Does a higher minimum wage accelerate labour division in agricultural production? Evidence from the main riceplanting area in China

Agricultural production outsourcing, a new means of agricultural production, can optimise the allocation of resources, reduce agricultural production costs, and improve agricultural productivity. However, farmers’ outsourcing behaviours are strongly interfered with by many factors such as economics, technology and institutions. Using a farmer-level data set from 2014 to 2018 in China, we examine the effects of the minimum wage increase on rice farmers’ production outsourcing behaviours. Our study relies on a Logit regression framework and uses the control function (C.F.) approach to address potential endogeneity concerns. Results show that the minimum wage increase significantly reduces the probability of farmers conducting production outsourcing. We also examine the heterogeneous effects of the minimum wage increase, and find that compared with other outsourcing services, the adverse effects on harvesting outsourcing are the strongest; the negative effects on production outsourcing are stronger for rice farmers with higher education. Our results provide new insights into understanding how labour regulation affects labour division in agricultural production

New Global Synchronization Analysis for Complex Networks with Coupling Delay

Global synchronization analysis for complex networks with coupling delay is investigated. Firstly the constant time delay is analyzed and then the case for time-varying delay is considered. Sufficient conditions for network synchronization are given based on Lyapunov functional, linear matrix inequality, and Kronecker product technique. The unknown variables in the sufficient conditions are fewer than those in the recent reference. Moreover, for the time-varying delay case, we find that the conditions are dependent on the bounds of both time delay and its derivative, and the derivative of the time-varying delay can be any value in the bounds. Finally, numerical examples are given to validate the effectiveness of the obtained results

Study on Flavor Characteristics and Nutritional Evaluation of Free Amino Acids in Walnut Pellicle

In order to explore the composition, taste characteristics and nutritional value of free amino acids in pellicle of different varieties of walnut, the content of free amino acid in the pellicle of 6 walnut varieties was detected, and the taste activity value (TAV) analysis, principal component analysis and comprehensive evaluation were carried out. The results showed that a total of 17 free amino acids could be detected in the pellicle of walnut, with a total content of 2673.86~3490.12 mg/kg. Nine medicinal amino acids accounted for 57.67%~68.23% of the total amino acids, and Leu was the first limiting amino acid in the pellicle. Glu, Asp, Thr, Cys and Arg were the main amino acids of free amino acids in the pellicle, with Glu having the highest content. The TAV value of Glu among the six cultivars was 2.34~3.81, which contributed the most to the umami of the pellicle. The TAV values of Arg in 'Jing 861', 'Bokexiang' and 'Jinboxiang 8' were 1.03~1.26, which contributed to the bitterness of the pellicle. Among the flavor amino acids, the content of umami amino acids was the highest, while aromatic amino acids had the lowest contentm. The ratio of bitter to sweet amino acid content in the 'Nonghe 1', 'Jing 861', 'Bokexiang' and 'Jinboxiang 8' was greater than 1. While the ratio of bitter to sweet amino acid content in the 'Fenhe 2' and ' Fenhe 4' was less than 1. The comprehensive quality of amino acids was also relatively higher. The amino acids in pellicle had high nutritional value and medicinal value, and the taste was bitter, as a food auxiliary material to supplement Thr, Ile and sulfur-containing amino acids, it could increase the overall taste richness of food

A global monthly field of seawater pH over 3 decades: a machine learning approach

The continuous uptake of anthropogenic CO2 by the ocean leads to ocean acidification, which is an ongoing threat to the marine ecosystem. The ocean acidification rate was globally documented in the surface ocean but limited below the surface. Here, we present a monthly four-dimensional 1°×1° gridded product of global seawater pH, derived from a machine learning algorithm trained on pH observations at total scale and in-situ temperature from the Global Ocean Data Analysis Project (GLODAP). The constructed pH product covers the years 1992–2020 and depths from the surface to 2 km on 41 levels. Three types of machine learning algorithms were used in the pH product construction, including self-organizing map neural networks for region dividing, a stepwise algorithm for predictor selection, and feed-forward neural networks (FFNN) for non-linear relationship regression. The performance of the machine learning algorithm was validated using real observations by a cross validation method, where four repeating iterations were carried out with 25 % varied observations for each evaluation and 75 % for training. The constructed pH product is evaluated through comparisons to time series observations and the GLODAP pH climatology. The overall root mean square error between the FFNN constructed pH and the GLODAP measurements is 0.028, ranging from 0.044 in the surface to 0.013 at 2000 m. The pH product is distributed through the data repository of the Marine Science Data Center of the Chinese Academy of Sciences at http://dx.doi.org/10.12157/IOCAS.20230720.001 (Zhong et al., 2023)

