Machine learning and data decompositions for complex networked dynamical systems

Thesis (Ph.D.)--University of Washington, 2016-08

Data-driven and data-oriented methods for materials science and technologies

The discovery of new materials and their functions has always been a fundamental component of technological progress. Nowadays, the quest for new materials is stronger than ever: sustainability, medicine, robotics and electronics are all key assets which depend on the ability to create specifically tailored materials. However, designing materials with desired properties is a difficult task, and the complexity of the discipline makes it difficult to identify general criteria. While scientists developed a set of best practices (often based on experience and expertise), this is still a trial-and-error process. This becomes even more complex when dealing with advanced functional materials. Their properties depend on structural and morphological features, which in turn depend on fabrication procedures and environment, and subtle alterations leads to dramatically different results. Because of this, materials modeling and design is one of the most prolific research fields. Many techniques and instruments are continuously developed to enable new possibilities, both in the experimental and computational realms. Scientists strive to enforce cutting-edge technologies in order to make progress. However, the field is strongly affected by unorganized file management, proliferation of custom data formats and storage procedures, both in experimental and computational research. Results are difficult to find, interpret and re-use, and a huge amount of time is spent interpreting and re-organizing data. This also strongly limit the application of data-driven and machine learning techniques. This work introduces possible solutions to the problems described above. Specifically, it talks about developing features for specific classes of advanced materials and use them to train machine learning models and accelerate computational predictions for molecular compounds; developing method for organizing non homogeneous materials data; automate the process of using devices simulations to train machine learning models; dealing with scattered experimental data and use them to discover new patterns.

Internet of healthcare (law): privacy and data protection aspects in an internet of everything

The purpose of this research study is to discuss privacy and data protection-related regulatory and compliance challenges posed by digital transformation in healthcare in the wake of the COVID-19 pandemic. The public health crisis accelerated the development of patient-centred remote/hybrid healthcare delivery models that make increased use of telehealth services and related digital solutions. The large-scale uptake of IoT-enabled medical devices and wellness applications, and the offering of healthcare services via healthcare platforms (online doctor marketplaces) have catalysed these developments. However, the use of new enabling technologies (IoT, AI) and the platformisation of healthcare pose complex challenges to the protection of patient’s privacy and personal data. This happens at a time when the EU is drawing up a new regulatory landscape for the use of data and digital technologies. Against this background, the study presents an interdisciplinary (normative and technology-oriented) critical assessment on how the new regulatory framework may affect privacy and data protection requirements regarding the deployment and use of Internet of Health Things (hardware) devices and interconnected software (AI systems). The study also assesses key privacy and data protection challenges that affect healthcare platforms (online doctor marketplaces) in their offering of video API-enabled teleconsultation services and their (anticipated) integration into the European Health Data Space. The overall conclusion of the study is that regulatory deficiencies may create integrity risks for the protection of privacy and personal data in telehealth due to uncertainties about the proper interplay, legal effects and effectiveness of (existing and proposed) EU legislation. The proliferation of normative measures may increase compliance costs, hinder innovation and ultimately, deprive European patients from state-of-the-art digital health technologies, which is paradoxically, the opposite of what the EU plans to achieve.

The BRAzilian Seismographic Integrated Systems (BRASIS): infrastructure and data management

In geophysics and seismology, raw data need to be processed to generate useful information that can be turned into knowledge by researchers. The number of sensors that are acquiring raw data is increasing rapidly. Without good data management systems, more time can be spent in querying and preparing datasets for analyses than in acquiring raw data. Also, a lot of good quality data acquired at great effort can be lost forever if they are not correctly stored. Local and international cooperation will probably be reduced, and a lot of data will never become scientific knowledge. For this reason, the Seismological Laboratory of the Institute of Astronomy, Geophysics and Atmospheric Sciences at the University of Sao Paulo (IAG-USP) has concentrated fully on its data management system. This report describes the efforts of the IAG-USP to set up a seismology data management system to facilitate local and international cooperation.

Crystallization, data collection and data processing of maltose-binding protein (MalE) from the phytopathogen Xanthomonas axonopodis pv. citri

Maltose-binding protein is the periplasmic component of the ABC transporter responsible for the uptake of maltose/maltodextrins. The Xanthomonas axonopodis pv. citri maltose-binding protein MalE has been crystallized at 293 Kusing the hanging-drop vapour-diffusion method. The crystal belonged to the primitive hexagonal space group P6(1)22, with unit-cell parameters a = 123.59, b = 123.59, c = 304.20 angstrom, and contained two molecules in the asymetric unit. It diffracted to 2.24 angstrom resolution.

