The UK National Homicide Therapeutic Service: a retrospective naturalistic study among 929 bereaved individuals

Homicidal bereavement puts survivors at risk of developing a broad range of lasting and severe mental health problems. Previous research has often relied on relatively small and homogenous samples. Still, little is known about what factors influence the expression of symptoms following homicidal bereavement. Preventive and curative treatments often do not consider the complex coherence between the emotional, judicial, financial, and societal challenges that likely arise following a homicide. Despite the severity of its consequences on mental health, no gold standard for the preventative and curative treatment of mental health issues in homicide survivors exists. We aimed to introduce a time-limited, traumatic grief-focused outreaching model of care designed specifically for homicide survivors, and to examine its potential effectiveness. Furthermore, we aimed to investigate what factors influence the severity of mental health problems and response to treatment. In the current study, self-reported data on five different outcome measures, namely, symptoms of posttraumatic stress, prolonged grief, depression, anxiety, and functional impairment were available from 929 homicidally bereaved treatment receiving adults. We used Latent Growth Modeling to analyze our repeated measures data and to classify individuals into distinct groups based on individual response patterns. Results showed that the current model of care is likely to be effective in reducing mental health complaints following homicidal bereavement. Having a history of mental illness, being younger of age and female, and having lost either a child or spouse consistently predicted greater symptom severity and functional impairment at baseline. For change in symptom severity and functional impairment during treatment, having a history of mental illness was the only consistent predictor across all outcomes. This study was limited by its reliance on self-reported data and cross-sectional design without a control group. Future prospective, longitudinal research across different cultures is needed in order to replicate the current findings and enhance generalizability. That notwithstanding, findings provide a first step toward evaluating a novel service-delivery approach for homicide survivors and provide further insight in the development of mental health complaints following bereavement by homicide

The Caledonian face test: A new test of face discrimination

yesThis study aimed to develop a clinical test of face perception which is applicable to a wide range of patients and can capture normal variability. The Caledonian face test utilises synthetic faces which combine simplicity with sufficient realism to permit individual identification. Face discrimination thresholds (i.e. minimum difference between faces required for accurate discrimination) were determined in an "odd-one-out" task. The difference between faces was controlled by an adaptive QUEST procedure. A broad range of face discrimination sensitivity was determined from a group (N=52) of young adults (mean 5.75%; SD 1.18; range 3.33-8.84%). The test is fast (3-4min), repeatable (test-re-test r2=0.795) and demonstrates a significant inversion effect. The potential to identify impairments of face discrimination was evaluated by testing LM who reported a lifelong difficulty with face perception. While LM's impairment for two established face tests was close to the criterion for significance (Z-scores of -2.20 and -2.27) for the Caledonian face test, her Z-score was -7.26, implying a more than threefold higher sensitivity. The new face test provides a quantifiable and repeatable assessment of face discrimination ability. The enhanced sensitivity suggests that the Caledonian face test may be capable of detecting more subtle impairments of face perception than available tests.Non

A noninvasive method for measuring mammary apoptosis and epithelial cell activation in dairy animals using microparticles extracted from milk

AbstractMilk production from dairy animals has been described in terms of 3 processes: the increase in secretory cell numbers in late pregnancy and early lactation, secretion rate of milk per cell, and the decline in cell numbers as lactation progresses. This latter process is thought to be determined by the level of programmed cell death (apoptosis) found in the animal. Until now, apoptosis has been measured by taking udder biopsies, using magnetic resonance imaging scans, or using animals postmortem. This paper describes an alternative, noninvasive method for estimating apoptosis by measuring microparticles in milk samples. Microparticles are the product of several processes in dairy animals, including apoptosis. Milk samples from 12 Holstein cows, at or past peak lactation, were collected at 5 monthly samplings. The samples (n=57) were used to measure the number of microparticles and calculate microparticle density for 4 metrics: annexin V positive and merocyanine 540 dye positive, for both and total particles, in both whole milk (WM) and spun milk. Various measures of milk production were also recorded for the 12 cows, including daily milk yield, fat and protein percentage in the milk, somatic cell count, and the days in milk when the samples were taken. A high correlation was found between the 4 WM microparticle densities and days in milk (0.46 to 0.64), and a moderate correlation between WM microparticle densities and daily milk yield (−0.33 to −0.44). No significant relationships were found involving spun milk samples, somatic cell count, or fat and protein percentage. General linear model analyses revealed differences between cows for both level of microparticle density and its rate of change in late lactation. Persistency of lactation was also found to be correlated with the WM microparticle traits (−0.65 to −0.32). As apoptosis is likely to be the major contributor to microparticle numbers in late lactation, this work found a noninvasive method for estimating apoptosis that gave promising results. Further investigation is required to find out the factors affecting microparticle production and how it changes throughout lactation

Truth Table Invariant Cylindrical Algebraic Decomposition by Regular Chains

A new algorithm to compute cylindrical algebraic decompositions (CADs) is presented, building on two recent advances. Firstly, the output is truth table invariant (a TTICAD) meaning given formulae have constant truth value on each cell of the decomposition. Secondly, the computation uses regular chains theory to first build a cylindrical decomposition of complex space (CCD) incrementally by polynomial. Significant modification of the regular chains technology was used to achieve the more sophisticated invariance criteria. Experimental results on an implementation in the RegularChains Library for Maple verify that combining these advances gives an algorithm superior to its individual components and competitive with the state of the art

