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Summary The anatomical reorganization required for C4 photosynthesis should also impact plant hydraulics. Most C4 plants possess large bundle sheath cells and high vein density, which should also lead to higher leaf capacitance and hydraulic conductance (Kleaf). Paradoxically, the C4 pathway reduces water demand and increases water use efficiency, creating a potential mismatch between supply capacity and demand in C4 plant water relations. Here, we use phylogenetic analyses, physiological measurements, and models to examine the reorganization of hydraulics in closely related C4 and C3 grasses. The evolution of C4 disrupts the expected positive correlation between maximal assimilation rate (Amax) and Kleaf, decoupling a canonical relationship between hydraulics and photosynthesis generally observed in vascular plants. Evolutionarily young C4 lineages have higher Kleaf, capacitance, turgor loss point, and lower stomatal conductance than their C3 relatives. By contrast, species from older C4 lineages show decreased Kleaf and capacitance. The decline of Kleaf through the evolution of C4 lineages was likely controlled by the reduction in outside‐xylem hydraulic conductance, for example the reorganization of leaf intercellular airspace. These results indicate that, over time, C4 plants have evolved to optimize hydraulic investments while maintaining the anatomical requirements for the C4 carbon‐concentrating mechanism. [ABSTRACT FROM AUTHOR]

The reliability of irrigated area (IA) information dominates the performance of irrigation water use and crop modeling accuracy. IA is typically mapped using Food and Agriculture Organization (FAO) agricultural census and remote sensing indices. Recent advances in machine learning and sampling techniques further improve IA mapping. However, the relative performances of different IA mapping approaches and their capability in capturing long‐term IA temporal variability remain unknown. Here, 1861 county‐level IA information from Government Censored Data (GCD) during 2000–2021 are collected, cross‐validated, and employed to evaluate commonly used gridded IA data sets. Results show that IA data sets based on the direct interpolation of FAO agricultural census can accurately capture the spatial distribution of IA. However, FAO statistics are only available in a particular year, which cannot capture inter‐annual irrigation variations. In contrast, IA products solely based on vegetation indices are prone to positive biases over humid regions due to the lack of contrast in vegetation dynamics. Overall, the latest GCD‐based machine learning IA data sets are relatively more accurate, but they are also problematic in estimating IA trends due to the use of temporally static training samples. Such biases are tightly related to agricultural suitability (AS calculated using precipitation and potential evapotranspiration). This suggests that AS should be employed as an endogenous variable in future machine learning based IA mapping algorithms. Plain Language Summary: Understanding how much land is irrigated (Irrigated Area or IA) is crucial for accurate water use and crop modeling. Traditional IA maps are developed using data from the Food and Agriculture Organization (FAO) and remote sensing indices. Recent improvements, like machine learning, have enhanced IA mapping. However, the relative performances of these methods and their reliability in capturing long‐term changes in irrigated areas remain unknown. This study collects government‐censored county‐level IA data from 2000 to 2021, which is subsequently used for evaluating commonly used IA data sets. Results show that data sets directly using FAO data can reasonability capture the spatial distribution of IA but may miss year‐to‐year changes. On the other hand, data sets relying only on vegetation data tend to overestimate irrigated areas in humid regions. The latest machine learning‐based IA data sets are relatively more accurate but still contain significant uncertainties in IA trends. These biases are closely linked to agricultural suitability (calculated using precipitation and potential evapotranspiration), which may be useful for enhancing future IA mapping algorithms. Key Points: Remote sensing vegetation index is insufficient for identifying irrigated area over humid regionsMachine learning based irrigated area is sensitive to the quality of training sampleAll the irrigated area data sets are biased in representing the temporal dynamics of irrigated area [ABSTRACT FROM AUTHOR]

Objectives: To explore the mediating role of self‐esteem in social anxiety and QoL during the COVID‐19 local epidemic in China. Design: A cross‐sectional survey. Methods: This study conveniently selected 344 hypertensive patients from a Grade‐A tertiary hospital in Wuhu, Anhui Province, as the study population. Participants completed the demographic questionnaire, the social phobia inventory, the self‐esteem scale and the 36‐item short‐form health survey. Results: Social anxiety, self‐esteem and QoL were significantly correlated with each other. Social anxiety showed no direct effect on QoL (β = 0.011, p > 0.05). Social anxiety showed an indirect effect on QoL (β = −0.248, p < 0.001). Self‐esteem fully mediated the association between social anxiety and QoL in hypertensive patients. Patient or Public Contribution: Hypertensive patients in this study were participants during the data collection process. Nursing staff from the cardiology department at the hospital of a hospital in Wuhu City, Anhui Province assisted in the recruitment phase of the data collection process. [ABSTRACT FROM AUTHOR]

