Modeling Perceptual Aliasing in SLAM via Discrete-Continuous Graphical Models

Perceptual aliasing is one of the main causes of failure for Simultaneous Localization and Mapping (SLAM) systems operating in the wild. Perceptual aliasing is the phenomenon where different places generate a similar visual (or, in general, perceptual) footprint. This causes spurious measurements to be fed to the SLAM estimator, which typically results in incorrect localization and mapping results. The problem is exacerbated by the fact that those outliers are highly correlated, in the sense that perceptual aliasing creates a large number of mutually-consistent outliers. Another issue stems from the fact that most state-of-the-art techniques rely on a given trajectory guess (e.g., from odometry) to discern between inliers and outliers and this makes the resulting pipeline brittle, since the accumulation of error may result in incorrect choices and recovery from failures is far from trivial. This work provides a unified framework to model perceptual aliasing in SLAM and provides practical algorithms that can cope with outliers without relying on any initial guess. We present two main contributions. The first is a Discrete-Continuous Graphical Model (DC-GM) for SLAM: the continuous portion of the DC-GM captures the standard SLAM problem, while the discrete portion describes the selection of the outliers and models their correlation. The second contribution is a semidefinite relaxation to perform inference in the DC-GM that returns estimates with provable sub-optimality guarantees. Experimental results on standard benchmarking datasets show that the proposed technique compares favorably with state-of-the-art methods while not relying on an initial guess for optimization.Comment: 13 pages, 14 figures, 1 tabl

THE EFFECT OF FINTECH INVESTMENTS ON LISTED BANKS: EVIDENCE FROM AN ITALIAN SAMPLE

This paper analyses whether and how investments in financial technology (FinTech) affect performance, risk, and value of listed Italian banks. This paper tests the effect of return on equity (ROE) and capital asset pricing model (CAPM) Beta coefficient — and, secondly, of the price-to-book value (PBV) ratio, on a sample of 17 Italian listed banks from 2013 to 2019, representing the largest institutions operating in the Italian banking industry. The FinTech variable is declined into two different statuses: digital active banks and digital-focused banks. The study adds useful insights to the positive effects of innovation on banks’ value, in a market, like the Italian one, where investments in FinTech have spread in recent years. Controlling for other financial statements and market variables, the presence of FinTech investments does not affect the CAPM Beta coefficient, while the relationship is positive and significant with ROE for digital active banks only, and with the PBV for digital-focused banks. These results confirm a positive effect on performance for banks investing in FinTech, while greater expectations from investors and a positive effect on bank value creation are significant for digital-focused banks only

The impact of ECB loan valuation metrics on third-party loan pricing: A EU firm perspective

This paper delves into the implications for the bank behaviour about firm loan pricing conditions of the new direction undertaken by supervisory and regulatory authorities in the aftermath of the deterioration of the loan portfolio quality that hit EU banks. The 2014 AQR exercise embraces the new direction and extensively uses debt service coverage measures to assess a firm’s loan quality. We, therefore, check whether the DSCR has influenced debt pricing conditions by analysing a panel of 655 listed EU firms from 2009 to 2017. Our findings show that Z-score is unable to discriminate between high and low credit risk firms. The DSCR becomes significant only after 2014, highlighting the incremented importance of this ratio in the bank’s loan pricing determination. Our work contributes to the literature investigating third-party interdependencies with the interplay between lender-borrower relationship and loan pricing and further extends the literature on creditworthiness metrics beyond their mere default-prediction ability (Beaver, 1966; Houghton & Woodliff, 1987). Our results highlight the relevance of the DSCR in the bank’s loan pricing determination and inform firm managers about the drivers that influence the cost of debt thereby enhancing their operational and financial planning

Using Pathway Signatures as Means of Identifying Similarities among Microarray Experiments

