Efficient and Safe Robotic Autonomous Environment Exploration Using Integrated Frontier Detection and Multiple Path Evaluation

Autonomous exploration and remote sensing using robots have gained increasing attention in recent years and aims to maximize information collection regarding the external world without human intervention. However, incomplete frontier detection, an inability to eliminate inefficient frontiers, and incomplete evaluation limit further improvements in autonomous exploration efficiency. This article provides a systematic solution for ground mobile robot exploration with high efficiency. Firstly, an integrated frontier detection and maintenance method is proposed, which incrementally discovers potential frontiers and achieves incremental maintenance of the safe and informative frontiers by updating the distance map locally. Secondly, we propose a novel multiple paths planning method to generate multiple paths from the robot position to the unexplored frontiers. Then, we use the proposed utility function to select the optimal path and improve its smoothness using an iterative optimization strategy. Ultimately, the model predictive control (MPC) method is applied to track the smooth path. Simulation experiments on typical environments demonstrate that compared with the benchmark methods, the proposed method reduce the path length by 27.07% and the exploration time by 27.09% on average. The real-world experimental results also reveal that our proposed method can achieve complete mapping with fewer repetitive paths.

DAMAGE DETECTION IN LAMINATED COMPOSITES BY NEURAL NETWORKS AND HIGH ORDER FINITE ELEMENTS

In the aerospace industry, machine learning techniques are becoming more and more important for Structural Health Monitoring (SHM). In fact, they could be useful in giving a precise and complete mapping of damage distribution in a structure, including low-intensities or local defects, which cannot be detected via traditional tests. In this work, feedforward artificial neural networks (ANN) are employed for vibration-based damage detection in composite laminates. In the framework of Carrera Unified formulation (CUF), one-dimensional refined models in conjunction with layer-wise (LW) theory are adopted. CUF-based Monte Carlo simulations have been used for the creation of a dataset of damage scenarios for the training of the ANN. Therefore, the latter is fed with the vibrational characteristics of these structures. The trained ANN, given these dynamic parameters, is able to predict location and intensity of all damages in the laminated composite structures.

Logical Observation Identifiers Names and Codes (LOINC®) Applied to Microbiology: A National Laboratory Mapping Experience in Taiwan

Background and Objective: Logical Observation Identifiers Names and Codes (LOINC) is a universal standard for identifying laboratory tests and clinical observations. It facilitates a smooth information exchange between hospitals, locally and internationally. Although it offers immense benefits for patient care, LOINC coding is complex, resource-intensive, and requires substantial domain expertise. Our objective was to provide training and evaluate the performance of LOINC mapping of 20 pathogens from 53 hospitals participating in the National Notifiable Disease Surveillance System (NNDSS). Methods: Complete mapping codes for 20 pathogens (nine bacteria and 11 viruses) were requested from all participating hospitals to review between January 2014 and December 2016. Participating hospitals mapped those pathogens to LOINC terminology, utilizing the Regenstrief LOINC mapping assistant (RELMA) and reported to the NNDSS, beginning in January 2014. The mapping problems were identified by expert panels that classified frequently asked questionnaires (FAQs) into seven LOINC categories. Finally, proper and meaningful suggestions were provided based on the error pattern in the FAQs. A general meeting was organized if the error pattern proved to be difficult to resolve. If the experts did not conclude the local issue’s error pattern, a request was sent to the LOINC committee for resolution. Results: A total of 53 hospitals participated in our study. Of these, 26 (49.05%) used homegrown and 27 (50.95%) used outsourced LOINC mapping. Hospitals who participated in 2015 had a greater improvement in LOINC mapping than those of 2016 (26.5% vs. 3.9%). Most FAQs were related to notification principles (47%), LOINC system (42%), and LOINC property (26%) in 2014, 2015, and 2016, respectively. Conclusions: The findings of our study show that multiple stage approaches improved LOINC mapping by up to 26.5%.

P–331 The #Enzian classification: A comprehensive non-invasive and surgical description system for endometriosis

Study question Is there a classification for a complete mapping of endometriosis, including anatomical location, size of the lesions, and degree of involvement that can be used with both, diagnostics and surgery? Summary answer #Enzian classification improves in both, non-invasive diagnostic methods and surgical therapy for endometriosis as a universally usable classification system for all aspects of the disease. What is known already The most commonly used r-ASRM classification has certain limitations due to its incomplete description of DE, the complexity of the classification, and lack of reproducibility. In contrast, the Enzian classification, which has been implemented in the last decade, has proved to be the most suitable for the description of DE. However, since it does not include peritoneal and ovarian lesions and lacks a description of tubo-ovarian adhesions, it has not gained full acceptance. A combination of classification with different systems such as r-ASRM, EFI score and Enzian, may complicate classification of the disease due to overlaps and time-consuming documentation. Study design, size, duration The result is a consensus of a panel of renowned clinicians (working group), gynaecological surgeons and sonographers with extensive expertise in diagnosis and therapy of endometriosis. A first draft was written in 2019 by a joint effort of the first and last author and sent to all working group members. Taking all comments into account, a revised draft was then sent to all coauthors and repeated until a consensus was reached (9 revisions). Participants/materials, setting, methods Criteria used to invite the experts to participate in this consensus process included their having significant peer-reviewed publications in the field of diagnosis and management of endometriosis. Main results and the role of chance Our current proposal is the first of its kind to universally describe superficial and deep endometriosis, ovarian endometriosis, adenomyosis and adhesions by using a classification system that can be applied by gynaecologists, surgeons, sonographers and radiologists following the same principles. The correlation between preoperative and surgical staging, on the basis of the Enzian scheme, allows for consistent and clear classification of endometriosis, especially DE. Endometriosis can be mapped completely with one single classification system enabling the use of one common language. Limitations, reasons for caution This classification system is anatomically logical and should be easy to use. Further studies are ongoing and are needed to provide proof for the applicability, reproducibility and accuracy of the #Enzian classification for the description of endometriosis. Wider implications of the findings: #Enzian classification now enabled better coverage of various endometriosis localizations. The possibility of using this system preoperatively as well as postoperatively within the framework of diagnostics offers clinicians a significant improvement in the care of patients with such a complex disease. Trial registration number Not applicable

