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Prehistoric humans seem to have preferred inhabiting small river basins, which were closer in distance to most settlements compared to larger rivers. The Holocene landscape evolution is considered to have played a pivotal role in shaping the spatiotemporal patterns of these settlements. In this study, we conducted comprehensive research on the relationship between landscape evolution and settlement distribution within the Huangshui River basin, which is a representative small river in Central China with numerous early settlements, including a prehistoric city known as the Wangjinglou site (WJL). Using geoarchaeological investigations, optically stimulated luminescence dating, pollen analysis, and grain-size analysis, we analyzed the characteristics of the Holocene environment. The results indicate the presence of two distinct geomorphic systems, namely the red clay hills and the river valley. The red clay hills, formed in the Neogene, represent remnants of the Songshan piedmont alluvial fan that was eroded by rivers. There are three grades of terraces within the river valley. T3 is a strath terrace and formed around 8.0 ka. Both T2 and T1 are fill terraces, which were developed around 4.0 ka and during the historical period, respectively. The sedimentary features and pollen analysis indicate the existence of an ancient lake-swamp on the platform during 11.0–9.0 ka. This waterbody gradually shrank during 9.0–8.0 ka, and ultimately disappeared after 8.0 ka. Since then, the development of large-scale areas of water ceased on the higher geomorphic units. River floods also cannot reach the top of these high geomorphic units, where numerous prehistoric settlements are located, including the Xia–Shang cities of the WJL site. Our research demonstrates that landscape stability supported the long-term and sustainable development of ancient cultures and facilitated the establishment of the WJL ancient cities in the region.
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.
This paper presents a climbing robot (CR) designed for the purpose of pipeline maintenance, with capability to avoid the risks inherent in manual operations. In the design process, a three degree of freedom (DOF) parallel mechanism coupled with a remote center of motion (RCM) mechanism linkage mechanism were designed to serve as the CR’s climbing mechanism, which met the specific demands for climbing movements. The modified Kutzbach–Grübler formula and the screw theory were applied to calculate the DOFs of the CR. Then, the inverse and forward position analysis for the CR was derived. Furthermore, velocity and acceleration analysis of parallel mechanism were conducted and derived the Jacobian matrix, through which the singularity of parallel mechanism was analyzed. In order to evaluate kinematic performance of parallel mechanism, the motion/force transmission index (LTI) of workspace was calculated, which directed the followed dimensional optimization process. According to the optimization result, a prototype was constructed and a series of motion experiments were carried out to validate its climbing capability.
In this study, nine isonitrogenous experimental diets containing graded levels of carbohydrates (40 g/kg, 80 g/kg and 120 g/kg) and crude lipids (80 g/kg, 120 g/kg and 160 g/kg) were formulated in a two-factor (3 × 3) orthogonal design. A total of 945 mandarin fish with similar body weights were randomly assigned to twenty-seven tanks, and the experiment diets were fed to triplicate tanks twice daily for 10 weeks. Results showed that different dietary treatments did not significantly affect the survival rate and growth performance of mandarin fish. However, high dietary lipid and carbohydrate levels significantly decreased the protein content of the whole body and muscle of cultured fish. The lipid content of the whole body, liver and muscle all significantly increased with increasing levels of dietary lipid, while only liver lipid level was significantly affected by dietary carbohydrate level. Hepatic glycogen content increased significantly with increasing dietary carbohydrate levels. As to liver antioxidant capacity, malondialdehyde content increased significantly with increasing dietary lipid or carbohydrate content, and catalase activity showed an opposite trend. Superoxide dismutase activity increased significantly with increasing levels of dietary lipid but decreased first and then increased with increasing dietary carbohydrate levels. Additionally, the increase in both dietary lipid and carbohydrate levels resulted in a significant reduction in muscle hardness. Muscle chewiness, gumminess and shear force were only affected by dietary lipid levels and decreased significantly with increasing dietary lipid levels. In conclusion, considering all the results, the appropriate dietary lipids and carbohydrate levels for mandarin fish were 120 g/kg and 80 g/kg, respectively.