Widespread use of microarrays has generated large amounts of data, the interrogation of the public microarray repositories, identifying similarities between microarray experiments is now one of the major challenges. Approaches using defined group of genes, such as pathways and cellular networks (pathway analysis), have been proposed to improve the interpretation of microarray experiments. We propose a novel method to compare microarray experiments at the pathway level, this method consists of two steps: first, generate pathway signatures, a set of descriptors recapitulating the biologically meaningful pathways related to some clinical/biological variable of interest, second, use these signatures to interrogate microarray databases. We demonstrate that our approach provides more reliable results than with gene-based approaches. While gene-based approaches tend to suffer from bias generated by the analytical procedures employed, our pathway based method successfully groups together similar samples, independently of the experimental design. The results presented are potentially of great interest to improve the ability to query and compare experiments in public repositories of microarray data. As a matter of fact, this method can be used to retrieve data from public microarray databases and perform comparisons at the pathway level

El impacto del cambio climático en las crisis humanitarias

A partir de un análisis histórico de la tipología de intervenciones humanitarias a lo largo delas últimas décadas el artículo hace hincapié en como el cambio climático puede tener consecuencias directas también en el impacto a nivel humanitario y en la capacidad del sistema en dar una respuesta adecuadas a las mayores necesidades que deriven de ello.Beside the well-known environmental problems linked to the use of resources, the greenhouse effects and the climate change will have big impacts on disasters and humanitarian crises in the future decades. This is because the impact of climate change is intimately related to others underlying risk factors such as the population growth and the uncontrolled urbanization. According to a pessimistic scenario the humanitarian system could be shortly stressed by its inability to respond to the increased needs

DOOR-SLAM: Distributed, Online, and Outlier Resilient SLAM for Robotic Teams

To achieve collaborative tasks, robots in a team need to have a shared understanding of the environment and their location within it. Distributed Simultaneous Localization and Mapping (SLAM) offers a practical solution to localize the robots without relying on an external positioning system (e.g. GPS) and with minimal information exchange. Unfortunately, current distributed SLAM systems are vulnerable to perception outliers and therefore tend to use very conservative parameters for inter-robot place recognition. However, being too conservative comes at the cost of rejecting many valid loop closure candidates, which results in less accurate trajectory estimates. This paper introduces DOOR-SLAM, a fully distributed SLAM system with an outlier rejection mechanism that can work with less conservative parameters. DOOR-SLAM is based on peer-to-peer communication and does not require full connectivity among the robots. DOOR-SLAM includes two key modules: a pose graph optimizer combined with a distributed pairwise consistent measurement set maximization algorithm to reject spurious inter-robot loop closures; and a distributed SLAM front-end that detects inter-robot loop closures without exchanging raw sensor data. The system has been evaluated in simulations, benchmarking datasets, and field experiments, including tests in GPS-denied subterranean environments. DOOR-SLAM produces more inter-robot loop closures, successfully rejects outliers, and results in accurate trajectory estimates, while requiring low communication bandwidth. Full source code is available at https://github.com/MISTLab/DOOR-SLAM.git.Comment: 8 pages, 11 figures, 2 table

Static Probabilistic Timing Analysis in Presence of Faults

Accurate timing prediction for software execution is becoming a problem due to the increasing complexity of computer architecture, and the presence of mixed-criticality workloads. Probabilistic caches were proposed to set bounds to Worst Case Execution Time (WCET) estimates and help designers improve system resource usage. However, as technology scales down, system fault rates increase and timing behavior is affected. In this paper, we propose a Static Probabilistic Timing Analysis (SPTA) approach for caches with evict-on-miss random replacement policy using a state space modeling technique, with consideration of fault impacts on both timing analysis and task WCET. Different scenarios of transient and permanent faults are investigated. Results show that our proposed approach provides tight probabilistic WCET (pWCET) estimates and as fault rate increases, the timing behavior of the system can be affected significantly

