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Low serum albumin levels increase coronary morbidity, mortality, and postoperative cardiovascular risk. Therefore, this study investigated the relationship between these levels and the length of hospital stay in patients undergoing percutaneous coronary intervention (PCI) for acute coronary syndrome. A total of 350 patients were divided into quartiles according to serum albumin levels. Univariate and multivariate analyses were performed to identify factors associated with the length of hospital stay. A non-linear regression analysis of serum albumin and length of hospital stay was also performed. The results of the multifactorial analysis revealed low serum albumin levels as an independent predictor of longer hospital stay, even in the fully adjusted model. In the segmented linear regression model, serum albumin level showed a U-shaped relationship with the length of hospital stay. In conclusion, low serum albumin level was an independent predictor of longer hospital stay in patients undergoing PCI for acute coronary syndrome, with shorter stays observed for increasing serum albumin levels. Low serum albumin can be used to identify patients who require longer hospitalization and may need additional nutritional support or interventions to improve their prognosis. [ABSTRACT FROM AUTHOR]

Forecasting China's carbon price accurately can encourage investors and manufacturing industries to take quantitative investments and emission reduction decisions effectively. The inspiration for this paper is developing an error-corrected carbon price forecasting model integrated fuzzy dispersion entropy and deep learning paradigm, named ICEEMDAN-FDE-VMD-PSO-LSTM-EC. Initially, the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) is used to primary decompose the original carbon price. Subsequently, the fuzzy dispersion entropy (FDE) is conducted to identify the high-complexity signals. Thirdly, the variational mode decomposition (VMD) and deep learning paradigm of particle swarm optimized long short-term memory (PSO-LSTM) models are employed to secondary decompose the high-complexity signals and perform out-of-sample forecasting. Finally, the error-corrected (EC) method is conducted to re-modify and strengthen the above-predicted accuracy. The results conclude that the forecasting performance of ICEEMDAN-type secondary decomposition models is significantly better than the primary decomposition models, the deep learning PSO-LSTM-type models have superiority in forecasting China carbon price, and the EC method for improving the forecasting accuracy has been proved. Noteworthy, the proposed model presents the best forecasting accuracy, with the forecasting errors RMSE, MAE, MAPE, and Pearson's correlation are 0.0877, 0.0407, 0.0009, and 0.9998, respectively. Especially, the long-term forecasting ability for 750 consecutive trading prices is outstanding. Those conclusions contribute to judging the carbon price characteristics and formulating market regulations. [ABSTRACT FROM AUTHOR]

This study investigates the effects of different lubrication conditions on drawing force and microcup formation during micro deep drawing (MDD). Results show that graphene lubricant, in combination with TiO2 nanolubricants, has the potential to reduce friction during MDD. The peak drawing force was reduced by 15.39% when both lubricants were used together, while the use of TiO2 nanolubricant and 10.0 mg/ml graphene lubricant reduced it by 6.03% and 14.52%, respectively. The study also reveals that lubricants reduce wrinkling during the formation of microcups by minimising energy consumption during the primary formation. However, the combination of TiO2 nanolubricant and graphene lubricant can cause inhomogeneous formation on the upper part of the blank, leading to more apparent wrinkling. Overall, the study highlights the potential of TiO2 nanolubricant and graphene lubricant in reducing friction and improving microcup formation during MDD. [ABSTRACT FROM AUTHOR]

Influenced by the global economy, politics, energy and other factors, the price of carbon market fluctuates sharply. It is of great practical significance to explore a suitable measurement method of extreme risk of carbon market. Considering that the return series of carbon market has the characteristics of leptokurtosis, fat tail, skewness and multifractal, and there maybe many extreme risk values in the carbon market, this paper introduces the Skewed-t distribution which can describe the characteristics of leptokurtosis, fat tail and skewness of return series into MSM model which can describe multifractal characteristic of return series to model volatility of carbon market. On the basis, based on the extreme value theory, this paper constructs Skewed-t-MSM-EVT model to measure extreme risk of carbon market. This paper chooses EUA market as the object to study extreme risk of carbon market, and draws the following conclusions: Skewed-t-MSM-EVT model has significantly higher prediction accuracy for carbon market's VaR than MSM-EVT models under other distributions (including normal distribution, t distribution, GED distribution); Skewed-t-MSM-EVT model is superior to traditional Skewed-t-FIGARCH-EVT and Skewed-t-GARCH-EVT models in predicting carbon market's VaR. This research has important practical significance for accurately grasping the risk of carbon market and promoting energy conservation and emission reduction. [ABSTRACT FROM AUTHOR]

