The whitefly, Bemisia tabaci is a cryptic species complex in which one member, Middle East-Asia Minor 1 (MEAM1) has invaded globally. After invading large countries like Australia, China, and the USA, MEAM1 spread rapidly across each country. In contrast, our analysis of MEAM1 in India showed a very different pattern. Despite the detection of MEAM1 being contemporaneous with invasions in Australia, the USA, and China, MEAM1 has not spread widely and instead remains restricted to the southern regions. An assessment of Indian MEAM1 genetic diversity showed a level of diversity equivalent to that found in its presumed home range and significantly higher than that expected across the invaded range. The high level of diversity and restricted distribution raises the prospect that its home range extends into India. Similarly, while the levels of diversity in Australia and the USA conformed to that expected for the invaded range, China did not. It suggests that China may also be part of its home range. We also observed that diversity across the invaded range was primarily accounted for by a single haplotype, Hap1, which accounted for 79.8% of all records. It was only the invasion of Hap1 that enabled outbreaks to occur and MEAM1’s discovery.

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.

Increasing evidence indicates that (poly)phenol consumption can have beneficial effects in human brain function(1). The overall aim of this project is to investigate whether consumption of a (poly)phenol rich cranberry drink improve mental health and cognitive function in university students via the gut-brain axis.

A parallel randomised controlled trial was conducted in 72 young healthy final year university students assigned to consume 236 mL cranberry drink (442 mg polyphenols) or nutrient matched placebo, daily for 12 weeks. The primary outcome was mood, measured as Total Mood Disturbance (TMD), using the Profile of Mood States (POMS) questionnaire. Secondary outcomes included stress, anxiety and depression levels, measured using the Perceived Stress Scale (PSS), and the Hospital Anxiety Depression Scale (HADS) questionnaire, salivary cortisol levels and cognitive function measured using the Online General Cognitive Assessment Battery (CogniFit). All of these questionnaires were measured every 4 weeks. Blood and urine samples were collected to measure inflammatory markers, gut-brain-axis metabolites, short chain fatty acids (SCFA), and cranberry polyphenols metabolites. Faecal samples were also collected for measuring gut microbiome diversity and composition and faecal metabolomics. Diet was assessed using food frequency questionnaires (FFQ), 7-day food diaries (EPIC) and 24 h online dietary recalls (intake 24) during the study. Linear mixed-effect model (LMM) and ANCOVA were used to investigate the relationship between the 2 trial arms.

No significant differences were found between treatments for mood, stress levels, anxiety, depression, circulating short chain fatty acids or inflammatory markers, however a significantly lower diurnal area under the curve of salivary cortisol (p = 0.010) and significantly higher short-term memory (Z-score: p = 0.024; Raw-score: p = 0.034) was found at 12 weeks in the cranberry group compared with the placebo. Besides, significant differences between interventions were found in plasma gut-brain axis metabolites, including the kynurenine and bile acids pathway which were kynurenine (p = 0.023), kynurenic (p = 0.032), quinolinic (p = 0.018), and glycolithocholic acid (p = 0.04) as well as several plasma and urinary cranberry (poly)phenol metabolites were modulated by cranberry consumption.

In conclusion, daily cranberry (poly)phenol supplementation for 12 week did not improve mood, stress, anxiety, and depression symptoms in healthy university students, however it may modulate cortisol levels and some aspects of cognitive function via the gut-brain axis.

A distributed cooperative guidance law without numerical singularities is proposed for the simultaneous attack a stationary target by multiple vehicles with field-of-view constraints. Firstly, the vehicle engagement motion model is transformed into a multi-agent model. Then, based on the state-constrained consensus protocol, a coordination control law with field-of-view (FOV) constraints is proposed. Finally, the cooperative guidance law has been improved to make it more suitable for practical application. Numerical simulations verified the effectiveness and robustness of the proposed guidance law in the presence of acceleration saturation, communication delays and measurement noise.

