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The identification and detection of pesticides is crucial to protecting both the environment and human health. However, it can be challenging to conveniently and rapidly differentiate between different types of pesticides. We developed a supramolecular fluorescent sensor array, in which calixarenes with broad-spectrum encapsulation capacity served as recognition receptors. The sensor array exhibits distinct fluorescence change patterns for seven tested pesticides, encompassing herbicides, insecticides, and fungicides. With a reaction time of just three minutes, the sensor array proves to be a rapid and efficient tool for the discrimination of pesticides. Furthermore, this supramolecular sensing approach can be easily extended to enable real-time and on-site visual detection of varying concentrations of imazalil using a smartphone with a color scanning application. This work not only provides a simple and effective method for pesticide identification and quantification, but also offers a versatile and advantageous platform for the recognition of other analytes in relevant fields. [ABSTRACT FROM AUTHOR]

The non-photosynthetic vegetation – soil separation index (NSSI) and normalized difference vegetation index (NDVI) can be used to simultaneously estimate the fractional cover of non-photosynthetic vegetation (fNPV), photosynthetic vegetation (fPV), and bare soil (fBS) in vegetation ecosystems. However, these estimates suffer from problems due to shading by dense vegetation or topography. Based on field-measured data and on hyperspectral data acquired by unmanned aerial vehicles, we analyse how shading affects the morphology of NDVI-NSSI and enhanced vegetation index – NSSI (EVI-NSSI). We also investigate the simultaneous estimation of fNPV, fPV, and fBS. The results show that the NDVI-NSSI normalized difference feature space mitigates the impact of shade. Shade causes the NDVI-NSSI and EVI-NSSI to shift rightward parallel to the BS axis and leftward parallel to the PV axis, respectively. Although such shifts may hinder the determination of NPV, PV, and BS endmembers, they do not affect the spectral separation of NPV. Overall, with the NDVI-NSSI and EVI-NSSI methods, the estimation error for fNPV under shaded conditions is approximately 5% greater than that under illuminated conditions. Shaded green vegetation more strongly affects the estimation error of fPV and fBS in EVI-NSSI than in NDVI-NSSI, whereas fBS and fPV depend more strongly on shade than fNPV. [ABSTRACT FROM AUTHOR]

In the realm of automated industry and smart production, the deployment of fault warning systems is crucial for ensuring equipment reliability and enhancing operational efficiency. Although there are a multitude of existing methodologies for fault warning, the proficiency of these systems in processing and analysing data is increasingly challenged by the progression of industrial apparatus and the escalating magnitude and intricacy of the data involved. To address these challenges, this research outlines an innovative fault warning methodology that combines a bi-directional long short-term memory (Bi-LSTM) network with an enhanced hunter–prey optimisation (EHPO) algorithm. The Bi-LSTM network is strategically utilised to outline complex temporal patterns in machinery operational data, while the EHPO algorithm is employed to meticulously fine-tune the hyperparameters of the Bi-LSTM, aiming to enhance the accuracy and generalisability of fault warning. The EHPO algorithm, building upon the foundational hunter–prey optimisation (HPO) framework, introduces an advanced population initialisation process, integrates a range of strategic exploration methodologies, and strengthens its search paradigms through the incorporation of the differential evolution (DE) algorithm. This comprehensive enhancement aims to boost the global search efficiency and accelerate the convergence speed of the algorithm. Empirical analyses, conducted using datasets from real-world industrial scenarios, have validated the improved warning performance of this proposed methodology against some benchmark techniques, as evidenced by superior metrics such as root mean square error (RMSE) and mean absolute error (MAE), albeit with a slight increase in computational resource requirements. This study not only proposes a novel paradigm for fault warning within complex industrial frameworks but also contributes to the discourse on hyperparameter optimisation within the field of machine learning algorithms. [ABSTRACT FROM AUTHOR]

The number of people suffering from scrub typhus, which is not of concern, is increasing year by year, especially in Yunnan Province, China. From June 1, 2021 to August 15, 2022, a total of 505 mammalian samples were collected from farm, forest, and residential habitats with high incidence of scrub typhus in Yunnan, China, for nPCR (nested PCR) and qPCR (quantitative real-time PCR) detection of Orientia tsutsugamushi. A total of 4 orders of murine-like animals, Rodentia (87.52%, n = 442), Insectivora (10.29%, n = 52), Lagomorpha (1.79%, n = 9) and Scandentia (0.40%, n = 2) were trapped. Comparing the qPCR infection rates in the three habitats, it was no significant difference that the infection rate of residential habitat (44.44%) and that of the farm habitat (45.05%, P>0.05), which is much larger than that of the forest habitat (3.08%) (P<0.001). Three genotypes (Karp-like, Kato-like and TA763-like) of O. tsutsugamushi were found from Yunnan, China in this study. [ABSTRACT FROM AUTHOR]

