Resonance Frequency Analysis (RFA) during early healing

Objectives: - to monitor resonance frequency analysis (RFA) in relation to the jawbone characteristics during the early phases of healing and incorporation of Straumann® dental implants with an SLA surface. Material and methods: 17 Straumann 4.1mm implants (10mm) and 7 Straumann 4.8mm implants (10mm) were installed and ISQ determined at baseline and after 1, 2, 3, 4, 5, 6, 8 and 12 weeks. Central bone cores were analyzed from the 4.1mm implants using micro CT for bone volume density (BVD) and bone trabecular connectivity (BTC). Results: Pocket probing depths ranged between 2-4mm and bleeding on probing between 5-20%. At baseline, BVD varied between 24 and 65% and BTC between 4.9 and 25.4 for the 4.1mm implants. Baseline ISQ varied between 55 and 74 with a mean of 61.4. No significant correlations were found between BVD or BTC and ISQ Values. For the 4.8mm diameter implants baseline ISQ values ranged from 57 – 70 with a mean of 63.3. Over the healing period ISQ values increased at 1 week and decreased after 2-3 weeks. After 4 weeks ISQ values, again increased slightly, no significant differences were noted over time. One implant (4.1mm) lost stability at 3 weeks. Its ISQ value had dropped from 68 to 45. However the latter value was determined after the clinical diagnosis of instability. Conclusion: ISQ values of 57 – 70 represented homeostasis and implant stability. However no predictive value for loosing implant stability can be attributed to RFA since decease occurred after the fact.

Stability measurements of 1-stage implants in the edentulous mandible by means of resonance frequency analysis

OBJECTIVE: Resonance frequency analysis (RFA) is a method of measuring implant stability. However, little is known about RFA of implants with long loading periods. The objective of the present study was to determine standard implant stability quotients (ISQs) for clinical successfully osseointegrated 1-stage implants in the edentulous mandible. MATERIALS AND METHODS: Stability measurements by means of RFA were performed in regularly followed patients who had received 1- stage implants for overdenture support. The time interval between implant placement and measurement ranged from 1 year up to 10 years. The short-term group comprised patients who were followed up to 5 years, while the long-term group included patients with an observation time of > 5 years up to 10 years. For further comparison RFA measurements were performed in a matching group with unloaded implants at the end of the surgical procedure. For statistical analysis various parameters that might influence the ISQs of loaded implants were included, and a mixed-effects model applied (regression analysis, P <.0125). RESULTS: Ninety-four patients were available with a total of 205 loaded implants, and 16 patients with 36 implants immediately after the surgical procedure. The mean ISQ of all measured implants was 64.5 +/- 7.9 (range, 58 to 72). Statistical analysis did not reveal significant differences in the mean ISQ related to the observation time. The parameters with overall statistical significance were the diameter of the implants and changes in the attachment level. In the short-term group, the gender and the clinically measured attachment level had a significant effect. Implant diameter had a significant effect in the long-term group. CONCLUSIONS: A mean ISQ of 64.5 +/- 7.9 was found to be representative for stable asymptomatic interforaminal implants measured by the RFA instrument at any given time point. No significant differences in ISQ values were found between implants with different postsurgical time intervals. Implant diameter appears to influence the ISQ of interforaminal implants.

Topographic time-frequency decomposition of the EEG

Frequency-transformed EEG resting data has been widely used to describe normal and abnormal brain functional states as function of the spectral power in different frequency bands. This has yielded a series of clinically relevant findings. However, by transforming the EEG into the frequency domain, the initially excellent time resolution of time-domain EEG is lost. The topographic time-frequency decomposition is a novel computerized EEG analysis method that combines previously available techniques from time-domain spatial EEG analysis and time-frequency decomposition of single-channel time series. It yields a new, physiologically and statistically plausible topographic time-frequency representation of human multichannel EEG. The original EEG is accounted by the coefficients of a large set of user defined EEG like time-series, which are optimized for maximal spatial smoothness and minimal norm. These coefficients are then reduced to a small number of model scalp field configurations, which vary in intensity as a function of time and frequency. The result is thus a small number of EEG field configurations, each with a corresponding time-frequency (Wigner) plot. The method has several advantages: It does not assume that the data is composed of orthogonal elements, it does not assume stationarity, it produces topographical maps and it allows to include user-defined, specific EEG elements, such as spike and wave patterns. After a formal introduction of the method, several examples are given, which include artificial data and multichannel EEG during different physiological and pathological conditions.

