Abstract
A bacterial strain was isolated from a brackish water sample of Tagus river, Alcochete, Portugal and was designated TO1_6(T). It forms light pink colonies on M13 medium supplemented with N-acetylglucosamine. Cells are pear-shaped to spherical, form rosettes and divide by budding. Strain TO1_6(T) presents a mesophilic and neutrophilic profile, with optimum growth at 20 to 25 degrees C and pH 7.0 to 7.5, and vitamin supplementation is not required to promote its growth. The genome of the novel isolate is 7.77 Mbp in size and has a DNA G+C content of 56.3%. Based on its 16S rRNA gene sequence, this strain is affiliated with the phylum Planctomycetota. Further taxonomic characterization using additional phylogenetic markers, namely rpoB gene sequence (encoding the beta-subunit of the DNA-dependent RNA polymerase), as well as Percentage of conserved proteins, average nucleotide identity and average amino acid identity, suggest the affiliation of strain TO1_6(T) to the genus Stieleria, a recently described taxon in the family Pirellulaceae, order Pirellulales and class Planctomycetia. Based on the genotypic, phylogenetic and physiological characterization, we here describe a new species represented by the type strain TO1_6(T) (=CECT 30432(T), =LMG 32465(T)), for which the name Stieleria tagensis sp. nov. is proposed.

Abstract
Primary healthcare (PHC) is a fundamental pillar in a health system, and its role has only been enhanced in the COVID-19 pandemic. The emergence of COVID-19 required health systems and, in particular, PHCs to develop a constant capacity to adapt and resist adversity. Therefore, it was considered important to identify innovative measures and thus the experience of a family health unit (USF) in Portugal - USF Arte Nova (USFAN) was reported. After carrying out a systematic review of the literature and interviews with the Presidents of the Clinical and Health Councils of five Health Centre Groupings, the measures identified were gathered and compared to the ones carried out by USFAN. Subsequently, the study identified the measures considered to be truly original executed by the health unit. Between the measures presented, the use of an access prioritization score was highlighted, as were daily briefing regarding the management of resources and equipment, qualification of the use of personal protective equipment, the project that aimed to optimize the use of paper; the use of a drive-through method to update the National Vaccination Program; and the daily training and sharing of information about COVID-19. In light of the current pandemic, innovative practices and tools have been created and carried out by the healthcare professionals in response to the growing needs of the population. This shows the resilience of these professionals and constitutes an opportunity to share and implement these tools in other health-care facilities highlighting the continuing chance of improving.

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E-commerce has become an essential aspect of modern life, providing consumers worldwide with convenience and accessibility. However, the high volume of short and noisy product descriptions in text streams of massive e-commerce platforms translates into an increased number of clusters, presenting challenges for standard model-based stream clustering algorithms. This is the case of a dataset extracted from the Brazilian NF-e Project containing electronic invoice product descriptions, including many product clusters. While LDA-based clustering methods have shown to be crucial, they have been mainly evaluated on datasets with few clusters. We propose the Topic Model with Contextual Outlier Handling (TMCOH) method to overcome this limitation. This method combines the Dirichlet Process, specific word representation, and contextual outlier detection techniques to recycle identified outliers aiming to integrate them into appropriate clusters later on. The experimental results for our case study demonstrate the effectiveness of TMCOH when compared to state-of-the-art methods and its potential for application to text clustering in large datasets.

Abstract
Digital transformation plays a significant role in modernizing and improving the efficiency of ports around the world. However, digitalization also brings a set of challenges that ports must face. They have to respond to several unique challenges because of the complexity of their operations and the varying demands of stakeholders. This study seeks to identify and summarize the challenges of digital transformation processes in ports. For this purpose, the World Ports Sustainability Program database was used. The findings revealed 74 digitalization initiatives carried out by ports, which makes it possible to recognize 7 dimensions and 32 sub-dimensions of challenges to the digital transformation process. Among the identified dimensions are port infrastructure, the interconnection between various systems, the port organization model, regulation, security and privacy, market evolution, and the establishment of partnerships to implement these projects. The results of this study are relevant to mitigate the risks of the digitalization process in ports and respond to market needs that demand greater transparency and visibility of their operations.