of 0.10112. Its predictive performance significantly outperforms COA-BP, DA-BP, PSO-BP, and traditional BP models. The predicted response curves closely match the actual responses across acceleration, velocity, and displacement dimensions. This study provides a highly accurate and reliable solution for vibration condition monitoring at critical locations within optical equipment.

Environmental stressors triggering the translational inhibition and SG formation include ER stress, nutrient starvation, ultraviolet radiation, oxidative stress, heat shock, cold shock, proteasome inhibition, hyperosmotic stress, eIF4A inhibition, nitric oxide accumulation [11], perturbation of pre-mRNA splicing [12] and treatment with puromycin that results in disassembled polysomes [13]. RNA aggregation also plays a role in SG formation, which in turn, might be regulated by RNA helicases [19]. [...]the abundance of mRNAs in the cytoplasm probably affects SGs formation. [...]severe acute respiratory syndrome coronavirus (SARS-CoV) and MERS-CoV nsp1 suppresses host gene expression by mediating host mRNA degradation [44]; the PLpro nsp3 of SARS-CoV and MERS-CoV harbors deubiquitinase activity and interferes with type I IFN responses [45,46]; Feline Infectious Peritonitis Coronavirus (FCoV) and Porcine Delta-coronavirus (PDCoV) nsp5 inhibits type I IFN response by cleaving NEMO [47,48]; porcine epidemic diarrhea virus (PEDV) nsp16 restricts IFN production and facilitate virus replication [49]. Furthermore, we used SG-defective cells to demonstrate that SGs play an anti-viral role by promoting the IFN response. [...]the anti-SG formation by nsp15 is conserved in different genera of coronaviruses.

To date, incineration is the main method of municipal solid waste (MSW) disposal. Fly ash and bottom ash (BA) are generated in large amounts from municipal solid waste incineration (MSWI), but the disposal of incineration residues poses a significant challenge to large cities with limited landfill space. The feasibility of using MSWI-BA to replace natural sand in the preparation of self-compacting mortar (SCM) was investigated to realize the resource utilization of MSWI-BA. The changes in SCM regarding durability, mechanical properties and workability when MSWI-BA was added at varying ratios were explored in this study. In addition, the changes in SCM microstructure, dynamic modulus of elasticity (DME) and ultrasonic pulse velocity (UPV) under the impacts of MSWI-BA were investigated. Eventually, the environmental and economic effects of SCM were weighed via the material sustainability index. It was found that (1) there was a drop of 23.79–44.69% in the compressive strength of SCM and a drop of 12.22–30.99% in the flexural strength, due to the incorporation of MSWI-BA; (2) the drying shrinkage of SCM increased from 2.9 to 11.76%, and the chloride migration coefficient increased from 4.66 to 46.06%, due to the incorporation of MSWI-BA; (3) the production costs, carbon footprint and energy consumption of SCM could be reduced, due to the addition of MSWI-BA; and (4) SCM could satisfy the engineering requirements of durability, mechanical properties and workability. Therefore, MSWI-BA was found to be a feasible method for the production of SCM.

Ultra-high-performance concrete (UHPC) has been used as an advanced construction material in civil engineering because of its excellent mechanical properties and durability. However, with the depletion of the raw material (river sand) used for preparing UHPC, it is imperative to find a replacement material. Recycled sand is an alternative raw material for preparing UHPC, but it degrades the performance. In this study, we investigated the use of graphene oxide (GO) as an additive for enhancing the properties of UHPC prepared from recycled sand. The primary objective was to investigate the effects of GO on the mechanical properties and durability of the UHPC at different concentrations. Additionally, the impact of the GO additive on the microstructure of the UHPC prepared from recycled sand was analysed at different mixing concentrations. The addition of GO resulted in the following: (1) The porosity of the UHPC prepared from recycled sand was reduced by 4.45–11.35%; (2) the compressive strength, flexural strength, splitting tensile strength, and elastic modulus of the UHPC prepared from recycled sand were enhanced by 8.24–16.83%, 11.26–26.62%, 15.63–29.54%, and 5.84–12.25%, respectively; (3) the resistance of the UHPC to penetration of chloride ions increased, and the freeze–thaw resistance improved; (4) the optimum mixing concentration of GO in the UHPC was determined to be 0.05 wt.%, according to a comprehensive analysis of its effects on the microstructure, mechanical properties, and durability of the UHPC. The findings of this study provide important guidance for the utilisation of recycled sand resources.

