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MgO-Y 2 O 3 :Eu composite ceramics with high quantum yield and excellent thermal performance were successfully synthesized by vacuum sintering. All samples exhibited uniform composite microstructures and pure binary phase. Eu3+ ions were completely incorporated into Y 2 O 3 phase, and the optimal Eu concentration is 15 at%. Sintered at 1800 °C, the fluorescent properties of MgO- z vol% Y 2 O 3 : Eu (z = 30, 40, 50, 60, 70, 100) composites proved to be independent on component proportion, including the similar fluorescence lifetimes (953–983 μs), quantum yield (70%−80%), and activation energy (ΔE) of thermal quenching (0.163 eV). Significantly, thermal conductivity of composites with 30 vol%, 50 vol% and 70 vol% MgO attained 11.58, 17.45, and 29.65 W/(m∙K) at room temperature, which are nearly 2, 3, and 5 times as high as that of 15 at% Eu:Y 2 O 3 ceramic (5.90 W/(m∙K)), respectively, demonstrating their potential for application in high-power-density display and lighting technology. [ABSTRACT FROM AUTHOR]

Transparent calcium oxide (CaO) ceramic was successfully fabricated by pressureless vacuum sintering technique with 0.5 at% YF 3 as the sintering additive. In consideration of the hydrolysis of CaO, the precursor powders were calcined at 600 °C. Within the sintering temperature range of 1150–1450 °C, the effect of YF 3 additive on the phase structure, relative density, transmittance, and microstructure of CaO ceramics was studied. Benefiting from the assisted liquid-phase sintering mechanism and vacancy diffusion mechanism of YF 3 , full-dense (3.35 g/cm3) YF 3 -doped CaO transparent ceramic was fabricated at 1350 °C with high thermal conductivity of 15.42 W/(m·K). The in-line transmittance attained 47.10% at the wavelength of 1200 nm. Moreover, the hydrolysis resistance was extremely enhanced due to the pore-free structure. Compared to the CaO ceramic with low relative density of 78.66%, the weight gain of full-dense CaO ceramic greatly decreased from 22% to 1.2% within 35 days. [ABSTRACT FROM AUTHOR]

Improper management practices lead to the reduction of phosphorus availability by rice and an increase in the risk of phosphorus release to the environment in paddy fields. This study aims at exploring the effects of biochar with the applicated rate of 0, 20, 40 t ha−1 under controlled or flooding irrigation on utilization efficiency of phosphorus fertilizer and phosphorus leaching loss from fields by observing the dynamics of phosphorus in paddy fields throughout the rice growing period. The results indicated that biochar application lessened the TP and DRP leaching loss by 6.77–17.62% and 6.22–10.28% respectively. It was also found that biochar improved the phosphorus efficiency of rice by 5.33–10.33%and reduced the soil phosphorus surplus by 3.45–6.66% for the increased soil Olsen-P concentration and soil solution dissolved reactive P concentration. In comparison with flooding irrigation, controlled irrigation apparently decreased P leaching loss by 34.64–55.15% by controlling the downward migration of phosphorus in soil solution. Although biochar addition in the field increased production cost, it was proved increasing net economic benefit by 2558–4655 yuan ha−1 y−1, which attributes to the increased rice yield in biochar applicated treatment. In order to improve phosphorus efficiency of rice and reduce the risk of phosphorus release to the environment, a combination of biochar and water-saving irrigation applied in rice fields can provide cleaner production of rice with a promising option, thus bringing both environmental and economic benefits. [Display omitted] • Dynamics of P in soil and soil solution were monitored in biochar applicated paddy field under water-saving irrigation. • Biochar application and water saving irrigation reduced P leaching loss from paddy field. • Biochar application increased P efficiency in water-saving paddy field. • Biochar drove the increase of available P content. [ABSTRACT FROM AUTHOR]

