Raman and infrared spectra of dimethyl ether 13C-isotopologue (CH3O13CH3) from a CCSD(T) potential energy surface

So far, no experimental data of the infrared and Raman spectra of 13C isotopologue of dimethyl ether are available. With the aim of providing some clues of its low-lying vibrational bands and with the hope of contributing in a next spectral analysis, a number of vibrational transition frequencies below 300 cm−1 of the infrared spectrum and around 400 cm−1 of the Raman spectrum have been predicted and their assignments were proposed. Calculations were carried out through an ab initio three dimensional potential energy surface based on a previously reported one for the most abundant dimethyl ether isotopologue (M. Villa et al., J. Phys. Chem. A 115 (2011) 13573). The potential function was vibrationally corrected and computed with a highly correlated CCSD(T) method involving the COC bending angle and the two large amplitude CH3 internal rotation degrees of freedom. Also, the Hamiltonian parameters could represent a support for the spectral characterization of this species. Although the computed vibrational term values are expected to be very accurate, an empirical adjustment of the Hamiltonian has been performed with the purpose of anticipating some workable corrections to any possible divergence of the vibrational frequencies. Also, the symmetry breaking derived from the isotopic substitution of 13C in the dimethyl ether was taken into account when the symmetrization procedure was applied.

Shaking table tests of structures with hysteretic dampers: experimental results vs. prediction using non-linear static methods

The use of seismic hysteretic dampers for passive control is increasing exponentially in recent years for both new and existing buildings. In order to utilize hysteretic dampers within a structural system, it is of paramount importance to have simplified design procedures based upon knowledge gained from theoretical studies and validated with experimental results. Non-linear Static Procedures (NSPs) are presented as an alternative to the force-based methods more common nowadays. The application of NSPs to conventional structures has been well established; yet there is a lack of experimental information on how NSPs apply to systems with hysteretic dampers. In this research, several shaking table tests were conducted on two single bay and single story 1:2 scale structures with and without hysteretic dampers. The maximum response of the structure with dampers in terms of lateral displacement and base shear obtained from the tests was compared with the prediction provided by three well-known NSPs: (1) the improved version of the Capacity Spectrum Method (CSM) from FEMA 440; (2) the improved version of the Displacement Coefficient Method (DCM) from FEMA 440; and (3) the N2 Method implemented in Eurocode 8. In general, the improved version of the DCM and N2 methods are found to provide acceptable accuracy in prediction, but the CSM tends to underestimate the response.

Remote sensing of LAI, chlorophyll and leaf nitrogen pools of crop- and grasslands in five European landscapes.

Leaf nitrogen and leaf surface area influence the exchange of gases between terrestrial ecosystems and the atmosphere, and play a significant role in the global cycles of carbon, nitrogen and water. The purpose of this study is to use field-based and satellite remote-sensing-based methods to assess leaf nitrogen pools in five diverse European agricultural landscapes located in Denmark, Scotland (United Kingdom), Poland, the Netherlands and Italy. REGFLEC (REGularized canopy reFLECtance) is an advanced image-based inverse canopy radiative transfer modelling system which has shown proficiency for regional mapping of leaf area index (LAI) and leaf chlorophyll (CHLl) using remote sensing data. In this study, high spatial resolution (10–20 m) remote sensing images acquired from the multispectral sensors aboard the SPOT (Satellite For Observation of Earth) satellites were used to assess the capability of REGFLEC for mapping spatial variations in LAI, CHLland the relation to leaf nitrogen (Nl) data in five diverse European agricultural landscapes. REGFLEC is based on physical laws and includes an automatic model parameterization scheme which makes the tool independent of field data for model calibration. In this study, REGFLEC performance was evaluated using LAI measurements and non-destructive measurements (using a SPAD meter) of leaf-scale CHLl and Nl concentrations in 93 fields representing crop- and grasslands of the five landscapes. Furthermore, empirical relationships between field measurements (LAI, CHLl and Nl and five spectral vegetation indices (the Normalized Difference Vegetation Index, the Simple Ratio, the Enhanced Vegetation Index-2, the Green Normalized Difference Vegetation Index, and the green chlorophyll index) were used to assess field data coherence and to serve as a comparison basis for assessing REGFLEC model performance. The field measurements showed strong vertical CHLl gradient profiles in 26% of fields which affected REGFLEC performance as well as the relationships between spectral vegetation indices (SVIs) and field measurements. When the range of surface types increased, the REGFLEC results were in better agreement with field data than the empirical SVI regression models. Selecting only homogeneous canopies with uniform CHLl distributions as reference data for evaluation, REGFLEC was able to explain 69% of LAI observations (rmse = 0.76), 46% of measured canopy chlorophyll contents (rmse = 719 mg m−2) and 51% of measured canopy nitrogen contents (rmse = 2.7 g m−2). Better results were obtained for individual landscapes, except for Italy, where REGFLEC performed poorly due to a lack of dense vegetation canopies at the time of satellite recording. Presence of vegetation is needed to parameterize the REGFLEC model. Combining REGFLEC- and SVI-based model results to minimize errors for a "snap-shot" assessment of total leaf nitrogen pools in the five landscapes, results varied from 0.6 to 4.0 t km−2. Differences in leaf nitrogen pools between landscapes are attributed to seasonal variations, extents of agricultural area, species variations, and spatial variations in nutrient availability. In order to facilitate a substantial assessment of variations in Nl pools and their relation to landscape based nitrogen and carbon cycling processes, time series of satellite data are needed. The upcoming Sentinel-2 satellite mission will provide new multiple narrowband data opportunities at high spatio-temporal resolution which are expected to further improve remote sensing capabilities for mapping LAI, CHLl and Nl.

