We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Little is known about the association between iodine nutrition status and bone health. The present study aimed to explore the connection between iodine nutrition status, bone metabolism parameters, and bone disease (osteopenia and osteoporosis). A cross-sectional survey was conducted involving 391, 395, and 421 adults from iodine fortification areas (IFA), iodine adequate areas (IAA), and iodine excess areas (IEA) of China. Iodine nutrition status, bone metabolism parameters and BMD were measured. Our results showed that, in IEA, the urine iodine concentrations (UIC) and serum iodine concentrations (SIC) were significantly higher than in IAA. BMD and Ca2+ levels were significantly different under different iodine nutrition levels and the BMD were negatively correlated with UIC and SIC. Univariate linear regression showed that gender, age, BMI, menopausal status, smoking status, alcohol consumption, UIC, SIC, free thyroxine, TSH, and alkaline phosphatase were associated with BMD. The prevalence of osteopenia was significantly increased in IEA, UIC ≥ 300µg/L and SIC > 90µg/L groups. UIC ≥ 300µg/L and SIC > 90µg/L were risk factors for BMD T value < -1.0 SD. In conclusion, excess iodine can not only lead to changes in bone metabolism parameters and BMD, but is also a risk factor for osteopenia and osteoporosis.
In this paper, we propose a hybrid sparse array design utilizing Delaunay Triangulation algorithm for element positioning and Convex algorithm for element excitation optimization. This Delaunay Triangulation algorithm yields a radiation pattern devoid of grating lobes. Then Convex algorithm is used to optimize the element excitations to further decrease side-lobe-level. The minimum inter-element distance is as large as 8 times of wavelength. The peak-side-lobe-level can be −17.3 dB. Furthermore, beam steering can be achieved with good performance within 80° field-of-view range.
Sensory neuron membrane protein (SNMP) gene play a crucial role in insect chemosensory systems. However, the role of SNMP in the host searching behaviour of Rhopalosiphum padi (Hemiptera: Aphididae), a highly destructive pest of cereal crops, has not been clearly understood. Our previous research has shown that three wheat volatile organic compounds (VOCs) – (E)-2-hexenol, linalool, and octanal can attract R. padi, but the involvement of SNMP in the aphid’s olfactory response to these wheat VOCs has not to be elucidated. In this study, only one SNMP gene was cloned and characterised from R. padi. The results revealed that the SNMP belongs to the SNMP1 subfamily and was named RpadSNMP1. RpadSNMP11 was predominantly expressed in the antennae of the aphid, with significantly higher expression levels observed in winged forms, indicating that it is involved in olfactory responses of R. padi. RpadSNMP1 expression was significantly up-regulated following starvation, and the expression of this gene showed a decreasing trend after 24 h of aphid feeding. Functional analysis through RpadSNMP1 knockdown demonstrated a significant decrease in R. padi’s ability to search for host plants. The residence time of R. padi injected with dsRpadSNMP1 significantly shortened in response to (E)-2-hexenol, linalool and octanal according to the four-arm olfactometer, indicating the crucial role of RpadSNMP1 in mediating the aphid’s response to these wheat VOCs. Molecular docking suggested potential binding interactions between RpadSNMP1 and three wheat VOCs. Overall, these findings provided evidence for the involvement of RpadSNMP1 in host plant searching and lay a foundation for developing new methods to control this destructive pest.
This paper presents a notched ultra-wideband antenna designed to suppress interference from narrowband communication systems. The antenna features a defected ground structure and a stepped microstrip feedline for improved impedance matching and enhanced bandwidth. A bent slot structure is incorporated into the radiating patch to achieve the band-notched characteristic. It has a wide tunable frequency range which allows for flexible adjustment of the notch frequency. Traditional optimization methods, such as numerical analysis, are computationally expensive and inefficient, while heuristic algorithms are less precise. To address these challenges, an improved one-dimensional convolutional neural network (1DCNN-IPS) model is proposed for optimizing the bent slot design more efficiently. The trained 1DCNN-IPS model can accurately predict the antenna’s electromagnetic parameters, reducing mean squared error and training times compared to traditional methods. This provides an efficient and precise solution for antenna structural optimization.
