Capturing natural-colour 3D models of insects for species discovery

Collections of biological specimens are fundamental to scientific understanding and characterization of natural diversity. This paper presents a system for liberating useful information from physical collections by bringing specimens into the digital domain so they can be more readily shared, analyzed, annotated and compared. It focuses on insects and is strongly motivated by the desire to accelerate and augment current practices in insect taxonomy which predominantly use text, 2D diagrams and images to describe and characterize species. While these traditional kinds of descriptions are informative and useful, they cannot cover insect specimens "from all angles" and precious specimens are still exchanged between researchers and collections for this reason. Furthermore, insects can be complex in structure and pose many challenges to computer vision systems. We present a new prototype for a practical, cost-effective system of off-the-shelf components to acquire natural-colour 3D models of insects from around 3mm to 30mm in length. Colour images are captured from different angles and focal depths using a digital single lens reflex (DSLR) camera rig and two-axis turntable. These 2D images are processed into 3D reconstructions using software based on a visual hull algorithm. The resulting models are compact (around 10 megabytes), afford excellent optical resolution, and can be readily embedded into documents and web pages, as well as viewed on mobile devices. The system is portable, safe, relatively affordable, and complements the sort of volumetric data that can be acquired by computed tomography. This system provides a new way to augment the description and documentation of insect species holotypes, reducing the need to handle or ship specimens. It opens up new opportunities to collect data for research, education, art, entertainment, biodiversity assessment and biosecurity control.Comment: 24 pages, 17 figures, PLOS ONE journa

Towards high-throughput 3D insect capture for species discovery and diagnostics

Digitisation of natural history collections not only preserves precious information about biological diversity, it also enables us to share, analyse, annotate and compare specimens to gain new insights. High-resolution, full-colour 3D capture of biological specimens yields color and geometry information complementary to other techniques (e.g., 2D capture, electron scanning and micro computed tomography). However 3D colour capture of small specimens is slow for reasons including specimen handling, the narrow depth of field of high magnification optics, and the large number of images required to resolve complex shapes of specimens. In this paper, we outline techniques to accelerate 3D image capture, including using a desktop robotic arm to automate the insect handling process; using a calibrated pan-tilt rig to avoid attaching calibration targets to specimens; using light field cameras to capture images at an extended depth of field in one shot; and using 3D Web and mixed reality tools to facilitate the annotation, distribution and visualisation of 3D digital models.Comment: 2 pages, 1 figure, for BigDig workshop at 2017 eScience conferenc

Dual Control for Nonlinear Model Predictive Control

In this thesis we treat the problem of Dual Control for Nonlinear Model Predictive Control (NMPC) from a perspective of Optimal Experimental Design (OED). Controlling uncertain processes poses great challenges as well as offers opportunities for mathematicians in recent years. While the Dynamic Programming principle might hold, its applicability is limited to a few very simple cases. This calls for the study of approximation methods and real-time algorithms. In this work we study optimal control problems with uncertain parameters and states and develop new methods based on Dual Control. We first carry out a sensitivity analysis to assess the effect of uncertainty on the control performance. By analyzing the interplay between the performance control task and the information gain task, we propose novel approaches to the Dual Control problem in the context of NMPC with the help of OED. Furthermore, we present the statistical background and probabilistic bounds for the realized controller performance with respect to the original objective. Therefore, we essentially fill a gap in the literature. As NMPC drives the process in the course of time and the estimation procedure runs, it is of interest to understand the convergence properties and the asymptotic properties of the parameter and state estimates. We devote one chapter to the investigation of asymptotic properties of the Least Squares (LS) estimates, showing that in some cases the estimation problem is ill-posed leading to divergence. With the use of a sequential LS method, however, convergence can be retained. A convergence result is established. On the other hand, we observe that for some processes, if the states of interest are stable, the convergence of parameter estimates may become irrelevant. This motivates our study on partial stability for NMPC which extends the classical stability analysis of NMPC by several fundamental results, including general stability results without terminal costs or terminal constraints. Another source of motivation for this thesis is the study of nonlinear Optimal Experimental Design. Since optimal designs are computed for specific values of parameters but the true ones are unknown, it is important to assess the optimality of designs as well as to find a way to reach the true parameters. This motivates our study on sequential OED in the framework of Dual Control. For this purpose, we reformulate the problem of sequential OED to make it applicable for the Dynamic Programming principle. We also build a bridge between continuous designs and discrete designs by presenting several results on finite support for continuous OED. The methods have been implemented and we illustrate the obtained results by examples ranging from classics to practical applications in vehicle control and chemical engineering

Heuristic regularization methods for numerical differentiation

AbstractIn this paper, we use smoothing splines to deal with numerical differentiation. Some heuristic methods for choosing regularization parameters are proposed, including the L-curve method and the de Boor method. Numerical experiments are performed to illustrate the efficiency of these methods in comparison with other procedures

Self-organizing & stochastic behaviors during the regeneration of hair stem cells

Stem cells cycle through active and quiescent states. Large populations of stem cells in an organ may cycle randomly or in a coordinated manner. Although stem cell cycling within single hair follicles has been studied, less is known about regenerative behavior in a hair follicle population. By combining predictive mathematical modeling with in vivo studies in mice and rabbits, we show that a follicle progresses through cycling stages by continuous integration of inputs from intrinsic follicular and extrinsic environmental signals based on universal patterning principles. Signaling from the WNT/bone morphogenetic protein activator/inhibitor pair is coopted to mediate interactions among follicles in the population. This regenerative strategy is robust and versatile because relative activator/inhibitor strengths can be modulated easily, adapting the organism to different physiological and evolutionary needs

