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The sliding mode observer (SMO)–based sensorless control is essentially a discontinuous switching control algorithm. Therefore, there is large speed or torque chattering in the permanent magnet synchronous motor (PMSM) with existing sliding mode observer–based control methods. In order to solve this problem well, an algorithm based on an improved sliding mode observer is proposed. In detail, the piecewise power function approach is used to replace the traditional ones, that is, the sgn function or the sigmoid function approach. Simulation verifications are conducted to validate the effectiveness of the proposed observer. It shows that the piecewise power function–based sliding mode observer algorithm has obvious advantages in the stability of the three-phase current, namely, it improves the estimation accuracy of the rotor position, rotor speed, and dynamic response to various loads. For further verification, the proposed sliding mode observer algorithm is implemented and verified in a marine electric propulsion motor with a DSP chip of TMS320F28377D. Experimental results validate that the piecewise power function–based sliding mode observer algorithm has high control accuracy and fewer fluctuations, which are all vital in marine engineering.

Abstract Backgroundː Stroke, primarily resulting from ischemic conditions, is the foremost cause of mortality and long-term impairment and is frequently associated with narrowing of the carotid arteries. Although carotid endarterectomy (CEA) is the treatment of choice, it carries the risk of cerebral ischemia and reduced blood flow. Transcranial Doppler (TCD) ultrasound offers a nonintrusive method to assess cerebral blood circulation during CEA, potentially enhancing surgical outcomes. The objective of this study was to assess the clinical utility and safety of TCD monitoring during CEA and to identify factors influencing postoperative complications. Methods This retrospective analysis included 158 CEA patients (from January 2021–August 2023) who underwent TCD monitoring and whose data were compared to historical standard care data. The primary outcomes were operation duration and artery occlusion time. Secondary outcomes included carotid shunt usage, seven-day postoperative complications, and six-month carotid artery patency. Logistic regression identified factors linked to adverse reactions, and a predictive model was evaluated with a receiver operating characteristic (ROC) curve. Resultsː Comparative analysis indicated significant reductions in both the duration of surgery (113.26 ± 7.29 min) and artery occlusion time (21.85 ± 2.92 min) for patients monitored with TCD (P

The systemic benefits of anti-inflammatory pharmacotherapy vary across cardiovascular diseases in clinical practice. We aimed to evaluate the application of artificial intelligence to acute type A aortic dissection (ATAAD) patients to determine the optimal target population who would benefit from urinary trypsin inhibitor use (ulinastatin). Patient characteristics at admission in the Chinese multicenter 5A study database (2016–2022) were used to develop an inflammatory risk model to predict multiple organ dysfunction syndrome (MODS). The population (5,126 patients from 15 hospitals) was divided into a 60% sample for model derivation, with the remaining 40% used for model validation. Next, we trained an extreme gradient-boosting algorithm (XGBoost) to develop a parsimonious patient-level inflammatory risk model for predicting MODS. Finally, a top-six-feature tool consisting of estimated glomerular filtration rate, leukocyte count, platelet count, De Ritis ratio, hemoglobin, and albumin was built and showed adequate predictive performance regarding its discrimination, calibration, and clinical utility in derivation and validation cohorts. By individual risk probability and treatment effect, our analysis identified individuals with differential benefit from ulinastatin use (risk ratio [RR] for MODS of RR 0.802 [95% confidence interval (CI) 0.656, 0.981] for the predicted risk of 23.5%–41.6%; RR 1.196 [0.698–2.049] for the predicted risk of 41.6%). By using artificial intelligence to define an individual’s benefit based on the risk probability and treatment effect prediction, we found that individual differences in risk probability likely have important effects on ulinastatin treatment and outcome, which highlights the need for individualizing the selection of optimal anti-inflammatory treatment goals for ATAAD patients.

Abstract Objective The study objective was to investigate the use of peripheral blood biomarkers as predictors of patient survival. The aim of this study was to identify the baseline peripheral blood biomarkers associated with clinical outcome in patients with early lung cancer (stage I-II) treated with surgery. Methods We included and analysed data from 376 patients with early-stage lung cancer who underwent a standard lobectomy. Univariate and multivariate Cox regression analyses were performed on all patients to assess the relationships between progression-free survival (PFS) and overall survival (OS) and the peripheral blood biomarker metrics measured before surgical treatment. The peripheral blood parameters included monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and dimeric fibrin fragment D (D-dimer). Results After univariate Cox regression analysis, low MLR, low NLR, low PLR and low D-dimer values were significantly associated with both better OS and PFS (all p

