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Objective: This study aimed to develop and validate a predictive model for assessing the efficacy of neoadjuvant chemotherapy (NACT) in nasopharyngeal carcinoma (NPC) by integrating radiomics and pathomics features using a particle swarm optimization-supported support vector machine (PSO-SVM). Methods: A retrospective multi-center study was conducted, which included 389 NPC patients who received NACT from three institutions. Radiomics features were extracted from magnetic resonance imaging scans, while pathomics features were derived from histopathological images. A total of 2,667 radiomics features and 254 pathomics features were initially extracted. Feature selection involved intra-class correlation coefficient evaluation, Mann-Whitney U test, Spearman correlation analysis, and least absolute shrinkage and selection operator regression. The PSO-SVM model was constructed and validated using 10-fold cross-validation on the training set and further evaluated using an external validation set. Model performance was assessed using the area under the curve (AUC) of the receiver operating characteristic curve, calibration curves, and decision curve analysis. Results: Eight significant predictive features (five radiomics and three pathomics) were identified. The PSO-SVM radiopathomics model achieved superior performance compared to models based solely on radiomics or pathomics features. The AUCs for the PSO-SVM radiopathomics model were 0.917 (95% CI: 0.887–0.948) in internal validation and 0.814 (95% CI: 0.742–0.887) in external validation. Calibration curves demonstrated good agreement between predicted probabilities and actual outcomes. Decision curve analysis showed that the PSO-SVM radiopathomics model provided higher clinical net benefit over a wider range of risk thresholds compared to other models. Conclusion: The PSO-SVM radiopathomics model effectively integrates radiomics and pathomics features, offering enhanced predictive accuracy and clinical utility for assessing NACT efficacy in NPC. The multi-center approach and robust validation underscore its potential for personalized treatment planning, supporting improved clinical decision-making for NPC patients. [ABSTRACT FROM AUTHOR]

Cellulose nanocrystals (CNCs) are environmentally friendly building blocks used in the preparation of chiral nematic iridescent films through evaporation‐induced self‐assembly. However, the brittleness of CNC films limits their versatility, especially in applications that require mechanical flexibility. In this study, it is innovatively engineered flexible colored CNC films entirely composed of cellulose by introducing cross‐linked chemically modified cellulose nanofibers (CNFs) as a supporting network. By reducing the surface charge content of CNFs and anchoring them in a network, the disruption to the self‐assembly process of CNCs caused by CNFs is minimized. This effectively preserves the structural colors of CNCs films. Furthermore, the CNFs network enhances the tensile strength and elongation of these all‐cellulose composite films, enabling them to be folded with excellent flexibility while still maintaining a high Young's modulus. Vibrant red, green, and blue‐colored all‐cellulose photonic films can also be achieved by simply adjusting the sonication energy input on the suspension of CNCs. The all‐cellulose‐based flexible films have the potential to be applied as an eco‐friendly and sustainable photonic material when flexibility is essential, for instance, in applications like flexible sensors, anti‐counterfeit labels, or foldable display components. [ABSTRACT FROM AUTHOR]

Deferred diabetic skin healing is an ever‐growing complication owing to the hyperglycemic microenvironment, which accelerates the generation of advanced glycated end products (AGEs) and provides a hotbed for pathogenic infection. Here, the H2S‐evolving bio‐heterojunction enzyme (BioHJzyme), which is consisted by MXene/FeS2 and glucose oxidase (GOx) is devised. It presents glutathione peroxidase (GPx)‐ and peroxidase (POD)‐mimetic antibacterial activity for anti‐pathogens and wound regeneration by AGEs depression. The GOx catalyzes glucose, resulting in reducing the bacterial nutrient and supplying H2O2. The POD‐mimetic activity of the BioHJzyme catalyzes the H2O2 to hydroxyl radical (•OH) with a turnover number of 4.45 × 10−1 s−1, while the GPx‐mimetic activity of it consumes glutathione for further •OH accumulation. The anti‐pathogens can be enhanced by near infrared laser (NIR) irradiation owing to the efficient separation of electron‐hole pairs originated from the heterostructure, which presents NIR‐activatable •OH and 1O2 production. Moreover, the BioHJzyme evolves H2S in acidic environment, acting as an H2S donor, which protects cells around the wound from oxidative damage and AGEs, rescues mitochondrial respiration, improves the extracellular matrix deposition and ameliorates dysfunction of fibroblasts for diabetic skin regeneration through TGF‐β/Smad pathway. The work provides a proof‐of‐concept for bacteria‐invaded diabetic wound regeneration via H2S‐evolving BioHJzyme. [ABSTRACT FROM AUTHOR]

