Evaluación de la psicopatología del preescolar mediante el Early Childhood Inventory-4 (ECI-4): concordancia entre padres y maestros.= Assessment of psychopathology in preschool age children through the Early Childhood Inventory-4 (ECI-4): Agreement among parents and teachers

El objetivo principal de este estudio es conocer la concordancia entre informantes, padres y maestros, en cada una de las dimensiones o categorías diagnósticas del Early Childhood Inventory-4 (ECI-4). Además, se pretende analizar la influencia de la presencia de problemas de salud en los padres en la descripción y valoración de la conducta de una muestra de 204 alumnos de preescolar (3 a 6 años) de perfiles socioeconómicos diferentes. Los resultados indican que los padres tienden a valorar con mayor severidad los síntomas, observándose una mayor concordancia entre informantes en los relativos a los trastornos del desarrollo

A hybrid approach of knowledge-based reasoning for structural assessment

La idea básica de detección de defectos basada en vibraciones en Monitorización de la Salud Estructural (SHM), es que el defecto altera las propiedades de rigidez, masa o disipación de energía de un sistema, el cual, altera la respuesta dinámica del mismo. Dentro del contexto de reconocimiento de patrones, esta tesis presenta una metodología híbrida de razonamiento para evaluar los defectos en las estructuras, combinando el uso de un modelo de la estructura y/o experimentos previos con el esquema de razonamiento basado en el conocimiento para evaluar si el defecto está presente, su gravedad y su localización. La metodología involucra algunos elementos relacionados con análisis de vibraciones, matemáticas (wavelets, control de procesos estadístico), análisis y procesamiento de señales y/o patrones (razonamiento basado en casos, redes auto-organizativas), estructuras inteligentes y detección de defectos. Las técnicas son validadas numérica y experimentalmente considerando corrosión, pérdida de masa, acumulación de masa e impactos. Las estructuras usadas durante este trabajo son: una estructura tipo cercha voladiza, una viga de aluminio, dos secciones de tubería y una parte del ala de un avión comercial.

An integrated assessment of carbon dioxide capture and storage in the UK

Geological carbon dioxide storage (CCS) has the potential to make a significant contribution to the decarbonisation of the UK. Amid concerns over maintaining security, and hence diversity, of supply, CCS could allow the continued use of coal, oil and gas whilst avoiding the CO2 emissions currently associated with fossil fuel use. This project has explored some of the geological, environmental, technical, economic and social implications of this technology. The UK is well placed to exploit CCS with a large offshore storage capacity, both in disused oil and gas fields and saline aquifers. This capacity should be sufficient to store CO2 from the power sector (at current levels) for a least one century, using well understood and therefore likely to be lower-risk, depleted hydrocarbon fields and contained parts of aquifers. It is very difficult to produce reliable estimates of the (potentially much larger) storage capacity of the less well understood geological reservoirs such as non-confined parts of aquifers. With the majority of its large coal fired power stations due to be retired during the next 15 to 20 years, the UK is at a natural decision point with respect to the future of power generation from coal; the existence of both national reserves and the infrastructure for receiving imported coal makes clean coal technology a realistic option. The notion of CCS as a ‘bridging’ or ‘stop-gap’ technology (i.e. whilst we develop ‘genuinely’ sustainable renewable energy technologies) needs to be examined somewhat critically, especially given the scale of global coal reserves. If CCS plant is built, then it is likely that technological innovation will bring down the costs of CO2 capture, such that it could become increasingly attractive. As with any capitalintensive option, there is a danger of becoming ‘locked-in’ to a CCS system. The costs of CCS in our model for UK power stations in the East Midlands and Yorkshire to reservoirs in the North Sea are between £25 and £60 per tonne of CO2 captured, transported and stored. This is between about 2 and 4 times the current traded price of a tonne of CO2 in the EU Emissions Trading Scheme. In addition to the technical and economic requirements of the CCS technology, it should also be socially and environmentally acceptable. Our research has shown that, given an acceptance of the severity and urgency of addressing climate change, CCS is viewed favourably by members of the public, provided it is adopted within a portfolio of other measures. The most commonly voiced concern from the public is that of leakage and this remains perhaps the greatest uncertainty with CCS. It is not possible to make general statements concerning storage security; assessments must be site specific. The impacts of any potential leakage are also somewhat uncertain but should be balanced against the deleterious effects of increased acidification in the oceans due to uptake of elevated atmospheric CO2 that have already been observed. Provided adequate long term monitoring can be ensured, any leakage of CO2 from a storage site is likely to have minimal localised impacts as long as leaks are rapidly repaired. A regulatory framework for CCS will need to include risk assessment of potential environmental and health and safety impacts, accounting and monitoring and liability for the long term. In summary, although there remain uncertainties to be resolved through research and demonstration projects, our assessment demonstrates that CCS holds great potential for significant cuts in CO2 emissions as we develop long term alternatives to fossil fuel use. CCS can contribute to reducing emissions of CO2 into the atmosphere in the near term (i.e. peak-shaving the future atmospheric concentration of CO2), with the potential to continue to deliver significant CO2 reductions over the long term.

