Aiming at the problems of poor coordination effect and low positioning accuracy of unmanned aerial vehicle (UAV) formation cooperative navigation in complex environments, an adaptive time-varying factor graph framework UAV formation cooperative navigation algorithm is proposed. The proposed algorithm uses the factor graph to describe the relationship between the navigation state of the UAV fleet and its own measurement information as well as the relative navigation information, and detects the relative navigation information at each moment by the double-threshold detection method to update the factor graph model at the current moment. And the robust estimation is combined with the factor graph, and the weight function measurements are used in the construction of the factor nodes for adaptive adjustment to make the system highly robust. The simulation results show that the proposed method realises the effective fusion of airborne multi-source sensing information and relative navigation information, which effectively improves the UAV formation cooperative navigation accuracy.

The unsteady flow physics of wind-turbine wakes under dynamic forcing conditions are critical to the modelling and control of wind farms for optimal power density. Unsteady forcing in the streamwise direction may be generated by unsteady inflow conditions in the atmospheric boundary layer, dynamic induction control of the turbine or streamwise surge motions of a floating offshore wind turbine due to floating-platform oscillations. This study seeks to identify the dominant flow mechanisms in unsteady wakes forced by a periodic upstream inflow condition. A theoretical framework for the problem is derived, which describes travelling-wave undulations in the wake radius and streamwise velocity. These dynamics encourage the aggregation of tip vortices into large structures that are advected along in the wake. Flow measurements in the wake of a periodically surging turbine were obtained in an optically accessible towing-tank facility, with an average diameter-based Reynolds number of 300 000 and with surge-velocity amplitudes of up to 40 % of the mean inflow velocity. Qualitative agreement between trends in the measurements and model predictions is observed, supporting the validity of the theoretical analyses. The experiments also demonstrate large enhancements in the recovery of the wake relative to the steady-flow case, with wake-length reductions of up to 46.5 % and improvements in the available power at 10 diameters downstream of up to 15.7 %. These results provide fundamental insights into the dynamics of unsteady wakes and serve as additional evidence that unsteady fluid mechanics can be leveraged to increase the power density of wind farms.

The prevalence of helminths in pigs was investigated in five rural communities situated on the embankment of Dongting Lake in Zhiyang County, Hunan Province, People's Republic of China, in an area known to be endemic for Schistosoma japonicum. The helminth prevalences identified on the basis of faecal egg count analysis were: Oesophagostomum spp. (86.7%), Ascaris suum (36.7%), Metastrongylus spp. (25.8%), Strongyloides spp. (25.8%), Trichuris suis (15.8%), Globocephalus spp. (6.7%), Gnathostoma spp. (4.2%), Schistosoma japonicum (5.0%) and Fasciola spp. (1.3%). Post mortem examinations of a small number of pigs depositing eggs of different helminth species revealed the presence of Oesophagostomum dentatum, O. quadrispinulatum, A. suum, Metastrongylus apri, M. pudendotectus, T. suis, G. hispidum and Ascarops dentata. Prevalences of all helminths, with the exception of Oesophagostomum spp., were higher in young pigs (< 8 months old) compared with adult pigs. Prevalences of trematodes were very low, especially for S. japonicum which had decreased dramatically compared with previous reports from this area of P.R. China, whereas prevalences of nematodes were generally in agreement with those reported from other Yangtze River Provinces. Results from helminth prevalence studies in pigs, conducted in other provinces of P.R. China between 1987 and 1997, are presented and discussed. It was concluded that a government helminth control programme, implemented in 1995 to control S. japonicum infection in pigs in Hunan Province, may have resulted in a greatly reduced prevalence of S. japonicum in pigs in this region.

Echinococcosis poses a significant threat to public health. The Chinese government has implemented prevention and control measures to mitigate the impact of the disease. By analyzing data from the Chinese Center for Disease Control and Prevention and the State Council of the People’s Republic of China, we found that implementation of these measures has reduced the infection rate by nearly 50% between 2004 to 2022 (from 0.3975 to 0.1944 per 100,000 person-years). Nonetheless, some regions still bear a significant disease burden, and lack of detailed information limites further evaluation of the effects on both alveolar and cystic echinococcosis. Our analysis supports the continuing implementation of these measures and suggests that enhanced wildlife management, case-based strategies, and surveillance systems will facilitate disease control.

