Our study aimed to develop and validate a nomogram to assess talaromycosis risk in hospitalized HIV-positive patients. Prediction models were built using data from a multicentre retrospective cohort study in China. On the basis of the inclusion and exclusion criteria, we collected data from 1564 hospitalized HIV-positive patients in four hospitals from 2010 to 2019. Inpatients were randomly assigned to the training or validation group at a 7:3 ratio. To identify the potential risk factors for talaromycosis in HIV-infected patients, univariate and multivariate logistic regression analyses were conducted. Through multivariate logistic regression, we determined ten variables that were independent risk factors for talaromycosis in HIV-infected individuals. A nomogram was developed following the findings of the multivariate logistic regression analysis. For user convenience, a web-based nomogram calculator was also created. The nomogram demonstrated excellent discrimination in both the training and validation groups [area under the ROC curve (AUC) = 0.883 vs. 0.889] and good calibration. The results of the clinical impact curve (CIC) analysis and decision curve analysis (DCA) confirmed the clinical utility of the model. Clinicians will benefit from this simple, practical, and quantitative strategy to predict talaromycosis risk in HIV-infected patients and can implement appropriate interventions accordingly.

We demonstrated a method to improve the output performance of a Ti:sapphire laser in the long-wavelength low-gain region with an efficient stimulated Raman scattering process. By shifting the wavelength of the high-gain-band Ti:sapphire laser to the long-wavelength low-gain region, high-performance Stokes operation was achieved in the original long-wavelength low-gain region of the Ti:sapphire laser. With the fundamental wavelength tuning from 870 to 930 nm, first-order Stokes output exceeding 2.5 W was obtained at 930–1000 nm, which was significantly higher than that directly generated by the Ti:sapphire laser, accompanied by better beam quality, shorter pulse duration and narrower linewidth. Under the pump power of 42.1 W, a maximum first-order Stokes power of 3.24 W was obtained at 960 nm, with a conversion efficiency of 7.7%. Furthermore, self-mode-locked modulations of first- and second-order Stokes generation were observed in Ti:sapphire intracavity solid Raman lasers for the first time.

Natural sepiolite has great potential for application in wound healing, haemostasis and medicines. This paper introduces a versatile solid-state sintering technique for preparing sepiolite-based nanocomposites with enhanced antibacterial properties, and the physical, structural, rheological and antibacterial properties of which were determined to be enhanced. The incorporation of nanosized Ag and metal oxides into sepiolite composites results in a notable improvement in their antibacterial efficacy against Escherichia coli and Staphylococcus aureus in comparison to the unmodified sepiolite. With a low silver content of just 5%, the sepiolite–Ag composite achieves an antibacterial rate of ~100%. Furthermore, the rheological properties exhibited by the sepiolite composites are noteworthy, suggesting their suitability for use in wound-dressing applications due to their exceptional workability. The methodology employed in this research has the potential to offer a viable substitute for the production of economical and effective natural antibacterial nanocomposites.

Trauma is a significant health issue that not only leads to immediate death in many cases but also causes severe complications, such as sepsis, thrombosis, haemorrhage, acute respiratory distress syndrome and traumatic brain injury, among trauma patients. Target protein identification technology is a vital technique in the field of biomedical research, enabling the study of biomolecular interactions, drug discovery and disease treatment. It plays a crucial role in identifying key protein targets associated with specific diseases or biological processes, facilitating further research, drug design and the development of treatment strategies. The application of target protein technology in biomarker detection enables the timely identification of newly emerging infections and complications in trauma patients, facilitating expeditious medical interventions and leading to reduced post-trauma mortality rates and improved patient prognoses. This review provides an overview of the current applications of target protein identification technology in trauma-related complications and provides a brief overview of the current target protein identification technology, with the aim of reducing post-trauma mortality, improving diagnostic efficiency and prognostic outcomes for patients.