The rhizosphere microbial community helps govern biogeochemical cycling and facilitates complex plant-soil feedback. Understanding the evolutionary dynamics of microbial community structure and functional genes during vegetation succession is crucial for quantifying and understanding ecosystem processes and functions in restored sandy deserts. In this study, the rhizosphere microbial community structure of 11–66-year-old dominant shrubs in a desert revegetation area was examined using shotgun metagenomic sequencing. The interactions between the microbial community structure, functional gene abundances, soil properties, and plant characteristics of different stand ages were comprehensively investigated. The abundance of unique species first increased before subsequently decreasing with stand age, with shared species accounting for only 47.33%–59.42% of the total operational taxonomic units (OTUs). Copiotrophs such as Actinobacteria and Proteobacteria were found to dominate the rhizosphere soil microbial community, with their relative abundance accounting for 75.28%–81.41% of the total OTUs. There was a gradual shift in dominant microbial functional genes being involved in cellular processes towards those involved in environmental information processing and metabolism as stand age increased. Additionally, temporal partitioning was observed in both the microbial co-occurrence network complexity and topological parameters within the rhizosphere soil. Redundancy analysis revealed that dissolved organic carbon was the primary determinant influencing shifts in microbial community structure. Understanding the evolution of microbial community structure and function contributes to identifying potential mechanisms associating the soil microbiome with dominant sand-fixing shrubs as well as understanding the rhizosphere microbiome assembly process. These results shed light on the role of the rhizosphere microbiome in biogeochemical cycling and other ecosystem functions following revegetation of temperate sandy deserts. [ABSTRACT FROM AUTHOR]

The method of preparation is a critical factor affecting the structure and properties of Bi2O3 material. In this work, Bi2O3 was synthesized through calcination (denoted as Bi2O3–C) and hydrothermal methods (denoted as Bi2O3–H), utilizing bismuth-based metal–organic framework (Bi–MOF) as the precursor. As an electrode material for supercapacitors, Bi2O3–H demonstrated outstanding rate performance (515 F g−1 at 50 A g−1) and remarkable cycle stability (74% retention after 4000 cycles). Subsequently, the Bi2O3-H underwent further processing through electron beam irradiation (EBI), resulting in a sample designated as Bi2O3–I. Following EBI treatment, the crystalline characteristics of Bi2O3–I and the concentration of oxygen vacancies (OVs) exhibited a significant improvement, thereby augmenting the material's conductivity. Because the positively charged OVs can quickly attract OH− from the electrolyte to the electrode surface, thereby accelerating the REDOX reaction, the current control mechanism of Bi2O3–I is partially derived from a surface-controlled pseudo-capacitance process. The irradiated Bi2O3-I electrode demonstrated superior capacitance (990 F−1 at 2 A g−1), enhanced rate performance (585 F−1 at 50 A g−1), and remarkable cycling stability (83% retention after 4000 cycles). [ABSTRACT FROM AUTHOR]

Data-driven machine learning approaches with precise predictive capabilities are proposed to address the long-standing challenges in the calculation of complex many-electron atomic systems, including high computational costs and limited accuracy. In this work, we develop a general workflow for machine learning-assisted atomic structure calculations based on the Cowan code's Hartree–Fock with relativistic corrections (HFR) theory. The workflow incorporates enhanced ElasticNet and XGBoost algorithms, refined using entropy weight methodology to optimize performance. This semi-empirical framework is applied to calculate and analyze the excited state energy levels of the 4f closed-shell Yb I atom, providing insights into the applicability of different algorithms under various conditions. The reliability and advantages of this innovative approach are demonstrated through comprehensive comparisons with ab initio calculations, experimental data, and other theoretical results. [ABSTRACT FROM AUTHOR]

