ASFL-YOLOX: an adaptive spatial feature fusion and lightweight detection method for insect pests of the Papilionidae family

IntroductionInsect pests from the family Papilionidae (IPPs) are a seasonal threat to citrus orchards, causing damage to young leaves, affecting canopy formation and fruiting. Existing pest detection models used by orchard plant protection equipment lack a balance between inference speed and accuracy.MethodsTo address this issue, we propose an adaptive spatial feature fusion and lightweight detection model for IPPs, called ASFL-YOLOX. Our model includes several optimizations, such as the use of the Tanh-Softplus activation function, integration of the efficient channel attention mechanism, adoption of the adaptive spatial feature fusion module, and implementation of the soft Dlou non-maximum suppression algorithm. We also propose a structured pruning curation technique to eliminate unnecessary connections and network parameters.ResultsExperimental results demonstrate that ASFL-YOLOX outperforms previous models in terms of inference speed and accuracy. Our model shows an increase in inference speed by 29 FPS compared to YOLOv7-x, a higher mAP of approximately 10% than YOLOv7-tiny, and a faster inference frame rate on embedded platforms compared to SSD300 and Faster R-CNN. We compressed the model parameters of ASFL-YOLOX by 88.97%, reducing the number of floating point operations per second from 141.90G to 30.87G while achieving an mAP higher than 95%.DiscussionOur model can accurately and quickly detect fruit tree pest stress in unstructured orchards and is suitable for transplantation to embedded systems. This can provide technical support for pest identification and localization systems for orchard plant protection equipment

Non-destructive detection of kiwifruit soluble solid content based on hyperspectral and fluorescence spectral imaging

The soluble solid content (SSC) is one of the important parameters depicting the quality, maturity and taste of fruits. This study explored hyperspectral imaging (HSI) and fluorescence spectral imaging (FSI) techniques, as well as suitable chemometric techniques to predict the SSC in kiwifruit. 90 kiwifruit samples were divided into 70 calibration sets and 20 prediction sets. The hyperspectral images of samples in the spectral range of 387 nm~1034 nm and the fluorescence spectral images in the spectral range of 400 nm~1000 nm were collected, and their regions of interest were extracted. Six spectral pre-processing techniques were used to pre-process the two spectral data, and the best pre-processing method was selected after comparing it with the predicted results. Then, five primary and three secondary feature extraction algorithms were used to extract feature variables from the pre-processed spectral data. Subsequently, three regression prediction models, i.e., the extreme learning machines (ELM), the partial least squares regression (PLSR) and the particle swarm optimization - least square support vector machine (PSO-LSSVM), were established. The prediction results were analyzed and compared further. MASS-Boss-ELM, based on fluorescence spectral imaging technique, exhibited the best prediction performance for the kiwifruit SSC, with the Rp2, Rc2 and RPD of 0.8894, 0.9429 and 2.88, respectively. MASS-Boss-PLSR based on the hyperspectral imaging technique showed a slightly lower prediction performance, with the Rp2, Rc2, and RPD of 0.8717, 0.8747, and 2.89, respectively. The outcome presents that the two spectral imaging techniques are suitable for the non-destructive prediction of fruit quality. Among them, the FSI technology illustrates better prediction, providing technical support for the non-destructive detection of intrinsic fruit quality

One-Pot Synthesis of Co-Based Coordination Polymer Nanowire for Li-Ion Batteries with Great Capacity and Stable Cycling Stability

Abstract Nanowire coordination polymer cobalt–terephthalonitrile (Co-BDCN) was successfully synthesized using a simple solvothermal method and applied as anode material for lithium-ion batteries (LIBs). A reversible capacity of 1132 mAh g−1 was retained after 100 cycles at a rate of 100 mA g−1, which should be one of the best LIBs performances among metal organic frameworks and coordination polymers-based anode materials at such a rate. On the basis of the comprehensive structural and morphology characterizations including fourier transform infrared spectroscopy, 1H NMR, 13C NMR, and scanning electron microscopy, we demonstrated that the great electrochemical performance of the as-synthesized Co-BDCN coordination polymer can be attributed to the synergistic effect of metal centers and organic ligands, as well as the stability of the nanowire morphology during cycling

Nitrogen, Phosphorus, and Sulfur Co-Doped Hollow Carbon Shell as Superior Metal-Free Catalyst for Selective Oxidation of Aromatic Alkanes

Metal-free heteroatom-doped carbocatalysts with a high surface area are desirable for catalytic reactions. In this study, we found an efficient strategy to prepare nitrogen, phosphorus, and sulfur co-doped hollow carbon shells (denote as NPS-HCS) with a surface area of 1020m(2)g(-1). Using a poly(cyclotriphosphazene-co-4,4-sulfonyldiphenol) (PZS) shell as carbon source and N, P, S-doping source, and the ZIF-67 core as structural template as well as extra N-doping source, NPS-HCS were obtained with a high surface area and superhydrophilicity. All these features render the prepared NPS-HCS a superior metal-free carbocatalyst for the selective oxidation of aromatic alkanes in aqueous solution. This study provides a reliable and facile route to prepare doped carbocatalysts with enhanced catalytic properties

Broad photoluminescence in ternary Ag-In-S and quaternary Ag-In-Zn-S nanoparticles: the role of Zn incorporation

Ternary Ag-In-S and quaternary Ag-In-Zn-S nanoparticles with different ratio of Ag/In/Zn/S are synthesized. The incorporation of Zn into Ag-In-S nanoparticles leads to the increase in the optical bandgap and the blue shift of photoluminescence (PL). The optical properties of these nanoparticles are significantly dependent on the chemical composition of nanoparticles. Time-resolved PL spectroscopy in nanosecond time regime is used to study the recombination processes of carriers, which involve the surface states and intrinsic crystallographic defects. These measurements support the donor-acceptor model, in which the PL is achieved by radiative recombination of the localized electron and hole

Au(I)-Catalyzed 6-endo-dig Cyclizations of Aromatic 1,5-Enynes to 2-(Naphthalen-2-yl)anilines Leading to Divergent Syntheses of Benzo[α]carbazole, Benzo[c,h]cinnoline and Dibenzo[i]phenanthridine Derivatives

A gold(I)-catalyzed 6-endo-dig cyclization of aromatic 1,5-enyne was developed to synthesize 2-(naphthalen-2-yl)aniline. The functional group tolerance of this cyclization was examined systematically and a possible mechanism was proposed. The derivatization of 2-(naphthalen-2-yl)aniline was carried out to facile access to benzo[α]carbazole, benzo[c,h]cinnoline and dibenzo[i]phenanthridine derivatives in a divergent way