Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptação cultural do questionário Speech, Spatial and Qualities of Hearing Scale (SSQ) para o Português Brasileiro

Objetivo Traduzir e adaptar, culturalmente, o questionario Speech, Spatial and Qualities of Hearing Scale(SSQ) para o Portugues Brasileiro.Metodos Foi realizada a traducao, retrotraducao, avaliacao por comite de especialistas e adaptacao cultural (pre-teste). A fase de adaptacao cultural constou da aplicacao do questionario em 40 brasileiros adultos, normo-ouvintes e alfabetizados em portugues. Foram elaboradas duas versoes do SSQ em portugues, a primeira aplicada no Grupo Piloto 1 (20 sujeitos) e, apos revisao do comite de especialistas, uma segunda versao foi aplicada no Grupo Piloto 2 (20 sujeitos). Para haver equivalencia cultural do questionario, e necessario que 85% dos individuos nao apresentem dificuldades para compreender as questoes. A consistencia interna do SSQ, em portugues, foi verificada por meio do coeficiente alfa de Cronbach.Resultados Foi identificada dificuldade de compreensao na questao 14 da Parte 2 e na questao 5 da Parte 3. As demais questoes foram compreendidas por mais de 85% dos participantes. As questoes problematicas foram revistas e modificadas, de forma a nao alterar o contexto. Na aplicacao da versao final do SSQ foi obtida uma boa equivalencia cultural para o Portugues Brasileiro, ja que 91,6% dos participantes relataram facil entendimento de todas as questoes. A analise estatistica revelou alto coeficiente alpha de Cronbach (>0,8), demonstrando boa consistencia interna entre os diversos itens do questionario.Conclusao A metodologia empregada foi eficaz para estabelecer a traducao e equivalencia cultural do SSQ para o Portugues Brasileiro.
Supporting “Everyday Analysts” in Safety- and Time-Critical Situations

The need for quick, timely, and accurate information is critical in emergency events. During mass emergencies, people assemble information from both official and unofficial sources. As digital access expands, people will increasingly incorporate information from digital sources into decision making and assess it against the local circumstances they experience. If we extrapolate what such behavior means for the future, we can see that information management under emergency conditions will need to become increasingly socially distributed. The key question then is how to assess the quality of information: how “good” or “bad” it is; whether it is “misinformation” or “disinformation. ” Borrowing from Simon's notion of satisficing, the authors argue that people's assessment of information helpfulness and credibility is a function of the “everyday analytic” skills they employ during mass emergencies. To facilitate the critical work of “everyday analysts,” we outline a research agenda for the development of analytical support tools.
Validation of a parent report measure of cognitive development in very preterm infants

Parental report may provide an inexpensive alternative to standardized assessments of children's development. We have adapted and validated a parental questionnaire on cognitive development for use with very preterm infants. Sixty‐four 2‐year‐olds (28 males, 36 females) born less than 30 weeks' gestation (median 28.5 weeks, range 23 to 31 weeks), median birth weight 980g (range 500 to 1905g) were assessed using the Mental Development Index (MDI) of the Bayley Scales of Infant Development‐II and the parental questionnaire. Significant correlations between parent report and MDI scores (r=0.54−0.68, p<0.001) indicated good concurrent validity. Diagnostic use of the parent report for predicting an MDI score of less than 70 was assessed by using receiver operating characteristic (ROC) curves. The optimal cut off produced equal sensitivity and specificity (81%), indicating good discriminatory power in diagnosing developmental delay. Test‐retest reliability was demonstrated and accuracy of parent reporting was not affected by sociodemographic factors. Our questionnaire provides a valid outcome measure for use in randomized trials or large population surveys.
Fast alignment using probabilistic indexing

