Diverse Effects of Women’s Employment on Fertility: Insights From Italy and Poland

In this paper, we look into how country-specific factors shape the interrelationship between childbearing and women’s labor supply. To this end, we compare Italy and Poland, two low-fertility countries where the country-specific obstacles to work and family reconciliation are similarly strong but which differ in the history of women’s labor supply and the extent to which couples’ material aspirations are satisfied by men’s earnings. Our findings show that women’s employment clearly conflicts with childbearing in Italy, while in Poland women tend to combine the two activities, despite the similar difficulties they face. These results challenged the standard microeconomic explanations and point to the importance of other country-specific factors, apart from conditions for work and family reconciliation, in shaping women’s employment and fertility decisions, such as economic incentives or culturally rooted behavioral patterns. Overall, our study provides thus foundations for explaining the variation in the relationship between women’s employment and fertility in an enlarged Europe

Multiple-point statistical simulation for hydrogeological models: 3D training image development and conditioning strategies

Most studies about the application of geostatistical simulations based on multiple-point statistics (MPS) to hydrogeological modelling focus on relatively fine-scale models and concentrate on the estimation of facies-level, structural uncertainty. Much less attention is paid to the use of input data and optimal construction of training images. For instance, even though the training image should capture a set of spatial geological characteristics to guide the simulations, the majority of the research still relies on 2D or quasi-3D training images. In the present study, we demonstrate a novel strategy for 3D MPS modelling characterized by: (i) realistic 3D training images, and (ii) an effective workflow for incorporating a diverse group of geological and geophysical data sets. The study covers an area of 2810 km2 in the southern part of Denmark. MPS simulations are performed on a subset of the geological succession (the lower to middle Miocene sediments) which is characterized by relatively uniform structures and dominated by sand and clay. The simulated domain is large and each of the geostatistical realizations contains approximately 45 million voxels with size 100 m × 100 m × 5 m. Data used for the modelling include water well logs, high-resolution seismic data, and a previously published 3D geological model. We apply a series of different strategies for the simulations based on data quality, and develop a novel method to effectively create observed sand/clay spatial trends. The training image is constructed as a small 3D voxel model covering an area of 90 km2. We use an iterative training image development strategy and find that even slight modifications in the training image create significant changes in simulations. Thus, the study underlines that it is important to consider both the geological environment, and the type and quality of input information in order to achieve optimal results from MPS modelling. In this study we present a possible workflow to build the training image and effectively handle different types of input information to perform large-scale geostatistical modellin

Development of a Self-Sufficient LoRaWAN Sensor Node with Flexible and Glass Dye-Sensitized Solar Cell Modules Harvesting Energy from Diffuse Low-Intensity Solar Radiation

This paper aims to demonstrate the viability of energy harvesting for wide area wireless sensing systems based on dye-sensitized solar cells (DSSCs) under diffuse sunlight conditions, proving the feasibility of deploying autonomous sensor nodes even under unfavorable outdoor scenarios, such as during cloudy days, in the proximity of tall buildings, among the trees in a forest and during winter days in general. A flexible thin-film module and a glass thin-film module, both featuring an area smaller than an A4 sheet of paper, were initially characterized in diffuse solar light. Afterward, the protype sensor nodes were tested in a laboratory in two different working conditions, emulating outdoor sunlight in unfavorable lighting and weather to reconstruct a worst-case scenario. A Li-Po battery was employed as a power reserve for a long-range wide area network (LoRaWAN)-based sensor node that transmitted data every 8 h and every hour. To this end, an RFM95x LoRa module was used, while the node energy management was attained by exploiting a nano-power boost charger buck converter integrated circuit conceived for the nano-power harvesting from the light source and the managing of the battery charge and protection. A positive charge balance was demonstrated by monitoring the battery trend along two series of 6 and 9 days, thus allowing us to affirm that the system’s permanent energy self-sufficiency was guaranteed even in the worst-case lighting and weather scenario

Complex Dynamics in Digital Nonlinear Oscillators: Experimental Analysis and Verification

A specific topology of Digital Nonlinear Oscillators (DNOs) has been implemented by using commercial off-the-shelf digital components to experimentally verify and demonstrate the capability of these circuits to support complex dynamics, independently from their implementation technology. In detail, a direct experimental evidence of the DNO dynamical behavior is presented at the analog level with a bifurcation diagram analysis, investigation of periodic and chaotic attractors, and dynamical stability. The autonomous circuit has been investigated as a source of entropy, adopting different figures of merit, including the Lempel–Ziv Complexity, to evaluate the dynamics measured under different operating conditions

Gas sensing properties of In2O3 nano-films obtained by low temperature pulsed electron deposition technique on alumina substrates

Nanostructured Indium(III) oxide (In2O3) films deposited by low temperature pulsed electron deposition (LPED) technique on customized alumina printed circuit boards have been manufactured and characterized as gas sensing devices. Their electrical properties have monitored directly during deposition to optimize their sensing performance. Experimental results with oxidizing (NO2) as well as reducing (CO) gases in both air and inert gas carriers are discussed and modeled