Bifunctional catalysts that are highly active toward both the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) are attractive for efficient electrochemical water splitting. ...Herein, we report a bifunctional FeCoOOH nanosheet catalyst for highly efficient electrochemical water splitting in an alkaline electrolyte. The FeCoOOH nanosheet arrays were grown directly on the surface of a porous Ni foam by using a simple hydrothermal method. Because of their binary oxyhydroxide structure and high electrical conductivity intrinsic to direct growth, these FeCoOOH nanosheets exhibited excellent activities toward both the HER and OER. With the use of this bifunctional FeCoOOH catalyst, an alkaline water electrolyzer in a two‐electrode configuration achieved 10 mA cm−2 only at a cell voltage of 1.62 V without iR compensation in 1 m KOH, which outperformed that based on the combination of commercial IrO2 and Pt/C catalysts.
FeCoOOH nanosheet arrays were grown directly on the surface of a porous Ni foam by using a simple hydrothermal method. The FeCoOOH nanosheets exhibited excellent activities toward both the HER and OER. The water electrolyzer based on the FeCoOOH nanosheet catalyst outperformed one based on the combination of the commercial IrO2 and Pt/C catalysts.
Rickettsia felis is an obligate intracellular bacterium that is being increasingly recognized as an etiological agent of human rickettsial disease globally. The agent is transmitted through the bite ...of an infected vector, the cat flea, Ctenocephalides felis, however there is to date, no consensus on the pathogen's vertebrate reservoir, required for the maintenance of this agent in nature. This study for the first time, demonstrates the role of the domestic dog (Canis familiaris) as a vertebrate reservoir of R. felis. The ability of dogs to sustain prolonged periods of rickettsemia, ability to remain asymptomatically infected with normal haematological parameters and ability to act as biological vehicles for the horizontal transmission of R. felis between infected and uninfected fleas provides indication of their status as a mammalian reservoir of this emerging zoonosis.
Hierarchically organized porous carbonized‐Co3O4 inverse opal nanostructures (C‐Co3O4 IO) are synthesized via complementary colloid and block copolymer self‐assembly, where the triblock copolymer ...Pluronic P123 acts as the template and the carbon source. These highly ordered porous inverse opal nanostructures with high surface area display synergistic properties of high energy density and promising bifunctional electrocatalytic activity toward both the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). It is found that the as‐made C‐Co3O4 IO/Ketjen Black (KB) composite exhibits remarkably enhanced electrochemical performance, such as increased specific capacity (increase from 3591 to 6959 mA h g−1), lower charge overpotential (by 284.4 mV), lower discharge overpotential (by 19.0 mV), and enhanced cyclability (about nine times higher than KB in charge cyclability) in Li–O2 battery. An overall agreement is found with both C‐Co3O4 IO/KB and Co3O4 IO/KB in ORR and OER half‐cell tests using a rotating disk electrode. This enhanced catalytic performance is attributed to the porous structure with highly dispersed carbon moiety intact with the host Co3O4 catalyst.
Hierarchical porous carbonized cobalt oxide inverse opal (C‐Co3O4 IO) nanostructures are fabricated via one‐pot direct carbonization of inorganic‐precursors‐containing block copolymer infiltrated into colloid assembly and proposed as efficient electrocatalysts in Li–O2 battery. C‐Co3O4 IO shows remarkable bifunctional electrocatalysis due to facilitated charge transport and optimized composition. The Li–O2 cell exhibits prominent performance in terms of capacity, overpotential, and cyclability.
Summary
The Xanthomonas transcription activator‐like effector (TALE) protein AvrBs3 transcriptionally activates the executor‐type resistance (R) gene Bs3 from pepper (Capsicum annuum), thereby ...triggering a hypersensitive cell death reaction (HR). AvrBs3 also triggers an HR in tomato (Solanum lycopersicum) upon recognition by the nucleotide‐binding leucine‐rich repeat (NLR) R protein Bs4. Whether the executor‐type R protein Bs3 and the NLR‐type R protein Bs4 use common or distinct signalling components to trigger an HR remains unclear.
CRISPR/Cas9‐mutagenesis revealed, that the immune signalling node EDS1 is required for Bs4‑ but not for Bs3‐dependent HR, suggesting that NLR‑ and executor‐type R proteins trigger an HR via distinct signalling pathways. CRISPR/Cas9‐mutagenesis also revealed that tomato Bs4 suppresses the virulence function of both TALEs, the HR‐inducing AvrBs3 protein and of AvrHah1, a TALE that does not trigger an HR in tomato.
