Weak-lensing calibration of a stellar mass-based mass proxy for redMaPPer and Voronoi Tessellation clusters in SDSS Stripe 82

We present the first weak lensing calibration of $\mu_{\star}$, a new galaxy cluster mass proxy corresponding to the total stellar mass of red and blue members, in two cluster samples selected from the SDSS Stripe 82 data: 230 redMaPPer clusters at redshift $0.1\leq z<0.33$ and 136 Voronoi Tessellation (VT) clusters at $0.1 \leq z < 0.6$. We use the CS82 shear catalog and stack the clusters in $\mu_{\star}$ bins to measure a mass-observable power law relation. For redMaPPer clusters we obtain $M_0 = (1.77 \pm 0.36) \times 10^{14}h^{-1} M_{\odot}$, $\alpha = 1.74 \pm 0.62$. For VT clusters, we find $M_0 = (4.31 \pm 0.89) \times 10^{14}h^{-1} M_{\odot}$, $\alpha = 0.59 \pm 0.54$ and $M_0 = (3.67 \pm 0.56) \times 10^{14}h^{-1} M_{\odot}$, $\alpha = 0.68 \pm 0.49$ for a low and a high redshift bin, respectively. Our results are consistent, internally and with the literature, indicating that our method can be applied to any cluster finding algorithm. In particular, we recommend that $\mu_{\star}$ be used as the mass proxy for VT clusters. Catalogs including $\mu_{\star}$ measurements will enable its use in studies of galaxy evolution in clusters and cluster cosmology.Comment: Updated to be consistent with the published versio

Dispersal syndromes are poorly associated with climatic niche differences in the Azorean seed plants

Aim: Environmental niche tracking is linked to the species ability to disperse. While well investigated on large spatial scales, dispersal constraints also influence small-scale processes and may explain the difference between the potential and the realized niche of species at small scales. Here we test whether niche size and niche fill differ systematically according to dispersal syndrome within isolated oceanic islands. We expect that species with higher dispersal abilities (anemochorous or endozoochorous) will have a higher niche fill, despite their environmental niche size. Location: Azores archipelago. Taxon: Native seed plants. Methods: We combined a georeferenced database of the species distribution within the archipelago (Azorean Biodiversity Portal/GBIF) with an expert-based dispersal syndrome categorization and a high-resolution climatic grid (CIELO model). Using four climatic variables (Annual Mean Temperature, Mean Diurnal Range, Annual Precipitation, Precipitation Seasonality), we calculated a four-dimensional hypervolume to estimate the niche size of each species. Niche fill was quantified as the suitable climatic space of the island that was occupied by the focal species. Results: We found a significant relationship between dispersal syndromes and niche size, and also between dispersal syndromes and niche fill. Such relationships presented no phylogenetic signal. Endozoochorous species display higher niche fill compared to epizoochorous and hydrochorous species, and larger niches than anemochorous and epizoochorous. Differences among the remaining groups are not significant for either niche size or for niche fill. Main conclusions: The ability of a species to track its niche at small scales is not tightly related to its dispersal syndrome, although endozoochorous species track their niche more efficiently than the rest of groups. Despite being intuitively appealing, dispersal syndrome classifications might not be the most appropriate tools for understanding dispersal processes at small scales.info:eu-repo/semantics/acceptedVersio

Comportamento Eletroquímico da Liga Ti-12Mo-13Nb na condição envelhecida em solução de NaCl 0,9 %

Ti e suas ligas são amplamente usados como implantes ortopédicos devido a sua melhor resistência à corrosão, biocompatibilidade, maior resistência específica e menor módulo de elasticidade que os outros biomateriais metálicos. Estudos mostram que a liga Ti-12Mo-13Nb envelhecida a 500ºC/24 h apresenta alta razão dureza/módulo de elasticidade. Portanto, o objetivo deste trabalho consistiu em analisar o comportamento eletroquímico da liga Ti-12Mo-13Nb envelhecida a 500ºC/24 h, visando seu uso como material biomédico. O comportamento eletroquímico foi realizado por curvas de polarização potenciodinâmica usando solução de NaCl 0,9 % para simular o fluido corpóreo. Os resultados mostraram que, a liga Ti-12Mo-13Nb apresentou menores valores de densidade de corrente que a liga Ti-6Al- 4V em praticamente toda a faixa estudada

Estimating the time-dependent performance of nanocatalysts in fuel cells based on a cost-normalization approach

CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESResearchers have developed new catalysts for fuel cells (FC), whose performances are compared after applying different normalization procedures. However, there is not a standard procedure. The current produced from CO electrooxidation was compared for Pt4271119801988CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESCONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPES454516/2014-2SEM INFORMAÇÃOThe authors acknowledge financial assistance from CNPq (grant No. 454516/2014-2), FUNDECT (grant No. 026/2015), CAPES and FINE

Quantum Configuration and Phase Spaces: Finsler and Hamilton Geometries

In this paper, we review two approaches that can describe, in a geometrical way, the kinematics of particles that are affected by Planck-scale departures, named Finsler and Hamilton geometries. By relying on maps that connect the spaces of velocities and momenta, we discuss the properties of configuration and phase spaces induced by these two distinct geometries. In particular, we exemplify this approach by considering the so-called $q$-de Sitter-inspired modified dispersion relation as a laboratory for this study. We finalize with some points that we consider as positive and negative ones of each approach for the description of quantum configuration and phases spaces.Comment: 22 pages. Matches published version. Invited contribution for Physics. Special Issue "New Advances in Quantum Geometry

