First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

Modelling the Provenance of Data in Autonomous Systems

Determining the provenance of data, i.e. the process that led to that data, is vital in many disciplines. For example, in science, the process that produced a given result must be demonstrably rigorous for the result to be deemed reliable. A provenance system supports applications in recording adequate documentation about process executions to answer queries regarding provenance, and provides functionality to perform those queries. Several provenance systems are being developed, but all focus on systems in which the components are textitreactive, for example Web Services that act on the basis of a request, job submission system, etc. This limitation means that questions regarding the motives of autonomous actors, or textitagents, in such systems remain unanswerable in the general case. Such questions include: who was ultimately responsible for a given effect, what was their reason for initiating the process and does the effect of a process match what was intended to occur by those initiating the process? In this paper, we address this limitation by integrating two solutions: a generic, re-usable framework for representing the provenance of data in service-oriented architectures and a model for describing the goal-oriented delegation and engagement of agents in multi-agent systems. Using these solutions, we present algorithms to answer common questions regarding responsibility and success of a process and evaluate the approach with a simulated healthcare example.

Newly Automated System For Integrated Assessment Of The Conditions Of Underwater Gas Pipelines

An underwater gas pipeline is the portion of the pipeline that crosses a river beneath its bottom. Underwater gas pipelines are subject to increasing dangers as time goes by. An accident at an underwater gas pipeline can lead to technological and environmental disaster on the scale of an entire region. Therefore, timely troubleshooting of all underwater gas pipelines in order to prevent any potential accidents will remain a pressing task for the industry. The most important aspect of resolving this challenge is the quality of the automated system in question. Now the industry doesn't have any automated system that fully meets the needs of the experts working in the field maintaining underwater gas pipelines. Principle Aim of this Research: This work aims to develop a new system of automated monitoring which would simplify the process of evaluating the technical condition and decision making on planning and preventive maintenance and repair work on the underwater gas pipeline. Objectives: Creation a shared model for a new, automated system via IDEF3; Development of a new database system which would store all information about underwater gas pipelines; Development a new application that works with database servers, and provides an explanation of the results obtained from the server; Calculation of the values MTBF for specified pipelines based on quantitative data obtained from tests of this system. Conclusion: The new, automated system PodvodGazExpert has been developed for timely and qualitative determination of the physical conditions of underwater gas pipeline; The basis of the mathematical analysis of this new, automated system uses principal component analysis method; The process of determining the physical condition of an underwater gas pipeline with this new, automated system increases the MTBF by a factor of 8.18 above the existing system used today in the industry.

Synthesis, characterization, and application of modified silica in the removal and preconcentration of lead ions from natural river water

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Effect of rinsing with water immediately after neutral gel and foam fluoride topical application on enamel remineralization: An in situ study

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

An assessment approach for application of spermatic data in phylogenetic analyses: Within the genus Moenkhausia Eigenmann, 1903 (Characiformes: Characidae)

Spermiogenesis and sperm ultrastructure from 21 species of Moenkhausia and others related genera are described. To evaluate the phylogenetic signals, 18 unordered characters were utilized in implied weighting analysis through the program TNT 1.1. Four variations of spermiogenesis were found. In the earliest spermatids, the nucleus can be positioned lateral, eccentric, strongly eccentric or nearly medial in relation to the distal centriole. The nuclear rotation can be present or absent. These spermiogenesis processes are related or intermediate to Type I and Type III. Taking into account the degrees of nuclear rotation during the spermiogenesis and other characteristics, distinct forms of spermatozoa are observed among the species analyzed. The phylogenetic analysis yielded a single most parsimonious tree with fit value 2.70000 and the topology obtained founds Moenkhausia as non-monophyletic. However, some hypothesis of relationships previously proposed viz the clade 20, which contains the type species Moenkhausia xinguensis, is recovered herein. This clade is supported by five synapomorphies, and it allows the supposition that these species constitute a monophyletic group. The whole topology is presented and discussed. © 2012 The Authors. Acta Zoologica © 2012 The Royal Swedish Academy of Sciences.