Gravel mulching is a widely employed strategy for water conservation in arid agricultural regions, with potential implications for soil carbon (C) sequestration and greenhouse gas emissions. However, soil respiration and CO2-C emissions remain uncertain owing to less consideration of the influence of precipitation patterns and planting age. In this study, we investigated the soil respiration rate (Rsoil) and cumulative CO2-C emission (Ccum), both measured over a period of 72 h, along with soil properties and enzyme activities under different precipitation conditions based on gravel mulching with different planting ages. We analyzed the effects of planting ages on Rsoil and Ccum and revealed the underlying mechanisms driving changes in environmental factors on Rsoil and Ccum. The results demonstrated that the Rsoil reached the maximum value at about 1 h, 0.5 h, and 0.25 h after rewetting in 1, 10, and 20 years of gravel mulching under the condition with 1 mm, 5 mm, and 10 mm of precipitation, respectively, whereas the Rsoil exhibited its maximum at about 8 h after soil rewetting under precipitation of 30 mm. The Ccum induced by precipitation pulses tends to decrease with increasing years of gravel mulching. The Ccum was 0.0061 t ha−1 in the 20-year gravel-mulched soil, representing a 53.79% reduction compared to the 1-year gravel-mulched soil. Soil organic matter (SOM), planting ages, and alkaline phosphatase (ALP) were the primary factors influencing the Rsoil and Ccum in 0–20 cm, while SOM, planting ages, and soil porosity (AirP) were the key factors affecting the Rsoil and Ccum in 20–40 cm. The Rsoil and Ccum in the 0–20 cm soil were regulated by soil enzyme activities, while those of 20–40 cm soil were controlled by soil properties. This indicates that the decrease in Rsoil and Ccum is caused by soil degradation, characterized by a decrease in SOM and ALP. This study offers a novel insight into the long-term environmental impact of gravel mulching measures in arid areas, which is helpful in providing a theoretical basis for dryland agricultural management. It is imperative to consider the duration of gravel mulching when predicting the potential for C sequestration in arid agricultural areas. [ABSTRACT FROM AUTHOR]

In recent years, wide‐bandgap semiconductor β‐Ga2O3 material has been widely studied because of its excellent properties. Simultaneously, 2D metal oxides (2DMOs) have also become a focus of research owing to their superior stability and unique physical properties arising from quantum confinement effects. Therefore, the exploration of 2D β‐Ga2O3 is expected to reveal its novel electrical properties in electronic applications. However, the synthesis of high‐quality 2D β‐Ga2O3 remains a formidable challenge. Herein, a confined space is constructed to synthesize high‐quality 2D β‐Ga2O3 nanoflakes by enhancing the control of the kinetics of chemical vapor deposition process. In the device results, it is shown that the grown nanoflakes have excellent switching properties and potential artificial synaptic response characteristics. Based on this premise, an artificial recognition system for handwritten numerals is developed, achieving a peak recognition accuracy of approximately 96%. This system holds significant potential for application within an emerging neuromorphic recognition framework tailored for advanced driver‐assistance systems. In this work, a new feasible pathway is provided for the synthesis of 2D non‐layered oxides and the potential of 2D oxides in the field of neuroanalog electronics and recognition is shown, thereby advancing the fields of 2D β‐Ga2O3 electronics and 2DMOs electronics. [ABSTRACT FROM AUTHOR]

In recent years, recommendation systems have made significant strides through the application of graph neural networks (GNNs). However, most of the existing methods primarily focus on modeling user–item interactions, often failing to account for the distinct roles of different types of neighboring nodes during the graph convolution process. Moreover, the intricate relationships between user and item attributes are frequently underexplored, which constrains further improvement in the performance of recommendation models. To overcome these challenges, this paper proposes an attribute-aware graph convolutional network recommendation model (AAGCNR). This model accounts for the complex interrelationships between user and item attributes while distinguishing between different types of neighboring nodes during graph convolution. First, a multi-head self-attention mechanism is applied to capture the semantic relationships among attributes across various semantic spaces. Additionally, a bilinear interaction module is employed to facilitate interactions between attributes. Since different neighboring nodes exert different influences on target nodes, the model performs convolutional aggregation by leveraging the interrelationships of these attributes throughout the graph convolution process. Experiments conducted on real-world datasets reveal that AAGCNR outperforms other benchmark algorithms, particularly in terms of RECALL and NDCG metrics. [ABSTRACT FROM AUTHOR]