Research findings based on the data of current automatic identification systems (AISs) can only be applied to some parts of navigation research owing to their insufficient mining depth. Previously, route planning research has been based on the waypoint and corresponding optimised algorithm without considering the actual navigation situation and sailing habits. The planned route considerably differs from the actual sailing route, and the application result is undesirable. A novel solution to support the route planning problem has been introduced owing to the large accumulation of AIS big data. In this study, the ship navigable route framework (SNRF) which is reflected by real data via mining AIS big data serves as the basic network for the planned maritime route. This study uses the concept of manifold distance based on AIS big data to build a maritime SNRF through high-density searching. It can provide basic theoretical support for actual navigation distance calculation, route planning and route accessibility inspection in the future.
Green water loads on prismatic obstacles (representing topside structures) mounted on the raised deck of a simplified vessel are investigated using computational fluid dynamics simulations and physical model testing with emphasis on examining different structure shapes, orientation angles and relative structure size. For each scenario investigated, several flow features are identified that characterize the green water interaction with the structure and influence loads, namely delayed flow diversion, formation of a vertical jet, scattered wave formation and the development of complex wake patterns. Comparing across structures, these interactions are more pronounced for blunt objects, and the associated force impulse is larger. For example, a cube with flow at normal incidence is found to experience approximately twice the force impulse of a circular cylinder of the same projected area. Equally, rotation of the cube leads to reduced run-up height and streamwise force on the structure. To explain these trends, a theoretical model based on Newtonian flow theory is adopted. This model provides an estimate of the streamwise force exerted on obstacles in high-Froude-number flows and shows good agreement with the numerical results when the flow is supercritical, shallow (small water depth relative to structure width) and the structure is tall (large structure height relative to water depth). Despite some limitations, the model should provide an efficient force prediction tool for practical use in design.
We incorporate the liquidity trap and private behavioral preferences into a New Keynesian dynamic stochastic general equilibrium model to analyze fiscal multipliers. The results indicate that the influence of the liquidity trap on fiscal policy is driven by a combination of the interest rate transmission effect and the precautionary savings effect, showing a notable amplification of multipliers based on estimates from U.S. data. Furthermore, we examine two types of private behavioral preferences: habit formation and investor confidence. Habit formation significantly boosts short-term government spending multipliers while exhibiting diverse impacts on different types of taxation. Compared to superficial habits, deep habits result in flatter multiplier curves. Investor confidence, being highly sensitive to output fluctuations, enhances both spending and tax multipliers over the medium to long term. Additionally, the investor confidence channel slightly amplifies the expansionary effect of the liquidity trap on multipliers, contrasting with the impact of habit formation.
Knowledge is growing on the essential role of neural circuits involved in aberrant cognitive control and reward sensitivity for the onset and maintenance of binge eating.
Aims
To investigate how the brain's reward (bottom-up) and inhibition control (top-down) systems potentially and dynamically interact to contribute to subclinical binge eating.
Method
Functional magnetic resonance imaging data were acquired from 30 binge eaters and 29 controls while participants performed a food reward Go/NoGo task. Dynamic causal modelling with the parametric empirical Bayes framework, a novel brain connectivity technique, was used to examine between-group differences in the directional influence between reward and executive control regions. We explored the proximal risk factors for binge eating and its neural basis, and assessed the predictive ability of neural indices on future disordered eating and body weight.
Results
The binge eating group relative to controls displayed fewer reward-inhibition undirectional and directional synchronisations (i.e. medial orbitofrontal cortex [mOFC]–superior parietal gyrus [SPG] connectivity, mOFC → SPG excitatory connectivity) during food reward_nogo condition. Trait impulsivity is a key proximal factor that could weaken the mOFC–SPG connectivity and exacerbate binge eating. Crucially, this core mOFC–SPG connectivity successfully predicted binge eating frequency 6 months later.
