A critical review on application of photocatalysis for toxicity reduction of real wastewaters

Advanced oxidation processes (AOPs) such as photocatalysis are widely studied for degradation of organic pollutants of contaminants of emerging concern (CECs). However, degradation of organic pollutants leads to formation of by-products, which may be more toxic than parental contaminants. The toxicity of wastewater treated by photocatalysis is topical issue. In this review paper recent studies concerned with photocatalytic detoxification of real industrial and municipal wastewater were assembled and critically discussed. Such issues as challenges for application of photocatalytic wastewater detoxification, feasibility of various toxicity tests, reuse of photocatalysts, cost estimation, etc. were considered. Based on reviewed literature it can be suggested that photocatalysis might not always be a promising treatment method for degradation of organic pollutants in real wastewaters and/or wastewater detoxification from the application point of view. (C) 2020 The Authors. Published by Elsevier Ltd.Peer reviewe

Description and composition of bio-inspired design patterns: a complete overview

In the last decade, bio-inspired self-organising mechanisms have been applied to different domains, achieving results beyond traditional approaches. However, researchers usually use these mechanisms in an ad-hoc manner. In this way, their interpretation, definition, boundary (i.e. when one mechanism stops, and when another starts), and implementation typically vary in the existing literature, thus preventing these mechanisms from being applied clearly and systematically to solve recurrent problems. To ease engineering of artificial bio-inspired systems, this paper describes a catalogue of bio-inspired mechanisms in terms of modular and reusable design patterns organised into different layers. This catalogue uniformly frames and classifies a variety of different patterns. Additionally, this paper places the design patterns inside existing self-organising methodologies and hints for selecting and using a design patter

TriggerCit: Early Flood Alerting using Twitter and Geolocation - A Comparison with Alternative Sources

Rapid impact assessment in the immediate aftermath of a natural disaster is essential to provide adequate information to international organisations, local authorities, and first responders. Social media can support emergency response with evidence-based content posted by citizens and organisations during ongoing events. In the paper, we propose TriggerCit: an early flood alerting tool with a multilanguage approach focused on timeliness and geolocation. The paper focuses on assessing the reliability of the approach as a triggering system, comparing it with alternative sources for alerts, and evaluating the quality and amount of complementary information gathered. Geolocated visual evidence extracted from Twitter by TriggerCit was analysed in two case studies on floods in Thailand and Nepal in 2021.Comment: 12 pages Keywords Social Media, Disaster management, Early Alertin

Tuple MapReduce and Pangool: an associated implementation

This paper presents Tuple MapReduce, a new foundational model extending MapReduce with the notion of tuples. Tuple MapReduce allows to bridge the gap between the low-level constructs provided by MapReduce and higher-level needs required by programmers, such as compound records, sorting, or joins. This paper shows as well Pangool, an open-source framework implementing Tuple MapReduce. Pangool eases the design and implementation of applications based on MapReduce and increases their flexibility, still maintaining Hadoop's performance. Additionally, this paper shows: pseudo-codes for relational joins, rollup, and the PageRank algorithm; a Pangool's code example; benchmark results comparing Pangool with existing approaches; reports from users of Pangool in industry; and the description of a distributed database exploiting Pangool. These results show that Tuple MapReduce can be used as a direct, better-suited replacement of the MapReduce model in current implementations without the need of modifying key system fundamentals

Image-based Social Sensing: Combining AI and the Crowd to Mine Policy-Adherence Indicators from Twitter

Social Media provides a trove of information that, if aggregated and analysed appropriately can provide important statistical indicators to policy makers. In some situations these indicators are not available through other mechanisms. For example, given the ongoing COVID-19 outbreak, it is essential for governments to have access to reliable data on policy-adherence with regards to mask wearing, social distancing, and other hard-to-measure quantities. In this paper we investigate whether it is possible to obtain such data by aggregating information from images posted to social media. The paper presents VisualCit, a pipeline for image-based social sensing combining recent advances in image recognition technology with geocoding and crowdsourcing techniques. Our aim is to discover in which countries, and to what extent, people are following COVID-19 related policy directives. We compared the results with the indicators produced within the CovidDataHub behavior tracker initiative. Preliminary results shows that social media images can produce reliable indicators for policy makers.Comment: 10 pages, 9 figures, to be published in Proceedings of ICSE Software Engineering in Society, May 202

Collaboration and Performance of Citizen Science Projects Addressing the Sustainable Development Goals

Measuring the progress towards the Sustainable Development Goals (SDGs) requires the collection of relevant and reliable data. To do so, Citizen Science can provide an essential source of non-traditional data for tracking progress towards the SDGs, as well as generate social innovations that enable such progress. At its core, citizen science relies on participatory processes involving the collaboration of stakeholders with diverse standpoints, skills, and backgrounds. The ability to measure these participatory processes is therefore key for the monitoring and evaluation of citizen science projects and to support the decisions of their coordinators. Here, we show that the monitoring of social interaction networks provides unique insights on the participatory processes and outcomes of citizen science projects. We studied fourteen early-stage citizen science projects that participated in an innovation cycle focused on SDG 13, Climate Action, as part of the Crowd4SDG project. We implemented a monitoring strategy to measure the collaborative profiles of citizen science teams. This allowed us to generate dynamic interaction networks across complementary dimensions, making visible both formal and informal interactions associated with the division of labor, collaborations, advice seeking, and communication processes of the projects during their development. Leveraging jury evaluation data, we showed that while team composition and communication are associated with project quality, measures of collaboration and activity are associated with engagement quality. Overall, monitoring social interaction dynamics helps build a more comprehensive picture of participatory processes, which is of importance for guiding citizen science projects and for designing initiatives leveraging citizen science to address the SDGs

