Jets from young stars and brown dwarfs

The protostellar outflow mechanism operates for a significant fraction of the pre-main sequence phase of a solar mass star and is thought to have a key role in star and perhaps even planet formation. This energetic mechanism manifests itself in several different forms and on many scales. Thus outflow activity can be probed in numerous different regimes from radio to X-ray wavelengths. Recent discoveries have shown that it is not only solar mass stars that launch outflows during their formation but also the sub-stellar brown dwarfs. In this article what is currently known about jets from young stars is summarised, including an outline of why it is important to study jets. The second part of this article is dedicated to jets from young brown dwarfs. While only a small number of brown dwarf outflows have been investigated to date, interesting properties have been observed. Here observations of brown dwarf outflows are described and what is currently known of their properties compared to low mass protostellar outflows.Comment: Astronomische Nachrichten, Special Issue: Reviews in Modern Astrononm

HH 1158: The lowest luminosity externally irradiated Herbig-Haro jet

We have identified a new externally irradiated Herbig-Haro (HH) jet, HH 1158, within ~2 pc of the massive OB type stars in the sigma Orionis cluster. At an Lbol ~ 0.1 Lsun, HH 1158 is the lowest luminosity irradiated HH jet identified to date in any cluster. Results from the analysis of high-resolution optical spectra indicate asymmetries in the brightness, morphology, electron density, velocity, and the mass outflow rates for the blue and red-shifted lobes. We constrain the position angle of the HH 1158 jet at 102+/-5 degree. The mass outflow rate and the mean accretion rate for HH 1158 using multiple diagnostics are estimated to be (5.2 +/- 2.6) x 10^(-10) Msun/yr and (3.0 +/- 1.0) x 10^(-10) Msun/yr, respectively. The properties for HH 1158 are notably similar to the externally irradiated HH 444 -- HH 447 jets previously identified in sigma Orionis. In particular, the morphology is such that the weaker jet beam is tilted towards the massive stars, indicating a higher extent of photo-evaporation. The high value for the Halpha/[SII] ratio is also consistent with the ratios measured in other irradiated jets, including HH 444 -- HH 447. The presence of an extended collimated jet that is bipolar and the evidence of shocked emission knots make HH 1158 the first unique case of irradiated HH jets at the very low-luminosity end, and provides an opportunity to learn the physical properties of very faint HH jet sources.Comment: Accepted in ApJ Letter

Are ethical predisposition and governance critical for success in National Health Service construction projects in England?

Critical success factors (CSF) for project success have been studied for nearly half a century, but there are few studies on governance and none on ethical predisposition as a CSF for project success. Although governance and ethical predisposition may appear to be unconnected, they are not. Governance is an organisation’s codified expression of moral behaviour, a set of rules that require compliance. Ethical predisposition is an individual’s preference for judging whether an act is moral based on following the rules or the outcome of one’s actions. As ethical predisposition affects decisions about the value of rules compliance, an understanding of ethical pre-disposition is helpful in the study of governance. Rationale: The NHS is a large user of construction services and the UK Government’s 2019 investment plan for investment healthcare infrastructure suggests that it will continue to be so. Successful project outcome is vital because of the negative impact that late, over budget and poor-quality NHS projects have on service provision and public finances. Aim: To investigate whether ethical predisposition and governance are CSFs for construction projects in the English NHS. Research Questions: Question 1 a) What is the ethical predisposition of project personnel in English NHS construction projects? b) What impact does ethical predisposition have on project success English NHS construction projects? Question 2: What impact do corporate and project governance have on English NHS construction projects? Objectives: to explore the ethical predisposition of client-side personnel in the delivery of construction projects; examine the relationship between ethical predisposition and project success; examine the relationship between project governance and project success; explain how success is measured and develop a project assurance model to guide project sponsors in the establishment of good governance in projects A mixed methods explanatory approach was employed using a survey and six follow-up face-to-face interviews. The survey revealed the predominance of rules-following, low effectiveness of corporate governance and evidence that time, cost and quality are not the main measures of project success. Statistical analysis showed weak correlation between ethical predisposition and governance and project success. Interviews suggested that culture, the trust board’s project oversight, and the lack of knowledge about project performance in the operational phase need to be addressed. It was concluded that ethical predisposition and governance are not levers for success, but rather should be adopted as measures of success because they are associated with openness, transparency and public confidence. Measurement of project success should be carried out at the end of the project management phase and during the operational phase. A Project Assurance Model (PAM) was developed to guide corporate boards in their stewardship of projects in the project management and operational phases

Automatic segmentation of skin cancer images using adaptive color clustering

This paper presents the development of an adaptive image segmentation algorithm designed for the identification of the skin cancer and pigmented lesions in dermoscopy images. The key component of the developed algorithm is the Adaptive Spatial K-Means (A-SKM) clustering technique that is applied to extract the color features from skin cancer images. Adaptive-SKM is a novel technique that includes the primary features that describe the color smoothness and texture complexity in the process of pixel assignment. The A-SKM has been included in the development of a flexible color-texture image segmentation scheme and the experimental data indicates that the developed algorithm is able to produce accurate segmentation when applied to a large number of skin cancer (melanoma) images