Chondrosarcoma of the Sternum Treated with En Bloc Resection: A Case Report

Introduction: Chondrosarcomas are malignant neoplasms of cartilaginous mesenchymal. The diagnosis is based on a complete radiological examination. The treatment of choice is surgical, being the only curative option due to the resistance of the lesions to chemotherapy and radiotherapy. Case presentation: 66-year-old male patient presenting chest pain, dry cough and occasional dyspnea, diagnosed with sternal chondrosarcoma and treated with en bloc resection of the tumor mass.Conclusion: A primary chondrosarcoma of the sternum was treated with resection of the anterior costal railing, pericardium, tumor mass and partial sternectomy, en bloc. Reconstruction was performed using Marlex microporous mesh

A computational procedure to identify significant overlap of differentially expressed and genomic imbalanced regions in cancer datasets†

The integration of high-throughput genomic data represents an opportunity for deciphering the interplay between structural and functional organization of genomes and for discovering novel biomarkers. However, the development of integrative approaches to complement gene expression (GE) data with other types of gene information, such as copy number (CN) and chromosomal localization, still represents a computational challenge in the genomic arena. This work presents a computational procedure that directly integrates CN and GE profiles at genome-wide level. When applied to DNA/RNA paired data, this approach leads to the identification of Significant Overlaps of Differentially Expressed and Genomic Imbalanced Regions (SODEGIR). This goal is accomplished in three steps. The first step extends to CN a method for detecting regional imbalances in GE. The second part provides the integration of CN and GE data and identifies chromosomal regions with concordantly altered genomic and transcriptional status in a tumor sample. The last step elevates the single-sample analysis to an entire dataset of tumor specimens. When applied to study chromosomal aberrations in a collection of astrocytoma and renal carcinoma samples, the procedure proved to be effective in identifying discrete chromosomal regions of coordinated CN alterations and changes in transcriptional levels

The orphan nuclear receptor COUP-TFII coordinates hypoxia-independent proangiogenic responses in hepatic stellate cells

BACKGROUND & AIMS: Hepatic stellate cell (HSC) transdifferentiation into collagen-producing myofibroblasts is a key event in hepatic fibrogenesis, but the transcriptional network that controls the acquisition of the activated phenotype is still poorly understood. In this study, we explored whether the nuclear receptor chicken ovalbumin upstream promoter-transcription factor II (COUP-TFII) is involved in HSC activation and in the multifunctional role of these cells during the response to liver injury. METHODS: COUP-TFII expression was evaluated in normal and cirrhotic livers by immunohistochemistry and Western blot. The role of COUP-TFII in HSC was assessed by gain and loss of function transfection experiments and by generation of mice with COUP-TFII deletion in HSC. Molecular changes were determined by gene expression microarray and RT-qPCR. RESULTS: We showed that COUP-TFII is highly expressed in human fibrotic liver and in mouse models of hepatic injury. COUP-TFII expression rapidly increased upon HSC activation and it was associated with the regulation of genes involved in cell motility, proliferation and angiogenesis. Inactivation of COUP-TFII impairs proliferation and invasiveness in activated HSC and COUP-TFII deletion in mice abrogate HSC activation and angiogenesis. Finally, co-culture experiments with HSC and liver sinusoidal endothelial cells (SEC) showed that COUP-TFII expression in HSC influenced SEC migration and tubulogenesis via a hypoxia-independent and nuclear factor κB-dependent mechanism. CONCLUSION: This study elucidates a novel transcriptional pathway in HSC that is involved in the acquisition of the proangiogenic phenotype and regulates the paracrine signals between HSC and SEC during hepatic wound healing. LAY SUMMARY: In this study, we identified an important regulator of HSC pathobiology. We showed that the orphan receptor COUP-TFII is an important player in hepatic neoangiogenesis. COUP-TFII expression in HSC controls the crosstalk between HSC and endothelial cells coordinating vascular remodelling during liver injury. TRANSCRIPT PROFILING: ArrayExpress accession E-MTAB-1795