Activity recognition is one of the significant technologies accompanying the development of the Internet of Things (IoT). It can help in recording daily life activities or reporting emergencies, thus improving the user's quality of life and safety, and even easing the workload of caregivers. This study proposes a human activity recognition (HAR) system based on activity data obtained via the micro-Doppler effect, combining a two-stream one-dimensional convolutional neural network (1D-CNN) with a bidirectional gated recurrent unit (BiGRU). Initially, radar sensor data are used to generate information related to time and frequency responses using short-time Fourier transform (STFT). Subsequently, the magnitudes and phase values are calculated and fed into the 1D-CNN and Bi-GRU models to extract spatial and temporal features for subsequent model training and activity recognition. Additionally, we propose a simple cross-channel operation (CCO) to facilitate the exchange of magnitude and phase features between parallel convolutional layers. An open dataset collected through radar, named Rad-HAR, is employed for model training and performance evaluation. Experimental results demonstrate that the proposed 1D-CNN+CCO-BiGRU model demonstrated superior performance, achieving an impressive accuracy rate of 98.2%. This outperformance of existing systems with the radar sensor underscores the proposed model's potential applicability in real-world scenarios, marking a significant advancement in the field of HAR within the IoT framework. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to construct a model based on 23 enrolled molecules to evaluate prognoses of pT2/3N0M0 esophageal squamous cell carcinoma (ESCC) patients with up to 20 years of follow-up. Methods: The lasso-Cox model was used to identify the candidate molecule. A nomogram was conducted to develop the survival model (molecular score, MS) based on the molecular features. Cox regression and Kaplan-Meier analysis were used in this study. The concordance index (C-index) was measured to compare the predicted ability between different models. The primary endpoint was overall survival (OS). Results: A total of 226 patients and 23 proteins were enrolled in this study. Patients were classified into high-risk (MS-H) and low-risk (MS-L) groups based on the MS score of 227. The survival curves showed that the MS-L cohort had better 5-year and 10-year survival rates than the MS-H group (5-year OS: 51.0% vs. 8.0%; 10-year OS: 45.0% vs. 5.0%, all p < 0.001). Furthermore, multivariable analysis confirmed MS as an independent prognostic factor after eliminating the confounding factors (Hazard ratio 3.220, p < 0.001). The pT classification was confirmed to differentiate ESCC patients' prognosis (Log-rank: p = 0.029). However, the combination of pT and MS could classify survival curves evidently (overall p < 0.001), which showed that the prognostic prediction efficiency was improved significantly by the combination of the pT and MS than by the classical pT classification (C-index: 0.656 vs. 0.539, p < 0.001). Conclusions: Our study suggested an MS for significant clinical stratification of T2/3N0M0 ESCC patients to screen out subgroups with poor prognoses. Besides, the combination of pT staging and MS could predict survival more accurately for this cohort than the pT staging system alone. [ABSTRACT FROM AUTHOR]

Photodynamic therapy (PDT) is a promising treatment against bacteria‐caused infections. By producing large amounts of reactive oxygen species (ROS), PDT can effectively eliminate pathogenic bacteria, without causing drug resistance. However, excessive ROS may also impose an oxidative stress on surrounding tissues, resulting in local inflammation. To avoid this major drawback and limit pro‐inflammation during PDT, this work prepared a supramolecular photosensitizer (TPP‐CN/CP5) based on host‐guest interactions between a cysteine‐responsive cyano‐tetraphenylporphyrin (TPP‐CN) and a water‐soluble carboxylatopillar[5]arene (CP5). TPP‐CN/CP5 not only possesses excellent photodynamic antibacterial properties, but also shows good anti‐inflammatory and cell protection capabilities. Under 660 nm light irradiation, TPP‐CN/CP5 could rapidly produce abundant ROS for sterilization. After the PDT process, the addition of cysteine (Cys) triggers the release of H2S from TPP‐CN. H2S then stops the induced inflammation by inhibiting the production of related inflammatory factors. Both in vitro and in vivo experiments show the excellent antibacterial effects and anti‐inflammatory abilities of TPP‐CN/CP5. These results will certainly promote the clinical application of PDT in the treatment of bacterial infectious diseases. [ABSTRACT FROM AUTHOR]

In this work, we present an extensive analysis of the thermodynamics and holographic properties of three-dimensional C-metrics in the FG gauge, where we find that the free energy is equal to the Euclidean on-shell action with a generic conformal factor. For the black hole solutions we find that Smarr relation and the first law of thermodynamics can be formulated when the contributions of the boundary entropy are considered. We also compute holographic entanglement entropy following the AdS/BCFT formalism. By comparing the free energies of different bulk solutions with a fixed flat torus boundary geometry, we find that a specific type of accelerating black hole is dominant in the high temperature regime. [ABSTRACT FROM AUTHOR]

The Yellow River Basin (YRB) is an important region for both ecological and economic growth in China, and a healthy and stable ecological environment is fundamental to achieving high-quality development. Investigating the spatio-temporal changs of vegetation carbon sinks in the YRB is necessary to improve understanding of the regional carbon cycle. This study analyzed the YRB using the Google Earth Engine (GEE) platform. The basin was divided into sections based on ecological function regionalization schemes. We applied Theil-Sen median trend analysis and Spearman correlation analysis, along with the lasso regression model, to examine the NPP's temporal and spatial patterns and its driving factors in these regions. The objective was to examine the NPP' s temporal and spatial patterns and its driving factors in these regions, identifying commonalities within regions and differences between regions, while analyzing in a targeted manner the lack of vegetation carbon sequestration in ecological areas. This study highlighted the importance of ecological engineering in ecological civilization and carbon neutrality, providing scientific theoretical support and a decision-making basis for the realization of carbon neutrality. The research results indicate significant upward trends (p <0.001) in both the average annual NPP (AANPP) growth rate (57.98%) and the total annual NPP (TANPP) growth rate (41.9%) in the YRB from 2001 to 2020. The multi-year average NPP (MYANPP) exhibit a spatial distribution with high values in the south and low values in the north. The spatial distribution of NPP exhibits notable spatial aggregation and heterogeneity, where regions demonstrating improvement trends constitute 93.01% of the area, and approximately 79.73% of this region displays low volatility. A high-value area is concentrated in the Agroecological Zone of the Fenwei Basin (I-11), the Loess Plateau Agriculture and Grassland Ecological Zone (I-12), and the Qinba Mountains Deciduous and Evergreen Broad-leaved Forest Ecological Zone (I-15), with significant spatial differences. Temperature, precipitation, and forests are the foremost elements affecting NPP in the YRB, exhibiting positive correlations. Conversely, farmland displays negative correlations. Overall, NPP shows an increasing trend in all ecological function areas, and the NPP of the YRB shows a trend of improvement as a whole, as the ecological environment of the YRB has improved significantly. • Significant differences in NPP were observed among ecological functional zones. • The vegetation condition of the Yellow River Basin has been improved continuously. • Population, temperature, precipitation, forest were the main driving factor of NPP. • The average annual NPP and the total annual NPP increased significantly. [ABSTRACT FROM AUTHOR]

