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The interaction of helminth infections with type 2 diabetes (T2D) has been a major area of research in the past few years. This paper, therefore, focuses on the systematic review of the effects of helminthic infections on metabolism and immune regulation related to T2D, with mechanisms through which both direct and indirect effects are mediated. Specifically, the possible therapeutic role of helminths in T2D management, probably mediated through the modulation of host metabolic pathways and immune responses, is of special interest. This paper discusses the current possibilities for translating helminth therapy from basic laboratory research to clinical application, as well as existing and future challenges. Although preliminary studies suggest the potential for helminth therapy for T2D patients, their safety and efficacy still need to be confirmed by larger-scale clinical studies.
This study explored mental workload recognition methods for carrier-based aircraft pilots utilising multiple sensor physiological signal fusion and portable devices. A simulation carrier-based aircraft flight experiment was designed, and subjective mental workload scores and electroencephalogram (EEG) and photoplethysmogram (PPG) signals from six pilot cadets were collected using NASA Task Load Index (NASA-TLX) and portable devices. The subjective scores of the pilots in three flight phases were used to label the data into three mental workload levels. Features from the physiological signals were extracted, and the interrelations between mental workload and physiological indicators were evaluated. Machine learning and deep learning algorithms were used to classify the pilots’ mental workload. The performances of the single-modal method and multimodal fusion methods were investigated. The results showed that the multimodal fusion methods outperformed the single-modal methods, achieving higher accuracy, precision, recall and F1 score. Among all the classifiers, the random forest classifier with feature-level fusion obtained the best results, with an accuracy of 97.69%, precision of 98.08%, recall of 96.98% and F1 score of 97.44%. The findings of this study demonstrate the effectiveness and feasibility of the proposed method, offering insights into mental workload management and the enhancement of flight safety for carrier-based aircraft pilots.
The transport process of a relativistic electron beam (REB) in high-density and degenerate plasmas holds significant importance for fast ignition. In this study, we have formulated a comprehensive theoretical model to address this issue, incorporating quantum degeneracy, charged particle collisions and the effects of electromagnetic (EB) fields. We model the fuel as a uniform density region and particularly focus on the effect of quantum degeneracy during the transport of the REB, which leads to the rapid growth of a self-generated EB field and a subsequently significant self-organized pinching of the REB. Through our newly developed hybrid particle-in-cell simulations, we have observed a two-fold enhancement of the heating efficiency of the REB compared with previous intuitive expectation. This finding provides a promising theoretical framework for exploring the degeneracy effect and the enhanced self-generated EB field in the dense plasma for fast ignition, and is also linked to a wide array of ultra-intense laser-based applications.
Interlaminar delamination damage is a common and typical defect in the context of structural damage in carbon fiber-reinforced resin matrix composites. The technology to identify such damage is crucial for improving the safety and reliability of structures. In this paper, we fabricated carbon fiber-reinforced composite laminates with different degrees of delamination damage, conducted static load experiments on them and used femtosecond fiber Bragg grating sensors (fsFBG) to determine their structural state to investigate the effects of delamination damage on their performance. We constructed a model to identify damage based on the deep residual shrinkage network, and used experimental data to enable it to identify varying degrees of delamination damage to carbon fiber-reinforced composites with an accuracy of 97.98%.
During the investigation of parasitic pathogens of Mytilus coruscus, infection of a Perkinsus-like protozoan parasite was detected by alternative Ray's Fluid Thioglycolate Medium (ARFTM). The diameter of hypnospores or prezoosporangia was 8–27 (15.6 ± 4.0, n = 111) μm. The prevalence of the Perkinsus-like species in M. coruscus was 25 and 12.5% using ARFTM and PCR, respectively. The ITS1-5.8S-ITS2 fragments amplified by PCR assay had 100% homology to that of P. beihaiensis, suggesting that the protozoan parasite was P. beihaisensis and M. coruscus was its new host in East China Sea (ECS). Histological analysis showed the presence of trophozoites of P. beihaiensis in gill, mantle and visceral mass, and the schizonts only found in visceral mass. Perkinsus beihaiensis infection led to inflammatory reaction of hemocyte and the destruction of digestive tubules in visceral mass, which had negative effect on health of the farmed M. coruscus and it deserves more attention.
