Abstract
Th chapter presents an empirical study on a Brazilian cyber-activism movement on Instagram associated with the hashtag #CorpoLivre (#FreeBody in Portuguese). This movement, which was established in 2018, has published more than 3,000 posts and has over 400,000 followers, disseminates anti-fatphobia and real body discourses, and promotes a positive relationship between women and their bodies beyond traditional beauty standards. The study analyses the posts made by the feminist movement on Instagram in December 2022, with a sample size of 101 posts. The study adopted the framework developed by Khurana and Knight for the analysis, which enables the classification of the sample posts in terms of message appeal, orientation, engagement, popularity, and image characteristics. This framework was used to examine the relationship between content characteristics and engagement. Additionally, the study includes a content analysis of the posts' comments, specifically evaluating the valence (positive, negative, or neutral) to assess the effectiveness of the characteristics of the posts. © 2023, IGI Global. All rights reserved.

Abstract

Abstract
Recommender systems position themselves as powerful tools in the support of relevance and personalization, presenting remarkable potential in the area of marketing. The cold-start customer problematic presents a challenge within this topic, leading to the need of distinguishing user features and preferences based on a restricted set of transactional information. This paper proposes a hybrid recommender system that aims to leverage transactional and portfolio information as indicating characteristics of customer behaviour. Four independent systems are combined through a parallelised weighted hybrid design. The first individual system utilises the price, target age, and brand of each product to develop a content-based recommender system, identifying item similarities. Secondly, a keyword-based content system uses product titles and descriptions to identify related groups of items. The third system utilises transactional data, defining similarity between products based on purchasing patterns, categorised as a collaborative model. The fourth system distinguishes itself from the previous approaches by leveraging association rules, using transactional information to establish antecedent and precedence relationships between items through a market basket analysis. Two datasets were analysed: product portfolio and transactional datasets. The product portfolio had 17,118 unique products and the included 4,408,825 instances from 2 June 2021 until 2 June 2022. Although the collaborative system demonstrated the best evaluation metrics when comparing all systems individually, the hybridisation of the four systems surpassed each of the individual systems in performance, with a 8.9% hit rate, 6.6% portfolio coverage, and with closer targeting of customer preferences and smaller bias.

Abstract
This paper presents PyAnaDroid, an open-source, fully-customizable execution pipeline designed to benchmark the performance of Android native projects and applications, with a special emphasis on benchmarking energy performance. PyAnaDroid is currently being used for developing large-scale mobile software empirical studies and for supporting an advanced academic course on program testing and analysis. The presented artifact is an expandable and reusable pipeline to automatically build, test and analyze Android applications. This tool was made openly available in order to become a reference tool to transparently conduct, share and validate empirical studies regarding Android applications. This document presents the architecture of PyAnaDroid, several use cases, and the results of a preliminary analysis that illustrates its potential. Video demo: https://youtu.be/7AV3nrh4Qc8

Abstract
Martial arts (MAs) are a global training system that goes far beyond physical preparation and self-defence. They have been known for a long time, and their wisdom and impact are impressive. The paper illustrates matters about MAs which are relevant to decision making (DM). The recognition of the limitations of the sole dependence on physical ability (hard approaches) is a breakthrough in MAs. The pillars of body and technique are not enough to reach a global vision and overcome severe problems. MAs are committed to mastering faculties linked to intuition, emotions, and thought-free operations, signifying the pillar mind. These revelations have insightful implications for DM and the promptness in approaching the growing complexity of decision problems. Special attention is devoted to the mind, representing a soft paradigm, emphasising the human dimension, integrating intuition and complying with ethics. Finally, the paper delineates a MAs way to improve DM as science and art. © 2023 Inderscience Enterprises Ltd.. All rights reserved.

Abstract
The temporal distribution of acoustic cues in whispered speech was analyzed using the gating paradigm. Fifteen Portuguese participants listened to real disyllabic words produced by four Portuguese speakers. Lexical choices, confidence scores, isolation points (IPs), and recognition points (RPs) were analyzed. Mixed effects models predicted that the first syllable and 70% of the total duration of the second syllable were needed for lexical choices to be above chance level. Fricatives' place, not voicing, had a significant effect on the percentage of correctly identified words. IP and RP values of words with postalveolar voiced and voiceless fricatives were significantly different.