Biblioteca Digital do IPB
Repositório de Publicações do Instituto Politécnico de Bragança
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Artificial intelligence tools in community pharmacy: a literature review
Publication . Castro, Francisco; Pires, Gonçalo; Pinto, Isabel C.; Cunha, José; Nascimento, Luís; Costa, Xavier Taboada
Community pharmacies play a vital role in public health, serving as the first point of contact for many patients. With the increasing workload and complexity of care, artificial intelligence (AI) is being explored as a way to enhance pharmaceutical services [1] [2] [3]. Objective: This literature review aims to explore the current AI-based hardware and software technologies applied in community pharmacy, the barriers to their implementation, and their impact on pharmaceutical care. Methodology: A literature review was conducted using PubMed, focusing on articles from 2020 to 2025. Keywords included "artificial intelligence", "community pharmacy", "hardware", "software" and "robots". Inclusion criteria prioritized full-text studies of scoping reviews, systematic reviews or narrative reviews, about AI applications in community pharmacy. Results: The review identified a variety of AI tools, such as dispensing robots, decision-support systems, inventory management platforms, and chatbots. Benefits reported include improved medication adherence (up to +40%), reduced dispensing errors (up to -75%), and increased operational efficiency. Major implementation barriers are high costs, insufficient training, lack of technological infrastructure, and data privacy concerns. Conclusion: AI technologies offer promising opportunities to optimize processes and enhance patient safety in community pharmacy. However, successful integration requires strategic investment in training, infrastructure, and ethical safeguards to ensure safe and effective use.
UV Radiation: Applications on Surfaces in the Food Industry
Publication . Maioto, Rita; Santos, Stefanie; Dias, Albino A.; Aires, Cristina; Inês, António; Sedrine, Nabiha Ben; Mendes, Paulo; Rodrigues, Paula; Sampaio, Ana
Ultraviolet radiation, particularly in the UVC sub-band 200–280 nm, is a non-thermal disinfection technology capable of inactivating a broad spectrum of microorganisms primarily through nucleic acid damage and protein oxidation. Its effectiveness depends on wavelength, irradiance, exposure time, environmental conditions, and microbial characteristics, such as species and repair capacity. In food processing environments, where equipment surfaces and packaging materials are critical control points for microbial contamination, UVC offers several advantages, including the absence of chemical residues, and compatibility with sustainable sanitization strategies. However, efficacy is strongly influenced by surface properties. Smooth, non-porous, reflective materials (stainless steel, glass), and photocatalytic metal coatings, enhance UVC performance, whereas rough, porous, or fibrous surfaces reduce penetration and create shadowing effects that limit microbial inactivation. This review synthesizes current evidence on UV-based decontamination in the food industry, highlighting both its potential and limitations. The findings emphasize that, although UVC radiation is effective in microbial control, its implementation must consider the complex interactions between surface properties, microorganisms and irradiation parameters, requiring optimization for each environment and application. Further research is therefore needed into: (i) wavelength-tuned systems, (ii) hybrid technologies (UV–plasma or UV-photocatalysis), (iii) material integrity and durability of materials under repeated exposure, and (iv) emerging alternative light sources.
Balancing costs and benefits in lithium mining: management and sustainability challenges in Barroso, Portugal
Publication . Pereira, Hugo; Leite, Joaquim; Carmo, Cecília M. R.
Portugal holds Europe's largest lithium reserves, positioning itself as a potential leading producer of this critical mineral. This prospect has sparked widespread debate over the
economic advantages and environmental trade-offs of lithium extraction. The conscious and sustainable exploitation of these deposits could be the key to reversing the trend of
population decline and agricultural neglect, revitalizing the region with new job opportunities and technological progress. This exploitation could also stimulate investment in infrastructure and research, consolidating the region as an innovative center in the energy sector. This study examines the management and sustainability challenges in lithium mining in Barroso, Portugal, providing insights into the complex cost-benefit dynamics at play. Grounded in management accounting principles, particularly cost-benefit analysis and sustainability, the research employs a single case study methodology. Secondary data from relevant documents is analyzed through content analysis. Findings reveal the economic, social, and environmental costs and benefits of the project and highlight the tensions between its economic proponents and local environmental and social stakeholders.
The role of sleep on physical and cognitive performance of ultra-endurance athletes: a systematic review
Publication . Guilherme, Larissa; Rodrigues, Bruno; Rosa, Carla; Leite, Luciano; Scheer, Volker; Forte, Pedro; Hermsdorff, Helen; Kravchychyn, Ana; Souza, Helton
Sleep is an important factor for recovery and performance in endurance sports, yet its role in ultra-endurance events remains unclear due to extreme physical and cognitive demands and disrupted sleep patterns. This systematic review aimed to analyze the role of sleep in physical and cognitive performance in ultra-endurance athletes. This systematic review followed PRISMA guidelines. A comprehensive search was conducted in May 2025 across PubMed/Medline, Embase, SPORTDiscus, and Web of Science. Two researchers independently screened, selected, extracted, and assessed data quality using the JBI tools (PROSPERO ID: CRD420251042220). Of 424 articles, 16 met inclusion criteria, totaling data from 1389 athletes. Regarding physical performance, better outcomes were associated with no or less sleep during competition (TST), extended sleep the night before, and increased time in light sleep. In contrast, longer wake time, lower sleep quality, greater sleepiness during competition, and higher sleep efficiency were linked to poorer performance. Cognitive performance was positively associated with pre-race sleep quality and mid-race naps. Conversely, greater accumulated sleep before testing was linked to worse cognitive outcomes. Sleep, particularly total sleep time (TST), plays an important role in ultra-endurance performance, although this relationship may be non-linear and influenced by race context and individual strategies. Pre-race and intra-race sleep strategies such as napping and extended sleep may benefit performance. Further rigorous and longitudinal studies are needed to clarify sleep’s impact on performance and recovery in ultra-endurance contexts.
Goliath and the cognitive load theory
Publication . Freitas, Tiago Carvalho; Costa Neto, Alvaro; Pereira, Maria João; Henriques, Pedro Rangel
A successful teaching effort is usually dependant on several factors. From the right environment, to a precisely worded exercise statement, it rests on the teacher's shoulders the concoction of the most effective learning assets to their students. A significant part of this process lies on practise: students commonly solidify their knowledge by solving exercises. Creating new programming exercises, specially in high-demand environments such as large classrooms, is a repetitive and error-prone process, specially when stacked with other typical affairs that educators are required to attend to. Goliath, one of the two main contributions of this article, is a template-based, Artificial Intelligence (AI) supported exercise generator, that aims to facilitate the creation of exercise repositories. By using a Domain-Specific Language (DSL) to define exercise templates, combined with the automatic generation of different exercise types, educators can use Goliath's features to improve their exercise repositories, both in size and variety. This systematic approach allows for greater control and automatisation than using a Large Language Model (LLM) directly, as the exercises’ main components can be pre-defined and pre-configured via their templates. Goliath, which is available online for free access, has been tested and its usability assessed. Combined with these functionalities, the content of the exercises themselves, the manner in which they are presented, and how they are rated for difficulty should also be considered in high regard when designing programming exercises. The Cognitive Load Theory (CLT) provides a conceptual foundation to understand problem-solving mechanisms that are commonly found in several aspects and situations of daily life, such as solving programming exercises. This foundation has been explored and systematically structured to construct the second main contribution of this article: guides to create exercise templates in Goliath founded on the Cognitive Load Theory, aiming to improve both teaching and learning computer programming.