Brønsted acid catalyzed Ficini [2 + 2] cycloaddition of ynamides with enones.

Herein, we describe a novel metal-free Brønsted acid-catalyzed Ficini [2 + 2] cycloaddition of ynamides with enones under mild reaction conditions, leading to the formation of various cyclobutenamides in generally good to excellent yields within short reaction times. This work represents the first example of ynamides involved in a nonmetal-catalyzed [2 + 2] cycloaddition with enones.

Evolutionary trends and analysis of the driving factors of Ulva prolifera green tides: A study based on the random forest algorithm and multisource remote sensing images.

Understanding the prolonged spatiotemporal evolution and identifying the underlying causes of Ulva prolifera green tides play pivotal roles in managing such occurrences, restoring water ecology, and fostering sustainable development in marine ecosystems. Satellite remote sensing represents the primary choice for monitoring Ulva prolifera green tides due to its capability for extensive, long-term ocean monitoring. Based on multi-source remote sensing images, ecological and environmental datasets, and machine learning algorithms, therefore, this study focused on "remote sensing modelling - evolution history - change trends - mechanism analysis" to elucidate both the remote sensing monitoring models and the underlying driving factors governing the spatiotemporal evolution of Ulva prolifera green tides in the highly impacted South Yellow Sea of China. With the use of GOCI Ⅰ/Ⅱ images, an hybrid remote sensing extraction model merging the robustness of the random forest (RF) model and the optical algae cloud index (ACI) was established to map Ulva prolifera distribution patterns. The ACI-RF method exhibited exceptional performance, with an F1 score surpassing 0.95, outperforming alternative methods such as the support vector machine (SVM) and K-nearest neighbour (KNN) methods. On the basis, we analysed the evolutionary trends and the driving factors determining these distribution patterns using meteorological data, runoff data, and data on various water quality parameters (SST, ocean current speed, wind speed, precipitation, DO, PAR, Si, NO3-, PO43-and N/P). Over the period from 2011 to 2022, excluding 2021, there was a notable decline in the area of Ulva prolifera green tides, varying between 397 and 2689.9 km2, with an average annual reduction rate of 3%. The maximum annual biomass varied between 0.12 and 15.9 kt. Notably, more than 75% of the area of Ulva prolifera green tides exhibited northward drift, which was significantly influenced by northern currents and wind fields. The analysis of driving factors indicates that factors such as average sea surface temperature, eastward wind speed, northward wind speed, precipitation, PO43- and N/P/Si significantly influence the biological growth rate of Ulva prolifera. Furthermore, coastal land use change and surface runoff, particularly surface runoff in June, significantly impacted the growth rate of Ulva prolifera, with Pearson correlation coefficients of 0.74 and 0.67, respectively. Against the background of global warming and severe deterioration in the marine environment, Ulva prolifera blooms persist. Consequently, two distinct management strategies were proposed based on the distribution patterns and cause analysis results for addressing Ulva prolifera green tides: establishing a continuous protection framework for rivers, lakes, and nearshore areas to mitigate pollutant inputs and implementing precise environmental monitoring measures in urban expansion areas and farmlands to combat overgrowth-induced green tides. This methodology could be applied in other regions affected by marine ecological disasters, and the criteria for selecting influencing factors offer a valuable reference for designing tailored and proactive measures aimed at controlling Ulva prolifera green tides.

Annulations of Ynamides with 1,2-Benzisothiazoles to Construct 1,4-Benzothiazepines and 3-Aminoisoquinolines.

Two distinct TMSOTf-catalyzed annulation reactions between ynamides and 1,2-benzisothiazoles have been developed. The direction of the reaction could be easily switched by applying different thermodynamic-controlled conditions. At room temperature, ynamides undergo a [5 + 2] annulation reaction with 1,2-benzisothiazoles to afford 1,4-benzothiazepines, whereas under heating conditions a desulfurizative annulation reaction proceeds well to access 3-aminoisoquinolines. These two protocols provide biologically important 1,4-benzothiazepines and 3-aminoisoquinolines with high efficiency with broad substrate scopes under mild reaction conditions.

