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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]

Recently, the concept of half-wormholes is introduced to give a resolution to the factorization puzzle in holography and help understand better the relation between ensemble average theories and gravity in the bulk. Half-wormholes are proposed to be the contributions to the gravitational path integral that correspond to fluctuations of each individual theory around the average of the whole ensemble of theories. In this paper, we further explore the extent to which the half-wormhole interpretation is applicable. In particular, to further demonstrate that the half-wormhole interpretation is not merely a feature of a specific theory but is a general feature of ensemble average theories, we examine various models, including different enriched 0-dimensional SYK-like models, the 1-dimensional Brownian SYK model and its generalization. To further demonstrate that the half-wormhole interpretation applies to more general probability distributions apart from the zero-mean Gaussian distribution, we consider random couplings with other non-trivial moments. Specifically, introducing a non-trivial mean value to the random coupling renders the spectral correlators to exhibit both disconnected saddles and connected saddles. The inclusion of higher-order moments leads to new "multi-linked half-wormhole" saddles. We also clarify the distinctions between the unlinked half-wormhole and the linked half-wormhole in our modified Brownian SYK model. [ABSTRACT FROM AUTHOR]

ADP-ribosylation factor-like protein 13B (ARL13B), a regulatory GTPase and guanine exchange factor (GEF), enriches in primary cilia and promotes tumorigenesis in part by regulating Smoothened (SMO), GLI, and Sonic Hedgehog (SHH) signaling. Gliomas with increased ARL13B, SMO, and GLI2 expression are more aggressive, but the relationship to cilia is unclear. Previous studies have showed that increasing ARL13B in glioblastoma cells promoted ciliary SMO accumulation, independent of exogenous SHH addition. Here, we show that SMO accumulation is due to increased ciliary, but not extraciliary, ARL13B. Increasing ARL13B expression promotes the accumulation of both activated SMO and GLI2 in glioma cilia. ARL13B-driven increases in ciliary SMO and GLI2 are resistant to SMO inhibitors, GDC-0449, and cyclopamine. Surprisingly, ARL13B-induced changes in ciliary SMO/GLI2 did not correlate with canonical changes in downstream SHH pathway genes. However, glioma cell lines whose cilia overexpress WT but not guanine exchange factor-deficient ARL13B, display reduced INPP5e, a ciliary membrane component whose depletion may favor SMO/GLI2 enrichment. Glioma cells overexpressing ARL13B also display reduced ciliary intraflagellar transport 88 (IFT88), suggesting that altered retrograde transport could further promote SMO/GLI accumulation. Collectively, our data suggest that factors increasing ARL13B expression in glioma cells may promote both changes in ciliary membrane characteristics and IFT proteins, leading to the accumulation of drug-resistant SMO and GLI. The downstream targets and consequences of these ciliary changes require further investigation. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) is a critical parameter for the dynamic simulation of land surface processes and for analyzing variations on regional or global scales. Obtaining LST with high spatiotemporal resolution is a subject of intensive and ongoing research. This study proposes a pixel-wise temporal alignment iterative linear regression model for downscaling based on MODIS LST products. This approach allows us to address the problem of high temporal resolution but low spatial resolution of the ERA5 reanalysis LST product while remaining immune to the pixel loss caused by clouds. The hourly ERA5 LST of the study area for 2012–2021 was downscaled to a 1000 m resolution, and its accuracy was verified by comparison with measured data from meteorological stations. The downscaled LST offers intricate details and is faithful to the LST characteristics of distinct land-cover categories. In comparison with other downscaling techniques, the proposed technique is more stable and preserves the spatial distribution of the ERA5 LST with minimal missing pixels. The pixel-wise average R2 and mean absolute error for the MODIS view times are 0.87 and 2.7 K, respectively, for cloud-free conditions on a 1000 m scale. The accuracy verification using data from meteorological stations indicates that the overall error is lower during cloudless periods rather than during overcast periods, during the night rather than during the day, and at MODIS view times rather than at non-view times. The maximum and minimum mean errors are 0.13 K for cloud-free periods and −0.98 K for cloudy periods, indicating a slight underestimation and overestimation, respectively. Conversely, the maximum and minimum mean absolute errors are 2.01 K for the daytime and 0.85 K for the nighttime. Therefore, the model ensures higher accuracy during cloudy periods with only the clear-sky LST used as input data, making it suitable for long-term, all-weather ERA5 LST downscaling. [ABSTRACT FROM AUTHOR]