Assessment of potential climate change impacts on peatland dissolved organic carbon release and drinking water treatment from laboratory experiments

Catchments draining peat soils provide the majority of drinking water in the UK. Over the past decades, concentrations of dissolved organic carbon (DOC) have increased in surface waters. Residual DOC can cause harmful carcinogenic disinfection by-products to form during water treatment processes. Increased frequency and severity of droughts combined with and increased temperatures expected as the climate changes, have potentials to change water quality. We used a novel approach to investigate links between climate change, DOC release and subsequent effects on drinking water treatment. We designed a climate manipulation experiment to simulate projected climate changes and monitored releases from peat soil and litter, then simulated coagulation used in water treatment. We showed that the ‘drought’ simulation was the dominant factor altering DOC release and affected the ability to remove DOC. Our results imply that future short-term drought events could have a greater impact than increased temperature on DOC treatability.

Automatic and objective assessment of alternating tapping performance in Parkinson’s disease

This paper presents the development and evaluation of a method for enabling quantitative and automatic scoring of alternating tapping performance of patients with Parkinson’s disease (PD). Ten healthy elderly subjects and 95 patients in different clinical stages of PD have utilized a touch-pad handheld computer to perform alternate tapping tests in their home environments. First, a neurologist used a web-based system to visually assess impairments in four tapping dimensions (‘speed’, ‘accuracy’, ‘fatigue’ and ‘arrhythmia’) and a global tapping severity (GTS). Second, tapping signals were processed with time series analysis and statistical methods to derive 24 quantitative parameters. Third, principal component analysis was used to reduce the dimensions of these parameters and to obtain scores for the four dimensions. Finally, a logistic regression classifier was trained using a 10-fold stratified cross-validation to map the reduced parameters to the corresponding visually assessed GTS scores. Results showed that the computed scores correlated well to visually assessed scores and were significantly different across Unified Parkinson’s Disease Rating Scale scores of upper limb motor performance. In addition, they had good internal consistency, had good ability to discriminate between healthy elderly and patients in different disease stages, had good sensitivity to treatment interventions and could reflect the natural disease progression over time. In conclusion, the automatic method can be useful to objectively assess the tapping performance of PD patients and can be included in telemedicine tools for remote monitoring of tapping.

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

Assessment of PD Speech Anomalies @ Home

Background: Voice processing in real-time is challenging. A drawback of previous work for Hypokinetic Dysarthria (HKD) recognition is the requirement of controlled settings in a laboratory environment. A personal digital assistant (PDA) has been developed for home assessment of PD patients. The PDA offers sound processing capabilities, which allow for developing a module for recognition and quantification HKD. Objective: To compose an algorithm for assessment of PD speech severity in the home environment based on a review synthesis. Methods: A two-tier review methodology is utilized. The first tier focuses on real-time problems in speech detection. In the second tier, acoustics features that are robust to medication changes in Levodopa-responsive patients are investigated for HKD recognition. Keywords such as Hypokinetic Dysarthria , and Speech recognition in real time were used in the search engines. IEEE explorer produced the most useful search hits as compared to Google Scholar, ELIN, EBRARY, PubMed and LIBRIS. Results: Vowel and consonant formants are the most relevant acoustic parameters to reflect PD medication changes. Since relevant speech segments (consonants and vowels) contains minority of speech energy, intelligibility can be improved by amplifying the voice signal using amplitude compression. Pause detection and peak to average power rate calculations for voice segmentation produce rich voice features in real time. Enhancements in voice segmentation can be done by inducing Zero-Crossing rate (ZCR). Consonants have high ZCR whereas vowels have low ZCR. Wavelet transform is found promising for voice analysis since it quantizes non-stationary voice signals over time-series using scale and translation parameters. In this way voice intelligibility in the waveforms can be analyzed in each time frame. Conclusions: This review evaluated HKD recognition algorithms to develop a tool for PD speech home-assessment using modern mobile technology. An algorithm that tackles realtime constraints in HKD recognition based on the review synthesis is proposed. We suggest that speech features may be further processed using wavelet transforms and used with a neural network for detection and quantification of speech anomalies related to PD. Based on this model, patients' speech can be automatically categorized according to UPDRS speech ratings.

