Anopheles mosquitoes transmit malaria which is one of the world's most threatening diseases. Anopheles dirus (sensu stricto) is among the main vectors of malaria in South East Asia. The mosquito innate immune response is the first line of defence against malaria parasites during its development. The immune deficiency (IMD) pathway, a conserved immune signaling pathway, influences anti-Plasmodium falciparum activity in Anopheles gambiae, An. stephensi and An. albimanus. The aim of the study was to determine the role of Rel2, an IMD pathway-controlled NF-kappaβ transcription factor, in An. dirus.
Activated sludge (AS) is a biological treatment process that is employed in wastewater treatment plants. Filamentous bacteria in AS plays an important role in the settling ability of the sludge. Proper settling of the sludge is essential for normal functionality of the wastewater plants, where filamentous bulking is always a persistent problem preventing sludge from settling. The performance of AS plants is conventionally monitored by physico-chemical procedures. An alternative way of monitoring the AS in wastewater treatment process is to use image processing and analysis. Good performance of the image segmentation algorithms is important to quantify flocs and filaments in AS. In this article, an algorithm is proposed to perform segmentation of filaments in the phase contrast images using phase stretch transform. Different values of strength (S) and warp (W) are tested to obtain optimum segmentation results and decrease the halo and shade-off artefacts encountered in phase contrast microscopy. The performance of the algorithm is assessed using DICE coefficient, accuracy, false positive rate (FPR), false negative rate (FNR) and Rand index (RI). Sixty-one gold approximations of ground truth images were manually prepared to assess the segmentation results. Thirty-two of them were acquired at 10× magnification and 29 of them were acquired at 20× magnification. The proposed algorithm exhibits better segmentation performance with an average DICE coefficient equal to 52.25%, accuracy 99.74%, FNR 41.8% and FPR 0.14% and RI 99.49%, based on 61 images.
Activated sludge system is generally used in wastewater treatment plants for processing domestic influent. Conventionally the activated sludge wastewater treatment is monitored by measuring physico-chemical parameters like total suspended solids (TSSol), sludge volume index (SVI) and chemical oxygen demand (COD) etc. For the measurement, tests are conducted in the laboratory, which take many hours to give the final measurement. Digital image processing and analysis offers a better alternative not only to monitor and characterize the current state of activated sludge but also to predict the future state. The characterization by image processing and analysis is done by correlating the time evolution of parameters extracted by image analysis of floc and filaments with the physico-chemical parameters. This chapter briefly reviews the activated sludge wastewater treatment; and, procedures of image acquisition, preprocessing, segmentation and analysis in the specific context of activated sludge wastewater treatment. In the latter part additional procedures like z-stacking, image stitching are introduced for wastewater image preprocessing, which are not previously used in the context of activated sludge. Different preprocessing and segmentation techniques are proposed, along with the survey of imaging procedures reported in the literature. Finally the image analysis based morphological parameters and correlation of the parameters with regard to monitoring and prediction of activated sludge are discussed. Hence it is observed that image analysis can play a very useful role in the monitoring of activated sludge wastewater treatment plants.
The fundamental step in brain research deals with recording electroencephalogram (EEG) signals and then investigating the recorded signals quantitatively. Topographic EEG (visual spatial representation of EEG signal) is commonly referred to as brain topomaps or brain EEG maps. In this chapter, full search full search block motion estimation algorithm has been employed to track the brain activity in brain topomaps to understand the mechanism of brain wiring. The behavior of EEG topomaps is examined throughout a particular brain activation with respect to time. Motion vectors are used to track the brain activation over the scalp during the activation period. Using motion estimation it is possible to track the path from the starting point of activation to the final point of activation. Thus it is possible to track the path of a signal across various lobes.
The state of activated sludge wastewater treatment process (AS WWTP) is conventionally identified by physico-chemical measurements which are costly, time-consuming and have associated environmental hazards. Image processing and analysis-based linear regression modeling has been used to monitor the AS WWTP. But it is plant- and state-specific in the sense that it cannot be generalized to multiple plants and states. Generalized classification modeling for state identification is the main objective of this work. By generalized classification, we mean that the identification model does not require any prior information about the state of the plant, and the resultant identification is valid for any plant in any state. In this paper, the generalized classification model for the AS process is proposed based on features extracted using morphological parameters of flocs. The images of the AS samples, collected from aeration tanks of nine plants, are acquired through bright-field microscopy. Feature-selection is performed in context of classification using sequential feature selection and least absolute shrinkage and selection operator. A support vector machine (SVM)-based state identification strategy was proposed with a new agreement solver module for imbalanced data of the states of AS plants. The classification results were compared with state-of-the-art multiclass SVMs (one-vs.-one and one-vs.-all), and ensemble classifiers using the performance metrics: accuracy, recall, specificity, precision, F measure and kappa coefficient (κ). The proposed strategy exhibits better results by identification of different states of different plants with accuracy 0.9423, and κ 0.6681 for the minority class data of bulking.
Image processing and analysis is an effective tool for monitoring and fault diagnosis of activated sludge (AS) wastewater treatment plants. The AS image comprise of flocs (microbial aggregates) and filamentous bacteria. In this paper, nine different approaches are proposed for image segmentation of phase-contrast microscopic (PCM) images of AS samples. The proposed strategies are assessed for their effectiveness from the perspective of microscopic artifacts associated with PCM. The first approach uses an algorithm that is based on the idea that different color space representation of images other than red-green-blue may have better contrast. The second uses an edge detection approach. The third strategy, employs a clustering algorithm for the segmentation and the fourth applies local adaptive thresholding. The fifth technique is based on texture-based segmentation and the sixth uses watershed algorithm. The seventh adopts a split-and-merge approach. The eighth employs Kittler's thresholding. Finally, the ninth uses a top-hat and bottom-hat filtering-based technique. The approaches are assessed, and analyzed critically with reference to the artifacts of PCM. Gold approximations of ground truth images are prepared to assess the segmentations. Overall, the edge detection-based approach exhibits the best results in terms of accuracy, and the texture-based algorithm in terms of false negative ratio. The respective scenarios are explained for suitability of edge detection and texture-based algorithms.
