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Background There is a close association between diet and abdominal pain; however, relationship between inflammatory diet and characteristics of abdominal pain has not been characterized yet. Methods This study analyzed baseline data from the UK Biobank, 3-item DHQ-Abdominal Pain Questionnaire (DHQ-3Q), which including abdominal pain in the past 3 months, severity of abdominal pain, and frequency of abdominal pain, and data from the National Health and Nutrition Examination Survey (NHANES) from 2017 to 2020. Energy-adjusted Dietary Inflammatory Index (E-DII), constructed based on 26 or 27 nutrients, was analyzed using continuous or categorical methods. Logistic regression and restricted cubic spline analyses examined the association between E-DII and abdominal pain. Results In UK Biobank, compared to participants in the lowest quintile of E-DII, the adjusted ORs for the highest quintile were 1.12 (95% CI 1.02–1.24; P  = .022), 1.05 (95% CI 1.00–1.09; P  = .030), 1.26 (95% CI 1.17–1.36; P  < .001), and 1.10 (95% CI 1.00–1.20; P  = .044) for chronic abdominal pain, abdominal pain in the past three months, severity of abdominal pain, and frequency of abdominal pain, respectively. In NHANES, compared to participants in the lowest quintile of E-DII, the adjusted ORs for the highest quintile were 1.46 (95% CI 1.20–1.77; P  < .001), 1.75 (95% CI 1.20–2.60; P  = .005), 1.45 (95% CI 1.14–1.87; P  = .003), and 1.18 (95% CI 0.82–1.72; P  = .380) for abdominal pain in the past year, upper left abdominal pain, upper middle abdominal pain, and upper right abdominal pain. Additionally, there was a nonlinear correlation between E-DII score and DHQ-3Q (P nonlinear <.001). Conclusion Following a pro-inflammatory diet is linked to a higher likelihood of experiencing abdominal pain, as well as increased severity and frequency of such pain. Therefore, further longitudinal studies are necessary to investigate this relationship. [ABSTRACT FROM AUTHOR]

Highly reliable mechanical systems can lead to significant losses in the event of failure, and the lack of comprehensive failure data presents challenges for developing techniques such as critical part identification and failure prediction. In light of this, this paper proposes a meta‐action‐based fault prediction method that effectively addresses the issue of limited fault data. Initially, the mechanical system is decomposed utilizing the "Function‐Motion‐Action" (FMA) methodology to derive individual meta‐action units (MAUs). Subsequently, the limited sample of fault data from the mechanical system is combined with processed expert knowledge to construct the corresponding fault propagation‐directed graph. Furthermore, the key MAUs are determined by applying the Decision–Making Trial and Evaluation Laboratory (DEMATEL) method. Last, the degradation data of the key MAUs is acquired by monitoring them, and a non‐homogeneous discrete grey model (DNGM) integrated with an improved BP neural network is proposed to facilitate the fault prediction of MAUs. Using an industrial robot as a case study, the prediction results demonstrate the superiority of the method proposed in this paper over a single gray model and neural network, thereby providing a reliable prediction approach for anticipating the future trends of data‐deficient mechanical systems. [ABSTRACT FROM AUTHOR]

Previous studies have suggested that exposure to air pollutants may be associated with specific blood indicators or anemia in certain populations. However, there is insufficient epidemiological data and prospective evidence to evaluate the relationship between environmental air pollution and specific types of anemia. We conducted a large-scale prospective cohort study based on the UK Biobank. Annual average concentrations of NO2, PM2.5, PM2.5-10, and PM10 were obtained from the ESCAPE study using the Land Use Regression (LUR) model. The association between atmospheric pollutants and different types of anemia was investigated using the Cox proportional hazards model. Furthermore, restricted cubic splines were used to explore exposure-response relationships for positive associations, followed by stratification and effect modification analyses by gender and age. After adjusting for demographic characteristics, 3-4 of the four types of air pollution were significantly associated with an increased risk of iron deficiency, vitamin B12 deficiency and folate deficiency anemia, while there was no significant association with other defined types of anemia. After full adjustment, we estimated that the hazard ratios (HRs) of iron deficiency anemia associated with each 10 μg/m3 increase in NO2, PM2.5, and PM10 were 1.04 (95%CI: 1.02, 1.07), 2.00 (95%CI: 1.71, 2.33), and 1.10 (95%CI: 1.02, 1.20) respectively. The HRs of folate deficiency anemia with each 10 μg/m3 increase in NO2, PM2.5, PM2.5-10, and PM10 were 1.25 (95%CI: 1.12, 1.40), 4.61 (95%CI: 2.03, 10.47), 2.81 (95%CI: 1.11, 7.08), and 1.99 (95%CI: 1.25, 3.15) respectively. For vitamin B12 deficiency anemia, no significant association with atmospheric pollution was found. Additionally, we estimated almost linear exposure-response curves between air pollution and anemia, and interaction analyses suggested that gender and age did not modify the association between air pollution and anemia. Our research provided reliable evidence for the association between long-term exposure to PM10, PM2.5, PM2.5-10, NO2, and several types of anemia. NO2, PM2.5, and PM10 significantly increased the risk of iron deficiency anemia and folate deficiency anemia. Additionally, we found that the smaller the PM diameter, the higher the risk, and folate deficiency anemia was more susceptible to air pollution than iron deficiency anemia. No association was observed between the four types of air pollution and hemolytic anemia, aplastic anemia, and other types of anemia. Although the mechanisms are not well understood, we emphasize the need to limit the levels of PM and NO2 in the environment to reduce the potential impact of air pollution on folate and iron deficiency anemia. [ABSTRACT FROM AUTHOR]

