3,733 research outputs found
Structured Machine Learning for Robotics
Machine Learning has become the essential tool for automating tasks that consist in predicting the output associated to a certain input.
However many modern algorithms are mainly developed for the simple cases of classification and regression. Structured prediction is the field concerned with predicting outputs consisting of complex objects such as graphs, orientations or sequences. While these objects are often of practical interest, they do not have many of the mathematical properties that allow to design principled and computationally feasible algorithms with traditional techniques.
In this thesis we investigate and develop algorithms for learning manifold-valued functions in the context of structured prediction. Differentiable manifolds are a mathematical abstraction used in many domains to describe sets with continuous constraints and non-Euclidean geometric properties.
By taking a structured prediction approach we show how to define statistically consistent estimators for predicting elements of a manifold, in constrast to traditional structured predition algorithms that are restricted to output sets with finite cardinality.
We introduce a wide range of applications that leverage manifolds structures. Above all, we study the case of the hyperbolic manifold, a space suited for representing hierarchical data. By representing supervised datasets within hyperbolic space we show how it is possible to invent new concepts in a previously known hierarchy and show promising results in hierarchical classification.
We also study how modern structured approaches can help with practical robotics tasks, either improving performances in behavioural pipelines or showing more robust predictions for constrained tasks. Specifically, we show how structured prediction can be used to tackle inverse kinematics problems of redundant robots, accounting for the constraints of the robotic joints. We also consider the task of biological motion detection and show that by leveraging the sequence structure of video streams we significantly reduce the latency of the application. Our studies are complemented by empirical evaluations on both synthetic and real data
Electrokinetic Lattice Boltzmann solver coupled to Molecular Dynamics: application to polymer translocation
We develop a theoretical and computational approach to deal with systems that
involve a disparate range of spatio-temporal scales, such as those comprised of
colloidal particles or polymers moving in a fluidic molecular environment. Our
approach is based on a multiscale modeling that combines the slow dynamics of
the large particles with the fast dynamics of the solvent into a unique
framework. The former is numerically solved via Molecular Dynamics and the
latter via a multi-component Lattice Boltzmann. The two techniques are coupled
together to allow for a seamless exchange of information between the
descriptions. Being based on a kinetic multi-component description of the fluid
species, the scheme is flexible in modeling charge flow within complex
geometries and ranging from large to vanishing salt concentration. The details
of the scheme are presented and the method is applied to the problem of
translocation of a charged polymer through a nanopores. In the end, we discuss
the advantages and complexities of the approach
Effect of Different Egg Products on Lipid Oxidation of Biscuits
Egg products are one of the main ingredients used in bakery industries, and they contain
cholesterol. Cholesterol su ers several chemical changes during the food processes, allowing some
potentially toxic compounds called cholesterol oxidized products (COPs). Thus, the aim of this work
was to study the evolution of lipid oxidation from eggs to egg products, and to evaluate the influence
of egg products on COPs formation in biscuits formulated with them. The results confirmed that
spray-drying technology improves the cholesterol oxidation 2.6 times compared to pasteurized eggs.
Biscuit samples showed a COPs content that is strictly related to the egg products used. Samples
formulated with spray-dried eggs noticed lower amounts of COPs compared to those formulated
with pasteurized eggs. It is important to stress that COPs composition was di erent between the two
samples, underlining that the kinetic of COPs formation is dependent on the type of egg products.Spanish Ministry of Economy and Competitiveness (MINECO)
RYC-2015-1879
Formal verification of storm topologies through D-VerT
Data-intensive applications (DIAs) based on so-called Big Data technologies are nowadays a common solution adopted by IT companies to face their growing computational needs. The need for highly reliable applications able to handle huge amounts of data and the availability of infrastructures for distributed computing rapidly led industries to develop frame-works for streaming and big-data processing, like Apache Storm and Spark. The definition of methodologies and principles for good software design is, therefore, fundamental to support the development of DIAs. This paper presents an approach for non-functional analysis of DIAs through D- VerT, a tool for the architectural assessment of Storm applications. The verification is based on a translation of Storm topologies into the CLTLoc metric temporal logic. It allows the designer of a Storm application to check for the existence of components that cannot process their workload in a timely manner, typically due to an incorrect design of the topology
Variable stars in the ultra-faint dwarf spheroidal galaxy Ursa Major I
We have performed the first study of the variable star population of Ursa
Major I (UMa I), an ultra-faint dwarf satellite recently discovered around the
Milky Way by the Sloan Digital Sky Survey. Combining time series observations
in the B and V bands from four different telescopes, we have identified seven
RR Lyrae stars in UMa I, of which five are fundamental-mode (RRab) and two are
first-overtone pulsators (RRc). Our V, B-V color-magnitude diagram of UMa I
