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AI education is rapidly becoming essential as artificial intelligence transforms industries, yet students with disabilities often encounter significant barriers to learning and engagement. This paper examines accessibility challenges encountered by learners with visual, cognitive, and physical disabilities when using foundational tools for AI development. Using HuggingFace, an influential open-source platform, as a case study, we analyze barriers such as insufficient screen reader support, complex interfaces, and information overload. We propose design recommendations to promote equity and inclusivity in AI tools, aiming to empower diverse learners to thrive in AI education. Our work highlights the importance of inclusive design for CS educators, researchers, and policymakers. 

AI education is rapidly becoming essential as artificial intelligence transforms industries, yet students with disabilities often encounter significant barriers to learning and engagement. This paper examines accessibility challenges encountered by learners with visual, cognitive, and physical disabilities when using foundational tools for AI development. Using HuggingFace, an influential open-source platform, as a case study, we analyze barriers such as insufficient screen reader support, complex interfaces, and information overload. We propose design recommendations to promote equity and inclusivity in AI tools, aiming to empower diverse learners to thrive in AI education. Our work highlights the importance of inclusive design for CS educators, researchers, and policymakers. 

Estimating the location of contact is a primary function of artificial tactile sensing apparatuses that perceive the environment through touch. Existing contact localization methods use flat geometry and uniform sensor distributions as a simplifying assumption, limiting their ability to be used on 3D surfaces with variable density sensing arrays. This paper studies contact localization on an artificial skin embedded with mutual capacitance tactile sensors, arranged non-uniformly in an unknown distribution along a semi-conical 3D geometry. A fully connected neural network is trained to localize the touching points on the embedded tactile sensors. The studied online model achieves a localization error of 5.7 ± 3.0 mm. This research contributes a versatile tool and robust solution for contact localization that is ambiguous in shape and internal sensor distribution. 

Previous research has shown that female and Hispanic students who are underrepresented in science, technology, engineering and mathematics (STEM) face more educational barriers than their non-Hispanic, male peers. However, little research has been conducted on the effects of intersectional identities in the STEM space. In an effort to bridge the gap in underrepresented students' experience, the PSEG Institute for Sustainability Studies organizes a paid, interdisciplinary, team-based, experiential learning and internship program called the Green Teams that occurs during 10 weeks of the summer. The Green Teams Program strives to provide undergraduate students from all backgrounds–academically, economically, and demographically–an opportunity to develop their abilities in STEM fields and prepare them to enter the professional world. Based upon a survey given post-internship, self-reported learning gains for all students were analyzed to determine if the program had a significantly greater impact on students who are from groups traditionally underrepresented in STEM in their STEM-related learning gains and their confidence in STEM disciplines. Through t-tests, a Principal Component Analysis (PCA), and a 2-way factorial Analysis of Variance (ANOVA), Hispanic and female participants were found to report significantly higher learning gains than their counterparts in multiple STEM areas from increased tolerance for obstacles to gains in self confidence. The results of the study suggest Hispanic and female students benefit from paid work experiences in STEM with diverse peers and intentional, supportive mentoring. This research on the Green Teams Program provides insight into how this approach positively impacts STEM education of individuals from traditionally underrepresented groups in STEM. The findings may help to further guide the development of the Green Teams Program and the adoption of paid, interdisciplinary, team-based, experiential learning and internship experiences in additional academic STEM settings. 

Abstract Paleosecular variation analysis is a primary tool for characterizing ancient geomagnetic behavior and its evolution through time. This study presents a new high‐quality directional data set, paleosecular variation of the Paleogene (PSVP), with and without correction for serial correlation, compiled from 1,667 sites from 45 different localities from the Paleogene and late Cretaceous (84–23 Ma). The data set is used to study the variability, structure, and latitude dependence of the geomagnetic field during that period by varying selection criteria and PSV models. Modeled values for the equatorial virtual geomagnetic pole (VGP) dispersion have over‐lapping uncertainty intervals within their uncertainty bounds between 8.3° and 18.6° for the past 250 Ma. We investigate the suitability of two descriptive models of PSV, Model G‐style quadratic fits and covariant Giant Gaussian Process models, and find that both styles of model fail to satisfactorily reproduce the latitude dependent morphology of PSV, but suggest that estimates of the equatorial VGP dispersion may still robustly characterize aspects of Earth's long‐term field morphology. During this time where the PSV behavior has not changed substantially, the reversal frequency has varied widely. The lack of a clear relationship between PSV behavior and reversal frequency is not trivially explained in the context of published findings regarding numerical geodynamo simulations. 