Aircraft ground taxiing contributes significantly to carbon emissions and engine wear. The electric towing tractor (ETT) addresses these issues by towing the aircraft to the runway end, thereby minimising ground taxiing. As the complexity of ETT towing operations increases, both the towing distance and time increase significantly, and the original method for estimating the number of ETTs is no longer applicable. Due to the substantial acquisition cost of ETT and the need to reduce waste while ensuring operational efficiency, this paper introduces for the first time an ETT quantity estimation model that combines simulation and vehicle scheduling models. The simulation model simulates the impact of ETT on apron operations, taxiing on taxiways and takeoffs and landings on runways. Key timing points for ETT usage by each aircraft are identified through simulation, forming the basis for determining the minimum number of vehicles required for airport operations using a hard-time window vehicle scheduling model. To ensure the validity of the model, simulation model verification is conducted. Furthermore, the study explores the influence of vehicle speed and airport scale on the required number of ETTs. The results demonstrate the effective representation of real-airport operations by the simulation model. ETT speed, airport runway and taxiway configurations, takeoff and landing frequencies and imbalances during peak periods all impact the required quantity of ETTs. A comprehensive approach considering these factors is necessary to determine the optimal number of ETTs.
Soluble Intercellular Adhesion Molecule-1 (sICAM-1) has emerged as an inflammatory biomarker of many essential functions. We investigated the level of sICAM-1 influenced by Clonorchis sinensis (C. sinensis) co-infection in chronic hepatitis B (CHB) patients to explore the degree of liver tissue inflammation and liver function damage after co-infection. The study included data from patients with C. sinensis mono-infection (n=27), hepatitis B virus (HBV) mono-infection (n=32), C. sinensis and HBV co-infection (n=24), post-hepatitis B liver cirrhosis (n=18), post-hepatitis B liver cirrhosis co-infected with C. sinensis (n=16), and healthy controls (n=39). The level of sICAM-1 was measured with specific enzyme-linked immunosorbent assay method. Compared to the healthy control group, all the experimental groups had significantly higher serum sICAM-1 levels. The levels of sICAM-1 in co-infected groups were significantly higher compared to the mono-infection groups and were positively correlated with the levels of glutamate aminotransferase (ALT) and aspartate aminotransferase (AST). Our research findings confirmed that co-infection could exacerbate liver tissue inflammation and liver function damage in patients, could raise the sICAM-1 level, and may lead to the chronicity of HBV infection. These results provide clues for pathological mechanism study and formulating treatment plans.
Adolescence is a period marked by highest vulnerability to the onset of depression, with profound implications for adult health. Neuroimaging studies have revealed considerable atrophy in brain structure in these patients with depression. Of particular importance are regions responsible for cognitive control, reward, and self-referential processing. However, the causal structural networks underpinning brain region atrophies in adolescents with depression remain unclear.
Objectives
This study aimed to investigate the temporal course and causal relationships of gray matter atrophy within the brains of adolescents with depression.
Methods
We analyzed T1-weighted structural images using voxel-based morphometry in first-episode adolescent patients with depression (n=80, 22 males; age = 15.57±1.78) and age, gender matched healthy controls (n=82, 25 males; age = 16.11±2.76) to identify the disease stage-specific gray matter abnormalities. Then, with granger causality analysis, we arranged the patients’ illness duration chronologically to construct the causal structural covariance networks that investigated the causal relationships of those atypical structures.
Results
Compared to controls, smaller volumes in ventral medial prefrontal cortex (vmPFC), dorsal anterior cingulate cortex (dACC), middle cingulate cortex (MCC) and insula areas were identified in patients with less than 1 year illness duration, and further progressed to the subgenual ACC, regions of default, frontoparietal networks in longer duration. Causal network results revealed that dACC, vmPFC, MCC and insula were prominent nodes projecting exerted positive causal effects to regions of the default mode and frontoparietal networks. The dACC, vmPFC and insula also had positive projections to the reward network, which included mainly the thalamus, caudate and putamen, while MCC also exerted a positive causal effect on the insula and thalamus.
Conclusions
These findings revealed the progression of structural atrophy in adolescent patients with depression and demonstrated the causal relationships between regions involving cognitive control, reward and self-referential processes.
