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This focused textbook demonstrates cutting-edge concepts at the intersection of machine learning (ML) and wireless communications, providing students with a deep and insightful understanding of this emerging field. It introduces students to a broad array of ML tools for effective wireless system design, and supports them in exploring ways in which future wireless networks can be designed to enable more effective deployment of federated and distributed learning techniques to enable AI systems. Requiring no previous knowledge of ML, this accessible introduction includes over 20 worked examples demonstrating the use of theoretical principles to address real-world challenges, and over 100 end-of-chapter exercises to cement student understanding, including hands-on computational exercises using Python. Accompanied by code supplements and solutions for instructors, this is the ideal textbook for a single-semester senior undergraduate or graduate course for students in electrical engineering, and an invaluable reference for academic researchers and professional engineers in wireless communications.
Few empirical studies have examined the collective impact of and interplay between individual factors on collaborative outcomes during major infectious disease outbreaks and the direct and interactive effects of these factors and their underlying mechanisms. Therefore, this study investigates the effects and underlying mechanisms of emergency preparedness, support and assurance, task difficulty, organizational command, medical treatment, and epidemic prevention and protection on collaborative outcomes during major infectious disease outbreaks.
Methods
A structured questionnaire was distributed to medical personnel with experience in responding to major infectious disease outbreaks. SPSS software was used to perform the statistical analysis. Structural equation modeling was conducted using AMOS 24.0 to analyze the complex relationships among the study variables.
Results
Organizational command, medical treatment, and epidemic prevention and protection had significant and positive impacts on collaborative outcomes. Emergency preparedness and supportive measures positively impacted collaborative outcomes during health crises and were mediated through organizational command, medical treatment, and epidemic prevention and protection.
Conclusions
The results underscore the critical roles of organizational command, medical treatment, and epidemic prevention and protection in achieving positive collaborative outcomes during health crises, with emergency preparedness and supportive measures enhancing these outcomes through the same key factors.
This paper presents an efficient trajectory planning method for a 4-DOF robotic arm designed for pick-and-place manipulation tasks. The method addresses several challenges, where traditional optimization approaches struggle with high dimensionality, and data-driven methods are costly to collect enough data. The proposed approach leverages Bézier curves for computationally efficient, smooth trajectory generation, minimizing abrupt changes in motion. When continuous solutions for the end-effector angle are unavailable, joint angles are interpolated using Bézier or Hermite interpolation. Additionally, we use custom metrics to evaluate deviation between the interpolated trajectory and the original trajectory, as well as the overall smoothness of the path. When a continuous solution exists, the trajectory is treated as a Gaussian process, where a prior factor is generated using the centerline. This prior is then combined with a smoothness factor to optimize the trajectory, ensuring it remains as smooth as possible within the feasible solution space through stochastic gradient descent. The method is evaluated through simulations in Nvidia Isaac Sim; results highlight the method’s suitability, and future work will explore enhancements in prior trajectory integration and smoothing techniques.
Hand, foot, and mouth disease (HFMD) shows spatiotemporal heterogeneity in China. A spatiotemporal filtering model was constructed and applied to HFMD data to explore the underlying spatiotemporal structure of the disease and determine the impact of different spatiotemporal weight matrices on the results. HFMD cases and covariate data in East China were collected between 2009 and 2015. The different spatiotemporal weight matrices formed by Rook, K-nearest neighbour (KNN; K = 1), distance, and second-order spatial weight matrices (SO-SWM) with first-order temporal weight matrices in contemporaneous and lagged forms were decomposed, and spatiotemporal filtering model was constructed by selecting eigenvectors according to MC and the AIC. We used MI, standard deviation of the regression coefficients, and five indices (AIC, BIC, DIC, R2, and MSE) to compare the spatiotemporal filtering model with a Bayesian spatiotemporal model. The eigenvectors effectively removed spatial correlation in the model residuals (Moran’s I < 0.2, p > 0.05). The Bayesian spatiotemporal model’s Rook weight matrix outperformed others. The spatiotemporal filtering model with SO-SWM was superior, as shown by lower AIC (92,029.60), BIC (92,681.20), and MSE (418,022.7) values, and higher R2 (0.56) value. All spatiotemporal contemporaneous structures outperformed the lagged structures. Additionally, eigenvector maps from the Rook and SO-SWM closely resembled incidence patterns of HFMD.
