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Research showing that risk for schizophrenia, bipolar disorder with psychosis, and other psychosis-spectrum diagnoses in adulthood is multidetermined has underscored the necessity of studying the additive and interactive factors in childhood that precede and predict future disorders. In this study, risk for the development of psychosis-spectrum disorders was examined in a 2-generation, 30-year prospective longitudinal study of 3,905 urban families against a sociocultural backdrop of changing economic and social conditions. Peer nominations of aggression, withdrawal, and likeability and national census information on neighborhood-level socioeconomic disadvantage in childhood, as well as changes in neighborhood socioeconomic conditions over the lifespan, were examined as predictors of diagnoses of schizophrenia, bipolar disorder, and other psychosis-spectrum disorders in adulthood relative to developing only nonpsychotic disorders or no psychiatric disorders. Individuals who were both highly aggressive and highly withdrawn were at greater risk for other psychosis-spectrum diagnoses when they experienced greater neighborhood disadvantage in childhood or worsening neighborhood conditions over maturation. Males who were highly aggressive but low on withdrawal were at greater risk for schizophrenia diagnoses. Childhood neighborhood disadvantage predicted both schizophrenia and bipolar diagnoses, regardless of childhood social behavior. Results provided strong support for multiple-domain models of psychopathology, and suggest that universal preventive interventions and social policies aimed at improving neighborhood conditions may be particularly important for decreasing the prevalence of psychosis-spectrum diagnoses in the future.
Layered transition metal dichalcogenides (TMDs) represent a diverse, emerging source of two-dimensional (2D) nanostructures with broad application in optoelectronics and energy. Chemical functionalization has evolved into a powerful tool to tailor properties of these 2D TMDs; however, functionalization strategies have been largely limited to the metallic 1T-polytype. The work herein illustrates that 2H-semiconducting liquid-exfoliated tungsten disulfide (WS2) undergoes a spontaneous redox reaction with gold (III) chloride (AuCl3). Au nanoparticles (NPs) predominantly nucleate at nanosheet edges with tuneable NP size and density. AuCl3 is preferentially reduced on multi-layer WS2 and resulting large Au aggregates are easily separated from the colloidal dispersion by simple centrifugation. This process may be exploited to enrich the dispersions in laterally large, monolayer nanosheets. It is proposed that thiol groups at edges and defects sides reduce the AuCl3 to Au0 and are in turn oxidized to disulfides. Optical emission, i.e. photoluminescence, of the monolayers remained pristine, while the electrocatalytic activity towards the hydrogen evolution reaction is significantly improved. Taken together, these improvements in functionalization, fabrication, and catalytic activity represent an important advance in the study of these emerging 2D nanostructures.
Irradiation of reactor pressure vessel (RPV) steels causes the formation of nanoscale microstructural features (termed radiation damage), which affect the mechanical properties of the vessel. A key tool for characterizing these nanoscale features is atom probe tomography (APT), due to its high spatial resolution and the ability to identify different chemical species in three dimensions. Microstructural observations using APT can underpin development of a mechanistic understanding of defect formation. However, with atom probe analyses there are currently multiple methods for analyzing the data. This can result in inconsistencies between results obtained from different researchers and unnecessary scatter when combining data from multiple sources. This makes interpretation of results more complex and calibration of radiation damage models challenging. In this work simulations of a range of different microstructures are used to directly compare different cluster analysis algorithms and identify their strengths and weaknesses.
The redshifted 21cm line of neutral hydrogen (Hi), potentially observable at low radio frequencies (~50–200 MHz), should be a powerful probe of the physical conditions of the inter-galactic medium during Cosmic Dawn and the Epoch of Reionisation (EoR). The sky-averaged Hi signal is expected to be extremely weak (~100 mK) in comparison to the foreground of up to 104 K at the lowest frequencies of interest. The detection of such a weak signal requires an extremely stable, well characterised system and a good understanding of the foregrounds. Development of a nearly perfectly (~mK accuracy) calibrated total power radiometer system is essential for this type of experiment. We present the BIGHORNS (Broadband Instrument for Global HydrOgen ReioNisation Signal) experiment which was designed and built to detect the sky-averaged Hi signal from the EoR at low radio frequencies. The BIGHORNS system is a mobile total power radiometer, which can be deployed in any remote location in order to collect radio frequency interference (RFI) free data. The system was deployed in remote, radio quiet locations in Western Australia and low RFI sky data have been collected. We present a description of the system, its characteristics, details of data analysis, and calibration. We have identified multiple challenges to achieving the required measurement precision, which triggered two major improvements for the future system.