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Interpretative phenomenological analysis was used to explore the simultaneous supervision experiences of counselors-in-training. Simultaneous supervision is when a supervisee receives clinical supervision from multiple supervisors. Sometimes this supervision includes a university supervisor and a site supervisor. Other times this supervision occurs when a student has multiple sites in one semester and receives supervision at each site. Counselors-in-training described their experiences with simultaneous supervision during the course of their education. Four superordinate themes emerged: making sense of multiple perspectives, orchestrating the process, supervisory relationship dynamics, and personal dispositions and characteristics. Results indicated that counselors-in-training experienced compounded benefits and challenges. Implications for supervisors, supervisees, and counselor education programs are provided.

Point defects in two-dimensional materials are of key interest for quantum information science. However, the parameter space of possible defects is immense, making the identification of high-performance quantum defects very challenging. Here, we perform high-throughput (HT) first-principles computational screening to search for promising quantum defects within WS2, which present localized levels in the band gap that can lead to bright optical transitions in the visible or telecom regime. Our computed database spans more than 700 charged defects formed through substitution on the tungsten or sulfur site. We found that sulfur substitutions enable the most promising quantum defects. We computationally identify the neutral cobalt substitution to sulfur (Co S0 ) and fabricate it with scanning tunneling microscopy (STM). The Co S0 electronic structure measured by STM agrees with first principles and showcases an attractive quantum defect. Our work shows how HT computational screening and nanoscale synthesis routes can be combined to design promising quantum defects.

Abstract: Point defects in two-dimensional materials are of key interest for quantum information science. However, the space of possible defects is immense, making the identification of high-performance quantum defects extremely challenging. Here, we perform high-throughput (HT) first-principles computational screening to search for promising quantum defects within WS2, which present localized levels in the band gap that can lead to bright optical transitions in the visible or telecom regime. Our computed database spans more than 700 charged defects formed through substitution on the tungsten or sulfur site. We found that sulfur substitutions enable the most promising quantum defects. We computationally identify the neutral cobalt substitution to sulfur (Co$_{\rm S}^{0}$) as very promising and fabricate it with scanning tunneling microscopy (STM). The Co$_{\rm S}^{0}$ electronic structure measured by STM agrees with first principles and showcases an attractive new quantum defect. Our work shows how HT computational screening and novel defect synthesis routes can be combined to design new quantum defects.

Despite the growing number of older adult drivers, knowledge on factors influencing their driving safety from device-collected behavior data in naturalistic driving environment is limited. This study utilizes GPS tracked driving data of 1,200 older adults in the US to examine the link between home neighborhood environment, driving exposure, and driving safety behaviors. Structural equation model results show that urban older adults exhibited more frequent events of very high-speed driving (\>80 mile/h, 130 km/h), rapid decelerations, and higher right-to-left turn ratios than their suburban and rural counterparts. This is partially explained by differences in driving exposure (i.e., more trips on high-speed roads, during nighttime, and shorter distances). Notably, living in neighborhoods with higher auto-oriented road densities and more nighttime destinations contribute substantially to unsafe driving behaviors.

Hydrogen is a zero-carbon energy carrier with potential to decarbonize industrial and transportation sectors, but its life-cycle greenhouse gas (GHG) emissions depend on its energy supply chain and carbon management measures (e.g., carbon capture and storage). Global support for clean hydrogen production and use has recently intensified. In the United States, Congress passed several laws that incentivize the production and use of renewable and low-carbon hydrogen, such as the Bipartisan Infrastructure Law (BIL) in 2021 and the Inflation Reduction Act (IRA) in 2022, which provides tax credits of up to $3/kg depending on the carbon intensity of the produced hydrogen. A comprehensive life-cycle accounting of GHG emissions associated with hydrogen production is needed to determine the carbon intensity of hydrogen throughout its value chain. In the United States, Argonne’s R&D GREET® (Greenhouse Gases, Regulated emissions, and Energy use in Technologies) model has been widely used for hydrogen carbon intensity calculations. This paper describes the major hydrogen technology pathways considered in the United States and provides data sources and carbon intensity results for each of the hydrogen production and delivery pathways using consistent system boundaries and most recent technology performance and supply chain data.

