Unmanned aerial vehicle (UAV) formations for bearing-only passive detection are increasingly important in modern military confrontations, and the array of the formation is one of the decisive factors affecting the detection accuracy of the system. How to plan the optimal geometric array in bearing-only detection is a complex nondeterministic polynomial problem, and this paper proposed the distributed stochastic subgradient projection algorithm (DSSPA) with layered constraints to solve this challenge. Firstly, based on the constraints of safe flight altitude and fixed baseline, the UAV formation is layered, and the system model for bearing-only cooperative localisation is constructed and analysed. Then, the calculation formula for geometric dilution of precision (GDOP) in the observation plane is provided, this nonlinear objective function is appropriately simplified to obtain its quadratic form, ensuring that it can be adapted and used efficiently in the system model. Finally, the proposed distributed stochastic subgradient projection algorithm (DSSPA) combines the idea of stochastic gradient descent with the projection method. By performing a projection operation on each feasible solution, it ensures that the updated parameters can satisfy the constraints while efficiently solving the convex optimisation problem of array planning. In addition to theoretical proof, this paper also conducts three simulation experiments of different scales, validating the effectiveness and superiority of the proposed method for bearing-only detection array planning in UAV formations. This research provides essential guidance and technical reference for the deployment of UAV formations and path planning of detection platforms.

Despite depression being a leading cause of global disability, neuroimaging studies have struggled to identify replicable neural correlates of depression or explain limited variance. This challenge may, in part, stem from the intertwined state (current symptoms; variable) and trait (general propensity; stable) experiences of depression.

Here, we sought to disentangle state from trait experiences of depression by leveraging a longitudinal cohort and stratifying individuals into four groups: those in remission (‘trait depression group’), those with large longitudinal severity changes in depression symptomatology (‘state depression group’), and their respective matched control groups (total analytic n = 1030). We hypothesized that spatial network organization would be linked to trait depression due to its temporal stability, whereas functional connectivity between networks would be more sensitive to state-dependent depression symptoms due to its capacity to fluctuate.

We identified 15 large-scale probabilistic functional networks from resting-state fMRI data and performed group comparisons on the amplitude, connectivity, and spatial overlap between these networks, using matched control participants as reference. Our findings revealed higher amplitude in visual networks for the trait depression group at the time of remission, in contrast to controls. This observation may suggest altered visual processing in individuals predisposed to developing depression over time. No significant group differences were observed in any other network measures for the trait-control comparison, nor in any measures for the state-control comparison. These results underscore the overlooked contribution of visual networks to the psychopathology of depression and provide evidence for distinct neural correlates between state and trait experiences of depression.

Exploratory process factor analysis (EPFA) is a data-driven latent variable model for multivariate time series. This article presents analytic standard errors for EPFA. Unlike standard errors for exploratory factor analysis with independent data, the analytic standard errors for EPFA take into account the time dependency in time series data. In addition, factor rotation is treated as the imposition of equality constraints on model parameters. Properties of the analytic standard errors are demonstrated using empirical and simulated data.

Structural equation models are increasingly used as a modeling tool for multivariate time series data in the social and behavioral sciences. Standard error estimators of SEM models, originally developed for independent data, require modifications to accommodate the fact that time series data are inherently dependent. In this article, we extend a sandwich-type standard error estimator of independent data to multivariate time series data. One required element of this estimator is the asymptotic covariance matrix of concurrent and lagged correlations among manifest variables, whose closed-form expression has not been presented in the literature. The performance of the adapted sandwich-type standard error estimator is evaluated using a simulation study and further illustrated using an empirical example.

