The combination of hydrogen evolution, nitric oxide oxidation and Zn-nitrate battery for energy conversion and storage by an efficient nitrogen-dopped CoO electrocatalyst with Turing structure.

We tuned the morphology from the needle-like Co(CO)(OH)·0.11HO to the unique Turing-structured CoCO through controlling the amount of glycerol in the solvothermal system, and then synthesized the Turing structure consisting of N-50 %-CoO hollow nanoparticles though the Kirkendall effect during nitriding process, which was applied as a novel bifunctional self-supporting electrode for efficient electrocatalytic hydrogen evolution reaction (HER) and electrocatalytic NO oxidation reaction (eNOOR). The eNOOR can be not only used as a substitution anode reaction of oxygen evolution reaction (OER) to couple with HER for efficient water splitting, but the production of nitrate from eNOOR also provides a strategy for the development of Zn-nitrate battery.

Quantifying Global Wetland Methane Emissions With In Situ Methane Flux Data and Machine Learning Approaches.

Wetland methane (CH) emissions have a significant impact on the global climate system. However, the current estimation of wetland CH emissions at the global scale still has large uncertainties. Here we developed six distinct bottom-up machine learning (ML) models using in situ CH fluxes from both chamber measurements and the Fluxnet-CH network.

Change Representation and Extraction in Stripes: Rethinking Unsupervised Hyperspectral Image Change Detection With an Untrained Network.

Deep learning-based hyperspectral image (HSI) change detection (CD) approaches have a strong ability to leverage spectral-spatial-temporal information through automatic feature extraction, and currently dominate in the research field. However, their efficiency and universality are limited by the dependency on labeled data. Although the newly applied untrained networks can avoid the need for labeled data, their feature volatility from the simple difference space easily leads to inaccurate CD results.

Engineered acetogenic bacteria as microbial cell factory for diversified biochemicals.

Acetogenic bacteria (acetogens) are a class of microorganisms with conserved Wood-Ljungdahl pathway that can utilize CO and CO/H as carbon source for autotrophic growth and convert these substrates to acetate and ethanol. Acetogens have great potential for the sustainable production of biofuels and bulk biochemicals using C1 gases (CO and CO) from industrial syngas and waste gases, which play an important role in achieving carbon neutrality. In recent years, with the development and improvement of gene editing methods, the metabolic engineering of acetogens is making rapid progress.

Epidemic Characteristics and Meteorological Risk Factors of Hemorrhagic Fever With Renal Syndrome in 151 Cities in China From 2015 to 2021: Retrospective Analysis.

Background: Hemorrhagic fever with renal syndrome (HFRS) continues to pose a significant public health threat to the population in China. Previous epidemiological evidence indicates that HFRS is climate sensitive and influenced by meteorological factors. However, past studies either focused on too-narrow geographical regions or investigated time periods that were too early.

The Intersection of cerebral cholesterol metabolism and Alzheimer's disease: Mechanisms and therapeutic prospects.

Alzheimer's disease (AD) is a common neurodegenerative disease in the elderly, the exact pathogenesis of which remains incompletely understood, and effective preventive and therapeutic drugs are currently lacking. Cholesterol plays a vital role in cell membrane formation and neurotransmitter synthesis, and its abnormal metabolism is associated with the onset of AD. With the continuous advancement of imaging techniques and molecular biology methods, researchers can more accurately explore the relationship between cholesterol metabolism and AD.

Tuberculosis-targeted next-generation sequencing and machine learning: An ultrasensitive diagnostic strategy for paucibacillary pulmonary tuberculosis and tuberculous meningitis.

Background: Existing diagnostic approaches for paucibacillary tuberculosis (TB) are limited by the low sensitivity of testing methods and difficulty in obtaining suitable samples.

Methods: An ultrasensitive TB diagnostic strategy was established, integrating efficient and specific TB targeted next-generation sequencing and machine learning models, and validated in clinical cohorts to test plasma cfDNA, cerebrospinal fluid (CSF) DNA collected from tuberculous meningitis (TBM) and pediatric pulmonary TB (PPTB) patients.

Results: In the detection of 227 samples, application of the specific thresholds of CSF DNA (AUC = 0.

Genome-Wide Association Study of Arsenic Accumulation in Polished Rice.

The accumulation of arsenic (As) in rice poses a significant threat to food safety and human health. Breeding rice varieties with low As accumulation is an effective strategy for mitigating the health risks associated with arsenic-contaminated rice. However, the genetic mechanisms underlying As accumulation in rice grains remain incompletely understood.

When Broad Learning System Meets Label Noise Learning: A Reweighting Learning Framework.

Broad learning system (BLS) is a novel neural network with efficient learning and expansion capacity, but it is sensitive to noise. Accordingly, the existing robust broad models try to suppress noise by assigning each sample an appropriate scalar weight to tune down the contribution of noisy samples in network training. However, they disregard the useful information of the noncorrupted elements hidden in the noisy samples, leading to unsatisfactory performance.

Plug-and-Play Priors for Multi-Shot Compressive Hyperspectral Imaging.

Multi-shot coded aperture snapshot spectral imaging (CASSI) uses multiple measurement snapshots to encode the three-dimensional hyperspectral image (HSI). Increasing the number of snapshots will multiply the number of measurements, making CASSI system more appropriate for detailed spatial or spectrally rich scenes. However, the reconstruction algorithms still face the challenge of being ineffective or inflexible.

Glycerol photocatalytic oxidation to higher value-added compounds via bismuth oxyhalide photocatalysts.

