Beyond convergence rates: Exact recovery with Tikhonov regularization with sparsity constraints

The Tikhonov regularization of linear ill-posed problems with an $\ell^1$ penalty is considered. We recall results for linear convergence rates and results on exact recovery of the support. Moreover, we derive conditions for exact support recovery which are especially applicable in the case of ill-posed problems, where other conditions, e.g. based on the so-called coherence or the restricted isometry property are usually not applicable. The obtained results also show that the regularized solutions do not only converge in the $\ell^1$-norm but also in the vector space $\ell^0$ (when considered as the strict inductive limit of the spaces $\R^n$ as $n$ tends to infinity). Additionally, the relations between different conditions for exact support recovery and linear convergence rates are investigated. With an imaging example from digital holography the applicability of the obtained results is illustrated, i.e. that one may check a priori if the experimental setup guarantees exact recovery with Tikhonov regularization with sparsity constraints

Overview of the PALM model system 6.0

In this paper, we describe the PALM model system 6.0. PALM (formerly an abbreviation for Parallelized Largeeddy Simulation Model and now an independent name) is a Fortran-based code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. This is a follow-up paper to the PALM 4.0 model description in Maronga et al. (2015). During the last years, PALM has been significantly improved and now offers a variety of new components. In particular, much effort was made to enhance the model with components needed for applications in urban environments, like fully interactive land surface and radiation schemes, chemistry, and an indoor model. This paper serves as an overview paper of the PALM 6.0 model system and we describe its current model core. The individual components for urban applications, case studies, validation runs, and issues with suitable input data are presented and discussed in a series of companion papers in this special issue

An untargeted multi-technique metabolomics approach to studying intracellular metabolites of HepG2 cells exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin

<p>Abstract</p> <p>Background</p> <p><it>In vitro </it>cell systems together with omics methods represent promising alternatives to conventional animal models for toxicity testing. Transcriptomic and proteomic approaches have been widely applied <it>in vitro </it>but relatively few studies have used metabolomics. Therefore, the goal of the present study was to develop an untargeted methodology for performing reproducible metabolomics on <it>in vitro </it>systems. The human liver cell line HepG2, and the well-known hepatotoxic and non-genotoxic carcinogen 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), were used as the <it>in vitro </it>model system and model toxicant, respectively.</p> <p>Results</p> <p>The study focused on the analysis of intracellular metabolites using NMR, LC-MS and GC-MS, with emphasis on the reproducibility and repeatability of the data. State of the art pre-processing and alignment tools and multivariate statistics were used to detect significantly altered levels of metabolites after exposing HepG2 cells to TCDD. Several metabolites identified using databases, literature and LC-nanomate-Orbitrap analysis were affected by the treatment. The observed changes in metabolite levels are discussed in relation to the reported effects of TCDD.</p> <p>Conclusions</p> <p>Untargeted profiling of the polar and apolar metabolites of <it>in vitro </it>cultured HepG2 cells is a valid approach to studying the effects of TCDD on the cell metabolome. The approach described in this research demonstrates that highly reproducible experiments and correct normalization of the datasets are essential for obtaining reliable results. The effects of TCDD on HepG2 cells reported herein are in agreement with previous studies and serve to validate the procedures used in the present work.</p

Feasibility of the Radner reading chards in low vision patients

Background: Being unable to read is a major problem for visually impaired patients. Since distance visual acuity (VA) does not adequately reflect reading ability, it is important to also evaluate near VA. The Radner Reading Charts (RRCs) are available to measure patients' reading performance. The present study tested the inter-chart and test-retest reliability of the RRCs in Dutch low-vision patients (i.e., visual acuity ≥0.3 logMAR) with various eye disorders. Methods: Thirty-eight patients read the three RRCs in random order. Then, about 1 month after the initial measurements, a test-retest procedure was performed in 15 of the 38 patients. Tested variables were reading acuity (logRAD), logRAD score, logRAD/logMAR ratio, maximum reading speed (MRS), and critical print size (CPS). Both MRS and CPS were calculated in two different ways. To determine the variability, a mixed-model analysis was used. Results: For all variables, the largest part of the variance was explained by the individual subject (86-89%) whereas the chart accounted for only 0-0.78% of the variability. Therefore, the inter-chart and test-retest reliability was high, except for the CPS which had a poor to moderate reliability (31-62%) when calculated in the two different ways. Conclusions: The inter-chart and test-retest results showed high reliability in patients with low vision due to various diseases; therefore, the charts are feasible to determine effects in large groups. © 2010 Springer-Verlag

