Large-Scale Detection of Non-Technical Losses in Imbalanced Data Sets

Non-technical losses (NTL) such as electricity theft cause significant harm to our economies, as in some countries they may range up to 40% of the total electricity distributed. Detecting NTLs requires costly on-site inspections. Accurate prediction of NTLs for customers using machine learning is therefore crucial. To date, related research largely ignore that the two classes of regular and non-regular customers are highly imbalanced, that NTL proportions may change and mostly consider small data sets, often not allowing to deploy the results in production. In this paper, we present a comprehensive approach to assess three NTL detection models for different NTL proportions in large real world data sets of 100Ks of customers: Boolean rules, fuzzy logic and Support Vector Machine. This work has resulted in appreciable results that are about to be deployed in a leading industry solution. We believe that the considerations and observations made in this contribution are necessary for future smart meter research in order to report their effectiveness on imbalanced and large real world data sets.Comment: Proceedings of the Seventh IEEE Conference on Innovative Smart Grid Technologies (ISGT 2016

Microenvironmental regulation of metastasis

Metastasis is a multistage process that requires cancer cells to escape from the primary tumour, survive in the circulation, seed at distant sites and grow. Each of these processes involves rate-limiting steps that are influenced by non-malignant cells of the tumour microenvironment. Many of these cells are derived from the bone marrow, particularly the myeloid lineage, and are recruited by cancer cells to enhance their survival, growth, invasion and dissemination. This Review describes experimental data demonstrating the role of the microenvironment in metastasis, identifies areas for future research and suggests possible new therapeutic avenues

Sleep and daytime psychomotor performance during acute and continuation treatment of major depressive disorder: double-blind randomised controlled trial of escitalopram vs paroxetine

Introduction. Disturbed sleep is a common depressive symptom which often persists despite otherwise successful pharmacological or psychological treatment, and is associated with increased risks of recurrence. As both worsened insomnia and daytime drowsiness are reported as treatment-emergent adverse effects with antidepressants, we wished to evaluate the effects of acute and continuation treatment on sleep and daytime psychomotor performance. Method. International, randomized, flexible-dose, parallel-group, comparator-controlled study involving 36 centres in 6 countries. Patients met DSM-IV criteria for current major depressive episode, with a baseline score of 22-40 on the Montgomery-Åsberg Depression Rating Scale (MADRS). After a single-blind one-week placebo run-in, patients were randomized to escitalopram (ESC) (10-20 mg/day) or paroxetine (PAR) (20-40 mg/day) for 8 weeks of acute treatment: those who were significantly improved could continue fixed-dose double-blind treatment for a further 19 weeks. Sleep and early morning behaviour were assessed by the Leeds Sleep Evaluation Questionnaire (LSEQ), psychomotor performance by Critical FIicker Fusion (CFF) and Choice Reaction Time, and cognitive function by the Cognitive Failures Questionnaire (CFQ). Assessments were undertaken at baseline and weeks 4, 8, 16 and 27. Results. 323 patients (ESC, 165; PAR, 158) started acute treatment and received at least one dose of study medication. There were no significant differences between treatment groups in reduction of depressive symptoms from baseline to week 8, but in severely depressed patients (baseline MADRS >30) escitalopram was superior (p<0.05; ANCOVA) to paroxetine at week 27. Sleep and daytime performance improved as depressive symptoms reduced. Two patients withdrew from the study due to the adverse effect of insomnia, and 1 due to somnolence. There were no significant differences between treatment groups in change from baseline on the LSEQ subscales for ‘getting to sleep’, ‘awakening from sleep’, or ‘behaviour following sleep’ although at week 4 ESC was superior (p<0.01; ANCOVA) to PAR on ‘quality of sleep’. There were no significant differences between treatment groups in the change from baseline in CFF, recognition or motor reaction times, or CFQ total score, at any of the scheduled assessments. Conclusion. In this study, only a small number of patients withdrew from antidepressant treatment due to adverse effects on sleep or daytime alertness. Repeated assessments of sleep and daytime performance indicated a steady improvement during acute and continuation treatment of major depressive disorder with both escitalopram and paroxetine. Source of funding. The overall randomised controlled trial was sponsored by Lundbeck Ltd