Novel Nitrogen Hybrid F Sensors Based on ESIPT Mechanism Achieving Super Low Detection Limits.

Two novel nitrogen hybrid fluorescent sensors based on the ESIPT mechanism were successfully synthesized for the detection of fluoride ions (F), and they exhibit high sensitivity and selectivity with a fast response. The detection limits even reach the parts per billion level. With the addition of F, both sensors showed a ratiometric fluorescence change with a large Stokes shift.

A facial expression recognition network using hybrid feature extraction.

Facial expression recognition faces great challenges due to factors such as face similarity, image quality, and age variation. Although various existing end-to-end Convolutional Neural Network (CNN) architectures have achieved good classification results in facial expression recognition tasks, these network architectures share a common drawback that the convolutional kernel can only compute the correlation between elements of a localized region when extracting expression features from an image. This leads to difficulties for the network to explore the relationship between all the elements that make up a complete expression.

Spatial heterogeneity response of soil salinization inversion cotton field expansion based on deep learning.

Soil salinization represents a significant challenge to the ecological environment in arid areas, and digital mapping of soil salinization as well as exploration of its spatial heterogeneity with crop growth have important implications for national food security and salinization management. However, the machine learning models currently used are deficient in mining local information on salinity and do not explore the spatial heterogeneity of salinity impacts on crops. This study developed soil salinization inversion models using CNN (Convolutional Neural Network), LSTM (Long Short-Term Memory Network), and RF (Random Forest) models based on 97 field samples and feature variables extracted from Landsat-8 imagery.

SIFusion: Lightweight infrared and visible image fusion based on semantic injection.

The objective of image fusion is to integrate complementary features from source images to better cater to the needs of human and machine vision. However, existing image fusion algorithms predominantly focus on enhancing the visual appeal of the fused image for human perception, often neglecting their impact on subsequent high-level visual tasks, particularly the processing of semantic information. Moreover, these fusion methods that incorporate downstream tasks tend to be overly complex and computationally intensive, which is not conducive to practical applications.

TCDDU-Net: combining transformer and convolutional dual-path decoding U-Net for retinal vessel segmentation.

Accurate segmentation of retinal blood vessels is crucial for enhancing diagnostic efficiency and preventing disease progression. However, the small size and complex structure of retinal blood vessels, coupled with low contrast in corresponding fundus images, pose significant challenges for this task. We propose a novel approach for retinal vessel segmentation, which combines the transformer and convolutional dual-path decoding U-Net (TCDDU-Net).

Understanding the Relationship of Closed Pore Structure in Biomass- derived Hard Carbon with Cellulose Regulating Strategy.

Recycling waste biomass to pyrolytic carbon has become a development direction of sodium-ion batteries (SIBs) anodes. However, it remains a challenge to precisely control the composition and structure of biomass to modify the properties of derived carbon. Herein, a strategy of hydrolyzing cellulose in phellem with sulfuric acid is proposed, which can promote cellulose fracture, reduce the graphitization and increase the content of closed pores in hard carbon.

Bacterial community structure and metabolomic profiles of yak milk and cattle-yak milk during refrigeration in Gannan region: Analysis of interspecific differences in milk spoilage.

The bacterial community dynamics and metabolomic profiles in raw yak (Y) milk and cattle-yak (CY) milk during refrigeration at 4 °C were investigated, followed by the elucidation of interspecific differences in milk storage. Bacterial communities and succession patterns were significantly different between the two milk types during refrigeration, with Lactococcus and Pseudomonas being the key distinguishing genera. Moreover, higher network complexity and tighter interactions were observed for the microbial community in CY milk than in Y milk.

Multi-area collision-free path planning and efficient task scheduling optimization for autonomous agricultural robots.

Collision-free path planning and task scheduling optimization in multi-region operations of autonomous agricultural robots present a complex coupled problem. In addition to considering task access sequences and collision-free path planning, multiple factors such as task priorities, terrain complexity of farmland, and robot energy consumption must be comprehensively addressed. This study aims to explore a hierarchical decoupling approach to tackle the challenges of multi-region path planning.

A Method for Real-Time Recognition of Safflower Filaments in Unstructured Environments Using the YOLO-SaFi Model.

The identification of safflower filament targets and the precise localization of picking points are fundamental prerequisites for achieving automated filament retrieval. In light of challenges such as severe occlusion of targets, low recognition accuracy, and the considerable size of models in unstructured environments, this paper introduces a novel lightweight YOLO-SaFi model. The architectural design of this model features a Backbone layer incorporating the StarNet network; a Neck layer introducing a novel ELC convolution module to refine the C2f module; and a Head layer implementing a new lightweight shared convolution detection head, Detect_EL.

