972 resultados para hereditary motor sensory neuropathy
Resumo:
Statistical modeling of traffic crashes has been of interest to researchers for decades. Over the most recent decade many crash models have accounted for extra-variation in crash counts—variation over and above that accounted for by the Poisson density. The extra-variation – or dispersion – is theorized to capture unaccounted for variation in crashes across sites. The majority of studies have assumed fixed dispersion parameters in over-dispersed crash models—tantamount to assuming that unaccounted for variation is proportional to the expected crash count. Miaou and Lord [Miaou, S.P., Lord, D., 2003. Modeling traffic crash-flow relationships for intersections: dispersion parameter, functional form, and Bayes versus empirical Bayes methods. Transport. Res. Rec. 1840, 31–40] challenged the fixed dispersion parameter assumption, and examined various dispersion parameter relationships when modeling urban signalized intersection accidents in Toronto. They suggested that further work is needed to determine the appropriateness of the findings for rural as well as other intersection types, to corroborate their findings, and to explore alternative dispersion functions. This study builds upon the work of Miaou and Lord, with exploration of additional dispersion functions, the use of an independent data set, and presents an opportunity to corroborate their findings. Data from Georgia are used in this study. A Bayesian modeling approach with non-informative priors is adopted, using sampling-based estimation via Markov Chain Monte Carlo (MCMC) and the Gibbs sampler. A total of eight model specifications were developed; four of them employed traffic flows as explanatory factors in mean structure while the remainder of them included geometric factors in addition to major and minor road traffic flows. The models were compared and contrasted using the significance of coefficients, standard deviance, chi-square goodness-of-fit, and deviance information criteria (DIC) statistics. The findings indicate that the modeling of the dispersion parameter, which essentially explains the extra-variance structure, depends greatly on how the mean structure is modeled. In the presence of a well-defined mean function, the extra-variance structure generally becomes insignificant, i.e. the variance structure is a simple function of the mean. It appears that extra-variation is a function of covariates when the mean structure (expected crash count) is poorly specified and suffers from omitted variables. In contrast, when sufficient explanatory variables are used to model the mean (expected crash count), extra-Poisson variation is not significantly related to these variables. If these results are generalizable, they suggest that model specification may be improved by testing extra-variation functions for significance. They also suggest that known influences of expected crash counts are likely to be different than factors that might help to explain unaccounted for variation in crashes across sites
Resumo:
There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states—perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of “excess” zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to “excess” zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed—and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros
Resumo:
Diabetic peripheral neuropathy (DPN) is one of the most debilitating complications of diabetes. DPN is a major cause of foot ulceration and lower limb amputation. Early diagnosis and management is a key factor in reducing morbidity and mortality. Current techniques for clinical assessment of DPN are relatively insensitive for detecting early disease or involve invasive procedures such as skin biopsies. There is a need for less painful, non-invasive and safe evaluation methods. Eye care professionals already play an important role in the management of diabetic retinopathy; however recent studies have indicated that the eye may also be an important site for the diagnosis and monitoring of neuropathy. Corneal nerve morphology has been shown to be a promising marker of diabetic neuropathy occurring elsewhere in the body, and emerging evidence tentatively suggests that retinal anatomical markers and a range of functional visual indicators could similarly provide useful information regarding neural damage in diabetes – although this line of research is, as yet, less well established. This review outlines the growing body of evidence supporting a potential diagnostic role for retinal structure and visual functional markers in the diagnosis and monitoring of peripheral neuropathy in diabetes.