[Display omitted] • DNDC-BC was established on the water balance principle and two-pool biochar model. • DNDC-BC can model GHG, SOC and rice yield of paddy under CI and biochar. • DNDC-BC performed better in simulating GHG and soil moisture than the original one. • Coupling CI and biochar decrease CH 4 and N 2 O emissions, boost SOC and rice yield. • CH 4 and N 2 O emissions from CI paddy are most sensitive to rainfall and irrigation. Simulating the impacts of biochar and controlled irrigation (CI, a water-saving irrigation technology without surface ponding of water) combination on greenhouse gas (GHG) emissions from paddy fields is crucial, however, the original DNDC model is not capable of capturing these management impacts on emissions. In this study, we have created a new modelling approach called DNDC-Biochar-Controlled Irrigation (DNDC-BC) by adding two modules to the original DNDC: the water balance principle, and the two-pool biochar model. The performance of the DNDC-BC was tested and validated using a two-year field experiment, designed with two irrigation treatments (flood irrigation (FI), and CI) and three biochar application rates (0, 20, and 40 t ha−1), carried in the Lake Taihu region, China. Results revealed that the DNDC-BC model performed satisfactorily in simulating impacts of biochar-CI combination on emissions of CH 4 , N 2 O, SOC, and grain yield. The corresponding R2 values of DNDC-BC increased by 22.63%-35.66%, 43.00%-71.26%, 1.06%-60.87% and 15.38%-34.78% compared with those of the original model. Sensitivity analysis for the DNDC-BC showed that CH 4 emissions were most sensitive to rainfall and irrigation; N 2 O emissions were sensitive to rainfall, irrigation and N fertilizer application rate, and SOC was sensitive to biochar application rates. Our results suggest that the combination of biochar- and CI can save water resources and mitigate GHG emissions without detrimental impacts on rice yield. The DNDC-BC can be used to estimate the long-term impacts of biochar-CI combination on GHG emission, crop productivity and climate change. [ABSTRACT FROM AUTHOR]

Quantifying greenhouse gas (GHG) emissions from irrigated paddy fields is of great significance for addressing climate change. Machine learning (ML) provides an alternative to empirical models and biogeochemical models, but it has not been used to simulate GHG emissions from paddy fields. In this study, a three-year field experiment dataset of paddy fields under controlled irrigation (CI, a kind of water-saving irrigation (WSI) technology) and flood irrigation (FI) in Kunshan, China, was collected, as well as a global dataset on WSI and FI. Then, the stacking ensemble model was developed based on three basic ML models, random forest (RF), K-Nearest Neighbor regression (KNN), gradient boosting regression (GBR), and a meta-learner, linear Regression (LR). Those models were used for the first time to simulate CH 4 and N 2 O emissions on different time scales from paddy fields under WSI and FI. The results showed that the cumulative CH 4 and N 2 O emissions from the WSI paddy fields decreased by 61.14% and increased by 19.52%, respectively, compared with FI. The ML algorithm can be applied to simulate daily, growth stages, and cumulative GHG emissions from paddy fields, but the performance of the linear regression model was worse than other ML models. Compared with the basic models, the stacking model improved the accuracy, improving the R 2 by 0.37∼13.36% and reducing the RMSE by 3.23∼42.78%. Soil redox, temperature, and moisture are necessary for accurate modeling. Meanwhile, training the model using data from WSI and FI separately is beneficial to improve the accuracy of the model. The availability of the stacking model in other stations was verified based on literature data, with R 2 varying between 0.7634 and 0.9985. Therefore, the stacking model is recommended to predict GHG emissions at different time scales from paddy fields, and this method can be extended to estimate GHG from paddy fields at various stations around the world. [Display omitted] • Machine learning (ML) was used to predict CH4 and N2O emissions from paddy fields. • The stacking model was the best in modeling greenhouse gas at various time scales. • Soil redox, temperature, and moisture are necessary for accurate modeling. • Separate training for different irrigated paddy fields is recommended. • The simulation method can be extended to paddy fields in different places. [ABSTRACT FROM AUTHOR]

