Left ventricular enlargement (LVE) is a common manifestation of cardiac remodeling that is closely associated with cardiac dysfunction, heart failure (HF), and arrhythmias. This study aimed to ...propose a machine learning (ML)-based strategy to identify LVE in HF patients by means of pulse wave signals. We constructed two high-quality pulse wave datasets comprising a non-LVE group and an LVE group based on the 264 HF patients. Fourier series calculations were employed to determine if significant frequency differences existed between the two datasets, thereby ensuring their validity. Then, the ML-based identification was undertaken by means of classification and regression models: a weighted random forest model was employed for binary classification of the datasets, and a densely connected convolutional network was utilized to directly estimate the left ventricular diastolic diameter index (LVDdI) through regression. Finally, the accuracy of the two models was validated by comparing their results with clinical measurements, using accuracy and the area under the receiver operating characteristic curve (AUC-ROC) to assess their capability for identifying LVE patients. The classification model exhibited superior performance with an accuracy of 0.91 and an AUC-ROC of 0.93. The regression model achieved an accuracy of 0.88 and an AUC-ROC of 0.89, indicating that both models can quickly and accurately identify LVE in HF patients. The proposed ML methods are verified to achieve effective classification and regression with good performance for identifying LVE in HF patients based on pulse wave signals. This study thus demonstrates the feasibility and potential of the ML-based strategy for clinical practice while offering an effective and robust tool for diagnosing and intervening ventricular remodeling.
Recent fruitful studies on rechargeable zinc-air battery have led to emergence of various bifunctional oxygen electrocatalysts, especially metal-based materials. However, their electrocatalytic ...configuration and evolution pathway during battery operation are rarely spotlighted. Herein, to depict the underlying behaviors, a concept named dynamic electrocatalyst is proposed. By selecting a bimetal nitride as representation, a current-driven "shell-bulk" configuration is visualized via time-resolved X-ray and electron spectroscopy analyses. A dynamic picture sketching the generation and maturation of nanoscale oxyhydroxide shell is presented, and periodic valence swings of performance-dominant element are observed. Upon maturation, zinc-air battery experiences a near two-fold enlargement in power density to 234 mW cm
, a gradual narrowing of voltage gap to 0.85 V at 30 mA cm
, followed by stable cycling for hundreds of hours. The revealed configuration can serve as the basis to construct future blueprints for metal-based electrocatalysts, and push zinc-air battery toward practical application.
The available training samples for hyperspectral image (HSI) are limited, which will lead to the failure to improve the classification accuracy. Aiming at increasing the number of available training ...samples, a superpixel pair (SSP) method is proposed to solve the problem of small samples. Combining the advantages of pixel pair (PP) and superpixel, the number of original training samples are augmented multiple times. The SSP method mainly includes three steps: first, according to the regional clustering-based spatial preprocessing (RCSPP) algorithm and its improved algorithms, superpixel segmentation is carried out to realize the first sample enlargement; second, the first expanded training samples are paired to form SSP; last, SVM and deep CNN are used to train and learn the SSP, and the testing pixels obtain the final result through the voting mechanism. Experimental results based on three HSI data sets demonstrate that the proposed method can achieve better classification performance than some existing algorithms to solve the problem of small samples and very small samples classification.
Supercritical water fluidized bed is a novel gasification reactor which can achieve efficient and clean utilization of coal. The rough surface of particle produced during grinding and thermochemical ...conversion processing will deeply affect supercritical water-particle two-phase flow and heat transfer characteristics. In this paper, fully resolved numerical simulation of supercritical water flow past single rough sphere particle with the Reynolds number ranging from 10 to 200 was carried out to investigate the effect of surface roughness. The simulation results show that as roughness increases, the separation bubbles generated in the dimple enhance the flow separation but has no significant effect on the drag coefficient. Particle surface-average Nusselt number decreases with an increase of roughness and surface enlargement coefficient due to the isolation effect at low Re and local separation bubbles in the dimple at high Re. Furthermore, the effect of surface enlargement coefficient on heat transfer efficiency factor for supercritical water near the critical point is greater than that under constant property condition and has a higher dependence on Re.
This study aimed to analyze the effect of resistance training (RT) performed until volitional failure with low, moderate, and high loads on muscle hypertrophy and muscle strength in healthy adults ...and to assess the possible participant-, design-, and training-related covariates that may affect the adaptations.
