Automated Residential Area Generalization: Combination of Knowledge-Based Framework and Similarity Measurement

The major reason that the fully automated generalization of residential areas has not been achieved to date is that it is difficult to acquire the knowledge that is required for automated generalization and for the calculation of spatial similarity degrees between map objects at different scales. Furthermore, little attention has been given to generalization methods with a scale reduction that is larger than two-fold. To fill this gap, this article develops a hybrid approach that combines two existing methods to generalize residential areas that range from 1:10,000 to 1:50,000. The two existing methods are Boffet’s method for free space acquisition and kernel density analysis for city hotspot detection. Using both methods, the proposed approach follows a knowledge-based framework by implementing map analysis and spatial similarity measurements in a multiscale map space. First, the knowledge required for residential area generalization is obtained by analyzing multiscale residential areas and their corresponding contributions. Second, residential area generalization is divided into two subprocesses: free space acquisition and urban area outer boundary determination. Then, important parameters for the two subprocesses are obtained through map analysis and similarity measurements, reflecting the knowledge that is hidden in the cartographer’s mind. Using this acquired knowledge, complete generalization steps are formed. The proposed approach is tested using multiscale datasets from Lanzhou City. The experimental results demonstrate that our method is better than the traditional methods in terms of location precision and actuality. The approach is robust, comparatively insensitive to the noise of the small buildings beyond urban areas, and easy to implement in GIS software.

Differential Uptake of Murine and Human Exosomes by Normal and Inflamed Peripheral Tissues and Brain

Background: Exosomes function as an intercellular communication system conveying messages from donor to target cells in nearby or distant tissues. Many aspects of exosome trafficking remain unresolved, however. Here, we investigated uptake of ten radiolabeled murine or human exosomes of various cellular origins by the liver, kidney, spleen, and lung of male CD-1 mice. Methods: We radioactively labeled 10 exosomes from mouse or human cancerous or non-cancerous lines, injected them intravenously into male CD-1 mice, and studied their tissue uptake. We examined the ability of wheatgerm agglutinin (WGA), mannose-6 phosphate (M6P), and inflammation induced by lipopolysaccharide (LPS) to modulate uptake. We measured uptake rate using multiple-time regression analysis and used heat mapping and path analysis to correlate tissue and exosomal influences on uptake. Results: Except for the uptake of SCCVII exosomes by kidney, all exosomes were taken up by all tissues, although the uptake levels varied broadly among exosomes and tissues. The liver/serum uptake ratio for exosomes from primary human T-cells was the highest at 4,500 mL/g. Species of origin (mouse vs human) or source (cancerous vs noncancerous cells) did not influence tissue uptake. The uptake of some exosomes was altered by WGA and LPS but not by M6P, except for uptake inhibition of J774A.1 exosomes by liver, suggesting use of the M6P receptor. WGA or LPS treatments enhanced uptake of exosomes by brain and lung but inhibited uptake by liver and spleen. Response to LPS was not, however, predictive of response to WGA. No evidence for a universal binding site controlling exosome uptake was obtained. Applying path analysis and heat map analysis to the data, including our published results for brain, we found that exosome uptake patterns for lung and brain responded similarly to WGA or to LPS, whereas those for liver and spleen clustered together. In path analysis, the 10 exosomes clustered into distinct groups, suggesting that their bindings sites are similarly clustered. Conclusions: Uptake of exosomes by peripheral tissues is differentially regulated by both exosomes and target tissues and is dependent on the number and types of mutually interactive binding sites.

Satellite-Based Precipitation Estimates Validation Using Surface Stations in the Central Region of the State of São Paulo, From 1981 to 2019

With the advance of remote sensing technologies, meteorological satellites have become an alternative in the process of monitoring and measuring meteorological variables, both spatially and temporally. The present study brings some additional elements to the validation of satellite-based precipitation estimates by evaluating the CHIRPS (Climate Hazards Group Infra-Red Precipitation with Station) monthly product for the central region of the state of São Paulo, Brazil, in the period 1981-2019. Initially, the general relationship between satellite estimates and surface rainfall data is assessed using the linear adjustment and error analysis in both temporal and spatial perspectives, followed by a trend analysis using Laplace test. The monthly map analysis showed a better performance of CHIRPS during the dry period (April to August) than for the wet period (October to March). Finally, monthly trends showed, in general, the same pattern of variability in rainfall over 38 years and a prevalence toward the reduction of rainfall. In summary, CHIRPS product seems a reasonable alternative for regions that lack historical rainfall information.

