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| 2. |
- Sandercock, P, et al.
(author)
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EPITHET--where next?
- 2008
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In: The Lancet. Neurology. - 1474-4422. ; 7:7, s. 570-571
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Journal article (other academic/artistic)
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| 3. |
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| 4. |
- Bo, Stefano, et al.
(author)
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Detecting Concentration Changes with Cooperative Receptors
- 2015
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In: Journal of statistical physics. - : Springer-Verlag New York. - 0022-4715 .- 1572-9613. ; 162:5, s. 1365-1382
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Journal article (peer-reviewed)abstract
- Cells constantly need to monitor the state of the environment to detect changes and timely respond. The detection of concentration changes of a ligand by a set of receptors can be cast as a problem of hypothesis testing, and the cell viewed as a Neyman–Pearson detector. Within this framework, we investigate the role of receptor cooperativity in improving the cell’s ability to detect changes. We find that cooperativity decreases the probability of missing an occurred change. This becomes especially beneficial when difficult detections have to be made. Concerning the influence of cooperativity on how fast a desired detection power is achieved, we find in general that there is an optimal value at finite levels of cooperation, even though easy discrimination tasks can be performed more rapidly by noncooperative receptors.
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| 5. |
- Bo, Stefano, et al.
(author)
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Multiple-scale stochastic processes : Decimation, averaging and beyond
- 2017
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In: Physics reports. - : Elsevier. - 0370-1573 .- 1873-6270. ; 670, s. 1-59
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Journal article (peer-reviewed)abstract
- The recent experimental progresses in handling microscopic systems have allowed to probe them at levels where fluctuations are prominent, calling for stochastic modeling in a large number of physical, chemical and biological phenomena. This has provided fruitful applications for established stochastic methods and motivated further developments. These systems often involve processes taking place on widely separated time scales. For an efficient modeling one usually focuses on the slower degrees of freedom and it is of great importance to accurately eliminate the fast variables in a controlled fashion, carefully accounting for their net effect on the slower dynamics. This procedure in general requires to perform two different operations: decimation and coarse-graining. We introduce the asymptotic methods that form the basis of this procedure and discuss their application to a series of physical, biological and chemical examples. We then turn our attention to functionals of the stochastic trajectories such as residence times, counting statistics, fluxes, entropy production, etc. which have been increasingly studied in recent years. For such functionals, the elimination of the fast degrees of freedom can present additional difficulties and naive procedures can lead to blatantly inconsistent results. Homogenization techniques for functionals are less covered in the literature and we will pedagogically present them here, as natural extensions of the ones employed for the trajectories. We will also discuss recent applications of these techniques to the thermodynamics of small systems and their interpretation in terms of information-theoretic concepts.
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| 6. |
- Calcagno, A., et al.
(author)
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Alzheimer Dementia in People Living With HIV
- 2021
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In: Neurology-Clinical Practice. - : Ovid Technologies (Wolters Kluwer Health). - 2163-0402 .- 2163-0933. ; 11:5
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Journal article (peer-reviewed)abstract
- Objective Given the aging of people living with HIV (PLWH) and the high prevalence of HIV-associated neurocognitive disorders, we aimed at describing the clinical, instrumental, and CSF features of PLWH diagnosed with Alzheimer dementia (AD). Methods The databases of 3 large Italian outpatient clinics taking care of more than 9,000 PLWH were searched for the diagnosis of AD. After obtaining patients' or their next of kin's consent for publication, anonymous data were collected in an excel spreadsheet and described. Routinely collected CSF biomarkers and radiologic imaging results were recorded whether available. Results Four patients were included in this case series who were diagnosed with AD aged between 60 and 74 years. All participants were on highly active antiretroviral therapy and showed nondetectable serum HIV RNA. Memory impairment was the most prominent cognitive feature. The diagnosis was obtained considering the exclusion of other potential causes, MRI and fluorodeoxyglucose-PET features, and, in (in 2/4), CSF AD biomarkers levels. In 1 patient, longitudinal CSF tau/p-tau increased, and beta-amyloid(1-42) decreased over time despite antiretroviral therapy containing nucleotide reverse transcriptase inhibitors. Conclusions In older PLWH cognitive symptoms may represent the onset of AD: a multidisciplinary team may be needed for reaching a likely in vivo diagnosis.
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| 7. |
- Celani, A., et al.