[Display omitted] • We propose a novel decoupled Image and Frequency-domain Spatial-Spectral Framework. • The proposed module extracts multi-scale features from dual domains. • A module can transfer the advantages of convolution to the transformer. • The proposed neural network can achieve better performance. Hyperspectral image classification (HSIC) is a rapidly developing field that utilizes deep learning methods. However, the reliance on convolutional neural networks (CNNs) for spectral–spatial feature extraction presents certain limitations. Specifically, the use of the fixed-position convolutional kernels in CNNs hinders their ability to capture fully the spectral information around the spatial central pixel, thereby overlooking critical differences between features. To address this issue, a decoupled image- and frequency-domain spectral–spatial framework for HSIC was developed in this study. This method incorporates image- and frequency-domain-based multiscale learnable convolutional attention to refine the differentiating features of the different feature distributions. Additionally, a novel frequency-domain information enhancement module was designed to extract the structural shape and texture details under the semantic constraints of the frequency phase, complementing the image domain to improve the extracted feature maps. Furthermore, a simple and efficient hierarchical feature representation module was introduced to extract both local and global information effectively from the fused features. The experimental results obtained using three open datasets and a practical hyperspectral image of the Gaofen-5 satellite demonstrate that the proposed method outperforms other state-of-the-art HSIC methods. [ABSTRACT FROM AUTHOR]

As the invasion of alien species intensifies, the native salt marsh vegetation, especially the ecosystem of Suaeda salsa (S. salsa), in Chinese coastal wetlands has been severely disrupted, significantly impeding its functionality within coastal wetland ecosystems. Chlorophyll content (C ab) is an important parameter for monitoring the growth and health status of vegetation. However, the remote sensing mechanism of C ab for different phenotypes of green and red vegetation influenced by betacyanin under different water and salt conditions is not clear. Therefore, to further clarify the remote sensing mechanism of S. salsa and improve the generality of C ab prediction for different phenotypes under different water and salt conditions, we designed a growth experiment under different groundwater levels and salt concentrations. This experiment was used to simulate the growth of S. salsa in different habitats in nature and investigate the relationship between their physicochemical parameters, spectra, and environmental stress. We propose using the specific absorption coefficient of betacyanin (Beta) to adjust PROSAIL-D to better fit the spectral characteristics of S. salsa. The relationship between Beta and C ab was utilized to further optimize the simulation accuracy of the PROSAIL-D model in different environments. Feature extraction algorithms, including differential enhancement of two-dimensional correlation spectroscopy (FD-2DCOS) and three-band models, were introduced to construct multiple spectral features for establishing a C ab prediction model for S. salsa. The research results showed that: (1) S. salsa had the best response of C ab and spectra to salinity under a higher groundwater level and showed a gradual reddening trend. (2) The spectral curves simulated by the adjusted PROSAIL-D model were more consistent with the spectral characteristics of S. salsa under different water-salt environments, and the simulation effect could be further optimized by using the relationship between Beta and C ab. (3) The FD-2DCOS analysis method we proposed could highlight the useful spectral information related to C ab better than the original 2DCOS algorithm. The final eight spectral features of (1/R 701 –1/R 540)R 540 , Mean(D 590 – 600), Mean(D 660 – 670), Mean(D 677 – 685), FDVI_NRG, FDVI_NIR, Skewness (D 677 – 750) and Position(D 677 – 750) had the best response to C ab of S. salsa , and had the least influence on LAI and soil background. (4) The particle swarm optimization random forest regression (PSO-RFR) model based on eight spectral features and adding 70% measured spectral data performed the best in predicting the actual C ab of S. salsa , with an RMSE of 2.326 μg·cm−2. Although further optimization and calibration of the adjusted PROSAIL-D model and C ab prediction model of S. salsa are needed in the future, this study extended its application to S. salsa , a special local salt marsh vegetation, and promoted the development of C ab monitoring of salt marsh vegetation in coastal wetlands. • C ab of Suaeda salsa responds best to salinity stress under high groundwater table. • The adjusted PROSAIL-D model is more suitable for the simulation of Suaeda salsa. • Pay attention to the ratio of betacyanin and C ab when using PROSAIL-D simulation. • The proposed FD-2DCOS can better highlight the information of C ab in the spectrum. • The constructed PSO-RFR model can better predict the C ab of Suaeda salsa. [ABSTRACT FROM AUTHOR]

The best solution to address environmental pollution caused by arsenic-containing hazardous waste is to prepare high-purity elemental arsenic from such waste. The key to this approach lies in the efficient separation of arsenic from various impurities. This paper presents a viable solution for producing high-purity elemental arsenic from arsenic-alkali slag, and the keylies in utilizing the selective precipitation of magnesium ammonium arsenate (MgNH 4 AsO 4) to achieve efficient separation of arsenic from alkali, antimony, and other impurities. Thermodynamic analysis and hydrometallurgical condition experiments indicate that in complex alkaline arsenic-containing solutions, over 90% of arsenic components can selectively precipitate in the form of MgNH 4 AsO 4. The content of arsenic in the resulting precipitate reaches approximately 30%, while the content of antimony is below 0.1%. This achieves efficient enrichment of arsenic and preliminary separation of impurities in complex arsenic-alkali slag. Thermodynamic analysis and pyrometallurgical condition experiments demonstrate that the precipitate of MgNH 4 AsO 4 can be reduced to elemental arsenic with an arsenic content reaching 99.85%, and an antimony content as low as 0.05%. This achieves a profound separation of arsenic from impurities. Based on the research presented in this paper, a production line was established that enables the deep resource utilization of arsenic-alkali slag. [Display omitted] • The deep resource utilization of AAS was realized. • The arsenic in the AAS was separated in the form of MgNH 4 AsO 4. • 3. The MgNH 4 AsO 4 precipitate was reduced to elemental arsenic. • An annual AAS disposal line of 20,000 tons has been built. [ABSTRACT FROM AUTHOR]

In this paper, an energy-stable finite element method with the Crank–Nicolson type of temporal discretization scheme is developed and analyzed for a class of nonlinear fourth-order parabolic equations (including the Swift–Hohenberg (SH) equation and the extended Fisher–Kolmogorov (EFK) equation). In addition to the energy stability properties, the optimal spatial convergence properties in both L ∞ (L 2) - and L ∞ (H 1) -norm and the second-order temporal approximation rate are also obtained for numerical solutions approximating to the real solution and its Laplacian for the developed energy-stable finite element method in both semi- and fully discrete schemes. Numerical experiments are carried out to validate all attained theoretical results. • Energy-stable FEM is developed for a class of nonlinear fourth-order parabolic equations. • The model is more general than Swift–Hohenberg/extended Fisher–Kolmogorov equation. • Semi-discrete and Crank–Nicolson/fully discrete schemes are developed and analyzed. • The discrete energy is proved to be stable all the time for both schemes. • Optimal convergences in both L ∞ (H 1) - and L ∞ (L 2) -norm are obtained for both schemes. • Numerical results of 7 numerical experiments agree with all theoretical results. [ABSTRACT FROM AUTHOR]