The chemistry of Al transformation has been well documented, though little is known about the mechanisms of structural perturbation of Al precipitates by carbonates at a molecular level. The purpose of the present study was to investigate the structural perturbation of Al precipitates formed under the influence of carbonates. Initial carbonate/Al molar ratios (MRs) used were 0, 0.1, and 0.5 after aging for 32 days, then the samples were analyzed by X-ray absorption near edge structure spectroscopy (XANES), X-ray diffraction (XRD), Fourier-transform infrared absorption spectroscopy (FTIR), and chemical analysis. The XRD data were in accord with the FTIR results, which revealed that as the carbonate/Al MR was increased from 0 to 0.1, carbonate preferentially retarded the formation of gibbsite and had relatively little effect on the formation of bayerite. As the carbonate/Al MR was increased to 0.5, however, the crystallization of both gibbsite and bayerite was completely inhibited. The impact of carbonate on the nature of Al precipitates was also evident in the increase of adsorbed water and inorganic C contents with increasing carbonate/Al MR. The Al K- and L- edge XANES data provide the first evidence illustrating the change in the coordination number of Al from 6-fold to mixed 6- and 4-fold coordination in the structural network of short-range ordered (SRO) Al precipitates formed under the increasing perturbation of carbonate. The fluorescence yield spectra of the O K-edge show that the intensity of the peak at 534.5 eV assigned to σ* transitions of Al-O and O-H bonding decreased with increasing carbonate/Al MR. The XANES data, along with the evidence from XRD, FTIR, and chemical analysis showed clearly that carbonate caused the alteration of the coordination nature of the Al-O bonding through perturbation of the atomic bonding and structural configuration of Al hydroxides by complexation with Al in the SRO network of Al precipitates. The surface reactivity of an Al-O bond is related to its covalency and coordination geometry. The present findings were, therefore, of fundamental significance in understanding the low-temperature geochemistry of Al and its impacts on the transformation, transport, and fate of nutrients and pollutants in the ecosystem.

Transverse stimulated Raman scattering (TSRS) in potassium dihydrogen phosphate (KDP) and deuterated potassium dihydrogen phosphate (DKDP) plates for large-aperture, inertial confinement fusion (ICF)-class laser systems is a well-recognized limitation giving rise to parasitic energy conversion and laser-induced damage. The onset of TSRS is manifested in plates exposed to the ultraviolet section of the beam. TSRS amplification is a coherent process that grows exponentially and is distributed nonuniformly in the crystal and at the crystal surfaces. To understand the growth and spatial distribution of TSRS energy in various configurations, a modeling approach has been developed to simulate the operational conditions relevant to ICF-class laser systems. Specific aspects explored in this work include (i) the behavior of TSRS in large-aperture crystal plates suitable for third-harmonic generation and use as wave plates for polarization control in current-generation ICF-class laser system configurations; (ii) methods, and their limitations, of TSRS suppression and (iii) optimal geometries to guide future designs.

Planting patterns have significant effects on rice growth. Nonetheless, little is known about differences in annual crop yield and resource utilization among mechanized rice planting patterns in a rice–wheat cropping system. Field experiments were conducted from 2014 to 2017 using three treatments: pot seedling transplanting for rice and row sowing for wheat (PST-RS), carpet seedling transplanting for rice and row sowing for wheat (CST-RS) and row sowing for both crops (RS-RS). The results showed that, compared with RS-RS, PST-RS and CST-RS prolonged annual crop growth duration by 25–26 and 13–15 days, increased effective accumulated temperature by 399 and 212°C days and increased cumulative solar radiation by 454 and 228 MJ/m2 because of the earlier sowing of rice by 28 and 16 days in PST-RS and CST-RS, respectively. Compared with RS-RS, the annual crop yield of PST-RS and CST-RS increased by 3.1–3.8 and 2.0–2.6 t/ha, respectively, because of the increase in the number of spikelets/kernels per hectare, aboveground biomass, mean leaf area index and grain–leaf ratio. In addition, temperature production efficiency, solar radiation production efficiency and solar radiation use efficiency were higher in PST-RS, followed by CST-RS and RS-RS. These results suggest that mechanized rice planting patterns such as PST-RS increase annual crop production in rice–wheat cropping systems by increasing yield and solar energy utilization.

The past 50 yr of advances in weed recognition technologies have poised site-specific weed control (SSWC) on the cusp of requisite performance for large-scale production systems. The technology offers improved management of diverse weed morphology over highly variable background environments. SSWC enables the use of nonselective weed control options, such as lasers and electrical weeding, as feasible in-crop selective alternatives to herbicides by targeting individual weeds. This review looks at the progress made over this half-century of research and its implications for future weed recognition and control efforts; summarizing advances in computer vision techniques and the most recent deep convolutional neural network (CNN) approaches to weed recognition. The first use of CNNs for plant identification in 2015 began an era of rapid improvement in algorithm performance on larger and more diverse datasets. These performance gains and subsequent research have shown that the variability of large-scale cropping systems is best managed by deep learning for in-crop weed recognition. The benefits of deep learning and improved accessibility to open-source software and hardware tools has been evident in the adoption of these tools by weed researchers and the increased popularity of CNN-based weed recognition research. The field of machine learning holds substantial promise for weed control, especially the implementation of truly integrated weed management strategies. Whereas previous approaches sought to reduce environmental variability or manage it with advanced algorithms, research in deep learning architectures suggests that large-scale, multi-modal approaches are the future for weed recognition.

Patent data have been utilized for engineering design research for long because it contains massive amount of design information. Recent advances in artificial intelligence and data science present unprecedented opportunities to mine, analyse and make sense of patent data to develop design theory and methodology. Herein, we survey the patent-for-design literature by their contributions to design theories, methods, tools, and strategies, as well as different forms of patent data and various methods. Our review sheds light on promising future research directions for the field.