(author)
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Anomalous thermodynamics at the microscale
- 2012
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In: Physical Review Letters. - 0031-9007 .- 1079-7114. ; 109:26, s. 260603-
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Journal article (peer-reviewed)abstract
- Particle motion at the microscale is an incessant tug-of-war between thermal fluctuations and applied forces on one side and the strong resistance exerted by fluid viscosity on the other. Friction is so strong that completely neglecting inertia - the overdamped approximation - gives an excellent effective description of the actual particle mechanics. In sharp contrast to this result, here we show that the overdamped approximation dramatically fails when thermodynamic quantities such as the entropy production in the environment are considered, in the presence of temperature gradients. In the limit of vanishingly small, yet finite, inertia, we find that the entropy production is dominated by a contribution that is anomalous, i.e., has no counterpart in the overdamped approximation. This phenomenon, which we call an entropic anomaly, is due to a symmetry breaking that occurs when moving to the small, finite inertia limit. Anomalous entropy production is traced back to futile phase-space cyclic trajectories displaying a fast downgradient sweep followed by a slow upgradient return to the original position.
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| 8. |
- Colabrese, S., et al.
(author)
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Flow Navigation by Smart Microswimmers via Reinforcement Learning
- 2017
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In: Physical Review Letters. - 0031-9007. ; 118:15
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Journal article (peer-reviewed)abstract
- Smart active particles can acquire some limited knowledge of the fluid environment from simple mechanical cues and exert a control on their preferred steering direction. Their goal is to learn the best way to navigate by exploiting the underlying flow whenever possible. As an example, we focus our attention on smart gravitactic swimmers. These are active particles whose task is to reach the highest altitude within some time horizon, given the constraints enforced by fluid mechanics. By means of numerical experiments, we show that swimmers indeed learn nearly optimal strategies just by experience. A reinforcement learning algorithm allows particles to learn effective strategies even in difficult situations when, in the absence of control, they would end up being trapped by flow structures. These strategies are highly nontrivial and cannot be easily guessed in advance. This Letter illustrates the potential of reinforcement learning algorithms to model adaptive behavior in complex flows and paves the way towards the engineering of smart microswimmers that solve difficult navigation problems.
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| 9. |
- Colabrese, S., et al.
(author)
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Smart inertial particles
- 2018
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In: Physical Review Fluids. - 2469-990X. ; 3:8
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Journal article (peer-reviewed)abstract
- We performed a numerical study to train smart inertial particles to target specific flow regions with high vorticity through the use of reinforcement learning algorithms. The particles are able to actively change their size to modify their inertia and density. In short, using local measurements of the flow vorticity, the smart particle explores the interplay between its choices of size and its dynamical behavior in the flow environment. This allows it to accumulate experience and learn approximately optimal strategies of how to modulate its size in order to reach the target high-vorticity regions. We consider flows with different complexities: a two-dimensional stationary Taylor-Green-like configuration, a two-dimensional time-dependent flow, and finally a three-dimensional flow given by the stationary Arnold-Beltrami-Childress (ABC) helical flow. We show that smart particles are able to learn how to reach extremely intense vortical structures in all the tackled cases.
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| 10. |
- Gustavsson, Kristian, 1980, et al.
(author)
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Finding efficient swimming strategies in a three-dimensional chaotic flow by reinforcement learning
- 2017
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In: European Physical Journal E. - : Springer Science and Business Media LLC. - 1292-8941 .- 1292-895X. ; 40:12
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Journal article (peer-reviewed)abstract
- We apply a reinforcement learning algorithm to show how smart particles can learn approximately optimal strategies to navigate in complex flows. In this paper we consider microswimmers in a paradigmatic three-dimensional case given by a stationary superposition of two Arnold-Beltrami-Childress flows with chaotic advection along streamlines. In such a flow, we study the evolution of point-like particles which can decide in which direction to swim, while keeping the velocity amplitude constant. We show that it is sufficient to endow the swimmers with a very restricted set of actions (six fixed swimming directions in our case) to have enough freedom to find efficient strategies to move upward and escape local fluid traps. The key ingredient is the learning-from-experience structure of the algorithm, which assigns positive or negative rewards depending on whether the taken action is, or is not, profitable for the predetermined goal in the long-term horizon. This is another example supporting the efficiency of the reinforcement learning approach to learn how to accomplish difficult tasks in complex fluid environments.
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