With the speed of industrialization accelerating, the traditional energy is in the predicament of being exhausted. Humans urgently need a clean energy to maintain the peace and development. Triboelectric nanogenerator (TENG) is a tiny device that collects and converts the renewable energy, such as wind, vibration and tidal/blue energy, into electrical energy. As the most significant working principle of TENG, contact electrification (CE) has been broadly studied since it was documented thousands of years ago. A large number of related researches are reported. However, most of them are focused on the polymer materials, device structures and potential applications. There are few literatures about the mechanism of CE, especially in the semiconductor–semiconductor case. Semiconductor–semiconductor CE is a promising method to generate electricity, which has been used in many fields, such as the photodetector and displacement sensor. Therefore, it is necessary to establish a serious and detailed theory in order to deeply explain the underlying mechanisms of semiconductor–semiconductor CE. In this work, a novel Fermi level model based on energy band theory is proposed to illustrate the semiconductor–semiconductor CE mechanism. By assembling a ZnO/Si vertical contact-separation (CS) mode TENG, the charge transfer introduced by CE is systematically measured. According to the energy band theory and TENG governing equation, the experimental data is qualitatively and quantitatively analyzed. Moreover, the effects of different concentrations of growth solutions on the morphology of ZnO nanowires and the Fermi level difference between ZnO and Si are explored as well. Results show that it is the Fermi level difference that dominates the short circuit transfer charge amount and direction of semiconductor–semiconductor CE mechanism. Our work can be applied to understand the CE mechanism in semiconductor–semiconductor case and broaden the application prospects of semiconductor-based TENG. [ABSTRACT FROM AUTHOR]

This work systematically studies the island formula in the general asymptotically flat eternal black holes in generalized dilaton gravity theories or higher-dimensional spherical black holes. Under some reasonable and mild assumptions, we prove that (the boundary of) the island always appears barely outside the horizon in the late time of Hawking radiation, so the information paradox is resolved. In particular, we find a proper island in the Liouville black hole that solves the previous the puzzle. [ABSTRACT FROM AUTHOR]

In this work, we revisit the calculation of Rényi entropy in AdS3/(B)CFT2. We find that gravity solutions with brane intersection will lead to negative Rényi entropy. [ABSTRACT FROM AUTHOR]

Nucleotides and their derivatives are vital biomarkers that play essential roles in biochemical reactions and influence processes of metabolism and anabolism. However, discriminating between various structurally similar nucleotides and their phosphate derivatives using convenient means still poses a challenge. Here, we designed a supramolecular fluorescence sensor array constructed with four different calixarenes loaded with dyes to discriminate between nucleotides and their phosphate derivatives. Based on the differences in the ability of calixarenes to recognise various nucleotides and nucleotide phosphates, a unique fluorescence response pattern is generated for each analyte. With the assistance of linear discriminant analysis, the discrimination of target analytes is effectively achieved. Subsequent assays involving various concentrations of nucleoside triphosphates and mixtures of nucleotide phosphates have also verified the potential of this sensor array based on calixarenes in the investigation of nucleotides. [ABSTRACT FROM AUTHOR]

In this paper, an energy-conserving finite element method is developed and intensively analyzed for a class of nonlinear fourth-order wave equations in a general sense for the first time, where the two-level, Crank-Nicolson type of temporal discretization scheme is designed to cooperate with the Lagrange finite element approximation in space in order to achieve the conservation of discrete energy at each time step. The energy conservation is crucial in engineering field to preserve the total energy as constant for dynamic vibration problems of beams and thin plates that can be modeled by the presented wave equations. In addition, the optimal spatial convergence properties in both L 2 - and H 1 -norm and the second-order temporal approximation rate are obtained for finite element solutions of u (deflection), Δ u (bending moment) and/or u t (deflection speed) at the same time. Numerical experiments are carried out to validate all attained theoretical results. [ABSTRACT FROM AUTHOR]

Background: Kidney stones are composed of approximately 70–80% calcium oxalate. However, the exact mechanism of formation of calcium oxalate kidney stones remains unclear. In this study, we investigated the roles of endoplasmic reticulum stress (ERS), reactive oxygen species (ROS), and the NF-κB signalling pathway in the pathogenesis of oxalate-induced renal tubular epithelial cell injury and its possible molecular mechanisms. Methods: We established a model to evaluate the formation of kidney stones by intraperitoneal injection of glyoxylic acid solution into mice and assessed cell morphology, apoptosis, and the expression levels of ERS, ROS, and NF-κB signalling pathway-related proteins in mouse renal tissues. Next, we treated HK-2 cells with potassium oxalate to construct a renal tubular epithelial cell injury model. We detected the changes in autophagy, apoptosis, and mitochondrial membrane potential and investigated the ultrastructure of the cells by transmission electron microscopy. Western blotting revealed the expression levels of apoptosis and autophagy proteins; mitochondrial structural and functional proteins; and ERS, ROS, and NF-κB (p65) proteins. Lastly, we studied the downregulation of NF-κB activity in HK-2 cells by lentivirus interference and confirmed the interaction between the NF-κB signalling and ERS/ROS pathways. Results: We observed swelling of renal tissues, increased apoptosis of renal tubular epithelial cells, and activation of the ERS, ROS, and NF-κB signalling pathways in the oxalate group. We found that oxalate induced autophagy, apoptosis, and mitochondrial damage in HK-2 cells and activated the ERS/ROS/NF-κB pathways. Interestingly, when the NF-κB signalling pathway was inhibited, the ERS/ROS pathway was also inhibited. Conclusion: Oxalate induces HK-2 cell injury through the interaction between the NF-κB signalling and ERS/ROS pathways. [ABSTRACT FROM AUTHOR]