Clinical study on survival rate of short implants placed in the posterior mandibular region: resonance frequency analysis.

OBJECTIVE Short implants are increasingly used, but there is doubt about their performance being similar to that of regular implants. The aim of this study was to compare the mechanical stability of short implants vs. regular implants placed in the edentulous posterior mandible. MATERIAL AND METHODS Twenty-three patients received a total of 48 short implants (5 × 5.5 mm and 5 × 7 mm) and 42 regular implants (4 × 10 mm and 4 × 11.5 mm) in the posterior mandible. Patients who received short implants had <10 mm of bone height measured from the bone crest to the outer wall of the mandibular canal. Resonance frequency analysis (RFA) was performed at time intervals T0 (immediately after implant placement), T1 (after 15 days), T2 (after 30 days), T3 (after 60 days), and T4 (after 90 days). RESULTS The survival rate after 90 days was 87.5% for the short implants and 100% for regular implants (P < 0.05). There was no significant difference between the implants in time intervals T1, T2, T3, and T4. In T0, the RFA values of 5 × 5.5 implants were higher than values of 5 × 7 and 4 × 11.5 implants (P < 0.05). A total of six short implants that were placed in four patients were lost (three of 5 × 5.5 mm and three of 5 × 7 mm). Three lost implants started with high ISQ values, which progressively decreased. The other three lost implants started with a slightly lower ISQ value, which rose and then began to fall. CONCLUSIONS Survival rate of short implants after 90 days was lower than that of regular implants. However, short implants may be considered a reasonable alternative for rehabilitation of severely resorbed mandibles with reduced height, to avoid performing bone reconstruction before implant placement. Patients need to be aware of the reduced survival rate compared with regular implants before implant placement to avoid disappointments.

Environmental variables modeling based on remote sensing data using time series analysis: forestry and agricultural applications