Knowledge discovery and data mining in biological databases

The new technologies for Knowledge Discovery from Databases (KDD) and data mining promise to bring new insights into a voluminous growing amount of biological data. KDD technology is complementary to laboratory experimentation and helps speed up biological research. This article contains an introduction to KDD, a review of data mining tools, and their biological applications. We discuss the domain concepts related to biological data and databases, as well as current KDD and data mining developments in biology.

Molecular immunology databases and data repositories

Over recent years databases have become an extremely important resource for biomedical research. Immunology research is increasingly dependent on access to extensive biological databases to extract existing information, plan experiments, and analyse experimental results. This review describes 15 immunological databases that have appeared over the last 30 years. In addition, important issues regarding database design and the potential for misuse of information contained within these databases are discussed. Access pointers are provided for the major immunological databases and also for a number of other immunological resources accessible over the World Wide Web (WWW). (C) 2000 Elsevier Science B.V. All rights reserved.

Effect of coinfection with STDs and of STD treatment on HIV shedding in genital-tract secretions - Systematic review and data synthesis

Objective: To determine whether coinfection with sexually transmitted diseases (STD) increases HIV shedding in genital-tract secretions, and whether STD treatment reduces this shedding. Design: Systematic review and data synthesis of cross-sectional and cohort studies meeting. predefined quality criteria. Main Outcome Measures: Proportion of patients with and without a STD who had detectable HIV in genital secretions, HIV toad in genital secretions, or change following STD treatment. Results: Of 48 identified studies, three cross-sectional and three cohort studies were included. HIV was detected significantly more frequently in participants infected with Neisseria gonorrhoeae (125 of 309 participants, 41%) than in those without N gonorrhoeae infection (311 of 988 participants, 32%; P = 0.004). HIV was not significantly more frequently detected in persons infected with Chlamydia trachomatis (28 of 67 participants, 42%) than in those without C trachomatis infection (375 of 1149 participants, 33%; P = 0.13). Median HIV load reported in only one study was greater in men with urethritis (12.4 x 10(4) versus 1.51 x 10(4) copies/ml; P = 0.04). In the only cohort study in which this could be fully assessed, treatment of women with any STD reduced the proportion of those with detectable HIV from 39% to 29% (P = 0.05), whereas this proportion remained stable among controls (15-17%), A second cohort study reported fully on HIV load; among men with urethritis, viral load fell from 12.4 to 4.12 x 10(4) copies/ml 2 weeks posttreatment, whereas viral load remained stable in those without urethritis. Conclusion: Few high-quality studies were found. HIV is detected moderately more frequently in genital secretions of men and women with a STD, and HIV load is substantially increased among men with urethritis, Successful STD treatment reduces both of these parameters, but not to control levels. More high-quality studies are needed to explore this important relationship further.

Magnetic field effects on the conductivity of organic bipolar and unipolar devices at room temperature

Magnetic field effects on the conductivity of different types of organic devices: undoped and dye doped aluminium (III) 8-hydroxyquinoline (Alq(3))-based organic light emitting diodes (OLEDs), electron-only Alq(3)-based diodes, and a hole-only N,N`-diphenyl-N,N`-bis(1-naphthyl)1,1`-biphenyl-4,4`-diamine (alpha-NPD)-based diode were studied at room temperature. Only negative magnetoresistance (MR) was observed for the Alq(3)-based devices. The addition of a rubrene dye in Alq(3)-based OLEDs quenches the MR by a factor of 5. The alpha-NPD hole-only device showed only positive MR. Our results are discussed with respect to the actual models for MR in organic semiconductors. Our results are in good agreement with the bipolaron model. (C) 2009 Elsevier B.V. All rights reserved.

Electromyographic standardized indices in healthy Brazilian young adults and data reproducibility

