Concurrent Mapping Research Articles

Multi-mode filter target tracking method for mobile robot using multi-agent reinforcement learning

Multi-mode filtering target tracking for mobile robot has important research significance for robot path planning, motion control and tracking robot targets. To address the problem that it is difficult for mobile robot to track targets in unknown environments, a multi-mode filtering target tracking method for mobile robot using multi-agent reinforcement learning is proposed. First, based on the extended kalman filter and combined with probability data association, the observation values in different motion modes are calculated and the system state is updated in real time, to achieve concurrent mapping, location and state estimation for each robot. Second, state communication among multi-mobile robot are established, and the multi-agent reinforcement learning model is built. Finally, based on the agent reinforcement learning model, based on the communication and communication among multi-tracking agents and the location of the target agent, the target tracking task is allocated to shorten the total path of the tracking agent, and the multi-target tracking of multi-mobile robot is completed by constantly learning and updating the strategy. The results show that the maximum tracking error of the target is 7 mm, and the calculation time of each step is only 51.1ms. The tracking success rate, observation rate and coverage rate are all high. It has important research value in robot location and navigation, service robot and other fields.

Locus of nonword repetition impairments in Mandarin-speaking children with developmental language disorder

Current theories of nonword repetition (NWR) impairments for children with Developmental Language Disorder (DLD) are developed predominantly using data from Indo-European languages. Seldom have relevant theories been attested to the morph-syllabic language Mandarin Chinese. The present research aimed to explore the locus of NWR impairments for Mandarin children with DLD. 80 Mandarin-speaking children with typical development (TD) and 80 children with DLD were compared on nonword repetition accuracy and error types. It was a three-factor design with language groups (children with DLD vs. TD children) as the between-subjects factor, and components (onset, rhyme, and tone) and syllable numbers (one to four syllables) as the within-subjects factors. The analysis showed that both groups had less accuracy on the two phonological segments (onset and rhyme) relative to tone and showed more errors in multi-syllable nonwords. Children with DLD exhibited more noticeable errors in onsets and rhymes, although they did not display similar issues with tones compared to TD children. Repeated measures ANOVAs showed that children with DLD had pronounced errors in onsets, especially in repeating multi-syllable nonwords. Error type analysis revealed that children with DLD displayed more multiple than single errors in nonword repetition. The results support the “segment-to-frame association” theory, suggesting that Mandarin children with DLD are constrained in the concurrent mapping process between onsets, rhymes, and tones.

Concurrent mapping of brain ontogeny and phylogeny within a common space: Standardized tractography and applications.

Developmental and evolutionary effects on brain organization are complex, yet linked, as evidenced by the correspondence in cortical area expansion across these vastly different time scales. However, it is still not possible to study concurrently the ontogeny and phylogeny of cortical areal connections, which is arguably more relevant to brain function than allometric measurements. Here, we propose a novel framework that allows the integration of structural connectivity maps from humans (adults and neonates) and nonhuman primates (macaques) onto a common space. We use white matter bundles to anchor the common space and use the uniqueness of cortical connection patterns to these bundles to probe area specialization. This enabled us to quantitatively study divergences and similarities in connectivity over evolutionary and developmental scales, to reveal brain maturation trajectories, including the effect of premature birth, and to translate cortical atlases between diverse brains. Our findings open new avenues for an integrative approach to imaging neuroanatomy.

Mapping α- and β-diversity of mangrove forests with multispectral and hyperspectral images