Amino acids are fundamental to sustaining life. They are crucial for intracellular processes, such as energy metabolism, biosynthesis of nucleotides, and maintenance of oxidative homeostasis. These processes ensure the proper functioning of cells (including immune cells) and organs. Many studies have demonstrated that immune cells, as key players in immune regulation, have distinct amino acid demands, and their rapid growth and activation are shaped by amino acid availability in their microenvironment. In particular, the proliferation, maturation, and functional responses of innate immune cells are closely linked to amino acid metabolism. The transport, sensing, and mobilization of amino acids drive metabolic reprogramming to support these processes. Therefore, this review focuses on the influence of amino acids on the fate and function of immune cells across development, homeostasis, activation, and effector phases, highlighting the underlying mechanisms. It provides a scientific basis for improving disease resistance and production efficiency in animals.
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 ≥ 300 µg/l and SIC > 90 µg/l groups. UIC ≥ 300 µg/l and SIC > 90 µg/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.
The dissolution kinetics occurring on clay minerals are influenced by various factors, including pH, temperature and mineral lattice structure. However, the influence of the surfactant is rarely studied. In the present work, cationic surfactants were investigated in terms of the dissolution of clay minerals in acidic environments. Kaolinite was selected as the representative clay mineral. The cationic surfactant inhibited the dissolution of clay minerals because it limited the attack of H+ on the kaolinite surface and then inhibited the dissolution of kaolinite by modifying the hydrophilicity of the kaolinite surface towards hydrophobicity. The inhibition ability of the surfactant might be related to its molecular structure and the type of acid used in dissolution experiments.
Fine particulate matter (PM2·5) is a known risk factor for heart failure (HF), while plant-based dietary patterns may help reduce HF risk. This study examined the combined impact of PM2·5 exposure and a plant-based diet on HF incidence. A total of 190 092 participants from the UK Biobank were included in this study. HF cases were identified through linkage to the UK National Health Services register, with follow-up lasting until October 2022 in England, August 2022 in Scotland and May 2022 in Wales. Annual mean PM2·5 concentration was obtained using a land use regression model, while the healthful plant-based diet index (hPDI) was calculated using the Oxford WebQ tool based on two or more 24-hour dietary assessments of seventeen major food groups. Cox proportional hazard models assessed the associations of PM2·5 and hPDI with HF risk, and interactions were evaluated on additive and multiplicative scales. During a median of 13·4-year follow-up, 4351 HF cases were recorded. Participants in the highest PM2·5 tertile had a 23 % increased HF risk (hazard ratio: 1·23, 95 % CI: 1·14, 1·32) compared with those in the lowest tertile. Moderate or high hPDI was associated with reduced HF risk relative to low hPDI. The lowest HF risk was observed in individuals with high hPDI and low PM2·5 exposure, underscoring the protective role of a plant-based diet, particularly in areas with lower PM2·5 levels. A healthy plant-based diet may mitigate HF risk, especially in populations exposed to lower PM2·5 levels.
