Search Results (54)

Early printed books, particularly incunabula, are invaluable archives of the beginnings of modern educational systems. However, their complex layouts, antique typefaces, and page degradation caused by bleed-through and ink fading pose significant challenges for automatic transcription. In this work, we present a modular pipeline that addresses these problems by combining modern layout analysis and language modeling techniques. The pipeline begins with historical layout-aware text segmentation using Kraken, a neural network-based tool tailored for early typographic structures. Initial optical character recognition (OCR) is then performed with Kraken’s recognition engine, followed by post-correction using a fine-tuned ByT5 transformer model trained on manually aligned line-level data. By learning to map noisy OCR outputs to verified transcriptions, the model substantially improves recognition quality. The pipeline also integrates a preprocessing stage based on our previous work on bleed-through removal using robust statistical filters, including non-local means, Gaussian mixtures, biweight estimation, and Gaussian blur. This step enhances the legibility of degraded pages prior to OCR. The entire solution is open, modular, and scalable, supporting long-term preservation and improved accessibility of cultural heritage materials. Experimental results on 15th-century incunabula show a reduction in the Character Error Rate (CER) from around 38% to around 15% and an increase in the Bilingual Evaluation Understudy (BLEU) score from 22 to 44, confirming the effectiveness of our approach. This work demonstrates the potential of integrating transformer-based correction with layout-aware segmentation to enhance OCR accuracy in digital humanities applications. Full article

Efficient prediction of shallow-water acoustic transmission loss (TL) is crucial for underwater detection, recognition, and communication systems. Traditional physical modeling methods require repeated calculations for each new scenario in practical waveguide environments, leading to low computational efficiency. Deep learning approaches, based on data-driven principles, enable accurate input–output approximation and batch processing of large-scale datasets, significantly reducing computation time and cost. To establish a rapid prediction model mapping sound speed profiles (SSPs) to acoustic TL through controllable generation, this study proposes a hybrid framework that integrates a variational autoencoder (VAE) and a normalizing flow (Flow) through a two-stage training strategy. The VAE network is employed to learn latent representations of TL data on a low-dimensional manifold, while the Flow network is additionally used to establish a bijective mapping between the latent variables and underwater physical parameters, thereby enhancing the controllability of the generation process. Combining the trained normalizing flow with the VAE decoder could establish an end-to-end mapping from SSPs to TL. The results demonstrated that the VAE–Flow network achieved higher computational efficiency, with a computation time of 4 s for generating 1000 acoustic TL samples, versus the over 500 s required by the KRAKEN model, while preserving accuracy, with median structural similarity index measure (SSIM) values over 0.90. Full article

A passive time reversal method with a metamodel (PTR-MM) is proposed to improve underwater source localization under ocean conditions. PTR-MM eliminates model mismatch errors by replacing the conventional sound propagation model with a Kriging metamodel. This metamodel is optimally constructed based on measured sound field data. The method combines a metamodel with a passive time reversal (PTR) process to generate a focused sound field whose intensity peaks correspond to source positions. In numerical simulations using the KRAKEN model in a range-independent waveguide, PTR-MM accurately localizes single and multiple sources, is insensitive to mismatches in key environmental parameters, and maintains unbiased performance down to −20 dB signal-to-noise ratios (SNRs). Experimental validation on the SWellEx-96 Event S5 dataset confirms that PTR-MM outperforms conventional PTR in both single- and dual-source localizations, achieving most mean absolute percentage errors (MAPEs) below 10% when trained and tested in consistent environments. Further studies reveal that localization accuracy depends primarily on signal quality, array aperture, and element spacing, rather than on source frequency. However, PTR-MM performance degrades if the metamodel is trained in an environment that differs from the test conditions. The above findings demonstrate the potential of combining PTR with a metamodel for robust and real-time localization. Full article

This study investigates viral composition in wastewater through metagenomic analysis, evaluating the performance of four bioinformatic tools—Genome Detective, CZ.ID, INSaFLU-TELEVIR and Trimmomatic + Kraken2—on samples collected from four sites in each of two wastewater treatment plants (WWTPs) in Lisbon, Portugal in April 2019. From each site, we collected and processed separately three replicates and one pool of nucleic acids extracted from the replicates. A total of 32 samples were processed using sequence-independent single-primer amplification (SISPA) and sequenced on an Illumina MiSeq platform. Across the 128 sample–tool combinations, viral read counts varied widely, from 3 to 288,464. There was a lack of consistency between replicates and their pools in terms of viral abundance and diversity, revealing the heterogeneity of the wastewater matrix and the variability in sequencing effort. There was also a difference between software tools highlighting the impact of tool selection on community profiling. A positive correlation between crAssphage and human pathogens was found, supporting crAssphage as a proxy for public health surveillance. A custom Python pipeline automated viral identification report processing, taxonomic assignments and diversity calculations, streamlining analysis and ensuring reproducibility. These findings emphasize the importance of sequencing depth, software tool selection and standardized pipelines in advancing wastewater-based epidemiology. Full article

