Evaluation of WGS-subtyping methods for epidemiological surveillance of foodborne salmonellosis

Background: Salmonellosis is one of the most common foodborne diseases worldwide. Although human infection by non-typhoidal Salmonella (NTS) enterica subspecies enterica is associated primarily with a self-limiting diarrhoeal illness, invasive bacterial infections (such as septicaemia, bacteraemia and meningitis) were also reported. Human outbreaks of NTS were reported in several countries all over the world including developing as well as high-income countries. Conventional laboratory methods such as pulsed field gel electrophoresis (PFGE) do not display adequate discrimination and have their limitations in epidemiological surveillance. It is therefore very crucial to use accurate, reliable and highly discriminative subtyping methods for epidemiological characterisation and outbreak investigation. Methods: Here, we used different whole genome sequence (WGS)-based subtyping methods for retrospective investigation of two different outbreaks of Salmonella Typhimurium and Salmonella Dublin that occurred in 2013 in UK and Ireland respectively. Results: Single nucleotide polymorphism (SNP)-based cluster analysis of Salmonella Typhimurium genomes revealed well supported clades, that were concordant with epidemiologically defined outbreak and confirmed the source of outbreak is due to consumption of contaminated mayonnaise. SNP-analyses of Salmonella Dublin genomes confirmed the outbreak however the source of infection could not be determined. The core genome multilocus sequence typing (cgMLST) was discriminatory and separated the outbreak strains of Salmonella Dublin from the non-outbreak strains that were concordant with the epidemiological data however cgMLST could neither discriminate between the outbreak and non-outbreak strains of Salmonella Typhimurium nor confirm that contaminated mayonnaise is the source of infection, On the other hand, other WGS-based subtyping methods including multilocus sequence typing (MLST), ribosomal MLST (rMLST), whole genome MLST (wgMLST), clustered regularly interspaced short palindromic repeats (CRISPRs), prophage sequence profiling, antibiotic resistance profile and plasmid typing methods were less discriminatory and could not confirm the source of the outbreak. Conclusions: Foodborne salmonellosis is an important concern for public health therefore, it is crucial to use accurate, reliable and highly discriminative subtyping methods for epidemiological surveillance and outbreak investigation. In this study, we showed that SNP-based analyses do not only have the ability to confirm the occurrence of the outbreak but also to provide definitive evidence of the source of the outbreak in real-time

Image compression based on 2D Discrete Fourier Transform and matrix minimization algorithm

In the present era of the internet and multimedia, image compression techniques are essential to improve image and video performance in terms of storage space, network bandwidth usage, and secure transmission. A number of image compression methods are available with largely differing compression ratios and coding complexity. In this paper we propose a new method for compressing high-resolution images based on the Discrete Fourier Transform (DFT) and Matrix Minimization (MM) algorithm. The method consists of transforming an image by DFT yielding the real and imaginary components. A quantization process is applied to both components independently aiming at increasing the number of high frequency coefficients. The real component matrix is separated into Low Frequency Coefficients (LFC) and High Frequency Coefficients (HFC). Finally, the MM algorithm followed by arithmetic coding is applied to the LFC and HFC matrices. The decompression algorithm decodes the data in reverse order. A sequential search algorithm is used to decode the data from the MM matrix. Thereafter, all decoded LFC and HFC values are combined into one matrix followed by the inverse DFT. Results demonstrate that the proposed method yields high compression ratios over 98% for structured light images with good image reconstruction. Moreover, it is shown that the proposed method compares favorably with the JPEG technique based on compression ratios and image quality

Mitigation of Side-Effect Modulation in Optical OFDM VLC Systems

Side-effect modulation (SEM) has the potential to be a significant source of interference in future visible light communication (VLC) systems. SEM is a variation in the intensity of the light emitted by a luminaire and is usually a side-effect caused by the power supply used to drive the luminaires. For LED luminaires powered by a switched mode power supply, the SEM can be at much higher frequencies than that emitted by conventional incandescent or fluorescent lighting. It has been shown that the SEM caused by commercially available LED luminaires is often periodic and of low power. In this paper, we investigate the impact of typical forms of SEM on the performance of optical OFDM VLC systems; both ACO-OFDM and DCO-OFDM are considered. Our results show that even low levels of SEM power can significantly degrade the bit-error-rate performance. To solve this problem, an SEM mitigation scheme is described. The mitigation scheme is decision-directed and is based on estimating and subtracting the fundamental component of the SEM from the received signal. We describe two forms of the algorithm; one uses blind estimation while the other uses pilot-assisted estimation based on a training sequence. Decision errors, resulting in decision noise, limit the performance of the blind estimator even when estimation is based on very long signals. However, the pilot system can achieve more accurate estimations, thus better performance. Results are first presented for typical SEM waveforms for the case where the fundamental frequency of the SEM is known. The algorithms are then extended to include a frequency estimation step and the mitigation algorithm is shown also to be effective in this case

Enhancing suicide risk assessment through the use of visual metaphor : a thesis presented in partial fulfillment of the requirements for the degree of Master of Health Science in Psychology at Massey University, Albany Campus, New Zealand

Competent assessment and management of the risk of harm is a core competency that mental health professionals are expected to possess. However, despite this expectation, adequate training programs have been lacking for decades and, even when risk assessment training is provided, it is often reported as being insufficient. The literature indicates that training delivery methods often include passive and didactic methods during supervision or seminar sessions. To help enhance the learning of suicide risk factors, some authors proposed a visual metaphor that visually and metaphorically depicts all suicide risk factors. The main purpose of this study was to examine the efficacy of the proposed visual metaphor. A pilot RCT was undertaken to test several hypotheses, all of which predicted that the visual metaphor would demonstrate superior effects when compared with the conventional textual teaching methods. A group of 22 psychology students were randomized into either a control group (who learnt suicide risk factors via the conventional textual teaching methods) or a treatment group (that learnt the risk factors using the visual metaphor in addition to the conventional textual teaching methods). Memory recall, knowledge transfer, cognitive load, and satisfaction were all tested at the end of the learning sessions. Independent samples t tests indicated that the visual metaphor was effective in improving memory recall and knowledge transfer and reducing the cognitive load. The differences between the two groups’ post-learning scores were significant in each of these outcome measures. The treatment group also expressed higher satisfaction levels in comparison to the control group. Overall the visual metaphor of suicide risk factors was found to be superior to the conventional teaching methods in teaching suicide risk factors to university psychology students. Limitations, implications of this study and directions for future research are discussed

The application of combined momentum and blade element theory for aerodynamics performance analysis of rotating blades

In this thesis, a simulation package for the Six Degrees of Freedom (6DOF ) motion of an underwater vehicle is developed. Mathematical modeling of an underwater vehicle is done and the parameters needed to write such a simulation package are obtained from an existing underwater vehicle available in the literature. Basic equations of motion are developed to simulate the motion of the underwater vehicle and the parameters needed for the hydrodynamic modeling of the vehicle is obtained from the available literature. 6DOF simulation package prepared for the underwater vehicle was developed using the MATLAB environment. S-function hierarchy is developed using the same platform with C++ programming language. With the usage of Sfunctions the problems related to the speed of the platform have been eliminated. The use of S- function hierarchy brought out the opportunity of running the simulation package on other independent platforms and get results for the simulation. Keywords: Underwater Vehicle Simulation, Virtual Reality Modeling Language (VRML ), MATLAB S-function, Simulink, C++, 6DOF