Remote sensing retrieval and driving analysis of phytoplankton density in the large storage freshwater lake: A study based on random forest and Landsat-8 OLI.

Remote sensing monitoring of seasonal changes in phytoplankton density and analyses of the driving factors of phytoplankton densities are necessary for assessing the health of aquatic ecosystems, controlling lake eutrophication, and formulating ecological restoration policies. Building upon the satellite-ground synchronization experiment that involves the in situ aquatic ecological monitoring conducted in Nansi Lake, which is the largest storage lake situated along the eastern route of the South-to-North Water Diversion Project, we developed a phytoplankton density retrieval model utilizing the random forest (RF) method and Landsat-8 OLI data. On this basis, we mapped the seasonal fluctuations and spatial disparities in the phytoplankton densities from 2013 to 2023. Subsequently, we conducted a detailed analysis of the driving factors and considered both the natural and anthropogenic aspects. The results indicate that (1) the RF model, when utilizing three band combinations, yielded favorable results with R2, RMSE and MAE values of 0.67, 1.31 × 106 cells/L and 1.18 × 106 cells/L, respectively. (2) The phytoplankton densities exhibited both seasonal and spatial variations, with higher concentrations in summer and autumn than in spring and winter. Significantly, the northwestern region of Zhaoyang Lake and the southeastern region of Weishan Lake had substantially greater phytoplankton densities than did the other areas. Furthermore, overarching upward trends were observed from 2013 to 2023, reflecting an annual rate of increase of 3.32%. (3) An analysis of the causal factors indicated that temperatures and gross agricultural production levels are the primary drivers influencing the seasonal variations and distributions of phytoplankton densities. In the future, we will delve into the potential of deep learning and utilize various satellite sensors to explore the intricacies of phytoplankton monitoring, as well as the complex mechanisms that influence aquatic ecological health.

TMSOTf-Catalyzed Reactions of N-Arylynamides with Sulfilimines To Construct 2-Aminoindoles and α-Arylated Amidines.

Here, we disclose an efficient TMSOTf-catalyzed C-H annulation of aryl-terminated N-arylynamides with sulfilimines, leading to the practical assembly of various valuable 2-aminoindoles in generally moderate to excellent yields with a broad range of functional groups, while nonaryl terminated N-arylynamides undergo TMSOTf-catalyzed aminative arylation with sulfilimines providing α-arylated amidines.

A novel multivariate time series prediction of crucial water quality parameters with Long Short-Term Memory (LSTM) networks.

Intelligent prediction of water quality plays a pivotal role in water pollution control, water resource protection, emergency decision-making for sudden water pollution incidents, tracking and evaluation of water quality changes in river basins, and is crucial to ensuring water security. The primary methodology employed in this paper for water quality prediction is as follows: (1) utilizing the comprehensive pollution index method and Mann-Kendall (MK) trend analysis method, an assessment is made of the pollution status and change trend within the basin, while simultaneously extracting the principal water quality parameters based on their respective pollution share rates; (2) employing the spearman method, an analysis is conducted to identify the influential factors impacting each key parameter; (3) subsequently, a water quality parameter prediction model, based on Long Short-Term Memory (LSTM) analysis, is constructed using the aforementioned driving factor analysis outcomes. The developed LSTM model in this study showed good prediction performance. The average coefficient of determination (R2) of the prediction of crucial water quality parameters such as total nitrogen (TN) and dissolved oxygen (DO) reached 0.82 and 0.86 respectively. Additionally, the error analysis of WQI prediction results showed that >75% of the prediction errors were in the range of 0-0.15. The comparative analysis revealed that the LSTM model outperforms both the random forest (RF) model in time series prediction and demonstrates superior robustness and applicability compared to the AutoRegressive Moving Average with eXogenous inputs model (ARMAX). Hence, the model developed in this study offers valuable technical assistance for water quality prediction and early warning systems, particularly in economically disadvantaged regions with limited monitoring capabilities. This contribution facilitates resource optimization and promotes sustainable development.