Amino modified nanofibers anchored to Prussian blue nanoparticles selectively remove Cs from water.

To improve the selective separation performance of silica nanofibers (SiO NFs) for cesium ions (Cs) and overcome the defects of Prussian blue nanoparticles (PB NPs), PB/SiO-NH NFs were prepared to remove Cs from water. Among them, 3-aminopropyltriethoxysilane (APTES) underwent an alkylation reaction with SiO, resulting in the formation of a dense Si-O-Si network structure that decorated the surface of SiO NFs. Meanwhile, the amino functional groups in APTES combined with Fe and then reacted with Fe to form PB NPs, which anchored firmly on the aminoated SiO NFs surface.

Unveiling unconventional CH4-Xe compounds and their thermodynamic properties at extreme conditions.

Inert gases (e.g., He and Xe) can exhibit chemical activity at high pressure, reacting with other substances to form compounds of unexpected chemical stoichiometry.

Data fusion of near-infrared and Raman spectroscopy: An innovative tool for non-destructive prediction of the TVB-N content of salmon samples.

Total volatile basic nitrogen (TVB-N) serves as a crucial indicator for evaluating the freshness of salmon. This study aimed to achieve accurate and non-destructive prediction of TVB-N content in salmon fillets stored in multiple temperature settings (-20, 0, -4, 20 °C, and dynamic temperature) using near-infrared (NIR) and Raman spectroscopy. A partial least square support vector machine (LSSVM) regression model was established through the integration of NIR and Raman spectral data using low-level data fusion (LLDF) and mid-level data fusion (MLDF) strategies.

Quantitative Characterization of Coal Shale Pores and Fractures Based on Combined High-Pressure Mercury Pressure and Low-Temperature N/CO Adsorption Methods.

Coal shale gas is an important type of shale gas. The microscopic pore size distribution and pore structure characteristics of coal shale determine the macroscopic storage and transportation of coal shale gas. In order to quantitatively characterize the microscopic pore size distribution and pore structure properties of coal shale from a multiscale perspective, the pore size distribution and pore structure of coal shale specimens with different grain sizes were quantitatively characterized using low-temperature N/CO adsorption and high-pressure mercuric pressure methods, taking the coal shale of high-gas mines of the Dongbaowei Mine in the Shuangyashan Basin as the object of study.

Improving the detection accuracy of the dual SERS aptasensor system with uncontrollable SERS "hot spot" using machine learning tools.

Background: Simultaneous detection of food contaminants is crucial in addressing the collective health hazards arising from the presence of multiple contaminants. However, traditional multi-competitive surface-enhanced Raman scattering (SERS) aptasensors face difficulties in achieving simultaneous accurate detection of multiple target substances due to the uncontrollable SERS "hot spots". In this study, using chloramphenicol (CAP) and estradiol (E2) as two target substances, we introduced a novel approach that combines machine learning methods with a dual SERS aptasensor, enabling simultaneous high-sensitivity and accurate detection of both target substances.

Electron transfer mediated photo-Fenton-like synergistic catalysis of Fe,Cu-doped MIL-101 coupled with AgPO: Quantitative evaluation and DFT calculations.

Widespread use of tetracycline (TC) results in its persistent residue and bioaccumulation in aquatic environments, posing a high toxicity to non-target organisms. In this study, a bimetal-doped composite material AgPO/MIL-101(Fe,Cu) has been designed for the treatment of TC in aqueous solutions. As the molar ratio of Fe/Cu in composite is 1:1, the obtained material AP/MFeCu is placed in an aqueous environment under visible light irradiation in the presence of 3 mM peroxydisulfate (PDS), which forms a photo-Fenton-like catalytic system that can completely degrade TC (10 mg/L) within 60 min.

Extending Unique 1D Double-Chains to 2D Layers with Birefringent Gain by Introducing a Hydroxyl Group.

It remains a significant hurdle for discovering birefringent materials in the deep ultraviolet (DUV, λ < 200 nm). It is well-known that the OH anions are recognized for their capability to eliminate the dangling bonds from terminal oxygen atoms, promoting the ultraviolet (UV) cutoff edge blueshift and regulating the crystal structure. Here, two new barium hydroxyborates, BaBO(OH)(HO) (BaBOH) and NaBaBO(OH)(HO) (NaBaBOH), were designed and synthesized while displaying different dimensions.

Experimental and Numerical Investigation of Polymer-Based 3D-Printed Lattice Structures with Largely Tunable Mechanical Properties Based on Triply Periodic Minimal Surface.