Monogalactosyldiacylglycerol (MGDG) is the most abundant polar lipid in thylakoid membrane, wherein it plays critical roles related to thylakoid membrane assembly and function in diatoms. However, diatom MGDG biosynthesis has not been fully characterized. In this study, we investigated the role of a novel MGDG synthase (ptMGD2), which is one of the key enzymes for MGDG biosynthesis, in the model diatom Phaeodactylum tricornutum. An analysis of subcellular localization demonstrated that the ptMGD2 is mainly localized in plastids. Gene disruption by gene editing of ptMGD2 resulted in delayed growth, decrease in oxygen evolution rate, reduced MGDG and digalactosyldiacylglycerol (using MGDG as the substrate) content as well as lipid remodeling. Considered together, these observations provide novel insights into the importance of ptMGD2 for regulating MGDG biosynthesis and its potential roles in biotechnical application of Phaeodactylum.

This paper reveals the coupling mechanism of government support, financial support, and innovation. Using panel data from 28 provinces in China from 2007 to 2016 as a research sample, the coupling coordination degree model is used to measure the coupling coordination degree of government support, financial support, and innovation, and the empirical analysis of its relationship with economic development is conducted through projection pursuit model, static panel data model and dynamic panel data model. The main results show that: (1) The coupling coordination degree of government support, financial support, and innovation in the eastern, central, and western region is on the rise, but there are large differences between regions. (2) The coupling coordination degree of government support, financial support, and innovation has a significant positive impact on economic development, and there are regional differences in its role in promoting economic development. That is, the coupling coordination degree of government support, financial support, and innovation has significantly promoted the economic development of the eastern region, but has no significant impact on the economic development of the central and western region.

BackgroundGlobally, esophageal cancer ranks as the seventh most common cancer. Esophageal squamous cell carcinoma (ESCC) is one of its major histological types. ESCC accounts for the vast majority of cases in China, and the mortality rate is high. Cisplatin, the standard adjuvant chemotherapy drug for ESCC, has a modest response rate due to the development of drug resistance. Hinokiflavone (HF) is a natural biflavonoid compound with anti-melanoma activity. However, its anti-tumor effect on ESCC and the underlying mechanisms remain largely unknown.MethodsThe ESCC cell lines KYSE150 and TE14 were used. The cell counting kit-8 assay and flow cytometry analysis, along with colony formation, EdU, wound healing, and Transwell migration assays, were performed to assess cell characteristics (viability, migration, invasion, and apoptosis) following treatment with HF. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), western blotting, and molecular docking were used to investigate the pathways potentially modulated by HF. In vivo anti-tumor effects of HF were also investigated using a mouse xenograft model.ResultsOur findings revealed that HF inhibited ESCC cell proliferation. Hoechst 33342 staining, annexin V-FITC/PI staining, and western blotting confirmed that HF causes caspase-dependent apoptosis. KEGG pathway enrichment analysis and western blotting indicated that the PI3K/AKT/mTOR pathway played an important role in the process of HF-induced apoptosis. Furthermore, HF effectively impaired the migration and invasion abilities of KYSE150 cells and downregulated the expression of the matrix metalloproteinases (MMP) MMP2 and MMP9. HF inhibited tumor growth and exhibited minimal toxicity in the organs of the KYSE150 xenograft model.ConclusionThis is the first study to demonstrate the inhibition of ESCC growth and progression by HF. The underlying mechanism is through blocking the PI3K/AKT/mTOR signaling pathway, thereby inhibiting cell proliferation and inducing apoptosis. HF can be used as a complementary/alternative agent for ESCC therapy.

Background and Aims: Clinical studies have reported positive results with omega-3 supplements in patients with cancer. This study aimed to evaluate the efficacy of omega-3 fatty acid supplementation in improving the nutritional status and inflammatory markers of patients with lung cancer.Methods: In a randomized, double-blind, parallel design trial, 60 patients with lung cancer at nutritional status/risk based on the Nutrition Risk Screening 2002 were randomized to be allocated to two study groups, receiving omega-3 fatty acid supplements [eicosapentaenoic acid (EPA) 1.6 g and docosahexaenoic acid (DHA) 0.8 g] or placebo for 12 weeks. Anthropometric measurements [weight, body mass index (BMI), the circumference of the upper arm, and skinfold thickness of triceps], nutrition-based laboratory indices (hemoglobin, albumin, triglyceride, and cholesterol), and inflammatory markers [C-reactive protein (CRP), tumor necrosis factor alpha (TNF-α), and interleukin 6 (IL-6)] were measured before and after the intervention as study outcomes.Results: No significant difference between the two study groups was observed regarding basic characteristics and study outcomes. Compared with placebo group, omega-3 fatty acid supplementation group showed significant higher weight (66.71 ± 9.17 vs. 61.33 ± 8.03, p = 0.021), albumin (4.74 ± 0.80 vs. 4.21 ± 0.77, p = 0.013), and triglyceride (130.90 ± 25.17 vs. 119.07 ± 14.44, p = 0.032). Inflammatory markers were significantly reduced in omega-3 group compared to placebo (CRP 1.42 ± 0.63 vs. 3.00 ± 1.05, p = 0.001 and TNF-α 1.92 ± 0.65 vs. 4.24 ± 1.19, p = 0.001). No significant difference was observed between the two study groups regarding changes in BMI, the circumference of the upper arm, skinfold thickness of triceps, triglyceride, cholesterol, and IL-6 (p > 0.05).Conclusions: Omega-3 fatty acid supplementation can improve nutritional status and suppress the systemic inflammatory response in patients with lung cancer.Clinical Trial Registration:www.socialscienceregistry.org, identifier: AEARCTR-0007165.