Conclusions
These findings point to a particularly important role of the bottom-up interactions between cortical reward and frontoparietal control circuits in subclinical binge eating, which offers novel insights into the neural hierarchical mechanisms underlying problematic eating, and may have implications for the early identification of individuals suffering from strong binge eating-associated symptomatology in the general population.
To speed up the construction of grassroots medical and health teams in China, free training of rural order-oriented medical students was launched in June 2010. Based on the theory of policy tools, a quantitative analysis of policy texts at the national level was conducted to explore the use of policy tools and to put forward corresponding suggestions for adjustments.
Methods
From January to February 2023, the research team searched the Peking University Treasure Database and the official websites of the State Council, the National Health Commission, the Ministry of Education, and other ministries for national policy documents related to free training of order-oriented medical students published from June 2010 to May 2023. A policy tool and policy target analysis framework were used to quantitatively analyze the policy documents.
Results
A total of 16 policy documents were included and 213 policy provisions were extracted. From the perspective of policy tools, the proportion of policy provisions using imperative policy tools was the highest (63.4%), followed by advisory policy tools (18.8%). and reward-based policy tools (13.6%). Functional expansion tools (2.8%) and authoritative restructuring tools (1.4%) accounted for a relatively low proportion. The institutional education stage is the main policy target, with provisions accounting for 75 percent (162 articles), followed by the continuing education stage (17.6%; 38 articles), and the postgraduate education stage (7.4%; 16 articles).
Conclusions
The distribution of policy tools for the free training policy of rural order-oriented medical students in China needs to be balanced, and the internal combination of the same policy tools needs to be optimized. The policy targets were mainly concentrated in the education stage of universities.
With the aging population, chronic diseases have become a serious threat to public health in China. Adhering to the doctor’s advice is an effective strategy for controlling chronic diseases, and the preferences of patients with chronic disease has an important impact on compliance with medication. However, there is insufficient research exploring this aspect.
Methods
In this study patients with chronic disease were selected by stratified random sampling to participate in a survey carried out in three cities of a province in eastern China. The discrete choice experiment used a questionnaire of D-efficiency experimental design to measure the medication choices of patients with chronic disease. The main attributes included drug price, onset of action, adverse reactions, traditional Chinese or Western medicine, domestic drug, and reimbursed by medical insurance. The data were analyzed using a mixed logit model.
Results
A total of 1,062 valid questionnaires were received. The 1,045 questionnaires that passed the consistency test covered three prefecture-level cities, nine counties, and 216 villages. All drug attributes were statistically significant for selection preferences. The preference of patients in rural areas with chronic disease was “quick onset of action” (β=2.491), “Western medicine” (β=0. 826), “medical insurance” (β=0.556), “domestic drugs” (β=0.286), and “very few adverse reactions” (β=0.170). “Drug price” also had an impact on medication preferences among patients in rural areas with chronic disease (β=−0.013).
Conclusions
Onset of action is the attribute of medications that is of most concern for patients in rural areas with chronic disease. Subgroup analysis showed that these patients were predominantly female, had a primary school education or lower, were younger than 69 years, were unemployed, and had an annual income between CNY10,000 (USD1,396.78) and CNY50,000 (USD6,983.92). They were willing to pay more for drugs with a quick onset of action, Western medicines, and drugs with reimbursed by medical insurance.
The paper presents a novel control method aimed at enhancing the trajectory tracking accuracy of two-link mechanical systems, particularly nonlinear systems that incorporate uncertainties such as time-varying parameters and external disturbances. Leveraging the Udwadia–Kalaba equation, the algorithm employs the desired system trajectory as a servo constraint. First, the system’s constraints to construct its dynamic equation and apply generalized constraints from the constraint equation to an unconstrained system. Second, we design a robust approximate constraint tracking controller for manipulator control and establish its stability using Lyapunov’s law. Finally, we numerically simulate and experimentally validate the controller on a collaborative platform using model-based design methods.
