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In this article, we present a one-parameter fractional multiplicative integral identity and use it to derive a set of inequalities for multiplicatively ss-convex mappings. These inequalities include new discoveries and improvements upon some well-known results. Finally, we provide an illustrative example with graphical representations, along with some applications to special means of real numbers within the domain of multiplicative calculus.

Exosome-like nanoparticles （ELNs） are nano-sized extracellular vesicles enclosed by lipid bilayer membrane and secreted by cells; And carrying a variety of cargo, including lipids, proteins, miRNAs and secondary metabolites. Plant ELNs have received widespread attention due to their unique structure and excellent physiological activity. This review summarizes the isolation methods, characteristics, components and functions of plant ELNs, focusing on the application of multi-omics technologies in plant ELNs. In addition, some suggestions for further study of plant ELNs were put forward.

Objective To establish a fungal image-assisted classification model using deep learning technology. Methods The microscope images of people infected with Aspergillus, Saccharomyces and Cryptococcus neoformans were retrospectively collected from the Eighth Medical Center of PLA General Hospital from September 2020 to April 2021. The images were randomly divided into training set, validation set and test set according to the ratio of 7∶1.5∶1.5. The improved MobileNetV2 network structure was trained using the training set, a convolutional neural network (CNN) fungal image 11 classification model based on multi-scale attention mechanism was constructed and the parameters were debugged based on the validation set. Machine identification results were taken as the gold standard, the performance of the model on 11 fungal image classification tasks was evaluated, and the results were shown by precision, recall and F1 value. In addition, the performance of the proposed model with 5 classic CNN models were compared, and the results were measured in terms of model parameters, memory usage, frames per second (FPS), accuracy, and area under the curve (AUC) of receiver operating characteristic curve. Results A total of 7666 fungal microscope images were collected, including 2781, 4115, and 770 images of Aspergillus, Saccharomyces, and Cryptococcus neoformans, respectively. Among them, there were 5366 training images, 1150 validation images, and 1150 test images. The improved MobileNetV2 model had high performance for the classification of 11 fungal images in the test set. The precision rate was distributed between 96.36% and 100%, the recall rate was distributed between 96.53% and 100%, and the F1 value was distributed between 97.01% and 100%. The parameters, memory usage, FPS, accuracy, and AUC of the improved MobileNetV2 model were 4.22 M, 356.89 M, 573, (99.09±0.18)%, and 0.9944±0.0018, respectively, and the comprehensive performance was better than 5 kinds of classical networks. Conclusion The proposed fungal image classification model based on the improved MobileNetV2 can obtain higher fungal image recognition ability while maintaining low computational cost, with an overall performance better than classical CNN model.

Conductive elastomer materials based on carbon black (CB) filled bromo-isobutylene-isoprene rubber (BIIR)/polypropylene (PP) thermoplastic vulcanizate (TPV) were prepared by two step method and one step method. The microstructure, mechanical properties, electrical resistivity, thermal stability, electromagnetic interference shielding performance, and fracture surface morphology of composite materials were studied. The result shows the serious aggregation of CB in one-step TPV, but the uniform dispersion of CB in two-step TPV. In addition, the two-step TPV shows a higher electromagnetic interference (EMI) shielding performance and lower conductivity penetration threshold. The penetration threshold of the two-step TPV is 9.1%, and the maximum reflection loss of the two-step TPV16 is −29.5 dB. Therefore, this research offers an uncomplicated and scalable melt mixing approach method to manufacture conductive thermoplastic vulcanizates with excellent EMI shielding.

Morchella is a genus of fungi with the ability to concentrate Cd both in the fruit-body and mycelium. However, the molecular mechanisms conferring resistance to Cd stress in Morchella are unknown. Here, RNA-based transcriptomic sequencing was used to identify the genes and pathways involved in Cd tolerance in Morchella spongiola. 7444 differentially expressed genes (DEGs) were identified by cultivating M. spongiola in media containing 0.15, 0.90, or 1.50 mg/L Cd2+. The DEGs were divided into six sub-clusters based on their global expression profiles. GO enrichment analysis indicated that numerous DEGs were associated with catalytic activity, cell cycle control, and the ribosome. KEGG enrichment analysis showed that the main pathways under Cd stress were MAPK signaling, oxidative phosphorylation, pyruvate metabolism, and propanoate metabolism. In addition, several DEGs encoding ion transporters, enzymatic/non-enzymatic antioxidants, and transcription factors were identified. Based on these results, a preliminary gene regulatory network was firstly proposed to illustrate the molecular mechanisms of Cd detoxification in M. spongiola. These results provide valuable insights into the Cd tolerance mechanism of M. spongiola and constitute a robust foundation for further studies on detoxification mechanisms in macrofungi that could potentially lead to the development of new and improved fungal bioremediation strategies.