Background: Tendon and nerve transfers are used for functional reconstruction in cases of proximal radial nerve injury complicated by humeral fractures in patients who do not show functional recovery after primary nerve repair. The effectiveness of pronator teres (PT) nerve branch transfer to the extensor carpi radialis brevis (ERCB) nerve branch for wrist extension reconstruction was investigated and compared to the results of tendon transfer.Methods: This study included 10 patients with proximal radial nerve injury, who did not show functional recovery after primary nerve repair at our hospital between April 2016 and May 2019. The nerve transfer procedure included PT nerve branch transfer to the ECRB nerve branch to restore wrist extension and the flexor carpi radialis (FCR) nerve branch to the posterior interosseous nerve (PIN) to restore thumb and finger extension. Tendon transfer procedures included PT transfer to the ECRB for wrist extension, FCR transfer to the extensor digitorum communis (EDC) for finger extension and palmaris longus (PL) transfer to the extensor pollicis longus (EPL) for thumb extension.Results: Five patients recovered Medical Research Council grade M4 muscle strength in the ECRB and EPL in both tendon and nerve groups. Two patients recovered grade M3 strength and three patients recovered grade M4 strength in the EDC in the tendon transfer group, and all five patients recovered grade M4 strength in the EDC in the nerve transfer group. Limited wrist flexion was observed only in one patient in the tendon transfer group.Conclusion: PT nerve branch transfer to the ECRB nerve branch combined with FCR nerve branch transfer to PIN is a useful strategy for wrist and fingers extension reconstruction in patients with proximal radial nerve injuries. [ABSTRACT FROM AUTHOR]

Background: Kidney stones are composed of approximately 70–80% calcium oxalate. However, the exact mechanism of formation of calcium oxalate kidney stones remains unclear. In this study, we investigated the roles of endoplasmic reticulum stress (ERS), reactive oxygen species (ROS), and the NF-κB signalling pathway in the pathogenesis of oxalate-induced renal tubular epithelial cell injury and its possible molecular mechanisms. Methods: We established a model to evaluate the formation of kidney stones by intraperitoneal injection of glyoxylic acid solution into mice and assessed cell morphology, apoptosis, and the expression levels of ERS, ROS, and NF-κB signalling pathway-related proteins in mouse renal tissues. Next, we treated HK-2 cells with potassium oxalate to construct a renal tubular epithelial cell injury model. We detected the changes in autophagy, apoptosis, and mitochondrial membrane potential and investigated the ultrastructure of the cells by transmission electron microscopy. Western blotting revealed the expression levels of apoptosis and autophagy proteins; mitochondrial structural and functional proteins; and ERS, ROS, and NF-κB (p65) proteins. Lastly, we studied the downregulation of NF-κB activity in HK-2 cells by lentivirus interference and confirmed the interaction between the NF-κB signalling and ERS/ROS pathways. Results: We observed swelling of renal tissues, increased apoptosis of renal tubular epithelial cells, and activation of the ERS, ROS, and NF-κB signalling pathways in the oxalate group. We found that oxalate induced autophagy, apoptosis, and mitochondrial damage in HK-2 cells and activated the ERS/ROS/NF-κB pathways. Interestingly, when the NF-κB signalling pathway was inhibited, the ERS/ROS pathway was also inhibited. Conclusion: Oxalate induces HK-2 cell injury through the interaction between the NF-κB signalling and ERS/ROS pathways. [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 accurate mapping of urban impervious surfaces from remote sensing images is crucial for understanding urban land-cover change and addressing impervious-surface-change-related environment issues. To date, the authors of most studies have built indices to map impervious surfaces based on shortwave infrared (SWIR) or thermal infrared (TIR) bands from middle–low-spatial-resolution remote sensing images. However, this limits the use of high-spatial-resolution remote sensing data (e.g., GaoFen-2, Quickbird, and IKONOS). In addition, the separation of bare soil and impervious surfaces has not been effectively solved. In this article, on the basis of the spectra analysis of impervious surface and non-impervious surface (vegetation, water, soil and non-photosynthetic vegetation (NPV)) data acquired from world-recognized spectral libraries and Sentinel-2 MSI images in different regions and seasons, a novel spectral index named the Normalized Impervious Surface Index (NISI) was proposed for extracting impervious area information by using blue, green, red and near-infrared (NIR) bands. We performed comprehensive assessments for the NISI, and the results demonstrated that the NISI provided the best studied performance in separating the soil and impervious surfaces from Sentinel-2 MSI images. Furthermore, regarding impervious surfaces mapping accuracy, the NISI had an overall accuracy (OA) of 89.28% (±0.258), a producer's accuracy (PA) of 89.76% (±1.754), and a user's accuracy (UA) of 90.68% (±1.309), which were higher than those of machine learning algorithms, thus supporting the NISI as an effective measurement for urban impervious surfaces mapping and analysis. The results indicate the NISI has a high robustness and a good applicability. [ABSTRACT FROM AUTHOR]