The alignment method is a model-based object recognition technique that determines possible object transformations from three hypothesized matches of model and image points. For images and/or models with many features, the running time of the alignment method can be large. Methods of reducing the number of matches that must be examined are presented. The techniques described are the use of the probabilistic indexing system, and the elimination of groups of model points that produce large errors in the transformation determined by the alignment method. Results are presented which show that it is possible to achieve a speedup of over two orders of magnitude while still finding a correct alignment. <<ETX>>
Design parameters and uncertainty bound estimation functions for adaptive-robust control of robot manipulators

In this paper, a parameter and uncertainty bound estimation functions for adaptive-robust control of robot manipulators are developed. A Lyapunov function is defined and parameters and uncertainty bound estimation functions are developed based on the Lyapunov function. Thus, stability of an uncertain system is guaranteed and uniform boundedness of the tracking error is achieved. As distinct from previous parameter and bound estimation laws, the parameters and uncertainty bounds are updated as a function of a combination of trigonometric function depending on robot parameters and tracking error. Based on the same Lyapunov function, a robust control law is also defined and the stability of the uncertain system is proved under the same set of conditions. Simulation results are given to illustrate the tracking performance of the proposed adaptive-robust controller.
Insulin sensitivity, insulinemia, and coronary artery disease: the Insulin Resistance Atherosclerosis Study.

OBJECTIVE The aim of this study was to evaluate whether low insulin sensitivity (Si) measured using a modified frequently sampled intravenous glucose tolerance test with minimal model analysis is associated with coronary artery disease (CAD) independent of other cardiovascular risk factors. RESEARCH DESIGN AND METHODS We studied 1,482 women and men, age 40-69 years old, African American (28%), Hispanic (34%), or non-Hispanic white (38%), with normal (45%), impaired (23%), or diabetic (32%) glucose tolerance. CAD defined as confirmed past myocardial infarction, coronary artery bypass graft, coronary angioplasty, or presence of a major Q-wave was found in 91 participants. RESULTS The odds ratio (OR) for CAD was greatest among individuals in the two lowest quintiles of Si (2.4, 95% CI 1.0-5.6 and 4.7, 2.1-10.7) compared with the highest Si quintile. After adjusting for demographic and cardiovascular risk factors, a decrement from the 75th to 25th percentile in Si was associated with a 56% increase in CAD (P=0.028). Similar increments in fasting or 2-h insulin levels were associated with, respectively, only 15 (NS) and 3% (NS) increases in CAD. The association between Si and CAD was partially mediated by insulin, HDL cholesterol and triglyceride levels, hypertension, diabetes, and obesity, but not LDL cholesterol or cigarette smoking. CONCLUSIONS Low Si is associated with CAD independently of and stronger than plasma insulin levels. Part of the association is accounted for by dyslipidemia, hypertension, diabetes, and obesity.
Update on biologicals for treatment of juvenile idiopathic arthritis

Introduction: The development of biologics has markedly changed the treatment of JIA. Complete control of the disease and remission has today become the main goal of treatment preventing long-term damage and disability. Areas covered: This review gives an overview of the current treatment options using biologics in JIA. The biologic drugs are discussed on the basis of recent clinical trials. Expert opinion: While JIA is a group of heterogeneous diseases, differences in their biology turned out to influence treatment success with different biologics. TNF inhibitors emerged to be the most commonly used biologics for the treatment of JIA. First they were successful for the treatment of rheumatoid factor positive and negative polyarticular JIA. TNF inhibitors have also been studied in patients with enthesitis-related arthritis, psoriatic arthritis, and extended olioarthritis, and approval of at least etanercept is expected. Second-line biologics are abatacept and tocilizumab. For systemic onset JIA, tocilizumab, and the IL-1 inhibitors anakinra and canakinumab have been successfully studied. In the treatment of JIA, biologics have emerged as potent drugs to control the disease. New advancements will be crucial for further improvement of treatment options in JIA.
Adaptive Harmonic IIR Notch Filters for Frequency Estimation and Tracking

