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Candidate Dark Galaxy-2: Validation and Analysis of an Almost Dark Galaxy in the Perseus Cluster
Get PDFCandidate Dark Galaxy-2 (CDG-2) is a potential dark galaxy consisting of four globular clusters (GCs) in the Perseus cluster, first identified in D. Li et al. through a sophisticated statistical method. The method searched for overdensities of GCs from a Hubble Space Telescope (HST) survey targeting Perseus. Using the same HST images and new imaging data from the Euclid survey, we report the detection of extremely faint but significant diffuse emission around the four GCs of CDG-2. We thus have exceptionally strong evidence that CDG-2 is a galaxy. This is the first galaxy detected purely through its GC population. Under the conservative assumption that the four GCs make up the entire GC population, preliminary analysis shows that CDG-2 has a total luminosity of LV,gal = 6.2 ± 3.0 × 106L⊙ and a minimum GC luminosity of LV,GC = 1.03 ± 0.2 × 106 L⊙. Our results indicate that CDG-2 is one of the faintest galaxies having associated GCs, while at least ∼16.6% of its light is contained in its GC population. This ratio is likely to be much higher (∼33%) if CDG-2 has a canonical GC luminosity function (GCLF). In addition, if the previously observed GC-to-halo mass relations apply to CDG-2, it would have a minimum dark matter halo mass fraction of 99.94% to 99.98%. If it has a canonical GCLF, then the dark matter halo mass fraction is ≳99.99%. Therefore, CDG-2 may be the most GC dominated galaxy and potentially one of the most dark matter dominated galaxies ever discovered
Construction of Ultraslow-Spreading Oceanic Crust: New Insights on Volcanic Processes and Deposits From High-Resolution Mapping at the Mohns Ridge
Get PDFThe volcanic activity at ultraslow-spreading ridges is less understood compared with that at faster-spreading ridges. Studies of year-to-year changes along the faster-spreading ridges have provided important information regarding the size and frequency of eruptions. However, ultraslow-spreading ridges produce less frequent eruptions, limiting the possibility to study short-term changes in the seafloor morphology to understand longer-term volcanic processes. Therefore, a different approach is needed to estimate the size and frequency of volcanic eruptions at the slowest spreading ridges. Here, we use meter-scale bathymetric maps and backscatter data together with visual observations and geochronology of both basalts and sediments to study the construction of three axial volcanic ridges (AVRs) along the northern half of the ultraslow-spreading Mohns Ridge. Our study finds that most eruptions produce low-effusion rate pillow lavas (82% of the volcanic terrain). We define “lava flow units” as mappable building-blocks of the ARVs, each with a coherent morphology, which may be emplaced during multiple eruptions, but we envision over a relatively short time span (years to decades). These units vary in size from individual hummocks to larger edifices (0.42 × 106 to 38 × 106 m3). Moreover, we estimate the eruptive frequencies per AVR to be on a hundred-year scale. These spatial-temporal constraints in AVR volcanism offer insight into long-term magma flux and spatial focusing along magma-starved ultraslow spreading ridge systems
Young audience and VOD platforms of linear television. Perceptions about Playz, Mtmad and Flooxer
Get PDFIntroduction: The new audiovisual paradigm, marked by flexible consumption, a wide catalog and a participatory audience, increases the interest of linear television in connecting with young people. To that end, the channels manage specialized content platforms. This research aims to analyze Mtmad, Playz and Flooxer, and the perceptions about them. The specific objectives are to examine the catalogs; evaluate identification with management chains; analyze youth-content identification and study their consumption habits. Methodology: A content analysis based on web structures and catalogs is proposed; and a survey of 160 young people about their knowledge, identification and consumption patterns. Results: Mtmad leads in terms of web design, mainly in structure and user experience. In terms of content, the three platforms present similar numbers of titles, although heterogeneity of strategies is observed. Mtmad opts for reality television, and Flooxer and Playz for fiction. According to the survey, Mtmad is the best-known platform but Playz is the most consumed, the most identified with linear television and with whose catalog young people feel more identified. Discussion: What young people consume the most are series, even though they appreciate innovative formats starring Influencers. They do not identify with linear television, but they use and identify more with the platform that they directly associate with a conventional network. Conclusions: Despite the different strategies and perceptions of young people, a homogeneous tendency to produce content that encourages interactivity is detected
A short pragmatic tool for evaluating community engagement: Partnering for Health Improvement and Research Equity