Applying machine learning to the problem of choosing a heuristic to select the variable ordering for cylindrical algebraic decomposition

Cylindrical algebraic decomposition(CAD) is a key tool in computational algebraic geometry, particularly for quantifier elimination over real-closed fields. When using CAD, there is often a choice for the ordering placed on the variables. This can be important, with some problems infeasible with one variable ordering but easy with another. Machine learning is the process of fitting a computer model to a complex function based on properties learned from measured data. In this paper we use machine learning (specifically a support vector machine) to select between heuristics for choosing a variable ordering, outperforming each of the separate heuristics.Comment: 16 page

Psychopathology in a treatment-seeking sample of homicidally bereaved individuals:Latent class analysis

Background: Violently bereaved individuals are at increased risk of developing severe and comorbid disorders. Comorbidity may increase psychiatric symptom severity and suicide risk and decrease psychosocial functioning compared with having one disorder. We aimed to identify subgroups of individuals with similar symptom patterns, describe prevalence rates and overall levels of prolonged grief disorder (PGD), posttraumatic stress disorder (PTSD), major depressive disorder (MDD), and generalized anxiety disorder (GAD) per class, and explore associations between class membership and personal and homicide related variables. Methods: We investigated the comorbidity of symptoms of PGD, PTSD, MDD, and GAD in a sample of 923 treatment-seeking homicidally bereaved individuals by deploying latent class analysis. Results: Three subgroups were identified: (i) a moderate distress, low depression class (12.4%), (ii) a high distress, moderate depression class (42.7%), and (iii) a high distress and high depression class (45.0%). Prevalence rates and total scores of the questionnaires followed the pattern of iii ≥ ii ≥ i (ps ≤ .001). Being female and having experienced prior life stress distinguished between all classes (ps ≤ .05). Limitations: The data-driven analytic approach and reliance on self-reported routine outcome monitoring data limit the generalizability and validity of the study. Strengths include the large sample size and the inclusion of four measures in a treatment-seeking, violently bereaved sample. Conclusions: Classes were most clearly distinguishable based on symptom severity, indicating high comorbidity following bereavement by homicide. This argues for an integrated treatment that targets different complaints simultaneously rather than successively

Unconventional particle-hole mixing in the systems with strong superconducting fluctuations

Development of the STM and ARPES spectroscopies enabled to reach the resolution level sufficient for detecting the particle-hole entanglement in superconducting materials. On a quantitative level one can characterize such entanglement in terms of the, so called, Bogoliubov angle which determines to what extent the particles and holes constitute the spatially or momentum resolved excitation spectra. In classical superconductors, where the phase transition is related to formation of the Cooper pairs almost simultaneously accompanied by onset of their long-range phase coherence, the Bogoliubov angle is slanted all the way up to the critical temperature Tc. In the high temperature superconductors and in superfluid ultracold fermion atoms near the Feshbach resonance the situation is different because of the preformed pairs which exist above Tc albeit loosing coherence due to the strong quantum fluctuations. We discuss a generic temperature dependence of the Bogoliubov angle in such pseudogap state indicating a novel, non-BCS behavior. For quantitative analysis we use a two-component model describing the pairs coexisting with single fermions and study their mutual feedback effects by the selfconsistent procedure originating from the renormalization group approach.Comment: 4 pages, 4 figure

More is the Same; Phase Transitions and Mean Field Theories

This paper looks at the early theory of phase transitions. It considers a group of related concepts derived from condensed matter and statistical physics. The key technical ideas here go under the names of "singularity", "order parameter", "mean field theory", and "variational method". In a less technical vein, the question here is how can matter, ordinary matter, support a diversity of forms. We see this diversity each time we observe ice in contact with liquid water or see water vapor, "steam", come up from a pot of heated water. Different phases can be qualitatively different in that walking on ice is well within human capacity, but walking on liquid water is proverbially forbidden to ordinary humans. These differences have been apparent to humankind for millennia, but only brought within the domain of scientific understanding since the 1880s. A phase transition is a change from one behavior to another. A first order phase transition involves a discontinuous jump in a some statistical variable of the system. The discontinuous property is called the order parameter. Each phase transitions has its own order parameter that range over a tremendous variety of physical properties. These properties include the density of a liquid gas transition, the magnetization in a ferromagnet, the size of a connected cluster in a percolation transition, and a condensate wave function in a superfluid or superconductor. A continuous transition occurs when that jump approaches zero. This note is about statistical mechanics and the development of mean field theory as a basis for a partial understanding of this phenomenon.Comment: 25 pages, 6 figure

The Spin-Dependent Structure Functions of Nuclei in the Meson-Nucleon Theory

A theoretical approach to the investigation of spin-dependent structure functions in deep inelastic scattering of polarized leptons off polarized nuclei, based on the effective meson-nucleon theory and operator product expansion method, is proposed and applied to deuteron and $^3He$. The explicit forms of the moments of the deuteron and $^3He$ spin-dependent structure functions are found and numerical estimates of the influence of nuclear structure effects are presented.Comment: 42 pages revtex, 7 postscript figures available from above e-mail upon request. Perugia preprint DFUPG 92/9