Topotactic synthesis of high-entropy sulfide nanosheets as efficient pre-catalysts for water oxidation.

Herein, quinary CoFeNiCuCr sulfide nanosheets with a high-entropy feature and rough surface were fabricated via a topotactic transformation pathway from high-entropy layered metal hydroxides, and display facile pre-oxidation and improved intrinsic activity towards the robust oxygen evolution reaction.

Lattice-disordered high-entropy metal hydroxide nanosheets as efficient precatalysts for bifunctional electro-oxidation.

Electro-oxidation reactions (EORs) are important half reactions in overall and assisted water electrolysis, which are crucial in achieving economic and sustainable hydrogen production and realizing simultaneous wastewater treatment. Current studies indicate that the high-valence metal ions that are locally enriched in the catalysts or generated in situ during the anodic preoxidation process are active species for EORs. Hence, designing (pre)catalysts with enriched local active sites and boosted preoxidation is of great importance. In this work, with a focus on improving the EOR performance toward the oxygen evolution reaction (OER) and the urea oxidation reaction (UOR), we fabricated a lattice-disordered high-entropy FeCuCoNiZn hydroxide nanoarray catalyst that exhibits robust bifunctional OER and UOR behavior. The high-entropy feature could bring in a unique catalytic ensemble effect and remarkably improve the intrinsic OER/UOR activity. The lattice-disordered structure could not only enrich the local high-valence metal ions as active sites but also provide abundant reactive surface sites to accelerate the preoxidation process, thus leading to enriched active sites for the OER and UOR. Benefitting from the structural merits, the lattice-disordered high-entropy catalyst exhibits excellent OER and UOR activity with low overpotential, large current density and enhanced intrinsic activity, and no performance degradation but dramatic 35.3% and 88.7% enhancement in activity can be achieved during the long-term OER and UOR tests, respectively. The robust OER and UOR performance makes the lattice-disordered high-entropy catalyst a promising candidate for overall and urea-assisted water electrolysis from industrial, agricultural and sanitary wastewater.

Two-stage neural network via sensitivity learning for 2D photonic crystal bandgap maximization.

We propose a two-stage neural network method to maximize the bandgap of 2D photonic crystals. The proposed model consists of a fully connected deep feed-forward neural network (FNN) and U-Net, which are employed, respectively, to generate the shape function and learn the sensitivity. The shape is generated by the FNN during the entire optimization process, and obtaining the sensitivity can be split into two steps. In the first step of the optimization, the sensitivity is calculated by finite element analysis (FEA) and the result is used as a sample to train the U-Net. Second, the optimization procedure is adopted instead of FEA, where a trained U-Net is used to generate the corresponding sensitivity. The main advantage of such an approach is that the shape function and sensitivity can be obtained by neural networks without solving a partial differenital equation. Therefore, the computational cost can be reduced by the proposed method without using large training sets. The effectiveness of the proposed method is verified in the numerical experiments in terms of the optimized shape and time consumption.

Remote Sensing Evaluation of Total Suspended Solids Dynamic with Markov Model: A Case Study of Inland Reservoir across Administrative Boundary in South China.

