Convective initiation and storm life‐cycles in convection‐permitting simulations of the Met Office Unified Model over South Africa

Convective initiation is a challenge for convection‐permitting models due to its sensitivity to sub‐km processes. We evaluate the representation of convective storms and their initiation over South Africa during four summer months in Met Office Unified Model simulations at 1.5‐km horizontal grid length. Storm size distributions from the model compare well against radar observations, but rainfall in the model is predominantly produced by large storms (50 km in diameter or larger) in the evening, whereas radar observations show most rainfall occurs throughout the afternoon, from storms 10‐50 km in diameter. In all months, modelled maximum number of storm initiations occurs at least 2 hours prior to the radar‐observed maximum. However, the diurnal cycle of rainfall compares well between model and observations, suggesting the numerous storm initiations in the simulations do not produce much rainfall. Modelled storms are generally less intense than in the radar observations, especially in early summer. In February, when tropical influences dominate, the simulated storms are of similar intensity to observed storms. Simulated storms tend to reach their peak intensity in the first 15 minutes after initiation, then gradually become less intense as they grow. In radar observations, storms reach their peak intensity 15‐30 minutes into their life cycle, stay intense as they grow larger, then gradually weaken after they have reached their maximum diameter. Two November case studies of severe convection are analysed in detail. Higher resolution grid length initiates convection slightly earlier (300 m cf. 1.5 km) with the same science settings. Two 1.5‐km simulations that apply more sub‐grid mixing have delayed convective initiation. Analysis of soundings indicates little difference in convective indices, suggesting that differences in convection may be attributed to choices in sub‐grid mixing parameters

General dynamical equations of motion for elastic body systems

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76290/1/AIAA-11407-643.pd

Stimulus-dependent maximum entropy models of neural population codes

Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. To be able to infer a model for this distribution from large-scale neural recordings, we introduce a stimulus-dependent maximum entropy (SDME) model---a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. The model is able to capture the single-cell response properties as well as the correlations in neural spiking due to shared stimulus and due to effective neuron-to-neuron connections. Here we show that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. As a result, the SDME model gives a more accurate account of single cell responses and in particular outperforms uncoupled models in reproducing the distributions of codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like surprise and information transmission in a neural population.Comment: 11 pages, 7 figure

Dephasing dynamics across different local vibrational modes and crystalline environments

The perturbed free induction decay (PFID) observed in ultrafast infrared spectroscopy was used to unveil the rates at which different vibrational modes of the same atomic-scale defect can interact with their environment. The N3VH0 defect in diamond provided a model system, allowing a comparison of stretch and bend vibrational modes within different crystal lattice environments. The observed bend mode (first overtone) exhibited dephasing times T2=2.8(1)  ps, while the fundamental stretch mode had surprisingly faster dynamics T2<1.7 ps driven by its more direct perturbation of the crystal lattice, with increased phonon coupling. Further, at high defect concentrations the stretch mode’s dephasing rate was enhanced. The ability to reliably measure T2 via PFID provides vital insights into how vibrational systems interact with their local environment

Paradigmatic Approaches to Studying Environment and Human Health: (Forgotten) Implications for Interdisciplinary Research

Copyright © 2013 ElsevierInterdisciplinary research is increasingly promoted in a wide range of fields, especially so in the study of relationships between the environment and human health. However, many projects and research teams struggle to address exactly how researchers from a multitude of disciplinary and methodological backgrounds can best work together to maximize the value of this approach to research. In this paper, we briefly review the role of interdisciplinary research, and emphasize that it is not only our discipline and methods, but our research paradigms, that shape the way that we work. We summarize three key research paradigms - positivism, postpositivism and interpretivism - with an example of how each might approach a given environment-health research issue. In turn, we argue that understanding the paradigm from which each researcher operates is fundamental to enabling and optimizing the integration of research disciplines, now argued by many to be necessary for our understanding of the complexities of the interconnections between human health and our environment as well as their impacts in the policy arena. We recognize that a comprehensive interrogation of research approaches and philosophies would require far greater length than is available in a journal paper. However, our intention is to instigate debate, recognition, and appreciation of the different worlds inhabited by the multitude of researchers involved in this rapidly expanding field

Behaviour change strategies for reducing blood pressure-related disease burden: findings from a global implementation research programme.

