Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model

A physically motivated statistical model is used to diagnose variability and trends in wintertime ( October - March) Global Precipitation Climatology Project (GPCP) pentad (5-day mean) precipitation. Quasi-geostrophic theory suggests that extratropical precipitation amounts should depend multiplicatively on the pressure gradient, saturation specific humidity, and the meridional temperature gradient. This physical insight has been used to guide the development of a suitable statistical model for precipitation using a mixture of generalized linear models: a logistic model for the binary occurrence of precipitation and a Gamma distribution model for the wet day precipitation amount. The statistical model allows for the investigation of the role of each factor in determining variations and long-term trends. Saturation specific humidity q(s) has a generally negative effect on global precipitation occurrence and with the tropical wet pentad precipitation amount, but has a positive relationship with the pentad precipitation amount at mid- and high latitudes. The North Atlantic Oscillation, a proxy for the meridional temperature gradient, is also found to have a statistically significant positive effect on precipitation over much of the Atlantic region. Residual time trends in wet pentad precipitation are extremely sensitive to the choice of the wet pentad threshold because of increasing trends in low-amplitude precipitation pentads; too low a choice of threshold can lead to a spurious decreasing trend in wet pentad precipitation amounts. However, for not too small thresholds, it is found that the meridional temperature gradient is an important factor for explaining part of the long-term trend in Atlantic precipitation.

The effects of pre- and postnatal depression in fathers: a natural experiment comparing the effects of exposure to depression on offspring

Background: Depression in fathers in the postnatal period is associated with an increased risk of behavioural problems in their offspring, particularly for boys. The aim of this study was to examine for differential effects of depression in fathers on children's subsequent psychological functioning via a natural experiment comparing prenatal and postnatal exposure. Methods:In a longitudinal population cohort study (the Avon Longitudinal Study of Parents and Children (ALSPAC)) we examined the associations between depression in fathers measured in the prenatal and postnatal period (measured using the Edinburgh Postnatal Depression Scale), and later behavioural/emotional and psychiatric problems in their children, assessed at ages 31/2 and 7 years. Results: Children whose fathers were depressed in both the prenatal and postnatal periods had the highest risks of subsequent psychopathology, measured by total problems at age 31/2 years (Odds Ratio 3.55; 95% confidence interval 2.07, 6.08) and psychiatric diagnosis at age 7 years (OR 2.54; 1.19, 5.41). Few differences emerged when prenatal and postnatal depression exposure were directly compared, but when compared to fathers who were not depressed, boys whose fathers had postnatal depression only had higher rates of conduct problems aged 31/2 years (OR 2.14; 1.22, 3.72) whereas sons of the prenatal group did not (OR 1.41; .75, 2.65). These associations changed little when controlling for maternal depression and other potential confounding factors. Conclusions: The findings of this study suggest that the increased risk of later conduct problems, seen particularly in the sons of depressed fathers, maybe partly mediated through environmental means. In addition, children whose fathers are more chronically depressed appear to be at a higher risk of emotional and behavioural problems. Efforts to identify the precise mechanisms by which transmission of risk may occur should be encouraged to enable the development of focused interventions to mitigate risks for young children.

Mothers' attributions following their child's diagnosis of autistic spectrum disorder: exploring links with maternal levels of stress, depression and expectations about their child's future

Although the impact of autism spectrum disorders (ASDs) on the family is well recognized, the way mothers attempt to make sense of the diagnosis is largely unexplored. However, in other disabilities, attributions have been shown to predict a variety of outcomes including maternal wellbeing and engagement in treatment. Using Weiner's (198S) three-dimensional model, 16 mothers were interviewed to examine the nature and impact of their beliefs about their child's ASD using semi-structured interviews and measures of depression, parenting stress and expectations for their child's future. The findings suggested that mothers made a diverse and complex range of attributions that were consistent with Weiner's dimensions of locus of cause, stability and controllability. The nature of their attributions reflected particular difficulties associated with ASDs, such as uncertainties regarding cause and prognosis. Taking account of mothers' search for meaning will better enable professionals to support families following diagnosis.

A comparison-based diagnosis algorithm tailored for crossed cube multiprocessor systems

Comparison-based diagnosis is an effective approach to system-level fault diagnosis. Under the Maeng-Malek comparison model (NM* model), Sengupta and Dahbura proposed an O(N-5) diagnosis algorithm for general diagnosable systems with N nodes. Thanks to lower diameter and better graph embedding capability as compared with a hypercube of the same size, the crossed cube has been a promising candidate for interconnection networks. In this paper, we propose a fault diagnosis algorithm tailored for crossed cube connected multicomputer systems under the MM* model. By introducing appropriate data structures, this algorithm runs in O(Nlog(2)(2) N) time, which is linear in the size of the input. As a result, this algorithm is significantly superior to the Sengupta-Dahbura's algorithm when applied to crossed cube systems. (C) 2004 Elsevier B.V. All rights reserved.

Thalassaemia: its diagnosis and interpretation in past skeletal populations

The diagnosis of thalassaemia in archaeological populations has long been hindered by a lack of pathogonomic features, and the non-specific nature of cribra orbitalia and porotic hyperostosis. In fact, clinical research has highlighted more specific diagnostic criteria for thalassaemia major and intermedia based on changes to the thorax (‘rib-within-a-rib’ and costal osteomas). A recent re-examination of 364 child skeletons from Romano-British Poundbury Camp, Dorset revealed children with general ‘wasting’ of the bones and three children who demonstrated a variety of severe lesions (e.g. zygomatic bone and rib hypertrophy, porotic hyperostosis, rib lesions, osteopenia and pitted diaphyseal shafts) that are inconsistent with dietary deficiency alone, and more consistent with a diagnosis of genetic anaemia. Two of these children displayed rib lesions typical of those seen in modern cases of thalassaemia. The children of Poundbury Camp represent the first cases of genetic anaemia identified in a British archaeological population. As thalassaemia is a condition strongly linked to Mediterranean communities, the presence of this condition in a child from England, found within a mausoleum, suggests that they were born to wealthy immigrant parents living in this small Roman settlement in Dorset. This paper explores the diagnostic criteria for genetic anaemia in the archaeological literature and what its presence in ancient populations can contribute to our knowledge of past human migration.

Adaptive alarm processor for fault diagnosis on power transmission networks

The authors describe a learning classifier system (LCS) which employs genetic algorithms (GA) for adaptive online diagnosis of power transmission network faults. The system monitors switchgear indications produced by a transmission network, reporting fault diagnoses on any patterns indicative of faulted components. The system evaluates the accuracy of diagnoses via a fault simulator developed by National Grid Co. and adapts to reflect the current network topology by use of genetic algorithms.