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The rapid advancement in science, technology, and information over the past decades has led to a wide application of intelligent irrigation technologies worldwide. Using the multi-faceted approach, we analyze the past trajectory and future perspective of intelligent irrigation technologies by depth-examination of theoretical and engineering research as well as the granted patent applications over the past decades. The data used in the analysis were based on the publications indexed by Science Citation Index of Web of Science and Engineering Index (EI) of Scopus, as well as granted patents indexed in Derwent Innovations. This paper focused on performance index, competitiveness, research hotspots, and developing trend of intelligent irrigation. The results show that intelligent irrigation has well steadily established worldwide in terms of its perception, control, decision-making and management. In addition, six research areas have emerged over the past decades: irrigation technologies under drought stress, field experiments and water and fertilizer use efficiency, monitoring soil and water, intelligent irrigation systems, sustainable development and water-saving irrigation, and water balance and irrigation water management. Technologically, there are two active research areas in intelligent irrigation: real-time irrigation control and developing water-saving intelligent irrigation devices. Looking ahead, research in intelligent irrigation is expected to be in sustainability and scalability, as well as its combinations with other technologies. It has potential to safeguard food security and revitalize rural regions worldwide.

【Background and Objective】 Pepper is a shallow-rooted cash crop characterized by high leaf area index (LAI) and stomatal conductivity. It is sensitive to soil water change, and excessive or insufficient irrigation could thus inhibit its development, resulting in a decrease in yield and fruit quality. Reducing irrigation amount at different growth stages to maintain soil moisture at optimal levels has been posited as an improved cultivation method to improve yield and quality of the pepper. This paper aims to investigate the effect of water deficit at different growth stages on growth, yield and quality of chili pepper in the middle and low reaches of the Yellow River. 【Method】 The experiment was conducted in a solar greenhouse in Xinxiang, Henan province, with the pepper irrigated by drip irrigation. Three water deficits were imposed at flowering-fruiting stage (K) and fruiting stage (J) at different levels: severe water deficit by keeping the soil moisture content at 55%-65% of the field capacity (K1 and J1), moderate water deficit by keeping soil moisture content at 65%-75% of the field capacity (K2 and J2), sufficient irrigation by keeping soil moisture content at 75%-85% of the field capacity (K3 and J3). In each treatment, we measured plant height, stem diameter, yield and fruit quality of the pepper. 【Result】 ① Water deficit in reproductive stage reduced plant height and stem diameter of the pepper, while a moderate water deficit in flowering-fruiting stage and fruiting stage did not significantly affect plant height and stem diameter. ② The combination of K2 and J3 increased the yield of the pepper, promoted formation of marketable fruits. Compared with the combination of K3 and J3, the combination K2+J3 increased the yield of marketable fruits by 18.9%. ③ The combination of K2 and J3 had the highest soluble sugar content; the combination of K1 and J1 gave the highest dihydrocapsaicin content; the combination of K2 and J2 had the highest capsaicin, soluble protein, and vitamin C content. 【Conclusion】 A moderate water deficit during the flowering - fruiting stage combined with a sufficient irrigation at fruiting stage can improve yield and fruit quality for the greenhouse chili pepper.

Extracellular vesicles (EVs) are nanosized particles that are released by various cell types and play vital roles in intercellular communication. They carry biological molecules reflecting the physiological and pathological states of their source cells and tissues, showing potential as biomarkers. However, the impact of demographic factors like age and sex on the properties of blood plasma EVs remains underexplored. This study aims to fill this gap by evaluating how these factors influence the particle count and proteomic profiles of plasma EV preparations and corresponding protein fractions. Plasma samples from 120 healthy volunteers were collected and pooled into six groups: young males (age: 27.6 ± 4.0), young females (27.4 ± 3.8), middle‐aged males (48.8 ± 3.8), middle‐aged females (48.9 ± 3.9), old males (69.3 ± 3.9), and old females (69.4 ± 4.3). EV‐ and protein‐enriched fractions were separated by size‐exclusion chromatography (SEC). Fractions were characterized for particle number concentration and protein composition to identify characteristics affected by age and biological sex. Plasma EVs and corresponding protein fractions exhibited distinct characteristics, with differential enrichment of markers related to EVs and other blood components, including lipoproteins. Proteomic profiles of both EVs and protein fractions displayed sex‐ and age‐dependent differences. Differentially abundant proteins displayed functions previously identified in the context of aging and sex differences, highlighting their utility as biomarkers. Age and sex significantly affect the characteristics of plasma EVs and proteins, potentially influencing their efficacy and interpretation as biomarkers in clinical applications. This study lays the groundwork for detailed mechanistic research to understand how EVs mediate age‐ and sex‐related effects in health. [ABSTRACT FROM AUTHOR]