Get PDFBackground: As community-engaged research (CEnR), community-based participatory research (CBPR) and patient-engaged research (PEnR) have become increasingly recognized as valued research approaches in the last several decades, there is need for pragmatic and validated tools to assess effective partnering practices that contribute to health and health equity outcomes. This article reports on the co-creation of an actionable pragmatic survey, shortened from validated metrics of partnership practices and outcomes. Methods: We pursued a triple aim of preserving content validity, psychometric properties, and importance to stakeholders of items, scales, and constructs from a previously validated measure of CBRP/CEnR processes and outcomes. There were six steps in the methods: (a) established validity and shortening objectives; (b) used a conceptual model to guide decisions; (c) preserved content validity and importance; (d) preserved psychometric properties; (e) justified the selection of items and scales; and (f) validated the short-form version. Twenty-one CBPR/CEnR experts (13 academic and 8 community partners) completed a survey and participated in two focus groups to identify content validity and importance of the original 93 items. Results: The survey and focus group process resulted in the creation of the 30-item Partnering for Health Improvement and Research Equity (PHIRE) survey. Confirmatory factor analysis and a structural equation model of the original data set resulted in the validation of eight higher-order scales with good internal consistency and structural relationships (TLI \u3e 0.98 and SRMR \u3c 0.02). A reworded version of the PHIRE was administered to an additional sample demonstrating good reliability and construct validity. Conclusion: This study demonstrates that the PHIRE is a reliable instrument with construct validity compared to the larger version from which it was derived. The PHIRE is a straightforward and easy-to-use tool, for a range of CBPR/CEnR projects, that can provide benefit to partnerships by identifying actionable changes to their partnering practices to reach their desired research and practical outcomes
Comparing E-MOSAICS predictions of high-redshift proto-globular clusters with JWST observations in lensed galaxies
Get PDFHigh-resolution imaging and strong gravitational lensing of high-redshift galaxies have enabled the detection of compact sources with properties similar to nearby massive star clusters. Often found to be very young, these sources may be globular clusters detected in their earliest stages. In this work, we compare predictions of high-redshift (-10) star cluster properties from the E-MOSAICS simulation of galaxy and star cluster formation with those of the star cluster candidates in strongly lensed galaxies from JWST and Hubble Space Telescope (HST) imaging. We select galaxies in the simulation that match the luminosities of the majority of lensed galaxies with star cluster candidates observed with JWST. We find that the luminosities, ages, and masses of the brightest star cluster candidates in the high-redshift galaxies are consistent with the E-MOSAICS model. In particular, the brightest cluster ages are in excellent agreement. The results suggest that star clusters in both low- and high-redshift galaxies may form via common mechanisms. However, the brightest clusters in the lensed galaxies tend to be - brighter and dex more massive than the median E-MOSAICS predictions. We discuss the large number of effects that could explain the discrepancy, including simulation and observational limitations, stellar population models, cluster detection biases, and nuclear star clusters. Understanding these limitations would enable stronger tests of globular cluster formation models
Riparian Restoration Increases Soil Microbial Biomass in Marin County Rangelands, but Soil Carbon Stock is Less Responsive
No full textLand use change has caused the degradation of 70% of the Earth’s soils, directly altering soil microbial communities and carbon cycling. Interest in carbon farming practices is growing, but studies that document the nuances of soil carbon flux in specific bioregions are still too few. In this study, I examined how one practice, riparian restoration, alters soil carbon stock and microbial community structure over time. Using a paired sampling time series design, I collected soil samples from twelve riparian forests and adjacent rangelands near Marin County, California. Young and mature sites ranged from five to 29 years since restoration, and remnant sites had been undisturbed for at least 70 years. Soil bulk density decreased over time while microbial biomass, represented by phospholipid fatty acid abundances, increased over time. Remnant forests supported less dense soils with a larger mass of microbes per unit of volume. The following four functional groups increased with age of restoration: gram (+/-) and (-) bacteria, arbuscular mycorrhizal fungi and saprophytic fungi, however neither soil organic carbon stock nor carbon:nitrogen nor fungal:bacterial ratios changed with restoration age. The microbial biomass pattern I saw in Marin County’s restored riparian soils echoes microbial community development patterns described by authors in other restored systems and provides promising evidence of the value of restoration as a carbon farming strategy, but the short- and long-term effects of restoration on soil organic carbon serve as a caution against assuming benefits without measuring carefully
Understanding and Evaluating Genomic Language Models
Get PDFLarge Language Models (LLMs) have shown remarkable capabilities in interpreting complex patterns across various domains, yet their application to genomic data remains limited. We see great potential in leveraging LLMs for vital biological tasks, such as predicting transcription factor binding sites and identifying antibiotic-resistant genes. This emergent behavior positions LLMs as powerful tools for enhancing our understanding of intricate biological language. LLMs trained specifically on genomic data, such as DNA sequences, operate distinctly compared to those trained on natural language. This difference is evident not only in the architectural landscape of the models but also in the methodologies employed by tokenizers to handle nucleotide sequences. In this work, we aim to develop and train LLMs tailored for genomic sequences, focusing on the E. coli organism as our initial case study. Our approach utilizes the widely used GPT-2-like model architecture, where we explore various tokenization strategies to quantify the sequence-to-compressed size ratio. Furthermore, we will present an evaluation of the E. coli models, demonstrating their intrinsic performance, and demonstrating how In-Context Learning could be applied to quantify how well the model understands the genomic language. Keywords: Genomics, Large Language Models, Evaluatio
