Sensor Control for Multi-Object Tracking Using Labeled Multi-Bernoulli Filter

The recently developed labeled multi-Bernoulli (LMB) filter uses better approximations in its update step, compared to the unlabeled multi-Bernoulli filters, and more importantly, it provides us with not only the estimates for the number of targets and their states, but also with labels for existing tracks. This paper presents a novel sensor-control method to be used for optimal multi-target tracking within the LMB filter. The proposed method uses a task-driven cost function in which both the state estimation errors and cardinality estimation errors are taken into consideration. Simulation results demonstrate that the proposed method can successfully guide a mobile sensor in a challenging multi-target tracking scenario

Information theoretic approach to robust multi-Bernoulli sensor control

A novel sensor control solution is presented, formulated within a Multi-Bernoulli-based multi-target tracking framework. The proposed method is especially designed for the general multi-target tracking case, where no prior knowledge of the clutter distribution or the probability of detection profile are available. In an information theoretic approach, our method makes use of R\`{e}nyi divergence as the reward function to be maximized for finding the optimal sensor control command at each step. We devise a Monte Carlo sampling method for computation of the reward. Simulation results demonstrate successful performance of the proposed method in a challenging scenario involving five targets maneuvering in a relatively uncertain space with unknown distance-dependent clutter rate and probability of detection

Multi-Bernoulli Sensor-Control via Minimization of Expected Estimation Errors

This paper presents a sensor-control method for choosing the best next state of the sensor(s), that provide(s) accurate estimation results in a multi-target tracking application. The proposed solution is formulated for a multi-Bernoulli filter and works via minimization of a new estimation error-based cost function. Simulation results demonstrate that the proposed method can outperform the state-of-the-art methods in terms of computation time and robustness to clutter while delivering similar accuracy

On the occurrence of oscillatory modulations in the power-law behavior of dynamic and kinetic processes in fractals

The dynamic and kinetic behavior of processes occurring in fractals with spatial discrete scale invariance (DSI) is considered. Spatial DSI implies the existence of a fundamental scaling ratio (b_1). We address time-dependent physical processes, which as a consequence of the time evolution develop a characteristic length of the form $\xi \propto t^{1/z}$, where z is the dynamic exponent. So, we conjecture that the interplay between the physical process and the symmetry properties of the fractal leads to the occurrence of time DSI evidenced by soft log-periodic modulations of physical observables, with a fundamental time scaling ratio given by $\tau = b_1 ^z$. The conjecture is tested numerically for random walks, and representative systems of broad universality classes in the fields of irreversible and equilibrium critical phenomena.Comment: 6 pages, 3 figures. Submitted to EP

Analytical Solution of the Voter Model on Disordered Networks

We present a mathematical description of the voter model dynamics on heterogeneous networks. When the average degree of the graph is $\mu \leq 2$ the system reaches complete order exponentially fast. For $\mu >2$, a finite system falls, before it fully orders, in a quasistationary state in which the average density of active links (links between opposite-state nodes) in surviving runs is constant and equal to $\frac{(\mu-2)}{3(\mu-1)}$, while an infinite large system stays ad infinitum in a partially ordered stationary active state. The mean life time of the quasistationary state is proportional to the mean time to reach the fully ordered state $T$, which scales as $T \sim \frac{(\mu-1) \mu^2 N}{(\mu-2) \mu_2}$, where $N$ is the number of nodes of the network, and $\mu_2$ is the second moment of the degree distribution. We find good agreement between these analytical results and numerical simulations on random networks with various degree distributions.Comment: 20 pages, 8 figure

Erythropoietin Couples Hematopoiesis with Bone Formation

It is well established that bleeding activates the hematopoietic system to regenerate the loss of mature blood elements. We have shown that hematopoietic stem cells (HSCs) isolated from animals challenged with an acute bleed regulate osteoblast differentiation from marrow stromal cells. This suggests that HSCs participate in bone formation where the molecular basis for this activity is the production of BMP2 and BMP6 by HSCs. Yet, what stimulates HSCs to produce BMPs is unclear.In this study, we demonstrate that erythropoietin (Epo) activates Jak-Stat signaling pathways in HSCs which leads to the production of BMPs. Critically, Epo also directly activates mesenchymal cells to form osteoblasts in vitro, which in vivo leads to bone formation. Importantly, Epo first activates osteoclastogenesis which is later followed by osteoblastogenesis that is induced by either Epo directly or the expression of BMPs by HSCs to form bone.These data for the first time demonstrate that Epo regulates the formation of bone by both direct and indirect pathways, and further demonstrates the exquisite coupling between hematopoiesis and osteopoiesis in the marrow

Tracking and coordinating an international curation effort for the CCDS Project

The Consensus Coding Sequence (CCDS) collaboration involves curators at multiple centers with a goal of producing a conservative set of high quality, protein-coding region annotations for the human and mouse reference genome assemblies. The CCDS data set reflects a ‘gold standard’ definition of best supported protein annotations, and corresponding genes, which pass a standard series of quality assurance checks and are supported by manual curation. This data set supports use of genome annotation information by human and mouse researchers for effective experimental design, analysis and interpretation. The CCDS project consists of analysis of automated whole-genome annotation builds to identify identical CDS annotations, quality assurance testing and manual curation support. Identical CDS annotations are tracked with a CCDS identifier (ID) and any future change to the annotated CDS structure must be agreed upon by the collaborating members. CCDS curation guidelines were developed to address some aspects of curation in order to improve initial annotation consistency and to reduce time spent in discussing proposed annotation updates. Here, we present the current status of the CCDS database and details on our procedures to track and coordinate our efforts. We also present the relevant background and reasoning behind the curation standards that we have developed for CCDS database treatment of transcripts that are nonsense-mediated decay (NMD) candidates, for transcripts containing upstream open reading frames, for identifying the most likely translation start codons and for the annotation of readthrough transcripts. Examples are provided to illustrate the application of these guidelines

Serotonergic chemosensory neurons modify the <i>C. elegans</i> immune response by regulating G-protein signaling in epithelial cells

The nervous and immune systems influence each other, allowing animals to rapidly protect themselves from changes in their internal and external environment. However, the complex nature of these systems in mammals makes it difficult to determine how neuronal signaling influences the immune response. Here we show that serotonin, synthesized in Caenorhabditis elegans chemosensory neurons, modulates the immune response. Serotonin released from these cells acts, directly or indirectly, to regulate G-protein signaling in epithelial cells. Signaling in these cells is required for the immune response to infection by the natural pathogen Microbacterium nematophilum. Here we show that serotonin signaling suppresses the innate immune response and limits the rate of pathogen clearance. We show that C. elegans uses classical neurotransmitters to alter the immune response. Serotonin released from sensory neurons may function to modify the immune system in response to changes in the animal's external environment such as the availability, or quality, of food