Identification of the origins of maritime-traded porcelain, though key to unravelling ancient production and trade dynamics, remains challenging. The authors present a pioneering micro-provenance analysis of Dehua-style porcelain from the late-twelfth-century Nanhai I shipwreck, recovered from the South China Sea. By pinpointing the origins of porcelain subtypes, including those bearing ink inscriptions, this study provides greater nuance in understanding spatial patterns of production and the impact of buyer/seller choice in maritime trade. The findings further highlight the effectiveness of portable x-ray fluorescence as a high-precision provenancing analysis and offer insights into porcelain production timelines in south-east China.
Compacted bentonite, used as an engineering barrier for permanent containment of high-level radioactive waste, is susceptible to mineral evolution resulting in compromise of the expected barrier performance due to alkaline–thermal chemical interaction in the near-field. To elucidate the mineral-evolution mechanisms within bentonite and the transformation of the nuclide adsorption properties during that period, experimental evolution of bentonite was conducted in a NaOH solution with a pH of 14 at temperatures ranging from 60 to 120°C. The results showed that temperature significantly affects the stability of minerals in bentonite under alkali conditions. The dissolution rate of fine-grained cristobalite in bentonite exceeds that of smectite, with the phase-transition products of smectite being temperature-dependent. As the temperature rises, smectite experiences a three-stage transformation: initially, at 60°C, the lattice structure thins due to the collapse of the octahedral sheets; at 80°C, the lattice disintegrates and reorganizes into a loose framework akin to albite; and by 100°C, it further reorganizes into a denser framework resembling analcime. The adsorption properties of bentonite exhibit a peak inflection point at 80°C, where the dissolution of the smectite lattice eliminates interlayer pores and exposes numerous polar or negatively charged sites which results in a decrease in specific surface area and an increase in cation exchange capacity and adsorption capacity of Eu3+. This research provides insights into the intricate evolution of bentonite minerals and the associated changes in radionuclide adsorption capacity, contributing to a better understanding of the stability of bentonite barriers and the effective long-term containment of nuclear waste.
The axisymmetric nozzle mechanism is the core part for thrust vectoring of aero engine, which contains complex rigid-flexible coupled multibody system with joints clearance and significantly reduces the efficiency in modeling and calculation, therefore the kinematics and dynamics analysis of axisymmetric vectoring nozzle mechanism based on deep neural network is proposed. The deep neural network model of the axisymmetric vector nozzle is established according to the limited training data from the physical dynamic model and then used to predict the kinematics and dynamics response of the axisymmetric vector nozzle. This study analyses the effects of joint clearance on the kinematics and dynamics of the axisymmetric vector nozzle mechanism by a data-driven model. It is found that the angular acceleration of the expanding blade and the driving force are mostly affected by joint clearance followed by the angle, angular velocity and position of the expanding blade. Larger joint clearance results in more pronounced fluctuations of the dynamic response of the mechanism, which is due to the greater relative velocity and contact force between the bushing and the pin. Since axisymmetric vector nozzles are highly complex nonlinear systems, traditional numerical methods of dynamics are extremely time-consuming. Our work indicates that the data-driven approach greatly reduces the computational cost while maintaining accuracy, and can be used for rapid evaluation and iterative computation of complex multibody dynamics of engine nozzle mechanism.
This study aimed to evaluate the association between vegetable intake and major depressive disorder (MDD) through cross-sectional analysis and bidirectional two-sample Mendelian randomisation (MR).
Design:
Cross-sectional analysis was conducted on National Health and Nutrition Examination Survey (NHANES) data from 2005 to 2018 and the corresponding Food Patterns Equivalents Database (FPED). Genome-wide association study (GWAS) data were obtained from UK Biobank and Psychiatric Genomics Consortium (PGC) dataset. Logistic regression analysis was performed after calculating the weights of the samples. Inverse variance weighted, MR-Egger and weighted median methods were used to evaluate the causal effects.
Setting:
A Patient Health Questionnaire-9 score ≥ 10 was considered to indicate MDD. Low vegetable intake was defined as < 2 cups of vegetables per day.
