Search results for "PIM"

showing 10 items of 3280 documents

Social learning within and across predator species reduces attacks on novel aposematic prey

2020

Abstract To make adaptive foraging decisions, predators need to gather information about the profitability of prey. As well as learning from prey encounters, recent studies show that predators can learn about prey defences by observing the negative foraging experiences of conspecifics. However, predator communities are complex. While observing heterospecifics may increase learning opportunities, we know little about how social information use varies across predator species.Social transmission of avoidance among predators also has potential consequences for defended prey. Conspicuous aposematic prey are assumed to be an easy target for naïve predators, but this cost may be reduced if multipl…

0106 biological sciencesvaroitusväripredator-prey interactionsForagingZoologyAposematism010603 evolutionary biology01 natural scienceseläinten käyttäytyminenPredationpetoeläimetAnimalsaposematismPasseriformesSocial informationPredatorEcology Evolution Behavior and Systematicsheterospecific informationBehavioural EcologyParussaaliseläimetbiologyconspecific information010604 marine biology & hydrobiologyCyanistespredator–prey interactionsSocial learningbiology.organism_classificationsosiaalinen oppiminensocial learningPredatory Behavior1181 Ecology evolutionary biologyavoidance learningAnimal Science and ZoologyResearch Article
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Automatic Profiling of Open-Ended Survey Data on Medical Workplace Teaching

2019

On-the-job medical training is known to be challenging due to the fast-paced environment and strong vocational profile. It relies on on-site supervisors, mainly doctors and nurses with long practical experience, who coach and teach their less experienced colleagues, such as residents and healthcare students. These supervisors receive pedagogical training to ensure that their guidance and teaching skills are constantly improved. The aim of such training is to develop participants’ patient, collegiate and student guidance skills in a multiprofessional environment, and to expand their understanding of guidance as part of their work as supervisors of healthcare professionals. In this paper, we …

020205 medical informaticsFinnish natural language processing02 engineering and technologyEducationterveysala0502 economics and businessHealth caretyössäoppiminen0202 electrical engineering electronic engineering information engineeringComputingMilieux_COMPUTERSANDEDUCATIONProfiling (information science)ta516ammattitaitota316ta113Medical educationHealth professionalsComputingMilieux_THECOMPUTINGPROFESSIONlcsh:T58.5-58.64business.industrylcsh:Information technologytekstinlouhintahealthcare vocational training guidance interaction Finnish natural language processing05 social sciencesGeneral Engineeringhealthcare vocational trainingTeaching skillsVocational educationMedical trainingSurvey data collectionguidance interactiontyöpaikkaohjaajattiedonlouhintabusinessPsychologylcsh:L050203 business & managementNatural languagesurvey-tutkimuslcsh:EducationInternational Journal of Emerging Technologies in Learning (iJET)
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Using Recorded Audio Feedback in Cross-Cultural e-Education Environments to Enhance Assessment Practices in a Higher Education

2018

Providing feedback to learners on their writing assignments is perhaps one of the most important and time-consuming tasks that a supervisor performs. In e-Education environments, giving feedback becomes more challenging because there are often no possibilities for face-to-face discussions with learners. Typically, a supervisor provides comments to learners in written form via email; however, the use of recorded audio feedback (RAF) in e-Education environments has become a viable alternative. The purpose of this case study was to examine learners’ perceptions of RAF and written feedback for their assignments at the University of Jyväskylä (Finland) and at Keio University SFC (Japan). Formati…

020205 medical informaticsHigher educationoppiminenProcess (engineering)cross-cultural higher educationBest practicesuullinen palaute02 engineering and technologyFormative assessment0202 electrical engineering electronic engineering information engineeringMathematics educationCross-culturalta516Hofstede's cultural dimensions theorycultural dimensionsta113e-Education environmentsSupervisorbusiness.industryrecorded audio feedbackGeneral Arts and Humanities05 social sciencespalaute050301 educationäänitiedostotverkko-oppiminenta5141Audio feedbackbusinessPsychology0503 educationformative feedback
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Extreme minimal learning machine: Ridge regression with distance-based basis