Analysis of Time Series Gene Expression and DNA Methylation Reveals the Molecular Features of Myocardial Infarction Progression

Myocardial infarction (MI) is one of the deadliest diseases in the world, and the changes at the molecular level after MI and the DNA methylation features are not clear. Understanding the molecular characteristics of the early stages of MI is of significance for the treatment of the disease. In this study, RNA-seq and MeDIP-seq were performed on heart tissue from mouse models at multiple time points (0 h, 10 min, 1, 6, 24, and 72 h) to explore genetic and epigenetic features that influence MI progression. Analysis based on a single point in time, the number of differentially expressed genes (DEGs) and differentially methylated regions (DMRs) increased with the time of myocardial infarction, using 0 h as a control group. Moreover, within 10 min of MI onset, the cells are mainly in immune response, and as the duration of MI increases, apoptosis begins to occur. Analysis based on time series data, the expression of 1012 genes was specifically downregulated, and these genes were associated with energy metabolism. The expression of 5806 genes was specifically upregulated, and these genes were associated with immune regulation, inflammation and apoptosis. Fourteen transcription factors were identified in the genes involved in apoptosis and inflammation, which may be potential drug targets. Analysis based on MeDIP-seq combined with RNA-seq methodology, focused on methylation at the promoter region. GO revealed that the downregulated genes with hypermethylation at 72 h were enriched in biological processes such as cardiac muscle contraction. In addition, the upregulated genes with hypomethylation at 72 h were enriched in biological processes, such as cell-cell adhesion, regulation of the apoptotic signaling pathway and regulation of angiogenesis. Among these genes, the Tnni3 gene was also present in the downregulated model. Hypermethylation of Tnni3 at 72 h after MI may be an important cause of exacerbation of MI

The SISAL database: a global resource to document oxygen and carbon isotope records from speleothems

Stable isotope records from speleothems provide information on past climate changes, most particularly information that can be used to reconstruct past changes in precipitation and atmospheric circulation. These records are increasingly being used to provide “out-of-sample” evaluations of isotope-enabled climate models. SISAL (Speleothem Isotope Synthesis and Analysis) is an international working group of the Past Global Changes (PAGES) project. The working group aims to provide a comprehensive compilation of speleothem isotope records for climate reconstruction and model evaluation. The SISAL database contains data for individual speleothems, grouped by cave system. Stable isotopes of oxygen and carbon (δ 18O, δ 13C) measurements are referenced by distance from the top or bottom of the speleothem. Additional tables provide information on dating, including information on the dates used to construct the original age model and sufficient information to assess the quality of each data set and to erect a standardized chronology across different speleothems. The metadata table provides location information, information on the full range of measurements carried out on each speleothem and information on the cave system that is relevant to the interpretation of the records, as well as citations for both publications and archived data. The compiled data are available at https://doi.org/10.17864/1947.147

Evaluating model outputs using integrated global speleothem records of climate change since the last glacial

Although quantitative isotopic data from speleothems has been used to evaluate isotope-enabled model simulations, currently no consensus exists regarding the most appropriate methodology through which to achieve this. A number of modelling groups will be running isotope-enabled palaeoclimate simulations in the framework of the Coupled Model Intercomparison Project Phase 6, so it is timely to evaluate different approaches to use the speleothem data for data-model comparisons. Here, we illustrate this using 456 globally-distributed speleothem δ18O records from an updated version of the Speleothem Isotopes Synthesis and Analysis (SISAL) database and palaeoclimate simulations generated using the ECHAM5-wiso isotope-enabled atmospheric circulation model. We show that the SISAL records reproduce the first-order spatial patterns of isotopic variability in the modern day, strongly supporting the application of this dataset for evaluating model-derived isotope variability into the past. However, the discontinuous nature of many speleothem records complicates procuring large numbers of records if data-model comparisons are made using the traditional approach of comparing anomalies between a control period and a given palaeoclimate experiment. To circumvent this issue, we illustrate techniques through which the absolute isotopic values during any time period could be used for model evaluation. Specifically, we show that speleothem isotope records allow an assessment of a model’s ability to simulate spatial isotopic trends. Our analyses provide a protocol for using speleothem isotopic data for model evaluation, including screening the observations to take into account the impact of speleothem mineralogy on 18O values, the optimum period for the modern observational baseline, and the selection of an appropriate time-window for creating means of the isotope data for palaeo time slices