To study the impact of the agricultural information system based on the Internet of Things (IoT) on the income of agricultural products, an agricultural information system was constructed based on ...the agricultural IoT technology, and its impact on the income of agricultural products was discussed through the deep belief network. First, the relevant theories of agricultural IoT were introduced. Then, an agricultural information system based on agricultural IoT technology was constructed, and a deep belief network model was proposed. The vegetable prices and influencing factors were collected. The data were distributed in the range of 0–1 after normalization. The collinearity between the data was eliminated through principal component analysis. Then, the principal component analysis of vegetable prices and influencing factors from 2015 to 2019 was performed. A total of 96 sample data of calibration set and 24 sample data of test machine were collected. The optimal number of hidden layers of the deep belief network model and the number of nodes contained in the hidden layer were obtained through experiments. The results show that the first, second, and third hidden layers have 8, 6, and 10 nodes, respectively; the prediction accuracy of the deep belief network model is more accurate than that of the BP neural network and wavelet neural network. Besides, the absolute value of the prediction error of the deep belief model is within 0.1, which has good prediction accuracy. In short, the deep belief model has a good development prospect in agricultural product price forecasting, and it can provide relevant reference for the establishment and research of other agricultural product price forecasting models.
This letter aims to obtain a closed‐form performance metric using the smoothing posterior Cramér–Rao lower bound (PCRLB) for a class of direct discrete‐time kinematic models. By decoupling the ...state‐space model into separate position, velocity and acceleration components using an independent dynamic representation, the velocity component in the a priori distribution is converted into a position component. Based on the above derivations, the closed‐form PCRLB is developed. The effectiveness of the proposed bound is demonstrated by contrasting the proposed smoothing PCRLB with the traditional recursive PCRLB in a bearings‐only target tracking scenario.
This letter develops a novel closed‐form PCRLB capable of computing the smoothing PCRLB for batch discrete‐time estimation, achieved through state decoupling. The simulation results corroborate the effectiveness of the proposed bound.
With the intensification of global climate change, low-carbon energy has become a hot topic, and governments around the world are implementing corresponding policies to promote its use. This research ...first establishes a Multi-universe Quantum Harmony Search-Algorithm Dynamic Fuzzy System Ensemble (MUQHS-DMFSE) composite model for carbon emission prediction. This model combines the MUQHS algorithm with the DMFSE method by designing the workflow of the MUQHS algorithm, creating a DMFSE composite prediction model, introducing a sliding factor matrix, and using the MUQHS algorithm to search for the optimal sliding factors, thus obtaining optimized prediction values. In the research on low-carbon economic development, the research applies the Data Envelopment Analysis (DEA) method and establishes Charnes-Cooper-Rhodes (CCR) and Banker-Charnes-Cooper (BCC) models to assess the technical efficiency, pure technical efficiency, and scale efficiency of decision-making units. This research also uses the BCC model to project the production frontier and calculate input redundancy and output gap rates, and evaluate low-carbon economic development. Through the establishment and application of these two models, the research achieves carbon emission prediction and low-carbon economic analysis, validating the feasibility of the research methodology. The results show that the composite model can effectively predict carbon emissions, with a Mean Absolute Percentage Error (MAPE) below 3.5% and Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) below 200 tons, demonstrating the feasibility and accuracy of the model. The research on low-carbon economic development in S Province based on the DEA method reveals the need for energy structure adjustment, clean and renewable energy promotion, control of carbon emissions, and optimization of industrial structure with a focus on developing the tertiary industry. Therefore, the use of artificial intelligence and big data analysis can provide more precise insights into the trends and patterns of low-carbon economic development, as well as more effective predictions of future energy demand and resource supply, offering high practical value and scientific significance.
Topology optimization (TO) is a dependable approach to obtain innovative designs with improved performance. This study presents a TO method based on the adjoint lattice Boltzmann method (ALBM) and ...the level set method which is developed for both one‐way coupled and two‐way coupled convective heat transfer problems. The adjoint lattice Boltzmann model for fully coupled natural convection system is derived, and the coupled solution strategy is applied in the ALBM. The forward model is validated by the finite element simulation, while the adjoint model and the sensitivity expression is validated by a finite difference check, and the whole TO method is validated by a typical pure fluid flow optimization problem given in the literature. The validated TO method is then applied to enhance the heat transfer of forced convection in a two‐dimensional open chamber, and the Pareto frontier of the bi‐objective optimization is further presented and the effects of the blockages at the inlet and outlet on the overall performance are revealed. Finally, the two‐dimensional natural convection process in a closed cavity is optimized, in which the effective heat transfer coefficient can be increased to 3.96 ∼ 6.11 times of that without the optimized design when the Grashof number ranges from 1.7 to 4.2 × 105. Moreover, effects of Grashof number, porosity limitation and solid thermal diffusivity on the optimization results are analyzed in detail. Physically reasonable designs are obtained for both forced convection and natural convection systems under various parameter settings, demonstrating the effectiveness and robustness of the presented TO method.
This article presents a topology optimization method based on the adjoint lattice Boltzmann method and the level set method which is developed for both one‐way coupled and two‐way coupled convective heat transfer problems. The adjoint model for fully coupled natural convection system is derived, and the coupled solution strategy is applied. The natural convection heat transfer in a closed cavity is optimized using the above method, and the figure shows the optimal geometries under different values of Grashof number.