Mangrove deforestation has rapidly declined by an order of magnitude compared to that reported for the 20th century, but the remaining mangrove ecosystems are still undergoing biodiversity loss and degradation. Labor-intensive ground surveys that are usually used for terrestrial plant biodiversity assessment are difficult to conduct in the mangrove forests. Assessing plant biodiversity from space does offer a novel perspective, but existing solutions are mainly focused on estimating α- or β-diversities (i.e., diversity within communities or diversity among communities) alone. This paper applied a novel holistic biodiversity approach that could partition γ-diversity into α- and β-diversities for plant diversity mapping with operational satellites (WorldView-2, Sentinel-2, and Zhuhai-1) and field plots in the Qinglangang Provincial Nature Reserve, Hainan, China. We compared the resulting outputs of the α-diversity from the holistic method (SDα) to those by the coefficient of variation (CV) and the Rao's Q index, and the contributions of individual spectral features to α- and β-diversity were also measured. Results indicated that α- and β-diversities accounted for ~30% and ~ 70% of the total diversity in the Reserve, respectively. α-diversity derived from the WorldView-2 images showed statistically higher correlations with the observed Shannon's index (R2: 0.20–0.42) compared to that from Sentinel-2 and Zhuhai-1 (R2: 0.03–0.15). β-diversity derived from WorldView-2 images had the highest accuracy (90.00%), followed by that from Sentinel-2 and Zhuhai-1 (83.33% and 73.33%, respectively). Red-edge and near-infrared spectral features were the most informative features for diversity mapping while shortwave infrared (SWIR) features were also valuable for β-diversity mapping. Concurrent mapping of α- and β-diversities of mangrove forests represents the first step toward achieving rapid biodiversity monitoring schemes of mangrove forests over a national or global scale.

Concurrent mapping of multiple epigenetic marks and co-occupancy using ACT2-seq

BackgroundGenome-wide profiling of epigenetic marks is a core technology in molecular genetics. Co-occupancy of different epigenetic marks or protein factors at the same genomic locations must often be inferred from multiple independently collected data sets. However, this strategy does not provide direct evidence of co-enrichment in the same cells due to the existence of cellular heterogeneity. To address this issue, we have developed a technique termed ACT2-seq that is capable of concurrently profiling multiple epigenetic marks in a single biological sample. In addition to reducing the numbers of samples required for experiments, ACT2-seq is capable of mapping co-occupancy of epigenetic factors on chromatin. This strategy provides direct evidence of co-enrichment without requiring complex single-molecule, single-cell, or magnetic bead-based approaches.ResultsWe concurrently profiled pairs of two epigenetic marks using ACT2-seq as well as three marks in individual samples. Data obtained using ACT2-seq were found to be reproducible and robust. ACT2-seq was capable of cleanly partitioning concurrently mapped data sets that exhibited distinct enrichment patterns. Using ACT2-seq, we identified distinct relationships between co-occupancy of specific histone modifications and gene expression patterns.ConclusionsWe conclude that ACT2-seq presents an attractive option for epigenomic profiling due to its ease of use, potential for reducing sample and sequencing costs, and ability to simultaneously profile co-occupancy of multiple histone marks and/or chromatin-associated proteins.

Unknown hostile environment-oriented autonomous WSN deployment using a mobile robot

In this study, we consider the Internet of Things (IoT) with an autonomous deployment framework and seek optimal localizable k-coverage (OLKC) strategies to preserve the connectivity and robustness in IoT networks to assist robots during disaster recovery activities. Therefore, we define localizable k-coverage as the covered region within which a mobile robot can localize itself aided by k neighboring beacon nodes (BNs) in a wireless sensor network (WSN). To this end, we first propose the optimal localizable k-coverage WSN deployment problem (OLKWDP) and present a novel framework that preserves WSN connectivity and robustness for mobile robots. To localize a mobile robot with at least k BNs and overcome the network hole problem that can occur in unknown hostile environments, we propose a hole recovery method for the OLKC achieved by a mobile robot that knows the concurrent mapping, deployment and localization of the WSN. We then present a mapping-to-image transformation method to reveal the interactions between the WSN deployment and the network holes for the OLKC while constructing the online mapping. To solve the OLKWDP, we also develop two optimality conditions to achieve maximum coverage by the proposed OLKC in the unknown hostile environment using the minimum number of sensors. Moreover, we analyze the factors that influence the probability of success of the OLKC and the factors that influence the performance of a mobile robot when determining the WSN deployment. The simulation results illustrate that our framework outperforms the trilateration and spanning tree (TST) method in unknown hostile environment exploration and can achieve the OLKC in a WSN. In 27 simulated situations, our framework achieved average rates of nearly 100% 1-coverage, 91.34% 2-coverage and 89.00% 3-coverage.