Participants:
30 861 U.S. adults from NHANES. The GWAS data sample size related to vegetable intake were comprised 448 651 and 435 435 cases respectively, while the GWAS data sample size associated with MDD encompassed 500 199 cases.
Results:
There were 23 249 (75·33 %) participants with low vegetable intake. The relationship between vegetable intake and MDD was nonlinear. In the multivariate model adjusted for sex, age, education, marital status, poverty income ratio, ethnicity and BMI, participants with low vegetable intake were associated with an increased risk of MDD (OR = 1·53, 95 % CI (1·32, 1·77), P < 0·001). Bidirectional MR showed no causal effects between vegetable intake and MDD.
Conclusions:
Cross-sectional analysis identified a significant relationship between vegetable intake and MDD, whereas the results from bidirectional two-sample MR did not support a causal role.
In a cross-sectional study of 20 Massachusetts long-term care (LTC) facilities, 19% (n = 449) of residents received antibiotics, with approximately one-third having a documented penicillin allergy. This documented allergy decreased the likelihood of prescribing beta-lactam antibiotics for infections. Improved penicillin allergy assessments and delabeling could optimize antibiotic prescribing in LTC settings.
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.
Gut microbiome changed dramatically during pregnancy and played important roles in metabolic status and reproductive endocrinology in mammals. However, investigating the functional microbiota and metabolites to improve the reproductive performance and understanding the host–microbiota interaction are still arduous tasks. This study aims to reveal the dominant strains and metabolites that improve the reproductive performance. We analyzed the fecal microbiota composition and metabolic status of higher yield Chinese pig breed Meishan (MS) sows and lower yield but widespread raised hybrid pig breed Landrace × Yorkshire (L × Y) sows on days 28 and 100 of gestation. Results showed that MS sows had higher litter sizes and steroid hormone level but lower short-chain fatty acid level in feces. Fecal metabolomic analysis revealed that MS sows showed a different metabolic status compared with L × Y sows both at early and late pregnancy, which enriched with phenylpropanoid biosynthesis, bile secretion, steroid hormone biosynthesis, and plant secondary metabolite biosynthesis. In addition, 16S rDNA and internal transcribed spacer sequencing indicated that MS sows showed different structures of microbiota community and exhibited an increased bacterial α-diversity but non-differential fungal α-diversity than L × Y sows. Moreover, we found that the litter sizes and bacteria including Sphaerochaeta, Solibacillus, Oscillospira, Escherichia–Shigella, Prevotellaceae_UCG-001, dgA-11_gut_group, and Bacteroides, as well as fungi including Penicillium, Fusarium, Microascus, Elutherascus, and Heydenia both have positive association to the significant metabolites at the early pregnancy. Our findings revealed significant correlation between reproductive performance and gut microbiome and provided microbial and metabolic perspective to improve litter sizes and steroid hormones of sows.
The Righi–Leduc heat flux generated by the self-generated magnetic field in the ablative Rayleigh–Taylor instability driven by a laser irradiating thin targets is studied through two-dimensional extended-magnetohydrodynamic simulations. The perturbation structure gets into a low magnetization state though the peak strength of the self-generated magnetic field could reach hundreds of teslas. The Righi–Leduc effect plays an essential impact both in the linear and nonlinear stages, and it deflects the total heat flux towards the spike base. Compared to the case without the self-generated magnetic field included, less heat flux is concentrated at the spike tip, finally mitigating the ablative stabilization and leading to an increase in the velocity of the spike tip. It is shown that the linear growth rate is increased by about 10% and the amplitude during the nonlinear stage is increased by even more than 10% due to the feedback of the magnetic field, respectively. Our results reveal the importance of Righi–Leduc heat flux to the growth of the instability and promote deep understanding of the instability evolution together with the self-generated magnetic field, especially during the acceleration stage in inertial confinement fusion.