Background: According to the Mozena classification system, stage IIb and stage III ingrown toenail cases are considered as severe ones; however, limited options are available for treatment. Aims: To lower the recurrence rate and achieve primary intention healing in severe ingrown toenail cases by the modified Howard–Dubois technique. Methods: Forty patients were included in this study. In this procedure, a fish-mouth like soft tissue along the nail groove to the tip of the toe was resected, the upper surface of the distal phalanx was flattened and the nail bed matrix was remodelled. The European Quality of Life (EuroQol) questionnaire and Surgical Satisfaction Questionnaire were used to assess the outcomes. Results: There were no recurrences observed during the follow-up period. Healing time from surgery to back to school or work was 10.82 days on an average (range: 7–23 days). According to the results of EuroQol questionnaire, improvements were achieved in the areas of mobility (50%), looking after myself (10%), doing usual activities (35%), having pain or discomfort (95%) and feeling worried, sad, or unhappy (55%). According to the results of Surgical Satisfaction Questionnaire, 38 (95%) patients indicated that they would undergo the surgery again if they 'had to do it all over again' and 36 (90%) patients said that they would recommend the procedure to others. Conclusions: This modified Howard–Dubois technique was an effective, safe and cosmetic alternation for the treatment of ingrown toenail in severe or relapsed cases. [ABSTRACT FROM AUTHOR]

Using remote-sensing technology to accurately map the composition and distribution of tree species is vital for sustainable forest resource management. Sentinel-2 data with the dense time-series observations enable to identify tree species. However, few studies clarify the differences in classification using Sentinel-2 images in natural forest and planted forest. Two study areas with different forest environments (planted forest and natural forest) were selected to evaluate the potential of Sentinel-2 imagery. Our results show that red-edge band, short-wave infrared (SWIR) band and vegetation indices (VIs), such as Red-Edge Normalized Difference Vegetation Index (ReNDVI), Soil-Adjusted Vegetation Index (SAVI), and Enhanced Vegetation Index (EVI), have important effects on tree species classification, especially in the growing season. By using two machine learning algorithms (support vector machine [SVM] and random forest [RF]), the results show that the classification accuracy for planted forests (91.27% in SVM and 88.35% in RF) significantly exceeds that of natural forests (84.34% in SVM and 81.03% in RF). This accuracy difference may be related to the spatial heterogeneity inside the forest and the surrounding environmental implications. Although the multi-temporal Sentinel-2 images produce satisfactory accuracy for classifying tree species, further research is needed to improve the classification accuracy. [ABSTRACT FROM AUTHOR]

The flexor pollicis longus muscle and flexor digitorum profundus muscle are innervated by the branches of the anterior interosseous nerve (AIN). Therefore, the commonly used methods of restoring the fingers and thumb flexion in lower brachial plexus injury have mainly focused on the AIN. We transferred the brachialis muscle branch of the musculocutaneous nerve (brachialis nerve) to the AIN using the vascularized lateral antebrachial cutaneous nerve (LACN) as a nerve graft to restore the flexion function of the fingers and thumb. This anatomical study was performed in 16 formalin-fixed upper extremities from 8 frozen cadavers. The brachialis nerve and the AIN were dissected. The bridged portion of the transected LACN was not dissected; only the two transected ends of the LACN were dissected, which kept the native blood supply of the intervening graft of the LACN from being destroyed. The diameters of the transected nerve ends of the brachialis nerve, AIN, and proximal and distal ends of the LACN were measured separately. Specimens of the measured nerve tissue were sent for toluidine blue staining, and the number of nerve fibers in each transected nerve branch was counted. The diameters of the brachialis nerve, AIN, and proximal and distal transected ends of LACN were 1.37 SD0.25 mm, 1.54 SD0.14 mm, 2.07 SD0.29, and 1.76 SD0.14 mm, with 1109 SD422, 1318 SD546, 1684 SD327, and 1378 SD667 myelinated nerve fibers, respectively. The fingers and thumb flexion function of the patient recovered gradually from 8 months after surgery. Using the vascularized LACN as an in situ nerve graft to transfer the brachialis nerve to the AIN was a feasible alternative technique to restore the flexion function of fingers and thumb in lower brachial plexus injury. [ABSTRACT FROM AUTHOR]

Carbon nanotubes orientation has a significant impact on the performance of carbon nanotubes/epoxy resin (CNTs/EP) composite materials. The ultrasonic velocity is sensitive to the degree of carbon nanotubes orientation. However, the time-of-flight (TOF) is difficulty to accurately measured due to ultrasonic echo aliasing and waveform distortion occurred in the thin CNTs/EP composite material. Therefore, the ultrasonic characterization method of carbon nanotubes orientation based on the sparse representation is studied in this paper. Two groups of CNTs/EP specimens are taken as research objects. Firstly, the dictionary is constructed by Gabor function, and the matching degree between dictionary and ultrasonic echo signals is researched. Then, the matching pursuit (MP) algorithm is used to solve the problem of dictionary redundancy and obtain the best matching atom; the signal reconstruction is completed and ultrasonic TOF of carbon nanotubes is extracted more accurately. Finally, a carbon nanotubes orientation prediction model based on the sparse representation is established. The result shows that the Gabor dictionary has good similarity with ultrasonic echo signals and the root mean square relative error is 0.0147. The degree of carbon nanotubes orientation and ultrasonic velocity have positive correlation. The carbon nanotubes orientation prediction model relative error is 5.58%. This paper has provided an effective method to characterize the degree of carbon nanotubes orientation. [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]

