Special supervisory homes in Sweden : paper presented September 12:th at the 7:th EUSARF Congress 2002 in Trondheim : Revitalising Residential and Foster Care

Sweden is the only Scandinavian country that uses closed treatment institutions based on coercive measures within the child welfare system, on a large scale, for the education and treatment of young criminal offenders and drug users. In Sweden there are in 2002 some 30 “homes for specialized supervision” of varying sizes and degrees of specialization – all run by a national board of institutional care. The total number of beds is some 650 and, in closed units, 385. My study was carried out during the 1990´s in Råby Youth Home, the oldest correctional institution in Sweden, started as a House of refuge in 1838. The question guiding my research was: How are we to understand the paradox that there is widespread use and acceptance of organizations like reform schools, while they lack any sign of success in rehabilitating their clients? The empirical material of the case study consists of observations carried out in one of Råby’s treatment units, in-depth interviews with the staff and an investigation of case notes on all youth that were admitted to Råby between 1982 and 1993. Follow-up interviews were made on a representative sample of all boys and girls that were admitted during the periods of 1985-1987 and 1990-1993. We managed to find and interview 61 out of a possible total of 95 former residents. We found that almost 80 percent of the young men and women had committed one or more serious crimes during the follow-up period, that almost 70 percent had used drugs, other than alcohol, and some 70 percent of the boys continued with one or more institutional placements in special supervisory homes or in prison. We also found that only 30 percent were more or less socially well adjusted at follow up. The girls were divided 50-50 between the good and bad outcome criteria, while the boys were divided on a ratio of 20-80. Incarceration in combination with the loss of freedom and the indeterminate time of placement were found to be the most fundamental reasons behind the development of hidden group resistances and adjustment- strategies among the residents. The official goals, ideologies and treatment interventions were not experienced as such by the youths – rather as punishment and confinement. Despite an internationally high standard of care, i.e. educated and skilled personnel, good economic resources, high standard of residence, nourishing meals three times a day, and safe living conditions for the youth, - external and internal processes seem to produce further criminalisation and drug addiction and difficulties in rehabilitating the youths to normal life. The reform school as a treatment organisation seems to be in conflict with itself as a social institution

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Book review

Hierarchical spectral clustering reveals brain size and shape changes in asymptomatic carriers of C9orf72

Traditional methods for detecting asymptomatic brain changes in neurodegenerative diseases such as Alzheimer\u27s disease or frontotemporal degeneration typically evaluate changes in volume at a predefined level of granularity, e.g. voxel-wise or in a priori defined cortical volumes of interest. Here, we apply a method based on hierarchical spectral clustering, a graph-based partitioning technique. Our method uses multiple levels of segmentation for detecting changes in a data-driven, unbiased, comprehensive manner within a standard statistical framework. Furthermore, spectral clustering allows for detection of changes in shape along with changes in size. We performed tensor-based morphometry to detect changes in the Genetic Frontotemporal dementia Initiative asymptomatic and symptomatic frontotemporal degeneration mutation carriers using hierarchical spectral clustering and compared the outcome to that obtained with a more conventional voxel-wise tensor- and voxel-based morphometric analysis. In the symptomatic groups, the hierarchical spectral clustering-based method yielded results that were largely in line with those obtained with the voxel-wise approach. In asymptomatic C9orf72 expansion carriers, spectral clustering detected changes in size in medial temporal cortex that voxel-wise methods could only detect in the symptomatic phase. Furthermore, in the asymptomatic and the symptomatic phases, the spectral clustering approach detected changes in shape in the premotor cortex in C9orf72. In summary, the present study shows the merit of hierarchical spectral clustering for data-driven segmentation and detection of structural changes in the symptomatic and asymptomatic stages of monogenic frontotemporal degeneration

Hierarchical spectral clustering reveals brain size and shape changes in asymptomatic carriers of <i>C9orf72</i>

Traditional methods for detecting asymptomatic brain changes in neurodegenerative diseases such as Alzheimer's disease or frontotemporal degeneration typically evaluate changes in volume at a predefined level of granularity, e.g. voxel-wise or in a priori defined cortical volumes of interest. Here, we apply a method based on hierarchical spectral clustering, a graph-based partitioning technique. Our method uses multiple levels of segmentation for detecting changes in a data-driven, unbiased, comprehensive manner within a standard statistical framework. Furthermore, spectral clustering allows for detection of changes in shape along with changes in size. We performed tensor-based morphometry to detect changes in the Genetic Frontotemporal dementia Initiative asymptomatic and symptomatic frontotemporal degeneration mutation carriers using hierarchical spectral clustering and compared the outcome to that obtained with a more conventional voxel-wise tensor- and voxel-based morphometric analysis. In the symptomatic groups, the hierarchical spectral clustering-based method yielded results that were largely in line with those obtained with the voxel-wise approach. In asymptomatic C9orf72 expansion carriers, spectral clustering detected changes in size in medial temporal cortex that voxel-wise methods could only detect in the symptomatic phase. Furthermore, in the asymptomatic and the symptomatic phases, the spectral clustering approach detected changes in shape in the premotor cortex in C9orf72. In summary, the present study shows the merit of hierarchical spectral clustering for data-driven segmentation and detection of structural changes in the symptomatic and asymptomatic stages of monogenic frontotemporal degeneration.© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain

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Intet resum

Constraints on the χ_(c1) versus χ_(c2) polarizations in proton-proton collisions at √s = 8 TeV

The polarizations of promptly produced χ_(c1) and χ_(c2) mesons are studied using data collected by the CMS experiment at the LHC, in proton-proton collisions at √s=8  TeV. The χ_c states are reconstructed via their radiative decays χ_c → J/ψγ, with the photons being measured through conversions to e⁺e⁻, which allows the two states to be well resolved. The polarizations are measured in the helicity frame, through the analysis of the χ_(c2) to χ_(c1) yield ratio as a function of the polar or azimuthal angle of the positive muon emitted in the J/ψ → μ⁺μ⁻ decay, in three bins of J/ψ transverse momentum. While no differences are seen between the two states in terms of azimuthal decay angle distributions, they are observed to have significantly different polar anisotropies. The measurement favors a scenario where at least one of the two states is strongly polarized along the helicity quantization axis, in agreement with nonrelativistic quantum chromodynamics predictions. This is the first measurement of significantly polarized quarkonia produced at high transverse momentum