Polyol esters are abundant bio‐based resources. Integration of polyol esters into the production chain of fine chemicals would reduce carbon emissions and improve the sustainability of the chemical ...industry. An efficient synthetic route to phenoxyethanols was developed through catalytic hydroxyethylation of phenols with ethylene glycol diacetate as the reagent. This method showed the potential of ethylene glycol diester as a safe and sustainable substitute for ethylene oxide, a useful but toxic reagent. A variety of phenoxyethanol esters were produced in high yield under simple catalytic conditions. Mechanistic studies revealed that the reaction underwent a neighboring group participation process.
A Lewis acid‐catalyzed, solvent‐free hydroxyethylation strategy that converts phenols into phenoxyethanol esters is reported. Ethylene glycol diesters are used as renewable and safe alternatives to the harmful ethylene oxide. Oligomerization byproducts from ethylene oxide are also avoided. Applications are demonstrated in upcycling of polyester plastics and preparation of bioactive chemicals.
Transport infrastructure connectivity (TIC) has strong endogeneity issues, making it difficult to directly assess its impact on local conflict resolution. This study presents new evidence of the ...effects of TIC on conflict resolution by conducting a natural experiment and applying machine learning methods to overcome the endogeneity issue. Based on global conflict data from 2010 to 2017, the empirical results show the following: (1) TIC can significantly improve countries’ global ranking for conflict resolution; in particular, the marginal benefit of developed countries is greater than that of developing countries. (2) The mechanism behind this effect is the promotion of trade facilitation, a more balanced employment ratio across genders, and improved income levels through TIC, which further enhances the conflict governance capacity of countries. In light of the findings, policy-makers should consider the opportunity to combine TIC with greater security for the realization of economic and social benefits, taking into account the significant opportunities for developing countries and the importance of balance across genders and income levels.
Rice is cooked and consumed after a short-term cooling which is associated with the short-term starch retrogradation. The two most important textural attributes (hardness & stickiness) of 28 cooked ...rice varieties were investigated in this study, based on the causal relations between starch chain-length distributions (CLD) and short-term retrogradation properties. Size-exclusion chromatography (SEC) was used to characterize the starch CLD, while the setback viscosity (SBV) from rapid visco-analyzer and hydrogel firmness (HF) from textural profile analyzer were represented as characteristics of the short-term retrogradation process. Pearson correlations showed that regardless of amylose content, rice starches containing relatively shorter amylose molecules with short to long chains, and more amylopectin medium and long chains with the degree of polymerization (DP) > 69 can all promote the short-term retrogradation rate, resulting in cooked rice with a hard and non-sticky texture. It also suggests that both SBV and HF could be utilized to predict the final cooked rice texture such as the hardness and stickiness. Furthermore, rice starches with a relatively higher amount of medium chains but less short chains within the amylopectin molecules are related to a less sticky texture of the cooked rice. The current study provides important information for rice industry and breeding programs to develop new varieties with targeted eating qualities.
Rice starches with a higher amylose content, relatively less amount of amylose swith hort and long chains, while relatively more amylopectin with medium and long chains have a faster short-term retrogradation rate, resulting in a harder but less sticky texture of cooked rice. Furthermore, rice starches with more amylopectin medium chains and relatively less amylopectin short chains could result in a less sticky texture of cooked rice. Display omitted
•Cooked rice texture of 28 different rice varieties were investigated.•Setback viscosity and hydrogel firmness can predict cooked rice texture.•Starch short-term retrogradation determines cooked rice texture.•Both amylopectin and amylose molecules are involved in short-term retrogradation.•Starch chain length features controlling cooked rice texture are revealed.
Using small molecules to control the function of proteins in live cells with complete specificity is highly desirable, but challenging. Here we report a small-molecule switch that can be used to ...control protein activity. The approach uses a phosphine-mediated Staudinger reduction to activate protein function. Genetic encoding of an ortho-azidobenzyloxycarbonyl amino acid using a pyrrolysyl transfer RNA synthetase/tRNA
pair in mammalian cells enables the site-specific introduction of a small-molecule-removable protecting group into the protein of interest. Strategic placement of this group renders the protein inactive until deprotection through a bioorthogonal Staudinger reduction delivers the active wild-type protein. This developed methodology was applied to the conditional control of several cellular processes, including bioluminescence (luciferase), fluorescence (enhanced green fluorescent protein), protein translocation (nuclear localization sequence), DNA recombination (Cre) and gene editing (Cas9).
Abstract
Infections induce a set of pleiotropic responses in animals, including anorexia, adipsia, lethargy and changes in temperature, collectively termed sickness behaviours
1
. Although these ...responses have been shown to be adaptive, the underlying neural mechanisms have not been elucidated
2–4
. Here we use of a set of unbiased methodologies to show that a specific subpopulation of neurons in the brainstem can control the diverse responses to a bacterial endotoxin (lipopolysaccharide (LPS)) that potently induces sickness behaviour. Whole-brain activity mapping revealed that subsets of neurons in the nucleus of the solitary tract (NTS) and the area postrema (AP) acutely express FOS after LPS treatment, and we found that subsequent reactivation of these specific neurons in FOS
2A-iCreERT2
(also known as TRAP2) mice replicates the behavioural and thermal component of sickness. In addition, inhibition of LPS-activated neurons diminished all of the behavioural responses to LPS. Single-nucleus RNA sequencing of the NTS–AP was used to identify LPS-activated neural populations, and we found that activation of ADCYAP1
+
neurons in the NTS–AP fully recapitulates the responses elicited by LPS. Furthermore, inhibition of these neurons significantly diminished the anorexia, adipsia and locomotor cessation seen after LPS injection. Together these studies map the pleiotropic effects of LPS to a neural population that is both necessary and sufficient for canonical elements of the sickness response, thus establishing a critical link between the brain and the response to infection.
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