A Hierarchical Tracking Strategy for Vision-Based Applications On-Board UAVs

In this paper, we apply a hierarchical tracking strategy of planar objects (or that can be assumed to be planar) that is based on direct methods for vision-based applications on-board UAVs. The use of this tracking strategy allows to achieve the tasks at real-time frame rates and to overcome problems posed by the challenging conditions of the tasks: e.g. constant vibrations, fast 3D changes, or limited capacity on-board. The vast majority of approaches make use of feature-based methods to track objects. Nonetheless, in this paper we show that although some of these feature-based solutions are faster, direct methods can be more robust under fast 3D motions (fast changes in position), some changes in appearance, constant vibrations (without requiring any specific hardware or software for video stabilization), and situations in which part of the object to track is outside of the field of view of the camera. The performance of the proposed tracking strategy on-board UAVs is evaluated with images from realflight tests using manually-generated ground truth information, accurate position estimation using a Vicon system, and also with simulated data from a simulation environment. Results show that the hierarchical tracking strategy performs better than wellknown feature-based algorithms and well-known configurations of direct methods, and that its performance is robust enough for vision-in-the-loop tasks, e.g. for vision-based landing tasks.

Statistical distributions obtained from the compression of monodisperse, soft and frictionless particles

The cyclic compression of several granular systems has been simulated with a molecular dynamics code. All the samples consisted of bidimensional, soft, frictionless and equal-sized particles that were initially arranged according to a squared lattice and were compressed by randomly generated irregular walls. The compression protocols can be described by some control variables (volume or external force acting on the walls) and by some dimensionless factors, that relate stiffness, density, diameter, damping ratio and water surface tension to the external forces, displacements and periods. Each protocol, that is associated to a dynamic process, results in an arrangement with its own macroscopic features: volume (or packing ratio), coordination number, and stress; and the differences between packings can be highly significant. The statistical distribution of the force-moment state of the particles (i.e. the equivalent average stress multiplied by the volume) is analyzed. In spite of the lack of a theoretical framework based on statistical mechanics specific for these protocols, it is shown how the obtained distributions of mean and relative deviatoric force-moment are. Then it is discussed on the nature of these distributions and on their relation to specific protocols.

Development of a human movement monitoring system based on wearable devices

It is essential to remotely and continuously monitor the movements of individuals in many social areas, for example, taking care of aging people, physical therapy, athletic training etc. Many methods have been used, such as video record, motion analysis or sensor-based methods. Due to the limitations in remote communication, power consumption, portability and so on, most of them are not able to fulfill the requirements. The development of wearable technology and cloud computing provides a new efficient way to achieve this goal. This paper presents an intelligent human movement monitoring system based on a smartwatch, an Android smartphone and a distributed data management engine. This system includes advantages of wide adaptability, remote and long-term monitoring capacity, high portability and flexibility. The structure of the system and its principle are introduced. Four experiments are designed to prove the feasibility of the system. The results of the experiments demonstrate the system is able to detect different actions of individuals with adequate accuracy.