Minerals and trace elements are essential for human health and wellness. Fruits can be an important dietary source of these micronutrients. For centuries, native Australian fruits have been a vital source of nutrition and well-being for the Indigenous Communities(1). However, comprehensive information on the mineral and trace element composition of these native fruits, including broad-leaved Geebung (Persoonia stradbrokensis), is lacking. Therefore, the aim of the present study was to determine the mineral and trace element composition of broad-leaved Geebung, an important but still underutilised native Australian fruit, at different maturity stages. Inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma-optical emission spectroscopy (ICP-OES) were used to analyse the fruit. Statistical analysis was performed using one-way ANOVA and the means (n = 3) were compared by Tukey’s multiple comparison post hoc test with p < 0.05 as significant. Calcium and potassium could be identified as the main minerals, and iron, zinc and manganese as the main trace elements. The calcium content in broad-leaved Geebung was lower than Australian desert lime, kakadu plum, and riberry, respectively (35.7-271.5 vs. 384.2 vs. 282.5 vs. 307.7 mg/100g dry weight (DW))(2). Potassium has a vital role in the prevention of bone loss and is essential for the heart, kidney, and blood pressure. The potassium content of broad-leaved Geebung fruit was lower than Australian desert lime, kakadu plum, lemon aspen, quandong and riberry (average 516.4 vs. 1287.8 vs. 1905.5 vs. 1512.9 vs. 3456.2 vs. 1715.7 mg/100g DW)(2), which contributes to approximately 15% recommended dietary allowance (RDA). Iron is the main element in the production of hemoglobin and is important for maintaining healthy blood. Iron content in the fruit ranged from 0.8-2.6 mg/100g DW, which was higher than that of Davidson’s plum (1.2 mg/100g DW), but lower than the Green Plum, Australian desert lime, and kakadu plum (3.8 vs. 4.7 vs. 4.0 mg/100g DW) (2,3). Besides, the manganese levels were relatively high in broad-leaved Geebung fruit and considerably higher than in other native Australian fruits such as Kakadu plums, Desert limes and Quandongs (11.2-26.4 vs. 3.5 vs. 0.9 vs. 0.3 mg/100 g DW)(2). Interestingly, the mineral and trace element content decreased (p < 0.05) during fruit maturity. In general, broad-leaved Geebung fruit can provide considerable amounts of essential minerals and trace elements and its potential as a healthy “snack” alternative should be investigated further.
Transient numerical simulations were conducted to investigate the influence of large amplitude and fast impact backpressure on a shock train. The fundamental problem consists of a shock train within a constant-area channel with a Ma=1.61 inflow and a pulse backpressure applied to the outlet. The pressure disturbance in the isolator has an intense forcing-response lag. From the moment of the backpressure peak appearance, it takes 36 times the backpressure duration for the pressure disturbance to reach the upstream end. It moves upstream with time in the form of a normal shock wave. As time progresses, the normal shock degenerates into a $\lambda $ shock and a compression wave behind due to the action of viscous dissipation in the boundary layer. Eventually, a multi-stage shock train is formed. The maximum backpropagation distance is a quadratic function of both the pulse backpressure peak and duration, and the relationship between these variables was determined by fitting. When the integral value of backpressure to time is fixed, reducing the backpressure peak while increasing the duration will reduce the backpressure pulsation at the isolator outlet, which will be more conducive to shortening the maximum backpropagation distance than reducing the duration and increasing the backpressure peak. The values of backpressure peak and duration are obtained from the detonation combustion case, which ensures the authenticity of backpressure characteristics. The relevant research conclusions can provide a reference for the design of the isolator of pulse detonation ramjet.
The chemistry of Al transformation has been well documented, though little is known about the mechanisms of structural perturbation of Al precipitates by carbonates at a molecular level. The purpose of the present study was to investigate the structural perturbation of Al precipitates formed under the influence of carbonates. Initial carbonate/Al molar ratios (MRs) used were 0, 0.1, and 0.5 after aging for 32 days, then the samples were analyzed by X-ray absorption near edge structure spectroscopy (XANES), X-ray diffraction (XRD), Fourier-transform infrared absorption spectroscopy (FTIR), and chemical analysis. The XRD data were in accord with the FTIR results, which revealed that as the carbonate/Al MR was increased from 0 to 0.1, carbonate preferentially retarded the formation of gibbsite and had relatively little effect on the formation of bayerite. As the carbonate/Al MR was increased to 0.5, however, the crystallization of both gibbsite and bayerite was completely inhibited. The impact of carbonate on the nature of Al precipitates was also evident in the increase of adsorbed water and inorganic C contents with increasing carbonate/Al MR. The Al K- and L- edge XANES data provide the first evidence illustrating the change in the coordination number of Al from 6-fold to mixed 6- and 4-fold coordination in the structural network of short-range ordered (SRO) Al precipitates formed under the increasing perturbation of carbonate. The fluorescence yield spectra of the O K-edge show that the intensity of the peak at 534.5 eV assigned to σ* transitions of Al-O and O-H bonding decreased with increasing carbonate/Al MR. The XANES data, along with the evidence from XRD, FTIR, and chemical analysis showed clearly that carbonate caused the alteration of the coordination nature of the Al-O bonding through perturbation of the atomic bonding and structural configuration of Al hydroxides by complexation with Al in the SRO network of Al precipitates. The surface reactivity of an Al-O bond is related to its covalency and coordination geometry. The present findings were, therefore, of fundamental significance in understanding the low-temperature geochemistry of Al and its impacts on the transformation, transport, and fate of nutrients and pollutants in the ecosystem.
