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A divergent intramolecular phosphination of alkynes is developed. Fine tuning of chemo- and regioselectivity has been realized by just adding LiBr or H

Herein, we report a facile and highly atom-economic approach to 2-phosphafurans by using simple 2-chloroethylphosphine and acetylenic ketones. The key step of this protocol utilizes the Lewis acidity of electrophilic phosphinidenes to induce an intramolecular cyclization with enones. Dearomative hetero-Diels-Alder reactions of 2-phosphafurans provide two series of bicyclic phosphacycles. This rare synthetic application of Lewis acidity of electrophilic phosphinidene complexes represents a new frontier of phosphinidene chemistry.

One way of reducing environmental pollution is to reduce our dependence on fossil fuels by replacing them with solar radiation (Rs), which is one of the main sources of clean and renewable energy. In this study, daily Rs values at seven meteorological stations in Iran (Ahvaz, Isfahan, Kermanshah, Mashhad, Bandar Abbas, Kerman and Tabriz) over 2010-2019 were estimated using empirical models, support vector machine (SVM), SVM coupled with cuckoo search algorithm (SVM-CSA) and multi-model approach in the form of two structures. In structure 1, data from each station were divided into training and testing sets. In structure 2, data from the former four stations were used for model training, and those from the latter three stations were used to test the models. The results showed that using meteorological parameters improved estimation accuracy compared with the use of geographical parameters for both SVM and SVM-CSA models. Coupling the CSA to SVM did improve the accuracy of radiation estimates, reducing RMSE by up to 38% (Kermanshah station) and 36% (Tabriz station) for the first structure and about 42.4% (Tabriz station) for the second. Performance analysis of the models over three intervals including, the first, middle and last third of measured radiation values at each station showed that for both structures (except at Tabriz station), the best model performance in under- and over-estimation sets of radiation values was obtained, respectively, in the first third interval (first structure, Mashhad station, RMSE = 28.39 J.cm

Cooperative palladium-catalyzed and P(NEt2)3-mediated (4 + 1) annulations are developed, leading to a big library of spirooxindole derivatives in high structural diversity.

Both DFT calculations and experimental results revealed that the lone pair of the adjacent atom X facilitates the phosphirane fragmentation to form electrophilic phosphinidene complexes.

A facile access to mono-C-alkynyl-o-carboranes from o-carboranes and arylsulfonylacetylenes was developed. This facile process tolerates a wide variety of functional groups, occurs at mild conditions in one-pot procedure with short reaction time. The obtained mono-C-alkynyl-o-carboranes can be easily derivatized to synthesize 1,2-difunctionalized o-carboranes. This work provides a useful tool for the functionalization of o-carboranes.

Tandem [5 + 1] carbonyl cyclization/[8 + 2] cycloaddition reactions of phosphiranes and tropones were developed as a straightforward method to access 6,5,7-fused tricyclic scaffolds.

Herein we report a diastereodivergent synthesis of fully disubstituted spiro[indoline-3,2′-pyrrolidin]-2-ones through base-promoted (3 + 2) cycloadditions. Importantly, the catalysts are found to have full control over the configuration of the stereocenters. When a Lewis base (PCy3) is used as a catalyst, good yields and excellent diastereoselectivities are obtained, regardless of the properties of the substituents, whereas spiro[indoline-3,2′-pyrrolidin]-2-ones of a different diastereoisomer are produced in good yields when a Bronsted base (K2CO3) is used. ESI-MS experiments proved the existence of key zwitterionic intermediates.

Oxytocin (Oxt) and vasopressin (Avp) are two neuropeptides with many central actions related to social cognition. The oxytocin (Oxtr) and vasopressin 1b (Avpr1b) receptors are co-expressed in the pyramidal neurons of the hippocampal subfield CA2 and are known to play a critical role in social memory formation. How the neuropeptides perform this function in this region is not fully understood. Here, we report the behavioral effects of a life-long conditional removal (knockout, KO) of either the Oxtr alone or both Avpr1b and Oxtr from the pyramidal neurons of CA2 as well as the resultant changes in synaptic transmission within the different fields of the hippocampus. Surprisingly, the removal of both receptors results in mice that are unable to habituate to a familiar female presented for short duration over short intervals but are able to recognize and discriminate females when presented for a longer duration over a longer interval. Importantly, these double KO mice were unable to discriminate between a male littermate and a novel male. Synaptic transmission between CA3 and CA2 is enhanced in these mice, suggesting a compensatory mechanism is activated to make up for the loss of the receptors. Overall, our results demonstrate that co-expression of the receptors in CA2 is necessary to allow intact social memory processing.