The co-existence of rats and humans in urban environments has long been a cause for concern regarding human health because of the potential for rats to harbor and transmit disease-causing pathogens. Here, we analyze whole-genome sequence (WGS) data from 41 Escherichia coli isolates collected from rat feces from 12 locations within the city of Chicago, IL, United States to determine the potential for rats to serve as a reservoir for pathogenic E. coli and describe its population structure. We identified 25 different serotypes, none of which were isolated from strains containing significant virulence markers indicating the presence of Shiga toxin-producing and other disease-causing E . coli . Nor did the E. coli isolates harbor any particularly rare stress tolerant or antimicrobial resistance genes. We then compared the isolates against a public database of approximately 100,000 E. coli and Shigella isolates of primarily food, food facility, or clinical origin. We found that only one isolate was genetically similar to genome sequences in the database. Phylogenetic analyses showed that isolates cluster by serotype, and there was little geographic structure (e.g., isolation by distance) among isolates. However, a greater signal of isolation by distance was observed when we compared genetic and geographic distances among isolates of the same serotype. This suggests that E. coli serotypes are independent lineages and recombination between serotypes is rare. 

The Target Absorbers for Neutrals (TANs) represent one of the most radioactive regions in the Large Hadron Collider. Seven 40cm long fused silica rods with different dopant specifications, manufactured by Heraeus, were irradiated in one of the TANs located around the ATLAS experiment by the Beam RAte of Neutrals (BRAN) detector group. This campaign took place during Run 2 data taking, which occurred between 2016 and 2018. This paper reports a complete characterization of optical transmission per unit length of irradiated fused silica materials as a function of wavelength (240 nm–1500 nm), dose (up to 18 MGy), and level of OH and H2 dopants introduced in the manufacturing process. The dose delivered to the rods was estimated using Monte Carlo simulations performed by the CERN FLUKA team. 

Abstract Despite the f₀(980) hadron having been discovered half a century ago, the question about its quark content has not been settled: it might be an ordinary quark-antiquark ($${{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}$) meson, a tetraquark ($${{\rm{q}}}\overline{{{\rm{q}}}}{{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}q\overline{q}$) exotic state, a kaon-antikaon ($${{\rm{K}}}\overline{{{\rm{K}}}}$$ $K\overline{K}$) molecule, or a quark-antiquark-gluon ($${{\rm{q}}}\overline{{{\rm{q}}}}{{\rm{g}}}$$ $q\overline{q}g$) hybrid. This paper reports strong evidence that the f₀(980) state is an ordinary$${{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}$meson, inferred from the scaling of elliptic anisotropies (v₂) with the number of constituent quarks (n_q), as empirically established using conventional hadrons in relativistic heavy ion collisions. The f₀(980) state is reconstructed via its dominant decay channel f₀(980) →π⁺π⁻, in proton-lead collisions recorded by the CMS experiment at the LHC, and itsv₂is measured as a function of transverse momentum (p_T). It is found that then_q= 2 ($${{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}$state) hypothesis is favored overn_q= 4 ($${{\rm{q}}}\overline{{{\rm{q}}}}{{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}q\overline{q}$or$${{\rm{K}}}\overline{{{\rm{K}}}}$$ $K\overline{K}$states) by 7.7, 6.3, or 3.1 standard deviations in thep_T< 10, 8, or 6 GeV/cranges, respectively, and overn_q= 3 ($${{\rm{q}}}\overline{{{\rm{q}}}}{{\rm{g}}}$$ $q\overline{q}g$hybrid state) by 3.5 standard deviations in thep_T< 8 GeV/crange. This result represents the first determination of the quark content of the f₀(980) state, made possible by using a novel approach, and paves the way for similar studies of other exotic hadron candidates.