Introduction: Rapid identification of infected individuals through viral RNA or antigen detection followed by effective personal isolation is usually the most effective way to prevent the spread of a newly emerging virus. Large-scale detection involves mass specimen collection and transportation. For biosafety reasons, denaturing viral transport medium has been extensively used during the SARS-CoV-2 pandemic. However, the high concentrations of guanidinium isothiocyanate (GITC) in such media have raised issues around sufficient GITC supply and laboratory safety. Moreover, there is a lack of denaturing transport media compatible with SARS-CoV-2 RNA and antigen detection. Methods: Here, we tested whether supplementing media containing low concentrations of GITC with ammonium sulfate (AS) would affect the throatswab detection of SARS-CoV-2 or a viral inactivation assay targeting coronavirus and other enveloped and non-enveloped viruses. The effect of adding AS to the media on RNA stability and its compatibility with SARS-CoV-2 antigen detection were also tested. Results and discussion: We found that adding AS to the denaturing transport media reduced the need for high levels of GITC, improved SARS-COV-2 RNA detection without compromising virus inactivation, and enabled the denaturing transport media compatible with SARS-CoV-2 antigen detection. [ABSTRACT FROM AUTHOR]

The Bohai Sea and its surrounding areas are rich in oil and natural gas and play an important role in industry, agriculture and the economy. However, the Bohai Sea suffers severely from sea ice in the winter. While previous research has predominantly focused on methods for retrieving sea ice parameters in the Bohai Sea, analyses of their long-term statistical patterns have been limited. The Geostationary Ocean Color Imager (GOCI) is the first geostationary satellite for ocean color remote sensing, offering high spatial and temporal resolution, which greatly facilitates the extraction of Bohai Sea ice parameters. Utilizing GOCI data, we systematically extracted relevant sea ice parameters for the Bohai Sea region from 2011 to 2021. These parameters include sea ice concentration, sea ice thickness, and sea ice drift. We conducted a comprehensive statistical analysis of the long-term sea ice changes in the Bohai Sea and found that the development process of winter sea ice area is different from the sea ice thickness, and the direction of sea ice drift is basically unchanged. Then we developed statistical models linking sea ice parameters with ocean dynamic factors such as temperature, wind, and drift currents. Among them, the correlation coefficient between the predicted value and the measured value of the sea ice area model is the highest, reaching 0.8382. Furthermore, we examined the previously unexplored relationship between daily sea ice area, sea ice thickness, and accumulated temperature with their respective starting temperatures and accumulation periods. This study provides critical data to support Bohai Sea ice monitoring and marine environmental research. The results of this study contribute to a better understanding of sea ice change trends in the Bohai Sea and inform the development of disaster prevention and mitigation measures. [ABSTRACT FROM AUTHOR]

Maintenance strategy selection is an important step in maintenance management, which is the basis for implementing maintenance optimization and formulating specific maintenance schemes. This paper takes the meta-action unit (MU) as the research object, considers the randomness and fuzziness of expert evaluation and the interaction between evaluation criteria in the selection process of maintenance strategy, and proposes a maintenance strategy selection method based on cloud DEMATEL-ANP. Firstly, DEMATEL based on cloud model is used to establish the interaction model between the main criteria, determine the weighted cloud weight of the super matrix and the inner dependencies of the sub-criteria under the same main criteria. Then, the cloud-ANP model is used to determine the outer dependencies relationship and construct the cloud super matrix, so as to obtain the cloud weight of each evaluation criteria in maintenance strategy selection. By using the subjective and objective weighting method, the evaluation of different experts on different maintenance strategy criteria is integrated, and the priority of alternative maintenance strategies of MU is obtained. Finally, different methods are used to sort and compare the alternative maintenance strategies of the rotating body rotation MU of the CNC turntable, which verifies the scientificity and effectiveness of the maintenance strategy selection method based on cloud DEMATEL-ANP are verified. [ABSTRACT FROM AUTHOR]

Selecting the right cathode material is a key component to achieving high‐energy and long‐lifespan aqueous zinc‐ion batteries (AZIBs); however, the development of cathode materials still faces serious challenges due to the high polarization of Zn2+. In this work, MnV12O31·10H2O (MnVO) synthesized via a one‐step hydrothermal method is proposed as a promising cathode material for AZIBs. Because the stable layered structure and hieratical morphology of MnVO provide a large layer space for rapid ion transports, this material exhibits high specific capacity (433 mAh g−1 at 0.1 A g−1), an outstanding long‐term cyclability (5000 cycles at a current density of 3 A g−1), and an excellent energy density (454.65 Wh kg−1). To illustrate the intercalation mechanism, ex situ X‐Ray diffraction, Fourier transform infrared spectroscopy, and X‐ray photoelectron spectroscopy are adopted, uncovering an H+/Zn2+ dual‐cation co‐intercalation processes. In addition, density‐functional theory calculation analysis shows that MnVO has a delocalized electron cloud and the diffusion energy barrier of Zn2+ in MnVO is low, which promotes the Zn2+ transport and consequently improves the reversibility of the battery upon deep cycling. The key and enlightening insights are provided in the results for designing high‐performance vanadium‐oxide‐based cathode materials for AZIBs. [ABSTRACT FROM AUTHOR]

Background: Genetic and environmental factors contribute to migraine and the comorbidities of anxiety and depression. However, the association between genetic polymorphisms in the transient receptor potential (TRP) channels and glutamatergic synapse genes with the risk of migraine and the comorbidities of anxiety and depression remain unclear. Methods: 251 migraine patients containing 49 comorbidities with anxiety and 112 with depression and 600 controls were recruited. A customized 48-plex SNPscan kit was used for genotyping 13 SNPs of nine target genes. Logistic regression was conducted to analyze these SNPs' association with the susceptibility of migraine and comorbidities. The generalized multifactor dimension reduction (GMDR) was applied to analyze the SNP-SNP and geneenvironment interactions. The GTEx database was used to examine the effects of the significant SNPs on gene expressions. Results: The TRPV1 rs8065080 and TRPV3 rs7217270 were associated with an increased risk of migraine in the dominant model [ORadj (95% CI): 1.75 (1.09-2.90), p = 0.025; 1.63 (1.02-2.58), p = 0.039, respectively]. GRIK2 rs2227283 was associated with migraine in the edge of significance [ORadj (95% CI) = 1.36 (0.99-1.89), p = 0.062]. In migraine patients, TRPV1 rs222741 was associated with both anxiety risk and depression risk in the recessive model [ORadj (95% CI): 2.64 (1.24-5.73), p = 0.012; 1.97 (1.02-3.85), p = 0.046, respectively]. TRPM8 rs7577262 was associated with anxiety (ORadj = 0.27, 95% CI = 0.10-0.76, p = 0.011). TRPV4 rs3742037, TRPM8 rs17862920 and SLC17A8 rs11110359 were associated with depression in dominant model [ORadj (95% CI): 2.03 (1.06-3.96), p = 0.035; 0.48 (0.23-0.96), p = 0.042; 0.42 (0.20-0.84), p = 0.016, respectively]. Significant eQTL and sQTL signals were observed for SNP rs8065080. Individuals with GRS (Genetic risk scores) of Q4 (14-17) had a higher risk of migraine and a lower risk of comorbidity anxiety than those with Genetic risk scores scores of Q1 (0-9) groups [ORadj (95% CI): 2.31 (1.39-3.86), p = 0.001; 0.28 (0.08-0.88), p = 0.034, respectively]. Conclusion: This study suggests that TRPV1 rs8065080, TRPV3 rs7217270, and GRIK2 rs2227283 polymorphism may associate with migraine risk. TRPV1 rs222741 and TRPM8 rs7577262 may associate with migraine comorbidity anxiety risk. rs222741, rs3742037, rs17862920, and rs11110359 may associate with migraine comorbidity depression risk. Higher GRS scores may increase migraine risk and decrease comorbidity anxiety risk. [ABSTRACT FROM AUTHOR]