The carbon market relies on market-oriented financial means to solve the problem of carbon emissions. An effective carbon pricing mechanism can improve market efficiency and better serve the implementation of carbon emission reduction. The limited attention of investors increases the uncertainty of carbon market volatility and is an important exogenous factor affecting the price of carbon assets. This study innovatively mines keywords of investor attention on the carbon market through online news texts and eliminates those that have no causal link to carbon price forecasting in order to reduce noise. The results show that the keyword extraction method based on news text mining is better than that of nontext mining. Meanwhile, a carbon price forecasting model based on a particle-swarm-optimization LSTM model structure is constructed, and the forecasting accuracy is improved. The results show that carbon market investors pay more attention to carbon quota supply and demand, carbon prices, environmental change, and the energy market. The results have important implications for the development of effective carbon market policies and risk management. [ABSTRACT FROM AUTHOR]

Intermediate roll shifting (IRS) is widely used for improving the strip shape in the six-high tandem cold mill, but most related studies are limited to a single stand. To fill the knowledge gap, a three-dimensional (3D) multi-stand elastic–plastic finite element (FE) model was developed for a continuously variable crown (CVC)-6 tandem cold mill using data transfer, which was then validated by industrial experimental results. Based on this FE model, the effects of the IRS on the strip crown, strip flatness, loaded roll gap profile and contact normal stress between rolls at each stand were quantitatively analysed. The results show that from Stand 1 (S1) to Stand 5 (S5), the regulation ability of the IRS on the strip crown shows a decreasing trend, which depends on the strip plastic rigidity; in contrast, the regulation ability on the quadratic flatness experiences an obvious increase from S1 to Stand 4 (S4), then a drop at S5, while the IRS exerts little effect on the quartic flatness and quartic crown of the loaded roll gap. Moreover, the most uniform distribution of contact normal stress emerges at different IRSs from S1 to S5. These findings can contribute to a better understanding of the role of the IRS in controlling the strip shape during tandem cold rolling (TCR). [ABSTRACT FROM AUTHOR]

Numerous studies have demonstrated a correlation between serum 25-hydroxyvitamin D (25OHD) and endometriosis. However, the precise nature of this association remains elusive. The causal connection between 25OHD and endometriosis remains uncertain, as it is yet to be determined whether one directly influences the other. The objective of our research was to investigate the cause-and-effect connection between 25OHD and endometriosis. The study employed Mendelian randomization (MR) in a bidirectional two-sample investigation to examine the causal relationship between 25OHD and endometriosis. The analysis utilized the most recent publicly accessible statistics from the genome-wide association study (GWAS) encompassing 25OHD, endometriosis, and its five subtypes. The primary analytical approach employed was Inverse-Variance Weighting (IVW), accompanied by supplementary analysis methods including weighted median, MR-Egger, simple mode, and weighted mode. Furthermore, sensitivity analyses were conducted to assess the potential influence of heterogeneity and pleiotropy on the MR outcomes. MR primary analysis showed no significant causal effect of 25OHD on endometriosis (OR = 0.892, 95%CI = 0.745 ~ 1.068, P = 0.213). Similarly, there was no evidence to support a causal relationship of endometriosis on 25OHD (IVW Beta = 0.005, 95%CI = 0.993 ~ 1.018, P = 0.406). However, when conducting MR analysis on different subtypes of endometriosis and 25OHD, we found a positive correlation between endometriosis of ovary and 25OHD level (IVW Beta = 0.012, 95%CI = 1.002 ~ 1.022, P = 0.024). This study indicates that there is no causal relationship between serum 25OHD and endometriosis. However, it is important to note that serum 25OHD levels will increase in patients with endometriosis of the ovary. Further observational studies and clinical trials are indispensable. [ABSTRACT FROM AUTHOR]