The hallmark of coronavirus infection lies in its ability to evade host immune defenses, a process intricately linked to the nuclear entry of transcription factors crucial for initiating the expression of antiviral genes. Central to this evasion strategy is the manipulation of the nucleocytoplasmic trafficking system, which serves as an effective target for the virus to modulate the expression of immune response-related genes. In this investigation, we discovered that infection with the infectious bronchitis virus (IBV) dynamically impedes the nuclear translocation of several transcription factors such as IRF3, STAT1, STAT2, NF-κB p65, and the p38 MAPK, leading to compromised transcriptional induction of key antiviral genes such as IFNβ, IFITM3, and IL-8. Further examination revealed that during the infection process, components of the nuclear pore complex (NPC), particularly FG-Nups (such as NUP62, NUP153, NUP42, and TPR), undergo cytosolic dispersion from the nuclear envelope; NUP62 undergoes phosphorylation, and NUP42 exhibits a mobility shift in size. These observations suggest a disruption in nucleocytoplasmic trafficking. Screening efforts identified the IBV nucleocapsid (N) protein as the agent responsible for the cytoplasmic distribution of FG-Nups, subsequently hindering the nuclear entry of transcription factors and suppressing the expression of antiviral genes. Interactome analysis further revealed that the IBV N protein interacts with the scaffold protein RACK1, facilitating the recruitment of activated protein kinase C alpha (p-PKCα) to RACK1 and relocating the p-PKCα-RACK1 complex to the cytoplasm. These observations are conserved across diverse coronaviruses N proteins. Concurrently, the presence of both RACK1 and PKCα/β proved essential for the phosphorylation and cytoplasmic dispersion of NUP62, the suppression of antiviral cytokine expression, and efficient virus replication. These findings unveil a novel, highly effective, and evolutionarily conserved mechanism.

The pathological mechanisms underlying ischemic stroke are highly complex, with the neuroinflammatory response triggered by cerebral ischemia-reperfusion being a major contributor to secondary brain damage. This response significantly impedes neural tissue regeneration. Despite advancements in treatment, current anti-inflammatory strategies remain suboptimal in terms of safety and efficacy. This study aimed to develop an all-natural nanomedicine delivery system for the transnasal administration of puerarin, combined with the endogenous anti-inflammatory peptide Ac2-26, to enhance neuroprotection against ischemic stroke through a synergistic anti-inflammatory approach. In this study, collagen nanoparticles (PueNps) loaded with puerarin were synthesized, followed by the preparation of a chitosan hydrogel. The PueNps and Ac2-26 were co-encapsulated within the hydrogel, resulting in the formation of the PueNps&Ac2-26 gel formulation. The physicochemical properties of this formulation, as well as its biodistribution and anti-ischemic efficacy in the MCAO rat brain, were evaluated. In this formulation system, the bioavailability of puerarin and Ac2-26 was enhanced, exhibiting sustained-release properties, which enabled efficient brain-targeted delivery. It effectively alleviated neurological impairment in MCAO rats, reduced the volume of cerebral infarction, and decreased brain water content. Additionally, the PueNps&Ac2-26 gel significantly inhibited neuroinflammation in rats and alleviated oxidative stress. The PueNps&Ac2-26 gel is a purely natural and efficient formulation system, offering a promising approach for the clinical treatment of ischemic stroke in the future.

