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There have recently been calls to consider the development of student empathy within engineering coursework. We argue that this goal may be reached by infusing more traditional engineering coursework with humanities. Our Humanities-Driven Science, Technology, Engineering, and Mathematics (HDSTEM) curriculum uses a humanities format as a context to discuss science and engineering advancement. The foundation of an HDSTEM curriculum is that it would reassert the importance of humans and human impact in science and engineering, while recognizing the social, political, and cultural catalysts and outcomes of technological innovation. Therefore, we hypothesize that through an HDSTEM curriculum, students will not only develop technically accurate solutions to problems posed in an engineering curriculum but will also question their ideas' impact on society. For this project, we draw on the case of an HDSTEM course, “World War II and Technology,” taught at Texas Tech University (TTU) and Rochester Institute of Technology (RIT). Specifically, we will present the analysis of linking specific problem-solving exercises and assignments that embed empathy with the delivery of the courses following an HDSTEM instruction modality. The problem-solving exercises and assignments incorporate the traditional Six Sigma define, measure, analyze, implement, and control (DMAIC) process. In these assignments, students were asked to reverse engineer technical, scientific, and logistical problems seen during World War II. In a more straightforward means to elicit empathy, students were assigned an additional empathize step with the DMAIC (EDMAIC) during two of these assignments. The empathize step was generic, asking students to take the perspective of the creators, users, and others affected by the problem and consider the societal needs and constraints of the time. Students completed four of these assignments (2 DMAICs bookending 2 (EDMAICs) throughout the course. Combining HDSTEM instruction modality and empathy problem-solving assignments, preliminary discourse analysis of assignments, which looks deeply at the language students used to create empathetic dispositions/identities within their work, revealed that students integrated empathy into technology design at various levels at both TTU and RIT. These disposition levels in empathy were observed and subjectively quantified using common rubrics. These outcomes result even from delivery at pre- and post-pandemic timeframes and at two institutions (i.e., the course was offered at TTU in the fall of 2019 and at RIT in the fall of 2022). In this consideration, the HDSTEM curriculum and empathy-embedded assignments have shown a cultivation of empathetic disposition among students. Further, based on these differing implementations, we will also present and comment on the experience of implementing the TTU course treatment at a new institution, RIT, to serve as a protocol in the future. These courses will be offered again in the fall of 2023 year to offer a comprehensive comparison between first-time (or one-off) in contrast to a sustained delivery of an HDSTEM curriculum. 

Water vapor (H₂O) is one of the brightest molecular emitters after carbon monoxide (CO) in galaxies with high infrared (IR) luminosity, allowing us to investigate the warm and dense phase of the interstellar medium (ISM) where star formation occurs. However, due to the complexity of its radiative spectrum, H₂O is not frequently exploited as an ISM tracer in distant galaxies. Therefore, H₂O studies of the warm and dense gas at high-zremain largely unexplored. In this work, we present observations conducted with the Northern Extended Millimeter Array (NOEMA) toward threez > 6 IR-bright quasarsJ2310+1855,J1148+5251, andJ0439+1634targeted in their multiple para- and ortho-H₂O transitions (3₁₂ − 3₀₃, 1₁₁ − 0₀₀, 2₂₀ − 2₁₁, and 4₂₂ − 4₁₃), as well as their far-IR (FIR) dust continuum. By combining our data with previous measurements from the literature, we estimated the dust masses and temperatures, continuum optical depths, IR luminosities, and star formation rates (SFR) from the FIR continuum. We modeled the H₂O lines using the MOLPOP-CEP radiative transfer code, finding that water vapor lines in our quasar host galaxies are primarily excited in the warm, dense (with a gas kinetic temperature and density ofT_kin = 50 K,n_H2 ∼ 10^4.5 − 10⁵ cm⁻³) molecular medium with a water vapor column density ofN_H2O ∼ 2 × 10¹⁷ − 3 × 10¹⁸ cm⁻³. High-JH₂O lines are mainly radiatively pumped by the intense optically-thin far-IR radiation field associated with a warm dust component at temperatures ofT_dust ∼ 80 − 190 K that account for < 5 − 10% of the total dust mass. In the case of J2310+1855, our analysis points to a relatively high value of the continuum optical depth at 100 μm (τ₁₀₀ ∼ 1). Our results are in agreement with expectations based on the H₂O spectral line energy distribution of local and high-zultra-luminous IR galaxies and active galactic nuclei (AGN). The analysis of the Boltzmann diagrams highlights the interplay between collisions and IR pumping in populating the high H₂O energy levels and it allows us to directly compare the excitation conditions in the targeted quasar host galaxies. In addition, the observations enable us to sample the high-luminosity part of the H₂O–total-IR (TIR) luminosity relations (L_H2O − L_TIR). Overall, our results point to supralinear trends that suggest H₂O–TIR relations are likely driven by IR pumping, rather than the mere co-spatiality between the FIR continuum- and line-emitting regions. The observedL_H2O/L_TIRratios in ourz > 6 quasars do not show any strong deviations with respect to those measured in star-forming galaxies and AGN at lower redshifts. This supports the notion that H₂O can be likely used to trace the star formation activity buried deep within the dense molecular clouds. 

Abstract This paper presents a bilinear log model, for predicting temperature-dependent ultimate strength of high-entropy alloys (HEAs) based on 21 HEA compositions. We consider the break temperature,T_break, introduced in the model, an important parameter for design of materials with attractive high-temperature properties, one warranting inclusion in alloy specifications. For reliable operation, the operating temperature of alloys may need to stay belowT_break. We introduce a technique of global optimization, one enabling concurrent optimization of model parameters over low-temperature and high-temperature regimes. Furthermore, we suggest a general framework for joint optimization of alloy properties, capable of accounting for physics-based dependencies, and show how a special case can be formulated to address the identification of HEAs offering attractive ultimate strength. We advocate for the selection of an optimization technique suitable for the problem at hand and the data available, and for properly accounting for the underlying sources of variations.