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Based on the tunable diode laser absorption spectroscopy (TDLAS) technology, one-dimensional and multi-dimensional combustion parameter monitoring systems were designed to simultaneously monitor multiple combustion field parameters in the furnace (such as temperature, CO, CO2, and NO concentration, etc.). In the one-dimensional system, the optical switch technology was applied to measure the multiple combustion parameters simultaneously. In the two-dimensional system, the spectrometer technology and algebraic reconstruction technique (ART) were introduced to inversion calculate and measure the two-dimensional combustion parameters in a layer. On this basis, the three-dimensional system was designed. The measurement procedures of three-dimensional combustion parameters were as follows: the combustion region in the furnace was divided into multilayer sections; the two-dimensional combustion parameters were reconstructed based on ART; the three-dimensional combustion parameters were reconstructed using the multilayer combustion parameter data. The combustion filed parameter monitoring system contributes to the fine combustion adjustment in the future.

Despite the recent advancements in dialogue systems, persona-driven chatbots are still in their infancy. Previous studies on persona-driven dialogue generation demonstrated its ability in generating responses that contain more detailed persona information. However, the challenge of maintaining persona consistency and contextual coherence still persists in persona-driven dialogue generation. Moreover, current methods have limitations in processing multi-source inputs and identifying interlocutor intents due to the absence of trustworthy labels and effective modeling. Additionally, numerous approaches rely on pre-trained large-scale language models that require costly computational resources. To address these challenges, a lightweight hierarchical intent-inferring pointer network is proposed for multi-source persona-driven dialogue generation. The proposed method involves detecting interlocutor intents in chitchat and utilizing pseudo labeling and natural language inference techniques to generate intent labels. Our model is evaluated on a benchmark dataset PersonaChat. The experimental results show that our model outperforms the strongest baseline by 13.47% and 4.28% in terms of persona consistency and contextual coherence, respectively. [ABSTRACT FROM AUTHOR]

An enhanced quick, easy, cheap, effective, rugged, and safe (QuEChERS) purification method utilizing multi‐walled carbon nanotubes (MWCNTs) has been developed and coupled with liquid chromatography‐tandem mass spectrometry for the determination of eight quinolone drug residues in quail eggs. The sample was extracted using ethylenediamine tetraacetic acid‐McIlvaine buffer (pH = 4.0) and 2% formic acid in acetonitrile, followed by salting out with MgSO4, and purification with primary secondary amine (PSA), MWCNT, and Octadecylsilane (C18). The method demonstrated linear relationships for the target compounds within the range of 2–100 µg/L with correlation coefficients (r) exceeding 0.99. The limits of detection and quantification were determined to be 0.4 and 0.8 µg/kg, respectively. Validation through a three‐level spiking test (low, medium, and high) in quail eggs resulted in an average recovery rate ranging from 86.8% to 113.7%, with relative standard deviations between 2.6% and 10.2% (n = 6). This method offers rapid operation, excellent purification efficiency, and high sensitivity, making it suitable for the qualitative and quantitative analysis of quinolone drug residues in eggs. Application of this method to a batch of 20 quail eggs revealed the presence of enrofloxacin and ciprofloxacin, suggesting a potential risk of non‐compliant quinolones use in quail egg production. [ABSTRACT FROM AUTHOR]

