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Phosphate resources are non-renewable and are increasingly depleting. Currently, the primary raw material for commercial ABC dry powder fire-extinguishing agents is a processed product derived from the limited reserves of phosphorus ore. Consequently, there is an urgent imperative to innovate and develop novel types of dry powder fire-extinguishing agents. In this work, a simple physical blending process was utilized to modify the abundant and cost-effective hydromagnesite (HM) powder, which has been proven to be a promising dry powder extinguishant with a pronounced physical cooling effect on fire suppression. The HM powder added to 10 wt.% diammonium hydrogen phosphate (DAP) showed a shorter extinguishing time and a lower agent dosage compared with the unmodified powder and commercially available monoammonium phosphate (MAP) in both the liquid and solid fire experiments. Notably, the HM/DAP composite dry powder extinguished fires with the lowest CO concentration, indicating superior environmental friendliness and human safety. These findings indicate the potential of the HM/DAP composite dry powder as a promising candidate for future fire-extinguishing applications. [ABSTRACT FROM AUTHOR]

The sensorless vector control method of synchronous reluctance motors (SynRMs), based on extended back electromotive force (EMF) or flux observation, has been widely applied in the medium- or high-speed range. However, in the low-speed and low-current range, the extended back-EMF and flux are nearly zero. The use of the current frequency (I-f) control method can enable the motor to pass through the low-speed region, thereby ensuring that the back-EMF and flux reach a large value. I-f control methods that are widely used in permanent magnet synchronous motors (PMSMs) may encounter many problems when applied to SynRMs. The most serious issue is the inability to adjust the current amplitude to control the rotor angle and achieve a smooth transition to sensorless control. Based on various issues, this article proposes an I-f control method with four stages that can be used in SynRMs. This method uses a simple inductance identification method to solve the flux saturation phenomenon of SynRMs and then uses high-frequency voltage injection to continuously adjust the current amplitude and rotor angle position in conjunction with this inductance identification method. The effectiveness of this method is experimentally demonstrated on a 5.5 kW SynRM. [ABSTRACT FROM AUTHOR]

ABSTRACT Objective Methods Results Conclusions To investigate the cellular components and immunological characteristics of the head and neck rhabdomyosarcoma (RMS) microenvironment.We conducted single‐cell transcriptomics to analyze the cellular components of the RMS microenvironment. CellChat was utilized for analyzing intercellular interactions. The cancer genome atlas database was used for validation. CIBERSORT was applied for immune infiltration profiling. Functional enrichment analyses were performed using the Kyoto Encyclopedia of Genes and Genomes. Gene set scores were calculated using single‐sample gene set enrichment analysis. Subcutaneous allograft models and bulk RNA sequencing were used for validation. Flow cytometry and immunohistochemistry were used to identify M2‐like macrophages.Our findings revealed an extremely low presence of neutrophils in RMS samples compared with normal sample. RMS sample with high Schwann cell infiltration exhibited an increase in M2‐like macrophage infiltration. Receptor‐ligand pairs, specifically MIF‐CD74 and PTN‐SDC3, were identified between Schwann cells and M2‐like macrophages. In the RMS sample characterized by significant Schwann cell infiltration, M2‐like macrophages demonstrate robust expression of axon guidance factors and are enriched in the axon guidance pathway.Our study provides valuable insights into the microenvironment and immunological characteristics of RMS, offering crucial information for further research and potential therapeutic strategies. [ABSTRACT FROM AUTHOR]

