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Land consolidation has become an organized and widely implemented project in rural areas. However, research remains somewhat scarce on the contributing mechanism of land consolidation to farmer income in developing countries. Using provincial panel data from China, this study employs a fixed effects model to analyze the influence of high-standard farmland construction on farmer income and underlying mechanisms. Results suggest that the implementation of high-standard farmland construction can significantly augment farmer income. Reduction in agricultural production cost, improvement in agricultural management benefit and increase in non-farm income have led to the boost in income. The relationship between income and high-standard farmland construction exhibits regional disparities, with the most significant impacts concentrated in economically developed areas and low relief degree areas. Our findings suggest that it is imperative for the Chinese government to persistently promote the establishment of high-standard farmland, and further enhance its positive influence on advancing agricultural cost-effectiveness and expanding non-farm income channels for farmers.

Fault-fracture bodies are developed in the southwestern margin of Ordos Basin， and thus， the study on the controlling effect of fracture bodies on sweet spot distribution of Yanchang Formation reservoirs needs to be deepened. In this paper， based on the extensive seismic and logging interpretation results， the characteristics of fault-fracture bodies are described from the point of view of their evolution mechanism， and then the controlling effect of fault-fracture bodies on oil and gas is systematically discussed. The results show that vertical strike-slip faults are developed in the southwest margin of Ordos Basin， with Y-shaped， flower-like， and negative flower-like structures. The faults usually pass through the bottom of Chang 7 Member， the bottom of Yan’an Formation， the bottom of the Cretaceous series， and the basement. Some of the faults retain the early reverse fault properties， indicating that the late inversion degree is not complete. The main fault has different shapes and migrations in different parts， and the section shows the cyclic transformation of tension-torsion and compression-torsion properties. On the plane， different types of fracture combinations appear alternately. The development model of strike-slip faults is established， and the strike-slip faults have typical characteristics of “multi-stage activity and inherited development”. Chang 8 Member mainly develops vertical fractures and horizontal bedding fractures. The development frequency of horizontal bedding fractures is 62.5%， while that of vertical fractures is 37.5%. The oil level of vertical fractures is relatively higher. Fractures are mainly developed in fine sandstone in distributary channels. When the distance from the main fault is greater than 1.25-1.5 km， the degree of fracture development decreases sharply， showing a fault-fracture body boundary. In addition， fractures are relatively developed in the single sand body within 6 m from the main fault. When the thickness of the single sand body exceeds 6 m， the degree of fracture development decreases sharply. The study shows that the index system based on sedimentation （foundation）， structure （dominant）， and fracture （effective） can effectively predict the favorable zones of Chang 8 fault-fracture body reservoir.

This paper investigates the impact of digital transformation on innovation within the agribusiness sector, both theoretically and empirically, through an examination of Chinese A-share agriculture-related listed companies spanning from 2011 to 2021. The findings suggest that digital transformation significantly enhances innovation capability of agribusiness, while concurrently fostering improvements of its innovation quality. These results hold robust following an endogeneity test and a series of robustness tests. Our heterogeneity analysis found that digital transformation exerts a more pronounced influence on promoting innovation among state-owned agribusinesses, those located in the eastern region of China, and those facing heightened financing constraints. Mechanism testing revealed that digital transformation not only enhances the technological capabilities of agribusiness but also alleviates their financial constraints, thereby facilitating the convergence of innovative resources such as technology, talent and capital to agribusiness, and consequently elevating agribusi-ness innovation levels. This paper elucidates the impacts and mechanisms of digital transformation on agribusiness innovation, offering valuable insights for decision-makers aiming to foster agribusiness innovation, particularly in developing nations.

Objective: In order to solve the problem of manual weighting of dragon fruit, including time-consuming, laborious and expensive, an automated weight estimation method based on machine vision and machine learning was proposed in this research. Methods: Firstly, 106 dragon fruits were weighed, recorded and photographed, and images of dragon fruits were constructed. Secondly, binary images were obtained after denoising and segmentation. Moreover, the three features of pixel area, major axis pixel length and minor axis pixel length of dragon fruits were extracted on the basis of binary images. The three features of each image and their corresponding weights were combined into a set of data, which was divided into training set and test set according to the ratio of 7∶3. Finally, the training set was input into the Gradient Boosting, Random Forest, K-Neighbors and Artificial Neural Networks machine-learning models for training, and the test sets were used for model evaluation. Results: The evaluation index of the Artificial Neural network performed well compared with other models, with R2 of 0.986 and RMSE of 13.091. Conclusion: The experimental result demonstrates that the method proposed in this research can accomplish the weight estimation of dragon fruit effectively, and meet the weight estimation requirements of dragon fruit.