Automatic spiral analysis for objective assessment of motor symptoms in Parkinson's disease

Objective: To develop a method for objective quantification of PD motor symptoms related to Off episodes and peak dose dyskinesias, using spiral data gathered by using a touch screen telemetry device. The aim was to objectively characterize predominant motor phenotypes (bradykinesia and dyskinesia), to help in automating the process of visual interpretation of movement anomalies in spirals as rated by movement disorder specialists. Background: A retrospective analysis was conducted on recordings from 65 patients with advanced idiopathic PD from nine different clinics in Sweden, recruited from January 2006 until August 2010. In addition to the patient group, 10 healthy elderly subjects were recruited. Upper limb movement data were collected using a touch screen telemetry device from home environments of the subjects. Measurements with the device were performed four times per day during week-long test periods. On each test occasion, the subjects were asked to trace pre-drawn Archimedean spirals, using the dominant hand. The pre-drawn spiral was shown on the screen of the device. The spiral test was repeated three times per test occasion and they were instructed to complete it within 10 seconds. The device had a sampling rate of 10Hz and measured both position and time-stamps (in milliseconds) of the pen tip. Methods: Four independent raters (FB, DH, AJ and DN) used a web interface that animated the spiral drawings and allowed them to observe different kinematic features during the drawing process and to rate task performance. Initially, a number of kinematic features were assessed including ‘impairment’, ‘speed’, ‘irregularity’ and ‘hesitation’ followed by marking the predominant motor phenotype on a 3-category scale: tremor, bradykinesia and/or choreatic dyskinesia. There were only 2 test occasions for which all the four raters either classified them as tremor or could not identify the motor phenotype. Therefore, the two main motor phenotype categories were bradykinesia and dyskinesia. ‘Impairment’ was rated on a scale from 0 (no impairment) to 10 (extremely severe) whereas ‘speed’, ‘irregularity’ and ‘hesitation’ were rated on a scale from 0 (normal) to 4 (extremely severe). The proposed data-driven method consisted of the following steps. Initially, 28 spatiotemporal features were extracted from the time series signals before being presented to a Multilayer Perceptron (MLP) classifier. The features were based on different kinematic quantities of spirals including radius, angle, speed and velocity with the aim of measuring the severity of involuntary symptoms and discriminate between PD-specific (bradykinesia) and/or treatment-induced symptoms (dyskinesia). A Principal Component Analysis was applied on the features to reduce their dimensions where 4 relevant principal components (PCs) were retained and used as inputs to the MLP classifier. Finally, the MLP classifier mapped these components to the corresponding visually assessed motor phenotype scores for automating the process of scoring the bradykinesia and dyskinesia in PD patients whilst they draw spirals using the touch screen device. For motor phenotype (bradykinesia vs. dyskinesia) classification, the stratified 10-fold cross validation technique was employed. Results: There were good agreements between the four raters when rating the individual kinematic features with intra-class correlation coefficient (ICC) of 0.88 for ‘impairment’, 0.74 for ‘speed’, 0.70 for ‘irregularity’, and moderate agreements when rating ‘hesitation’ with an ICC of 0.49. When assessing the two main motor phenotype categories (bradykinesia or dyskinesia) in animated spirals the agreements between the four raters ranged from fair to moderate. There were good correlations between mean ratings of the four raters on individual kinematic features and computed scores. The MLP classifier classified the motor phenotype that is bradykinesia or dyskinesia with an accuracy of 85% in relation to visual classifications of the four movement disorder specialists. The test-retest reliability of the four PCs across the three spiral test trials was good with Cronbach’s Alpha coefficients of 0.80, 0.82, 0.54 and 0.49, respectively. These results indicate that the computed scores are stable and consistent over time. Significant differences were found between the two groups (patients and healthy elderly subjects) in all the PCs, except for the PC3. Conclusions: The proposed method automatically assessed the severity of unwanted symptoms and could reasonably well discriminate between PD-specific and/or treatment-induced motor symptoms, in relation to visual assessments of movement disorder specialists. The objective assessments could provide a time-effect summary score that could be useful for improving decision-making during symptom evaluation of individualized treatment when the goal is to maximize functional On time for patients while minimizing their Off episodes and troublesome dyskinesias.