Cyclic dermal BMP signalling regulates stem cell activation during hair regeneration

In the age of stem cell engineering it is critical to understand how stem cell activity is regulated during regeneration. Hairs are mini-organs that undergo cyclic regeneration throughout adult life1, and are an important model for organ regeneration. Hair stem cells located in the follicle bulge2 are regulated by the surrounding microenvironment, or niche3. The activation of such stem cells is cyclic, involving periodic -catenin activity4, 5, 6, 7. In the adult mouse, regeneration occurs in waves in a follicle population, implying coordination among adjacent follicles and the extrafollicular environment. Here we show that unexpected periodic expression of bone morphogenetic protein 2 (Bmp2) and Bmp4 in the dermis regulates this process. This BMP cycle is out of phase with the WNT/-catenin cycle, thus dividing the conventional telogen into new functional phases: one refractory and the other competent for hair regeneration, characterized by high and low BMP signalling, respectively. Overexpression of noggin, a BMP antagonist, in mouse skin resulted in a markedly shortened refractory phase and faster propagation of the regenerative wave. Transplantation of skin from this mutant onto a wild-type host showed that follicles in donor and host can affect their cycling behaviours mutually, with the outcome depending on the equilibrium of BMP activity in the dermis. Administration of BMP4 protein caused the competent region to become refractory. These results show that BMPs may be the long-sought 'chalone' inhibitors of hair growth postulated by classical experiments. Taken together, results presented in this study provide an example of hierarchical regulation of local organ stem cell homeostasis by the inter-organ macroenvironment. The expression of Bmp2 in subcutaneous adipocytes indicates physiological integration between these two thermo-regulatory organs. Our findings have practical importance for studies using mouse skin as a model for carcinogenesis, intra-cutaneous drug delivery and stem cell engineering studies, because they highlight the acute need to differentiate supportive versus inhibitory regions in the host skin

Uterine selection of human embryos at implantation

Human embryos frequently harbor large-scale complex chromosomal errors that impede normal development. Affected embryos may fail to implant although many first breach the endometrial epithelium and embed in the decidualizing stroma before being rejected via mechanisms that are poorly understood. Here we show that developmentally impaired human embryos elicit an endoplasmic stress response in human decidual cells. A stress response was also evident upon in vivo exposure of mouse uteri to culture medium conditioned by low-quality human embryos. By contrast, signals emanating from developmentally competent embryos activated a focused gene network enriched in metabolic enzymes and implantation factors. We further show that trypsin, a serine protease released by pre-implantation embryos, elicits Ca2+ signaling in endometrial epithelial cells. Competent human embryos triggered short-lived oscillatory Ca2+ fluxes whereas low-quality embryos caused a heightened and prolonged Ca2+ response. Thus, distinct positive and negative mechanisms contribute to active selection of human embryos at implantation

Optogenetics and deep brain stimulation neurotechnologies

Brain neural network is composed of densely packed, intricately wired neurons whose activity patterns ultimately give rise to every behavior, thought, or emotion that we experience. Over the past decade, a novel neurotechnique, optogenetics that combines light and genetic methods to control or monitor neural activity patterns, has proven to be revolutionary in understanding the functional role of specific neural circuits. We here briefly describe recent advance in optogenetics and compare optogenetics with deep brain stimulation technology that holds the promise for treating many neurological and psychiatric disorders

Integrating transposable elements in the 3D genome

Chromosome organisation is increasingly recognised as an essential component of genome regulation, cell fate and cell health. Within the realm of transposable elements (TEs) however, the spatial information of how genomes are folded is still only rarely integrated in experimental studies or accounted for in modelling. Whilst polymer physics is recognised as an important tool to understand the mechanisms of genome folding, in this commentary we discuss its potential applicability to aspects of TE biology. Based on recent works on the relationship between genome organisation and TE integration, we argue that existing polymer models may be extended to create a predictive framework for the study of TE integration patterns. We suggest that these models may offer orthogonal and generic insights into the integration profiles (or "topography") of TEs across organisms. In addition, we provide simple polymer physics arguments and preliminary molecular dynamics simulations of TEs inserting into heterogeneously flexible polymers. By considering this simple model, we show how polymer folding and local flexibility may generically affect TE integration patterns. The preliminary discussion reported in this commentary is aimed to lay the foundations for a large-scale analysis of TE integration dynamics and topography as a function of the three-dimensional host genome

Defending the genome from the enemy within:mechanisms of retrotransposon suppression in the mouse germline

The viability of any species requires that the genome is kept stable as it is transmitted from generation to generation by the germ cells. One of the challenges to transgenerational genome stability is the potential mutagenic activity of transposable genetic elements, particularly retrotransposons. There are many different types of retrotransposon in mammalian genomes, and these target different points in germline development to amplify and integrate into new genomic locations. Germ cells, and their pluripotent developmental precursors, have evolved a variety of genome defence mechanisms that suppress retrotransposon activity and maintain genome stability across the generations. Here, we review recent advances in understanding how retrotransposon activity is suppressed in the mammalian germline, how genes involved in germline genome defence mechanisms are regulated, and the consequences of mutating these genome defence genes for the developing germline