Single-molecule orientation-localization microscopy (SMOLM) builds upon super-resolved localization microscopy by imaging orientations and rotational dynamics of individual molecules in addition to their positions. This added dimensionality provides unparalleled insights into nanoscale biophysical and biochemical processes, including the organization of actin networks, movement of molecular motors, conformations of DNA strands, growth and remodeling of amyloid aggregates, and composition changes within lipid membranes. In this review, we discuss recent innovations in SMOLM and cover three key aspects: (1) biophysical insights enabled by labeling strategies that endow fluorescent probes to bind totargets with orientation specificity; (2) advanced imaging techniques that leverage the physics of light-matter interactions and estimation theory to encode orientation information with high fidelity into microscope images; and (3) computational methods that ensure accurate and precise data analysis and interpretation, even in the presence of severe shot noise. Additionally, we compare labeling approaches, imaging hardware, and publicly available analysis software to aid the community in choosing the best SMOLM implementation for their specific biophysical application. Finally, we highlight future directions for SMOLM, such as the development of probes with improved photostability and specificity, the design of “smart” adaptive hardware, and the use of advanced computational approaches to handle large, complex datasets. This review underscores the significant current and potential impact of SMOLM in deepening our understanding of molecular dynamics, paving the way for future breakthroughs in the fields of biophysics, biochemistry, and materials science.

Obesity is a complex condition which is significantly impacted by an individual’s biology, environment and behavioural factors. Excess energy dense (ED)(kJ/g) food intake (1), higher eating rate (2), increased eating frequency (3) and eating later in the day (4) have all been linked with obesity, but findings are mixed and require clarification using robust and objective measures of food intake behaviour. The aim of this research was to investigate associations between these eating behaviours and energy intake (EI) within a controlled residential setting in 65 participants (BMI 36.4 ±11.0 (range 17.6-65.2); 9 optimal weight, 15 overweight and 41 with obesity/severe obesity; age 44.3±12.7 years (range 18.6-67.6 years), 44F,21M).

As part of baseline measurements for a larger study (5) participants were assessed for 36hrs (twonights) within the Human Intervention Studies Unit at Ulster University, UK, and had ad lib access to a personalised menu (n 54 foods) representing a range of low/high fat macronutrient mix food groups with varying carbohydrate and protein content (6). Food intake and eating behaviour were measured covertly and validated by CCTV. Study outcomes were 24-hour EI (MJ), ED (kJ/g), % nutrient contribution to total EI, as well as parameters of eating including: size (g, kJ) speed (g/min; kJ/min;), number (n) and duration (mins) of eating occasions (defined as consumption of at least 210kJ separated by ≥5 minutes) and the timing of eating (epochs: 7-11am, 11:01-3pm, 3:01-7pm, 7:01-11pm). On the final morning, blood samples were collected before and 90mins after a standardised breakfast for the analysis of glicentin, a proglucagon-derived peptide. Associations between total EI and measures of eating behaviour were assessed using Spearman’s Rank

Correlation analysis showed weak positive associations between total EI and fasting glicentin (r = 0.296, p = 0.024), ED (r = 0.364, p = 0.004), and moderate associations with number (r = 0.419, p = 0.001) and size of eating occasions (r = 0.415, p = 0.005) as well as total weight of food consumed (r= 0.634, p<0.001). Of note, there was also a positive association between EI/eating occasion and a faster eating rate as expressed by [kJ/min (r = 0.519; p<0.001)] but not g/min (r = 0.276, p = 0.07). There was also a stronger relationship between EI and lean mass (r = 0.450, p<0.001) than bodyweight (r = 0.291, p = 0.023).

These findings suggest that food portion size and increased eating frequency may be a more important drivers of EI than dietary ED, and that the rate of eating higher ED foods may be linked to consuming a higher energy meal. These findings are skewed towards individuals with obesity but if confirmed highlight a need for weight management programmes to strengthen strategies to improve portion control and to limit grazing behaviours. There is also a need for robust randomised controlled trials to determine if eating slower reduces overall EI.

Despite national dietary guidelines, dairy intakes remain low in China, partially because of high prevalence of lactose malabsorption1. The fibre intake adequacy is also low comparing to the recommendation in China2. Milk-N is a new range of fortified and non-fortified low-lactose/highfibre milk products. In this study we analyzed the associations between consumption of Milk-N products and nutritional status using diet modelling3.