Recent rapid warming has caused uneven impacts on the composition, structure, and functioning of northern ecosystems. It remains unknown how climatic drivers control linear and non-linear trends in ecosystem productivity. Based on a plant phenology index (PPI) product at a spatial resolution of 0.05° over 2000–2018, we used an automated polynomial fitting scheme to detect and characterize trend types (i.e., polynomial trends and no-trends) in the yearly-integrated PPI (PPIINT) for northern (> 30°N) ecosystems and their dependence on climatic drivers and ecosystem types. The averaged slope for the linear trends (p < 0.05) of PPIINT was positive across all the ecosystems, among which deciduous broadleaved forests and evergreen needle-leaved forests (ENF) showed the highest and lowest mean slopes, respectively. More than 50% of the pixels in ENF, arctic and boreal shrublands, and permanent wetlands (PW) had linear trends. A large fraction of PW also showed quadratic and cubic trends. These trend patterns agreed well with estimates of global vegetation productivity based on solar-induced chlorophyll fluorescence. Across all the biomes, PPIINT in pixels with linear trends showed lower mean values and higher partial correlation coefficients with temperature or precipitation than in pixels without linear trends. Overall, our study revealed the emergence of latitudinal convergence and divergence in climatic controls on the linear and non-linear trends of PPIINT, implying that northern shifts of vegetation and climate change may potentially increase the non-linear nature of climatic controls on ecosystem productivity. These results can improve our understanding and prediction of climate-induced changes in plant phenology and productivity and facilitate sustainable management of ecosystems by accounting for their resilience and vulnerability to future climate change.

We developed novel shackled P-chiral ligands based on 1-phosphanorbornenes and oxazolines. They were subsequently evaluated in palladium-catalyzed (4+2) annulations, producing enantioenriched tetrahydropyran scaffolds in good yields with high site selectivity and enantioselectivity. Moreover, chemoselective (4+4) products were also achieved by using acyclic imines. In addition, density functional theory calculations were performed to afford the energy profile of the Michael addition step and ring formation step. This demonstrated that the enantioselective (4+2) annulations and the chemoselective reaction between (4+2) and (4+4) products were mostly under thermodynamic control.

Modeling inland water quality by remote sensing has already demonstrated its capacity to make accurate predictions. However, limitations still exist for applicability in diverse regions, as well as to retrieve non-optically active parameters (nOAC). Models are usually trained only with water samples from individual or local groups of waterbodies, which limits their capacity and accuracy in predicting parameters across diverse regions. This study aims to increase data availability to understand the performance of models trained with heterogeneous databases from both remote sensing and field measurement sources to improve machine learning training. This paper seeks to build a dataset with worldwide lake characteristics using data from water monitoring programs around the world paired with harmonized data of Landsat-8 and Sentinel-2. Additional feature engineering is also examined. The dataset is then used for model training and prediction of water quality at the global scale, time series analysis and water quality maps for lakes in different continents. Additionally, the modeling performance of nOACs are also investigated. The results show that trained models achieve moderately high correlations for SDD, TURB and BOD (R2 = 0.68) but lower performances for TSM and NO3-N (R2 = 0.43). The extreme learning machine (ELM) and the random forest regression (RFR) demonstrate better performance. The results indicate that ML algorithms can process remote sensing data and additional features to model water quality at the global scale and contribute to address the limitations of transferring and retrieving nOAC. However, significant limitations need to be considered, such as calibrated harmonization of water data and atmospheric correction procedures. Moreover, further understanding of the mechanisms that facilitate nOAC prediction is necessary. We highlight the need for international contributions to global water quality datasets capable of providing extensive water data for the improvement of global water monitoring.

Cough variant asthma (CVA), also called concealed asthma or allergic asthma, is the most common cause of chronic cough in children. The disorder is mainly characterized by a nonproductive dry cough associated with a high recurrence rate that is conventionally treated with antibiotics, anti-inflammatory medications, cough suppressants, or expectorants. For millennia, Chinese herbal medicine (CHM) has been used widely in China to treat pediatric CVA cases, although high-quality evidence of CHM efficacy is lacking. In this study, the effectiveness and safety of Xiehuangjiejing (XHJJ) granule will be evaluated when used alone to treat children with CVA.A randomized, double-blind, parallel, placebo-controlled multicenter trial will be conducted over the course of 2 weeks. A total of 180 CVA patients of ages between 4 and 7 years old will be randomly assigned to the experimental group (XHJJ granules, 4.5 g administered 3 times daily) or control group (matched placebo, 4.5 g administered 3 times daily) in a 2:1 ratio based on subject number per group, respectively. The trial will consist of a 7-day medical interventional stage and a 7-day follow-up stage. On day 7 of the follow-up stage, an evaluation of all subjects will be carried out to assess cough symptom score as the primary outcome and several secondary outcomes, including TCM (traditional Chinese medicine) syndrome score, lung function, and dosage of salbutamol aerosol inhaler therapy. Safety assessments will also be evaluated during the trial.The aim of this study was to examine the effectiveness and safety of Xiehuangjiejing (XHJJ) granule using a trial protocol designed to yield high-quality, statistically robust results for use in evaluating CHM as a treatment for CVA in children.

