Anisotropic excitation spectra of GaAs/AlGaAs quantum wells grown on vicinal plane substrates

We report measurements of the photoluminescence excitation spectra of a series of GaAs/AlGaAs quantum well samples grown on vicinal plane substrates with differing off‐cut angles. When the plane of polarization of the exciting light is changed we have observed a clear variation in the ratio of the strength of the n=1 light and heavy hole exciton transitions in samples grown on vicinal plane substrates. This behavior is attributed to anisotropic scattering at steps in the heterointerface

InGaN micro-LEDs integrated onto an ultra-thin, colloidal quantum dot functionalized glass platform

We demonstrate an integrated color-converting device by transfer printing blue-emitting micro-sized InGaN LEDs onto an ultra-thin glass platform functionally enhanced with colloidal quantum dots. Color conversion and waveguiding properties of the structure are presented

Transfer printed multi-color integrated devices for visible light communication applications

Integrated multi-color devices for visible light communication applications are fabricated by transfer printing blue-emitting GaN light emitting diodes (LEDs) onto a green-emitting LED array and a colloidal quantum dot color-converter structure

Identifying key factors of student academic performance by subgroup discovery

Published online: 21 June 2018Identifying the factors that influence student academic performance is essential to provide timely and effective support interventions. The data collected during enrolment and after commencement into a course provide an important source of information to assist with identifying potential risk indicators associated with poor academic performance and attrition. Both predictive and descriptive data mining techniques have been applied on educational data to discover the significant reasons behind student performance. These techniques have their own advantages and limitations. For example, predictive techniques tend to maximise accuracy for correctly classifying students, while the descriptive techniques simply search for interesting student features without considering their academic outcome. Subgroup discovery is a data mining method which takes the advantages of both predictive and descriptive approaches. This study uses subgroup discovery to extract significant factors of student performance for a certain outcome (Pass or Fail). In thiswork, we have utilised student demographic and academic data recorded at enrolment, aswell as course assessment and participation data retrieved from the institution’s learning management system (Moodle) to detect the factors affecting student performance. The results have demonstrated the effectiveness of the subgroup discovery method in general in identifying the factors, and the pros and cons of some popular subgroup discovery algorithms used in this research. From the experiments, it has been found that students, who have indigent socio-economic background or been admitted based on special entry requirement, are most likely to fail. The experiments on Moodle data have revealed that students having lower level of access to the course resources and forum have higher possibility of being unsuccessful. From the combined data, we have identified some interesting subgroups which are not detected using enrolment or Moodle data separately. It has been found that those students, who study off-campus or part-time and have a low level of contributions to the course learning activities, are more likely to be the low-performing students.Sumyea Helal, Jiuyong Li, Lin Liu, Esmaeil Ebrahimie, Shane Dawson, Duncan J. Murra

Magnetic fields and Sunyaev-Zel'dovich effect in galaxy clusters

In this work we study the contribution of magnetic fields to the Sunyaev Zeldovich (SZ) effect in the intracluster medium. In particular we calculate the SZ angular power spectrum and the central temperature decrement. The effect of magnetic fields is included in the hydrostatic equilibrium equation by splitting the Lorentz force into two terms one being the force due to magnetic pressure which acts outwards and the other being magnetic tension which acts inwards. A perturbative approach is adopted to solve for the gas density profile for weak magnetic fields (< 4 micro G}). This leads to an enhancement of the gas density in the central regions for nearly radial magnetic field configurations. Previous works had considered the force due to magnetic pressure alone which is the case only for a special set of field configurations. However, we see that there exists possible sets of configurations of ICM magnetic fields where the force due to magnetic tension will dominate. Subsequently, this effect is extrapolated for typical field strengths (~ 10 micro G) and scaling arguments are used to estimate the angular power due to secondary anisotropies at cluster scales. In particular we find that it is possible to explain the excess power reported by CMB experiments like CBI, BIMA, ACBAR at l > 2000 with sigma_8 ~ 0.8 (WMAP 5 year data) for typical cluster magnetic fields. In addition we also see that the magnetic field effect on the SZ temperature decrement is more pronounced for low mass clusters ( ~ 2 keV). Future SZ detections of low mass clusters at few arc second resolution will be able to probe this effect more precisely. Thus, it will be instructive to explore the implications of this model in greater detail in future works.Comment: 20 pages, 8 figure

Examining the Higgs boson potential at lepton and hadron colliders: a comparative analysis