Abstract Multiple myeloma (MM) therapeutics have evolved tremendously in recent years, with significant improvement in patient outcomes. As newer treatment options are developed, stem cell transplant (SCT) remains an important modality that provides excellent disease control and delays the progression of disease. Over the years, SCT use has increased overall in the U.S., but two distinct gaps remain, including suboptimal use overall and racial-ethnic disparities. We evaluated the National Cancer Database (NCDB) to study what sociodemographic factors might play a role within a given racial-ethnic group leading to disparate SCT utilization, such that targeted approaches can be developed to optimize SCT use for all. In nearly 112,000 cases belonging to mutually exclusive categories of non-Hispanic Whites (NHW), non-Hispanic Blacks (NHB), Hispanics, non-Hispanic Asians (NHA), and others, we found certain factors including age, comorbidity index, payor type, facility type (academic vs. community) and facility volume to be uniformly associated with SCT use for all the racial-ethnic groups, while gender was not significant for any of the groups. There were several other factors that had a differential impact on SCT utilization among the various race-ethnicity groups studied, including year of diagnosis (significant for NHW, NHB, and Hispanics), income level (significant for NHW and Hispanics), literacy level (significant for NHW and NHB), and geographic location of the treatment facility (significant for NHW and NHA). The suboptimal SCT utilization overall in the U.S. suggests that there may be room for improvement for all, even including the majority NHW, while we continue to work on factors that lead to disparities for the traditionally underserved populations. This study helps identify sociodemographic factors that may play a role specifically in each group and paves the way to devise targeted solutions such that resource utilization and impact can be maximized.

Background: Oscillation and pulmonary expansion (OPE) therapy can decrease postoperative pulmonary complications in a general surgical population, but its effect after cardiac surgery has not been reported, to our knowledge. We hypothesized that using an OPE device after cardiac surgery before extubation would decrease pulmonary complications. Methods: This retrospective cohort study included adults undergoing elective open cardiac surgery at our institution from January 2018 through January 2019, who had an American Society of Anesthesiologists score of 3 or greater. For mechanically ventilated patients after cardiac surgery, a new OPE protocol was adopted, comprising an initial 10-min OPE treatment administered in-line with the ventilator circuit, then continued treatments for 48 h after extubation. The primary outcome measure was the occurrence of severe postoperative respiratory complications, including the need for antibiotics, increased use of supplemental oxygen, and prolonged hospital length of stay (LOS). Demographic, clinical, and outcome data were compared between patients receiving usual care (involving post-extubation hyperinflation) and those treated under the new OPE protocol. The primary outcome measure was the occurrence of severe postoperative respiratory complications, including the need for antibiotics, increased use of supplemental oxygen, and prolonged hospital length of stay (LOS). Demographic, clinical, and outcome data were compared between patients receiving usual care (involving post-extubation hyperinflation) and those treated under the new OPE protocol. Results: Of 104 patients, 54 patients received usual care, and 50 received OPE. Usual-care recipients had more men (74% vs. 62%; p = 0.19) and were older (median, 70 vs. 67 years; p = 0.009) than OPE recipients. The OPE group had a significantly shorter hospital LOS than the usual-care group (mean, 6.2 vs. 7.4 days; p = 0.04). Other measures improved with OPE but did not reach significance: shorter ventilator duration (mean, 0.6 vs. 1.1 days with usual care; p = 0.06) and shorter LOS in the intensive care unit (mean, 2.7 vs. 3.4 days; p = 0.06). On multivariate analysis, intensive care unit LOS was significantly shorter for the OPE group (mean difference, −0.85 days; 95% CI, −1.65 to −0.06; p = 0.04). The OPE group had a lower percentage of postoperative complications (10% vs. 20%). Conclusions: OPE therapy after cardiac surgery is associated with decreased intensive care unit (ICU) and hospital LOS.

Materials imperfections in planar superconducting quantum circuits - in particular, two-level-system (TLS) defects - contribute significantly to decoherence, ultimately limiting the performance of quantum computation and sensing. The identification of specific parasitic layers and their associated loss contributions has, however, proven elusive. Using a combination of x-ray photoemission spectroscopy (XPS) and analytical scanning transmission electron microscopy (STEM), we determine the thickness, chemical composition, and location of the oxides present in niobium-on-silicon coplanar-waveguide (CPW) resonators and quantify their respective contributions to the measured single-photon quality factor (Q). Using selective chemical etching, we reduce first the substrate-air oxide then the metal-air oxide thickness, dramatically reducing both TLS (δTLS) and non-TLS (δhi) losses, resulting in a median Q value over 5×106, with individual devices approaching 6×106. We find that silicon surface oxides host 70% of TLS losses, with a δTLS:δhi loss-density ratio near 11:1. In contrast, niobium surface oxides host 77% of non-TLS losses, uniformly distributed within the oxide layer, with a δTLS:δhi loss-density ratio of 3:4 for the superconducting circuits investigated in this work. Only 7% of losses come from other sources, including the niobium-silicon interface, which is sufficiently clean in our devices to allow epitaxial Nb nucleation on Si. As we mitigate surface losses through selective modification of the interface dielectrics, we arrive in a regime where TLS losses are no longer dominant, which will allow other types of losses in superconducting circuits to be investigated in more detail, including nonequilibrium quasiparticles.