Optimization methods for the operating room management under uncertainty: stochastic programming vs. decomposition approach

The operating theatres are the engine of the hospitals; proper management of the operating rooms and its staff represents a great challenge for managers and its results impact directly in the budget of the hospital. This work presents a MILP model for the efficient schedule of multiple surgeries in Operating Rooms (ORs) during a working day. This model considers multiple surgeons and ORs and different types of surgeries. Stochastic strategies are also implemented for taking into account the uncertain in surgery durations (pre-incision, incision, post-incision times). In addition, a heuristic-based methods and a MILP decomposition approach is proposed for solving large-scale ORs scheduling problems in computational efficient way. All these computer-aided strategies has been implemented in AIMMS, as an advanced modeling and optimization software, developing a user friendly solution tool for the operating room management under uncertainty.

Gene-based approach to human gene-phenotype correlations

Elucidating the genetic basis of human phenotypes is a major goal of contemporary geneticists. Logically, two fundamental and contrasting approaches are available, one that begins with a phenotype and concludes with the identification of a responsible gene or genes; the other that begins with a gene and works toward identifying one or more phenotypes resulting from allelic variation of it. This paper provides a conceptual overview of phenotype-based vs. gene-based procedures with emphasis on gene-based methods. A key feature of a gene-based approach is that laboratory effort first is devoted to developing an assay for mutations in the gene under regard; the assay then is applied to the evaluation of large numbers of unrelated individuals with a variety of phenotypes that are deemed potentially resulting from alleles at the gene. No effort is directed toward chromosomally mapping the loci responsible for the phenotypes scanned. Example is made of my laboratory’s successful use of a gene-based approach to identify genes causing hereditary diseases of the retina such as retinitis pigmentosa. Reductions in the cost and improvements in the speed of scanning individuals for DNA sequence anomalies may make a gene-based approach an efficient alternative to phenotype-based approaches to correlating genes with phenotypes.

Innovative analytical strategies for the development of sensor devices and mass spectrometry methods

Il lavoro presentato in questa tesi di Dottorato è incentrato sullo sviluppo di strategie analitiche innovative basate sulla sensoristica e su tecniche di spettrometria di massa in ambito biologico e della sicurezza alimentare. Il primo capitolo tratta lo studio di aspetti metodologici ed applicativi di procedure sensoristiche per l’identificazione e la determinazione di biomarkers associati alla malattia celiaca. In tale ambito, sono stati sviluppati due immunosensori, uno a trasduzione piezoelettrica e uno a trasduzione amperometrica, per la rivelazione di anticorpi anti-transglutaminasi tissutale associati a questa malattia. L’innovazione di questi dispositivi riguarda l’immobilizzazione dell’enzima tTG nella conformazione aperta (Open-tTG), che è stato dimostrato essere quella principalmente coinvolta nella patogenesi. Sulla base dei risultati ottenuti, entrambi i sistemi sviluppati si sono dimostrati una valida alternativa ai test di screening attualmente in uso per la diagnosi della celiachia. Rimanendo sempre nel contesto della malattia celiaca, ulteriore ricerca oggetto di questa tesi di Dottorato, ha riguardato lo sviluppo di metodi affidabili per il controllo di prodotti “gluten-free”. Il secondo capitolo tratta lo sviluppo di un metodo di spettrometria di massa e di un immunosensore competitivo per la rivelazione di prolammine in alimenti “gluten-free”. E’ stato sviluppato un metodo LC-ESI-MS/MS basato su un’analisi target con modalità di acquisizione del segnale selected reaction monitoring per l’identificazione di glutine in diversi cereali potenzialmente tossici per i celiaci. Inoltre ci si è focalizzati su un immunosensore competitivo per la rivelazione di gliadina, come metodo di screening rapido di farine. Entrambi i sistemi sono stati ottimizzati impiegando miscele di farina di riso addizionata di gliadina, avenine, ordeine e secaline nel caso del sistema LC-MS/MS e con sola gliadina nel caso del sensore. Infine i sistemi analitici sono stati validati analizzando sia materie prime (farine) che alimenti (biscotti, pasta, pane, etc.). L’approccio sviluppato in spettrometria di massa apre la strada alla possibilità di sviluppare un test di screening multiplo per la valutazione della sicurezza di prodotti dichiarati “gluten-free”, mentre ulteriori studi dovranno essere svolti per ricercare condizioni di estrazione compatibili con l’immunosaggio competitivo, per ora applicabile solo all’analisi di farine estratte con etanolo. Terzo capitolo di questa tesi riguarda lo sviluppo di nuovi metodi per la rivelazione di HPV, Chlamydia e Gonorrhoeae in fluidi biologici. Si è scelto un substrato costituito da strips di carta in quanto possono costituire una valida piattaforma di rivelazione, offrendo vantaggi grazie al basso costo, alla possibilità di generare dispositivi portatili e di poter visualizzare il risultato visivamente senza la necessità di strumentazioni. La metodologia sviluppata è molto semplice, non prevede l’uso di strumentazione complessa e si basa sull’uso della isothermal rolling-circle amplification per l’amplificazione del target. Inoltre, di fondamentale importanza, è l’utilizzo di nanoparticelle colorate che, essendo state funzionalizzate con una sequenza di DNA complementare al target amplificato derivante dalla RCA, ne permettono la rivelazione a occhio nudo mediante l’uso di filtri di carta. Queste strips sono state testate su campioni reali permettendo una discriminazione tra campioni positivi e negativi in tempi rapidi (10-15 minuti), aprendo una nuova via verso nuovi test altamente competitivi con quelli attualmente sul mercato.

