Psychometric properties of the Spanish version of the mindful attention awareness scale (MAAS) in patients with fibromyalgia

Background Mindful-based interventions improve functioning and quality of life in fibromyalgia (FM) patients. The aim of the study is to perform a psychometric analysis of the Spanish version of the Mindful Attention Awareness Scale (MAAS) in a sample of patients diagnosed with FM. Methods The following measures were administered to 251 Spanish patients with FM: the Spanish version of MAAS, the Chronic Pain Acceptance Questionnaire, the Pain Catastrophising Scale, the Injustice Experience Questionnaire, the Psychological Inflexibility in Pain Scale, the Fibromyalgia Impact Questionnaire and the Euroqol. Factorial structure was analysed using Confirmatory Factor Analyses (CFA). Cronbach's α coefficient was calculated to examine internal consistency, and the intraclass correlation coefficient (ICC) was calculated to assess the test-retest reliability of the measures. Pearson’s correlation tests were run to evaluate univariate relationships between scores on the MAAS and criterion variables. Results The MAAS scores in our sample were low (M = 56.7; SD = 17.5). CFA confirmed a two-factor structure, with the following fit indices [sbX2 = 172.34 (p < 0.001), CFI = 0.95, GFI = 0.90, SRMR = 0.05, RMSEA = 0.06. MAAS was found to have high internal consistency (Cronbach’s α = 0.90) and adequate test-retest reliability at a 1–2 week interval (ICC = 0.90). It showed significant and expected correlations with the criterion measures with the exception of the Euroqol (Pearson = 0.15). Conclusion Psychometric properties of the Spanish version of the MAAS in patients with FM are adequate. The dimensionality of the MAAS found in this sample and directions for future research are discussed.

Bias and learning in temporal binding: intervals between actions and outcomes are compressed by prior bias

It has consistently been shown that agents judge the intervals between their actions and outcomes as compressed in time, an effect named intentional binding. In the present work, we investigated whether this effect is result of prior bias volunteers have about the timing of the consequences of their actions, or if it is due to learning that occurs during the experimental session. Volunteers made temporal estimates of the interval between their action and target onset (Action conditions), or between two events (No-Action conditions). Our results show that temporal estimates become shorter throughout each experimental block in both conditions. Moreover, we found that observers judged intervals between action and outcomes as shorter even in very early trials of each block. To quantify the decrease of temporal judgments in experimental blocks, exponential functions were fitted to participants’ temporal judgments. The fitted parameters suggest that observers had different prior biases as to intervals between events in which action was involved. These findings suggest that prior bias might play a more important role in this effect than calibration-type learning processes.

A partial dependence factorial analysis to deal with selection bias in observational studis

This thesis presents a creative and practical approach to dealing with the problem of selection bias. Selection bias may be the most important vexing problem in program evaluation or in any line of research that attempts to assert causality. Some of the greatest minds in economics and statistics have scrutinized the problem of selection bias, with the resulting approaches – Rubin’s Potential Outcome Approach(Rosenbaum and Rubin,1983; Rubin, 1991,2001,2004) or Heckman’s Selection model (Heckman, 1979) – being widely accepted and used as the best fixes. These solutions to the bias that arises in particular from self selection are imperfect, and many researchers, when feasible, reserve their strongest causal inference for data from experimental rather than observational studies. The innovative aspect of this thesis is to propose a data transformation that allows measuring and testing in an automatic and multivariate way the presence of selection bias. The approach involves the construction of a multi-dimensional conditional space of the X matrix in which the bias associated with the treatment assignment has been eliminated. Specifically, we propose the use of a partial dependence analysis of the X-space as a tool for investigating the dependence relationship between a set of observable pre-treatment categorical covariates X and a treatment indicator variable T, in order to obtain a measure of bias according to their dependence structure. The measure of selection bias is then expressed in terms of inertia due to the dependence between X and T that has been eliminated. Given the measure of selection bias, we propose a multivariate test of imbalance in order to check if the detected bias is significant, by using the asymptotical distribution of inertia due to T (Estadella et al. 2005) , and by preserving the multivariate nature of data. Further, we propose the use of a clustering procedure as a tool to find groups of comparable units on which estimate local causal effects, and the use of the multivariate test of imbalance as a stopping rule in choosing the best cluster solution set. The method is non parametric, it does not call for modeling the data, based on some underlying theory or assumption about the selection process, but instead it calls for using the existing variability within the data and letting the data to speak. The idea of proposing this multivariate approach to measure selection bias and test balance comes from the consideration that in applied research all aspects of multivariate balance, not represented in the univariate variable- by-variable summaries, are ignored. The first part contains an introduction to evaluation methods as part of public and private decision process and a review of the literature of evaluation methods. The attention is focused on Rubin Potential Outcome Approach, matching methods, and briefly on Heckman’s Selection Model. The second part focuses on some resulting limitations of conventional methods, with particular attention to the problem of how testing in the correct way balancing. The third part contains the original contribution proposed , a simulation study that allows to check the performance of the method for a given dependence setting and an application to a real data set. Finally, we discuss, conclude and explain our future perspectives.