In this paper, a functionality unit named as meta-action unit (MAU) is proposed to correlate the system function with the part actions and assess reliability of mechanical system. Firstly, the function of system is decomposed into multiple MAUs by function-movement-action (FMA). Then, the lifetime of MAU is fitted by Weibull distribution, and its parameters are estimated by support vector regression (SVR). In addition, taking the distributions of MAU as marginal distributions, the lifetime distribution of mechanical system is constructed by copula function to assess system reliability, and its parameters are estimated using the maximum likelihood estimator (MLE). Further, the reliability assessment accuracy based on MAU is compared with that from traditional method based on mechanical part failure modes. Finally, the reliability assessment of the indexing turntable (IT) is performed as an example to illustrate the feasibility and reasonability of the proposed method. [ABSTRACT FROM AUTHOR]

The ongoing pandemic of coronavirus disease 2019 (COVID‐19) caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has posed a major public health threat worldwide and emphasizes an urgent need for effective therapeutics. Recently, Ordonez et al. identified sulforaphane (SFN) as a novel coronavirus inhibitor both in vitro and in mice, but the mechanism of action remains elusive. In this study, we independently discovered SFN for its inhibitory effect against SARS‐CoV‐2 using a target‐based screening approach, identifying the viral 3‐chymotrypsin‐like protease (3CLpro) as a target of SFN. Mechanistically, SFN inhibits 3CLpro in a reversible, mixed‐type manner. Moreover, enzymatic kinetics studies reveal that SFN is a slow‐binding inhibitor, following a two‐step interaction. Initially, an encounter complex forms by specific binding of SFN to the active pocket of 3CLpro; subsequently, the isothiocyanate group of SFN as "warhead" reacts covalently to the catalytic cysteine in a slower velocity, stabilizing the SFN‐3CLpro complex. Our study has identified a new lead of the covalent 3CLpro inhibitors which has potential to be developed as a therapeutic agent to treat SARS‐CoV‐2 infection. [ABSTRACT FROM AUTHOR]

Accuracy-related key quality characteristics (ARKQCs), namely accuracy, accuracy stability, and accuracy retainability, are important performance indicators to characterize the machining accuracy of machine tools. To achieve accurate allocation in the design stage, this paper reveals the coupling relationships among ARKQCs and proposes a meta-action-oriented collaborative allocation optimization method for ARKQCs of machine tools. Taking the function-motion-action decomposition tree as the allocation path, the error modeling mechanism of each layer is analyzed, and the error models of the F-M layer and M-A layer are established. Based on the error model, a quasi-Monte Carlo algorithm–based improved Sobol method is used to analyze the sensitivity of child layer error components to parent layer accuracy, and the accuracy stability model of machine tools is established. Taking the cost, reliability, and quality loss factors as objective functions, the ARKQC allocation optimization model is constructed, and NSGA-II algorithm is used to solve it optimally. To verify the effectiveness of the proposed method, a computer numerical control (CNC) gear milling machine is taken as a practical case, and a machining accuracy reliability evaluation method based on the quasi-Monte Carlo simulation is proposed to verify the rationality of the allocation results. This method provides theoretical guidance for comprehensively improving the accuracy design quality of CNC machine tools. [ABSTRACT FROM AUTHOR]

In the process of reliability comprehensive evaluation based on meta-action theory, the structural interactions between contemporaneous meta-action (CMA) will have a great impact on the whole evaluation process. Therefore, it is necessary to analyze the reliability coupling mechanism between T-translation-type CMA in conducting reliability comprehensive evaluation of CNC machine tools. In light of this fact, this paper first introduces the structure and the reliability coupling reasons of T-translation-type CMA briefly. Then, the forces and deformation of the worktable movement meta-action unit under two cases that the frame deforms along the length direction and the width direction of rail are analyzed, and the dynamic models of the target meta-action unit based on a simplified single-degree-of-freedom model are constructed. What is more, the active learning Kriging-Monte Carlo simulation (ALK-MCS) method is utilized to calculate the reliability of target meta-action. At last, the rationality and effectiveness of the dynamic model and the reliability calculation method proposed in this paper are verified by numerical simulation and experiment, and the reliability coupling mechanism of T-translation-type CMA under two kinds of frame deformation is analyzed. [ABSTRACT FROM AUTHOR]

Accurately identifying the error transfor path of the meta-action unit was the premise of error analysis. A new method was proposed to judge the error transmission path of the meta-action units based on the concept of DOF constraints in mechanical systems. Firstly, the DOF constraint requirements of the precision output parts and the initial error transfer path were determined by analyzing the functions and the structures of the meta-action units. Secondly, the constraint properties of the joint surfaces were analyzed, and the DOF constraint properties of the precision output parts were calculated along the error transfer path. The error transfer path was determined by comparing the obtained constraint property with the designed constraint property. Compared with traditional methods, the proposed method improves the efficiency of the analysis and identification of the error transfer paths greatly. [ABSTRACT FROM AUTHOR]