This paper addresses the feasibility of implementing spatial diversity techniques to mitigate interference signals using low-cost GNSS receivers. Global Navigation Satellite Systems (GNSSs) remain at the core of navigation technologies and obtaining precise and robust positioning solutions in harsh scenarios becomes essential for the proper functioning of modern applications. Furthermore, this challenge is even more complex when mass-market receivers are addressed, since the previous requirements must be achieved while maintaining low-cost architectures. A promising solution is to use beamforming techniques, which exploit the spatial domain to achieve enhanced reliability and robustness. In this paper, the potential of beamforming in mass-market receivers is analyzed by implementing two interference mitigation techniques and using a five-channel low-cost software defined radio (SDR), KrakenSDR. The results show that the algorithms implemented are able to mitigate strong interference signals, allowing the GNSS receiver to compute an accurate positioning solution. Full article

This study investigates acoustic propagation and transmission loss in shallow water at an unexplored site in the northern Arabian Sea near the Pakistan coastline using a normal mode theoretical framework. Sound propagation in shallow water with range-independent bathymetry was analyzed using a customized Kraken C program to compute eigenvalues and eigenfunctions. The sound speed profile and clay silt sediment samples of the northern Arabian Sea, which characterize the water column and ocean bottom, respectively, were determined. Coherent and incoherent transmission losses for frequencies ranging from 50 to 500 Hz were calculated across different ranges and depths. Results indicate significant intensity fluctuations with increasing range, leading to higher transmission loss. Low frequencies (50–225 Hz) exhibit more significant transmission loss, while higher frequencies (230–500 Hz) show reduced loss. Transmission loss is higher for receivers at 19 m depth compared to those at shallower depths (8 m and 12 m) because the receivers are positioned near the layer of bottom sediments. Factors such as source and receiver depth, sediment properties, bottom roughness, and sound frequency significantly influence transmission loss. The novel dataset for the region supports the assessment of sonar performance, underwater communication, navigation, and marine life exploration. Full article

Purpose: To characterize microbial keratitis diversity utilizing species richness and Shannon Diversity Index. Methods: Corneal impression membrane was used to collect samples. All swabs were processed and analyzed by Biolab Laboratory (level V—SSN Excellence: ISO 9001:2015), Biolab Srl (Ascoli Piceno, Italy). DNA extraction, library preparation, and sequencing were performed in all samples. After sequencing, low-quality and polyclonal sequences were filtered out by the Ion software. At this point, we employed Kraken2 for microbial community analysis in keratitis samples. Nuclease-free water and all the reagents included in the experiment were used as a negative control. The primary outcome was the reduction in bacterial DNA (microbial load) at T1, expressed as a percentage of the baseline value (T0). Richness and Shannon alpha diversity metrics, along with Bray–Curtis beta diversity values, were calculated using the phyloseq package in R. Principal coordinate analysis was also conducted to interpret these metrics. Results: 19 samples were included in the study. The results exhibited a motley species richness, with the highest recorded value surpassing 800 species. Most of the samples displayed richness values ranging broadly from under 200 to around 600, indicating considerable variability in species count among the keratitis samples. Conclusions: A significant presence of both typical and atypical bacterial phyla in keratitis infections, underlining the complexity of the disease’s microbial etiology. Full article

Wild birds are a natural reservoir for zoonotic viruses. To clarify the role of migratory birds in viruses spread in Poyang Lake, we investigated the microbiome of 250 wild bird samples from 19 species in seven orders. The bacterial and viral content abundance and diversity were preliminarily evaluated by Kraken2 and Bracken. After de novo assembly by Megahit and Vamb, viral contigs were identified by CheckV. The reads remapped to viral contigs were quantified using Bowtie2. The bacterial microbiome composition of the samples covers 1526 genera belonging to 175 bacterial orders, while the composition of viruses covers 214 species belonging to 22 viral families. Several taxonomic biomarkers associated with avian carnivory, oral sampling, and raptor migration were identified. Additionally, 17 complete viral genomes belonging to Astroviridae, Caliciviridae, Dicistroviridae, Picornaviridae, and Tombusviridae were characterized, and their phylogenetic relationships were analyzed. This pioneering metagenomic study of migratory birds in Poyang Lake, China illuminates the diverse microbial landscape within these birds. It identifies potential pathogens, and uncovers taxonomic biomarkers relevant to varied bird habitats, feeding habits, ecological classifications, and sample types, underscoring the public health risks associated with wintering migratory birds. Full article

