Recent developments in random finite sets (RFSs) have yielded a variety of tracking methods that avoid data association. This paper derives a form of the full Bayes RFS filter and observes that data ...association is implicitly present, in a data structure similar to multiple hypothesis tracking (MHT). Subsequently, algorithms are obtained by approximating the distribution of associations. Two algorithms result: one nearly identical to joint integrated probabilistic data association (JIPDA), and another related to the multiple target multi-Bernoulli (MeMBer) filter. Both improve performance in challenging environments.
Multiobject tracking provides situational awareness that enables new applications for modern convenience, public safety, and homeland security. This paper presents a factor graph formulation and a ...particle-based sum-product algorithm (SPA) for scalable detection and tracking of extended objects. The proposed method dynamically introduces states of newly detected objects, efficiently performs probabilistic multiple-measurement to object association, and jointly infers the geometric shapes of objects. Scalable extended object tracking (EOT) is enabled by modeling association uncertainty by measurement-oriented association variables and newly detected objects by a Poisson birth process. Contrary to conventional EOT methods, a fully particle-based approach makes it possible to describe different geometric object shapes. The proposed method can reliably detect, localize, and track a large number of closely-spaced extended objects without gating and clustering of measurements. We demonstrate significant performance advantages of our approach compared to the recently introduced Poisson multi-Bernoulli mixture filter. In particular, we consider a simulated scenarios with up to twenty closely-spaced objects and a real autonomous driving application where measurements are captured by a lidar sensor.
The joint probabilistic data association (JPDA) filter is a popular tracking methodology for problems involving well-spaced targets, but it is rarely applied in problems with closely spaced targets ...due to its complexity in these cases, and due to the well-known phenomenon of coalescence. This paper addresses these difficulties using random finite sets (RFSs) and variational inference, deriving a highly tractable, approximate method for obtaining the multi-Bernoulli distribution that minimizes the set Kullback-Leibler (KL) divergence from the true posterior, working within the RFS framework to incorporate uncertainty in target existence. The derivation is interpreted as an application of expectation-maximization (EM), where the missing data is the correspondence of Bernoulli components (i.e., tracks) under each data association hypothesis. The missing data is shown to play an identical role to the selection of an ordered distribution in the same ordered family in the set JPDA algorithm. Subsequently, a special case of the proposed method is utilized to provide an efficient approximation of the minimum mean optimal subpattern assignment estimator. The performance of the proposed methods is demonstrated in challenging scenarios in which up to twenty targets come into close proximity.
Statistical dialog systems (SDSs) are motivated by the need for a data-driven framework that reduces the cost of laboriously handcrafting complex dialog managers and that provides robustness against ...the errors created by speech recognizers operating in noisy environments. By including an explicit Bayesian model of uncertainty and by optimizing the policy via a reward-driven process, partially observable Markov decision processes (POMDPs) provide such a framework. However, exact model representation and optimization is computationally intractable. Hence, the practical application of POMDP-based systems requires efficient algorithms and carefully constructed approximations. This review article provides an overview of the current state of the art in the development of POMDP-based spoken dialog systems.
Although both natural and induced regulatory T (nTreg and iTreg) cells can enforce tolerance, the mechanisms underlying their synergistic actions have not been established. We examined the functions ...of nTreg and iTreg cells by adoptive transfer immunotherapy of newborn Foxp3-deficient mice. As monotherapy, only nTreg cells prevented disease lethality, but did not suppress chronic inflammation and autoimmunity. Provision of Foxp3-sufficient conventional T cells with nTreg cells reconstituted the iTreg pool and established tolerance. In turn, acute depletion of iTreg cells in rescued mice resulted in weight loss and inflammation. Whereas the transcriptional signatures of nTreg and in vivo-derived iTreg cells were closely matched, there was minimal overlap in their T cell receptor (TCR) repertoires. Thus, iTreg cells are an essential nonredundant regulatory subset that supplements nTreg cells, in part by expanding TCR diversity within regulatory responses.
► iTreg cells are essential to the maintenance of peripheral tolerance ► nTreg and iTreg cells serve distinct nonredundant functions in vivo ► Distinct TCR specificities explain iTreg and nTreg cell nonredundancy
Parasitic isopods of Bopyroidea and Cryptoniscoidea (commonly referred to as epicarideans) are unique in using crustaceans as both intermediate and definitive hosts. In total, 795 epicarideans are ...known, representing ~7.7% of described isopods. The rate of description of parasitic species has not matched that of free-living isopods and this disparity will likely continue due to the more cryptic nature of these parasites. Distribution patterns of epicarideans are influenced by a combination of their definitive (both benthic and pelagic species) and intermediate (pelagic copepod) host distributions, although host specificity is poorly known for most species. Among epicarideans, nearly all species in Bopyroidea are ectoparasitic on decapod hosts. Bopyrids are the most diverse taxon (605 species), with their highest diversity in the North West Pacific (139 species), East Asian Sea (120 species), and Central Indian Ocean (44 species). The diversity patterns of Cryptoniscoidea (99 species, endoparasites of a diverse assemblage of crustacean hosts) are distinct from bopyrids, with the greatest diversity of cryptoniscoids in the North East Atlantic (18 species) followed by the Antarctic, Mediterranean, and Arctic regions (13, 12, and 8 species, respectively). Dajidae (54 species, ectoparasites of shrimp, mysids, and euphausids) exhibits highest diversity in the Antarctic (7 species) with 14 species in the Arctic and North East Atlantic regions combined. Entoniscidae (37 species, endoparasites within anomuran, brachyuran and shrimp hosts) show highest diversity in the North West Pacific (10 species) and North East Atlantic (8 species). Most epicarideans are known from relatively shallow waters, although some bopyrids are known from depths below 4000 m. Lack of parasitic groups in certain geographic areas is likely a sampling artifact and we predict that the Central Indian Ocean and East Asian Sea (in particular, the Indo-Malay-Philippines Archipelago) hold a wealth of undescribed species, reflecting our knowledge of host diversity patterns.
