921 resultados para Automatic crash notification


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Previous research conducted in the late 1980’s suggested that vehicle impacts following an initial barrier collision increase severe occupant injury risk. Now over twenty-five years old, the data used in the previous research is no longer representative of the currently installed barriers or US vehicle fleet. The purpose of this study is to provide a present-day assessment of secondary collisions and to determine if full-scale barrier crash testing criteria provide an indication of secondary collision risk for real-world barrier crashes. The analysis included 1,383 (596,331 weighted) real-world barrier midsection impacts selected from thirteen years (1997-2009) of in-depth crash data available through the National Automotive Sampling System (NASS) / Crashworthiness Data System (CDS). For each suitable case, the scene diagram and available scene photographs were used to determine roadside and barrier specific variables not available in NASS/CDS. Binary logistic regression models were developed for second event occurrence and resulting driver injury. Barrier lateral stiffness, post-impact vehicle trajectory, vehicle type, and pre-impact tracking conditions were found to be statistically significant contributors toward secondary event occurrence. The presence of a second event was found to increase the likelihood of a serious driver injury by a factor of seven compared to cases with no second event present. Twenty-four full-scale crash test reports were obtained for common non-proprietary US barriers, and the risk of secondary collisions was determined using recommended evaluation criteria from NCHRP Report 350. It was found that the NCHRP Report 350 exit angle criterion alone was not sufficient to predict second collision occurrence for real-world barrier crashes.

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Milk cortisol concentration was determined under routine management conditions on 4 farms with an auto-tandem milking parlor and 8 farms with 1 of 2 automatic milking systems (AMS). One of the AMS was a partially forced (AMSp) system, and the other was a free cow traffic (AMSf) system. Milk samples were collected for all the cows on a given farm (20 to 54 cows) for at least 1 d. Behavioral observations were made during the milking process for a subset of 16 to 20 cows per farm. Milk cortisol concentration was evaluated by milking system, time of day, behavior during milking, daily milk yield, and somatic cell count using linear mixed-effects models. Milk cortisol did not differ between systems (AMSp: 1.15 +/- 0.07; AMSf: 1.02 +/- 0.12; auto-tandem parlor: 1.01 +/- 0.16 nmol/L). Cortisol concentrations were lower in evening than in morning milkings (1.01 +/- 0.12 vs. 1.24 +/- 0.13 nmol/L). The daily periodicity of cortisol concentration was characterized by an early morning peak and a late afternoon elevation in AMSp. A bimodal pattern was not evident in AMSf. Finally, milk cortisol decreased by a factor of 0.915 in milking parlors, by 0.998 in AMSp, and increased by a factor of 1.161 in AMSf for each unit of ln(somatic cell count/1,000). We conclude that milking cows in milking parlors or AMS does not result in relevant stress differences as measured by milk cortisol concentrations. The biological relevance of the difference regarding the daily periodicity of milk cortisol concentrations observed between the AMSp and AMSf needs further investigation.

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Recently developed computer applications provide tools for planning cranio-maxillofacial interventions based on 3-dimensional (3D) virtual models of the patient's skull obtained from computed-tomography (CT) scans. Precise knowledge of the location of the mid-facial plane is important for the assessment of deformities and for planning reconstructive procedures. In this work, a new method is presented to automatically compute the mid-facial plane on the basis of a surface model of the facial skeleton obtained from CT. The method matches homologous surface areas selected by the user on the left and right facial side using an iterative closest point optimization. The symmetry plane which best approximates this matching transformation is then computed. This new automatic method was evaluated in an experimental study. The study included experienced and inexperienced clinicians defining the symmetry plane by a selection of landmarks. This manual definition was systematically compared with the definition resulting from the new automatic method: Quality of the symmetry planes was evaluated by their ability to match homologous areas of the face. Results show that the new automatic method is reliable and leads to significantly higher accuracy than the manual method when performed by inexperienced clinicians. In addition, the method performs equally well in difficult trauma situations, where key landmarks are unreliable or absent.

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OBJECTIVE: Besides DNA, dental radiographs play a major role in the identification of victims in mass casualties or in corpses with major postmortem alterations. Computed tomography (CT) is increasingly applied in forensic investigations and is used to scan the dentition of deceased persons within minutes. We investigated different restoration materials concerning their radiopacity in CT for dental identification purposes. METHODS: Extracted teeth with different filling materials (composite, amalgam, ceramic, temporary fillings) were CT scanned. Radiopacities of the filling materials were analyzed in extended CT scale images. RESULTS: Radiopacity values ranged from 6000-8500HU (temporary fillings), 4500-17000HU (composite fillings) and >30710HU (Amalgam and Gold). The values were used to define presets for a 3D colored volume rendering software. CONCLUSIONS: The effects of filling material caused streak artifacts could be distinctively reduced for the assessment of the dental status and a postprocessing algorithm was introduced that allows for 3D color encoded visualization and discrimination of different dental restorations based on postmortem CT data.

