Adaptive predefined-time robust control for nonlinear time-delay systems with different power Hamiltonian functions

The article studies $H_\infty$ control as well as adaptive robust control issues on the predefined time of nonlinear time-delay systems with different power Hamiltonian functions. First, for such Hamiltonian systems with external disturbance and delay phenomenon, we construct the appropriate Lyapunov function and Hamiltonian function of different powers. Then, a predefined-time $H_\infty$ control approach is presented to stabilize the systems within a predefined time. Furthermore, when considering nonlinear Hamiltonian system with unidentified disturbance, parameter uncertainty and delay, we devise a predefined-time adaptive robust strategy to ensure that the systems reach equilibrium within one predefined time and have better resistance to disturbance and uncertainty. Finally, the validity of the results is verified with a river pollution control system example

DiffusionPhase: Motion Diffusion in Frequency Domain

In this study, we introduce a learning-based method for generating high-quality human motion sequences from text descriptions (e.g., ``A person walks forward"). Existing techniques struggle with motion diversity and smooth transitions in generating arbitrary-length motion sequences, due to limited text-to-motion datasets and the pose representations used that often lack expressiveness or compactness. To address these issues, we propose the first method for text-conditioned human motion generation in the frequency domain of motions. We develop a network encoder that converts the motion space into a compact yet expressive parameterized phase space with high-frequency details encoded, capturing the local periodicity of motions in time and space with high accuracy. We also introduce a conditional diffusion model for predicting periodic motion parameters based on text descriptions and a start pose, efficiently achieving smooth transitions between motion sequences associated with different text descriptions. Experiments demonstrate that our approach outperforms current methods in generating a broader variety of high-quality motions, and synthesizing long sequences with natural transitions

Addressing rural–urban income gap in China through farmers’ education and agricultural productivity growth via mediation and interaction effects

Narrowing the rural–urban income gap is an important challenge in achieving sustained and stable economic and social development in China. The present study investigates the role of farmers’ education and agricultural productivity growth in influencing the rural–urban income gap by applying mediation, interaction, and quantile regression models to provincial panel data of China from 2003 to 2017. Results show that, first of all, China’s agricultural productivity (TFP) continues to improve, and it is mainly driven by technical change (TC), with no significant role of technical efficiency change (TEC) or stable scale change (SC). Improving farmers’ education not only directly narrows the rural–urban income gap but also indirectly improves agricultural productivity to further narrow the rural–urban income gap. Due to differences in income sources of farmers, the corresponding impacts of farmers’ education and agricultural productivity growth on the rural–urban income gap also differ. Policy recommendations include continued investments in farmers’ education and training as well as modernization of agricultural for higher productivity growth

Short-term PV power prediction based on the 24 traditional Chinese solar terms and adaboost-GA-BP model

High-precision, short-term power forecasting for photovoltaic systems not only reduces unnecessary energy consumption but also provides power grid security. To this end, in this paper we propose a photovoltaic short-term power forecasting model based on the division of data of the 24 traditional Chinese solar terms and the Adaboost-GA-BP model. The 24 solar terms were condensed from the laws of meteorology, phenology, and seasonal changes to adapt to agricultural times in ancient China and have become intangible cultural heritage. This article first analyzes the numerical characteristics of meteorological factors and demonstrates their close correlation with the turning points of the 24 solar terms. Second, using Standardized Euclidean Distance and Spearman’s Correlation Coefficients to analyze data similarity between the Gregorian half-months and the 24 solar terms divisions for comparative analysis purposes, it is shown that the intragroup data under the division of the 24 solar terms have a higher similarity, leading to an average decrease of 15.68%, 40.57%, 14.68%, and 14.64% in the MAE, MSE, RMSE, and WMAPE of the predicted results, respectively. Finally, based on the data derived from the 24 solar terms, the combined algorithm was compared with the Adaboost-GA-BP model and then was verified. The genetic algorithm and Adaboost were used to optimize the BP neural network algorithm in initial value assignment and neural network structure, resulting in a 23.42%, 18.12%, and 22.28% reduction in the mean values of the MAE, RMSE, and WMAPE of the predicted results, respectively. Analysis of the results show that using the Adaboost-GA-BP model based on the 24 solar terms for short-term photovoltaic power forecasting can improve the accuracy of photovoltaic power forecasting and significantly improve the predictive performance of the model

Simvastatin reduces atherogenesis and promotes the expression of hepatic genes associated with reverse cholesterol transport in apoE-knockout mice fed high-fat diet

<p>Abstract</p> <p>Background</p> <p>Statins are first-line pharmacotherapeutic agents for hypercholesterolemia treatment in humans. However the effects of statins on atherosclerosis in mouse models are very paradoxical. In this work, we wanted to evaluate the effects of simvastatin on serum cholesterol, atherogenesis, and the expression of several factors playing important roles in reverse cholesterol transport (RCT) in apoE-/- mice fed a high-fat diet.</p> <p>Results</p> <p>The atherosclerotic lesion formation displayed by oil red O staining positive area was reduced significantly by 35% or 47% in either aortic root section or aortic arch en face in simvastatin administrated apoE-/- mice compared to the control. Plasma analysis by enzymatic method or ELISA showed that high-density lipoprotein-cholesterol (HDL-C) and apolipoprotein A-I (apoA-I) contents were remarkably increased by treatment with simvastatin. And plasma lecithin-cholesterol acyltransferase (LCAT) activity was markedly increased by simvastatin treatment. Real-time PCR detection disclosed that the expression of several transporters involved in reverse cholesterol transport, including macrophage scavenger receptor class B type I, hepatic ATP-binding cassette (ABC) transporters ABCG5, and ABCB4 were induced by simvastatin treatment, the expression of hepatic ABCA1 and apoA-I, which play roles in the maturation of HDL-C, were also elevated in simvastatin treated groups.</p> <p>Conclusions</p> <p>We demonstrated the anti-atherogenesis effects of simvastatin in apoE-/- mice fed a high-fat diet. We confirmed here for the first time simvastatin increased the expression of hepatic ABCB4 and ABCG5, which involved in secretion of cholesterol and bile acids into the bile, besides upregulated ABCA1 and apoA-I. The elevated HDL-C level, increased LCAT activity and the stimulation of several transporters involved in RCT may all contribute to the anti-atherosclerotic effect of simvastatin.</p

