Status of coral reef fish communities within the Mombasa Marine Protected Area, Kenya, more than a decade after establishment

The abundance, trophic composition and diversity of fish were investigated in the Mombasa Marine Protected Area (MPA) on the Kenya coast over a period of four years (2004-2007) sixteen years after its establishment to determine its effectiveness. Fish monitoring data collected using belt transects revealed significant differences in fish abundance, distribution and composition between the MPA’s no-take area and a partially-protected area with controlled exploitation. Although seasonal variation was apparent in the trophic composition, annual differences over the four year study period were not significant. Results indicated that differences in fish composition within the MPA were due to a greater abundance of haemulids (nocturnal carnivores) and acanthurids (herbivores) in the no-take area than in the partially-protected area. Fish diversity also varied between the no-take area and the partially-protected area with a higher Shannon-Wiener diversity index associated with the no-take area. Dominance was higher in the partially-protected area than in the no-take area and was also higher during the southeast (SE) monsoon season. These results support the claim of greater effectiveness of the fully protected no-take area, compared to the partially-protected area in sustaining the rich fish community found in previous studies

Can a single image processing algorithm work equally well across all phases of DCE-MRI?

Image segmentation and registration are said to be challenging when applied to dynamic contrast enhanced MRI sequences (DCE-MRI). The contrast agent causes rapid changes in intensity in the region of interest and elsewhere, which can lead to false positive predictions for segmentation tasks and confound the image registration similarity metric. While it is widely assumed that contrast changes increase the difficulty of these tasks, to our knowledge no work has quantified these effects. In this paper we examine the effect of training with different ratios of contrast enhanced (CE) data on two popular tasks: segmentation with nnU-Net and Mask R-CNN and registration using VoxelMorph and VTN. We experimented further by strategically using the available datasets through pretraining and fine tuning with different splits of data. We found that to create a generalisable model, pretraining with CE data and fine tuning with non-CE data gave the best result. This interesting find could be expanded to other deep learning based image processing tasks with DCE-MRI and provide significant improvements to the models performance

Developing a simulated intelligent instrument to measure user behavior toward cybersecurity policies

Institutions struggle to protect themselves from threats and cybercrime. Therefore, they devote much attention to improving information security infrastructures. Users’ behaviors were explored via a traditional questionnaire research instrument in a data collocate process. The questionnaire explores users’ behaviors theoretically, so the respondents’ answers to the questionnaire are insufficiently reliable, and the responses might not reflect actual behavior based on the human bias when facing theoretical problems. This study aims to solve unreliable responses to the questionnaire by developing a simulated intelligent instrument to measure users’ behaviors toward cybersecurity policies in an experimental study using gamification

Self-Organizing Maps to determine global distribution patterns of mangrove plant species and analysis of threats using socio-economic indicators

Abstract Commonly, the distribution of each mangrove species is shown by localizing them in a geographic map using coordinates and this information is not so much explored using socioeconomic influences. Furthermore, it is difficult to visualize which species of mangroves have the same distribution on a global scale and how the socio-economic influences can affect the species with a restricted distribution. Therefore, we ask the following questions: Which species are more affected by human pressure? Which biogeographic regions are more threatened? Which human impacts are influencing the degradation of mangroves? In order to answer these questions, we used the technique of neural networks called Self-Organizing Maps (SOM), because it is an efficient tool for geovisualizing high-dimensional data. In addition, SOM approximate the probability density function of input data and it has been used as an alternative to traditional statistical methods to efficiently deal with datasets ruled by complex, non-linear relationships. The input data are the distribution of plant species that contain the presence/absence data for each country extracted from the Mangrove Reference Database and Herbarium (Massó i Alemán et al., 2010), which includes the World Atlas of Mangrove

Association of single nucleotide polymorphisms with renal cell carcinoma in Algerian population

Background: Renal cell carcinoma (RCC) is a common malignant tumor of the urinary system. The etiology of RCC is a complex interaction between environmental and multigenetic factors. Genome-wide association studies have iden? tifed new susceptibility risk loci for RCC. We examined associations of genetic variants of genes that are involved in metabolism, DNA repair and oncogenes with renal cancer risk. A total of 14 single nucleotide polymorphisms (SNPs) in 11 genes (VEGF, VHL, ATM, FAF1, LRRIQ4, RHOBTB2, OBFC1, DPF3, ALDH9A1 and EPAS1) were examined. Methods: The current case?control study included 87 RCC patients and 114 controls matched for age, gender and ethnic origin. The 14 tag-SNPs were genotyped by Sequenom MassARRAY? iPLEX using blood genomic DNA. Results: Genotype CG and allele G of ATM rs1800057 were signifcantly associated with RCC susceptibility (p=0.043; OR=8.47; CI=1.00?71.76). Meanwhile, we found that genotype AA of rs67311347 polymorphism could increase the risk of RCC (p=0.03; OR=2.95; IC=1.10?7.89). While, genotype TT and T allele of ALDH9A1 rs3845536 were observed to approach signifcance for a protective role against RCC (p=0.007; OR=0.26; CI=0.09?0.70). Conclusion: Our results indicate that ATM rs1800057 may have an efect on the risk of RCC, and suggest that ALDH9A1 was a protective factor against RCC in Algerian populatio

Conduction disturbances in Tako Tsubo cardiomyopathy: A cause or a consequence?

Tako-Tsubo cardiomyopathy (TTC) is a reversible cardiomyopathy mimicking acute myocardial infarction characterized by a transient left ventricular (LV) apical ballooning without epicardial coronary artery disease [1]. Most remarkable is the complete reversibility of this cardiomyopathy resolving spontaneously within several weeks [1]. Conduction pathway disorders were rarely associated with TTC. We described two cases of TTC with conduction disorders persisting after improvement of left ventricular wall motion that finally motivated the implantation of pacemakers