In many signal processing applications, adaptive frequency estimation and tracking of noisy narrowband signals is often required in communications, radar, sonar, controls, biomedical signal processing, and the applications such as detection of a noisy sinusoidal signal and cancellation of periodic signals. In order to achieve the objective of frequency tracking and estimation, an adaptive finite impulse response (FIR) filter or an adaptive infinite impulse response (IIR) notch filter is generally applied. Although an adaptive FIR filter has the stability advantage over an adaptive IIR notch filter, it requires a larger number of filter coefficients. In practical situations, an adaptive IIR notch filter (Chicharo & Ng, 1990; Kwan & Martin, 1989; Nehorai, 1985) is preferred due to its less number of filter coefficients and hence less computational complexity. More importantly, a second-order adaptive pole/zero constrained IIR notch filter (Xiao et al, 2001; Zhou & Li, 2004) can effectively be applied to track a single sinusoidal signal. If a signal contains multiple frequency components, then we can estimate and track its frequencies using a higher-order adaptive IIR notch filter constructed by cascading second-order adaptive IIR notch filters (Kwan & Martin, 1989). To ensure the global minimum convergence, the filter algorithm must begin with initial conditions, which require prior knowledge of the signal frequencies. However, in many practical situations, a sinusoidal signal may be subjected to nonlinear effects (Tan & Jiang, 2009a, 2009b) in which possible harmonic frequency components are generated. For example, the signal acquired from a sensor may undergo saturation through an amplifier. In such an environment, we may want to estimate and track the signal’s fundamental frequency as well as any harmonic frequencies. Using a second-order adaptive IIR notch filter to estimate fundamental and harmonic frequencies is insufficient, since it only accommodates one frequency component. On the other hand, applying a higher-order IIR notch filter may not be effective due to adopting multiple adaptive filter coefficients and local minimum convergence of the adaptive algorithm. In addition, monitoring the global minimum using a grid search method requires a huge number of computations, and thus makes the notch filter impractical in real time processing. Therefore, in this chapter, we propose and investigate a novel adaptive harmonic IIR notch filter with a single adaptive coefficient to efficiently perform frequency estimation and tracking in a harmonic frequency environment.
Systemic Inflammatory Response Syndrome in Tissue-Type Plasminogen Activator–Treated Patients is Associated With Worse Short-term Functional Outcome

Background and Purpose— Systemic inflammatory response syndrome (SIRS) is a generalized inflammatory state. The primary goal of the study was to determine whether differences exist in outcomes in SIRS and non-SIRS intravenous tissue-type plasminogen activator–treated patients. Methods— Consecutive patients were retrospectively reviewed for the evidence of SIRS during their admission. SIRS was defined as the presence of ≥2 of the following: body temperature <36°C or >38°C, heart rate >90, respiratory rate >20, and white blood cells <4000/mm or >12 000 mm, or >10% bands. Patients diagnosed with infection (via positive culture) were excluded. Results— Of the 241 patients, 44 had evidence of SIRS (18%). Adjusting for pre–tissue-type plasminogen activator National Institutes of Health Stroke Scale, age, and race, SIRS remained a predictor of poor functional outcome at discharge (odds ratio [OR], 2.58; 95% confidence interval [CI], 1.16–5.73; P=0.0197). Conclusions— In our sample of tissue-type plasminogen activator–treated (tPA) patients, ~1 in 5 patients developed SIRS. Furthermore, we found the presence of SIRS to be associated with poor short-term functional outcomes and prolonged length of stay.
Touch & connect and touch & select: interacting with a computer by touching it with a mobile phone

Exchanging data between a mobile phone and a computer such as a laptop is still a very cumbersome process. This paper presents two different techniques, touch & connect and touch & select, designed help to overcome this problem and facilitate and speed up spontaneous interactions between such devices. Using touch & connect, the user can physically touch a computer in order to pair a Bluetooth connection and initiate a file transfer between these two devices. Touch & select extends this concept in that users can select a specific object or location on the computer screen by simply touching it with the mobile phone. We report the implementation of these interaction techniques based on Near Field Communication (NFC) tags and present a formal, comparative study focusing on transferring images. The results provide clear evidence of the advantages of touch & connect and touch & select when compared with current Bluetooth-based implementations. Considering task completion time for uploading and downloading pictures, touch & select was 43% and touch & connect 31% faster than the conventional Bluetooth-based approach.
Habits in Context: A Synthesis, with Implications for Research in Occupational Science