We used data from China Health and Nutrition Survey-20114, participants above 20y were included in the analysis (n = 12127, 47% men, 53% women). Nutrient intakes were estimated through 3 days dietary record and household food inventory. Two diet scenarios were modelled: A) Adding a serving (200ml) of generic milk or of Milk-N to participants not meeting the dairy recommendation, and B) Substituting dairy food intakes with Milk-N in equivalent amount for dairy consuming participants. Paired t-test and Pearson’s Chi-squared test were used to compare the amount of intake and prevalence of nutrient intake adequacy between the two types of addition, and before and after the substitution.

Overall, 17.4% of participants consumed dairy foods with an average intake of 160.5g/day, among those 81.2% consumed milk. Only 1.1% of the population met dairy intake recommendations.

In the addition scenario, compared to the addition of generic milk, adding one serving of fortified or non-fortified Milk-N increased fibre intake by 25-35% (from 17.6g/day to 22-23.8 g/day), leading to increased fibre intake adequacy from 16.4% to 27.0-32.8%, i.e. 65-100% increase. Addition of fortified Milk-N improved daily average intakes of calcium, iron, zinc, vitamins A and C by 27-31%, 9%, 8%, 3%, and 16%, respectively. Consequently, the proportion of the population with inadequate intakes decreased (p<0.01) for generic milk vs fortified Milk-N as follows, for calcium (66.3% vs. 23.4-29.6%), iron (5.5% vs. 2.2%), zinc (28.1% vs. 18.9%), vitamin A (61.7% vs. 52.7%) and vitamin C (62.4% vs. 51.5%).

In the substitution scenario, replacing current dairy food intake with fortified or non-fortified Milk-N increased fibre intake by 20-27% (from 18.4 to 22.0-23.4g/day), leading to increased proportion of dairy consumers with adequate fibre intake from 18.7% to 28.2-32.3%, i.e., 51-73% increase. Substitution with fortified Milk-N improved intakes of calcium, iron, zinc, vitamins A and C by 2327%, 7%, 7%, 10%, and 12%, respectively. Consequently, the proportion of dairy consumers with inadequate micronutrient intakes significantly decreased (p<0.01) for calcium (from 72.9% to 50.353.3%), iron (from 7.5% to 4.7%), zinc (from 33.0% to 26.1%), vitamin A (from 56.9% to 47.4%), and vitamin C (from 60.2% to 50.8%).

In addition to the reduced lactose that helps to address lactose malabsorption, consumption of any Milk-N alternative could improve fibre intake, while fortified Milk-N could also contribute to reducing micronutrient inadequacies in Chinese adults.

In the present paper, we consider the following fractional double phase problem with nonlocal reaction:

\begin{align*}\qquad \quad \left\{\begin{array}{lll}(- \Delta)_p^s u + (- \Delta)_q ^s u + V(\varepsilon x) (|u|^{p - 2} u + |u|^{q - 2} u) = \left(\frac{1}{|x|^\mu} * F(u)\right) f(u) & \ \text{in}\ \mathbb{R}^N, \\u \in W^{s,p}(\mathbb{R}^N) \cap W^{s,q}(\mathbb{R}^N) ,\ u \gt 0 & \ \text{in}\ \mathbb{R}^N,\end{array}\right\}\end{align*}

where ɛ is apositive parameter, $0 \lt s \lt 1$, $2 \leqslant p \lt q \lt \min\{2p, N / s\}$, $0 \lt \mu \lt sp$, $(- \Delta)_t^s$ $(t \in \left\{p,q\right\})$ is the fractional t-Laplace operator, the reaction term $f : \mathbb{R} \mapsto \mathbb{R}$ is continuous, and the potential $V \in C (\mathbb{R}^N , \mathbb{R})$ satisfying a local condition. Using a variational approach and topological tools (the non-standard C1-Nehari manifold analysis and the abstract category theory), multiplicity of positive solutions and concentration properties for the above problem are established. Our results extend and complement some previous contributions related to double phase variational integrals.