Yield and rice quality indicators of crops are a direct reflection of the rational irrigation and fertilizer strategy. However, the effects of controlled irrigation (CI) combined with the split application of fertilization managements (straw returning, organic fertilizer, and conventional fertilizer) on rice quality are not clear in southeast China. This study aims at exploring the effects of three fertilization managements applied under CI or flooding irrigation on rice yield, quality, enzyme activity, and soluble sugar content including 43 indicators, to determine the optimal comprehensive evaluation model, management, and representative indexes. The results showed that compared with CF (CI + conventional fertilizer), CS (CI + straw returning) significantly increased yield (27.65%), irrigation water use efficiency (6.20%), chalky grain rate (9.67%), chalkiness (1.83%), protein content (4.29%), and amylose content (0.33%), indicating that CS improved yield and milling quality but decreased cooking and appearance quality. This was mainly because CS promoted the activities of alpha-amylase, ADPG (ADP-glucose pyrophosphorylase), and GBSS (granule-bound starch synthase) and reduced the soluble sugar content in rice. Grey relational degree analysis (GRD), the entropy method (ETM), and TOPSIS (the technique for order preference by similarity to an ideal solution) were used to comprehensively evaluate the rice quality and determined that CS treatments could synergistically improve yield and rice quality. The five indexes (adhesive strength, HPV, ADPG, soluble sugar (leaf), yield) and TOPSIS model can be used as the best indexes and model to evaluate the rice quality. These results could provide scientific management and evaluate practices for high-yield and high-quality rice cultivation, which may be promising for a cleaner production strategy. [ABSTRACT FROM AUTHOR]

Accurate water level prediction is the premise of farmland waterlogging prediction. A simple water level prediction model (FDPRE) based on four machine learning (ML) algorithms and weather forecasts were developed. The model can not only predict two key driving factors of waterlogging, rainfall and node water level but also estimate disaster losses. The results showed that the random forest and Multiple perception model (R2 ranged from 0.7180 to 0.9803 and 0.5717 to 0.9965) performed best. In the case of flooding lasting for one day, the economic loss of waterlogging under the 100 mm rainfall scenario (23.53 million dollars) was much higher than that under the 50 mm rainfall (12.69 million dollars). Under the two rainfall scenarios, the yield reduction rate in the lower reaches of the Sihu basin was higher than that in the upper reaches. The method of coupling ML and weather forecasts can well predict farmland waterlogging. • FDPRE, a simple water level prediction model, was developed. • Farmland flood disaster was predicted on machine learning and weather forecast. • Random forest performed best among the four machine learning models at most sites. • The economic loss of waterlogging under 100 mm rainfall was much higher than 50 mm. [ABSTRACT FROM AUTHOR]

Biochar application (BA) and controlled irrigation (CI) can realize the resource utilization of biowaste and water respectively. Both BA and CI can affect soil carbon pool dynamics and greenhouse gas (GHG) emissions in paddy fields, but their synergistic effects and the microbial mechanism remain unclear. This study investigated the effects of BA on CO 2 exchange, GHG emissions, and soil microbial diversity of paddy fields under CI. BA increased soil respiration rate (R s) from CI paddy fields by 23.81%–41.45 %, possibly due to the increase of Curvibacter , while BA reduced global warming potential by 25.85%–37.84 %. The reduction of N 2 O emission under CI with BA may be attributed to the increase of Proteobacteria and the decrease of Nitrospira. CI decreased the net ecosystem exchange (NEE) and soil organic carbon but increased R s and dissolved organic carbon, compared with flood irrigation. Lactobacillus and Mortierella were dominant bacteria and fungi at milk stage. In addition, BA and CI mitigated CH 4 emissions and reduced the abundance of Russula. Both bacteria and fungi play important roles in soil carbon cycle, which is mainly affected by soil temperature, humidity, and ammonium. These results indicate that BA combined with CI is a promising cleaner production strategy to simultaneously improve soil health, mitigate GHG emission, and mediate soil microbial community structure. [Display omitted] • Biochar decreased the global warming potential by 25.85%–37.84 %. • Biochar reduced N 2 O emission via enriching Proteobacteria and reducing Nitrospira. • Biochar increased soil respiration by 23.81%–41.45 % via enriching Curvibacter. • Both biochar and controlled irrigation reduced Russula and mitigated CH 4 emissions. • Biochar decreased the abundance of Mortierella , thereby increased soil carbon pool. [ABSTRACT FROM AUTHOR]

