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Background

The integration of artificial intelligence (AI) into healthcare is rapidly advancing, with profound implications for medical practice. However, a gap exists in formal AI education for pre-medical students. This study evaluates the effectiveness of the AI in Medicine Association (AIM), an extracurricular program designed to equip pre-medical students with foundational AI knowledge.

Methods

A quasi-experimental pretest-posttest control group design was employed, comparing knowledge acquisition between students participating in the AIM program (cohort group) and a control group of students not participating. The intervention spanned four weeks and included hands-on AI training, ethical considerations, data preprocessing, and model evaluation. Pretest and posttest assessments measured AI knowledge and pathology-related skills.

Results

Participants in the AIM program demonstrated significant improvements in both AI knowledge and pathology-related scores. The cohort group showed a large effect size across all measured domains, particularly in pathology, with Cohen’s d values ranging from 1.83 to 4.74. Statistical analysis confirmed robust, significant improvements in test scores (t-test and Mann-Whitney U test, p < 0.001). There was no significant correlation between previous AI experience or attitudes toward AI and overall score improvement.

Conclusions

The AIM program effectively improved pre-medical students’ understanding of AI and its application in medicine, particularly in pathology. This study highlights the potential of extracurricular programs to address the need for AI education in medical curricula, especially in the pre-medical phase, and suggests that such initiatives could serve as a model for other institutions seeking to integrate AI education into healthcare training.

The Nancy Grace Roman Space Telescope is poised to revolutionize our scientific understanding of exoplanets, dark matter, dark energy, and general astrophysics, including through an innovative community approach to defining and executing sky surveys. The Roman Observations Time Allocation Committee (ROTAC) was convened to recommend time allocations for the three Core Community Surveys (CCS) using the Wide Field Instrument (WFI): the High Latitude Wide Area Survey, the High Latitude Time Domain Survey, and the Galactic Bulge Time Domain Survey, as well as balance the time allocation for the General Astrophysics Surveys. Each CCS had a corresponding Definition Committee that collected community input and designed proposals for a nominal (in-guide) survey, as well as underguide and overguide options with smaller and larger time allocations, respectively. These options explored different ways of fulfilling the mission science requirements while maximizing general astrophysics science goals enabled by the surveys. In this report, the ROTAC lays out its recommendations for the three CCS observing designs and the WFI time allotment for CCS (74.5%) and the General Astrophysics Surveys (25.5%).

Prior work [e.g., McInerny (1992). Noise Control Eng. J. 38(1), 5–16; McInerny (1996). J. Aircraft 33(3), 511–517; Franken (1958). Noise Control 4(3), 8–16] has resulted in models for estimating overall sound power levels (OAPWLs) and maximum overall sound pressure levels (OASPL_max) from jet and rocket engines. Based on fundamental flow properties, this paper builds on previous results and presents simple methods for predicting OAPWL and OASPL_max from heated supersonic jets and rockets. A method for estimating ground effects on OASPL_max is also presented. The model's performance is evaluated for launched Atlas V and Vulcan Centaur rockets and an installed F404 jet engine at engine conditions ranging from 38% thrust through afterburner. The results show good agreement for OASPL_max ⁠, where the root mean square error is confined to less than 2 dB for the rockets and jet engine conditions considered.

We investigated the growth of carbon nanotubes (CNTs) directly on stainless steel substrates. The CNTs were grown using a two-step process: oxidation of the stainless steel surface and CNT growth. The samples were oxidized in an 800 °C furnace fed with a flow of air for 4 min. CNTs were grown by switching the flow to ethylene, which both reduces the oxide and initializes CNT growth. The time of CNT growth was varied to understand how the samples evolved over time. To better understand the growth mechanisms, we isolated cross-sections of the CNT-substrate interface using a focused ion beam. These cross-sections were investigated with transmission electron microscopy and energy dispersive X-ray spectroscopy. CNTs were seen to grow from iron-rich nanoparticles embedded in the oxide layer. The oxide layer was also seen to lose iron over time, suggesting that these iron nanoparticles were reduced out of the oxide. The base particles were embedded in the oxide layer, leaving cavities when the CNTs were removed. The diameters of the nanotubes were also seen to grow over time as a result of carbon infiltration. The effects of the embedded particle and infiltration quickly isolate the catalyst, leading to short CNTs (1–10 µm).

The hexagonal antiferromagnet MnTe has attracted enormous interest as a prototypical example of a spin-compensated magnet in which the combination of crystal and spin symmetries lifts the spin degeneracy of the electron bands without the need for spin-orbit coupling, a phenomenon called nonrelativistic spin splitting (NRSS). Subgroups of NRSS are determined by the specific spin-interconverting symmetry that connects the two opposite-spin sublattices. In MnTe, this symmetry is rotation, leading to the subgroup with spin splitting away from the Brillouin zone center, often called altermagnetism. MnTe also has the largest spontaneous magnetovolume effect of any known antiferromagnet, implying strong coupling between the magnetic moment and volume. This magnetostructural coupling offers a potential knob for tuning the spin-splitting properties of MnTe. Here, we use neutron diffraction with in situ applied pressure to determine the effects of pressure on the magnetic properties of MnTe and further explore this magnetostructural coupling. We find that applying pressure significantly increases the Néel temperature, but decreases the ordered magnetic moment. We explain this as a consequence of strengthened magnetic exchange interactions under pressure, resulting in higher 𝑇N, with a simultaneous reduction of the local moment of individual Mn atoms, described here via density functional theory. This reflects the increased orbital hybridization and electron delocalization with pressure. These results shed light on the competition between magnetic exchange interactions and the strength of individual magnetic moments and show that the magnetic properties of MnTe can be controlled by pressure, opening the door to improved properties for spintronic applications through tuning via physical or chemical pressure.

Broadband shock-associated noise (BSN) is a major source of high-frequency noise in imperfectly expanded supersonic jets. While BSN has been extensively studied, source characterization from full-scale engines remains limited. This paper investigates BSN source and radiation characteristics from a full-scale, installed GE F404 engine on the T-7A trainer aircraft using acoustic holography. Apparent BSN sources are identified along the nozzle lipline and corroborated with in-situ imaging. The observed shock spacing aligns with similar jets in the literature but deviates significantly from traditional analytical models. Likewise, BSN peak frequencies at forward angles match trends from other full-scale jets but differ from simulations and lab-scale data, likely due to temperature and scale-related differences. A widely used BSN frequency model underperforms when relying on historical analytic shock spacing predictions but yields excellent agreement when corrected with measured spacing. Coherence analysis reveals connections between upstream-directed BSN and downstream Mach wave radiation, and shows elevated coherence between shock cells, indicating a partially coherent, distributed BSN source.