Morphological instability analysis of a misfit strained core-shell nanowire for the growth of quantum dots

Nell'ambito delle nanostrutture, un ruolo primario è svolto dai punti quantici. In questo lavoro siamo interessati all'analisi teorica del processo di creazione dei punti quantici: esso può avvenire per eteroepitassia, in particolare secondo il metodo studiato da Stranski-Krastanov. Un film di Germanio viene depositato su un substrato di Silicio in modo coerente, cioè senza dislocazioni, e, a causa del misfit tra le maglie dei due materiali, c'è un accumulo di energia elastica nel film. A una certa altezza critica questa energia del film può essere ridotta se il film si organizza in isole (punti quantici), dove la tensione può essere rilassata lateralmente. L'altezza critica dipende dai moduli di Young (E, υ), dal misfit tra le maglie (m) e dalla tensione superficiali (γ). Il trasporto di materiale nel film è portato avanti per diffusione superficiale. Il punto focale nell'analisi delle instabilità indotte dal misfit tra le maglie dei materiali è la ricerca delle caratteristiche che individuano il modo di crescita più rapido dei punti quantici. In questo lavoro siamo interessati ad un caso particolare: la crescita di punti quantici non su una superficie piana ma sulla superficie di un nanofilo quantico a geometria cilindrica. L'analisi delle instabilità viene condotta risolvendo le equazioni all'equilibrio: a tal fine sono state calcolate le distribuzioni del tensore delle deformazioni e degli sforzo di un nanofilo core-shell con una superficie perturbata al primo ordine rispetto all'ampiezza della perturbazione. L'analisi è stata condotta con particolari condizioni al contorno ed ipotesi geometriche, e diverse scelte dello stato di riferimento del campo degli spostamenti. Risolto il problema elastico, è stata studiata l'equazione dinamica di evoluzione descrivente la diffusione di superficie. Il risultato dell'analisi di instabilità è il tasso di crescita in funzione del numero d'onda q, con diversi valori del raggio del core, spessore dello shell e modo normale n, al fine di trovare il più veloce modo di crescita della perturbazione.

Twitter data analysis for financial markets

Over the time, Twitter has become a fundamental source of information for news. As a one step forward, researchers have tried to analyse if the tweets contain predictive power. In the past, in financial field, a lot of research has been done to propose a function which takes as input all the tweets for a particular stock or index s, analyse them and predict the stock or index price of s. In this work, we take an alternative approach: using the stock price and tweet information, we investigate following questions. 1. Is there any relation between the amount of tweets being generated and the stocks being exchanged? 2. Is there any relation between the sentiment of the tweets and stock prices? 3. What is the structure of the graph that describes the relationships between users?

An angiographic analysis of atherosclerosis progression in below-the-knee arteries after femoropopliteal angioplasty in claudicants

Purpose: To report an angiographic investigation of midterm atherosclerotic disease progression in below-the-knee (BTK) arteries of claudicants. Methods: Angiograms were performed in 58 consecutive claudicants (35 men; mean age 68.3±8.7 years) with endovascular treatment of femoropopliteal arteries in 58 limbs after a mean follow-up of 3.6±1.2 years. Angiograms were reviewed in consensus by 2 experienced readers blinded to clinical data. Progression of atherosclerosis in 4 BTK arterial segments (tibioperoneal trunk, anterior and posterior tibial arteries, and peroneal artery) was assessed according to the Bollinger score. The composite per calf Bollinger score represented the average of the 4 BTK arterial segment scores. The association of the Bollinger score with cardiovascular risk factors and gender was scrutinized. Results: A statistically significant increase in atherosclerotic burden was observed for the mean composite per calf Bollinger score (5.7±8.3 increase, 95% CI 3.5 to 7.9, p<0.0001), as well as for each single arterial segment analyzed. In multivariate linear regression analysis, diabetes mellitus was associated with a more pronounced progression of atherosclerotic burden in crural arteries (β: 5.6, p=0.035, 95% CI 0.398 to 10.806). Conclusion: Progression of infrapopliteal atherosclerotic lesions is common in claudicants during midterm follow-up. Presence of diabetes mellitus was confirmed as a major risk factor for more pronounced atherosclerotic BTK disease progression.