Zero valent iron (ZVI) coupled with bioreactors is arising as a promising technology for antibiotic resistance genes (ARGs) mitigation, whereas the succession and behaviors of microbes caused by ZVI in relieving ARGs propagation remain unclear. Herein, the effects of ZVI on microbial quorum sensing (QS), quorum quenching (QQ) system and community dynamics were examined in anaerobic bioreactor fed with oxytetracycline (tet), to illustrate the roles of evolutive microbial communication and community composition in ARGs attenuation. With the addition of 5 g/L ZVI, the total absolute abundance of tet ARGs was retarded by approximate 95% and 72% in sludge and effluent after 25 days operation. The abundance of mobile genetic elements and the heredity of antibiotic resistant bacteria revealed the declined horizontal and vertical transfer of ARGs, which directly led to the reduced ARGs propagation. Potential mechanisms are that the positive effects of ZVI on QQ activity via the functional bacteria enrichment inhibited QS system and thus ARGs transfer. Partial least--squares path modeling further demonstrated that ARGs abundance was strongly limited by the dynamics of bacterial composition and thereby less frequent microbial communication. These results provide new insights into the mechanisms of antibiotic resistome remission in anaerobic bioreactor modified by ZVI. [Display omitted] • Zero valent iron could mitigate ARGs propagation in anaerobic bioreactor. • Horizontal transfer of ARGs and proliferation of resistant strains were suppressed. • The weakened bacterial communication led to decreased ARGs transfer. • The reduced potential host bacteria contributed to relieving ARGs dissemination. [ABSTRACT FROM AUTHOR]

Coordination of yield, quality and economic benefits increase remains an attractive problem in agricultural production. This study investigated how irrigation regimes could synergistically interact with different fertilization to increase irrigation water use efficiency (IWUE), yield, quality and output/input ratio in rice. A field experiment was conducted during 2020–2021 with three fertilization management (straw returning, organic fertilizer, conventional fertilizer) and two irrigation regimes (controlled irrigation (CI) and flood irrigation (FI)). This study reveals that CI reduced rice plant height (5.24% ∼ 11.99%), tiller number (9.52% ∼ 26.31%), SPAD (7.98% ∼ 15.83%), yield (9.12% ∼ 9.23%), and protein (4.85% ∼ 5.02%) compared to FI. Conversely, CI improved chalky grain rate (5.83% ∼ 8.52%), chalkiness (11.35% ∼ 14.68%), IWUE (51.01% ∼ 59.91%). CS (controlled irrigation + straw returning) and CM (controlled irrigation + organic fertilizer) significantly boosted rice quality and yield compared to CF (controlled irrigation + conventional fertilizer): setting rate increased by 20.23% (CS) and 18.20% (CM), yield rose by 19.43% (CS) and 19.83% (CM), and positive impacts were observed in polished rice rate, head milled rice rate, and protein content. However, both CS and CM led to reduced amylose content (0.35% and 1.06%) and taste value (0.82% and 3.25%). The study observed consistent interannual changes in straw returning, while variations were noted in organic fertilizer application. This difference was primarily attributed to the significant influence of temperature (with a 5.34 ℃ difference during the two years at the milky ripening stage). The analysis of economic benefits showed that the output/input ratio of CS was the highest, ranging from 2.69% to 2.88%. By employing the TOPSIS method, an integrated multi-index decision analysis approach, CS was identified as the optimal mode for rice in southern China. The study provides an optimal irrigation and fertilization model for the synergistic realization of water saving, high yield, high quality, economic benefits, and further achieves the goal of sustainable agricultural development. • Under controlled irrigation (CI), rice growth, yield, appearance and nutritional quality got worse. • CS (controlled irrigation + straw returning) could increase yield, milling, appearance and nutritional quality. • CM (controlled irrigation + organic fertilizer) can promote rice yield and quality, but unstable under climate influence. • The analysis of economic benefits shows that the output/input ratio of CS was the highest. • Using the TOPSIS method, the optimal management mode was determined as CS. [ABSTRACT FROM AUTHOR]