2019

The extreme learning machine (ELM) and the minimal learning machine (MLM) are nonlinear and scalable machine learning techniques with a randomly generated basis. Both techniques start with a step in which a matrix of weights for the linear combination of the basis is recovered. In the MLM, the feature mapping in this step corresponds to distance calculations between the training data and a set of reference points, whereas in the ELM, a transformation using a radial or sigmoidal activation function is commonly used. Computation of the model output, for prediction or classification purposes, is straightforward with the ELM after the first step. In the original MLM, one needs to solve an addit…

0209 industrial biotechnologyComputer scienceCognitive Neuroscienceneuraalilaskentaneuroverkot02 engineering and technologyrandomized learning machinesSet (abstract data type)extreme learning machine020901 industrial engineering & automationArtificial Intelligenceextreme minimal learning machine0202 electrical engineering electronic engineering information engineeringExtreme learning machineta113Training setBasis (linear algebra)Model selectionminimal learning machineOverlearningComputer Science ApplicationskoneoppiminenTransformation (function)020201 artificial intelligence & image processingAlgorithmNeurocomputing
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A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms

2017

Evolutionary algorithms are widely used for solving multiobjective optimization problems but are often criticized because of a large number of function evaluations needed. Approximations, especially function approximations, also referred to as surrogates or metamodels are commonly used in the literature to reduce the computation time. This paper presents a survey of 45 different recent algorithms proposed in the literature between 2008 and 2016 to handle computationally expensive multiobjective optimization problems. Several algorithms are discussed based on what kind of an approximation such as problem, function or fitness approximation they use. Most emphasis is given to function approxim…

0209 industrial biotechnologyMathematical optimizationComputer scienceComputationEvolutionary algorithmComputational intelligence02 engineering and technologyMulti-objective optimizationTheoretical Computer Science020901 industrial engineering & automation0202 electrical engineering electronic engineering information engineeringmulticriteria optimizationsurrogateresponse surface approximationcomputational costmetamodelFitness approximationpareto optimalitypareto-tehokkuusFunction (mathematics)monitavoiteoptimointiFunction approximationkoneoppiminen020201 artificial intelligence & image processingGeometry and TopologySoftware
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Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?

2020

Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem. Several different solvers can be applied to the resulting linear problem. In this paper, a thorough comparison of possible and recently proposed, especially randomized, algorithms is carried out for this problem with a representative set of regression datasets. In addition, we compare MLM with shallow and deep feedforward neural network models and study the effects of the number of observations and the number of features with a special dat…

0209 industrial biotechnologyrandom projectionlcsh:Computer engineering. Computer hardwareComputational complexity theoryComputer scienceRandom projectionlcsh:TK7885-789502 engineering and technologyMachine learningcomputer.software_genresupervised learningapproximate algorithmsSet (abstract data type)regressioanalyysi020901 industrial engineering & automationdistance–based regressionalgoritmit0202 electrical engineering electronic engineering information engineeringordinary least–squaresbusiness.industrySupervised learningsingular value decompositionminimal learning machineMultilaterationprojektioRandomized algorithmkoneoppiminenmachine learningScalabilityFeedforward neural network020201 artificial intelligence & image processingArtificial intelligenceapproksimointibusinesscomputerMachine Learning and Knowledge Extraction
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Role of AxyZ Transcriptional Regulator in Overproduction of AxyXY-OprZ Multidrug Efflux System in Achromobacter Species Mutants Selected by Tobramycin

2017

ABSTRACT AxyXY-OprZ is an RND-type efflux system that confers innate aminoglycoside resistance to Achromobacter spp. We investigated here a putative TetR family transcriptional regulator encoded by the axyZ gene located upstream of axyXY-oprZ . An in-frame axyZ gene deletion assay led to increased MICs of antibiotic substrates of the efflux system, including aminoglycosides, cefepime, fluoroquinolones, tetracyclines, and erythromycin, indicating that the product of axyZ negatively regulates expression of axyXY-oprZ . Moreover, we identified an amino acid substitution at position 29 of AxyZ (V29G) in a clinical Achromobacter strain that occurred during the course of chronic respiratory tract…

