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Although topographic mapping missions and geological surveys carried out by Autonomous Underwater Vehicles (AUVs) are becoming increasingly prevalent, the lack of precise navigation in these scenarios still limits their application. This paper deals with the problems of long-term underwater navigation for AUVs and provides new mapping techniques by developing a Bathymetric Simultaneous Localisation And Mapping (BSLAM) method based on graph SLAM technology. To considerably reduce the calculation cost, the trajectory of the AUV is divided into various submaps based on Differences of Normals (DoN). Loop closures between submaps are obtained by terrain matching; meanwhile, maximum likelihood terrain estimation is also introduced to build weak data association within the submap. Assisted by one weight voting method for loop closures, the global and local trajectory corrections work together to provide an accurate navigation solution for AUVs with weak data association and inaccurate loop closures. The viability, accuracy and real-time performance of the proposed algorithm are verified with data collected onboard, including an 8 km planned track recorded at a speed of 4 knots in Qingdao, China.
Sn–Sb alloy is an ideal candidate for lead-free solder; however, its performance has been inferior to that of Sn–Pb alloy. Here, the authors used ab initio molecular dynamics simulation to investigate the interatomic interaction in Sn–Sb-based lead-free solders. By calculating the electron density distribution, bond population, and partial density of states, the authors found that the Sn–Sb bonds are a mixture of nonlocalized metal and localized covalent bonds. The covalent bond between Sn and Sb is easy to break at higher temperatures, so Sn–Sb (6.4 wt%) had better fluidity than other studied Sn–Sb alloys. Furthermore, adding Cu or Ag into Sn–Sb alloys can decrease the strength of covalent bonds and stabilize the metal bonds, which improves the metallicity and wettability of the Sn–Sb–Cu and Sn–Sb–Cu–Ag systems when the temperature increases. These results are all in good agreement with experimental findings and have significant value for the development of new solder alloys.
In this perspective, the authors challenge the status quo of polymer innovation. The authors first explore how research in polymer design is conducted today, which is both time consuming and unable to capture the multi-scale complexities of polymers. The authors discuss strategies that could be employed in bringing together machine learning, data curation, high-throughput experimentation, and simulations, to build a system that can accurately predict polymer properties from their descriptors and enable inverse design that is capable of designing polymers based on desired properties.
A high energy electron density modulator from a high-intensity laser standing wave field is studied herein by investigating the ultrafast motion of electrons in the field. Electrons converge at the electric field antinodes, and the discrete electron density peaks modulated by the field located at the corresponding laser phases of kx = nπ, (n = 0, 1, 2, …), that is, the modulation period is 1/2 the wavelength of the individual laser. We also discussed the influence of the laser parameters such as laser intensity and waist size on the beam modulator. It is shown that a long interaction length (waist) or sufficiently high field intensity is essential for relativistic electron density modulation.
Understand the fundamental theory and practical design aspects of green and soft wireless communications networks with this expert text. It provides comprehensive and unified coverage of 5G physical layer design, as well as design of the higher and radio access layers and the core network, drawing on viewpoints from both academia and industry. Get to grips with the theory through authoritative discussion of information-theoretical results, and learn about fundamental green design trade-offs, software-defined network architectures, and energy efficient radio resource management strategies. Applications of wireless big data and artificial intelligence to wireless network design are included, providing an excellent design reference, and real-world examples of employment in software-defined 5G networks and energy saving solutions from wireless communications companies and cellular operators help to connect theory with practice. This is an essential text for graduate students, professionals and researchers.
Toxigenic Clostridium difficile (C. difficile) carriers represent an important source in the transmission of C. difficile infection (CDI) during hospitalisation, but its prevalence and mode in patients with hepatic cirrhosis are not well established. We investigated longitudinal changes in carriage rates and strain types of toxigenic C. difficile from admission to discharge among hepatic cirrhosis patients. Toxigenic C. difficile was detected in 104 (19.8%) of 526 hepatic cirrhosis patients on admission, and the carriage status changed in a portion of patients during hospitalisation. Approximately 56% (58/104) of patients lost the colonisation during their hospital stay. Among the remaining 48 patients who remained positive for toxigenic C. difficile, the numbers of patients who were positive at one, two, three and four isolations were 10 (55.6%), three (16.7%), two (11.1%) and three (16.7%), respectively. Twenty-eight patients retained a particular monophyletic strain at multiple isolations. The genotype most frequently identified was the same as that frequently identified in symptomatic CDI patients. A total of 25% (26/104) of patients were diagnosed with CDI during their hospital stay. Conclusions: Colonisation with toxigenic C. difficile strains occurs frequently in cirrhosis patients and is a risk factor for CDI.
The association between gestational weight gain (GWG) and exclusive breast-feeding (EBF) practices remains unclear. The present study evaluated the association between GWG and EBF in the first 6 months postpartum among primiparas in rural China.
The study population was drawn from a previous randomized controlled trial, and the relevant data were obtained from an electronic, population-based perinatal system and a monitoring system for child health care. GWG was categorized according to the guidelines of the Institute of Medicine.
Five rural counties in Hebei Province, China.
A total of 8449 primiparas.
Of the women, 58·7 % breast-fed exclusively for the first 6 months postpartum. Overweight women who gained either more or less weight than the recommended GWG tended to experience failure of EBF (OR=0·49; 95 % CI 0·34, 0·70; P<0·001 and OR=0·79; 95 % CI 0·63, 0·99; P=0·048, respectively). The same results were also observed among obese women; the OR for lower and greater weight gain were 0·28 (95 % CI 0·08, 0·94; P=0·04) and 0·55 (95 % CI 0·32, 0·95; P=0·03), respectively.
GWG that is below or above the Institute of Medicine recommendations is associated with EBF behaviour for the first 6 months postpartum in overweight and obese primiparas in rural China.
Conventional underwater navigation and positioning methods for Autonomous Underwater Vehicles (AUVs) either require the installation of acoustic arrays, which make AUVs less independent, or result in cumulative errors. This paper proposes an Underwater Terrain Positioning Method (UTPM) using Maximum a Posteriori (MAP) estimation and a Pulse Coupled Neural Network (PCNN) model for highly accurate navigation by AUVs. The PCNN model is used as a secondary discriminant to effectively identify pseudo-anchor points in flat terrain feature areas and to find the true positioning point, which significantly improves the matching positioning accuracy in these areas. Simulation results show that the proposed method effectively corrects Inertial Navigation System (INS) cumulative errors and has high matching positioning accuracy, which satisfy the requirements of AUV underwater navigation and positioning.