REGULATION OF WHOLE-BODY ENERGY HOMEOSTASIS WITH GROWTH HORMONE REPLACEMENT THERAPY AND ENDURANCE EXERCISE

We hypothesized that network analysis is useful to expose coordination between whole body and myocellular levels of energy metabolism and can identify entities that underlie skeletal muscle's contribution to growth hormone-stimulated lipid handling and metabolic fitness. We assessed 112 metabolic parameters characterizing metabolic rate and substrate handling in tibialis anterior muscle and vascular compartment at rest, after a meal and exercise with growth hormone replacement therapy (GH-RT) of hypopituitary patients (n = 11). The topology of linear relationships (| r | ≥ 0.7, P ≤ 0.01) and mutual dependencies exposed the organization of metabolic relationships in three entities reflecting basal and exercise-induced metabolic rate, triglyceride handling, and substrate utilization in the pre- and postprandial state, respectively. GH-RT improved aerobic performance (+5%), lean-to-fat mass (+19%), and muscle area of tibialis anterior (+2%) but did not alter its mitochondrial and capillary content. Concomitantly, connectivity was established between myocellular parameters of mitochondrial lipid metabolism and meal-induced triglyceride handling in serum. This was mediated via the recruitment of transcripts of muscle lipid mobilization (LIPE, FABP3, and FABP4) and fatty acid-sensitive transcription factors (PPARA, PPARG) to the metabolic network. The interdependence of gene regulatory elements of muscle lipid metabolism reflected the norm in healthy subjects (n = 12) and distinguished the regulation of the mitochondrial respiration factor COX1 by GH and endurance exercise. Our observations validate the use of network analysis for systems medicine and highlight the notion that an improved stochiometry between muscle and whole body lipid metabolism, rather than alterations of single bottlenecks, contributes to GH-driven elevations in metabolic fitness.

Analysis of the erosive effect of different dietary substances and medications

Excessive consumption of acidic drinks and foods contributes to tooth erosion. The aims of the present in vitro study were twofold: (1) to assess the erosive potential of different dietary substances and medications; (2) to determine the chemical properties with an impact on the erosive potential. We selected sixty agents: soft drinks, an energy drink, sports drinks, alcoholic drinks, juice, fruit, mineral water, yogurt, tea, coffee, salad dressing and medications. The erosive potential of the tested agents was quantified as the changes in surface hardness (ΔSH) of enamel specimens within the first 2 min (ΔSH2-0 = SH2 min - SHbaseline) and the second 2 min exposure (ΔSH4-2 = SH4 min - SH2 min). To characterise these agents, various chemical properties, e.g. pH, concentrations of Ca, Pi and F, titratable acidity to pH 7·0 and buffering capacity at the original pH value (β), as well as degree of saturation (pK - pI) with respect to hydroxyapatite (HAP) and fluorapatite (FAP), were determined. Erosive challenge caused a statistically significant reduction in SH for all agents except for coffee, some medications and alcoholic drinks, and non-flavoured mineral waters, teas and yogurts (P < 0·01). By multiple linear regression analysis, 52 % of the variation in ΔSH after 2 min and 61 % after 4 min immersion were explained by pH, β and concentrations of F and Ca (P < 0·05). pH was the variable with the highest impact in multiple regression and bivariate correlation analyses. Furthermore, a high bivariate correlation was also obtained between (pK - pI)HAP, (pK - pI)FAP and ΔSH.