The Global Alliance for Chronic Diseases comprises the majority of the world's public research funding agencies. It is focussed on implementation research to tackle the burden of chronic diseases in low- and middle-income countries and amongst vulnerable populations in high-income countries. In its inaugural research call, 15 projects were funded, focussing on lowering blood pressure-related disease burden. In this study, we describe a reflexive mapping exercise to identify the behaviour change strategies undertaken in each of these projects.Using the Behaviour Change Wheel framework, each team rated the capability, opportunity and motivation of the various actors who were integral to each project (e.g. community members, non-physician health workers and doctors in projects focussed on service delivery). Teams then mapped the interventions they were implementing and determined the principal policy categories in which those interventions were operating. Guidance was provided on the use of Behaviour Change Wheel to support consistency in responses across teams. Ratings were iteratively discussed and refined at several group meetings.There was marked variation in the perceived capabilities, opportunities and motivation of the various actors who were being targeted for behaviour change strategies. Despite this variation, there was a high degree of synergy in interventions functions with most teams utilising complex interventions involving education, training, enablement, environmental restructuring and persuasion oriented strategies. Similar policy categories were also targeted across teams particularly in the areas of guidelines, communication/marketing and service provision with few teams focussing on fiscal measures, regulation and legislation.The large variation in preparedness to change behaviour amongst the principal actors across these projects suggests that the interventions themselves will be variably taken up, despite the similarity in approaches taken. The findings highlight the importance of contextual factors in driving success and failure of research programmes. Forthcoming outcome and process evaluations from each project will build on this exploratory work and provide a greater understanding of factors that might influence scale-up of intervention strategies

Artificial intelligence for dementia genetics and omics

Genetics and omics studies of Alzheimer's disease and other dementia subtypes enhance our understanding of underlying mechanisms and pathways that can be targeted. We identified key remaining challenges: First, can we enhance genetic studies to address missing heritability? Can we identify reproducible omics signatures that differentiate between dementia subtypes? Can high-dimensional omics data identify improved biomarkers? How can genetics inform our understanding of causal status of dementia risk factors? And which biological processes are altered by dementia-related genetic variation? Artificial intelligence (AI) and machine learning approaches give us powerful new tools in helping us to tackle these challenges, and we review possible solutions and examples of best practice. However, their limitations also need to be considered, as well as the need for coordinated multidisciplinary research and diverse deeply phenotyped cohorts. Ultimately AI approaches improve our ability to interrogate genetics and omics data for precision dementia medicine

Complement dysregulation is a prevalent and therapeutically amenable feature of long COVID

Background Long COVID encompasses a heterogeneous set of ongoing symptoms that affect many individuals after recovery from infection with SARS-CoV-2. The underlying biological mechanisms nonetheless remain obscure, precluding accurate diagnosis and effective intervention. Complement dysregulation is a hallmark of acute COVID-19 but has not been investigated as a potential determinant of long COVID. Methods We quantified a series of complement proteins, including markers of activation and regulation, in plasma samples from healthy convalescent individuals with a confirmed history of infection with SARS-CoV-2 and age/ethnicity/sex/infection/vaccine-matched patients with long COVID. Findings Markers of classical (C1s-C1INH complex), alternative (Ba, iC3b), and terminal pathway (C5a, TCC) activation were significantly elevated in patients with long COVID. These markers in combination had a receiver operating characteristic predictive power of 0.794. Other complement proteins and regulators were also quantitatively different between healthy convalescent individuals and patients with long COVID. Generalized linear modeling further revealed that a clinically tractable combination of just four of these markers, namely the activation fragments iC3b, TCC, Ba, and C5a, had a predictive power of 0.785. Conclusions These findings suggest that complement biomarkers could facilitate the diagnosis of long COVID and further suggest that currently available inhibitors of complement activation could be used to treat long COVID

Inflammatory arthritis in HIV positive patients: A practical guide

Background: Musculoskeletal manifestations of the human immunodeficiency virus (HIV) have been described since the outset of the global HIV epidemic. Articular syndromes that have been described in association with HIV include HIV-associated arthropathy, seronegative spondyloarthropathies (SPA) (reactive arthritis, psoriatic arthritis (PsA) and undifferentiated SPA), rheumatoid arthritis (RA) and painful articular syndrome. Methods: We carried out a computer-assisted search of PubMed for the medical literature from January 1981 to January 2015 using the keywords HIV, acquired immune-deficiency syndrome, rheumatic manifestations, arthritis, spondyloarthropathy, anti-TNF and disease modifying antirheumatic drugs. Only English language literature was included and only studies involving adult human subjects were assessed. Results: There are challenges in the management of inflammatory arthritis in patients who are HIV-positive, including difficulties in the assessment of disease activity and limited information on the safety of immunosuppressive drugs in these individuals. Conclusions: This review focuses on the clinical characteristics of the inflammatory articular syndromes that have been described in association with HIV infection and discusses the therapeutic options for these patients

A Case of Chronic Infectious Arthritis of the Temporomandibular Joint Associated with Osteomyelitis without Malocclusion

Infectious arthritis of the temporomandibular joint (TMJ) is rare, and previous reports have identified malocclusion resulting from condylar deformity and displacement of the condyle as one of the clinical characteristics of the disease. Here we report the case of a 33-year-old man with chronic infectious arthritis of the TMJ without malocclusion associated with osteomyelitis of the right mandible. Based on radiological findings of more prominent inflammation at the TMJ than in other regions and on the observed efficacy of antibiotic administration, we made a diagnosis of suppurative arthritis of the TMJ. Based on our empirical experience, including the present case, we speculate that refusal to cooperate with medical care may be a factor in the development of infectious arthritis of the TMJ