Numerical study of neutron beam divergence in a beam-fusion scenario employing laser driven ions

The most established route to create a laser-based neutron source is by employing laser accelerated, low atomic-number ions in fusion reactions. In addition to the high reaction cross-sections at moderate energies of the projectile ions, the anisotropy in neutron emission is another important feature of beam-fusion reactions. Using a simple numerical model based on neutron generation in a pitcher–catcher scenario, anisotropy in neutron emission was studied for the deuterium–deuterium fusion reaction. Simulation results are consistent with the narrow-divergence ( ∼ 70 ° full width at half maximum) neutron beam recently served in an experiment employing multi-MeV deuteron beams of narrow divergence (up to 30° FWHM, depending on the ion energy) accelerated by a sub-petawatt laser pulse from thin deuterated plastic foils via the Target Normal Sheath Acceleration mechanism. By varying the input ion beam parameters, simulations show that a further improvement in the neutron beam directionality (i.e. reduction in the beam divergence) can be obtained by increasing the projectile ion beam temperature and cut-off energy, as expected from interactions employing higher power lasers at upcoming facilities.

Semantic feature-based visual attention model for pedestrian detection

Objective
Pedestrian detection under video surveillance systems has always been a hot topic in computer vision research. These systems are widely used in train stations, airports, large commercial plazas, and other public places. However, pedestrian detection remains difficult because of complex backgrounds. Given its development in recent years, the visual attention mechanism has attracted increasing attention in object detection and tracking research, and previous studies have achieved substantial progress and breakthroughs. We propose a novel pedestrian detection method based on the semantic features under the visual attention mechanism.
Method
The proposed semantic feature-based visual attention model is a spatial-temporal model that consists of two parts: the static visual attention model and the motion visual attention model. The static visual attention model in the spatial domain is constructed by combining bottom-up with top-down attention guidance. Based on the characteristics of pedestrians, the bottom-up visual attention model of Itti is improved by intensifying the orientation vectors of elementary visual features to make the visual saliency map suitable for pedestrian detection. In terms of pedestrian attributes, skin color is selected as a semantic feature for pedestrian detection. The regional and Gaussian models are adopted to construct the skin color model. Skin feature-based visual attention guidance is then proposed to complete the top-down process. The bottom-up and top-down visual attentions are linearly combined using the proper weights obtained from experiments to construct the static visual attention model in the spatial domain. The spatial-temporal visual attention model is then constructed via the motion features in the temporal domain. Based on the static visual attention model in the spatial domain, the frame difference method is combined with optical flowing to detect motion vectors. Filtering is applied to process the field of motion vectors. The saliency of motion vectors can be evaluated via motion entropy to make the selected motion feature more suitable for the spatial-temporal visual attention model.
Result
Standard datasets and practical videos are selected for the experiments. The experiments are performed on a MATLAB R2012a platform. The experimental results show that our spatial-temporal visual attention model demonstrates favorable robustness under various scenes, including indoor train station surveillance videos and outdoor scenes with swaying leaves. Our proposed model outperforms the visual attention model of Itti, the graph-based visual saliency model, the phase spectrum of quaternion Fourier transform model, and the motion channel model of Liu in terms of pedestrian detection. The proposed model achieves a 93% accuracy rate on the test video.
Conclusion
This paper proposes a novel pedestrian method based on the visual attention mechanism. A spatial-temporal visual attention model that uses low-level and semantic features is proposed to calculate the saliency map. Based on this model, the pedestrian targets can be detected through focus of attention shifts. The experimental results verify the effectiveness of the proposed attention model for detecting pedestrians.

Intraclonal heterogeneity is a critical early event in the development of myeloma and precedes the development of clinical symptoms.

The mechanisms involved in the progression from monoclonal gammopathy of undetermined significance (MGUS) and smoldering myeloma (SMM) to malignant multiple myeloma (MM) and plasma cell leukemia (PCL) are poorly understood but believed to involve the sequential acquisition of genetic hits. We performed exome and whole-genome sequencing on a series of MGUS (n=4), high-risk (HR)SMM (n=4), MM (n=26) and PCL (n=2) samples, including four cases who transformed from HR-SMM to MM, to determine the genetic factors that drive progression of disease. The pattern and number of non-synonymous mutations show that the MGUS disease stage is less genetically complex than MM, and HR-SMM is similar to presenting MM. Intraclonal heterogeneity is present at all stages and using cases of HR-SMM, which transformed to MM, we show that intraclonal heterogeneity is a typical feature of the disease. At the HR-SMM stage of disease, the majority of the genetic changes necessary to give rise to MM are already present. These data suggest that clonal progression is the key feature of transformation of HR-SMM to MM and as such the invasive clinically predominant clone typical of MM is already present at the SMM stage and would be amenable to therapeutic intervention at that stage.