This paper proposes a robust control approach to achieve high-precision trajectory tracking for permanent magnet linear motor (PMLM) system containing uncertainties by describing the dynamic model of PMLM based on the Udwadia-Kalaba equation combined with constraint-following method. First, the system of PMLM is described as a constraint-following system by adding the generalized constraint force to the unconstrained Udwadia-Kalaba equation of PMLM system. Second, the robust constraint-following controller is designed based on the proposed model after uncertainty analysis. Moreover, the proposed controller is verified to guarantee deterministic performance for uncertain systems: uniformly bounded and uniformly ultimately bounded. Third, the numerical simulation and experimental validation demonstrate the effectiveness of proposed controller. Finally, the design approach of constraint-following can be applied to other systems with uncertainties.
We aim to explore the association between caffeine and its metabolites and bone mineral density (BMD) in postmenopausal women. Data of 4286 postmenopausal women were extracted from the National Health and Nutrition Examination Survey (NHANES) database in 2009–14 in this cross-sectional study. Weighted linear regression and stepwise regression analyses were used to screen the covariates. Weighted univariate and multivariate linear regression analyses were used to explore the associations between caffeine and its metabolites and BMD. The evaluation index was estimated value (β) with 95 % confidence intervals (CIs). We also explored these relationships in age subgroups. The median BMD level among the eligible women was 0⋅7 gm/cm2. After adjusting for covariates including age, body mass index (BMI), fat intake, Calcium (Ca) supplements, diabetes mellitus (DM), angina pectoris, parental history of osteoporosis (OP), anti-osteoporosis therapy, poverty income ratio (PIR), vitamin D (VD) supplements, coronary heart disease (CHD), and previous fracture, we found that caffeine intake was not significantly related to the BMD reduction (β = 0, P = 0⋅135). However, caffeine metabolites, including MethyluricAcid3, MethyluricAcid7, MethyluricAcid37, Methylxanthine3, and Methylxanthine37, were negatively associated with the BMD (all P < 0⋅05). In addition, MethyluricAcid37 and Methylxanthine37 were negatively associated with BMD in females aged <65 years old, while MethyluricAcid3 and Methylxanthine3 were noteworthy in those who aged ≥65 years old. The roles of caffeine and its metabolites in BMD reduction and OP in postmenopausal women needed further exploration.
Research articles in the clinical and translational science literature commonly use quantitative data to inform evaluation of interventions, learn about the etiology of disease, or develop methods for diagnostic testing or risk prediction of future events. The peer review process must evaluate the methodology used therein, including use of quantitative statistical methods. In this manuscript, we provide guidance for peer reviewers tasked with assessing quantitative methodology, intended to complement guidelines and recommendations that exist for manuscript authors. We describe components of clinical and translational science research manuscripts that require assessment including study design and hypothesis evaluation, sampling and data acquisition, interventions (for studies that include an intervention), measurement of data, statistical analysis methods, presentation of the study results, and interpretation of the study results. For each component, we describe what reviewers should look for and assess; how reviewers should provide helpful comments for fixable errors or omissions; and how reviewers should communicate uncorrectable and irreparable errors. We then discuss the critical concepts of transparency and acceptance/revision guidelines when communicating with responsible journal editors.
A 60-d feeding trial was conducted to explore the potential regulatory effects of dietary Clostridium butyricum cultures (CBC) supplementation in high-carbohydrate diet (HCD) on carbohydrate utilisation, antioxidant capacity and intestinal microbiota of largemouth bass. Triplicate groups of largemouth bass (average weight 35·03 ± 0·04 g), with a destiny of twenty-eight individuals per tank, were fed low-carbohydrate diet and HCD supplemented with different concentration of CBC (0 %, 0·25 %, 0·50 % and 1·00 %). The results showed that dietary CBC inclusion alleviated the hepatic glycogen accumulation induced by HCD intake. Additionally, the expression of hepatic ampkα1 and insulin signaling pathway-related genes (ira, irb, irs, p13kr1 and akt1) increased linearly with dietary CBC inclusion, which might be associated with the activation of glycolysis-related genes (gk, pfkl and pk). Meanwhile, the expression of intestinal SCFA transport-related genes (ffar3 and mct1) was significantly increased with dietary CBC inclusion. In addition, the hepatic antioxidant capacity was improved with dietary CBC supplementation, as evidenced by linear decrease in malondialdehyde concentration and expression of keap1, and linear increase in antioxidant enzyme activities (total antioxidative capacity, total superoxide dismutase and catalase) and expression of antioxidant enzyme-related genes (nrf2, sod1, sod2 and cat). The analysis of bacterial 16S rRNA V3–4 region indicated that dietary CBC inclusion significantly reduced the enrichment of Firmicutes and potential pathogenic bacteria genus Mycoplasma but significantly elevated the relative abundance of Fusobacteria and Cetobacterium. In summary, dietary CBC inclusion improved carbohydrate utilization, antioxidant capacity and intestinal microbiota of largemouth bass fed HCD.