The precise recognition and sensing of steroids, a type of vital biomolecules, hold immense practical value across various domains. In this study, we introduced corral[4]BINOLs (C[4]BINOLs), a pair of enantiomeric conjugated deep‐cavity hosts, as novel synthetic receptors for binding steroids. Due to the strong hydrophobic effect of their deep nonpolar, chiral cavities, the two enantiomers of C[4]BINOLs demonstrated exceptionally high recognition affinities (up to 1012 M−1) for 16 important steroidal compounds as well as good enantioselectiviy (up to 15.5) in aqueous solutions, establishing them as the most potent known steroid receptors. Harnessing their ultrahigh affinity, remarkable enantioselectivity, and fluorescence emission properties, the two C[4]BINOL enantiomers were employed to compose a fluorescent sensor array which achieved discrimination and sensing of 16 structurally similar steroids at low concentrations. [ABSTRACT FROM AUTHOR]

The precise recognition and sensing of steroids, a type of vital biomolecules, hold immense practical value across various domains. In this study, we introduced corral[4]BINOLs (C[4]BINOLs), a pair of enantiomeric conjugated deep‐cavity hosts, as novel synthetic receptors for binding steroids. Due to the strong hydrophobic effect of their deep nonpolar, chiral cavities, the two enantiomers of C[4]BINOLs demonstrated exceptionally high recognition affinities (up to 1012 M−1) for 16 important steroidal compounds as well as good enantioselectiviy (up to 15.5) in aqueous solutions, establishing them as the most potent known steroid receptors. Harnessing their ultrahigh affinity, remarkable enantioselectivity, and fluorescence emission properties, the two C[4]BINOL enantiomers were employed to compose a fluorescent sensor array which achieved discrimination and sensing of 16 structurally similar steroids at low concentrations. [ABSTRACT FROM AUTHOR]

Simple Summary: Bartonella is an intracellular parasitic zoonotic pathogen that can infect animals and cause a variety of human diseases. The prevalence and the copy number of Bartonella spp. in different tissues in small mammals were studied using conventional PCR and real-time quantitative PCR in Yunnan Province, China. Results showed a 31.5% detection rate, varying across species. Genetic analysis identified thirty, ten, and five strains based on ssrA, rpoB, and gltA genes, with nucleotide identities ranging from 92.1% to 100.0%. Seven species of Bartonella were identified, including B. grahamii, B. rochalimae, B. sendai, B. koshimizu, B. phoceensis, B. taylorii, and a new species in Episoriculus leucops (GS136). Analysis of the different tissues naturally infected by Bartonella spp. revealed varied copy numbers across different tissues, with the highest load in spleen tissue. These findings underscore Bartonella's species diversity and host range in Yunnan Province, highlighting the presence of extensive tissue tropism in Bartonella spp. naturally infecting small mammalian tissues. Bartonella is an intracellular parasitic zoonotic pathogen that can infect animals and cause a variety of human diseases. This study investigates Bartonella prevalence in small mammals in Yunnan Province, China, focusing on tissue tropism. A total of 333 small mammals were sampled from thirteen species, three orders, four families, and four genera in Heqing and Gongshan Counties. Conventional PCR and real-time quantitative PCR (qPCR) were utilized for detection and quantification, followed by bioinformatic analysis of obtained DNA sequences. Results show a 31.5% detection rate, varying across species. Notably, Apodemus chevrieri, Eothenomys eleusis, Niviventer fulvescens, Rattus tanezumi, Episoriculus leucops, Anourosorex squamipes, and Ochotona Thibetana exhibited infection rates of 44.4%, 27.7%, 100.0%, 6.3%, 60.0%, 23.5%, and 22.2%, respectively. Genetic analysis identified thirty, ten, and five strains based on ssrA, rpoB, and gltA genes, with nucleotide identities ranging from 92.1% to 100.0%. Bartonella strains were assigned to B. grahamii, B. rochalimae, B. sendai, B. koshimizu, B. phoceensis, B. taylorii, and a new species identified in Episoriculus leucops (GS136). Analysis of the different tissues naturally infected by Bartonella species revealed varied copy numbers across different tissues, with the highest load in spleen tissue. These findings underscore Bartonella's diverse species and host range in Yunnan Province, highlighting the presence of extensive tissue tropism in Bartonella species naturally infecting small mammalian tissues. [ABSTRACT FROM AUTHOR]

• Aging of FeS nanoparticles seriously affects arsenic removal but slight on copper. • Controllable FeS are the targeted sulfurizing agents in different acidity wastewater. • BP-GA model are developed to precisely predict copper and arsenic removal with R of 0.9923. • Temperature and FeS aging time are necessary to gain high separation accuracy. • The model provides an essential reference in selecting sulfurizing reagent types. Iron sulfide (FeS) is a promising material for separating copper and arsenic from strongly acidic wastewater due to its S2− slow-release effect. However, uncertainties arise because of the constant changes in wastewater composition, affecting the selection of operating parameters and FeS types. In this study, the aging method was first used to prepare various controllable FeS nanoparticles to weaken the arsenic removal ability without affecting the copper removal. Orthogonal experiments were conducted, and the results identified the Cu/As ratio, H 2 SO 4 concentration, and FeS dosage as the three main factors influencing the separation efficiency. The backpropagation artificial neural network (BP-ANN) model was established to determine the relationship between the influencing factors and the separation efficiency. The correlation coefficient (R) of overall model was 0.9923 after optimizing using genetic algorithm (GA). The BP-GA model was also solved using GA under specific constraints, predicting the best solution for the separation process in real-time. The predicted results show that the high temperature and long aging time of FeS were necessary to gain high separation efficiency, and the maximum separation factor can reached 1,400. This study provides a suitable sulfurizing material and a set of methods and models with robust flexibility that can successfully predict the separation efficiency of copper and arsenic from highly acidic environments. [Display omitted] [ABSTRACT FROM AUTHOR]