Humic acid (HA) can cause environmental pollution, due to which, its removal from aqueous solutions has become an increasingly important issue. Although bentonite has an affinity for HA, the adsorption capacity of raw bentonite is still poor. As a commonly used organic modifier, 3-aminopropyltriethoxyorganosilane (APTES) exhibits excellent flocculation capability for HA. Therefore, the objective of the present study was to investigate the effectiveness of the addition of 3-aminopropyltriethoxyorganosilane (APTES) to raw bentonite to increase the adsorption of HA from aqueous solution. The experimental results showed that, when the solid-to-liquid ratio was 1:1, the amino-modified bentonite exhibited the highest adsorption capacity (qmax = 272.23 mg g-1). The adsorption affinity of amino-modified bentonite was mainly determined by the number of amino groups loaded onto its surface. The adsorption of HA on amino-modified bentonite occurred through electrostatic interactions and hydrogen bonding. These findings demonstrate the excellent potential of amino-modified bentonite in effectively remediating HA pollution.

The aeroacoustic characteristics of flying vehicles with pitch-fixed rotors differ from traditional helicopters with pitch-controlled rotor blades. Accurate predictions of rotor noise are still challenging because many uncertainty factors and unsteadinesses exist. This work investigates the aeroacoustic effects of rotational speed deviation, rotation speed fluctuation, blade vibration and blade geometric asymmetry. The analysis is based on the efficient computation of rotor noise under different working conditions. The mean aerodynamic variables are computed using the blade element moment theory, while small-amplitude fluctuations are introduced to account for the unsteadiness and uncertainty factors. It is shown that periodic rotation speed fluctuations and blade vibrations can produce significant extra tones. By contrast, if the fluctuations and vibrations are random, the noise level in a wide frequency range is increased. The intriguing result reminds us of the need to revisit the rotor broadband noise sources commonly attributed to turbulent flows. The influences are observer angle dependent, and the extra noise production is more significant in the upstream and downstream directions. The asymmetric blade geometry can cause extra tonal noise at the harmonics of the blade shaft frequency. The noise features of dual rotors are also investigated. Usually, the noise is sensitive to the initial phase difference and rotation directions due to the interference effect. However, the noise features are vastly altered if there are slight differences in the rotation speeds. Although the influences of some factors on rotor noise were already known, the present study provides a more comprehensive analysis of the problem. The results also highlight the need to consider these practical factors for accurate noise prediction of multi-rotor flying vehicles.

Stochastic models are essential for precise navigation and positioning of the global navigation satellite system (GNSS). A stochastic model can influence the resolution of ambiguity, which is a key step in GNSS positioning. Most of the existing multi-GNSS stochastic models are based on the GPS empirical model, while differences in the precision of observations among different systems are not considered. In this paper, three refined stochastic models, namely the variance components between systems (RSM1), the variances of different types of observations (RSM2) and the variances of observations for each satellite (RSM3) are proposed based on the least-squares variance component estimation (LS-VCE). Zero-baseline and short-baseline GNSS experimental data were used to verify the proposed three refined stochastic models. The results show that, compared with the traditional elevation-dependent model (EDM), though the proposed models do not significantly improve the ambiguity resolution success rate, the positioning precision of the three proposed models has been improved. RSM3, which is more realistic for the data itself, performs the best, and the precision at elevation mask angles 20°, 30°, 40°, 50° can be improved by 4⋅6%, 7⋅6%, 13⋅2%, 73⋅0% for L1-B1-E1 and 1⋅1%, 4⋅8%, 16⋅3%, 64⋅5% for L2-B2-E5a, respectively.

Drilling and sampling are the most direct and effective methods available to study Antarctic subglacial lakes. Based on the Philberth probe, a Recoverable Autonomous Sonde (RECAS) allows for in situ lake water measurement and sampling, through the addition of an upper thermal tip and a cable recoiling mechanism. RECAS-200, a prototype of RECAS, has a drilling depth of 200 m, a surface supply voltage of 800 VAC and a downhole power of ~9.6 kW during drilling. In this study, a heating control system for RECAS-200 was designed. The system avoids the need for high-power step-down converters, by separating heating power from control power, thereby reducing the overall weight of the probe and avoiding the need to increase cable diameter. We also introduce a self-developed, small, solid-state, 800 VAC power regulator and a fuzzy PID temperature control algorithm. Their purpose was to manage the power adjustment of each heating element and to provide closed-loop temperature control of certain heating elements which can easily burn out due to overheating. Test results indicated that the proposed RECAS-200 heating control system met all our design specifications and could be easily assembled into the RECAS-200 probe.