Background: Zoster-associated pain (ZAP) is notoriously difficult to treat. Pulsed radiofrequency (PRF) and short-term nerve electrical stimulation (st-NES) have been proven effective treatments for ZAP. However, it is still unclear which technique provides improved analgesia in ZAP. This study is based on a large-scale, long-term follow-up to evaluate the efficacy and safety between st-NESand PRF. Materials and methods: All eligible ZAP patients treated with st-NES or PRF in our department were enrolled. Cohorts were divided into the st-NES group and the PRF group. A 1:1 ratio propensity score matching (PSM) was used to balance the baseline characteristics. The PS-matched cohort was adopted to investigate the efficacy and safety of the two treatments. The ordinal regression analysis was performed to determine the variables affecting the treatment effect of ZAP. Results: A total of 226 patients were included after PSM. The numerical rating scale (NRS) scores in st-NES and PRF groups considerably reduced compared to baseline levels after treatment. The NRS scores in the st-NES group were obviously lower than those in the PRF group at discharge, 1, 3, 6, 12, and 24 months. During the follow-up period, the NRS reduction rate remained higher in the st-NES group than in the PRF group (P < 0.01). The dosage of medication, Pittsburgh Sleep Quality Index (PSQI) score, and the number of patients with aggravated pain after discharge in the st-NES group were significantly less than in the PRF group after treatment. Conclusion: Short-term nerve electrical stimulation has been shown to be more advantageous than PRF for pain relief and quality of life improvement for ZAP patients. [ABSTRACT FROM AUTHOR]

Cholesterol crystals participate in cholesterol nucleation; however, the role of cholesterol crystals in gallstone development is unknown. Mucin secretion contributes to increased size of gallstones. Cholesterol crystals activate inflammasomes and participate in many sterile inflammation related human diseases. We investigated the role of cholesterol crystals and mucins in sterile inflammation and gallstone enlargement. We found that expression of mucin 5AC (MUC5AC), NOD-, LRR- and pyrin domain-containing protein 3 (NLRP3) and interleukin-1b (IL-1b) was increased significantly in tissues adjacent to gallstones. Experiments in vitro showed that cholesterol crystals promote MUC5AC secretion; they also increase expression of NLRP3, NLR family CARD domain-containing 4 (NLRC4), apoptosis-associated speck-like protein containing caspase recruitment domain (ASC), and cleaved caspase-1 in biliary epithelial cells. Inhibition of Inflammasomes by NLRP3, ASC or caspase-1 small interfering RNAs reduced MUC5AC secretion. Also, the IL-1 receptor antagonist, IL1RA, and caspase-1 inhibitor, Ac-YVAD, both inhibited MUC5AC secretion induced by cholesterol crystals. We found that inflammasome activation participates in cholesterol crystal induced mucin secretion and gallstone development. [ABSTRACT FROM AUTHOR]

Previous studies seldom consider the difference of preventive maintenance effect on different failure processes when establishing the preventive maintenance model. Meanwhile, preventive maintenance models usually assume that minimal repair is performed for each failure, but this assumption is not applicable in some systems. Once this assumption is made for the inapplicable system, the maintenance strategy obtained by the established preventive maintenance model will not be optimal. In order to get a better maintenance policy to reduce maintenance cost, this paper divides the system failure processes into two types: wear-out type and damage-type. The model assumes that preventive maintenance can reduce the probability of damage-type failure, but it has no effect on wear-out type failure. At the same time, for the system studied in this paper, it is assumed that after corrective maintenance, the overall state of the system is worse than the moment just prior to the failure. Then, an extended preventive maintenance optimization model based on generalized Polya process is established. Finally, a practical algorithm is designed to solve the model. The analysis of numerical examples shows the potential value of the proposed method, which may provide maintenance guidance for enterprises and save maintenance costs. [ABSTRACT FROM AUTHOR]

Preventive maintenance is an important means to extend equipment life and improve equipment reliability. Traditional preventive maintenance decision-making is often based on components or the entire system, the granularity is too large and the decision-making is not accurate enough. The meta-action unit is more refined than the component or system, so the maintenance decision-making based on the meta-action unit is more accurate. Therefore, this paper takes the meta-action unit as the research carrier, considers the imperfect preventive maintenance, based on the hybrid hazard rate model, established the imperfect preventive maintenance optimization model of the meta-action unit, and the optimization solution algorithm was given for the maintenance strategy. Finally, through numerical analysis, the validity of the model is verified, and the influence of different maintenance costs on the optimal maintenance strategy and optimal maintenance cost rate is analyzed. [ABSTRACT FROM AUTHOR]

Reliability optimal allocation is a critical method in engineering and operation fields to improve and ensure product quality. However, conventional model generally uses the single objective with research and development (R & D) cost or product reliability. Moreover, the popular particle swarm optimization (PSO) algorithm solving the model has insufficient global search ability. In this paper, a novel reliability optimal allocation method is developed based on double-objective model and multi-population PSO (MPPSO) algorithm. The cost function is established considering all the cost related to reliability using analytical hierarchical process (AHP) and ordered weighted averaging (OWA) operator. Multi-population particle swarm optimization algorithm is developed based on information exchange mechanism among subpopulations. In the algorithm, the inertia weight is optimized by chaotic map, and different mutation operations are carried out on the subpopulations. An illustrative example, which implements to computer numerical control (CNC) grinding machine, is presented to illustrate the practicality and application of the proposed method. Finally, the comparison and analysis are implemented to show the advantage of proposed model and MPPSO algorithm. [ABSTRACT FROM AUTHOR]

Aqueous zinc‐ion batteries (AZIBs) have become a promising alternative energy storage device due to their lower cost and better safety performance than lithium‐ion batteries (LIBs). However, the biggest challenge is the need to develop electrode materials with higher capacity and longer life than LIBs at present. Herein this work, a tunnel‐structured sodium vanadate (NaV6O15) is synthesized by molten salt method as the cathode materials for AZIBs. The prepared NaV6O15 nanosheets have a high specific capacity of 325 mAh g−1 at a current density of 0.1 A g−1, and the capacity retention rate is as high as 127.08% under 1000 cycling at a current density of 1 A g−1. This excellent performance is mainly attributed to the stable tunneled structure, which provides an effective diffusion path for Zn2+ insertion and avoids structural damage. Herein the subsequent cycles, Zn2+ is mainly inserted/extracted in NaV6O15 and Zn3(OH)2V2O7·2H2O. The preparation of NaV6O15 cathode materials and the molten salt method provide a certain reference value for the development of AZIBs in this work. [ABSTRACT FROM AUTHOR]

