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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.
Le Liang, Southeast University, Nanjing,Shi Jin, Southeast University, Nanjing,Hao Ye, University of California, Santa Cruz,Geoffrey Ye Li, Imperial College of Science, Technology and Medicine, London
Le Liang, Southeast University, Nanjing,Shi Jin, Southeast University, Nanjing,Hao Ye, University of California, Santa Cruz,Geoffrey Ye Li, Imperial College of Science, Technology and Medicine, London
Le Liang, Southeast University, Nanjing,Shi Jin, Southeast University, Nanjing,Hao Ye, University of California, Santa Cruz,Geoffrey Ye Li, Imperial College of Science, Technology and Medicine, London
Le Liang, Southeast University, Nanjing,Shi Jin, Southeast University, Nanjing,Hao Ye, University of California, Santa Cruz,Geoffrey Ye Li, Imperial College of Science, Technology and Medicine, London
Le Liang, Southeast University, Nanjing,Shi Jin, Southeast University, Nanjing,Hao Ye, University of California, Santa Cruz,Geoffrey Ye Li, Imperial College of Science, Technology and Medicine, London
Le Liang, Southeast University, Nanjing,Shi Jin, Southeast University, Nanjing,Hao Ye, University of California, Santa Cruz,Geoffrey Ye Li, Imperial College of Science, Technology and Medicine, London
Le Liang, Southeast University, Nanjing,Shi Jin, Southeast University, Nanjing,Hao Ye, University of California, Santa Cruz,Geoffrey Ye Li, Imperial College of Science, Technology and Medicine, London
Le Liang, Southeast University, Nanjing,Shi Jin, Southeast University, Nanjing,Hao Ye, University of California, Santa Cruz,Geoffrey Ye Li, Imperial College of Science, Technology and Medicine, London
Le Liang, Southeast University, Nanjing,Shi Jin, Southeast University, Nanjing,Hao Ye, University of California, Santa Cruz,Geoffrey Ye Li, Imperial College of Science, Technology and Medicine, London
Le Liang, Southeast University, Nanjing,Shi Jin, Southeast University, Nanjing,Hao Ye, University of California, Santa Cruz,Geoffrey Ye Li, Imperial College of Science, Technology and Medicine, London
Le Liang, Southeast University, Nanjing,Shi Jin, Southeast University, Nanjing,Hao Ye, University of California, Santa Cruz,Geoffrey Ye Li, Imperial College of Science, Technology and Medicine, London
Le Liang, Southeast University, Nanjing,Shi Jin, Southeast University, Nanjing,Hao Ye, University of California, Santa Cruz,Geoffrey Ye Li, Imperial College of Science, Technology and Medicine, London
Coherent combining of several low-energy few-cycle beams offers a reliable and feasible approach to producing few-cycle laser pulses with energies exceeding the multi-joule level. However, time synchronization and carrier-envelope phase difference (ΔCEP) between pulses significantly affect the temporal waveform and intensity of the combined pulse, requiring precise measurement and control. Here, we propose a concise optical method based on the phase retrieval of spectral interference and quadratic function symmetry axis fitting to simultaneously measure the time synchronization and ΔCEP between few-cycle pulses. The control precision of our coherent beam combining system can achieve a time delay stability within 42 as and ΔCEP measurement precision of 40 mrad, enabling a maximum combining efficiency of 98.5%. This method can effectively improve the performance and stability of coherent beam combining systems for few-cycle lasers, which will facilitate the obtaining of high-quality few-cycle lasers with high energy.
The Mamyshev oscillator (MO) is well-known for its high modulation depth, which provides an excellent platform for achieving both high average power and short pulse durations. However, this characteristic typically limits the high-repetition-rate pulse generation. Herein, we construct an MO that achieves a gigahertz (GHz) repetition rate through harmonic mode-locking. The laser can reach up to the 93rd order, which corresponds to the repetition rate of 1.6 GHz. The maximum achieved output average power is 3 W at a repetition rate of 1.2 GHz (69th order), with the corresponding pulse duration compressed to 51 fs. To our knowledge, this is the first time that the GHz repetition rate in an MO has been obtained simultaneously with the recorded average power and pulse duration.
Laser-driven inertial confinement fusion (ICF) diagnostics play a crucial role in understanding the complex physical processes governing ICF and enabling ignition. During the ICF process, the interaction between the high-power laser and ablation material leads to the formation of a plasma critical surface, which reflects a significant portion of the driving laser, reducing the efficiency of laser energy conversion into implosive kinetic energy. Effective diagnostic methods for the critical surface remain elusive. In this work, we propose a novel optical diagnostic approach to investigate the plasma critical surface. This method has been experimentally validated, providing new insights into the critical surface morphology and dynamics. This advancement represents a significant step forward in ICF diagnostic capabilities, with the potential to inform strategies for enhancing the uniformity of the driving laser and target surface, ultimately improving the efficiency of converting laser energy into implosion kinetic energy and enabling ignition.