Using Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, MEDLINE, CINAHL, EMBASE, SPORTDiscus, and Web of Science databases were searched. Including only studies that performed sets to volitional failure, the effects of low- (>15 repetitions maximum (RM)), moderate- (9-15 RM), and high-load (≤8 RM) RTs were examined in healthy adults. Network meta-analysis was undertaken to calculate the standardized mean difference (SMD) between RT loads in overall and subgroup analyses involving studies deemed of high quality. Associations between participant-, design-, and training-related covariates with SMD were assessed by univariate and multivariate network meta-regression analyses.
Twenty-eight studies involving 747 healthy adults were included. Although no differences in muscle hypertrophy between RT loads were found in overall (P = 0.113-0.469) or subgroup analysis (P = 0.871-0.995), greater effects were observed in untrained participants (P = 0.033) and participants with some training background who undertook more RT sessions (P = 0.031-0.045). Muscle strength improvement was superior for both high-load and moderate-load compared with low-load RT in overall and subgroup analysis (SMD, 0.60-0.63 and 0.34-0.35, respectively; P < 0.001-0.003), with a nonsignificant but superior effect for high compared with moderate load (SMD, 0.26-0.28, P = 0.068).
Although muscle hypertrophy improvements seem to be load independent, increases in muscle strength are superior in high-load RT programs. Untrained participants exhibit greater muscle hypertrophy, whereas undertaking more RT sessions provides superior gains in those with previous training experience.
Developmental and environmental signals converge on cell cycle machinery to achieve proper and flexible organogenesis under changing environments. Studies on the plant cell cycle began 30 years ago, ...and accumulated research has revealed many links between internal and external factors and the cell cycle. In this review, we focus on how phytohormones and environmental signals regulate the cell cycle to enable plants to cope with a fluctuating environment. After introducing key cell cycle regulators, we first discuss how phytohormones and their synergy are important for regulating cell cycle progression and how environmental factors positively and negatively affect cell division. We then focus on the well-studied example of stress-induced G2 arrest and view the current model from an evolutionary perspective. Finally, we discuss the mechanisms controlling the transition from the mitotic cycle to the endocycle, which greatly contributes to cell enlargement and resultant organ growth in plants.
Background and aim Secreted frizzled-related protein 2 (sFRP2) has been reported to be involved in cardiovascular diseases. However, its role in cardiac hypertrophy induced by pressure overload is ...still elusive. We aimed to examine the role of sFRP2 in the development of cardiac hypertrophy in vivo and in vitro. Methods and results Following cardiac hypertrophy stimulated by aortic banding (AB), the expression of sFRP2 was downregulated in the hypertrophic ventricle. Adeno-associated virus 9 (AAV9) was injected through the tail vein to overexpress sFRP2 in the mouse myocardium. Overexpression of sFRP2 alleviated cardiomyocyte hypertrophy and interstitial fibrosis, as identified by the reduced cardiomyocyte cross-sectional area, heart weight/body weight ratio, and left ventricular (LV) collagen ratio. Additionally, sFRP2 decreased cardiomyocyte apoptosis induced by pressure overload. Western blot showed that sFRP2 prevented the expression of active beta-catenin. The Wnt/beta-catenin agonist LiCl (1 mmol/kg) abolished the inhibitory effects of sFRP2 on cardiac hypertrophy and apoptosis, as evidenced by the increased cross-sectional area and LV collagen ratio and the deterioration of echocardiographic data. Conclusion Our study indicated that decreased sFRP2 levels were observed in failing mouse hearts. Overexpression of sFRP2 attenuated myocyte hypertrophy and interstitial fibrosis induced by hypertrophic stimuli by inhibiting the Wnt/beta-catenin pathway. We revealed that sFRP2 may be a promising therapeutic target for the development of cardiac remodeling.
In modern manufacturing systems, operators' role is evolving continuously in relation to the main production paradigms affecting how companies approach their manufacturing and logistics operations. ...If the introduction of Lean Manufacturing principles has affected workers' well-being directly, the adoption of digital technologies is modifying how factory work is organised and performed. As a result, digitalised and Lean Manufacturing contexts require operators to enhance their skills increasingly to perform several tasks and functions. This paper examines the evolution of operators' role in production by recalling two main work design paradigms that originated in the 1960s: Job Enlargement and Job Enrichment. Indeed, through a literature review and development of a causal loop diagram (CLD), this research points out how the main features of Industry 4.0 and Lean Manufacturing jointly affect the Job Enlargement and Job Enrichment concepts. The study significantly helps reshape work design in next-generation production systems, shedding light on the implications and relationships of the most widespread manufacturing paradigm, i.e. Lean Manufacturing and Industry 4.0, using Job Enrichment and Job Enlargement strategies. A CLD also can be a helpful tool for practitioners to understand what factors to leverage to increase efficiency and worker satisfaction.
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