Aqueous zinc-ion batteries (ZIBs) is a potential energy storage system due to its advantages of low cost, good safety, and high theoretical capacity (820 mAh gâˆ'1). However, the lack of cathode materials with long cycle stability severely restricts the development of ZIBs. In this paper, V2O5/ NaV6O15 nanocomposites are synthesized by molten salt method in one step and used as cathode material for ZIBs, which have good electrochemical performances. The specific capacity of the materials remain 160 mAh gâˆ'1 when the current density is 0.5 A gâˆ'1 after 1000 cycles, and the capacity retention rate is 102.03% when the current density is 5 A gâˆ'1 for 1000 cycles. This is mainly due to the large number of active sites generated by crystal defects and the synergistic interaction between the dual-phase materials, which reduces the stress of ions inserted/extracted during the Zn2+ storage process and improves the electrochemical performance. [ABSTRACT FROM AUTHOR]

With the popularization and application of technologies such as monitoring and sensing, the application of condition-based maintenance has become increasingly widespread. However, most traditional condition-based maintenance strategies focus on a component or system, which is too large for fault diagnosis and location. Moreover, imperfect maintenance is seldom considered and most of them only optimize the single variable in condition-based maintenance decision. In this paper, the meta-action unit is taken as the research object, and the Wiener process is used to describe the performance degradation of the meta-action unit. Considering that the maintenance quality deteriorates with the increase of the number of maintenance, and has randomness, the beta distribution is used to establish an imperfect preventive maintenance quality model. A new maintenance optimization strategy is proposed, with the long-term maintenance cost rate as the goal, to obtain the best preventive maintenance threshold, inspection cycle and the optimal number of maintenance. Finally, a Monte Carlo simulation was used to solve numerically and analyze the influence of each parameter on the optimal decision. It can provide a reference for the decision-making when developing maintenance policies. [ABSTRACT FROM AUTHOR]

Cancer immunotherapy frequently fails because most carcinomas have few T cells, suggesting that cancers can suppress T cell infiltration. Here, we show that cancer cells of human pancreatic ductal adenocarcinoma (PDA), colorectal cancer, and breast cancer are coated with transglutaminase-2 (TGM2)-dependent covalent CXCL12-keratin-19 (KRT19) heterodimers that are organized as filamentous networks. Since a dimeric form of CXCL12 suppresses the motility of human T cells, we determined whether this polymeric CXCL12-KRT19 coating mediated T cell exclusion. Mouse tumors containing control PDA cells exhibited the CXCL12-KRT19 coating, excluded T cells, and did not respond to treatment with anti-PD-1 antibody. Tumors containing PDA cells not expressing either KRT19 or TGM2 lacked the CXCL12-KRT19 coating, were infiltrated with activated CD8+ T cells, and growth was suppressed with anti-PD-1 antibody treatment. Thus, carcinomas assemble a CXCL12-KRT19 coating to evade cancer immune attack. [ABSTRACT FROM AUTHOR]

Background: This study elucidated the regulatory roles of milk glycoprotein core fucosylation on the gut microbiota of breast-fed infants. Objectives: In order to investigate the effects of core fucosylation of maternal milk N-glycan on the intestinal functions in newborn mice, Fut8+/+ → Fut8+/+ and Fut8± → Fut8+/+ models were established. Results: The results indicated that the gut microbiota diversity was altered and production of Bifidobacterium and Lactobacillus was reduced in the intestine of Fut8± → Fut8+/+mice. Furthermore, the levels of SCFAs were decreased in the gut of Fut8± → Fut8+/+infant. To further investigate the effects of core fucosylation of breast milk N-glycan on the intestinal inflammation in newborns, NEC models were established, and Fut8+/+ off-springs with experimentally induced NEC were fed with the breast milk of Fut8+/+ and Fut8± maternal mice. Our data revealed that reduced core fucosylation of breast milk N-glycan could be responsible for the intestinal inflammation in NEC offspring, as the production of pro-inflammatory cytokines including IL-1b, IL-6, IL-17A and TNF-a was significantly upregulated in Fut8± → Fut8+/+NEC group, while the levels of anti-inflammatory cytokine IL-10 were remarkably reduced. Furthermore, Treg/Th17 balance in the intestine was disturbed in Fut8± → Fut8+/+NEC newborn, suggesting the impaired immune development caused by reduced core fucosylation of breast milk. Conclusion: These findings indicated that core fucosylation of maternal milk N-glycan could assist the colonization of gut Lactobacillus and Bifidobacterium and regulate the Treg/Th17 balance, subsequently preventing intestinal inflammation in breast-fed newborns. [ABSTRACT FROM AUTHOR]

In order to enhance quality and reliability of mechanical and electrical products, the methods of taking corresponding corrective measures to eliminate or alleviate product failure in advance have been widely concerned. Failure mode and effects analysis (FMEA) is a typical prevention reliability analysis method. However, there are some drawbacks in traditional FMEA method. To overcome these drawbacks, we propose a hybrid risk evaluation method, which combines picture fuzzy sets (PFSs), the PF-linear programming model (PF-LPM) method and the PF-weighted aggregated sum product assessment (PF-WASPAS) method. We adopt PFSs to evaluate risks of products. In order to overcome drawback of the traditional distance between PFSs, some new distance measures between PFSs based on the Dice similarity and the Jaccard similarity are proposed by us. The PF-LPM method which considers the subjective weights of risk factors and calculates synthetical deviation with the Dice similarity-based distance is utilized to calculate the weights of risk factors. Moreover, the PFWA operator and the PFWG operator are used by us to fuse experts' evaluation information. Then, the PF-WASPAS method is utilized to rank failure modes. Finally, an illustrative example with respect to pallet exchange rack is introduced, and the rationality, effectiveness and applicability of the proposed method are verified by a discussion and comparison. [ABSTRACT FROM AUTHOR]