3D Convolutional Neural Networks for Remote Pulse Rate Measurement and Mapping from Facial Video

Remote pulse rate measurement from facial video has gained particular attention over the last few years. Research exhibits significant advancements and demonstrates that common video cameras correspond to reliable devices that can be employed to measure a large set of biomedical parameters without any contact with the subject. A new framework for measuring and mapping pulse rate from video is presented in this pilot study. The method, which relies on convolutional 3D networks, is fully automatic and does not require any special image preprocessing. In addition, the network ensures concurrent mapping by producing a prediction for each local group of pixels. A particular training procedure that employs only synthetic data is proposed. Preliminary results demonstrate that this convolutional 3D network can effectively extract pulse rate from video without the need for any processing of frames. The trained model was compared with other state-of-the-art methods on public data. Results exhibit significant agreement between estimated and ground-truth measurements: the root mean square error computed from pulse rate values assessed with the convolutional 3D network is equal to 8.64 bpm, which is superior to 10 bpm for the other state-of-the-art methods. The robustness of the method to natural motion and increases in performance correspond to the two main avenues that will be considered in future works.

Development of multifunctional Overhauser-enhanced magnetic resonance imaging for concurrent in vivo mapping of tumor interstitial oxygenation, acidosis and inorganic phosphate concentration

Tumor oxygenation (pO2), acidosis (pH) and interstitial inorganic phosphate concentration (Pi) are important parameters of the malignant behavior of cancer. A noninvasive procedure that enables visualization of these parameters may provide unique information about mechanisms of tumor pathophysiology and provide clues to new treatment targets. In this research, we present a multiparametric imaging method allowing for concurrent mapping of pH, spin probe concentration, pO2, and Pi using a single contrast agent and Overhauser-enhanced magnetic resonance imaging technique. The developed approach was applied to concurrent multifunctional imaging in phantom samples and in vivo in a mouse model of breast cancer. Tumor tissues showed higher heterogeneity of the distributions of the parameters compared with normal mammary gland and demonstrated the areas of significant acidosis, hypoxia, and elevated Pi content.

Concurrent mapping of brain activation from multiple subjects during social interaction by hyperscanning: a mini-review.

Social interaction plays an essential role in acquiring knowledge and developing our own personalities in our daily life. Meanwhile, functional magnetic resonance imaging (fMRI)-, electroencephalograph (EEG)-, and functional near inferred spectroscopy (fNIRS)-hyperscanning, enables us to concurrently map brain activation from two or more participants who are engaged in social interaction simultaneously. In this review, we first highlight the recent technologies advances and the most significant findings towards social interaction by using the hyperscanning method. In addition, we also illustrate several well-designed hyperscanning tasks that have been extensively adopted for the study of social interaction. Basically, hyperscanning contains six categories of experimental paradigms that can track the interactive neural process of interest. Furthermore, it contains two main elucidated neural systems which are involved in social interaction, including the mirror neuron system (MNS) and mentalizing system (MS). Finally, future research directions and clinical implications that are associated with hyperscanning are also highlighted and discussed.

Incremental Layer Assignment for Timing Optimization

With VLSI technology nodes scaling into the nanometer regime, interconnect delay plays an increasingly critical role in timing. For layer assignment, most works deal with via counts or total net delays, ignoring critical paths of each net and resulting in potential timing issues. In this article, we propose an incremental layer assignment framework targeting delay optimization in timing the critical path of each net. A set of novel techniques are presented: self-adaptive quadruple partition based on K × K division benefits the runtime; semidefinite programming is utilized for each partition; and the sequential mapping algorithm guarantees integer solutions while satisfying edge capacities; additionally, concurrent mapping offers a global view of assignment and post delay optimization reduces the path timing violations. The effectiveness of our work is verified by ISPD’08 benchmarks.

Fabrication of Scanning Electrochemical Microscopy-Atomic Force Microscopy Probes to Image Surface Topography and Reactivity at the Nanoscale.