The recently emerged SARS-CoV-2 Omicron sublineages, including the BA.2-derived XBB.1.5 (Kraken), XBB.1.16 (Arcturus), and EG.5.1 (Eris), have accumulated several spike mutations that may increase immune escape, affecting vaccine effectiveness. Older adults are an understudied group at significantly increased risk of severe COVID-19. Here we report the neutralizing activities of 177 sera samples from 59 older adults, aged 62–97 years, 1 and 4 months after vaccination with a 4th dose of ChAdOx1-S (Oxford/AstraZeneca) and 3 months after a 5th dose of Comirnaty Bivalent Original/Omicron BA.4/BA.5 vaccine (Pfizer-BioNTech). The ChAdOx1-S vaccination-induced antibodies neutralized efficiently the ancestral D614G and BA.4/5 variants, but to a much lesser extent the XBB.1.5, XBB.1.16, and EG.5.1 variants. The results showed similar neutralization titers between XBB.1.16 and EG.5.1 and were lower compared to XBB.1.5. Sera from the same individuals boosted with the bivalent mRNA vaccine contained higher neutralizing antibody titers, providing a better cross-protection against Omicron XBB.1.5, XBB.1.16 and EG.5.1 variants. Previous history of infection during the epidemiological waves of BA.1/BA.2 and BA.4/BA.5, poorly enhanced neutralization activity of serum samples against XBBs and EG.5.1 variants. Our data highlight the continued immune evasion of recent Omicron subvariants and support the booster administration of BA.4/5 bivalent vaccine, as a continuous strategy of updating future vaccine booster doses to match newly emerged SARS-CoV-2 variants. Full article

The importance of lung microbiome changes in developing chronic lung allograft dysfunction (CLAD) after lung transplantation is poorly understood. The lung microbiome–immune interaction may be critical in developing CLAD. In this context, examining alterations in the microbiome and immune cells of the lungs following CLAD, in comparison to the lung condition immediately after transplantation, can offer valuable insights. Four adult patients who underwent lung retransplantation between January 2019 and June 2020 were included in this study. Lung tissues were collected from the same four individuals at two different time points: at the time of the first transplant and at the time of the explantation of CLAD lungs at retransplantation due to CLAD. We analyzed whole-genome sequencing using the Kraken2 algorithm and quantified the cell fractionation from the bulk tissue gene expression profile for each lung tissue. Finally, we compared the differences in lung microbiome and immune cells between the lung tissues of these two time points. The median age of the recipients was 57 years, and most (75%) had undergone lung transplants for idiopathic pulmonary fibrosis. All patients were administered basiliximab for induction therapy and were maintained on three immunosuppressants. The median CLAD-free survival term was 693.5 days, and the median time to redo the lung transplant was 843.5 days. Bacterial diversity was significantly lower in the CLAD lungs than at transplantation. Bacterial diversity tended to decrease according to the severity of the CLAD. Aerococcus, Caldiericum, Croceibacter, Leptolyngbya, and Pulveribacter genera were uniquely identified in CLAD, whereas no taxa were identified in lungs at transplantation. In particular, six taxa, including Croceibacter atlanticus, Caldiserium exile, Dolichospermum compactum, Stappia sp. ES.058, Kinetoplastibacterium sorsogonicusi, and Pulveribacter suum were uniquely detected in CLAD. Among immune cells, CD8+ T cells were significantly increased, while neutrophils were decreased in the CLAD lung. In conclusion, unique changes in lung microbiome and immune cell composition were confirmed in lung tissue after CLAD compared to at transplantation. Full article

We report on Moonbase, an innovative pipeline that builds upon the established tools of MetaPhlAn and Kraken2, enhancing their capabilities for more precise taxonomic detection and quantification in diverse microbial communities. Moonbase enhances the performance of Kraken2 mapping by providing an efficient method for constructing project-specific databases. Moonbase was evaluated using synthetic metagenomic samples and compared against MetaPhlAn3 and generalized Kraken2 databases. Moonbase significantly improved species precision and quantification, outperforming marker genes and generalized databases. Construction of a phylogenetic tree from 16S genome data in Moonbase allowed for the incorporation of UniFrac-type phylogenetic information into diversity calculations of samples. We demonstrated that the resulting analysis increased statistical power in distinguishing microbial communities. This study highlights the continual evolution of metagenomic tools with the goal of improving metagenomic analysis and highlighting the potential of the Moonbase pipeline. Full article