Collaborative conversion of methane and carbon dioxide into sustainable chemicals is an appealing solution to simultaneously overcome both environmental problems and energy crisis. However, this reaction is limited to the preparation of syngas with the unfavorable feature for transportation and storage. Herein, liquid formaldehyde as product is fabricated by the collaborative conversion of methane and carbon dioxide using anatase phase titanium dioxide as photocatalyst. The productivity reaches 14.65 mmol g−1 with 88.32% selectivity. In situ diffuse reflectance Fourier transform infrared spectroscopy, isotope testes, and theoretical calculation clarify that the photoexcited holes and electrons engage into methane oxidation and carbon dioxide reduction over anatase using surface hydroxyl species and oxygen vacancy as active sites, respectively. The consumption of surface hydroxyl species on methane oxidation promotes the oxygen vacancy formation for carbon dioxide adsorption, mutually the carbon dioxide provides the oxygen atom for surface hydroxyl species facilitating methane oxidation. The consumption of photoelectrons and photoholes on carbon dioxide reduction and methane oxidation balances the number of photogenerated carriers and ensures the catalytic system stability. In this work, the avenue is broadened toward the co‐conversion of greenhouse gas into desirable chemical products in a sustainable way. [ABSTRACT FROM AUTHOR]

As living standards rise, enhancing quality has become a central objective for many researchers. Soilless cultivation, known for its efficient use of resources, is increasingly used in vegetable production. It is critical to develop effective water and fertilizer management strategies to achieve high-quality yields and promote sustainable development in modern agriculture. This study employed an orthogonal experimental design to assess the impact of varying nutrient solution concentrations (50%, 75%, 100%, and 125% of Hoagland's), lower irrigation thresholds (40%, 55%, 70%, and 85% field capacity (FC)), and ozone concentrations (0, 1, 2, and 4 mg·L−1) on lettuce growth, yield, quality, and water–fertilizer use efficiency. The results indicated that fixed nutrient solution concentrations and lower irrigation thresholds enhanced growth metrics for lettuce. Similarly, increasing ozone concentrations initially improved, then reduced growth metrics when the lower irrigation threshold was constant. Furthermore, maintaining stable ozone concentrations while raising the nutrient solution concentration initially boosted, then diminished, growth indicators. Optimal conditions for water and fertilizer management were identified at a nutrient solution concentration of 75% to 100% and an ozone concentration of 0 to 1 mg·L−1. Variance analysis highlighted the significant effects of nutrient solution concentration, lower irrigation thresholds, and ozone concentrations on lettuce yield, quality, and water and fertilizer use efficiency. Range analysis revealed the optimal management combination to be a nutrient solution concentration of 100%, an 85% lower FC irrigation threshold, and an ozone concentration of 1 mg·L−1, yielding 16.82 t·ha−1 of lettuce and a water use efficiency of 40.14 kg·m−3. These findings provide theoretical support for the sustainable advancement of soilless cultivation in contemporary agriculture. [ABSTRACT FROM AUTHOR]

The average winding temperature of a transformer (AWTT), serving as a key indicator for assessing the running state of the transformer, is of utmost importance in determining a transformer's electrical properties and the insulation longevity of the transformer. An accurate prediction of AWTT is essential for ensuring the safe operation of the transformer. A novel method for predicting AWTT is introduced based on the analysis of field monitoring data. Firstly, the thermal characteristics and operational mechanisms of oil-immersed transformers are examined. Secondly, a factor analysis model is developed to streamline the network structure, accounting for the strong correlations among ambient temperature, load current, and top oil temperature. Thirdly, the independent temperature factor and load factor are extracted as pivotal features, and then input into the fully connected neural network to predict AWTT. Through a case study involving a 110 kV/10 kV oil-immersed transformer, the results show that the proposed method reduces redundant correlation information compared to traditional methods and improves the prediction accuracy of AWTT, establishing a foundation for further transformer state assessments. [ABSTRACT FROM AUTHOR]