Detection of arbitrarily-shaped clusters using a neighbor-expanding approach: A case study on murine typhus in South Texas

<p>Abstract</p> <p>Background</p> <p>Kulldorff's spatial scan statistic has been one of the most widely used statistical methods for automatic detection of clusters in spatial data. One limitation of this method lies in the fact that it has to rely on scan windows with predefined shapes in the search process, and therefore it cannot detect cluster with arbitrary shapes. We employ a new neighbor-expanding approach and introduce two new algorithms to detect cluster with arbitrary shapes in spatial data. These two algorithms are called the maximum-likelihood-first (MLF) algorithm and non-greedy growth (NGG) algorithm. We then compare the performance of these two new algorithms with the spatial scan statistic (SaTScan), Tango's flexibly shaped spatial scan statistic (FlexScan), and Duczmal's simulated annealing (SA) method using two datasets. Furthermore, we utilize the methods to examine clusters of murine typhus cases in South Texas from 1996 to 2006.</p> <p>Result</p> <p>When compared with the SaTScan and FlexScan method, the two new algorithms were more flexible and sensitive in detecting the clusters with arbitrary shapes in the test datasets. Clusters detected by the MLF algorithm are statistically more significant than those detected by the NGG algorithm. However, the NGG algorithm appears to be more stable when there are no extreme cluster patterns in the data. For the murine typhus data in South Texas, a large portion of the detected clusters were located in coastal counties where environmental conditions and socioeconomic status of some population groups were at a disadvantage when compared with those in other counties with no clusters of murine typhus cases.</p> <p>Conclusion</p> <p>The two new algorithms are effective in detecting the location and boundary of spatial clusters with arbitrary shapes. Additional research is needed to better understand the etiology of the concentration of murine typhus cases in some counties in south Texas.</p

In vivo study on the performance of therapeutic intraocular lens loaded with an antibiotic and an anti-inflammatory

Abstract in proceedings of the Fourth International Congress of CiiEM: Health, Well-Being and Ageing in the 21st Century, held at Egas Moniz’ University Campus in Monte de Caparica, Almada, from 3–5 June 2019.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.info:eu-repo/semantics/publishedVersio

Bottom-Up Fabrication of PEG Brush on Poly(dimethylsiloxane) for Antifouling Surface Construction

Poly(dimethylsiloxane) silicones have found many applications in biomedical devices, whereas their surface hydrophobicity always brings about unexpected bioadhesion, causing complications of the implanted biomedical devices. In this work, surface-initiated reversible addition-fragmentation chain transfer (SI-RAFT) polymerization was utilized to generate PEG brushes on silicone surface, obtaining highly hydrophilic surface coatings. Such PEG brush coated silicone presents excellent antifouling to protein, cells, and bacteria, which may have great potential in implantable biomaterial surface modifications

Dual drug delivery from hydrophobic and hydrophilic intraocular lenses: in-vitro and in-vivo studies

Posterior capsule opacification (PCO) still remains the most frequent long term complication after cataract surgery, while endophthalmitis is rare but severe and should be prevented at all cost. Intraocular lenses (IOLs) with different designs (eg. edge and body-haptics angle) and materials (acrylic hydrophobic and acrylic hydrophilic surfaces) have been studied to reduce PCO. For the prevention of endophthalmitis, intracameral injection followed or not by topical treatment with antibiotics and anti-inflammatories are usually prescribed. The objective of this work was to investigate the use of IOLs as controlled release platforms of two drugs, the antibiotic moxifloxacin (MXF) and the anti-inflammatory ketorolac (KTL) that could advantageously substitute the usual treatment. Two types of IOLs were chosen, hydrophobic and hydrophilic. Hydrophobic IOLs have shown better results in the prevention of PCO because they adhere better to the posterior capsular bag, while hydrophilic IOLs are advised in the case of patients with uveitis, glaucoma or diabetes. The IOLs were loaded with MXF + KTL and sterilized by high hydrostatic pressure. Both IOLs reduced the tendency for adhesion of LECs. In vivo tests were done to compare the concentration of the drugs in the aqueous humor obtained after eye drops administration and drug-loaded IOLs implantation. The developed IOLs were able to release MXF and KTL at therapeutic levels, in a sustained way, which contrasts with the eye drops prophylaxis. No PCO signs were detected and histological analyses demonstrated biocompatibility of these devices.publishe