Ara h 1 is recognized as a major peanut allergen. The effects of high hydrostatic pressure (HHP) on the immunoreactivity and structure of Ara h 1 were investigated in this study. The immunoreactivity of Ara h 1 was considerably reduced (P < 0.01) after HHP treatment (≥ 400 MPa) with the increase of pressure holding time. The maximum reduction of 74.32% was achieved at 600 MPa for 1200 s. The particle size and molecular weight of Ara h 1 increased, and the secondary/tertiary structure changed markedly. The decrease of the immunoreactivity of Ara h 1 was mainly due to the changes in conformation (especially the tertiary structure) and the formation of new multimers, resulting in the inactivation of immunoreactive sites. Results indicate that HHP technology has the potential to be applied to the preparation of hypoallergenic peanut products. [ABSTRACT FROM AUTHOR]

The wear behavior of Ti–45Al–7Nb–0.3W (at%) alloy prepared by powder metallurgy (P/M) has been investigated using pin-on-disk wear tests at the room temperature. The dry sliding wear tests were performed against on a zirconia disk in different environments, viz, argon, hydrogen in nitrogen mixture, air and oxygen. The worn surfaces of Ti–45Al–7Nb–0.3W pins and wear debris were examined by scanning electron microscope, X-ray diffractometer and X-ray photoelectron spectroscopy. It was found that the high Nb containing Ti–45Al–7Nb–0.3W alloy didn't exhibit better wear resistance in the presence of oxygen than commercial γ-TiAl (Ti–47Al–2Nb–2Cr–0.2W) alloy. The oxidation on the worn surface and spalling of oxides caused by the mechanical force during sliding were the main reason for the high wear losses in the air and oxygen. The zirconia disk underwent a phase transformation caused by the high contact temperature and stress during the sliding tests. The abrasive particles produced in the wear tests largely consisted of the zirconia particles in different environments, except in the pure oxygen. The hard zirconia debris was embedded into the friction layer on the worn surfaces of TiAl pins, which provided protection against wear to some extent. The main wear mechanisms of Ti–45Al–7Nb–0.3W alloy were abrasive wear of two-body and three-body, some delamination and plastic deformation. [ABSTRACT FROM AUTHOR]

Purpose: Cancer cells alter regular metabolic pathways in order to sustain rapid proliferation. One example of metabolic remodeling in cancerous tissue is the upregulation of pyruvate kinase isoenzyme M2 (PKM2), which is involved in aerobic glycolysis. Indeed, PKM2 has previously been identified as a tumor biomarker and as a potential target for cancer therapy. Here, the role of PKM2 in the anticancer efficacy of 5-fluorouracil (5-FU) was evaluated in colorectal cancer (CRC).Methods: HCT116, SW480 and HT-29 cells were used by transfection with lentiviral vectors expressing short hairpin RNA (shRNA) against PKM2. In response to 5-FU treatment, cellular proliferation was examined, the levels of ATP/ADP ratio were monitored, the intracellular accumulation of 5-FU was measured, and intracellular levels of phosphoenolpyruvate (PEP), pyruvate and lactate were evaluated by using liquid chromatography-mass spectrometry (LC-MS). A CRC subcutaneous tumor model was performed to investigate the effect of PKM2 inhibition on 5-FU efficacy in vivo.Results: Suppression of PKM2 resulted in changes in glucose metabolism, leading to decreased synthesis of adenosine triphosphate (ATP). Reduced levels of ATP/ADP ratio resulted in the intracellular accumulation of 5-FU, consequently enhancing the therapeutic efficacy of this drug in several CRC cell lines. Furthermore, the enhanced efficacy of 5-FU by simultaneous inhibition of PKM2 was demonstrated in an in vivo HCT116 CRC model.Conclusion: We show that the combination treatment showed superior anticancer efficacy as compared to 5-FU alone. These findings suggest that targeting PKM2 can increase the efficacy of chemotherapy, potentially providing a new approach for improving the outcome of chemotherapy in patients with CRC. [ABSTRACT FROM AUTHOR]

To ensure running safety, the secondary spring loads of railway vehicles must be well equalized. Due to the coupling interactive effects of these hyper static suspended structures, the equalization adjustment through shimming procedure is quite complex. Therefore, an effective and reliable method in application is developed in this paper. Firstly, the best regulation of spring load is solved based on a mechanical model of the secondary suspension system, providing a target for actual adjustment. To reveal the relationship between secondary spring load distribution and shim quantity sequence, a forecasting model is constructed and then modified experimentally with consideration of car body’s elastic deformation. Further, a gradient-based algorithm with a momentum operation is proposed for the load optimization. Effectiveness of the whole method has been verified on a test rig. It is experimentally confirmed that this research provides an important basis for achieving an optimal regulation of spring load distribution for multiple types of railway vehicles. [ABSTRACT FROM AUTHOR]

