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The information unavailability of a global navigation satellite system (GNSS) for geo‐localization in many military and tourism applications implies the need to employ other applicable types of information, such as automatic image‐based location recognition. Unlike most existing localization methods that use GNSS information to locate an initial position, this paper proposes an automatic geo‐localization framework that does not require GNSS data. The proposed framework is a two‐stage pipeline that uses a query image and digital elevation model (DEM) data as input. The authors frame automatic geo‐localization without GNSS recordings as a skyline matching problem. By extracting the skyline from the DEM data and query images, the query image can be localized by matching the query skyline feature to the DEM skyline database. It has been demonstrated that this low‐cost approach can perform efficiently in mountainous or hilly areas to produce reliable localization results. The system was tested on 50 testing site points within a large‐scale area (China, 202.6 km2), and an average position error of 43.13 m was detected within 4.5 s. [ABSTRACT FROM AUTHOR]

Drawing on the theory of planned behavior, we investigate the legitimacy of platform governance and whether consumers with greater ranges of risk propensity are more likely to purchase innovative products. This study develops a moderated mediation model involving risk propensity, cognitive legitimacy, purchase intention and perceived benefit. To examine our hypotheses, we conducted a survey of 315 consumers from Shanghai, China. The results reveal that risk propensity is positively related to consumers' purchase intentions, in which cognitive legitimacy plays a mediating role. Furthermore, the interaction suggests that perceived benefit moderates the relationship between risk propensity and cognitive legitimacy. [ABSTRACT FROM AUTHOR]

The porcine epidemic diarrhea virus (PEDV) causes a highly contagious disease in pigs, which is one of the most devastating viral diseases of swine in the world. In China, PEDV was first confirmed in 1984 and PEDV infections occurred sporadically from 1984 to early 2010. From late 2010 until present, PEDV infections have swept every province or region in China. In this study, we analyzed a total of 186 full-length spike genes and deduced proteins of all available complete genomes of PEDVs isolated in China during 2007–2019. A total of 28 potential recombination events were identified in the spike genes of PEDVs in China. Spike gene recombination not only expanded the genetic diversity of PEDVs in the GII genogroup, but also resulted in the emergence of a new evolutional branch GI-c during 2016–2018. In addition, comparative analysis of spike proteins between GI-a prototype virulent CV777 and GII strain AJ1102 reveals that the amino acid variations could affect 20 potential linear B cell epitopes, demonstrating a dramatic antigen drift in the spike protein. These results provide a thorough view of the information about the genetic and antigenic diversity of PEDVs circulating in China and therefore could benefit the development of suitable strategies for disease control. [ABSTRACT FROM AUTHOR]

Essential trace elements (ETEs) are essential nutrients for keeping the nervous system functioning. Associations between ETEs and cognitive function are still inconclusive and limited. We aimed to investigate the individual and joint associations between ETEs and cognitive function among older adults. A population (N = 2181) at an average age≥ 65 from Yiwu cohort in China was available for this study. Whole blood chromium (Cr), selenium (Se), manganese (Mn), and copper (Cu) concentrations were measured by inductively coupled plasma mass spectrometry (ICP-MS). Cognitive function was assessed using the Mini-Mental State Examination (MMSE), consisting of five specific cognitive domains: orientation, registry, attention and calculation, recall, and language and praxis. Linear regression, restricted cubic spline (RCS) analysis, and Bayesian kernel machine regression (BKMR) were used to analyze the individual and joint associations between ETEs and cognitive function. The association between Cr and MMSE score presented an inverted-U shape (Q3 versus Q1: β = 0.774, 95 % CI: 0.297, 1.250; Q4 versus Q1: β = 0.481, 95 % CI: 0.006, 0.956); and Cr was especially associated with the registry, recall, and language and praxis. Per IQR (36.32 μg/L) increase of Se was positively associated with the MMSE score (β = 0.497, 95 % CI: 0.277, 0.717) and all five cognitive domains. The BKMR showed that the dose-response association between Se and cognitive function increased initially and then decreased with increasing Se concentration when fixed the other ETEs in median. ETEs mixture was positively associated with cognitive function, and Se (posterior inclusion probabilities, PIPs = 0.915) was the most important contributor within the ETEs mixture. The nonlinear association between Cr and cognitive function suggested further exploration of an appropriate concentration range for ETEs. A positive association between mixed ETEs and cognitive function is a reminder that their joint association should be considered. Further prospective studies or intervention studies are warranted to validate our findings in the future. [Display omitted] • The association between Cr and cognitive function presented an inverted-U shape. • The joint association between ETEs mixture and cognitive function was positive. • Se was the most important contributor to cognitive function within the mixture. [ABSTRACT FROM AUTHOR]

• Support vector machine (SVM) provides accuracy of classification over 99% • Following SVM, time counting in each style has accuracy over 99% • Stroke count could be accomplished with 93% accuracy. • The three functions above could be done with only one accelerometer. Aerobic exercises on land could be quantified and tracked objectively, but swimming style recognition has remained unexplored. Taking the advantages of signal processing and machine learning on acceleration signals, the purpose of this study was, by analyzing swimming accelerometer data, to explore a set of algorithm in tracking swimming activities, including recognizing swimming styles, counting time and counting strokes in each style. A total of 17 participants (9 females) from the swimming team of the Southeast University of China was recruited. They performed breaststroke, front crawl, backstroke and butterfly, four 50-meter-lap each, with an ActiGraph GT9X inertia measurement unit on wrist of their preferred side. Overall, 78.7 ± 14.6, 148.5 ± 21.7, 151.2 ± 14.4, 98 ± 16.3 strokes were performed and evaluated on breaststroke, front crawl, backstroke and butterfly, respectively. In classification, three classifiers were examined and the result showed that support vector machine (SVM) provided the best accuracy of classification (over 99%). In time counting, the accuracy was over 99% and in stroke counting, the overall single-lap accuracy rate was 93.3%. In conclusion, with a combination of an objective measure and machine-learning algorithm, tracking swimming activities, including swimming style classification, counting swimming time and strokes, by a accelerometer becomes possible. [ABSTRACT FROM AUTHOR]