996 resultados para Multicommodity flow algorithms
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Background: The aim of this study was to evaluate how hospital capacity was managed focusing on standardizing the admission and discharge processes. Methods: This study was set in a 900-bed university affiliated hospital of the National Health Service, near Barcelona (Spain). This is a cross-sectional study of a set of interventions which were gradually implemented between April and December 2008. Mainly, they were focused on standardizing the admission and discharge processes to improve patient flow. Primary administrative data was obtained from the 2007 and 2009 Hospital Database. Main outcome measures were median length of stay, percentage of planned discharges, number of surgery cancellations and median number of delayed emergency admissions at 8:00 am. For statistical bivariate analysis, we used a Chi-squared for linear trend for qualitative variables and a Wilcoxon signed ranks test and a Mann–Whitney test for non-normal continuous variables. Results: The median patients’ global length of stay was 8.56 days in 2007 and 7.93 days in 2009 (p<0.051). The percentage of patients admitted the same day as surgery increased from 64.87% in 2007 to 86.01% in 2009 (p<0.05). The number of cancelled interventions due to lack of beds was 216 patients in 2007 and 42 patients in 2009. The median number of planned discharges went from 43.05% in 2007 to 86.01% in 2009 (p<0.01). The median number of emergency patients waiting for an in-hospital bed at 8:00 am was 5 patients in 2007 and 3 patients in 2009 (p<0.01). Conclusions: In conclusion, standardization of admission and discharge processes are largely in our control. There is a significant opportunity to create important benefits for increasing bed capacity and hospital throughput.
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In this paper, we present a comprehensive study of different Independent Component Analysis (ICA) algorithms for the calculation of coherency and sharpness of electroencephalogram (EEG) signals, in order to investigate the possibility of early detection of Alzheimer’s disease (AD). We found that ICA algorithms can help in the artifact rejection and noise reduction, improving the discriminative property of features in high frequency bands (specially in high alpha and beta ranges). In addition to different ICA algorithms, the optimum number of selected components is investigated, in order to help decision processes for future works.
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In this paper we present a quantitative comparisons of different independent component analysis (ICA) algorithms in order to investigate their potential use in preprocessing (such as noise reduction and feature extraction) the electroencephalogram (EEG) data for early detection of Alzhemier disease (AD) or discrimination between AD (or mild cognitive impairment, MCI) and age-match control subjects.
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BACKGROUND: This study validates the use of phycoerythrin (PE) and allophycocyanin (APC) for fluorescence energy transfer (FRET) analyzed by flow cytometry. METHODS: FRET was detected when a pair of antibody conjugates directed against two noncompetitive epitopes on the same CD8alpha chain was used. FRET was also detected between antibody conjugate pairs specific for the two chains of the heterodimeric alpha (4)beta(1) integrin. Similarly, the association of T-cell receptor (TCR) with a soluble antigen ligand was detected by FRET when anti-TCR antibody and MHC class I/peptide complexes (<<tetramers>>) were used. RESULTS: FRET efficiency was always less than 10%, probably because of steric effects associated with the size and structure of PE and APC. Some suggestions are given to take into account this and other effects (e.g., donor and acceptor concentrations) for a better interpretation of FRET results obtained with this pair of fluorochromes. CONCLUSIONS: We conclude that FRET assays can be carried out easily with commercially available antibodies and flow cytometers to study arrays of multimolecular complexes.
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Postprint (published version)
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The orchestration of collaborative learning processes in face-to-facephysical settings, such as classrooms, requires teachers to coordinate students indicating them who belong to each group, which collaboration areas areassigned to each group, and how they should distribute the resources or roles within the group. In this paper we present an Orchestration Signal system,composed of wearable Personal Signal devices and an Orchestration Signal manager. Teachers can configure color signals in the manager so that they are transmitted to the wearable devices to indicate different orchestration aspects.In particular, the paper describes how the system has been used to carry out a Jigsaw collaborative learning flow in a classroom where students received signals indicating which documents they should read, in which group they were and in which area of the classroom they were expected to collaborate. The evaluation results show that the proposed system facilitates a dynamic, visual and flexible orchestration.