Atmospheric levels of atomic mercury pollution were measured using spectroscopic techniques in the city of Guangzhou, Guangdong Province, China. Assessments were mainly performed at ground level using a portable (vehicle mounted or hand carried) Zeeman modulation correlation spectrometer (Lumex RA-915M), and the results are given in easily comprehensible diagrams. Measurements were made with continuous recording in car traverses along major roads which cross the city, but also at selected spots, such as at a university campus with laboratory buildings. Further, pollution levels at different locations were recorded when walking through a major and a small hospital. While concentrations in the city in the range 3–10 ng/m3 were typical, and strongly dependent on the traffic situation, very high concentrations (up to 1300 ng/m3) were found at certain indoor hospital locations, again drawing attention to the fact that high mercury levels due to inadequate handling routines can remain undetected but could readily be eliminated by adequate measurements and subsequent sanitation.

We present a joint experimental and theoretical study of parametric resonance of spin wave eigenmodes in Ni$_{80}$Fe$_{20}$/Pt bilayer nanowires. Using electrically detected magnetic resonance, we measure the spectrum of spin wave eigenmodes in transversely magnetized nanowires and study parametric excitation of these eigenmodes by a microwave magnetic field. We also develop an analytical theory of spin wave eigenmodes and their parametric excitation in the nanowire geometry that takes into account magnetic dilution at the nanowire edges. We measure tuning of the parametric resonance threshold by antidamping spin Hall torque from a direct current for the edge and bulk eigenmodes, which allows us to independently evaluate frequency, damping and ellipticity of the modes. We find good agreement between theory and experiment for parametric resonance of the bulk eigenmodes but significant discrepancies arise for the edge modes. The data reveals that ellipticity of the edge modes is significantly lower than expected, which can be attributed to strong modification of magnetism at the nanowire edges. Our work demonstrates that parametric resonance of spin wave eigenmodes is a sensitive probe of magnetic properties at edges of thin-film nanomagnets., Comment: 24 pages, 9 figures

There are widespread Mesozoic-Cenozoic terrestrial volcanic activities in East China, and they produced favorable geologic factors for the volcanic reservoirs. To reveal the spatio-temporal evolution of regional volcanisms and their tectonic setting, we subdivide Mesozoic-Cenozoic volcanic activities into 6 volcanic cycles (I-VI), and summarize the temporal-spatial distribution, rock association and tectonic setting of each cycle. The Cycle I forms a post-orogenic intraplate bimodal volcanic association. The cycles II and III include arc volcanic associations formed in compressional and extensional subduction environments, respectively. The Cycle IV contains a post-orogenic arc bimodal association. The Cycle V is a basaltic association of tholeiite series under initial rift setting, and the Cycle VI is basaltic association of alkaline series under typical rift setting. The volcanic strata between each cycle are bounded by regional unconformity. The above 6 volcanic cycles correspond to 6 sequential stages of tectonic evolutions from the Early Jurassic post-orogeny, the Mid-Jurassic-Cretaceous subduction of the paleo-Pacific Plate to the Cenozoic marginal rifting. According to the geological characteristics of volcanic reservoirs in different volcanic cycles, it is put forward that the Cycle V is the major formation period of volcanic reservoirs in East China and should be the focus of exploration, and that the volcanic reservoirs of the Cycle IV are also worthy of attention.

For satellite interactions missions such as autonomous docking, the key to successful completion of these missions is to autonomously and accurately detect targets’ information. The missions with h...

