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In this paper, we synthesize the differences in grayscale and texture information of phosphorite X-ray images and extract a total of six feature quantities under their grayscale and texture features, respectively. After feature fusion, a fuzzy support vector machine classifier with a normal plane-type affiliation function is used to optimize the binary classification method of traditional support vector machines, which improves the accuracy of classification. To improve the sorting model’s division of the optimal classification hyperplane, the centroid position of the two types of samples is considered comprehensively. In order to give full play to the classification performance of the sorting model, the particle swarm algorithm is further used to optimize the core parameters of the fuzzy support vector machine, the penalty factor, and the kernel parameters to complete the construction of the classifier model. In the face of the mixed colloidal phosphorite that can not be exploited, based on the PSO-NP-FSVM photoelectric sorting operation, the concentrate yield rate, operation recovery rate, and optical sorting waste rate are 56.52%, 20.87%, and 71.17%, respectively. After photoelectric sorting, the grade of concentrate P2 O5 can be increased to 20.98%, which can meet the requirements for the grade of the processing plant. Therefore, the photoelectric sorting process combined with a fuzzy algorithm is capable of meeting the actual production requirements.

In acquiring language, differences in input can greatly affectlearning outcomes, but which aspects of language learning aremost sensitive to input variations, and which are robust, remainsdebated. A recent modeling study successfully reproduced aphenomenon empirically observed in early phonetic learning—learning about the sounds of the native language in the firstyear of life—despite using input that differed in quantity andspeaker composition from what a typical infant would hear. Inthis paper, we carry out a direct test of that model’s robustnessto input variations. We find that, despite what the original resultsuggested, the learning outcomes are sensitive to properties ofthe input and that more plausible input leads to a better fit withempirical observations. This has implications for understandingearly phonetic learning in infants and underscores the impor-tance of using realistic input in models of language acquisition.

Transient ischemic attack (TIA) is an early warning sign of stroke and death, necessitating suitable animal models due to the associated clinical diagnostic challenges. In this study, we developed a TIA model using flexible spatially targeted photothrombosis combined with real-time blood flow imaging feedback. By modulating the excitation light using wavefront technology, we precisely created a square light spot (50 × 250 µm), targeted at the distal middle cerebral artery (dMCA). The use of laser speckle contrast imaging (LSCI) provided real-time feedback on the ischemia, while the excitation light was ceased upon reaching complete occlusion. Our results demonstrated that the photothrombus formed in the dMCA and spontaneously recanalized within 10 min (416.8 ± 96.4 s), with no sensorimotor deficits or infarction 24 h post-TIA. During the acute phase, ischemic spreading depression occurred in the ipsilateral dorsal cortex, leading to more severe ischemia and collateral circulation establishment synchronized with the onset of dMCA narrowing. Post-reperfusion, the thrombi were primarily in the sensorimotor and visual cortex, disappearing within 24 h. The blood flow changes in the dMCA were more indicative of cortical ischemic conditions than diameter changes. Our method successfully establishes a photochemical TIA model based on the dMCA, allowing for the dynamic observation and control of thrombus formation and recanalization and enabling real-time monitoring of the impacts on cerebral blood flow during the acute phase of TIA. [ABSTRACT FROM AUTHOR]

The acid–base surface properties of vivianite crystals highly affect the adsorption capacity of vivianite for heavy metals and organic matters in aqueous solution. Therefore, the aim of the study was to innovatively explore and quantify the acid–base surface characterization of vivianite crystals in aqueous solution. It was found that the two surface active adsorption sites (≡POH and ≡FeOH) and five surface species thereof (i.e., ≡PO, ≡POH, ≡FeOH, ≡FeO−, and ≡FeOH2+) underwent surface reaction on vivianite crystals. Moreover, the active surface site and point of zero charge of vivianite crystals were 18 sites/nm2 and pH 5.9. Importantly, constant capacitance model was successfully employed to model the titration data, from which the distribution of surface species as function of pH and surface reaction constants were also accurately derived. The finding herein can be applied for plausible modeling molecular‐scale adsorption of the impurities on vivianite surface. [ABSTRACT FROM AUTHOR]