Cleavers, an annual or winter annual broadleaf weed in the Rubiaceae family, has become troublesome in the wheat fields of the Huang-Huai-Hai region in China due to its herbicide resistance. In North America the common name of the plant is stickwilly; in China it known as cleavers. Four populations of cleavers (JS-15, SD-10, JS-22, and AH-20) were collected from wheat fields in Jiangsu, Shandong, and Anhui provinces, where the plant was not being controlled with applications of florasulam. The aims of this study were to identify the herbicide resistance patterns and investigate the mechanism underlying florasulam resistance. Whole-plant dose-response experiments revealed a notable variation in the degree of resistance exhibited by three specific populations toward florasulam, in comparison to the most sensitive population (S and AH-9), with the highest resistance index reaching 841.4. A gene-sequencing assay for acetolactate synthase (ALS) found that plants that were resistant to ALS from the JS-15, JS-22, and AH-20 populations had a Trp-574-Leu mutation, while no known ALS resistance mutations were discovered in SD-10 plants. In vitro ALS enzyme activity assays also indicated that the extractable ALS from JS-15, JS-22, and AH-20 plants was greatly resistant to florasulam relative to plants that are susceptible. Additionally, according to the resistance rating system, all resistant populations were susceptible to carfentrazone-ethyl + MCPA-sodium and bipyrazone + fluroxypyr-methyl. AH-20, JS-15, and JS-22 exhibited resistance to selected ALS, 4-hydroxyphenylpyruvate dioxygenase (HPPD), and photosystem II (PS II) complex inhibitors, demonstrating RR and RRR resistance profiles, whereas AH-9 displayed sensitivity to virtually all tested agents. The SD-10 population, on the other hand, exhibited RR and RRR resistance to HPPD and PS II inhibitors, and sensitivity to tribenuron-methyl. These findings indicate that a target site–based mechanism drives resistance to the ALS inhibitor florasulam in populations of cleavers, but nontarget site resistance may also have contributed to resistance, but this was not investigated. Other herbicides with different sites of action were tested and were active against cleavers.
A modeling method of multi-objective optimization design for parallel mechanisms (PMs) is proposed, whose implementation is illustrated with 2RPU-RPS mechanism as an example. The orientation of biased output axis on moving platform is depicted by spherical attitude angles, and its kinematic model is deduced through vector method. With screw theory as mathematic tool, a comprehensive evaluation method of kinematic performance for PM is established. On this basis, the expensive constrained multi-objective optimization model of dimensional parameters for the discussed mechanism is constructed. The NSDE-II algorithm, formed by replacing the genetic algorithm operators in non-dominated sorting genetic algorithm II (NSGA-II) with DE operators, is utilized to solve this multi-objective optimization problem, thus obtaining multiple Pareto optimal solutions with engineering application significance, which proves the feasibility and effectiveness of the proposed modeling method and algorithm. Moreover, the normalization coverage space and the minimum adjacent vector angle are proposed to evaluate the computational performance of NSDE-II. Finally, the potential engineering application value for the optimized 2RPU-RPS PM is presented.
The school–vacation cycle may have impacts on the psychological states of adolescents. However, little evidence illustrates how transition from school to vacation impacts students’ psychological states (e.g. depression and anxiety).
Aims
To explore the changing patterns of depression and anxiety symptoms among adolescent students within a school–vacation transition and to provide insights for prevention or intervention targets.
Method
Social demographic data and depression and anxiety symptoms were measured from 1380 adolescent students during the school year (age: 13.8 ± 0.88) and 1100 students during the summer vacation (age: 14.2 ± 0.93) in China. Multilevel mixed-effect models were used to examine the changes in depression and anxiety levels and the associated influencing factors. Network analysis was used to explore the symptom network structures of depression and anxiety during school and vacation.
Results
Depression and anxiety symptoms significantly decreased during the vacation compared to the school period. Being female, higher age and with lower mother's educational level were identified as longitudinal risk factors. Interaction effects were found between group (school versus vacation) and the father's educational level as well as grade. Network analyses demonstrated that the anxiety symptoms, including ‘Nervous’, ‘Control worry’ and ‘Relax’ were the most central symptoms at both times. Psychomotor disturbance, including ‘Restless’, ‘Nervous’ and ‘Motor’, bridged depression and anxiety symptoms. The central and bridge symptoms showed variation across the school vacation.