Health technology assessment (HTA) agencies assess evidence to support decision making about which technologies to provide and pay for in the health system. HTA impact is understood as the influence that HTA report findings can have in the health system, including impacts on reimbursement decisions, changes to health outcomes, or broader system or societal impacts. The International Network of Agencies for Health Technology Assessment (INAHTA) is a global network of publicly funded HTA agencies. INAHTA’s mission, in part, is to advance the impact of HTA to support reimbursement decisions and the optimal use of health system resources. Each year, INAHTA awards the David Hailey Award for Best Impact Story to the member agency that shares the best story, as voted by fellow members, about HTA impact. The impact story sharing program in INAHTA contributes to a deeper understanding of what works well (or not so well) in achieving HTA impact. This paper provides six impact stories from agencies that were finalists for the 2021 and 2022 David Hailey Impact Award for Best Impact Story: the Institut national d’excellence en santé et en services sociaux, the Malaysian Health Technology Assessment Section, Ontario Health, the Center for Drug Evaluation, the National Institute for Health and Care Excellence, and Health Technology Wales. These stories demonstrate that HTA agencies can, in differing ways, effectively support governments in their efforts to place evidence at the centre of decision making.

This paper develops a novel full-state-constrained intelligent adaptive control (FIAC) scheme for a class of uncertain nonlinear systems under full state constraints, unmodeled dynamics and external disturbances. The key point of the proposed scheme is to appropriately suppress and compensate for unmodeled dynamics that are coupled with other states of the system under the conditions of various disturbances and full state constraints. Firstly, to guarantee that the time-varying asymmetric full state constraints are obeyed, a simple and valid nonlinear error transformation method has been proposed, which can simplify the constrained control problem of the system states into a bounded control problem of the transformed states. Secondly, considering the coupling relationship between the unmodeled dynamics and other states of the controlled system such as system states and control inputs, a decoupling approach for coupling uncertainties is introduced. Thereafter, owing to the employed dynamic signal and bias radial basis function neural network (BIAS-RBFNN) improved on traditional RBFNN, the adverse effects of unmodeled dynamics on the controlled system can be suppressed appropriately. Furthermore, the matched and mismatched disturbances are reasonably estimated and circumvented by a mathematical inequality and a disturbance observer, respectively. Finally, numerical simulations are provided to demonstrate the effectiveness of the proposed FIAC strategy.

The study applies a two-dimensional adaptive mesh refinement (AMR) method to estimate the coordinates of the locations of the centre of vortices in steady, incompressible flow around a square cylinder placed within a channel. The AMR method is robust and low cost, and can be applied to any incompressible fluid flow. The considered channel has a blockage ratio of $1/8$. The AMR is tested on eight cases, considering flows with different Reynolds numbers ($5\le Re\le 50$), and the estimated coordinates of the location of the centres of vortices are reported. For all test cases, the initial coarse meshes are refined four times, and the results are in good agreement with the literature where a very fine mesh was used. Furthermore, this study shows that the AMR method can capture the location of the centre of vortices within the fourth refined cells, and further confirms an improvement in the estimation with more refinements.

The main purpose of this article is to present the nonlinear unsteady behaviour for jet transport aircraft response to serious atmosphere turbulence in cruise flight and to provide the appropriate mitigation concepts for pilots in the pilot training course of the IATA – Loss of Control In-flight (LOC-I) program. The flight data of a twin-jet and a four-jet transport aircraft encountered serious atmosphere turbulence are the study cases for this article. This study uses flight data mining and fuzzy-logic modeling of artificial intelligence techniques to establish nonlinear unsteady aerodynamic models. Since the rapid change of aerodynamic characteristics in turbulence, so the study uses decoupled longitudinal and lateral-directional motion to identify various eigenvalue motion modes of nonlinear unsteady behaviour through digital 6-DOF flight simulation. It is found that the changes of the main flight variables in the aerodynamic scene and flight environment of the two aircraft are different, but the profiles of five eigenvalue motion modes are actually similar. Those similar eigenvalue motion modes can formulate preventive actions related to the flight handling quality for safe and efficient control by pilots to execute the flight tasks. The one with a large drop height during the ups and downs motion between the two is chosen to construct the movement mechanism of nonlinear unsteady behaviours. The assessments of dynamic stability characteristics of nonlinear unsteady behaviour based on the approaches of oscillatory motion and eigenvalue motion modes related to loss of control will be demonstrated in this article. To develop preventive actions, the situation awareness response to the induced mutation of nonlinear unsteady behaviour on the pilot’s operations will be a further research task in the future.