In this paper, we introduce the concept of the perfect ϕ\phi -type to describe the growth of the maximal molecule of Laplace-Stieltjes transform by using the more general function than the usual. Based on this concept, we investigate the approximation and growth of analytic functions F(s)F(s) defined by Laplace-Stieltjes transforms convergent in the half plane and obtain some results about the necessary and sufficient conditions on analytic functions F(s)F(s) defined by Laplace-Stieltjes transforms with perfect ϕ\phi -type, which are some generalizations and improvements of the previous results given by Kong [On generalized orders and types of Laplace-Stieltjes transforms analytic in the right half-plane, Acta Math. Sin. 59A (2016), 91–98], Singhal and Srivastava [On the approximation of an analytic function represented by Laplace-Stieltjes transformations, Anal. Theory and Appl. 31 (2015), 407–420].

After long-term operation, the flow characteristics of the high-pressure regulating valve of a thermal power unit may be shifted to a certain extent, resulting in inconsistent changes in the total valve position and opening degree, which in turn affects the PFR function of the unit. Based on the historical operation data of a thermal power unit, the flow characteristics of the unit's high-pressure regulating valve are optimized using an improved particle swarm algorithm. By experimentally verifying the primary FM in different total valve position intervals, the influence of valve flow characteristics on the primary FM function is discussed. The results of the primary FM example show that, with the optimized valve flow characteristics, the output response index of the unit in 15 and 30 seconds is increased to 85.44% and 94.11%, respectively, which meets the assessment requirements of the grid-connected operation and management of the power plant for the primary FM, and optimizes the primary FM performance of the unit.

In combination with features such as intensive labor and speech in the customer service report field, this paper discusses the design of a customer service report system based on artificial intelligence automatic speech recognition technology and big data text classification technology. The proposed system realizes functions like a flat IVR menu, quick transcription and input of work orders, dynamic tracking of failure hotspots, automatic classification and accumulation of the knowledge base, speech emotion detection and real-time supervision of service quality, and it can improve the user experience and reduce the labor strengths of customer service staff. The automatically accumulated knowledge base can further assist with feedback to resolve the difficult problem that the emerging intelligent network Q&A and intelligent robots rely on a manually summarized knowledge base.

BackgroundAdoptive transfer of T cells is a burgeoning cancer therapeutic approach. However, the fate of the cells, once transferred, is most often unknown. We describe the first clinical experience with a non-invasive biomarker to assay the apoptotic cell fraction (ACF) after cell therapy infusion, tested in the setting of head and neck squamous cell carcinoma (HNSCC). A patient with HNSCC received autologous tumor-infiltrating lymphocytes (TILs) labeled with a perfluorocarbon (PFC) nanoemulsion cell tracer. Nanoemulsion, released from apoptotic cells, clears through the reticuloendothelial system, particularly the Kupffer cells of the liver, and fluorine-19 (19F) magnetic resonance spectroscopy (MRS) of the liver was used to non-invasively infer the ACF.MethodsAutologous TILs were isolated from a patient in their late 50s with relapsed, refractory human papillomavirus-mediated squamous cell carcinoma of the right tonsil, metastatic to the lung. A lung metastasis was resected for T cell harvest and expansion using a rapid expansion protocol. The expanded TILs were intracellularly labeled with PFC nanoemulsion tracer by coincubation in the final 24 hours of culture, followed by a wash step. At 22 days after intravenous infusion of TILs, quantitative single-voxel liver 19F MRS was performed in vivo using a 3T MRI system. From these data, we model the apparent ACF of the initial cell inoculant.ResultsWe show that it is feasible to PFC-label ~70×1010 TILs (F-TILs) in a single batch in a clinical cell processing facility, while maintaining >90% cell viability and standard flow cytometry-based release criteria for phenotype and function. Based on quantitative in vivo 19F MRS measurements in the liver, we estimate that ~30% cell equivalents of adoptively transferred F-TILs have become apoptotic by 22 days post-transfer.ConclusionsSurvival of the primary cell therapy product is likely to vary per patient. A non-invasive assay of ACF over time could potentially provide insight into the mechanisms of response and non-response, informing future clinical studies. This information may be useful to developers of cytotherapies and clinicians as it opens an avenue to quantify cellular product survival and engraftment.

We describe an in vivo imaging probe platform that is readily modifiable to accommodate binding of different molecular targeting moieties and payloads for multimodal image generation. In this work, we demonstrate the utility of perfluorocarbon (PFC) nanoemulsions incorporating dibenzocyclooctyne (DBCO) by enabling postemulsification functionalization via a click reaction with azide-containing ligands. The addition of DBCO-lipid to the surfactant in PFC nanoemulsions did not affect nanoemulsion size or nanoemulsion stability. As proof-of-concept, fluorescent dye-azides were conjugated to PFC nanoemulsions, demonstrating the feasibility of functionalization the by click reaction. Uptake of the fluorescent PFC by macrophages was demonstrated both in vitro in cultured macrophages and in situ in an acute inflammation mouse model, where fluorescence imaging and 1H/19F magnetic resonance imaging (MRI) were used for in vivo detection. Overall, these data demonstrate the potential of PFC nanoemulsions incorporating DBCO as a versatile platform for generating functionalized probes.