Concurrent mapping of chemical reactivity and morphology of heterogeneous electrocatalysts at the nanoscale allows identification of active areas (protrusions, flat film surface, or cracks) responsible for productive chemistry in these materials. Scanning electrochemical microscopy (SECM) can map surface characteristics, record catalyst activity, and identify chemical products at solid-liquid electrochemical interfaces. It lacks, however, the ability to distinguish topographic features where surface reactivity occurs. Here, we report the design and fabrication of scanning probe tips that combine SECM with atomic force microscopy (AFM) to perform measurements at the nanoscale. Our probes are fabricated by integrating nanoelectrodes with quartz tuning forks (QTFs). Using a calibration standard fabricated in our lab to test our probes, we obtain simultaneous topographic and electrochemical reactivity maps with a lateral resolution of 150 nm.

High resolution in situ mapping of microstrain and microstructure evolution reveals damage resistance criteria in dual phase steels

Microstructures of multi-phase alloys undergo morphological and crystallographic changes upon deformation, corresponding to the associated microstructural strain fields. The multiple length and time scales involved therein create immense complexity, especially when microstructural damage mechanisms are also activated. An understanding of the relationship between microstructure and damage initiation can often not be achieved by post-mortem microstructural characterization alone. Here, we present a novel multi-probe analysis approach. It couples various scanning electron microscopy methods to microscopic-digital image correlation (μ-DIC), to overcome various challenges associated with concurrent mapping of the deforming microstructure along with the associated microstrain fields. For this purpose a contrast- and resolution-optimized μ-DIC patterning method and a selective pattern/microstructure imaging strategy were developed. They jointly enable imaging of (i) microstructure-independent pattern maps and (ii) pattern-independent microstructure maps. We apply this approach here to the study of damage nucleation in ferrite/martensite dual-phase (DP) steel. The analyses provide four specific design guidelines for developing damage-resistant DP steels.

Abstract 2051: Three-dimensional in vivo photoacoustic tracking of targeted nanoparticles in a pancreatic cancer model

Abstract The use of targeted gold nanoparticles (AuNPs) has shown tremendous promise in the early detection and improved therapy of cancer. Successful development and implementation of these new theranostic approaches, however, depends on sufficient transvascular migration and specific accumulation of AuNPs to extravascular tumor tissue. This study utilized photoacoustic (PA) imaging to track - in three dimensions and through 24 hours - the extravasation and accumulation of targeted AuNPs in a subcutaneous murine model of prostate cancer. AuNPs (nanorods; 760-nm peak) targeting the Luteinizing-hormone-releasing hormone receptor were systemically injected into three mice bearing PC-3 human prostate cancer tumors; as a control, three additional mice were injected with PEGylated AuNPs. For all particle-tracking studies, multi-wavelength (680, 760, 800, 920, & 940 nm), volumetric (spherical volume with 25.6-mm diameter) PA imaging was conducted at pre-injection, post-injection, 15-min, 60-min, 240-min, and 24-hr time points; the imaging volume contained the tumor and the spleen (control). Following imaging, tumors were excised and inductively coupled plasma mass spectrometry (ICP-MS) of samples and two-photon imaging of histological sections was performed to confirm AuNP accumulation and diffusion, respectively. Volumetric PA perfusion assessment was then conducted by monitoring the wash-out of indocyanine green (ICG) in near real-time (0.25 Hz for 180 s post-injection). All PA imaging studies were performed on the Nexus 128 preclinical imaging system (Endra Inc., Ann Arbor, MI). Spectral unmixing of the multi-wavelength PA data was achieved to segment AuNPs and deoxy-/oxyhemoglobin (i.e. for local hypoxia assessment). Accumulation and extravasation data of the targeted AuNPs in the tumor were then compared to tumor perfusion data, PA-derived tumor hypoxia data, PEGylated AuNP accumulation data in the tumor, AuNP accumulation data in the spleen, and ICP-MS/histological analysis. Results of the study establish that volumetric PA imaging with multi-wavelength unmixing is able to track nanoparticle accumulation and extravasation throughout an in vivo tumor model. The location and relative degree of particle accumulation was also found to correlate with PA-based perfusion and vascularity assessment. This study demonstrates that volumetric PA imaging has the spatiotemporal resolution and sensitivity to track extravasation of AuNPs in an in vivo tumor model. This in vivo tracking ability - along with concurrent PA-based perfusion and hypoxia mapping - could be of significant benefit in understanding and improving nanoparticle targeting for the diagnosis and treatment of cancer. Citation Format: Richard Bouchard, Tatiana Wolfe, Michael Thornton, Timothy Morgan, Trevor Mitcham, Shanta Bhattarai, Jonathan Grant, Jihyoun Lee, John Hazle, Sunil Krishnan. Three-dimensional in vivo photoacoustic tracking of targeted nanoparticles in a pancreatic cancer model. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2051. doi:10.1158/1538-7445.AM2014-2051