Characteristics of Soil Bacterial Community in the Decomposition Process Inside and Outside Moso Bamboo Stumps

Purpose: Soil bacteria comprise the largest number of soil microorganisms and play an important role in moso bamboo (Phyllostachys edulis) stump decay; however, the characteristics of soil bacterial communities inside and outside these stumps remain unclear. Methods: The characteristics of soil bacterial communities inside and outside Phyllostachys edulis bamboo stumps were analyzed under three different levels of decay using high-throughput sequencing technology. Results: The abundance of operational taxonomic units inside and outside the bamboo stumps increased as the decay progressed; Proteobacteria, Acidobacteria, Actinobacteria, Planctomycetes, and Verrucomicrobia were the most abundant phyla in the soil inside and outside the bamboo stumps. In the outside bamboo stumps, there was a very significant positive correlation of Acidobacteria and Planctomycetes with the decaying degree of bamboo stumps. At the class level, Alphaproteobacteria, Gammaproteobacteria, and Planctomycetacia were the most abundant bacteria in the bamboo stumps. Inside the stumps, the decaying degree of bamboo stumps was significantly positively correlated with Alphaproteobacteria and significantly negatively correlated with Gammaproteobacteria and Bacilli. Principal component analysis and the heat map analysis at the genus level indicated similarities among soil bacterial communities inside the moderately and severely decayed bamboo stumps and among the communities outside the mildly and moderately decayed bamboo stumps. Conclusion: Our results augment our understanding of the expeditious degradation process of bamboo stumps, and provide a theoretical basis and reference for microbiological research, sustainable bamboo stump operations, and degradation methods of bamboo forests.

Identifying HRM Practices for Improving Information Security Performance

This article focuses on identifying key human resource management (HRM) practices necessary for improving information security performance from the perspective of IT professionals. The Importance-Performance Map Analysis (IPMA) via SmartPLS 3.0 was employed and 232 samples were collected from information technology (IT) professionals in 43 organizations. The analysis identified information security training, background checks and monitoring as very important HRM practices that could improve the performance of organizational information security. In particular, the study found training on mobile devices security and malware; background checks and monitoring of potential, current and former employees as of high importance but with low performance. Thus, these key areas need to be improved with top priority. Conversely, the study found accountability and employee relations as being overly emphasized by the organisations. The findings raised some useful implications and information for HR and IT leaders to consider in future information security strategy.

Identifying HRM Practices for Improving Information Security Performance

This article focuses on identifying key human resource management (HRM) practices necessary for improving information security performance from the perspective of IT professionals. The Importance-Performance Map Analysis (IPMA) via SmartPLS 3.0 was employed and 232 samples were collected from information technology (IT) professionals in 43 organizations. The analysis identified information security training, background checks and monitoring as very important HRM practices that could improve the performance of organizational information security. In particular, the study found training on mobile devices security and malware; background checks and monitoring of potential, current and former employees as of high importance but with low performance. Thus, these key areas need to be improved with top priority. Conversely, the study found accountability and employee relations as being overly emphasized by the organisations. The findings raised some useful implications and information for HR and IT leaders to consider in future information security strategy.

Variability and trends of climate extremes indices from the observed and downscaled GCMs data over 1950–2020 period in Chattogram City, Bangladesh

This study was intended to evaluate the variability and trends of climate extremes by incorporating daily data from Chattogram station and from the high-resolution Coordinated Regional Climate Downscaling Experiment (CORDEX) for two different time series. Here, we also focused on evaluating the performance of the selected RCMs (CanESM2, CSIRO, and GFDL from CORDEX) using Taylor diagrams and heat map analysis. Twenty-two extreme climate indices from ETCCDI were computed for 1950–1989 and 1990–2020 periods. Mann–Kendall and Sen's slope test were performed to estimate the trends from the indices from both station and RCMs data. Highly significant increasing trend for the warm days and warm nights’ frequencies were found, whereas, the frequency of cold days and cold nights indicated significantly decreasing trend. On the other hand, mild increasing trend in 1-day and 5-day maximum rainfall was detected. Also, the average annual precipitation has increased by 6% from the 1950–1989 to 1990–2020 period. During the last three decades, the region has experienced more heavier rainfall in the monsoon but increased water stress in the dry season. The two-fold effects of climate change on the local hydrology revealed by this study need to be addressed properly for the sustainable development of this region.