Background: Osteosarcoma (OS) metastasis is the most common cause of cancer-related mortality, however, no sufficient clinical biomarkers have been identified. In this study, we identified five genes to help predict metastasis at diagnosis. Methods: We performed weighted gene co-expression network analysis (WGCNA) to identify the most relevant gene modules associated with OS metastasis. An important machine learning algorithm, the support vector machine (SVM), was employed to predict key genes for classifying the OS metastasis phenotype. Finally, we investigated the clinical significance of key genes and their enriched pathways. Results: Eighteen modules were identified in WGCNA, among which the pink, red, brown, blue, and turquoise modules demonstrated good preservation. In the five modules, the brown and red modules were highly correlated with OS metastasis. Genes in the two modules closely interacted in protein–protein interaction networks and were therefore chosen for further analysis. Genes in the two modules were primarily enriched in the biological processes associated with tumorigenesis and development. Furthermore, 65 differentially expressed genes were identified as common hub genes in both WGCNA and protein–protein interaction networks. SVM classifiers with the maximum area under the curve were based on 30 and 15 genes in the brown and red modules, respectively. The clinical significance of the 45 hub genes was analyzed. Of the 45 genes, 17 were found to be significantly correlated with survival time. Finally, 5/17 genes, including ADAP2 (P = 0.0094), LCP2 (P = 0.013), ARHGAP25 (P = 0.0049), CD53 (P = 0.016), and TLR7 (P = 0.04) were significantly correlated with the metastatic phenotype. In vitro verification, western blotting, wound healing analyses, transwell invasion assays, proliferation assays, and colony formation assays indicated that ARHGAP25 promoted OS cell migration, invasion, proliferation, and epithelial–mesenchymal transition. Conclusion: We identified five genes, namely ADAP2, LCP2, ARHGAP25, CD53, and TLR7, as candidate biomarkers for the prediction of OS metastasis; ARHGAP25 inhibits MG63 OS cell growth, migration, and invasion in vitro, indicating that ARHGAP25 can serve as a promising specific and prognostic biomarker for OS metastasis. [ABSTRACT FROM AUTHOR]

As solid waste posing a great threat to the environmental system, the disposal of arsenic-alkali slag has become the top priority in the development of the antimony industry. In this paper, a novel technological scheme combining the advantages of chemical precipitation and fractional crystallization is proposed for the safe disposal and resource utilization of arsenic-alkali slag. The scheme is mainly composed of three parts, namely, leaching of arsenic-alkali slag, selective removal of arsenic in the arsenic-alkali solution, and evaporation crystallization of alkali solution. In the leaching part, the optimum leaching parameters are determined by orthogonal tests. In the arsenic and alkali separation part, based on thermodynamic analysis, the selective removal of arsenic from arsenic-alkali solution is realized by forming ammonium magnesium arsenate (MgNH 4 AsO 4) precipitation. In the evaporation crystallization part, the crystalline product with sodium carbonate (Na 2 CO 3) content of 89.87% is obtained by the evaporation crystallization experiment. The whole process does not produce secondary pollution and realizes the reuse of wastewater. The final products are leaching residue, arsenic slag, and sodium carbonate with an arsenic content of 0.83%, 24.93%, and 0.18%, respectively. [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]

We consider dynamics of scalar and vector fields on gravitational backgrounds of the Wess-Zumino-Witten models. For SO(4) and its cosets, we demonstrate full separation of variables for all fields and find a close analogy with a similar separation of vector equations in the backgrounds of the Myers-Perry black holes. For SO(5) and higher groups separation of variables is found only in some subsectors. [ABSTRACT FROM AUTHOR]

The study was designed and conducted to evaluate the plant‐based diet status and its association with erectile function (EF) in Chinese young healthy men. From July 2018 to May 2020, 116 objectively proved physically and psychologically healthy men were selected. Clinical questionnaires, detailed physical examinations and blood tests were all assessed. An overall plant‐based diet index (PDI) and a healthful plant‐based diet index (hPDI) were developed from each participant to measure plant‐based diet quantitatively. The EF was measured by both the International Index of Erectile Function‐5 (IIEF‐5) and the surrogated measures of endothelial function, peripheral levels of nitric oxide (NO) and E‐selectin. In subjects, the mean PDI and hPDI were 53.8 ± 8.2 and 54.7 ± 8.9 respectively. Results of multivariate analysis showed that both PDI and hPDI were negatively associated with BMI (all p <.05), but had no relationships with NO, E‐selectin, TT levels and IIEF‐5 scores (all p >.05). In a subgroup of male population, Chinese young healthy men, the plant‐based diet, measured by PDI and hPDI, was not related to erectile function. The population can adhere to plant‐based diet to keep healthy without concerns of negative influence on erectile function. [ABSTRACT FROM AUTHOR]

• The solar potential in different residential blocks is simulated. • The influences of block morphological parameters on solar potential are varified. • Four parameters that impact on the block solar potential more than 70% are verified. • The facade PV capacity in high-rise and hybrid residential blocks is more than 66%. • The average PV installation rate of roof, south and west facade is 96%, 32% and 39%. Block-scale application of photovoltaic technology in city is becoming a viable solution for renewable energy utilization. Rapid urbanization process has made urban buildings have huge development potential for solar energy in China, especially in residential areas that occupy large parts of the city. However, the residential blocks in China show differences in the morphological layout and parameters, which means they have diverse potential for solar energy development. This paper studies the effect of quantified morphological parameters on solar potential for residential blocks in Wuhan, China. The distribution characteristics of solar potential in different block environments are discussed. Various strategies are evaluated in terms of the installation position and height of PV modules. The results showed that floor area ratio, building density, average building height and building interval have significant impact on solar potential for residential block, and their correlation can reach 75%, 71%, 78% and 72% respectively. The average PV installation ratio of roof, south facade and west facade can reach 96%, 32% and 39% respectively. The results of this paper not only provide a reference to the block-scale application of PV technology in urban environment, but also stimulate the implementation of photovoltaic policies on various residential blocks in China. [ABSTRACT FROM AUTHOR]