• A porous hollow molecularly imprinted microsphere was synthesized by O/W/O composite emulsion polymerization. • The obtained microspheres were superparamagnetic and thermo-responsive. • The HMMIM adsorption capacity toward BSA was 89.9 mg/g and a good separation efficacy toward BSA was observed in bovine whole blood. Molecular imprinting technology is highly successful for low-molecular-weight molecules, but is still confronted with many challenges for proteins. This study introduces a strategy to synthesize hollow magnetic molecularly imprinted microspheres (HMMIMs) under Fe 3 O 4 magnetic nanoparticles matrix, by oil-in-water-in-oil composite emulsion polymerization with alkylphenol ethoxylates and Span-80 as emulsifiers. The synthesis conditions after optimization were 1.0 mmol thermo-sensitive functional monomer N-isopropylacrylamide, 1.0 mmol cross-linker N, N-methylene bisacrylamide, 2.0 wt% vinyl-modified silk fibroin, and 50 mg Fe 3 O 4 @COOH nanoparticles. The morphology structure and the forming process of the acquired HMMIMs were well characterized by POM, SEM, TEM and FT-IR. The HMMIMs were synthesized successfully with a porous structure and large specific surface area. The particle size of the obtained HMMIMs was at 10–20 µm. The obtained microspheres were superparamagnetic and thermo-responsive. The HMMIM adsorption capacity at 25 °C toward bovine serum albumin (BSA) was 89.9 mg/g and the BSA separation factor in BSA/BHb mixtures was 2.12. A good separation efficacy toward BSA was also observed in bovine whole blood. The prepared HMMIM possessed heterogeneous active sites, the BSA adsorption process on HMMIM was chemisorption controlled. [ABSTRACT FROM AUTHOR]

Insects are rich in various microorganisms, which play diverse roles in affecting host biology. Although most Drosophila species prefer rotten fruits, the agricultural pest Drosophila suzukii attacks ripening fruits before they are harvested. We have reported that the microbiota has positive and negative impacts on the agricultural pest D. suzukii on nutrient‐poor and ‐rich diets, respectively. On nutrient‐poor diets, microbes provide protein to facilitate larval development. But how they impede D. suzukii development on nutrient‐rich diets is unknown. Here we report that Acetobacter pomorum (Apo), a commensal bacterium in many Drosophila species and rotting fruit, has several detrimental effects in D. suzukii. Feeding D. suzukii larvae nutrient‐rich diets containing live Apo significantly delayed larval development and reduced the body weight of emerged adults. Apo induced larval immune responses and downregulated genes of digestion and juvenile hormone metabolism. Knockdown of these genes in germ‐free larvae reproduced Apo‐like weakened phenotypes. Apo was confirmed to secrete substantial amounts of gluconic acid. Adding gluconic acid to the D. suzukii larval diet hindered larval growth and decreased adult body weight. Moreover, the dose of gluconic acid that adversely affected D. suzukii did not negatively affect Drosophila melanogaster, suggesting that D. suzukii is less tolerant to acid than D. melanogaster. Taken together, these findings indicate that D. suzukii is negatively affected by gluconic acid, which may explain why it prefers ripening fruit over Apo‐rich rotting fruit. These results show an insect's tolerance to microbes can influence its ecological niche. [ABSTRACT FROM AUTHOR]

Radiation injury (RI) is a common occurrence in malignant tumors patients receiving radiation therapy. While killing tumor cells, normal tissue surrounding the target area is inevitably irradiated at a certain dose, which can cause varying results of radiation injury. Currently, there are limited clinical treatments available for radiation injuries. In recent years, the negative effects of stem cell therapy have been reported more clearly and non-cellular therapies such as exosomes have become a focus of attention for researchers. As a type of vesicle-like substances secreted by mesenchymal stem cells (MSC), MSC derived exosomes (MSC-exo) carry DNA, mRNA, microRNA (miRNAs), specific proteins, lipids, and other active substances involved in intercellular information exchange. miRNAs released by MSC-exo are capable of alleviating and repairing damaged tissues through anti-apoptosis, modulating immune response, regulating inflammatory response and promoting angiogenesis, which indicates that MSC-exo miRNAs have great potential for application in the prevention and treatment of radiation injury. Therefore, it is necessary to explore the underlying therapeutic mechanisms of MSC-exo miRNAs in this process, which may shed new lights on the treatment of radiation injury. Increasing evidence confirms that MSC-exo has shown encouraging applications in tissue repair due to the anti-apoptotic, immunoreactive, and pro-angiogenesis effects of the miRNAs it carries as intercellular communication carriers. However, miRNA-based therapeutics are still in their infancy and many practical issues remain to be addressed for clinical applications. [ABSTRACT FROM AUTHOR]

Scene text detection is an important research field in computer vision, playing a crucial role in various application scenarios. However, existing scene text detection methods often fail to achieve satisfactory results when faced with text instances of different sizes, shapes, and complex backgrounds. To address the challenge of detecting diverse texts in natural scenes, this paper proposes a multi-scale natural scene text detection method based on attention feature extraction and cascaded feature fusion. This method combines global and local attention through an improved attention feature fusion module (DSAF) to capture text features of different scales, enhancing the network's perception of text regions and improving its feature extraction capabilities. Simultaneously, an improved cascaded feature fusion module (PFFM) is used to fully integrate the extracted feature maps, expanding the receptive field of features and enriching the expressive ability of the feature maps. Finally, to address the cascaded feature maps, a lightweight subspace attention module (SAM) is introduced to partition the concatenated feature maps into several sub-space feature maps, facilitating spatial information interaction among features of different scales. In this paper, comparative experiments are conducted on the ICDAR2015, Total-Text, and MSRA-TD500 datasets, and comparisons are made with some existing scene text detection methods. The results show that the proposed method achieves good performance in terms of accuracy, recall, and F-score, thus verifying its effectiveness and practicality. [ABSTRACT FROM AUTHOR]

