Austrian Academy of Sciences
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Measuring the Effect of Employment uncertainty on Fertility in Europe (A literature review)
No full textNumerous studies have looked at the effect that employment uncertainty has on fertility/childbearing. However, there is a lack of consensus about how to conceptualise and measure it. This paper first reviews issues surrounding the conceptualisation and existing measures of employment uncertainty. It then reviews existing measure of employment uncertainty in the context of fertility decisions. Finally, it raises considerations about their use while suggesting directions for further study
Analysis of Inequalities in Waiting Time at the Visit to the Physician using the Regression Modeling for Duration Data
No full textWhen we visit our physician, we usually have to wait for a more or less longduration until we are called into the doctors’ office. This study revealsinequalities in the waiting time at the visit to the general practitioner byusing multiplicative intensity regression analysis, which is frequently usedfor modeling time to event data. In general, people with higher educationhave a higher efficiency to reduce waiting time. Further, Austrians show ahigher efficiency than foreigners. With regard to health-related factors,those with better health and less frequent consultations have also a higherefficiency to reduce waiting time. It also matters where people live. Thoseliving in rural areas in general wait longer, and furthermore, the longer thejourney from home to the doctors’ practice takes, the longer is the waitingtime
Depopulation and rural shrinkage in Subantarctic Biosphere Reserves: envisioning re-territorialization by young people. eco.mont (Journal on Protected Mountain Areas Research and Management)|eco.mont Vol. 13 special issue 2021|
No full textLandscape-scale conservation at the regional level is an important challenge for Biosphere Reserves (BRs), especially those located in areas suffering from depopulation and rural shrinkage. This is the case of the BRs of the southernmost part of Chile, in the Magallanes region. An analysis of the implications of deterritorialization (the radical reduction or disappearance of inhabitants, their traditional ecological practices, and their material and affective links with the territory) is lacking in the literature, particularly in relation to the migration of young people towards other human settlements. This is a critical situation for BRs because there is a tight link between depopulation and the sustainability of socio-ecological systems. Here we discuss, on the one hand, the limitations and negative impacts of repopulation attempts by extractive industries and, on the other, the possibilities of involving rural youth in initiatives that encourage the re-territorialization of ecological practices and knowledge that have been developed by generations of local inhabitants, as a way of promoting bioculturally sustainable modes of re-inhabiting these territories
A combined finite element and machine learning approach for the prediction of specific cutting forces and maximum tool temperatures in machining. ETNA - Electronic Transactions on Numerical Analysis
No full textIn machining, specific cutting forces and temperature fields are of primary interest. These quantities depend on many machining parameters, such as the cutting speed, rake angle, tool-tip radius, and uncut chip thickness. The finite element method (FEM) is commonly used to study the effect of these parameters on the forces and temperatures. However, the simulations are computationally intensive and thus, it is impractical to conduct a simulation-based parametric study for a wide range of parameters. The purpose of this work is to present, as a proof-of-concept, a hybrid methodology that combines the finite element method (FE method) and machine learning (ML) to predict specific cutting forces and maximum tool temperatures for a given set of machining conditions. The finite element method was used to generate the training and test data consisting of machining parameter values and the corresponding specific cutting forces and maximum tool temperatures. The data was then used to build a predictive model based on artificial neural networks. The FE models consist of an orthogonal plane-strain machining model with the workpiece being made of the Aluminum alloy Al 2024-T351. The finite element package Abaqus/Explicit was used for the simulations. Specific cutting forces and maximum tool temperatures were calculated for several different combinations of uncut chip thickness, cutting speed and the rake angle. For the machine learning-based predictive models, artificial neural networks were selected. The neural network modeling was performed using Python with Adam as the training algorithm. Both shallow neural networks (SNN) and deep neural networks (DNN) were built and tested with various activation functions (ReLU, ELU, tanh, sigmoid, linear) to predict specific cutting forces and maximum tool temperatures. The optimal neural network architecture along with the activation function that produced the least error in prediction was identified. By comparing the neural network predictions with the experimental data available in the literature, the neural network model is shown to be capable of accurately predicting specific cutting forces and temperatures
Table S1 – List of typical culinary products from Austrian BRs. eco.mont (Journal on Protected Mountain Areas Research and Management)|eco.mont Vol. 13 special issue 2021|
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II. Morphonotactics in speech production. Veröffentlichungen zur Linguistik und Kommunikationsforschung|Experimental, Acquisitional and Corpus linguistic Approaches to the Study of Morphonotactics Veröffentlichungen zur Linguistik und Kommunikationsforschung Band 33|
No full textGender differences in visitor motivation and satisfaction: the case of Golija-Studenica Biosphere Reserve, Serbia. eco.mont (Journal on Protected Mountain Areas Research and Management)|eco.mont Vol. 13 special issue 2021|
No full textThe UNESCO Golija-Studenica Biosphere Reserve (BR) is located in southwestern Serbia. Its captivating beauty, breath-taking landscape diversity, and preserved natural and cultural values make it one of the country’s most beautiful mountains. This paper aims to determine the differences in motivation and level of satisfaction with the tourism offer of Golija-Studenica BR based on the visitor’s gender. Motivation and satisfaction of 642 visitors to Golija-Studenica BR were analysed using factor analysis, Cronbach’s alpha coefficient and regression analysis. Research findings confirm that gender matters – there is a gender-based impact on the motivation and satisfaction of visitors. The paper makes both scientific and practical contributions. Thus far, insufficient attention has been given to researching motivation and satisfaction of visitors to biosphere reserves in Serbia. Therefore, this paper can serve as a scientific basis for future research, for the improvement of the tourism offer of Golija- Studenica BR with the aim of encouraging its diversity, and for the development of sustainable tourism in this destination
Archaeologia Austriaca Band 105/2021 - Gesamt PDF. Archaeologia Austriaca|Archaeologia Austriaca Band 105/2021 Band 105/2021|
No full textA Tale of Disaster Experience in Two Countries: Does Education Promote Disaster Preparedness in the Philippines and Thailand
No full textPreparing for a disaster can substantially minimize loss and damages from natural hazards.Amongst other socio-demographic determinants, disaster experience and education are foundto be key predictors of individual disaster preparedness. This paper explores the pathwaysthrough which education enhances disaster preparedness and the interplay between educationand experience in shaping preparedness behaviours. Data analysis is based on face-to-faceinterviews in two disaster-prone countries: the Philippines and Thailand. While education raisesthe propensity to prepare against disasters, we further find that the effect of education ondisaster preparedness is mainly mediated through social capital and disaster risk perception inThailand but there is no evidence that education is mediated through other observable channelsin the Philippines. This in turn suggests that the underlying mechanisms explaining theeducation effects are highly context-specific. Furthermore, we show that education raises disasterpreparedness only for the households that have not been affected by a disaster in the past.One explanation could be that education improves abstract reasoning and anticipation skillssuch that the better educated undertake preventive measures without needing to first experiencethe harmful event and then learn later