Proteome analysis in cardiovascular pathophysiology using Dahl rat model

Dahl salt-sensitive (DS) and salt-resistant (DR) inbred rat strains represent a well established animal model for cardiovascular research. Upon prolonged administration of high-salt-containing diet, DS rats develop systemic hypertension, and as a consequence they develop left ventricular hypertrophy, followed by heart failure. The aim of this work was to explore whether this animal model is suitable to identify biomarkers that characterize defined stages of cardiac pathophysiological conditions. The work had to be performed in two stages: in the first part proteomic differences that are attributable to the two separate rat lines (DS and DR) had to be established, and in the second part the process of development of heart failure due to feeding the rats with high-salt-containing diet has to be monitored. This work describes the results of the first stage, with the outcome of protein expression profiles of left ventricular tissues of DS and DR rats kept under low salt diet. Substantial extent of quantitative and qualitative expression differences between both strains of Dahl rats in heart tissue was detected. Using Principal Component Analysis, Linear Discriminant Analysis and other statistical means we have established sets of differentially expressed proteins, candidates for further molecular analysis of the heart failure mechanisms.

Periodic breathing during ascent to extreme altitude quantified by spectral analysis of the respiratory volume signal

High altitude periodic breathing (PB) shares some common pathophysiologic aspects with sleep apnea, Cheyne-Stokes respiration and PB in heart failure patients. Methods that allow quantifying instabilities of respiratory control provide valuable insights in physiologic mechanisms and help to identify therapeutic targets. Under the hypothesis that high altitude PB appears even during physical activity and can be identified in comparison to visual analysis in conditions of low SNR, this study aims to identify PB by characterizing the respiratory pattern through the respiratory volume signal. A number of spectral parameters are extracted from the power spectral density (PSD) of the volume signal, derived from respiratory inductive plethysmography and evaluated through a linear discriminant analysis. A dataset of 34 healthy mountaineers ascending to Mt. Muztagh Ata, China (7,546 m) visually labeled as PB and non periodic breathing (nPB) is analyzed. All climbing periods within all the ascents are considered (total climbing periods: 371 nPB and 40 PB). The best crossvalidated result classifying PB and nPB is obtained with Pm (power of the modulation frequency band) and R (ratio between modulation and respiration power) with an accuracy of 80.3% and area under the receiver operating characteristic curve of 84.5%. Comparing the subjects from 1(st) and 2(nd) ascents (at the same altitudes but the latter more acclimatized) the effect of acclimatization is evaluated. SaO(2) and periodic breathing cycles significantly increased with acclimatization (p-value < 0.05). Higher Pm and higher respiratory frequencies are observed at lower SaO(2), through a significant negative correlation (p-value < 0.01). Higher Pm is observed at climbing periods visually labeled as PB with > 5 periodic breathing cycles through a significant positive correlation (p-value < 0.01). Our data demonstrate that quantification of the respiratory volume signal using spectral analysis is suitable to identify effects of hypobaric hypoxia on control of breathing.

Application and comparison of classification algorithms for recognition of Alzheimer's disease in electrical brain activity (EEG)

The early detection of subjects with probable Alzheimer's disease (AD) is crucial for effective appliance of treatment strategies. Here we explored the ability of a multitude of linear and non-linear classification algorithms to discriminate between the electroencephalograms (EEGs) of patients with varying degree of AD and their age-matched control subjects. Absolute and relative spectral power, distribution of spectral power, and measures of spatial synchronization were calculated from recordings of resting eyes-closed continuous EEGs of 45 healthy controls, 116 patients with mild AD and 81 patients with moderate AD, recruited in two different centers (Stockholm, New York). The applied classification algorithms were: principal component linear discriminant analysis (PC LDA), partial least squares LDA (PLS LDA), principal component logistic regression (PC LR), partial least squares logistic regression (PLS LR), bagging, random forest, support vector machines (SVM) and feed-forward neural network. Based on 10-fold cross-validation runs it could be demonstrated that even tough modern computer-intensive classification algorithms such as random forests, SVM and neural networks show a slight superiority, more classical classification algorithms performed nearly equally well. Using random forests classification a considerable sensitivity of up to 85% and a specificity of 78%, respectively for the test of even only mild AD patients has been reached, whereas for the comparison of moderate AD vs. controls, using SVM and neural networks, values of 89% and 88% for sensitivity and specificity were achieved. Such a remarkable performance proves the value of these classification algorithms for clinical diagnostics.

