An online pattern recognition method of lower limb movements is proposed based on the personalized surface electromyography (sEMG) signals, and the corresponding experimental researches are performed in the rehabilitation training. Further, a wireless wearable acquisition instrument is used. Based on this instrument, a host computer for the personal online recognition and real-time control of rehabilitation training is developed. Three time-domain features and two features in the nonlinear dynamics are selected as the joint set of the characteristic values for the sEMG signals. Then a particle swarm optimization (PSO) algorithm is used to optimize the feature channels, and a k-nearest neighbor (KNN) algorithm and the extreme learning machine (ELM) algorithm are combined to classify and recognize individual sample data. Based on the multi-pose lower limb rehabilitation robot, the real-time motion recognition and the corresponding rehabilitation training are carried out by using the online personalized classifier. The experimental results of eight subjects indicate that it takes only 6 min to build an online personalized classifier for the four types of the lower limb movements. The recognition between switches of different rehabilitation training movements is timely and accurate, with an average recognition accuracy of more than 95%. These results demonstrate that this system has a strong practicability.

A novel data-driven modal analysis method, reduced-order variational mode decomposition (RVMD), is proposed, inspired by the Hilbert–Huang transform and variational mode decomposition (VMD), to resolve transient or statistically non-stationary flow dynamics. First, the form of RVMD modes (referred to as an ‘elementary low-order dynamic process’, ELD) is constructed by combining low-order representation and the idea of intrinsic mode function, which enables the computed modes to characterize the non-stationary properties of space–time fluid flows. Then, the RVMD algorithm is designed based on VMD to achieve a low-redundant adaptive extraction of ELDs in flow data, with the modes computed by solving an elaborate optimization problem. Further, a combination of RVMD and Hilbert spectral analysis leads to a modal-based time-frequency analysis framework in the Hilbert view, providing a potentially powerful tool to discover, quantify and analyse the transient and non-stationary dynamics in complex flow problems. To provide a comprehensive evaluation, the computational cost and parameter dependence of RVMD are discussed, as well as the relations between RVMD and some classic modal decomposition methods. Finally, the virtues and utility of RVMD and the modal-based time-frequency analysis framework are well demonstrated via two canonical problems: the transient cylinder wake and the planar supersonic screeching jet.

People search can be reformulated as submodular maximization problems to achieve solutions with theoretical guarantees. However, the number of submodular function outcome is $2^N$ from N sets. Compressing functions via nonlinear Fourier transform and spraying out sets are two ways to overcome this issue. This research proposed the submodular deep compressed sensing of convolutional sparse coding (SDCS-CSC) and applied the Topological Fourier Sparse Set (TFSS) algorithms to solve people search problems. The TFSS is based on topological and compressed sensing techniques, while the CSC is based on DCS techniques. Both algorithms enable an unmanned aerial vehicle to search for the people in environments. Experiments demonstrate that the algorithms can search for the people more efficiently than the benchmark approaches. This research also suggests how to select CSC or TFSS algorithms for different search problems.

OBJECTIVES/SPECIFIC AIMS: The aim of this study is to determine whether quantitative measures of knee structures including effusion, bone marrow lesions, cartilage, and meniscal damage can improve upon an existing model of demographic and clinical characteristics to classify accelerated knee osteoarthritis (AKOA). METHODS/STUDY POPULATION: We conducted a case-control study using data from baseline and four annual follow-up visits from the osteoarthritis initiative. Participants had no radiographic knee osteoarthritis (KOA) at baseline. AKOA is defined as progressing from no KOA to advance-stage KOA in at least 1 knee within 48 months. AKOA knees were matched 1:1 based on sex to (1) participants who did not develop KOA within 48 months and (2) participants who developed KOA but not AKOA. Analyses were person based. Classification and regression tree analysis was used to determine the important variables and percent of variance explained. RESULTS/ANTICIPATED RESULTS: A previous classification and regression tree analysis found that age, BMI, serum glucose, and femorotibial angle explained 31% of the variability between those who did and did not develop AKOA. Including structural measurements as candidate variables yielded a model that included effusion, BMI, serum glucose, cruciate ligament degeneration and coronal slope and explained 39% of the variability. DISCUSSION/SIGNIFICANCE OF IMPACT: Knee structural measurements improve classification of participants who developed AKOA Versus those who did not. Further research is needed to better classify patients at risk for AKOA.

In a model where investors disagree about the fundamentals of two stocks, the state-price density depends on investor disagreements for both stocks, especially the larger stock. This implies that disagreement among investors in a large firm has a spillover effect on the pricing of other stocks owned by these investors. The pricing effects of investor disagreements crucially depend on the average belief biases. Empirical findings support the novel model prediction of a disagreement spillover effect and help reconcile some mixed evidence in the literature.