Design for Mobile Mental Health:An Exploratory Review

A large number of mobile mental health apps are available to the public but current knowledge about requirements of designing such solutions is scarce, especially from sociotechnical and user centred points of view. Due to the significant role of mobile apps in the mental health service models, identifying the design requirements of mobile mental health solutions is crucial. Some of those requirements have been addressed individually in the literature, but there are few research studies that show a comprehensive picture of this domain. This exploratory review aims to facilitate such holistic understanding. The main search keywords of the review were identified in a cross-disciplinary requirements workshop. The search was started by finding some core references in the healthcare databases. A wider range of references then has been explored using a snowball method. Findings showed that there is a good understanding of individual design requirements in current literature but there are few examples of implementing a combination of different design requirements in real world products. The design processes specifically developed for mobile mental health apps are also rare. Most studies on operational mobile mental health apps address major mental health issues while prevention and wellbeing areas are underdeveloped. In conclusion, the main recommendations for designing future mobile mental health solutions include: moving towards sociotechnical and open design strategies, understanding and creating shared value, recognizing all dimensions of efficacy, bridging design and medical research and development, and considering an ecosystem perspective

Can human amblyopia be treated in adulthood?

Amblyopia is a common visual disorder that results in a spatial acuity deficit in the affected eye. Orthodox treatment is to occlude the unaffected eye for lengthy periods, largely determined by the severity of the visual deficit at diagnosis. Although this treatment is not without its problems (poor compliance, potential to reduce binocular function, etc) it is effective in many children with moderate to severe amblyopia. Diagnosis and initiation of treatment early in life are thought to be critical to the success of this form of therapy. Occlusion is rarely undertaken in older children (more than 10 years old) as the visual benefits are considered to be marginal. Therefore, in subjects where occlusion is not effective or those missed by mass screening programs, there is no alternative therapy available later in life. More recently, burgeoning evidence has begun to reveal previously unrecognized levels of residual neural plasticity in the adult brain and scientists have developed new genetic, pharmacological, and behavioral interventions to activate these latent mechanisms in order to harness their potential for visual recovery. Prominent amongst these is the concept of perceptual learning—the fact that repeatedly practicing a challenging visual task leads to substantial and enduring improvements in visual performance over time. In the normal visual system the improvements are highly specific to the attributes of the trained stimulus. However, in the amblyopic visual system, learned improvements have been shown to generalize to novel tasks. In this paper we ask whether amblyopic deficits can be reduced in adulthood and explore the pattern of transfer of learned improvements. We also show that developing training protocols that target the deficit in stereo acuity allows the recovery of normal stereo function even in adulthood. This information will help guide further development of learning-based interventions in this clinical group

Screening out irrelevant cell-based models of disease

The common and persistent failures to translate promising preclinical drug candidates into clinical success highlight the limited effectiveness of disease models currently used in drug discovery. An apparent reluctance to explore and adopt alternative cell-and tissue-based model systems, coupled with a detachment from clinical practice during assay validation, contributes to ineffective translational research. To help address these issues and stimulate debate, here we propose a set of principles to facilitate the definition and development of disease-relevant assays, and we discuss new opportunities for exploiting the latest advances in cell-based assay technologies in drug discovery, including induced pluripotent stem cells, three-dimensional (3D) co-culture and organ-on-a-chip systems, complemented by advances in single-cell imaging and gene editing technologies. Funding to support precompetitive, multidisciplinary collaborations to develop novel preclinical models and cell-based screening technologies could have a key role in improving their clinical relevance, and ultimately increase clinical success rates