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Neuropeptide Y (NPY) is a peptide with vasoconstrictor properties known to be present in the central nervous system as well as in sympathetic nerve endings and the adrenal medulla. The purposes of this study were to investigate in normotensive conscious rats the effects of nonpressor doses of NPY on cardiac output and regional blood flow distribution (using radiolabeled microspheres) as well as on plasma renin activity, plasma catecholamine and vasopressin levels. NPY (0.1 microgram/min) infused i.v. for 30 min modified neither blood pressure nor heart rate. Cardiac index was at comparable levels in NPY- as in vehicle-treated rats (17.7 +/- 1.6, n = 8, vs. 21.3 +/- 0.9 ml/min/100 g, n = 8, mean +/- S.E.M.). There was no significant difference in regional blood flow distribution between the two groups of rats, except for the large intestine (0.42 +/- 0.06 vs. 0.71 +/- 0.1 ml/min/g in NPY- and vehicle-treated rats, respectively, P less than .05). Basal plasma renin activity and catecholamine levels were not modified by NPY whereas plasma vasopressin levels were lower (P less than .05) in rats given NPY (0.76 +/- 0.3 pg/ml, n = 8) than in those having received the vehicle (2.2 +/- 0.4 pg/ml).(ABSTRACT TRUNCATED AT 250 WORDS)
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BACKGROUND: Active screening by mobile teams is considered the best method for detecting human African trypanosomiasis (HAT) caused by Trypanosoma brucei gambiense but the current funding context in many post-conflict countries limits this approach. As an alternative, non-specialist health care workers (HCWs) in peripheral health facilities could be trained to identify potential cases who need testing based on their symptoms. We explored the predictive value of syndromic referral algorithms to identify symptomatic cases of HAT among a treatment-seeking population in Nimule, South Sudan. METHODOLOGY/PRINCIPAL FINDINGS: Symptom data from 462 patients (27 cases) presenting for a HAT test via passive screening over a 7 month period were collected to construct and evaluate over 14,000 four item syndromic algorithms considered simple enough to be used by peripheral HCWs. For comparison, algorithms developed in other settings were also tested on our data, and a panel of expert HAT clinicians were asked to make referral decisions based on the symptom dataset. The best performing algorithms consisted of three core symptoms (sleep problems, neurological problems and weight loss), with or without a history of oedema, cervical adenopathy or proximity to livestock. They had a sensitivity of 88.9-92.6%, a negative predictive value of up to 98.8% and a positive predictive value in this context of 8.4-8.7%. In terms of sensitivity, these out-performed more complex algorithms identified in other studies, as well as the expert panel. The best-performing algorithm is predicted to identify about 9/10 treatment-seeking HAT cases, though only 1/10 patients referred would test positive. CONCLUSIONS/SIGNIFICANCE: In the absence of regular active screening, improving referrals of HAT patients through other means is essential. Systematic use of syndromic algorithms by peripheral HCWs has the potential to increase case detection and would increase their participation in HAT programmes. The algorithms proposed here, though promising, should be validated elsewhere.
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Background: The aim of this study was to evaluate how hospital capacity was managed focusing on standardizing the admission and discharge processes. Methods: This study was set in a 900-bed university affiliated hospital of the National Health Service, near Barcelona (Spain). This is a cross-sectional study of a set of interventions which were gradually implemented between April and December 2008. Mainly, they were focused on standardizing the admission and discharge processes to improve patient flow. Primary administrative data was obtained from the 2007 and 2009 Hospital Database. Main outcome measures were median length of stay, percentage of planned discharges, number of surgery cancellations and median number of delayed emergency admissions at 8:00¿am. For statistical bivariate analysis, we used a Chi-squared for linear trend for qualitative variables and a Wilcoxon signed ranks test and a Mann¿Whitney test for non-normal continuous variables. Results:The median patients' global length of stay was 8.56 days in 2007 and 7.93 days in 2009 (p<0.051). The percentage of patients admitted the same day as surgery increased from 64.87% in 2007 to 86.01% in 2009 (p<0.05). The number of cancelled interventions due to lack of beds was 216 patients in 2007 and 42 patients in 2009. The median number of planned discharges went from 43.05% in 2007 to 86.01% in 2009 (p<0.01). The median number of emergency patients waiting for an in-hospital bed at 8:00¿am was 5 patients in 2007 and 3 patients in 2009 (p<0.01). Conclusions: In conclusion, standardization of admission and discharge processes are largely in our control. There is a significant opportunity to create important benefits for increasing bed capacity and hospital throughput.
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The noise power spectrum (NPS) is the reference metric for understanding the noise content in computed tomography (CT) images. To evaluate the noise properties of clinical multidetector (MDCT) scanners, local 2D and 3D NPSs were computed for different acquisition reconstruction parameters.A 64- and a 128-MDCT scanners were employed. Measurements were performed on a water phantom in axial and helical acquisition modes. CT dose index was identical for both installations. Influence of parameters such as the pitch, the reconstruction filter (soft, standard and bone) and the reconstruction algorithm (filtered-back projection (FBP), adaptive statistical iterative reconstruction (ASIR)) were investigated. Images were also reconstructed in the coronal plane using a reformat process. Then 2D and 3D NPS methods were computed.In axial acquisition mode, the 2D axial NPS showed an important magnitude variation as a function of the z-direction when measured at the phantom center. In helical mode, a directional dependency with lobular shape was observed while the magnitude of the NPS was kept constant. Important effects of the reconstruction filter, pitch and reconstruction algorithm were observed on 3D NPS results for both MDCTs. With ASIR, a reduction of the NPS magnitude and a shift of the NPS peak to the low frequency range were visible. 2D coronal NPS obtained from the reformat images was impacted by the interpolation when compared to 2D coronal NPS obtained from 3D measurements.The noise properties of volume measured in last generation MDCTs was studied using local 3D NPS metric. However, impact of the non-stationarity noise effect may need further investigations.
