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Guaranteed 2D pose graph SLAM with bounded noises:An efficient interval approach
Get PDFThis paper focuses on developing a performance guaranteed state estimation algorithm for 2D pose graph problems for mobile robots. Different from probabilistic methods, the measurement noises are only assumed to be bounded without any prior knowledge about their distributions. Based on the interval analysis, we first propose a vanilla sequential contractor that iteratively uses edge-wise noise bounds to contract pose intervals at the nodes, which can provide the guaranteed feasible domains that contain the ground-truth values. Then, to improve the efficiency in solving large-scale pose graphs, an efficient batch contractor is developed by improving the update order and exploiting a relaxation of the nonlinear measurement functions. The effectiveness and efficiency of our approaches are validated on simulated and real-world datasets. Note to Practitioners—Pose graph is one of the most popular formulations for the state estimations of mobile robots. There have been many probabilistic algorithms for pose graphs based on the Gaussian-like measurement noise assumption. However, the measurement noises in many practical situations may not follow Gaussian distributions but have hard bounds. Consequently, the existing pose graph algorithms are far away from achieving the expected high reliability in the practical safety-critical applications such as autonomous driving. To achieve guaranteed performance, an efficient interval based approach is proposed for the large-scale pose graph problems with hard bound measurement noises. It can provide the guaranteed hard error bounds for the robot poses, which has the potential in uncertainty quantification, reliability analysis and outlier detection of safety-critical systems
Translational genomics of osteoarthritis in 1,962,069 individuals
Get PDFOsteoarthritis is the third most rapidly growing health condition associated with disability, after dementia and diabetes1. By 2050, the total number of patients with osteoarthritis is estimated to reach 1 billion worldwide2. As no disease-modifying treatments exist for osteoarthritis, a better understanding of disease aetiopathology is urgently needed. Here we perform a genome-wide association study meta-analyses across up to 489,975 cases and 1,472,094 controls, establishing 962 independent associations, 513 of which have not been previously reported. Using single-cell multiomics data, we identify signal enrichment in embryonic skeletal development pathways. We integrate orthogonal lines of evidence, including transcriptome, proteome and epigenome profiles of primary joint tissues, and implicate 700 effector genes. Within these, we find rare coding-variant burden associations with effect sizes that are consistently higher than common frequency variant associations. We highlight eight biological processes in which we find convergent involvement of multiple effector genes, including the circadian clock, glial-cell-related processes and pathways with an established role in osteoarthritis (TGFβ, FGF, WNT, BMP and retinoic acid signalling, and extracellular matrix organization). We find that 10% of the effector genes express a protein that is the target of approved drugs, offering repurposing opportunities, which can accelerate translation
Decompose, deduce, and dispose:A memory-limited metacognitive model of human problem solving
Get PDFMany real-world problems are defined by complex systems of interlocking constraints. How people are able to solve these problems with such limited working memory capacity remains poorly understood. We propose a formal model of human problem-solving under memory constraints that uses metacognitive knowledge of its own memory limits to guide subproblem choice. We compare our model to human gameplay in two experiments using a variant of the classic game Minesweeper. In Experiment 1, we find that participants' accuracy was influenced both by the order of subproblems and their ability to externalize intermediate results, indicative of a memory bottleneck in reasoning. In Experiment 2, we used a mouse-tracking paradigm to assess participants' subproblem choice and time allocation. The model captures key patterns of subproblem ordering, error, and time allocation. Our results point toward memory limits and strategies for navigating those limits as central elements of human problem-solving
A lightweight approach to gait abnormality detection for At Home health monitoring
