Abstract
This work presents an interrogator system based on an erbium-doped fiber ring cavity for refractive-index measurements. This fiber ring cavity is assisted by a fiber Bragg grating and a phase-shift fiber Bragg grating, both with a similar central emission wavelength to increase the output power levels.

Abstract
Cancer diagnosis is of major importance in the field of human medical pathology, wherein a cell division process known as mitosis constitutes a relevant biological pattern analyzed by professional experts, who seek for such occurrence in presence and number through visual observation of microscopic imagery. This is a time-consuming and exhausting task that can benefit from modern artificial intelligence approaches, namely those handling object detection through deep learning, from which YOLO can be highlighted as one of the most successful, and, as such, a good candidate for performing automatic mitoses detection. Considering that low sensibility for rotation/flip variations is of high importance to ensure mitosis deep detection robustness, in this work, we propose an offline augmentation procedure focusing rotation operations, to address the impact of lost/clipped mitoses induced by online augmentation. YOLOv4 and YOLOv5 were compared, using an augmented test dataset with an exhaustive set of rotation angles, to investigate their performance. YOLOv5 with a mixture of offline and online rotation augmentation methods presented the best averaged F1-score results over three runs. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Abstract
Extracting keywords from textual data is a crucial step for text analysis. One such process may involve a considerable amount of time when done manually. In this paper, we show how keyword extraction techniques can be used to untap texts of political nature. To accomplish this objective, we conduct a case-study on top of 16 Portuguese (PT) political party programs made available in the context of the legislative elections that took place in 30th of January 2022. Our contributions are two-fold. At the level of resources, we make available a curated dataset and a python notebook that systematizes the process of transforming text into quantitative data and into visual aspects. At the methodological level, we propose to extend the keyword extraction algorithm used in this study to extract the most relevant keywords, not only from individual political party programs, but also across the entire collection of documents. A further contribution is the case-study itself, which calls attention to the fact that such solutions may be of interest not only to common people, but also to journalists or politicians alike. Broadly, we demonstrate how the discussion and the analysis that stems from the results obtained may foster the political science research by making available large-scale processing of documents with marginal costs.

Abstract
Purpose: The assessment and observation of critical service factors within the retail industry have garnered increased importance in recent times, due to their perceived ability to shape superior future strategies. The aim of this study is to investigate the service elements that are deemed essential by consumers in the retail sector, specifically targeting the grocery retail industry. Design/Methodology/Approach: Our methodological framework incorporates a systematic review of previous literature and a meta-analysis of past studies that highlight the pivotal service elements within the chosen industry. Following the evaluation of existing literature, 55 studies met the inclusion criteria and were selected for further investigation. The systematic review first compiled information from multiple studies, which was then followed by a meta-analysis. This enabled us to statistically analyze the empirical data from the chosen studies, thereby drawing significant conclusions. Findings: The analyses pinpoint that elements such as personal interaction attributes, product quality and availability, and reliable service are of utmost importance to consumers. Interestingly, customer satisfaction was the only outcome that was positively influenced by all the examined service attributes. Additionally, our findings underscore that certain moderators, such as geographic region and timing of the study, sway the relationship between service attributes and customer outcomes. Originality: Despite numerous meta-analyses attempting to pinpoint the key service attributes for consumers, to the best of our understanding, this study is the first to focus on the retail industry, specifically on hypermarkets, supermarkets, or grocery stores. Therefore, this research bridges a gap in the literature and offers a significant contribution to the academic community by proposing an agenda for future research on customer service factors. It also provides invaluable insight for retail managers, outlining numerous practical implications and offering guidance.

Abstract
This paper describes the participation of the Artificial Intelligence and Information Retrieval (AIIR) Lab from the University of Southern Maine and the Laboratory of Artificial Intelligence and Decision Support (LIAAD) lab from INESC TEC in the CLEF 2023 SimpleText lab. There are three tasks defined for SimpleText: (T1) What is in (or out)?, (T2) What is unclear?, and (T3) Rewrite this!. Five runs were submitted for Task 1 using traditional Information Retrieval, and Sentence-BERT models. For Task 2, three runs were submitted, using YAKE! and KBIR keyword extraction models. Finally, for Task 3, two models were deployed, one using OpenAI Davinci embeddings and the other combining two unsupervised simplification models.

Abstract
This paper proposes a proof of concept for a reflective fiber optic sensor based on multimode interference, designed to measure glucose concentrations in aqueous solutions that mimic the range of glucose concentrations found in human saliva. The sensor is fabricated by splicing a short section of coreless silica fiber into a standard single-mode fiber. By studying the principles of multimode interference and Self-imaging it was developed a sensing head that has a total length of 29.1 mm, approximately equal to the second self-image cycle. This sensing head allowed us to detect low concentrations of glucose (ranging from 0 to 268 mg/dl).