Delaware Reservoirs’ Drought Risk Assessment: A Paleo View

The Delaware River provides half of New York City's drinking water, is a habitat for wild trout, American shad and the federally endangered dwarf wedge mussel. It has suffered four 100‐year floods in the last seven years. A drought during the 1960s stands as a warning of the potential vulnerability of the New York City area to severe water shortages if a similar drought were to recur. The water releases from three New York City dams on the Delaware River's headwaters impact not only the reliability of the city’s water supply, but also the potential impact of floods, and the quality of the aquatic habitat in the upper river. The goal of this work is to influence the Delaware River water release policies (FFMP/OST) to further benefit river habitat and fisheries without increasing New York City's drought risk, or the flood risk to down basin residents. The Delaware water release policies are constrained by the dictates of two US Supreme Court Decrees (1931 and 1954) and the need for unanimity among four states: New York, New Jersey, Pennsylvania, and Delaware ‐‐ and New York City. Coordination of their activities and the operation under the existing decrees is provided by the Delaware River Basin Commission (DRBC). Questions such as the probability of the system approaching drought state based on the current FFMP plan and the severity of the 1960s drought are addressed using long record paleo‐reconstructions of flows. For this study, we developed reconstructed total annual flows (water year) for 3 reservoir inflows using regional tree rings going back upto 1754 (a total of 246 years). The reconstructed flows are used with a simple reservoir model to quantify droughts. We observe that the 1960s drought is by far the worst drought based on 246 years of simulations (since 1754).

Increase in severity of molar-incisor hypomineralization and its relationship with the colour of enamel opacity: a prospective cohort study

Background. Predicting risk of posteruptive enamel breakdown (PEB) of molar-incisor hypomineralization (MIH) opacity is a difficult but important clinical task. Therefore, there is a need to evaluate these aspects through longitudinal studies.Objective. The aim of this longitudinal study was to analyse the relationship between colours of MIH opacity of children aged 6-12 (baseline) and other clinical and demographic variables involved in the increase in severity of MIH.Materials and methods. A blinded prospective 18-month follow-up was conducted with 147 individuals presenting mild MIH. Tooth-based incidence of increase in severity of MIH (PEB or atypical restorations) was used as dependent measurement. Enamel opacities were recorded according to colour shades of white, yellow and brown, allowing assessment of susceptibility to structural loss over time, according to colour of MIH opacity. Poisson regression models were used to adjust the results for demographic and clinical variables.Results. Brown and yellow MIH opacities were at higher risk for PEB and atypical restorations than those of white ones, even after adjustment for clinical and demographic variables.Conclusion. Teeth presenting mild MIH severity associated with yellow and brown enamel opacities were at high risk for increase in severity of MIH than lighter ones. This result could help clinicians determine a risk-based treatment for children with MIH.

Functional capacity of Brazilian patients with Parkinson's disease (PD): Relationship between clinical characteristics and disease severity

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The Brazilian Research Consortium on Obsessive-Compulsive Spectrum Disorders: recruitment, assessment instruments, methods for the development of multicenter collaborative studies and preliminary results

OBJETIVO: Descrever o recrutamento de pacientes, instrumentos de avaliação, métodos para o desenvolvimento de estudos colaborativos multicêntricos e os resultados preliminares do Consórcio Brasileiro de Pesquisa em Transtornos do Espectro Obsessivo-Compulsivo, que inclui sete centros universitários. MÉTODO: Este estudo transversal incluiu entrevistas semi-estruturadas (dados sociodemográficos, histórico médico e psiquiátrico, curso da doença e diagnósticos psiquiátricos comórbidos) e instrumentos que avaliam os sintomas do transtorno obsessivo-compulsivo (Escala para Sintomas Obsessivo-Compulsivos de Yale-Brown e Escala Dimensional para Sintomas Obsessivo-Compulsivos de Yale-Brown), sintomas depressivos (Inventário de Depressão de Beck), sintomas ansiosos (Inventário de Ansiedade de Beck), fenômenos sensoriais (Escala de Fenômenos Sensoriais da Universidade de São Paulo), juízo crítico (Escala de Avaliação de Crenças de Brown), tiques (Escala de Gravidade Global de Tiques de Yale) e qualidade de vida (questionário genérico de avaliação de qualidade de vida, Medical Outcome Quality of Life Scale Short-form-36 e Escala de Avaliação Social). O treinamento dos avaliadores consistiu em assistir cinco entrevistas filmadas e entrevistar cinco pacientes junto com um pesquisador mais experiente, antes de entrevistar pacientes sozinhos. A confiabilidade entre todos os líderes de grupo para os instrumentos mais importantes (Structured Clinical Interview for DSM-IV, Dimensional Yale-Brown Obsessive-Compulsive Scale, Universidade de São Paulo Sensory Phenomena Scale ) foi medida após seis entrevistas completas. RESULTADOS: A confiabilidade entre avaliadores foi de 96%. Até março de 2008, 630 pacientes com transtorno obsessivo-compulsivo tinham sido sistematicamente avaliados. A média de idade (±SE) foi de 34,7 (±0,51), 56,3% eram do sexo feminino e 84,6% caucasianos. Os sintomas obsessivo-compulsivos mais prevalentes foram os de simetria e os de contaminação. As comorbidades psiquiátricas mais comuns foram depressão maior, ansiedade generalizada e transtorno de ansiedade social. O transtorno de controle de impulsos mais comum foi escoriação neurótica. CONCLUSÃO: Este consórcio de pesquisa, pioneiro no Brasil, permitiu delinear o perfil sociodemográfico, clínico e terapêutico do paciente com transtorno obsessivo-compulsivo em uma grande amostra clínica de pacientes. O Consórcio Brasileiro de Pesquisa em Transtornos do Espectro Obsessivo-Compulsivo estabeleceu uma importante rede de colaboração de investigação clínica padronizada sobre o transtorno obsessivo-compulsivo e pode abrir o caminho para projetos semelhantes destinados a integrar outros grupos de pesquisa no Brasil e em todo o mundo.