The common deleterious genetic defects in Holstein cattle include haplotypes 1–6 (HH1–HH6), haplotypes for cholesterol deficiency (HCD), bovine leukocyte adhesion deficiency (BLAD), complex vertebral malformation (CVM) and brachyspina syndrome (BS). Recessive inheritance patterns of these genetic defects permit the carriers to function normally, but homozygous recessive genotypes cause embryo loss or neonatal death. Therefore, rapid detection of the carriers is essential to manage these genetic defects. This study was conducted to develop a single‐tube multiplex fluorescent amplification–refractory mutation system (mf‐ARMS) PCR method for efficient genotyping of these 10 genetic defects and to compare its efficiency with the kompetitive allele specific PCR (KASP) genotyping assay. The mf‐ARMS PCR method introduced 10 sets of tri‐primers optimized with additional mismatches in the 3′ end of wild and mutant‐specific primers, size differentiation between wild and mutant‐specific primers, fluorescent labeling of universal primers, adjustment of annealing temperatures and optimization of primer concentrations. The genotyping of 484 Holstein cows resulted in 16.12% carriers with at least one genetic defect, while no homozygous recessive genotype was detected. This study found carrier frequencies ranging from 0.0% (HH6) to 3.72% (HH3) for individual defects. The mf‐ARMS PCR method demonstrated improved detection, time and cost efficiency compared with the KASP method for these defects. Therefore, the application of mf‐ARMS PCR for genotyping Holstein cattle is anticipated to decrease the frequency of lethal alleles and limit the transmission of these genetic defects. [ABSTRACT FROM AUTHOR]

AbstractHeart failure (HF) is the leading cause of death from cardiovascular disease, and early diagnosis using serum markers holds extraordinary significance for the treatment of patients. N-terminal brain natriuretic peptide (NT-proBNP) is the gold standard for HF diagnosis. Herein, a novel, rapid, sensitive, and immune-sensing strategy for NT-proBNP is reported employing an enzyme-linked immunosorbent assay (ELISA) that combines the use of magnetic biological probes and the fluorogenic substrate Ampliflu Red. Functionalized immunomagnetic nanoparticles with large surface areas provide an abundant reaction platform and reduce the analysis time due to their superparamagnetic properties. Ampliflu Red is catalyzed by horseradish peroxidase (HRP) using hydrogen peroxide (H2O2) to produce strong fluorescence and a low background. The reported method achieved a good detection limit of 2.73 ng mL−1 and a wide linear range from 3.13 to 100 ng mL−1. The analysis time was less than 1 h, which is superior to that of traditional ELISA (3–4 h). In addition, the recoveries of spiked human serum were satisfactory, indicating that the proposed strategy has potential applications for the rapid determination of NT-proBNP and other biomarkers in clinical settings. [ABSTRACT FROM AUTHOR]

With the increase in the scale of breeding at modern pastures, the management of dairy cows has become much more challenging, and individual recognition is the key to the implementation of precision farming. Based on the need for low-cost and accurate herd management and for non-stressful and non-invasive individual recognition, we propose a vision-based automatic recognition method for dairy cow ear tags. Firstly, for the detection of cow ear tags, the lightweight Small-YOLOV5s is proposed, and then a differentiable binarization network (DBNet) combined with a convolutional recurrent neural network (CRNN) is used to achieve the recognition of the numbers on ear tags. The experimental results demonstrated notable improvements: Compared to those of YOLOV5s, Small-YOLOV5s enhanced recall by 1.5%, increased the mean average precision by 0.9%, reduced the number of model parameters by 5,447,802, and enhanced the average prediction speed for a single image by 0.5 ms. The final accuracy of the ear tag number recognition was an impressive 92.1%. Moreover, this study introduces two standardized experimental datasets specifically designed for the ear tag detection and recognition of dairy cows. These datasets will be made freely available to researchers in the global dairy cattle community with the intention of fostering intelligent advancements in the breeding industry. [ABSTRACT FROM AUTHOR]

Summary In wireless charging systems for electric vehicles, fluctuations in coil mutual inductance can affect both system output power and efficiency. This paper introduces a coil mutual inductance model that accounts for metal shielding material. The formula for coil mutual inductance is derived using Maxwell's equations and boundary conditions. Additionally, the paper presents a tactic for adapting the mutual inductance with the aid of an intelligent optimization algorithm, which is utilized for steadying the mutual inductance of the transmission coil. Lastly, a model of the transmission coil is developed to authenticate the practicality of the mutual inductance equation and the adaptation scheme. Measurement and calculation results indicate that the difference between the calculated value of the mutual inductance formula and the actual mutual inductance value of the coil, following deflection and offset, is below 5%. Moreover, the algorithm, along with the employed adaptation strategy, consistently demonstrates effectiveness in maintaining the mutual inductance value within a predefined range. The temporal efficiency of the algorithm, as measured by the time taken to determine this coordinate position, is consistently under 1 s. This ensures that the algorithm exhibits a rapid response time, a crucial attribute in ensuring its practical utility. [ABSTRACT FROM AUTHOR]

Polypeptides, as natural polyelectrolytes, are assembled into tailored proteins to integrate chromophores and catalytic sites for photosynthesis. Mimicking nature to create the water‐soluble nanoassemblies from synthetic polyelectrolytes and photocatalytic molecular species for artificial photosynthesis is still rare. Here, we report the enhancement of the full‐spectrum solar‐light‐driven H2 production within a supramolecular system built by the co‐assembly of anionic metalloporphyrins with cationic polyelectrolytes in water. This supramolecular photocatalytic system achieves a H2 production rate of 793 and 685 μmol h−1 g−1 over 24 h with a combination of Mg or Zn porphyrin as photosensitizers and Cu porphyrin as a catalyst, which is more than 23 times higher than that of free molecular controls. With a photosensitizer to catalyst ratio of 10000 : 1, the highest H2 production rate of >51,700 μmol h−1 g−1 with a turnover number (TON) of >1,290 per molecular catalyst was achieved over 24 h irradiation. The hierarchical self‐assembly not only enhances photostability through forming ordered stackings of the metalloporphyrins but also facilitates both energy and electron transfer from antenna molecules to catalysts, and therefore promotes the photocatalysis. This study provides structural and mechanistic insights into the self‐assembly enhanced photostability and catalytic performance of supramolecular photocatalytic systems. [ABSTRACT FROM AUTHOR]