Analysis of AvrBs3‑ and AvrHah1‐induced host transcripts and disease phenotypes in CRISPR/Cas9‐induced bs4 mutant plants indicates that both TALEs target orthologous transcription factor genes to promote disease in tomato and pepper host plants.
Our studies display that tomato mutants lacking the TALE‐sensing Bs4 protein provide a novel platform to either uncover TALE‐induced disease phenotypes or genetically dissect components of executor‐triggered HR.
Mangroves can be considered as biogeochemical reactors along (sub)tropical coastlines, acting both as sinks or sources for trace metals depending on environmental factors. In this study, we ...characterized the role of a mangrove estuary, developing downstream a densely populated megacity (Ho Chi Minh City, Vietnam), on the fate and partitioning of trace metals. Surface water and suspended particulate matter were collected at four sites along the estuarine salinity gradient during 24 h cycling in dry and rainy seasons. Salinity, pH, DO, TSS, POC, DOC, dissolved and particulate Fe, Mn, Cr, As, Cu, Ni, Co and Pb were measured. TSS was the main trace metals carrier during their transit in the estuary. However, TSS variations did not explain the whole variability of metals distribution. Mn, Cr and As were highly reactive metals while the other metals (Fe, Ni, Cu, Co and Pb) presented stable log KD values along the estuary. Organic matter dynamic appeared to play a key role in metals fractioning. Its decomposition during water transit in the estuary induced metal desorption, especially for Cr and As. Conversely, dissolved Mn concentrations decreased along the estuary, which was suggested to result from Mn oxidative precipitation onto solid phase due to oxidation and pH changes. Extra sources as pore-water release, runoff from adjacent soils, or aquaculture effluents were suggested to be involved in trace metal dynamic in this estuary. In addition, the monsoon increased metal loads, notably dissolved and particulate Fe, Cr, Ni and Pb.
•Partitioning and distribution of 8 trace metals were studied in a mangrove estuary.•TSS was the main trace metals carrier during their transit in the estuary.•The monsoon induced increased metal inputs to the estuary.•Most of dissolved metals exhibited a non-conservative behavior whatever the season.•Mn, Cr and As were highly reactive, OM or DO playing a key role in their dynamics.
Determining the price movement of stocks is a challenging problem to solve because of factors such as industry performance, economic variables, investor sentiment, company news, company performance, ...and social media sentiment. People can predict the price movement of stocks by applying machine learning algorithms on information contained in historical data, stock candlestick-chart data, and social-media data. However, it is hard to predict stock movement based on a single classifier. In this study, we proposed a multichannel collaborative network by incorporating candlestick-chart and social-media data for stock trend predictions. We first extracted the social media sentiment features using the Natural Language Toolkit and sentiment analysis data from Twitter. We then transformed the stock’s historical time series data into a candlestick chart to elucidate patterns in the stock’s movement. Finally, we integrated the stock’s sentiment features and its candlestick chart to predict the stock price movement over 4-, 6-, 8-, and 10-day time periods. Our collaborative network consisted of two branches: the first branch contained a one-dimensional convolutional neural network (CNN) performing sentiment classification. The second branch included a two-dimensional (2D) CNN performing image classifications based on 2D candlestick chart data. We evaluated our model for five high-demand stocks (Apple, Tesla, IBM, Amazon, and Google) and determined that our collaborative network achieved promising results and compared favorably against single-network models using either sentiment data or candlestick charts alone. The proposed method obtained the most favorable performance with 75.38% accuracy for Apple stock. We also found that the stock price prediction achieved more favorable performance over longer periods of time compared with shorter periods of time.
Nowadays, a number of machine learning prediction methods are being applied in the field of landslide susceptibility modeling of the large area especially in the difficult hilly terrain. In the ...present study, hybrid machine learning approaches of Reduced Error Pruning Trees (REPT) and different ensemble techniques were used for the construction of four novel hybrid models namely Bagging based Reduced Error Pruning Trees (BREPT), MultiBoost based Reduced Error Pruning Trees (MBREPT), Rotation Forest-based Reduced Error Pruning Trees (RFREPT), Random Subspace-based Reduced Error Pruning Trees (RSREPT) for landslide susceptibility assessment and prediction. In total, ten topographical and geo-environmental landslide conditioning factors were considered for analyzing their spatial relationship with landslide occurrences. Receiver Operating Characteristic curve, Statistical Indexes, and Root Mean Square Error methods were used to validate performance of these models. Analysis of model results indicate that the BREPT is the best model for landslide susceptibility assessment in comparison to other models.