Distance Effects in Mental Space and Time Travels

Distance Effects in Mental Space and Time Travels

Simultaneous Localization and Mapping Trends and Humanoid Robot Linkages

Simultaneous localization and mapping (SLAM), also known as concurrent mapping and localization (CML), is an important topic or robotics files. This method produces a real-time map of an environment and finds the current position of a robot on that map. This method is generally used to solve the problem of “Where am I?” for localization, “Where do I go?” for goal determination, and “How do I go there?” for robot motion planning. Recently, the number of studies in this area has increased rapidly and expanded to different areas. In this paper analyzes SLAM or CML, which is currently a hot topic in the field of robotic research. In addition, this paper describes methods for solving SLAM problems, presents evaluation methods for SLAM, analyzes recent research on SLAM worldwide, and studies the academic importance of SLAM. This paper also reviews the use of SLAM for humanoid robots and aims to address the issue of the significance of SLAM engine in the future of stereo vision on humanoid robots.

Non-destructive studies of fuel pellets by neutron resonance absorption radiography and thermal neutron radiography

Many isotopes in nuclear materials exhibit strong peaks in neutron absorption cross sections in the epithermal energy range (1–1000eV). These peaks (often referred to as resonances) occur at energies specific to particular isotopes, providing a means of isotope identification and concentration measurements. The high penetration of epithermal neutrons through most materials is very useful for studies where samples consist of heavy-Z elements opaque to X-rays and sometimes to thermal neutrons as well. The characterization of nuclear fuel elements in their cladding can benefit from the development of high resolution neutron resonance absorption imaging (NRAI), enabled by recently developed spatially-resolved neutron time-of-flight detectors. In this technique the neutron transmission of the sample is measured as a function of spatial location and of neutron energy. In the region of the spectra that borders the resonance energy for a particular isotope, the reduction in transmission can be used to acquire an image revealing the 2-dimensional distribution of that isotope within the sample. Provided that the energy of each transmitted neutron is measured by the neutron detector used and the irradiated sample possesses neutron absorption resonances, then isotope-specific location maps can be acquired simultaneously for several isotopes. This can be done even in the case where samples are opaque or have very similar transmission for thermal neutrons and X-rays or where only low concentrations of particular isotopes are present (<0.1atom% in some cases). Ultimately, such radiographs of isotope location can be utilized to measure isotope concentration, and can even be combined to produce three-dimensional distributions using tomographic methods.In this paper we present the proof-of-principle of NRAI and transmission Bragg edge imaging performed at Flight Path 5 (FP5) at the LANSCE pulsed, moderated neutron source of Los Alamos National Laboratory. A set of urania mockup fuel assemblies with intentionally introduced defects was investigated. The maps of elemental composition of pellets containing urania and tungsten were obtained simultaneously by resonance absorption imaging with spatial resolution better than ∼200μm, while the voids and cracks were revealed by the transmission images obtained with thermal and cold neutrons. Our proof-of-principle experiments demonstrate that simultaneous acquisition of resonance and Bragg edge spectra enables concurrent mapping of isotope distributions, imaging of cracks and voids as well as measurements of some crystallographic parameters of fuel assemblies and their cladding. A detailed study of energy-dependent neutron statistics achievable at FP5 with our present detection system is also presented for a wide range of neutron energies.