Four fundamental models that describe the spread of Monkeypox disease are analyzed: the SIR-SIR, SEIR-SIR, SIR-SEIR, and SEIR-SEIR models. They form the basis of most Monkeypox diseases models that are currently discussed in the literature. It is shown that the way the model subpopulations are organized in disease outbreaks and evolve relative to each other is determined by the relevant unstable system eigenvectors, also called order parameters. For all models, analytical expressions of the order parameters are derived. Under appropriate conditions these order parameters describe the initial outbreak phases of exponential increase in good approximation. It is shown that all four models exhibit maximally two order parameters and maximally one human–animal order parameter. The human–animal order parameter firmly connects the outbreak dynamics in the animal system with the dynamics in the human system. For the special case of the SIR-SIR model, it is found that the two possible order parameters completely describe the dynamics of infected humans and animals during entire infection waves. Finally, a simulation of a Monkeypox infection wave illustrates that in line with the aforementioned analytical results the leading order parameter explains most of the variance in the infection dynamics.

Individual atomic defects in 2D materials impact their macroscopic functionality. Correlating the interplay is challenging, however, intelligent hyperspectral scanning tunneling spectroscopy (STS) mapping provides a feasible solution to this technically difficult and time consuming problem. Here, dense spectroscopic volume is collected autonomously via Gaussian process regression, where convolutional neural networks are used in tandem for spectral identification. Acquired data enable defect segmentation, and a workflow is provided for machine-driven decision making during experimentation with capability for user customization. We provide a means towards autonomous experimentation for the benefit of both enhanced reproducibility and user-accessibility. Hyperspectral investigations on WS2 sulfur vacancy sites are explored, which is combined with local density of states confirmation on the Au{111} herringbone reconstruction. Chalcogen vacancies, pristine WS2, Au face-centered cubic, and Au hexagonal close-packed regions are examined and detected by machine learning methods to demonstrate the potential of artificial intelligence for hyperspectral STS mapping.

Abstract Neurons that participate in sensory processing often display “ON” responses, i.e., fire transiently at the onset of a stimulus. ON transients are widespread, perhaps universal to sensory coding, yet their function is not always well-understood. Here, we show that ON responses in the Drosophila thermosensory system extrapolate the trajectory of temperature change, priming escape behavior if unsafe thermal conditions are imminent. First, we show that second-order thermosensory projection neurons (TPN-IIIs) and their Lateral Horn targets (TLHONs), display ON responses to thermal stimuli, independent of direction of change (heating or cooling) and of absolute temperature. Instead, they track the rate of temperature change, with TLHONs firing exclusively to rapid changes (>0.2 °C/s). Next, we use connectomics to track TLHONs’ output to descending neurons that control walking and escape, and modeling and genetic silencing to demonstrate how ON transients can flexibly amplify aversive responses to small thermal change. Our results suggest that, across sensory systems, ON transients may represent a general mechanism to systematically anticipate and respond to salient or dangerous conditions.

Qubits made from superconducting materials are a mature platform for quantum information science application, such as quantum computing. However, material-based losses are now a limiting factor in reaching the coherence times needed for applications. In particular, knowledge of the atomistic structure and properties of the circuit materials is needed to identify, understand, and mitigate material-based decoherence channels. In this work, we characterize the atomic structure of the native oxide film formed on Nb resonators by comparing fluctuation electron microscopy experiments to density functional theory calculations, finding that an amorphous layer is consistent with an Nb2O5 stoichiometry. Comparing x-ray absorption measurements at the Oxygen K edge with first-principles calculations, we find evidence of d-type magnetic impurities in our sample, known to cause impedance in proximal superconductors. This work identifies the structural and chemical composition of the oxide layer grown on Nb superconductors and shows that soft x-ray absorption can fingerprint magnetic impurities in these superconducting systems.

