Dissociation of the benzene molecule by UV and soft X-rays in circumstellar environment

Benzene molecules, present in the proto-planetary nebula CRL 618, are ionized and dissociated by UV and X-ray photons originated from the hot central star and by its fast wind. Ionic species and free radicals produced by these processes can lead to the formation of new organic molecules. The aim of this work is to study the photoionization and photodissociation processes of the benzene molecule, using synchrotron radiation and time of flight mass spectrometry. Mass spectra were recorded at different energies corresponding to the vacuum ultraviolet (21.21 eV) and soft X-ray (282-310 eV) spectral regions. The production of ions from the benzene dissociative photoionization is here quantified, indicating that C6H6 is more efficiently fragmented by soft X-ray than UV radiation, where 50% of the ionized benzene molecules survive to UV dissociation while only about 4% resist to X-rays. Partial ion yields of H+ and small hydrocarbons such as C2H2+, C3H3+ and C4H2+ are determined as a function of photon energy. Absolute photoionization and dissociative photoionization cross sections have also been determined. From these values, half-life of benzene molecule due to UV and X-ray photon fluxes in CRL 618 were obtained.Comment: The paper contains 8 pages, 9 figures and 4 tables. Accepted to be published on MNRAS on 2008 November 2

Characterization of acetonitrile ice irradiated by X-rays employing the PROCODA code: II. Desorption processes

In this work, we focus on the study of radiation induced desorption processes that occurred in acetonitrile ice irradiated by broadband X-rays (6 eV to 2 keV) monitored by FTIR spectroscopy at different radiation fluences. In a previous work, we used the PROCODA code to derive the chemical evolution of the ice. Here, we have obtained that the acetonitrile desorbed column density is at least two orders of magnitude larger than the desorbed column densities of daughter or granddaughter molecular species at chemical equilibrium stage. This indicates that total desorption column density is mainly governed by the father molecule, as also previously hypothesized in experimental studies. This occurs basically because the acetonitrile column density is larger than the other ones. In particular, at chemical equilibrium acetonitrile desorption column density represents almost 98\% of the total, while it is close to 1\% for H, CN and CH$_2$, the species with larger molecular desorption percentages at chemical equilibrium. Another derived quantity is what we called intrinsic desorption rate, which is a number per second for individual species. Some of the larger intrinsic desorption rates were: CH$_3$CN ($6.2\times 10^{-6}$), CN ($6.2\times 10^{-6}$), H ($5.7\times 10^{-6}$), CH$_2$ ($5.7\times 10^{-6}$) and C$_2$N$_2$ ($4.4\times 10^{-6}$). These results help to put constrain in astrochemical models and can be also useful to clarify some astronomical radio observations.Comment: To appear in MNRA

Latent variable mixture modelling and individual treatment prediction

Understanding which groups of patients are more or less likely to benefit from specific treatments has important implications for healthcare. Many personalised medicine approaches in mental health employ variable-centred approaches to predicting treatment response, yet person-centred approaches that identify clinical profiles of patients can provide information on the likelihood of a range of important outcomes. In this paper, we discuss the use of latent variable mixture modelling and demonstrate its use in the application of a patient profiling algorithm using routinely collected patient data to predict outcomes from psychological treatments. This validation study analysed data from two services, which included n = 44,905 patients entering treatment. There were different patterns of reliable recovery, improvement and clinical deterioration from therapy, across the eight profiles which were consistent over time. Outcomes varied between different types of therapy within the profiles: there were significantly higher odds of reliable recovery with High Intensity therapies in two profiles (32.5% of patients) and of reliable improvement in three profiles (32.2% of patients) compared with Low Intensity treatments. In three profiles (37.4% of patients) reliable recovery was significantly more likely if patients had CBT vs Counselling. The developments and potential application of latent variable mixture approaches are further discussed

Radiolysis of ammonia-containing ices by energetic, heavy and highly charged ions inside dense astrophysical environments

Deeply inside dense molecular clouds and protostellar disks, the interstellar ices are protected from stellar energetic UV photons. However, X-rays and energetic cosmic rays can penetrate inside these regions triggering chemical reactions, molecular dissociation and evaporation processes. We present experimental studies on the interaction of heavy, highly charged and energetic ions (46 MeV Ni^13+) with ammonia-containing ices in an attempt to simulate the physical chemistry induced by heavy ion cosmic rays inside dense astrophysical environments. The measurements were performed inside a high vacuum chamber coupled to the heavy ion accelerator GANIL (Grand Accelerateur National d'Ions Lourds) in Caen, France.\textit{In-situ} analysis is performed by a Fourier transform infrared spectrometer (FTIR) at different fluences. The averaged values for the dissociation cross section of water, ammonia and carbon monoxide due to heavy cosmic ray ion analogs are ~2x10^{-13}, 1.4x10^{-13} and 1.9x10^{-13} cm$^2$, respectively. In the presence of a typical heavy cosmic ray field, the estimated half life for the studied species is 2-3x10^6 years. The ice compaction (micropore collapse) due to heavy cosmic rays seems to be at least 3 orders of magnitude higher than the one promoted by (0.8 MeV) protons . In the case of the irradiated H2O:NH3:CO ice, the infrared spectrum at room temperature reveals five bands that were tentatively assigned to vibration modes of the zwitterionic glycine (+NH3CH2COO-).Comment: Accepted to be published in Astronomy and Astrophysics; Number of pages: 12; Number of Figures: 7; Number of Tables:

Predicting treatment outcome in psychological treatment services by identifying latent profiles of patients

BACKGROUND: The outcomes of psychological therapies for anxiety and depression vary across individuals and symptom domains. Being able to predict treatment response from readily available patient data at presentation has potentially important benefits in aiding decisions about the most suitable interventions for a patient. This paper presents a method of identifying subgroups of patients using latent profile analysis, and comparing response to psychological treatments between these profiles. METHODS: All outpatients taken into treatment at two psychological treatment services in London, UK and who provided basic demographic information and standardized symptom measures were included in the analysis (n=16636). RESULTS: Latent Profile Analysis was performed on intake data to identify statistically different groups of patients, which were then examined in longitudinal analyses to determine their capacity to predict treatment outcomes. Comparison between profiles showed considerable variation in recovery (74-15%), deterioration rates (5-20%), and levels of attrition (17-40%). Further variation in outcomes was found within the profiles when different intensities of psychological intervention were delivered. LIMITATIONS: Latent profiles were identified using data from two services, so generalisability to other services should be considered. Routinely collected patient data was included, additional patient information may further enhance utility of the profiles. CONCLUSIONS: These results suggest that intake data can be used to reliably classify patients into profiles that are predictive of outcome to different intensities of psychological treatment in routine care. Algorithms based on these kinds of data could be used to optimize decision-making and aid the appropriate matching of patients to treatment