Machine Learning-Based Early Warning System for Urban Flood Management

Characterisation of predictive limits of data-driven models (e.g. ANN) for urban flooding based on actual rainfall.With the growth in urban population and other pressures, such as climate change, the impact and severity of urban flood events are likely to continue to increase. “Intelligent water networks” are viewed as the way forward to ensure that infrastructure services are flexible, safe, reliable and economical. Reduction of flood-risk from urban drainage and sewerage infrastructure is likely to require increasingly sophisticated computational techniques to keep pace with the level of data that is collected both from meteorological and online water monitoring systems in the field. This paper describes and characterises an example of an Early Warning System (EWS), designated "RAPIDS" (RAdar Pluvial flooding Identification for Drainage System) that deals with urban drainage systems and the utilisation of rainfall data concurrently to predict flooding of multiple urban areas in near real-time using a single multi-output Artificial Neural Network (ANN). The system has the potential to provide early warning for decision makers within reasonable time, this being a key requirement determining the operational usefulness of such systems. Computational methods that require hours or days to run will not be able to keep pace with fast-changing situations such as manhole flooding or Combined Sewer Overflow (CSO) spills and thus the system developed is able to react in close to real time. This paper includes a sensitivity analysis and demonstrates that the - predictive capability of such a system based on actual rainfall is limited to a maximum of the Time of Concentration (ToC) of each node being modelled. To achieve operationally useful prediction times, predictions of rainfall as input signals are likely to be needed for most urban drainage networks.UKWIR RTM project (2011-12

Targeting the affective brain-a randomized controlled trial of real-time fMRI neurofeedback in patients with depression.

open access articleFunctional magnetic resonance imaging neurofeedback (fMRI-NF) training of areas involved in emotion processing can reduce depressive symptoms by over 40% on the Hamilton Depression Rating Scale (HDRS). However, it remains unclear if this efficacy is specific to feedback from emotion-regulating regions. We tested in a single-blind, randomized, controlled trial if upregulation of emotion areas (NFE) yields superior efficacy compared to upregulation of a control region activated by visual scenes (NFS). Forty-three moderately to severely depressed medicated patients were randomly assigned to five sessions augmentation treatment of either NFE or NFS training. At primary outcome (week 12) no significant group mean HDRS difference was found (B = −0.415 [95% CI −4.847 to 4.016], p = 0.848) for the 32 completers (16 per group). However, across groups depressive symptoms decreased by 43%, and 38% of patients remitted. These improvements lasted until follow-up (week 18). Both groups upregulated target regions to a similar extent. Further, clinical improvement was correlated with an increase in self-efficacy scores. However, the interpretation of clinical improvements remains limited due to lack of a sham-control group. We thus surveyed effects reported for accepted augmentation therapies in depression. Data indicated that our findings exceed expected regression to the mean and placebo effects that have been reported for drug trials and other sham-controlled high-technology interventions. Taken together, we suggest that the experience of successful self-regulation during fMRI-NF training may be therapeutic. We conclude that if fMRI-NF is effective for depression, self-regulation training of higher visual areas may provide an effective alternative

Penalty-free feasibility boundary convergent multi-objective evolutionary algorithm for the optimization of water distribution systems

This paper presents a new penalty-free multi-objective evolutionary approach (PFMOEA) for the optimization of water distribution systems (WDSs). The proposed approach utilizes pressure dependent analysis (PDA) to develop a multi-objective evolutionary search. PDA is able to simulate both normal and pressure deficient networks and provides the means to accurately and rapidly identify the feasible region of the solution space, effectively locating global or near global optimal solutions along its active constraint boundary. The significant advantage of this method over previous methods is that it eliminates the need for ad-hoc penalty functions, additional “boundary search” parameters, or special constraint handling procedures. Conceptually, the approach is downright straightforward and probably the simplest hitherto. The PFMOEA has been applied to several WDS benchmarks and its performance examined. It is demonstrated that the approach is highly robust and efficient in locating optimal solutions. Superior results in terms of the initial network construction cost and number of hydraulic simulations required were obtained. The improvements are demonstrated through comparisons with previously published solutions from the literature

The ventro-medial prefrontal cortex: a major link between the autonomic nervous system, regulation of emotion, and stress reactivity?