Habits, rather than being mundane or trivial, are significant learned behaviors embedded in an ecocultural context (of time, place, and society) with which they engage in a dialectical relationship. Habits enable or frustrate adaptation to environmental challenges. In a positive mode, habits relate to personal meaning, identity, competence, satisfaction, and self-expression. The study of habits requires adoption of an ethical, scholarly, and holistic approach. Occupational science needs to continue its investigation and synthesis of interdisciplinary knowledge about habits, including identification of the environmental conditions that further occupation; the “affordances” (environmental potentials for action) that provide occupational resources; the habit patterns that contribute to health, and to identification and reclamation of people's strengths, capabilities, and interests; the process of learning of new habits; reconstruction of the self through habit change; and the relationship of engagement in occupation to being in place in one's ecoculture. Such study may require that occupational scientists critically assess their epistemological assumptions and research approaches.
A polynomial segment model based statistical parametric speech synthesis sytem

In this paper, we present a statistical parametric speech synthesis system based on the polynomial segment model (PSM). As one of the segmental models for speech signals, PSM explicitly describes the trajectory of the features in a speech segment, and keeps the internal dynamics of the segment. In this work, spectral and excitation parameters are modeled by PSMs simultaneously, while the duration for each segment is modeled by a single Gaussian distribution. A top-down K-means clustering technique is applied for model tying. Mean trajectories acquired from PSMs are used directly to generate speech parameters according to the estimated segment duration. An English speech synthesizer back-end is implemented on CMU Arctic corpus and the performance of the new approach is compared with the classical HMM-based one. Experimental results show that PSM modeling can achieve similar naturalness and intelligence of the synthetic speech as HMM modeling. The system is in the early stage of its development.
A Gaussian Process Based Online Change Detection Algorithm for Monitoring Periodic Time Series

Online time series change detection is a critical component of many monitoring systems, such as space and air-borne remote sensing instruments, cardiac monitors, and network traffic profilers, which continuously analyze observations recorded by sensors. Data collected by such sensors typically has a periodic (seasonal) component. Most existing time series change detection methods are not directly applicable to handle such data, either because they are not designed to handle periodic time series or because they cannot operate in an online mode. We propose an online change detection algorithm which can handle periodic time series. The algorithm uses a Gaussian process based non-parametric time series prediction model and monitors the difference between the predictions and actual observations within a statistically principled control chart framework to identify changes. A key challenge in using Gaussian process in an online mode is the need to solve a large system of equations involving the associated covariance matrix which grows with every time step. The proposed algorithm exploits the special structure of the covariance matrix and can analyze a time series of length T in O(T^2) time while maintaining a O(T) memory footprint, compared to O(T^4) time and O(T^2) memory requirement of standard matrix manipulation methods. Wemore » experimentally demonstrate the superiority of the proposed algorithm over several existing time series change detection algorithms on a set of synthetic and real time series. Finally, we illustrate the effectiveness of the proposed algorithm for identifying land use land cover changes using Normalized Difference Vegetation Index (NDVI) data collected for an agricultural region in Iowa state, USA. Our algorithm is able to detect different types of changes in a NDVI validation data set (with ~80% accuracy) which occur due to crop type changes as well as disruptive changes (e.g., natural disasters). « less
Epidemiological study of child & adolescent psychiatric disorders in urban & rural areas of Bangalore, India.