Assessment of vitamin A status in chronic obstructive pulmonary disease patients and healthy smokers

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Preliminary core sets of measures for disease activity and damage assessment in juvenile systemic lupus erythematosus and juvenile dermatomyositis

Objective. To identify preliminary core sets of outcome variables for disease activity and damage assessment in juvenile systemic lupus erythematosus (JSLE) and juvenile dermatomyositis (JDM). Methods. Two questionnaire surveys were mailed to 267 physicians from 46 different countries asking each member to select and rank the response variables used when assessing clinical response in patients with JSLE or JDM. Next, 40 paediatric rheumatologists from 34 countries met and, using the nominal group technique, selected the domains to be included in the disease activity and damage core sets for JSLE and JDM. Results. A total of 41 response variables for JSLE and 37 response variables for JDM were selected and ranked through the questionnaire surveys. In the consensus conference, domains selected for both JSLE and JDM activity or damage core sets included the physician and parent/patient subjective assessments and a global score tool. Domains specific for JSLE activity were the immunological tests and the kidney function parameters. Concerning JDM, functional ability and muscle strength assessments were indicated for both activity and damage core sets, whereas serum muscle enzymes were included only in the activity core set. A specific paediatric domain called 'growth and development' was introduced in the disease damage core set for both diseases and the evaluation of health-related quality of life was advised in order to capture the influence of the disease on the patient lifestyle. Conclusions. We developed preliminary core sets of measures for disease activity and damage assessment in JSLE and JDM. The prospective validation of the core sets is in progress.

Depression severity levels and cognitive functions in institutionalized elderly patients

Depression is a highly prevalent illness among institutionalized aged and assumes peculiar characteristics such as the risk for progressing to dementia. The aims of this study was to assess the cognitive functions of institutionalized elderly with clinical diagnosis of depression and compare the severity of depressive symptoms with cognitive performance. From 120 residents at a nursing home in Rio Claro, Brazil, we study 23 individuals (mean age: 74.3 years; mean schooling: 4.0 years) with diagnosis of depression. At first, a clinical diagnosis of depression and measurement of its symptoms using the Geriatric Depression Scale were performed. The patient then underwent a neuropsychological assessment based on the following tests: Mini-Mental Examination, Verbal Fluency, Visual Perception, Immediate Memory, Recent Memory, Recognition, Clock Drawing Test. The patients were divided into two groups: those with less severe depression symptoms (Group 1: N=9) and more severe symptoms (Group 2: N=14). The significant difference between symptom severity of the two groups was p=0.0001. Patients with more severe symptoms revealed a slightly inferior cognitive performance in most of the tests when compared to those with less severe symptoms (p>0.05). In relation to Verbal Fluency, patients with more severe depression symptoms presented a significantly inferior cognitive performance when compared to those with less severe symptoms (p=0.0082). Verbal Fluency revealed to be a more sensitive test for measuring early cognitive alterations in institutionalized aged with depression, and appears to be a useful resource in monitoring the cognitive functions of patients faced with the risk of dementia. © Copyright Moreira Jr. Editora.