Background Late-onset seborrhoeic dermatitis seriously affects patients' quality of life. Studies have shown an association between air pollution and other inflammatory skin diseases. However, associations between air pollution exposures and the incidence of late-onset seborrhoeic dermatitis have not been elucidated. Objectives To investigate air pollution's role in the incidence of late-onset seborrhoeic dermatitis. Methods We engaged a prospective cohort analysis utilizing the UK Biobank database. Exposure data spanning various years for specific air pollutants, namely particulate matter [PM; with an aerodynamic diameter of ≤ 2.5 µm (PM2.5), between 2.5 and 10 μm (PM2.5–10), ≤ 10 μm (PM10)] along with nitrogen oxides (NO plus NO2, denoted NOx) and NO2, were incorporated. Through a composite air pollution score constructed from five pollutants and employing Cox proportional hazards models, the relationship between air pollution and seborrhoeic dermatitis was delineated. Results Our examination of 193 995 participants identified 3363 cases of seborrhoeic dermatitis. Higher concentrations of specific pollutants, particularly in the upper quartile (Q4), were significantly linked to an elevated risk of seborrhoeic dermatitis. Notably, PM2.5, PM10, NO2 and NOx exhibited hazard ratios of 1.11, 1.15, 1.22 and 1.15, respectively. The correlation was further solidified with a positive association between air pollution score increments and onset of seborrhoeic dermatitis. Intriguingly, this association was accentuated in certain demographics, including younger men, socioeconomically deprived people, smokers, daily alcohol consumers, and those engaging in regular physical activity. Conclusions Our findings revealed that air pollution exposures were associated with incidence of late-onset seborrhoeic dermatitis. These results emphasize the importance of preventing environmental air pollution exposures to mitigate the risk of developing the condition. [ABSTRACT FROM AUTHOR]

Low‐grade cervical intraepithelial neoplasia (CIN1) is an early stage of cervical cancer development. Previously, we reported that exposure to polycyclic aromatic hydrocarbons (PAHs) increases the risk of cervical precancerous lesions, especially in females with a high‐risk human papillomavirus (HR‐HPV) infection. However, the effects of PAHs on CIN1 progression remain unclear. A community‐based prospective cohort study was conducted to evaluate the role of exposure to PAHs in the progression of CIN1. A total of 564 patients diagnosed with CIN1 were followed‐up at 6, 12, and 24 months, post‐diagnosis, to determine CIN1 reversion, persistence, and progression. Exposure to PAHs was determined by the urine 1‐hydroxipayrene (1‐OHP) level. Our results showed that the 1‐OHP level was significantly higher in patients with CIN1 persistence/progression than in those with reversion (P <.05). High exposure to PAHs increased the risk of CIN1 persistence/progression, with hazard ratios (HR), 95% confidence intervals (CI) of (1.62, 1.24–2.67), (1.98, 1.42–2.75), and (2.37, 1.61–3.49) at 6, 12, and 24 months, post‐diagnosis, respectively. The effect was enhanced with HR‐HPV positivity, as determined at 6 (1.82, 1.24–2.67), 12 (3.02, 1.74–5.23), and 24 (2.51, 1.48–4.26) months, post‐diagnosis. Moreover, the predictive value of exposure to PAHs for CIN1 persistence/progression was higher in HR‐HPV‐positive patients than in HR‐HPV‐negative patients. The results revealed that exposure to PAHs facilitated the malignant progression of CIN1 and hindered its reversal, particularly in patients with HR‐HPV infection. Our findings provide novel insights into early prevention and intervention targeting the initiation and progression of cervical neoplasia. [ABSTRACT FROM AUTHOR]

Insufficient flexibility is a major barrier to the development of new power systems. Leveraging the resource allocation function of the electricity market is a promising way to enhance the flexibility of power systems and promote the consumption of renewables. The reasonable allocation of ancillary service costs plays a pivotal role in this function. Towards the target of "who causes, who shares," various research related to cost allocation has been conducted. However, there is a lack of quantitative analysis of the impact of different cost allocation mechanisms on the market participants' revenues. Whether various cost allocation mechanisms can alleviate the insufficient flexibility problem of power systems needs to be validated. With this in mind, taking operating reserve ancillary services as an example, a long-term market operation simulation model with energy-reserve joint clearing is established in this paper based on the time series production simulation. According to this, the revenues of market participants under different reserve cost allocation mechanisms are quantified. Besides, a self-dispatch model for the energy storage (ES) equipped by renewables is established, based on which the impact of ES on the revenues of renewables under different cost allocation mechanisms is analyzed. Case studies based on practical data from a provincial power grid in China demonstrate that with the well-designed reserve cost allocation mechanism, the revenues of flexible resources can be ensured. Meanwhile, renewables are incentivized to reduce their fluctuations and uncertainties by equipping the ES. Hence, the insufficient flexibility problem of power systems can be alleviated from both supply and requirements perspectives. [ABSTRACT FROM AUTHOR]