Failure mode and effects analysis is a widely applied risk assessment method in various engineering and management domains. However, the identification of failure modes is difficult and uncountable. Therefore, a function–motion–action (FMA) decomposition method is developed to identify failure modes from the perspective of motion and extraordinarily suitable for mechatronic products. In the typical risk assessment, the ranking orders of failure modes are determined by risk priority number (RPN), which has been criticized for several drawbacks and improved by some alternative RPNs, but some drawbacks still exist, such as duplicate values, narrow admissible value range, and missing failure modes' and risk factors' weights. This study formulates several alternative weighted RPNs to overcome the above drawbacks, and the final ranking orders of failure modes are garnered through the integrated RPN (IRPN). First, failure modes are identified via the proposed FMA decomposition method and evaluated with crisp values, whose weights are aggregated from the basic failure modes' weights. Second, the weights of the basic failure modes, risk factors and different RPN methods are derived from analytic hierarchy process. Third, the conditional weights of risk factors are determined by incorporating risk factors' weights and failure modes' conditional weights deduced from Shannon entropy. Next, several alternative weighted RPNs and IRPN are formulated to rank failure modes' risk levels. Finally, an illustrative example about computer numerical control machine center is presented to demonstrate the application and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In order to improve the lifetime and reliability of equipment operation stage, it is necessary to carry out maintenance for components. The typical selective maintenance model does not consider the maintenance quality uncertainty and the failure effects, which may make the decision-maker overestimates the reliability of completing the next task after system maintenance, resulting in incorrect maintenance decision and prone to serious consequences of failure. In this paper, the potential discrepancy between the target maintenance quality and the actual maintenance quality of the decision maker is considered. At the same time, a multi-state FMECA is proposed to measure the failure effects under different states. Finally, the selective maintenance model of the multi-state series systems is established and solved by the genetic algorithm. The results show that considering the effect of component failure and the uncertainty of maintenance quality has an influence on maintenance decision. The maintenance decision made in this way is more consistent with the engineering practice. [ABSTRACT FROM AUTHOR]

Due to the poor conductivity of Fe based, Cu based and Co based electrode materials commonly used in the electrochemical detection of glucose, and the uneven stirring and poor conductivity of the traditional preparation method based on glassy carbon electrode. In order to solve the above problems, in this work, CdIn2O4 with high electrical conductivity was directly grown on three-dimensional (3D) Ni foam to prepare electrode materials for non-enzymatic glucose sensors. CdIn2O4 nanoparticles is prepared from cadmium acetate and indium nitrate hydrate in benzyl alcohol by non-aqueous sol–gel method. The electrocatalytic oxidation performances of CdIn2O4 electrode material for non-enzymatic glucose are studied. The results show that the proposed CdIn2O4 electrode material has good electrochemical properties and sensing performance for glucose detection. The electrochemical response of CdIn2O4 electrode material to glucose is recorded that calibration plot for glucose concentrations ranging from 1.0 μM to 1.0 mM (R2 = 0.99), a limit detection of 0.08 μM, an excellent sensitivity of 3.2925 mA.mM−1.cm−2, a rapid response time of 1.58 s, a good selectivity and a good long-term stability. These demonstrate the significant potential of CdIn2O4 electrode material based on 3D Ni foam as non-enzymatic glucose sensors, which makes it possible to use it as a practical glucose detector. This work could introduce a new concept of nanoparticles modified electrode material grown directly on 3D Ni foam, thus a simple and reliable electrochemical glucose sensor platform is realized. This study was completed in 2019 in the school of materials and energy, Yunnan University. [ABSTRACT FROM AUTHOR]

A reliability allocation method for mechanical transmission systems was proposed to quantify the uncertainty, aimed at the uncertainty in the reliability allocation of mechanical transmission systems. The minimum granularity of reliability allocation (i.e. meta-action) in transmission systems was extracted by the decomposition method of "function-motion-action (FMA)". A method for calculating the sensitivity of the transmission systems was proposed based on the Sobol' of LRA according to the reliability mathematical model of meta-action, which quantified the reliability sensitivity of meta-actions in the transmission systems, and the key meta-actions that affected the reliability of transmission systems were identified. The mapping relationship between the meta-action and the system reliability was established, and the mapping results were solved. The application results show that the method has high calculation accuracy and provides guidance for the reliability allocation of mechanical transmission systems. [ABSTRACT FROM AUTHOR]

Effectively and quantificationally detecting hazardous gas n-butanol is very significant in daily life, which can bring about a safe living condition for humans. In this study, the one-dimensional In2O3 nanorods were successfully synthesized via hydrothermal route and post-heat treatment. Noticeably, one-dimensional nanorods structures were obtained and the products presented a superior growth orientation along with (222) plane. Additionally, systematical gas-sensing measurements of the sensor made from In2O3 nanorods towards hazardous n-butanol gas were conducted. Results exhibited that the fabricated sensor showed excellent n-butanol sensing properties, with aspects to a superior response value of 342.20 with concentration 100 ppm at 240 °C, remarkable selectivity, fast response/recovery times (77.5/34.2 s) and good stability. More interestingly, the detection limit of sensor as low as 500 ppb and a good linearity relationship between response values and n-butanol concentrations was presented. Gas-sensitive properties of this sensor are better than previously reported in n-butanol detection. All results demonstrate that one-dimensional In2O3 nanorod is a promising sensor material to practical applications in effectively detecting n-butanol gas. [ABSTRACT FROM AUTHOR]

Background: The vacuole/lysosome is the final destination of autophagic pathways, but can also itself be degraded in whole or in part by selective macroautophagic or microautophagic processes. Diverse molecular mechanisms are involved in these processes, the characterization of which has lagged behind those of ATG-dependent macroautophagy and ESCRT-dependent endosomal multivesicular body pathways. Results: Here we show that as yeast cells gradually exhaust available nutrients and approach stationary phase, multiple vacuolar integral membrane proteins with unrelated functions are degraded in the vacuolar lumen. This degradation depends on the ESCRT machinery, but does not strictly require ubiquitination of cargos or trafficking of cargos out of the vacuole. It is also temporally and mechanistically distinct from NPC-dependent microlipophagy. The turnover is facilitated by Atg8, an exception among autophagy proteins, and an Atg8-interacting vacuolar membrane protein, Hfl1. Lack of Atg8 or Hfl1 led to the accumulation of enlarged lumenal membrane structures in the vacuole. We further show that a key function of Hfl1 is the membrane recruitment of Atg8. In the presence of Hfl1, lipidation of Atg8 is not required for efficient cargo turnover. The need for Hfl1 can be partially bypassed by blocking Atg8 delipidation. Conclusions: Our data reveal a vacuolar membrane protein degradation process with a unique dependence on vacuole-associated Atg8 downstream of ESCRTs, and we identify a specific role of Hfl1, a protein conserved from yeast to plants and animals, in membrane targeting of Atg8. [ABSTRACT FROM AUTHOR]