Color image segmentation using a spatial k-means clustering algorithm

This paper details the implementation of a new adaptive technique for color-texture segmentation that is a generalization of the standard K-Means algorithm. The standard K-Means algorithm produces accurate segmentation results only when applied to images defined by homogenous regions with respect to texture and color since no local constraints are applied to impose spatial continuity. In addition, the initialization of the K-Means algorithm is problematic and usually the initial cluster centers are randomly picked. In this paper we detail the implementation of a novel technique to select the dominant colors from the input image using the information from the color histograms. The main contribution of this work is the generalization of the K-Means algorithm that includes the primary features that describe the color smoothness and texture complexity in the process of pixel assignment. The resulting color segmentation scheme has been applied to a large number of natural images and the experimental data indicates the robustness of the new developed segmentation algorithm

Adaptive pre-filtering techniques for colour image analysis

One important step in the process of colour image segmentation is to reduce the errors caused by image noise and local colour inhomogeneities. This can be achieved by filtering the data with a smoothing operator that eliminates the noise and the weak textures. In this regard, the aim of this paper is to evaluate the performance of two image smoothing techniques designed for colour images, namely bilateral filtering for edge preserving smoothing and coupled forward and backward anisotropic diffusion scheme (FAB). Both techniques are non-linear and have the purpose of eliminating the image noise, reduce weak textures and artefacts and improve the coherence of colour information. A quantitative comparison between them will be evaluated and also the ability of such techniques to preserve the edge information will be investigated

Color image segmentation using a self-initializing EM algorithm

This paper presents a new method based on the Expectation-Maximization (EM) algorithm that we apply for color image segmentation. Since this algorithm partitions the data based on an initial set of mixtures, the color segmentation provided by the EM algorithm is highly dependent on the starting condition (initialization stage). Usually the initialization procedure selects the color seeds randomly and often this procedure forces the EM algorithm to converge to numerous local minima and produce inappropriate results. In this paper we propose a simple and yet effective solution to initialize the EM algorithm with relevant color seeds. The resulting self initialised EM algorithm has been included in the development of an adaptive image segmentation scheme that has been applied to a large number of color images. The experimental data indicates that the refined initialization procedure leads to improved color segmentation

Evaluation of local orientation for texture classification

The aim of this paper is to present a study where we evaluate the optimal inclusion of the texture orientation in the classification process. In this paper the orientation for each pixel in the image is extracted using the partial derivatives of the Gaussian function and the main focus of our work is centred on the evaluation of the local dominant orientation (which is calculated by combining the magnitude and local orientation) on the classification results. While the dominant orientation of the texture depends strongly on the observation scale, in this paper we propose to evaluate the macro-texture by calculating the distribution of the dominant orientations for all pixels in the image that sample the texture at micro-level. The experimental results were conducted on standard texture databases and the results indicate that the dominant orientation calculated at micro-level is an appropriate measure for texture description

Performance characterization of clustering algorithms for colour image segmentation

This paper details the implementation of three traditional clustering techniques (K-Means clustering, Fuzzy C-Means clustering and Adaptive K-Means clustering) that are applied to extract the colour information that is used in the image segmentation process. The aim of this paper is to evaluate the performance of the analysed colour clustering techniques for the extraction of optimal features from colour spaces and investigate which method returns the most consistent results when applied on a large suite of mosaic images

Fully automated segmentation and tracking of the intima media thickness in ultrasound video sequences of the common carotid artery

Abstract—The robust identification and measurement of the intima media thickness (IMT) has a high clinical relevance because it represents one of the most precise predictors used in the assessment of potential future cardiovascular events. To facilitate the analysis of arterial wall thickening in serial clinical investigations, in this paper we have developed a novel fully automatic algorithm for the segmentation, measurement, and tracking of the intima media complex (IMC) in B-mode ultrasound video sequences. The proposed algorithm entails a two-stage image analysis process that initially addresses the segmentation of the IMC in the first frame of the ultrasound video sequence using a model-based approach; in the second step, a novel customized tracking procedure is applied to robustly detect the IMC in the subsequent frames. For the video tracking procedure, we introduce a spatially coherent algorithm called adaptive normalized correlation that prevents the tracking process from converging to wrong arterial interfaces. This represents the main contribution of this paper and was developed to deal with inconsistencies in the appearance of the IMC over the cardiac cycle. The quantitative evaluation has been carried out on 40 ultrasound video sequences of the common carotid artery (CCA) by comparing the results returned by the developed algorithm with respect to ground truth data that has been manually annotated by clinical experts. The measured IMTmean ± standard deviation recorded by the proposed algorithm is 0.60 mm ± 0.10, with a mean coefficient of variation (CV) of 2.05%, whereas the corresponding result obtained for the manually annotated ground truth data is 0.60 mm ± 0.11 with a mean CV equal to 5.60%. The numerical results reported in this paper indicate that the proposed algorithm is able to correctly segment and track the IMC in ultrasound CCA video sequences, and we were encouraged by the stability of our technique when applied to data captured under different imaging conditions. Future clinical studies will focus on the evaluation of patients that are affected by advanced cardiovascular conditions such as focal thickening and arterial plaques