The formation of siderite and magnetite by Fe(III)-reducing bacteria may play an important role in C and Fe geochemistry in subsurface and ocean sediments. The objective of this study was to identify environmental factors that control the formation of siderite (FeCO3) and magnetite (Fe3O4) by Fe(III)-reducing bacteria. Psychrotolerant (<20°C), mesophilic (20–35°C) and thermophilic (>45°C) Fe(III)-reducing bacteria were used to examine the reduction of a poorly crystalline iron oxide, akaganeite (β-FeOOH), without a soluble electron shuttle, anthraquinone disulfuonate (AQDS), in the presence of N2, N2-CO2(80:20, V:V), H2 and H2-CO2 (80:20, V:V) headspace gases as well as in -buffered medium (30–210 mM) under a N2 atmosphere. Iron biomineralization was also examined under different growth conditions such as salinity, pH, incubation time, incubation temperature and electron donors. Magnetite formation was dominant under a N2 and a H2 atmosphere. Siderite formation was dominant under a H2-CO2 atmosphere. A mixture of magnetite and siderite was formed in the presence of a N2-CO2 headspace. Akaganeite was reduced and transformed to siderite and magnetite in a -buffered medium (>120 mM) with lactate as an electron donor in the presence of a N2 atmosphere. Biogeochemical and environmental factors controlling the phases of the secondary mineral suite include medium pH, salinity, electron donors, atmospheric composition and incubation time. These results indicate that microbial Fe(III) reduction may play an important role in Fe and C biogeochemistry as well as C sequestration in natural environments.
Transient electromagnetic field plays very important roles in the evolution of high-energy-density matter or laser plasma. Now, a new design is proposed in this paper to diagnose the transient magnetic field, using relativistic electron bunch as a probe based on high-energy electron radiography. And based on this scheme, the continuous distribution of magnetic strength field can be snapshotted. For 1 mm thick quadrupole magnet model measured by 50 MeV probe electron beams, the simulation result indicates that this diagnosis has spatial resolution better than 4 microns and high measurement accuracy for strong magnetic strength and high magnetic gradient field no matter whether the magnetic interaction is focusing or defocusing for the range from -510 T∗μm to 510 T∗μm.
The target backsheath field acceleration mechanism is one of the main mechanisms of laser-driven proton acceleration (LDPA) and strongly depends on the comprehensive performance of the ultrashort ultra-intense lasers used as the driving sources. The successful use of the SG-II Peta-watt (SG-II PW) laser facility for LDPA and its applications in radiographic diagnoses have been manifested by the good performance of the SG-II PW facility. Recently, the SG-II PW laser facility has undergone extensive maintenance and a comprehensive technical upgrade in terms of the seed source, laser contrast and terminal focus. LDPA experiments were performed using the maintained SG-II PW laser beam, and the highest cutoff energy of the proton beam was obviously increased. Accordingly, a double-film target structure was used, and the maximum cutoff energy of the proton beam was up to 70 MeV. These results demonstrate that the comprehensive performance of the SG-II PW laser facility was improved significantly.
As a typical plasma-based optical element that can sustain ultra-high light intensity, plasma density gratings driven by intense laser pulses have been extensively studied for wide applications. Here, we show that the plasma density grating driven by two intersecting driver laser pulses is not only nonuniform in space but also varies over time. Consequently, the probe laser pulse that passes through such a dynamic plasma density grating will be depolarized, that is, its polarization becomes spatially and temporally variable. More importantly, the laser depolarization may spontaneously take place for crossed laser beams if their polarization angles are arranged properly. The laser depolarization by a dynamic plasma density grating may find application in mitigating parametric instabilities in laser-driven inertial confinement fusion.