Subglacial lake exploration is of great interest to the science community. RECoverable Autonomous Sonde (RECAS) provides an exploration tool to measure and sample subglacial lake environments while the subglacial lake remains isolated from the glacier surface and atmosphere. This paper presents an electronic control system design of 200 m prototype of RECAS. The proposed electronic control system consists of a surface system, a downhole control system, and a power transfer and communication system. The downhole control system is the core element of RECAS, and is responsible for sonde status monitoring, sonde motion control, subglacial water sampling and in situ analysis. A custom RS485 temperature sensor was developed to cater for the limited size and depth requirements of the system. We adopted a humidity-based measurement to monitor for a housing leak. This condition is because standard leak detection monitoring of water conductivity may be inapplicable to pure ice in Antarctica. A water sampler control board was designed to control the samplers and monitor the on/off state. A high-definition camera system with built-in storage and self-heating ability was designed to perform the video recording in the subglacial lake. The proposed electronic control system is proven effective after a series of tests.

Much progress has been made in understanding the environmental and hormonal systems regulating winter diapause. However, transcriptional regulation of summer diapause is still largely unknown, making it difficult to understand an all-around regulation profile of seasonal adaptation. To bridge this gap, comparison RNA-seq to profile the transcriptome and to examine differential gene expression profiles between non-diapause, summer diapause, and winter diapause groups were performed. A total number of 113 million reads were generated and assembled into 79,117 unigenes, with 37,492 unigenes categorized into 58 functional gene ontology groups, 25 clusters of orthologous group categories, and 256 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. KEGG analysis mapped 2108 differentially expressed genes to 48 and 67 pathways for summer and winter diapauses, respectively. Enrichment statistics showed that 11 identical pathways similarly overlapped in the top 20 enriched functional groups both related to summer and winter diapauses. We also identified 35 key candidate genes for universal and differential functions related to summer and winter diapause preparation. Furthermore, we identified some genes involved in the signaling and metabolic pathways that may be the key drivers to integrate environmental signals into the summer and winter diapause preparation. The current study provided valuable insights into global molecular mechanisms underpinning diapause preparation.

The edge surface warping defect seriously affect the surface quality of strips. In this paper, a technology for diagnosis of warping defects in hot-rolled strip based on data-driven methods is studied. Based on the mechanism analysis of the warping defects, the process parameters affecting the warping defects were sorted out and used as the original input parameters of the defect diagnosis model. Firstly, a diagnostic model that combines the deep belief network and contribution plots of each dimensionality reduction layer is proposed. The deep belief network that integrates each dimensionality reduction layer can predict product defects more accurately and stably than the traditional deep belief network. Meanwhile, on the basis of the pre-judgment model, the method of contribution plot is further introduced to trace the defects, and the comprehensive diagnosis function of model pre-judgment and traceability is realized. Finally, collected the production data from a hot rolling production line for a period of time. Tested the model and predicted a hit rate of 85%. The main influencing factors of edge surface warping defects were determined that the rate of defect decrease with the increase of furnace temperature. When the heating temperature of the second stage of the heating furnace is higher than 1160°C, the incidence of defects is significantly reduced. Defect rate is relatively low within 240min of total furnace time. With the first and third pass phosphorus removal equipment turned on, the incidence of defects was relatively low.

A gravity-driven water film falling down an ice sheet is considered within the framework of a long-wave approximation. The integral-boundary-layer method, modified with the account of the phase transition, is adopted to describe the evolution of both the free surface of a water film and the interface between the ice and water. A set of governing equations consisting of five coupled nonlinear partial differential equations is established. The linear instability analysis of the uniform base flow is performed, and the result is in good agreement with the Orr–Sommerfeld analysis of the linearized Navier–Stokes equations. The phase transition at the interface between the ice and water plays a role in stabilizing the system linearly with long-wavelength perturbations. The nonlinear solutions of the steady travelling waves are constructed numerically. The phase transition tends to suppress the dispersion of the interfacial wave. Comparisons to direct numerical simulation of the Navier–Stokes equations, which are performed with an extended marker and cell method, show a remarkable agreement. The integral-boundary-layer method captures the water film thickness and the topography of the ice sheet satisfactorily. The phase transition is observed to enhance the backflow phenomenon in the capillary region of the solitary-like interfacial wave.