Determination of histopathological tumor grade in neuroepithelial brain tumors by using spectral pattern analysis of in vivo spectroscopic data

OBJECT: In this study, 1H magnetic resonance (MR) spectroscopy was prospectively tested as a reliable method for presurgical grading of neuroepithelial brain tumors. METHODS: Using a database of tumor spectra obtained in patients with histologically confirmed diagnoses, 94 consecutive untreated patients were studied using single-voxel 1H spectroscopy (point-resolved spectroscopy; TE 135 msec, TE 135 msec, TR 1500 msec). A total of 90 tumor spectra obtained in patients with diagnostic 1H MR spectroscopy examinations were analyzed using commercially available software (MRUI/VARPRO) and classified using linear discriminant analysis as World Health Organization (WHO) Grade I/II, WHO Grade III, or WHO Grade IV lesions. In all cases, the classification results were matched with histopathological diagnoses that were made according to the WHO classification criteria after serial stereotactic biopsy procedures or open surgery. Histopathological studies revealed 30 Grade I/II tumors, 29 Grade III tumors, and 31 Grade IV tumors. The reliability of the histological diagnoses was validated considering a minimum postsurgical follow-up period of 12 months (range 12-37 months). Classifications based on spectroscopic data yielded 31 tumors in Grade I/II, 32 in Grade III, and 27 in Grade IV. Incorrect classifications included two Grade II tumors, one of which was identified as Grade III and one as Grade IV; two Grade III tumors identified as Grade II; two Grade III lesions identified as Grade IV; and six Grade IV tumors identified as Grade III. Furthermore, one glioblastoma (WHO Grade IV) was classified as WHO Grade I/II. This represents an overall success rate of 86%, and a 95% success rate in differentiating low-grade from high-grade tumors. CONCLUSIONS: The authors conclude that in vivo 1H MR spectroscopy is a reliable technique for grading neuroepithelial brain tumors.

Social Networks Analysis

This morning Dr. Risser will introduce you to the basic ideas of social network analysis. You will learn some history behind the study of social networks. Dr. Risser will introduce you to mathematical measures of social networks including centrality measures and measures of spread and cohesion. You will also learn how to use a computer program to analyze social network data

Analyzing online communication from a social network point of view: questions, problems, perspectives

This programmatic paper investigates the possibilities, chances, and risks of analyzing personal and professional online communication from the point of view of interactional sociolinguistics combined with modern social network analysis (SNA). Thus, it has two complementing goals: One is the exploration of adequate, innovative concepts and methods for analyzing online communication, the other is to use online communication and its ontological and functional specificities to enrich the conceptual and methodological background of SNA. The paper is organized in two parts. It begins with an introduction to recent developments in sociolinguistic social network analysis. Here, three interesting new concepts and tools are discussed: latent versus emergent networks (Watts 1991), coalitions (Fitzmaurice 2000a, Fitzmaurice 2000b), and communities of practice (Wenger 1998

Repeatability analysis of global and local metrics of brain structural networks

Computational network analysis provides new methods to analyze the human connectome. Brain structural networks can be characterized by global and local metrics that recently gave promising insights for diagnosis and further understanding of neurological, psychiatric and neurodegenerative disorders. In order to ensure the validity of results in clinical settings the precision and repeatability of the networks and the associated metrics must be evaluated. In the present study, nineteen healthy subjects underwent two consecutive measurements enabling us to test reproducibility of the brain network and its global and local metrics. As it is known that the network topology depends on the network density, the effects of setting a common density threshold for all networks were also assessed. Results showed good to excellent repeatability for global metrics, while for local metrics it was more variable and some metrics were found to have locally poor repeatability. Moreover, between subjects differences were slightly inflated when the density was not fixed. At the global level, these findings confirm previous results on the validity of global network metrics as clinical biomarkers. However, the new results in our work indicate that the remaining variability at the local level as well as the effect of methodological characteristics on the network topology should be considered in the analysis of brain structural networks and especially in networks comparisons.