Foodborne diseases are ongoing and significant public health concerns. This study analysed data obtained from the Foodborne Outbreaks Surveillance System of Wenzhou to comprehensively summarise the characteristics of foodborne outbreaks from 2012 to 2022. A total of 198 outbreaks were reported, resulting in 2,216 cases, 208 hospitalisations, and eight deaths over 11 years. The findings suggested that foodborne outbreaks were more prevalent in the third quarter, with most cases occurring in households (30.8%). Outbreaks were primarily associated with aquatic products (17.7%) as sources of contamination. The primary transmission pathways were accidental ingestion (20.2%) and multi-pathway transmission (12.1%). Microbiological aetiologies (46.0%), including Vibrio parahaemolyticus, Salmonella ssp., and Staphylococcus aureus, were identified as the main causes of foodborne outbreaks. Furthermore, mushroom toxins (75.0%), poisonous animals (12.5%), and poisonous plants (12.5%) were responsible for deaths from accidental ingestion. This study identified crucial settings and aetiologies that require the attention of both individuals and governments, thereby enabling the development of effective preventive measures to mitigate foodborne outbreaks, particularly in coastal cities.
The AIMTB rapid test assay is an emerging test, which adopted a fluorescence immunochromatographic assay to measure interferon-γ (IFN-γ) production following stimulation of effector memory T cells in whole blood by mycobacterial proteins. The aim of this article was to explore the ability of AIMTB rapid test assay in detecting Mycobacterium tuberculosis (MTB) infection compared with the widely applied QuantiFERON-TB Gold Plus (QFT-Plus) test among rural doctors in China. In total, 511 participants were included in the survey. The concordance between the QFT-Plus test and the AIMTB rapid test assay was 94.47% with a Cohen’s kappa coefficient (κ) of 0.84 (95% CI, 0.79–0.90). Improved concordance between the two tests was observed in males and in participants with 26 or more years of service as rural doctors. The quantitative values of the QFT-Plus test was higher in individuals with a result of QFT-Plus-/AIMTB+ as compared to those with a result of QFT-Plus-/AIMTB- (p < 0.001). Overall, our study found that there was an excellent consistency between the AIMTB rapid test assay and the QFT-Plus test in a Chinese population. As the AIMTB rapid test assay is fast and easy to operate, it has the potential to improve latent tuberculosis infection testing and treatment at the community level in resource-limited settings.
We report on an improved ytterbium-doped yttrium aluminum garnet thin-disk multi-pass amplifier for kilowatt-level ultrafast lasers, showcasing excellent beam quality. At a repetition rate of 800 kHz, the 6.8 ps, 276 W seed laser is amplified up to an average power of 1075 W, corresponding to a pulse energy of 1.34 mJ. The 36-pass amplifier is designed as a compact mirror array in which the beam alternately propagates between the mirrors and the disk by a quasi-collimated state. We adopted a quasi-collimated propagation to confine stray and diffracted light by the slight curvature of the disk, which enables us to achieve an outstanding extraction efficiency of up to 57% with excellent beam quality in stable laser operation at high power. The beam quality at 1075 W was measured to be M2 < 1.51. Furthermore, stability testing was demonstrated with a root-mean-square power fluctuation of less than 1.67% for 10 min.
The neural correlates underlying late-life depressive symptoms and cognitive deterioration are largely unclear, and little is known about the role of chronic physical conditions in such association. This research explores both concurrent and longitudinal associations between late-life depressive symptoms and cognitive functions, with examining the neural substrate and chronic vascular diseases (CVDs) in these associations.
Methods
A total of 4109 participants (mean age = 65.4, 63.0% females) were evaluated for cognitive functions through various neuropsychological assessments. Depressive symptoms were assessed by the Geriatric Depression Scale and CVDs were self-reported. T1-weighted magnetic resonance imaging (MRI), diffusion tensor imaging, and functional MRI (fMRI) data were acquired in a subsample (n = 791).
Results
Cognitively, higher depressive symptoms were correlated with poor performance across all cognitive domains, with the strongest association with episodic memory (r = ‒0.138, p < 0.001). Regarding brain structure, depressive symptoms were negatively correlated with thalamic volume and white matter integrity. Further, white matter integrity was found to mediate the longitudinal association between depressive symptoms and episodic memory (indirect effect = −0.017, 95% CI −0.045 to −0.002) and this mediation was only significant for those with severe CVDs (β = −0.177, p = 0.008).