0301 basic medicineAchromobacterCefepime030106 microbiologyPopulationAchromobacterMicrobial Sensitivity TestsBiologymedicine.disease_causeMicrobiology03 medical and health scienceschemistry.chemical_compoundAntibiotic resistanceBacterial ProteinsMechanisms of ResistanceDrug Resistance Multiple BacterialTobramycinmedicineHumansPharmacology (medical)TetRAmino Acid Sequence[SDV.BBM.BC]Life Sciences [q-bio]/Biochemistry Molecular Biology/Biochemistry [q-bio.BM]educationComputingMilieux_MISCELLANEOUSPharmacologyeducation.field_of_studyPseudomonas aeruginosaMembrane Transport Proteins[SDV.BBM.BM]Life Sciences [q-bio]/Biochemistry Molecular Biology/Molecular biologyGene Expression Regulation Bacterialbiology.organism_classification[SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/BacteriologyAnti-Bacterial Agents3. Good healthInfectious DiseasesAmino Acid SubstitutionchemistryPseudomonas aeruginosaTobramycinTrans-ActivatorsEffluxGene DeletionBacterial Outer Membrane Proteinsmedicine.drugAntimicrobial Agents and Chemotherapy
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The Multifaced Role of STAT3 in Cancer and Its Implication for Anticancer Therapy

2021

Signal transducer and activator of transcription (STAT) 3 is one of the most complex regulators of transcription. Constitutive activation of STAT3 has been reported in many types of tumors and depends on mechanisms such as hyperactivation of receptors for pro-oncogenic cytokines and growth factors, loss of negative regulation, and excessive cytokine stimulation. In contrast, somatic STAT3 mutations are less frequent in cancer. Several oncogenic targets of STAT3 have been recently identified such as c-myc, c-Jun, PLK-1, Pim1/2, Bcl-2, VEGF, bFGF, and Cten, and inhibitors of STAT3 have been developed for cancer prevention and treatment. However, despite the oncogenic role of STAT3 having been…

0301 basic medicineGene isoformSTAT3 Transcription FactorCarcinogenesistumor suppressorPIM1Antineoplastic AgentsReviewBiologyCatalysisstatInorganic ChemistrySTAT3lcsh:Chemistry03 medical and health sciences0302 clinical medicineNeoplasmsDrug DiscoverymedicineAnimalsHumanscancerNeoplasm InvasivenessMolecular Targeted TherapyPhysical and Theoretical ChemistrySTAT3Molecular BiologyTranscription factorlcsh:QH301-705.5SpectroscopyNeovascularization PathologicOrganic ChemistryAlternative splicingtumor promoterCancerGeneral Medicinemedicine.diseaseComputer Science ApplicationsGene Expression Regulation Neoplastic030104 developmental biologylcsh:Biology (General)lcsh:QD1-999030220 oncology & carcinogenesisCancer researchbiology.proteinSTAT proteinInternational Journal of Molecular Sciences
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Use of next generation sequencing technologies for the diagnosis and epidemiology of infectious diseases

2020

[ES]: Por primera vez, la tecnología de secuenciación masiva permite acceder a la información genómica a un precio y a una escala tales, que se está implementado en la práctica clínica y epidemiológica rutinaria. Los obstáculos para dicha implementación son todavía muchos. Sin embargo, ya existen muchos ejemplos de las grandes ventajas que supone en comparación con métodos anteriores. Esto es, sobre todo, porque con una sola determinación podemos obtener simultáneamente información epidemiológica del microorganismo causante, así como de su perfil de resistencias, si bien estas ventajas están más o menos desarrolladas según el patógeno considerado. En esta revisión se repasan varios ejemplos…

0301 basic medicineMicrobiology (medical)GenomeComputer scienceDiagnósticoResistance030106 microbiologyResistenciasComputational biologyClinical Practice03 medical and health sciencesVigilancie0302 clinical medicineSecuenciación masivaEpimediologyNext generation sequencingVigilanciaDiagnosisEpidemiologíaRoutine clinical practiceGenomic information030212 general & internal medicineGenomaEnfermedades Infecciosas y Microbiología Clínica
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Pimasertib (PIM) versus dacarbazine (DTIC) in patients (pts) with cutaneous NRAS melanoma: a controlled, open-label phase II trial with crossover

2016

0301 basic medicineOncologyNeuroblastoma RAS viral oncogene homologmedicine.medical_specialtybusiness.industryMelanomaHematologymedicine.disease03 medical and health sciences030104 developmental biology0302 clinical medicineOncology030220 oncology & carcinogenesisInternal medicinemedicinePimasertibIn patientDacarbazine - DTICOpen labelbusinessAnnals of Oncology
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