Design examples using µ-synthesis: Space shuttle lateral axis FCS during reentry

This paper studies the application of Structured Singular Values (SSV or µ) for analysis and synthesis of the Space Shuttle lateral axis flight control system (FCS) during reentry. While this is a fairly standard FCS problem in most respects, the aircraft model is highly uncertain due to the poorly known aerodynamic characteristics (e.g. aero coefficients). Comparisons are made of the conventional FCS with alternatives based on H∞ optimal control and µ-synthesis. The problem as formulated is particularly interesting and challenging because the uncertainty is large and highly structured

A Characterization of all Solutions to the Four Block General Distance Problem

All solutions to the four block general distance problem which arises in H^∞ optimal control are characterized. The procedure is to embed the original problem in an all-pass matrix which is constructed. It is then shown that part of this all-pass matrix acts as a generator of all solutions. Special attention is given to the characterization of all optimal solutions by invoking a new descriptor characterization of all-pass transfer functions. As an application, necessary and sufficient conditions are found for the existence of an H^∞ optimal controller. Following that, a descriptor representation of all solutions is derived

Imaging and Dynamics of Light Atoms and Molecules on Graphene

Observing the individual building blocks of matter is one of the primary goals of microscopy. The invention of the scanning tunneling microscope [1] revolutionized experimental surface science in that atomic-scale features on a solid-state surface could finally be readily imaged. However, scanning tunneling microscopy has limited applicability due to restrictions, for example, in sample conductivity, cleanliness, and data aquisition rate. An older microscopy technique, that of transmission electron microscopy (TEM) [2, 3] has benefited tremendously in recent years from subtle instrumentation advances, and individual heavy (high atomic number) atoms can now be detected by TEM [4 - 7] even when embedded within a semiconductor material [8, 9]. However, detecting an individual low atomic number atom, for example carbon or even hydrogen, is still extremely challenging, if not impossible, via conventional TEM due to the very low contrast of light elements [2, 3, 10 - 12]. Here we demonstrate a means to observe, by conventional transmision electron microscopy, even the smallest atoms and molecules: On a clean single-layer graphene membrane, adsorbates such as atomic hydrogen and carbon can be seen as if they were suspended in free space. We directly image such individual adatoms, along with carbon chains and vacancies, and investigate their dynamics in real time. These techniques open a way to reveal dynamics of more complex chemical reactions or identify the atomic-scale structure of unknown adsorbates. In addition, the study of atomic scale defects in graphene may provide insights for nanoelectronic applications of this interesting material.Comment: 9 pages manuscript and figures, 9 pages supplementary informatio

Information heat engine: converting information to energy by feedback control

In 1929, Leo Szilard invented a feedback protocol in which a hypothetical intelligence called Maxwell's demon pumps heat from an isothermal environment and transduces it to work. After an intense controversy that lasted over eighty years; it was finally clarified that the demon's role does not contradict the second law of thermodynamics, implying that we can convert information to free energy in principle. Nevertheless, experimental demonstration of this information-to-energy conversion has been elusive. Here, we demonstrate that a nonequilibrium feedback manipulation of a Brownian particle based on information about its location achieves a Szilard-type information-energy conversion. Under real-time feedback control, the particle climbs up a spiral-stairs-like potential exerted by an electric field and obtains free energy larger than the amount of work performed on it. This enables us to verify the generalized Jarzynski equality, or a new fundamental principle of "information-heat engine" which converts information to energy by feedback control.Comment: manuscript including 7 pages and 4 figures and supplementary material including 6 pages and 8 figure

Millennial scale persistence of organic carbon bound to iron in Arctic marine sediments

Burial of organic material in marine sediments represents a dominant natural mechanism of long-term carbon sequestration globally, but critical aspects of this carbon sink remain unresolved. Investigation of surface sediments led to the proposition that on average 10-20% of sedimentary organic carbon is stabilised and physically protected against microbial degradation through binding to reactive metal (e.g. iron and manganese) oxides. Here we examine the long-term efficiency of this rusty carbon sink by analysing the chemical composition of sediments and pore waters from four locations in the Barents Sea. Our findings show that the carbon-iron coupling persists below the uppermost, oxygenated sediment layer over thousands of years. We further propose that authigenic coprecipitation is not the dominant factor of the carbon-iron bounding in these Arctic shelf sediments and that a substantial fraction of the organic carbon is already bound to reactive iron prior deposition on the seafloor