Facing the Void: Overcoming Missing Data in Multi-View Imagery

In some scenarios, a single input image may not be enough to allow the object classification. In those cases, it is crucial to explore the complementary information extracted from images presenting the same object from multiple perspectives (or views) in order to enhance the general scene understanding and, consequently, increase the performance. However, this task, commonly called multi-view image classification, has a major challenge: missing data. In this paper, we propose a novel technique for multi-view image classification robust to this problem. The proposed method, based on state-of-the-art deep learning-based approaches and metric learning, can be easily adapted and exploited in other applications and domains. A systematic evaluation of the proposed algorithm was conducted using two multi-view aerial-ground datasets with very distinct properties. Results show that the proposed algorithm provides improvements in multi-view image classification accuracy when compared to state-of-the-art methods. The code of the proposed approach is available at https://github.com/Gabriellm2003/remote_sensing_missing_data.Output Status: Forthcoming/Available Onlin

Rainfall Prediction in the State of Paraíba, Northeastern Brazil Using Generalized Additive Models

The state of Paraíba is part of the semi-arid region of Brazil, where severe droughts have occurred in recent years, resulting in significant socio-economic losses associated with climate variability. Thus, understanding to what extent precipitation can be influenced by sea surface temperature (SST) patterns in the tropical region can help, along with a monitoring system, to set up an early warning system, the first pillar in drought management. In this study, Generalized Additive Models for Location, Scale and Shape (GAMLSS) were used to filter climatic indices with higher predictive efficiency and, as a result, to perform rainfall predictions. The results show the persistent influence of tropical SST patterns in Paraíba rainfall, the tropical Atlantic Ocean impacting the rainfall distribution more effectively than the tropical Pacific Ocean. The GAMLSS model showed predictive capability during summer and southern autumn in Paraíba, highlighting the JFM (January, February and March), FMA (February, March and April), MAM (March, April and May), and AMJ (April, May and June) trimesters as those with the highest predictive potential. The methodology demonstrates the ability to be integrated with regional forecasting models (ensemble). Such information has the potential to inform decisions in multiple sectors, such as agriculture and water resources, aiming at the sustainable management of water resources and resilience to climate risk

Comportamento eletroquímico da liga Ti-10mo-20nb

Ligas de Ti, do tipo b compostas de elementos não tóxicos estão sendo desenvolvidas para implantes biomédicos. As vantagens destas ligas incluem seu baixo módulo de elasticidade, boa compatibilidade mecânica assim como boa resistência à corrosão e, além disso, as variáveis de processamento podem ser controladas para obter propriedades desejadas. Estudos preliminares mostraram que a liga Ti-10Mo-20Nb envelhecida a 500ºC/4 h apresentou alta razão dureza/módulo de elasticidade. Diante do contexto, o objetivo deste trabalho é apresentar o comportamento eletroquímico da liga Ti-10Mo- 20Nb envelhecida a 500ºC/4 h. O testes de corrosão foram realizados na temperatura de 25oC. Os resultados mostraram que esta exibiu uma camada passivadora

Bio-Based Fire Retardant for Coco Lumber using Aloe barbadensis miller (Aloe Vera), Mangifera indica (Mango), or Persea americana (Avocado) and Boron Additives

Accidental fires are prevalent in low-income communities and one of the solutions to decrease fire risk is to apply fire retardants on combustible materials. While extensive research was available in creating fire retardants with inorganic chemicals, further studies are needed for bio-based fire retardants. The development of bio-based fire retardants involves testing organic matter for the presence of fire-retardant compounds such as nitrogen, phosphorus, and polyphenols. This study sought to determine the effectiveness of the peels of Aloe barbadensis miller (aloe vera), Mangifera indica (mangoes), and Persea americana (avocados) in creating bio-based fire retardants for coco lumber. Maceration was used to get the fruit and plant extracts. Boric acid and borax were also added as additives to boost fire retarding properties. The burning behavior of the lumber was observed in a modified horizontal flammability test and a modified flame spread test and measured in terms of mass loss, smoke density, char yield, and charring rate. The results revealed that among the fruits, the mango-based fire-retardant inhibited mass loss the most (M = 0.006, SD = 0.003), while the avocado-based fire-retardant inhibited smoke the most (M = 0.036, SD = 0.016). No significant difference was found among the groups as determined by One-way ANOVA and MANOVA (p \u3e 0.05). An indirect relationship was found between smoke density and char yield, which may be examined to improve the smoke suppressing ability of commercial fire retardants. Future studies may also refine the plant extracts and use standard flammability tests

CAPIVARA: Cost-Efficient Approach for Improving Multilingual CLIP Performance on Low-Resource Languages

This work introduces CAPIVARA, a cost-efficient framework designed to enhance the performance of multilingual CLIP models in low-resource languages. While CLIP has excelled in zero-shot vision-language tasks, the resource-intensive nature of model training remains challenging. Many datasets lack linguistic diversity, featuring solely English descriptions for images. CAPIVARA addresses this by augmenting text data using image captioning and machine translation to generate multiple synthetic captions in low-resource languages. We optimize the training pipeline with LiT, LoRA, and gradient checkpointing to alleviate the computational cost. Through extensive experiments, CAPIVARA emerges as state of the art in zero-shot tasks involving images and Portuguese texts. We show the potential for significant improvements in other low-resource languages, achieved by fine-tuning the pre-trained multilingual CLIP using CAPIVARA on a single GPU for 2 hours. Our model and code is available at https://github.com/hiaac-nlp/CAPIVARA