Level-Based Analysis of the Population-Based Incremental Learning Algorithm

The Population-Based Incremental Learning (PBIL) algorithm uses a convex combination of the current model and the empirical model to construct the next model, which is then sampled to generate offspring. The Univariate Marginal Distribution Algorithm (UMDA) is a special case of the PBIL, where the current model is ignored. Dang and Lehre (GECCO 2015) showed that UMDA can optimise LeadingOnes efficiently. The question still remained open if the PBIL performs equally well. Here, by applying the level-based theorem in addition to Dvoretzky--Kiefer--Wolfowitz inequality, we show that the PBIL optimises function LeadingOnes in expected time $\mathcal{O}(n\lambda \log \lambda + n^2)$ for a population size $\lambda = \Omega(\log n)$, which matches the bound of the UMDA. Finally, we show that the result carries over to BinVal, giving the fist runtime result for the PBIL on the BinVal problem.Comment: To appea

Association of lower total bilirubin level with statin usage: the United States National Health and Nutrition Examination Survey 1999–2008

OBJECTIVE: A low circulating level of bilirubin is associated with increased cardiovascular risk. As statins can stimulate heme oxygenase-1 (HO-1), which increases bilirubin production, we investigated whether statins in routine use increase total bilirubin levels in subjects at high cardiovascular risk. METHODS: Data from 3290 subjects with self-reported history of hypercholesterolemia, diabetes, or cardiovascular diseases in the United States National Health and Nutrition Examination Survey (NHANES) 1999-2008 were analyzed. RESULTS: Subjects taking statins (n = 1156) had lower total bilirubin levels than those not taking any lipid-lowering medication (n = 2134) after adjusting for age, sex, race/ethnicity, and survey period (adjusted mean = 0.699 vs 0.729 mg/dl respectively, P=0.001). The association remained significant after adjusting for more covariates (P = 0.002), but was attenuated after further adjusting for glycosylated hemoglobin, insulin resistance index, and low-density lipoprotein (LDL) cholesterol (P = 0.043). The use of lovastatin, rosuvastatin, and cerivastatin was associated with lower total bilirubin levels in the full adjustment model (P < 0.05). CONCLUSION: The use of statins was associated unexpectedly with lower total bilirubin levels. This could be explained at least partly by the effect of statins on glycemia and LDL cholesterol. Our results do not suggest that the anti-oxidant and anti-inflammatory effects of statins are due to HO-1 induction and increased serum bilirubin levels.postprin

A Modified Sequence-to-point HVAC Load Disaggregation Algorithm

This paper presents a modified sequence-to-point (S2P) algorithm for disaggregating the heat, ventilation, and air conditioning (HVAC) load from the total building electricity consumption. The original S2P model is convolutional neural network (CNN) based, which uses load profiles as inputs. We propose three modifications. First, the input convolution layer is changed from 1D to 2D so that normalized temperature profiles are also used as inputs to the S2P model. Second, a drop-out layer is added to improve adaptability and generalizability so that the model trained in one area can be transferred to other geographical areas without labelled HVAC data. Third, a fine-tuning process is proposed for areas with a small amount of labelled HVAC data so that the pre-trained S2P model can be fine-tuned to achieve higher disaggregation accuracy (i.e., better transferability) in other areas. The model is first trained and tested using smart meter and sub-metered HVAC data collected in Austin, Texas. Then, the trained model is tested on two other areas: Boulder, Colorado and San Diego, California. Simulation results show that the proposed modified S2P algorithm outperforms the original S2P model and the support-vector machine based approach in accuracy, adaptability, and transferability

Functional significance may underlie the taxonomic utility of single amino acid substitutions in conserved proteins

We hypothesized that some amino acid substitutions in conserved proteins that are strongly fixed by critical functional roles would show lineage-specific distributions. As an example of an archetypal conserved eukaryotic protein we considered the active site of ß-tubulin. Our analysis identified one amino acid substitution—ß-tubulin F224—which was highly lineage specific. Investigation of ß-tubulin for other phylogenetically restricted amino acids identified several with apparent specificity for well-defined phylogenetic groups. Intriguingly, none showed specificity for “supergroups” other than the unikonts. To understand why, we analysed the ß-tubulin Neighbor-Net and demonstrated a fundamental division between core ß-tubulins (plant-like) and divergent ß-tubulins (animal and fungal). F224 was almost completely restricted to the core ß-tubulins, while divergent ß-tubulins possessed Y224. Thus, our specific example offers insight into the restrictions associated with the co-evolution of ß-tubulin during the radiation of eukaryotes, underlining a fundamental dichotomy between F-type, core ß-tubulins and Y-type, divergent ß-tubulins. More broadly our study provides proof of principle for the taxonomic utility of critical amino acids in the active sites of conserved proteins