•New hybrid models of REPT and its ensembles developed for landslide susceptibility modeling.•RMSE, accuracy, Chi square test, and ROC curve used for validation of the models.•Results indicate that BREPT is the best method for modeling of landslide susceptibility.
From the methanol extract of the Cryptolepis buchananii fruits, four undescribed pentacyclic triterpenene glycosides (1–4) and five known pentacyclic triterpenenes (5–9) were isolated. Their ...structures were determined to be uncargenin C 28‐O‐α‐L‐rhamnopyranosyl‐(1→2)‐β‐D‐glucopyranosyl ester (1), 3‐O‐β‐D‐glucopyranosyluncargenin C 28‐O‐α‐L‐rhamnopyranosyl‐(1→2)‐β‐D‐glucopyranosyl ester (2), 3‐O‐β‐D‐glucopyranosyl‐(1→6)‐β‐D‐glucopyranosyl‐6β,23‐dihydroxyursolic acid 28‐O‐α‐L‐rhamnopyranosyl‐(1→2)‐β‐D‐glucopyranosyl ester (3), 3‐O‐β‐D‐glucopyranosyl‐(1→2)‐β‐D‐glucopyranosylasiatic acid 28‐O‐α‐L‐rhamnopyranosyl‐(1→2)‐β‐D‐glucopyranosyl ester (4), asiatic acid (5), 2α,3β,23‐trihydroxyoleana‐11,13(18)‐dien‐28‐oic acid (6), arjunolic acid (7), 6β‐hydroxyarjunolic acid (8), and actinidic acid (9) based on analyses of their HR‐ESI‐MS, 1D and 2D NMR spectra. All the isolates showed significantly NO production inhibition in LPS‐activated RAW264.7 cells with the IC50 values ranging from 18.79 to 37.57 μM, compared to that of the positive control compound, dexamethasone, which showed IC50 value of 14.05 μM.
In the knowledge economy, intangible assets and intellectual property rights are increasingly recognized as a substance of competencies. As an emerging market of the world, Asian developing countries ...experience various issues related to intellectual property rights protection. Meanwhile, the current literature on intellectual property rights with an emphasis placed on Asia is quite scarce. Therefore, this study explores the determinants of the strength of intellectual property rights in 25 Asian developing countries during the 11-year period from 2006 to 2016. Using the fixed effects model (FEM) and random effects model (REM) with the Hausman test, the paper discovers the positive impacts of economic growth, trade openness, and WTO participation on the protection level of intellectual property rights. Unexpectedly, education is a negative determinant of intellectual property rights protection. This study aims to demonstrate the overall status quos of intellectual property rights regimes across Asian developing countries, so provide an important theoretical background for innovators, governments, and policymakers to design optimal intellectual property rights strategies.
The Surface Ocean CO2 Atlas (SOCAT) of CO2 fugacity (fCO2) observations is a key resource supporting annual assessments of CO2 uptake by the ocean and its side effects on the marine ecosystem. SOCAT ...data are usually released with a lag of up to 1.5 years which hampers timely quantification of recent variations of carbon fluxes between the Earth System components, not only with the ocean. This study uses a statistical ensemble approach to analyze fCO2 with a latency of one month only based on the previous SOCAT release and a series of predictors. Results indicate a modest degradation in a retrospective prediction test for 2021–2022. The generated fCO2 and fluxes for January–August 2023 show a progressive reduction in the Equatorial Pacific source following the La Niña retreat. A breaking‐record decrease in the northeastern Atlantic CO2 sink has been diagnosed on account of the marine heatwave event in June 2023.
Plain Language Summary
There is a growing need to monitor carbon emissions and removals over the globe in near real time in order to correctly interpret changes in CO2 concentrations as they unfold. For the oceans, the best information comes from measurements of the surface ocean CO2 fugacity (fCO2) by the international marine carbon research community. So far, this data is mostly available 6 to 18 months behind real time after collection, qualification, harmonization, and processing. Here, we show that a set of biological, chemical, and physical predictors available in near real time, allows the information contained in the “old” fCO2 measurements to be transferred over time. Based on a statistical technique, we combine all these data sources to estimate global monthly maps of fCO2 and of CO2 fluxes at the air‐sea interface within one month behind real time and with good accuracy.
Key Points
We demonstrate the capacity of statistical models to generate global maps of fCO2 and air‐sea flux with a latency reduced to one month
A decrease in the CO2 source for January to August 2023 diagnosed in the tropical Pacific coheres with the retreat of the La Niña event
An unusual northeastern Atlantic sink reduction diagnosed for June 2023 is linked to record heat and exceptionally low winds
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