Abstract Background Ecological models suggest that interventions targeting specific behaviors are most effective when supported by the environment. This study prospectively examined the interactions between neighborhood walkability and an mHealth intervention in a large-scale, adequately powered trial to increase moderate-to-vigorous physical activity (MVPA). Methods Healthy, insufficiently active adults (N = 512) were recruited purposefully from census block groups ranked on walkability (high/low) and socioeconomic status (SES, high/low). Participants were block-randomized in groups of four to WalkIT Arizona, a 12-month, 2 × 2 factorial trial evaluating adaptive versus static goal setting and immediate versus delayed financial reinforcement delivered via text messages. Participants wore ActiGraph GT9X accelerometers daily for one year. After recruitment, a walkability index was calculated uniquely for every participant using a 500-m street network buffer. Generalized linear mixed-effects hurdle models tested for interactions between walkability, intervention components, and phase (baseline vs. intervention) on: (1) likelihood of any (versus no) MVPA and (2) daily MVPA minutes, after adjusting for accelerometer wear time, neighborhood SES, and calendar month. Neighborhood walkability was probed at 5th, 25th, 50th, 75th, and 95th percentiles to explore the full range of effects. Results Adaptive goal setting was more effective in increasing the likelihood of any MVPA and daily MVPA minutes, especially in lower walkable neighborhoods, while the magnitude of intervention effect declined as walkability increased. Immediate reinforcement showed a greater increase in any and daily MVPA compared to delayed reinforcement, especially relatively greater in higher walkable neighborhoods. Conclusions Results partially supported the synergy hypotheses between neighborhood walkability and PA interventions and suggest the potential of tailoring interventions to individuals’ neighborhood characteristics. Trial Registration Preregistered at clinicaltrials.gov (NCT02717663).

Combinatorial fusion analysis (CFA) is an approach for combining multiple scoring systems using the rank-score characteristic function and cognitive diversity measure. One example is to combine diverse machine learning models to achieve better prediction quality. In this work, we apply CFA to the synthesis of metal halide perovskites containing organic ammonium cations via inverse temperature crystallization. Using a data set generated by high-throughput experimentation, four individual models (support vector machines, random forests, weighted logistic classifier, and gradient boosted trees) were developed. We characterize each of these scoring systems and explore 66 possible combinations of the models. When measured by the precision on predicting crystal formation, the majority of the combination models improves the individual model results. The best combination models outperform the best individual models by 3.9 percentage points in precision. In addition to improving prediction quality, we demonstrate how the fusion models can be used to identify mislabeled input data and address issues of data quality. In particular, we identify example cases where all single models and all fusion models do not give the correct prediction. Experimental replication of these syntheses reveals that these compositions are sensitive to modest temperature variations across the different locations of the heating element that can hinder or enhance the crystallization process. In summary, we demonstrate that model fusion using CFA can not only identify a previously unconsidered influence on reaction outcome but also be used as a form of quality control for high-throughput experimentation.

Surface plasmons have found a wide range of applications in plasmonic and nanophotonic devices. The combination of plasmonics with three-dimensional photonic crystals has enormous potential for the efficient localization of light in high surface area photoelectrodes. However, the metals traditionally used for plasmonics are difficult to form into three-dimensional periodic structures and have limited optical penetration depth at operational frequencies, which limits their use in nanofabricated photonic crystal devices. The recent decade has seen an expansion of the plasmonic material portfolio into conducting ceramics, driven by their potential for improved stability, and their conformal growth via atomic layer deposition has been established. In this work, we have created three-dimensional photonic crystals with an ultrathin plasmonic titanium nitride coating that preserves photonic activity. Plasmonic titanium nitride enhances optical fields within the photonic electrode while maintaining sufficient light penetration. Additionally, we show that post-growth annealing can tune the plasmonic resonance of titanium nitride to overlap with the photonic resonance, potentially enabling coupled-phenomena applications for these three-dimensional nanophotonic systems. Through characterization of the tuning knobs of bead size, deposition temperature and cycle count, and annealing conditions, we can create an electrically- and plasmonically-active photonic crystal as-desired for a particular application of choice.

The study examined the determinants that affect tourism receipts in Thailand. To this end, quarterly data from eight main provinces of Thailand from the period 2015-2019 were used and constituted a repeated measures design. Accordingly, a generalized linear mixed model was applied for developing two different random intercept models by treating 1) province, and 2) a combination of province and calendar quarter as cluster-specific effects. It was found that determinants that increased tourism receipts were the number of visitors, the average cost per day, the length of stay of visitors, the presence of low-cost airlines, and a relatively low offence rate. Moreover, an increase in the number of visitors in the fourth quarter produced a higher amount of additional receipts as compared to a similar increase in the first quarter. Specifically, for Thailand attracting high-spending tourists and extending tourist visas for more than 30 days is recommended. Beyond Thailand, uncovering interaction effects as described above may help tourism agencies to focus their limited resources on the determinants that matter.

