Small urban parks act as local acoustic refuges, yet their nocturnal soundscapes are rarely quantified at fine spatial scales. We assessed within-park spatio-temporal heterogeneity in Langiewicz Park (~1.1 ha), Wrocław, Poland, using a network of five autonomous AudioMoth recorders mounted on lighting poles at 3.5 m height during early spring campaigns (March–April 2025). Continuous nocturnal recordings (18:00–06:00) were collected, and for each recording, we computed a suite of ecoacoustic indicators capturing acoustic energy (RMS), biophony–anthrophony balance (NDSI), temporal complexity (ACI), spectral diversity (ADI), biotic activity (BI), and acoustic Entropy (H). Indicator time series were aggregated to 15 min resolution to characterise nocturnal trajectories, and dominant patterns were quantified using polynomial trend models and principal component analysis. Despite the small park area and inter-sensor spacing of 50–70 m, indicator distributions differed significantly among microphone locations, with particularly strong spatial contrasts observed in NDSI and BI. Seasonal shifts between March and April further modified the multivariate soundscape structure and the positioning of monitoring sites. These results demonstrate fine-scale nocturnal heterogeneity within a single compact urban park. Our findings suggest that multipoint monitoring design is essential to capture the complex micro-soundscape structures in urban green spaces that single-sensor approaches typically overlook.

The purpose of this paper is to analyze the media visibility of investments implemented in Wrocław, with a particular focus on the democratization of urban processes through the Wrocław Participatory Budget (WPB) and to study the public perception of these projects within the local information landscape. The paper presents an integrated analytical methodology combining geospatial data from the Spatial Information System of Wrocław (SIP) with textual data from the full corpus of local news articles from Wrocław. A hybrid data processing pipeline was used, including filtering of articles about Wrocław, geoparsing of location names, matching articles to investments using classic Term Frequency-Inverse Document Frequency (TF-IDF) models and embedding in language models such as HerBERT, and sentiment analysis using the XLM-T model. The results reveal strong imbalances in the visibility of WPB projects, that almost 90% of investments were not mentioned even once in the media. Temporal sentiment analysis indicated differences between categories of WPB projects. The results confirm the existence of “media deserts” and “islands of attention,” which leads to information exclusion for specific local communities and marginalized groups. This translates into asymmetry in residents’ knowledge of the real scope of the WPB program. The paper emphasizes the importance of Geographic Information System (GIS) fusion methods with natural language processing models (NLP) for urban research, and identifies directions for further analysis, including accompanying problems and limitations in the present day.

Reference genome and transcriptome are fundamental components of RNA-seq analysis and can influence transcript quantification and downstream differential expression results. Although GRCh38 is the current human reference build, GRCh37 remains in use in research and clinical bioinformatics workflows. The extent to which reference transcriptome choice affects transcriptomic inference in breast cancer remains insufficiently characterized. We performed a comparative analysis of publicly available RNA-seq data comprising two MCF7 breast cancer cell-line samples and two healthy breast tissue samples from the European Nucleotide Archive (PRJEB4829). Identical preprocessing, transcript quantification, and differential expression workflows were applied using GRCh37- and GRCh38-based reference transcriptomes. Reference transcriptome-dependent variability was further examined by comparing the same samples quantified under the two reference transcriptomes. Concordance of differentially expressed genes and pathway enrichment was assessed, and sensitivity to reference transcriptome choice was evaluated for genes included in the MammaPrint and Naderi expression signatures and selected hereditary cancer gene panels. The MCF7-versus-normal-tissue comparison identified 15,950 differentially expressed genes using GRCh37 and 16,348 using GRCh38, with 13,899 genes shared between the two analyses. The most significantly enriched Hallmark and KEGG pathways were also concordant between annotations. Principal component analysis showed that the dominant pattern of variation in the MCF7-versus-normal-tissue comparison was associated with biological status. In contrast, when the same MCF7 samples were quantified using different reference transcriptomes, reference transcriptome choice represented a major source of variation. Expression of genes comprising the evaluated prognostic signatures and hereditary cancer panels showed no significant differences in median expression between reference transcriptomes. However, individual cancer-relevant genes, including PTEN, RAD51D, NANOG, and SOX11, demonstrated reference transcriptome-dependent expression differences. In this proof-of-concept analysis, reference transcriptome choice produced measurable differences in RNA-seq quantification and differential expression, while broad biological patterns and the aggregate expression of established gene signatures were relatively stable. Reference transcriptome-dependent variability became particularly apparent when biological heterogeneity was limited, suggesting that reference transcriptome choice can act as a hidden analytical variable in transcriptomic studies. These findings support explicit reporting and version control of reference annotations and highlight the need for validation in larger, independently replicated breast cancer cohorts before drawing clinical conclusions.