Triply periodic minimal surfaces (TPMSs) have demonstrated significant potential in lattice structure design and have been successfully applied across multiple industrial fields. In this work, a novel lattice structure with tunable anisotropic properties is proposed based on two typical TPMS types, and their mechanical performances are studied both experimentally and numerically after being fabricated using a polymer 3D printing process. Initially, adjustments are made to the original TPMS lattice structures to obtain honeycomb lattice structures, which are found to possess significant anisotropy, by utilizing numerical homogenization methods.

Adsorption-desorption characteristics of coal-bearing shale gas under three-dimensional stress state studied by low field nuclear magnetic resonance spectrum experiments.

The micro-scale gas adsorption-desorption characteristics determine the macro-scale gas transport and production behavior. To reveal the three-dimensional stress state-induced gas adsorption-desorption characteristics in coal-bearing shale reservoirs from a micro-scale perspective, the coal-bearing shale samples from the Dongbaowei Coal Mine in the Shuangyashan Basin were chosen as the research subject. Isothermal adsorption-desorption experiments under three-dimensional stress state were conducted using the low field nuclear magnetic resonance (L-NMR) T spectrum method to simulate the in-situ coal-bearing shale gas adsorption-desorption process.

Automatic detection method for tobacco beetles combining multi-scale global residual feature pyramid network and dual-path deformable attention.

Aiming at the problems of identifying storage pest tobacco pest beetles from images that have few object pixels and considerable image noise, and therefore suffer from lack of information and identifiable features, this paper proposes an automatic monitoring method of tobacco beetle based on Multi-scale Global residual Feature Pyramid Network and Dual-path Deformable Attention (MGrFPN-DDrGAM). Firstly, a Multi-scale Global residual Feature Pyramid Network (MGrFPN) is constructed to obtain rich high-level semantic features and more complete information on low-level features to reduce missed detection; Then, a Dual-path Deformable receptive field Guided Attention Module (DDrGAM) is designed to establish long-range channel dependence, guide the effective fusion of features and improve the localization accuracy of tobacco beetles by fitting the spatial geometric deformation features of and capturing the spatial information of feature maps with different scales to enrich the feature information in the channel and spatial. Finally, to simulate a real scene, a multi-scene tobacco beetle dataset is created.

Fe-doping green fluorescent carbon dots via co-electrolysis of chrysoidine G and potassium ferrocyanide for sensitive Cr(VI) detection.

In this study, we aimed to synthesis of Fe-doping green fluorescent carbon dots (G-CDs) through the co-electrolysis of chrysoidine G and potassium ferrocyanide for Cr(VI) detection. The use of potassium ferrocyanide improves the quantum yield and sensing performance of G-CDs toward Cr(VI). The G-CDs have a maximum excitation wavelength of 308 nm and an emission wavelength of 510 nm.

Physiological functions of glucose transporter-2: From cell physiology to links with diabetes mellitus.

Glucose is a sugar crucial for human health since it participates in many biochemical reactions. It produces adenosine 5'-triphosphate (ATP) and nucleosides through glucose metabolic and pentose phosphate pathways. These processes require many transporter proteins to assist in transferring glucose across cells, and the most notable ones are glucose transporter-2 (GLUT-2) and sodium/glucose cotransporter 1 (SGLT1).

Spectral data fusion in nondestructive detection of food products: Strategies, recent applications, and future perspectives.

In recent years, the food industry has shown a growing interest in the development of rapid and nondestructive analytical methods. However, the utilization of a solitary nondestructive detection technique offers only a constrained extent of physical or chemical insights regarding the sample under examination. To overcome this limitation, the amalgamation of spectroscopy with data fusion strategies has emerged as a promising approach.

Preparation and Electrochemical Performance of NaLiFePOF/C Composite Cathode Materials with Different Lithium/Sodium Ratios.

With their advantages of abundant raw material reserves, safety, and low toxicity and cost, sodium-ion batteries (SIBs) have gained increasing attention in recent years. Thanks to a high theoretical specific capacity (124 mAh g), a high operating voltage (about 3.2 V), and a very stable three-dimensional layered structure, sodium ferric fluorophosphate (NaFePOF, NFPF) has emerged as a strong candidate to be used as a cathode material for SIBs.

Genome-wide identification, evolution, and role of SPL gene family in beet (Beta vulgaris L.) under cold stress.

Background: SPL transcription factors play vital roles in regulating plant growth, development, and abiotic stress responses. Sugar beet (Beta vulgaris L.), one of the world's main sugar-producing crops, is a major source of edible and industrial sugars for humans.