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.

Abstract
Assessing the evolution of the performance of water supply and sanitation services is essential to monitor progress towards the universalization of water services, as specified by the Sustainable Development Goal 6 of Agenda 2030, adopted by United Nations member countries. Brazil, a developing country with a continental size and geographical diversity, will face significant challenges to achieve this goal. The main objective of this paper is to evaluate the evolution of productivity of water supply and sanitation services in Brazilian municipalities in the period 2012-2019. The analysis also explores whether water services' performance is balanced across the country, with a specific analysis of performance at the macroregion level. From a methodological perspective, this research evaluates productivity change over time using a Malmquist Productivity Index estimated with a metafrontier, satisfying the circularity property. It also develops a pseudo Malmquist index that compares productivity levels across macro-regions. The results revealed a productivity loss of approximately 4% at the national level, with an unequal profile across the macro-regions. The Southeast municipalities stand out for exhibiting, on average, higher productivity levels than the South and Northeast municipalities.

Abstract
PurposeThe current student selection process for short-term mobility actions under the Erasmus + program (i.e. intensive programs and blended intensive programs) is based exclusively on the students' order of enrolment and their grades. This study offers an alternative approach using the analytic hierarchy process based on a four-layer model that collects information about the specificities of each project and the profile of the students and also promotes greater inclusion and homogenization of the project teams.Design/methodology/approachA decision support system was built by decomposing it into three stages: the predesign stage, in which the problem is characterized, and the user requirements are identified; the design stage, in which the models, the database and the interfaces are formulated; and the field stage, in which six test scenarios were built to validate the proposed solution.FindingsThe results show that this model can be applied with various selection criteria among students and consider both their hard and soft skills. It can also be applied to help build teams in which the students' knowledge is aligned with the technical skills required by the projects.Originality/valueThe proposed approach is innovative in that it responds to the emerging challenge of short-term European mobility programs that aim to involve students with multidisciplinary competencies. The solution considers both hard and soft skills in the selection of students, which allows changing the student selection paradigm and obtaining potentially more homogeneous multicultural teams with greater learning potential.