Situation-aware technologies enabled by multitarget tracking will lead to new services and applications in fields such as autonomous driving, indoor localization, robotic networks, and crowd ...counting. In this tutorial paper, we advocate a recently proposed paradigm for scalable multitarget tracking that is based on message passing or, more concretely, the loopy sum-product algorithm. This approach has advantages regarding estimation accuracy, computational complexity, and implementation flexibility. Most importantly, it provides a highly effective, efficient, and scalable solution to the probabilistic data association problem, a major challenge in multitarget tracking. This fact makes it attractive for emerging applications requiring real-time operation on resource-limited devices. In addition, the message passing approach is intuitively appealing and suited to nonlinear and non-Gaussian models. We present message-passing-based multitarget tracking methods for single-sensor and multiple-sensor scenarios, and for a known and unknown number of targets. The presented methods can cope with clutter, missed detections, and an unknown association between targets and measurements. We also discuss the integration of message-passing-based probabilistic data association into existing multitarget tracking methods. The superior performance, low complexity, and attractive scaling properties of the presented methods are verified numerically. In addition to simulated data, we use measured data captured by two radar stations with overlapping fields-of-view observing a large number of targets simultaneously.
Nicotinamide adenine dinucleotide (NAD), a cofactor for hundreds of metabolic reactions in all cell types, plays an essential role in metabolism, DNA repair, and aging. However, how NAD metabolism is ...impacted by the environment remains unclear. Here, we report an unexpected trans-kingdom cooperation between bacteria and mammalian cells wherein bacteria contribute to host NAD biosynthesis. Bacteria confer resistance to inhibitors of NAMPT, the rate-limiting enzyme in the amidated NAD salvage pathway, in cancer cells and xenograft tumors. Mechanistically, a microbial nicotinamidase (PncA) that converts nicotinamide to nicotinic acid, a precursor in the alternative deamidated NAD salvage pathway, is necessary and sufficient for this protective effect. Using stable isotope tracing and microbiota-depleted mice, we demonstrate that this bacteria-mediated deamidation contributes substantially to the NAD-boosting effect of oral nicotinamide and nicotinamide riboside supplementation in several tissues. Collectively, our findings reveal an important role of bacteria-enabled deamidated pathway in host NAD metabolism.
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•Bacteria confer host cells with resistance to NAMPT inhibitors (NAMPTis)•Bacteria produce deamidated NAD precursors and prevent NAD depletion•Bacteria rescue NAMPTi-induced toxicity through nicotinamidase PncA•Oral NAM and NR boost in vivo NAD largely via microbiota-dependent deamidated pathway
Shats et al. describe an unexpected trans-kingdom interaction between bacteria and mammals, wherein bacteria contribute to mammalian host NAD biosynthesis through a microbial nicotinamidase (PncA). This bacteria/gut microbiota-mediated facilitation of the deamidated NAD biosynthesis is important for the efficacy of commercial oral NAD-boosting supplements in mice.
We provide a derivation of the Poisson multi-Bernoulli mixture (PMBM) filter for multitarget tracking with the standard point target measurements without using probability generating functionals or ...functional derivatives. We also establish the connection with the <inline-formula><tex-math notation="LaTeX">\delta</tex-math></inline-formula> -generalized labeled multi-Bernoulli (<inline-formula><tex-math notation="LaTeX">\delta</tex-math></inline-formula> -GLMB) filter, showing that a <inline-formula><tex-math notation="LaTeX">\delta</tex-math></inline-formula>-GLMB density represents a multi-Bernoulli mixture with labeled targets so it can be seen as a special case of PMBM. In addition, we propose an implementation for linear/Gaussian dynamic and measurement models and how to efficiently obtain typical estimators in the literature from the PMBM. The PMBM filter is shown to outperform other filters in the literature in a challenging scenario.
In a 2016 survey of 704 National Science Foundation (NSF) Biological Sciences Directorate principal investigators (BIO PIs), nearly 90% indicated they are currently or will soon be analyzing large ...data sets. BIO PIs considered a range of computational needs important to their work, including high performance computing (HPC), bioinformatics support, multistep workflows, updated analysis software, and the ability to store, share, and publish data. Previous studies in the United States and Canada emphasized infrastructure needs. However, BIO PIs said the most pressing unmet needs are training in data integration, data management, and scaling analyses for HPC-acknowledging that data science skills will be required to build a deeper understanding of life. This portends a growing data knowledge gap in biology and challenges institutions and funding agencies to redouble their support for computational training in biology.
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