Novel f-CaO soft sensor for cement clinker based on integrated model of dual-parallel structure.

Aiming at the problem that the cement production process is inherently affected by uncertainty, time delay, and strong coupling among variables, this paper proposed a novel soft sensor of free calcium oxide in a cement clinker. The model utilizes a dual-parallel integrated structure with an optimized integration of one-dimensional convolutional neural networks, long and short-term memory networks, graphical neural networks, and extreme gradient boosting. The proposed model can mitigate the risks associated with overfitting while incorporating the strengths of each individual model and excels in extracting both local and global features as well as temporal and spatial characteristics from the original time series data, ensuring its stability. The experimental results demonstrate that this dual-parallel integrated model exhibits superior robustness, predictive accuracy, and generalization capabilities when compared to single models or enhancements made to other deep learning algorithms.

IFKMHC: Implicit Fuzzy K-Means Model for High-Dimensional Data Clustering.

The graph-information-based fuzzy clustering has shown promising results in various datasets. However, its performance is hindered when dealing with high-dimensional data due to challenges related to redundant information and sensitivity to the similarity matrix design. To address these limitations, this article proposes an implicit fuzzy k-means (FKMs) model that enhances graph-based fuzzy clustering for high-dimensional data. Instead of explicitly designing a similarity matrix, our approach leverages the fuzzy partition result obtained from the implicit FKMs model to generate an effective similarity matrix. We employ a projection-based technique to handle redundant information, eliminating the need for specific feature extraction methods. By formulating the fuzzy clustering model solely based on the similarity matrix derived from the membership matrix, we mitigate issues, such as dependence on initial values and random fluctuations in clustering results. This innovative approach significantly improves the competitiveness of graph-enhanced fuzzy clustering for high-dimensional data. We present an efficient iterative optimization algorithm for our model and demonstrate its effectiveness through theoretical analysis and experimental comparisons with other state-of-the-art methods, showcasing its superior performance.

Self-template synthesis of mesoporous and biodegradable Fe3O4 nanospheres as multifunctional nanoplatform for cancer therapy.

Superparamagnetic Fe3O4 nanospheres have demonstrated great potential as important components in nanomedicine for cancer imaging and therapy. One of the major obstacles that impedes their application is the slow degradation of ingested Fe3O4 nanospheres, which potentially causes long-term health risks. To tackle this issue, we proposed to fabricate Fe3O4 nanospheres with mesoporous structure via a simple self-template etching method. The mesoporous Fe3O4 nanospheres not only offered large specific surface area and weak-acidic responsive degradability, but also exhibited T2-weighted magnetic resonance contrast enhancement and magnetic targeting, which made them possible to serve as excellent cancer therapeutic nanoplatform. Both inorganic photothermal therapeutic Au nanoparticles and organic chemotherapeutic doxorubicin hydrochloride were demonstrated to be successfully loaded onto such kind of nanoplatform, and the hybrid nanomedicine demonstrated synergistic photothermal and chemotherapeutic activity for tumor elimination under near infrared irradiation and improved biodegradability in weak acidic tumor microenvironment. We believe that this study paved a simple way for designing multifunctional Fe3O4-based biodegradable nanomedicine.

The dissemination effect of human-computer interactive advertising news-Using the theory of media audience and emotion management.

The development and application of network media has seriously impacted the social information dissemination environment dominated by traditional media. To break the dissemination barriers encountered by traditional media, this work probes into the dissemination effect of human-computer interactive advertising news. An in-depth analysis of the current dissemination situation of interactive online advertising (IOA) is firstly conducted, and then the methods to effectively guide and manage audience emotions are studied. Finally, an improved LeNet-5 model is established to identify audience emotions. The improvement of the LeNet-5 model in this work is composed of the following four points. (1) The convolution module sets Inception_conv3 and Inception_conv5 are adopted to replace the third convolutional layer Conv3 and the fifth layer Conv5 of the LeNet-5, respectively. (2) The size of the convolution kernel is changed. The original convolution kernel is replaced by two 3 × 3 convolution kernels in the Inception_conv3 and Inception_conv5 module sets. (3) The number of convolution kernels is reasonably changed. (4) The Batch Normalization (BN) layer is used. The experimental results show that interactive advertisements have the better dissemination effects among the audiences with older age, higher education, and in more developed cities. The improved LeNet-5 network can effectively solve the over-fitting and gradient disappearance, with a good robustness. The recognition rate reaches more than 81%, which is higher than the traditional LeNet-5 network by 3%. It can be known that the accuracy of the improved LeNet-5 network image recognition is significantly promoted. This research provides a certain reference for the optimization of news dissemination.

Hollow Prussian Blue Nanospheres for Photothermal/Chemo-Synergistic Therapy.