Conclusions
The school–vacation transition had an impact on students’ depression and anxiety symptoms. Prevention and intervention strategies for adolescents’ depression and anxiety during school and vacation periods should be differentially developed.
Chapter 17 discusses China’s Criminal Procedure Law, which provides a general cooperation obligation for all relevant entities, including service providers. As collecting data from service providers has become increasingly important in criminal investigations, the past decade has witnessed a certain number of laws, regulations and explanatory documents adopted to specify service providers’ cooperation obligations. This chapter systematically studies these provisions and summarizes the rich content of service providers’ cooperation obligations relating to collection of historical and real-time data in criminal investigations as well as in their daily operation. It also discusses future improvements to the current legislations, namely more protection of sensitive data, due process in evidence collection and criminal liability for service providers when cooperation obligations cannot be fulfilled. Based on China’s position of respecting data sovereignty, China requires data to be stored locally. Foreign LEAs can obtain data from Chinese service providers only via mutual legal assistance, and service providers in China are prohibited from providing data directly to foreign LEAs.
Robot pick-and-place for unknown objects is still a very challenging research topic. This paper proposes a multi-modal learning method for robot one-shot imitation of pick-and-place tasks. This method aims to enhance the generality of industrial robots while reducing the amount of data and training costs the one-shot imitation method relies on. The method first categorizes human demonstration videos into different tasks, and these tasks are classified into six types to symbolize as many types of pick-and-place tasks as possible. Second, the method generates multi-modal prompts and finally predicts the action of the robot and completes the symbolic pick-and-place task in industrial production. A carefully curated dataset is created to complement the method. The dataset consists of human demonstration videos and instance images focused on real-world scenes and industrial tasks, which fosters adaptable and efficient learning. Experimental results demonstrate favorable success rates and loss results both in simulation environments and real-world experiments, confirming its effectiveness and practicality.
In this paper, we consider the discrete Orlicz chord Minkowski problem and solve the existence of this problem, which is the nontrivial extension of the discrete $L_{p}$ chord Minkowski problem for ${0<p<1}$.
The effects of the evolution of vortices on the aeroacoustics generated by a hovering wing are numerically investigated by using a hybrid method of an immersed boundary–finite difference method for the three-dimensional incompressible flows and a simplified model based on the Ffowcs Williams-Hawkings acoustic analogy. A low-aspect-ratio ($AR=1.5$) rectangular wing at low Reynolds ($Re=1000$) and Mach ($M=0.04$) numbers is investigated. Based on the simplified model, the far-field acoustics is shown to be dominated by the time derivative of the pressure on the wing surface. Results show that vortical structure evolution in the flow fields, which is described by the divergence of the convection term of the incompressible Navier–Stokes equations in a body-fixed reference frame, determines the time derivative of the surface pressure and effectively the far-field acoustics. It dominates over the centrifugal acceleration and Coriolis acceleration terms in determining the time derivative of the surface pressure. The position of the vortex is also found to affect the time derivative of the surface pressure. A scaling analysis reveals that the vortex acoustic source is scaled with the cube of the flapping frequency.
The present study offers a twofold contribution on counter-gradient transport (CGT) of turbulent scalar flux. First, by examining turbulent scalar mixing through synchronized particle image velocimetry and planar laser-induced fluorescence on an inclined jet in cross-flow, we clarify the previously unexplained phenomenon of CGT, revealing key flow structures, their spatial distribution and modelling implications. Statistical analysis identifies two distinct CGT regions: local cross-gradient transport in the windward shear layer and non-local effects near the wall after injection. These behaviours are driven by specific flow structures, namely Kelvin–Helmholtz vortices (local) and wake vortices (non-local), suggesting that scalar flux can be decomposed into a gradient-type term for gradient diffusion and a term for large-eddy stirring. Second, we propose a new approach for reconstruction of turbulent mean flow and scalar fields using continuous adjoint data assimilation (DA). By rectifying model-form errors through anisotropic correction under observational constraints, our DA model minimizes discrepancies between experimental measurements and numerical predictions. As expected, the introduced forcing term effectively identifies regions where traditional models fall short, particularly in the jet centreline and near-wall regions, thereby enhancing the accuracy of the mean scalar field. These enhancements occur not only within the observation region but also in unseen regions, underscoring present DA approach's reliability and practicality for reproducing mean flow behaviours from limited data. These findings lay a solid foundation for adjoint-based model-consistent data-driven methods, offering promising potential for accurately predicting complex flow scenarios like film cooling.