Genomic contamination remains a pervasive challenge in (meta)genomics, prompting the development of numerous detection tools. Despite the attention that this issue has attracted, a comprehensive comparison of the available tools is absent from the literature. Furthermore, the potential effect of horizontal gene transfer on the detection of genomic contamination has been little studied. In this study, we evaluated the efficiency of detection of six widely used contamination detection tools. To this end, we developed a simulation framework using orthologous group inference as a robust basis for the simulation of contamination. Additionally, we implemented a variable mutation rate to simulate horizontal transfer. Our simulations covered six distinct taxonomic ranks, ranging from phylum to species. The evaluation of contamination levels revealed the suboptimal precision of the tools, attributed to significant cases of both over-detection and under-detection, particularly at the genus and species levels. Notably, only so-called “redundant” contamination was reliably estimated. Our findings underscore the necessity of employing a combination of tools, including Kraken2, for accurate contamination level assessment. We also demonstrate that none of the assayed tools confused contamination and horizontal gene transfer. Finally, we release CRACOT, a freely accessible contamination simulation framework, which holds promise in evaluating the efficacy of future algorithms. Full article

The use of radio direction finding techniques in order to identify and reject harmful interference has been a topic of discussion both past and present for signals in the GNSS bands. Advances in commercial off-the-shelf radio hardware have led to the development of new low-cost, compact, phase coherent receiver platforms such as the KrakenSDR from KrakenRF whose testing and characterization will be the primary focus of this paper. Although not specifically designed for GNSSs, the capabilities of this platform are well aligned with the needs of GNSSs. Testing results from both benchtop and in the field will be displayed which verify the KrakenSDR’s phase coherence and angle of arrival estimates to array dependent resolution bounds. Additionally, other outputs from the KrakenSDR such as received signal strength indicators and the angle of arrival confidence values show strong connections to angle of arrival estimate quality. Within this work the testing that will be primarily presented is at 900 MHz, with results presented from a government-sponsored event where the Kraken was tested at 1575.42 MHz. Finally, a discussion of calibration of active antenna arrays for angle of arrival is included as the introduction of active antenna elements used in GNSS signal collection can influence angle of arrival estimation. Full article

Graft-versus-host disease (GvHD) is a severe complication after hematopoietic stem cell transplantation (HSCT). Our study focused on identifying multidrug-resistant (MDR) gut bacteria associated with GvHD-prone guts and association with gut microbiota (GM) diversity, bacteriome, and mycobiome composition in post-HSCT patients. We examined 11 pediatric patients with acute lymphoblastic leukemia (ALL), including six with GvHD, within three time points: seven days pre-HSCT, seven days post-, and 28 days post-HSCT. The gut microbiome and its resistome were investigated using metagenomic sequencing, taxonomically classified with Kraken2, and statistically evaluated for significance using appropriate tests. We observed an increase in the abundance of MDR bacteria, mainly Enterococcus faecium strains carrying msr(C), erm(T), aac(6′)-li, dfrG, and ant(6)-la genes, in GvHD patients one week post-HSCT. Conversely, non-GvHD patients had more MDR beneficial bacteria pre-HSCT, promoting immunosurveillance, with resistance genes increasing one-month post-HSCT. MDR beneficial bacteria included the anti-inflammatory Bacteroides fragilis, Ruminococcus gnavus, and Turicibacter, while most MDR bacteria represented the dominant species of GM. Changes in the gut mycobiome were not associated with MDR bacterial monodominance or GvHD. Significant α-diversity decline (Shannon index) one week and one month post-HSCT in GvHD patients (p < 0.05) was accompanied by increased Pseudomonadota and decreased Bacteroidota post-HSCT. Our findings suggest that MDR commensal gut bacteria may preserve diversity and enhance immunosurveillance, potentially preventing GvHD in pediatric ALL patients undergoing HSCT. This observation has therapeutic implications. Full article

Taxonomic profiling of ancient metagenomic samples is challenging due to the accumulation of specific damage patterns on DNA over time. Although a number of methods for metagenome profiling have been developed, most of them have been assessed on modern metagenomes or simulated metagenomes mimicking modern metagenomes. Further, a comparative assessment of metagenome profilers on simulated metagenomes representing a spectrum of degradation depth, from the extremity of ancient (most degraded) to current or modern (not degraded) metagenomes, has not yet been performed. To understand the strengths and weaknesses of different metagenome profilers, we performed their comprehensive evaluation on simulated metagenomes representing human dental calculus microbiome, with the level of DNA damage successively raised to mimic modern to ancient metagenomes. All classes of profilers, namely, DNA-to-DNA, DNA-to-protein, and DNA-to-marker comparison-based profilers were evaluated on metagenomes with varying levels of damage simulating deamination, fragmentation, and contamination. Our results revealed that, compared to deamination and fragmentation, human and environmental contamination of ancient DNA (with modern DNA) has the most pronounced effect on the performance of each profiler. Further, the DNA-to-DNA (e.g., Kraken2, Bracken) and DNA-to-marker (e.g., MetaPhlAn4) based profiling approaches showed complementary strengths, which can be leveraged to elevate the state-of-the-art of ancient metagenome profiling. Full article