Plasma jet formation was studied in a vacuum arc configured with a conical cathode located inside a hollow cylindrical anode. The outside of this anode was insulated, except at a 0.4 mm diameter micropore. The grounded vacuum chamber also served as an anode. The hollow cylindrical anode was connected to the grounded chamber anode through a resistor R. 170 A 14 μs arcs were excited by a pulse generator comprised of a series connection of a 0.1 F capacitor bank charged to 12 kV, a 200 μH inductor, and a 30 Ω resistor. Two plasma jets formed during the arc discharge, one originating from the cathode tip and the other through the micropore. It was found that when R was increased from 0 Ω to 1 MΩ, (1) the plasma jet originating at the micropore weakened, (2) the peak current to the hollow cylindrical anode decreased from 73 A to 0, and (3) the peak arc current decreased from 176 A to 150 A. Plasma jet velocities for R = 0 were inferred from the difference between electron current peak times at two probes, to be 9 km/s for the plasma jet from the cathode and 27 km/s for the plasma jet at the micropore. [ABSTRACT FROM AUTHOR]

Dimethyl sulfoxide (DMSO) is a universally used solvent in various synthetic reactions, and trace amounts of DMSO residual are often seen on the surface of chemical product. It is difficult to quickly determine whether the residual DMSO is washed completely. This work reports a CdII metal–organic framework (MOF) SXU‐4 which can detect trace amounts of DMSO in various solvents. Fluorescence experiments reveal its turn‐on fluorescence effect toward DMSO with high selectivity and sensitivity, indicating that it can be used as an effective luminescent probe for rapid chemical product purity detection by testing the washing solution. Crystallographically characterized DMSO loaded SXU‐4 (DMSO@SXU‐4), in combination with computational results uncover that the enhanced DMSO–MOF conjugation through multiple DMSO–MOF supramolecule interactions and charge rearrangement are the main causes of fluorescence intensification. [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]

• A new type of 2D-on-3D MOF heterostructure (Cu-MOF@In-MOF) was constructed via anisotropic growth. • This "dimensionality-hybrid" nanostructure simultaneously handle the composition and dimensionality of the heterostructure. • The well-defined Cu-MOF@In-MOF exhibited superb photocatalytic activity and stability for Cr (VI) reduction. • Z-scheme heterojunction of Cu-MOF@In-MOF promoted the separation of hole-electron pairs and boosted electron transfer rate. A novel two-dimensional (2D)–on-3D metal–organic framework (MOF) "dimensionality-hybrid" heterostructure was established by the anisotropic growth method and exploited as the robust photocatalyst to efficiently remove Cr(VI) ions in the polluted water system under visible irradiation. The 2D Cu-MOF nanosheet was in situ grown around the 3D In-MOF nanorods, thus forming the MOF-on-MOF Z-scheme heterojunction (denoted as Cu-MOF@In-MOF). Benefiting to the large specific surface area (718.1 m2 g−1) and promoted the photoabsorption property within visible-light region, the attained Cu-MOF@In-MOF heterojunction exhibited the remarkably enhanced separation ability of photocarriers and electron transfer. Comparing with the sole MOFs (Cu-MOF and In-MOF) the 2D/3D Cu-MOF@In-MOF Z-scheme heterojunction demonstrated high photocatalytic reduction efficiency toward Cr(VI) (98%) within 1 h under visible-light irradiation (50 mg/L, pH 5.4), markedly higher than those of the sole MOFs and most of reported photocatalysts (50 mg/L, pH 5.4). Moreover, the photocatalysis mechanism of the Cr(VI) reduction by Cu-MOF@In-MOF was provided based on the analysis of energy band structure trapping experiments and electron spin resonance results. The presented MOF-on-MOF photocatalyst shows the synergistic effect of various components for efficiently photocatalytic removal of harmful pollutants in water, thus giving the great potential applications in environmental governance field. [ABSTRACT FROM AUTHOR]

