Mapping technological innovation dynamics in artificial intelligence domains: Evidence from a global patent analysis

Artificial intelligence (AI) is emerging as a technology at the center of many political, economic, and societal debates. This paper formulates a new AI patent search strategy and applies this to provide a landscape analysis of AI innovation dynamics and technology evolution. The paper uses patent analyses, network analyses, and source path link count algorithms to examine AI spatial and temporal trends, cooperation features, cross-organization knowledge flow and technological routes. Results indicate a growing yet concentrated, non-collaborative and multi-path development and protection profile for AI patenting, with cross-organization knowledge flows based mainly on interorganizational knowledge citation links.

Recent Spatial and Temporal Trends of Malaria in Korea

This study was done to provide an analytical overview on the latest malaria infection clusters by evaluating temporal trends during 2010-2019 in Korea. Incheon was the most likely cluster (MLC) for all cases of malaria during the total period. MLCs for P. falciparum, vivax, malariae, ovale, and clinically diagnosed malaria without parasitological confirmation were Jeollanam-do, Incheon, Gangwon-do, Gyeongsangnam-do, and Jeollabuk-do, respectively. Malaria was decreasing in most significant clusters, but Gwangju showed an increase for all cases of malaria, P. vivax and clinically diagnosed cases. Malaria overall, P. falciparum and P. vivax seem to be under control thanks to aggressive health measures. This study might provide a sound scientific basis for future control measures against malaria in Korea.

octoFLUshow: an Interactive Tool Describing Spatial and Temporal Trends in the Genetic Diversity of Influenza A Virus in U.S. Swine

Influenza A virus (IAV) is passively surveilled in swine in the United States through a U.S. Department of Agriculture-administered surveillance system. We present an interactive Web tool to visualize and explore trends in the genetic and geographic diversity of IAV derived from the surveillance system.

Importance and Problems of Landscape Diversity Conservation in the Environmental Policy of Poorly Developed Regions

The environmental strategy for regional development is implemented through regional environmental programs. Their list of indicators that track the effectiveness of planned tasks shows that the most important regional aspects are not always properly reflected. The specificity of spatial and temporal trends in the development of regions, the peculiarities of territorial changes in geosystems, and the dynamics of the ratio of disturbed and undisturbed territories are of particular importance in highlighting the tasks in the context of the application of particular indicators. In the context of increased economic activity in the Russian Far East, facilitated by the policy of improving priority social and economic development areas, the regions identify their own tasks for sustainable development. From the perspective of the geographical approach, the content of the concept of landscape diversity, contained in the environmental program of Khabarovsk Territory to reflect spatial changes, is briefly presented. Landscapes as integral systems are considered from the point of view of their positions in the system of taxa of the regional hierarchy. The significance of “landscape diversity conservation” criterion for solving the same problem as a priority for this territory has been shown. The necessity of its application in the region has been considered due to the concentration of natural complexes of a high hierarchical rank, their significant share within the region, the uniqueness and at the same time a high degree of landscape vulnerability to anthropogenic impact due to increased economic activity, the imperfection of the PA network etc.

Spatio-temporal patterns of childhood pneumonia in Bhutan: a Bayesian analysis

Pneumonia is one of the top 10 diseases by morbidity in Bhutan. This study aimed to investigate the spatial and temporal trends and risk factors of childhood pneumonia in Bhutan. A multivariable Zero-inflated Poisson regression model using a Bayesian Markov chain Monte Carlo simulation was undertaken to quantify associations of age, sex, altitude, rainfall, maximum temperature and relative humidity with monthly pneumonia incidence and to identify the underlying spatial structure of the data. Overall childhood pneumonia incidence was 143.57 and 10.01 per 1000 persons over 108 months of observation in children aged < 5 years and 5–14 years, respectively. Children < 5 years or male sex were more likely to develop pneumonia than those 5–14 years and females. Each 1 °C increase in maximum temperature was associated with a 1.3% (95% (credible interval [CrI] 1.27%, 1.4%) increase in pneumonia cases. Each 10% increase in relative humidity was associated with a 1.2% (95% CrI 1.1%, 1.4%) reduction in the incidence of pneumonia. Pneumonia decreased by 0.3% (CrI 0.26%, 0.34%) every month. There was no statistical spatial clustering after accounting for the covariates. Seasonality and spatial heterogeneity can partly be explained by the association of pneumonia risk to climatic factors including maximum temperature and relative humidity.