Avaliações e testes dos métodos MASW e ReMi por meio do tratamento de dados empíricos e sintéticos em um programa de processamento e inversão desenvolvido em MATLAB e sua implicação em um problema geológico na Bacia de Taubaté

Os métodos de ondas superficiais com ênfase nas ondas Rayleigh foram utilizados como o núcleo desse trabalho de Doutorado. Inicialmente, as ondas Rayleigh foram modeladas permitindo o estudo de sensibilidade de suas curvas de dispersão sob diferentes configurações de parâmetros físicos representando diversos modelos de camadas, em que pôde ser observado parâmetros com maior e menor sensibilidade e também alguns efeitos provocados por baixas razões de Poisson. Além disso, na fase de inversão dos dados a modelagem das ondas Rayleigh foi utilizada para a construção da função objeto, que agregada ao método de mínimos quadrados, a partir do método de Levenberg-Marquardt, permitiu a implementação de um algoritmo de busca local responsável pela inversão de dados das ondas superficiais. Por se tratar de um procedimento de busca local, o algoritmo de inversão foi complementado por uma etapa de pré-inversão com a geração de um modelo inicial para que o procedimento de inversão fosse mais rápido e eficiente. Visando uma eficiência ainda maior do procedimento de inversão, principalmente em modelos de camadas com inversão de velocidades, foi implementado um algoritmo de pós-inversão baseado em um procedimento de tentativa e erro minimizando os valores relativos da raiz quadrada do erro quadrático médio (REQMr) da inversão dos dados. Mais de 50 modelos de camadas foram utilizados para testar a modelagem, a pré-inversão, inversão e pós-inversão dos dados permitindo o ajuste preciso de parâmetros matemáticos e físicos presentes nos diversos scripts implementados em Matlab. Antes de inverter os dados adquiridos em campo, os mesmos precisaram ser tratados na etapa de processamento de dados, cujo objetivo principal é a extração da curva de dispersão originada devido às ondas superficiais. Para isso, foram implementadas, também em Matlab, três metodologias de processamento com abordagens matemáticas distintas. Essas metodologias foram testadas e avaliadas com dados sintéticos e reais em que foi possível constatar as virtudes e deficiências de cada metodologia estudada, bem como as limitações provocadas pela discretização dos dados de campo. Por último, as etapas de processamento, pré-inversão, inversão e pós-inversão dos dados foram unificadas para formar um programa de tratamento de dados de ondas superficiais (Rayleigh). Ele foi utilizado em dados reais originados pelo estudo de um problema geológico na Bacia de Taubaté em que foi possível mapear os contatos geológicos ao longo dos pontos de aquisição sísmica e compará-los a um modelo inicial existente baseado em observações geomorfológicas da área de estudos, mapa geológico da região e informações geológicas globais e locais dos movimentos tectônicos na região. As informações geofísicas associadas às geológicas permitiram a geração de um perfil analítico da região de estudos com duas interpretações geológicas confirmando a suspeita de neotectônica na região em que os contatos geológicos entre os depósitos Terciários e Quaternários foram identificados e se encaixaram no modelo inicial de hemi-graben com mergulho para Sudeste.