Bismuth oxyhalides (BiOX) including BiOCl, BiOBr, and BiOI, were well synthesized using solvothermal technique and then used in the aqueous phase photooxidation of glycerol as a catalyst. The as-synthesized BiOBr could achieve the highest glycerol transformation of around 85.6% in 8 h under ultraviolet light (UV) irradiation among as-synthesized BiOXs.

China's dietary changes would increase agricultural blue and green water footprint.

Agriculture accounts for 61 % of fresh water consumption in China. Although population and diet have a significant impact on water consumption, little is known about the reasons for and extent of their influence. Changes in the blue and green water footprint of 20 agricultural sectors in 31 Chinese provinces were estimated in 5 scenarios by applying the environmentally expanded multi-regional input-output model.

[Genetic modification of acetogens and optimization of fermentation process in C1-gas bioconversion].

The current linear economy model relies on fossil energy and increases CO emissions, which contributes to global warming and environmental pollution. Therefore, there is an urgent need to develop and deploy technologies for carbon capture and utilization to establish a circular economy. The use of acetogens for C1-gas (CO and CO) conversion is a promising technology due to high metabolic flexibility, product selectivity, and diversity of the products including chemicals and fuels.

Longitudinal Changes in Milk Microorganisms in the First Two Months of Lactation of Primiparous and Multiparous Cows.

The present experiment was carried out to analyze the longitudinal changes in milk microorganisms. For this purpose, milk samples were collected from 12 healthy cows ( = 96; six primiparous cows and six multiparous cows) at eight different time points. The characteristics and variations in microbial composition were analyzed by 16S rRNA gene high-throughput sequencing.

A Review of Convex Clustering From Multiple Perspectives: Models, Optimizations, Statistical Properties, Applications, and Connections.

Traditional partition-based clustering is very sensitive to the initialized centroids, which are easily stuck in the local minimum due to their nonconvex objectives. To this end, convex clustering is proposed by relaxing K -means clustering or hierarchical clustering. As an emerging and excellent clustering technology, convex clustering can solve the instability problems of partition-based clustering methods.

Liquid-Phase Dehydration of Glycerol to Acrolein with ZSM-5-Based Catalysts in the Presence of a Dispersing Agent.

Liquid-phase dehydration of glycerol to acrolein was investigated with solid acid catalysts, including H-ZSM-5, HPO-modified H-ZSM-5, HPWO·14HO and CsHPWO, in the presence of sulfolane ((CH)SO) as a dispersing agent under atmospheric pressure N in a batch reactor. High weak-acidity H-ZSM-5, high temperatures and high-boiling-point sulfolane improved the activity and selectivity for the production of acrolein through suppressing the formation of polymers and coke and promoting the diffusion of glycerol and products. Brønsted acid sites were soundly demonstrated to be responsible for dehydration of glycerol to acrolein by infrared spectroscopy of pyridine adsorption.

Modal-Regression-Based Broad Learning System for Robust Regression and Classification.

A novel neural network, namely, broad learning system (BLS), has shown impressive performance on various regression and classification tasks. Nevertheless, most BLS models may suffer serious performance degradation for contaminated data, since they are derived under the least-squares criterion which is sensitive to noise and outliers. To enhance the model robustness, in this article we proposed a modal-regression-based BLS (MRBLS) to tackle the regression and classification tasks of data corrupted by noise and outliers.

A chromosome-level genome assembly reveals that a bipartite gene cluster formed via an inverted duplication controls monoterpenoid biosynthesis in Schizonepeta tenuifolia.

Biosynthetic gene clusters (BGCs) are regions of a genome where genes involved in a biosynthetic pathway are in proximity. The origin and evolution of plant BGCs as well as their role in specialized metabolism remain largely unclear. In this study, we have assembled a chromosome-scale genome of Japanese catnip (Schizonepeta tenuifolia) and discovered a BGC that contains multiple copies of genes involved in four adjacent steps in the biosynthesis of p-menthane monoterpenoids.

Structure and physicochemical properties of low digestible Euryale ferox Salisb. seed starch.

Background: Euryale ferox Salisb. is widely grown in China and Southeast Asia as a grain crop and medicinal plant. The composition, morphology, structure, physicochemical properties, thermal properties, and in vitro digestibility of North Euryale ferox seeds starch (NEFS), hybrid Euryale ferox seeds starch (HEFS), and South Euryale ferox seeds starch (SEFS) were studied.

Molecular Engineering of Peripheral Substitutions to Construct Efficient Acridine Core-Based Hole Transport Materials for Perovskite Solar Cells.

The development of highly efficient hole transport materials (HTMs) for perovskite solar cells (PSCs) has been a hot research topic. Acridine and its derivatives are gradually utilized as new blocks for optoelectronic applications, which stems from its rigid conjugated structure, shedding a new light on this old molecule. Meanwhile, its application in PSCs as a HTM has not been well explored, and the efficiency of 9,10-dihydroacridine (ACR)-based HTMs is relatively low.

Biomimetic Gradient Hydrogel Actuators with Ultrafast Thermo-Responsiveness and High Strength.

Most current hydrogel actuators suffer from either poor mechanical properties or limited responsiveness. Also, the widely used thermo-responsive poly-(-isopropylacrylamide) (PNIPAM) homopolymer hydrogels have a slow response rate. Thus, it remains a challenge to fabricate thermo-responsive hydrogel actuators with both excellent mechanical and responsive properties.