Hydrogeochemical monitoring and modelling of saltwater intrusion in lowlands (Ferrara, IT)

Because of the potentially irreversible impact of groundwater quality deterioration in the Ferrara coastal aquifer, answers concerning the assessment of the extent of the salinization problem, the understanding of the mechanisms governing salinization processes, and the sustainability of the current water resources management are urgent. In this light, the present thesis aims to achieve the following objectives: Characterization of the lowland coastal aquifer of Ferrara: hydrology, hydrochemistry and evolution of the system The importance of data acquisition techniques in saltwater intrusion monitoring Predicting salinization trends in the lowland coastal aquifer Ammonium occurrence in a salinized lowland coastal aquifer Trace elements mobility in a saline coastal aquifer

Dynamics of coastal aquifers: data-driven forecasting and risk analysis

This work is focused on the study of saltwater intrusion in coastal aquifers, and in particular on the realization of conceptual schemes to evaluate the risk associated with it. Saltwater intrusion depends on different natural and anthropic factors, both presenting a strong aleatory behaviour, that should be considered for an optimal management of the territory and water resources. Given the uncertainty of problem parameters, the risk associated with salinization needs to be cast in a probabilistic framework. On the basis of a widely adopted sharp interface formulation, key hydrogeological problem parameters are modeled as random variables, and global sensitivity analysis is used to determine their influence on the position of saltwater interface. The analyses presented in this work rely on an efficient model reduction technique, based on Polynomial Chaos Expansion, able to combine the best description of the model without great computational burden. When the assumptions of classical analytical models are not respected, and this occurs several times in the applications to real cases of study, as in the area analyzed in the present work, one can adopt data-driven techniques, based on the analysis of the data characterizing the system under study. It follows that a model can be defined on the basis of connections between the system state variables, with only a limited number of assumptions about the "physical" behaviour of the system.

Identification of glacial meltwater runoff in a karstic environment and its implication for present and future water availability

Glaciers all over the world are expected to continue to retreat due to the global warming throughout the 21st century. Consequently, future seasonal water availability might become scarce once glacier areas have declined below a certain threshold affecting future water management strategies. Particular attention should be paid to glaciers located in a karstic environment, as parts of the meltwater can be drained by underlying karst systems, making it difficult to assess water availability. In this study tracer experiments, karst modeling and glacier melt modeling are combined in order to identify flow paths in a high alpine, glacierized, karstic environment (Glacier de la Plaine Morte, Switzerland) and to investigate current and predict future downstream water availability. Flow paths through the karst underground were determined with natural and fluorescent tracers. Subsequently, geologic information and the findings from tracer experiments were assembled in a karst model. Finally, glacier melt projections driven with a climate scenario were performed to discuss future water availability in the area surrounding the glacier. The results suggest that during late summer glacier meltwater is rapidly drained through well-developed channels at the glacier bottom to the north of the glacier, while during low flow season meltwater enters into the karst and is drained to the south. Climate change projections with the glacier melt model reveal that by the end of the century glacier melt will be significantly reduced in the summer, jeopardizing water availability in glacier-fed karst springs.

Stratigraphic analysis of lake level fluctuations in Lake Ohrid: an integration of high resolution hydro-acoustic data and sediment cores

Abstract. Ancient Lake Ohrid is a steep-sided, oligotrophic, karst lake that was tectonically formed most likely within the Pliocene and often referred to as a hotspot of endemic biodiversity. This study aims on tracing significant lake level fluctuations at Lake Ohrid using high-resolution acoustic data in combination with lithological, geochemical, and chronological information from two sediment cores recovered from sub-aquatic terrace levels at ca. 32 and 60m water depth. According to our data, significant lake level fluctuations with prominent lowstands of ca. 60 and 35m below the present water level occurred during Marine Isotope Stage (MIS) 6 and MIS 5, respectively. The effect of these lowstands on biodiversity in most coastal parts of the lake is negligible, due to only small changes in lake surface area, coastline, and habitat. In contrast, biodiversity in shallower areas was more severely affected due to disconnection of today sublacustrine springs from the main water body. Multichannel seismic data from deeper parts of the lake clearly image several clinoform structures stacked on top of each other. These stacked clinoforms indicate significantly lower lake levels prior to MIS 6 and a stepwise rise of water level with intermittent stillstands since its existence as water-filled body, which might have caused enhanced expansion of endemic species within Lake Ohrid.

The Response of a Small Stream in the Lesni Potok Forested Catchment, Central Czech Republic, to a Short-Term In-Stream Acidification

Lesni Potok stream drains a forested headwater catchment in the central Czech Republic. It was artificially acidified with hydrochloric acid (HCl) for four hours to assess the role of stream substrate in acid-neutralisation and recovery. The pH was lowered from 4.7 to 3.2. Desorption of Ca and MP and desorption or solution of Al dominated acid-neutralisation; Al mobilisation was more important later. The stream substrate released 4.542 meq Ca, 1, 184 meq Mg, and 2,329 meq Al over a 45 in long and I in wide stream segment, smaller amounts of Be. Cd, Fe, and Mn were released. Adsorption of SO42- and desorption of F- occurred during the acidification phase of the experiment. The exchange reactions were rapidly reversible for Ca, Mg and SO42- but not symmetric as the substrate resorbed 1083, 790 and 0 meq Ca, Mg, and Al. respectively, in a 4-hour recovery period. Desorption of SO42- occurred during the resorption of Ca and Mg. These exchange and dissolution reactions delay acidification, diminish the pH depression and retard recovery from episodic acidification. The behaviour of the stream substrate-water interaction resembles that for soil-soil water interactions. A mathematical dynamic mass-balance based model, MASS (Modelling Acidification of Stream Sediments), was developed which simulates the adsorption and desorption of base cations during the experiment and was successfully calibrated to the experimental data.