P>The determination of normal parameters is an important procedure in the evaluation of the stomatognathic system. We used the surface electromyography standardization protocol described by Ferrario et al. (J Oral Rehabil. 2000;27:33-40, 2006;33:341) to determine reference values of the electromyographic standardized indices for the assessment of muscular symmetry (left and right side, percentage overlapping coefficient, POC), potential lateral displacing components (unbalanced contractile activities of contralateral masseter and temporalis muscles, TC), relative activity (most prevalent pair of masticatory muscles, ATTIV) and total activity (integrated areas of the electromyographic potentials over time, IMPACT) in healthy Brazilian young adults, and the relevant data reproducibility. Electromyography of the right and left masseter and temporalis muscles was performed during maximum teeth clenching in 20 healthy subjects (10 women and 10 men, mean age 23 years, s.d. 3), free from periodontal problems, temporomandibular disorders, oro-facial myofunctional disorder, and with full permanent dentition (28 teeth at least). Data reproducibility was computed for 75% of the sample. The values obtained were POC Temporal (88 center dot 11 +/- 1 center dot 45%), POC masseter (87 center dot 11 +/- 1 center dot 60%), TC (8 center dot 79 +/- 1 center dot 20%), ATTIV (-0 center dot 33 +/- 9 center dot 65%) and IMPACT (110 center dot 40 +/- 23 center dot 69 mu V/mu V center dot s %). There were no statistical differences between test and retest values (P > 0 center dot 05). The Technical Errors of Measurement (TEM) for 50% of subjects assessed during the same session were 1 center dot 5, 1 center dot 39, 1 center dot 06, 3 center dot 83 and 10 center dot 04. For 25% of the subjects assessed after a 6-month interval, the TEM were 0 center dot 80, 1 center dot 03, 0 center dot 73, 12 center dot 70 and 19 center dot 10. For all indices, there was good reproducibility. These electromyographic indices could be used in the assessment of patients with stomatognathic dysfunction.

Effects of feeding high levels of cactus (Opuntia ficus-indica Mill) cladodes on urinary output and electrolyte excretion in goats

A study was conducted to determine the effects of feeding spineless cactus cladodes on diuresis and urinary electrolyte excretion in goats. Five bucks were used in a 5 x 5 Latin square experiment with 17-day periods. Experimental diets contained (g/kg dry matter (DM) basis) 370, 470, 570, 670, and 770 spineless cactus cladodes. Water consumption from feed and urine output increased linearly (P<0.05) as the level of cactus cladodes in the diet increased. However, water intake from drinking was low and unaffected by cactus cladode level. Creatinine clearance and urinary Na excretion were similar for all dietary treatments while K excretion decrease linearly (P<0.05) as the level of cactus cladodes in the diet increased. Feeding cactus cladodes caused diuresis and reduced urinary K excretion in goats. Possible reasons for these effects include water over-consumption from cactus cladodes and high dietary K intake. (C) 2007 Elsevier B.V. All rights reserved.

Optimal input states and feedback for interferometric phase estimation

We derive optimal N-photon two-mode input states for interferometric phase measurements. Under canonical measurements the phase variance scales as N-2 for these states, as compared to N-1 or N-1/2 for states considered bq previous authors. We prove, that it is not possible to realize the canonical measurement by counting photons in the outputs of the interferometer, even if an adjustable auxiliary phase shift is allowed in the interferometer. However. we introduce a feedback algorithm based on Bayesian inference to control this auxiliary phase shift. This makes the measurement close to a canonical one, with a phase variance scaling slightly above N-2. With no feedback, the best result (given that the phase to be measured is completely unknown) is a scaling of N-1. For optimal input states having up to four photons, our feedback scheme is the best possible one, but for higher photon numbers more complicated schemes perform marginally better.

Breeding for low input conditions and consequences for participatory plant breeding: Examples from tropical maize and wheat

Participatory plant breeding (PPB) has been suggested as an effective alternative to formal plant breeding (FPB) as a breeding strategy for achieving productivity gains under low input conditions. With genetic progress through PPB and FPB being determined by the same genetic variables, the likelihood of success of PPB approaches applied in low input target conditions was analyzed using two case studies from FPB that have resulted in significant productivity gains under low input conditions: (1) breeding tropical maize for low input conditions by CIMMYT, and (2) breeding of spring wheat for the highly variable low input rainfed farming systems in Australia. In both cases, genetic improvement was an outcome of long-term investment in a sustained research effort aimed at understanding the detail of the important environmental constraints to productivity and the plant requirements for improved adaptation to the identified constraints, followed up by the design and continued evaluation of efficient breeding strategies. The breeding strategies used differed between the two case studies but were consistent in their attention to the key determinants of response to selection: (1) ensuring adequate sources of genetic variation and high selection pressures for the important traits at all stages of the breeding program, (2) use of experimental procedures to achieve high levels of heritability in the breeding trials, and (3) testing strategies that achieved a high genetic correlation between performance of germplasm in the breeding trials and under on-farm conditions. The implications of the outcomes from these FPB case studies for realizing the positive motivations for adopting PPB strategies are discussed with particular reference for low input target environment conditions.