Flow control of a low-aspect-ratio flat-plate heaving wing at an average angle of attack of $10^{\circ }$ by a steady-blowing jet is numerically studied by using a feedback immersed boundary–lattice Boltzmann method. Blowing jets at the leading edge, mid-chord and trailing edge are considered. The wing enjoys the highest lift production with the trailing-edge downstream blowing jet, which improves the average lift by 50.0 % at $Re = 1000$ and 22.9 % at $Re = 5000$ through the enhancement of the tip vortex circulation caused by the increase in the mass flux of the shear layer at the wing tips. This increase in mass flux decreases as $Re$ increases from 1000 to 5000 due to its self-limiting mechanism. A mid-chord vertical blowing jet induces a middle vortex which enhances the lift production but the enhancement is smaller than that of trailing-edge downstream blowing jet. Other jet arrangements do not significantly increase the lift coefficient, but the mid-chord upstream blowing jet experiences a significant reduction in the drag coefficient, leading to an increase of 50.6 % in the average lift-to-drag ratio. The effectiveness of the flow control is not significantly affected by the aspect ratio.
Superhydrophobic (SHPo) surfaces can capture a thin layer of air called a plastron under water to reduce skin friction. Although a ~30 % drag reduction has been recently reported with longitudinal micro-trench SHPo surfaces under a boat and in a towing tank, the results lacked the consistency to establish a clear trend. Designed based on Yu et al. (J. Fluid Mech, vol. 962, 2023, A9), this work develops and tests a series of high-performance SHPo surface coupons that can sustain a pinned plastron underneath a passenger motorboat revamped to reach 14 knots. Importantly, plastrons in a pinned state, not just their existence, are confirmed during flow experiments for the first time. All the drag-reduction data measured on different longitudinal micro-trenches are found to collapse if plotted against slip length in wall units. In comparison, aligned posts and transverse trenches show less and little drag reduction, respectively, confirming the adverse effect of the spanwise slip in turbulent flows. This report not only verifies SHPo surfaces can provide a consistent drag reduction at high speeds in open sea but also shows that one may predict the amount of drag reduction in turbulent flows using the physical slip length obtained for Stokes flows.
Three new species of Gyrodactylus were identified from the body surface of the Triplophysa species from the Qinghai-Tibet Plateau, Gyrodactylus triplorienchili n. sp. on Triplophysa orientalis in northern Tibet, G. yellochili n. sp. on T. sellaefer and T. scleroptera and G. triplsellachili n. sp. on T. sellaefer and T. robusta in Lanzhou Reach of the Yellow River. The three newly identified species share the nemachili group species’ characteristic of having inturning hamulus roots. Gyrodactylus triplorienchili n. sp. shared a quadrate sickle heel and a thin marginal hook sickle, two morphological traits that set them apart from G. yellochili n. sp. However, they may be identified by the distinct shapes of the sickle base and marginal hook sickle point. Gyrodactylus triplsellachili n. sp. had much larger opisthaptoral hard part size than the other two species. The three new species show relatively low interspecific differences of 2.9–5.3% p-distance for ITS1-5.85-ITS2 rDNA sequences. Phylogenetic analysis indicated that the three new species formed a well-supported monophyletic group (bp = 99) with the other nemachili group species.
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.