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Should we be conscious of girl or boy factors in hyperuricemia? Analysis of the population-based The german language well being interview and examination survey regarding adults (DEGS1).
cerevisiae could be employed to improve the sensory quality of citrus wines. These results would provide not only methods to improve the sensory quality of citrus wine, but also a valuable reference for the selection of non-Saccharomyces yeast strains for fruit wine fermentation.For wireless communication networks, cognitive radio (CR) can be used to obtain the available spectrum, and wideband compressed sensing plays a vital role in cognitive radio networks (CRNs). Using compressed sensing (CS), sampling and compression of the spectrum signal can be simultaneously achieved, and the original signal can be accurately recovered from the sampling data under sub-Nyquist rate. Using a set of wideband random filters to measure the channel energy, only the recovery of the channel energy is necessary, rather than that of all the original channel signals. Based on the semi-tensor product, this paper proposes a new model to achieve the energy compression and reconstruction of spectral signals, called semi-tensor product compressed spectrum sensing (STP-CSS), which is a generalization of traditional spectrum sensing. The experimental results show that STP-CSS can flexibly generate a low-dimensional sensing matrix for energy compression and parallel reconstruction of the signal. Compared with the existing methods, STP-CSS is proved to effectively reduce the calculation complexity of sensor nodes. Hence, the proposed model markedly improves the spectrum sensing speed of network nodes and saves storage space and energy consumption.Poultry frequently account for the highest prevalence of extended-spectrum beta-lactamase (ESBL)-producing Enterobacteriaceae in livestock. To investigate the impact of direct-fed microbials (DFM) and phytobiotic feed additives on prevalence and conjugation of extended-spectrum beta-lactamase (ESBL)-producing Enterobacteriaceae, an animal trial was conducted. see more Lactobacillus agilis LA73 and Lactobacillus salivarius LS1 and two commercial phytogenic feed additives (consisting of carvacrol, cinnamaldehyde, and eugenol) were used as feed additives either alone or as a combination of DFM and phytogenic feed additive. An ESBL-producing E. coli donor and a potentially pathogenic Salmonella Typhimurium recipient were inoculated at 5 × 109 cells/mL in cecal contents from 2-week-old broilers. Conjugation frequencies were determined after 4 h aerobic co-incubation at 37 °C and corrected for the impact of the sample matrix on bacterial growth of donor and recipient. Surprisingly, indigenous Enterobacteriaceae acted as recipients instead of the anticipated Salmonella recipient. The observed increase in conjugation frequency was most obvious in the groups fed the combinations of DFM and phytogenic product, but merely up to 0.6 log units. Further, cecal samples were examined for ESBL-producing Enterobacteriaceae on five consecutive days in broilers aged 27-31 days. All samples derived from animals fed the experimental diet showed lower ESBL-prevalence than the control. It is concluded that Lactobacillus spp. and essential oils may help to reduce the prevalence of ESBL-harboring plasmids in broilers, while the effect on horizontal gene transfer is less obvious.Mouthpart structures were observed in four species of Largidae using scanning electron microscopy to investigate their morphological disparity, and linked to changes in feeding specialization. The examined species are pests that feed mainly on seeds and plant sap of forbs, shrubs, and trees. Their external mouthparts are described in detail for the first time herein. The cone-like labrum and four-segmented tube-like labium are shorter in Physopelta species than in Macrocheraia grandis (Grey). The labium surface in all studied species bears nine types of sensilla (St1-St2, Sb1-3, Sch, Sca1-2, Sm). The distributions of sensilla on particular labial segments varies among the studied species. The tripartite apex of the labium consists of two lateral lobes and an apical plate that is partly divided in Physopelta species, and not divided in Macrocheraia. Each lateral lobe possesses a sensillar field with 10 thick-walled uniporous sensilla basiconica, one multiporous sensillum styloconicum, and one long non-porous hrait more adapted for sucking sap from phloem or parenchymal cells.Visual inertial odometry (VIO) is the front-end of visual simultaneous localization and mapping (vSLAM) methods and has been actively studied in recent years. In this context, a time-of-flight (ToF) camera, with its high accuracy of depth measurement and strong resilience to ambient light of variable intensity, draws our interest. Thus, in this paper, we present a realtime visual inertial system based on a low cost ToF camera. The iterative closest point (ICP) methodology is adopted, incorporating salient point-selection criteria and a robustness-weighting function. In addition, an error-state Kalman filter is used and fused with inertial measurement unit (IMU) data. To test its capability, the ToF-VIO system is mounted on an unmanned aerial vehicle (UAV) platform and operated in a variable light environment. The estimated flight trajectory is compared with the ground truth data captured by a motion capture system. Real flight experiments are also conducted in a dark indoor environment, demonstrating good agreement with estimated performance. The current system is thus shown to be accurate and efficient for use in UAV applications in dark and Global Navigation Satellite System (GNSS)-denied environments.Hyperspectral image (HSI) consists of hundreds of narrow spectral band components with rich spectral and spatial information. Extreme Learning Machine (ELM) has been widely used for HSI analysis. However, the classical ELM is difficult to use for sparse feature leaning due to its randomly generated hidden layer. In this paper, we propose a novel unsupervised sparse feature learning approach, called Evolutionary Multiobjective-based ELM (EMO-ELM), and apply it to HSI feature extraction. Specifically, we represent the task of constructing the ELM Autoencoder (ELM-AE) as a multiobjective optimization problem that takes the sparsity of hidden layer outputs and the reconstruction error as two conflicting objectives. Then, we adopt an Evolutionary Multiobjective Optimization (EMO) method to solve the two objectives, simultaneously. To find the best solution from the Pareto solution set and construct the best trade-off feature extractor, a curvature-based method is proposed to focus on the knee area of the Pareto solutions.
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