SARS-CoV-2 on the move: Reviewing Innate vs Acquired for Covid-19

In this article we have put down certain facts reported so far and raised some pertinent questions to understand the progress of Covid-19 disease. We have discussed the important role of innate immunity to tame Covid-19. Basics of innate and adaptive immunity has been discussed for general audience. Subsequently, we have discussed why immunity fails leading to ‘immunity escape’. We have asked and tried to address few concerns such as: Can vaccines drive the pathogen to mutate to a higher virulent strain?; Evolution of more virulent pathogens; Evidence of new variants; Evidence of variants evading immunity; Antibody cocktail demand for new design of vaccine; Evidence of SARS-CoV-2 evades T cell responses; Imperfect leaky vaccine; Complete Mapping of Mutations to the SARS-CoV-2 Spike Receptor-Binding Domain; Where is the originally identified SARS-CoV-2 (labeled as D614) found first in Wuhan, China; Deletion of spike glycoprotein itself: How to fix missing?; What is the present status?; To be or not to be vaccinated?; The challenge of antigenic drift and antigenic shift; What causes variant and can it be controlled?; A new dawn in the fight against the disease, to be or not to be worried?; Judging the risk “risk management”; Prophylactic measures for covid 19: Changing Diet and life style; Maneuvering the pandemic and finally the “Take away message”.

Delta Deposits on Mars: A Global Perspective

<p>The presence of delta deposits on Mars has been thoroughly demonstrated for decades and large scale mapping [1,2] highlighted the presence of several delta fans mainly located on the dichotomy boundary. While a previous delta inventory was compiled by Morgan et al. [3], we aim to update and finalize a complete mapping of delta deposits in order to allow the examination of the evolution and distribution of standing bodies of water on Mars. The objective of our project focuses on the production of a global catalogue of water-related features at the Martian surface, which are commonly studied separately or at smaller scales.</p><p>Globally, we located around 150 deltas among which many were not previously included in published literature [e.g. 1,2,4]. We then examined the deltas based on two main traits. Firstly, we measured the length of the feeding channels since it may be (i) a proxy for the duration of the aqueous activity in the channel-delta system, and (ii) proportional to the age of the delta [2]. The latter relationship links older deltas near Chryse Planitia (>3 Ga) to longer valleys, while younger deltas are usually fed by shorter valleys [2]. Secondly, we measured the elevation of the delta population and compared the obtained dataset with the hypothesized sea level elevation of -2540 ± 177 m firstly suggested by Di Achille and Hynek [1] for a northern ocean through the analysis of deltas.</p><p>We observed that, if the relationship between feeding channel length and delta age found for a sub-group of the population [2] is applicable as a rule of thumb to all deltas, many of the deposits have the potential to be Hesperian or Amazonian in age. They would thus be younger than the ocean that might have occupied the northern lowlands during the Noachian-Hesperian boundary period [1] and thus be unrelated to a global sea level range. In fact, less than half of the delta population is related to medium/long feeding channels (>30 km). Abundant pristine morphologies, both related to channels and deltas, also supports the hypothesis that part of the population is younger than Noachian. Additionally, the large variety of elevations where the deltaic deposits can be found and the very small amount of deltas included in the sea level elevation range proposed by Di Achille and Hynek [1] raise questions about the generation and environmental implications of these features, especially when seen at global scale.</p><p> </p><p>[1] Di Achille, G. & Hynek, B. M., Nat. Geosci. 3, 459–463 (2010).</p><p>[2] Hauber, E. et al., J. Geophys. Res. E Planets 118, 1529–1544 (2013).</p><p>[3] Morgan, A. M., et al., Lunar Planet. Sci. Conf. (2018).</p><p>[4] Ori, G.G. et al., J. Geophys. Res. E Planets 105, 17629–17641 (2000).</p>

MetaFetcheR: An R package for complete mapping of small compound data

MotivationSmall-compound databases contain large amount of information for metabolites and metabolic pathways. However, the plethora of such databases and the redundancy of their information lead to major issues with analysis and standardization. Lack of preventive establishment of means of data access at the infant stages of a project might lead to mislabelled compounds, reduced statistical power and large delays in delivery of results.ResultsWe developed MetaFetcheR, an open-source R package that links metabolite data from several small-compound databases, resolves inconsistencies and covers a variety of use-cases of data fetching. We showed that the performance of MetaFetcheR was superior to existing approaches and databases by benchmarking the performance of the algorithm in two independent case studies based on two published datasets.AvailabilityMetaFetcheR is available at https://github.com/komorowskilab/MetaFetcheR/.