BackgroundThe hepatic metastasis pattern of esophageal cancer (EC) has not been fully explored. The primary objective of this study was to explore the predictors of esophageal cancer with hepatic metastasis (ECHM) at the time of diagnosis. In addition, we also analyzed the factors affecting ECHM prognosis.MethodsWe used the Surveillance, Epidemiology and End Result (SEER) database to identify ECHM patients at the time of initial diagnosis. The ECHM predictors were identified using multivariate logistic regression. Multivariate Cox regression and competing survival risk analyses were performed to identify factors associated with all-cause mortality and EC-specific mortality of ECHM, respectively.ResultsA total of 10,965 eligible EC patients were identified in the SEER database between 2010 and 2016, of which 1,197 were ECHM patients, accounting for 10.9% of the entire cohort. In the whole cohort, eight ECHM predictors (age, primary site, grade, histology type, T staging, N staging, insurance status, and number of extrahepatic metastatic sites) were determined using multivariate logistic regression analysis. Multivariate Cox regression and multivariate competing survival risks models confirmed that the male sex, advanced age, squamous cancer, and multiple extrahepatic metastasis increased the risk of both all-cause and EC-specific mortality, whereas chemotherapy and chemotherapy plus radiotherapy significantly reduced the risk of both.ConclusionsThis study explored population-level predictors of hepatic metastasis at the time of EC diagnosis and analyzed the clinical characteristics affecting the prognosis in ECHM patients. These findings may provide clinicians with a reference for the screening and treatment of hepatic metastasis in EC.

BackgroundEsophageal cancer is one of the most common cancer types, with its most common distant metastatic site being the lung. Currently, population-based data regarding the proportion and prognosis of patients with esophageal cancer with lung metastases (ECLM) at the time of diagnosis is insufficient. Therefore, we aimed to determine the proportion of patients with ECLM at diagnosis, as well as to investigate the prognostic parameters of ECLM.MethodsThis population-based observational study obtained data from the Surveillance, Epidemiology, and End Results (SEER) database registered between 2010 and 2016. Multivariable logistic regression was performed to identify predictors of the presence of ECLM at diagnosis. Multivariable Cox regression and competing risk analysis were used to assess prognostic factors in patients with ECLM. Median survival was estimated using Kaplan–Meier curves.ResultsOf 10,965 patients diagnosed with esophageal cancer between 2010 and 2016, 713 (6.50%) presented with initial lung metastasis at diagnosis. Lung metastasis represented 27.15% of all cases with metastatic disease to any distant site. Considering all patients with esophageal cancer, multivariable logistic regression indicated that pathology grade, pathology type, T staging, N staging, race, and number of extrapulmonary metastatic sites were predictive factors for the occurrence of lung metastases at diagnosis. The median survival time of patients with ECLM was 4.0 months. Patients receiving chemotherapy or chemoradiotherapy had the longest median overall survival, 7.0 months. Multivariable Cox regression indicated that age, histology type, T2 staging, number of extrapulmonary metastatic sites, and treatment (chemotherapy, radiotherapy, or chemoradiotherapy) were independent predictors for overall survival (OS). Multivariable competing risk analysis determined that age, number of extrapulmonary metastatic sites, and treatment were independent predictors for esophageal cancer-specific survival (CSS).ConclusionThe findings of this study may provide important information for the early diagnosis of ECLM, as well as aid physicians in choosing appropriate treatment regimens for these patients.

Abstract In this paper, we propose a new nonlinear stochastic SIRS epidemic model with standard incidence rate and saturated treatment function. The main purpose of this paper is to investigate the threshold dynamics of the nonlinear stochastic SIRS epidemic model by making use of stochastic inequality techniques. By using Lyapunov methods and Itô’s formula, we first prove the existence and uniqueness of a global positive solution for the corresponding limiting system. Furthermore, we obtain sufficient conditions for the extinction and persistence in mean of the nonlinear stochastic SIRS epidemic model by using the techniques of a series of stochastic inequalities. Finally, we provide some numerical simulations to illustrate the performance of our theoretical findings.