With the rapid development of modern power systems, the structure and operation of distribution networks are becoming increasingly complex, demanding higher levels of intelligence and digitization. Digital twin, as a virtual cutting-edge technique, can effectively reflect the operational status of distribution networks, offering new possibilities for real-time monitoring, optimization and other functions for distribution networks. Building efficient and accurate models is the foundation of enabling a digital twin of distribution networks. This paper proposes a digital twin operating system for distribution networks with renewable energy based on robust state estimation and deep learning-based renewable energy prediction. Furthermore, the identification and correction of possible bad or missing data based on deep learning are also included to purify the input data for the digital twin system. A digital twin test platform is also proposed in the paper. A case study and evaluations based on a real-time digital simulator are carried out to verify the accuracy and real-time performance of the established digital twin system. In general, the proposed method can provide the basis and foundation for distribution network management and operation, as well as intelligent power system operation. [ABSTRACT FROM AUTHOR]

Aims Advanced age is associated with an increased risk of adverse cardiovascular events. The relationship between biological age acceleration (BAA), cardiac size, cardiac function, and heart failure (HF) is not well-defined. Methods and results Utilizing the UK Biobank cohort, we assessed biological age using the Klemera–Doubal and PhenoAge methods. BAA was quantified by residual analysis compared with chronological age. Cardiovascular magnetic resonance (CMR) imaging provided detailed insights into cardiac structure and function. We employed multivariate regression to examine links between BAA and CMR-derived cardiac phenotypes. Cox proportional hazard regression models analysis was applied to explore the causative relationship between BAA and HF. Additionally, Mendelian randomization was used to investigate the genetic underpinnings of these associations. A significant correlation was found between increased BAA and deleterious changes in cardiac structure, such as diminished left ventricular mass, lower overall ventricular volume, and reduced stroke volumes across ventricles and atria. Throughout a median follow-up of 13.8 years, participants with greater biological aging showed a heightened risk of HF [26% per standard deviation (SD) increase in KDM-BA acceleration, 95% confidence intervals (CI): 23–28%; 33% per SD increase in PhenoAge acceleration, 95% CI: 32–35%]. Mendelian randomization analysis suggests a likely causal link between BAA, vital cardiac metrics, and HF risk. Conclusion In this cohort, accelerated biological aging may serve as a risk indicator for altered cardiac dimensions, functionality, and the onset of heart failure among middle-aged and elderly adults. It holds promise as a focal point for evaluating risk and developing targeted interventions. [ABSTRACT FROM AUTHOR]

Hydatidosis is an endemic disease causing a severe threat to public health. Drugs and surgery have been utilized for treatment, but their efficiency is not adequate. Therefore, new methods are required for treating such diseases. In this study, we attempt to evaluate the efficiency of radiotherapy for hydatidosis in sheep. The sheep naturally infected with pulmonary hydatid were randomly divided into four groups, including the control group subjected to no irradiation and the other three groups subjected to 30, 45, and 60 Gy irradiation, respectively. Gene expression of caspase-3 and gadd45a and protein expression of BCL-2 and BAX in the lung tissues were evaluated after treatment. Our data showed that the irradiation with a dose of 30, 45, and 60 Gy significantly induced the expression of caspase-3 and gadd45a. Immunohistochemical staining showed that the BCL-2 protein was downregulated after exposure to 45 Gy of irradiation, whereas the BAX expression was downregulated after irradiation at a dose of 45 and 60 Gy, respectively. On this basis, we speculated that 45 Gy might be a safe and effective dose for treating pulmonary hydatidosis in sheep, which induced lower expression of caspase-3 and gadd45a in the cyst and a downregulation of BCL-2 and BAX in the adjacent lung tissues.