A Citizen Science Approach for Analyzing Social Media With Crowdsourcing

Social media have the potential to provide timely information about emergency situations and sudden events. However, finding relevant information among the millions of posts being added every day can be difficult, and in current approaches developing an automatic data analysis project requires time and technical skills. This work presents a new approach for the analysis of social media posts, based on configurable automatic classification combined with Citizen Science methodologies. The process is facilitated by a set of flexible, automatic and open-source data processing tools called the Citizen Science Solution Kit. The kit provides a comprehensive set of tools that can be used and personalized in different situations, particularly during natural emergencies, starting from images and text contained in the posts. The tools can be employed by citizen scientists for filtering, classifying, and geolocating the content with a human-in-the-loop approach to support the data analyst, including feedback and suggestions on how to configure the automated tools, and techniques to gather inputs from citizens. Using flooding scenario as a guiding example, this paper illustrates the structure and functioning of the different tools proposed to support citizens scientists in their projects, and a methodological approach to their use. The process is then validated by discussing three case studies based on the Albania earthquake of 2019, the Covid-19 pandemic, and the Thailand floods of 2021. The results suggest that a flexible approach to tools composition and configuration can support a timely setup of an analysis project by citizen scientists, especially in case of emergencies in unexpected locations.ISSN:2169-353

Propuesta estratégica: Lanzamiento de yogurt innovador para la empresa Molitalia

El presente trabajo recopila la investigación de mercado, desarrollo de branding y propuesta de campaña desarrollada para una marca en la categoría de yogures. El estudio responde al pedido de la empresa Molitalia por proponer una narrativa de marca con un posicionamiento innovador, coherente y sólido bajo la marca Costa. Para ello, desarrolla una investigación previa a partir de fuentes primarias y secundarias para conocer la situación del mercado del yogurt liderado por marcas como Gloria y Laive. Asimismo, aplica herramientas cuantitativas y cualitativas para la recolección de hallazgos que sustentan la elección de un público demográficamente millenial que ha crecido consumiendo yogures con toppings como el Battimix. En esa línea, la investigación profundiza y se inspira en el concepto de los Kidults o kidultescentes como un segmento rentable y en crecimiento a nivel local y mundial. Como resultado, la propuesta de marca YoFrik y su respectiva campaña publicitaria se basan en el concepto de “la diversión de escoger con libertad”, una propuesta juvenil, disruptiva y diferente a las opciones tradicionales dentro del mercado del yogurt.The current investigation embraces the market research, branding development and campaign proposal for a brand in the yogurt market. As a request of Molitalia, this study proposes a brand narrative aligned with an innovative, coherent, and solid brand positioning under the Costa brand. In order to do that, a primary and secondary sources investigation of the yogurt market is carried out. Likewise, quantitative and qualitative research tools are applied to collect findings that support the choice of a demographically millennial audience that has grown up consuming topping yogurts such as Battimix. Moreover, as an inspiration for the behavioral characteristics of our market target, this investigation deepens the concept of the Kidults as a profitable growing segment in Peru and around the world. As a result, the proposed brand YoFrik and its advertising campaign are created based on the concept of “the enjoyment to choose freely”, a youthful, disruptive and different yogurt brand

Knowledge, attitudes and preventive practices of primary health care professionals towards alcohol use: A national, cross-sectional study.

Introduction Primary care (PC) professionals' knowledge about alcohol use has been identified as one of the barriers PC providers face in their clinic. Both PC professionals’ level of training and attitude are crucial in the clinical practice regarding alcohol use. Objective To evaluate the knowledge, attitude, and preventive practices of Spanish PC physicians and nurses towards alcohol use. Design An observational, descriptive, cross-sectional, multi-center study. Methodology Location: PC centers of the Spanish National Health System (NHS). Participants: PC physicians and nurses selected randomly from health care centers, and by sending an e-mail to semFYC and SEMERGEN members. Healthcare providers completed an online survey on knowledge, attitude, and follow-up recommendations for reducing alcohol intake. A descriptive, bivariate, and multivariate statistical analysis was conducted (p<0.05). Results Participants: 1,760 healthcare providers completed the survey (75.6% [95% CI 73.5–77.6] family physicians; 11.4% [95% CI 9.9–12.9] medical residents; and 12.5% [95% CI 10.9–14.1] nurses), with a mean age of 44.7 (SD 11.24, range: 26–64, 95% CI: 47.2–48.2). Knowledge was higher in family physicians (p<0.001), older professionals (Spearman's r = 0.11, p<0.001), and resident trainers (p<0.001). The PC professional most likely to provide advice for reducing alcohol use was: a nurse (p <0.001), female (p = 0.010), between 46 and 55 years old (p <0.001). Conclusions PC providers’ knowledge and preventive practices regarding alcohol use are scarce, hence specific training strategies to increase their knowledge and improve their attitude and skills with regard to this health problem should be considered a healthcare policy priority.post-print507 K