Get PDFGait abnormality detection is a growing application in machine learning based health assessment due to its potential in domains from clinical health reviews to at home health monitoring. This latter application is of particular use for older adults, who are more likely to experience health issues that can be indicated by changes in gait, namely through fall-related injuries or age-related degenerative diseases like Parkinson's disease. While there exists a great deal of research concerning machine learning models for detecting everything from freezing-of-gait to falls, much of this work relies on clinical assessment settings and large models with extensive data, making many developments unusable in at-home applications where such technology could be used to great benefit in maintaining the independence and health of older adults. To address this gap in the literature, we introduce a new 15-person synthetic gait abnormality dataset named WeightGait and a lightweight ST-GCN model to demonstrate the feasibility of smaller models with lower computational costs in detecting gait abnormalities in an environment more analogous to the conditions found in an at-home setting. For the task of identifying gait abnormalities in the WeightGait dataset, this method achieves 94.4 % accuracy, an improvement of between 4.9 % and 15.41 % on comparable gait assessment methods
Modeling, Capacity Studies, Antenna and System Designs for 6G/B6G 3D Continuous-Space Radio Channels Enabled by Electromagnetic Information Theory
No full textChannel theory is a fundamental theory of wireless communications. The sixth generation (6G) and beyond 6G (B6G) wireless communication networks are expected to provide space-air- ground-sea global coverage. Base stations and users tend to move in three dimensional (3D) continuous spaces, while antennas and propagation environments can be tightly coupled. The underlying channels show an evolutionary trend to 3D continuous-space radio channels that combine antennas and wireless propagation channels, in comparison to discrete local-space wireless propagation channels in previous generations. This introduces new challenges for channel modeling, channel capacity analysis, antenna design, system design, etc. To address these challenges, this paper performs a comprehensive study on 3D continuous-space radio channels in 6G/B6G with the aid of electromagnetic information theory (EIT) that integrates electromagnetic theory, information theory, wireless propagation channel modeling theory,and antenna theory. We start by revealing the connections and gaps between these four fundamental theories. Then, an in-depth investigation on the four major research thrusts of3D continuous-space radio channels is provided: 1) channel measurements and modeling, 2) channel capacity analysis, 3) general antenna design, and 4) wireless system design. We aim toexplore the intrinsic relationships between antenna parameters, channel parameters, channel characteristics, channel capacity, and communication system performance. Finally, future research directions and challenges for 3D continuous-space radio channels are outlined. Our study endeavors to establish a fundamental framework for 3D continuous-space radio channels, with the potential to catalyze breakthroughs in 6G/B6G theories
Reading between the lines in the Barany Lab:Lessons on written and unwritten science and mathematics
No full textPurposeI reflect on my childhood experiences in the Barany Lab and connect them to several findings and themes from my subsequent career researching the history and culture of science and mathematics.MethodsEmphasizing the role of language and of written and unwritten aspects of science, together with their playful and communal characteristics, I connect George Barany’s scientific perspectives to insights from my own fields of study.ResultsThese insights include considerations of the formative role of wordplay, the multiple meanings of mathematical texts and practices, the role of blackboards in science, and misperceptions of the Fields Medal in mathematics.ConclusionFocusing on written and unwritten play and imagination humanizes science and the communities that pursue it
Experiential learning in construction history through models
No full textA critical reflection on the PG Construction History course at the University of Edinburgh is made as the coursework (modelling of historical technical details) has taken a central role in the learning experience of the students. The variety of cases and modelling tech-niques, and engagement by the students are all reviewed as a learning environment of Making, exploring beyond the current reproduction of specific techniques and the discus-sion of their associated building culture for the assessment of the course through essays. The learning experience is acknowledged to be rich, which questions whether the syllabus, learning outcomes and activities (lectures and the associated workshops) need a re-focus to enable and properly assess a Making environment. The development of this learning experience and its relationship with current trends and definitions in the construction his-tory discipline are further investigated showing potential strong pedagogical and practice links
Addressing the synergistic effect of hydraulic diameter and aspect ratio on experimental flow boiling in microchannels