Background and Aims: This study aimed to evaluate the antifibrotic effects of NF-E2-Related Factor 2 (Nrf2) on intestinal fibrosis. Intestinal fibrosis is a common complication of Crohn's disease; however, its mechanism of intestinal fibrosis is largely unclear.Methods: BALB/c mice received 2,4,6-trinitrobenzene sulfonic acid weekly via intrarectal injections to induce chronic fibrotic colitis. They also diet containing received 1% (w/w) tert-butylhydroquinone (tBHQ), which is an agonist of Nrf2. Human intestinal fibroblasts (CCD-18Co cells) were pretreated with tBHQ or si-Nrf2 followed by stimulation with transforming growth factor-β1 (TGF-β1), which transformed the cells into myofibroblasts. The main fibrosis markers such as α-smooth muscle actin, collagen I, tissue inhibitor of metalloproteinase-1, and TGF-β1/SMADs signaling pathway were detected by quantitative real-time RT-PCR, immunohistochemical analysis, and Western blot analysis. Levels of cellular reactive oxygen species (ROS) were detected by dichlorodihydrofluorescein diacetate.Results: tBHQ suppressed the intestinal fibrosis through the TGF-β1/SMADs signaling pathway in TNBS-induced colitis and CCD-18Co cells. Moreover, Nrf2 knockdown enhanced the TGF-β1-induced differentiation of CCD-18Co cells. ROS significantly increased in TGF-β1-stimulated CCD-18Co cells. Pretreatment with H2O2, the primary component of ROS, was demonstrated to block the effect of tBHQ on reducing the expression of TGF-β1. Moreover, scavenging ROS by N-acetyl cysteine could inhibit the increasing expression of TGF-β1 promoted by Nrf2 knockdown.Conclusions: The results suggested that Nrf2 suppressed intestinal fibrosis by inhibiting ROS/TGF-β1/SMADs pathway in vivo and in vitro. [ABSTRACT FROM AUTHOR]

Bismuth ferrite (BiFeO) acting as a significant multiferroic material exhibits unique magnetic and ferroelectric properties. Here we report the size-controlled synthesis of BiFeO nanoparticles via a facile and stable Pechini sol-gel method, in which uses tartaric acid as a complexing agent, ethylene glycol as a polymerizing agent. It is found that the nanoparticle size is sensitive to the gel-forming temperature. The nanoparticles with size as small as 30 nm have been obtained. A sequential reaction process and the mechanism of size controllable growth of BiFeO has been presented. The effects of size on optical and magnetic properties have been also investigated. The decreasing particles lead to blue shift in the band gap. BiFeO nanoparticles show weak ferromagnetic character due to a Fe oxidation state, and the magnetization increases with decrease in the particle size. [ABSTRACT FROM AUTHOR]

In order to control the locomotive wheel (axle) load distribution, a shimming process to adjust the locomotive secondary spring loads was heretofore developed. An immune dominance clonal selection multi-objective algorithm based on the artificial immune system was presented to further improve the performance of the optimization algorithm for locomotive secondary spring load adjustment, especially to solve the lack of control on the output shim quantity. The algorithm was designed into a two-level optimization structure according to the preferences of the problem, and the priori knowledge of the problem was used as the immune dominance. Experiments on various types of locomotives show that owing to the novel algorithm, the shim quantity is cut down by 30%-60% and the calculation time is about 90% less while the secondary spring load distribution is controlled on the same level as before. The application of this optimization algorithm can significantly improve the availability and efficiency of the secondary spring adjustment process. [ABSTRACT FROM AUTHOR]

According to the shearing force character and the deformation coordination condition of shell at the station of supports, the mathematical models to calculate contact angle and contact pressure distribution between tyre and shell were set up, the formulae of bending moment and bending stress of tyre were obtained. Taking the maximum of tyre fatigue life as the optimal objective, the optimization model of tyre support angle was built. The computational results show that when tyre support angle is 30°, tyre life is far less than that when tyre support angle is optimal, which is 35.6°, and it is unsuitable to stipulate tyre support angle to be 30° in traditional design. The larger the load, the less the nominal stress amplitude increment of tyre, the more favorable the tyre fatigue life when tyre support angle is optimal. [ABSTRACT FROM AUTHOR]