Search results for "Sensory defect"

showing 2 items of 2 documents

Post-traumatic trigeminal neuropathy. A study of 63 cases.

2010

Introduction. Trigeminal neuropathy is most often secondary to trauma. The present study explores the underlying causes and the factors that influence recovery. Material and methods. A retrospective case study was made involving 63 patients with trigeminal neuropathy of traumatologic origin, subjected to follow-up for at least 12 months. Results. Fifty-four percent of all cases were diagnosed after mandibular third molar surgery. In 37 and 19 patients the sensory defect was located in the territory innervated by the mental and lingual nerve, respectively. Pain was reported in 57% of the cases, and particularly among the older patients. Regarding patient disability, quality of life was not a…

AdultMalemedicine.medical_specialtyAdolescentTrigeminal neuropathyMandibular third molarYoung AdultQuality of lifeOlder patientsSensory defectMedicineHumansYoung adultGeneral DentistryLingual nerveAgedRetrospective Studiesbusiness.industryRetrospective cohort studyMiddle Aged:CIENCIAS MÉDICAS [UNESCO]SurgeryOrofacial Pain-TMJDOtorhinolaryngologyUNESCO::CIENCIAS MÉDICASSurgeryFemaleTrigeminal Nerve InjuriesResearch-ArticlebusinessMedicina oral, patologia oral y cirugia bucal
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Use of electronic nose to determine defect percentage in oils. Comparison with sensory panel results

2010

Abstract An electronic nose based on an array of 6 metal oxide semiconductor sensors was used, jointly with linear discriminant analysis (LDA) and artificial neural network (ANN) method, to classify oils containing the five typical virgin olive oil (VOO) sensory defects (fusty, mouldy, muddy, rancid and winey). For this purpose, these defects, available as single standards of the International Olive Council, were added to refined sunflower oil. According to the LDA models and the ANN method, the defected samples were correctly classified. On the other hand, the electronic nose data was used to predict the defect percentage added to sunflower oil using multiple linear regression models. All …

food.ingredientOLIVE OILfoodOxide semiconductorSensory defectLinear regressionMaterials ChemistryStatistical analysisElectrical and Electronic EngineeringInstrumentationMathematicsElectronic nosebusiness.industrySunflower oilELECTRONIC NOSEMetals and AlloysPattern recognitionSTATISTICAL ANALYSISCondensed Matter PhysicsLinear discriminant analysisSurfaces Coatings and FilmsElectronic Optical and Magnetic MaterialsSENSORY DEFECTSENSORY THRESHOLDArtificial intelligencebusinessOlive oil
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