No full textThe effects of hydraulic diameter (Dh) and aspect ratio (AR) on flow boiling heat transfer characteristics in rectangular microchannels under uniform heating are elucidated in this work. The microchannels tested have Dh of 762 µm, 727 µm, and 909 µm. The Dh = 762 µm microchannel has an AR of 20, while the other two have an AR of 10, with each microchannel having a length of 80 mm. While hydrofluoroether HFE-7000 is selected as the working fluid with a saturation temperature of 34 °C. The experiment covered low flow rate conditions with Reynolds number Re ranging from 22.72 to 68.15 and a heat flux range of 0.05 to 16.02 kW/m2. During the experiment the inlet and outlet temperatures and pressures are measured, while high-speed and infrared cameras captured the flow patterns and wall temperature distributions. Results indicate that as heat flux increases, bubble flow, slug flow, transitional flow, and annular flow, sequentially occur in the microchannel. Meanwhile increasing the AR enhances liquid film thickness in both churn and annular flows, in turn increasing thermal resistance. At high AR the occurrence of liquid film fluctuations also increases, causing the film to thin or even rupture in localized areas, exposing the microchannel walls and forming hot spots, therefore resulting in a worse heat transfer performance. Comparing the different flow pattern maps at the front, middle and rear of the channel, it shows that a higher AR shifts the flow regime transition lines towards the lower outlet vapor quality end, whereas a reduced Dh increases the vapor quality necessary for flow regime transitions. The Dh = 727 µm microchannel achieves superior heat transfer performance. A smaller Dh reduces the effective wetting area, thereby diminishing the resistance of conduction and convection, enhancing the microchannel’s heat transfer performance. This is consistent with the heat transfer results and the increase in thermal resistance as Dh decreases for medium and high Re studied. The coefficient of performance (COP) for microchannels is defined as the ratio of effective input heat to pump power, while increasing the AR effectively reduces pressure drop and enhances overall performance, the Dh exerts a more significant impact on COP than the AR
Tackling poverty across the United Kingdom. Devolution, difference and discourse
No full textThe UK welfare state is often considered as being highly centralised, yet the design and administration of UK social security involves significant spatial variations in law, policy, and practice. As such, where you live in the UK can affect the value of benefits and cash transfers you are entitled to, as well as how you experience benefit administration. In this article we advocate for greater consideration of spatial variations in social security and draw attention to existing policy differences in the devolved nations and across localities. The article explores policy discourse and design differences to identify competing narratives and to encourage greater consideration of spatial policy developments in social security. Drawing attention to the Safety Nets research project, it argues that a better understanding of the causes and outcomes of spatial variation in social security provision is necessary in the context of governance reforms to increase devolution and decentralistion including the rise of mayoral regions in England
Recovering copper from e-waste:recyclable precipitation versus solvent extraction with carbon emission assessment
No full textAs the demand for copper continues to rise, so too does the need for sustainable methods for its recovery from waste streams. Taking inspiration from phenolic oxime reagents used in solvent extraction, the development of two recyclable ligands that act as selective precipitants for the recovery of copper from aqueous mixed-metal acidic solutions is reported. Switching the mode of action from traditional solvent extraction to precipitation eliminates the need for an organic solvent, fulfilling an important principle of green chemistry. The ligand designs feature ditopic phenolic oxime or pyrazole units that result in metal coordination at two sites, thereby promoting the formation of infinite coordination polymers that precipitate from solution. Complete copper recovery from single-metal solutions of CuSO4 and from mixed-metal solutions that contain nickel, zinc, cobalt and iron is demonstrated, under mildly acidic conditions. The copper was recovered from the loaded precipitates by washing with dilute sulfuric acid, and the ligands reused directly for multiple cycles without loss of performance. Furthermore, 96% of the copper present in a leachate solution derived from waste printed circuit boards was recovered using the phenolic pyrazole ligand. The carbon emissions of this process were also estimated by life cycle assessment and compared with those generated from the recovery of copper by ACORGA M5910, a typical phenolic oxime solvent extractant, with the precipitation process found to be more environmentally benign.</p
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