Aims: To investigate loneliness, depression and sleep quality in patients with Type 2 Diabetes (T2DM) and to examine the mediating role of depression between loneliness and sleep quality among this group of patients with T2DM. Design: A cross‐sectional study. Methods: A group of T2DM patients was recruited from a tertiary hospital affiliated with a university in Wuhu City, Anhui Province from May to October 2021 by convenient sampling. Pearson correlation analysis and structural equation modelling were used for data analysis in this study. Results: The direct effect of loneliness on sleep quality was not statistically significant, but the indirect effect of depression on sleep quality was statistically significant. Depression mediated the relationship between loneliness and sleep quality. Depression can affect emotional health and reduce sleep quality. We should reduce the loneliness of patients, prevent the occurrence of depression and improve the quality of sleep. [ABSTRACT FROM AUTHOR]

Frequency‐adaptive prefilters are widely used in the phase‐locked loop (PLL) to suppress input disturbances. However, the parameters of the PLL and prefilters are often designed separately or based on an inaccurate model. The positive feedback effect introduced by the frequency adaption (FA) is usually ignored, leading to non‐optimal performance. Based on the accurate small‐signal model with a particular focus on the FA, this paper proposes an optimal design method for these advanced PLLs. The PLL based on dual second‐order generalized integrator (DSOGI) is taken as an example to demonstrate the principle. With different gain margins, the optimal damping factors of DSOGI and PLL, as well as the natural frequency of PLL, are obtained using the proposed method. Then the global optimal parameters are obtained by evaluating the settling time and overshoot. The analysis shows that the truly optimal parameters are quite different with those provided in the literature, and the dynamic performance is significantly enhanced without degrading the steady‐state performance. Experimental results are presented to verify the theoretical analysis. [ABSTRACT FROM AUTHOR]

Each of >20 independent evolutions of C4 photosynthesis in grasses required reorganization of the Calvin–Benson‐cycle (CB‐cycle) within the leaf, along with coordination of C4‐cycle enzymes with the CB‐cycle to maximize CO2 assimilation. Considering the vast amount of time over which C4 evolved, we hypothesized (i) trait divergences exist within and across lineages with both C4 and closely related C3 grasses, (ii) trends in traits after C4 evolution yield the optimization of C4 through time, and (iii) the presence/absence of trends in coordination between the CB‐cycle and C4‐cycle provides information on the strength of selection. To address these hypotheses, we used a combination of optimality modelling, physiological measurements and phylogenetic‐comparative‐analysis. Photosynthesis was optimized after the evolution of C4 causing diversification in maximal assimilation, electron transport, Rubisco carboxylation, phosphoenolpyruvate carboxylase and chlorophyll within C4 lineages. Both theory and measurements indicated a higher light‐reaction to CB‐cycle ratio (Jatpmax/Vcmax) in C4 than C3. There were no evolutionary trends with photosynthetic coordination between the CB‐cycle, light reactions and the C4‐cycle, suggesting strong initial selection for coordination. The coordination of CB‐C4‐cycles (Vpmax/Vcmax) was optimal for CO2 of 200 ppm, not to current conditions. Our model indicated that a higher than optimal Vpmax/Vcmax affects assimilation minimally, thus lessening recent selection to decrease Vpmax/Vcmax. Summary Statement: When C4 evolved in grass lineages affects the current optimization of photosynthetic traits, with two exceptions: 1. the coordination between light reactions, Calvin‐Benson and C4 cycles shows no evolutionary trend, suggesting strong initial selection for tight coordination, and 2. The coordination between Calvin‐Benson and C4 cycle is optimal for CO2 of 200 ppm, as opposed to current CO2. [ABSTRACT FROM AUTHOR]

Summary: A three‐dimensional, two‐phase, non‐isothermal proton exchange membrane (PEM) water electrolyzer model was developed, aiming to reveal water and heat distribution characteristics and to explore the effects of various parameters on heat and mass transfer and performance of the electrolyzer. The results show that the electrolyzer performance depends on the combined effect of heat and mass, especially at high voltages. Although increasing the inlet velocity can accelerate the discharge of bubbles, it causes a larger temperature drop which degrades the performance. Increasing the inlet temperature can effectively improve the kinetic reaction rate of the catalyst layer and reduce the ohmic resistance of the membrane, which promotes the performance improvement. Decreasing the contact angle of anode gas diffusion layer (A‐GDL) and increasing its porosity is beneficial to the transport of liquid water and improves the performance, but excessive porosity leads to a rapid increase in the ohmic resistance of A‐GDL, and the optimal porosity range is 0.5 to 0.6. In addition, changes in A‐GDL porosity and contact angle have little effect on temperature. Decreasing the thickness of the membrane can significantly improve the performance, but accelerate the increase of the membrane temperature at high voltage. [ABSTRACT FROM AUTHOR]