The cyst nematodes, subfamily Heteroderinae, are plant pathogens of worldwide economic significance. A new cyst nematode of the genus Cactodera within the Heteroderinae, Cactodera xinanensis n. sp., was isolated from rhizospheres of crops in the Guizhou and Sichuan provinces of southwest China. The new species was characterized by having the cyst with a length/width = 1.3 ± 0.1 (1.1–1.6), a fenestral diameter of 28.1 ± 4.3 (21.3–38.7) μm, vulval denticles present; second-stage juvenile with stylet 21.5 ± 0.5 (20.3–22.6) μm long, tail 59.4 ± 2.0 (55.9–63.8) μm long and hyaline region 28.7 ± 2.7 (25.0–36.3) μm long, lateral field with four incisures; the eggshell with punctations. The new species can be differentiated from other species of Cactodera by a longer tail and hyaline region of second-stage juveniles. Phylogenetic relationships within populations and species of Cactodera are given based on the analysis of the internal transcribed spacer (ITS-rRNA), the large subunit of the nuclear ribosomal RNA (28S-rRNA) D2-D3 region and the partial cytochrome oxidase subunit I (COI) gene sequences here. The ITS-rRNA, 28S-rRNA and COI gene sequences clearly differentiated Cactodera xinanensis n. sp. from other species of Cactodera. A key and a morphological identification characteristic table for the species of Cactodera are included in the study.

Polarized electron beam production via laser wakefield acceleration in pre-polarized plasma is investigated by particle-in-cell simulations. The evolution of the electron beam polarization is studied based on the Thomas–Bargmann–Michel–Telegdi equation for the transverse and longitudinal self-injection, and the depolarization process is found to be influenced by the injection schemes. In the case of transverse self-injection, as found typically in the bubble regime, the spin precession of the accelerated electrons is mainly influenced by the wakefield. However, in the case of longitudinal injection in the quasi-1D regime (for example, F. Y. Li et al., Phys. Rev. Lett. 110, 135002 (2013)), the direction of electron spin oscillates in the laser field. Since the electrons move around the laser axis, the net influence of the laser field is nearly zero and the contribution of the wakefield can be ignored. Finally, an ultra-short electron beam with polarization of $99\%$ can be obtained using longitudinal self-injection.

Echinococcosis poses a significant threat to public health. The Chinese government has implemented prevention and control measures to mitigate the impact of the disease. By analyzing data from the Chinese Center for Disease Control and Prevention and the State Council of the People’s Republic of China, we found that implementation of these measures has reduced the infection rate by nearly 50% between 2004 to 2022 (from 0.3975 to 0.1944 per 100,000 person-years). Nonetheless, some regions still bear a significant disease burden, and lack of detailed information limites further evaluation of the effects on both alveolar and cystic echinococcosis. Our analysis supports the continuing implementation of these measures and suggests that enhanced wildlife management, case-based strategies, and surveillance systems will facilitate disease control.

Competition among the two-plasmon decay (TPD) of backscattered light of stimulated Raman scattering (SRS), filamentation of the electron-plasma wave (EPW) and forward side SRS is investigated by two-dimensional particle-in-cell simulations. Our previous work [K. Q. Pan et al., Nucl. Fusion 58, 096035 (2018)] showed that in a plasma with the density near 1/10 of the critical density, the backscattered light would excite the TPD, which results in suppression of the backward SRS. However, this work further shows that when the laser intensity is so high ($>{10}^{16}$ W/cm2) that the backward SRS cannot be totally suppressed, filamentation of the EPW and forward side SRS will be excited. Then the TPD of the backscattered light only occurs in the early stage and is suppressed in the latter stage. Electron distribution functions further show that trapped-particle-modulation instability should be responsible for filamentation of the EPW. This research can promote the understanding of hot-electron generation and SRS saturation in inertial confinement fusion experiments.