BACKGROUND: The integration of NIR photothermal therapy and chemotherapy is considered as a promising technique for future cancer therapy. Hollow Prussian nanospheres have attracted much attention due to excellent near-infrared photothermal conversion effect and drug-loading capability within an empty cavity. However, to date, the hollow Prussian nanospheres have been prepared by a complex procedure or in organic media, and their shell thickness and size cannot be controlled. Thus, a simple and controllable route is highly desirable to synthesize hollow Prussian nanospheres with controllable parameters. MATERIALS AND METHODS: Here, in our designed synthesis route, the traditional FeCl3 precursor was replaced with Fe2O3 nanospheres, and then the Prussian blue (PB) nanoparticles were engineered into hollow-structured PB (HPB) nanospheres through an interface reaction, where the Fe2O3 colloidal template provides Fe3+ ions. The reaction mechanism and control factors of HPB nanospheres were systematically investigated. Both in vitro and in vivo biological effects of the as-synthesized HPB nanospheres were evaluated in detail. RESULTS: Through systematical experiments, a solvent-mediated interface reaction mechanism was put forward, and the parameters of HPB nanospheres could be easily adjusted by growth time and template size under optimal water and ethanol ratio. The in vitro tests show the rapid and remarkable photothermal effects of the as-prepared HPB nanospheres under NIR laser irradiation (808 nm). Meanwhile, HPB nanospheres also demonstrated a high DOX loading capacity of 440 mg g-1 as a drug carrier, and the release of the drug can be regulated by the heat from PB shell under the exposure of an NIR laser. The in vivo experiments confirmed the outstanding performance of HPB nanospheres in photothermal/chemo-synergistic therapy of cancer. CONCLUSION: A solvent-mediated template route was developed to synthesize hollow Prussian blue (HPB) nanospheres in a simple and controllable way. The in vitro and in vivo results demonstrate the as-synthesized HPB nanospheres as a promising candidate due to their low toxicity and high efficiency for cancer therapy.

An analytical strategy for accurate, rapid and sensitive quantitative analysis of isoflavones in traditional Chinese medicines using ultra-high performance supercritical fluid chromatography: Take Radix Puerariae as an example.

Isoflavones are phenolic phytoestrogens due to their structural similarity to estradiol, so they usually serve as active component for quality control of traditional Chinese medicines (TCMs) rich in isoflavones. However, TCMs contains various kinds of similar isoflavones, especially isomers, which to a significant extent hinders accurate analysis of isoflavones in TCMs. Here, we present a novel analytical strategy for quality control of TCMs rich in isoflavones using ultra-high performance supercritical fluid chromatography coupled to photodiode array detection (UHPSFC-PDA) and tandem mass spectrometry (UHPSFC-MS/MS). Both chromatography and mass spectrometry parameters were optimized in order to develop an accurate, rapid, sensitive method for quantification of isoflavones. The reproducibility of quantitative analysis of multi-components by single marker (QAMS) using UHPSFC-PDA was discussed in terms of mobile phase gradient, temperature and backpressure for the first time. An analytical method for the analysis of isoflavones using UHPSFC-MS/MS was developed for the first time, and the established method was successfully applied to quantify isoflavones in three species of Radix Puerariae. The study showed Radix Pueraria Peduncularis contained higher amounts of isoflavones than Radix Puerariae Thomsonii, and it is worth noting that Radix Pueraria Peduncularis was often overlooked by researchers. It took less than 8 min with the current method and the limit of detection was not more than 0.05 ng/ml, which was definitely sufficient for anlysis of various samples from TCMs without enrichment.

Biosynthesis of staphylococcal enterotoxin A by genetic engineering technology and determination of staphylococcal enterotoxin A in water by HPLC-ESI-TOF.

Staphylococcal enterotoxin A (SEA) was the major virulence factor of Staphylococcus aureus and a biomarker of S. aureus. To establish a fast, low cost, high accuracy, reliable, and simple method for detecting S. aureus, SEA was analyzed by HPLC-ESI-TOF. SEA was not yet commercially available in universal, so SEA was prepared before it was analyzed by HPLC-ESI-TOF. The result showed that high purified SEA was successfully prepared and SEA has normal distribution in mass spectra. A large amount of recombinant SEA (rSEA) was obtained by engineering technology and was purified by Ni affinity chromatography column, and the expression and purity of rSEA and SEA were analyzed by SDS-PAGE. The factors effected on ionization of SEA were studied, and the qualitative analysis of SEA by HPLC-ESI-TOF. The result showed that large amount of SEs expressed within a short time at 28 °C or thereabouts, and there was no impurity bands in electrophorogram after rSEA was purified by Ni affinity chromatography column. In addition, the SEA which had homologous AA sequence with wild SEA was made by rSEA. The retention of SEA in column and ionization of SEA in ESI-TOF were studied for qualitative analysis of S. aureus. The result showed that the content of formic acid in mobile phase was an important factor for ionization of SEs in ESI-TOF. And the result provided theoretical foundation for qualitative detection of S. aureus. [SEs + nH+ + mNH4+] n+m+ was shown on ESI-TOF spectra when SEA was detected by ESI-TOF in positive ion mode, and the numerical value of n+m was less than or equal to the number of basic amino acids in SEs. This method was applied to determine SEA in water samples preliminarily, and the detection limit of SEA in spiked water sample was 3 mg/kg. The limit of detection of 3 mg/kg was low sensitivity for low molecular weight matters, but it was high sensitivity for SEA which had a high molecular weight of 27 kDa. Of SEA, 3 mg/kg was equivalent to 10-4 mmol/kg of SEA. This study can provide evidence for establishing method to determine SEA in real samples.

Simple, rapid, and environmentally friendly method for the separation of isoflavones using ultra-high performance supercritical fluid chromatography.

Isoflavones are natural substances that exhibit hormone-like pharmacological activities. The separation of isoflavones remains an analytical challenge because of their similar structures. We show that ultra-high performance supercritical fluid chromatography can be an appropriate tool to achieve the fast separation of 12 common dietary isoflavones. Among the five tested columns the Torus DEA column was found to be the most effective column for the separation of these isoflavones. The impact of individual parameters on the retention time and separation factor was evaluated. These parameters were optimized to develop a simple, rapid, and green method for the separation of the 12 target analytes. It only took 12.91 min using gradient elution with methanol as an organic modifier and formic acid as an additive. These isoflavones were determined with limit of quantitation ranging from 0.10 to 0.50 µg/mL, which was sufficient for reliable determination of various matrixes.