A dual-band dual-polarized wearable antenna that applies to two different operating modes of wireless body area networks is proposed in this letter. The antenna radiates simultaneously in the ISM band at 2.45 and 5.8 GHz. It consists of a rigid button-like radiator and a flexible fabric radiator. At 2.45 GHz, an omnidirectional circularly polarized pattern is radiated by the flexible radiator, which is suitable for the on-body communication. At the same time, a linearly polarized broadside pattern for off-body communication is generated by button radiator at 5.8 GHz. The antenna has been validated in free space and human body environments. The impedance bandwidth at 2.45 and 5.8 GHz are 5% and 35%, and the gain is measured to be 0.15 and 5.95 dBi, respectively. Furthermore, the specific absorption rates are simulated. At 2.45 and 5.8 GHz, the results averaged over 1 g of body tissue are 0.128 and 0.055 W/kg. The maximum value at both bands is below the IEEE C95.3 standard of 1.6 W/kg.

Over-expansion flow can generate asymmetric shock wave interactions, which lead to significant lateral forces on a nozzle. However, there is still a lack of a suitable theory to explain the phenomenon of asymmetry. The current work carefully investigates the configurations of shock wave interactions in a planar nozzle, and proposes a theoretical method to analyse the asymmetry of over-expansion flows. First, various possible flow patterns of over-expansion flows are discussed, including regular and Mach reflections. Second, the free interaction theory and the minimum entropy production principle are used to analyse the boundary layer flow and main shock wave interactions, establish the relationship between the separation shock strength and separation position, and predict asymmetric configurations. Finally, experiments are conducted to validate the theoretical method, and similar experiments from other studies are discussed to demonstrate the effectiveness of the proposed method. Results demonstrate that the direction of asymmetric over-expansion flow is random, and the separated flow strives to adopt a pattern with minimal total pressure loss. Asymmetric interaction is a mechanism through which the flow can achieve a more efficient thermodynamic balance by minimising entropy production.

Automatic visual localization of electric vehicle (EV) charging ports presents significant challenges in uncertain environments, such as varying surface textures, reflections, lighting and observation distance. Existing methods require extensive real-world training data and well-focused images to achieve robust and accurate localization. However, both requirements are difficult to meet under variable and unpredictable conditions. This paper proposes a 2-stage vision-based localization approach. Firstly, the image synthesis technique is used to reduce the cost of real-world data collection. A task-oriented parameterization protocol (TOPP) is proposed to optimize the quality of the synthetic images. Secondly, an autofocus and servoing strategy is proposed. A hybrid detector is employed to enhance sharpness assessment performance, while a visual servoing method based on single exponential smoothing (SES) is developed to enhance stability and efficiency during the search process. Experiments were conducted to evaluate image synthesis efficiency, detection accuracy, and servoing performance. The proposed method achieved 99% detection accuracy on the real-world port images, and guided the robot to the optimal imaging position within 16 s, outperforming comparable approaches. These results highlight its potential for robust automated charging in real-world scenarios.

Epidemiologic evidence on the association between dietary choline, betaine and mortality risk remains limited, particularly among non-Western populations. We examined the association of dietary choline and betaine with all-cause mortality in Chinese adults using data from the China Health and Nutrition Survey 1991–2015. We included 9027 men and 8828 women without CVD and cancer at baseline. Dietary intake was assessed using 3-day 24-hour dietary recalls and household food inventories. Death was ascertained through household surveys in each wave. Time-dependent Cox proportional hazards regression models estimated multivariable-adjusted hazard ratios (HRs) and 95 % CIs. During a median follow-up of 9·1 years, 891 men and 687 women were deceased. Higher total choline intake was associated with lower all-cause mortality in both men (HRQ5 v. Q1 = 0·58 (95 % CI: 0·45, 0·74)) and women (HRQ5 v. Q1 = 0·59 (95 % CI: 0·44, 0·78)). The dose–response curve were reverse J-shaped in men and L-shaped in women (both P-nonlinear ≤ 0·005). Similarly, fat-soluble choline intake was inversely associated with mortality in both men (HRQ5 v. Q1 = 0·59 (95 % CI: 0·46, 0·75)) and women (HRQ5 v. Q1 = 0·53 (95 % CI: 0·40, 0·70)), showing reverse J-shaped patterns (both P-nonlinear < 0·001). A J-shaped association between water-soluble choline and mortality was observed in women (P-nonlinear < 0·001), but a null association was found in men. Betaine intake was not associated with all-cause mortality in either sex. Our findings suggest that adequate choline intake is linked to reduced all-cause mortality in Chinese adults with predominantly plant-based diets.

The whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) is economically one of the most threatening pests in tomato cultivation, which not only causes direct damage but also transmits many viruses. Breeding whitefly-resistant tomato varieties is a promising and environmentally friendly method to control whitefly populations in the field. Accumulating evidence from tomato and other model systems demonstrates that flavonoids contribute to plant resistance to herbivorous insects. Previously, we found that high flavonoid-producing tomato line deterred whitefly oviposition and settling behaviours, and was more resistant to whiteflies compared to the near-isogenic low flavonoid-producing tomato line. The objective of the current work is to describe in detail different aspects of the interaction between the whitefly and two tomato lines, including biochemical processes involved. Electrical penetration graph recordings showed that high flavonoid-producing tomato reduced whitefly probing and phloem-feeding efficiency. We also studied constitutive and induced plant defence responses and found that whitefly induced stronger reactive oxygen species accumulation through NADPH oxidase in high flavonoid-producing tomato than in low flavonoid-producing tomato. Moreover, whitefly feeding induced the expression of callose synthase genes and resulted in callose deposition in the sieve elements in high flavonoid-producing tomato but not in low flavonoid-producing tomato. As a consequence, whitefly feeding on high flavonoid-producing tomato significantly decreased uptake of phloem and reduced its performance when compared to low flavonoid-producing tomato. These results indicate that high flavonoid-producing tomato provides phloem-based resistance against whitefly infestation and that the breeding of such resistance in new varieties could enhance whitefly management.

Emission line galaxies (ELGs) are crucial for cosmological studies, particularly in understanding the large-scale structure of the Universe and the role of dark energy. ELGs form an essential component of the target catalogue for the Dark Energy Spectroscopic Instrument (DESI), a major astronomical survey. However, the accurate selection of ELGs for such surveys is challenging due to the inherent uncertainties in determining their redshifts with photometric data. In order to improve the accuracy of photometric redshift estimation for ELGs, we propose a novel approach CNN–MLP that combines convolutional neural networks (CNNs) with multilayer perceptrons (MLPs). This approach integrates both images and photometric data derived from the DESI Legacy Imaging Surveys Data Release 10. By leveraging the complementary strengths of CNNs (for image data processing) and MLPs (for photometric feature integration), the CNN–MLP model achieves a $\sigma_{\mathrm{NMAD}}$ (normalised median absolute deviation) of 0.0140 and an outlier fraction of 2.57%. Compared to other models, CNN–MLP demonstrates a significant improvement in the accuracy of ELG photometric redshift estimation, which directly benefits the target selection process for DESI. In addition, we explore the photometric redshifts of different galaxy types (Starforming, Starburst, AGN, and Broadline). Furthermore, this approach will contribute to more reliable photometric redshift estimation in ongoing and future large-scale sky surveys (e.g. LSST, CSST, and Euclid), enhancing the overall efficiency of cosmological research and galaxy surveys.

Regenerative involution is crucial for renewing the mammary gland and maximizing milk production. However, the temporal profiles indicators of oxidative status during this phase are still unclear. In this study, Experiment 1 aimed to investigate the dynamic changes in indicators of oxidative status in plasma during regenerative involution. The dairy goats were dried off at 8 weeks (wk) before kidding (−8 wk, n = 14) or −12 wk (n = 6). The blood samples taken at −8, −7, −6, −5, −4, −3, −2, −1 wk, on the day for kidding (0 wk) and the first week after kidding (+1 wk, milk production 1.28 ± 0.31 kg per day). Experiment 2 aimed to investigate the dynamic changes in indicators of oxidative status in mammary cells. Seven selected goats were biopsied for tissue collection and cell isolation at −8, −4, −1, +1 wk (milk production 1.28 ± 0.31 kg per day), respectively. Plasma analysis in Experiment 1 showed an increase in reactive oxygen species (ROS) levels, peaking at −4 wk (P < 0.01). No significant differences were observed between the dry-off treatments (P = 0.36). The activity of superoxide dismutase (SOD) in plasma remained stable from −7 wk to the first week after kidding (+1 wk), while glutathione peroxidase (GSH-Px) activity peaked at −4 wk. An increased catalase activity was observed at +1 wk (P < 0.01), indicating its response to lactation. In Experiment 2, an increase in ROS levels in isolated mammary cells was observed at −4 wk, while SOD, GSH-Px, and malondialdehyde levels in tissue homogenates rose around kidding (P < 0.01). The dynamic change of the oxidative status suggests that targeted antioxidant strategies would be helpful for regenerative involution of mammary gland in ruminants.