Plant propagules are crucial flora memory materials in restoration practice. Awakening flora memory from plant propagules (i.e. seeds, root fragments, rhizomes, corms, and tubers) in the translocated topsoil from a donor site is a rapid method for forest restoration on degraded sites globally. However, it remains unclear to what extent manageable measures, such as light reduction and watering, affect flora memory awakening. We employed a quadratic saturation D‐optimal design in a forest topsoil translocation experiment to quantify the effects of light reduction and watering on flora memory awakening. We used the cumulative number and richness of plantlets emerging from plant propagules to represent the extent of flora memory awakening. Our results show that any combinations of light reduction and watering significantly increased both the cumulative number and richness of plantlets across different life forms. Light reduction had a significantly more positive effect on flora memory awakening than watering. Different life forms exhibited different parabolic or positive linear relationships in responses to light reduction and watering. Light reduction of about 60% of the degraded site and watering of about 80% of the donor site resulted in the highest number and richness of plantlets. We concluded that light reduction and watering combinations were effective in kick‐starting the flora memory awakening in a semiarid subtropical forest after topsoil translocation. [ABSTRACT FROM AUTHOR]

Catalytic therapies, such as chemodynamic therapy and ferroptosis, harness the tumor microenvironment to enhance the specificity and penetration of treatments, thus improving targeted tumor therapy. Despite these advancements, treatment effectiveness varies due to individual differences, making precise monitoring of drug activity and dosage essential to optimize therapy. Traditional imaging strategies, which monitor metal ion release or reactive oxygen species production, frequently fail to well correlate with therapeutic outcome. Herein, this study have developed an integrated self‐monitoring catalytic therapy platform that combines palladium‐ and manganese‐based nanoparticles (PdMn NPs) with caspase‐3 activated probe (Casp probe). Dual‐channel MRI and fluorescent probe, responsive to both low pH and caspase‐3 activity, significantly enhances the accuracy of real‐time therapeutic evaluations, allowing for early reporting treatment response (in 6 h), earlier than tumor volume reduction (8 days). This approach improves the assessment of therapeutic outcomes and aligns with the shift toward individualized cancer treatment protocols. [ABSTRACT FROM AUTHOR]

ObjectiveMaterials and MethodsResultsConclusionsTo investigate the mechanisms behind acquired resistance to erlotinib in head and neck squamous cell carcinoma (HNSCC) with a focus on the role of cancer‐associated fibroblasts (CAFs) and the PI3K/AKT signaling pathway.This study analyzed gene expression profiles of erlotinib‐sensitive and ‐resistant HNSCC cell lines using datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. It included microarray and RNA‐sequencing data, differentially expressed genes (DEGs) analysis, and pathway enrichment. In vitro experiments assessed the functional role of CAFs and the impact of the extracellular matrix component COL5A2 on erlotinib resistance.We identified 124 DEGs associated with erlotinib resistance, with key genes like COL5A2 significantly upregulated. CAFs were found to highly express COL5A2, enhancing erlotinib resistance by activating the PI3K/AKT pathway. Higher erlotinib resistance scores correlated with increased infiltration of CAFs.Erlotinib resistance in HNSCC is significantly influenced by the tumor microenvironment (TME), particularly through CAFs and the PI3K/AKT pathway. Targeting these mechanisms may offer new therapeutic strategies to overcome resistance in HNSCC patients. [ABSTRACT FROM AUTHOR]

For the sensorless control in a low-speed range of synchronous reluctance motors (SynRMs), injecting random high-frequency (HF) square-wave-type voltages has become a widely used and technologically mature method. It can solve the noise problem of traditional injection signal methods. However, all injection signal methods will cause problems such as torque ripple, which causes speed fluctuations. This article proposes a self-regulating random model algorithm for the random injection signal method, which includes a quantity adaptive module for adding additional random processes, an evaluation module for evaluating torque deviation degree, and an updated model module that is used to receive signals from the other two modules and complete model changes and output random model elements. The main function of this algorithm is to create a model that updates to suppress the evaluation value deviation based on the evaluation situation and outputs an optimal sequence of random numbers, thereby limiting speed bias always in a small range; this can reduce unnecessary changes in the output value of the speed regulator. The feasibility and effectiveness of the proposed algorithm and control method have been demonstrated in experiments based on a 5-kW synchronous reluctance motor. [ABSTRACT FROM AUTHOR]