Clean energy has emerged as the focal point of global energy and power development. With the advancement of 5G technology and the Internet of Things (IoT), the demand for sustainable energy supply has become more pressing, leading to widespread attention to vibration energy harvesting technology. This technology enables the conversion of vibrational energy from natural phenomena such as ocean waves and wind, as well as machinery operation and human activities, into electrical energy, thus supporting the expansion of self‐sustained IoT systems. This review provides an overview of the progress in vibration energy harvesting technology and discusses the integration of this technology with self‐powered sensors and artificial intelligence. These integrations are reflected in the enhanced accuracy of environmental monitoring, increased efficiency in intelligent transportation and industrial production, and improved quality of life through intelligent healthcare and smart home. Such applications demonstrate the significant potential of self‐sustained artificial IoT in promoting environmental sustainability and elevating the level of intelligent living. In summary, exploring and applying vibration energy harvesting technology to support the autonomous operation of IoT devices is key to building a more sustainable, intelligent, and interconnected world. [ABSTRACT FROM AUTHOR]

Dimensionality of covalent organic frameworks (COFs), in terms of 2D and 3D, must greatly influence their properties and functionalities due to the different electronic and porous structures, but still less investigated in the 20 years history. Herein, on the basis of the imidization reaction of phthalocyanine‐based tetraanhydride monomers with either 1,4‐phenylenediamine or 1,3,5,7‐tetra(4‐aminophenyl)adamantine, 2D and 3D imide‐bonded COFs with sql and pts topology have been prepared to explore their third‐order nonlinear optical (NLO) properties. In contrast to metal‐free analogues, both 2D and 3D copper‐phthalocyanine COFs have the enhanced NLO behaviors according to the open aperture Z‐scan and optical limiting (OL) results recorded under a nanosecond laser at 532 nm. In particular, 2D COFs with strong π–π staking phthalocyanine units show the NLO property with bigger third‐order nonlinear susceptibility (Imχ(3)) and unique reverse saturation absorption response at 1064 nm than that of 3D species with dispersed conjugated modules. Furthermore, femtosecond transient absorption spectra disclose the longer excited lifetimes of copper COFs than metal free samples, helpful in their NLO property. These findings clearly disclose the materials advantages of 2D phthalocyanine COFs toward the NLO characteristics and provide new candidates for OL application. [ABSTRACT FROM AUTHOR]

Cooperating with distributed energy storage, distributed generation is with the potential of supply load stably under both normal and failure periods of distribution network. Therefore, distributed generation has not only electricity value, but also capacity value. The capacity value can be characterized by credible capacity index. However, the uncertainty of the distributed generation output and the sequential characteristics of energy-storage operation must be considered during a united credible capacity evaluation. A united credible capacity evaluation method of distributed generation and energy storage based on active island operation is proposed. The proposed method carries out day-ahead economic dispatching under a normal state and island partition under a fault state, alternately, to realize accurate reliability calculation, which is the key link of credible capacity searching. The main work is as follows. First, a day-ahead economic dispatching model under normal state is established to obtain the sequential remaining electricity information of energy storage. Second, the models of maximum island partition and optimal island rectification are established based on electricity sufficiency and power balance information. By solving the maximum island partition and optimal island rectification models alternately, optimal island partition schemes under the fault state could be achieved. Then, the convergence criterion based on variance coefficients instead of artificial selection is designed in reliability calculation. Finally, the united credible capacity of distributed generation and energy storage is evaluated in the PG&E 69-bus system. It is found that credible capacity value increases by 23%, 53%, and 61%, respectively, under the energy storage allocation ratios of 20%, 30%, and 40%. It can be seen that the integration of energy storage makes a significant impact on distributed generation credible capacity value.

Reprecipitation synthesis has been demonstrated to be a simple and convenient route to fabricate high quality perovskite quantum dots toward display applications, whereas the limited chemical yields (< 10%) and difficulty of purification limited its further application. In order to overcome this issue, we here report a modified emulsion synthesis by introducing phase transfer strategy, which achieving effective extraction of newly formed perovskite quantum dots into non-polar solvent and avoiding the degradation of perovskite quantum dots to a large extent. Based on this strategy, gram-scale CH3NH3PbBr3 quantum dots were fabricated in 10 mL (~0.02 mol/L) colloidal solution with chemical yields larger than 70%. The as fabricated CH3NH3PbBr3 quantum dots exhibit an emission peak of 453 nm and a full width at half maximum of only 14 nm. Moreover, electroluminescent devices based on blue emitting CH3NH3PbBr3 quantum dots were also explored with a maximum luminance of 32 cd/m2, showing potential applications in blue light emitting devices.