Distributional Impacts of Tobacco Excise Taxes in Serbia.

Introduction: Numerous studies worldwide have investigated the impact of tobacco tax increase on household welfare, focusing on concerns regarding potential tobacco taxation regressivity and its effects on the poorest, whereas their scope was limited to the working population.

Aims And Methods: To explore the effects of tax changes on household budgets, accounting for the retired population as well, we employed the modified Extended Cost-Benefit Analysis framework, assuming a 43.6% specific tax increase that fits the European Union (EU) Tobacco Tax Directive recommendation of minimum EUR 90 excise taxes per 1000 cigarettes.

Human health risk assessment framework for new water resource recovery-based bio-composite materials.

A new type of bio-composite material is being produced from water-recovered resources such as cellulose fibres from wastewater, calcite from the drinking water softening process, and grass and reed from waterboard sites. These raw materials may be contaminated with pathogens and chemicals such as , heavy metals, and resin compounds. A novel risk assessment framework is proposed here, addressing human health risks during the production of new bio-composite materials.

Environmental risk assessment related to using resource recovery-based bio-composite materials in the aquatic environment with new laboratory leaching test data.

The concept of circular economy, aiming at increasing the sustainability of products and services in the water and other sectors, is gaining momentum worldwide. Driven by this concept, novel bio-composite materials produced by recovering resources from different parts of the water cycle are now manufactured in The Netherlands. The new materials are used for different products such as canal bank protection elements, as an alternative to similar elements made of hardwood.

Addressing data scarcity in optical matrix multiplier modeling using transfer learning.

We present and experimentally evaluate the use of transfer learning to address experimental data scarcity when training neural network (NN) models for Mach-Zehnder interferometer mesh-based optical matrix multipliers. Our approach involves pretraining the model using synthetic data generated from a less accurate analytical model and fine-tuning it with experimental data. Our investigation demonstrates that this method yields significant reductions in modeling errors compared to using an analytical model or a standalone NN model when training data is limited.

Affordability of cigarettes in ten Southeastern European countries between 2008 and 2019.

Background: The empirical evidence shows that tobacco consumption is strongly associated with its affordability. The nominal growth in tobacco prices imposed by taxation should exceed or at least keep pace with nominal income growth, ensuring that tobacco products become less affordable over time. No analysis covering affordability issues in the Southeastern European (SEE) region has been conducted prior to this research.