Solar energy has been rapidly utilized in urban environments owing to its significant potential to fulfill the energy demand. The precise forecasting of solar energy, including solar radiation and photovoltaic power forecasting, is crucial for effective energy utilization in cities. Currently, artificial intelligence algorithms, including machine learning (ML) and deep learning (DL) algorithms, have been widely utilized in the research of solar energy forecasting and have shown excellent performance. The different research scales lead to variations in the influencing factors and forecasting approaches used in solar energy prediction. Therefore, this paper provides a comprehensive review of solar radiation and photovoltaic power forecasting research using ML and DL algorithms from a multi-scale perspective, including the meso-scale, micro-scale, and building-scale forecasting in urban environments. The aim is to summarize the state-of-the-art progress and evaluate the solar forecasting effectiveness in diverse research scenarios. The characteristic analyses of ML- and DL-based solar forecasting approaches, prediction models, forecasting horizons, inputs and outputs were conducted for different research scales. This paper discusses the existing issues and future research directions for multiscale solar energy forecasting in cities. The analyses can help researchers and engineers in identifying suitable prediction algorithms and approaches. Consequently, this exploration can contribute to the efficient utilization of solar radiation and photovoltaic power generation in multi-scale urban environments. [Display omitted] • Machine learning and deep learning-based solar radiation and photovoltaic power forecasting research in urban environment are classified from a multi-scale perspective. • The characteristics and key points of solar radiation and photovoltaic power forecasting at the meso-scale, micro-scale, and building-scale in cities are analyzed. • Solar radiation and photovoltaic power forecasting approaches, prediction models, input and output values, and forecasting horizons are discussed. • Future research directions of solar radiation and photovoltaic power forecasting in urban environment are presented. [ABSTRACT FROM AUTHOR]

Aim of the Study: Mason type III radial head fractures are a source of concern due to the severe injury and poor recovery. At present, radial head resection, open reduction and internal fixation (ORIF), and prosthetic replacement are three common treatment methods for these fractures. The clinical efficacy and postoperative complications are controversial, which makes it difficult for physicians to determine the most appropriate regimen. Herein, this present prospective, non-randomized, parallel-controlled study was conducted to compare the therapeutic effects and identify the most effective treatment method for Mason type III radial head fracture. Materials and Methods: We assessed patients with Mason type III radial head fracture treated with resection, prosthetic replacement, and ORIF to compare preoperative and postoperative pain condition, elbow joint function, curative effect, and complication rate. A visual analog scale was used to score pain. The elbow joint function was observed using the Broberg–Morrey elbow joint score. Results: No significant differences were found in patient demographics among the resection, prosthetic replacement, and ORIF groups. The prosthetic replacement and ORIF procedures were more complex and had higher technical requirements. Prosthetic replacement and ORIF enabled higher elbow joint scores and lower pain scores than resection. Excellent and good ratings were highest and complication rates were lowest in the prosthetic replacement group, followed by the ORIF group. Conclusion: Our results showed that prosthetic replacement is more effective than ORIF and radial head resection in relieving pain, functional recovery and reducing complications in the treatment of Mason type III radial head fractures. [ABSTRACT FROM AUTHOR]

Micro-cathode arc thruster (µCAT) is an electric propulsion device that uses metal cathode material as propellent to create plasma and ultimately produce thrust, which is suitable to serve as a propulsion system for microsatellites. In order to improve propulsion performance of the µCAT, a structure using a segmented insulated anode with a slit (SISA-µCAT), which mainly consists of a truncated-cone-shaped cathode, an insulating sleeve, a segmented anode including proximal anode and distant anode, and an anodic insulation layer with a slit, is proposed in this paper. We compare and analyze the differences in discharge characteristics, plasma generation characteristics and propulsion performance among the SISA-µCAT, a segmented exposed anode µCAT (SEA-µCAT) and the known non-segmented exposed anode µCAT (NSEA-µCAT). Study results show that when adopting the SISA-µCAT, plasma ejection performance is effectively improved by utilizing the special spatial electric field formed between segmented anode and the slit structure on the anodic insulation layer, thus improving the propulsion performance of the µCAT. During a single shot, compared with the NSEA-µCAT, peak values of generated thrust and thrust-to-power ratio are increased by 11.4 times and 10.4 times, respectively, by using the SISA-µCAT. Plasma parameters indicate that peak plasma density and propagation speed are increased by 8.2 times and 2.93 times, respectively. [ABSTRACT FROM AUTHOR]

Molecular design to improve catalyst performance is significant but challenging. In enzymes, residue groups that are close to reaction centers play critical roles in regulating activities. Using this bioinspired strategy, three water‐soluble polymers were designed with appending Co porphyrins and different side‐chain groups to mimic enzyme reaction centers and activity‐controlling residue groups, respectively. With these polymers, high hydrogen evolution efficiency was achieved in neutral aqueous media for electro‐ (turnover frequency >2.3×104 s−1) and photocatalysis (turnover number >2.7×104). Porphyrin units are surrounded and protected by polymer chains, and more importantly, the activity can be tuned with different side‐chain groups. Therefore, instead of revising molecular structures that is difficult from both design and synthesis points of view, polymers can be used to improve molecular solubility and stability and simultaneously regulate activity by using side‐chain groups. [ABSTRACT FROM AUTHOR]

Molecular design to improve catalyst performance is significant but challenging. In enzymes, residue groups that are close to reaction centers play critical roles in regulating activities. Using this bioinspired strategy, three water‐soluble polymers were designed with appending Co porphyrins and different side‐chain groups to mimic enzyme reaction centers and activity‐controlling residue groups, respectively. With these polymers, high hydrogen evolution efficiency was achieved in neutral aqueous media for electro‐ (turnover frequency >2.3×104 s−1) and photocatalysis (turnover number >2.7×104). Porphyrin units are surrounded and protected by polymer chains, and more importantly, the activity can be tuned with different side‐chain groups. Therefore, instead of revising molecular structures that is difficult from both design and synthesis points of view, polymers can be used to improve molecular solubility and stability and simultaneously regulate activity by using side‐chain groups. [ABSTRACT FROM AUTHOR]