[Display omitted] • nZVI exposure increased the antibiotic resistome in anaerobic digestion. • Efflux pump and rRNA methyltransferase shaped the antibiotic resistome variation. • Improved adaptability of efflux pump benefited the anaerobes withstanding nZVI. • Increased acquisition of rRNA methyltransferase preserved the structure of protein. • Polyspecificity of multidrug resistance drove the ARGs evolution in anaerobes. Nano zero-valent iron (nZVI) assisted anaerobic digestion (AD) is considered an effective approach for mediating antibiotic resistance genes (ARGs) dissemination in activated sludge. However, little is known about the mechanisms that drive antibiotic resistomes evolution in relation with their physiological roles distinct from protection of bacteria against antimicrobials. Metagenomic sequencing showed that efflux pumps and rRNA methyltransferase genes were the most prevalent ARGs in anaerobes, being responsible for the variations of antibiotic resistome upon nZVI addition. Particularly, to withstand the oxidative stimuli derived from initially 9 days nZVI exposure, genes involved in the two component systems (PhoRB , BaeSR , EvgSA) and global regulator networks (MarA , SoxS) were increased, activating the chromosomally encoded intrinsic efflux pumps expression. Furthermore, to benefit for survival, the polyspecific efflux pumps were involved in the microbial physiological adaptations of enhanced siderophores, lipid moieties, and quorum sensing molecules exportation, which induced the adaptative efflux pumps expression. On the other hand, to maintain the protein synthesis under oxidative condition, genes encoding Rsm, Erm, and Rlu family methyltransferases were notably up-regulated via horizontal transfer, inducing the acquired rRNA methylation resistance. Importantly, after prolonged exposure to nZVI for 18 and 27 days, the antibiotic resistomes were measurably decreased, due to the recovered oxidative state and increased membrane rigidity. Overall, these findings provide a deep understanding on the necessity of antibiotic resistome evolution for anaerobes to adapt to nZVI exposure for survival, which can be introduced to improve the ARGs risks analysis. [ABSTRACT FROM AUTHOR]

To the Editors, VEXAS syndrome is a recently described entity in which an X-linked somatic mutation in I UBA1 i causes widespread inflammatory manifestations in older men, typically accompanied by a hematological disorder, particularly myelodysplastic syndromes [[2]]. Finally, a condition similar to adult-onset Still's disease, which shares both clinical and pathophysiological features with HLH, has been reported in several patients with VEXAS syndrome [[3], [11]]. Diagnosis of HLH in patients with VEXAS syndrome may be challenging due to pre-existing cytopenia and inflammatory manifestations. [Extracted from the article]

Noncontinuous flooding irrigation is an important means of reducing water use, mitigating greenhouse gas emission, and maintaining crop yield in rice production systems. Quantifying the CH 4 and N 2 O emissions in continuous and noncontinuous flooding irrigation systems is crucial to the exploration of sustainable water management practices in rice systems. In this study, a simple "anaerobic ball" method was incorporated into the WHCNS (soil Water Heat Carbon Nitrogen Simulator) model to simulate and evaluate the CH 4 and N 2 O emissions under continuous and noncontinuous flooding irrigation conditions. This model considers the processes of dissolved organic carbon (DOC) release and transport in the soil profile, CH 4 production, oxidation, and transport, and N 2 O production, reduction, and transport. Three years of field experiment data, including soil and environment variables (e.g., ponding water depth, soil water content, and soil temperature) and daily CH 4 and N 2 O emission fluxes under different irrigation practices were collected to test the improved WHCNS model. Results show that the model performs well in simulating soil and environment variables, with performance indices IA , NSE , and Pearson's r varying from 0.772 to 0.966, 0.530–0.853, and 0.780–0.934, respectively. Furthermore, the daily dynamics of CH 4 and N 2 O emissions were captured under different rice irrigation systems, with average IA , NSE , and Pearson's r values of 0.857, 0.476, and 0.763, respectively. The observed and simulated results indicate that noncontinuous irrigation reduces CH 4 emission but increases N 2 O emission. Compared with continuous flooding irrigation, noncontinuous flooding irrigation significantly decreased the accumulated CH 4 emission by 82.1%, but significantly increased the N 2 O emission by 129.4%, resulting in the global warming potential reduction of 23.5%. The improved model reflects the effects of continuous and noncontinuous flooding practices on CH 4 and N 2 O emissions, and exhibits great potential for the development of sustainable water management for rice production systems. [Display omitted] • A process-based model was developed to simulate GHG emission for continuous and noncontinuous flooding rice systems. • A simple "anaerobic ball" method was incorporated into WHCNS_Rice model for simulating CH 4 and N 2 O emission. • The model performed well in CH 4 and N 2 O emission for continuous and noncontinuous flooding rice systems. • Controlled irrigation significantly decreased the CH 4 emission by 82.1%, but increased N 2 O emission by 129.4%. • WHCNS_Rice model showed a great potential for developing sustainable water management to achieve a low GHG emission. [ABSTRACT FROM AUTHOR]