A novel synthetic air data estimation method without using air data sensors is presented, and the method only relies on the information from the Navigation System (NS) and Flight Control System (FCS). The aircraft's aerodynamic model is also required to make a connection between the FCS control parameters and the NS measurements. The airspeed, angle of attack and sideslip, angular velocity and wind speed are defined as state vectors, and state equations are established through the aircraft's aerodynamic model and dynamics. Linear velocity and angular velocity provided by the navigation system are considered as the measurement vector. To deal with variable wind fields, a novel Initialised Three-step Extended Kalman Filter (ITEKF), which considers the wind speed as an unknown input, is developed to track the variation of wind speed. Simulation results based on a Generic Hypersonic Vehicle (GHV) model are presented and compared with an existing method. Factors affecting the method's accuracy include the navigation system accuracy and the aerodynamic model error, are also discussed.

A new ternary compound Al5NdNi2 was prepared by melting a stoichiometric mixture of aluminum, neodymium, and nickel in an arc furnace and annealing in vacuum. The crystal structure of Al5NdNi2 was studied by X-ray powder diffraction technique and Rietveld analysis. All diffraction lines of Al5NdNi2 were indexed, and the lattice parameters were refined with an orthorhombic structure type of space group Immm (No.71) using Rietveld analysis program DBWS-9807. The lattice parameters are presented, a = 7.0508(1) Å, b = 9.5690(1) Å, c = 3.9792(1) Å, V = 268.47 Å3, Z = 2, ρ = 4.91 g cm−3, and RIR = 1.23.

Surface elevation data for sea ice in the northwesternty - Weddell Sea, Antarctica, collected by a helicopter-borne laser altimeter during the Winter Weddell Outflow Study 2006, were used to estimate the form drag on pressure ridges and its contribution to the total wind drag, and the air-ice drag coefficient at a reference height of 10 m under neutral stability conditions (C dn(10)). This was achieved by partitioning the total wind drag into two components: form drag on pressure ridges and skin drag over rough sea-ice surfaces. The results reveal that for the compacted ice field, the contribution of form drag on pressure ridges to the total wind drag increases with increasing ridging intensity Ri (where Ri is the ratio of mean ridge height to spacing), while the contribution decreases with increasing roughness length. There is also an increasing trend in the air-ice drag coefficient C dn(10) as ridging intensity R i increases. However, as roughness length increases, C dn(10) increases at lower ridging intensities (Ri < 0.023) but decreases at lower ridging intensities (0.023 < Ri < 0.05). These opposing trends are mainly caused by the dominance of the form drag on pressure ridges and skin drag over rough ice surfaces. Generally, the form drag becomes dominant only when the ridging intensity is sufficiently large, while the skin drag is the dominant component at relatively larger ridging intensities. These results imply that a large value of C dn(10) is caused not only by the form drag on pressure ridges, but also by the skin drag over rough ice surfaces. Additionally, the estimated drag coefficients are consistent with reported measurements in the northwestern Weddell Sea, further demonstrating the feasibility of the drag partition model.

We reconstructed the centennial climate changes for the period of 9–7 cal ka BP in the upper region of the Changjiang (Yangtze) River Delta plain. A general warming and wetting trend from 8560 to 7220 cal yr BP was indicated by the decrease in Quercus (deciduous) and increases in Quercus (evergreen), Pinus, and Polypodiaceae spores. However, there were several brief climate fluctuations. A notable palynological change, from regional assemblages dominated by arboreal pollen to local assemblages mainly consisting of nonarboreal pollen, reflects climate fluctuations. The key indices of Quercus (deciduous), Pinus, herbs, fern spores, and palynological concentrations showed similar signs of centennial climate fluctuations. We suggest that the climate changes of the Dongge Cave and Yangtze River Delta regions were mainly affected by the East Asian summer monsoon (EASM) during the period of 9–7 cal ka BP. The general warming trend may be associated with an intensified EASM, and solar activity may be one of the important factors driving the centennial climate changes. The ~8.2 ka event was also recorded in the Yangtze River Delta region, which suggests that there was a close relationship between the EASM and Greenland climate during the early Holocene.