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OBJECTIVE: To evaluate the effectiveness of a practice nurse led strategy to improve the notification and treatment of partners of people with chlamydia infection. DESIGN: Randomised controlled trial. SETTING: 27 general practices in the Bristol and Birmingham areas. PARTICIPANTS: 140 men and women with chlamydia (index cases) diagnosed by screening of a home collected urine sample or vulval swab specimen. INTERVENTIONS: Partner notification at the general practice immediately after diagnosis by trained practice nurses, with telephone follow up by a health adviser; or referral to a specialist health adviser at a genitourinary medicine clinic. MAIN OUTCOME MEASURES: Primary outcome was the proportion of index cases with at least one treated sexual partner. Specified secondary outcomes included the number of sexual contacts elicited during a sexual history, positive test result for chlamydia six weeks after treatment, and the cost of each strategy in 2003 sterling prices. RESULTS: 65.3% (47/72) of participants receiving practice nurse led partner notification had at least one partner treated compared with 52.9% (39/68) of those referred to a genitourinary medicine clinic (risk difference 12.4%, 95% confidence interval -1.8% to 26.5%). Of 68 participants referred to the clinic, 21 (31%) did not attend. The costs per index case were 32.55 pounds sterling for the practice nurse led strategy and 32.62 pounds sterling for the specialist referral strategy. CONCLUSION: Practice based partner notification by trained nurses with telephone follow up by health advisers is at least as effective as referral to a specialist health adviser at a genitourinary medicine clinic, and costs the same. Trial registration Clinical trials: NCT00112255.

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OBJECTIVE: To examine the effectiveness of methods to improve partner notification by patient referral (index patient has responsibility for informing sex partners of their exposure to a sexually transmitted infection). DESIGN: Systematic review of randomised trials of any intervention to supplement simple patient referral. DATA SOURCES: Seven electronic databases searched (January 1990 to December 2005) without language restriction, and reference lists of retrieved articles. REVIEW METHODS: Selection of trials, data extraction, and quality assessment were done by two independent reviewers. The primary outcome was a reduction of incidence or prevalence of sexually transmitted infections in index patients. If this was not reported data were extracted according to a hierarchy of secondary outcomes: number of partners treated; number of partners tested or testing positive; and number of partners notified, located, or elicited. Random effects meta-analysis was carried out when appropriate. RESULTS: 14 trials were included with 12 389 women and men diagnosed as having gonorrhoea, chlamydia, non-gonococcal urethritis, trichomoniasis, or a sexually transmitted infection syndrome. All studies had methodological weaknesses that could have biased their results. Three strategies were used. Six trials examined patient delivered partner therapy. Meta-analysis of five of these showed a reduced risk of persistent or recurrent infection in patients with chlamydia or gonorrhoea (summary risk ratio 0.73, 95% confidence interval 0.57 to 0.93). Supplementing patient referral with information for partners was as effective as patient delivered partner therapy. Neither strategy was effective in women with trichomoniasis. Two trials found that providing index patients with chlamydia with sampling kits for their partners increased the number of partners who got treated. CONCLUSIONS: Involving index patients in shared responsibility for the management of sexual partners improves outcomes. Health professionals should consider the following strategies for the management of individual patients: patient delivered partner therapy, home sampling for partners, and providing additional information for partners.

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OBJECTIVE: The purpose of this study was to evaluate in a phantom study the effect of patient size on radiation dose for abdominal MDCT with automatic tube current modulation. MATERIALS AND METHODS: One or two 4-cm-thick circumferential layers of fat-equivalent material were added to the abdomen of an anthropomorphic phantom to simulate patients of three sizes: small (cross-sectional dimensions, 18 x 22 cm), average size (26 x 30 cm), and oversize (34 x 38 cm). Imaging was performed with a 64-MDCT scanner with combined z-axis and xy-axis tube current modulation according to two protocols: protocol A had a noise index of 12.5 H, and protocol B, 15.0 H. Radiation doses to three abdominal organs and the skin were assessed. Image noise also was measured. RESULTS: Despite increasing patient size, the image noise measured was similar for protocol A (range, 11.7-12.2 H) and protocol B (range, 13.9-14.8 H) (p > 0.05). With the two protocols, in comparison with the dose of the small patient, the abdominal organ doses of the average-sized patient and the oversized patient increased 161.5-190.6%and 426.9-528.1%, respectively (p < 0.001). The skin dose increased as much as 268.6% for the average-sized patient and 816.3% for the oversized patient compared with the small patient (p < 0.001). CONCLUSION: Oversized patients undergoing abdominal MDCT with tube current modulation receive significantly higher doses than do small patients. The noise index needs to be adjusted to the body habitus to ensure dose efficiency.

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Electroencephalograms (EEG) are often contaminated with high amplitude artifacts limiting the usability of data. Methods that reduce these artifacts are often restricted to certain types of artifacts, require manual interaction or large training data sets. Within this paper we introduce a novel method, which is able to eliminate many different types of artifacts without manual intervention. The algorithm first decomposes the signal into different sub-band signals in order to isolate different types of artifacts into specific frequency bands. After signal decomposition with principal component analysis (PCA) an adaptive threshold is applied to eliminate components with high variance corresponding to the dominant artifact activity. Our results show that the algorithm is able to significantly reduce artifacts while preserving the EEG activity. Parameters for the algorithm do not have to be identified for every patient individually making the method a good candidate for preprocessing in automatic seizure detection and prediction algorithms.

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Automatic identification and extraction of bone contours from X-ray images is an essential first step task for further medical image analysis. In this paper we propose a 3D statistical model based framework for the proximal femur contour extraction from calibrated X-ray images. The automatic initialization is solved by an estimation of Bayesian network algorithm to fit a multiple component geometrical model to the X-ray data. The contour extraction is accomplished by a non-rigid 2D/3D registration between a 3D statistical model and the X-ray images, in which bone contours are extracted by a graphical model based Bayesian inference. Preliminary experiments on clinical data sets verified its validity