Dissolved Organic Carbon (DOC) in inland waters plays an essential role in the global carbon cycle and has significant public health effects. Machine learning (ML) together with remote sensing has emerged as a powerful and promising combination to quantify water quality parameters from space. However, inland water sample data for DOC is limited. Hence, little is known about the potential to quantify DOC content in inland waters, especially over large-scale areas. This study presents the first attempt to estimate DOC in inland waters over a large-scale area using satellite data and ML methods with the newly published open-source dataset AquaSat. Four ML approaches, namely Random Forest Regression (RFR), Support Vector Regression (SVR), Gaussian Process Regression (GPR), and a Multilayer Backpropagation Neural Network (MBPNN) were trained using more than 16 thousand samples across the continental United States matched with satellite data from Landsat 5, 7 and 8 missions. Satellite data from the Landsat missions were further extended with environmental data from the ERA5-Land product and used as input to train the ML algorithms. Our results show that including environmental data as inputs considerably improved the prediction of DOC for all ML algorithms, with GPR showing the most promising performance results with moderate estimation errors (RMSE: 4.08 mg/L). Permutation feature importance analysis showed that the wavelength range in the visible Green band (from Landsat) and the monthly average air temperature (from ERA5-Land) were the most important variables for the ML approaches. The results demonstrate the predictive strength of GPR and its useful feature to derive per pixel standard deviations for detailed analysis. Our results further highlight the important role of considering environmental processes to explain DOC variations over large scales. The application and performance of the GPR in mapping spatiotemporal variations of DOC in an entire water body were discussed by taking Lake Okeechobee (the 8

The management and conservation of lakes should be conducted in the context of catchments because lakes collect water and materials from their upstream catchments. Thus, the datasets of catchment-level characteristics are essential for limnology studies. Lakes are widely spread on the Tibetan Plateau (TP), with a total lake area exceeding 50 000 km2, accounting for more than half of the total lake area in China. However, there has been no dataset of lake-catchment characteristics in this region to date. This study constructed the first dataset of lake-catchment characteristics for 1525 lakes with areas from 0.2 to 4503 km2 on the TP. Considering that large lakes block the transport of materials from upstream to downstream, lake catchments are delineated in two ways: the full catchment, which refers to the full upstream-contributing area of each lake, and the inter-lake catchments, which are obtained by excluding the contributing areas of upstream lakes larger than 0.2 km2 from the full catchment. There are six categories (i.e., lake body, topography, climate, land cover/use, soil and geology, and anthropogenic activity) and a total of 721 attributes in the dataset. Besides multi-year average attributes, the time series of 16 hydrological and meteorological variables are extracted, which can be used to drive or validate lumped hydrological models and machine learning models for hydrological simulation. The dataset contains fundamental information for analyzing the impact of catchment-level characteristics on lake properties, which on the one hand, can deepen our understanding of the drivers of lake environment change, and on the other hand can be used to predict the water and sediment properties in unsampled lakes based on limited samples. This provides exciting opportunities for lake studies in a spatially explicit context and promotes the development of landscape limnology on the TP. The dataset of lake-catchment characteristics for the Tibetan Plateau (LCC-TP v1.0) is accessible at the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/Terre.tpdc.272026, Liu, 2022).

The activation of CS

Dearomatization reactions have recently emerged as a powerful tool for the rapid buildup of molecular complexity. Here, an unparalleled thermal dearomatization [4+2] cycloaddition reaction between benzene derivatives and a 2

Palmer Drought Severity Index (PDSI) is known as a robust agricultural drought index since it considers the water balance conditions in the soil. It has been widely used as a reference index for monitoring agricultural drought. In this study, the PDSI time series were calculated for nine synoptic stations to monitor agricultural drought in semi-arid region located at Zagros mountains of Iran. Autoregressive Moving Average (ARMA) was used as the stochastic model while Radial Basis Function Neural Network (RBFNN) and Support Vector Machine (SVM) were applied as Machine Learning (ML)-based techniques. According to the time series analysis of PDSI, for the driest months the most PDSI drought events are normal drought and mild drought conditions. As an innovation, Dragonfly Algorithm (DA) was used in this study to optimize the SVM’s parameters, called as the hybrid SVM-DA model. It is worthy to mention that the hybrid SVM-DA is developed as a meta-innovative model for the first time in hydrological studies. The novel hybrid SVM-DA paradigm could improve the SVM’s accuracy up to 29% in predicting PDSI and therefore was found as the superior model. The best statistics for this model were obtained as Root Mean Squared Error (RMSE) = 0.817, Normalized RMSE (NRMSE) = 0.097, Wilmott Index (WI) = 0.940, and R = 0.889. The Mean Absolute Error values of the PDSI predictions via the novel SVM-DA model were under 0.6 for incipient drought, under 0.7 for mild and moderate droughts. In general, the error values in severe and extreme droughts were more than the other classes; however, the hybrid SVM-DA was the best-performing model in most of the cases.