Resumo:
Background, aim, and scope Urban motor vehicle fleets are a major source of particulate matter pollution, especially of ultrafine particles (diameters < 0.1 µm), and exposure to particulate matter has known serious health effects. A considerable body of literature is available on vehicle particle emission factors derived using a wide range of different measurement methods for different particle sizes, conducted in different parts of the world. Therefore the choice as to which are the most suitable particle emission factors to use in transport modelling and health impact assessments presented as a very difficult task. The aim of this study was to derive a comprehensive set of tailpipe particle emission factors for different vehicle and road type combinations, covering the full size range of particles emitted, which are suitable for modelling urban fleet emissions. Materials and methods A large body of data available in the international literature on particle emission factors for motor vehicles derived from measurement studies was compiled and subjected to advanced statistical analysis, to determine the most suitable emission factors to use in modelling urban fleet emissions. Results This analysis resulted in the development of five statistical models which explained 86%, 93%, 87%, 65% and 47% of the variation in published emission factors for particle number, particle volume, PM1, PM2.5 and PM10 respectively. A sixth model for total particle mass was proposed but no significant explanatory variables were identified in the analysis. From the outputs of these statistical models, the most suitable particle emission factors were selected. This selection was based on examination of the statistical robustness of the statistical model outputs, including consideration of conservative average particle emission factors with the lowest standard errors, narrowest 95% confidence intervals and largest sample sizes, and the explanatory model variables, which were Vehicle Type (all particle metrics), Instrumentation (particle number and PM2.5), Road Type (PM10) and Size Range Measured and Speed Limit on the Road (particle volume). Discussion A multiplicity of factors need to be considered in determining emission factors that are suitable for modelling motor vehicle emissions, and this study derived a set of average emission factors suitable for quantifying motor vehicle tailpipe particle emissions in developed countries. Conclusions The comprehensive set of tailpipe particle emission factors presented in this study for different vehicle and road type combinations enable the full size range of particles generated by fleets to be quantified, including ultrafine particles (measured in terms of particle number). These emission factors have particular application for regions which may have a lack of funding to undertake measurements, or insufficient measurement data upon which to derive emission factors for their region. Recommendations and perspectives In urban areas motor vehicles continue to be a major source of particulate matter pollution and of ultrafine particles. It is critical that in order to manage this major pollution source methods are available to quantify the full size range of particles emitted for traffic modelling and health impact assessments.
Resumo:
Measurements in the exhaust plume of a petrol-driven motor car showed that molecular cluster ions of both signs were present in approximately equal amounts. The emission rate increased sharply with engine speed while the charge symmetry remained unchanged. Measurements at the kerbside of nine motorways and five city roads showed that the mean total cluster ion concentration near city roads (603 cm-3) was about one-half of that near motorways (1211 cm-3) and about twice as high as that in the urban background (269 cm-3). Both positive and negative ion concentrations near a motorway showed a significant linear increase with traffic density (R2=0.3 at p<0.05) and correlated well with each other in real time (R2=0.87 at p<0.01). Heavy duty diesel vehicles comprised the main source of ions near busy roads. Measurements were conducted as a function of downwind distance from two motorways carrying around 120-150 vehicles per minute. Total traffic-related cluster ion concentrations decreased rapidly with distance, falling by one-half from the closest approach of 2m to 5m of the kerb. Measured concentrations decreased to background at about 15m from the kerb when the wind speed was 1.3 m s-1, this distance being greater at higher wind speed. The number and net charge concentrations of aerosol particles were also measured. Unlike particles that were carried downwind to distances of a few hundred metres, cluster ions emitted by motor vehicles were not present at more than a few tens of metres from the road.
Resumo:
Aim/hypothesis Immune mechanisms have been proposed to play a role in the development of diabetic neuropathy. We employed in vivo corneal confocal microscopy (CCM) to quantify the presence and density of Langerhans cells (LCs) in relation to the extent of corneal nerve damage in Bowman's layer of the cornea in diabetic patients. Methods 128 diabetic patients aged 58±1 yrs with a differing severity of neuropathy based on Neuropathy Deficit Score (NDS—4.7±0.28) and 26 control subjects aged 53±3 yrs were examined. Subjects underwent a full neurological evaluation, evaluation of corneal sensation with non-contact corneal aesthesiometry (NCCA) and corneal nerve morphology using corneal confocal microscopy (CCM). Results The proportion of individuals with LCs was significantly increased in diabetic patients (73.8%) compared to control subjects (46.1%), P=0.001. Furthermore, LC density (no/mm2) was significantly increased in diabetic patients (17.73±1.45) compared to control subjects (6.94±1.58), P=0.001 and there was a significant correlation with age (r=0.162, P=0.047) and severity of neuropathy (r=−0.202, P=0.02). There was a progressive decrease in corneal sensation with increasing severity of neuropathy assessed using NDS in the diabetic patients (r=0.414, P=0.000). Corneal nerve fibre density (P<0.001), branch density (P<0.001) and length (P<0.001) were significantly decreased whilst tortuosity (P<0.01) was increased in diabetic patients with increasing severity of diabetic neuropathy. Conclusion Utilising in vivo corneal confocal microscopy we have demonstrated increased LCs in diabetic patients particularly in the earlier phases of corneal nerve damage suggestive of an immune mediated contribution to corneal nerve damage in diabetes.
