Factors influencing community case management and care hours for clients with traumatic brain injury living in the UK

Objective: To investigate the relationship between deficits associated with traumatic brain injury (TBI) and case management (CM) and care/support (CS) in two UK community samples. Research design: Prospective descriptive study. Method: Case managers across the UK and from a single UK CM service contributed client profiles to two data sets (Groups 1 and 2, respectively). Data were entered on demographics, injury severity, functional skills, functional-cognition (including executive functions), behaviour and CM and CS hours. Relationships were explored between areas of disability and service provision. Results: Clients in Group 2 were more severely injured, longer post-injury and had less family support than clients in Group 1. There were few significant differences between Groups 1 and 2 on measures of Functionalskill, Functional-cognition and Behaviour disorder. Deficits in Functionalskills were associated with CS, but not CM. Deficits in measures of executive functions (impulsivity, predictability, response to direction) were related to CM, but not to CS. Insight was related to both CM and CS. Variables related to behaviour disorder were related to CM, but were less often correlated to CS. Conclusions: The need for community support is related not only to Functionalskills (CS), but also to behaviour disorder, self-regulatory skills and impaired insight (CM)

Upper body movement analysis of multiple limb asymmetry in 367 clinically lame horses

Background Compensatory lameness is common in horses and evaluation can be challenging. Objectives To investigate patterns of compensatory movements in clinical cases with fore- or hindlimb lameness before and after diagnostic analgesia. Study design Retrospective clinical study. Methods Multiple limb lameness of 367 horses was characterised by type (push-off, impact or mixed), limb (fore- or hindlimb in predominant lameness) and side (ipsi- or contralateral in concurrent lameness) using a body-mounted inertial sensor (BMIS). Diagnostic analgesia was performed until the percentage improvement of the vector sum in forelimb lameness and the mean difference of the maximum or minimum pelvic height (PDmax or PDmin) in hindlimb lameness was >= 50%. Linear mixed model and post-estimation of effects were performed by contrast command with multiple comparisons adjusted by Bonferroni method. Correlation of pre- and post-analgesia of all head and pelvis asymmetry parameters was tested with Spearman's rank correlation. Results Improvement in vector sum per mm after diagnostic analgesia in forelimb impact lameness positively correlated with decrease in PDmax in contralateral mixed lameness (0.187 mm, r = .58, P < .05). Improvement in PDmin per mm after diagnostic analgesia in hindlimb mixed and PDmax in hindlimb push-off lameness decreased vector sum in ipsilateral forelimb impact lameness by 0.570 and 0.696 mm, respectively (P < .05), with no positive correlation. Main limitations A variety of cases with inhomogeneous distribution of lameness patterns was investigated retrospectively, therefore, it is impossible to distinguish between true multiple limb lameness and compensatory lameness in this clinical material. Conclusions Various asymmetry patterns of concurrent lameness were seen in horses with naturally occurring primary forelimb impact lameness with contralateral compensatory hindlimb lameness with a mixed component being the most common. In horses with hindlimb lameness, compensatory movements were seen in ipsilateral forelimbs, mostly as an ipsilateral impact lameness during straight line trot

Travelling for Umrah:destination attributes, destination image, and post-travel intentions

This paper examines the links between cosmopolitanism, self-identity, and a desire for social interaction perceived destination image and behavioural intentions. A model tested using a sample of 538 Iranian visitors to Mecca for the purpose of Umrah. The result from the structural model suggests that destination attributes influence perceived destination image. Further, such tourists are likely to revisit or recommend Islamic destinations if their experience matches their perceived image of the destination. This implies that, while the religious characteristics of the destination remain important, destination managers cannot disregard the tangential, non-religious attributes of a destination which are crucial in order to satisfy more conventional tourist desires. As such, this study suggests that those managing religious travel destinations should endeavour to foster a welcoming image, where experience, interaction and tolerance are at the forefront of the destination’s offering

Ladder operator for the one-dimensional Hubbard model

The one-dimensional Hubbard model is integrable in the sense that it has an infinite family of conserved currents. We explicitly construct a ladder operator which can be used to iteratively generate all of the conserved current operators. This construction is different from that used for Lorentz invariant systems such as the Heisenberg model. The Hubbard model is not Lorentz invariant, due to the separation of spin and charge excitations. The ladder operator is obtained by a very general formalism which is applicable to any model that can be derived from a solution of the Yang-Baxter equation.Comment: 4 pages, no figures, revtex; final version to appear in Phys. Rev. Let

Educational risk factors for psychological truancy in Lesotho: a qualitative exploration

A qualitative case study design was used to explore educational risk factors that may contribute to psychological truancy in a Lesotho secondary school. Purposively sampled teachers (n = 4, females = 50%) and pupils (n = 4, females = 75%), who have experience of psychological truancy, took part in a focus group and individual interviews. Inductive content analysis was used to analyse data emanating from the interviews. The findings indicate that pupil–teacher relationships, the use of English as medium of instruction and a lack of resources may be educational risk factors contributing to psychological truancy. Positive pupil–teacher relationships and active classroom engagement are prerequisites for successful and active learning

Biomarkers of systemic inflammation predict survival with first-line immune checkpoint inhibitors in non-small-cell lung cancer