An effective multiplex real-time polymerase chain reaction (PCR) assay for the simultaneous detection of three major pathogens, Nosema bombycis Nägeli (Microsporidia: Nosematidae), Bombyx mori nucleopolyhedrovirus (Baculoviridae: genus Alphabaculovirus) (NPV), and Bombyx mori densovirus (Parvoviridae: genus Iteravirus) (DNV), in silkworms (Bombyx mori (Linnaeus); Lepidoptera: Bombycidae) was developed in this study. Polymerase chain reaction and real-time PCR tests and basic local alignment search tool searches revealed that the primers and probes used in this study had high specificities for their target species. The ability of each primer/probe set to detect pure pathogen DNA was determined using a plasmid dilution panel, in which under optimal conditions the multiplex real-time PCR assay showed high efficiency in the detection of three mixed target plasmids with a detection limit of 8.5×103 copies for N. bombycis and Bombyx mori NPV (BmNPV) and 8.5×104 copies for Bombyx mori DNV (BmDNV). When the ability to detect these three pathogens was examined in artificially inoculated silkworms, our method presented a number of advantages over traditional microscopy, including specificity, sensitivity, and high-throughput capabilities. Under the optimal volume ratio for the three primer/probe sets (3:2:2=N. bombycis:BmNPV:BmDNV), the multiplex real-time PCR assay showed early detection of BmNPV and BmDNV by day 1 post inoculation using DNA templates of the three pathogens in various combinations from individually infected silkworms; the early detection of N. bombycis was possible by day 3 post inoculation using the DNA isolated from the midgut of N. bombycis-infected silkworms.

To evaluate the effects of different anthropogenic activities on zooplankton and the pelagic ecosystem, we conducted seasonal cruises in 2010 to assess spatial heterogeneity among the mesozooplankton communities of Xiangshan Bay, a subtropical semi-enclosed bay in China. The evaluation included five different areas: a kelp farm, an oyster farm, a fish farm, the thermal discharge area of a power plant, and an artificial reef, and we aimed to identify whether anthropogenic activities dominated spatial variation in the mesozooplankton communities. The results demonstrated clear spatial heterogeneity among the mesozooplankton communities of the studied areas, dominantly driven by natural hydrographic properties, except in the area near the thermal discharge outlet of the power station. In the outlet area, thermal shock caused by the discharge influenced the mesozooplankton community by decreasing abundance and biomass throughout the four seasons, even causing a shift in the dominant species near the outlet during summer from Acartia pacifica to eurythermal and warm water taxa. Unique features of the mesozooplankton community in the oyster farm may be due to the combined effects of oyster culture and the natural environment in the branch harbour. However, kelp and fish culture, and the construction of an artificial reef did not exert any obvious influence on the mesozooplankton communities up to 2010, probably because of the small scale of the aquaculture and a time lag in the rehabilitation effects of the artificial reef. Thus, our results suggested that the dominant factors influencing spatial variations of mesozooplankton communities in Xiangshan Bay were still the natural hydrographic properties, but the thermal discharge was an anthropogenic activity that changed the pelagic ecosystem, and should be supervised.

Using phytolith analysis from a well-dated and high-resolution sediment sequence in the apex of northern Yangtze Delta, we investigate environmental changes, the rise and decline of rice exploitation and possible impacts of environment on rice exploitation during the early mid-Holocene. The phytolith sequence documents a relatively warm and dry interval during ca.9000 to 8200 cal yr BP, followed by climatic amelioration before 7200 cal yr BP. Phytolith evidence indicates that rice exploitation at the apex of northern Yangtze Delta began at 8200 cal yr BP, flourished by 7700 cal yr BP and ceased after 7400 cal yr BP. The first emergence of marine diatom species approximately 7300 cal yr BP likely indicates an accelerated sea-level rise. The apparent correlation of the initiation of rice exploitation with climatic amelioration during the early mid-Holocene suggests that climatic changes may have played an important role in facilitating rice exploitation. Both the ideal climatic conditions and stable sea level enabled flourishing rice exploitation during 8200 to 7400 cal yr BP. Although the climate remained warm and wet after 7400 cal yr BP, local sea-level rise possibly led to the termination of earlier rice exploitation at this site of the northern Yangtze Delta.

In this article, we report on the preparation of few-layered MoS2/graphene nanocomposite (MoS2/GNS-G) with enlarged interlayer distance as the lithium-ion battery anode via a facile hydrothermal method followed by glucose-assisted thermal annealing. During the synthesis, glucose serving as a small organic molecule can interlay into MoS2 nanosheets, which effectively hinder the aggregation and restacking of MoS2 during the process of heat treatment, retaining a sandwich structure of the composite. The enlarged interlayer distance (approximately 0.98 nm), along with the inserted amorphous carbon, could promote efficient lithium migration into active sites, buffer the volume change and stabilize the electrode structure effectively during the lithium insertion/extraction cycling. Electrochemical tests demonstrate that the MoS2/GNS-G delivers a high discharge capacity of 1583.0 mA h/g in the initial cycle at current density of 100 mA/g. The specific capacity remained at the relative high value of 673.5 mA h/g even at a current density of 1000 mA/g.