Resumo:
Purpose. The objective of this study was to explore the discriminative capacity of non-contact corneal esthesiometry (NCCE) when compared with the neuropathy disability score (NDS) score—a validated, standard method of diagnosing clinically significant diabetic neuropathy. Methods. Eighty-one participants with type 2 diabetes, no history of ocular disease, trauma, or surgery and no history of systemic disease that may affect the cornea were enrolled. Participants were ineligible if there was history of neuropathy due to non-diabetic cause or current diabetic foot ulcer or infection. Corneal sensitivity threshold was measured on the eye of dominant hand side at a distance of 10 mm from the center of the cornea using a stimulus duration of 0.9 s. The NDS was measured producing a score ranging from 0 to 10. To determine the optimal cutoff point of corneal sensitivity that identified the presence of neuropathy (diagnosed by NDS), the Youden index and “closest-to-(0,1)” criteria were used. Results. The receiver-operator characteristic curve for NCCE for the presence of neuropathy (NDS ≥3) had an area under the curve of 0.73 (p = 0.001) and, for the presence of moderate neuropathy (NDS ≥6), area of 0.71 (p = 0.003). By using the Youden index, for an NDS ≥3, the sensitivity of NCCE was 70% and specificity was 75%, and a corneal sensitivity threshold of 0.66 mbar or higher indicated the presence of neuropathy. When NDS ≥6 (indicating risk of foot ulceration) was applied, the sensitivity was 52% with a specificity of 85%. Conclusions. NCCE is a sensitive test for the diagnosis of minimal and more advanced diabetic neuropathy and may serve as a useful surrogate marker for diabetic and perhaps other neuropathies.
Resumo:
Common mode voltage generated by a power converter in combination with parasitic capacitive couplings is a potential source of shaft voltage in an AC motor drive system. In this paper, a three-phase motor drive system supplied with a single-phase AC-DC diode rectifier is investigated in order to reduce shaft voltage in a three-phase AC motor drive system. In this topology, the common mode voltage generated by the inverter is influenced by the AC-DC diode rectifier because the placement of the neutral point is changing in different rectifier circuit states. A pulse width modulation technique is presented by a proper placement of the zero vectors to reduce the common mode voltage level, which leads to a cost effective shaft voltage reduction technique without load current distortion, while keeping the switching frequency constant. Analysis and simulations have been presented to investigate the proposed method.
Resumo:
Background Little or no research has been done in the overweight child on the relative contribution of multisensory information to maintain postural stability. Therefore, the purpose of this study was to investigate postural balance control under normal and experimentally altered sensory conditions in normal-weight versus overweight children. Methods Sixty children were stratified into a younger (7–9 yr) and an older age group (10–12 yr). Participants were also classified as normal-weight (n = 22) or overweight (n = 38), according to the international BMI cut-off points for children. Postural stability was assessed during quiet bilateral stance in four sensory conditions (eyes open or closed, normal or reduced plantar sensation), using a Kistler force plate to quantify COP dynamics. Coefficients of variation were calculated as well to describe intra-individual variability. Findings Removal of vision resulted in systematically higher amounts of postural sway, but no significant BMI group differences were demonstrated across sensory conditions. However, under normal conditions lower plantar cutaneous sensation was associated with higher COP velocities and maximal excursion of the COP in the medial-lateral direction for the overweight group. Regardless of condition, higher variability was shown in the overweight children within the 7–9 yr old subgroup for postural sway velocity, and more specifically medial–lateral velocity. Interpretation In spite of these subtle differences, results did not establish any clear underlying sensory organization impairments that may affect standing balance performance in overweight children compared to normal-weight peers. Consequently, it is believed that other factors account for overweight children's functional balance deficiencies.