Traditional machine tool reliability modeling methods take static parts as the research object, ignoring the characteristic that the function and performance of computer numerical control (CNC) machine tool are ultimately driven by its most basic actions, and the traditional reliability modeling methods do not fully consider the randomness of machine tool failure. In view of this, this paper gave an improved four‐parameter nonhomogeneous Poisson process reliability modeling method based on meta‐action (MA), and a comprehensive method of system reliability was presented. A CNC machine tool made in China was taken as an example, and the reliability model of MA and the whole machine were built by the proposed method. The proposed method was compared with other methods by Akaike information criterion and Bayesian information criterion, and the method proposed in this paper was proved to be better. The reliability indexes of the system were simulated, and then the general trend of system reliability indexes was obtained by least squares support vector machines. The results verify the applicability and validity of this method, and lay a foundation for further research on the machine tool reliability based on metamotion. [ABSTRACT FROM AUTHOR]

Objective: To investigate the inhibition effect of dexamethasone with different concentration gradients on the expression of MMP-1, -3, and -13 in a bone joint cell model of IL-1β-induced SW1353 cells. Methods: The SW1353 cells were placed in a culture medium containing 10¹-108 nmol/L dexamethasone, and after 12 hours of culture, the appropriate intervention concentration range of dexamethasone was screened by the MTS for subsequent experiments. After SW1353 cells were induced with 10 ng/mL IL-1β, 101-107 nmol/L dexamethasone was given for intervention, and RT-PCR was used to detect the mRNA expression of MMP-1, -3, and -13. The protein was extracted after the intervention of 104 nmol/L dexamethasone, and western blot was used to detect the protein expression of MMP-1, -3, and -13. Results: MTS proliferation experiment results showed that 101-107 nmol/L dexamethasone had no significant effect on SW1353 cell viability, while 108 nmol/L dexamethasone had a significant inhibitory effect on SW1353 (p <0.05). There was no obvious effect on cell viability after adding 10 ng/mL IL-1β. RT-PCR results indicated that the IL-1β group had a significant increase in the mRNA expression of MMP-1, -3, and -13 compared with the blank control group, and the difference was statistically significant (p <0.05). After intervention with 10²-107 nmol/L dexamethasone, MMP-1 mRNA expression decreased (p <0.05); after intervention with 103107 nmol/L dexamethasone, MMP-3 mRNA expression decreased (p < 0.05); after intervention with 10-107 nmol/L dexamethasone, the mRNA expression of MMP-13 decreased (p <0.05). The Western blot results showed that compared with the blank control group, the protein levels of MMP-1, -3, and -13 in the IL-1β group were significantly increased; the protein levels of MMP-1, -3, and -13 were significantly reduced after the intervention of 104 nmol/L dexamethasone. Conclusion: Dexamethasone can inhibit the expression of MMP1, MMP-3, and MMP-13 in the IL-1β-induced OA cell model at the mRNA and protein levels. [ABSTRACT FROM AUTHOR]

Formaldehyde (HCHO) is a colorless and irritating volatile organic compound, which has been proven to be one of the raw materials that cause pathological building syndrome, as well as a major source of indoor environmental pollution. Long-term exposure of human body to formaldehyde will cause certain health risks, so it is of great practical significance to develop a fast and effective formaldehyde detection sensor. Tin dioxide (SnO2), an n-type semiconductor metal oxide with a specific bandgap (3.62 eV, at 300 K), has been widely used as efficient sensors material for hazardous gases detecting. Different ratios of Sm-doped SnO2 nanoparticles had been successfully prepared by a simple solvothermal route and used as sensing materials in this work. The sample structure, micromorphology, and ingredient were characterized by XRD, SEM, TEM, XPS, and other methods of formaldehyde gas-sensing characteristics were studied. The results shown the optimum compound ratio of Sm-doped SnO2 nanoparticles was 5.0 mol%, the optimal operating temperature was 160 °C, and the sensor shown high gas response, reliable stability and selectivity to formaldehyde. The sensor shown the outstanding gas-sensing performances to formaldehyde ascribed the average grain size of the Sm-doped SnO2 nanoparticles and the positive role of Sm. Besides, the possible gas-sensing mechanism of the prepared sensor to formaldehyde was analyzed in detail. [ABSTRACT FROM AUTHOR]

Scenic vistas of Quanzhou are displayed in a 720° perspective as an immersive live 3D display to provide a real digitalized virtual reality experience. In this paper, we report our research on simulating and exploring the extensive scenery of the Quanzhou Maritime Silk Route to support cultural tourism. Users can access the "Maritime Silk Route" applet on their mobile phone by approaching a sensor or scanning a QR code. [ABSTRACT FROM AUTHOR]

Due to the existence of coupling relationships, quality characteristics form a variation propagation process, which increases the risk possibility of product quality. In order to improve the robustness of quality characteristics, this paper proposes a fuzzy clustering-based key quality characteristics decoupling planning considering risk criticality. Firstly, based on the design structure matrix, a modular correlation matrix of key quality characteristics was established to quantify the coupling relationships among them. Secondly, according to the variation characteristics of quality characteristics, the variation propagation model is constructed to identify the potential quality risk. Thirdly, the fuzzy clustering algorithm is used to obtain the optimal control sequence of key quality characteristics. Finally, the computerized numerical control machine tool is taken as an actual case, the effectiveness and superiority of this method are verified by the comparison of the numerical result and method. This method provides a new indicator system solution for the coupling analysis of product design. [ABSTRACT FROM AUTHOR]