The endoribonuclease (EndoU) nsp15 of coronaviruses plays a crucial role in evading host innate immune responses by reducing the abundance of viral double-stranded RNA (dsRNA). However, our understanding of its interactions with host cellular targets remains limited. In this study, we demonstrate that overexpression of nsp15 from four coronavirus genera inhibits cellular protein synthesis and causes nuclear retention of PABPC1. Mutation analysis confirms the essential role of EndoU activity in these processes. Fluorescence in situ hybridization (FISH) analysis shows that cellular mRNA co-localizes with nsp15 in certain cells. Real time RT-PCR indicates that the mRNA levels of several antiviral genes decrease in cells expressing nsp15, and this reduction depends on the EndoU activity of nsp15. Using infectious bronchitis virus (IBV) as a model, we investigate the inhibitory effect of nsp15 on protein translation during infection. We find that infection with IBV with functional nsp15 suppresses protein synthesis in a PKR-eIF2α independent manner, with PABPC1 mainly located in the cytoplasm. However, infection with EndoU activity-deficiency mutant virus rIBV-nsp15-H238A results in the accumulation of viral dsRNA, triggering a PKR-eIF2α-dependent shutdown of protein synthesis and leading to the nuclear relocation of PABPC1. In the absence of the PKR-eIF2α pathway, IBV is still able to suppress host protein synthesis, while the inhibitory effect of rIBV-nsp15-H238A on protein synthesis was significantly reduced. Although nsp15 locates to replication-transcription complex (RTC) during infection, RNA immunoprecipitation (RIP)-Seq analysis confirms that IBV nsp15 binds to six viral RNAs and 237 cellular RNAs. The proteins encoded by the nsp15-associated cellular RNAs predominantly involved in translation. Additionally, proteomic analysis of the nsp15 interactome identifies 809 cellular proteins, which are significantly enriched in pathways related to ribosome biogenesis, RNA processing, and translation. Therefore, nsp15 helps virus circumvent the detrimental PKR-eIF2α pathway by reducing viral dsRNA accumulation and suppresses host protein synthesis by targeting host RNAs and proteins. This study reveals unique yet conserved mechanisms of protein synthesis shutdown by catalytically active nsp15 EndoU, shedding light on how coronaviruses regulate host protein expression.

[This corrects the article DOI: 10.1371/journal.ppat.1012987.].

Disassembly plays an important role in the production process. Screw automatic unfastening guided by a robot has been widely used in the fields of industrial manufacturing and maintenance. Different from the previous studies that have used a flexible effector and expensive sensors, this paper presents a novel unfastening strategy based on robot vision for a hexagonal screw with an arbitrary loose state. In a robotic system, an industrial camera and a servo unfastening tool are installed at a robotic end-effector. The main contributions of this work are as follows. A camera pose adjustment method is proposed to obtain high-quality images of a target screw. The hexagonal screw pose calculation method based on the geometric analysis is developed to complete the screw–tool engagement. The cooperated motion of a robot and an unfastening tool is planned for the screw unfastening action. The effectiveness of the proposed control strategy is verified by experiments, and the influence of the motion speed on the unfastening quality is analyzed using the torque data collected by the unfastening tool. The analysis results can provide a significant foundation for the motion parameter selection in the proposed strategy.

For complex equipment, it is easy to over-evaluate the impact of failure on production by estimating the reliability level only through failure probability. To remedy this problem, this paper proposes a statistical evaluation method based on fuzzy failure data considering the multi-state characteristics of equipment failures. In this method, the new reliability-evaluation scheme is firstly presented based on the traditional statistical analysis method using the Weibull distribution function. For this scheme, the failure-grade index is defined, and a fuzzy-evaluation method is also proposed by comprehensively considering failure severity, failure maintenance, time, and cost; this is then combined with the time between failures to characterize the failure state. Based on the fuzzy failure data, an improved adaptive-failure small-sample-expansion method is proposed based on the classical bootstrap method and the deviation judgment between distributions of the original and newborn samples. Finally, a novel reliability-evaluation model, related to the failure grade and its membership degree, is established to quantify the reliability level of equipment more realistically. Example cases for three methods of the scheme (the failure-grade fuzzy-evaluation method, the sample-expansion method, and the reliability-evaluation modeling method) are presented, respectively, to validate the effectiveness and significance of the proposed reliability-evaluation technology.