En la actualidad, el seguimiento de la dinámica de los procesos medio ambientales está considerado como un punto de gran interés en el campo medioambiental. La cobertura espacio temporal de los datos de teledetección proporciona información continua con una alta frecuencia temporal, permitiendo el análisis de la evolución de los ecosistemas desde diferentes escalas espacio-temporales. Aunque el valor de la teledetección ha sido ampliamente probado, en la actualidad solo existe un número reducido de metodologías que permiten su análisis de una forma cuantitativa. En la presente tesis se propone un esquema de trabajo para explotar las series temporales de datos de teledetección, basado en la combinación del análisis estadístico de series de tiempo y la fenometría. El objetivo principal es demostrar el uso de las series temporales de datos de teledetección para analizar la dinámica de variables medio ambientales de una forma cuantitativa. Los objetivos específicos son: (1) evaluar dichas variables medio ambientales y (2) desarrollar modelos empíricos para predecir su comportamiento futuro. Estos objetivos se materializan en cuatro aplicaciones cuyos objetivos específicos son: (1) evaluar y cartografiar estados fenológicos del cultivo del algodón mediante análisis espectral y fenometría, (2) evaluar y modelizar la estacionalidad de incendios forestales en dos regiones bioclimáticas mediante modelos dinámicos, (3) predecir el riesgo de incendios forestales a nivel pixel utilizando modelos dinámicos y (4) evaluar el funcionamiento de la vegetación en base a la autocorrelación temporal y la fenometría. Los resultados de esta tesis muestran la utilidad del ajuste de funciones para modelizar los índices espectrales AS1 y AS2. Los parámetros fenológicos derivados del ajuste de funciones permiten la identificación de distintos estados fenológicos del cultivo del algodón. El análisis espectral ha demostrado, de una forma cuantitativa, la presencia de un ciclo en el índice AS2 y de dos ciclos en el AS1 así como el comportamiento unimodal y bimodal de la estacionalidad de incendios en las regiones mediterránea y templada respectivamente. Modelos autorregresivos han sido utilizados para caracterizar la dinámica de la estacionalidad de incendios y para predecir de una forma muy precisa el riesgo de incendios forestales a nivel pixel. Ha sido demostrada la utilidad de la autocorrelación temporal para definir y caracterizar el funcionamiento de la vegetación a nivel pixel. Finalmente el concepto “Optical Functional Type” ha sido definido, donde se propone que los pixeles deberían ser considerados como unidades temporales y analizados en función de su dinámica temporal. ix SUMMARY A good understanding of land surface processes is considered as a key subject in environmental sciences. The spatial-temporal coverage of remote sensing data provides continuous observations with a high temporal frequency allowing the assessment of ecosystem evolution at different temporal and spatial scales. Although the value of remote sensing time series has been firmly proved, only few time series methods have been developed for analyzing this data in a quantitative and continuous manner. In the present dissertation a working framework to exploit Remote Sensing time series is proposed based on the combination of Time Series Analysis and phenometric approach. The main goal is to demonstrate the use of remote sensing time series to analyze quantitatively environmental variable dynamics. The specific objectives are (1) to assess environmental variables based on remote sensing time series and (2) to develop empirical models to forecast environmental variables. These objectives have been achieved in four applications which specific objectives are (1) assessing and mapping cotton crop phenological stages using spectral and phenometric analyses, (2) assessing and modeling fire seasonality in two different ecoregions by dynamic models, (3) forecasting forest fire risk on a pixel basis by dynamic models, and (4) assessing vegetation functioning based on temporal autocorrelation and phenometric analysis. The results of this dissertation show the usefulness of function fitting procedures to model AS1 and AS2. Phenometrics derived from function fitting procedure makes it possible to identify cotton crop phenological stages. Spectral analysis has demonstrated quantitatively the presence of one cycle in AS2 and two in AS1 and the unimodal and bimodal behaviour of fire seasonality in the Mediterranean and temperate ecoregions respectively. Autoregressive models has been used to characterize the dynamics of fire seasonality in two ecoregions and to forecasts accurately fire risk on a pixel basis. The usefulness of temporal autocorrelation to define and characterized land surface functioning has been demonstrated. And finally the “Optical Functional Types” concept has been proposed, in this approach pixels could be as temporal unities based on its temporal dynamics or functioning.

Aesthetic appreciation: event-related field and time-frequency analyses

Improvements in neuroimaging methods have afforded significant advances in our knowledge of the cognitive and neural foundations of aesthetic appreciation. We used magnetoencephalography (MEG) to register brain activity while participants decided about the beauty of visual stimuli. The data were analyzed with event-related field (ERF) and Time-Frequency (TF) procedures. ERFs revealed no significant differences between brain activity related with stimuli rated as “beautiful” and “not beautiful.” TF analysis showed clear differences between both conditions 400 ms after stimulus onset. Oscillatory power was greater for stimuli rated as “beautiful” than those regarded as “not beautiful” in the four frequency bands (theta, alpha, beta, and gamma). These results are interpreted in the frame of synchronization studies.

Time evolution of frequency components In a chaotic digital signal

The type of signals obtained has conditioned chaos analysis tools. Almost in every case, they have analogue characteristics. But in certain cases, a chaotic digital signal is obtained and theses signals need a different approach than conventional analogue ones. The main objective of this paper will be to present some possible approaches to the study of this signals and how information about their characteristics may be obtained in the more straightforward possible way. We have obtained digital chaotic signals from an Optical Logic Cell with some feedback between output and one of the possible control gates. This chaos has been reported in several papers and its characteristics have been employed as a possible method to secure communications and as a way to encryption. In both cases, the influence of some perturbation in the transmission medium gave problems both for the synchronization of chaotic generators at emitter and receiver and for the recovering of information data. A proposed way to analyze the presence of some perturbation is to study the noise contents of transmitted signal and to implement a way to eliminate it. In our present case, the digital signal will be converted to a multilevel one by grouping bits in packets of 8 bits and applying conventional methods of time-frequency analysis to them. The results give information about the change in signals characteristics and hence some information about the noise or perturbations present. Equivalent representations to the phase and to the Feigenbaum diagrams for digital signals are employed in this case.