Signals of Opportunity Reflectometry (SoOp-R) employs the communication system, GNSS (Global Navigation Satellite System) constellation and other potential Signals of Opportunity (SoOp) as the transmitters. In recent years, it has gained increased interests. Several experiments have been carried out, however it is still in the initial development stage. Theoretical predictions of SoOp Reflectometry for land surface parameters detection, such as soil moisture and vegetation biomass, should be carried out simultaneously. Meanwhile, at present less works are paid attention to the polarization study of the polarizations. The first-order radiative transfer equation models are employed here and they are developed according to the wave synthesis technique to get the various polarization combinations. Using the two models as analysis tools, we simulate the bistatic scattering at all potential SoOp Reflectometry bands, i.e., P-, L-, C- and X-band for circular polarizations and linear polarizations. While the original commonly used microwave scattering models are linear polarizations, here we compare the difference. Although the models can simulate bistatic scattering at any incident angles and scattering angles. Four special observation geometry are taken into considerations during the analysis. Using the developed models as tools, the developed models establish the relationship between the land surface parameters (such as soil moisture, soil roughness and vegetation water content, diameters et al.) and bistatic radar cross section. The forward scattering models developed here enables the understanding of the effects of different geophysical parameters and transmitter–receiver observation scenarios on the bisatic scattering at any polarization combinations for any potential SoOP reflectometry bands. Robust retrieval methods for soil moisture and vegetation biomass can benefit from the forward scattering models.

Herein we reported a novel phosphine-catalyzed (4 + 2) cyclization reaction of electron-deficient conjugated dienes with enones to generate functionalized dihydropyran skeletons. A mechanistic investigation reveals that the reaction produces a new phosphonium zwitterion, which undergoes consecutive reactions. In addition, an asymmetric variant was developed by efficient and economical chiral phosphine catalysis.

We have developed an unprecedented approach for the synthesis of transient 1-phosphafulvenes through three component reactions of phospholes. The generation of 1-phosphafulvenes was demonstrated by in situ [6 + 4] cycloaddition with 2H-phospholes and [6 + 6] self-dimerization. The [6 + 4] and [6 + 6] reaction pathway could be modulated by the starting ketones and aldehydes. The construction of 1-phosphafulvenes is illustrated by a proposed mechanism combining nucleophilic addition of phospholide to the iminium or isomerized azomethine ylide and a [1,5]-shift of phosphole.

Although narrow band imaging (NBI) has been a useful modality for detecting and delineating esophageal squamous cell carcinoma (ESCC), there is a risk of incorrectly determining the margins of some lesions even with NBI. This study aimed to develop an artificial intelligence (AI) system for detecting superficial ESCC and precancerous lesions and delineating the extent of lesions under NBI.Nonmagnified NBI images from four hospitals were collected and annotated. Internal and external image test datasets were used to evaluate the detection and delineation performance of the system. The delineation performance of the system was compared with that of endoscopists. Furthermore, the system was directly integrated into the endoscopy equipment, and its real-time diagnostic capability was prospectively estimated.The system was trained and tested using 10047 still images and 140 videos from 1112 patients and 1183 lesions. In the image testing, the accuracy of the system in detecting lesions in internal and external tests was 92.4% and 89.9%, respectively. The accuracy of the system in delineating extents in internal and external tests was 88.9% and 87.0%, respectively. The delineation performance of the system was superior to that of junior endoscopists and similar to that of senior endoscopists. In the prospective clinical evaluation, the system exhibited satisfactory performance, with an accuracy of 91.4% in detecting lesions and an accuracy of 85.9% in delineating extents.The proposed AI system could accurately detect superficial ESCC and precancerous lesions and delineate the extent of lesions under NBI.

In this report, a series of biphosphirane complexes 1 were synthesized from the phosphiranide complex. The binuclear Mn2(CO)10-catalyzed intramolecular dimerization of these biphosphirane complexes...

The phospha-Diels–Alder reaction between 2H-phospholes and arylallenes affords 6-methylene-1-phosphanorbornenes in high yields with excellent regioselectivity. This Diels–Alder reaction proceeds at the internal CC double bond of allenes selectively. DFT calculations of possible transition states finely demonstrate the regioselectivity of the reaction. The nucleophilic addition of Ph2PH to 6-methylene-1-phosphanorbornene sulfides and subsequent desulfurization provide the bidentate phosphine ligands 6, which have a fascinating 1-phosphanorbornene modified PCH2CH2P skeleton. The potential applications of 6 as ligands were demonstrated by coordination with transition metals.

A simple method to synthesize luminescent λ5-phosphanaphthalenes and zwitterionic nido-carborane fused six-membered phosphacycles was developed from the reaction of ortho-phosphinobenzoaldehydes or ortho-phosphinocarboranylaldehydes with an electron-deficient alkyne, respectively. Similar results were obtained with the imino analogues.