32 research outputs found
Psychological consultancy in mental health teams
No full textLiterature Review:
Psychological consultation is a common activity in mental health services, but evidence concerning its theoretical grounding, processes, and outcomes are relatively rare. Fifteen mixed method consultation studies were included in the review. Studies were assessed for methodological quality, and found to range from limited to strong. Cognitive behavioural consultation was the main approach used and consultation was most frequently delivered via formulation meetings. Psychological consultation appears to particularly improve staff understanding about clients and consultants should remain visible and accessible to teams. Practical and methodological developments are suggested to the consultation evidence base.
Research Report:
This empirical study aimed to measure the effectiveness of cognitive analytic consultancy (CAC) offered within a community team and then to explore the possible mechanisms of change. An A-B with follow-up small N case series (N=5) design was used that utilised a mixed methodology employing outcome measures and semi-structured interviews. There were significant improvements in client fragmentation, staff competence and emotional exhaustion, and alliance from a client perspective. Potential mechanism of change included the therapists approach, using the sequential diagrammatic reformulation, and acknowledging that difficult processes helped recovery. Further head-to-head trials comparing CAC to other consultation frameworks appears warranted
Relative Importance of explicative variable from nine candidate models: sum of w AICc (chance of a model to be selected, which range from 0 to 1) of all the models where a variable were included.
No full textHigher values define more important variables. Values higher than 0.50 are in boldface.</p
Potential extinction debt estimated by the number of sensitive bird species, based on 1978 patch size as predictive variable (model in the chart) in Pontal do Paranapanema, SP-Brazil.
No full textPotential extinction debt estimated by the number of sensitive bird species, based on 1978 patch size as predictive variable (model in the chart) in Pontal do Paranapanema, SP-Brazil.</p
Generalized Silver Codes
No full textFor an nt transmit, nr receive antenna system (nt × nt system), a full-rate space time block code (STBC) transmits at least nmin = min(nt,nr) complex symbols per channel use. The well-known Golden code is an example of a full-rate, full-diversity STBC for two transmit antennas. Its ML-decoding complexity is of the order of M2.5 for square M-QAM. The Silver code for two transmit antennas has all the desirable properties of the Golden code except its coding gain, but offers lower ML-decoding complexity of the order of M2. Importantly, the slight loss in coding gain is negligible compared to the advantage it offers in terms of lowering the ML-decoding complexity. For higher number of transmit antennas, the best known codes are the Perfect codes, which are full-rate, full-diversity, information lossless codes (for nr ≥ nt) but have a high ML-decoding complexity of the order of Mntnmin (for nr ≥ nt, the punctured Perfect codes are considered). In this paper, a scheme to obtain full-rate STBCs for 2a transmit antennas and any nr with reduced ML-decoding complexity of the order of Mnt(nmin-3/4)-0.5 is presented. The codes constructed are also information lossless for nr ≥ nt, like the Perfect codes, and allow higher mutual information than the comparable punctured Perfect codes for nr ≥ nt. These codes are referred to as the generalized Silver codes, since they enjoy the same desirable properties as the comparable Perfect codes (except possibly the coding gain) with lower ML-decoding complexity, analogous to the Silver code and the Golden code for two transmit antennas. Simulation results of the symbol error rates for four and eight transmit antennas show that the generalized Silver codes match the punctured Perfect codes in error performance while offering lower ML-decoding complexity
Landscape variables for the nine candidate models of linear regression: multiple (m01–m03, considering only the additive effect of explicative variables and m10 –m12, considering the interactive effect of explicative variables) and simple regression (m04–m09).
No full textThe variables AREA and PROX represent the logarithm of patch area and degree of proximity calculated for different dates in the Pontal do Paranapanema, Brazil.</p
Location of Pontal do Paranapanema region and its changes in forest cover.
No full textLocation of Pontal do Paranapanema region and its changes in forest cover.</p
Best regression models selected (Δi AICc < 2) that explain the variation of <i>bird groups’ richness</i>, using AICc, including: pseudo R<sup>2</sup> –coefficients of determination; AICc–the model distance to the “real” model; Δi AICc–relative value of AICc and w AICc–Akaike’s weight, chance for the model to be selected.
No full textBest regression models selected (Δi AICc bird groups’ richness, using AICc, including: pseudo R2 –coefficients of determination; AICc–the model distance to the “real” model; Δi AICc–relative value of AICc and w AICc–Akaike’s weight, chance for the model to be selected.</p
Variation across time in percentage of forest (PF), the mean Euclidean distance to nearest neighbor among the patches (ENN), number of patches (NP), and mean largest patches size (MLP), in Pontal do Paranapanema region.
No full textVariation across time in percentage of forest (PF), the mean Euclidean distance to nearest neighbor among the patches (ENN), number of patches (NP), and mean largest patches size (MLP), in Pontal do Paranapanema region.</p
List of species probably most susceptible to local extinction following community relaxation in forest fragments.
No full textList of species probably most susceptible to local extinction following community relaxation in forest fragments.</p
Patterns of diversity for threatened and data deficient species in Brazil.
No full text<p>Threatened species are those listed as Vulnerable, Endangered, or Critically Endangered on the IUCN Red List.</p