Objective: An analytical method was established for determination of 13 kinds of bisphenols and alkylphenol compounds in liquid dairy products by salting-out-assisted liquid-liquid extraction coupled with HPLC-MS/MS. Methods: The salting-out-assisted liquid-liquid extraction pre-treatment method was adopted, and the detection was performed in the mode of negative ion source multiple reaction monitoring （MRM） by triple quadrupole mass spectrometry, and quantitative analysis was performed by matrix external standard method. Besides, the effect of extraction solvent type, selection and the usage of salting-out agents on the recoveries were studied and the performance of the method was evaluated. Results: The liquid dairy products were liquid-liquid extracted with acetonitrile as extraction solvent and 0.4 g sodium chloride as salting-out agents. The 13 kinds of phenols had a good linear relationship, and the correlation coefficients were all ＞ 0.99. The standard recovery rates of milk and yoghurt were 81.5% to 118.1% and 80.8% to 107.6%, respectively, and the relative standard deviations were 1.89% to 12.3% and 1.12% to 11.9%. The detection limits were 0.15 to 0.75 μg/kg, and the quantification limits were 0.5 to 2.5 μg/kg. One of the commercially available liquid dairy product was found to contain 4-NP, and the concentrations was 9.28 μg/kg. Conclusion: The established method is suitable for the rapid detection of 13 kinds of bisphenols and alkylphenol compounds in liquid dairy products.

BACKGROUND Sepiolite is a layered hydrous magnesium-rich silicate clay mineral. The content of inorganic elements in sepiolite is an important basis for revealing the source of ore-forming materials, the nature of ore-forming fluids and the genesis of the deposit. It is usually determined by inductively coupled plasma-optical emission spectrometry (ICP-OES) and inductively coupled plasma-mass spectrometry (ICP-MS), high temperature excitation of inductively coupled plasma (ICP) will produce a large number of spectral interferences. High purity argon is needed to maintain the stability of ICP. Continuous gas supply for sepiolite detection in remote mining areas will also cause the problem of inconvenient gas procurement and transportation. OBJECTIVES In order to reduce the spectral interference and realize the accurate analysis of major and trace elements in sepiolite samples from remote mining areas. METHODS An analytical method was developed for accurate determination of major elements Mg, Al, Ca, Fe, K, Na and trace elements Cu, Zn, Mn and Pb in sepiolite by microwave plasma-atomic emission spectroscopy (MP-AES). Microwave digestion of sepiolite by using HNO3-HCl-HF as a mixed acid not only avoids the loss of analytes during sample processing, but also speeds up the sample processing and improves the stability of the sample solution. By selecting the analysis wavelength of the spectral line for analyte, using the fast linear interference correction (FLIC) technology to correct the spectral interference, and selecting Lu as the internal standard element corrected the matrix effect, which improved sensitivity and accuracy. RESULTS The limit of detection (LOD) was 0.19-14.6μg/L. The accuracy of the method was verified by the national standard reference material sepiolite (GBW07138). The relative error between the measured value and the certified value of analytes was between -5.0% and 6.7%, which verified the accuracy and reliability of the method. CONCLUSIONS The method has the advantages of low LOD, wide linear range, and accurate results. MP-AES uses its own nitrogen generator to provide nitrogen as the working gas for plasma, without introducing a complex gas, which improves the analysis efficiency, and is especially suitable for remote mining areas where gas procurement and transportation are inconvenient.