Investigating the driving forces of NOx generation from energy consumption in China

In China, nitrogen oxide (NOx) emissions have been declining in recent years, whereas NOx generation continues to increase. This has prompted a growing focus of policy design to inspect the driving mechanisms of NOx generation. In this study, a decomposition model of NOx generation in China from 1995 to 2014 was built using the Logarithmic Mean Divisia Index (LMDI) method. According to the decomposition results, technological effects (e.g., energy intensity and the sector generation factor) inhibited NOx generation in China, while gross domestic product (GDP) per capita was found to have the most positive effect on increasing NOx generation, accounting for 151.00% of the total change and showing an increasing trend in recent years. The sector structure of energy consumption always increased NOx generation, which contradicts the results of previous studies. All population effects considered in this study contributed to the growth in NOx generation. The population scale effect was increasingly impactful on the growth of NOx generation; the population spatial structure was active but less impactful. In general, technological impact cannot offset the increases caused by economic, structural, and population effects. Considering NOx reduction policy in China, more attention should be given to emission reduction policies, energy consumption, and socio-economic effects; together, these approaches will improve initiatives to reduce NOx

Frontiers and future of immunotherapy for pancreatic cancer: from molecular mechanisms to clinical application

Pancreatic cancer is a highly aggressive malignant tumor, that is becoming increasingly common in recent years. Despite advances in intensive treatment modalities including surgery, radiotherapy, biological therapy, and targeted therapy, the overall survival rate has not significantly improved in patients with pancreatic cancer. This may be attributed to the insidious onset, unknown pathophysiology, and poor prognosis of the disease. It is therefore essential to identify and develop more effective and safer treatments for pancreatic cancer. Tumor immunotherapy is the new and fourth pillar of anti-tumor therapy after surgery, radiotherapy, and chemotherapy. Significant progress has made in the use of immunotherapy for a wide variety of malignant tumors in recent years; a breakthrough has also been made in the treatment of pancreatic cancer. This review describes the advances in immune checkpoint inhibitors, cancer vaccines, adoptive cell therapy, oncolytic virus, and matrix-depletion therapies for the treatment of pancreatic cancer. At the same time, some new potential biomarkers and potential immunotherapy combinations for pancreatic cancer are discussed. The molecular mechanisms of various immunotherapies have also been elucidated, and their clinical applications have been highlighted. The current challenges associated with immunotherapy and proposed strategies that hold promise in overcoming these limitations have also been discussed, with the aim of offering new insights into immunotherapy for pancreatic cancer

Case study of a rhizosphere microbiome assay on a bamboo rhizome with excessive shoots.

Peer reviewe

Exploring retinal ganglion cells encoding to multi-modal stimulation using 3D microelectrodes arrays

Microelectrode arrays (MEA) are extensively utilized in encoding studies of retinal ganglion cells (RGCs) due to their capacity for simultaneous recording of neural activity across multiple channels. However, conventional planar MEAs face limitations in studying RGCs due to poor coupling between electrodes and RGCs, resulting in low signal-to-noise ratio (SNR) and limited recording sensitivity. To overcome these challenges, we employed photolithography, electroplating, and other processes to fabricate a 3D MEA based on the planar MEA platform. The 3D MEA exhibited several improvements compared to planar MEA, including lower impedance (8.73 ± 1.66 kΩ) and phase delay (−15.11° ± 1.27°), as well as higher charge storage capacity (CSC = 10.16 ± 0.81 mC/cm2), cathodic charge storage capacity (CSCc = 7.10 ± 0.55 mC/cm2), and SNR (SNR = 8.91 ± 0.57). Leveraging the advanced 3D MEA, we investigated the encoding characteristics of RGCs under multi-modal stimulation. Optical, electrical, and chemical stimulation were applied as sensory inputs, and distinct response patterns and response times of RGCs were detected, as well as variations in rate encoding and temporal encoding. Specifically, electrical stimulation elicited more effective RGC firing, while optical stimulation enhanced RGC synchrony. These findings hold promise for advancing the field of neural encoding

Different origin-derived exosomes and their clinical advantages in cancer therapy

Exosomes, as a class of small extracellular vesicles closely related to the biological behavior of various types of tumors, are currently attracting research attention in cancer diagnosis and treatment. Regarding cancer diagnosis, the stability of their membrane structure and their wide distribution in body fluids render exosomes promising biomarkers. It is expected that exosome-based liquid biopsy will become an important tool for tumor diagnosis in the future. For cancer treatment, exosomes, as the “golden communicators” between cells, can be designed to deliver different drugs, aiming to achieve low-toxicity and low-immunogenicity targeted delivery. Signaling pathways related to exosome contents can also be used for safer and more effective immunotherapy against tumors. Exosomes are derived from a wide range of sources, and exhibit different biological characteristics as well as clinical application advantages in different cancer therapies. In this review, we analyzed the main sources of exosomes that have great potential and broad prospects in cancer diagnosis and therapy. Moreover, we compared their therapeutic advantages, providing new ideas for the clinical application of exosomes