Time motion analysis of 2001 and 2002 super 12 rugby

The aim of this study was to quantify movements of Super 12 rugby players in competition because information on elite rugby players' movements is unavailable. Players were categorized into forwards [front (n = 16) and back row (n = 15)] and backs [inside (n = 9) and outside backs (n = 7)] and their movements analysed by video-based time motion analysis. Movements were classified as rest (standing, walking and jogging) and work (striding, sprinting, static exertion, jumping, lifting or tackling). The total time, number and duration of individual activities were assessed, with differences between groups evaluated using independent sample t-tests (unequal variances), while differences between halves were assessed with paired sample t-tests. Forwards had 7:47 min:s (95% confidence limits: 6:39 to 8:55 min:s, P

A review of time-motion analysis and combat development in mixed martial arts matches at regional level tournaments

Mixed martial arts (MMA) have become a fast-growing worldwide expansion of martial arts competition, requiring high level of skill, physical conditioning, and strategy, and involving a synthesis of combat while standing or on the ground. This study quantified the effort-pause ratio (EP), and classified effort segments of stand-up or groundwork development to identify the number of actions performed per round in MMA matches. 52 MMA athletes participated in the study (M age = 24 yr., SD = 5; average experience in MMA = 5 yr., SD = 3). A one-way analysis of variance with repeated measurements was conducted to compare the type of action across the rounds. A chi-squared test was applied across the percentages to compare proportions of different events. Only one significant difference (p < .05) was observed among rounds: time in groundwork of low intensity was longer in the second compared to the third round. When the interval between rounds was not considered, the EP ratio (between high-intensity effort to low-intensity effort plus pauses) WE S 1:2 to 1:4. This ratio is between ratios typical for judo, wrestling, karate, and taekwondo and reflects the combination of ground and standup techniques. Most of the matches ended in the third round, involving high-intensity actions, predominantly executed during groundwork combat.

Pre-run-time schedulability analysis of P-NET fieldbus networks

P-NET is a fieldbus industrial communication standard, which uses a Virtual Token Passing MAC mechanism. In this paper we establish pre-run-time schedulability conditions for supporting real-time traffic with P-NET. Essentially we provide formulae to evaluate the minimum message deadline, ensuring the transmission of real-time messages within a maximum time bound

Quantifying consistency of Event Related Potentials across subjects based on single-trial topographic analysis

Introduction: Non-invasive brain imaging techniques often contrast experimental conditions across a cohort of participants, obfuscating distinctions in individual performance and brain mechanisms that are better characterised by the inter-trial variability. To overcome such limitations, we developed topographic analysis methods for single-trial EEG data [1]. So far this was typically based on time-frequency analysis of single-electrode data or single independent components. The method's efficacy is demonstrated for event-related responses to environmental sounds, hitherto studied at an average event-related potential (ERP) level. Methods: Nine healthy subjects participated to the experiment. Auditory meaningful sounds of common objects were used for a target detection task [2]. On each block, subjects were asked to discriminate target sounds, which were living or man-made auditory objects. Continuous 64-channel EEG was acquired during the task. Two datasets were considered for each subject including single-trial of the two conditions, living and man-made. The analysis comprised two steps. In the first part, a mixture of Gaussians analysis [3] provided representative topographies for each subject. In the second step, conditional probabilities for each Gaussian provided statistical inference on the structure of these topographies across trials, time, and experimental conditions. Similar analysis was conducted at group-level. Results: Results show that the occurrence of each map is structured in time and consistent across trials both at the single-subject and at group level. Conducting separate analyses of ERPs at single-subject and group levels, we could quantify the consistency of identified topographies and their time course of activation within and across participants as well as experimental conditions. A general agreement was found with previous analysis at average ERP level. Conclusions: This novel approach to single-trial analysis promises to have impact on several domains. In clinical research, it gives the possibility to statistically evaluate single-subject data, an essential tool for analysing patients with specific deficits and impairments and their deviation from normative standards. In cognitive neuroscience, it provides a novel tool for understanding behaviour and brain activity interdependencies at both single-subject and at group levels. In basic neurophysiology, it provides a new representation of ERPs and promises to cast light on the mechanisms of its generation and inter-individual variability.