BACKGROUND & OBJECTIVE There are limited data on child mental health needs in our country. Therefore, an epidemiological study to determine the prevalence rates of child and adolescent psychiatric disorders was initiated as a two-centre (Bangalore and Lucknow) study by the Indian Council of Medical Research. It also aimed to study the psychosocial correlates of the psychiatric disorders. We present here the findings of Bangalore Centre. METHODS In Bangalore, 2064 children aged 0-16 yr, were selected by stratified random sampling from urban middle-class, urban slum and rural areas. The screening stage was followed by a detailed evaluation stage. The ICD-10 DCR criteria were used to reach a penta-axial diagnosis. RESULTS The results indicated a prevalence rate of 12.5 per cent among children aged 0-16 yr. There were no significant differences among prevalence rates in urban middle class, slum and rural areas. The psychiatric morbidity among 0-3 yr old children was 13.8 per cent with the most common diagnoses being breath holding spells, pica, behaviour disorder NOS, expressive language disorder and mental retardation. The prevalence rate in the 4-16 yr old children was 12.0 per cent. Enuresis, specific phobia, hyperkinetic disorders, stuttering and oppositional defiant disorder were the most frequent diagnoses. When impairment associated with the disorder was assessed, significant disability was found in 5.3 per cent of the 4-16 yr group. Assessment of felt treatment needs indicated that only 37.5 per cent of the families perceived that their children had any problem. Physical abuse and parental mental disorder were significantly associated with psychiatric disorders. INTERPRETATION & CONCLUSION Prevalence rates of psychiatric morbidity in 0-16 yr old children in India were found to be lower than Western figures. Middle class urban areas had highest and urban slum areas had lowest prevalence rates. The implications for clinical training, practice and policy initiatives are discussed.
on ‘ Diet and mental health ’ Food for thought : the role of dietary flavonoids in enhancing human memory , learning and neurocognitive performance

Emerging evidence suggests that dietary-derived flavonoids have the potential to improve human memory and neuro-cognitive performance via their ability to protect vulnerable neurons, enhance existing neuronal function and stimulate neuronal regeneration. Long-term potentiation (LTP) is widely considered to be one of the major mechanisms underlying memory acquisition, consolidation and storage in the brain and is known to be controlled at the molecular level by the activation of a number of neuronal signalling pathways. These pathways include the phosphatidylinositol-3 kinase/protein kinase B/Akt (Akt), protein kinase C, protein kinase A, Ca–calmodulin kinase and mitogen-activated protein kinase pathways. Growing evidence suggests that flavonoids exert effects on LTP, and consequently memory and cognitive performance, through their interactions with these signalling pathways. Of particular interest is the ability of flavonoids to activate the extracellular signal-regulated kinase and the Akt signalling pathways leading to the activation of the cAMP-response element-binding protein, a transcription factor responsible for increasing the expression of a number of neurotrophins important in LTP and long-term memory. One such neurotrophin is brain-derived neurotrophic factor, which is known to be crucial in controlling synapse growth, in promoting an increase in dendritic spine density and in enhancing synaptic receptor density. The present review explores the potential of flavonoids and their metabolite forms to promote memory and learning through their interactions with neuronal signalling pathways pivotal in controlling LTP and memory in human subjects.
Investigation of Torque Characteristics in a Novel Permanent Magnet Flux Switching Machine With an Outer-Rotor Configuration

This paper comprehensively investigates the torque characteristics of a novel permanent magnet flux switching (PMFS) machine with outer-rotor configuration. Due to the nature of severe magnetic saturations in the machine, it is of particular interest to ascertain the extent of impact of the load conditions on the overall torque output as well as its component parts. The frozen permeability techniques are implemented in finite element analysis (FEA) to segregate the output torque of the outer-rotor PMFS machine into three parts: cogging torque, reluctance torque, and permanent magnet torque. 2-D FEA is first employed to reveal the effects of phase current amplitudes and angles on those three torque components as well as the overall torque, while the 3-D FEA is carried out to further uncover the influences of end effects on the torque characteristics of the machine. Finally, experimental tests on a prototype machine are performed to validate the torque characteristic predictions by FEA.