This study aimed to establish a model for predicting the three-year survival status of patients with hypopharyngeal squamous cell carcinoma using artificial intelligence algorithms.
Method
Data from 295 patients with hypopharyngeal squamous cell carcinoma were analysed retrospectively. Training sets comprised 70 per cent of the data and test sets the remaining 30 per cent. A total of 22 clinical parameters were included as training features. In total, 12 different types of machine learning algorithms were used for model construction. Accuracy, sensitivity, specificity, area under the receiver operating characteristic curve and Cohen's kappa co-efficient were used to evaluate model performance.
Results
The XGBoost algorithm achieved the best model performance. Accuracy, sensitivity, specificity, area under the receiver operating characteristic curve and kappa value of the model were 80.9 per cent, 92.6 per cent, 62.9 per cent, 77.7 per cent and 58.1 per cent, respectively.
Conclusion
This study successfully identified a machine learning model for predicting three-year survival status for patients with hypopharyngeal squamous cell carcinoma that can offer a new prognostic evaluation method for the clinical treatment of these patients.
This paper studied the use of eye movement data to form criteria for judging whether pilots perceive emergency information such as cockpit warnings. In the experiment, 12 subjects randomly encountered different warning information while flying a simulated helicopter, and their eye movement data were collected synchronously. Firstly, the importance of the eye movement features was calculated by ANOVA (analysis of variance). According to the sorting of the importance and the Euclidean distance of each eye movement feature, the warning information samples with different eye movement features were obtained. Secondly, the residual shrinkage network modules were added to CNN (convolutional neural network) to construct a DRSN (deep residual shrinkage networks) model. Finally, the processed warning information samples were used to train and test the DRSN model. In order to verify the superiority of this method, the DRSN model was compared with three machine learning models, namely SVM (support vector machine), RF (radom forest) and BPNN (backpropagation neural network). Among the four models, the DRSN model performed the best. When all eye movement features were selected, this model detected pilot perception of warning information with an average accuracy of 90.4%, of which the highest detection accuracy reached 96.4%. Experiments showed that the DRSN model had advantages in detecting pilot perception of warning information.
Water fountains (WFs) are thought to represent an early stage in the morphological evolution of circumstellar envelopes surrounding low- and intermediate-mass evolved stars. These objects are considered to transition from spherical to asymmetric shapes. Despite their potential importance in this transformation process of evolved stars, there are only a few known examples. To identify new WF candidates, we used databases of circumstellar OH (1612 MHz) and H2O (22.235 GHz) maser sources, and compared the velocity ranges of the two maser lines. Finally, 41 sources were found to have a velocity range for the H2O maser line that exceeded that of the OH maser line. Excluding known planetary nebulae and after reviewing the maser spectra in the original literature, we found for 11 sources the exceedance as significant, qualifying them as new WF candidates.
Planting patterns have significant effects on rice growth. Nonetheless, little is known about differences in annual crop yield and resource utilization among mechanized rice planting patterns in a rice–wheat cropping system. Field experiments were conducted from 2014 to 2017 using three treatments: pot seedling transplanting for rice and row sowing for wheat (PST-RS), carpet seedling transplanting for rice and row sowing for wheat (CST-RS) and row sowing for both crops (RS-RS). The results showed that, compared with RS-RS, PST-RS and CST-RS prolonged annual crop growth duration by 25–26 and 13–15 days, increased effective accumulated temperature by 399 and 212°C days and increased cumulative solar radiation by 454 and 228 MJ/m2 because of the earlier sowing of rice by 28 and 16 days in PST-RS and CST-RS, respectively. Compared with RS-RS, the annual crop yield of PST-RS and CST-RS increased by 3.1–3.8 and 2.0–2.6 t/ha, respectively, because of the increase in the number of spikelets/kernels per hectare, aboveground biomass, mean leaf area index and grain–leaf ratio. In addition, temperature production efficiency, solar radiation production efficiency and solar radiation use efficiency were higher in PST-RS, followed by CST-RS and RS-RS. These results suggest that mechanized rice planting patterns such as PST-RS increase annual crop production in rice–wheat cropping systems by increasing yield and solar energy utilization.