Vortex shedding in the wake of a cylinder in uniform flow can be suppressed via the application of a porous coating; however, the suppression mechanism is not fully understood. The internal flow field of a porous coated cylinder (PCC) can provide a deeper understanding of how the flow within the porous medium affects the wake development. A structured PCC (SPCC) was three-dimensionally printed using a transparent material and tested in water tunnel facilities using flow visualisation and tomographic particle image velocimetry at outer-diameter Reynolds numbers of $Re = 7 \times 10^{3}$ and $7.3 \times 10^{4}$, respectively. The internal and near-wall flow fields are analysed at the windward and mid-circumference regions. Flow stagnation is observed in the porous layer on the windward side and its boundary is shown to fluctuate with time in the outermost porous layer. This stagnation region generates a quasi-aerodynamic body that influences boundary layer development on the SPCC inner diameter, that separates into a shear layer within the porous medium. For the first time via experiment, spectral content within the separated shear layer reveals vortex shedding processes emanating through single pores at the outer diameter, providing strong evidence that SPCC vortex shedding originates from the inner diameter. Velocity fluctuations linked to this vortex shedding propagate through the porous layers into the external flow field at a velocity less than that of the free stream. The Strouhal number linked to this velocity accurately predicts the SPCC vortex shedding frequency.

The control of a wing-in-ground craft (WIG) usually allows for many needs, like cruising, speed, survival and stealth. Various degrees of emphasis on these requirements result in different trajectories, but there has not been a way of integrating and quantifying them yet. Moreover, most previous studies on other vehicles’ multi-objective trajectory is planned globally, lacking for local planning. For the multi-objective trajectory planning of WIGs, this paper proposes a multi-objective function in a polynomial form, in which each item represents an independent requirement and is adjusted by a linear or exponential weight. It uses the magnitude of weights to demonstrate how much attention is paid relatively to the corresponding demand. Trajectories of a virtual WIG model above the wave trough terrain are planned using reward shaping based on the introduced multi-objective function and deep reinforcement learning (DRL). Two conditions are considered globally and locally: a single scheme of weights is assigned to the whole environment, and two different schemes of weights are assigned to the two parts of the environment. Effectiveness of the multi-object reward function is analysed from the local and global perspectives. The reward function provides WIGs with a universal framework for adjusting the magnitude of weights, to meet different degrees of requirements on cruising, speed, stealth and survival, and helps WIGs guide an expected trajectory in engineering.

The paper addresses the six-degree-of-freedom coupled control problem for spacecraft formation flying subject to actuator saturation and input quantisation whilst considering limited communication resources. Firstly, a novel event-triggered distributed observer without continuous communications is presented to recover the information of the virtual leader. Remarkably, by embedding a hyperbolic tangent function-based nonlinear term into the triggering condition, the event-based observer realises a more reasonable trigger threshold. Subsequently, an adding-a-power-integrator-based fixed-time control algorithm is proposed for the follower spacecraft. Further, the control scheme ingeniously compensates for the actuator saturation and the input quantisation problems without embedding auxiliary systems. Finally, numerical simulations are carried out to highlight the advantages of the theoretical results.

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.

A multiple-vehicles time-coordination guidance technique based on deep learning is suggested to address the cooperative guiding problem of hypersonic gliding vehicle entry phase. A dual-parameter bank angle profile is used in longitudinal guiding to meet the requirements of time coordination. A vehicle trajectory database is constructed along with a deep neural network (DNN) structure devised to fulfill the error criteria, and a trained network is used to replace the conventional prediction approach. Moreover, an extended Kalman filter is constructed to detect changes in aerodynamic parameters in real time, and the aerodynamic parameters are fed into a DNN. The lateral guiding employs a logic for reversing the sign of bank angle, which is based on the segmented heading angle error corridor. The final simulation results demonstrate that the built DNN is capable of addressing the cooperative guiding requirements. The algorithm is highly accurate in terms of guiding, has a fast response time, and does not need inter-munition communication, and it is capable of solving guidance orders that satisfy flight requirements even when aerodynamic parameter disruptions occur.