Three new species of Gyrodactylus were identified from the body surface of the Triplophysa species from the Qinghai-Tibet Plateau, Gyrodactylus triplorienchili n. sp. on Triplophysa orientalis in northern Tibet, G. yellochili n. sp. on T. sellaefer and T. scleroptera and G. triplsellachili n. sp. on T. sellaefer and T. robusta in Lanzhou Reach of the Yellow River. The three newly identified species share the nemachili group species’ characteristic of having inturning hamulus roots. Gyrodactylus triplorienchili n. sp. shared a quadrate sickle heel and a thin marginal hook sickle, two morphological traits that set them apart from G. yellochili n. sp. However, they may be identified by the distinct shapes of the sickle base and marginal hook sickle point. Gyrodactylus triplsellachili n. sp. had much larger opisthaptoral hard part size than the other two species. The three new species show relatively low interspecific differences of 2.9–5.3% p-distance for ITS1-5.85-ITS2 rDNA sequences. Phylogenetic analysis indicated that the three new species formed a well-supported monophyletic group (bp = 99) with the other nemachili group species.

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.

We consider the dynamic wetting and dewetting processes of films and droplets of complex liquids on planar surfaces, focusing on the case of colloidal suspensions, where the particle interactions can be sufficiently attractive to cause agglomeration of the colloids within the film. This leads to an interesting array of dynamic behaviours within the liquid and of the liquid–air interface. Incorporating concepts from thermodynamics and using the thin-film approximation, we construct a model consisting of a pair of coupled partial differential equations that represent the evolution of the liquid film and the effective colloidal height profiles. We determine the relevant phase behaviour of the uniform system, including finding associated binodal and spinodal curves, helping to uncover how the emerging behaviour depends on the particle interactions. Performing a linear stability analysis of our system enables us to identify parameter regimes where agglomerates form, which we independently confirm through numerical simulations and continuation of steady states, to construct bifurcation diagrams. We obtain various dynamics such as uniform colloidal profiles in an unstable situation evolving into agglomerates and thus elucidate the interplay between dewetting and particle aggregation in complex liquids on surfaces.

Syphilis remains a serious public health problem in mainland China that requires attention, modelling to describe and predict its prevalence patterns can help the government to develop more scientific interventions. The seasonal autoregressive integrated moving average (SARIMA) model, long short-term memory network (LSTM) model, hybrid SARIMA-LSTM model, and hybrid SARIMA-nonlinear auto-regressive models with exogenous inputs (SARIMA-NARX) model were used to simulate the time series data of the syphilis incidence from January 2004 to November 2023 respectively. Compared to the SARIMA, LSTM, and SARIMA-LSTM models, the median absolute deviation (MAD) value of the SARIMA-NARX model decreases by 352.69%, 4.98%, and 3.73%, respectively. The mean absolute percentage error (MAPE) value decreases by 73.7%, 23.46%, and 13.06%, respectively. The root mean square error (RMSE) value decreases by 68.02%, 26.68%, and 23.78%, respectively. The mean absolute error (MAE) value decreases by 70.90%, 23.00%, and 21.80%, respectively. The hybrid SARIMA-NARX and SARIMA-LSTM methods predict syphilis cases more accurately than the basic SARIMA and LSTM methods, so that can be used for governments to develop long-term syphilis prevention and control programs. In addition, the predicted cases still maintain a fairly high level of incidence, so there is an urgent need to develop more comprehensive prevention strategies.

Background: Over the past decade, worldwide stroke incidence has been increasing among young adults (≤65years), which has implications during the most dynamic period of their life. There is a dearth of research exploring young adults stroke patients’ experiences, healthy lifestyle habits, preferences, and recommendations for brain care-related initiatives. The study aimed to gain knowledge and a deeper understanding of young adult stroke patients’ experiences, lifestyle habits, and support needs for brain care-related education and interventions. Methods: A descriptive qualitative study was used. Participants who took part in the quantitative phase of a larger mixed methods study (n=103 that expressed an interest in the qualitative phase, were invited to take part in semi-structured focus groups. Simultaneous data collection and analysis are being conducted. Data are being analyzed using inductive thematic analysis outlined by Braun and Clarke (2006). Results: Findings will be available by May 20, 2024. Conclusions: Study findings will be essential to 1) mobilize an understanding of young adult stroke patients’ lived experience; 2) reconceptualize the current model of stroke care and services that is traditionally geared towards older adults; and 3) inform the development of brain care-related education and interventions to meet the unique needs, priorities, and preferences of young adult stroke patients.

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.