Past and Future Trajectories of Farmland Loss Due to Rapid Urbanization Using Landsat Imagery and the Markov-CA Model: A Case Study of Delhi, India

This study integrated multi-temporal Landsat images, the Markov-Cellular Automation (CA) model, and socioeconomic factors to analyze the historical and future farmland loss in the Delhi metropolitan area, one of the most rapidly urbanized areas in the world. Accordingly, the major objectives of this study were: (1) to classify the land use and land cover (LULC) map using multi-temporal Landsat images from 1994 to 2014; (2) to develop and calibrate the Markov-CA model based on the Markov transition probabilities of LULC classes, the CA diffusion factor, and other ancillary factors; and (3) to analyze and compare the past loss of farmland and predict the future loss of farmland in relation to rapid urban expansion from the year 1995 to 2030. The predicted results indicated the high accuracy of the Markov-CA model, with an overall accuracy of 0.75 and Kappa value of 0.59. The predicted results showed that urban expansion is likely to continue to the year of 2030, though the rate of increase will slow down from the year 2020. The area of farmland has decreased and will continue to decrease at a relatively stable rate. The Markov-CA model provided a better understanding of the past, current, and future trends of LULC change, with farmland loss being a typical change in this region. The predicted result will help planners to develop suitable government policies to guide sustainable urban development in Delhi, India

Fractal dimension of a transportation network and its relationship with urban growth: a study of the Dallas - Fort Worth area

A city and its transportation network are both complicated systems. Fractal geometry provides an effective way to describe the complex property of geographical features. This paper uses a modified box-counting method to describe the fractal property of urban transportation networks. Assuming that human settlements of different sizes are all operated by the same growth procedure, this paper investigates the relationship between the mass size of cities and the complexity of their road systems. The results confirm that, as cities grow from small to large, their transportation networks generally become more complicated -- the urban spaces are filled up more densely by city roads and the locations within a city are more accessible. The quantitative relationship identified between the complexity of urban transportation network and city size provides an empirical guide for the planning and policymaking of urban development and road construction.

Stability and Bifurcation Analysis for a Predator-Prey Model with Discrete and Distributed Delay

We propose a two-dimensional predatory-prey model with discrete and distributed delay. By the use of a new variable, the original two-dimensional system transforms into an equivalent three-dimensional system. Firstly, we study the existence and local stability of equilibria of the new system. And, by choosing the time delay τ as a bifurcation parameter, we show that Hopf bifurcation can occur as the time delay τ passes through some critical values. Secondly, by the use of normal form theory and central manifold argument, we establish the direction and stability of Hopf bifurcation. At last, an example with numerical simulations is provided to verify the theoretical results. In addition, some simple discussion is also presented

Fishpond Mapping by Spectral and Spatial-Based Filtering on Google Earth Engine: A Case Study in Singra Upazila of Bangladesh

Inland aquaculture in Bangladesh has been growing fast in the last decade. The underlying land use/land cover (LULC) change is an important indicator of socioeconomic and food structure change in Bangladesh, and fishpond mapping is essential to understand such LULC change. Previous research often used water indexes (WI), such as Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI), to enhance water bodies and use shape-based metrics to assist classification of individual water features, such as coastal aquaculture ponds. However, inland fishponds in Bangladesh are generally extremely small, and little research has investigated mapping of such small water objects without high-resolution images. Thus, this research aimed to bridge the knowledge gap by developing and evaluating an automatic fishpond mapping workflow with Sentinel-2 images that is implemented on Google Earth Engine (GEE) platform. The workflow mainly includes two steps: (1) the spectral filtering phase that uses a pixel selection technique and an image segmentation method to automatically identify all-year-inundated water bodies and (2) spatial filtering phase to further classify all-year-inundated water bodies into fishponds and non-fishponds using object-based features (OBF). To evaluate the performance of the workflow, we conducted a case study in the Singra Upazila of Bangladesh, and our method can efficiently map inland fishponds with a precision score of 0.788. Our results also show that the pixel selection technique is essential in identifying inland fishponds that are generally small. As the workflow is implemented on GEE, it can be conveniently applied to other regions