Background: Spermatogonial stem cell (SSC) transplantation technology as a promising option for male fertility preservation has received increasing attention, along with efficient SSC purification technology as a necessary technical support; however, the safety of such application in patients with tumors remains controversial. Methods: In this study, we used a green fluorescent protein mouse xenograft model of B cell acute lymphocytic leukemia. We isolated and purified SSCs from the testicular tissue of model mice using density gradient centrifugation, immune cell magnetic bead separation, and flow cytometry. The purified SSCs were transplanted into convoluted seminiferous tubules of the nude mice and C57BL/6 male mice subjected to busulfan. The development and proliferation of SSCs in the recipient testis were periodically tested, along with whether B cell acute lymphocytic leukemia was induced following SSC implantation. The genetic characteristics of the offspring obtained from natural mating were also observed. Results: In testicular leukemia model mice, a large number of BALL cells infiltrated into the seminiferous tubule, spermatogenic cells, and sperm cells in the testis tissue decreased. After spermatogonial stem cell transplantation, the transplanted SSCs purified by immunomagnetic beads and flow cytometry methods colonized and proliferated extensively in the basement of the seminiferous tubules of mice; a large number of spermatogenic cells and sperm were found in recipient testicular tissue after 12 weeks of SSC transplantation. In leukemia detection in nude mice after transplantation in the three SSC purification groups, a large number of BALL cells could be detected in the blood of recipient mice 2–3 weeks after transplantation in the density gradient centrifugation group, but not in the blood of the flow cytometry sorting group and the immunomagnetic bead group after 16 weeks of observation. Conclusions: In this study, we confirmed that immunomagnetic beads and flow cytometry methods of purifying SSCs from the testicular tissue of the testicular leukemia mouse model could be safely applied to the SSC transplantation technology without concomitant tumor implantation. The results thus provide a theoretical basis for the application of tumor SSC cryopreservation for fertility preservation in patients with tumors. [ABSTRACT FROM AUTHOR]

• A self-healing hydrogel with sequential delivery property was developed for wound healing. • The self-healing ability of hydrogel was due to dynamic imine and acylhydrazone bonds. • The encapsulated CHA was released rapidly, and the bFGF was sustainably released. • The hydrogel could inhibit infection promptly and accelerate wound healing continuously. • This hydrogel is a highly promising dressing material for wound healing. The conventional injectable hydrogels as wound dressing materials frequently encounter bacterial infection and lack self-healing ability. Besides, the hydrogels injected into the irregular wound sites are easily damaged by external forces, which further hinder wound healing. To make up for these deficiencies, we developed a novel hydrogel with the unique properties including dynamic covalent based self-healing, antibacterial and sequential drug release. This injectable and self-healing hydrogel was constructed via the dynamic reaction of aminated gelatin (NGel), adipic acid dihydrazide (ADH) and oxidized dextran (ODex). After injection or damage, the broken hydrogel pieces performed excellent self-healing capability to generate an integral hydrogel owing to dynamic imine and acylhydrazone bonds. Meanwhile, bFGF@PLGA microspheres and chlorhexidine acetate (CHA) were embedded into the hydrogels. This bFGF@PLGA/CHA/hydrogel presented a good biodegradability, and it could retain the morphological stability after swelling. Moreover, bFGF@PLGA/CHA/hydrogels achieved the sequential release of CHA and bFGF during the drug release assay. When topically applied onto the wound skin of rats, the hydrogels can effectively prevent infection at the early stages due to the rapid release of CHA, then further accelerate cell proliferation and wound healing through the sustained release of bFGF. These results indicate that the proposed self-healing hydrogel with sequential release properties is a highly promising dressing material for wound healing. [ABSTRACT FROM AUTHOR]

Purpose: Knee arthroscopy, with its unique advantages, has become a routine surgery and is widely carried out around the world. Venous thromboembolism (VTE) after knee arthroscopy is a potentially serious complication. This article analyzes the effects of anticoagulant therapy after knee arthroscopy.Methods: We used key words or entry terms without any limitations to search the PubMed, Embase, and Cochrane Library databases. Randomized controlled trials (RCTs) of drug prophylaxis for VTE after knee arthroscopy until November 2017 were included in our review.Results: This systematic review identified nine RCTs, consisting of 4290 patients, investigating drug prophylaxis in knee arthroscopy. There are three main drugs for preventing thrombosis after arthroscopic knee surgery: low-molecular-weight heparin (LMWH), rivaroxaban, and aspirin. Our study concluded that there is no difference in symptomatic VTE (excluding symptomatic distal DVT) risk during anticoagulant prophylaxis (RR, 0.98; 95% CI, 0.44-2.19; I2 value = 0%; P = 0.97). Moreover, there was a lower incidence of symptomatic distal DVT (RR, 0.16; 95% CI, 0.06-0.45; I2 value = 0%; P = 0.0005) in the anticoagulant group than in the control group.Conclusions: In our study, anticoagulant therapy after knee arthroscopy was ineffective. We recommend that anticoagulants not be provided routinely after knee arthroscopy. [ABSTRACT FROM AUTHOR]