We investigate inclusive Standard Model Higgs boson pair production at lepton and hadron colliders for Higgs boson masses in the range 120 GeV < m_H < 200 GeV. For m_H < 140 GeV we find that hadron colliders have a very limited capability to determine the Higgs boson self-coupling, \lambda, due to an overwhelming background. We also find that, in this mass range, supersymmetric Higgs boson pairs may be observable at the LHC, but a measurement of the self coupling will not be possible. For m_H > 140 GeV we examine ZHH and HH nu bar-nu production at a future e+e- linear collider with center of mass energy in the range of sqrt{s}=0.5 - 1 TeV, and find that this is likely to be equally difficult. Combining our results with those of previous literature, which has demonstrated the capability of hadron and lepton machines to determine \lambda in either the high or the low mass regions, we establish a very strong complementarity of these machines.Comment: Revtex, 25 pages, 2 tables, 10 figure

Self-consistent description of nuclear compressional modes

Isoscalar monopole and dipole compressional modes are computed for a variety of closed-shell nuclei in a relativistic random-phase approximation to three different parametrizations of the Walecka model with scalar self-interactions. Particular emphasis is placed on the role of self-consistency which by itself, and with little else, guarantees the decoupling of the spurious isoscalar-dipole strength from the physical response and the conservation of the vector current. A powerful new relation is introduced to quantify the violation of the vector current in terms of various ground-state form-factors. For the isoscalar-dipole mode two distinct regions are clearly identified: (i) a high-energy component that is sensitive to the size of the nucleus and scales with the compressibility of the model and (ii) a low-energy component that is insensitivity to the nuclear compressibility. A fairly good description of both compressional modes is obtained by using a ``soft'' parametrization having a compression modulus of K=224 MeV.Comment: 28 pages and 10 figures; submitted to PR

New hadrons as ultra-high energy cosmic rays

Ultra-high energy cosmic ray (UHECR) protons produced by uniformly distributed astrophysical sources contradict the energy spectrum measured by both the AGASA and HiRes experiments, assuming the small scale clustering of UHECR observed by AGASA is caused by point-like sources. In that case, the small number of sources leads to a sharp exponential cutoff at the energy E<10^{20} eV in the UHECR spectrum. New hadrons with mass 1.5-3 GeV can solve this cutoff problem. For the first time we discuss the production of such hadrons in proton collisions with infrared/optical photons in astrophysical sources. This production mechanism, in contrast to proton-proton collisions, requires the acceleration of protons only to energies E<10^{21} eV. The diffuse gamma-ray and neutrino fluxes in this model obey all existing experimental limits. We predict large UHE neutrino fluxes well above the sensitivity of the next generation of high-energy neutrino experiments. As an example we study hadrons containing a light bottom squark. These models can be tested by accelerator experiments, UHECR observatories and neutrino telescopes.Comment: 17 pages, revtex style; v2: shortened, as to appear in PR

Relating constructs of attention and working memory to social withdrawal in Alzheimer's disease and schizophrenia: issues regarding paradigm selection

Central nervous system diseases are not currently diagnosed based on knowledge of biological mechanisms underlying their symptoms. Greater understanding may be offered through an agnostic approach to traditional disease categories, where learning more about shared biological mechanisms across conditions could potentially reclassify sub-groups of patients to allow realisation of more effective treatments. This review represents the output of the collaborative group “PRISM”, tasked with considering assay choices for assessment of attention and working memory in a transdiagnostic cohort of Alzheimer''s disease and schizophrenia patients exhibiting symptomatic spectra of social withdrawal. A multidimensional analysis of this nature has not been previously attempted. Nominated assays (continuous performance test III, attention network test, digit symbol substitution, N-back, complex span, spatial navigation in a virtual environment) reflected a necessary compromise between the need for broad assessment of the neuropsychological constructs in question with several pragmatic criteria: patient burden, compatibility with neurophysiologic measures and availability of preclinical homologues

Relating constructs of attention and working memory to social withdrawal in Alzheimer's disease and schizophrenia: issues regarding paradigm selection

Central nervous system diseases are not currently diagnosed based on knowledge of biological mechanisms underlying their symptoms. Greater understanding may be offered through an agnostic approach to traditional disease categories, where learning more about shared biological mechanisms across conditions could potentially reclassify sub-groups of patients to allow realisation of more effective treatments. This review represents the output of the collaborative group "PRISM", tasked with considering assay choices for assessment of attention and working memory in a transdiagnostic cohort of Alzheimer's disease and schizophrenia patients exhibiting symptomatic spectra of social withdrawal. A multidimensional analysis of this nature has not been previously attempted. Nominated assays (continuous performance test III, attention network test, digit symbol substitution, N-back, complex span, spatial navigation in a virtual environment) reflected a necessary compromise between the need for broad assessment of the neuropsychological constructs in question with several pragmatic criteria: patient burden, compatibility with neurophysiologic measures and availability of preclinical homologues