Tecniche di progettazione tollerante alle variazioni per circuiti digitali in tecnologie nanometriche

The digital electronic market development is founded on the continuous reduction of the transistors size, to reduce area, power, cost and increase the computational performance of integrated circuits. This trend, known as technology scaling, is approaching the nanometer size. The lithographic process in the manufacturing stage is increasing its uncertainty with the scaling down of the transistors size, resulting in a larger parameter variation in future technology generations. Furthermore, the exponential relationship between the leakage current and the threshold voltage, is limiting the threshold and supply voltages scaling, increasing the power density and creating local thermal issues, such as hot spots, thermal runaway and thermal cycles. In addiction, the introduction of new materials and the smaller devices dimension are reducing transistors robustness, that combined with high temperature and frequently thermal cycles, are speeding up wear out processes. Those effects are no longer addressable only at the process level. Consequently the deep sub-micron devices will require solutions which will imply several design levels, as system and logic, and new approaches called Design For Manufacturability (DFM) and Design For Reliability. The purpose of the above approaches is to bring in the early design stages the awareness of the device reliability and manufacturability, in order to introduce logic and system able to cope with the yield and reliability loss. The ITRS roadmap suggests the following research steps to integrate the design for manufacturability and reliability in the standard CAD automated design flow: i) The implementation of new analysis algorithms able to predict the system thermal behavior with the impact to the power and speed performances. ii) High level wear out models able to predict the mean time to failure of the system (MTTF). iii) Statistical performance analysis able to predict the impact of the process variation, both random and systematic. The new analysis tools have to be developed beside new logic and system strategies to cope with the future challenges, as for instance: i) Thermal management strategy that increase the reliability and life time of the devices acting to some tunable parameter,such as supply voltage or body bias. ii) Error detection logic able to interact with compensation techniques as Adaptive Supply Voltage ASV, Adaptive Body Bias ABB and error recovering, in order to increase yield and reliability. iii) architectures that are fundamentally resistant to variability, including locally asynchronous designs, redundancy, and error correcting signal encodings (ECC). The literature already features works addressing the prediction of the MTTF, papers focusing on thermal management in the general purpose chip, and publications on statistical performance analysis. In my Phd research activity, I investigated the need for thermal management in future embedded low-power Network On Chip (NoC) devices.I developed a thermal analysis library, that has been integrated in a NoC cycle accurate simulator and in a FPGA based NoC simulator. The results have shown that an accurate layout distribution can avoid the onset of hot-spot in a NoC chip. Furthermore the application of thermal management can reduce temperature and number of thermal cycles, increasing the systemreliability. Therefore the thesis advocates the need to integrate a thermal analysis in the first design stages for embedded NoC design. Later on, I focused my research in the development of statistical process variation analysis tool that is able to address both random and systematic variations. The tool was used to analyze the impact of self-timed asynchronous logic stages in an embedded microprocessor. As results we confirmed the capability of self-timed logic to increase the manufacturability and reliability. Furthermore we used the tool to investigate the suitability of low-swing techniques in the NoC system communication under process variations. In this case We discovered the superior robustness to systematic process variation of low-swing links, which shows a good response to compensation technique as ASV and ABB. Hence low-swing is a good alternative to the standard CMOS communication for power, speed, reliability and manufacturability. In summary my work proves the advantage of integrating a statistical process variation analysis tool in the first stages of the design flow.