Polypeptides, as natural polyelectrolytes, are assembled into tailored proteins to integrate chromophores and catalytic sites for photosynthesis. Mimicking nature to create the water‐soluble nanoassemblies from synthetic polyelectrolytes and photocatalytic molecular species for artificial photosynthesis is still rare. Here, we report the enhancement of the full‐spectrum solar‐light‐driven H2 production within a supramolecular system built by the co‐assembly of anionic metalloporphyrins with cationic polyelectrolytes in water. This supramolecular photocatalytic system achieves a H2 production rate of 793 and 685 μmol h−1 g−1 over 24 h with a combination of Mg or Zn porphyrin as photosensitizers and Cu porphyrin as a catalyst, which is more than 23 times higher than that of free molecular controls. With a photosensitizer to catalyst ratio of 10000 : 1, the highest H2 production rate of >51,700 μmol h−1 g−1 with a turnover number (TON) of >1,290 per molecular catalyst was achieved over 24 h irradiation. The hierarchical self‐assembly not only enhances photostability through forming ordered stackings of the metalloporphyrins but also facilitates both energy and electron transfer from antenna molecules to catalysts, and therefore promotes the photocatalysis. This study provides structural and mechanistic insights into the self‐assembly enhanced photostability and catalytic performance of supramolecular photocatalytic systems. [ABSTRACT FROM AUTHOR]

Exposure to gestational diabetes mellitus (GDM) during pregnancy has significant consequences for the unborn baby and newborn infant. However, whether and how GDM exposure induces the development of neonatal brain hypoxia/ischemia-sensitive phenotype and the underlying molecular mechanisms remain unclear. In this study, we used a late GDM rat model induced by administration of streptozotocin (STZ) on gestational day 12 and investigated its effects of GDM on neonatal brain development. The pregnant rats exhibited increased blood glucose levels in a dose-dependent manner after STZ administration. STZ-induced maternal hyperglycemia led to reduced blood glucose levels in neonatal offspring, resulting in growth restriction and an increased brain to body weight ratio. Importantly, GDM exposure increased susceptibility to hypoxia/ischemia (HI)-induced brain infarct sizes compared to the controls in both male and female neonatal offspring. Further molecular analysis revealed alterations in the PTEN/AKT/mTOR/autophagy signaling pathway in neonatal male offspring brains, along with increased ROS production and autophagy-related proteins (Atg5 and LC3-II). Treatment with the PTEN inhibitor bisperoxovanadate (BPV) eliminated the differences in HI-induced brain infarct sizes between the GDM-exposed and the control groups. These findings provide novel evidence of the development of a brain hypoxia/ischemia-sensitive phenotype in response to GDM exposure and highlight the role of the PTEN/AKT/mTOR/autophagy signaling pathway in this process. • STZ-induced maternal hyperglycemia (GDM) decreases neonatal offspring blood glucose levels. • Prenatal exposure to GDM produces a growth restriction and asymmetrical brain development. • GDM exposure causes alterations in the PTEN/AKT/mTOR/autophagy signaling pathway in neonatal offspring. • Prenatal GDM exposure programs a hypoxia/ischemia (HI)-sensitive phenotype of neonatal brain. [ABSTRACT FROM AUTHOR]

• Enhanced nonlinear optical properties were observed in Cr 2 AlB 2 /PbS vdW heterostructure. • The enhancements of nonlinear optical properties can be attributed to the carrier migration between Cr 2 AlB 2 and PbS. • Stable conventional soliton output is experimentally demonstrated by using Cr 2 AlB 2 SA and Cr 2 AlB 2 /PbS vdW heterostructure SA, respectively. Rapid progress has been realized in the nonlinear optical device applications of 2D materials. 2D materials are attractive due to their characteristics optical nonlinearities and distinctive light-matter interactions, which assure them promising nonlinear optical devices for ultrashort pulses generating. Cr 2 AlB 2 , a member of the new series of 2D materials known as MBenes, has been predicted to have potential saturable absorption properties. In this study, the saturable absorption properties of Cr 2 AlB 2 and Cr 2 AlB 2 /PbS vdW heterostructure SAs are investigated. In comparison with Cr 2 AlB 2 , the Cr 2 AlB 2 /PbS vdW heterostructure exhibits better saturable absorption. The enhancements of nonlinear optical properties can be attributed to the carrier migration between heterostructure. The simulation results based on the Ginzburg-Landu equation are employed to predict the laser performances of Cr 2 AlB 2 and Cr 2 AlB 2 /PbS heterostructure SA. By incorporating SAs in the cavity, highly stable conventional solitons were observed. Both simulation and experimental results demonstrate that Cr 2 AlB 2 /PbS vdW heterostructure has superior pulse performance compared to the Cr 2 AlB 2 SA. These results demonstrate that Cr 2 AlB 2 /PbS vdW heterostructure processes better saturable absorption properties and serves as a promising SA in ultrashort pulse generation. [ABSTRACT FROM AUTHOR]

• Enhanced nonlinear optical properties were observed in Mo 4/3 B 2 T 2 /TiO 2 vdW heterostructure. • The enhancement is due to the carrier migration in the heterostructure. • Stable conventional soliton and harmonic solitons output are experimentally demonstrated by using Mo 4/3 B 2 T 2 /TiO 2 heterostructure SA. Van der Waals heterostructure have garnered significant interest in ultrafast laser generation because of their attractive saturable absorption properties, holding promise for application in optics, medicine, and optoelectronics. In this study, the saturable absorption properties of TiO 2 , Mo 4/3 B 2 T 2 , and Mo 4/3 B 2 T 2 /TiO 2 vdW heterostructure SAs are investigated. The integration of the SAs into the cavity reveals the observation of fundamentally conventional solitons. The output characteristics of conventional solitons based on three SAs are recorded. These results suggest that the saturable absorption of Mo 4/3 B 2 T 2 /TiO 2 vdW heterostructure is enhanced obviously compared with that of Mo 4/3 B 2 T 2 and TiO 2. Furthermore, 2nd-, 4th-, and 5th-order harmonic solitons are achieved, corresponding to the repetition rate of 20.36 MHz, 42.71 MHz, and 53.39 MHz, respectively. We established a model in order to understand the saturable absorption properties of the Mo 4/3 B 2 T 2 /TiO 2 , which suggests the enhancements of the saturable absorption are attributed to the carrier migration between Mo 4/3 B 2 T 2 and TiO 2. Our results indicate that Mo 4/3 B 2 T 2 /TiO 2 vdW heterostructure can be used as an excellent nonlinear optical material, which can be used as an SA in ultrafast pulse generation. [ABSTRACT FROM AUTHOR]