Quantum sensing and computation can be realized with superconductingmicrowave circuits. Qubits are engineered quantum systems of capacitors andinductors with non-linear Josephson junctions. They operate in thesingle-excitation quantum regime, photons of $27 \mu$eV at 6.5 GHz. Quantumcoherence is fundamentally limited by materials defects, in particularatomic-scale parasitic two-level systems (TLS) in amorphous dielectrics atcircuit interfaces.[1] The electric fields driving oscillating charges inquantum circuits resonantly couple to TLS, producing phase noise anddissipation. We use coplanar niobium-on-silicon superconducting resonators toprobe decoherence in quantum circuits. By selectively modifying interfacedielectrics, we show that most TLS losses come from the silicon surface oxide,and most non-TLS losses are distributed throughout the niobium surface oxide.Through post-fabrication interface modification we reduced TLS losses by 85%and non-TLS losses by 72%, obtaining record single-photon resonator qualityfactors above 5 million and approaching a regime where non-TLS losses aredominant. [1]M\"uller, C., Cole, J. H. & Lisenfeld, J. Towards understandingtwo-level-systems in amorphous solids: insights from quantum circuits. Rep.Prog. Phys. 82, 124501 (2019)

Quantum dot-like single-photon sources in transition metal dichalcogenides (TMDs) exhibit appealing quantum optical properties but lack a well-defined atomic structure and are subject to large spectral variability. Here, we demonstrate electrically stimulated photon emission from individual atomic defects in monolayer WS2 and directly correlate the emission with the local atomic and electronic structure. Radiative transitions are locally excited by sequential inelastic electron tunneling from a metallic tip into selected discrete defect states in the WS2 bandgap. Coupling to the optical far field is mediated by tip plasmons, which transduce the excess energy into a single photon. The applied tip-sample voltage determines the transition energy. Atomically resolved emission maps of individual point defects closely resemble electronic defect orbitals, the final states of the optical transitions. Inelastic charge carrier injection into localized defect states of two-dimensional materials provides a powerful platform for electrically driven, broadly tunable, atomic-scale single-photon sources.

Free-standing ultrathin (∼2 nm) films of several oxides (Al2O3,TiO2, and others) have been developed, which are mechanically robust and transparent to electrons with Ekin ≥ 200 eV and to photons. We demonstrate their applicability in environmental X-ray photoelectron and infrared spectroscopy for molecular level studies of solid-gas (≥1 bar) and solid-liquid interfaces. These films act as membranes closing a reaction cell and as substrates and electrodes for electrochemical reactions. The remarkable properties of such ultrathin oxides membranes enable atomic/molecular level studies of interfacial phenomena, such as corrosion, catalysis, electrochemical reactions, energy storage, geochemistry, and biology, in a broad range of environmental conditions.

The electron beam (e-beam) in the scanning electron microscopy (SEM) provides an appealing mobile heating source for thermal metrology with spatial resolution of ∼1 nm, but the lack of systematic quantification of the e-beam heating power limits such application development. Here, we systemically study e-beam heating in LPCVD silicon nitride (SiNx) thin-films with thickness ranging from 200 to 500 nm from both experiments and complementary Monte Carlo simulations using the CASINO software package. There is good agreement about the thickness-dependent e-beam energy absorption of thin-film between modeling predictions and experiments. Using the absorption results, we then demonstrate adapting the e-beam as a quantitative heating source by measuring the thickness-dependent thermal conductivity of SiNx thin-films, with the results validated to within 7% by a separate Joule heating experiment. The results described here will open a new avenue for using SEM e-beams as a mobile heating source for advanced nanoscale thermal metrology development.

Mn2+ doping of lead halide perovskites has garnered recent interest because it produces stable orange luminescence in tandem with perovskite emission. Here, we observe enhanced Mn2+ luminescence at the edges of Mn2+-doped CsPbCl3 perovskite microplates and suggest an explanation for its origin using the high spatiotemporal resolution of time-resolved cathodoluminescence (TRCL) imaging. We reveal two luminescent decay components that we attribute to two different Mn2+ populations. While each component appears to be present both near the surface and in the bulk, the origin of the intensity variation stems from a higher proportion of the longer lifetime component near the perovskite surface. We suggest that this higher emission is caused by an increased probability of electron-hole recombination on Mn2+ near the perovskite surface due to an increased trap concentration there. This observation suggests that such surface features have yet untapped potential to enhance emissive properties via control of surface-to-volume ratio.