Transition‐metal sulfides have gained considerable attention for the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) in rechargeable Zn‐air batteries owing to their natural abundance, chemical stability, and efficient activity. Here, cobalt sulfide nanocrystalline supported on the 3D hierarchically flower‐like porous nanocarbon (mC‐CoSx‐50) electrocatalysts have been synthesized through a combination of metal‐organic complexation and porous silica templates for efficient bifunctional oxygen catalysis. With the high specific surface area, high nitrogen content and heteroatom doping, the as‐synthesized mC‐CoSx‐50 exhibits an excellent bifunctional oxygen catalytic performance. Remarkably, the rechargeable Zn‐air batteries assembled with the cobalt sulfide‐based hierarchically porous electrocatalysts reveal a high peak power density and excellent cycling stability in comparison with Pt/C+RuO2 owing to the synergistic effects between cobalt sulfide nanocrystallines and hierarchically porous carbon. We envision that this work not only offers high‐performance metal sulfide for future clean energy conversion but also provides a facial strategy for constructing hierarchically porous carbon‐supported catalyst. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM) recurrence is attributed to the presence of therapy‐resistant glioblastoma stem cells. Steroid receptor coactivator‐1 (SRC‐1) acts as an oncogenic regulator in many human tumors. The relationship between SRC‐1 and GBM has not yet been studied. Herein, we investigate the role of SRC‐1 in GBM. In this study, we found that SRC‐1 expression is positively correlated with grades of glioma and inversely correlated with glioma patient's prognosis. Steroid receptor coactivator‐1 promotes the proliferation, migration, and tumor growth of GBM cells. Notably, SRC‐1 knockdown suppresses the stemness of GBM cells. Mechanistically, long noncoding RNA X‐inactive specific transcript (XIST) is regulated by SRC‐1 at the posttranscriptional level and mediates the function of SRC‐1 in promoting stemness‐like properties of GBM. Steroid receptor coactivator‐1 can promote the expression of Kruppel‐like factor 4 (KLF4) through the XIST/microRNA (miR)‐152 axis. Additionally, arenobufagin and bufalin, SRC small molecule inhibitors, can reduce the proliferation and stemness of GBM cells. This study reveals SRC‐1 promotes the stemness of GBM by activating the long noncoding RNA XIST/miR‐152/KLF4 pathway and provides novel markers for diagnosis and therapy of GBM. [ABSTRACT FROM AUTHOR]

A new series of 4‐hexyl‐4H‐thieno[3,2‐b]indole (HxTI) based organic chromophores is developed by structural engineering of the electron donor (D) group in the D–HxTI–benzothiadiazole‐phenyl‐acceptor platform with different fluorenyl moieties, such as unsubstituted fluorenyl (SGT‐146) and hexyloxy (SGT‐147), decyloxy (SGT‐148) and hexyloxy‐phenyl substituted (SGT‐149) fluorenyl moieties. In comparison to a reference dye SGT‐137 with a biphenyl‐based donor, the effects of the donating ability and bulkiness of the fluorenyl based donor in this D–π–A‐structured platform on molecular properties and photovoltaic performance are investigated to establish the structure–property relationship. The photovoltaic performance of dye‐sensitized solar cells (DSSCs) is improved according to the bulkiness of the donor groups. As a result, the DSSCs based on SGT‐149 show high power conversion efficiencies (PCEs) of 11.7% and 10.0% with a [Co(bpy)3]2+/3+ (bpy = 2,2′‐bipyridine) and an I−/I3− redox electrolyte, respectively. Notably, the co‐sensitization of SGT‐149 with a SGT‐021 porphyrin dye by utilizing a simple "cocktail" method, exhibit state‐of‐the‐art PCEs of 14.2% and 11.6% with a [Co(bpy)3]2+/3+ and an I−/I3− redox electrolyte, respectively. [ABSTRACT FROM AUTHOR]

Dye-Sensitized Solar Cells: 14.2% Efficiency Dye-Sensitized Solar Cells by Co-sensitizing Novel Thieno[3,2-b]indole-Based Organic Dyes with a Promising Porphyrin Sensitizer (Adv. Keywords: co-sensitization; dye-sensitized solar cells; D- -A structure; organic dyes; structure-performance relationship EN co-sensitization dye-sensitized solar cells D- -A structure organic dyes structure-performance relationship 1 1 1 04/23/20 20200421 NES 200421 In article number 2000124, Hwan Kyu Kim and co-workers develop a series of highly efficient organic dyes and a simple co-sensitization method for dye-sensitized solar cells with state-of-the-art efficiency. Co-sensitization, dye-sensitized solar cells, D- -A structure, organic dyes, structure-performance relationship. [Extracted from the article]