Resumo:
Automobiles have deeply impacted the way in which we travel but they have also contributed to many deaths and injury due to crashes. A number of reasons for these crashes have been pointed out by researchers. Inexperience has been identified as a contributing factor to road crashes. Driver’s driving abilities also play a vital role in judging the road environment and reacting in-time to avoid any possible collision. Therefore driver’s perceptual and motor skills remain the key factors impacting on road safety. Our failure to understand what is really important for learners, in terms of competent driving, is one of the many challenges for building better training programs. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. A multidisciplinary approach is necessary to explain how driving abilities evolves with on-road driving experience. To our knowledge, driver assistance systems have never been comprehensively used in a driver training context to assess the safety aspect of driving. The aim and novelty of this thesis is to develop and evaluate an Intelligent Driver Training System (IDTS) as an automated assessment tool that will help drivers and their trainers to comprehensively view complex driving manoeuvres and potentially provide effective feedback by post processing the data recorded during driving. This system is designed to help driver trainers to accurately evaluate driver performance and has the potential to provide valuable feedback to the drivers. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the driving tasks. Therefore, the proposed IDTS utilizes fuzzy set theory for the assessment of driver performance. The proposed research program focuses on integrating the multi-sensory information acquired from the vehicle, driver and environment to assess driving competencies. After information acquisition, the current research focuses on automated segmentation of the selected manoeuvres from the driving scenario. This leads to the creation of a model that determines a “competency” criterion through the driving performance protocol used by driver trainers (i.e. expert knowledge) to assess drivers. This is achieved by comprehensively evaluating and assessing the data stream acquired from multiple in-vehicle sensors using fuzzy rules and classifying the driving manoeuvres (i.e. overtake, lane change, T-crossing and turn) between low and high competency. The fuzzy rules use parameters such as following distance, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvres to assess competency. These rules that identify driving competency were initially designed with the help of expert’s knowledge (i.e. driver trainers). In-order to fine tune these rules and the parameters that define these rules, a driving experiment was conducted to identify the empirical differences between novice and experienced drivers. The results from the driving experiment indicated that significant differences existed between novice and experienced driver, in terms of their gaze pattern and duration, speed, stop time at the T-crossing, lane keeping and the time spent in lanes while performing the selected manoeuvres. These differences were used to refine the fuzzy membership functions and rules that govern the assessments of the driving tasks. Next, this research focused on providing an integrated visual assessment interface to both driver trainers and their trainees. By providing a rich set of interactive graphical interfaces, displaying information about the driving tasks, Intelligent Driver Training System (IDTS) visualisation module has the potential to give empirical feedback to its users. Lastly, the validation of the IDTS system’s assessment was conducted by comparing IDTS objective assessments, for the driving experiment, with the subjective assessments of the driver trainers for particular manoeuvres. Results show that not only IDTS was able to match the subjective assessments made by driver trainers during the driving experiment but also identified some additional driving manoeuvres performed in low competency that were not identified by the driver trainers due to increased mental workload of trainers when assessing multiple variables that constitute driving. The validation of IDTS emphasized the need for an automated assessment tool that can segment the manoeuvres from the driving scenario, further investigate the variables within that manoeuvre to determine the manoeuvre’s competency and provide integrated visualisation regarding the manoeuvre to its users (i.e. trainers and trainees). Through analysis and validation it was shown that IDTS is a useful assistance tool for driver trainers to empirically assess and potentially provide feedback regarding the manoeuvres undertaken by the drivers.