Learning Structure with Multivariate Information Bottleneck and Exploration of New Methods in Sequential Decision Making
No full textResearch in useful information extraction has been motivated by the increasing demand to extract insights from unstructured data, and by the need to store and transmit great volumes of information, often originating in unstructured data such as videos. Research in rate distortion and information bottleneck paved the path for understanding and guiding the design of lossy encoders, capable of extracting relevant information. Independently, research in deep representation learning has enabled numerous applications for unstructured high-dimensional data such as images. However, the interpretability of the deep learning methods remained limited. Several desired properties of learned representations have been suggested, including disentanglement. We suggest that the Multivariate Information Bottleneck (MIB) is a natural solution to interpretable deep representation learning, as it can be used to obtain properties that previously required explicit optimization implicitly. To test this, we explore a particular instance of MIB, a parallel structure, as a fitting framework for disentanglement. While the structure can be applied to generative disentanglement, we focus on a variation relating to a relevant variable and suggest a corresponding evaluation metric. We experimentally show that while relevant disentanglement is achievable with current methods, it remains limited due to non-trivial challenges. We discuss the said limitation and the further directions
Post-Fire Succession in an Old-growth Coast Redwood (Sequoia Sempervirens) Forest in the Santa Cruz Mountain Bioregion
Get PDFFire is a common disturbance in the western United States, and variation in its frequency and intensity can significantly impact species recovery and distribution across ecosystems. While fire frequency and intensity are increasing in coast redwood forests, little is known about how this forest type responds to high-intensity wildfires. In 2020, a high-intensity wildfire burned large portions of the coast redwood forest in the Santa Cruz Mountains, including over 1,700 ha of old-growth. This event created a unique opportunity to evaluate post-fire succession. This research assessed vegetation recovery across high and low to moderate severity burned areas using random sampling at Big Basin Redwoods State Park. Data collected four years post-fire were compared to one-year post-fire surveys and included trees, shrubs, and herbaceous species. Descriptive and inferential statistical analysis were used to assess recovery over time and by burn severity. Results indicate significant increases in shrub and herbaceous cover, with fire-adapted Ceanothus thyrsiflorus Eschsch. dominating high-severity burned areas. Herbaceous species also exhibited recovery, though non-native plants cover increased, potentially influencing long-term succession. Tree regeneration was primarily driven by basal sprouting, ensuring coast redwood persistence, though both Douglas-fir and coast redwood also showed significant seedling recruitment. These findings underscore the complex interactions shaping post-fire forest dynamics and highlight the importance of understanding such patterns to inform management strategies that support the resiliency of coast redwood forests in an era of increasing wildfires
Multi-Species Telemetry Quantifies Current and Future Efficacy of a Remote Marine Protected Area
Get PDFLarge-scale marine protected areas (LSMPAs; \u3e 1000 km2) provide important refuge for large mobile species, but most do not encompass species\u27 ranges. To better understand current and future LSMPA value, we concurrently tracked nine species (seabirds, cetaceans, pelagic fishes, manta rays, reef sharks) at Palmyra Atoll and Kingman Reef (PKMPA) in the U.S. Pacific Islands Heritage Marine National Monument. PKMPA and the U.S. Exclusive Economic Zone encompassed 39% and 54% of species movements (n = 83; tracking duration range: 0.5–350 days), respectively. Species distribution models indicated 73% of PKMPA contained highly suitable habitat. Under two projected future scenarios (SSP 1–2.6, “Sustainability”; SSP 3–7.0, “Rocky Road”), strong sea surface temperature gradients initially could cause abrupt oceanic change resulting in predicted habitat loss in 2040–2050, followed by an equilibrium response and regained habitat by 2090–2100. Current and future suitable habitats were available adjacent to PKMPA, suggesting that increased MPA size could enhance protection. Our three-tiered approach combining animal tracking with publicly available remote sensing data and future projected environmental scenarios could be used to design, study, and monitor protected areas throughout the world. Holistic approaches that encompass diverse species and habitat use can enhance assessments of protected area designs. Animal telemetry and remote sensing may be helpful for ascertaining the extent to which other MPAs protect large mobile species in the future