Abstract
According to the literature, there is a research gap regarding digital advertising. This exploratory study focuses on how advertising on the social networks Instagram, Facebook and YouTube, three digital platform giants, is interpreted. Which has the most informative, most interesting, less irritating, and, as a consequence, most effective publicity? We performed a survey, which had 106 answers, and using descriptive statistics we concluded that Instagram and Facebook have better and less irritating publicity than YouTube. On Instagram and Facebook, despite 77,5% and 95,7% (respectively) of the respondents having indicated that they ignore the adverts which are presented, the quantity of people who visit and buy the advertised products is visibly higher, when compared to the numbers registered on YouTube. In contrast with YouTube, the survey sample evaluates Instagram as the platform with the most interesting publicity, in accordance with user preferences. YouTube has less direct and less segmented publicity than Instagram and Facebook.

Abstract
In this paper we analyze a class of multi-parametric quadratic program (mpQP) with parameters in the objective function. Except for parameters in coefficients associated with the linear term, the coefficient of the quadratic term, which is a positive definite matrix, is multiplied by a scalar parameter, while the quadratic coefficient of a standard mpQP is deterministic. We reveal the optimal solution is a linear fractional function in the parameters, and the critical regions remain polyhedral. The discussed mpQP can be reformulated as a standard mpQP via variable and parameter transformations. The proposed method is used to evaluate the economic operation of a residential energy system under time-and-level-of-use electricity pricing, highlighting the potential application in practical problems.

Abstract
Future cities of the Global South will not only rapidly urbanise but will also get warmer from climate change and urbanisation induced effects. It will trigger a multi-fold increase in cooling demand, especially at a residential level, mitigation to which remains a policy and research gap. This study forwards a novel residential energy stress mitigation framework called REST to estimate warming climate-induced energy stress in residential buildings using a GIS-driven urban heat island and energy modelling approach. REST further estimates rooftop solar potential to enable solar photo-voltaic (PV) based decentralised energy solutions and establish an optimised routine for peer-to-peer energy sharing at a neighbourhood scale. The optimised network is classified through a decision tree algorithm to derive sustainability rules for mitigating energy stress at an urban planning scale. These sustainability rules established distributive energy justice variables in urban planning context. The REST framework is applied as a proof-of-concept on a future smart city of India, named Amaravati. Results show that cooling energy stress can be reduced by 80 % in the study area through sensitive use of planning variables like Floor Space Index (FSI) and built-up density. It has crucial policy implications towards the design and implementation of a national level cooling action plans in the future cities of the Global South to meet the UN-SDG - 7 (clean and affordable energy) and SDG - 11 (sustainable cities and communities) targets.

Abstract
Multimedia content production is nowadays widespread due to technological advances, namely supported by smartphones and social media. Although the massive amount of media content brings new opportunities to the industry, it also obfuscates the relevance of marketing content, meant to maintain and lure new audiences. This leads to an emergent necessity of producing these kinds of contents as quickly and engagingly as possible. Creating these automatically would decrease both the production costs and time, particularly by using static media for the creation of short storytelling animated clips. We propose an innovative approach that uses context and content information to transform a still photo into an appealing context-aware video clip. Thus, our solution presents a contribution to the state-of-the-art in computer vision and multimedia technologies and assists content creators with a value-added service to automatically build rich contextualized multimedia stories from single photographs. © 2020 Owner/Author.

Abstract
The study of sensing materials to the detection of carbon dioxide (CO2) was achieved using p-nitrophenol (pNPh) as a colorimetric indicator. The sensing material was polymerized (NPLn), functionalized with 3-triethoxysilyl propyl isocyanate (IPTES) which sensitivity was tested in the form of a membrane as is and encapsulated in hollow silica nanoparticles. The sensing membranes were tested in a closed gas system comprising very precise flow controllers to deliver different concentrations of CO2 (vs. N2). The combination of the sensing membranes with multimode optical fibers and a dual-wavelength diode (LED) allows the measurement of the CO2 through the analysis of the induced absorbance changes with a self-referenced ratiometric scheme. The analysis of the sensing materials have shown significant changes in their chemical and physical properties and the results attest these materials with a strong potential for assessing CO2 dynamics in environmental, medical, and industrial applications.

Abstract