Abstract: “Non-Archie” phenomena are common in tight sandstone reservoirs with complicated pore structure, bringing challenges to the logging evaluation of tight sandstone. Based on the characteristics of tight sandstone pore structure, a new trapezoidal pore saturation model considering the effect of pore structure on rock conductivity is presented, in which the pore in tight sand is divided into straight pore with constant cross-sectional area and trapezoidal pore with variable cross-sectional area, and the total rock resistance is taken as the parallel resistance of these two parts to compressively consider the influence of pore structure and conductive volume on rock conductivity. The model parameters are studied by reconstructing the trapezoidal pore structure. Based on the trapezoidal pore reconstruction, characterization methods of model parameters were studied under the constraint of rock electrical properties test, and the variation was revealed of tortuosity, straight pore proportion and trapezoidal factors. The model was used in logging evaluation of tight sandstone of several wells, the results show the oil saturation obtained from the new model considering the effect of pore structure on electrical properties from the aspects of pore length and pore cross-section is in good accordance with the real regularity and petrophysical characteristics of the reservoir, and much closer to the formation oil-bearing conditions than that from the Archie model. Key words: Ordos Basin, Triassic Yanchang Formation, tight sandstone, pore structure, trapezoidal pore, saturation model

As a furan derivative from 5-hydroxymethylfurfural (HMF) or other biomass-based carbohydrates, 2,5-diformylfuran (DFF) is one of the most important platform molecules in the organic chemicals industry. Although it has many potential applications in the future, the production of DFF on a large scale is currently a challenge. As an alternative to the production of DFF from HMF, the target product DFF could be obtained from biomass-derived glucose with a complex catalytic system (AlCl3•6H2O/NaBr and a vanadium compound assisted with molecular oxygen) carried out in N,N-dimethylformamide (DMF). In this research, reactions were conducted in reactors with different capacities. The results showed that DFF yields based on glucose could reach 35 to 48% with almost complete transformation of glucose. This one-pot two-step reaction is characterized by the abundance and low cost of the starting materials and by the elimination of the separation and purification of HMF. This has great potential for applications in the future production of DFF on a large scale after further advancements and optimizations.

5-hydroxymethylfurfural (HMF) is an important bio-based platform chemical, and its aerobic selective oxidation to 2,5-diformylfuran (DFF) still remains a challenge. This work dealt with active manganese dioxide (AMD) and efficiently catalyzed HMF oxidation to DFF with a yield of ~73% at 393 K and 60 bar O2 in N,N-Dimethylformamide (DMF). Through analysis of liquid products and the catalyst characterization using X-ray diffraction (XRD), a scanning electron microscope (SEM), a transmission electron microscope (TEM), and an elemental analyzer, it can be seen that this AMD catalyst is a low-cost, efficient, and environmentally benign heterogeneous catalyst for the aerobic selective oxidation of HMF to DFF in a one-pot technique. These research results may provide guidance for the development of more efficient catalysts for the future industrial production of high-value added DFF.

The nanocomposite preparation procedure plays an important role in achieving a well-established heterostructured junction, and hence, an optimized photocatalytic activity. In this study, a series of g-C3N4/ZnO nanocomposites were prepared through two distinct procedures of a low-cost, environmentally-friendly, in-situ fabrication process, with urea and zinc acetate being the only precursor materials. The physicochemical properties of synthesized g-C3N4/ZnO composites were mainly characterized by XRD, UV⁻VIS diffuse reflectance spectroscopy (DRS), N2 adsorption-desorption, FTIR, TEM, and SEM. These nanocomposites’ photocatalytic properties were evaluated in methylene blue (MB) dye photodecomposition under UV and sunlight irradiation. Interestingly, compared with ZnO nanorods, g-C3N4/ZnO nanocomposites (x:1, obtained from urea and ZnO nanorods) exhibited weak photocatalytic activity likely due to a “shading effect„, while nanocomposites (x:1 CN, made from g-C3N4 and zinc acetate) showed enhanced photocatalytic activity that can be ascribed to the effective establishment of heterojunctions. A kinetics study showed that a maximum reaction rate constant of 0.1862 min-1 can be achieved under solar light illumination, which is two times higher than that of bare ZnO nanorods. The photocatalytic mechanism was revealed by determining reactive species through adding a series of scavengers. It suggested that reactive ●O2− and h+ radicals played a major role in promoting dye photodegradation.