Theoretical Calving Rates from Glaciers Along Ice Walls Grounded in Water of Variable Depths

Calving has been studied for glaciers ranging from slow polar glaciers that calve on dry land, such as on Deception Island (63.0-degrees-S, 60.6-degrees-W) in Antarctica, through temperate Alaskan tide-water glaciers, to fast outlet glaciers that float in fiords and calve in deep water, such as Jakobshavns Isbrae (69.2-degrees-N, 49.9-degrees-W) in Greenland. Calving from grounded ice walls and floating ice shelves is the main ablation mechanism for the Antarctic and Greenland ice sheets, as it was along marine and lacustrine margins of former Pleistocene ice sheets, and is for tide-water and polar glaciers. Yet, the theory of ice calving is underdeveloped because of inherent dangers in obtaining field data to test and constrain calving models. An attempt is made to develop a calving theory for ice walls grounded in water of variable depth, and to relate slab calving from ice walls to tabular calving from ice shelves. A calving law is derived in which calving rates from ice walls are controled by bending creep behind the ice wall, and depend on wall height h, forward bending angle-theta, crevasse distance c behind the ice wall and depth d of water in front of the ice wall. Reasonable agreement with calving rates reported by Brown and others (1982) for Alaskan tide-water glaciers is obtained when c depends on wall height, wall height above water and water depth. More data are needed to determine which of these dependencies is correct. A calving ratio c/h is introduced to understand the transition from slab calving to tabular calving as water deepens and the calving glacier becomes afloat.

Liquid–Vapor Interface of Formic Acid Solutions in Salt Water: A Comparison of Macroscopic Surface Tension and Microscopic in Situ X-ray Photoelectron Spectroscopy Measurements

The liquid–vapor interface is difficult to access experimentally but is of interest from a theoretical and applied point of view and has particular importance in atmospheric aerosol chemistry. Here we examine the liquid–vapor interface for mixtures of water, sodium chloride, and formic acid, an abundant chemical in the atmosphere. We compare the results of surface tension and X-ray photoelectron spectroscopy (XPS) measurements over a wide range of formic acid concentrations. Surface tension measurements provide a macroscopic characterization of solutions ranging from 0 to 3 M sodium chloride and from 0 to over 0.5 mole fraction formic acid. Sodium chloride was found to be a weak salting out agent for formic acid with surface excess depending only slightly on salt concentration. In situ XPS provides a complementary molecular level description about the liquid–vapor interface. XPS measurements over an experimental probe depth of 51 Å gave the C 1s to O 1s ratio for both total oxygen and oxygen from water. XPS also provides detailed electronic structure information that is inaccessible by surface tension. Density functional theory calculations were performed to understand the observed shift in C 1s binding energies to lower values with increasing formic acid concentration. Part of the experimental −0.2 eV shift can be assigned to the solution composition changing from predominantly monomers of formic acid to a combination of monomers and dimers; however, the lack of an appropriate reference to calibrate the absolute BE scale at high formic acid mole fraction complicates the interpretation. Our data are consistent with surface tension measurements yielding a significantly more surface sensitive measurement than XPS due to the relatively weak propensity of formic acid for the interface. A simple model allowed us to replicate the XPS results under the assumption that the surface excess was contained in the top four angstroms of solution.

Automatic X-ray landmark detection and shape segmentation via data-driven joint estimation of image displacements

In this paper, we propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. To detect landmarks, we estimate the displacements from some randomly sampled image patches to the (unknown) landmark positions, and then we integrate these predictions via a voting scheme. Our key contribution is a new algorithm for estimating these displacements. Different from other methods where each image patch independently predicts its displacement, we jointly estimate the displacements from all patches together in a data driven way, by considering not only the training data but also geometric constraints on the test image. The displacements estimation is formulated as a convex optimization problem that can be solved efficiently. Finally, we use the sparse shape composition model as the a priori information to regularize the landmark positions and thus generate the segmented shape contour. We validate our method on X-ray image datasets of three different anatomical structures: complete femur, proximal femur and pelvis. Experiments show that our method is accurate and robust in landmark detection, and, combined with the shape model, gives a better or comparable performance in shape segmentation compared to state-of-the art methods. Finally, a preliminary study using CT data shows the extensibility of our method to 3D data.