reaches V~23 mag (at a signal-to-noise ratio of ~ 6) and shows features typical
of a single old stellar population. The mean pulsation period of the RRab stars
= 0.628, {\sigma} = 0.071 days (or = 0.599, {\sigma} = 0.032 days,
if V4, the longest period and brightest variable, is discarded) and the
position on the period-amplitude diagram suggest an Oosterhoff-intermediate
classification for the galaxy. The RR Lyrae stars trace the galaxy horizontal
branch at an average apparent magnitude of = 20.43 +/- 0.02 mag
(average on 6 stars and discarding V4), giving in turn a distance modulus for
UMa I of (m-M)0 = 19.94 +/- 0.13 mag, distance d= 97.3 +6.0/-5.7 kpc, in the
scale where the distance modulus of the Large Magellanic Cloud is 18.5 +/- 0.1
mag. Isodensity contours of UMa I red giants and horizontal branch stars
(including the RR Lyrae stars identified in this study) show that the galaxy
has an S-shaped structure, which is likely caused by the tidal interaction with
the Milky Way. Photometric metallicities were derived for six of the UMa I RR
Lyrae stars from the parameters of the Fourier decomposition of the V-band
light curves, leading to an average metal abundance of [Fe/H] = -2.29 dex
({\sigma} = 0.06 dex, average on 6 stars) on the Carretta et al. metallicity
scale.Comment: Accepted for publication in Ap
Comparative elemental analysis of dairy milk and plant-based milk alternatives
Together with essential elements, toxic elements can also be found in food. In this study, we analysed the content of 41 elements in milk from mammals (cow, goat, and donkey) and plant-based milk alternatives (from soy, rice, oat, spelt, almond, coconut, hazelnut, walnut, cashew, hemp, and quinoa) using inductively coupled plasma mass spectrometry and cold vapour generation atomic fluorescence (for Hg). The analytical methods were validated using both milk certified reference materials and recovery experiments for different milk samples, obtaining satisfactory results in all cases. Only cow and goat milks were important sources of all major mineral elements like Ca, K, Mg, Na and P, and some minor elements like Se and Zn, while soy milk contained significant amounts of Cu and Fe, coconut milk contained Cr and Se, and hemp milk contained Mo. The level of toxic trace elements, including As, Cd, Hg, and Pb was very low in all analysed samples and did not pose any threat to consumers. The study is of significance for consumers of plant-based beverages from nutritional and food safety point of view. © 2020 Elsevier Lt
An overview on the local limit of non-local conservation laws, and a new proof of a compactness estimate
Consider a non-local (i.e., involving a convolution term) conservation law: when the convolution term converges to a Dirac delta, in the limit we formally recover a classical (or "local") conservation law. In this note we overview recent progress on this so-called non-local to local limit and in particular we discuss the case of anistropic kernels, which is extremely relevant in view of applications to traffic models. We also provide a new proof of a related compactness estimate
Do DLX3 and CD271 Protect Human Keratinocytes from Squamous Tumor Development?
Well-regulated epidermal homeostasis depends on the function of different classes of factors, such as transcription regulators and receptors. Alterations in this homeostatic balance may lead to the development of cutaneous squamous tumorigenesis. The homeobox transcription factor DLX3 is determinant for a p53-dependent regulation of epidermal differentiation and modulates skin carcinogenesis. The maintenance of skin homeostasis also involves the action of neurotrophins (NTs) and their receptors, Trk and CD271. While Trk receptor overexpression is a hallmark of cancer, there are conflicting data on CD271 expression and function in cutaneous SCC (cSCC). Previous studies have reported NT receptors expression in head and neck SSC (HNSCC). We show that CD271 is expressed at low levels in primary cSCC cells and the number of CD271+ cells correlates with cell cohesion in SCC spheroids. In normal epidermis, CD271 is expressed in proliferative progenitor cells and DLX3 in terminally differentiated keratinocytes. Brain-derived neurotrophic factor (BDNF) and neurotrophin 3 (NT3) increase DLX3 expression. In the absence of a functional BDNF receptor TrkB in keratinocytes, we hypothesize that the BDNF-dependent DLX3 response could be mediated via CD271. Altogether, our results support a putative CD271-DLX3 connection in keratinocytes, which might be crucial to preventing squamous skin cancer
Structured Prediction for CRiSP Inverse Kinematics Learning with Misspecified Robot Models
With the recent advances in machine learning, problems that traditionally
would require accurate modeling to be solved analytically can now be
successfully approached with data-driven strategies. Among these, computing the
inverse kinematics of a redundant robot arm poses a significant challenge due
to the non-linear structure of the robot, the hard joint constraints and the
non-invertible kinematics map. Moreover, most learning algorithms consider a
completely data-driven approach, while often useful information on the
structure of the robot is available and should be positively exploited. In this
work, we present a simple, yet effective, approach for learning the inverse
kinematics. We introduce a structured prediction algorithm that combines a
data-driven strategy with the model provided by a forward kinematics function
-- even when this function is misspecified -- to accurately solve the problem.
The proposed approach ensures that predicted joint configurations are well
within the robot's constraints. We also provide statistical guarantees on the
generalization properties of our estimator as well as an empirical evaluation
of its performance on trajectory reconstruction tasks.Comment: Accepted for publication in IEEE Robotics and Automation Letters
(2021) and presentation at IEEE International Conference on Robotics and
Automation (2021) Updated funding informatio
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