736 research outputs found
Procedural Decision Support Through The Use of PRODEMO
Procedural decisions, i.e., decisions involving the application of laws, regulations, prescriptions...constitute a tremendous amount of everyday decisions made in any kind of organizations. In this paper, decision tables are put forword as a basic technique enabling the user to structure and to check procedural decisions for completeness and correctness. It is shown that the use of the interactive PRODEMO (PROcedural DEcision MOdeling) system enhances the capabilities of the technique for modeling as well as for making procedural decisions
Combustion and emissions characteristics of a dual fuel engine operated on alternative gaseous fuels
Effect of a photoperiodic green light programme during incubation on embryo development and hatch process
Evaluation of a new multiplex pcr assay for the diagnosis of sexually transmitted infections pathogens in Rwanda Normal
Detection of embryo mortality and hatch using thermal differences among incubated chicken eggs
Accurate diagnosis of both the stage of embryonic mortality and the hatch process in incubated eggs is a fundamental component in troubleshooting and hatchery management. However, traditional methods disturb incubation, destroy egg samples, risk contamination, are time and labour-intensive and require specialist knowledge and training. Therefore, a new method to accurately detect embryonic mortality and hatching time would be of significant interest for the poultry industry if it could be done quickly, cheaply and be fully integrated into the process. In this study we have continuously measured individual eggshell temperatures and the corresponding micro-environmental air temperatures throughout the 21 days of incubation using standard low-cost temperature sensors. Moreover, we have quantified the thermal interaction between eggs and air by calculating thermal profile changes (temperature drop time, drop length and drop magnitude) that allowed us to detect four categories of egg status (infertile/early death, middle death, late death and hatch) during incubation. A decision tree induction classification model accurately (93.3%) predicted the status of 105 sampled eggs in comparison to the classical hatch residue breakout analyses. With this study we have provided a major contribution to the optimisation of incubation processes by introducing an alternative method for the currently practiced hatch residue breakout analyses.status: publishe
Batumi Raptor Count: autumn raptor migration count data from the Batumi bottleneck, Republic of Georgia
Achievements and state of the art of hydrogen fuelled IC engines after twenty years of research at Ghent University
Paper presented at the 8th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Mauritius, 11-13 July, 2011.Hydrogen could be “the” fuel for the future, not only for fuel cells but certainly for internal combustion engines.
The research on hydrogen started at Ghent University in 1990 with the adaptation of a Valmet diesel engine to hydrogen operation (atmospheric, carbureted version) to prove the capability of hydrogen as a fuel for IC engines. Since then several engines were modified for hydrogen use with the state of the art technologies (sequential injection, electronic management units). With European (Craft, Brite) and Belgian grants three buses demonstrated on several levels the application of hydrogen IC engines. At the moment the laboratory test proves an operation with a power output higher than the gasoline engine, with an equal efficiency of the diesel engine and with very low emissions (NOx less than 100 ppm).
The interests of the research group of Ghent University was not only for the experimental work, but also the combustion process is simulated (GUEST code). The estimated formula of the laminar flame speed of hydrogen by Verhelst is worldwide used in other research studies. At the moment a doctoral study examines the heat transfer in hydrogen engines, which is so different from the already not very accurate heat transfer models in gasoline and diesel engines.
In our laboratory tests, the hydrogen engine is ready for mass production (backfire safe, high power output, high efficiency, very low emissions). But storage on the vehicle recently and infrastructure of the fuel delivery are the bottle-necks for a real implementation of the hydrogen economy. From hydrogen, methanol can be produced on a sustainable way. Methanol is a liquid (no storage problem on het vehicle) and with minor modifications the same infrastructure can be used as for gasoline. Methanol has very good engine characteristics. Will methanol based on hydrogen be then “the” fuel of the future?mp201
Rise time evaluation of the heat flux microsensor (HFM) on a hot-air-gun test rig
Paper presented at the 8th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Mauritius, 11-13 July, 2011.Investigating the heat transfer inside internal combustion
engines is key in the search for higher efficiency, higher power
output and lower emissions. To understand the process and to
validate model predictions, heat flux measurements inside an
engine have to be conducted. In previous works, we have
always used a commercially available thermopile to measure
the heat transfer in a hydrogen combustion engine, but its large
dimensions pose concerns about the sensor’s response time.
Therefore, measurements have been done on a calibration rig
with a hot air flow as heat source. This paper presents a
comparison of the rise time of the thermopile with that of an
alternative sensor developed for heat transfer measurements in
gas turbines. The papers results in an increased confidence in
the thermopile sensor, because its response time is at least as
good as that of the alternative sensor. The results do show that
the reproducibility of the test rig can be improved. Moreover,
due to fluctuations in the heat flux level generated by the
source, only the order of magnitude of the measured heat flux
of two different experiments was comparable. Therefore, a new
calibration rig will be developed to improve the reproducibility
and to increase stability of the heat flux level of the heat source.mp201
Network diffusion modeling predicts neurodegeneration in traumatic brain injury
Objective
Traumatic brain injury (TBI) is a heterogeneous disease with multiple neurological deficits that evolve over time. It is also associated with an increased incidence of neurodegenerative diseases. Accordingly, clinicians need better tools to predict a patient’s long‐term prognosis.
Methods
Diffusion‐weighted and anatomical MRI data were collected from 17 adolescents (mean age = 15y8mo) with moderate‐to‐severe TBI and 19 healthy controls. Using a network diffusion model (NDM), we examined the effect of progressive deafferentation and gray matter thinning in young TBI patients. Moreover, using a novel automated inference method, we identified several injury epicenters in order to determine the neural degenerative patterns in each TBI patient.
Results
We were able to identify the subject‐specific patterns of degeneration in each patient. In particular, the hippocampus, temporal cortices, and striatum were frequently found to be the epicenters of degeneration across the TBI patients. Orthogonal transformation of the predicted degeneration, using principal component analysis, identified distinct spatial components in the temporal–hippocampal network and the cortico‐striatal network, confirming the vulnerability of these networks to injury. The NDM model, best predictive of the degeneration, was significantly correlated with time since injury, indicating that NDM can potentially capture the pathological progression in the chronic phase of TBI.
Interpretation
These findings suggest that network spread may help explain patterns of distant gray matter thinning, which would be consistent with Wallerian degeneration of the white matter connections (i.e., “diaschisis”) from diffuse axonal injuries and multifocal contusive injuries, and the neurodegenerative patterns of abnormal protein aggregation and transmission, which are hallmarks of brain changes in TBI. NDM approaches could provide highly subject‐specific biomarkers relevant for disease monitoring and personalized therapies in TBI
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