Promyelocytic leukemia nuclear bodies associate with transcriptionally active genomic regions

Cancer Research UK

Memory consolidation reconfigures neural pathways involved in the suppression of emotional memories

The ability to suppress unwanted emotional memories is crucial for human mental health. Through consolidation over time, emotional memories often become resistant to change. However, how consolidation impacts the effectiveness of emotional memory suppression is still unknown. Using event-related fMRI while concurrently recording skin conductance, we investigated the neurobiological processes underlying the suppression of aversive memories before and after overnight consolidation. Here we report that consolidated aversive memories retain their emotional reactivity and become more resistant to suppression. Suppression of consolidated memories involves higher prefrontal engagement, and less concomitant hippocampal and amygdala disengagement. In parallel, we show a shift away from hippocampal-dependent representational patterns to distributed neocortical representational patterns in the suppression of aversive memories after consolidation. These findings demonstrate rapid changes in emotional memory organization with overnight consolidation, and suggest possible neurobiological bases underlying the resistance to suppression of emotional memories in affective disorders

Detection of proteoglycan loss from articular cartilage using Brillouin microscopy, with applications to osteoarthritis

© 2019, OSA - The Optical Society. All rights reserved. The degeneration of articular cartilage (AC) occurs in osteoarthritis (OA), which is a leading cause of pain and disability in middle-aged and older people. The early diseaserelated changes in cartilage extra-cellular matrix (ECM) start with depletion of proteoglycan (PG), leading to an increase in tissue hydration and permeability. These early compositional changes are small (<10%) and hence difficult to register with conventional non-invasive imaging technologies (magnetic resonance and ultrasound imaging). Here we apply Brillouin microscopy for detecting changes in the mechanical properties and composition of porcine AC. OA-like degradation is mimicked by enzymatic tissue digestion, and we compare Brillouin microscopy measurements against histological staining of PG depletion over varying digestion times and enzyme concentrations. The non-destructive nature of Brillouin imaging technology opens new avenues for creating minimally invasive arthroscopic devices for OA diagnostics and therapeutic monitoring

An ICA-Based HVAC Load Disaggregation Method Using Smart Meter Data

This paper presents an independent component analysis (ICA) based unsupervised-learning method for heat, ventilation, and air-conditioning (HVAC) load disaggregation using low-resolution (e.g., 15 minutes) smart meter data. We first demonstrate that electricity consumption profiles on mild-temperature days can be used to estimate the non-HVAC base load on hot days. A residual load profile can then be calculated by subtracting the mild-day load profile from the hot-day load profile. The residual load profiles are processed using ICA for HVAC load extraction. An optimization-based algorithm is proposed for post-adjustment of the ICA results, considering two bounding factors for enhancing the robustness of the ICA algorithm. First, we use the hourly HVAC energy bounds computed based on the relationship between HVAC load and temperature to remove unrealistic HVAC load spikes. Second, we exploit the dependency between the daily nocturnal and diurnal loads extracted from historical meter data to smooth the base load profile. Pecan Street data with sub-metered HVAC data were used to test and validate the proposed methods.Simulation results demonstrated that the proposed method is computationally efficient and robust across multiple customers

PROTOCOL: Residential energy efficiency interventions: An effectiveness systematic review

This review aims to identify, appraise and synthesise the evidence available on the effectiveness of energy efficiency measure installations, including those bundled with behavioural interventions. The synthesis will estimate the overall impact of these interventions as well as examine possible causes of variation in impacts. We will also attempt to assess the cost-effectiveness of residential energy efficiency interventions

Interleukin-33 regulates tissue remodelling and inhibits angiogenesis in the eye

Age-related macular degeneration (AMD) is the leading cause of central vision loss worldwide. Loss of retinal pigment epithelium (RPE) is a major pathological hallmark in AMD with or without pathological neovascularization. Although activation of the immune system is implicated in disease progression, pathological pathways remain diverse and unclear. Here, we report an unexpected protective role of a pro-inflammatory cytokine, interleukin-33 (IL-33) in ocular angiogenesis. IL-33 and its receptor (ST2) are expressed constitutively in human and murine retina and choroid. When RPE was activated, IL-33 expression was markedly elevated in vitro. We found that IL-33 regulated tissue remodelling by attenuating wound-healing responses, including reduction in migration of choroidal fibroblasts and retinal microvascular endothelial cells, and inhibition of collagen gel contraction. In vivo, local administration of recombinant IL-33 inhibited murine choroidal neovascularization (CNV) formation, a surrogate of human neovascular AMD, and this effect was ST2-dependent. Collectively, these data demonstrate IL-33 as a potential immunotherapy and distinguishes pathways for subverting AMD pathology