257 Challenges in CFRD: The advantages of continuous glucose monitoring (CGM)

Introduction: With survival increasing in CF, CF-related diabetes (CFRD) and its assocated complications are more common. Achieving optimal glycaemic control can be particularly difficult despite traditional management methods. CGM provides greater insight into glycaemic trends through the day, and helps determine the benefits of treatment changes. We routinely use CGM for optimisation of diabetic control at our large CF centre (n = 282; 40% CFRD), and have explored its utility in the management of this CF complication. Method: We evaluated CGM traces in 29 CFRD patients over a 20 month period, along with any subsequent changes in weight, pulmonary function, HBA1C and antibiotic treatment. Food and exercise diaries completed during CGM were also evaluated. Results: See Table [Mean (SD)]: 69% gained weight, 72% improved their lung function (p< 0.0001) and 62% improved HBA1C (p< 0.0001). Overall, 45% required less IV antibiotic therapy (p< 0.0001) and 34% required fewer oral antibiotic courses. 90% of subjects had dietary adjustments following review of food and exercise diaries. 34% had a change in the type of insulin prescribed following CGM. Conclusion: This study demonstrates the utility of CGM to improve clinical status and optimize treatment including the dosage and type of insulin therapy. CGM used in conjunction with good education, support and the concurrent mapping of food and exercise diaries is of educational benefit allowing the fine-tuning of any adjustments of treatment.

Assessment of energy loss in aortic stenosis using Bayesian multipoint phase-contrast MRI

(TKE) and energy loss indices (ELI) are listed in Table 1. Compared to our previous data obtained in healthy subjects [3], peak TKE in the patients presented here was found to be significantly increased (149±12 J/m 3 vs. 1350 and 1630 J/m 3 , respectively). It is noteworthy that the patient with higher TKE values had a lower energy loss index. Values from Doppler echocardiography are given for comparison. Figure 1 shows maps of TKE in the aortic arch in both patients along with flow patterns derived from the velocity data. Conclusions Bayesian multipoint PC-MRI permits concurrent mapping of both mean kinetic and turbulent kinetic energy in patients and allows the assessment of relative energy loss and pressure gradients associated with aortic valve stenosis. The energy loss index was found to be approximately 8-fold higher as compared to healthy subjects [2] and may hold promise to serve as a novel marker for grading valve disease.

Inferring coastal processes from regional-scale mapping of 222Radon and salinity: examples from the Great Barrier Reef, Australia

The radon isotope 222Rn and salinity in coastal surface water were mapped on regional scales, to improve the understanding of coastal processes and their spatial variability. Radon was measured with a surface-towed, continuously recording multi-detector setup on a moving vessel. Numerous processes and locations of land–ocean interaction along the Central Great Barrier Reef coastline were identified and interpreted based on the data collected. These included riverine fluxes, terrestrially-derived fresh submarine groundwater discharge (SGD) and the tidal pumping of seawater through mangrove forests. Based on variations in the relationship of the tracers radon and salinity, some aspects of regional freshwater inputs to the coastal zone and to estuaries could be assessed. Concurrent mapping of radon and salinity allowed an efficient qualitative assessment of land–ocean interaction on various spatial and temporal scales, indicating that such surveys on coastal scales can be a useful tool to obtain an overview of SGD locations and processes.

Characterization of Slider Dynamics and Media Defects by Concurrent Methods Using Multifunctional Spinstand

As areal density increases towards Tb/in2, disk media defect detection becomes more critical. We have developed a media tester for concurrent multifunctional testing and mapping. A special test sample with defect features of various depths and sizes was fabricated by focused ion beam, and studied on the tester by concurrent magnetic read-back envelope measurement (ME) and laser Doppler vibrometry (LDV) mapping. The ME approach was found superior in detection sensitivity and resolution than LDV and shown to be useful for indirect detection of media surface physical variations. Besides defect characterization, ME mapping provided two-dimensional information on slider-surface interaction. However, correlation with other concurrent tests such as LDV and acoustic emission (AE) must be done, to eliminate spurious results. A concurrent mapping of AE, LDV, ME, and in situ flying height on media defects was also performed, and the excitation of different slider modes by different surface defects was observed in situ. Such concurrent testing is important towards providing an ldquoaccurate picturerdquo of the tested media surface and slider flying condition.