The making of professionals: Embedded civil society development in a transition country

The paper addresses the development of non-governmental organisations (NGOs) in transition settings. Caught in the balance of knowledge exchange and translation of ideas from abroad, organisations in turbulent setting legitimise their existence by learning through professional networks. By association, organisational actors gain acknowledgement by their sector by traversing the corridors of influence provided by international partnerships. What they learn is how to conduct themselves as agents of change in society, and how to deliver on stated missions and goals, therefore, legitimising their presence in a budding civil society at home. The paper presents a knowledge production and learning practices framework which indicates a presence of dual identity of NGOs - their “embeddedness” locally and internationally. Selected framework dimensions and qualitative case study themes are discussed with respect to the level of independence of organisational actors in the East from their partners in the West in a post-socialist context. A professional global civil society as organisations are increasingly managed in similar, professional ways (Anheier & Themudo 2002). Here knowledge “handling” and knowledge “translation” take place through partnership exchanges fostering capable and/or competitive change-inducing institutions (Czarniawska & Sevon 2005; Hwang & Suarez 2005). How professional identity presents itself in the third sector, as well as the sector’s claim to expertise, need further attention, adding to ongoing discussions on professions in institutional theory (Hwang & Powell 2005; Scott 2008; Noordegraaf 2011). A conceptual framework on the dynamic involved for the construction professional fields follows: • Multiple case analysis provides a taxonomy for understanding what is happening in knowledge transition, adaptation, and organisational learning capacity for NGOs with respect to their role in a networked civil society. With the model we can observe the types of knowledge produced and learning employed by organisations. • There are elements of professionalisation in third sector work organisational activity with respect to its accreditation, sources and routines of learning, knowledge claims, interaction with the statutory sector, recognition in cross-sector partnerships etc. • It signals that there is a dual embeddedness in the development of the sector at the core to the shaping the sector’s professional status. This is instrumental in the NGOs’ goal to gain influence as institutions, as they are only one part of a cross-sector mission to address complex societal problems The case study material highlights nuances of knowledge production and learning practices in partnerships, with dual embeddedness a main feature of the findings. This provides some clues to how professionalisation as expert-making takes shape in organisations: • Depending on the type of organisations’ purpose, over its course of development there is an increase in participation in multiple networks, as opposed to reliance on a single strategic partner for knowledge artefacts and practices; • Some types of organisations are better connected within international and national networks than others and there seem to be preferences for each depending on the area of work; • The level of interpretation or adaptation of the knowledge artefacts is related to an organisation’s embeddedness locally, in turn giving it more influence within the network of key institutions; An overreaching theme across taxonomy categories (Table 1)is “professionalisation” or developing organisational “expertise”, embodied at the individual, organisational, and sector levels. Questions relevant to the exercise of power arise: Is competence in managing a dual embeddedness signals the development of a dual identity in professionalisation? Is professionalisation in this sense a sign of organisations maturing into more capable partners to the arguably more experienced (Western) institutions, shifting the power balance? Or is becoming more professional a sign of domestication to the agenda of certain powerful stakeholders, who define the boundaries of the profession? Which dominant dynamics can be observed in a broadly-defined transition country civil society, where individual participation in the form of activism may be overtaking the traditional forms of organised development work, especially with the spread of social media?

Towards optical polarization control of laser-driven proton acceleration in foils undergoing relativistic transparency

Control of the collective response of plasma particles to intense laser light is intrinsic to relativistic optics, the development of compact laser-driven particle and radiation sources, as well as investigations of some laboratory astrophysics phenomena. We recently demonstrated that a relativistic plasma aperture produced in an ultra-thin foil at the focus of intense laser radiation can induce diffraction, enabling polarization-based control of the collective motion of plasma electrons. Here we show that under these conditions the electron dynamics are mapped into the beam of protons accelerated via strong charge-separation-induced electrostatic fields. It is demonstrated experimentally and numerically via 3D particle-in-cell simulations that the degree of ellipticity of the laser polarization strongly influences the spatial-intensity distribution of the beam of multi-MeV protons. The influence on both sheath-accelerated and radiation pressure-accelerated protons is investigated. This approach opens up a potential new route to control laser-driven ion sources.

Feature Selection for Anomaly Detection Using Optical Emission Spectroscopy

To maintain the pace of development set by Moore's law, production processes in semiconductor manufacturing are becoming more and more complex. The development of efficient and interpretable anomaly detection systems is fundamental to keeping production costs low. As the dimension of process monitoring data can become extremely high anomaly detection systems are impacted by the curse of dimensionality, hence dimensionality reduction plays an important role. Classical dimensionality reduction approaches, such as Principal Component Analysis, generally involve transformations that seek to maximize the explained variance. In datasets with several clusters of correlated variables the contributions of isolated variables to explained variance may be insignificant, with the result that they may not be included in the reduced data representation. It is then not possible to detect an anomaly if it is only reflected in such isolated variables. In this paper we present a new dimensionality reduction technique that takes account of such isolated variables and demonstrate how it can be used to build an interpretable and robust anomaly detection system for Optical Emission Spectroscopy data.