A qualitative study to explore the help seeking views relating to depression among older Black Caribbean adults living in the UK

Numbers of older adults are rising globally. In the UK, rates of mental ill-health are thought to be higher in Black Asian and Minority Ethnic community than in the white population. Older adults from BAME groups are an under researched group. It is important to understand the experiences and beliefs that underlie help seeking behaviour among BAME older adults to deliver effective, culturally appropriate and accessible services. This study aims to explore help seeking views and strategies utilised in relation to depression among older Black Caribbean people in the UK. Semi-structured interviews were conducted with 8 UK Black Caribbean participants, aged between 65-79 years. Transcripts were analysed using Interpretative Phenomenological Analysis. Three master themes emerged from the analysis: 1. “If you don’t know, you don’t seek help 2. ‘..I knew I was depressed”: 3. “You have to decide”: Attitudes to help seeking and mental health service use. Participants’ past personal experiences of coping with depression, including migratory histories, cultural and religious views and personal relationships influenced their help seeking views and preferred coping methods for depression

Analysis and application of digital spectral warping in analog and mixed-signal testing

Spectral warping is a digital signal processing transform which shifts the frequencies contained within a signal along the frequency axis. The Fourier transform coefficients of a warped signal correspond to frequency-domain 'samples' of the original signal which are unevenly spaced along the frequency axis. This property allows the technique to be efficiently used for DSP-based analog and mixed-signal testing. The analysis and application of spectral warping for test signal generation, response analysis, filter design, frequency response evaluation, etc. are discussed in this paper along with examples of the software and hardware implementation

A multiple testing approach to the regularisation of large sample correlation matrices

This paper proposes a novel regularisation method for the estimation of large covariance matrices, which makes use of insights from the multiple testing literature. The method tests the statistical significance of individual pair-wise correlations and sets to zero those elements that are not statistically significant, taking account of the multiple testing nature of the problem. The procedure is straightforward to implement, and does not require cross validation. By using the inverse of the normal distribution at a predetermined significance level, it circumvents the challenge of evaluating the theoretical constant arising in the rate of convergence of existing thresholding estimators. We compare the performance of our multiple testing (MT) estimator to a number of thresholding and shrinkage estimators in the literature in a detailed Monte Carlo simulation study. Results show that our MT estimator performs well in a number of different settings and tends to outperform other estimators, particularly when the cross-sectional dimension, N, is larger than the time series dimension, T IF the inverse covariance matrix is of interest then we recommend a shrinkage version of the MT estimator that ensures positive definitenes

A multiple testing approach to the regularisation of large sample correlation matrices

This paper proposes a novel regularisation method for the estimation of large covariance matrices, which makes use of insights from the multiple testing literature. The method tests the statistical significance of individual pair-wise correlations and sets to zero those elements that are not statistically significant, taking account of the multiple testing nature of the problem. The procedure is straightforward to implement, and does not require cross validation. By using the inverse of the normal distribution at a predetermined significance level, it circumvents the challenge of evaluating the theoretical constant arising in the rate of convergence of existing thresholding estimators. We compare the performance of our multiple testing (MT) estimator to a number of thresholding and shrinkage estimators in the literature in a detailed Monte Carlo simulation study. Results show that our MT estimator performs well in a number of different settings and tends to outperform other estimators, particularly when the cross-sectional dimension, N, is larger than the time series dimension, T IF the inverse covariance matrix is of interest then we recommend a shrinkage version of the MT estimator that ensures positive definitenes

Field theory of directed percolation with long-range spreading

It is well established that the phase transition between survival and extinction in spreading models with short-range interactions is generically associated with the directed percolation (DP) universality class. In many realistic spreading processes, however, interactions are long ranged and well described by L\'{e}vy-flights, i.e., by a probability distribution that decays in $d$ dimensions with distance $r$ as $r^{-d-\sigma}$. We employ the powerful methods of renormalized field theory to study DP with such long range, L\'{e}vy-flight spreading in some depth. Our results unambiguously corroborate earlier findings that there are four renormalization group fixed points corresponding to, respectively, short-range Gaussian, L\'{e}vy Gaussian, short-range DP and L\'{e}vy DP, and that there are four lines in the $(\sigma, d)$ plane which separate the stability regions of these fixed points. When the stability line between short-range DP and L\'{e}vy DP is crossed, all critical exponents change continuously. We calculate the exponents describing L\'{e}vy DP to second order in $\epsilon$-expansion, and we compare our analytical results to the results of existing numerical simulations. Furthermore, we calculate the leading logarithmic corrections for several dynamical observables.Comment: 12 pages, 3 figure