Transit Timing and Duration Variations for the Discovery and Characterization of Exoplanets

Transiting exoplanets in multi-planet systems have non-Keplerian orbits which can cause the times and durations of transits to vary. The theory and observations of transit timing variations (TTV) and transit duration variations (TDV) are reviewed. Since the last review, the Kepler spacecraft has detected several hundred perturbed planets. In a few cases, these data have been used to discover additional planets, similar to the historical discovery of Neptune in our own Solar System. However, the more impactful aspect of TTV and TDV studies has been characterization of planetary systems in which multiple planets transit. After addressing the equations of motion and parameter scalings, the main dynamical mechanisms for TTV and TDV are described, with citations to the observational literature for real examples. We describe parameter constraints, particularly the origin of the mass/eccentricity degeneracy and how it is overcome by the high-frequency component of the signal. On the observational side, derivation of timing precision and introduction to the timing diagram are given. Science results are reviewed, with an emphasis on mass measurements of transiting sub-Neptunes and super-Earths, from which bulk compositions may be inferred.Comment: Revised version. Invited review submitted to 'Handbook of Exoplanets,' Exoplanet Discovery Methods section, Springer Reference Works, Juan Antonio Belmonte and Hans Deeg, Eds. TeX and figures may be found at https://github.com/ericagol/TTV_revie

Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows

Background: Predicting progression from a stage of Mild Cognitive Impairment to dementia is a major pursuit in current research. It is broadly accepted that cognition declines with a continuum between MCI and dementia. As such, cohorts of MCI patients are usually heterogeneous, containing patients at different stages of the neurodegenerative process. This hampers the prognostic task. Nevertheless, when learning prognostic models, most studies use the entire cohort of MCI patients regardless of their disease stages. In this paper, we propose a Time Windows approach to predict conversion to dementia, learning with patients stratified using time windows, thus fine-tuning the prognosis regarding the time to conversion. Methods: In the proposed Time Windows approach, we grouped patients based on the clinical information of whether they converted (converter MCI) or remained MCI (stable MCI) within a specific time window. We tested time windows of 2, 3, 4 and 5 years. We developed a prognostic model for each time window using clinical and neuropsychological data and compared this approach with the commonly used in the literature, where all patients are used to learn the models, named as First Last approach. This enables to move from the traditional question "Will a MCI patient convert to dementia somewhere in the future" to the question "Will a MCI patient convert to dementia in a specific time window". Results: The proposed Time Windows approach outperformed the First Last approach. The results showed that we can predict conversion to dementia as early as 5 years before the event with an AUC of 0.88 in the cross-validation set and 0.76 in an independent validation set. Conclusions: Prognostic models using time windows have higher performance when predicting progression from MCI to dementia, when compared to the prognostic approach commonly used in the literature. Furthermore, the proposed Time Windows approach is more relevant from a clinical point of view, predicting conversion within a temporal interval rather than sometime in the future and allowing clinicians to timely adjust treatments and clinical appointments.FCT under the Neuroclinomics2 project [PTDC/EEI-SII/1937/2014, SFRH/BD/95846/2013]; INESC-ID plurianual [UID/CEC/50021/2013]; LASIGE Research Unit [UID/CEC/00408/2013

Metabolomics to unveil and understand phenotypic diversity between pathogen populations

Visceral leishmaniasis is caused by a parasite called Leishmania donovani, which every year infects about half a million people and claims several thousand lives. Existing treatments are now becoming less effective due to the emergence of drug resistance. Improving our understanding of the mechanisms used by the parasite to adapt to drugs and achieve resistance is crucial for developing future treatment strategies. Unfortunately, the biological mechanism whereby Leishmania acquires drug resistance is poorly understood. Recent years have brought new technologies with the potential to increase greatly our understanding of drug resistance mechanisms. The latest mass spectrometry techniques allow the metabolome of parasites to be studied rapidly and in great detail. We have applied this approach to determine the metabolome of drug-sensitive and drug-resistant parasites isolated from patients with leishmaniasis. The data show that there are wholesale differences between the isolates and that the membrane composition has been drastically modified in drug-resistant parasites compared with drug-sensitive parasites. Our findings demonstrate that untargeted metabolomics has great potential to identify major metabolic differences between closely related parasite strains and thus should find many applications in distinguishing parasite phenotypes of clinical relevance