Three-dimensional planar model estimation using multi-constraint knowledge based on k-means and RANSAC

Plane model extraction from three-dimensional point clouds is a necessary step in many different applications such as planar object reconstruction, indoor mapping and indoor localization. Different RANdom SAmple Consensus (RANSAC)-based methods have been proposed for this purpose in recent years. In this study, we propose a novel method-based on RANSAC called Multiplane Model Estimation, which can estimate multiple plane models simultaneously from a noisy point cloud using the knowledge extracted from a scene (or an object) in order to reconstruct it accurately. This method comprises two steps: first, it clusters the data into planar faces that preserve some constraints defined by knowledge related to the object (e.g., the angles between faces); and second, the models of the planes are estimated based on these data using a novel multi-constraint RANSAC. We performed experiments in the clustering and RANSAC stages, which showed that the proposed method performed better than state-of-the-art methods.

Numerical and experimental investigation of structural stiffness influence on ratcheting convection cell in granular soils under cyclic loading

Lateral cyclic loaded structures in granular soils can lead to an accumulation of irreversible strains by changing their mechanical response (densification) and forming a closed convective cell in the upper layer of the bedding. In the present thesis the convective cell dimension, formation and grain migration inside this closed volume have been studied and presented in relation to structural stiffness and different loads. This relation was experimentally investigated by applying a cyclic lateral force to a scaled flexible vertical element embedded in dry granular soil. The model was monitored with a camera in order to derive the displacement field by means of the PIV technique. Modelling large soil deformation turns out to be difficult, using mesh-based methods. Consequently, a mesh-free approach (DEM) was chosen in order to investigate the granular flow with the aim of extracting interesting micromechanical information. In both the numerical and experimental analyses the effect of different loading magnitudes and different dimensions of the vertical element were considered. The main results regarded the different development, shape and dimensions of the convection cell and the surface settlements. Moreover, the Discrete Element Method has proven to give satisfactory results in the modelling of large deformation phenomena such as the ratcheting convective cell.

Winding patterns for biplanar MRI shim coils with rectangular and circular target-field regions

A method is presented for calculating the winding patterns required to design independent zonal and tesseral biplanar shim coils for magnetic resonance imaging. Streamline, target-field, Fourier integral and Fourier series methods are utilized. For both Fourier-based methods, the desired target field is specified on the surface of the conducting plates. For the Fourier series method it is possible to specify the target field at additional depths interior to the two conducting plates. The conducting plates are confined symmetrically in the xy plane with dimensions 2a x 2b, and are separated by 2d in the z direction. The specification of the target field is symmetric for the Fourier integral method, but can be over some asymmetric portion pa < x < qa and sb < y < tb of the coil dimensions (-1 < p < q < 1 and -1 < s < t < 1) for the Fourier series method. Arbitrary functions are used in the outer sections to ensure continuity of the magnetic field across the entire coil face. For the Fourier series case, the entire field is periodically extended as double half-range sine or cosine series. The resultant Fourier coefficients are substituted into the Fourier series and integral expressions for the internal and external magnetic fields, and stream functions on both the conducting surfaces. A contour plot of the stream function directly gives the required coil winding patterns. Spherical harmonic analysis of field calculations from a ZX shim coil indicates that example designs and theory are well matched.

Predicting residue-wise contact orders in proteins by support vector regression

Background: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

A genetic algorithm based method for deregulated electricity market dispatch

In a deregulated electricity market, optimizing dispatch capacity and transmission capacity are among the core concerns of market operators. Many market operators have capitalized on linear programming (LP) based methods to perform market dispatch operation in order to explore the computational efficiency of LP. In this paper, the search capability of genetic algorithms (GAs) is utilized to solve the market dispatch problem. The GA model is able to solve pool based capacity dispatch, while optimizing the interconnector transmission capacity. Case studies and corresponding analyses are performed to demonstrate the efficiency of the GA model.