Objective: To investigate whether major dengue outbreaks in the last two decades in Kaohsiung follow a precise temporal pattern.
Methods: Government daily lab-confirmed dengue case data from three major dengue outbreaks occurring during the last two decades in Kaohsiung in 2002, 2014 and 2015, is utilized to compute the corresponding weekly cumulative percentage of total case numbers. We divide each of the three time series data into two periods to examine the corresponding weekly cumulative percentages of case numbers for each period. Pearson's correlation coefficient was calculated to compare quantitatively the similarity between the temporal patterns of these three years.
Results: Three cutoff points produce the most interesting comparisons and the most different outcomes. Pearson's correlation coefficient indicates quantitative discrepancies in the similarity between temporal patterns of the three years when using different cutoff points.
Conclusions: Temporal patterns in 2002 and 2014 are comparatively more similar in early stage. The 2015 outbreak started late in the year, but ended more like the outbreak in 2014, both with record-breaking number of cases. The retrospective analysis shows that the temporal dynamics of dengue outbreaks in Kaohsiung can strongly vary from one year to another, making it difficult to identify any common predictor.
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http://dx.doi.org/10.1016/j.apjtm.2017.03.009 | DOI Listing |
Neurosci Lett
January 2025
Department of Kinesiology and Applied Physiology, University of Delaware Newark DE USA. Electronic address:
Aging has a significant impact on brain structure, demonstrated by numerous MRI studies using diffusion tensor imaging (DTI). While these studies reveal changes in fractional anisotropy (FA) across different brain regions, they tend to focus on white matter tracts and cognitive regions, often overlooking gray matter and motor areas. Additionally, traditional DTI metrics can be affected by partial volume effects.
View Article and Find Full Text PDFJ Environ Manage
January 2025
School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou City, 450001, Henan Province, China. Electronic address:
Enhancing the understanding of the rainfall-runoff temporal dynamics in semi-arid and semi-humid regions is crucial for flood disaster mitigation. Loess Plateau is a unique environment within semi-arid and semi-humid regions, characterized by its deep loess soil, prevalent short-duration intense rainfall, and changes in underlying surface conditions. In this research, 25 catchments from the Loess Plateau were chosen to examine the temporal variations in event runoff responses across different time scales.
View Article and Find Full Text PDFJ Hazard Mater
January 2025
Federal Institute for Materials Research and Testing (BAM), Division 1.1 - Inorganic Trace Analysis, Richard-Willstätter-Straße 11, Berlin 12489, Germany. Electronic address:
Organotin (OT) compounds, while crucial in many industrial applications, pose substantial risks to the environment and human health. The toxicity and environmental behaviour of OTs depend on their chemical form, i.e.
View Article and Find Full Text PDFAnimal
December 2024
Department of Crop Sciences, Grassland Science, Georg-August-University Göttingen, Von-Siebold-Strasse 8, 37075 Göttingen, Germany; Centre for Biodiversity and Sustainable Land Use, Büsgenweg 1, 37075 Göttingen, Germany.
Animal welfare is integral to sustainable livestock production, and pasture access for cattle is known to enhance welfare. Despite positive welfare impacts, high labour requirements hinder the adoption of sustainable grazing practices such as rotational stocking management. Virtual fencing (VF) is an innovative technology for simplified, less laborious grazing management and remote animal monitoring, potentially facilitating the expansion of sustainable livestock production.
View Article and Find Full Text PDFNeural Netw
January 2025
School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430070, Hubei, China.
In the Imbalanced Multivariate Time Series Classification (ImMTSC) task, minority-class instances typically correspond to critical events, such as system faults in power grids or abnormal health occurrences in medical monitoring. Despite being rare and random, these events are highly significant. The dynamic spatial-temporal relationships between minority-class instances and other instances make them more prone to interference from neighboring instances during classification.
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