In contemporary neuroimaging studies, it has been observed that patients with major depressive disorder (MDD) exhibit aberrant spontaneous neural activity, commonly quantified through the amplitude of low-frequency fluctuations (ALFF). However, the substantial individual heterogeneity among patients poses a challenge to reaching a unified conclusion.
Methods
To address this variability, our study adopts a novel framework to parse individualized ALFF abnormalities. We hypothesize that individualized ALFF abnormalities can be portrayed as a unique linear combination of shared differential factors. Our study involved two large multi-center datasets, comprising 2424 patients with MDD and 2183 healthy controls. In patients, individualized ALFF abnormalities were derived through normative modeling and further deconstructed into differential factors using non-negative matrix factorization.
Results
Two positive and two negative factors were identified. These factors were closely linked to clinical characteristics and explained group-level ALFF abnormalities in the two datasets. Moreover, these factors exhibited distinct associations with the distribution of neurotransmitter receptors/transporters, transcriptional profiles of inflammation-related genes, and connectome-informed epicenters, underscoring their neurobiological relevance. Additionally, factor compositions facilitated the identification of four distinct depressive subtypes, each characterized by unique abnormal ALFF patterns and clinical features. Importantly, these findings were successfully replicated in another dataset with different acquisition equipment, protocols, preprocessing strategies, and medication statuses, validating their robustness and generalizability.
Conclusions
This research identifies shared differential factors underlying individual spontaneous neural activity abnormalities in MDD and contributes novel insights into the heterogeneity of spontaneous neural activity abnormalities in MDD.
In response to the complex and challenging task of long-distance inspection of small-diameter and variable-diameter mine holes, this paper presents a design for an adaptive small-sized mine hole robot. First, focusing on the environment of small-diameter mine holes, the paper analyzes the robot’s functions and overall structural framework. A two-wheeled wall-pressing robot with good mobility, arranged in a straight line, is designed. Furthermore, an adaptive variable-diameter method is devised, which involves constructing an adaptive variable-diameter model and proposing a control method based on position and force estimators, enabling the robot to perceive external forces. Lastly, to verify the feasibility of the structural design and adaptive variable-diameter method, performance tests and analyses are conducted on the robot’s mobility and adaptive variable-diameter capabilities. Experimental results demonstrate that the robot can move within small-diameter mine holes at any inclination angle, with a maximum horizontal crawling speed of 3.96 m/min. By employing the adaptive variable-diameter method, the robot can smoothly navigate convex platform obstacles and slope obstacles in mine holes with diameters ranging from 70 mm to 100 mm, achieving the function of adaptive variable-diameter within 2 s. Thus, it can meet the requirements of moving inside mine holes under complex conditions such as steep slopes and small and variable diameters.
Parallel manipulators with flexible morphing platform (FMP) provide potential solution in various application fields, such as shape-morphing underwater robot, deformable wings, and human–machine interfaces. However, there is still lack of effective approach for the design and analysis of such novel type of parallel manipulator. In this article, a 9-UPS redundant actuation parallel manipulator with flexible morphing moving platform is designed as a representative of this kind of manipulator. Correspondingly, a deformation estimation and shape control approach for the FMP is presented. The proposed deformation estimation approach is designed based on the bending energy, which can achieve high calculation efficiency and avoid complex mechanical definition and calculation. And the proposed shape control approach is realized by utilizing a nonrigid ICP match algorithm, which can continuously deform the morphing platform to an arbitrary target surface. A prototype of the 9-UPS parallel manipulator is fabricated and analyzed as verification. The experiment results show that the proposed approach offers a promising avenue for the deformation estimation and shape control of the morphing platform.
China is still among the 30 high-burden tuberculosis (TB) countries in the world. Few studies have described the spatial epidemiological characteristics of pulmonary TB (PTB) in Jiangsu Province. The registered incidence data of PTB patients in 95 counties of Jiangsu Province from 2011 to 2021 were collected from the Tuberculosis Management Information System. Three-dimensional spatial trends, spatial autocorrelation, and spatial–temporal scan analysis were conducted to explore the spatial clustering pattern of PTB. From 2011 to 2021, a total of 347,495 newly diagnosed PTB cases were registered. The registered incidence rate of PTB decreased from 49.78/100,000 in 2011 to 26.49/100,000 in 2021, exhibiting a steady downward trend (χ2 = 414.22, P < 0.001). The average annual registered incidence rate of PTB was higher in the central and northern regions. Moran’s I indices of the registered incidence of PTB were all >0 (P< 0.05) except in 2016, indicating a positive spatial correlation overall. Local autocorrelation analysis showed that ‘high–high’ clusters were mainly distributed in northern Jiangsu, and ‘low–low’ clusters were mainly concentrated in southern Jiangsu. The results of this study assist in identifying settings and locations of high TB risk and inform policy-making for PTB control and prevention.