Scutellarin plays an anti-tumor role in A549 lung cancer cells, but the underlying mechanism is unclear. In this study, scutellarin was used to treat A549 cells for 12, 24, and 48 h, followed by the addition of Tempo, a selective scavenger of mitochondrial reactive oxygen species (ROS) and SB431542, a transforming growth factor (TGF)-β1 receptor inhibitor. A dihydroethidium fluorescence probe was used to measure the intracellular ROS level, Cell Counting Kit-8 (CCK-8) was used to detect cell viability, and flow cytometry was performed to examine apoptosis. Western blots were used to detect the total protein level of TGF-β1, p-smad2, and cleaved caspase-3 in A549 cells. The results showed that scutellarin significantly inhibited cell viability and increased apoptosis. Scutellarin also promoted intracellular ROS production, TGF-β1/smad2 signaling pathway activation, and cleaved caspase-3 expression, which was partly reversed by Tempo. Moreover, scutellarin-induced intracellular ROS production and cleaved caspase-3 expression were inhibited by blocking the TGF-β1/smad2 pathway with SB431542. In conclusion, scutellarin promoted apoptosis and intracellular ROS accumulation, which could be abrogated by Tempo and SB431542 treatment in A549 cells. Our study indicated that scutellarin induced A549 cell apoptosis via the TGF-β1/smad2/ROS/caspase-3 pathway.

Nowadays, the Muslim community is under the spotlight. The ongoing international debate over Muslim minorities identities reflects the dilemma of their integration into non-Muslim modern multi-ethnic nations under the context of multiculturalism. One typical example is the heated debate between the West and China over Chinese Muslims, also known as Uyghurs, through media discourse. Western media, such as the BBC, claim that China assimilates and forces Uyghurs to integrate. The Chinese side, meanwhile, asserts that mainstream Western media reports are lies, smears, and fake. Facing the discourse challenges from the West, China applies media discourse to reinforce its understanding of Uyghurs in the international discourse system. The analysis reveals that the Chinese government has consciously aligned the image of Uyghurs with its Chinese national image, and building a real Xinjiang image on CGTN.

The quality of cultivated land is an important basis for guaranteeing grain yield, and improving the quality of cultivated land is an important initiative of the Chinese government to implement its food security strategy. This paper explores the effects of formal technical training and informal online self-directed learning on farmers’ willingness to adopt cultivated land conservation technology using farmer-level survey data. The results show that farmers’ participation in technical training effectively increased their willingness to adopt straw return technologies, but participation in online self-directed learning did not affect farmers’ willingness to adopt, while farmers who participated in both technical training and online self-directed learning had stronger willingness to adopt. These results show that internet-based self-directed learning is a useful supplement to the formal training system. Further analysis revealed that participation in technical training increased farmers’ awareness of the usefulness of the straw-return technology, which in turn increased their willingness to adopt the conservation technology of cropland. This paper clarifies the impact and mechanisms of the two main existing technology learning modes on farmers’ adoption of new technologies in rural China and provides a reference for the promotion of agricultural technology diffusion and the improvement of the quality of cultivated land in China.

In view of problems of poor accuracy and dependence on source coordinates of existing underground positioning algorithm, an underground positioning method based on GMapping algorithm and fingerprint map construction was proposed. The signal characteristics of unknown position is matched with signal distribution map, and the optimal positioning coordinates is selected, thereby improving accuracy of the underground positioning; by combining with GMapping algorithm, problem of high maintenance cost of fingerprint map construction process is avoided, and searching and matching efficiency of the algorithm is optimized. Actual test results show that the average positioning error of the proposed method is 57.7 cm, which can meet requirements of underground positioning.

In view of problems of low illumination, a lot of dust and complex electromagnetic environment in coal mine underground, and images' quality captured by underground monitoring equipment would be reduced in transferring process caused by underground noises, an underground monitoring image sharpening device based on embedded system was designed. The device uses wavelet threshold algorithm and DSP embedded system, and it can effectively restrain noise, meanwhile keep details characteristics and peak point of original images, which greatly enhances monitoring image clarity.

Kraft lignin was hydrothermally depolymerized at low temperature/short time in water for producing value-added phenolics. The effects of residence time (15, 60 min) and reaction temperature (130, 180, 230ºC) on yields of oils and phenolic compounds were studied in detail. Total oil yield was found to range between 7% and 10%. The compositions of oils were analyzed by GC-MS to confirm the main compound to be guaiacol (2-methoxy phenol) in the range of 12–55% of oil depending on different reaction conditions. The most interesting was the finding that maximum value of total oil yield (10% of kraft lignin) and guaiacol amount (55% of oil) was obtained at 130ºC/15, 60 min which is a low reaction temperature/short time, while the residual kraft lignins were analyzed by FTIR with respect to the conversion mechanism of kraft lignin by this process.