Frequent early failures are the key factors restricting the reliability improvement of CNC (computer numerical control) machine tools. In order to eliminate the early failures of CNC machine tools as much as possible, this paper defined the early failures of CNC machine tools strictly and divided the early failures into sudden early failures and progressive early failures. According to the characteristics of sudden early failures, the corresponding reliability analysis model was established by fishbone diagram and 5M1E (man, machine, material, method, measurement, environment) method. Based on the failure time rather than failure time intervals, the reliability analysis model of progressive early failures, which can reflect the dynamic characteristics of CNC machine tool failures, was established by BBIP (bounded bathtub intensity process) method in NHPP (non-homogeneous Poisson process). The reliability evaluation indexes of progressive early failures were given, and the analysis method of the influence of the relationship between former failure and latter failure on the established reliability model was given. CNC machine tools made in China were taken as the example, and the reliability analysis models of sudden early failures and progressive early failures were established and analyzed, respectively. The conclusion that different product failures of the same model could not be analyzed by the same parameter model is obtained. The results also verify the applicability and correctness of the proposed method, which lay a foundation for the elimination of early failure and the improvement of reliability of machine tools. [ABSTRACT FROM AUTHOR]

This paper devotes to providing a dynamic reliability model for linear guideways for the whole life. Since a linear guide is always worn, the wear degradation of the linear guide is established. Moreover, the profile error of rail is considered. To get the dynamic behavior of linear guides precisely, we developed a dynamic stiffness model of the system in terms of different load conditions and operation time. The reliability model with variant stochastic parameters is proposed according to the contact characteristics of linear guides. The Monte Carlo method is adopted to solve the reliability of linear guides. The simulation results show the reliability curve agrees with the experimental results, as well as the engineering experience in practice. The proposed model can be well applied to the reliability prediction for linear guideways. [ABSTRACT FROM AUTHOR]

Assembly precision is an important index, because it can ensure the quality of mechanical products and the final basis, and determine the overall performance of the products. In the early design stage, the prediction of assembly precision of schemes is significant. Therefore, considering part processing error, we proposed a prediction method for assembly precision of mechanical transmission system. Based on meta-action theory and small displacement torsor (SDT) model, common geometric elements were analyzed under multi-tolerance coupling and the error transfer of joint-surface for meta-action unit. Thus, we established the error model of joint-surface and qualitatively determined the potential error's accumulative transmission paths of transmission system. We also quantitatively built the assembly precision prediction model of transmission system combining with the Jacobian-Torsor method, and calculated the precision reliability value. Finally, the effectiveness was verified by an example of NC machine tool's transmission system. The method provides a way of thinking about solving the precision prediction and reliability evaluation of mechanical transmission systems in the early design stage and a basis for the final assembly precision prediction, simulation and testing of mechanical products. [ABSTRACT FROM AUTHOR]

Here, we reported the rare case of primary pleural squamous cell carcinoma (PPSCC) in a 71-year-old male patient. After chemo and targeted therapies, the patient showed continuous tumor progression and clinical deterioration. Fortunately, the patient had a high expression level of PD-L1 (80%) in the tumor tissues. Ultimately, the patient survived for additional 6 months with camrelizumab treatment. In summary, camrelizumab may be a good candidate for the treatment of PPSCC, especially in tumors with high PD-L1 expression. [ABSTRACT FROM AUTHOR]

In a semiconductor hetero-junction, the stripe/line-shaped scatters located at the hetero-interface lead to the anisotropic transport of two-dimensional electron gas (2DEG). The elastic scattering of infinitely long and uniform stripe/line-shaped scatters to 2DEG is theoretically investigated based on a general theory of anisotropic 2DEG transport [J. Schliemann and D. Loss, Phys. Rev. B 68 (16), 165311 (2003)], and the resulting 2DEG mobility along the applied electrical field is modeled to be a function of the angle between the field and the scatters. The anisotropy of the scattering and the mobility originate in essence from that the stripe/line-shaped scatters act upon the injecting two-dimensional wave vector by changing only its component perpendicular to the scatters. Three related scattering mechanisms in a nonpolar AlGaN/GaN hetero-junction are discussed as illustrations, including the striated morphology caused interface roughness scattering, and the polarization induced line charge dipole scattering and the misfit dislocation scattering at the AlGaN/GaN interface. Different anisotropic behaviors of the mobility limited by these scattering mechanisms are demonstrated, but analysis shows that all of them are determined by the combined effects of the anisotropic bare scattering potential and the anisotropic dielectric response of the 2DEG. [ABSTRACT FROM AUTHOR]

This paper presents a dynamic reliability analysis method of rolling linear guide considering the uncertainty of geometric parameters. A three degree of freedom (DOF) dynamic motion model of rolling linear guide that considers the complexity of the actual load is established. In order to improve the accuracy of reliability evaluation, interval model is used to express the uncertainty of geometric parameters. The reliability range of dynamic response is determined according to the accuracy grade of rolling linear guide. The interval reliability calculation method is used to analyze and calculate the horizontal and vertical dynamic reliability of rolling linear guide. Then, the comprehensive dynamic reliability of rolling linear guide is obtained. Finally, the dynamic reliability of the SHS-45R rolling linear guide is analyzed by using the reliability evaluation method described in this paper. And the validity and accuracy of the result is demonstrated by comparing with the Monte Carlo simulation. [ABSTRACT FROM AUTHOR]

Much research has focused on residual stress detection, analysis and elimination for alloy materials. There is however limited work considering residual stress in gray cast iron materials (HT200, 250, 300, 350) which are commonly used in heavy machine tool components. Herein an experimental program is undertaken to quantify the influence of typical machine tool production processes (casting, treatments, machining) on component residual stress. In addition, for a select component element (a guideway mounting surface), an extended measurement program tracks residual stress and surface deviations over a two-year period, quantifying the time-dependent behavior of production-induced stresses during initial in-service conditions. The experimental program establishes the relationship between material carbon content and component residual stress, with greater carbon content resulting in less residual stress. For the aging treatments (heating, vibration, natural aging), the program quantifies and ranks the achievable stress reductions (68.74%, 36.83%, 29.1%, respectively). Finally, the extended measurement program demonstrates that within 2 months of production, greater than 99% of process-induced residual stress has been released and surface deviation is less than 0.5 μm per month. [ABSTRACT FROM AUTHOR]