Local home bias: Theory and new empirical evidence from Italy

This thesis examines the literature on local home bias, i.e. investor preference towards geographically nearby stocks, and investigates the role of firm’s visibility, profitability, and opacity in explaining such behavior. While firm’s visibility is expected to proxy for the behavioral root originating such a preference, firm’s profitability and opacity are expected to capture the informational one. I find that less visible, and more profitable and opaque firms, conditionally to the demand, benefit from being headquartered in regions characterized by a scarcity of listed firms (local supply of stocks). Specifically, research estimates suggest that firms headquartered in regions with a poor supply of stocks would be worth i) 11 percent more if non-visible, non-profitable and non-opaque; ii) 16 percent more if profitable; and iii) 28 percent more if both profitable and opaque. Overall, as these features are able to explain most, albeit not all, of the local home bias effect, I reasonably argue and then assess that most of the preference for local is determined by a successful attempt to exploit local information advantage (60 percent), while the rest is determined by a mere (irrational) feeling of familiarity with the local firm (40 percent). Several and significant methodological, theoretical, and practical implications come out.

Apprendimento e self-awareness in robotica

Esposizione delle basi teoriche e delle tecniche di apprendimento in robotica, analisi del concetto di self-awareness ed esempi applicativi, concetti derivati quali continous self modelling e self-reflection, e casi di studio esemplificativi.

Un Sistema di Parcheggio Intelligente basato su Context-Awareness

Sistema di segnalazione automatica posti auto su strada. Implementato per Android con tecniche di apprendimento automatico supervisionato e Bluetooth per realizzare un'applicazione Context-Aware.

'Alternate-goal bias' in antisaccades and the influence of expectation

Saccadic performance depends on the requirements of the current trial, but also may be influenced by other trials in the same experiment. This effect of trial context has been investigated most for saccadic error rate and reaction time but seldom for the positional accuracy of saccadic landing points. We investigated whether the direction of saccades towards one goal is affected by the location of a second goal used in other trials in the same experimental block. In our first experiment, landing points ('endpoints') of antisaccades but not prosaccades were shifted towards the location of the alternate goal. This spatial bias decreased with increasing angular separation between the current and alternative goals. In a second experiment, we explored whether expectancy about the goal location was responsible for the biasing of the saccadic endpoint. For this, we used a condition where the saccadic goal randomly changed from one trial to the next between locations on, above or below the horizontal meridian. We modulated the prior probability of the alternate-goal location by showing cues prior to stimulus onset. The results showed that expectation about the possible positions of the saccadic goal is sufficient to bias saccadic endpoints and can account for at least part of this phenomenon of 'alternate-goal bias'.

Assessment of publication bias in dental specialty journals

OBJECTIVE: The purpose of this study was to investigate the presence of publication bias (acceptance of articles indicating statistically significant results). METHODS: The journals possessing the highest impact factor (2008 data) in each dental specialty were included in the study. The content of the 6 most recent issues of each journal was hand searched and research articles were classified into 4 type categories: cross-sectional, case-control, cohort, and interventional (nonrandomized clinical trials and randomized controlled trials). In total, 396 articles were included in the analysis. Descriptive statistics and univariate and multivariate logistic regression was used to examine the association between article-reported statistical significance (dependent variable) and journal impact factor and article study type subject area (independent variables). RESULTS: A statistically significant acceptance rate of positive result was found, ranging from 75% to 90%, whereas the value of impact factor was not related to publication bias among leading dental journals. Compared with other research designs, clinical intervention studies (randomized or nonrandomized) presented the highest percentage of nonsignificant findings (20%); RCTs represented 6% of the examined investigations. CONCLUSIONS: Compared with the Journal of Clinical Periodontology, all other subspecialty journals, except the Journal of Oral and Maxillofacial Surgery, showed significantly decreased odds of publishing an RCT, which ranged from 60% to 93% (P < .05).

Avoidance and inhibition do not predict nonrespondent bias among patients with inflammatory bowel disease

It has been suggested that participant withdrawal from studies can bias estimates. However, this is only possible when withdrawers and nonwithdrawers differ in an important way. We tested the hypothesis that withdrawers are more likely than nonwithdrawers to be avoidant and negatively affected.

[Evaluation of a preschool program to promote phonological awareness and letter-sound correspondence--long-term effects in the prevention of dyslexia at the end of the 3rd and 4th grades]

The present study evaluates the long-term effects of a preschool training in phonological awareness and letter- sound correspondence.