Conclusions
This study is one of the first to provide neural evidence elucidating the longitudinal associations between late-life depressive symptoms and cognitive dysfunction. Additionally, the severity of CVDs strengthened these associations, which enlightens the potential of managing CVDs as an intervention target for preventing depressive symptoms-related cognitive decline.
To address the issues of low positioning accuracy and weak robustness of prior visual simultaneous localization and mapping (VSLAM) systems in dynamic environments, a semantic VSLAM (Sem-VSLAM) approach based on deep learning is proposed in this article. The proposed Sem-VSLAM algorithm adds semantic segmentation threads in parallel based on the open-source ORB-SLAM2’s visual odometry. First, while extracting the ORB features from an RGB-D image, the frame image is semantically segmented, and the segmented results are detected and repaired. Then, the feature points of dynamic objects are eliminated by using semantic information and motion consistency detection, and the poses are estimated by using the remaining feature points after the dynamic feature elimination. Finally, a 3D point cloud map is constructed by using tracking information and semantic information. The experiment uses Technical University of Munich public data to show the usefulness of the Sem-VSLAM algorithm. The experimental results show that the Sem-VSLAM algorithm can reduce the absolute trajectory error and relative attitude error of attitude estimation by about 95% compared to the ORB-SLAM2 algorithm and by about 14% compared to the VO-YOLOv5s in a highly dynamic environment and the average time consumption of tracking each frame image reaches 61 ms. It is verified that the Sem-VSLAM algorithm effectively improves the robustness and positioning accuracy in high dynamic environment and owning a satisfying real-time performance. Therefore, the Sem-VSLAM has a better mapping effect in a highly dynamic environment.
MicroRNAs (miRNAs) play important roles in regulating salt tolerance in Dongxiang wild rice (DXWR, Oryza rufipogon Griff.). The development of salt-responsive miRNA-simple sequence repeat (SSR) markers will significantly bolster research on DXWR, providing novel tools for exploring salt-tolerant genetic resources and advancing the development of salt-tolerant rice varieties. In the present study, a total of 137 miRNA-SSR markers were successfully developed, specifically derived from miRNAs responsive to salt stress in DXWR. Subsequently, a subset of 20 markers was randomly selected for validation across three distinct DXWR populations, along with 35 modern rice varieties. Notably, 13 of these markers exhibited remarkable polymorphism. The polymorphic markers collectively amplified 52 SSR loci, averaging four alleles per locus. The polymorphism information content values associated with these loci spanned from 0.23 to 0.70, with a mean value of 0.49. Particularly noteworthy is the miR162a-SSR marker, which demonstrated distinct allelic patterns and holds potential as a diagnostic marker for discriminating the salt-tolerant rice varieties from the non-tolerant varieties. This study provides a valuable tool for genetic analysis and precision breeding, facilitating the identification and utilization of valuable salt-tolerant genetic resources.
To compare the benefits and drawbacks of traditional and automated conservation assessments, we used a field-based study and automated conservation assessments using GeoCAT, red and ConR to assess four species of Buddleja (Scrophulariaceae), a cosmopolitan genus of flowering plants. Buddleja colvilei, Buddleja sessilifolia, Buddleja delavayi and Buddleja yunnanensis are endemic to the Himalayan region. They have not yet been assessed for the IUCN Red List of Threatened Species but are facing elevated risks of extinction because of various anthropogenic and environmental pressures. Buddleja sessilifolia and B. delavayi are listed as Plant Species with Extremely Small Populations in Yunnan, China, where they are known to be threatened. Although automated assessments evaluated B. delavayi and B. yunnanensis as Endangered and B. sessilifolia and B. colvilei as Vulnerable, our field studies indicated a different categorization for three of the species: B. delavayi and B. yunnanensis as Critically Endangered and B. sessilifolia as Endangered. Our findings indicate that the accuracy and reliability of assessment methods can differ and that field surveys remain important for conservation assessments. We recommend an integrated approach addressing these limitations, to safeguard the future of other species endemic to the Himalayan region.
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.