Mathematical Structure of Relativistic Coulomb Integrals

We show that the diagonal matrix elements $,$ where $O$ $={1,\beta,i\mathbf{\alpha n}\beta}$ are the standard Dirac matrix operators and the angular brackets denote the quantum-mechanical average for the relativistic Coulomb problem, may be considered as difference analogs of the radial wave functions. Such structure provides an independent way of obtaining closed forms of these matrix elements by elementary methods of the theory of difference equations without explicit evaluation of the integrals. Three-term recurrence relations for each of these expectation values are derived as a by-product. Transformation formulas for the corresponding generalized hypergeometric series are discussed.Comment: 13 pages, no figure

qq-Trinomial identities

We obtain connection coefficients between $q$-binomial and $q$-trinomial coefficients. Using these, one can transform $q$-binomial identities into a $q$-trinomial identities and back again. To demonstrate the usefulness of this procedure we rederive some known trinomial identities related to partition theory and prove many of the conjectures of Berkovich, McCoy and Pearce, which have recently arisen in their study of the $\phi_{2,1}$ and $\phi_{1,5}$ perturbations of minimal conformal field theory.Comment: 21 pages, AMSLate

Cluster Analysis of Thermal Icequakes Using the Seismometer to Investigate Ice and Ocean Structure (SIIOS): Implications for Ocean World Seismology

Ocean Worlds are of high interest to the planetary community due to the potential habitability of their subsurface oceans. Over the next few decades several missions will be sent to ocean worlds including the Europa Clipper, Dragonfly, and possibly a Europa lander. The Dragonfly and Europa lander missions will carry seismic payloads tasked with detecting and locating seismic sources. The Seismometer to Investigate Ice and Ocean Structure (SIIOS) is a NASA PSTAR funded project that investigates ocean world seismology using terrestrial analogs. The goals of the SIIOS experiment include quantitatively comparing flight-candidate seismometers to traditional instruments, comparing single-station approaches to a small-aperture array, and characterizing the local seismic environment of our field sites. Here we present an analysis of detected local events at our field sites at Gulkana Glacier in Alaska and in Northwest Greenland approximately 80 km North of Qaanaaq, Greenland. Both field sites passively recorded data for about two weeks. We deployed our experiment on Gulkana Glacier in September 2017 and in Greenland in June 2018. At Gulkana there was a nearby USGS weather station which recorded wind data. Temperature data was collected using the MERRA satellite. In Greenland we deployed our own weather station to collect temperature and wind data. Gulkana represents a noisier and more active environment. Temperatures fluctuated around 0C, allowing for surface runoff to occur during the day. The glacier had several moulins, and during deployment we heard several rockfalls from nearby mountains. In addition to the local environment, Gulkana is located close to an active plate boundary (relative to Greenland). This meant that there were more regional events recorded over two weeks, than in Greenland. Greenlands local environment was also quieter, and less active. Temperatures remained below freezing. The Greenland ice was much thicker than Gulkana (~850 m versus ~100 m) and our stations were above a subglacial lake. Both conditions can reduce event detections from basal motion. Lastly, we encased our Greenland array in an aluminum vault and buried it beneath the surface unlike our array in Gulkana where the instruments were at the surface and covered with plastic bins. The vault further insulated the array from thermal and atmospheric events

A Generalized Epidemic Process and Tricritical Dynamic Percolation

The renowned general epidemic process describes the stochastic evolution of a population of individuals which are either susceptible, infected or dead. A second order phase transition belonging to the universality class of dynamic isotropic percolation lies between endemic or pandemic behavior of the process. We generalize the general epidemic process by introducing a fourth kind of individuals, viz. individuals which are weakened by the process but not yet infected. This sensibilization gives rise to a mechanism that introduces a global instability in the spreading of the process and therefore opens the possibility of a discontinuous transition in addition to the usual continuous percolation transition. The tricritical point separating the lines of first and second order transitions constitutes a new universality class, namely the universality class of tricritical dynamic isotropic percolation. Using renormalized field theory we work out a detailed scaling description of this universality class. We calculate the scaling exponents in an $\epsilon$-expansion below the upper critical dimension $d_{c}=5$ for various observables describing tricritical percolation clusters and their spreading properties. In a remarkable contrast to the usual percolation transition, the exponents $\beta$ and ${\beta}^{\prime}$ governing the two order parameters, viz. the mean density and the percolation probability, turn out to be different at the tricritical point. In addition to the scaling exponents we calculate for all our static and dynamic observables logarithmic corrections to the mean-field scaling behavior at $d_c=5$.Comment: 21 pages, 10 figures, version to appear in Phys. Rev.