Relationship between trade openness and economic growth of India: A time series analysis

The paper aims to examine the empirical relationship between trade openness and economic growth of India for the time period 1970-2010. Trade openness is a multi-dimensional concept and hence measures of both trade barriers and trade volumes have been used as proxies for openness. The estimation results from Vector Autoregressive method suggest that growth in trade volumes accelerate economic growth in case of India. We do not find any evidence from our analysis that trade barriers lower growth.

Multivariate ARIMA Compositional Time Series Analysis

A compositional time series is obtained when a compositional data vector is observed atdifferent points in time. Inherently, then, a compositional time series is a multivariatetime series with important constraints on the variables observed at any instance in time.Although this type of data frequently occurs in situations of real practical interest, atrawl through the statistical literature reveals that research in the field is very much in itsinfancy and that many theoretical and empirical issues still remain to be addressed. Anyappropriate statistical methodology for the analysis of compositional time series musttake into account the constraints which are not allowed for by the usual statisticaltechniques available for analysing multivariate time series. One general approach toanalyzing compositional time series consists in the application of an initial transform tobreak the positive and unit sum constraints, followed by the analysis of the transformedtime series using multivariate ARIMA models. In this paper we discuss the use of theadditive log-ratio, centred log-ratio and isometric log-ratio transforms. We also presentresults from an empirical study designed to explore how the selection of the initialtransform affects subsequent multivariate ARIMA modelling as well as the quality ofthe forecasts

Changes in the use of broad-spectrum antibiotics after withdrawal of cefepime from the market: an interrupted time series analysis

Background and objective: Cefepime was one of the most used broad-spectrum antibiotics in Swiss public acute care hospitals. The drug was withdrawn from market in January 2007, and then replaced by a generic since October 2007. The goal of the study was to evaluate changes in the use of broad-spectrum antibiotics after the withdrawal of the cefepime original product. Design: A generalized regression-based interrupted time series model incorporating autocorrelated errors assessed how much the withdrawal changed the monthly use of other broad-spectrum antibiotics (ceftazidime, imipenem/cilastin, meropenem, piperacillin/ tazobactam) in defined daily doses (DDD)/100 bed-days from January 2004 to December 2008 [1, 2]. Setting: 10 Swiss public acute care hospitals (7 with\200 beds, 3 with 200-500 beds). Nine hospitals (group A) had a shortage of cefepime and 1 hospital had no shortage thanks to importation of cefepime from abroad. Main outcome measures: Underlying trend of use before the withdrawal, and changes in the level and in the trend of use after the withdrawal. Results: Before the withdrawal, the average estimated underlying trend (coefficient b1) for cefepime was decreasing by -0.047 (95% CI -0.086, -0.009) DDD/100 bed-days per month and was significant in three hospitals (group A, P\0.01). Cefepime withdrawal was associated with a significant increase in level of use (b2) of piperacillin/tazobactam and imipenem/cilastin in, respectively, one and five hospitals from group A. After the withdrawal, the average estimated trend (b3) was greatest for piperacillin/tazobactam (+0.043 DDD/100 bed-days per month; 95% CI -0.001, 0.089) and was significant in four hospitals from group A (P\0.05). The hospital without drug shortage showed no significant change in the trend and the level of use. The hypothesis of seasonality was rejected in all hospitals. Conclusions: The decreased use of cefepime already observed before its withdrawal from the market could be explained by pre-existing difficulty in drug supply. The withdrawal of cefepime resulted in change in level for piperacillin/tazobactam and imipenem/cilastin. Moreover, an increase in trend was found for piperacillin/tazobactam thereafter. As these changes generally occur at the price of lower bacterial susceptibility, a manufacturers' commitment to avoid shortages in the supply of their products would be important. As perspectives, we will measure the impact of the changes in cost and sensitivity rates of these antibiotics.