Abstract An attempt has been made to selectively oxidise synthetic lignin-like polymer for fine chemicals. The G- and S-type polymers (G- and S- type lignin model polymers) were synthesized using simple aromatic compounds as starting materials and then oxidised to benzaldehydes by reacting them with Co(salen) catalytic system. The reaction was characterized by measuring the change of the polymer with FTIR, C-13 NMR and GC-MS spectroscopy. The results obtained by the FTIR and C-13 NMR showed that the effects of NaOH were important and higher yield of benzaldehydes characterized by GC-MS in the presence of NaOH in the course of catalytic oxidation of the polymer demonstrated these effects. From the results, the catalyst could suitably be used in green procedures for lignin transformation.

The reactivity of salen complexes toward hydrogen peroxide has been long recognized. Co(salen) was tested as catalyst for the aqueous oxidation of a refractory lignin-carbohydrate complex (LCC) isolated from sweet bamboo (Dendrocalamushamiltonii) in the presence of hydrogen peroxide as oxidant. Co(salen) catalyzed the reaction of hydrogen peroxide with LCC. From the spectra analyses, lignin units in LCC were undergoing ring-opening, side chain oxidation, demethoxylation, β-O-4 cleavage with Co(salen) catalytic oxidation. The degradation was also observed in the carbohydrate of LCC. The investigation on the refractory LCC degradation catalyzed by Co(salen) may be an important aspect for environmentally-oriented biomimetic bleaching in pulp and paper industry.

In view of problem that performance of RS485 bus will be decreased by underground complex electromagnetic environment, so as to influence data transmission of coal mine safety monitoring and control system, the paper indicated that it should make anti-interference design of RS485 bus through aspects of fault insurance circuit, electrical isolation, interface protection of anti-surge over-voltage and communication software programming, and gave implementation of the anti-interference design. The actual application showed that the anti-interference design can ensure stable running of data transmission of coal mine safety monitoring and control system.

In this paper, Co(salen) [salen = N, N’-bis(salicylidene)ethylenediamine] complex was studied as oxygen activators for the catalytic oxidation of a lignin model polymer using water as the solvent, with molecular oxygen and hydrogen peroxide as the oxidants. The effect of Co(salen) on oxidation was tested by spectroscopic methods (FTIR, 13C-NMR and GC-MS). The reactions catalysed by Co(salen) included Cα-alcohol oxidation, Cα-Cβ side chain cleavage, demethoxylation, aromatic ring cleavage, and β-O-4 cleavage. In addition to the mechanistic information obtained, the effect of Co(salen) suggests that Co(salen) can be important for the catalytic oxidation, as they affect the oxidation of lignin model polymer. The reaction performed in the presence of Co(salen) was more efficient than without it. The formation of aldehyde in the catalytic oxidation, as shown by GC-MS, could be identified as the mechanism of oxidative cleavage of the β-O-4 bonds.

Photoplethysmography (PPG) signal is potentially suitable in atrial fibrillation (AF) detection for its convenience in use and similarity in physiological origin to electrocardiogram (ECG). There are a few preceding studies that have shown the possibility of using the peak-to-peak interval of the PPG signal (PPIp) in AF detection. However, as a generalized model, the accuracy of an AF detector should be pursued on the one hand; on the other hand, its generalizability should be paid attention to in view of the individual differences in PPG manifestation of even the same arrhythmia and the existence of sub-types. Moreover, a binary classifier for atrial fibrillation and normal sinus rhythm is not convincing enough for the similarity between AF and ectopic beats. In this study, we project the atrial fibrillation detection as a multiple-class classification and try to propose a training pipeline that is advantageous both to the accuracy and generalizability of the classifier by designing and determining the configurable options of the pipeline, in terms of input format, deep learning model (with hyperparameter optimization), and scheme of transfer learning. With a rigorous comparison of the possible combinations of the configurable components in the pipeline, we confirmed that first-order difference of heartbeat sequence as the input format, a 2-layer CNN-1-layer Transformer hybridR model as the learning model and the whole model fine-tuning as the implementing scheme of transfer learning is the best combination for the pipeline (F1 value: 0.80, overall accuracy: 0.87)R.