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PURPOSE: Visualization of coronary blood flow in the right and left coronary system in volunteers and patients by means of a modified inversion-prepared bright-blood coronary magnetic resonance angiography (cMRA) sequence. MATERIALS AND METHODS: cMRA was performed in 14 healthy volunteers and 19 patients on a 1.5 Tesla MR system using a free-breathing 3D balanced turbo field echo (b-TFE) sequence with radial k-space sampling. For magnetization preparation a slab selective and a 2D selective inversion pulse were used for the right and left coronary system, respectively. cMRA images were evaluated in terms of clinically relevant stenoses (< 50 %) and compared to conventional catheter angiography. Signal was measured in the coronary arteries (coro), the aorta (ao) and in the epicardial fat (fat) to determine SNR and CNR. In addition, maximal visible vessel length, and vessel border definition were analyzed. RESULTS: The use of a selective inversion pre-pulse allowed direct visualization of the coronary blood flow in the right and left coronary system. The measured SNR and CNR, vessel length, and vessel sharpness in volunteers (SNR coro: 28.3 +/- 5.0; SNR ao: 37.6 +/- 8.4; CNR coro-fat: 25.3 +/- 4.5; LAD: 128.0 cm +/- 8.8; RCA: 74.6 cm +/- 12.4; Sharpness: 66.6 % +/- 4.8) were slightly increased compared to those in patients (SNR coro: 24.1 +/- 3.8; SNR ao: 33.8 +/- 11.4; CNR coro-fat: 19.9 +/- 3.3; LAD: 112.5 cm +/- 13.8; RCA: 69.6 cm +/- 16.6; Sharpness: 58.9 % +/- 7.9; n.s.). In the patient study the assessment of 42 coronary segments lead to correct identification of 10 clinically relevant stenoses. CONCLUSION: The modification of a previously published inversion-prepared cMRA sequence allowed direct visualization of the coronary blood flow in the right as well as in the left coronary system. In addition, this sequence proved to be highly sensitive regarding the assessment of clinically relevant stenotic lesions.
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The state of the art to describe image quality in medical imaging is to assess the performance of an observer conducting a task of clinical interest. This can be done by using a model observer leading to a figure of merit such as the signal-to-noise ratio (SNR). Using the non-prewhitening (NPW) model observer, we objectively characterised the evolution of its figure of merit in various acquisition conditions. The NPW model observer usually requires the use of the modulation transfer function (MTF) as well as noise power spectra. However, although the computation of the MTF poses no problem when dealing with the traditional filtered back-projection (FBP) algorithm, this is not the case when using iterative reconstruction (IR) algorithms, such as adaptive statistical iterative reconstruction (ASIR) or model-based iterative reconstruction (MBIR). Given that the target transfer function (TTF) had already shown it could accurately express the system resolution even with non-linear algorithms, we decided to tune the NPW model observer, replacing the standard MTF by the TTF. It was estimated using a custom-made phantom containing cylindrical inserts surrounded by water. The contrast differences between the inserts and water were plotted for each acquisition condition. Then, mathematical transformations were performed leading to the TTF. As expected, the first results showed a dependency of the image contrast and noise levels on the TTF for both ASIR and MBIR. Moreover, FBP also proved to be dependent of the contrast and noise when using the lung kernel. Those results were then introduced in the NPW model observer. We observed an enhancement of SNR every time we switched from FBP to ASIR to MBIR. IR algorithms greatly improve image quality, especially in low-dose conditions. Based on our results, the use of MBIR could lead to further dose reduction in several clinical applications.
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The infiltration of river water into aquifers is of high relevance to drinking-water production and is a key driver of biogeochemical processes in the hyporheic and riparian zone, but the distribution and quantification of the infiltrating water are difficult to determine using conventional hydrological methods (e.g., borehole logging and tracer tests). By time-lapse inverting crosshole ERT (electrical resistivity tomography) monitoring data, we imaged groundwater flow patterns driven by river water infiltrating a perialpine gravel aquifer in northeastern Switzerland. This was possible because the electrical resistivity of the infiltrating water changed during rainfall-runoff events. Our time-lapse resistivity models indicated rather complex flow patterns as a result of spatially heterogeneous bank filtration and aquifer heterogeneity. The upper part of the aquifer was most affected by the river infiltrate, and the highest groundwater velocities and possible preferential flow occurred at shallow to intermediate depths. Time series of the reconstructed resistivity models matched groundwater electrical resistivity data recorded on borehole loggers in the upper and middle parts of the aquifer, whereas the resistivity models displayed smaller variations and delayed responses with respect to the logging data. in the lower part. This study demonstrated that crosshole ERT monitoring of natural electrical resistivity variations of river infiltrate could be used to image and quantify 3D bank filtration and aquifer dynamics at a high spatial resolution.