Accurate and quantitative assessment of the impact of natural environmental changes and human activities on total suspended solids (TSS) concentration is one of the important components of water environment protection. Due to the limits of traditional cross-sectional point monitoring, a novel water quality evaluation method based on the Markov model and remote sensing retrieval is proposed to realize the innovation of large-scale spatial monitoring across administrative boundaries. Additionally, to explore the spatiotemporal characteristics and driving factors of TSS, a new three-band remote sensing model of TSS was built by regression analysis for the inland reservoir using the synchronous field spectral data, water quality samples and remote sensing data in the trans-provincial Hedi Reservoir in the Guangdong and Guangxi Provinces of South China. The results show that: (1) The three-band model based on the OLI sensor explained about 82% of the TSS concentration variation (R2=0.81, N=34,  p value<0.01) with an acceptable validation accuracy (RMSE=6.24 mg/L,MRE=18.02%, N=15), which is basically the first model of its kind available in South China. (2) The TSS concentration has spatial distribution characteristics of high upstream and low downstream, where the average TSS at 31.54 mg/L in the upstream are 2.5 times those of the downstream (12.55 mg/L). (3) Different seasons and rainfall are important factors affecting the TSS in the upstream cross-border area, the TSS in the dry season are higher with average TSS of 33.66 mg/L and TSS are negatively correlated with rainfall from upstream mankind activity. Generally, TSS are higher in rainy seasons than those in dry seasons. However, the result shows that TSS are negatively correlated with rainfall, which means human activities have higher impacts on water quality than climate change. (4) The Markov dynamic evaluation results show that the water quality improvement in the upstream Shijiao Town is the most obvious, especially in 2018, the improvement in the water quality level crossed three levels and the TSS were the lowest. This study provided a technical method for remote sensing dynamic monitoring of water quality in a large reservoir, which is of great significance for remediation of the water environment and the effective evaluation of the river and lake chief system in China.

Loss characteristics of Cd in soil aggregates under simulated rainfall conditions.

Soil particles exert a significant influence on the migration of heavy metals in soil and water environments. In this study, a simulated rainfall experiment was conducted to investigate the loss characteristics of cadmium (Cd) from a red soil surface. Two rainfall intensities (50 and 100 mm h-1) were considered and the distribution of Cd in different fractions (>1, 1-0.25, 0.25-0.05 and <0.05 mm) of aggregates lost from the soil was examined. The result showed that in the artificially polluted soil, the Cd content in different aggregates decreased with particle size, with the lowest Cd content in the <0.05 mm fraction aggregates. In the rainfall experiment, the runoff rate generally increased with the rainfall duration, while the sediment yield rate first increased and then remained stable. The loss rates of various fractions of aggregates in the sediment generally followed the order of (<0.05) mm > 1-0.25 mm > 0.25-0.05 mm > (>1) mm. The proportions of the <0.05 mm-fraction aggregates were the highest in the loss sediment throughout the entire rainfall process. The lost Cd was transported mainly in the sediment-bound form, while only a very small portion of Cd was lost in the water phase of runoff. High rainfall intensity led to greater Cd loss in runoff. In the lost sediment, the concentration of Cd was higher in the macroaggregates. The phenomenon of Cd enrichment in the fine particles was not observed. Although the concentration of Cd in the <0.05 mm fraction was the lowest, the contribution of this fraction to the total Cd content in the sediments was the highest.

[Treatment of Pilon fractures complicated with soft tissue injury by plate and lag screw fixation via posterolateral approach].

OBJECTIVE: To evaluate the clinical effects of plate and lag screw fixation for treatment of Pilon fractures complicated with soft tissue injury via posterolateral approach. METHODS: From May 2013 to June 2016, 25 patients with Pilon fractures complicated with soft tissue injury underwent open reduction and internal fixation via posterolateral approach. There were 15 males and 10 females, aged from 25 to 61 years old with an average of(39.6±0.2) years. Plate and lag screw fixation were used in operation. Healing of soft tissue contusion and abrasions in the ankle wounds and injuries were observed after operation. The Burwell-Charnley standard was applied to assess the quality of fracture reduction and the AOFAS Ankle foot scoring system(total score 100 points) was used to evaluate the clinical effects. RESULTS: All the patients were followed up from 6 to 24 months with an average of 12 months. All operative wounds and soft tissue injuries were healed. According to the Burwell-Charnley standard, 22 cases obtained excellent results with anatomic reduction, while 2 cases were dissatisfied, and 1 case poor. The AOFAS ankle foot scores were 90.2±7.5 on average, with 20 cases of excellent results, 3 good, 2 fair. CONCLUSIONS: Plate and lag screw fixation by posterolateral approach in treating Pilon fracture complicated with soft tissue injury shows advantage of avoiding injury to the anteromedial skin and soft tissue, provides forceful fixation without further injury.