Resumo:
The Tourism, Racing and Fair Trading (Miscellaneous Provisions) Act 2002 (“the Act”) which was passed on 18 April 2002 contains a number of significant amendments relevant to the operation of the Property Agents and Motor Dealers Act 2000. The main changes relevant to property transactions are: (i) Changes to the process for appointment of a real estate agent and consolidation of the appointment forms; (ii) Additions to the disclosure obligation of agents and property developers; (iii) Simplification of the process for commencing the cooling off period; (iv) Alteration of the common law position concerning when the parties are bound by a contract; (v) Removal of the requirement for a seller’s signature on the warning statement to be witnessed; (vi) Retrospective amendment of s 170 of the Body Corporate and Community Management Act 1997; (vii) Inclusion of a new power to allow inspectors to enter the place of business of a licensee or a marketeer without consent and without a warrant; and (viii) Inclusion of a new power for inspectors to require documents to be produced by marketeers. The majority of the amendments are effective from the date of assent, 24 April 2002, however, some of the amendments do not commence until a date fixed by proclamation. No proclamation has been made at the time of writing (2 May 2002). Where the amendments have not commenced this will be noted in the article. Before providing clients with advice, practitioners should carefully check proclamation details.
Resumo:
The Property Agents and Motor Dealers Act 2000 commenced on 1 July 2001. Significant changes have now been made to the Act by the Property Agents and Motor Dealers Amendment Act 2001 (“the amending Act”). The amending Act contains two distinct parts. First, ss 11-19 of the amending Act provide for increased disclosure obligations on real estate agents, property developers and lawyers together with an extension of the 5 business day cooling-off period imposed by the original Act to all residential property (other than contracts formed on a sale by auction). These provisions commenced on 29 October 2001. The remaining provisions of the amending Act provide for increased jurisdiction and powers to the Property Agents and Motor Dealers Tribunal (“the Tribunal”) enabling the Tribunal to deal with claims against marketeers. These provisions commenced on the date of assent, 21 September 2001.
Resumo:
One of the many difficulties associated with the drafting of the Property Agents and Motor Dealers Act 2000 (Qld) (‘the Act’) is the operation of s 365. If the requirements imposed by this section concerning the return of the executed contract are not complied with, the buyer and the seller will not be bound by the relevant contract and the cooling-off period will not commence. In these circumstances, it is clear that a buyer’s offer may be withdrawn. However, the drafting of the Act creates a difficulty in that the ability of the seller to withdraw from the transaction prior to the parties being bound by the contract is not expressly provided by s 365. On one view, if the buyer is able to withdraw an offer at any time before receiving the prescribed contract documentation the seller also should not be bound by the contract until this time, notwithstanding that the seller may have been bound at common law. However, an alternative analysis is that the legislative omission to provide the seller with a right of withdrawal may be deliberate given the statutory focus on buyer protection. If this analysis were correct the seller would be denied the right to withdraw from the transaction after the contract was formed at common law (that is, after the seller had signed and the fact of signing had been communicated to the buyer).
Resumo:
The Property Agents and Motor Dealers Act 2000 commenced on 1 July 2001. Significant changes have now been made to the Act by the Property Agents and Motor Dealers Amendment Act 2001 (“the amending Act”). The amending Act contains two distinct parts. First, ss 11-19 of the amending Act provide for increased disclosure obligations on real estate agents, property developers and lawyers together with an extension of the 5 business day cooling-off period imposed by the original Act to all residential property (other than contracts formed on a sale by auction). These provisions are expected to commence on 29 October 2001. The remaining provisions of the amending Act provide for increased jurisdiction and powers to the Property Agents and Motor Dealers Tribunal (“the Tribunal”) enabling the Tribunal to deal with claims against marketeers. These provisions commenced on the date of assent (21 September 2001).
Resumo:
This paper presents a fault diagnosis method based on adaptive neuro-fuzzy inference system (ANFIS) in combination with decision trees. Classification and regression tree (CART) which is one of the decision tree methods is used as a feature selection procedure to select pertinent features from data set. The crisp rules obtained from the decision tree are then converted to fuzzy if-then rules that are employed to identify the structure of ANFIS classifier. The hybrid of back-propagation and least squares algorithm are utilized to tune the parameters of the membership functions. In order to evaluate the proposed algorithm, the data sets obtained from vibration signals and current signals of the induction motors are used. The results indicate that the CART–ANFIS model has potential for fault diagnosis of induction motors.