Recent progress in neuroscience revealed diverse regions of the CNS which moderate autonomic and affective responses. The ventro-medial prefrontal cortex (vmPFC) plays a key role in these regulations. There is evidence that vmPFC activity is associated with cardiovascular changes during a motor task that are mediated by parasympathetic activity. Moreover, vmPFC activity makes important contributions to regulations of affective and stressful situations

Dose-Dependent Effects of Endotoxin on Neurobehavioral Functions in Humans

Clinical and experimental evidence document that inflammation and increased peripheral cytokine levels are associated with depression-like symptoms and neuropsychological disturbances in humans. However, it remains unclear whether and to what extent cognitive functions like memory and attention are affected by and related to the dose of the inflammatory stimulus. Thus, in a cross-over, double-blind, experimental approach, healthy male volunteers were administered with either placebo or bacterial lipopolysaccharide (LPS) at doses of 0.4 (n = 18) or 0.8 ng/kg of body weight (n = 16). Pro- and anti-inflammatory cytokines, norephinephrine and cortisol concentrations were analyzed before and 1, 1.75, 3, 4, 6, and 24 h after injection. In addition, changes in mood and anxiety levels were determined together with working memory (n-back task) and long term memory performance (recall of emotional and neutral pictures of the International Affective Picture System). Endotoxin administration caused a profound transient physiological response with dose-related elevations in body temperature and heart rate, increases in plasma interleukin (IL)-6, IL-10, tumor necrosis factor (TNF)-α and IL-1 receptor antagonist (IL-1ra), salivary and plasma cortisol, and plasma norepinephrine. These changes were accompanied by dose-related decreased mood and increased anxiety levels. LPS administration did not affect accuracy in working memory performance but improved reaction time in the high-dose LPS condition compared to the control conditon. In contrast, long-term memory performance was impaired selectively for emotional stimuli after administration of the lower but not of the higher dose of LPS. These data suggest the existence of at least two counter-acting mechanisms, one promoting and one inhibiting cognitive performance during acute systemic inflammation

Lithium and GSK3-β promoter gene variants influence white matter microstructure in bipolar disorder

Lithium is the mainstay for the treatment of bipolar disorder (BD) and inhibits glycogen synthase kinase 3-β (GSK3-β). The less active GSK3-β promoter gene variants have been associated with less detrimental clinical features of BD. GSK3-β gene variants and lithium can influence brain gray matter structure in psychiatric conditions. Diffusion tensor imaging (DTI) measures of white matter (WM) integrity showed widespred disruption of WM structure in BD. In a sample of 70 patients affected by a major depressive episode in course of BD, we investigated the effect of ongoing long-term lithium treatment and GSK3-β promoter rs334558 polymorphism on WM microstructure, using DTI and tract-based spatial statistics with threshold-free cluster enhancement. We report that the less active GSK3-β rs334558*C gene-promoter variants, and the long-term administration of the GSK3-β inhibitor lithium, were associated with increases of DTI measures of axial diffusivity (AD) in several WM fiber tracts, including corpus callosum, forceps major, anterior and posterior cingulum bundle (bilaterally including its hippocampal part), left superior and inferior longitudinal fasciculus, left inferior fronto-occipital fasciculus, left posterior thalamic radiation, bilateral superior and posterior corona radiata, and bilateral corticospinal tract. AD reflects the integrity of axons and myelin sheaths. We suggest that GSK3-β inhibition and lithium could counteract the detrimental influences of BD on WM structure, with specific benefits resulting from effects on specific WM tracts contributing to the functional integrity of the brain and involving interhemispheric, limbic, and large frontal, parietal, and fronto-occipital connections

Mourning and melancholia revisited: correspondences between principles of Freudian metapsychology and empirical findings in neuropsychiatry

Freud began his career as a neurologist studying the anatomy and physiology of the nervous system, but it was his later work in psychology that would secure his place in history. This paper draws attention to consistencies between physiological processes identified by modern clinical research and psychological processes described by Freud, with a special emphasis on his famous paper on depression entitled 'Mourning and melancholia'. Inspired by neuroimaging findings in depression and deep brain stimulation for treatment resistant depression, some preliminary physiological correlates are proposed for a number of key psychoanalytic processes. Specifically, activation of the subgenual cingulate is discussed in relation to repression and the default mode network is discussed in relation to the ego. If these correlates are found to be reliable, this may have implications for the manner in which psychoanalysis is viewed by the wider psychological and psychiatric communities

Microstructural Abnormalities in Subcortical Reward Circuitry of Subjects with Major Depressive Disorder

Previous studies of major depressive disorder (MDD) have focused on abnormalities in the prefrontal cortex and medial temporal regions. There has been little investigation in MDD of midbrain and subcortical regions central to reward/aversion function, such as the ventral tegmental area/substantia nigra (VTA/SN), and medial forebrain bundle (MFB).We investigated the microstructural integrity of this circuitry using diffusion tensor imaging (DTI) in 22 MDD subjects and compared them with 22 matched healthy control subjects. Fractional anisotropy (FA) values were increased in the right VT and reduced in dorsolateral prefrontal white matter in MDD subjects. Follow-up analysis suggested two distinct subgroups of MDD patients, which exhibited non-overlapping abnormalities in reward/aversion circuitry. The MDD subgroup with abnormal FA values in VT exhibited significantly greater trait anxiety than the subgroup with normal FA values in VT, but the subgroups did not differ in levels of anhedonia, sadness, or overall depression severity.These findings suggest that MDD may be associated with abnormal microstructure in brain reward/aversion regions, and that there may be at least two subtypes of microstructural abnormalities which each impact core symptoms of depression