INTRODUCTION: Pembrolizumab is an established first-line option for patients with advanced non-small-cell lung cancer (NSCLC) expressing programmed death-ligand 1 ≥50%. Durable responses are seen in a subset of patients; however, many derive little clinical benefit. Biomarkers of the systemic inflammatory response predict survival in NSCLC. We evaluated their prognostic significance in patients receiving first-line pembrolizumab for advanced NSCLC. METHODS: Patients treated with first-line pembrolizumab for advanced NSCLC with programmed death-ligand 1 expression ≥50% at two regional Scottish cancer centres were identified. Pretreatment inflammatory biomarkers (white cell count, neutrophil count, neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, albumin, prognostic nutritional index) were recorded. The relationship between these and progression-free survival (PFS) and overall survival (OS) were examined. RESULTS: Data were available for 219 patients. On multivariate analysis, albumin and neutrophil count were independently associated with PFS (P 7.5 × 10(9)/l to give a three-tier categorical score. SIPS predicted PFS [hazard ratio 2.06, 95% confidence interval (CI) 1.68-2.52 (P < 0.001)] and OS [hazard ratio 2.33, 95% CI 1.86-2.92 (P < 0.001)]. It stratified PFS from 2.5 (SIPS2), to 8.7 (SIPS1) to 17.9 months (SIPS0) (P < 0.001) and OS from 5.1 (SIPS2), to 12.4 (SIPS1) to 28.7 months (SIPS0) (P < 0.001). The relative risk of death before 6 months was 2.96 (95% CI 1.98-4.42) in patients with SIPS2 compared with those with SIPS0-1 (P < 0.001). CONCLUSIONS: SIPS, a simple score combining albumin and neutrophil count, predicts survival in patients with NSCLC receiving first-line pembrolizumab. Unlike many proposed prognostic scores, SIPS uses only routinely collected pretreatment test results and provides a categorical score. It stratifies survival across clinically meaningful time periods that may assist clinicians and patients with treatment decisions. We advocate validation of the prognostic utility of SIPS in this and other immune checkpoint inhibitor treatment settings

Quantum Monte Carlo study of the one-dimensional Holstein model of spinless fermions

The Holstein model of spinless fermions interacting with dispersionless phonons in one dimension is studied by a Green's function Monte Carlo technique. The ground state energy, first fermionic excited state, density wave correlations, and mean lattice displacement are calculated for lattices of up to 16 sites, for one fermion per two sites, i.e., a half-filled band. Results are obtained for values of the fermion hopping parameter of $t=0.1 \omega$, $\omega$, and $10 \omega$ where $\omega$ is the phonon frequency. At a finite fermion-phonon coupling $g$ there is a transition from a metallic phase to an insulating phase in which there is charge-density-wave order. Finite size scaling is found to hold in the metallic phase and is used to extract the coupling dependence of the Luttinger liquid parameters, $u_\rho$ and $K_\rho$, the velocity of charge excitations and the correlation exponent, respectively. For free fermions ($g=0$) and for strong coupling ($g^2 \gg t \omega$) our results agree well with known analytic results. For $t=\omega$ and $t=10\omega$ our results are inconsistent with the metal-insulator transition being a Kosterlitz-Thouless transition.\\Comment: 16 pages of ReVTeX, 11 figures in uuencoded compressed tar file. Minor changes to text. Our results are inconsistent with the metal-insulator transition studied being a Kosterlitz-Thouless transition. The figures are now in the correct order. To appear in Physical Review B, April 15, 199

Integration of Machine Learning and Mechanistic Models Accurately Predicts Variation in Cell Density of Glioblastoma Using Multiparametric MRI

Glioblastoma (GBM) is a heterogeneous and lethal brain cancer. These tumors are followed using magnetic resonance imaging (MRI), which is unable to precisely identify tumor cell invasion, impairing effective surgery and radiation planning. We present a novel hybrid model, based on multiparametric intensities, which combines machine learning (ML) with a mechanistic model of tumor growth to provide spatially resolved tumor cell density predictions. The ML component is an imaging data-driven graph-based semi-supervised learning model and we use the Proliferation-Invasion (PI) mechanistic tumor growth model. We thus refer to the hybrid model as the ML-PI model. The hybrid model was trained using 82 image-localized biopsies from 18 primary GBM patients with pre-operative MRI using a leave-one-patient-out cross validation framework. A Relief algorithm was developed to quantify relative contributions from the data sources. The ML-PI model statistically significantly outperformed (p \u3c 0.001) both individual models, ML and PI, achieving a mean absolute predicted error (MAPE) of 0.106 ± 0.125 versus 0.199 ± 0.186 (ML) and 0.227 ± 0.215 (PI), respectively. Associated Pearson correlation coefficients for ML-PI, ML, and PI were 0.838, 0.518, and 0.437, respectively. The Relief algorithm showed the PI model had the greatest contribution to the result, emphasizing the importance of the hybrid model in achieving the high accuracy

Algebraic Bethe ansatz method for the exact calculation of energy spectra and form factors: applications to models of Bose-Einstein condensates and metallic nanograins

In this review we demonstrate how the algebraic Bethe ansatz is used for the calculation of the energy spectra and form factors (operator matrix elements in the basis of Hamiltonian eigenstates) in exactly solvable quantum systems. As examples we apply the theory to several models of current interest in the study of Bose-Einstein condensates, which have been successfully created using ultracold dilute atomic gases. The first model we introduce describes Josephson tunneling between two coupled Bose-Einstein condensates. It can be used not only for the study of tunneling between condensates of atomic gases, but for solid state Josephson junctions and coupled Cooper pair boxes. The theory is also applicable to models of atomic-molecular Bose-Einstein condensates, with two examples given and analysed. Additionally, these same two models are relevant to studies in quantum optics. Finally, we discuss the model of Bardeen, Cooper and Schrieffer in this framework, which is appropriate for systems of ultracold fermionic atomic gases, as well as being applicable for the description of superconducting correlations in metallic grains with nanoscale dimensions. In applying all of the above models to physical situations, the need for an exact analysis of small scale systems is established due to large quantum fluctuations which render mean-field approaches inaccurate.Comment: 49 pages, 1 figure, invited review for J. Phys. A., published version available at http://stacks.iop.org/JPhysA/36/R6