A social network-based approach to assess de facto independence of regulatory agencies

This article uses a policy network perspective to assess the independence of regulatory agencies (RAs) in liberalized public utility sectors. We focus on the de facto independence of RAs from elected politicians, regulatees and other co-regulators. We go further than previous studies, which only undertook a general analysis of the de jure independence of RAs from political authorities. Specifically, we apply a social network analysis (SNA), which concentrates on the attributes and relational profiles of all actors involved in new regulatory arrangements. The concept of de facto independence is applied to the Swiss telecommunications sector in order to provide initial empirical insights. Results clearly show that SNA indicators are an appropriate tool to identify the de facto independence of RAs and can improve knowledge about the issues arising from the emergence of the ‘regulatory State’.

The structural substrate of brain function: analysis of brain structural networks based on diffusion-weighted imaging

The brain is a complex neural network with a hierarchical organization and the mapping of its elements and connections is an important step towards the understanding of its function. Recent developments in diffusion-weighted imaging have provided the opportunity to reconstruct the whole-brain structural network in-vivo at a large scale level and to study the brain structural substrate in a framework that is close to the current understanding of brain function. However, methods to construct the connectome are still under development and they should be carefully evaluated. To this end, the first two studies included in my thesis aimed at improving the analytical tools specific to the methodology of brain structural networks. The first of these papers assessed the repeatability of the most common global and local network metrics used in literature to characterize the connectome, while in the second paper the validity of further metrics based on the concept of communicability was evaluated. Communicability is a broader measure of connectivity which accounts also for parallel and indirect connections. These additional paths may be important for reorganizational mechanisms in the presence of lesions as well as to enhance integration in the network. These studies showed good to excellent repeatability of global network metrics when the same methodological pipeline was applied, but more variability was detected when considering local network metrics or when using different thresholding strategies. In addition, communicability metrics have been found to add some insight into the integration properties of the network by detecting subsets of nodes that were highly interconnected or vulnerable to lesions. The other two studies used methods based on diffusion-weighted imaging to obtain knowledge concerning the relationship between functional and structural connectivity and about the etiology of schizophrenia. The third study integrated functional oscillations measured using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) as well as diffusion-weighted imaging data. The multimodal approach that was applied revealed a positive relationship between individual fluctuations of the EEG alpha-frequency and diffusion properties of specific connections of two resting-state networks. Finally, in the fourth study diffusion-weighted imaging was used to probe for a relationship between the underlying white matter tissue structure and season of birth in schizophrenia patients. The results are in line with the neurodevelopmental hypothesis of early pathological mechanisms as the origin of schizophrenia. The different analytical approaches selected in these studies also provide arguments for discussion of the current limitations in the analysis of brain structural networks. To sum up, the first studies presented in this thesis illustrated the potential of brain structural network analysis to provide useful information on features of brain functional segregation and integration using reliable network metrics. In the other two studies alternative approaches were presented. The common discussion of the four studies enabled us to highlight the benefits and possibilities for the analysis of the connectome as well as some current limitations.

A class of exact Navier-Stokes solutions for homogeneous flat-plate boundary layers and their linear stability

We introduce a new boundary layer formalism on the basis of which a class of exact solutions to the Navier–Stokes equations is derived. These solutions describe laminar boundary layer flows past a flat plate under the assumption of one homogeneous direction, such as the classical swept Hiemenz boundary layer (SHBL), the asymptotic suction boundary layer (ASBL) and the oblique impingement boundary layer. The linear stability of these new solutions is investigated, uncovering new results for the SHBL and the ASBL. Previously, each of these flows had been described with its own formalism and coordinate system, such that the solutions could not be transformed into each other. Using a new compound formalism, we are able to show that the ASBL is the physical limit of the SHBL with wall suction when the chordwise velocity component vanishes while the homogeneous sweep velocity is maintained. A corresponding non-dimensionalization is proposed, which allows conversion of the new Reynolds number definition to the classical ones. Linear stability analysis for the new class of solutions reveals a compound neutral surface which contains the classical neutral curves of the SHBL and the ASBL. It is shown that the linearly most unstable Görtler–Hämmerlin modes of the SHBL smoothly transform into Tollmien–Schlichting modes as the chordwise velocity vanishes. These results are useful for transition prediction of the attachment-line instability, especially concerning the use of suction to stabilize boundary layers of swept-wing aircraft.