• Differential metabolites in milk with high and low milk fat percentage. • Amino acid metabolism can influence milk fat synthesis. • L-Histidine decreased milk fat concentration by inhibiting the triglycerides (TAG) synthesis pathway. • L-aspartic acid and L-Glutamic acid inhibited the milk fat synthesis through the Fatty acid (FA) de novo and TAG synthesis pathways. Milk is widely recognized as an important food source with health benefits. Different consumer groups have different requirements for the content and proportion of milk fat; therefore, it is necessary to investigate the differential metabolites and their regulatory mechanisms in milk with high and low milk fat percentages (MFP). In this study, untargeted metabolomics was performed on milk samples from 13 cows with high milk fat percentage (HF) and 13 cows with low milk fat percentage (LF) using ultra-high performance liquid chromatography coupled with mass spectrometry (UHPLC-MS/MS). Forty-eight potential differentially labeled compounds were screened using the orthogonal partial least squares-discriminant analysis (OPLS-DA) combined with the weighted gene co-expression network analysis (WGCNA) method. Amino acid metabolism was the key metabolic pathway with significant enrichment of L-histidine, 5-oxoproline, L-aspartic acid, and L-glutamic acid. The negative correlation with MFP differentiated the HF and LF groups. To further determine the potential regulatory role of these amino acids on milk fat metabolism, the expression levels of marker genes in the milk fat synthesis pathway were explored. It was noticed that L-histidine reduced milk fat concentration primarily by inhibiting the triglycerides (TAG) synthesis pathway. L-aspartic acid and L-glutamic acid inhibited milk fat synthesis through the fatty acid de novo and TAG synthesis pathways. This study provides new insights into the mechanism underlying milk fat synthesis and milk quality improvement. [ABSTRACT FROM AUTHOR]

Bacterial intestinal inflammation is a common disease of aquatic animal in high-density aquaculture. This study aims to construct a model of intestinal inflammation in northern snakehead, and analyze the intestinal transcriptome after Aeromonas hydrophila (A. hydrophila) infection by high-throughput sequencing technologies (RNA-seq), in order to obtain candidate genes and regulatory pathways that may participate in inflammatory response. Northern snakehead [(13.05 ± 2.39) g] were infected through anal for 24 h with different concentrations of A. hydrophila (1.0 × 10−4, 1.0 × 10−5, 1.0 × 10−6, 1.0 × 10−7 and 1.0 × 10−8 CFU/mL). Intestinal histology observation showed that infection with A. hydrophila caused obvious inflammatory responses in intestine, especially in hindgut. The results also indicated that intestinal permeability related parameters (D-LA and Na+-K+-ATP), immune-related parameters (C3, LZM, AKP, MPO, IL-1β and TNF-α) and immune-related gene expression (il-1β and tnf-α) were significantly changed compared to the CK group. In this process, high concentration of A. hydrophila infection caused the death of snakehead. On the basis of the above evaluation, we successfully constructed a model of intestinal inflammation induced by A. hydrophila in northern snakehead, and the optimal dosage of A. hydrophila was 1.0 × 10−6 CFU/mL. Subsequently, the constructed model was analyzed on the Illumina Genome Analyser II platform for intestinal transcriptome. Results showed that a total of 370,492,420 clean reads, 145,236 transcripts and 89,431 unigenes were obtained. Moreover, a total of 7566 differentially expressed genes (DEGs) were found, including 4486 upregulated genes and 3080 downregulated genes. Notably, the key pathways [Toll-like receptors (TLRs) and NOD-like receptors (NLRs)] and genes [ tlr1 , tlr2 , tlr5 , nf-κb , tnf-α , il-1β , il-10 , nod1 ] related to inflammation were discovered. These results revealed the response of northern snakehead to A. hydrophila at the transcriptional level, which provide insights for the regulatory mechanisms of intestinal inflammation in northern snakehead. • A model of intestinal inflammation in northern snakehead was constructed by Aeromonas hydrophila. • The optimal dosage of Aeromonas hydrophila for inducing intestinal inflammation in northern snakehead was 1.0 × 10−6 CFU/mL. • The key pathways and genes related to inflammation were discovered by high-throughput sequencing technologies. [ABSTRACT FROM AUTHOR]

[Display omitted] • Self-supporting MOF-based carbon nanofiber mat with two types of hollow structure was firstly prepared. • The material has high specific surface area of 935.5 m2 g-1 and total pore volume of 0.69 cm3 g−1 without complex activation process. • The material shows high benzene adsorption of 2.75 mmol g−1 at pressure of 0.1 kPa due to the strong π-π interaction. • Breakthrough adsorption experiments indicate the excellent performance for low-concentration benzene removal under high humidity with reusability. An ultraporous metal-organic framework (MOF)-based carbon nanofiber mat (CNFM4) with two types of hollow structure was prepared by electrospinning the mixed solution with polyacrylonitrile, polymethyl methacrylate and ZIF-8, followed by carbonization. The self-supporting CNFM4 has a higher Brunauer-Emmett-Teller (BET) specific surface area (S BET) (935.5 m2/g) and total pore volume (V total) (0.69 cm3 g−1) than the PAN, PAN/PMMA, PAN/ZIF-8-derived carbon nanofiber mats (CNFMs). Static adsorption experiment showed CNFM4 had a high benzene adsorption capacity of about 12 mmol g−1 at saturated vapor pressure at 298 K, due to its high V total. And even at low pressure of 0.1 kPa, its adsorption capacity still reached 2.75 mmol g−1, owing to its high S BET and rich micropore. The dynamic adsorption study showed CNFM4 has a breakthrough and saturation adsorption amount of 0.4902 and 0.5714 mmol g−1 at dry gas, respectively, and even at 60 RH%, they still can keep 0.2620 and 0.3642 mmol g−1, respectively, suggesting its application potential under the actual environment. The dynamic adsorption study also proves the important role of hollow structure at improving adsorption rate. This work provides a new idea for preparing the ultraporous MOF-based hollow CNFMs, and broadens the application of MOF-based CNFMs for VOCs removal. [ABSTRACT FROM AUTHOR]