The neglected tropical diseases, echinococcosis, schistosomiasis and toxoplasmosis are all globally widespread zoonotic diseases with potentially harmful consequences. There is very limited data available on the prevalence of these infections, except for schistosmiasis, in underdeveloped countries. This study aimed to determine the seroprevalence of Echinococcus multilocularis, Schistosoma mansoni, and Toxoplasma gondii antibodies in populations from the Monduli and Babati districts in Tanzania.
In this study, the seroprevalence of sparganosis and its relationship with sociodemographic factors in northern Tanzania have been assessed. A total of 216 serum samples from two rural districts, Monduli and Babati, were tested for sparganosis using an enzyme-linked immunosorbent assay. The seroprevalence of anti-sparganum IgG antibodies was 62.5% (95% confidence interval [CI] = 56.1-68.9) in all age groups. There were significant associations between district (relative risk [RR] = 1.95, 95% CI = 1.42-2.69), education (RR = 1.40, 95% CI = 1.15-1.70), and pet ownership with seropositivity (RR = 1.48, 95% CI = 1.02-2.16) based on univariate analysis. However, only the district was significantly associated with seropositivity (odds ratio = 4.20, 95% CI = 1.89-9.32) in binary logistic regression analysis. Providing health education to people residing in sparganosis-endemic areas is likely to improve the efficacy of preventative measures and reduce human disease burden.
Bangladesh is currently experiencing significant infrastructural development in road networking system through the construction or reconstruction of multiple roads and highways. Consequently, there is a rise in traffic intensity on roads and highways, along with a significant contamination of adjacent agricultural soils with heavy metals. The purpose of this study was to evaluate the ecological risk, health risk and the abundance of seven heavy metals (Cu, Mn, Pb, Cd, Cr, As, and Ni) in three distance gradients (0, 300, and 500 m) of agricultural soil along the Dhaka-Chattogram highway. The concentration of heavy metals was measured with an Atomic Absorption Spectrophotometer (AAS) on a total of 36 soil samples that were taken from 12 different sampling sites. Based on the findings, Cd had a high contamination factor for all distance gradients, whereas Cr had a moderate contamination factor in 67% of the study areas. According to the Pollution Load Index (PLI), Cd, Cr, and Pb were the predominant pollutants. Principal component analysis (PCA) result shows these metals mainly came from anthropogenic sources. The considerable positive correlations between Cu-Pb, Cu-Cd, Pb-Cd, and Cr-Ni all pointed to shared anthropogenic origins. As per Potential Ecological Risk Assessment (PERI) analysis, Pb, Cd, Cr, and Ni each contribute significantly and pose a moderate threat. The Target Hazard Quotient (THQ) values for all pathways of exposure to Pb and Cr in soils were more than 1, which would pose a significant risk to human health in the following order: THQadult female > THQadult male > THQchildren. This study will help to evaluate the human health risk and develop a better understanding of the heavy metal abundance scenario in the agricultural fields adjacent to this highway.
Zoonotic cases of Plasmodium knowlesi account for most malaria cases in Malaysia, and humans infected with P. cynomolgi, another parasite of macaques have recently been reported in Sarawak. To date the epidemiology of malaria in its natural Macaca reservoir hosts remains little investigated. In this study we surveyed the prevalence of simian malaria in wild macaques of three states in Peninsular Malaysia, namely Pahang, Perak and Johor using blood samples from 103 wild macaques (collected by the Department of Wildlife and National Parks Peninsular Malaysia) subjected to microscopic examination and nested PCR targeting the Plasmodium small subunit ribosomal RNA gene. As expected, PCR analysis yielded significantly higher prevalence (64/103) as compared to microscopic examination (27/103). No relationship between the age and/or sex of the macaques with the parasitaemia and the Plasmodium species infecting the macaques could be identified. Wild macaques in Pahang had the highest prevalence of Plasmodium parasites (89.7%), followed by those of Perak (69.2%) and Johor (28.9%). Plasmodium inui and P. cynomolgi were the two most prevalent species infecting the macaques from all three states. Half of the macaques (33/64) harboured two or more Plasmodium species. These data provide a baseline survey, which should be extended by further longitudinal investigations that should be associated with studies on the bionomics of the anopheline vectors. This information will allow an accurate evaluation of the risk of zoonotic transmission to humans, and to elaborate effective strategies to control simian malaria.
The sequence diversity of natural and laboratory populations of Brugia pahangi and Brugia malayi was assessed with Illumina resequencing followed by mapping in order to identify single nucleotide variants and insertions/deletions. In natural and laboratory Brugia populations, there is a lack of sequence diversity on chromosome X relative to the autosomes (πX/πA = 0.2), which is lower than the expected (πX/πA = 0.75). A reduction in diversity is also observed in other filarial nematodes with neo-X chromosome fusions in the genera Onchocerca and Wuchereria, but not those without neo-X chromosome fusions in the genera Loa and Dirofilaria. In the species with neo-X chromosome fusions, chromosome X is abnormally large, containing a third of the genetic material such that a sizable portion of the genome is lacking sequence diversity. Such profound differences in genetic diversity can be consequential, having been associated with drug resistance and adaptability, with the potential to affect filarial eradication.