Manganese (Mn) is a crucial trace element that actively participates in a diverse array of physiological processes. Mn is maintained at appropriate levels in the body by absorption and excretion by the body. Dysregulation of Mn homeostasis can lead to a variety of diseases, especially the accumulation of Mn in the brain, resulting in toxic side effects. We reviewed the metabolism and distribution of Mn at multiple levels, including organ, cellular and sub-cell levels. Mitochondria are the main sites of Mn metabolism and energy conversion in cells. Enhanced Mn superoxide dismutase activity reduces mitochondrial oxidative stress and inhibits cancer development. In addition, Mn enhances anti-cancer immune responses through the cGAS–STING pathway. We introduced various delivery vectors for Mn delivery to cancer sites for Mn supplementation and anti-cancer immunity. This review aims to provide new research perspectives for the application of Mn in the prevention and treatment of human diseases, especially by enhancing anti-cancer immune responses to inhibit cancer progression.

We investigate the dynamics of close-contact melting (CCM) on ‘gas-trapped’ hydrophobic surfaces, with specific focus on the effects of geometrical confinement and the liquid–air meniscus below the liquid film. By employing dual-series and perturbation methods under the assumption of small meniscus deflections, we obtain numerical solutions for the effective slip lengths associated with velocity $\lambda$ and temperature $\lambda _t$ fields, across various values of aspect ratio $\Lambda$ (defined as the ratio of the film thickness $h$ to the structure’s periodic length $l$) and gas–liquid fraction $\phi$. Asymptotic solutions of $\lambda$ and $\lambda _t$ for $\Lambda \ll 1$ and $\Lambda \gg 1$ are derived and summarised for different surface structures, interface shapes and $\Lambda$, which reveal a different trend of $\lambda$ for $\Lambda \ll 1$ and depending on the presence of a meniscus. In the context of constant-pressure CCM, our results indicate that longitudinal grooves can enhance heat transfer under the effects of confinement and a meniscus when $\Lambda \lesssim 0.1$ and $\phi \lt 1 - 0.5^{2/3} \approx 0.37$. For gravity-driven CCM, the parameters of $l$ and $\phi$ determine whether the melting rate is enhanced, reduced or nearly unaffected. We construct a phase diagram based on the parameter matrix $(\log _{10} l, \phi )$ to delineate these three regimes. Lastly, we derive two asymptotic solutions for predicting the variation in time of the unmelted solid height.

Understanding the vertical coherence of the pressure structure and its interaction with velocity fields is critical for elucidating the mechanisms of acoustic generation and radiation in hypersonic turbulent boundary layers. This study employs linear coherence analysis to examine the self-similar coherent structures in the velocity and pressure fields within a Mach 6 hypersonic boundary layer, considering a range of wall-to-recovery temperature ratios. The influence of wall cooling on the geometric characteristics of these structures, such as inclination angles and three-dimensional aspect ratios, is evaluated. Specifically, the streamwise velocity exhibits self-similar coherent structures with the streamwise/wall-normal aspect ratio ranging from 16.5 to 38.7, showing a linear increases with decreasing wall temperatures. Similar linear dependence between the streamwise/wall-normal aspect ratio and the wall temperatures are observed for the Helmholtz-decomposed streamwise velocity and the pressure field. In terms of velocity–pressure coupling, the solenoidal component exhibits stronger interactions with the pressure fields in the near-wall region, while the dilatational component has stronger interactions with the pressure field at large scales with the increase of height. Such coupling generally follows the distance-from-the-wall scaling of the pressure field, except in cooled wall cases. Using the linear stochastic estimation, the pressure field across the boundary layer is predicted by inputting the near-wall pressure/velocity signal along with the transfer kernel. The result demonstrates that near-wall pressure signals provide the most accurate description of the pressure field in higher regions of the boundary layer. As wall-mounted sensors can measure near-wall pressure fluctuations, this study presents a potential approach to predict the off-wall pressure field correlated with the near-wall structures based on wall-pressure measurements.

People, across a wide range of personal and professional domains, need to accurately detect whether the state of the world has changed. Previous research has documented a systematic pattern of over- and under-reaction to signals of change due to system neglect, the tendency to overweight the signals and underweight the system producing the signals. We investigate whether experience, and hence the potential to learn, improves people’s ability to detect change. Participants in our study made probabilistic judgments across 20 trials, each consisting of 10 periods, all in a single system that crossed three levels of diagnosticity (a measure of the informativeness of the signal) with four levels of transition probability (a measure of the stability of the environment). We found that the system-neglect pattern was only modestly attenuated by experience. Although average performance did not increase with experience overall, the degree of learning varied substantially across the 12 systems we investigated, with participants showing significant improvement in some high diagnosticity conditions and none in others. We examine this variation in learning through the lens of a simple linear adjustment heuristic, which we term the “δ-ϵ” model. We show that some systems produce consistent feedback in the sense that the best δ and ϵ responses for one trial also do well on other trials. We show that learning is related to the consistency of feedback, as well as a participant’s “scope for learning” how close their initial judgments are to optimal behavior.