As space missions are needed in the future, the assembly volume of the space truss will become larger and larger, and the advancing path of the on-orbit cellular robot to the mission target will become more and more complicated. If the shortest moving path cannot be found in the truss environment, the climbing time of the robot on the truss will be greatly increased. To improve the speed of the cellular robot moving to the target point on the large space truss, this paper designs a cellular robot structure and configuration suitable for climbing on the truss and uses the improved sparrow algorithm to solve the problem of robot motion path planning. By establishing a mathematical model of the space truss, the improved sparrow algorithm is used to find the shortest path between the starting point and the end point in the truss environment. Finally, the data of this algorithm are compared with the data of other algorithms. The data results show that the improved sparrow algorithm is very effective in solving the optimal path of the space truss. The improved sparrow algorithm keeps the same optimal path compared with the standard sparrow algorithm, and the overall reaction time is increased by 51.60%, and the number of effective iterations is increased by about 13.87%.
The burden of mental disorders is increasing worldwide, thus, affecting society and healthcare systems. This study investigated the independent influences of age, period and cohort on the global prevalence of mental disorders from 1990 to 2019; compared them by sex; and predicted the future burden of mental disorders in the next 25 years.
Methods
The age-specific and sex-specific incidence of mental disorders worldwide was analysed according to the general analysis strategy used in the Global Burden of Disease Study in 2019. The incidence and mortality trends of mental disorders from 1990 to 2019 were evaluated through joinpoint regression analysis. The influences of age, period and cohort on the incidence of mental disorders were evaluated with an age–period–cohort model.
Results
From 1990 to 2019, the sex-specific age-standardized incidence and disability-adjusted life years (DALY) rate decreased slightly. Joinpoint regression analysis from 1990 to 2019 indicated four turning points in the male DALY rate and five turning points in the female DALY rate. In analysis of age effects, the relative risk (RR) of incidence and the DALY rate in mental disorders in men and women generally showed an inverted U-shaped pattern with increasing age. In analysis of period effects, the incidence of mental disorders increased gradually over time, and showed a sub-peak in 2004 (RR, 1.006 for males; 95% CI, 1.000–1.012; 1.002 for women, 0.997–1.008). Analysis of cohort effects showed that the incidence and DALY rate decreased in successive birth cohorts. The incidence of mental disorders is expected to decline slightly over the next 25 years, but the number of cases is expected to increase.
Conclusions
Although the age-standardized burden of mental disorders has declined in the past 30 years, the number of new cases and deaths of mental disorders worldwide has increased, and will continue to increase in the near future. Therefore, relevant policies should be used to promote the prevention and management of known risk factors and strengthen the understanding of risk profiles and incidence modes of mental disorders, to help guide future research on control and prevention strategies.
Edited by
Jong Chul Ye, Korea Advanced Institute of Science and Technology (KAIST),Yonina C. Eldar, Weizmann Institute of Science, Israel,Michael Unser, École Polytechnique Fédérale de Lausanne
In this chapter, we show that image-domain deep-learning-only reconstruction methods have intrinsic limitations in reconstruction accuracy and generalizability to individual patients owing to the regressive nature of the method. The combination of deep learning methods with analytic reconstruction methods or statistical IR methods offers a promising opportunity to achieve personalized reconstruction with improved reconstruction accuracy and enhanced generalizability.