Search results for "EURA"
showing 10 items of 3336 documents
"Miehullisesti sotiman Kuningan ja Isänmaan edestä" : seurakuntapapiston käsitykset yhteiskunnasta Kustaa III:n sodan aikaisissa saarnoissa Ruotsin v…
2015
Papit olivat varhaismodernilla ajalla merkittäviä toimijoita Ruotsin valtakunnan paikallisyhteisöissä, joissa he olivat hengellisten toimiensa ohessa sidoshenkilöitä maallisen esivallan ja tavallisen kansan välillä. Pappien toiminta paikallisyhteisöissä korostui erityisesti sodan kaltaisten kriisitilanteiden aikana, jolloin valtakunnan sisäinen yhtenäisyys nousi keskeiseen rooliin. Tässä tutkielmassa tarkastellaan papiston käsityksiä yhteiskunnasta vuosina 1788–1790 käydyn Kustaa III:n sodan aikana. Sotien voidaan katsoa lähtökohtaisesti kärjistäneen ja tuoneen selkeämmiksi papiston saarnastuolista julistamia yhteiskunnallisia näkökantoja. 1700-luvulla yhteiskunta alkoi hiljalleen moniarvoi…
Global monitoring of soil animal communities using a common methodology.
2022
Here we introduce the Soil BON Foodweb Team, a cross-continental collaborative network that aims to monitor soil animal communities and food webs using consistent methodology at a global scale. Soil animals support vital soil processes via soil structure modification, consumption of dead organic matter, and interactions with microbial and plant communities. Soil animal effects on ecosystem functions have been demonstrated by correlative analyses as well as in laboratory and field experiments, but these studies typically focus on selected animal groups or species at one or few sites with limited variation in environmental conditions. The lack of comprehensive harmonised large-scale soil anim…
Multilayer perceptron training with multiobjective memetic optimization
2016
Machine learning tasks usually come with several mutually conflicting objectives. One example is the simplicity of the learning device contrasted with the accuracy of its performance after learning. Another common example is the trade-off that must often be made between the rate of false positive and false negative predictions in diagnostic applications. For computer programs that learn from data, these objectives are formulated as mathematical functions, each of which describes one facet of the desired learning outcome. Even functions that intend to optimize the same facet may behave in a subtly different and mutually conflicting way, depending on the task and the dataset being examined. Mul…
Node co-activations as a means of error detection : Towards fault-tolerant neural networks
2022
Context: Machine learning has proved an efficient tool, but the systems need tools to mitigate risks during runtime. One approach is fault tolerance: detecting and handling errors before they cause harm. Objective: This paper investigates whether rare co-activations – pairs of usually segregated nodes activating together – are indicative of problems in neural networks (NN). These could be used to detect concept drift and flagging untrustworthy predictions. Method: We trained four NNs. For each, we studied how often each pair of nodes activates together. In a separate test set, we counted how many rare co-activations occurred with each input, and grouped the inputs based on whether its class…
Performance Evaluation of EEG Based Mental Stress Assessment Approaches for Wearable Devices
2021
Mental stress has been identified as the root cause of various physical and psychological disorders. Therefore, it is crucial to conduct timely diagnosis and assessment considering the severe effects of mental stress. In contrast to other health-related wearable devices, wearable or portable devices for stress assessment have not been developed yet. A major requirement for the development of such a device is a time-efficient algorithm. This study investigates the performance of computer-aided approaches for mental stress assessment. Machine learning (ML) approaches are compared in terms of the time required for feature extraction and classification. After conducting tests on data for real-t…
Neural generators of the frequency-following response elicited to stimuli of low and high frequency: A magnetoencephalographic (MEG) study.
2021
The frequency-following response (FFR) to periodic complex sounds has gained recent interest in auditory cognitive neuroscience as it captures with great fidelity the tracking accuracy of the periodic sound features in the ascending auditory system. Seminal studies suggested the FFR as a correlate of subcortical sound encoding, yet recent studies aiming to locate its sources challenged this assumption, demonstrating that FFR receives some contribution from the auditory cortex. Based on frequency-specific phase-locking capabilities along the auditory hierarchy, we hypothesized that FFRs to higher frequencies would receive less cortical contribution than those to lower frequencies, hence supp…
Brain Functional Effects of Psychopharmacological Treatment in Major Depression: A Focus on Neural Circuitry of Affective Processing
2015
In the last two decades, neuroimaging research has reached a much deeper understanding of the neurobiological underpinnings of major depression (MD) and has converged on functional alterations in limbic and prefrontal neural networks, which are mainly linked to altered emotional processing observed in MD patients. To date, a considerable number of studies have sought to investigate how these neural networks change with pharmacological antidepressant treatment. In the current review, we therefore discuss results from a) pharmacological functional magnetic resonance imaging (fMRI) studies investigating the effects of selective serotonin or noradrenalin reuptake inhibitors on neural activation…
Convolutional Neural Network Based Sleep Stage Classification with Class Imbalance
2022
Accurate sleep stage classification is vital to assess sleep quality and diagnose sleep disorders. Numerous deep learning based models have been designed for accomplishing this labor automatically. However, the class imbalance problem existing in polysomnography (PSG) datasets has been barely investigated in previous studies, which is one of the most challenging obstacles for the real-world sleep staging application. To address this issue, this paper proposes novel methods with signal-driven and image-driven ways of noise addition to balance the imbalanced relationship in the training dataset samples. We evaluate the effectiveness of the proposed methods which are integrated into a convolut…
Exploring Oscillatory Dysconnectivity Networks in Major Depression During Resting State Using Coupled Tensor Decomposition
2022
Dysconnectivity of large-scale brain networks has been linked to major depression disorder (MDD) during resting state. Recent researches show that the temporal evolution of brain networks regulated by oscillations reveals novel mechanisms and neural characteristics of MDD. Our study applied a novel coupled tensor decomposition model to investigate the dysconnectivity networks characterized by spatio-temporal-spectral modes of covariation in MDD using resting electroencephalography. The phase lag index is used to calculate the functional connectivity within each time window at each frequency bin. Then, two adjacency tensors with the dimension of time frequency connectivity subject are constr…
Attentional bias towards interpersonal aggression in depression – an eye movement study
2020
Depressed individuals exhibit an attentional bias towards mood-congruent stimuli, yet evidence for biased processing of threat-related information in human interaction remains scarce. Here, we tested whether an attentional bias towards interpersonally aggressive pictures over interpersonally neutral pictures could be observed to a greater extent in depressed participants than in control participants. Eye movements were recorded while the participants freely viewed visually matched interpersonally aggressive and neutral pictures, which were presented in pairs. Across the groups, participants spent more time looking at neutral pictures than at aggressive pictures, probably reflecting avoidanc…